bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on the mechanism of salt relief and growth promotion of Enterobacter cloacae on cotton
Authors: Yue Haitao , Sun Shuwen , Ma Xiaoyun , Shen Shiwei , Luo Yiqian , Ma Xiaoli , Wu Ting , Li Shuang , Yang Zhengyang , Gong Yuxi
Published: August 2023

Aims
In-depth studies on plant ion uptake and plant growth-promoting rhizobacteria(PGPR) at the molecular level will help to further reveal the effects of PGPR on plants and their interaction mechanisms under salt stress.
Methods
Cotton was inoculated with a PGPR-Enterobacter cloacae Rs-35, and the ion uptake capacity, membrane transporter protein activity, and expression of key genes were determined under salt stress. Changes in the endogenous hormone content of cotton were also determined. Further, the genome-wide metabolic pathway annotation of E. cloacae Rs-35 and its differential enrichment pathway analysis of multi-omics under salinity environments were performed.
Results
In a pot experiment of saline-alkali soil, E. cloacae Rs-35-treated cotton significantly increased its uptake of K+ and Ca2+ and decreased uptake of Na+, elevated the activity of the H+-ATPase, and increased the sensitivity of the Na+/H+ reverse transporter protein on the vesicle membrane. Meanwhile, inoculation with E. cloacae Rs-35 could promote cotton maintain the indoleacetic acid(IAA) content under salt stress. Genome-wide annotation showed that E. cloacae Rs-35 was respectively annotated to 31, 38, and 130 related genes in osmotic stress, phytohormone and organic acid metabolism, and ion uptake metabolic pathway. Multi-omics differences analysis showed that E. cloacae Rs-35 were enriched to tryptophan metabolism, multiple amino acid biosynthesis, carbon and glucose synthesis, and oxidative phosphorylation metabolic pathways at the transcriptome, proteome, and metabolome.
Conclusion
E. cloacae Rs-35 can promote cotton balance cell ion concentration, stabilize intracellular IAA changes, stimulate induction of systemic tolerance, and promotes the growth of cotton plants under salt stress.
Study on Drip Flow Reaction About Biofilmby Pseudomonas Aeruginosa and Its Application to Evaluate Inhibitory Antibiofilm of Antibiotic
Authors: Hai Duong Vo -Thi- , Thuan Kieu Nguyen Phuc , Yen Nhi Dinh Thi , Viet Ha Cao Thi , Minh Thai Nguyen
Published: August 2023

Background: Pseudomonas aeruginosa (Pa) causes nosocomial infections, it has the ability to form biofilms in medical devices leading treatment to complicated. The purpose of this study is to build a biofilm model on Drip Flow Reaction (DFR) system and apply it to investigate the effects of antibiotics on biofilm formation.
Materials and method: The ability of Pa ATCC 9027, ATCC 27853 and PA 01 to form biofilms was investigated on DFR. This model is applied to evaluate the biofilm resistance of antibiotics through Flow cytometry (FCM).
Results: Successfully built biofilm model of Pa in DFR and obtained images on carrier and results from Flow Cytometry (FCM) machine analysis. The results revealed strains related to biofilm formation, time of antibiotic use is related to biofilm formation, the combination of colistin and rifampicin increased simultaneously both the inhibitory effect on biofilm formation and biofilm destruction (One-Way ANOVA test, p<0.01).
Conclusion: The study successfully investigated the biofilm-forming model and applied the Pa biofilm resistance in DRF with colistin and rifampicin.
Smart Chatbot System for Banking using Natural Language Processing Tools
Authors: Amama Clement , Okengwu Ugochi
Published: August 2023

This research work focuses on creating a Smart Chatbot System for banking that leverages Natural Language Processing Toolkit and Machine Learning. The study involves gathering and preprocessing a dataset of user queries and responses. Key words are defined for pattern matching, and a decision tree algorithm is used to train the model. The Chatbot's performance is evaluated, and the results demonstrate the successful development of a functional Chatbot with a high F1 score of 0.97, indicating 97% accuracy in understanding user queries and providing relevant responses. User testing and a comparison with an existing system reveal significant improvements achieved through the incorporation of NLP and machine learning algorithms. The Chatbot is designed with an intuitive and user-friendly interface accessible through a web application, and administrators have a separate back-end access to effectively manage the knowledge base. The research also identifies areas for future improvement, such as enhancing accuracy, incorporating system memory and anaphora resolution, and integrating a logging system. Addressing these limitations will contribute to the advancement and effectiveness of conversation agents in the banking sector.
Entrepreneurial intention of public hospital dentists and its importance factors: a study based on machine learning and binary logistic regression
Authors: Peng Bin , Li Jianzhong , Liu Dakang
Published: August 2023

As China's economic level continues to grow, people's standard of living is improving along with their awareness of oral health. The increased demand for high-quality dental services provides good opportunities for dentists to start their own businesses. Despite the rapid growth of private dental practices in China, more research is still needed to gain insight into the distinctive characteristics and influencing factors of dentists' entrepreneurial behavior. In this study, the entrepreneurial intention of dentists (the person's intention to leave the public hospital system and enter the private institution) was analyzed by collecting relevant questionnaires from public hospitals in five major cities of Guangdong Province, and the relationship between the entrepreneurial intention of dentists and their personal characteristics was analyzed using XGBoost method and binary logistic regression method. A total of 505 dentists' survey data were included in this study, and the top 5 influencing factors of importance were obtained based on the research analysis. Experiments showed that the importance-related features obtained in this study can play a high predictive role and have favorable stability, with an accuracy of more than 82% in XGBoost, decision tree and random forest classification algorithms. The prediction model of dentists' entrepreneurial intention based on machine learning algorithm is of high practical significance and can be incorporated into the screening and decision-making of dentists' entrepreneurial intention status. Based on this method, the entrepreneurial intention of relevant individuals can be accurately grasped, so that appropriate measures can be taken to promote the development and management of the industry.
Patients of a “street medicine” clinics in Brazil, “World’s Doctors”
Authors: Belkovsky Mikhael , Toledo Loic Monginet , Barroso Mariana Nobre , Raizer Milena Veiga , Luz Claudia Candido da , Garbini Stephanie de Oliveira , Silva Samir Adalberto Siqueira
Published: August 2023

“Street medicine” offers a complementary approach for marginalized population’s challenges, usually out of reach by the tradition health system. Our purpose is to describe the sociodemographic profile and the health-related challenges of patients served by a “street medicine” NGO. We analyzed retrospectively the patient cohort (2,226 patients) attending the “World’s Doctors” street-based mobile health clinics established in São Paulo from 1/2019 to 9/2022. Our results were compared with data publicly available of general Brazilian population. We observed more males (66.4%), black (22%), brown (38.8%) and indigenous (3.2%), with a higher mean age (45.7 years) compared to the general population (32.6 years), with low access to drinkable water. Higher prevalence of tuberculosis (2.2%) and STDs (4.5%) were observed, as well as alcohol and drug use disorders. The most common complaints to seek our service were: pain (36%), cough (7.78%), cutaneous lesions (6.11%), weakness (4.81%), and dizziness (4.03%). Patients served by our NGO present health conditions that go beyond main complains. Street based medicine complements traditional healthcare and would benefit from a multidisciplinary approach that involves dealing with social determinants of health and active surveillance and treatment of tuberculosis, STD, and alcohol and drug use disorders.
A New Human-Based Metaheuristic Algorithm for Solving Optimization Problems based on Preschool Education
Authors: Trojovský Pavel
Published: August 2023

This paper presents the Preschool Education Optimization Algorithm (PEOA), a novel metaheuristic algorithm designed to tackle optimization problems. Inspired by the concept of preschool education, PEOA is divided into three distinct phases (i) the gradual growth of the preschool teacher's educational influence, (ii) individual knowledge development guided by the teacher, and (iii) individual increase of knowledge and self-awareness. The algorithm's effectiveness in optimization is evaluated using twenty-three standard benchmark functions encompassing unimodal, high-dimensional multimodal, and fixed-dimensional multimodal types. The results demonstrate that PEOA excels in exploration, exploitation, and maintaining a balance between them throughout the optimization process. To provide a comprehensive analysis, the performance of PEOA is compared against ten well-known metaheuristic algorithms. The simulation results reveal that PEOA consistently outperforms the compared algorithms, yielding superior outcomes for the majority of benchmark functions. Furthermore, the implementation of PEOA in solving four engineering design problems illustrates its efficacy in real-world optimization applications.
An approximation of the local time of a Levy process.
Authors: DIOP Assane
Published: August 2023

The aim of this paper is to approximate the local time of a Levy processes X, from
observation times: Δn, · · · , [t/Δn]Δn.
Potential Impact of Insect Pollinators on the yield and quality of different cultivars of Cucumber (Cucumis sativus L.)
Authors: Mamoon-ur-Rashid Muhammad , Ali Habib
Published: August 2023

Cucumber (Cucumis sativus L.), a cross-pollinated crop of significant agricultural importance, we investigated the factors influencing cucumber fruit size, emphasizing the role of proper pollination. Four distinct cultivars, namely Quice, Dynasty, Mailini, and Full Moon cucumber, were employed in a comprehensive experimental setup. The study followed a split-plot design, comparing caged and un-caged conditions. Our results, based on data collected on fruit weight, length, the number of fruits per plant, and overall cucumber yield, unveiled critical insights into the pivotal role of insect pollinators in cucumber cultivation. Notably, six different species of insect pollinators, representing two orders within Hymenoptera and Lepidoptera, were identified as frequent visitors to cucumber blooms. The findings conclusively demonstrated that cucumber plants grown under un-caged conditions, with unrestricted access to insect pollinators, exhibited substantial improvements in various key parameters. This encompassed a significant increase in fruit weight, fruit length, the number of fruits per plant, and ultimately, the overall yield of the cucumber crop. Additionally, we observed that among the insect pollinators, honey bees displayed the highest mean foraging and population activities during the evening hours, emphasizing their particular importance in the pollination process. In light of these findings, we draw the important conclusion that cucumber is a crop highly dependent on pollinators, with insect pollinators playing an indispensable role in influencing both the quantity and quality of the cucumber yield. As a practical recommendation, we suggest that the strategic placement of honeybee colonies in close proximity to cucumber fields, specifically initiated 2 to 3 days after the commencement of flowering, can significantly enhance cucumber yields, thereby benefiting both growers and the agricultural industry as a whole. This study underscores the critical importance of pollinators in modern agriculture and highlights the potential for improved crop management strategies to maximize yield and quality.
Mammogram Uptake from Social Determinants of Health Can Be Lost in Translation to Individual Patients
Authors: Davis Matthew , Simpson Kit , Diaz Vanessa , Alekseyenko Alexander V.
Published: August 2023

Purpose
The objective of this study is to describe patterns in barriers to breast cancer screening uptake with the end goal of improving screening adherence and decreasing the burden of mortality due to breast cancer. This study looks at social determinants of health and their association to screening and mortality. It also investigates the extent that models trained on county data are generalizable to individuals.
Methods
County level screening uptake and age adjusted mortality due to breast cancer are combined with the Centers for Disease Controls Social Vulnerability Index (SVI) to train a model predicting screening uptake rates. Patterns learned are then applied to de-identified electronic medical records from individual patients to make predictions on mammogram screening follow through.
Results
Accurate predictions can be made about a county’s breast cancer screening uptake with the SVI. However, the association between increased screening, and decreased age adjusted mortality, doesn’t hold in areas with a high proportion of minority residents. It is also shown that patterns learned from county SVI data have little discriminative power at the patient level.
Conclusion
This study demonstrates that social determinants in the SVI can explain much of the variance in county breast cancer screening rates. However, these same patterns fail to discriminate which patients will have timely follow through of a mammogram screening test. This study also concludes that the core association between increased screening and decreased age adjusted mortality does not hold in high proportion minority areas.
The Brexit Impact on Inward FDI in the UK
Authors: Ellalee Haider , Alali Walid Y
Published: August 2023

This paper examines the potential Brexit impact on inward FDI (foreign direct investment) through its potential impact on the variables of the benchmark characterising the macroeconomy. Therefore, we propose to use automatic structural vector regression of Markov system change to distinguish between fluctuating and steady-state states of economics and compute, among others, the contemporary effects that FDI frequency innately generates. Our finds propose that Brexit leads to a depreciation of the pound sterling in the present economic ambience, which will lead to a long-term negative impact on foreign direct investment. The FDI inflows might be affected positively (at most) by the post-Brexit depreciation of the pound sterling only if this circumstance drove the UK economy into a period of inflation, highly volatile growth, interest rates and exchange rates: a rather unlikely scenario. Until then, the benefits of a lower pound sterling will only last for a short time.
End-Effector Impedance Control of Robotic Arm Based on Enhanced Neural Network RBF-PID-PSO
Authors: Wu Gengyao , Zhang Pengfei , Zhang Jie , Ma Ang , Xu Weitao
Published: August 2023

In the current calibration system for power transformers, In the current calibration systems for electrical power transformers, errors in the insertion and extraction of wiring terminals occur due to the reliance solely on camera-based positioning of the terminal's location by the robotic arm. This approach falls short in achieving precise assembly of various transformer terminals. Therefore, it is imperative to introduce active compliant control between the robotic arm's end-effector and the wiring terminal to enable smooth terminal assembly. This paper proposes a mechanical arm end-effector impedance control algorithm based on RBF-PID-PSO for terminal assembly. The algorithm employs a particle swarm optimization technique to adjust the weight matrix and center parameters within the Radial Basis Function (RBF) neural network. Simultaneously, a PID algorithm is introduced to optimize impedance control for end-effector forces. The impedance parameters obtained from the RBF neural network and the PID parameters are incorporated into the robotic arm model. This allows for the conversion of end-effector forces into position errors for impedance control, followed by the transformation of these errors into six joint angles through the robot's inverse kinematics. This ultimately achieves impedance control of end-effector forces. Comparative experiments and simulations conducted in Matlab demonstrate that this controller effectively reduces errors in force and torque control. Furthermore, it exhibits superior resistance to disturbances in force feedback signals, significantly improving compliant control performance.
Deciphering the molecular Classification of pediatric sepsis: Integrating WGCNA and Machine learning-based classification with immune signatures for the development of an advanced diagnostic model
Authors: Huang Junming , Chen Jinji , Wang Chengbang , Chen Shaohua , Mi Hua , Lai Lichuan
Published: August 2023

Background
Pediatric sepsis (PS) is a life-threatening infection associated with high mortality rates, necessitating a deeper understanding of its underlying pathological mechanisms. Recently discovered programmed cell death induced by copper has been implicated in various medical conditions, but its potential involvement in PS remains largely unexplored.
Methods
We first analyzed the expression patterns of cuproptosis-related genes (CRGs) and assessed the immune landscape of PS using the GSE66099 dataset. Subsequently, PS samples were isolated from the same dataset, and consensus clustering was performed based on differentially expressed CRGs. We applied weighted gene co-expression network analysis to identify hub genes associated with PS and cuproptosis. A diagnostic model for PS was then developed, comparing four different machine learning approaches, and its discriminatory performance was validated using quantitative real-time polymerase chain reaction (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA).
Results
We observed aberrant expression of 27 CRGs and a specific immune landscape in PS samples. Our findings revealed that patients in the GSE66099 dataset could be categorized into two cuproptosis clusters, each characterized by unique immune landscapes and varying functional classifications or enriched pathways. Among the machine learning approaches, Extreme Gradient Boosting demonstrated optimal performance as a diagnostic model for PS. Further analysis was conducted on the five most critical variables for subsequent investigation, involving qRT-PCR and ELISA of peripheral blood samples from both PS patients and HC.
Conclusion
Our study provides valuable insights into the molecular mechanisms underlying PS, highlighting the involvement of cuproptosis-related genes and immune cell infiltration.
Real-time traffic sign detection network based on Swin Transformer
Authors: Zhu Wei , Ying Yue , zheng Yayu , Chen Yikai , Huang Shucheng
Published: August 2023

In the field of autonomous driving, the detection of traffic signs remains a significant challenge, especially when it comes to the real-time detection of medium and small targets. The difficulty of detecting small objects decreases accuracy. To address these challenges, we propose a real-time traffic sign detection algorithm based on the Swin Transformer (RTSDST) that improves computation performance and accuracy for multi-scale target detection on SoCs installed onboard autonomous driving vehicles. Our approach includes a head specifically designed for detecting tiny objects, followed by the adoption of Swin Transformer blocks to effectively capture the spatial and channel dependencies of the feature maps, which improves the accuracy of detecting targets of varying sizes. To efficiently identify regions of interest in large coverage images, we employ a Residual Convolutional Attention Module to generate sequential feature maps between the channel and spatial dimensions and weigh them against the original map. A realistic traffic sign detection dataset, Tsinghua-Tencent 100K (TT100K), which includes medium and small traffic sign targets, was adopted in this article to evaluate the effectiveness of our proposed RTSDST. The evaluation results show that RTSDST has excellent performance on multi-scale scenes. Additionally, we also evaluated our network on the VisDrone dataset for small target detection. Our method has state-of-art performance on small targets.
Association of serum osteocalcin with bone microarchitecture and muscle mass in Beijing community-dwelling postmenopausal women.
Authors: Liu Shuying , Pang Qianqian , Guan Wenmin , Yu Fan , Wang Ou , Li Mei , Xing Xiaoping , Yu Wei , Jiang Yan , Xia Weibo
Published: August 2023

Background
Osteoporosis is a systemic skeletal disease with increasing bone fragility and prone to fracture. Osteocalcin (OC), as the most abundant non collagen in bone matrix, has been extensively used in clinic as a biochemical marker of osteogenesis. Two forms of OC were stated on circulation, including carboxylated osteocalcin (cOC) and undercarboxylated osteocalcin (ucOC). OC was not only involved in bone mineralization, but also in the regulation of muscle function.
Objective
This study explored the relationship between serum OC, cOC, ucOC levels and bone mineral density (BMD), bone microarchitecture, muscle mass and physical activity in Chinese postmenopausal women.
Method
216 community-dwelling postmenopausal women were randomized enrolled. All subjects completed biochemical measurements, including serum β-isomer of C-terminal telopeptides of type I collagen (β-CTX), N-terminal propeptide of type 1 procollagen (P1NP), alkaline phosphatase (ALP), OC, cOC and ucOC. They completed X-ray absorptiometry (DXA) scan to measure BMD, appendicular lean mass (ALM) and trabecular bone score (TBS). They completed high resolution peripheral quantitative CT (HR-pQCT) to assess peripheral bone microarchitectures.
Results
Serum OC, cOC and ucOC were elevated in osteoporosis postmenopausal women. In bone geometry, serum ucOC was positively related with total bone area (Tt.Ar) and trabecular area(Tb.Ar). In bone volumetric density, serum OC and ucOC were negatively associated with total volume bone mineral density (Tt.vBMD) and trabecular volume bone mineral density (Tb.vBMD). In bone microarchitecture, serum OC and ucOC were negatively correlative with Tb.N and Tb.BV/TV, and were positively correlated with Tb.Sp. Serum OC and ucOC were positively associated with Tb.1/N.SD. Serum OC was negatively related with Tb.Th. Serum ucOC was positively associated with ALM. The high level of serum OC was the risk factor of osteoporosis. ALM was the protective factor for osteoporosis.
Conclusion
All forms of serum OC were negatively associated with BMD. Serum OC and ucOC mainly influenced microstructure of trabecular bone in peripheral skeletons. Serum ucOC participated in modulating both bone microstructure and muscle mass.
Quality of life and affecting factors in myelofibrosis patients
Authors: Cho Yoo-Rin , Yoo Yang-Sook , Lee Sung-Eun
Published: August 2023

Purpose
This descriptive survey study aimed to identify factors that affect the health-related quality of life (HRQOL) of patients with myelofibrosis (MF), including primary MF, post-polycythemia vera MF, or post-essential thrombocythemia MF .
Methods
The study enrolled 189 myelofibrosis patients who were treated at the outpatient department of Seoul St. Mary's Hospital, the Catholic University of Korea, and data were collected using a structured questionnaire such as European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-Core (QLQ-C) 30 version 3.0. To explore the factors for affecting HRQOL, demographic, socioeconomic variables as well as disease-related variables were also collected.
Results
The quality of life of myelofibrosis patients averaged 41.53 out of 100; physical functioning was the lowest at 74.70, followed by social functioning at 75.22, and role functioning at 76.94. In terms of symptomatic quality of life, fatigue had the lowest score of 35.21, followed by insomnia and dyspnea at 26.45, and financial difficulties at 22.39. As for factors affecting quality of life, the higher the risk stratification (DIPSS Intermediate-2 and High), the lower the functional and symptomatic quality of life.
Conclusion
In this study, we demonstrate that HRQOL was strongly associated with myeloproliferative neoplasm symptoms and the independent factors affecting HRQOL in myelofibrosis patients. These findings can provide the help to develop interventions that can improve HRQOL of myelofibrosis patients.
Flexible capacitive humidity sensor based on potassium ion-doped PVA/CAB double-layer sensing film
Authors: Zhang Yonghua Zhang , Yao Songping , Zhang Jian , Kang Ling , Karthikeyan Sreejith , Wang Changlun
Published: August 2023

Humidity measurement plays an essential role in industrial and agricultural production, meteorological monitoring, medical services, and people’s comfortable life. Polymer materials-based humidity sensors have gained much research focus due to the good dielectric properties and the compatibility with a variety of coating and pattern processes of polymer materials. In this paper, for the first time, a flexible capacitive humidity sensor is presented based on doped polyvinyl alcohol (PVA)/ cellulose acetate butyrate (CAB) double-layer sensing film and polyimide (PI) substrate. Potassium ions (K+) are introduced into PVA for high effective capacitance, and CAB is used as protective film for preventing the hydrolysis of the doped PVA layer in high humidity environment. The fabricated novel sensor with a size of 20×20mm2 has a capacitance of 61.84pF at 10 percentage relative humidity (% RH) and 188.42pF at 90% RH. The average sensitivity is 1.414 pF/% RH. The maximum humidity hysteresis is about 5.83% RH at 50% RH. The response and recovery times from 25% RH to 75% RH were likewise measured to be 78.71s and 6.19s, respectively. In addition, the long-time measurements for 7 days and bending tests for 5000 cycles demonstrated a good long-time humidity detecting stability and high mechanical flexibility for the capacitive humidity sensor based on potassium ion-doped PVA/CAB double-layer sensing film.
Bactericidal and fungicidal activities of silver nanoparticles from tomato peel waste and its application in disinfecting metallic surfaces
Authors: Ali Esraa , Abd-Elhalim Basma T. , Hesham Esraa , Ahmed Shimaa , Mostafa Habiba , Gamal Ahmed , El-Sayed Salwa M. , Bakry Ashraf , Ebeed Naglaa , Elhariry Hesham , Galal Ahmed , Abu-Hussien Samah H.
Published: August 2023

According to their special physio-chemical properties, Nanoparticles have gained worldwide attention as a new bio-alternative for chemical control agents. This investigation aims to the eco-friendly synthesis of nanosilver particles from tomato peel extract(TPE-AgNPs) and evaluates their characteristics and inhibitory activities against pathogenic bacteria and fungi as well as their role in metallic surface disinfecting. To initiate biosynthesis, tomato peel extract was mixed with silver nitrate(AgNO3) solution until the color changes to reddish brown. Ultraviolet(UV-Visible) spectroscopy, Fourier-transform infrared(FTIR) spectroscopy, X-ray diffraction(XRD) analysis, and high resolution transmission electron microscopy(HR-TEM) techniques were used to characterize biosynthesized TPE-AgNPs. Results recorded that obtained TPE-AgNPs had a strong score(238nm) of Plasmon resonance(SPR) by SPR of 4.5. Functional groups of carboxyl, hydroxyl, phenolic, and amide groups existed and were detected by the FTIR spectrum. The synthesized TPE-AgNPs had an amorphous nature which was confirmed by XRD analysis. TEM analysis showed semi-spherical TPE-AgNPs sized from 4.44-27.59nm. The biosynthesized TPE-AgNPs had a negative zeta potential of -68.44 mV. The inhibitory activities of synthesized TPE-AgNPs were evaluated against eleven microbial pathogenic using well diffusion method, inhibition zone diameter(IZD) was measured in centimeters. Results showed that B. subtilis and E.coli was the most sensitive pathogens with IZD of 4.0 and 0.92cm, respectively However, L. monocytogenes and S. sonnei were the most resistant pathogens with IZD of 0.92 and 0.90 cm, respectively. Synthesized TPE-AgNPs from tomato peels had good inhibitory potentials against pathogenic fungi with IZD of 3.0 and 0.92cm against A. solani and C. albicans, respectively. Applying the use of TPE-AgNPs as bio disinfectant significantly decreased the microbial load of metallic blades and proves its efficiency as a disinfectant agent after 120min. of contacting. So, more applications on disinfecting metallic surfaces such as dentistry are indeed needed.
The Portrayal of Indigenous Knowledge Assets in Ethiopian Curricular and Pedagogic Practices : The Case of Oromo Indigenous Knowledge (Ethiopia)
Authors: Kufi Endalew
Published: August 2023

This research dealt with assessing the portrayal of Oromo Belief system in both liberal and secular educational provisions from the past to the present in order to mark the place of ritual and cultural endowments attached to Oromo Governance and Belief Systems.. Contextual discourse analysis was used in order to intensify the gap between religio-cultural and pedagogic/andragogic practices. The documents were selected through criterion sampling technique. Units of analysis were research articles and textbooks units. In the study, the findings indicated that, the Oromo religious and cultural endowments were regarded as ungodly and archaic where Orthodox Christian and Islam Religions were considered more advanced. In the feudal regime, the Orthodox Christian Religion dominated almost all views as a state-religion. In the socialist-era, the Marxist-Leninist Ideology overshadowed all religious thoughts excepting Orthodox Christian Religion and Islam to some extent. In the current federal system, all religions are said to be developing taken the system of education as secular and non-existence of any state-religion. Yet, the educational values of religion, especially indigenous religious views such as of Waaqeffannaa of Oromo and notable socio-cultural institutions are, still, denigrated since they are more ceremonial than practical. To that end, the upcoming generation is more likely to be kept far away from the indigenous religion and cultural endowments.
Prior water availability modifies the effect of heavy rainfall on dengue transmission: a time series analysis of passive surveillance data from southern China
Authors: Cheng Qu , Jing Qinlong , Collender Philip A. , Head Jennifer R. , Li Qi , Yu Hailan , Li Zhichao , Ju Yang , Chen Tianmu , Wang Peng , Cleary Eimear , Lai Shengjie
Published: August 2023

Background
Given the rapid geographic spread of dengue and the growing frequency and intensity of heavy rainfall events, it is imperative to understand the relationship between these phenomena in order to propose effective interventions. However, studies exploring the association between heavy rainfall and dengue infection risk have reached conflicting conclusions.
Methods
In this study, we use a distributed lag non-linear model to examine the association between dengue infection risk and heavy rainfall in Guangzhou, a dengue transmission hotspot in southern China, stratified by prior water availability.
Results
Our findings suggest that the effects of heavy rainfall are likely to be modified by prior water availability. A 24–55 day lagged impact of heavy rainfall was associated with an increase in dengue risk when prior water availability was low, with the greatest incidence rate ratio (IRR) of 1.37 (95% credible interval (CI): 1.02–1.83) occurring at a lag of 27 days. In contrast, a heavy rainfall lag of 7-121 days decreased dengue risk when prior water availability was high, with the lowest IRR of 0.59 (95% CI: 0.43–0.79), occurring at a lag of 45 days.
Conclusions
These findings may help to reconcile the inconsistent conclusions reached by previous studies and improve our understanding of the complex relationship between heavy rainfall and dengue infection risk.
A Hybrid Meta-Heuristic Algorithm for Application Module Placement in IoT-Fog-Cloud Computing Environment
Authors: Yakubu Ismail Zahradden , Murali M.
Published: August 2023

In recent years, fog computing has gained significant popularity for its reduced latency (delay), low power consumption, mobility, security and privacy, network bandwidth, and real-time responses. It provides cloud-like services to Internet of Things (IoT) applications at the edge of the network with minimal delay and real-time responses. Fog computing resources are finite, computationally constrained, and powered by battery cells, which require optimal power management. To facilitate the execution of IoT services on fog computing resources, applications are broken down into a group of data-dependent application modules. The application modules communicate and transfer data from one module to another in order to achieve a common goal. With the limitations on computing resource capacity and the rise in demand for these resources for application module processing, there is a need for a robust application module placement strategy. Inefficient application module placement can result in a tremendous hike in latency, a higher completion time, a fast drain on battery cells, and other placement problems. This paper focuses on minimising the average delay, completion time (Makespan time), and energy usage of the fog system while placing the data-dependent modules of the IoT application on resources in the fog layer. To achieve the said objectives, a hybrid meta-heuristic algorithm based on the Red Deer Algorithm (RDA) and the Harris Hawks Optimisation Algorithm (HHO) is proposed. The optimisation algorithms independently search for a placement solution in the search space and update the best solution based on some probability function. The proposed hybrid algorithm was implemented using the iFogSim simulator and evaluated based on average completion time, average latency, and average energy consumption. The simulation results show the effectiveness of the proposed hybrid heta-heuristic algorithm over the traditional RDA and HHO algorithms.
Design, and Green synthetic approach of the Aryl-tetrazolo-[1,5-a][1,8]naphthyridine Molecules and their in vitro anti-microbial activity and In silico molecular modeling studies
Authors: Sonyanaik Banoth , Ravi Dharavath , Shyam Perugu , kishore Kamal , Ashok Alishala , Sakram Boda
Published: August 2023

An efficient eco-friendly construction of 4-aryltetrazolo [1,5-a][1, 8]naphthyridine scaffolds has been successfully prepared through the microwave method in a short reaction time with good yields. The microwave method has unique advantages, short reaction time, easy workup procedure, and simple purification of the products. Synthesized entire molecules were evaluated for their antimicrobial activity among them compounds 6g and 6a revealed the highest anti-microbial activity. Moreover, in silico molecular modeling evaluation has been done by considering docking scores, hydrogen bond interactions, affinity, and the short distance between ligand and receptor. All the molecule’s good docking results shown with the target protein and obtained results were well complemented to the antimicrobial activity.
EvolveFNN: An interpretable framework for
early detection using longitudinal electronic
health record data
Authors: Zhang Yufeng , Wittrup Emily , Najarian Kayvan , Mathis Michael
Published: August 2023

The extensive adoption of artificial intelligence in clinical decision support systems necessitates a significant presence of ML models that clinicians can easily interpret. Therefore, we developed an RNN-based interpretable method, combining the fuzzy concepts and recurrent units, to train accurate and explainable models on high-dimensional longitudinal electronic health records data. Through supervised learning, our method allows the identification of variable encoding functions and significant rules. To demonstrate its performance and capabilities in classification and rule discovery, we first tested it on a simulation dataset. The proposed methods achieved the best model performance, and the rules learned are almost identical to
what we used to generate the synthetic data. Furthermore, we showcased a pilot application that proved its potential in the early detection of cardiac event onset. We constructed a prediction window of length from 30 days to 180 days and a 360-day retrospective observation window to evaluate our algorithm. Our proposed algorithm EvolveFNN with GRU unit achieved an AUPRC of 0.695 and an AUROC of 0.682 and EvolveFNN with LSTM unit achieved an AUPRC of 0.696 and an AUROC of 0.684 when the prediction window size is 180 days. The proposed algorithm obtained a comparable model performance to vanilla GRU models and remains relatively stable when the prediction window size changes. Examining the rules generated by our EvolveFNN model with the GRU unit, we found that the extracted rules align with clinical practices and existing literature. This provides potential risk factors not explored before in the population, such as chloride. To assess the generalizability of the algorithm, we conducted experiments on the MIMIC-III benchmark dataset for in-hospital mortality prediction. The results showed our proposed algorithms achieved model performance comparable to the top-performing GRU model and surpassed other approaches by providing transparent decision reasoning. In conclusion, our approach, EvolveFNN, can effectively train accurate, interpretable, and reliable models using large longitudinal electronic health records datasets, thereby offering valuable insights for clinicians.
Effects of Enhance Adherence Counselling on Viral Load Suppression Among High Viral Load HIV Seropositive Patients in a Nigerian Tertiary Health Facility
Authors: Oluwakemi Salami Aisha
Published: August 2023

Background: EAC helps clients overcome adherence hurdles and improve ART adherence. This study examines the effect of EAC on viral load suppression. Method: This quantitative study aims to determine the impacts of enhanced adherence counselling (EAC) on viral load in Defence Headquarters Medical Center, Abuja, Nigeria. The medical records of HIV clients on ART included in EAC were extracted from the hospital and analyzed to determine the impacts of EAC on viral loads suppression of clients in the program. Result: Almost half of the PLWHIV in EAC have been on ART for 6-10 years (47.6%), 42.9% for more than ten years, and 9.5% have been on ART for 1 – 5 years. 76.2% of respondents were on the 1st line of the ART regimen, while 23.8% were on the 2nd line. 97.6% of clients enrolled for EAC were at the WHO stage I HIV infection, and only one (2.4%) was in stage IV. 50% tested for viral load was due to viral blip, 28.6% due to unsuppressed viral load and 21.4% were tested to monitor their VL. Furthermore, of the 33 clients with viral load results, 14 (42.4%) had very low-level viremia (<50 copies/ml), 10 (30.3%) had low-level viremia (50–1000 copies/ml), but 9 (27.3%) still had high-level viremia (>1000 copies/ml). 42.9% enrolled for EAC because of pill burdens, 31.0% due to irregular dosing frequency, 19.0% because of pill social problems, and 2.1% were people lost to follow-up returned.. Keywords: Antiretroviral therapy, EAC, Viral load.
To Explore the Perceived Food Taboos during Pregnancy and their Relation to Maternal Nutrition and Health
Authors: Kayumba Rabecca
Published: August 2023

The purpose of this study was to explore perceived food taboos during pregnancy and their relation to maternal nutritional status and health outcomes. The study was guided by the following objectives: To investigate food taboos identified for pregnant women in Namwala District, to identify dietary taboos that were embraced by the Women and to highlight nutritional challenges related to dietary taboos during pregnancy. Descriptive research design was used as the framework for carrying out the study with an estimated population comprising pregnant women who attended and received antenatal services at various clinics. From this estimated population, a sample comprising 74 pregnant women was selected using Purposive sampling method. SPSS V25 was used to analyze the raw data descriptively. The results clearly showed widespread practice of food taboos during pregnancy and the main reason for adherence was culture. The following interventions were recommended: Developing a team of community care givers, with the inclusion of traditional leadership to help break the barrier of food taboos in maternal nutrition. The Ministry of Education can spearhead a curriculum with maternal nutritional education in the school curriculum as early as primary school level in order to discourage people from observing detrimental food taboos. Ante-natal Clinics should include awareness strategies and a Health Feeding Programme in order to provide nutritious meals to pregnant women whist attending antenatal, like School Health Nutrition (SHN) in schools. This strategy would increase ante-natal attendance with definite positive health outcomes among them, reduction in the number of Pre-term births in Zambia. Keywords: Antenatal, Community, Culture, Feeding, Health, Maternal, Nutrition, Taboos.
The Effect of Total Quality Management on Customer Satisfaction in the Downstream Petroleum Sector in Ghana
Authors: Ohipeni Michael Tetteh
Published: August 2023

Despite the introduction of Total Quality Management (TQM), there is a general observation of customer dissatisfaction surrounding service provision by the companies in the downstream petroleum sector in Ghana. This research sought to assess the impact of TQM on customer satisfaction with regards to the downstream petroleum sector in Ghana. A sample size of 360 respondents, consisting of 290 customers, 60 staffs and 10 management staffs across different companies within Accra was used for the study. The study revealed that successful implementation of TQM has a major and significant impact on customers’ satisfaction. TQM relies of the principle of stakeholder participation and involvement. There was however a shortfall with this principle as it was identified that staff of companies within the industry did not adequately involve themselves in rolling out the TQM concept. The study recommends management of the company to ensure full participation of all. The study revealed that the successful implementation of TQM has a significant effect customer satisfaction. However, the principle of participation and involvement by staff in the quality management chain was found not to be encouraging as staffs have not been adequately involved in rolling out the TQM concept in their companies. The study concludes that management of the companies in the sector should ensure full participation of all employees in the implementation of TQM through effective communication mechanisms to integrate quality disciplines into the culture and quality service activities of the company. Keywords: Total Quality Management, Downstream petroleum sector, Customer service.
Corporate Social Responsibility and Competitive Edge. Lesson from MTN Uganda
Authors: Ariyo Gracious Kazaara
Published: August 2023

The purpose of this research study was to explore the relationship between corporate social responsibility (CSR) and competitive advantage, using MTN Uganda as a case study. The study employed a qualitative research design, utilizing semi-structured interviews with MTN Uganda executives, employees, and customers, as well as a review of company reports and other relevant documents. Thematic analysis was used to identify key themes and patterns related to the relationship between CSR and competitive advantage. The findings showed that MTN Uganda has effectively used its CSR initiatives to improve its competitive position in the telecommunications market. The study found that CSR activities that benefit society and the environment have increased customer loyalty, attracted, and retained employees, and enhanced the company’s brand image. The study concluded that adopting a strategic approach to CSR can provide a competitive advantage, and that CSR should not be viewed as a cost, but rather as an investment in a company’s future success. The recommendations from this study can provide insights for other companies seeking to achieve similar benefits from CSR initiatives and contribute to the existing body of research on CSR and competitive advantage. Keywords: Corporate Social Responsibility (CSR), Competitive Edge, MTN Uganda.
Impact of Economic Growth on Poverty Reduction: Evidence from Ghana
Authors: Henneh Ofori Frimpong
Published: August 2023

The main purpose of this article is to examine the effect of economic growth on poverty reduction in Ghana using monetary measurement approach. A time series data was collected on the variables deemed to influence the above relationship including headcount poverty, government spending, inflation, unemployment, and per capita growth in GDP. The data span from 1990 to 2021 and was sourced from the World Development indicators wxebsite. The data was analyzed using autoregressive distributed lags (ARDL) regression model and augmented Dickey-Fuller (ADF) for unit root test. The findings showed that economic growth and government spending have an inverse but significant interrelationship with reduction of poverty. Also per capita GDP has a significant positive relationship with poverty reduction. The annual inflation levels have an inverse insignificant impact on poverty reduction. The relationship between unemployment and poverty alleviation is positive though insignificant. Government should put appropriate policies in place to sustain economic growth at appreciable levels in order to reduce poverty. Agricultural productivity should be improved to provide jobs for teeming unemployed youth. Inflation should be curtailed and kept at moderate levels to ginger economic activities in the country. The Government should spend on pro-poor activities and economic infrastructure to grow the economy, create jobs, reduce income disparity, and alleviate poverty. Keywords: Monetary poverty, Multidimensional poverty, Economic growth, Government spending, Ghana.