bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantum Fluid Operation: A Universal Chemical Engineering Building Block, Retiring the Continuous, Stirred Tank Reactor
Authors: Samid Gideon
Published: August 2024

The familiar stirred tank reactor poses an inherent challenge of variability. Some inflowing chemicals spend too little time in the reactor, and others stay too long, harming the uniformity of the end product. This issue can be addressed by replacing the continuous operation with a flow of individually treated fluid quanta. Ideally one would devise a universal fluid handling apparatus that can be adjusted to take care of all the needed chemical engineering unit operations. Proposing a cylinder shape capsule containing a rotating piston that moves back and forth between the edges of the capsule. The piston is cut through with certain fluid pass ways (holes) which may be shifting between being open, being closed, and anything in between. The combined movement of holes-drilled rotating piston will allow this universal unit to adjust for pumping, mixing and reacting fluid, and fluid components. By lining up the inner sides of the piston holes with fluid impact materials (FIM) the same generic unit can be used for catalytic reactions and for separation challenges. These generic units are linked "Lego like" to form a compound process, replacing the familiar continuous operation. The multi-mode piston (MMP) unit is completely specified by a digital representation of the shift position , the rotational position and the open/closed positions of the fluid pass ways. This allows for an efficient imposition of control strategy and for optimized manufacturing. The resultant digital representation renders the control strategy to become AI friendly, consistent with supervised learning tools for improving the efficiency of many chemical processes that transform from continuous mode to quantum fluid mode. While appearing promising, the concept is in its preliminary stages and its prospective impact is not yet well determined.
Dynamic Solvent Accessible Surface Areas of Proteogenic a-Amino Acids as a Function of Explored f,y Dihedral Angle Space Modelled using the Ac-Ala-Xaa-Ala-NH2 system and CHARMM36m Force Field
Authors: Burns William A , Lovas Sándor , Watts Charles R.
Published: August 2024

Solvent accessible surface area (SASA) of amino acid residues plays a significant role in inter-residue, protein-ligand, and protein-protein interactions. Affecting the exposure and interactions of hydrophobic and hydrophilic regions, driving protein folding. While previous SASA calculations are accurate with respect to the chosen parameters of simulation, they do not account for the dynamic behavior of peptides in solution under physiological conditions and cannot be used to compare populations within phi,psi dihedral angle space (phi,psi space). Molecular dynamics trajectories obtained at 310 K, 1 atm, and 150 mM NaCl for the Ac-Ala-Xaa-Ala-NH2 model peptides simulated using the CHARMM36m force field and TIP3Pm water as implemented in GROMACS 2022 were used to study SASA. The more balanced parametrization of CHARMM36m, resulted in increased sampling of beta region compared to alpha, alphaL, and epsilon regions were observed. There are statistically significant differences in SASA for the backbone and side chain comparing the beta, alpha, alphaL, epsilon and contiguous regions of phi,psi space. Differences occur in sampled phi,psi space particularly in the alphaL and epsilon regions of phi,psi space as a function of side chain size and chemical properties. The epsilon region of phi,psi space is not significantly sampled for multiple amino acids while the alphaL region is.
Comparison of Model Systems for Emulating Human Tissue and Physiology in Psychiatric Research
Authors: Cheng Kai , Kathuria Annie , Kshirsagar Anannya , Nixon John , Lau Jonathan , Yang Kun , Sawa Akira
Published: August 2024

The modeling of psychiatric disorders poses significant challenges due to the complex nature of these conditions, which encompass a range of neuropsychiatric diseases such as autism spectrum disorder (ASD), schizophrenia (SCZ), bipolar disorder (BD), post-traumatic stress disorder (PTSD), anxiety and depression. The rising global prevalence of mental disorders and the urgency for more effective treatments have propelled the development of innovative in vitro models. This review presents a thorough examination of two-dimensional (2D) versus three-dimensional (3D) induced pluripotent stem cell (iPSC) models of neuropsychiatric diseases, offering insights into their respective capacities to mimic neurodevelopment and cellular phenotypes observed in these conditions. Our comparative analysis reveals that while traditional 2D cultures have been instrumental in elucidating disease pathways and high-throughput drug screening, they fall short in replicating the intricate cellular architecture and environment of the human brain. On the other hand, 3D organoid models, including brain organoids, better recapitulate the spatial organization, cell-type diversity, and functional connectivity of brain tissue, offering a more physiologically relevant context for studying disease mechanisms and testing therapeutic interventions. We assess the progress in modeling ASD, Schizophrenia, Bipolar Disorder, PTSD, and depression, highlighting the advanced understanding of disease etiology and potential treatment avenues offered by 3D iPSC technologies. Challenges remain, including the scalability, reproducibility, and maturation of organoids, but the potential for personalized medicine and the elucidation of disease ontogeny is unparalleled. The review concludes with a perspective on the future directions of psychiatric disease modeling, emphasizing the integration of 3D iPSC models with high-throughput technologies and computational approaches to enhance our understanding and treatment of these debilitating conditions.
Abortion-related Mental Health Disorders at Midlife: Twenty-year Longitudinal Evidence from the United States
Authors: Sullins D. Paul
Published: August 2024

Background and Objectives. To examine trends in the links between induced abortion and subsequent mental health problems for U.S. women approaching completed fertility.
Materials and Methods. Panel data on a nationally-representative cohort of 3,842 ever-pregnant women assessed at mean ages of 15, 22, 28 and 37 years from the National Longitudinal Study of Adolescent to Adult Health (Add Health) were examined for pregnancy outcome-related mental health disorders, with extensive adjustment for confounders including sociodemographic dif-ferences, mental health history, and unwanted pregnancies. Outcomes were defined using pub-lished diagnostic criteria or validated index for depression, anxiety disorder, post-traumatic stress disorder (PTSD), and suicide ideation (affective problems); alcohol abuse, drug abuse, opioid abuse, and cannabis abuse (substance abuse problems); and summary counts of affective problems, substance abuse problems and total disorders. Results were adjusted for abortion under-reporting using cross-wave analysis.
Results. The relative risk of mental health disorder with exposure to induced abortion followed an inverted “V” pattern as women aged to midlife, increasing from Wave III (age 22; IRR 1.41) to Wave IV (age 28; IRR 1.67), then dropping sharply by Wave V (age 37; IRR 1.20). The population at-tributable fraction of mental health disorder due to abortion dropped from 18.1% at Wave IV to 8.0% at Wave V. Unlike previous Waves, at Wave V mental health risk was more strongly reduced by exposure to childbirth (IRR 0.70, 95% CI .63, .78, p < .001). Reduced relative metrics at Wave V were not due to reduced prevalence of mental health disorders for ever-aborting women, which increased from Wave IV to Wave V by 1.7%, but increased much more, by 20.5%, for never-aborting women.
Conclusion. At midlife approaching completed fertility, differential negative psychological out-comes for ever-aborting U.S. women remained elevated but reduced from younger ages.
Advances in Protein Dynamics: Unraveling the Molecular Motions Underlying Biological Functions and Therapeutic Innovations
Authors: Son Ahrum , Kim Woojin , Park Jongham , Lee Wonseok , Lee Yerim , Kim Hyunsoo
Published: August 2024

Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence have revolutionized our understanding of protein dynamics. Nuclear magnetic resonance spectroscopy provides atomic-resolution insights, while molecular dynamics simulations offer detailed trajectories of protein motions. The integration of machine learning, exemplified by AlphaFold2, has accelerated structure prediction and dynamics analysis. These approaches have revealed the importance of protein dynamics in allosteric regulation, enzyme catalysis, and intrinsically disordered proteins. The shift towards ensemble representations of protein structures and the application of single-molecule techniques have further enhanced our ability to capture the dynamic nature of proteins. Understanding protein dynamics is essential for elucidating biological mechanisms, designing drugs, and developing novel biocatalysts, marking a significant paradigm shift in structural biology and drug discovery.
Health Literacy: Structural Topic Modeling and Citation Trends
Authors: M. Tabak Benjamin , Britto Froner Matheus , C. de Almeida Rubiane Daniele , D. Couto Luzia Cláudia , Christiano Silva Thiago , de Fatima Faria Barbosa Sayonara
Published: August 2024

Health literacy is a growing research area with specific aspects and different instruments to measure health literacy. This article uses natural language processing model to analyze the academic corpora regarding seven health literacy instruments - Health Literacy Questionnaire, Mental Health Literacy Scale, Rapid Estimate of Adult Literacy in Medicine, Test of Functional Health Literacy in Adults, Health Literacy Survey, The Newest Vital Sign and eHealth Literacy Scale. We apply Structural Topic Modeling to all the abstracts of the selected academic corpora, label the topics based on their focus, and use the topic distribution with metadata to train a Random Forest algorithm for predicting yearly citations. We estimate Regression models based on the ranking of the most relevant features, which serves as a robustness check and to infer their impact on citation dynamics. We have found that Digital Health Literacy is positively associated with yearly citations, while other topics such as Functional Health Literacy and Women's Health reduce citation likelihood. Other article characteristics also have shown a significant role in the citation likelihood, such as the publication year, amount of articles and certain keywords. These findings portray the current landscape of health literacy research, highlighting literature gaps and popular topics.
Silicone Shoes for Treatment of Pododermatitis (Bumblefoot) in Pet Chickens – A Retrospective Case Series
Authors: Konicek Cornelia , Gumpenberger Michaela , Schramel Johannes Peter
Published: August 2024

Backyard chickens often suffer from foot pad dermatitis (FPD), a condition exacerbated by poor husbandry, nutritional deficiencies, and obesity. Pressure-relieving bandages, commonly used in treatment of FPD, are impractical for outdoor chickens as they quickly become wet and dirty, necessitating daily changes which are often unfeasible. This retrospective study explores the use of custom-fit silicone shoes, created via 3D-printed molds, as an alternative to traditional bandages. CT scans were used to design shoes, adapted from a design used for birds of prey. Over three years, 16 chickens with varying degrees of FPD were treated. The results demonstrated that sili-cone shoes were an effective treatment for FPD, allowing outdoor activity, and facilitated daily lesion care without frequent bandage changes. The median shoe-wearing period was 14 days, and most owners provided positive feedback. Despite some attachment issues, the occurrence of sec-ondary pressure marks and feather regrowth challenges, the silicone shoes offered better ventila-tion, reusability, and consistent pressure relief compared to traditional bandages. This study con-cludes that silicone shoes are a viable solution for managing FPD in backyard chickens, promoting faster healing and improved owner compliance.
Advancement in Research of Plant Beneficial Microorganisms: From Fermentation to Formulation Strategies and Applications in Agriculture
Authors: Vassileva Maria , Mocali Stefano , Martos Vanessa , Garcia del Moral Luis F , Vassilev Nikolay
Published: August 2024

In the last years, different biotechnological approaches were developed to reduce the indiscriminate use of chemical fertilizers and pesticides and enhance plant growth and health. The most attractive, safe, and environmentally mild alternatives include those based on plant beneficial microorganisms. After a long period of studies on isolation, selection, and characterisation of plant-beneficial microorganisms, the main lines of research have been oriented to optimising the fermentation processes to produce high-quality and large volumes of biomass/spores and their further formulation. However, further well-structured schemes for improvement of all main steps of the production of bio-formulates should be developed following the ideas based on “healthy soil-healthy plants-healthy humans”.
Effects of UV-B and UV-C Spectrum Supplementation on the Antioxidant Properties and Photosynthetic Activity of Lettuce Cultivars
Authors: Skowron Ernest , Trojak Magdalena , Pacak Ilona
Published: August 2024

Indoor farming systems enable plant production in precisely controlled environments, managing factors such as lighting, photoperiod, and nutrient supply, to enhance crop yield and quality. However, the implementation of stable growth conditions and the absence of stress stimulants can weaken plants' defense responses and limit the accumulation of bioactive, health beneficial phytochemicals. A potential solution is the controlled application of stressors, such as supplemental ultraviolet (UV) light, which stimulates secondary metabolites (SM) synthesis and increase overall antioxidant potential. To this end, we analyzed the efficiency of short-term pre-harvest supplementation of red-green-blue (RGB, LED) spectrum with ultraviolet B (UV-B, 311 nm) or C (UV-C, 254 nm) light to boost phytochemicals synthesis. Additionally, given the biological harm of UV radiation due to high-energy photons, we monitored plants’ photosynthetic activity during treatment. Our analyses showed that UV-B radiation, applied with a cumulative dose of 15.622 kJ m–2, did not negatively impact photosynthetic activity while significantly increasing the overall antioxidant potential of lettuce through enhanced levels of polyphenolic SM (total phenolics, flavonoids, anthocyanins) and ascorbic acid. Conversely, UV-C radiation, applied with a lower cumulative dose of 6.008 kJ m–2, induced anthocyanin accumulation in the green leaf cultivar but significantly harmed the photosynthetic apparatus and limited plant growth. These results are crucial for understanding the potential of UV light supplementation in producing functional plants.
AI and IoT in Automation and Security: A Vision for Next Generation Applications
Authors: Islam Md. Suzon
Published: August 2024

This article titled "AI and IoT in Automation and Security: A Vision for Next Generation Applications," explored the implications of marrying IoT with AI in the realms of automation and security; this piece goes further into what that entails. In this paper, we present innovative application descriptions arising from this technology convergence and its future-generation applications. We found that AI brings strong cyber security, predictive maintenance, and decision-making capabilities to the table due to its advanced algorithms and machine learning models. IoT has the potential to allow businesses to extract and generate big data, automate processes, and monitor in real-time thousands and even millions of businesses at once. For now, we believe some of the possible main conclusions will be that the smart city, stand-alone systems, and user experience will be quite consumer-friendly. Importantly, the study also assessed facets such as data protection, system interoperability, and a few others. Our vision underscores the essential of a strong structure to connect the full latent of AI and IoT, finally aiming to create more capable, protected, and approachable environments. Significant results include achieving 95.8% accuracy in anomaly detection and 93.4% accuracy in predictive maintenance. The showcasing results efficacy of AI models to enhance system reliability as well as operational efficiency. Vigorous encryption protocols performance ensures data security hence addressing issues of privacy. These culminations underscore the transformative potential of AI-IoT integration in next-generation automation and security applications.
Cacalol Acetate as Anticancer Agent: Anti-proliferative, Pro-apoptotic, Cytostatic and Anti-migratory Effects
Authors: Rostro-Alonso Gareth Omar , Castillo-Montoya Alejandro Israel , García-Acosta Juan Carlos , Aguilar-Llanos Erick Fernando , Quintas-Granados Laura Itzel , Villegas-Vazquez Edgar Yebran , Garcia-Aguilar Rosario , López-Muñoz Hugo , Sánchez-Sánchez Luis , Alvarado-Sansininea Jesús J. , Jiménez-Estrada Manuel , Cariño-Calvo Lizbeth , González-del-Carmen Manuel , Cortés Hernán , Leyva-Gómez Gerardo , Figueroa-González Gabriela , Reyes-Hernández Octavio Daniel
Published: August 2024

Cacalol (C), a sesquiterpene isolated from Psacalium decompositum, has demonstrated anti-inflammatory and antioxidant activities. Its cytotoxic, antiproliferative, and pro-apoptotic effects have been previously shown in an in vitro breast cancer model. A derivative, Cacalol Acetate (CA), shows potential in regulating these processes, which had not been previously reported. This study focused on an in vitro cervical cancer model, assessing CA's anti-proliferative, pro-apoptotic, cytostatic, and anti-migratory activities using the HeLa cell line. The natural anticancer agent I3C was used as a control for comparison. CA demonstrated significant antitumor activities, including inhibiting cell growth, inducing apoptosis, arresting cells in the G2 phase of the cell cycle, and inhibiting cell migration. These effects were notably greater compared to I3C. I3C, while following a similar trend, did not induce Cas-3 expression, suggesting a different apoptotic pathway. Neither CA nor I3C increased p62 and LC3B levels, indicating they do not stimulate autophagy marker expression. Both compounds inhibited HeLa cell migrate on and induced cell cycle arrest. Despite both holding promise as anticancer agents for cervical cancer, CA's lower cytotoxicity and stronger regulation of tumor phenotypes make it a more promising agent compared to I3C.
Nutrient-Dense African Indigenous Vegetables and Grains in the FAO Food Composition Table for Western Africa (WAFCT) Identified Using Nutrient Rich Food (NRF) Scores
Authors: Lara-Arevalo Jonathan , Laar Amos , Chaparro Maria Pia , Drewnowski and Adam
Published: August 2024

Nutrient profiling (NP) models that assess nutrient density of foods can help remedy micronutrient deficiencies. We used NP methods to identify the most nutrient-rich foods in the 2019 FAO/INFOODS Western Africa Food Composition Table (WAFCT). The WAFCT had complete data for 909 foods. Three versions of the well-established Nutrient Rich Food (NRF) model were used: 1) the original NRF9.3; 2) a new NRF6.3 based on 6 priority micronutrients (iron, zinc, calcium, folate, vitamin A, vitamin B12); and 3) NRF 15.3, based on 15 nutrients to encourage (NRF6.3 nutrients + vitamin D, vitamin E, vitamin C, vitamin B1, vitamin B2, vitamin B3, vitamin B6, copper, and magnesium). Data analyses used one-way ANOVAs and independent t-tests, with significance at α=0.05. Animal-source foods were rated higher by NRF6.3 priority micronutrient and NRF15.3 NP models than by the NRF9.3 model. African indigenous vegetables had higher protein content and higher nutrient density compared to non-indigenous vegetables. African indigenous grains had higher nutrient density compared to non-indigenous grains. Though animal-source foods received some of the highest scores, NP models adapted to the West African context showed that African indigenous vegetables and grains were also nutrient rich. Indigenous foods could be important sources of priority micronutrients for the region.
Physical Activity and Executive Functioning in Children and Adolescents with Congenital Heart Defects: A Scoping Review
Authors: Clifton Amanda , Kirk-Sanchez Neva , Cipriano Gerson , Moore James G , Cahalin Lawrence P.
Published: August 2024

Children and adolescents (C&A) with congenital heart defects (CHD) have decreased functional capacity and executive functioning (EF) due to brain abnormalities and decreased oxygen saturation. Exercise may improve EF via increased cognitive demands and cerebral blood supply. The purpose of this review was to identify current evidence describing the impact of physical activity (PA) interventions on EF in C&A with CHD. The following databases were searched from 2014-present: MEDLINE, EMBASE, CINAHL, Scopus, CENTRAL, and PsycInfo. Article inclusion criteria consisted of participants from birth to 18 years with CHD, interventions related to PA, and EF as an outcome. Articles were excluded if: adults were included, translation to English was impossible, and full access was unavailable. As a result of the review, 431 studies were screened. Three articles underwent full analyzation and only one met all criteria and this study found that with exercise there were significant improvements on self-reported cognitive functioning and parent-reported social functioning. Despite theoretical benefits, only one published study has investigated the role that PA interventions have on EF in C&A with CHD. Further investigation of the effect PA interventions have on EF in C&A with CHD is needed.
Managerial Myopia and Enterprise ESG Performance – Based on the Co-inhibiting Effect of Green Investment and Continuous Innovation
Authors: Cao Lingling , Jiang Hong , Niu Huawei
Published: August 2024

Under the new pattern of “double carbon” development, good ESG performance is the best way to promote the sustainable development of enterprises, and the ESG investment strategies are directly affected by the strategic vision of managers. Based on the upper echelons theory and stakeholder theory, this paper takes Chinese A-share listed companies from 2011 to 2022 as samples to empirically analyze the impact of managerial myopia on corporate ESG performance. The results show that managerial myopia significantly inhibits corporate ESG performance, mainly by inhibiting corporate green investment and green innovation sustainability. Furthermore, for state-owned enterprises (SOE), heavy polluting enterprises (HPE) and non-high-tech enterprises, the inhibitory effect of manager myopia on ESG performance is stronger. When the enterprise is in the growth stage, the above inhibition effect is more severe. For external governance, the greater the analyst attention and public environmental attention are, the more conducive they are to alleviating the restraining effect of managerial myopia on enterprise ESG performance. Therefore, effectively improving the time cognition level of managers and strengthening external supervision have become important measures for comprehensively optimizing the ESG performance.
The Funding Puzzle in Adult Education for Sustainable Development: Case Study of Slovenia
Authors: Košmerl Tadej , Radovan Marko , Radovan Danijela Makovec
Published: August 2024

This study investigates the landscape of public funding for Adult Education for Sustainable Development (AESD) in Slovenia, focusing on the distribution, types of funding, and their impact on accessibility and quality. Using a mixed methods approach to understand the distribution, types of funding, and their impacts on accessibility and quality. Data were collected through an online questionnaire completed by 59 organizations providing non-formal AESD, alongside semi-structured interviews conducted with 12 representatives. Key findings reveal a significant disparity between operational funding and that designated for AESD implementation, with non-governmental organizations (NGOs) emerging as the primary recipients of public funds. Notably, project-based funding predominates, raising concerns about the sustainability of AESD programs due to its typically time-limited nature. Public funding is essential for ensuring program accessibility and quality, as it enables organizations to hire experts and enhance curricula. However, the reliance on project-based grants creates instability, complicating long-term planning and program effectiveness. The study underscores the need for systematic and continuous funding strategies to support AESD, highlighting the importance of a cross-sectoral approach to policymaking. Overall, the research elucidates the intricate relationship between funding distribution, program effectiveness, and the advancement of sustainable development education.
Using light polarization to identify fiber orientation in carbon fiber components: metrological analysis
Authors: Chiominto Luciano , D’Emilia Giulio , Natale Emanuela
Published: August 2024

In this work, a method for measuring tow angles in carbon fiber components, based on the use of a polarized camera, is analyzed from a metrological point of view. Carbon fibers alter the direction of the reflected light electrical field, so that in each point of the surface of a composite piece the angle of polarization of reflected light matches the fiber orientation. A statistical analysis of the angle of linear polarization (AoLP) in each pixel of each examined area allows to evaluate the average winding angle. An evaluation of the measurement uncertainty of the method on a cylinder obtained by a filament winding process is carried out, and the result appears adequate for the study of the distribution of angles along the surface of the piece, in order to optimize the process.
Variation of Bacterial and Fungal Communities in Soils from Three Major Apple-Pear (Pyrus bretschneideri Rehd.) Orchards
Authors: Lyu Guangze , Hu Jiayang , Ma Jincai
Published: August 2024

The microbial communities are closely related to the overall health and quality of soil, but studies on microbial ecology in apple-pear orchard soils are limited. In the current study, 28 soil samples were collected from three apple-pear orchards in northeastern China, and the composition and structure of fungal and bacterial communities were investigated by high-throughput sequencing. Molecular ecological network showed that the keystone taxa of bacterial communities were Actinobacteria, Proteobacteria, Gemmatimonadetes, Acidobacteria, Nitrospirae, and Chloroflexi, and the keystone taxa of fungal communities was Ascomycota. Mantel tests showed that soil texture and pH were important factors shaping soil bacterial and fungal communities, and soil water soluble organic carbon (WSOC) and nitrate nitrogen (NO3--N) were also closely related to soil bacterial communities. Canonical correspondence analysis (CCA) and variation partition analysis (VPA) analysis revealed that geographic distance, soil texture, pH, and other soil properties could explain 10.55%, 13.5%, and 19.03% of the overall variation of bacterial communities, and they explained 11.61%, 13.03%, and 20.26% of the overall variation of fungal communities, respectively. The key stone taxa of bacterial and fungal communities in apple-pear orchard soils and their strong correlation with soil properties could provide useful clues toward sustainable management of orchards.
In-Situ Microstructural Evolution and Mechanical Performance of Nickel-Containing Steels During High-Temperature Heat Treatment: Precipitation Behavior and Its Impact on Material Properties
Authors: Sun Guojin , Li Zhenggui , Wang Qi
Published: August 2024

This study investigates the microstructural evolution and mechanical properties of steel subjected to high-temperature heat treatment, with a focus on the formation and effects of dark phase precipitates. High Temperature Confocal Laser Scanning Microscopy (HTCLSM) was employed to observe the in-situ changes in microstructure as the steel was heated from room temperature to 900°C. The observations revealed that dark phase precipitates, identified as chromium carbides (Cr7C3), began forming at approximately 820°C and increased in quantity and size up to 900°C. Scanning Electron Microscopy (SEM) and Energy-Dispersive X-ray Spectroscopy (EDX) confirmed that these precipitates significantly enhance the material's hardness, with microhardness values of 320 HV for the precipitates compared to 270 HV for the matrix. Tensile tests showed that the tensile strength of the steel increases with soaking time at 900°C, reaching a maximum after 3 minutes due to the strengthening effect of the precipitates. Beyond this point, strength decreases due to grain coarsening.
Evaluation of Anopheline Diversity and Abundance across Outdoor Collection Schemes Utilizing CDC Light Traps in Nchelenge District, Zambia
Authors: Jones Christine M , Ciubotariu Ilinca I , Gebhardt Mary E , Lupiya James Sichivula , Mbewe David , Muleba Mbanga , Stevenson Jennifer C , Norris Douglas E
Published: August 2024

In the global fight against malaria, standard vector control methods such as indoor residual spraying (IRS) and insecticide-treated nets (ITNs) are intended to protect inside residential structures and sleeping spaces. However, these methods can still leave individuals vulnerable to residual transmission from vectors that they may be exposed to outdoors. Nchelenge District in northern Zambia experiences high persistent malaria transmission even with ITNs and IRS in place. However, very few studies have examined outdoor vector activity. To assess diversity and abundance of outdoor foraging female anopheline mosquitoes, CDC light traps were used as proxy measures for mosquito host-seeking, set in three outdoor trapping schemes randomly assigned on different nights: 1) locations where people congregate at night outside of the house within the peri-domestic space, 2) animal pens or shelters, and 3) high human-trafficked areas, such as paths to latrines, where traps were baited with BG-Lure®. 1,087 total female anophelines were collected over a total of 74 trap nights. Anopheles funestus s.s. comprised the majority of the collection (86%), with An. gambiae s.s. (2%) and a highly diverse sampling of other anophelines (12%) making up the remainder. Plasmodium falciparum parasites were only detected in An. funestus (1%). No significant difference in species diversity or female anopheline abundance was detected between trapping schemes. Outdoor foraging anopheline mosquitoes, including a number of infectious An. funestus, may partially explain the difficulty of controlling malaria transmission in Nchelenge District where vector control is only targeted indoors. BG-Lure® shows some promise as an alternative to human-baited landing catch collections in this resource-poor setting.
A Comprehensive Survey on Diffusion Models and Their Applications
Authors: Ahsan Md Manjurul , Raman Shivakumar , Liu Yingtao , Siddique Zahed
Published: August 2024

Diffusion Models (DMs) are probabilistic models that create realistic samples by simulating the diffusion process, gradually adding and removing noise from data. These models have gained popularity in domains such as image processing, speech synthesis, and natural language processing due to their ability to produce high-quality samples. As DMs are being adopted in various domains, existing literature reviews that often focus on specific areas like computer vision or medical imaging may not serve a broader audience across multiple fields. Therefore, this review presents a comprehensive overview of DMs, covering their theoretical foundations and algorithmic innovations. We highlight their applications in diverse areas such as media quality, authenticity, synthesis, image transformation, healthcare, and more. By consolidating current knowledge and identifying emerging trends, this review aims to facilitate a deeper understanding and broader adoption of DMs and provide guidelines for future researchers and practitioners across diverse disciplines.
Predicting the Potential Distribution of Endangered Changnienia amoena S. S. Chien in China Based on Ensemble Modeling
Authors: Liu Ting , Cai Hanwei , Zhang Guangfu
Published: August 2024

Climate change has significant impacts on the distribution of orchids. The endemic and endan-gered orchids are more susceptible to climate change than widely distributed orchids. To date, lit-tle is known concerning the response of endangered Changnienia amoena, endemic to China, to different climate scenarios. Here, we chose RF, MaxEnt, and GBM to build an ensemble model af-ter using ten models from Biomod2 to project its potential distribution in China. The outcomes showed that the four key environmental factors influencing its distribution were mean diurnal temperature range, minimum temperature of the coldest month, temperature seasonality, and precipitation of the warmest quarter. This orchid was mainly distributed in western Hubei, the junction between Shaanxi and Sichuan, eastern Guizhou, northwestern Hunan, and the junction among Anhui, Henan, and Hubei provinces in the current. The total suitable area of C. amoena was 58.33 × 104 km2, only accounting for 6.08% of China's total territory, which is larger than known. However, only 4.48% of the suitable area is located within national nature reserves, and 3.33% within provincial nature reserves, respectively. During the Last Inter Glacial and mid-Holocene, its suitable areas were larger than the current. Under six future climate scenarios, its suitable areas may averagely decrease by 2.26% relative to the current, with severe habitat fragmentation. Col-lectively, the centroid of C. amoena is expected to migrate towards the southeast in the future. Therefore, our findings demonstrate that climate change takes an adverse effect on its potential distribution. We recommend expanding protected areas or establishing new conservation sites for C. amoena. Furthermore, our study can help to inform the development of conservation manage-ment strategies for other endangered orchids in China under climate change.
Design of an Environmental Sensor Board for Energy Harvesting: Integration of Conventional and Eco-friendly Sensors with Power Generation Sources
Authors: Landi Giovanni , Avallone Guerino , Barone Carlo , Pagano Sergio
Published: August 2024

A platform for indoor monitoring inside buildings, integrating both conventional and environmentally friendly devices with energy-harvesting sources, is proposed. Biomaterials such as gelatin and chitosan, derived from renewable resources, have been utilized to fabricate hydrogel and active layers for sensors and supercapacitors. These devices enhance the environmental profile of the proposed solution by employing sustainable materials and optimizing energy consumption. The developed electronic board prototype provides a versatile platform for testing various sensor configurations while accommodating different energy-harvesting sources. The article details the design of an energy harvesting system for indoor monitoring, covering various aspects regarding energy sources, power management circuits, and low-power microcontroller units. It examines energy storage devices and sensors, including both eco-friendly and commercial ones, as well as radio transceivers with different communication technologies. Additionally, an energy analysis to evaluate the performance and energy efficiency of the platform is presented.
The Adoption of Robotic Process Automation in Marketing Operations
Authors: Wilson George , Johnson Oliver , Brown William
Published: August 2024

This study investigates the adoption of Robotic Process Automation (RPA) in marketing operations, exploring its impact on efficiency, data accuracy, and overall effectiveness. RPA has emerged as a transformative technology, automating routine tasks such as data entry, report generation, and campaign management, which has significantly enhanced operational efficiency within marketing departments. By automating repetitive processes, RPA enables marketing professionals to focus on strategic and creative tasks, resulting in accelerated campaign execution and improved productivity. Additionally, the integration of RPA with Customer Relationship Management (CRM) systems has led to more accurate and consistent data, providing valuable real-time insights that enhance decision-making and personalization in marketing strategies. Despite these benefits, the study also highlights several challenges associated with RPA adoption. These include concerns about workforce implications, such as job displacement and the need for reskilling, as well as implementation difficulties related to system compatibility and workflow design. Ethical and regulatory considerations, particularly regarding data privacy and compliance, are also critical factors that organizations must address to maintain customer trust and adhere to legal standards. The study further explores the potential of integrating artificial intelligence (AI) with RPA to drive future innovations in marketing automation. AI-driven RPA offers advanced capabilities, including predictive modeling and personalized marketing, which promise to enhance the effectiveness of automation strategies. The findings underscore the need for organizations to adopt best practices in RPA implementation and remain adaptable to technological advancements to fully leverage the benefits of automation and maintain a competitive edge in the dynamic marketing landscape.
Influence of Fault Dip Angle and Strength on Fault Slip Characteristics of Gas Storage
Authors: Cheng Songlin , Wu Zhide , Qiu Xiaosong , Xu Haitao , Ding Guosheng , Liu Bingbing
Published: August 2024

The alternating stress caused by periodic high-pressure injection and extraction in gas storage can potentially induce fault slippage, compromising the sealing integrity of faults within these facil-ities. Understanding the mechanical behavior of faults under alternating stress is crucial for en-suring the long-term stability and safety of gas storage operations. To explore the impact of fault dip angle and fault gouge strength on fault slip characteristics, fault samples were prepared with uniaxial compressive strengths of 20.1, 30.2, 42.4, and 51.4 MPa at two distinct dip angles. Triaxial compression experiments were conducted under alternating stress conditions corresponding to operational pressures at a specific gas storage in China. Results indicate that faults with dip angles of 30° and 45° tend to fail at their weakest points. Increasing strength of fault gouge shifts failure mechanisms from interfacial failure between gouge and surrounding rock towards internal gouge failure, often accompanied by shear failure across sections, resulting in characteristic "X"-shaped conjugate shear failures. The decrease in the ratio of bedrock strength to fault gouge strength elucidates the observed phenomena of initial reduction followed by increased fault deformation. Transition points for faults with 30° and 45° dips occur around the strength ratios of 1.7/1 and 1.2/1, respectively. Fault damage exhibits a negative correlation with fault gouge strength and a positive correlation with fault dip angle. Samples with higher strength fault gouge at a 30° dip angle generally incur less damage compared to those with lower strength fault gouge at a 45° dip angle. Moreover, higher maximum static friction coefficients denote greater fault resistance to slipping, with 30° faults consistently demonstrating superior resistance compared to 45° faults. Additionally, higher strength fault gouge consistently enhances slip resistance under identical dip angles.
A Survey on Quantum Cryptography, its Protocols, Applications, and Challenges
Authors: Minhas Noman
Published: August 2024

This paper focuses on the concepts used in Quantum Cryptography and recent progress made. We look at the different categories of key distribution protocols that have been proposed and issues related to those. We then take an overview of two main approaches of communication using quantum cryptography concepts, i.e., ``Quantum Secure Direct Communication'' and ``Deterministic Secure Quantum Communication'', and limitations related to the usage of these schemes in a real-world system. At last, we list down the problems identified in the research and conclude our discussion by proposing areas of focus for future research.
A Novel Practical Approach for Directly Assessing COVID-19 Vaccine Efficacy against Hospitalization
Authors: Kirsch Steve , Marik Paul , Rogers Claire , Cosgrove Kirstin , Mead M. Nathaniel
Published: August 2024

We revisit a 2023 JAMA-published analysis of data from patients admitted for either COVID-19 or influenza to U.S. Veterans Administration (VA) hospitals in the fall/winter of 2022-2023. We note that baseline characteristics between the cohorts were similar, and the difference in vaccination rates was minimal, even after propensity score weighting. Had the vaccines been even minimally effective, significant differences in vaccination percentages would be expected. These findings call into question any efficacy claims associated with either the COVID-19 or influenza vaccines. Furthermore, the lack of efficacy of the influenza vaccines in reducing hospitalization is consistent with an earlier detailed study that found the same lack of efficacy, further validating the current result. This suggests that comparing vaccination rates between those hospitalized for different vaccine-preventable diseases can serve as a practical method for validating the vaccine efficacy claims of different vaccines.
Studying Engagement in Educational Settings: A Bibliometrics on High-Impact Academic Engagement Research
Authors: Loyola-Carrillo Paola , Vega-Muñoz Alejandro , Salazar-Sepúlveda Guido , Gil-Marín Miseldra , Adsuar-Sala José
Published: August 2024

Academic engagement provides opportunities and resources for students to engage in socio-educational interactions and academic learning. Our study provides an overview of high-impact research in academic engagement and the potential causes of its high valuation in the scientific community based on a bibliometric analysis of 4667 articles indexed in Web of Science, processed mainly by VOSviewer software. In terms of results, the publication of selected articles grows exponentially year by year, presenting concentration levels of 1% in authorship, 49% in a single country, and 5% of the journals. As well as 6% in highly cited articles, which in this case is associated with authors with high levels of publication. The most cited current topics are those relating academic engagement with motivation and emotional aspects.
1,2-Dicinnamoyl-Sn-Glycero-3-Phosphocholine Enhances Insulin Sensitivity and Increases the Expression Level of mtDNA-Encoded Genes in Insulin-Resistant 3T3-L1 Adipocytes – a Preliminary Study
Authors: Cierzniak Aneta , Gliszczyńska Anna , Małodobra-Mazur Małgorzata
Published: August 2024

Insulin resistance is a condition characterized by a reduced biological response to insulin. It is one of the most common metabolic diseases of modern civilization. Numerous naturally occurring substances have shown to have a positive effect in restoring the proper sensitivity to insulin. Mature 3T3-L1 adipocytes with artificially induced insulin resistance by palmitic acid (16:0) were used for the study. Cinnamic acid and 1,2-dicinnamoyl-sn-glycero-3-phosphocholin (1,2-diCA-PC) were tested at three concentrations: 25 μM, 50 μM, and 125 μM. The number of mitochondria and the expression of genes encoded by mtDNA were elucidated in control and experimental cells. In experimental cells treated with 1,2-diCA-PC, we displayed increased insulin-stimulated glucose uptake in a dose-dependent manner, accompanied by an increase in mtDNA copy number. Moreover, in experimental cells treated with 1,2-diCA-PC at the concentration of 125 μM, we observed a significant increase in the expression level of all analyzed genes encoded by mtDNA compared to control cells. Our study showed a relationship between improved cellular sensitivity to insulin by 1,2-diCA-PC and an increase in the number of mitochondria and expression levels of genes encoded by mtDNA. Summarizing, the results suggest a therapeutic potential of cinnamic acid derivative 1,2-diCA-PC in enhancing the insulin sensitivity of adipocytes.
The Role of Machine Learning in Predictive Analytics for Supply Chain Management
Authors: Wilson George , Johnson Oliver , Brown William
Published: August 2024

This study explores the transformative impact of machine learning on predictive analytics within supply chain management. As supply chains become increasingly complex and dynamic, traditional methods of forecasting and management are proving inadequate. Machine learning offers advanced algorithms capable of analyzing vast datasets to uncover patterns and trends that enhance decision-making processes. This research investigates how machine learning improves demand forecasting accuracy, optimizes inventory management, strengthens supplier relationships, and enhances risk management. The study employs a qualitative approach, analyzing data from industry case studies and expert interviews to identify key themes and challenges associated with the adoption of machine learning. Findings reveal that machine learning significantly improves forecasting precision, reduces inventory costs, and enables proactive supplier and risk management. However, challenges such as ensuring data quality, acquiring specialized skills, integrating new technologies with existing systems, and addressing ethical considerations are critical. The study also highlights the potential of emerging technologies like blockchain, IoT, and 5G to further enhance machine learning applications in supply chain management. This research contributes to a deeper understanding of how machine learning can drive innovation and efficiency in supply chains, while also addressing the hurdles that organizations must overcome. The results underscore the need for a balanced approach that incorporates technological advancements and ethical practices to fully leverage the benefits of machine learning.