Discover Journals

3 Feb 2025

You breathe life into your research by sharing it with the world. There’s power in having your findings validated by your peers, and published in black and white for the whole scientific community to see. It makes it real. So publish with us. bit.ly/40WbzOy

bit.lyBeneficial effects of an indole derivative melatonin analogue in estrogen receptor positive breast cancer - Discover Endocrinology and MetabolismBreast cancer has the highest incidence among cancers in women, with estrogens playing a pivotal role in the estrogen receptor-positive (ER+) subtype. Loca

19h

A study in Discover Endocrinology and Metabolism demonstrates indole-based melatonin analogue 1j as a promising therapeutic candidate for estrogen receptive positive breast cancer. #MedSky #OncoSky

bit.lyEnhancing preservation of tangible cultural heritage artifacts through digital twin technology and deep learning-based 3D point cloud completion - Discover ComputingIntroduction The preservation of tangible cultural heritage artifacts, particularly those created through intangible cultural heritage (ICH) practices such as traditional craftsmanship, is essential for sustainable urban development. Such artifacts embody the skills and knowledge transmitted through ICH. Digital twin technology offers a systematic approach to document and preserve these artifacts digitally. However, obtaining complete 3D models through close-range photogrammetry remains challenging due to occlusion, surface properties, and sensor limitations, resulting in incomplete point cloud data. Methods This study proposes a generative adversarial network with self-attention mechanism to complete missing 3D point cloud data of cultural heritage artifacts. The network employs a multi-layer perceptron for global feature extraction, self-attention modules for local detail capture, and a feature pyramid decoder for hierarchical point cloud generation. Results Quantitative evaluation on the ShapeNet dataset demonstrates that the proposed method achieves average errors of 5.541 (P→GT) and 4.183 (T→P) for complete point cloud completion, outperforming FinerPCN, PF-Net, and PFG-Net. For missing point cloud regions, the method achieves errors of 24.303 (P→GT) and 20.008 (GT→P). Discussion The proposed framework integrates digital twin concepts with deep learning-based 3D reconstruction to enhance the digital preservation of cultural heritage artifacts. By generating more complete and accurate point clouds, the method enables higher-quality 3D models suitable for virtual exhibition, documentation, and cultural transmission. A limitation is that validation on diverse heritage artifact geometries beyond ShapeNet has not yet been conducted.

1d

A study published in Discover Computing presents a proposed framework that integrates digital twin concepts with deep learning-based 3D reconstruction to enhance the digital preservation of cultural heritage artifacts. 🧪

2d

Sustainable breeding starts with genetic diversity. This research article in Discover Genetics and Evolution found low inbreeding in a red tilapia population over eight generations, supporting continued selection potential while underscoring the need for careful genetic management. bit.ly/4xElWEC 🌍

bit.lyEnergy justice and gender: bridging equity, access, and policy for sustainable development - Discover SustainabilityClean energy transitions are not just about technology. They are also about people, equity, and justice. Women play a pivotal role in advancing sustainable energy solutions, yet sociocultural, financial, and institutional barriers continue to limit their participation in decision-making and access to clean energy. This research combines BERTopic modeling, SDG mapping, and case study analysis to bridge quantitative insights with real-world narratives, offering a comprehensive examination of the gender‒energy nexus. Grounded in energy justice, gender empowerment, and SDG frameworks, the study applies Kabeer’s and Friedmann’s empowerment models to link agency, resources, and achievements with distributional, procedural, and recognitional justice in energy transitions. The study covered 616 publications identified through an extensive Scopus database search, spanning literature from 2015—coinciding with the adoption of SDGs—to 2024, specifically mapped to SDG 5 (gender) and SDG 7 (energy). Addressing the main energy justice dimensions and relevant SDGs, the findings of this systematic review reveal that clean energy adoption reduces unpaid domestic work (SDG 5.4), enhances women’s leadership (SDG 5.5), and strengthens economic opportunities (SDG 7.1, SDG 7.2) but remains constrained by gendered power dynamics, technology adaptation barriers, and financial accessibility issues. The study highlights how women’s participation in energy transitions leads to greater community engagement, increased household energy efficiency, and a shift toward sustainable energy behaviors. However, moderating factors of gender empowerment interventions show that intrahousehold bargaining, a lack of financial incentives, and limited representation in governance structures continue to restrict equitable energy access. Additionally, the findings emphasize that policies designed without a gender lens risk reinforcing existing inequalities rather than alleviating them. By embedding SDG goals in the analysis, this study ensures alignment with global sustainability goals and reinforces the urgency of justice-oriented energy policies. Advocating for inclusive, community-driven approaches, this research underscores the need for intersectional frameworks that integrate energy justice and gender empowerment, ensuring that energy transitions are not only technologically sound but also socially equitable and accessible to all.

3d

A study published in Discover Sustainability highlights how women’s participation in energy transitions leads to greater community engagement, increased household energy efficiency, and a shift toward sustainable energy behaviors. 🌍

bit.lyBringing Ancient Art to Life: Breathing Life into Shanshui Art with AI and Perlin NoiseWhen we think of traditional Chinese Shanshui (mountain-water) paintings, we imagine serene, timeless scenes of misty mountains and flowing rivers—a harmony between nature and artistic expression that has been refined over centuries. But what if these tranquil landscapes could come to life?

4d

What if an ancient Chinese landscape painting could breathe, flow, and move? In this behind the Paper blog, researchers combine Perlin Noise, Stable Diffusion, ControlNet, GPT-4, and AnimateDiff to transform traditional Shanshui art into dynamic animations while preserving its cultural essence. #AI

bit.lyHow does shock "impact" NASA's Mars rover's selection of optimal samples for return to Earth?For the first time in history, a NASA Mars rover is examining and carefully selecting samples to be brought back to Earth. But, most of Mars' surface has experienced shock from asteroid impacts. What are the consequences for studying shocked Martian rocks in Earth labs? Our team set out to find out.

5d

NASA's Mars rover is the first to collect samples for return to Earth, despite most of Mars' surface being affected by asteroid impacts. This Discover Space Behind the Paper blog post explores the implications of studying these shocked Martian rocks in Earth laboratories. 🌍

bit.lyFirst documentation of humpback whale (Megaptera novaeangliae) post-mortem attendance of a stillborn - Discover AnimalsCetaceans are some of the most charismatic marine species receiving regular widespread public attention. They display highly complex behaviour including post-mortem attentive behaviour sometimes referred to as grieving behaviour. Post-mortem attentive behaviour in cetaceans has been documented predominantly among odontocetes and remains largely absent from the literature on baleen whales, limiting current understanding of the cognitive and emotional dimensions of death-related responses in mysticete cetaceans. Here, we describe a case of prolonged post-mortem behaviour by a female humpback whale and her escort toward a deceased calf. The adult female remained in close proximity to the calf, engaging in repeated interactions and maintaining attendance over several hours and possibly days. Unlike reports in odontocetes, the female did not attempt to lift the calf to the surface. The observed behaviours were consistent with epimeletic and post-mortem attentive responses documented in socially complex mammals and indicating a strong maternal attachment to the calf. This case study highlights the need for continued systematic documentation of rare neonatal mortality events to better understand the cognitive, emotional, and evolutionary significance of post-mortem behaviour in large whales. Understanding how nonhuman animals respond to death provides insight into their emotional lives, social bonds, and cognitive capacities.

6d

What does grief look like in the ocean? A study in Discover Animals provides the first detailed documentation of a female humpback whale staying with and attending to her stillborn calf after death. The observation adds to growing evidence that some cetaceans may exhibit complex responses to loss. 🌍

bit.lyDigital twin-driven edge–cloud collaborative remote fault diagnosis and intelligent predictive maintenance for critical hydropower equipment - Discover Artificial IntelligenceTo address the problems of lagging remote monitoring, complex fault mechanisms, and inefficient maintenance decisions for key equipment in hydropower stations, this paper proposes a remote diagnosis and intelligent maintenance method based on edge-cloud collaboration and digital twin-driven approaches. A layered architecture encompassing equipment, perception, transmission, analysis, and service layers is constructed. A physical-geometric-behavior coupled digital twin model is established, and PLC-SCADA control systems, multi-source monitoring data, fault diagnosis models, and remaining life prediction methods are integrated to achieve a closed loop of equipment status perception, anomaly identification, degradation assessment, and maintenance optimization. Experimental verification is conducted on a dual-unit Pelton hydropower system. Results show that the proposed method exhibits higher fault diagnosis accuracy, better life prediction performance, and superior maintenance economy under complex operating conditions. Unlike existing digital twin-based monitoring systems, the proposed framework integrates edge–cloud collaboration, real-time physical–virtual synchronization, fault diagnosis, RUL prediction, and maintenance optimization into a unified workflow for critical hydropower equipment.

A study in Discover Artificial Intelligence proposes a remote diagnosis and intelligent maintenance method based on edge-cloud collaboration and digital twin-driven approaches for critical hydropower equipment. #STS #AI

bit.lyRainfall thresholds for flood early warning in the Babai River Basin, Nepal using rainfall-runoff modelling - Discover GeoscienceFlood is one of the most common hazards in Nepal that have a severe socio-economic effect especially in Himalayan basins that are dominated by monsoons. In this study, we constructed the rainfall thresholds of flood early warning in the Babai River Basin (BRB) by using a calibrated and validated Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) rainfall-runoff model. The model showed good performance, with the calibration values of NSE = 0.84, R² = 0.87, and PBIAS = − 5.6%, and validation values of NSE = 0.78, R² = 0.81, and PBIAS = − 7.9%. The historical flood occurrences and rain data (1990–2018) were examined at Chepang (mid-basin) and Bhada Bridge (basin outlet). The findings indicate that cumulative rainfall and peak discharge have a significant positive association, and amplified downstream runoff is by virtue of integrated basin runoff. The rainfall thresholds were calculated to obtain bankfull, warning, and danger levels of the river for 1-day, 3-day, and 5-day accumulations. Chepang had 105–110 mm of bankfull, 135–140 mm of warning, and 200–205 mm of danger levels, and the Bhada Bridge needed higher thresholds of 140–145 mm, 185–190 mm, and 240–245 mm for bankfull, warning, and danger, respectively. These thresholds provide a practical advice on anticipatory flood management in addition to current stage-based monitoring. Although the downstream discharge information is not well known and there may be some land-use and climate shifts, the study provides a feasible model of improving early warning of floods in the Himalayan basins. Communities at floods risk are ensured safer and more resilient with real time monitoring combined with risk-based planning.

Nepal and India face significant flood hazards in the Himalayan basins. A study in Discover Geoscience utilizes the HEC-HMS model to establish early warning rainfall thresholds for the Babai River Basin, enhancing real-time flood forecasting and preparedness.

bit.lyCurrent advancements and future research directions in the green synthesis and applications of nanoparticles - Discover NanoThe rapid expansion of research on green-synthesized nanoparticles (GSNPs), particularly those produced through biological processes, has generated a highly fragmented literature that obscures structural trends and translational gaps. This study conducts a comprehensive bibliometric analysis of publications indexed in Scopus between 2020 and 2025 to map the intellectual landscape of GSNPs and identify priority directions for future research. The findings demonstrate that silver nanoparticles (Ag NPs) dominate the field, driven by their established antibacterial effectiveness and broad biomedical and environmental utility. At the same time, plant extracts remain the primary biosynthetic resources, while alternative biological sources, including bacteria and fungi, are still inadequately investigated. The analysis also highlights the limited use of high-resolution characterization tools, including field emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), and X-ray photoelectron spectroscopy (XPS), compared to the prevalent conventional techniques, such as X-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM), revealing a persistent characterization gap at the nano–bio interface. The geographic analysis highlights Asia, especially India and China, as leading contributors, supported by dense international collaboration networks. Conceptually, the study clarifies green synthesis within the 12 principles of green chemistry, integrating biological, physical, and chemical methods and proposing a taxonomy that resolves the frequent conflation of green synthesis with biosynthesis alone. Finally, by linking bibliometric patterns to toxicity and regulatory keywords, the analysis exposes key barriers to commercialization. It outlines research strategies to advance GSNPs toward scalable and regulation-ready nanotechnology platforms. Graphical abstract

A study in Discover Nano outlines research strategies to advance green-synthesized nanoparticles toward scalable and regulation-ready nanotechnology platforms. 🌍🧪

bit.lyExtraction techniques, mechanistic insights for gut health, microbiota modulation, and industrial applications of diosgenin - Discover ChemistryBackground Diosgenin is a steroidal saponin of Dioscorea and Trigonella species, which has been gaining a lot of interest due to its health-promoting action. This review will summarize the potential usefulness of diosgenin, especially with regard to the use of diosgenin in the regulation of gastrointestinal microbiota, the effects, therapeutic mechanisms, utility, and practical implications. Objectives This review aims to comprehensively examine the phytochemistry, extraction techniques, biological mechanisms, and therapeutic potential of diosgenin, with emphasis on its role in gastrointestinal health. A systematic search of peer-reviewed literature published between 2019 and 2025 was conducted via PubMed, Scopus, and Web of Science, prioritizing clinical trials, animal studies, and systematic reviews in accordance with predefined inclusion criteria. Findings Diosgenin has been shown to have the ability to defend the gut, prevent cancer by modifying the signal transduction pathway of NF-kB and MAPK; thereby reinforcing the barrier to the gut and reducing inflammation. Diosgenin is also able to shift the intestinal microbiome in favor of healthy species, including Lactobacillus acidophilus and Bifidobacterium bifidum. Bioavailability may be modulated by new approaches in nanoparticle delivery or macromolecular cyclodextrin complexes. Conclusion and future directions Diosgenin may be applied in the treatment of gastrointestinal-associated conditions such as inflammatory bowel diseases (IBD) and colorectal cancer. What also makes it clinically significant is the capability to achieve the balance of the gut-brain axis. Future clinical trials and pharmacokinetics studies need to be conducted in order to know how diosgenin is demonstrated in functional foods and personalized medicine, and be able to use them in therapies. Graphical Abstract

A Review in Discover Chemistry discusses the potential usefulness of Diosgenin, a steroidal saponin of Dioscorea and Trigonella species, and its ability to defend the gut, prevent cancer and reduce inflammation. #Oncology

bit.lyThe "Stela Effect" of bright and dark narcissism on educational innovation in higher education: exploratory psychometric validationThis research has a story, like all research. And it is, above all, a human story, like all of them.

A Behind the Paper post in Discover Psychology introduces the“Stela Effect” in higher education where narcissistic traits in university educators, may be linked to higher student ratings and perceptions of innovation, challenging traditional views on effective teaching. #AcademicSky #PsychSciSky

Meet Discover Sustainability. An open-access journal publishing research across all fields relevant to sustainability, from environmental and social challenges to sustainable development. Know more: bit.ly/4hV2ywm

A study published in Discover Mental Health demonstrates that over 10% of laughter occurs in solitude and that it is not only enjoyed but can serve important roles in supporting health and wellbeing. bit.ly/42RWvRx #PsychSciSky

A study in Discover Education proposes the 7Cs positive youth development model as a valuable analytical tool for evaluating arts-based programs and the integration of such approaches into education and youth development policy. bit.ly/4wTRG7F #AcademicSky

bit.lyPredictors of reported dog bite injury severity among human, dog, and cat victims in Southern Colorado - Discover AnimalsDog bites harm both humans and other animals and can range from punctures to fatal wounds. Understanding the factors that are associated with the severity of these bite injuries, including characteristics of biting dogs and victim characteristics, can help public health officials design targeted interventions to reduce harm from bites. We use data from the Humane Society of the Pikes Peak Region of 1,116 reported dog bite incidents between 2019 and 2021 to conduct an exploratory analysis of the associations between sex, alteration status, and bite severity, and find that these are not associated with bite severity in our full sample. However, among our human-only victim sample we find that when the biting dog is male the odds of a severe bite injury compared to a moderate increase by 81.5% - though whether the dog is neutered or not is not associated with this outcome. Additionally, we find a nonlinear relationship between the age of victims and bite severity, with younger and older people more likely to be victims of severe dog bites. These findings add nuance to broader research on the incidence of dog bites by explaining some of the factors that account for more severe bites. In terms of policy, guardians, shelters, and others who interact with dogs should be cognizant of the increased risks posed to the young and the elderly when training and advising adoptions.

A study in Discover Animals analyzes 1,116 reported dog bite incidents in Southern Colorado, revealing that male dogs are associated with an 81.5% increased likelihood of severe injuries to human victims, and highlighting a U-shaped relationship between victim age and bite severity. #MedSky

bit.lyMapping satellite based research on climate change impacts and environmental responses through bibliometric analysis - Discover EnvironmentClimate change affects ecosystems, water resources, and human systems worldwide, while satellite remote sensing provides large-scale and repeated observations of environmental change. However, existing bibliometric assessments often examine individual environmental applications, methodological domains, or broader Earth observation research, providing limited understanding of the integrated development of satellite-based climate–environment research. This study addresses this gap by systematically examining the growth, scientific structure, collaboration patterns, and thematic evolution of satellite-based research on climate change impacts and environmental responses from 2001 to 2025. A dataset of 1,112 documents was compiled from the Web of Science Core Collection and Scopus and analyzed using bibliometric indicators, network analysis, Multiple Correspondence Analysis, thematic mapping, and thematic evolution. The results demonstrate sustained growth in the research field, concentration within a relatively small group of core journals, and a semi-centralized collaboration structure involving prominent authors, countries, and institutions. The thematic analysis reveals continuity of established MODIS- and NDVI-based environmental research alongside the emergence of climate-change-oriented, machine-learning, and cloud-based approaches, particularly random forest and Google Earth Engine. The study provides an integrated view of how satellite-based climate–environment research has developed across interconnected ecosystems, hydrological processes, vegetation dynamics, and climate-related environmental responses. The findings can support researchers in identifying major knowledge structures, emerging research directions, collaboration opportunities, and methodological trends, while also highlighting the need to interpret bibliometric patterns within the coverage limitations of WoS- and Scopus-indexed English-language literature.

A study in Discover Environment provides an integrated view of how satellite-based climate–environment research has developed across interconnected ecosystems, hydrological processes, vegetation dynamics, and climate-related environmental responses. 🌍

A study in Discover Agriculture examines the factors influencing smallholder farmers’ adoption trajectories for three key sustainable agricultural practices in Ethiopia: crop rotation, chemical fertilizer, and soil and water conservation. bit.ly/4hQimQS

bit.lyBeyond Tradition: What Camel Milk Handling in Somaliland Taught Us About Food SafetyCamel milk is deeply woven into daily life and livelihoods in Burao. Our study shows how hygiene, storage, training and traditional handling practices shape food-safety risks and where practical, culturally sensitive improvements can make the greatest difference.

A Behind the Paper post published in Discover Food examines how camel milk is produced, handled, transported and stored in Somaliland and what these practices may mean for consumer safety. #MedSky

bit.lyEnergy justice and gender: bridging equity, access, and policy for sustainable development - Discover SustainabilityClean energy transitions are not just about technology. They are also about people, equity, and justice. Women play a pivotal role in advancing sustainable energy solutions, yet sociocultural, financial, and institutional barriers continue to limit their participation in decision-making and access to clean energy. This research combines BERTopic modeling, SDG mapping, and case study analysis to bridge quantitative insights with real-world narratives, offering a comprehensive examination of the gender‒energy nexus. Grounded in energy justice, gender empowerment, and SDG frameworks, the study applies Kabeer’s and Friedmann’s empowerment models to link agency, resources, and achievements with distributional, procedural, and recognitional justice in energy transitions. The study covered 616 publications identified through an extensive Scopus database search, spanning literature from 2015—coinciding with the adoption of SDGs—to 2024, specifically mapped to SDG 5 (gender) and SDG 7 (energy). Addressing the main energy justice dimensions and relevant SDGs, the findings of this systematic review reveal that clean energy adoption reduces unpaid domestic work (SDG 5.4), enhances women’s leadership (SDG 5.5), and strengthens economic opportunities (SDG 7.1, SDG 7.2) but remains constrained by gendered power dynamics, technology adaptation barriers, and financial accessibility issues. The study highlights how women’s participation in energy transitions leads to greater community engagement, increased household energy efficiency, and a shift toward sustainable energy behaviors. However, moderating factors of gender empowerment interventions show that intrahousehold bargaining, a lack of financial incentives, and limited representation in governance structures continue to restrict equitable energy access. Additionally, the findings emphasize that policies designed without a gender lens risk reinforcing existing inequalities rather than alleviating them. By embedding SDG goals in the analysis, this study ensures alignment with global sustainability goals and reinforces the urgency of justice-oriented energy policies. Advocating for inclusive, community-driven approaches, this research underscores the need for intersectional frameworks that integrate energy justice and gender empowerment, ensuring that energy transitions are not only technologically sound but also socially equitable and accessible to all.

A study published in Discover Sustainability highlights how women’s participation in energy transitions leads to greater community engagement, increased household energy efficiency, and a shift toward sustainable energy behaviors. 🌍

bit.lyDiscover Toxicology, the future journal for your toxicology researchDiscover Toxicology -

An editorial in Discover Toxicology introduces the expertise and experience of the journal's editorial board, including the section editors who comprise its academic leadership, and invites researchers from the toxicology community to publish their next findings in this inclusive platform. #MedSky

As workplaces become increasingly shaped by technology and AI, knowing what makes an effective leader is more important than ever. A study in Discover Psychology finds that higher levels of consciousness are positively associated with stronger executive functioning among leaders. bit.ly/4iUcAjz

A study in Discover Sustainability analyzes the composition and physical characteristics of municipal solid waste in the canton of Balzar (Ecuador) and identifies alternatives for reuse within the framework of the circular economy. 🌍 bit.ly/4f9rn6e

bit.lyEnhancing preservation of tangible cultural heritage artifacts through digital twin technology and deep learning-based 3D point cloud completion - Discover ComputingIntroduction The preservation of tangible cultural heritage artifacts, particularly those created through intangible cultural heritage (ICH) practices such as traditional craftsmanship, is essential for sustainable urban development. Such artifacts embody the skills and knowledge transmitted through ICH. Digital twin technology offers a systematic approach to document and preserve these artifacts digitally. However, obtaining complete 3D models through close-range photogrammetry remains challenging due to occlusion, surface properties, and sensor limitations, resulting in incomplete point cloud data. Methods This study proposes a generative adversarial network with self-attention mechanism to complete missing 3D point cloud data of cultural heritage artifacts. The network employs a multi-layer perceptron for global feature extraction, self-attention modules for local detail capture, and a feature pyramid decoder for hierarchical point cloud generation. Results Quantitative evaluation on the ShapeNet dataset demonstrates that the proposed method achieves average errors of 5.541 (P→GT) and 4.183 (T→P) for complete point cloud completion, outperforming FinerPCN, PF-Net, and PFG-Net. For missing point cloud regions, the method achieves errors of 24.303 (P→GT) and 20.008 (GT→P). Discussion The proposed framework integrates digital twin concepts with deep learning-based 3D reconstruction to enhance the digital preservation of cultural heritage artifacts. By generating more complete and accurate point clouds, the method enables higher-quality 3D models suitable for virtual exhibition, documentation, and cultural transmission. A limitation is that validation on diverse heritage artifact geometries beyond ShapeNet has not yet been conducted.

A study published in Discover Computing presents a proposed framework that integrates digital twin concepts with deep learning-based 3D reconstruction to enhance the digital preservation of cultural heritage artifacts. 🧪

How reliable is social media when it comes to health advice? A study on TikTok's HIV self-testing education shows widespread sharing but varying quality of information. The lack of healthcare professionals highlights the need for improved collaboration with influencers. bit.ly/4AGrGj5 #MedSky

bit.lySystematic review on the potential role of terrestrial gastropods in microplastic transformation and bioremediation - Discover LifeObjective MPs are ubiquitous terrestrial ecosystem pollutants, posing risks to soil health and biota, and eventually food security. Though microbial and insect-mediated degradation of MPs has been explored, the roles of terrestrial gastropods, especially snails, remain underexplored. Methods This review synthesizes the available evidence on the presence of MPs in soils and critically assesses how land snails interact with and transform plastic particles. Literature published within the period 2000–2025 was analyzed to identify mechanisms of ingestion, fragmentation, and partial chemical alteration of plastics by snails. Results The results showed that radular abrasion and digestive processes can cause mechanical fragmentation and partial oxidation of polystyrene, as well as other polymers, in snails. This could increase the bioavailability of microplastics in soil microbial communities. Differences among species in feeding behavior, physiological responses, and gut microbiota composition affect the potential for degradation. Conclusion The review pinpoints the major gaps in knowledge, which relate to the scarce enzymatic evidence and the rarity of long-term or field-based studies. Integrated research is required to establish the ecological relevance and biotechnological potential of gastropods for mitigating soil microplastic pollution. Graphical Abstract

A Systematic Review in Discover Life highlights that terrestrial snails, particularly Achatina fulica, can mechanically fragment and partially chemically alter polystyrene, suggesting their potential as bioremediators in mitigating soil microplastic pollution. 🌍

Dysmenorrhea is a prevalent condition among women of reproductive age, yet many experience medication hesitancy. This Behind the Paper post assesses the prevalence, perception, reasons, alternative treatment practices in dysmenorrhea management among Nigerian female students. bit.ly/4ib2c6J #MedSky

A Review in Discover Oncology discusses potential utility of in silico techniques to bridge the gap between precision oncology and traditional medicine, as well as phytochemicals as supplemental medicines in lung cancer therapy. bit.ly/44Zt3Lf #OncoSky #MedSky

bit.lyMacrophytes-based solutions as tools to halt the collapse of freshwater biodiversity, functions and benefits - Discover EcologyAquatic ecosystems worldwide are increasingly degraded by eutrophication, habitat loss, hydrological alterations, invasive species, and climate change. At

A study in Discover Ecology synthesizes recent evidence on macrophyte-based solutions, their role in enhancing water quality and supporting biodiversity, and outlines the critical conditions and practices needed for successful implementation. 🌍

For decades aging research fixated on genes, but authors of this paper published in Discover Public Health show that living past 100 is shaped by a web of biology, lifestyle, environment, and social ties — not genetics alone. Read more here: bit.ly/4x1tHEa

Municipal solid waste in South Asia is now seen as an opportunity rather than just a disposal challenge. This Behind the Paper blog post highlights how adopting circular economy approaches like recycling and composting could transform waste into valuable resources. bit.ly/4cc4leB 🌍

bit.lyMetal and metal oxide nanoparticle-assisted molecular assays for the detection of SalmonellaDiscover Nano

A paper published in Discover Nano provides a comprehensive overview of the diverse applications and innovations of nanoparticles in the detection of Salmonella. #STS

bit.lyDigital twin-driven edge–cloud collaborative remote fault diagnosis and intelligent predictive maintenance for critical hydropower equipment - Discover Artificial IntelligenceTo address the problems of lagging remote monitoring, complex fault mechanisms, and inefficient maintenance decisions for key equipment in hydropower stations, this paper proposes a remote diagnosis and intelligent maintenance method based on edge-cloud collaboration and digital twin-driven approaches. A layered architecture encompassing equipment, perception, transmission, analysis, and service layers is constructed. A physical-geometric-behavior coupled digital twin model is established, and PLC-SCADA control systems, multi-source monitoring data, fault diagnosis models, and remaining life prediction methods are integrated to achieve a closed loop of equipment status perception, anomaly identification, degradation assessment, and maintenance optimization. Experimental verification is conducted on a dual-unit Pelton hydropower system. Results show that the proposed method exhibits higher fault diagnosis accuracy, better life prediction performance, and superior maintenance economy under complex operating conditions. Unlike existing digital twin-based monitoring systems, the proposed framework integrates edge–cloud collaboration, real-time physical–virtual synchronization, fault diagnosis, RUL prediction, and maintenance optimization into a unified workflow for critical hydropower equipment.

A study in Discover Artificial Intelligence proposes a remote diagnosis and intelligent maintenance method based on edge-cloud collaboration and digital twin-driven approaches for critical hydropower equipment. #STS #AI

bit.lyRainfall thresholds for flood early warning in the Babai River Basin, Nepal using rainfall-runoff modelling - Discover GeoscienceFlood is one of the most common hazards in Nepal that have a severe socio-economic effect especially in Himalayan basins that are dominated by monsoons. In this study, we constructed the rainfall thresholds of flood early warning in the Babai River Basin (BRB) by using a calibrated and validated Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) rainfall-runoff model. The model showed good performance, with the calibration values of NSE = 0.84, R² = 0.87, and PBIAS = − 5.6%, and validation values of NSE = 0.78, R² = 0.81, and PBIAS = − 7.9%. The historical flood occurrences and rain data (1990–2018) were examined at Chepang (mid-basin) and Bhada Bridge (basin outlet). The findings indicate that cumulative rainfall and peak discharge have a significant positive association, and amplified downstream runoff is by virtue of integrated basin runoff. The rainfall thresholds were calculated to obtain bankfull, warning, and danger levels of the river for 1-day, 3-day, and 5-day accumulations. Chepang had 105–110 mm of bankfull, 135–140 mm of warning, and 200–205 mm of danger levels, and the Bhada Bridge needed higher thresholds of 140–145 mm, 185–190 mm, and 240–245 mm for bankfull, warning, and danger, respectively. These thresholds provide a practical advice on anticipatory flood management in addition to current stage-based monitoring. Although the downstream discharge information is not well known and there may be some land-use and climate shifts, the study provides a feasible model of improving early warning of floods in the Himalayan basins. Communities at floods risk are ensured safer and more resilient with real time monitoring combined with risk-based planning.

22 Sept

Nepal and India face significant flood hazards in the Himalayan basins. A study in Discover Geoscience utilizes the HEC-HMS model to establish early warning rainfall thresholds for the Babai River Basin, enhancing real-time flood forecasting and preparedness.

21 Sept

A study in Discover Psychology proposes an explainable AI-based framework that can be used as a mental health screening and clinical decision-support tool to support early identification of individuals at risk. bit.ly/4habmy5 #PsychSky #STS #AI #MedSky

bit.lyImproving reliability of large language models via claim-level self-verification and uncertainty calibration - Discover Artificial IntelligenceLarge Language Models (LLMs) often generate fluent answers that appear confident even when they contain factual errors. This creates a reliability problem because users may trust incorrect answers when the model provides no meaningful signal of uncertainty. This paper proposes CLAIM-CAL, a claim-level self-verification framework for calibrated LLM reliability. Instead of assigning confidence to a complete answer directly, CLAIM-CAL decomposes an answer into atomic factual claims, verifies each claim using multiple verification probes, converts claim-level verdicts into a risk score, and then applies post-hoc calibration to obtain a more reliable confidence estimate. We evaluate CLAIM-CAL on the TruthfulQA generation benchmark using a 200-example experimental run with 60 examples for calibration and 140 examples for held-out testing. The proposed method is compared against direct answering, verbal confidence, self-consistency, and simple self-verification. In the held-out comparison, raw CLAIM-CAL achieved the highest observed accuracy among the evaluated methods but remained overconfident. Isotonic calibration reduced Expected Calibration Error (ECE), a bin-weighted gap between predicted confidence and empirical accuracy, from 0.212 for raw CLAIM-CAL to 0.038 [95% CI: 0.015, 0.106] after calibration, while maintaining accuracy at 0.757. To address calibration as a possible confound, we additionally applied isotonic calibration to the variable-confidence baselines on the same 60-example calibration split. In this fair calibrated comparison, CLAIM-CAL + Calibration achieved the strongest point estimate for 10-bin equal-width ECE (0.038) and Brier Score (0.146), although paired bootstrap confidence intervals show that ECE differences versus the closest calibrated baselines should be interpreted cautiously. The calibrated method also achieved selective accuracy of 0.824 at a 0.7 confidence threshold with 0.893 coverage. A second-pass judge prompt-robustness check on 50 sampled evaluations achieved 96.0% agreement and Cohen's kappa of 0.896. These findings suggest that claim-level verification produces a useful reliability signal, and that calibration is necessary to convert that signal into trustworthy confidence estimates for selective answering.

20 Sept

What if ChatGPT had to fact-check every sentence before answering?" A study in Discover Artificial Intelligence introduces CLAIM-CAL, a framework that breaks an LLM response into individual factual claims, verifies each claim independently, and then calibrates the model's confidence score. #STS

bit.lyRethinking Dengue Surveillance in BangladeshFollowing Bangladesh’s deadliest dengue outbreak, we examined how existing surveillance systems capture dengue burden and where gaps remain. This post shares the story behind our narrative review and why integrated surveillance matters.

19 Sept

Following Bangladesh’s deadliest dengue outbreak, this Behind the Paper blog explores how existing surveillance systems capture dengue burden, what gaps remain, and why integrated surveillance matters. #MedSky

bit.lyBringing Ancient Art to Life: Breathing Life into Shanshui Art with AI and Perlin NoiseWhen we think of traditional Chinese Shanshui (mountain-water) paintings, we imagine serene, timeless scenes of misty mountains and flowing rivers—a harmony between nature and artistic expression that has been refined over centuries. But what if these tranquil landscapes could come to life?

18 Sept

What if an ancient Chinese landscape painting could breathe, flow, and move? In this behind the Paper blog, researchers combine Perlin Noise, Stable Diffusion, ControlNet, GPT-4, and AnimateDiff to transform traditional Shanshui art into dynamic animations while preserving its cultural essence. #AI

bit.lyFirst documentation of humpback whale (Megaptera novaeangliae) post-mortem attendance of a stillborn - Discover AnimalsCetaceans are some of the most charismatic marine species receiving regular widespread public attention. They display highly complex behaviour including post-mortem attentive behaviour sometimes referred to as grieving behaviour. Post-mortem attentive behaviour in cetaceans has been documented predominantly among odontocetes and remains largely absent from the literature on baleen whales, limiting current understanding of the cognitive and emotional dimensions of death-related responses in mysticete cetaceans. Here, we describe a case of prolonged post-mortem behaviour by a female humpback whale and her escort toward a deceased calf. The adult female remained in close proximity to the calf, engaging in repeated interactions and maintaining attendance over several hours and possibly days. Unlike reports in odontocetes, the female did not attempt to lift the calf to the surface. The observed behaviours were consistent with epimeletic and post-mortem attentive responses documented in socially complex mammals and indicating a strong maternal attachment to the calf. This case study highlights the need for continued systematic documentation of rare neonatal mortality events to better understand the cognitive, emotional, and evolutionary significance of post-mortem behaviour in large whales. Understanding how nonhuman animals respond to death provides insight into their emotional lives, social bonds, and cognitive capacities.

17 Sept

What does grief look like in the ocean? A study in Discover Animals provides the first detailed documentation of a female humpback whale staying with and attending to her stillborn calf after death. The observation adds to growing evidence that some cetaceans may exhibit complex responses to loss. 🌍

bit.lyRecent advances and future prospects in methanol fuel cell technologies - Discover ElectrochemistryPurpose To review the current advances, persistent challenges, and future prospects of methanol fuel cell technologies, thereby supporting the transition toward low-carbon energy systems. Design/methodology This is a comprehensive review that analyzes recent global progress across key aspects of methanol fuel cell technology. The focus areas include catalyst development, membrane innovation, performance optimization, and system integration. Findings Recent advances in electrocatalysts, nanostructured membranes, and hybrid system designs have substantially enhanced the efficiency, durability, and operational flexibility of methanol fuel cells. This progress has enabled their expansion in transportation, portable electronics, stationary power, and industrial energy generation. Originality/value This review offers a holistic overview of the current state-of-the-art and identifies critical limiting factors, such as methanol crossover, limited long-term durability, and high production costs, that continue to constrain commercialization. It emphasizes the need for coordinated, multidisciplinary efforts in materials science and system engineering, alongside favorable policies, to accelerate adoption and position methanol fuel cells as an integral component of the future renewable-energy landscape.

16 Sept

A Review published in Discover Electrochemistry examines the current state, challenges, and future trajectory of methanol fuel cell technologies.

15 Sept

A Behind the Paper blog from Discover Sustainability examines how rural households in drought-prone Somaliland are adapting to changing livelihood conditions by combining farming, livestock and non-farm activities to manage climate and economic uncertainty. bit.ly/4rer6EL

bit.lyEvaluation of temperature and radiation based reference evapotranspiration methods over Cross River basin Nigeria - Discover EnvironmentThe accurate estimation of reference evapotranspiration (ETo) on seasonal and annual scale is vital for determination of water requirement of crops and impact of climate change on irrigated agriculture. This study investigates the influence of climatic variables (temperature, relative-humidity, solar-radiation, and wind speed) on ETo and comparison of the performance evaluation of temperature and radiation-based models over Cross River basin on seasonal and annual basis. Estimation of ETo was done using temperature-based; Schendel, Samani, Trajkovic, Droogers & Allen-2, Dorji, Hadria, Hargreaves-samani, Blaney-Morin-Nigeria, and radiation-based models; Jensen-Haise, Stephens and Stewart, Oudin, Abtew, Irmak-1, Copais, Tabari & Talaee-4, and Hargreaves under humid-tropic condition, with Penman–Monteith (PM-ETo) as a reference. Remotely-sensed meteorological variables from 1987 to 2017 were sourced from the Climatic Research Unit (CRU) database, over 22 stations. These variables were used for estimating ETo. Models were evaluated with coefficient of determination, a root-mean-square-error, Willmott’s index of agreement, Percentage-Bias and Nash–Sutcliffe Efficiency. Sensitivity analysis (± 5%) revealed that PM-ETo was most sensitive to solar-radiation and temperature, compared to relative-humidity and wind speed. Blaney-Morin-Nigeria demonstrated seasonal estimation bias. Further analysis revealed that radiation-based models out-performed the temperature-based models across all categories. Blaney-Morin-Nigeria and Copais recorded the best performance in dry season, while Hargreaves–Samani and Abtew recorded the best performance in rainy season. Abtew and Hargreaves–Samani recorded the best performance on annual basis. An increasing trend (slope = 0.0029 mm/day) of PM-ETo further suggests global warming scenario. This demonstrates the ability of radiation-driven models for crop water requirement estimation in data-scarce regions.

14 Sept

A study published in Discover Environment finds that radiation-based evapotranspiration (ETo) models outperform temperature-based ones in the Cross River basin, proving them as more reliable for seasonal and annual irrigation planning in data-scarce regions. 🌍

bit.lyResearch progress of exosomes used in the Alzheimer's disease treatment - Discover NanoAbstract Alzheimer's disease (AD) is a common form of dementia characterized by memory loss, cognitive and linguistic abilities declining and self-care capabilities diminishment. With the aging population globally, AD poses a significant threat to public health. Current treatments for AD aim to alleviate symptoms and slow down disease progression, but due to the limited understanding of underlying disease mechanisms, AD is still impossible to be cured yet. In recent years, there has been an exponential growth in exosome-related research because of their excellent biocompatibility ability, loading capacity and cellular internalization, making exosome to be one of the hotspots and a promising strategy in AD therapy research. This comprehensive review systematically explores the potential roles of various exosome-based nanotherapeutic strategy in AD treatment, with a particular focus on their specific biological mechanisms of action. Firstly, we elaborated on the pathological mechanisms of AD formation as well as the mechanisms related to the formation, secretion and function of exosome. Additionally, we highlighted the research progress in the development of exosome-based nanotherapeutic strategies for AD treatment and their corresponding biological mechanisms. Furthermore, we delved into the challenges and opportunities these strategies facing in clinical application. Looking forward to future research directions and trends, our review aims to provide a more comprehensive understanding and guidance with the application of exosome in AD treatment. Exosome-based nanotherapeutic strategies, as a new therapeutic approach, have opened up new possibilities for the treatment of AD and brought new light to patients. Graphical abstract Schematic diagram of exosome-based nanotherapy strategies for the treatment of AD. It can be roughly classified as: exosomes-based methods treating AD and bioengineered exosomes for the treatment of AD.

13 Sept

A Review published in Discover Nano explores the potential roles of various exosome-based nanotherapeutic strategies in Alzheimer’s disease treatment, with a particular focus on their mechanisms of action. #MedSky #alzsky

12 Sept

In a study published in Discover Public Health, authors use the Theory of Triadic Influence to illustrate how family, peers, and culture influence tobacco use. They emphasize that tobacco control is also about protecting futures and empowering communities beyond just policy. bit.ly/3T3I0J6

11 Sept

Early career researchers (ECRs) face a fundamental challenge: how do you transform promising research into real-world impact? This case study shows how a Springer Nature collection published in a Discover journal led to WHO citations & worldwide recognition: bit.ly/4hZEyYB #MedSky

bit.lyEnergy justice and gender: bridging equity, access, and policy for sustainable development - Discover SustainabilityClean energy transitions are not just about technology. They are also about people, equity, and justice. Women play a pivotal role in advancing sustainable energy solutions, yet sociocultural, financial, and institutional barriers continue to limit their participation in decision-making and access to clean energy. This research combines BERTopic modeling, SDG mapping, and case study analysis to bridge quantitative insights with real-world narratives, offering a comprehensive examination of the gender‒energy nexus. Grounded in energy justice, gender empowerment, and SDG frameworks, the study applies Kabeer’s and Friedmann’s empowerment models to link agency, resources, and achievements with distributional, procedural, and recognitional justice in energy transitions. The study covered 616 publications identified through an extensive Scopus database search, spanning literature from 2015—coinciding with the adoption of SDGs—to 2024, specifically mapped to SDG 5 (gender) and SDG 7 (energy). Addressing the main energy justice dimensions and relevant SDGs, the findings of this systematic review reveal that clean energy adoption reduces unpaid domestic work (SDG 5.4), enhances women’s leadership (SDG 5.5), and strengthens economic opportunities (SDG 7.1, SDG 7.2) but remains constrained by gendered power dynamics, technology adaptation barriers, and financial accessibility issues. The study highlights how women’s participation in energy transitions leads to greater community engagement, increased household energy efficiency, and a shift toward sustainable energy behaviors. However, moderating factors of gender empowerment interventions show that intrahousehold bargaining, a lack of financial incentives, and limited representation in governance structures continue to restrict equitable energy access. Additionally, the findings emphasize that policies designed without a gender lens risk reinforcing existing inequalities rather than alleviating them. By embedding SDG goals in the analysis, this study ensures alignment with global sustainability goals and reinforces the urgency of justice-oriented energy policies. Advocating for inclusive, community-driven approaches, this research underscores the need for intersectional frameworks that integrate energy justice and gender empowerment, ensuring that energy transitions are not only technologically sound but also socially equitable and accessible to all.

10 Sept

A study published in Discover Sustainability highlights how women’s participation in energy transitions leads to greater community engagement, increased household energy efficiency, and a shift toward sustainable energy behaviors. 🌍

bit.lyAxial compression behavior of FRP reinforced concrete columns based on database analysis and finite element validation - Discover Civil EngineeringThis study presents a comprehensive analytical evaluation of the axial compression behavior of fiber-reinforced polymer–reinforced concrete (FRP-RC) columns. The investigation focuses on the combined effects of transverse confinement, FRP material type, column geometry, and concrete compressive strength, while explicitly considering both short and slender column configurations to evaluate the influence of geometric slenderness on structural response. The compiled experimental database covers concrete strengths ranging from approximately 10 to 90 MPa and includes columns reinforced with glass fiber–reinforced polymer (GFRP) and carbon fiber–reinforced polymer (CFRP) longitudinal bars and transverse reinforcement. The database analysis indicates that reducing spiral pitch from relatively wide spacing (100–120 mm) to dense configurations (35–40 mm) leads to a significant increase in normalized axial strength (approximately 50–100%) and enhances post-peak stability. Increasing concrete compressive strength from 30 to 50 MPa is associated with an increase in peak load of approximately 20–40%, accompanied by a reduction in ductility of about 25–35%. Columns reinforced with CFRP generally exhibit higher axial capacity than their GFRP counterparts, with observed strength gains in the range of 15% to 50%, primarily due to the higher stiffness and confinement efficiency of CFRP. Geometric effects are also pronounced. Circular columns tend to provide 10–25% higher normalized capacity compared to square sections. In addition, increasing column slenderness (higher L/D ratio) is associated with reductions in axial strength of approximately 20–30%, reflecting the influence of stability and second-order effects. A nonlinear finite element model was employed to support and extend the experimental trends observed in the database analysis. The numerical simulations captured consistent behavioral patterns, confirming the sensitivity of peak load and post-peak response to confinement intensity, concrete strength, FRP stiffness, and slenderness ratio. Comparisons with common design provisions indicate generally good agreement between predicted and experimental strengths, with experimental-to-predicted ratios typically ranging from 0.95 to 1.10, although both conservative and unconservative predictions are observed, particularly for lightly confined or slender columns. The combined experimental synthesis and numerical validation provide a unified understanding of the governing mechanisms controlling the axial behavior of FRP-RC columns and offer a strengthened basis for future refinement of design recommendations.

9 Sept

By validating numerical models against a broad dataset, this study in Discover Civil Engineering, contributes valuable insights into the load-bearing behavior of FRP-reinforced concrete columns and supports the development of more reliable design approaches for sustainable construction.

bit.lyMapping the presence of artificial intelligence in investment fund: a systematic review - Discover Artificial IntelligenceObjective This study systematically reviews the integration of artificial intelligence (AI) with investment funds in the asset management industry and emphasizes its transformative impact. Aiming to bridge knowledge gaps, this study explores AI's position within the industry, analyzes its variety, and assesses the transformational implications of existing practices. Methodology Adhering to systematic review methodology, a comprehensive search was conducted across the Web of Science and Scopus databases, identifying 27 high-quality studies published from 2020 to 2024. The study was then analyzed thematically. Findings The first theme of the review classifies AI applications into front-end and back-end roles, illustrating the transition from traditional processes. On the front-end, AI assists simple activities by analyzing an investor's profile to determine a suitable fund, similar to a human financial consultant. The back-end sees AI performing autonomous trading and managing pooled fund investments, resembling a human fund manager. As a secondary theme, this review analyse AI deployment include using robo-advisors and chatbots for front-end tasks, screening analysis, predictive analytics, automated algorithmic trading, and automated trading technical analysis for back-end tasks. This study also includes a deductive discussion on the implications and transofrmation of AI deployment. Contribution/implications This review serves as an analytical framework to highlight AI in investment funds in asset management and serves as a springboard for future research and industrial applications.

8 Sept

A Review in Discover Artificial Intelligence serves as an analytical framework to highlight AI in investment funds in asset management and serves as a springboard for future research and industrial applications. #STS

bit.lySmart digital marketing for sustainable ecotourism: an integrated process optimization and fuzzy logic framework for adaptive decision-making - Discover SustainabilityThis study addresses the challenge of achieving sustainable marketing performance in fragile ecotourism destinations, where marketing activities must balance competitiveness with environmental preservation. A hybrid Smart Digital Marketing (SDM) framework that integrates Digital Six Sigma Marketing (DSSM) with fuzzy logic-based decision systems is developed and empirically evaluated to support adaptive decision-making under ecological constraints. Using an explanatory sequential mixed-methods design, the study combines survey data (N = 250), stakeholder interviews (N = 18), environmental observation scorecards, and computational modeling. The framework operationalizes three ecological and behavioral variables—environmental fragility, visitor load, and tourist satisfaction—as inputs to a Mamdani-type fuzzy inference system with 27 if–then rules, producing adaptive marketing intensity decisions aligned with carrying capacity. The pre–post analysis showed statistically significant observed improvements associated with framework implementation: campaign response time was reduced by 35.7%, process variance decreased by 39.4%, the process capability index increased from 0.94 to 1.42, and competitive positioning improved by 24.3%. The fuzzy inference system demonstrated adaptive modulation of marketing intensity from 0.80 under stable conditions to 0.19 under high ecological risk. The study contributes a practical, data-driven decision-support framework that enables organizations to align marketing strategies with ecological thresholds, extending Smart Digital Marketing as a dynamic capability within sustainability-sensitive tourism contexts. The framework provides a potentially transferable model for translating qualitative and ambiguous variables into structured, adaptive marketing decisions under environmental uncertainty.

7 Sept

Can AI-driven marketing help make tourism more sustainable? A study in Discover Sustainability suggests a practical, data-driven decision-support framework that enables organizations to align marketing strategies with ecological thresholds for sustainable ecotourism. 🌍