bluuebunny/crossref_metadata_2025 huggingface dataset:
The Russian Idea: Concept, Problem Field, Modern Interpretations
Authors:   Alexander Solzhenitsyn House of Russia Abroad, Ermishin Oleg ,   Financial University under the Government of the Russian Federation
Published: September 2024

The article is devoted to the concept of Russian idea and its interpretations in the works of Russian thinkers of the late 19th – early 21st century. At first, the author of the article analyzes the concepts of V.S. Solovyov and V.I. Ivanov, their main theses in works on the Russian idea. Then he proceeds to consider the book by N.A. Berdyaev “Russian idea”, which covers all ideological diver­sity in the works of Russian thinkers of the 19th – early 20th century. For N.A. Berdyaev “Russian idea” is the idea of community (“commonality”), “brotherhood of people and peoples”, turned to future universal salvation. On the example of the works of V.S. Solovyov, V.I. Ivanov and N.A. Berdyaev, the author of the article shows general problem field, which includes various as­pects of research in connection with the “Russian idea”. From Russian thinkers of the late 19th – first half of the 20th century the author of the article goes on to analyze works on the Russian idea of the beginning of the 21st century. In these studies, the authors not only follow the tradition established by their pre­decessors in understanding Russian idea, but try to make additions and offer their own interpretations (A.V. Gulyga, V.I. Gidirinsky, S.N. Kocherov, O.V. Pa­rilov, V.Yu. Kondratyev). An exception to the general direction is A.G. Dugin, proposing not just to explore Russian idea, but to reveal on the basis of M. Hei­degger’s philosophy the “Russian Beginning”, which will become the leading idea for philosophizing in Russia, will create conditions for the “possibility of Russian philosophy”. Modern interest in the topic of “Russian idea” shows its relevance and the need for further philosophical research
Performance-aware Optimal Controller Placements Via Genetic Algorithms for Software Defined Networking
Authors: Nuguse Gutema Bote , Gemeda Ketema Adere , Ramulu Perumalla Janaki , Krishna T. Gopi
Published: September 2024

Software-defined Network is a new paradigm of providing the efficient network management using the concept of control and data place separation. Multi-controllers designing is a promising way to achieve reliability and scalability. However, it brings the new problem of controller placement in a distributed architecture. For this, two recent approaches of controller placement (CP) are based on controller placement simulated annealing (CPSA) and controller placement particle swarm optimization (CPPSO). However, these approaches are still not effective in placement of controllers. Thus, there is performance degrading of the systems. To solve these problems, the controller placement based on a Genetic Algorithm (CPGA) has been proposed in this research. The proposed CPGA has used the fitness value of each node to locate the controllers at their optimal place. Also, the GA operations continues until it gets the optimal placement of controllers and after locating the controller at their appropriate place, it was used for a long time in the case of near optimal rather than the existing approaches. The performance comparison has been done based on parameters such as throughput and delay. It is observed with comparison of CPSA and CPPSO that the proposed CPGA outperforms on given parameters. The proposed CPGA shows efficiency in placing controllers at their optimal locations.
Good moms: dependent-young and their mothers cope better than others with longer dry season in plains zebras
Authors: Thel Lucie , Bonenfant Christophe , Chamaillé-Jammes Simon
Published: September 2024

In large herbivores, the timing of births often matches the seasonal peak of availability of food resources, likely to improve juvenile survival and reduce reproduction costs. Some species however breed year round, even in seasonal environments. To what extent being born during the lean season reduces juveniles and reproductive females survival remains mostly unknown. This holds particularly true in tropical ecosystems where the demographic processes underlying population dynamics are often poorly studied. We investigate the variability of survival for plains zebras (Equus quagga) in Hwange National Park (Zimbabwe), a highly seasonal savanna ecosystem. We used capture-recapture models to analyse long-term demographic data (2008-2019). We investigated the effect of seasonality as a categorical (wet versus dry season) and continuous (duration of the dry season) variable on survival. We found little variability in the survival of younger foals (< 6 m.o), whereas older foals and yearlings’ survival, which was higher on average, decreased with the length of the dry season. Female survival was high but decreased with increasing exposure to the dry season for the non-reproductive ones only. The probability of females becoming reproductive the next year was not affected by the length of the dry season. Together, our results highlight the importance of individual quality in reproductive performance, as reproductive females seem to buffer the effect of environmental variability on their own survival and that of their foal. Timing of birth in this population might be the result of a trade off between minimising mother’s reproductive costs and maximising juvenile survival.
Assessing the Impact of Renewable Energy Integration on Energy Efficiency within the China-Pakistan Economic Corridor (CPEC)
Authors: Bensadi Anis
Published: September 2024

The China-Pakistan Economic Corridor (CPEC) is a major development project that aims to enhance connectivity and cooperation between China and Pakistan. It is part of China's broader Belt and Road Initiative (BRI), which seeks to improve trade routes and economic integration across Asia, Africa, and Europe. The study examines the impact of renewable energies such as hydro, biofuel, solar PV, and geothermal on energy efficiency within the CPEC. The findings reveal significant inefficiencies in the hydroelectric and biofuel energies, where energy production increases while efficiency declines. In contrast, solar PV and geothermal power had no discernible impact on the energy efficiency, suggesting that either these technologies are not yet fully utilized, since still being in the early stages of integration into CPEC's energy grid. The study recommends implementing several practices such as modernizing infrastructure by replacing outdated facilities with advanced technology to improve energy conversion and transmission efficiency. Integrating automation and control systems to minimize losses and enhancing maintenance practices to extend facility lifespan and performance. Scaling up solar PV and geothermal technologies through supportive policies and investments. Integrating smart grid technologies to enhance renewable energy effectiveness through better energy management. Finally, increase research and development investment, with essential collaborations between academia, research, and the energy industry to develop tailored solutions to meet the unique needs of the CPEC project.
Excellence in asset management through reliability centered maintenance (RCM)
Authors: Moradi Yasin , Shahrokhi Mahmoud , Moradi Taha
Published: September 2024

This study presents an approach to the excellence of physical asset management through reliability-centered maintenance (RCM). The goal of this study was to simultaneously minimize the failure risk index and cost. For each of the selected failure modes, the frequency, severity of consequences, and difficulty of failure identification were estimated according to the failure analysis method and its consequences. Strategies to prevent these failures and their effects on the frequency, severity, and difficulty of detecting each failure mode (FM) were specified. A mathematical programming model was developed to determine the annual implementation plan for preventive measures (PM) according to the cost and their effect on the failure modes. The program also considered human resources and budget constraints. This program was solved using the exact solution method for a hypothetical example using GAMS software, and the results were discussed and analyzed for sensitivity. This analysis studies the effect of changing important parameters on the optimal solution. The approach of solving the problem in large dimensions using the genetic algorithm (GA) method was presented, the problem was solved in different dimensions, and its results were examined. The proposed approach can be used as a RCM planning method in strategic industries.
Sulfophenylated centimeter-size graphene membrane in a direct methanol fuel cell
Authors: Schneider Gregory , Zhang Weizhe , Makurat Max , Liu Xue , Liu Xiaoting , Li Yanglizhi , Kock Thomas , Jiao Andy , Jiang Guangya , Leist Christopher , Maheu Clément , Sezen Hikmet , Calvani Dario , Eren Ismail , Buda Francesco , Qi Haoyuan , Feng Xinliang , Heine Thomas , Kuc Agnieszka , Hofmann Jan , Kaiser Ute , Sun Luzhao , Jiang Lin , Liu Zhongfan
Published: September 2024

An ideal proton exchange membrane should only permeate protons and be leak-tight for fuels. Graphene is impermeable to water and poorly conducting to protons. Next to long-term stability an ideal and optimized proton exchange membrane therefore needs to fulfil two main criteria: proton permeability and selectivity. Within methanol fuel cells, the first ensures a high-power density, while the second prevents fuel cross-over between the electrodes, which deteriorates catalyst performance and, thereby, drastically lowers performance. However, proton conductivity and selectivity are antagonistic in polymer membranes concerning their performance1. Long channel length in state-of-the-art membranes such as Nafion 117 is therefore a prerequisite to obtaining proton selectivity, at the cost of an additional ionic resistance through such long channels. Pristine graphene2 already fulfils these two criteria, partly as the graphene basal plane is impermeable to water and other molecules3, and exhibits a certain degree of proton conductivity4, influenced by nanoscaled ripples5, corrugations6, particularly in monolayer graphene oxide7 and hydrogenated graphene8. Here, we chemically functionalized monolayer graphene to install sulfophenylated sp3 dislocations by diazotization. Selective to protons, transmembrane areal conductances surpass those of polymer membranes, while providing proton selectivity over methanol through such an atomically thin layer. By creating proton-conductive and selective paths through graphene, we unveil a covalent chemical route to rationalize transmembrane proton transport through 2D materials.
Unveiling Sensory Quality in Coffee: A Data-driven Exploration
Authors: Oliveira Bruno Pereira , Buozzi Mário Trama , Pinto Vinicius Pereira , Yasuoka Fatima Maria Mitsue , Neto Jarbas C. Castro
Published: September 2024

The coffee market is projected to reach approximately US$468.2 billion by 2024. Coffee farms are found on practically all continents, with Brazil being the world's largest producer, accounting for approximately 60% of global coffee sales volume. Brazil boasts 35 distinct regions that certify, protect, and characterize their coffee based on specific aspects such as Sul de Minas, Mogiana, and Amazonia. Coffee pricing is determined by taste characteristics and is evaluated through sensory analysis, where human tasters assess the coffee using the SCAA cupping protocol. This protocol involves assigning scores. This complex system necessitates a large and dedicated workforce to evaluate samples from farms worldwide. This analysis aims to evaluate and compare the coffee sample scores from around the globe. By analyzing the scores and the characteristics of the sample, we can gain insights into coffee behavior and potentially identify statistically significant differences between samples.
Complexity and mediating factors in farmers' climate perceptions and agricultural adaptation strategies in the Guatemalan Dry Corridor
Authors: Anderson Talia , Pons Diego , Taylor Matthew , Xuruc Antonia , Salvatierra Hugo Rodríguez , Guido Zack , Sullivan Jonathan , Liverman Diana , Anchukaitis Kevin
Published: September 2024

Projected precipitation decreases due to anthropogenic climate change will have serious consequences for the millions of households in Central America that rely on rainfed agriculture. However, a signal of anthropogenic climate change is not yet clear in regional precipitation data despite observations from many farmers throughout Central America who report recent changes in rainfall and associated losses to crop production and food security. Given the role of climate perceptions on adaptation and the substantial variability in regional climate, it is important to study uncertainties in both climate and social data and their implications for decision-making. We use a combination of satellite-based climate data and over 700 household surveys from two departments in Guatemala to better understand rainy season climate patterns over recent decades. Climate data reveal variable trends depending on the time period and location. Farmers' perceptions of rainfall trends are vary widely and we identify factors that may contribute to this lack of consensus. We also assess how farmers' observations and household characteristics influence agricultural practices. Our findings suggest that regional differences, including off-farm income sources, mediate farmers' modification to their agricultural practices, irrespective of whether a trend in rainfall is perceived or not. However, adjustments to agricultural maize practices are significantly associated with perceived rainfall changes where there is greater dependence on income derived from smallholder agriculture. Reconciling household- and community-level perceptions with observed and anticipated climate variability and change is therefore critical in these regions to ensure appropriate adaptation interventions and strategies.
Simulation of summer climate over East China by convection-permitting regional air-sea coupled model
Authors: Jiang Zhiyu , Tang Jianping , Wang Shuguang , Dong Guangtao , Wang Shuyu
Published: September 2024

In this research, the Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Model was utilized to study the summer climate over eastern China and its adjacent ocean from 2009 to 2018. The COAWST model, equipped with a convection-permitting resolution of approximately 4km, effectively replicated the patterns of precipitation for both land and ocean, including sub-daily extreme precipitation, and the diurnal cycle. The COAWST model offers accurate simulations of the land-sea contrast in terms of the diurnal cycle of precipitation, showing the peaks of rainfall over land and sea in the afternoon and morning respectively. The model exhibited higher skill in extreme precipitation intensity over the ocean, while it was more skillful in wet frequency over the land. The overestimation of land precipitation can be attributed to stronger water vapor flux convergence and latent heat flux in the model. The inclusion of ocean module affects the ocean condition through fresh water injection, which contribute to the sea surface temperature (SST) bias in the simulation. This article highlights the strong performance of the coupled atmosphere-ocean model in simulating coastal precipitation of eastern China.
A model for classifying information objects using neural networks and fuzzy logic
Authors: Mukhin Vadym , Zavgorodnii Valerii , Liskin Viacheslav , Syrota Sergiy , Czupryna-Nowak Aleksandra , Rusyn Bohdan , Banasik Arkadiusz , Woloszyn Jacek , Kempa Wojciech
Published: September 2024

This work is aimed at developing intelligent systems capable of automatically classifying types of educational materials. This will allow students to find the resources they need faster, and it will make it easier for teachers to manage content in educational platforms. The solution of the problem of recognition of information objects using fuzzy output systems and neural networks is considered. This approach combines the advantages of neural machine learning with the flexibility and efficiency of fuzzy logic, making these systems effective tools for solving problems related to fuzzy or uncertain data. An information model of a neural network for classifying information objects in e-learning systems has been developed. Experimental testing of the proposed approach was carried out on a data set, which consists of information objects from real e-learning systems, namely such as manuals, lectures, syllabuses, and textbooks. The results of experimental studies have shown that a neural network built based on fuzzy logic is able to classify various information objects efficiently and correctly in e-learning systems. It is shown that the integration of neural networks based on fuzzy logic into e-learning systems to improve the processes of classification of information objects makes it possible to increase the efficiency of educational resources management, ensuring accuracy and flexibility in processing various data.
Oryza rufipogon (Griff.), a conduit for rapid evolution of rice under stress-prone environments: a test case of UV-B resistance and exoferalization
Authors: Senapati Preetam Kumar , Kariali Ekamber , Kisan Kuntala , Mohapatra Pravat Kumar
Published: September 2024

In general, wild relatives of cultivated rice are a repository of stress-tolerant genes and have been used to introduce resistance into cultivated rice. Compared to other abiotic stresses like drought, heat, cold, salinity, and disease resistance, UV stress emerged late in the biosphere, and there has been minuscule research on its trait location for resistance among rice genotypes for a possible way of introgression into cultivated species. Wild rice O. rufipogon (Griff.) which is sensitive to UV stress was facilitated to cross-pollinate naturally with a UV stress-resistant traditional cultivated rice Meghadambaru and the hybridization impact on stress tolerance was assessed on the progeny as well as the progenitors. UV stress affects vegetative growth by the downregulation of photosynthetic activity of leaf, lemma + palea, and awns because of its inhibitory effects on SPAD index, Fv/Fm ratio, and ETR (rel), photochemical quenching qP (rel), maximal fluorescence Fm (rel) and release of fluorescence energy (OJIP curve) in all three genotypes. However, these indices in O. rufipogon were found more vulnerable. The Intergrade genotype resulted from the parental cross-inherited weedy characters of O. rufipogon and UV tolerance attributes of Meghadambaru of the F1 generation followed by the F2 generation. O. rufipogon exhibited rapid evolution to gain UV stress resistance in the natural cross, while Meghadambaru resurged in exo-feralization and resurrected to devolution to weedy attributes.
Diet, Metabolic Biomarkers, and Sensorineural Hearing Loss: A Mendelian Randomization and Mediation Analysis
Authors: Yang Haoxiang , Luo Yaxin , Chen Bing
Published: September 2024

Sensorineural hearing loss (SNHL) is influenced by genetic and environmental factors. This study explores the causal relationships between dietary choices, circulating metabolic biomarkers, and SNHL using Mendelian Randomization (MR) analysis. We utilized summary statistics from genome-wide association studies (GWAS) on dietary choices and metabolic biomarkers as exposures, with SNHL as the outcome. Two-sample MR analysis and mediation analysis were conducted to identify causal links and metabolic pathways. The MR analysis revealed that fish, oily fish, healthy food, and vegetable consumption significantly reduce the risk of SNHL. The mediation analysis further indicated that these protective effects are mediated by the ratios of DHA, omega-3, and polyunsaturated fatty acids to total fatty acids, with DHA mediating approximately 10.57% of the protective effect of oily fish consumption. Significant causal pathways link dietary choices and metabolic biomarkers to SNHL, suggesting that dietary modifications, particularly increasing the intake of fish, healthy foods, and vegetables, could serve as effective preventive strategies against SNHL. This study provides valuable insights into the interplay between diet, metabolism, and hearing health, guiding future preventive strategies.
Plasmodium SEY1 is a novel druggable target that contributes to imidazolopiperazine mechanism of action
Authors: Winzeler Elizabeth , Carolino Krypton , De Souza Mariana Laureano , Chen Daisy , Farre Jean-Claude , Blauwkamp James , Absalon Sabrina , Ghidelli-Disse Sonja , Morano Alexander , Dvorin Jeffrey , Lafuente-Monasterio Maria Jose , Gamo Francisco-Javier
Published: September 2024

The precise mode of action of ganaplacide (KAF156), a phase III antimalarial candidate, remains elusive. Here we employ omics-based methods with the closely related chemical analog, GNF179, to search for potential Plasmodium targets. Ranking potential targets derived from chemical genetics and proteomic affinity chromatography methodologies identifies SEY1, or Synthetic Enhancement of YOP1, which is predicted to encode an essential dynamin-like GTPase implicated in homotypic fusion of endoplasmic reticulum (ER) membranes. We demonstrate that GNF179 decreases Plasmodium SEY1 melting temperature. We further show that GNF179 binds to recombinant Plasmodium SEY1 and subsequently inhibits its GTPase activity, which is required for maintaining ER architecture. Using ultrastructure expansion microscopy, we find GNF179 treatment changes parasite ER and Golgi morphology. We also confirm that SEY1 is an essential gene in P. falciparum. These data suggest that SEY1 may contribute to the mechanism of action of imidazolopiperazines and is a new and attractive druggable target.
Optimizing Droplet Condensation for Eco-Friendly Cooling: Experimental and CFD Validation
Authors: Kothari Prafull , Pachouri Vikrant , Yadav Indrajit N
Published: September 2024

This study presents a novel cooling system that combines optimum droplet condensation and thermoelectric cooling to reduce energy consumption and environmental impact. With an amalgamation of conventional cooling models, the research adds a new form of nozzle and diffuser layout that increases droplet formation and cooling efficiency. The efficiency of the system was confirmed by experimental tests and modern CFD analysis that proved a 20% enhancement of cooling with a 15% energy saving compared to traditional techniques. The hybrid technique helps the cooler to be environmentally friendly and at the same time points out the possibilities of using the system in high-risk areas like data centers and pharmaceutical facilities. This helps in the development of sustainable cooling technology which goes a long way in providing industries with a probable solution to improving their sustainability and at the same time achieving better performance.
Dynamic Characteristics Analysis and Fault Feature Study of Bearings with Compound Defects
Authors: Ni Wenjun , zhang chang
Published: September 2024

To investigate the dynamic variation patterns of rolling bearings with compound faults, a dynamic finite element model of defective bearings was established in ANSYS based on explicit dynamics algorithms. This model fully considers factors such as bearing rotational speed, load, contact, and friction. The dynamic analysis of rolling bearings with composite faults, involving rolling element and outer raceway dents, was conducted. The study results indicate significant differences in shear stress and vibration acceleration characteristics at different rotational speeds. The higher the speed, the more severe the fluctuations in stress and vibration acceleration, which significantly impacts bearing life. To further extract and analyze fault features, the Variational Mode Decomposition was used to decompose the vibration signals obtained from explicit dynamic simulations, yielding Intrinsic Mode Function (IMF) components at different speeds. By calculating the kurtosis, sample entropy, and envelope entropy of each IMF component, a comprehensive evaluation index was established. The components were then ranked using a weighted average method, selecting those with higher evaluation indices as effective components. After performing a Fast Fourier Transform (FFT) on the effective components, time-domain and frequency-domain analysis successfully extracted crucial information containing bearing fault features. This provides important references for bearing condition monitoring and fault diagnosis.
Abundance and Characterization of Microplastics in Compost Produced in Mazandaran, Iran
Authors: Zazouli Mohammad Ali , Alashti Mahdieh Mohammadi , Dehghan Samaneh , Dehbandi Reza , Fendereski Afsaneh
Published: September 2024

One of the source of plastics and microplastics (MPs) entering the environment and the food chain is waste from various sources. Most plastic resins are utilized in packaging with relatively short lifespans; after consumption, these materials contribute to municipal solid waste. The composting process struggles to completely separate plastics, making microplastics a significant contaminant during composting. MPs are defined as plastic particles smaller than 5 mm. This study aims to examine the frequency, distribution, and characteristics of microplastics found in compost produced by Mazandaran compost factories. MPs in the samples were extracted and separated based on density differences and digestion. Subsequently, a stereomicroscope was used to observe the MPs. This cross-sectional study found an average microplastic content of 16,981 items/kg across all compost samples. Behshahr compost had the highest average at 1,818,622, while Babol had the lowest at 15,744 items/kg. The Kruskal-Wallis test indicated no statistically significant differences between the sampling stations (p > 0.05). The most common shapes were fibers (75%), with the predominant color being transparent-white (56%), and the most frequently observed size range was 500–1000 µm (40%). Additionally, polymers identified included polyurethane, nylon, low-density polypropylene, and polycarbonate. This study reveals the presence of microplastics in compost from Mazandaran's fertilizer and compost factories. To address this issue, it is essential to develop strategies for reducing plastic waste entering composting facilities and to establish effective monitoring programs to detect and identify microplastic hotspots.
Evaluating and Visualization of Renewable and Green Energy Research Productivity and Contribution: A Bibliometric Analysis of ISI Web of Science Databases
Authors: Cheema Waqas Akram , Ahmad Khurshid , Ali Nusrat
Published: September 2024

The field of Renewable Energy has seen exponential growth in academic publications. This paper aims to survey and analyze existing research in renewable energy, identifying influential publications, authors, and organizations to delineate key research areas. Data were gathered from Web of Science (Core Collections) using the search query "Renewable Energy OR Green Energy" for publications between 2011 and 2023. Analysis utilized various software tools such as VOSviewer, ScientoPy, R, and MS Excel. Findings indicate that the majority of publications in Renewable Energy or Green Energy are predominantly in English, with a consistent upward trend in publication rates. Adebayo, Tomiwa Sunday emerges as the most prolific author. China emerges as the leading nation in publication output, particularly attributed to North China Electric Power University, a notable institution in the field. Following the United States and India, China has contributed significantly in terms of both article production and citation reception. Elsevier stands out as the primary publishing source, while Renewable Energy is identified as the leading journal in terms of productivity and influence.
Head-on Collisions of Fuzzy/Cold Dark Matter Subhalos
Authors: Koo Hyeonmo
Published: September 2024

We perform head-on collision simulations of compact dark matter subhalos using distinct numerical methods for fuzzy dark matter (FDM) and cold dark matter (CDM) models.For FDM, we solve the Schrodinger-Poisson equations with a pseudospectral solver, while for CDM, we utilize a smoothed particle hydrodynamics N-body code. Our results show that velocity decrease of subhalos is significantly greater in FDM model than in CDM, particularly at lower initial velocities, attributed to gravitational cooling-a unique mechanism of stabilizing in FDM with dissipating kinetic energy.This stark contrast in energy dissipation between two DM models suggests that FDM may offer valuable insights into understanding the dynamic behaviors of DM during galaxy cluster collisions, such as those observed in the Bullet cluster and Abell 520.These findings strongly suggest that FDM is not only capable of explaining these complex astrophysical phenomena but also serves as a compelling alternative to the traditional CDM model, offering resolutions to longstanding discrepancies in DM behavior.
Exploring the needs and preferences of older trauma patients: A qualitative study
Authors: Williams Jill , Chapman Madi , Evans Cath J , Botha Martie , Murad Juvaria , Linde Dieter , Harrington Cindy , Crotty Maria , Laver Kate
Published: September 2024

Background: Trauma in older people is emerging as a major health issue, with falls being the most common cause. Despite existing guidelines for trauma care of older populations, adoption is limited and undertreatment persists. This study aimed to explore the needs and preferences of older people and their families following traumatic injuries and define key components of a trauma care model for older populations.
Methods: This research adopted participatory design principles, engaging older people and their families, who had interacted with local healthcare services, to participate in a workshop which included structured activities and questions designed to facilitate discussion of the participants’ experiences of trauma and subsequent healthcare. Qualitative data were collected, coded, and analyzed using thematic analysis.
Results: Seven patients and six family members attended one of two workshops. Most patient participants were women, with a mean age of 82 years. Participants reported negative feelings following trauma, including uncertainty, shock and fear, decreased confidence, and feeling burdensome. Recovery goals were focused on regaining independence, participating in movement and exercise, and maximizing social connection. Communication, empathy and interpersonal skills in care, and system-related factors were identified as key factors impacting care and recovery experience following trauma. To improve trauma care, participants recommended care coordination, improved access to home support and rehabilitation, investment in staff expertise and training, and a dedicated trauma service for older adults.
Conclusions: This study underscores the importance of a comprehensive and person-centered approach to trauma care for older people, offering valuable insights for healthcare providers and policymakers striving to enhance the quality of care and improve outcomes for this vulnerable population.
Cyclooctatetrathiophene Based MOF-Derived Porous Materials as High- Performance Anode for Lithium-Ion Batteries
Authors: Zhang Weimiao , Zhong Yuan , Shen Zhan , Meng Ya-Ru , Wang Yang , Xu Bingqing , Su Jian , Zhang Gen
Published: September 2024

Extensive research on anodes with higher capacity than carbon materials is driven by the demand for lithium-ion batteries with higher energy density. But cycling stability of high-capacity anodes is hindered by the structural collapse. Metal-organic frameworks (MOFs) are an emerging class of crystalline materials, and their derivatives are expected as alternative high-capacity anodes, resulting from the merits of easy functionalization and pore engineering. In this study, a novel porous Co-MOF-derived composite anode was prepared by the pyrolysis of nonporous Co-cyclooctatetrathiophene tetrapyridine (Co-COTTTP) template. The resulting porous carbon based composite anode demonstrated high specific capacity and long cycling stability in the assembled cells. Co-COTTTP-500 delivered a high reversible specific capacity of 1005.7 mAh g−1 after 100 cycles at 0.1 A g−1 and can be cycled steady for 800 cycles at 1 A g−1, indicating the structure stability during cell operation. The comprehensive investigation of the framework structure and the composition of Co-COTTTP-derived composite anodes revealed that the exposed rich redox active sites, appropriate degree of graphitization, and heteroatom doping in the composites effectively enhanced the electrochemical performance of the composite anodes. In summary, this study provides a feasible strategy to prepare high-performance MOF-derived anodes, contributing to the fabrication of high-energy-density lithium-ion batteries.
ISiamDW：Improved SiamRPN Target Tracking Algorithm Based on Inverted Residual Mobile Block
Authors: Jiang Zhengye , Li TianPing
Published: September 2024

The SiamRPN target tracking algorithm has received widespread attention due to its good balance between speed and performance. Its concise network structure makes it faster, but the tracking effect is not satisfactory. Especially in complex backgrounds, SiamRPN often loses targets. The SiamRPN algorithm lacks the ability to recognize interference from similar objects when using deep semantic features for tracking. Therefore, we have introduced an inverted residual mobile block for this purpose. The inverted residual mobile block utilizes multi-head self-attention and depthwise separable convolution cascades to decompose and recombine the feature information extracted from the backbone Siamese network of SiamRPN, improving the model's generalization ability and avoiding the influence of similar targets in complex scenes which may result in incorrect tracking. In addition, we extensively use depthwise separable convolutions to reduce the number of parameters and improve tracking efficiency. The tracker achieved good results on three large tracking benchmarks, including OTB2015, UAV123, and VOT2016. Especially in UAV123, it has excellent performance and can be applied in unmanned aerial vehicle tracking and enemy search.
Radon Quantification in Water and Dose Estimation via Inhalation and Ingestion Across Age Groups in the Pattan Region of North Kashmir
Authors: Pandith Tanveer Ahmad , Simnani Shakeel , Ahmad Rayees , Singh Krishna Pal , Gewali Jeeban Prasad
Published: September 2024

Human survival hinges on access to water, which provides vital necessities. It is crucial to secure reliable, affordable, and uncontaminated water to maintain health and sustain life. For the potential impact of radioactive water pollution on human well-being, a scintillation-based smart RnDuo detector was employed in the Pattan region of North Kashmir Baramulla to quantify radon levels in diverse underground water. The dose contribution to various organs through inhalation and ingestion pathways has been analyzed. The study assesses the levels of radon in water, which varied from 19.88 to 74.37 Bq/L with an average of 37.65 Bq/L. All of the values were higher than the USEPA's guideline of 11 Bq/L but lower than 100 Bq/L prescribed by WHO. The age group-wise inhalation and ingestion doses are higher than the 100 µSv/y recommended by WHO but within the prescribed range of 3–10 mSv/y as suggested by ICRP. Doses to various organs are calculated in the present study showing that lungs and gonads are highly impacted by radon exposure, followed by the esophagus, skin, and bones. The results of the present investigation will help to enhance the quality of the water and guide future epidemiological studies.
Improving the observed-to-expected ratio method to identify true patterns of multimorbidity
Authors: Baneshi Mohammad Reza , Mishra Gita Devi , Dobson Annette
Published: September 2024

Background In the study of multimorbidity, the observed-to-expected ratio is frequently used to identify triads of conditions associated with each other. However, the method may wrongly identify spurious triads which are only partially associated as being true triads. This paper aims to improve the method to identify mutually associated triads. Methods Data were simulated to emulate the characteristics of our empirical data. Using 25 simulated binary variables, 2,300 triads were created. For each triad, the following statistics were calculated: the observed-to-expected ratio, the logarithm of the observed-to-expected ratio known as the information component, and the lower confidence interval of the information component (\(\:{IC}_{0.025}\)). Furthermore, for each triad, we calculated three lift values (using association rule mining) to assess the dependency of each condition with the other two. Then, within each triad, \(\:{IC}_{0.025}\) for all three constituent pairs were calculated. \(\:{IC}_{0.025}<0\) indicates independent of conditions. Triads with three pairs having \(\:{IC}_{0.025}>0\) were defined as true. Triads with at least one of the pairs having \(\:{IC}_{0.025}<0\) were defined as false. Among the false triads, those with the triad \(\:{IC}_{0.025}>0\) were defined as spurious (i.e., the lower bound of the information component for the whole triad exceeding 0). Methods were then applied to the Australian national mortality data. Results In simulated data, 53.2% of false triads were spurious (i.e., while at least one pair was independent, \(\:{IC}_{0.025}\) of the triad exceeded 0). Through algebra, we illustrated that the closeness of the observed-to-expected ratio and lift is an indication of independence among some conditions within the triad. For all spurious triads, the observed-to-expected ratio and lift were close, suggesting dependency of a pair within the triad. The observed-to-expected ratio was about twice as high as the lift for true triads, indicating mutual associations. In the Australian national mortality data, for 95% of triads with high OE ratios, the observed-to-expected ratios and lifts were close suggesting dependency of a pair within the triad. Conclusion An associated pair may attract an unrelated condition and create a spurious triad. To guard against spurious findings, the observed-to-expected method should be used alongside the association rule mining.
Precise LEO orbit determination using regional PPP-B2b augmentation services
Authors: Zhou Haitao , Wang Lei , Chen Ruizhi , Li Jiansheng , Chen Mingjian , Li Linyang , Fu Wenju
Published: September 2024

The PPP-B2b service broadcasted by BDS-3 GEO satellites can provide centimeter to decimeter-level positioning accuracy in China and surrounding area. As a free satellite based-augmentation system, BDS PPP-B2b service also potentially benefits the low earth orbit (LEO) space users to improve the orbit determination accuracy. The challenge is the regional PPP-B2b augmentation information cannot cover the full orbit arc, so it has to switch the ephemeris datum between the PPP-B2b ephemeris and the broadcast ephemeris during the LEO precise orbit determination (POD). The PPP-B2b clock product is generated from a regional network, whose datum may not be consistency with the broadcast ephemeris, which hinders the seamless fusion between the PPP-B2b ephemeris and the broadcast ephemeris. In this study, we proposed a PPP-B2b enhanced model with hybrid LNAV/PPP-B2b clock offset datum transformation (CDT) and validated it with onboard GPS data from the GRACE satellites. Compared to the results using hybrid ephemeris without CDT, the results of reduced-dynamic and kinematic POD using the hybrid ephemeris reveal that the orbit accuracy with CDT is improved by 11.71% and 26.95% in 3D direction, and the LEO clock frequency stability with CDT is improved by 34.77% ~ 44.3% and 23.29% ~ 44.35% for different averaging times. The proposed CDT method achieves 2 decimeter accuracy in reduced-dynamic orbit and provides new application prospects for LEO POD based on regional PPP-B2b service.
Effect of heterogeneous catalysts on the mechanical and relaxometric behavior of lactic acid-cured epoxidized vegetable oil vitrimer
Authors: Rodrigues João Gabriel Passos , Neto Roberto Pinto Cucinelli , Arias Santiago , Pacheco Jose G. A. , Dias Marcos Lopes
Published: September 2024

Biobased vitrimeric materials were obtained from epoxidized canola oil (ECO) and lactic acid (LA) where zinc acetate (ZnAc) and ZnAl-layered double hydrox- ide (ZnAl) were used as transesterification catalysts at concentrations of 1 and 2wt%. Incorporation of these catalysts into the vitrimers was confirmed by X- ray diffraction analysis where characteristic crystalline peaks of the catalysts appeared in the vitrimers. NMR Relaxometric showed that the addition of cat- alysts reduced the density of cross-links and promoted increased mobility of polymer chains in the vitrimers. Mechanical tests revealed that the addition of both catalysts promoted decrease in some mechanical properties with a variation in rupture stress in the range of 0.71 to 0.11 MPa, rupture strain in the range of 21.3 to 49.4% and in Young’s modulus from 0.24 to 3.04 MPa. SEM images revealed that the addition of the catalysts introduced defects in the polymer matrix and increased the brittleness of the material.
Abnormal time series detection under unsupervised and multi-working conditions for power system of unmanned equipment
Authors: Zhang Chaoqi , Gou Xinyi , Zhang Qingzhen , Yu Guizhen
Published: September 2024

Due to the importance of the power subsystem in unmanned equipment (UE), it needs accurate anomaly detection methods to ensure its safe and stable operation. Under the condition of unsupervised and extremely lack of abnormal samples, deep learning methods and machine learning methods are difficult to apply. In addition, the operating conditions of UE are variable and abnormal modes are diverse, which bring greater challenges to the anomaly detection task. To solve the above problems, this paper proposes a new anomaly detection method for time series of unmanned equipment power system (UEPS). Firstly, a similarity measurement method based on series decomposition and fast dynamic time warping is introduced to improve the accuracy of series similarity measurement. Then, taking the time series as samples, the density clustering algorithm is applied to separate the categories with small sample number as anomaly categories. Finally, based on the normal class labels obtained by clustering, the support vector data description algorithm is used to realize new abnormal time series detection in the absence of abnormal samples. In the anomaly detection experiments on power system data in Unmanned Aircraft System Mission, the method proposed in this paper shows excellent performance, and effectively solves the problem of unsupervised, multi-working conditions and lack of abnormal samples.
Atrial Appendage Closure is Associated with Increased Risk for Postoperative Atrial Fibrillation
Authors: Shuhaiber Jeffrey , Abbas Mostafa , Moorland Thomas , Kirchner H. Lester , El-Manzalawy Yasser
Published: September 2024

Objectives
This study aims to examine the relationship between left atrial appendage closure (LAAC) and post-operative atrial fibrillation (POAF) in cardiac surgery patients with no pre-operative atrial fibrillation (AF).
Methods
We analyzed a cohort of 2059 adult patients in our Society of Thoracic Surgery (STS) database who underwent at least one of the following procedures between 2018 and 2021: coronary artery bypass grafting (CABG), aortic valve replacement, or mitral valve replacement. All patients had no pre-operative AF, and 169 (8.2%) of them received a left atrial appendage closure (LAAC). Primary outcome was new-onset POAF and secondary outcomes included 1-year mortality, 30-day readmission, 1-year incident stroke, and post-operative hospital length of stay (LOS). Patients without an LAAC were matched to LACC patients using a 1:1 nearest neighbor propensity score method to reduce the bias due to potential confounding. Associations between LAAC and postoperative adverse outcomes were assessed using appropriate statistical tests for matched analyses.
Results
The matched cohort included 162 pairs. LAAC was associated with elevated risk of new-onset POAF (41.4% vs 25.3%, p = 0.003), and postoperative hospital LOS (142.1 vs 120.5 hours, p = 0.001). The LAAC did not significantly impact all-cause 1-year mortality, 30-day readmission, and 1-year incident stroke.
Conclusions
In cardiac surgery patients with no pre-operative history AF, LAAC was associated with substantially higher rates of new-onset POAF, without a corresponding impact on risk of 1-year incident stroke, 30-day readmission, or 1-year mortality.
Optimized Power Management for Fuel Cells Electrical Vehicles Using High Step-Up Converter
Authors: Dinakaran K P , jebaselvi G D Anbarasi , Karthikeyan N
Published: September 2024

This paper proposes a new DC-DC converter at the front-end of the powertrain of FCVs which offers a high step-up voltage gain with low voltage stress. Battery systems of FCEVs supply a high voltage alternating current (AC) output while fuel cell systems in FCVs output low-voltage DC. In adopting electric drivetrains there is need to have efficient voltage conversion for the high voltage needed.. Conventional topology converters can often fail to provide the required voltage boost while also experiencing heavy efficiency degradation together with voltage stress affecting the elements of the converter’s circuit, which can reduce its reliability and shorten its lifespan. The converters’ TLO operating principles and performance indicators are comprehensively explored and analytically quantified using mathematical modeling. The findings of the study’s simulation support the theoretical propositions and highlight that the converter can deliver greater than tenfold string voltage gain while reducing the voltage stress on semiconductor switching devices and diodes. Since the DC-DC converter maintain a constant output voltage, is cheap, easy to construct, and has an efficiency of over 95% it is suitable for many FCV applications. It provides useful procedure for enhancing the efficiency and lifespan of FCVs through achieving high voltage and low stress conversion.
Greenness Assessment of High-Performance Liquid Chromatography Method for Simultaneous Estimation of Apigenin, Apocynin and Gallic Acid with Quality by Design Approach
Authors: Mevada Shweta , Patel Harsha U. , Shukla Saurabh
Published: September 2024

This study presents the development of an eco-friendly high-performance liquid chromatography (HPLC) method for the simultaneous determination of apigenin, apocynin, and gallic acid, integrating Analytical Quality by Design (AQbD) and Green Analytical Chemistry (GAC) principles. The objective was to enhance method efficiency while reducing environmental impact, energy consumption, and solvent use. An AQbD approach was employed, starting with quality risk assessment and scouting analysis, followed by optimization using Box–Behnken Design (BBD) to screen three key chromatographic parameters. The optimal chromatographic conditions were determined using a C18 Column (250 mm × 4.6 mm, 5 μm) with a mobile phase of Methanol: Water (80:20 %v/v), a flow rate of 1 mL/min, UV detection at 228 nm, and a temperature of 25 °C. The method demonstrated linearity over a concentration range of 1–5 μg/mL for the target compounds, with gallic acid as an internal standard. The method’s greenness profile was assessed using various evaluation tools, confirming its compliance with green analytical chemistry principles. The results indicate that the proposed HPLC method is not only effective and reliable but also environmentally sustainable, making it suitable for routine use in quality control laboratories. The integration of AQbD and GAC principles highlights the method's contribution to more sustainable and efficient analytical practices.