A document by Suryakant Verma. Click on the document to view its contents.

Objective: To examine differences in location of service and management for patients receiving early pregnancy loss (EPL) care based on racial/ethnic identity Design: Retrospective cohort study Setting: A single university-affiliated urban tertiary care center in the United States Population: A cohort of 796 received care for EPL at a single university-affiliated urban tertiary care center from July 1, 2021, through June 30, 2023. Methods: Descriptive statistics for demographic factors were generated reporting frequencies and percentages, continuous variables were expressed as a mean with standard deviation, and chi-squared tests were performed. Descriptive statistics were used to describe the demographics of this patient population and frequency of location of service and management type. Multivariate logistic regression models assessed the relationship between location of services (ED and OB triage vs. other), management type (expectant vs. active management), and patient race and ethnicity. Statistics are reported as adjusted odds ratio (aOR) and 95% confidence interval (CI). Main Outcome Measures: location of service, management type Results: There were differences in care location and management based on race/ethnicity. Black/African/African American and Hispanic/Latinx patients were more likely to receive care in the emergency department or gynecology triage compared to their white counterparts. Black/African/African American patients were also more likely to receive expectant management and office procedural management compared to their white counterparts. Receiving treatment in the emergency department or gynecology triage was associated with expectant management. Conclusions: Racial disparities exist in both location of service and management type for EPL.

Objective: This study explores the relationship between pregnancy intentions and maternal, newborn and child health (MNCH) behaviors. Design and Setting: Secondary data analysis of recent (2018-2023), cross-sectional Demographic and Health Surveys from 18 sub-Saharan African countries. Population: Survey respondents were women aged 15–49 years old with a child less than a year old who responded to survey questions about their pregnancy intentions for that child (N= 39,936). Methods: Logistic regressions and meta-analysis using fixed effects explored the relationship between pregnancy intentions and MNCH behaviors across study countries adjusting for sociodemographic and contextual variables. Measures: Pregnancy intentions were defined as i) intended versus unintended. MNCH behaviors included i) early ANC, ii) 4+ ANC contacts (ANC4+), iii) 3+ doses of intermittent preventive treatment of malaria in pregnancy (IPTp3+), iv) receipt of tetanus toxoid and v) immediate breastfeeding. Results: Overall, 24% of women did not want their index pregnancy (ranging from 11% in Burkina Faso to 48% in Gabon). Unintended pregnancies were associated with reduced odds of early ANC (aOR: 0.69, 95% CI: 0.66, 0.73), IPTp3+ (aOR: 0.85; 95% CI: 0.80, 0.90), receiving tetanus toxoid (AOR: 0.75; 95% CI: 0.69, 0.81), and immediate breastfeeding (AOR: 0.83; 95% CI: 0.80, 0.86). Conclusions: Study findings corroborate the role of reproductive health agency and pregnancy preparedness in optimizing maternal, newborn and child health outcomes. Integration of reproductive health services, malaria service delivery, and social and behavior change interventions can help to improve pregnancy outcomes.

OBJECTIVES: To assess the feasibility of ‘Tele-health Postoperative follow-up care Model’ in terms of provider, process and service recipient and to identify barriers, facilitators, robustness, safety and acceptability of the model. DESIGN: Feasibility Study SETTING: UCMS and GTB Hospital, Delhi, India POPULATION: Patients admitted in gynaecology ward for major elective gynaecological surgery METHODS: Women undergoing major elective gynaecological surgery from May 2023 to November 2024 were enrolled for follow-up using a telehealth model, consisting of virtual visits on days 7, 14, and 30, and a physical visit on day 42. Participants completed Modified Quality of Recovery-15 (Qo5-15) forms and satisfaction questionnaires. MAIN OUTCOME MEASURES: Feasibility of telemedicine follow-up (virtual vs. physical visits), provider and recipient satisfaction scores, technological performance, barriers (connectivity issues, missed appointments), facilitators (time and cost savings), efficacy (successful care delivery, complications), safety, and acceptability (adherence, satisfaction, costs). RESULTS: It was feasible to complete the ‘model’ follow-up in 60 patients with average number of 3.03 ± 0.18 virtual visits & 1.17 ± 0.41 physical visits respectively. Patient satisfaction was scored at (4.81/5) while provider satisfaction ranged from 4.73 to 4.95/5 through this model. In addition, patients saved on an average 205 minutes and 343.50 INR. Complications were encountered in 13.3% cases; majority managed successfully. 88.30% patients preferred a similar follow-up telehealth model in future. Modified QoR-15 score progressively increased throughout visits. CONCLUSION: Tele-health post-operative follow-up care model can be used as an upgradation to the existing postoperative services, even in low resource settings.

Noise, a prominent characteristic of cities and urban areas, can be harmful to a range of biota, especially animals dependent on acoustic communication. Urban noise, or anthrophony, is predominately low frequency, and can mask calls or put pressure on individuals to adjust their calls accordingly. Birds in urban areas appear to be singing at higher frequencies compared to their rural counterparts, but the mechanisms underlying these differences remain unresolved. Studying variation in noise levels at fine spatial scales will facilitate disentangling evolutionary from plastic responses to anthrophony, and help safeguard healthy bird populations. Along an urban-rural gradient, this study investigated the effect of urban noise on call parameters of the European robin (Erithacus rubecula). I also explored the impact of habitat size, distance from the edge of greenspaces, and distance from the nearest busy road on local noise levels. Road din was greater on weekdays, and distance from the nearest busy road was the only habitat characteristic that explained variation in local anthrophony. Minimum call frequency increased with anthrophony power density, while other call parameters were largely unaffected. These results are consistent with acoustic adaptation theory predicting increases in minimum frequency, and other plastic responses observed in robins. Because I observed differences in minimum frequency at fine spatial scales, it is unlikely that differences between urban and rural robins are due to evolutionary responses to urban din. Plasticity is a likely trait in urban birds, especially when confronted with variable noise sources and intensities. Future work should investigate the scope of this plasticity, both within robins and across urban birds.

Energy plays a fundamental role in driving economic growth, shaping industrial productivity, and fostering technological innovation. This study examines the intricate relationship between energy consumption and economic development, focusing on the experiences of countries such as the United States, Germany, China, Nigeria, Nepal, and Chile. The research explores key themes, including advancements in renewable energy, energy efficiency improvements, and the deployment of innovative energy technologies such as smart grids and battery storage systems. Findings emphasize the necessity of integrating energy sustainability into national economic strategies. The study highlights the role of policy interventions, technological advancements, and international cooperation in creating resilient and diversified energy systems to support long-term economic stability and environmental sustainability.

Poorly known, rare species are important biodiversity elements; understanding the relationships between their effective numbers, geographical distribution, ecology, and adaptive potential is an unquestionable, critical aspect to reverse biodiversity decline under climate change. Quercus crenata Lam. is a sporadic Mediterranean tree species with debated taxonomy and evolutionary history. Confusing identifications and a scattered distribution combine to an incautious lack of comprehensive and reliable information on its spatial distribution, ecology, and genetic resources, thereby hindering correct management and conservation efforts. This work undertook a first decisive step to address these knowledge gaps, integrating all previous dispersive information and presenting a comprehensive map of Q. crenata occurrences, with 923 established records: 495 new field observations and 428 verified from all available literature and online databases. The taxon occurs with extremely low individual numbers across central and northern Italy, southern France, western Slovenia and Croatia, mainly at altitudes between sea level and 1100 m a.s.l. The largest part of the species records are outside current networks of protected areas. The MaxEnt-based distribution model highlights Q. crenata adaptation to mild Mediterranean climates with moderate temperature fluctuations, moderate-to-high water requirements, and diverse soil types. A broader present potential distribution than currently assessed is suggested, underlining the possibility to identify new occurrences with accurate searches in targeted sites. Future range projections under three carbon emission scenarios with increasing severity (SSP1, SSP3, and SSP5) predict substantial range losses by 2100, ranging from 32% to a drastic 99% reduction under the most severe scenario (SSP5). On these bases, our findings underline the urgent need to improve current conservation practices, which should be conveniently implemented by exhaustive genetic investigations.

Globally, mammal species are experiencing unprecedented rates of extinction. Despite this, many small mammals remain understudied and even undescribed, posing a major barrier to effective conservation planning. Without formal study and documentation, it is impossible to make well informed management decisions for these species. This issue is particularly pronounced in Australia, where not only is the mammal extinction rate the highest in the world but the vast inaccessibility of much of the continent, combined with a shortage of expert taxonomists, has left a large portion of small mammal diversity poorly documented. One example of is the kultarr (Antechinomys laniger), a small, insectivorous marsupial in the family Dasyuridae that is distributed across much of the Australian arid zone. While currently considered a single species, previous morphological and molecular studies have suggested the presence of cryptic taxa within the group. Here, we resolve the taxonomy of the kultarr using 12S mitochondrial sequence data and genome-wide single nucleotide polymorphisms. We identify three clades of kultarr that are morphologically distinct, largely allopatric and show minimal evidence of genetic admixture. These clades differ in hindfoot length, body size, ear size, and craniodental morphology. The clades consist of an eastern semi-arid clade, a central Channel Country/Kati Thanda-Lake Eyre Basin clade, and a western deserts clade. We rediagnose A. laniger sensu stricto as the eastern clade, resurrect A. spenceri as the central clade and describe a new species, A. auritus sp. nov., as the western clade. This research highlights the importance of integrating morphological and genetic data in small mammal taxonomy and emphasises the need for comprehensive geographic sampling within widespread species complexes.

Pithecophaga jefferyi Ogilvie-Grant 1896 or the Philippine Eagle is endemic to the Philippines, and is currently listed as an IUCN “critically endangered” species. There is currently an urgent need for genetic information to enhance conservation breeding and preserve the genetic diversity of this species. In this study, we explored the use of mitogenome sequencing as a cost-effective alternative for the genetic studies of Philippine Eagles. Analysis of partial mitogenomes revealed a mean nucleotide diversity of 0.10 to 0.16 from the 27 samples sequenced. This is much lower compared to most threatened bird species. Furthermore, we also observed that most samples belong to a single genetic cluster based on k-means clustering of the pairwise genetic distances, although we detected potentially two distinct subpopulations which was supported by an isolation by distance analysis. Nevertheless, some Philippine Eagle individuals showed distinct nucleotide profiles, with eagles from three key biodiversity area dyads exhibiting high FST, indicating potential genetic differentiation. This suggests limited gene flow between these KBAs, but also their potential use to reinforce the nucleotide diversity in Philippine Eagle captive breeding programs. Finally, phylogenetic analysis of Philippine Eagles and other members of the Order Accipitriformes corroborates previous findings on the non-monophyletic status of the subfamily Circaetinae or the snake-eagles. Altogether, we demonstrate the utility of mitogenomes in assessing the genetic diversity and evolutionary relationships of avian species. Given the huge per-sample cost of whole genome sequencing, the approach utilizing mitogenome sequencing provides a cost-effective alternative to facilitate genetic studies of animals. We therefore anticipate an increasing utility of mitogenomes in population studies for biodiversity and genetic conservation research in the Philippines.

A document by yannian du. Click on the document to view its contents.

Large Language Models (LLMs) have revolutionized artificial intelligence by enabling sophisticated natural language understanding, generation, and reasoning. As these models evolve, context awareness has become a crucial factor in improving their adaptability, coherence, and decision-making capabilities. This paper explores the evolution of LLMs from rule-based systems to deep learning architectures, emphasizing advancements in contextual embeddings, multimodal learning, and real-time adaptation. We discuss the impact of reinforcement learning with human feedback (RLHF), memory-augmented models, and transformer-based architectures in enhancing contextual sensitivity. Additionally, ethical concerns such as bias, misinformation, and privacy risks are examined alongside mitigation strategies. The paper concludes by assessing future trends, including the integration of LLMs with edge AI, federated learning, and knowledge graphs to achieve more reliable, efficient, and human-aligned AI systems.

Biosimilar development of monoclonal antibodies (mAbs) is gaining significant momentum as numerous blockbuster biologics approach their patent expiry in the current decade. A critical challenge in biosimilar development lies in achieving product quality attributes comparable to the innovator product. The product quality attributes (PQAs) in upstream processing are influenced by multiple factors, including cell line selection, media composition, feed strategy, supplements, and bioreactor process parameters, with physical parameter optimization playing a pivotal role in enhancing both product titer and modulating PQAs. In this study, we systematically evaluated the impact of physical process parameters - pH, temperature, and initial seeding density - on N-glycan profiles and charge variants across four biosimilar development projects (Projects 1-4). Prediction models were developed using JMP software to establish parameter-attribute relationships. Our results demonstrated that lowering bioreactor pH reduced % acidic variants and % Afucosylation (AF) while increasing % basic variants and % galactosylation. Similarly, increased culture temperature resulted in lower % acidic variants and % AF. This knowledge base was successfully applied to expedite the development of a fifth mAb biosimilar development (Project 5), substantially reducing experimental iterations and development timelines, exemplifying the practical implementation of Bioprocessing 4.0 principles.

The rapid evolution of digital technologies has challenged traditional legal frameworks, necessitating the continuous adaptation of cyber law to address emerging societal and ethical concerns. This study examines the evolution of legal theory in the digital era, focusing on comparative perspectives of cyber law across different jurisdictions. It explores key areas such as data privacy, intellectual property, cybersecurity, digital rights, and the role of artificial intelligence in legal decision-making. By analyzing legislative developments, judicial interpretations, and regulatory frameworks, this research highlights the varying approaches nations adopt to balance innovation, security, and individual freedoms. Furthermore, the study assesses the societal implications of cyber law, particularly in the context of online governance, digital identity, and the ethical dilemmas posed by algorithmic decision-making. Through a comparative analysis, this research aims to identify best practices and propose a harmonized approach to cyber law that ensures legal adaptability and protects fundamental rights in an increasingly digital world. The findings contribute to the ongoing discourse on legal modernization, advocating for policies that promote technological advancement while safeguarding societal interests.

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1. IntroductionThe rapid digitization of healthcare records has led to an exponential increase in the volume of medical reports generated daily. Physicians, researchers, and healthcare providers must analyze these reports quickly to make informed clinical decisions. However, the sheer amount of textual data presents challenges in terms of processing time, information retrieval, and cognitive overload. Traditional summarization techniques, such as rule-based and statistical methods, often fall short in generating concise, contextually accurate summaries. Recent advancements in Natural Language Processing (NLP), particularly with transformer-based models like BERT, T5, and GPT, have demonstrated remarkable performance in text summarization tasks. Leveraging these models in a real-time, cloud-based framework can significantly enhance medical report summarization, improving efficiency and decision-making in healthcare environments.

1. The fitness of ramets or the whole clone may decline with risk spreading, although clonal plants can benefit much from clonal integration or division of labor. Whether clonal plants can alleviate these negative effects by severing stressful ramets as trees litter their old leaves and lower shading branches for resource economy deserves further research. 2. We determined whether an invasive clonal plant (Alternanthera philoxeroides) could selectively detach ramets subjected to extreme stress, thereby optimizing resource allocation and benefiting the remaining unstressed ramets. We named this functional trait anti-clonal integration, corresponding to the term clonal integration. 3. The results showed that the percentage of anti-clonal integration in A. philoxeroides increased with the stress duration. Furthermore, this percentage was greater under drought stress compared to shading or combined drought and shading stresses, and it was greater when the apical ramets were stressed than when the basal ramets were stressed. Moreover, the alive unstressed ramets benefited significantly from anti-clonal integration, and this benefit was greater when the apical ramets were stressed compared to when the basal ramets were stressed. 4. These findings suggested that clonal plants could optimize their resource allocation to enhance the fitness of the entire clones through anti-clonal integration under extreme stress conditions. Moreover, clonal plants may adopt either anti-clonal integration or clonal integration strategies to adapt to stressful environments depending on the stress intensity, thereby gaining competitive advantages. Nevertheless, whether this functional trait of anti-clonal integration applies to all clonal plants remains unclear, thus warranting further investigation. 5. Synthesis. We provide evidence that clonal plant A. philoxeroides could optimize their resource allocation to enhance the fitness of the entire clones through anti-clonal integration under extreme environmental stress conditions.

As we navigate the evolving public health landscape in Somalia, this study provides a comprehensive analysis of critical challenges, including water, sanitation, and hygiene (WASH), malnutrition and food insecurity, infectious diseases, maternal and child health, and the rising burden of non-communicable diseases (NCDs). The aftermath of prolonged conflict, economic instability, and environmental crises underscores the urgent need to strengthen healthcare infrastructure, enhance disease surveillance, and improve multi-sectoral collaboration. The complexities of governance, humanitarian aid, and healthcare access highlight the necessity for coordinated efforts between government institutions, NGOs, and international partners. From the urgent need to combat infectious disease outbreaks to the persistent challenges of food insecurity and high maternal mortality rates, this study explores multifaceted issues, advocating targeted interventions, sustainable policies, and equitable healthcare delivery. Addressing the root causes of public health disparities requires a commitment to resilience-building, community engagement, and policy-driven solutions. In this critical period, Somalia must embrace a unified vision that fosters collaboration, policy reform, and strategic investments, ensuring a future where public health remains a central pillar of national development and humanitarian response.

Reliable projections of tropical cyclones (TCs) and associated impacts remain hampered by both climate model resolution and simulation length. To address this, here we present updated projections of TCs for the southwest Pacific from a high-resolution downscaled ensemble of CMIP6 models. The downscaling implements a variable-resolution atmospheric model enhancing resolution over the southwest Pacific and New Zealand (~12-30km). We assess future changes in TC frequency, changes in large-scale environmental conditions, and associated extreme precipitation and winds across tropical and ex-tropical storm phases. Changes in TC track pathways are also investigated through cluster analysis. Across the downscaled simulations, robust changes in TC frequency were not found, including for a high-emissions scenario at end-of-century. Projections of the background environmental conditions are shown to be a significant source of uncertainty, owing to diverging projections of relative SST and tropical convection across the region in the host GCMs. However, very strong TCs (category 4 and above) show greater consensus for an increase in frequency, with 16 of 18 simulations across models and scenarios projecting an increase. Cluster analysis of TC tracks indicates a slight decrease in tracks that often impact northern parts of Australia. Extreme precipitation associated with TCs under a high-emissions scenario is projected to increase by ~30-35% averaged across models, both for storms in the tropics and ex-TCs impacting New Zealand. This increase exceeds Clausius-Clapeyron scaling in 5 of 6 simulations. These projected increases in associated extreme precipitation pose significant societal risks despite the remaining uncertainty in TC frequency changes.

To explore the compression characteristics and failure precursor of phyllite, the acoustic emission (AE) test was carried out on the condition of uniaxial compression experiments. A self-programmed computer procedure is used to complete the filtering, time-frequency transform and data analysis of AE signals. The uniaxial compression process of phyllite can be divided into three stages: calm stage, active stage, and intense stage, which corresponds to the low-frequency band (40-198kHz), intermediate frequency band (198-232kHz), and high-frequency band (232-400kHz). The first and second dominant frequencies exhibit strong aggregation along with the sequence of AE. Low main frequency ratio corresponds to high main amplitude ratio, and vice versa. When approaching the failure stage, there is a sudden change in the main amplitude ratio, a decreasing change in main frequency ratio along with an aggregation state. There is good consistency between the compressive characteristics reflected by the stress-strain curve and the main frequency characteristics by the AE signal, highlighting the characterization of AE technology. The results of this experiment can provide a certain application reference for the precursor of instability or failure in the engineering of phyllite rock mass.

Effective water resource management hinges on recognizing not just trends in average or extreme streamflow values, but also the underlying patterns and seasonal transitions that drive hydrological responses. To address this need, this study integrates Hierarchical Clustering Analysis (HCA) and Dynamic Time Warping (DTW) for streamflow pattern recognition, alongside an At Most One Change (AMOC) method to identify significant shifts in wet and dry periods. The Ensemble Empirical Mode Decomposition (EEMD) technique is further employed to reveal long-term trends within nonstationary streamflow data. The combined approach was applied to multi-decadal streamflow records from four major reservoirs in Taiwan. A station-based analysis highlights distinct regional behaviors: northern reservoirs tend toward earlier onsets of the wet season, while central and southern reservoirs show delayed transitions. Complementing these findings, a cluster-based analysis—grouping hydrological years with similar flow patterns—offers more nuanced insights into how seasonal shifts vary by reservoir. At Shihmen Reservoir, for example, one cluster exhibits delayed transitions that may stem from later typhoon landfalls, whereas another indicates earlier shifts possibly influenced by a stronger subtropical high. By coupling pattern recognition with targeted change-point detection, this methodology uncovers how climate change can affect not only the magnitude of streamflow but also the timing of critical seasonal events. Identifying these evolving flow patterns and their potential drivers has direct implications for water resource strategies, including reservoir operation guidelines and drought or flood mitigation measures. The proposed framework is readily adaptable to other regions, offering a valuable tool for managing complex streamflow dynamics under growing climatic uncertainty.

Hypercalcemia secondary to hyperparathyroidism mimicking Eclampsia during postpartum period in a young hypertensive woman: a case report

A document by Patryk Piekos. Click on the document to view its contents.

General relativity is an excellent model of gravity, but the theory is classical, not described by a quantum theory. There are many models of quantum gravity, they can be divided into background and independent from the background of the theory. In this paper, we consider the canonical approach to quantum gravity. But a completely different geometry and the concept of space is used. Instead of real space, consider the geometry of the fields in the momentum space. For this, the coordinates are considered by operators who are set in the space of momentum.

Hydrogen serves as a pivotal clean energy carrier. However, its production is confronted with efficiency-related obstacles. Direct current triboelectric nanogenerators (DC-TENG) present an environmentally sustainable alternative by transforming mechanical energy into direct electrical power suitable for water electrolysis. This review underscores the progress in DC-TENG mechanisms, advancements in material science, and strategies for effective integration aimed at hydrogen production. DC-TENG attain elevated efficiency levels through the optimization of triboelectric materials, the employment of nanostructured surfaces, and the implementation of scalable designs, thereby facilitating self-sustaining systems for hydrogen generation. Significant advancements encompass enhanced charge density and increased energy output, which contribute to a diminished dependence on external power sources. Nevertheless, challenges persist regarding material longevity, charge transfer efficiency, and the scalability of industrial applications. Future inquiries should emphasize enhancing materials, devising hybrid approaches, and facilitating uninterrupted integration into pre-existing infrastructures. DC-TENG exhibit considerable potential in propelling sustainable hydrogen production and playing a vital role in fostering a cleaner energy future.