ethicalabs/Research-Intent-Collab huggingface dataset:
Experimental Optimization on a Continuous-flow Reactive Distillation Reactor System for Biodiesel Production via Transesterification

A comprehensive study of biodiesel (canola methyl ester) synthesis was performed on a continuous  reactive distillation system. The transesterification reaction of vegetable oil and methanol is reversible in nature  with an equilibrium ester yield of about 75%. The reactive distillation, a process unit that enables reaction and  distillation in a single unit, is an excellent option for the biodiesel production and ideally can achieve 100%  reaction conversion. Effects of six process variables were evaluated on the reaction conversion, productivity  and soap formation. An inline static-mixer type pre-reactor was used prior to the RD column that achieved a  substantial portion of the reaction duty. Potassium methoxide is found to be significantly better catalyst than  KOH for achieving high conversion while low reboiler temperatures were favorable for lower soap formation.  The condenser in total reflux mode was found to be better than in total recycle mode. Surprisingly the feed  molar ratio and overall flow rate was not highly correlated to overall product conversion or soap formation.  Wide range of different quality parameters have been obtained with the 16 experiments performed on the RD  reactor system setup. The reaction conversion achieved on the RD reactor ranges from 41.46 - 94.94% with an  average of 76.32%. Similarly, the productivity varies from 16–55.8 kmol/ m3  reactor-h with an average of 32 kmol/  m3  reactor-h, which are equivalent to 5.6–19.5 m3/ m3  reactor-h with an average of 13.1 m3/ m3  reactor-h, respectively.  The optimum conditions predicted through statistics software would lead to reaction conversion rate >98%,  productivity > 50 kmol esters/ m3  reactor-h, or 17.5 m3/ m3  reactor-h, and soap formation of less than 7 moles per 100  moles of feed triglyceride. Experimental verification of such optimum operating conditions is under  investigation.
Biological Control Strategies and Integrated Arthropod Pest Management for Camellia oleifera

Camellia oleifera, commonly known as oil-tea, serves as one of China’s most economically important oil crops. To ensure continued production yield and quality, biological control measures, operating within the framework of integrated pest management, have been extensively adopted nationwide. Integrated pest management facilitates effective management of arthropod pests afflicting C. oleifera by integrating biological control strategies with traditional chemical control methods. This approach significantly reduces the reliance on chemical pesticides and minimizes adverse environmental impacts. Over 600 natural enemy species targeting pests have been documented within the C. oleifera agroecosystems in China including approximately 38 viral agents along with 41 fungal, 166 parasitoid, 336 predator, and several bacterial species. Notably, both insectile natural enemies and fungal biopesticides derived from microbial resources are currently being used at scale in C. oleifera cultivation regions, serving as crucial alternatives to the use of conventional chemical pesticides. This paper comprehensively reviews recent progress in research and the application of synergistic integration of biological control with traditional pest management strategies for C. oleifera. The current status of research on natural enemy resources is analyzed and knowledge gaps in the domain of C. oleifera pest management are identified. Furthermore, future research trajectories are proposed that are intended to provide a scientific basis for the green and sustainable development of the C. oleifera industry.
Randomized controlled trials and real life studies. Approaches and methodologies: a clinical point of view.

Randomized Controlled Trials (RCTs) are the "gold standard" for evaluating treatment outcomes providing information on treatments efficacy. They are designed to test a therapeutic hypothesis under optimal setting in the absence of confounding factors. For this reason they have high internal validity. The strict and controlled conditions in which they are conducted, leads to low generalizability because they are performed in conditions very different from real life usual care. Conversely, real life studies inform on the effectiveness of a treatment, that is, the measure of the extent to which an intervention does what is intended to do in routine circumstances. At variance to RCTs, real life trials have high generalizability, but low internal validity. Recently the number of real life studies has been rapidly growing in different areas of respiratory medicine, particularly in asthma and COPD. The role of such studies is becoming a hot topic in respiratory medicine, attracting research interest and debate. In the first part of this review we discuss some of the advantages and disadvantages of different types of RCTs and analyze the strengths and weaknesses of real life trials, considering the recent examples of some studies conducted in COPD. We then discuss methodological approaches and options to overcome some of the limitations of real life studies. Comparing the conclusions of effectiveness and efficacy trials can provide important pieces of information. Indeed, these approaches can result complementary, and they can guide the interpretation of each other results.
Robotic Process Automation (RPA) and HRIS Driving Efficiency in Payroll and Benefits Administration

Managing payroll and employee benefits can be a complex, time-consuming process. HR teams face issues like manual data entry errors, missed deadlines, inconsistent records, and difficulties keeping up with ever-changing tax and compliance regulations. These challenges slow down operations and impact employee satisfaction and trust. This white paper explores how Robotic Process Automation (RPA) and Human Resource Information Systems (HRIS) can simplify and streamline critical HR functions. It provides a clear picture of how organizations can modernize their payroll and benefits administration. RPA handles repetitive, rule-based tasks quickly and accurately, and HRIS systems centralize employee data and improve transparency. Together, they reduce manual workload, ensure accuracy, and create a more efficient, employee-friendly process. This paper explains how adopting these tools can help HR teams save time, cut costs, and deliver better results.
The law applicable to disputes regarding Central Bank digital currencies

In an environment where more than half of the states in the world aim to issue their own digital currencies, it is important to determine the law applicable to central bank digital currencies. One of the reasons that led to the emergence of CBDCs, a digital form of fiat currency issued by the central bank, is their ability to facilitate cross border transactions, which also introduces the element of foreignness when CBDCs are used in cross border transactions. Because CBDCs do not have physical existence like paper money and are intangible, the law applicable to disputes regarding CBDCs also varies. The most appropriate solution in terms of applicable law in CBDC related proprietary disputes is to determine the law of the state where the issuer has its statutory seat as the applicable law, unless a choice of law has been made in the digital asset itself or in the system in which it is recorded. In disputes between intermediaries and end users, the most appropriate solution would be to determine the applicable law in the agreements between them.
Deep learning generative model for conditional crystal structure prediction of sodium amide

Abstract                 Understanding the high-pressure behavior of sodium amide (NaNH2) is essential for its applications in hydrogen storage and chemical synthesis. Conventional structure prediction methods have been shown to struggle in accurately capture its pressure-induced phase transitions due to the complexity of its potential energy surface, which arises from strong ionic interactions, large unit cell size, and significant atomic rearrangements under compression. In this study, we introduce a deep learning generative framework that enables conditional crystal structure prediction by incorporating lattice parameters and space group symmetry as explicit constraints, and applying energy-guided diffusion sampling during generation. The framework uses a direct-space asymmetric unit (DAU) to represent each structure, enabling symmetry-consistent encoding and efficient reconstruction of full crystals through Wyckoff operations. Applied to NaNH2, this method successfully predicts the high-pressure γ-phase as a P21/c structure (Z = 16, 64 atoms), which was previously missed by conventional approaches. This phase is confirmed by synchrotron X-ray diffraction and remains stable up to 14.0 GPa. Further analysis of charge density and atomic rearrangement reveals the mechanisms driving the phase transitions and explains the robust stability of the γ-phase under high pressure. This work demonstrates the potential of our deep learning generative framework to accelerate structure prediction in complex ionic materials and provides an effective framework for modeling crystals with large unit cells accurately.
Impacts of traditional land uses on biodiversity outside conservation areas: effects on dung beetle communities of Vaalbos National Park

AbstractGrazing is one of the key processes in terrestrial ecosystems and this can be provided by both indigenous and domestic ungulates. However, a question remains whether or not traditional forms of land use such as the grazing of domestic animals support the maintenance of biodiversity. If it does not, then the second question becomes to what extent does grazing of domestic animals alter the systems and processes that support biodiversity? This study demonstrates that in attempting to answer this question, small organisms like dung beetles are ideal indicators that can be used to express significant differences between conserved (indigenous) and non‐conserved (domestic) land. As a general trend, studies that investigated these differences displayed differences through analysis of the diversity indices. This method has in most cases demonstrated a lack of contrast between conserved and non‐conserved land. In the existence of such uncertainty this study has demonstrated that in such cases, where the analysis of biodiversity indices fail to demonstrate significant differences a closer examination of actual species such as guilds and functional groups could confirm significant differences between conserved and non‐conserved land. These apparently conflicting findings reflect the need to consider the actual elements of biodiversity (e.g. species) when assessing conservation issues rather than just the statistical measures of biodiversity.
Computational Simulation and Algorithm Analysis for Solving Combinatorial Optimization Problems in Graph Theory and Discrete Mathematics

Combinatorial optimization is a fundamental area in operations research and computer science, focusing on identifying optimal solutions from a finite set of possibilities. This study explores the integration of branch and bound methods with heuristic algorithms to address optimization problems in graph theory and discrete mathematics. Python was employed for algorithm implementation due to its flexibility and comprehensive computational libraries, enabling efficient data analysis and visualization. Several benchmark problems were examined, including the Traveling Salesman Problem (TSP), Minimum Spanning Tree (MST), and Graph Coloring. Simulations were conducted using datasets of varying sizes (small, medium, and large) to evaluate performance across different scales. The results demonstrate that the hybrid approach achieves a balance between solution quality and computational efficiency, outperforming brute-force methods in terms of speed while maintaining near-optimal accuracy. Tabulated results and graphical comparisons highlight the reduction in computation time and improved scalability of the proposed method. The findings suggest that combining systematic search strategies with heuristics offers a practical and effective framework for solving complex combinatorial optimization problems. Recommendations for future research include testing scalability with larger datasets, incorporating advanced metaheuristics, and applying the approach to real-world domains such as logistics and network design.
Analysis of Respiratory Kinematics Device: Breath Detection from Motion Sensor Signals; Communication, Risk Perception, and Trust in COVID-19 Vaccine Uptake

Currently, the best way to identify labored breathing in a hospital patient is through bedside evaluation conducted by a health professional. However, this brief and intermittent inspection does not allow for rapid detection of and response to labored breathing in clinical settings, which can be an indicator of many medical conditions and acute complications. The Analysis of Respiratory Kinematics (ARK) device is a novel medical device that aims to address this problem. The ARK device consists of a series of motion sensors that adhere to a patient’s chest and back, which can be used for continuous monitoring of chest kinematics, allowing for remote detection of labored breathing. Our team aimed to design an algorithm to identify each individual breath in the ARK motion sensor signals for use in the creation of analytical tools for detection of labored breathing.   I conducted my STS research on a topic that is not directly related to my technical project, but that is highly relevant to the medical field today: COVID-19 vaccine uptake. Three different vaccines against the SARS-CoV-2 virus have been approved under Emergency Use Authorizations in the United States. Throughout the COVID-19 Pandemic, both before and after vaccines became available, there has been a widespread perception in the U.S. that vaccines against the virus will provide a technical solution to the pandemic. However, for vaccines to achieve the mass immunization that is hoped for, they must be taken up by the majority of the population. In the U.S., vaccine uptake is a complex problem involving many different stakeholders with varying ideas about the safety and necessity of vaccination. In addition, there are several unique factors of the COVID-19 Pandemic and the current social and political atmosphere of the U.S. that may play new roles in vaccine uptake, such as political polarization, an urgency to regain “normalcy”, and decreased trust in the Federal government. Rather than viewing COVID-19 vaccination through a technological deterministic lens, we must view it as a wicked problem worthy of STS investigation. To this end, I investigated COVID-19 vaccine uptake in the U.S. using both the Actant-Network Theory and the Technological Mediation Theory.
Bridging the Gender Participatory Gap in Water and Sanitation Rights Adjudication

Abstract                This article critically examines the justifications, litigation strategies, adjudicatory mechanisms and implications for strengthening gender participatory processes in domestic enforcement of the separate but critically interlinked rights to basic water and adequate sanitation services. The article first examines how the lack of women’s full, free and meaningful participation as key stakeholders both causes and contributes to gendered deprivation by examining three early leading jurisprudential examples from South Africa, Mazibuko and Others v City of Johannesburg (2009), Nokotyana and Others v Ekurhuleni Municipality (2009) and Beja and Others v Premier of the Western Cape (2011). Employing the literature on principles of adjudication and the discourse on equality, gender and dignity, the concept of ‘gender-responsive participatory justice’ (GPJ) is then put forth as a flexible analytical and strategic tool to mitigate the ad hoc gender-sensitive considerations that remain wholly inadequate to guaranteeing equality and non-discrimination commitments in practice. In doing so, the article emphasizes the critical nexus between procedure and the substantive values and functions of these rights in the form of autonomy-based equality and agency-based dignity. In the final instance, this examination is operationalized by a preliminary applied discussion of how gender-responsive deliberative principles of participation and their accompanying values can be utilized by practitioners and policy-makers to ultimately pursue proactive ways of guaranteeing that women’s participation becomes fully integrated in water and sanitation rights implementation.
From Top-Down to “Community-Centric” Approaches to Early Warning Systems: Exploring Pathways to Improve Disaster Risk Reduction Through Community Participation

Natural hazards and their related impacts can have powerful implications for humanity, particularly communities with deep reliance on natural resources. The development of effective early warning systems (EWS) can contribute to reducing natural hazard impacts on communities by improving risk reduction strategies and activities. However, current shortcomings in the conception and applications of EWS undermine risk reduction at the grassroots level. This article explores various pathways to involve local communities in EWS from top-down to more participatory approaches. Based on a literature review and three case studies that outline various levels of participation in EWS in Kenya, Hawai'i, and Sri Lanka, the article suggests a need to review the way EWS are designed and applied, promoting a shift from the traditional expert-driven approach to one that is embedded at the grassroots level and driven by the vulnerable communities. Such a community-centric approach also raises multiple challenges linked to a necessary shift of conception of EWS and highlights the need for more research on pathways for sustainable community engagement.
Protection Acts for Slovenian Linguistic Minority in Italy and the Municipality of Resia: Minority Rights between Law and Politics (Zaščitna zakonodaja za slovensko jezikovno manjšino v Italiji in občina Rezija: manjšinske pravice med pravom in politiko)

Resia is a part of Slovenian ethnic settlement in Italy, yet due to geographical and historical reasons, most of the population has not developed a sense of Slovenian ethnic identity, but rather, only their local one. After 1999 the municipality of Resia was included into three protection acts for Slovenian linguistic minority. Part of the population and the actual municipal government is categorically opposed to that, which has provoked many drastic conflicts in the valley. In this paper, the author presents and analyses the placement of the municipality of Resia into the protection acts for Slovenian minority, reasons for opposing this placement and the problems with the application of the minority protection by the authorities.
This report models the electrification of Pakistan's residential and transport sectors using the OSeMOSYS energy system framework. Three scenarios: Business-As-Usual (BAU), Electrification of Residential Sector (ERS), and Electrification of Transport Sector (ERTS) were analyzed to assess the impact of electrification on energy mix, emissions, and investment needs. The findings reveal that electrification, particularly through decentralized solar and wind energy, can significantly reduce carbon emissions, enhance energy security, and improve access to clean energy. The ERTS scenario shows the most dramatic shift, with an 84% reduction in emissions by 2050 and substantial growth in solar capacity. However, achieving these outcomes requires robust policy support, infrastructure investment, and improved data availability. The report recommends scaling up renewable energy investments, expanding electrification policies to other sectors, and strengthening institutional capacity to support a sustainable energy transition.

This report models the electrification of Pakistan’s residential and transport sectors using the OSeMOSYS energy system framework. Three scenarios: Business-As-Usual (BAU), Electrification of Residential Sector (ERS), and Electrification of Transport Sector (ERTS) were analyzed to assess the impact of electrification on energy mix, emissions, and investment needs. The findings reveal that electrification, particularly through decentralized solar and wind energy, can significantly reduce carbon emissions, enhance energy security, and improve access to clean energy. The ERTS scenario shows the most dramatic shift, with an 84% reduction in emissions by 2050 and substantial growth in solar capacity. However, achieving these outcomes requires robust policy support, infrastructure investment, and improved data availability. The report recommends scaling up renewable energy investments, expanding electrification policies to other sectors, and strengthening institutional capacity to support a sustainable energy transition.
All Stressors Are Not Equal: The Salience of Racial Discrimination and Appraisal for Blood Pressure in African American Women

ABSTRACT                        Objective             Psychosocial stress is a major predictor of chronic disease among African American (AA) women. Stress is a process involving exposure, appraisal of threat, coping, and psychobiologic adaptation. However, many studies focus on the frequency of stress events and/or coping; few explicitly study stress events and their appraisals; and AA women experience high levels of racial discrimination, a well-known form of social identity threat (i.e., negative experiences due to judgment based on identity). Stressors related to social identity threat may be differentially appraised and associated with divergent physiologic outcomes. This study examined the differences in the frequency and stressfulness associated with general stressors and racial discrimination in relation to blood pressure (BP) among AA women.                                   Methods             Multivariable regression was used on cross-sectional data from 208 middle-aged AA women residing in the San Francisco Bay Area.                                   Results             AA women reported less frequency of racial discrimination compared with general stressors, but were more likely to appraise racial discrimination events as stressful. Racial discrimination stressfulness was more strongly associated with systolic BP (SBP) than the number of racial discrimination events. There was a U-shaped association between racial discrimination stress and SBP, with those reporting “none” and “high/very high” distress having the highest SBP (b = 12.2 [2.7 to 21.8] and b = 15.7 [1.5–29.8], respectively, versus moderate stress). Conversely, those reporting “very low” general stressfulness had the lowest SBP (b = −7.9 [−15.8 to −0.1], versus moderate stress). Diastolic BP followed a similar pattern, although results were nonsignificant.                                   Conclusions             This study highlights the importance of stress appraisal measures and adds to the body of evidence documenting racial discrimination as a salient psychosocial stressor for AA women.