bluuebunny/crossref_metadata_2025 huggingface dataset:
Developing Sustainable Hospital Capacity Management Protocols Using Clinical Prognostic Analysis: A Novel Stochastic Model for Covid-19
Authors: Saadat Mohsen , Heydari Mohammad , Dongsheng Zhai
Published: May 2024

The relentless challenges posed by the COVID-19 pandemic have placed immense pressure on densely populated regions, such as Hong Kong, particularly in the context of an aging population. The burgeoning demand for healthcare services has necessitated the optimization of resource al-location within healthcare systems. This research presents an innovative analytical queueing model specifically tailored to address the intricate gridlock dynamics prevalent in healthcare systems, with a focused application in the challenging landscape of COVID-19 management. Hong Kong, like numerous other regions, has experienced a demo-graphic transition leading to heightened healthcare demands. Traditional methodologies for scrutinizing gridlock issues in healthcare settings, including simulation models, often prove suboptimal within the context of sophisticated optimization frameworks. This study, however, delves into analytical queueing models, offering a more efficient and effective approach. These models have been underexplored, primarily due to the intricacies involved in modeling gridlock propagation within restricted capacity, a critical concern magnified by the COVID-19 pandemic. The novel Queueing Model introduced in this research incorporates the maintenance of queue capacities and topological aspects as exogenous parameters, rendering it exceptionally adaptable for diverse gridlock-related applications. This adaptability is especially pertinent to healthcare management during the COVID-19 crisis. The model meticulously integrates the concept of gridlock, furnishing a comprehensive comprehension of its origins and repercussions. Validation of this model involves rigorous comparison with established methodologies, exact results, and simulation data, consistently high-lighting its versatility and precision. By applying the model to healthcare management, we scrutinize the dynamics of patient flow within a Hong Kong hospital, placing specific emphasis on the critical issue of bed blockage, further exacerbated by the COVID-19 pandemic. The model's gridlock decomposition unearths the nuanced impact of bed blockage on distinct hospital units, addressing the imperative requirement for quantifying in-patient bed blockage within healthcare systems during a pandemic.
Assessing the Effectiveness of Certification Programs in Ensuring Supply Chain Sustainability in the Renewable Energy Sector
Authors: Reynolds Samantha
Published: May 2024

This qualitative research investigates the effectiveness of certification programs in ensuring supply chain sustainability within the renewable energy sector. Through interviews and content analysis, the study explores stakeholder perceptions, challenges, and impacts of certification initiatives. Findings reveal diverse motivations driving certification adoption, including regulatory compliance, market differentiation, and corporate social responsibility. However, challenges such as greenwashing and limited transparency undermine the credibility and effectiveness of certification programs. Despite these challenges, certification initiatives drive incremental improvements in environmental performance and stakeholder engagement, fostering a culture of continuous improvement and innovation. Multi-stakeholder collaboration and context-specific approaches are essential to address regional disparities and promote sector-wide transformation. Strategies for improvement include strengthening monitoring and enforcement mechanisms, integrating emerging technologies, and aligning certification standards with broader sustainability goals. Overall, certification programs offer a pathway for promoting transparency, accountability, and responsible business practices within the renewable energy supply chain, contributing to the transition towards a more sustainable and resilient energy future.
Comparative Analysis of Length Deformation in Classical and Relativistic Mechanics
Authors: Thakur Soumendra Nath
Published: May 2024

This study presents a comparative analysis of length deformation in Classical and Relativistic Mechanics, specifically investigating 10-gram objects accelerating to 1% of the speed of light. By employing Hooke's Law in Classical Mechanics and the Relativistic Lorentz Factor, the research explores the implications of acceleration dynamics and the limitations inherent in Relativistic Mechanics. The results reveal significant differences in predicted length changes between the two frameworks, emphasizing the necessity of considering relativistic effects beyond velocity alone. This study underscores the critical importance of addressing the incomplete treatment of acceleration dynamics in Relativistic Mechanics to achieve a more accurate depiction of length deformation in high-speed scenarios.
A Structural Path Analysis Towards Examining Technological Factors Influencing SME’S Sustainability Through Social Media Marketing
Authors: Haque Rasheedul , Senathirajah Abdul Rahman bin S , Khalil Md Ibrahim , Qazi Sayeeduz Zafar , Ahmed Saif
Published: May 2024

Businesses use technological and social media marketing to respond to the Covid-19 pandemic. This study aims to understand better the factors that impact the spread of new technologies, the effectiveness of social media advertising, and the longevity of businesses. The study used a quantitative strategy based on partial least squares structural equation modeling to learn about the phenomenon of interest as much as possible. Dhaka, Bangladesh, small and medium-sized businesses participated in the survey. According to the findings, the popularity of internet and e-business technologies may be attributed to their apparent usefulness and ease of use. It is connecting internet/e-business technology, social media marketing, and the long-term success of small and medium-sized enterprises. Still, the expense factor was insufficient to prove that SMEs engage in social media advertising. Mediating effects between components may be better understood via internet/e-business technology and social media marketing, as shown by this study. This study is the first of its kind in Bangladesh and sheds light on the resilience of SMEs in the face of the Covivirus-19 pandemic, notwithstanding its focus on the capital city of Dhaka.
Research Review on Synthesis of Biowaste Graphene Quantum Dots for Supercapacitor Applications
Authors: singh priyanka , gupta Gopal
Published: May 2024

This research review explores the synthesis of graphene quantum dots (GQDs) from biowaste for supercapacitor applications, driven by the need for sustainable and efficient energy storage technologies. GQDs, with their unique properties like high surface area and excellent conductivity, hold promise for enhancing supercapacitor performance. Various synthesis methods, including hydrothermal/solvothermal processes, chemical exfoliation, carbonization/pyrolysis, and microwave-assisted synthesis, are discussed alongside characterization techniques to evaluate GQD properties. Biowaste-derived GQDs demonstrate significant potential by improving specific capacitance and cycling stability in supercapacitor electrodes. Challenges such as scalability and material purity are identified, with future directions focusing on enhancing energy density, cycle life, and cost-effectiveness to propel the adoption of biowaste-derived GQDs in commercial energy storage applications.
Gambaran Self-Acceptance (Penerimaan Diri) Pada Remaja yang Tinggal Bersama Orang Tua Tunggal Ibu
Authors: Islami Anisa Chelsea , Fitriyani Hilma
Published: May 2024

Penelitian ini bertujuan untuk mendapatkan pemahaman yang lebih dalam tentang penerimaan diri pada remaja yang tinggal dengan orang tua tunggal ibu. Tipe penelitian ini adalah penelitian kualitatif dengan menggunakan metode studi kasus. Informan utama dalam penelitian ini adalah 1 orang remaja akhir yang hidup dalam pengasuhan orangtua tunggal. eknik sampel yang digunakan adalah teknik purposif. Teknik pengumpulan data yang digunakan adalah wawancara mendalam atau indepth interview. Instrumen penelitian yang digunakan yaitu pedoman wawancara yang dikembangkan berdasar pada teori penerimaan diri Arthur Thomas Jersild (1978). Pemeriksaan keabsahan data dilakukan dengan melakukan triangulasi sumber, dengan melibatkan Ibu dan juga sahabat dari informan utama, triangulasi teori, dan triangulasi teknik. Hasil penelitian menunjukkan bahwa responden memiliki penerimaan diri yang baik. Penerimaan diri yang baik karena adanya dukungan, motivasi, pola pengasuhan tunggal yang baik serta peran keluarga yang harmonis sehingga mempengaruhi penerimaan diri informan.
Reviving Javanese Script through an Engaging Educational Game
Authors: A’amin Bagas Muzaky , Ratna Ika
Published: May 2024

This study introduces an educational game designed to teach the Javanese script to both children and adults. The game features three difficulty levels and aims to enhance intellect and creativity while keeping players engaged. The development process included system requirements analysis, design, implementation, and testing. Results show the game effectively teaches correct reading and spelling of Javanese characters and is easy to use for all ages. This application combines education and entertainment, making it a valuable tool for cultural learning and intellectual growth.
Highlight:

The game is designed for all ages, including adults.
It features three difficulty levels to enhance intellect and creativity.
The development process ensures the game is user-friendly and educational.

Keywoard: Javanese script, educational game, intellect enhancement, creativity, cultural learning
Fuzzy Logic Optimizes Global Inventory Management
Authors: Atika Dewi Nur , Sukmono Tedjo
Published: May 2024

Inventory control is crucial for balancing customer demand and inventory levels, especially in make-to-order production systems like those in refrigeration manufacturing. This study addresses the challenges faced by a company producing sandwich panels, where inefficiencies in inventory processing led to overstock and outstock issues. By applying the fuzzy inventory control method using Python, the study aimed to optimize inventory levels. The results showed a 6% reduction in inventory, from 191,307 m² to 182,619.4627 m², demonstrating the method's effectiveness. This approach can improve inventory management in similar industrial settings, aligning production with demand and reducing excess inventory.
Highlight:

Efficiency Boost: Fuzzy logic optimizes inventory, minimizing overstock and outstock.
Precise Management: Python aids accurate inventory analysis for informed decisions.
Cost Savings: Aligning inventory with demand reduces excess, enhancing profitability.

Keywoard: Inventory control, Fuzzy logic, Optimization, Production management, Industrial engineering
A Novel Rolling Horizon Based Solution Framework for Scheduling Airplane Maintenance
Authors: Güler Mehmet Güray
Published: May 2024

Maintenance, Repair and Overhaul (MRO) activities on aircraft and systems in aviation is a service sector that relies heavily on skilled workforce. The output of MRO activities is basically bringing the system reliability values, which decrease because of the use of aircraft and systems in certain flight times and landing and take-off numbers, to the default levels determined during the design phase. MRO companies are accountable to the civil aviation authorities who directly authorize them to ensure the required levels of reliability of their products. Airline companies request MRO services at the most convenient time and cost. However, the maintenance of an aircraft is a process that can take up to five weeks, includes plenty of jobs some of which may have stochastic durations, and many over-costed qualified technicians spend thousands of man-hours. In addition, each MRO company is involved in the maintenance of several airplanes arriving at different time intervals. In the study such a problem faced by an MRO company is addressed. The company’s aim is to schedule several incoming airplane maintenance projects. A framework that employs an integer programming (IP) model working on a rolling horizon (RH) setting is used.
Site selection and conceptual designs for beneficial use of dredged material sites for habitat creation in the lower Columbia River
Authors: Littles Chanda , Trachtenbarg David , Moritz Hans , Swanson Douglas , Woolbright Ryan , Herzog Kathryn , Borde Amy
Published: May 2024

Channel maintenance in most major rivers throughout the United States requires ongoing dredging to maintain navigability. The US Army Corps of Engineers explores several options for placement based on sediment characteristics, material quantity, cost, operational constraints, and minimization of potential adverse effects to existing resources and habitat. It is a priority to beneficially reuse dredged sediments to create habitat and retain sediments within the river system whenever possible. Nonetheless, there can be discrepancies among state and federal resource agencies, landowners, tribes, and various other stakeholders about what constitutes a benefit and how those benefits are ultimately weighed against short- and long-term tradeoffs. This work leveraged prior Regional Sediment Management efforts building consensus among stakeholders on a suite of viable strategies for in-water placement in the lower Columbia River. The goal was to identify suitable locations for applying the various strategies to maximize habitat benefits and minimize potential adverse effects. A multistep site-selection matrix was developed with criteria accounting for existing site conditions, overall placement capacity, tradeoffs, long-term maintenance, cost, stakeholder concerns, and landscape principles in the context of other habitat restoration projects implemented in the lower river. Three highly ranked sites were selected for conceptual design and exemplify results of collaborative beneficial use implementation.
Repair of Production Packer Leaks Riglessly Using Thermosetting Resin
Authors: Alo R. G. , Normann S. H. , Alam M. F. , Abdul Rani R. H. , Mappy M. B.
Published: May 2024

Leaks through the production packer, which serves as a primary barrier can compromise well integrity. Traditional methods to restore packer integrity typically entail costly workover operations, necessitating the deployment of a rig to replace the upper completion. This paper presents a cost-effective solution utilizing thermosetting resin, offering an economically viable alternative for remediating packer leaks without the need for heavy workover rigs.

The method employs gravity-feeding of thermosetting resin through the annular fluids to seal leaks located often thousands of meters deep. Resin is pumped into the annulus from the surface and descends by gravity to the packer, its cohesive nature allows it to sink through the annular fluids and settle on the packer. Some of the resin is then squeezed into the leak paths to seal the leak. The key characteristics of the thermosetting resin that facilitates gravity feeding includes its immiscibility in water-based fluids, low viscosity, adjustable density and setting time, and its ability to establish a permanent seal in an oil and gas well environment.

The methodology, successfully sealing packer leaks across multiple wells, utilizes simple equipment setups. By presenting various case histories, this paper explores the design and implementation of the innovative solution in diverse wells with varying configurations and conditions. The resin operations require only simple mixing and pumping equipment that is both lightweight and has very small footprint to mix, pump and place the thermosetting resin plug. It offers significant advantages in terms of time and operational simplicity. The cases presented demonstrate how this rigless repair method to reduce operational time and costs while effectively addressing production packer leaks in the oil and gas industry.

This solution not only showcases practical applications but also aligns with industry demands for economically viable and at the same time environmentally responsible and safer methods, making it a valuable contribution to the existing body of knowledge.
A Case Study on the Importance of Well Surveillance When Evaluating Alternative Barrier Technologies
Authors: Lynch Paul , Green Annabel , Garioch Andrew
Published: May 2024

Recent years have seen accelerated development of alternative barrier technologies to address the limitations of cement well integrity remediation. These technologies have the potential restore well barriers with increased effectiveness and reduced cost. However, industry acceptance of alternative barrier technologies has been slow due to the challenges of demonstrating their effectiveness in field application. Using well surveillance to evaluate the well integrity issue and verify barrier performance is often overlooked leading to poor or inconclusive outcomes.

The presented case study is a trial deployment of a chemical isolation solution supported by FiberLine Intervention (FLI) which was deployed to verify the barrier placement and performance. The unique feature of FLI is that it deploys bare optical fibres into the wellbore without requiring any conventional conveyancing methods, such as slickline or wireline. This makes it portable and compact, but with rapid deployment and real time survey capability it permits operations to be performed very quickly. This was critical to the operation due to time sensitivities around the pumping operation.

When the chemical isolation trial was not successful post pumping, the distributed sensing survey with FLI was able to diagnose that the chemical had not reached the intended target formation. It also identified that this was due to a loss of well integrity in the casing higher up the well. This provided the operator with information on a previously unknown integrity issue, but crucially without this it would have been assumed the treatment simply had not worked which would ultimately delay acceptance of this technology.
Assessment of Quality of Life of Prostate Cancer Patients Receiving Care in University of Nigeria Teaching Hospital Ituku-ozalla, Enugu State
Authors: Dim Obinna Felix , Azubuike Ekwuofu , Onyeoji Sandra Ogechi , Dim Ogechi Cynthia , Adibe Maxwell Ogochukwu
Published: May 2024

Introduction: Ensuring assessment of Health Status in research and clinical care enables improvement in treatment outcomes. This study aimed to evaluate the health status of prostate cancer patients at the University of Nigeria Teaching Hospital.
Methods: This study is a cross-sectional, descriptive survey involving 181 prostate cancer patients. Conducted in the University of Nigeria Teaching Hospital (UNTH), Ituku-Ozalla, Enugu state, over a period of five months (May to October 2023). Descriptive and inferential analyses was done using Statistical Package for Social Sciences, SPSS version 27. Correlation and post hoc tests, were employed to examine the relationships between socio-demographic variables and Health status Data was collected using a 15D Health status instrument. P≤0.05.
Results: Out of the 181 prostate cancer patients interviewed, 45.3% were 60 years and above. More than half were married. Most were employed with university education as their highest level of education. The 15D instrument showed that above half of prostate cancer patients had problem staying asleep (50.8%) and also had marked problems with their bladder (32%). About 34.3% of patients with prostate cancer have severe physical discomfort from pain and ache etc. There general state of health has a considerable effect on sexual activity. The quality of life of prostate cancer patients also increase as the level of education increases. (Graduate; 0.6840 ± 0.16934). Age and level of education are important determinant of quality of life in prostate cancer besides other socio-demographic variables.
Conclusion: Vitality and functional activities were the domains most affected by prostate cancer.
Examining the trend of decreasing precipitation in the Mediterranean area: A case study of Sicily from 1921 to 2023.
Authors: Monforte Pietro , Ragusa Maria Alessandra , Imposa Sebastiano
Published: May 2024

The objective of the authors is examines drought trends in Sicily over the past century. The analysis focuses on the nine provinces that comprise the region, The Standardized Precipitation Index (SPI) is used to identify pluviometric deficit at different time scales, including 3, 6, 12, and 24 months. Additionally, the Mann-Kendall test is applied to check if the SPI has a significant trend, especially if it is decreasing; as the SPI decreases, the pluviometric deficit increases.The statistical approach of the study confirms that in Sicily, meteorological and hydrological droughts are becoming more frequent. In addition, a rising trend of socio-economic droughts has been identified. It is therefore necessary to target mitigation and adaptation measures on the areas most vulnerable to drought in order to safeguard the agricultural sector and, consequently, a significant part of the region's productive activities. The methods used in this work could be applied to the management of water resources and the protection of the island's agricultural and economic sectors.
Myeloid NCOA4 sequesters KEAP1 to reduce ferroptosis for protection against salmonellosis in mice.
Authors: Xue Xiang , Arcos Mariella , Liu Zhaoli , Villareal Luke , Velez Paloma Kai , Desai Sharina , Noureddine Achraf , Martin David , Brinker C , Zhang Donna
Published: May 2024

Salmonellosis, caused by Salmonella enterica serovar Typhimurium, is a significant global
threat. Host immunity limits bacterial replication by inducing hepcidin, which degrades
ferroportin, reducing iron transfer. However, this boosts macrophage iron storage, aiding
intracellular pathogens like Salmonella. Mice lacking ferritin heavy chain (FTH1) in myeloid cells
suffer worsened Salmonella infection. Nuclear receptor co-activator 4 (NCOA4) regulates iron
release via FTH1 degradation during low iron, but its role in salmonellosis is unclear. Here, we
reveal that myeloid NCOA4 deficiency augments spleen iron levels and increases cellular iron
accumulation, oxidative stress, and ferroptosis in bone marrow-derived macrophages. This
deficiency also increases susceptibility to Salmonella-induced colitis in mice. Mechanistically,
NCOA4 suppresses oxidative stress by directly binding to the E3 ubiquitin ligase Kelch-like
ECH-associated protein 1 (KEAP1) and stabilizing the antioxidant transcription factor nuclear
factor-erythroid 2-related factor 2 (NRF2). Activation of NRF2 protects myeloid NCOA4 knockout
mice from Salmonella-induced colitis. Antioxidant Tempol and myeloid cell-targeted curcumin
offer protection against colitis in myeloid NCOA4-deficient mice. A low iron diet and ferroptosis
inhibition also mitigate the heightened colitis in these mice. Overexpression of myeloid cell-
specific NCOA4 confers protection against Salmonella-induced colitis via upregulating NRF2
signaling. Serum iron was reduced in myeloid NCOA4-overexpressing mice, but not in NCOA4-
deficient mice. Targeted serum metabolomics analysis revealed that many lipids were
decreased in myeloid NCOA4-deficient mice, while several of them were increased in myeloid
NCOA4-overexpressing mice. Together, this study not only advances our understanding of
NCOA4/KEAP1/NRF2/ferroptosis axis but also paves the way for novel myeloid cell-targeted
therapies to combat salmonellosis.
Impact of non optimal ambient temperature and temperature variation on the mortality of cardiovascular diseases: A research in Anhui province
Authors: Zhang Tao , Xie Huimin , Zhang Xu , Ni Jianping , Li Guoqing , Wu Hanqing , Zhu Jiansheng , Pan Faming
Published: May 2024

Given the backdrop of global climate change, future temperatures are anticipated to exhibit increased variability and extremity, amplifying health risks and the burden of diseases, a matter of heightened concern. The aim of this research was to evaluate the mortality risk associated with cardiovascular diseases (CVD) due to suboptimal temperatures (daily mean temperature) and temperature variations (diurnal temperature range). Daily data spanning from 2014 to 2020 in Wuhu City were gathered, encompassing meteorological factors, environmental pollutants, and cardiovascular disease mortality information, involving 64,758 CVD deaths. Time-series analyses were conducted utilizing generalized additive models (GAM) and distributed lag nonlinear models (DLNM). Burden analysis was executed to estimate the percentage and count of daily CVD deaths linked to daily mean temperature (DMT) and diurnal temperature range (DTR). Lastly, a sensitivity analysis was conducted to assess the robustness of the model. A horizontal S-shaped relationship exists between DMT and CVD mortality rate, where both high and low temperatures exhibit adverse effects, with high temperatures demonstrating a more pronounced impact than low temperatures. An inverted J-shaped relationship exists between DTR and mortality, wherein extreme DTR elevates the risk of CVD mortality. Variations in exposure responses occur among populations with diverse characteristics. The main cause of death burden is moderately high temperature rather than extreme temperature. Importantly, non-extreme temperatures account for the majority of cardiovascular disease deaths, potentially exerting serious adverse effects on local public health.
Research on the optimal scheduling of a multi- storage combined integrated energy system based on an energy supply grading strategy
Authors: Zhang Na , You Feng , Hu Bingqian , Li Jingyu , Liu Guangchen
Published: May 2024

As an important supporting technology for carbon neutrality strategy, the combination of an integrated energy system and hydrogen storage is expected to become a key research direction. To address the insufficient flexibility of multi-energy coupling in the integrated energy system and the overall strategic demand of low-carbon development, a multi-storage integrated energy system architecture that includes electric storage, heat storage and hydrogen storage is established. Then, according to the system status factors, such as energy cost, response characteristics and energy storage status, a hierarchical energy supply control strategy focusing on the energy supply priority of energy storage units is proposed. NSGA-Ⅱ-MOABC is created as the optimization algorithm to meet the demand of multi-energy coupling energy supply in the integrated energy system. Next, considering the system operational cost and carbon emission cost as the optimization goal, a comprehensive energy optimization scheduling model of multi-storage combined hierarchical energy supply is constructed. Based on the simulation example, the scheduling results of the multi-storage combined system are obtained, through comparative analysis, the addition of hydrogen storage can effectively improve the flexibility of system scheduling. Then, taking several scenarios as simulation examples, the hierarchical energy supply strategy can effectively reduce the system operation cost and carbon emission cost, and it also has a certain role in realizing the local consumption of renewable energy.
Investigating the Relationship between Herding Behaviour and Liquidity in the Johannesburg Stock Exchange
Authors: Ndlovu Godfrey , Stampanoni Michele
Published: May 2024

This paper examines the relationship between herd behaviour and liquidity in the South African equity market using a sample of 302 companies listed on the Johannesburg Stock Exchange, over the time period from 1996 to 2019. The study employs the herding measures proposed by Christie and Huang (1995) and Chang et al. (2000), while the well-known Amihud (2002) measure of illiquidity, combined with the adjustment from Karolyi et al. (2012), is used to measure liquidity. Daily and monthly data samples are used to ensure a comprehensive study of the short and long term effects of the herding relationship. When both measures of herding are used, the results indicate no evidence of herding over the period studied, and furthermore there is no significant evidence of herding when conditioning on high, average and low levels of liquidity. Additionally, we find that trading volume cannot trigger herding behaviour, even in liquid market conditions, and thus the empirical analysis suggests that herding is not present in the South African equity market. We also find that by applying Granger causality tests, there are no causal links between herding behaviour and liquidity.
JEL Codes: G1, G4
Proximity-induced exchange interaction and prolonged valley lifetime in MoSe2/CrSBr van-der-Waals heterostructure with orthogonal spin-orbit fields
Authors: Beer Andreas , Zollner Klaus , de Brito Caique Serati , Junior Paulo E. Faria , Ghiasi Talieh S. , Ingla-Aynes Josep , Mañas-Valero Samuel , Boix-Constant Carla , Watanabe Kenji , Taniguchi Takashi , Fabian Jaroslav , Zant Herre S. J. van der , Gobato Yara Galvão , Schüller Christian
Published: May 2024

Heterostructures, composed of semiconducting transition-metal dichalcogenides (TMDC) and magnetic van-der-Waals materials, offer exciting prospects for the manipulation of the TMDC valley
properties via proximity interaction with the magnetic material. We show that the atomic proximity of monolayer MoSe2 and the antiferromagnetic van-der-Waals crystal CrSBr leads to an unexpected breaking of time-reversal symmetry, with originally perpendicular spin-orbit fields. The observed effect can be traced back to a proximity-induced exchange interaction via first-principles calculations. Moreover, we find a more than two orders of magnitude longer valley lifetime of spin-polarized
charge carriers in the heterostructure, as compared to monolayer MoSe2/SiO2, driven by a Mott transition in the type-III band-aligned heterostructure. This opens new avenues for van-der-Waals engineering of valleytronic devices.
Performance Enhancement through Optimal Power Allocation for Downlink PD-NOMA-UFMC in 5G Networks using Genetic algorithm and MFO
Authors: Sharma Gopal K , Nigam Vineeta Saxena , Arya Rakesh K
Published: May 2024

With the rise of Fifth generation (5G) communication systems, there's a growing demand for efficient multiple access techniques capable of handling high data rates and accommodating a large user base. Power Domain Non-Orthogonal Multiple Access (PD-NOMA) combined with Universal Filtered Multi-Carrier (UFMC) has emerged as a promising solution to address these needs. This combination aims to enhance spectral efficiency, capacity, and user fairness in 5G networks by capitalizing on the strengths of both PD-NOMA and UFMC. Nevertheless, the efficient allocation of power among users poses an optimization challenge within the confines of a specified power budget to achieve optimal performance in PD-NOMA-UFMC systems. This paper presents a power optimization methodology for PD-NOMA-UFMC utilizing intelligent optimization techniques, namely Genetic Algorithm (GA) and Moth Flame Optimization (MFO) algorithm. The proposed approach aims to maximize the overall system throughput by dynamically assigning power levels to users based on their individual channel conditions. Simulation results showcase the effectiveness of the power optimization technique employing GA and MFO in enhancing the performance of PD-NOMA-UFMC systems in terms of throughput, fairness, and power efficiency. Additionally, the paper discusses comparative results of optimization using GA and MFO.
Developing computational thinking with social robots in linguistically heterogeneous classrooms – The case of Misty
Authors: Eckert Andreas , Juvonen Päivi
Published: May 2024

There is a growing body of knowledge on coding and computational thinking for young students in mathematics education and several attempts to lower the threshold for learning programming and programming languages have been reported. This study focuses on the challenges of teaching programming in a linguistically heterogeneous classroom by pursuing the research question How do multilingual students enact affordances of social robots while engaged in exploratory programming tasks? Grade 6 students (10-year old) worked in pairs or groups of three with programming challenges with the social robot Misty and its visual programming environment. The analysis reveals how students stay engaged in exploration for extended periods when language affordances are enacted. The combination of Misty’s physical presence and the visual programming environment creates opportunities for developing computational thinking. However, elements of the design of the tasks and limited language affordances also lead to frustration and/or disappointment amongst the students. There is potential in the use of social robots for teaching programming in linguistically heterogeneous classrooms, but implementation requires well researched design principles for tasks and a programming environment that allows for translanguaging pedagogy.
Metabolic Biomarkers and Endotypes as Predictors of Sepsis Outcomes: A Prospective Population-Based Cohort Analysis from the UK Biobank
Authors: Bai Hao , Yihui Li , Xue Yue , Zhao Shaohua , Meng Tingyu , Lu Ming , Wang Hao
Published: May 2024

Background
Understanding the impact of population metabolic landscapes on susceptibility and outcomes of sepsis is crucial for guiding clinical consultations. This study explores the relationship between plasma metabolites and the incidence and mortality of sepsis among affected populations.
Methods
The analysis utilized data from the UK Biobank community study, which involved Nuclear Magnetic Resonance (NMR) spectroscopy of 118,461 baseline plasma samples generated by Nightingale Health, up to December 31, 2013. Risk factors were identified through multivariate logistic regression analysis. Finally, principal component analysis was used to determine the major influencing factors. The data analysis period was from October 1, 2023, to December 1, 2023. Cox regression analysis was conducted to produce adjusted hazard ratios (HR) for the relationships between individual metabolic biomarkers and 11 principal components of metabolic biomarkers (which together explained 90% of the total variance in individual biomarkers) and their association with the incidence and mortality of sepsis.
Results
A total of 106,533 participants were included in the primary analysis (average age 60.67 years and 96% Caucasian). Total 3,486 cases of sepsis as defined by the study were identified, and among these, 635 instances of sepsis-related mortality occurred. The results showed that lipid and related lipoprotein (HR from 0.89 to 0.95), albumin (HR, 0.87 ,95% (confidence interval) CI, 0.84–0.90) are protective factors for the incident sepsis after adjusted for age, sex, ethnicity, qualifications, socio-economic status, chronic diseases. Metabolites of glycolysis, lipolysis and inflammation are risk factors for the sepsis incident and death. Subgroup analyses conducted on age, gender, and C-reactive protein levels, along with the reanalysis excluding the first two years of follow-up results, demonstrated robust findings. Overall, 13 metabolic biomarker PCs were independently associated with incidence sepsis. addition of PCs to an established risk prediction model, improved incidence sepsis (from 0.737 95% CI: 0.729, 0.744] to 0.792 (95% CI: 0.774, 0.807). Findings from this cohort study suggest that certain metabolic endotype: lower lipid and albumin levels, higher glycolysis, lipolysis, inflammatory plasma metabolites may be associated with an increased risk of sepsis and higher mortality.
Physical activity and social anxiety symptoms among Chinese college students: a chain mediation model of psychological resilience and sleep problems
Authors: Li Xin , Liu Yu , Rong Fan , Wang Rui , Li lanlan , Wei Runyu , Zhang Shichen , Wan Yuhui
Published: May 2024

Background
Social anxiety symptoms are common and harmful psychological illness in college students. Although some studies have illustrated that physical activity could reduce social anxiety symptoms, the specific mechanism is still unclear. Based on theoretical studies on resilience and sleep, this study constructed a chain mediation model to explore whether they mediate between physical activity and social anxiety symptoms among college students.
Methods
This study surveyed 9,530 college students from three colleges in China to explore the mediating effect of physical activity and sleep problems between physical activity and social anxiety symptoms. Participants were investigated with the International Physical Activity Questionnaire, Connor-Davidson Resilience Scale, Sleep-related problems, and the Social Interaction Anxiety Scale and the Social Phobia Scale.
Result
The study found that physical activity was negatively associated with social anxiety symptoms and sleep problems, but positively with psychological resilience. After controlling for sociodemographic variables, physical activity can not only indirectly alleviate social anxiety symptoms through the separate mediation of psychological resilience and sleep problems, but also through the chain mediation of psychological resilience and sleep problems.
Conclusion
These results suggest that improving physical activity levels could reduce social anxiety scores by increasing psychological resilience and sleep quality. This is of great reference significance for the prevention and intervention of college students' mental health.
SPBA-Net: Point Cloud Object Detection with Sparse Attention and Box Aligning
Authors: Sha Haojie , Li Kai , Gao Qingrui , Li Wang , Zhang Xuande , Wang Xiaohui
Published: May 2024

Object detection in point clouds is essential for various applications, including autonomous navigation, household robots,and augmented/virtual reality. However, during voxelization and Bird’s Eye View transformation, local point cloud data often remains sparse due to non-target areas and noise points, posing a significant challenge for feature extraction. In this paper,we propose a novel mechanism named Sparse Attention to enhance the semantic information of point clouds by calculating Euclidean distances between selected keypoints and others. Additionally, we introduce Instance-wise Box Aligning, a method for expanding predicted boxes and clustering the points within them to achieve precise alignment between predicted bounding boxes and ground-truth targets. Experimental results demonstrate the superiority of our proposed SPBA-Net in 3D object detection on point clouds compared to other state-of-the-art methods.
Establishing neuroanatomical correspondences across mouse and marmoset brain structures
Authors: Mitra Partha , Mezias Chris , Huo Bingxing , Bota Mihail , Jayakumar Jaikishan
Published: May 2024

Interest in the common marmoset is growing due to evolutionarily proximity to humans compared to laboratory mice, necessitating a comparison of mouse and marmoset brain architectures, including connectivity and cell type distributions. Creating an actionable comparative platform is challenging since these brains have distinct spatial organizations and expert neuroanatomists disagree. We propose a general theoretical framework to relate named atlas compartments across taxa and use it to establish a detailed correspondence between marmoset and mice brains. Contrary to conventional wisdom that brain structures may be easier to relate at higher levels of the atlas hierarchy, we find that finer parcellations at the leaf levels offer greater reconcilability despite naming discrepancies. Utilizing existing atlases and associated literature, we created a list of leaf-level structures for both species and establish five types of correspondence between them. One-to-one relations were found between 43% of the structures in mouse and 47% in marmoset, whereas 25% of mouse and 10% of marmoset structures were not relatable. The remaining structures show a set of more complex mappings which we quantify. Implementing this correspondence with volumetric atlases of the two species, we make available a computational tool for querying and visualizing relationships between the corresponding brains. Our findings provide a foundation for computational comparative analyses of mesoscale connectivity and cell type distributions in the laboratory mouse and the common marmoset.
Lyapunov stability of suspension bridges in turbulent flow
Authors: Barni Niccolò , Bartoli Gianni , Mannini Claudio
Published: May 2024

In the era of sleek, super slender suspension bridges, facing the issue of stability against dynamic wind actions represents an increasingly complex challenge. Despite the significant progress over the last decades, the impact of atmospheric turbulence on bridge stability remains partially not understood, evoking the need for innovative research approaches. This study aims to address a gap in current research by investigating the random flutter stability associated with variations in the angle of attack due to turbulence, which has not formally been addressed yet. The present investigation employs the 2D rational function approximation (2D RFA) model to express self-excited forces in a turbulent flow. The application of this type of models to bridge dynamics yields a viscoelastic coupled dynamic system characterized by memory effects and driven by broad-band long-time-scale noise, described here by a linear homogeneous time-variant differential equation, which shows apparent nonlinear features, and which has rarely been matter of research. Utilizing a Monte Carlo methodology, this work innovates in applying the largest Lyapunov exponent (LE) and the moment Lyapunov exponents (MLE) to study bridge random flutter stability. The calculation of LE and MLE under diverse turbulent wind conditions uncovers lower flutter stability than without turbulence effects. In most cases, sample and low-order p-th moment stability thresholds closely align with the bridge dynamic response pattern; therefore, the flutter critical wind speed is unequivocal. However, under certain turbulence scenarios, it is necessary to resort to MLE for a complete description of stability, evoking some additional consideration of which statistical moments should be considered for the engineering assessment of the flutter limit. Finally, this work provides a qualitative insight into the instability mechanisms by approximating the random parametric excitation with a sinusoidal gust and evaluating the time-periodic system stability via Floquet theory.
Can lithium salts alter the size and morphology of the Madagascar hissing cockroach’s neuroendocrine system?
Authors: Wojciak Rafal W . , Marciniak Paweł , Slocinska Malgorzata
Published: May 2024

Lithium salts have been used in psychiatry for decades as normothymics. The full mechanism of action of these drugs is not yet known. The limited work on lithium suggests that it may affect brain structure and size in humans and animals. This study aimed to determine the effect of lithium citrate and carbonate on the neuroendocrine system of Madagascar cockroaches. The animals were fed with the control and test diets (enriched with lithium citrate and carbonate at 0.1 and 0.01%, respectively). After anaesthesia, the insects were decapitated, and the brain and retrocerebral complex were removed. The study showed significant changes in the morphology of the examined elements of the neuroendocrine system of insects consuming lithium in the diet, mainly consisting of the enlargement of the examined structures, with increased doses of lithium and the preparation administered in the form of citrate having a greater effect. The morphotic changes in the endocrine system of the Madagascar cockroach exposed to lithium shown in this study may suggest that a similar phenomenon occurs in humans and animals exposed to lithium from the environment, food, or drugs. Further research on this topic may shed more light on the phenomenon.
Sophisticated Planar Chromatographic Method Estimation and Validation for Newer Combination of Lidocaine HCl and Diltiazem HCl For Anal Fissure
Authors: Shah Maitri , Kachhiya Hetaben , Tandel Jinal , Chhalotiya Usmangani , Shah Dimal , Patelia Adarsh , Patel Mehul
Published: May 2024

Newer drugs and drugs combinations for treatment of different diseases are approved by regulatory authorities. Such new combination of existing drugs like Lidocaine HCl and Diltiazem HCl has been approved for anal fissure treatment. The present study represents validated method for estimation of Lidocaine HCl and Diltiazem HCl in a combined gel dosage form applying High- performance thin layer chromatography. The stationary phase used in this method was pre-coated silica gel G60 F254 aluminium sheet (10 × 10 cm, 0.2 mm layer thickness), and the mobile phase was a mixture of toluene, methanol, ethyl acetate and two drops of ammonia (7: 2: 1% v/v/v). Resolved peaks of both drugs were obtained at the Rf value 0.59 for Lidocaine HCl and 0.48 for Diltiazem HCl. Analytical wavelength of 220 nm was selected based on overlay UV spectra of both the drugs. The correlation coefficient (r2) for Lidocaine HCl and Diltiazem HCl was found to be 0.9987 and 0.9980, respectively indicating a linear approach in the concentration range of 400–1200 ng/band for both. The method was found reproducible, accurate, precise, and robust for simultaneous estimation of Lidocaine HCl and Diltiazem HCl in bulk and pharmaceutical dosage form.
A science-based approach to classifying light vehicles in Europe: methodology and case studies
Authors: Laveneziana Lorenzo , Marin Andres L. , O’Brien Dermot , Prussi Matteo , Fontaras Georgios
Published: May 2024

Proper categorisation of light vehicles is crucial for analysing and comprehending the developments taking place in the road transport sector, that impact the environment, road safety, transport operation, and urban planning. However, current vehicle classification methods in Europe are based on empirical or legacy approaches, sometimes founded on obsolete criteria, and do not fully reflect recent changes in the vehicle fleet and market. This paper aims to establish a scientific approach for the classification of light vehicles by introducing a Bayesian statistical method to define vehicle segments in an explicit and reproducible way. Contrarily to previous studies that mostly depend on machine learning techniques, which, despite their high accuracy typically lack explainability, the proposed approach prioritises the transparency of classification decisions. Through an in-depth examination of vehicle physical attributes, key variables were identified and utilised to determine clear boundaries between segments. These boundaries were articulated through simple linear relationships of the chosen variables, thus providing well-defined criteria open for interpretation and verification. The algorithm could assign up to 82\% of the vehicles to the original segments. The accuracy demonstrated is comparable to that of several unsupervised machine learning models and transparently reveals the boundaries among different segments. The findings can be used by researchers and modellers to update existing vehicle fleet models, particularly those treating environmental and energy consumption impacts, or used as a possible standard for multi-purpose vehicle classification.