bluuebunny/crossref_metadata_2025 huggingface dataset:
Fréchet-derivative-based global sensitivity analysis of the physical random function model of ground motions
Authors: Wan Zhiqiang , Tao Weifeng , Ding Yanqiong , Xin Lifeng
Published: June 2023

Randomness in earthquake ground motions is prevalent in real engineering practices. Therefore, it is of paramount significance to utilize an appropriate model to simulate random ground motions. In this paper, a physical random function model of ground motions, which considers the source-path-site mechanisms of earthquakes, is employed for the seismic analysis. The probability density evolution method is adopted to quantify the extreme value distribution of structural responses. Then, the sensitivity analysis of the extreme value distribution with respect to basic model parameters is conducted via a newly developed Fréchet-derivative-based approach. A 10-story reinforced concrete frame structure, with nominal deterministic structural parameters and subjected to random ground motions, is studied. The results indicate that when the structure is still in a linear or weakly nonlinear stage in the situation of frequent earthquakes, the model parameter called the equivalent predominate circular frequency is of the most significance, with an importance measure (IM) greater than 0.8. Nonetheless, if the structure exhibits strong nonlinearity, such as in the case of a rare earthquake, the equivalent predominate circular frequency remains highly influential, but the Brune source parameter, which describes the decay process of the fault rupture, becomes important as well, with an IM increased from around 0.2 to around 0.4. These findings indicate that the IMs of basic model parameters are closely related to the embedded physical mechanisms of the structure, and the change in the physical state of the structure may provoke the change of IMs of basic inputs. Furthermore, some other issues are also outlined.
AGGREGATION PRICE MODELS FOR MICROGRIDS WITH DISTRIBUTED ENERGY RESOURCES
Authors: Denysiuk S. , Derevianko D. , Bielokha H. , Zaichenko S.
Published: June 2023

The development of Microgrid states the problem of choosing the optimal technologies for its composition.This paper is to present cost based demand-side management methods for the Microgrids with DistributedGeneration sources to optimize their operation. While implementing variable pricing models the aggregatorshould take into account characteristics of different Distributed Energy Resources (DER) (diesel engines, gasturbines, fuel cells, solar panels, small hydropower plants and wind turbines) and LCOE for each type of DER tostimulate each local electricity market participant separately. The system Microgrid using three diesel generatorsand the option of replacing one generator with a solar electric and wind generator installation was considered.
FEATURES OF ORGANIZATION AND USE OF ENERGY STORAGE SYSTEMS IN DISTRIBUTION NETWORKS
Authors: Zharkin A.F. , Popov V.A. , Yarmoliuk O.S. , Natalych V.O.
Published: June 2023

The article analyzes the features and formulates recommendations for the most effective use of the energy storage systems in electrical distribution systems and microgrids in the context of expanding the use of local renewable energy sources. Information about various energy storage technologies is summarized and recommendations are formulated regarding their best applying for various applications in the electric power industry. The tasks that can and should be solved by energy storage systems in distribution networks are considered, as a result of which the expediency of forming hybrid storage systems is substantiated. Based on the analysis of the bibliography and consideration of international experience, the main problems have been identified that require further research for a reasonable choice of the structure, parameters, locations and modes of operation of hybrid energy storage systems, taking into account the specifics of the structure and operation of domestic electric distribution systems with local energy sources. Under the implementation of hybrid energy storage systems, a fundamentally new problem of determining the optimal parameters of individual components of such systems arises, which was practically not covered in published works on this issue. Additionally, difficulty in solving this task is the need for its complex solution, since, firstly, the parameters of the individual components of the hybrid energy storage system are most likely interdependent, and secondly, it is necessary to take into account the involvement of the storage systems in the solution of a number of optimization problems inherent in the electrical distribution systems. In order to facilitate the use of energy storage devices, it is advisable to create a comprehensive standard that allows you to evaluate and compare the quality and performance of different technologies, helps energy storage users justify the type and parameters, as well as optimal placement for maximum benefit.
ENERGY STORAGE DEVICES. MAIN TYPES AND PROSPECTS OF APPLICATION
Authors: Myrutenko P. , Listovshchyk L.
Published: June 2023

The article considers energy storage equipment as a key element of the power supply chain. The need to accumulate energy arose at the beginning of the creation of energy networks and, with the development of technologies for the production, transmission and consumption of energy, the relevance of the creation and rational use of storage devices is growing. Quite a few types of storage devices have already been created, some of them are quite widely used, many are still at the testing stage, but have good chances for development and integration into power systems of various types. The article attempts to analyze the main types of energy storage devices, which differ from each other in the way of accumulation, energy, type of energy, storage time, accumulated power, etc. and summarizes their main characteristics in order to compare them with each other. 

The results obtained in this article will allow us to pre-select a certain type of energy storage device depending on the power system that is being designed, which will make it possible to most rationally manage energy flows in the process of transmission, energy storage and its supply to the grid.
ESTUDO SOBRE SEGREGAÇÃO URBANA NO BAIRRO RESIDENCIAL JARDIM MATO GROSSO – PEDRA PRETA – MATO GROSSO
Authors: Pereira Aires José , Pereira Paulo Ricardo Silva , Oliveira Max Roberto de
Published: June 2023

O presente trabalho tem como tema o estudo sobre segregação urbana do bairro residencial Vila Jardim Mato Grosso – Pedra Preta - MT. Com objetivo a busca e a compreensão acerca do funcionamento do planejamento urbano e sua intervenção na configuração da paisagem urbana da vila através da análise na qual a mesma foi proposta.  Esta parte da necessidade de observar a organização do espaço urbano da Vila Jardim Mato Grosso, surge pela necessidade das observações juntamente com a sociedade que ali convive, uma que se tem disposto todo um aparato para estruturar essa organização de forma eficiente e adequada às necessidades da localidade. Apesar disso o espaço ainda está estruturado de forma notoriamente caótica, na qual demostra problemas tanto no âmbito social, representado pela falta de infraestrutura urbana e ausência de serviços básicos entre eles, saúde, asfalto, moradia, segurança, drenagem pluvial, tratamento de esgoto, quanto ambiental o mesmo sendo observados pelas erosões, deslizamentos de terra, inundações desde seu surgimento, compactação do solo e etc. O método é o qualitativo apontando para uma pesquisa qualitativa, no método hipotético dedutivo, no que possibilitou aos sujeitos entrevistados emitirem suas opiniões sobre o tema em discussão. Para mencionar as questões, se busca responder com a presente pesquisa na qual fez-se um levantamento teórico-conceitual com embasamento nos pressupostos teóricos de diversos autores que tratam do tema abordado.
Application of Bilinear Softening Laws and Fracture Toughness of Foamed Concrete
Authors: Maulana Malik Ridwan , Ahmad Hilton , Sugiman Sugiman
Published: June 2023

Fracture and failure performance of foamed concrete materials were conducted using three methods, i.e., inverse analysis, digital image correlation (DIC) and finite element modelling (FEM) from tested normalized notched beams under three-point bending. From this study, several characteristics both experimental and FEM are discussed. However inverse analysis is only well applicable for series GF-30. The bilinear softening of the testing beam was estimated to identify fracture energy (GF), critical crack length (ac) and elastic modulus (E) with values of 0.015 N/mm, 54.5 mm, and 13 GPa, respectively. Additionally, fracture toughness was calculated by adopting double-K (initiation fracture of 6.907 MPa.mm0.5, unstable fracture of 23.186 MPa.mm0.5 and cohesive fracture of 16.278 MPa.mm0.5). Two-dimensional FEA Modelling of fracture was carried out using a Traction Separation Law (TSL), incorporating extended finite element method (XFEM) and cohesive zone (CZM) techniques. A sensitivity study was carried out, global mesh size of two and damage stabilization cohesive with the value of 1 × 10-5 showed good convergence and were used in other models. Furthermore, by comparing experimental observation using DIC, reliability FEM was validated and showed good acceptance to simulating the crack propagation.
Research on Information Fusion System Implementation Based on ARM-Based FPGA
Authors: Tsai Yu-Hsiang , Yan Yung-Jhe , Hsiao Meng-Hsin , Yu Tzu-Yi , Ou-Yang Mang
Published: June 2023

This research uses ARM-based FPGA to implement the computation of a virtual-real fusion hardware system. It also evaluates the acceleration effect of virtual-real fusion execution speed after connecting related hardware acceleration and provides a reference for real-time information fusion system design. The hardware uses Xilinx Zynq UltraScale+ MPSoC ZCU102 Evaluation Kit. It also obtains color and depth images with Intel® RealsenseTM D435i depth cameras. This system receives image data through the Linux system built on the ARM and fed to the FPGA for object detection using CNN models. In addition, it develops a module for rapidly performing registration between the color images and the depth images. It can calculate the size and position of the display information on the transparent display according to the pixel coordinates and depth values of the human eye and the object. The fusion took about 47ms on a personal computer with a GPU RTX2060 and 25ms on the ZCU102. The acceleration is nearly 168%. Finally, the results were successfully transplanted into the retail display system for demonstration.
Experimental Analysis on a Spray Hydrocooler with Cold Energy Storage for Litchi
Authors: Huang Hao , Lv Enli , Lu Huazhong , Guo Jiaming
Published: June 2023

The shortage of precooling equipment in litchi producing regions could lead to a high loss rate, poor quality of litchis. It is urgent to develop a portable precooling device for litchi producing regions. In this study, a novel spray hydrocooler with thermal energy storage (TES) were designed, fabricated, and tested. A simple mathematical model of TES capacity, ice coil thermal resistance and refrigeration system was employed to determine hydrocooler parameters. Then designed the structure of the spray hydrocooler. Maximum charging test was implemented with full TES capacity and litchi spray hydrocooling experiments were carried out at different charging times, spray flow rate, and litchi load with one-third TES capacity. Results showed that: (1) the spray hydrocooler allows for the rapid and effective precooling of litchis; (2) the hydrocooler can precool 299 kg litchis with one-third TES storage, meet the precooling requirements; (3) the effective TES capacity achieved 1.25×108 J at the maximum TES capacity of the hydrocooler, while the energy efficiency ratio (EER) is 2; (4) the precooling capacity was maximum and the average power consumption was minimum when the litchi load was 23 kg and the spray flow rate was 30 L min-1. Longer charging time is the most important factor in increasing precooling capacity and reducing average power consumption.
Training in Digital Skills – The Perspective of Workers in Public Sector
Authors: Lopes Ana Sofia , Sargento Ana , Farto Joana
Published: June 2023

Digital transformation can become a complex process when workers have insufficient skills, which makes training in the digital field essential. Herein, we intended to relate digital literacy perceived by workers with their training needs for the Portuguese public sector context. Additionally, based in the Human capital theory, we also investigate which professional/demographic characteristics increase training propensity in digital fields. Through an online questionnaire, a dataset with information on 573 workers was obtained. Data analysis was made by using a probabilistic regression model and additional statistical techniques. The results revealed that workers with higher levels of education and higher professional skills have higher probability of participating in training in the digital field. On average, workers reveal low levels of digital knowledge and low participation in training in the digital fields, but the majority present a willingness to participate in future training sessions, especially in the fields of Dataset management, Cybersecurity and Communication systems. This study provides information on training in the digital field of workers in the public sector, which is essential for public organizations to better prepare for digital transformation. Additionally, it contributes to a very recent literature on digital learning, and it can be extended to other contexts.
The Current State of Charcot–Marie–Tooth Disease Treatment
Authors: Okamoto Yuji , Takashima Hiroshi
Published: June 2023

Charcot–Marie–Tooth disease (CMT) and associated neuropathies constitute the most predominant genetically transmitted neuromuscular conditions; however, effective pharmacological treatments remain elusive. The extensive genetic heterogeneity of CMT, which impacts the peripheral nerves and results in a lifelong disability, presents a significant barrier to the development of comprehensive treatments. An estimated 100 loci within the human genome are linked to various forms of CMT and its related inherited neuropathies. This review delves into prospective therapeutic strategies used for the most frequently encountered CMT variants, namely CMT1A, CMT1B, CMTX1, and CMT2A. Compounds such as PXT3003, which are currently under clinical and preclinical investigation, and a broad array of therapeutic agents and their corresponding mechanisms have been discussed in this review. Furthermore, the progress in established gene therapy techniques, including gene replacement via viral vectors, exon skipping using antisense oligonucleotides, splicing modification, and gene knockdown, has been appraised. Each of these gene therapies has the potential for substantial advancements in future research.
Analytical Approximations to Charged Black Hole Solutions in Einstein-Maxwell-Weyl Gravity
Authors: Li Sheng-Yuan , Zhang Ming , Zou De-Cheng , Lai Meng-Yun
Published: June 2023

The Homotopy Analysis Method (HAM) is a useful method to derive analytical approximate solutions of black holes in modified gravity theories. In this paper, we study the Einstein-Weyl gravity coupled with Maxwell field, and obtain analytical approximation solutions for charged black holes by using the HAM. It is found that the analytical approximate solutions are sufficiently accurate in the entire spacetime outside the black hole's event horizon, and also consistent with numerical ones for charged black holes in the Einstein-Maxwell-Weyl gravity.
RL-Based Detection, Tracking, and Classification of Malicious UAV Swarm through Airborne Cognitive Multibeam Multifunction Phased Array Radar
Authors: Khawaja Wahab , Yaqoob Qasim , Guvenc Ismail
Published: June 2023

Detecting, tracking, and classifying unmanned aerial vehicles (UAVs) in a swarm presents significant challenges due to their small and diverse radar cross-sections, multiple flight altitudes, velocities, and close trajectories. To overcome these challenges, adjustments of the radar parameters and/or position of the radar (for airborne platforms) are often required during runtime. The runtime adjustments help to overcome the anomalies in the detection, tracking, and classification of UAVs. The runtime adjustments are performed either manually or through fixed algorithms, each of which can have its limitations for complex and dynamic scenarios. In this work, we propose the use of multi-agent reinforcement learning (RL) to carry out the runtime adjustment of the radar parameters and position of the radar platform. The radar used in our work is a multibeam multifunction phased array radar (MMPAR) placed onboard UAVs. The simulations show the cognitive adjustment of the MMPAR parameters and position of the airborne platform using RL helps to overcome anomalies in the detection, tracking, and classification of UAVs in a swarm. A comparison with other artificial intelligence (AI) algorithms shows that RL performs better due to runtime learning of the environment through rewards.
First Record of Cetacean Killed in an Artisanal Fish Aggregating Device in Italian Waters
Authors: Manfrini Valerio , Fortuna Caterina Maria , Cocumelli Cristiano
Published: June 2023

Fish Aggregating Devices (FADs) are anchored floating structures often made with cheap scrapped materials and used to aggregate pelagic fish under their artificial shadow. Globally, the dangerous impact of FADs has well known. They pose a severe threat due to known and unknown levels of bycatch, the danger to navigation, and their high potential to become marine litter. Entanglement and consequent mortality in FADs of protected species and species of conservation concern (e.g., sharks, sea turtles, and cetaceans) are a serious concern for several international inter-governmental bodies (e.g., EU, GFCM, and IWC). This work describes the first case of a cetacean, a striped dolphin (Stenella coeruleoalba), killed by a FAD in the Mediterranean Sea. This dolphin was found stranded along the coast of the central Tyrrhenian Sea. The evidence suggests that this specimen suffered a painful death. Although this is the first confirmed case of a cetacean killed by a FAD in Italian waters, given the extent of the deployment of FADs, the scale of this type of interaction with protected species might be seriously underestimated. Therefore, actions and monitoring need to be implemented urgently to effectively protect and conserve marine biodiversity.
Cyclic Peptides with Antifungal Properties Derived from Bacteria, Fungi, Natural Products, and Synthetic Sources
Authors: Helmy Naiera M. , Parang Keykavous
Published: June 2023

Fungal infections pose a significant threat to human health, particularly in immunocompromised individuals. Due to several factors, such as the inappropriate use of antimicrobial drugs, the emergence of resistance in microorganisms, and increasing demand for less cytotoxic antifungal agents for immunocompromised patients, antifungal research has gained significant attention in recent years. Antifungal peptides, and among them, cyclic peptides, are a class of antifungal agents that have been under development since the 1960s. Using cyclic peptides as a promising approach for combating antifungal resistance in pathogenic fungi has gained significant attention in recent years. The identification of antifungal cyclic peptides from various sources has been possible due to the widespread interest in peptide research in recent decades. It is increasingly important to evaluate the narrow to broad-spectrum antifungal activity and the mode of action of synthetic and natural cyclic peptides for both synthesized and extracted peptides. This short review aims to highlight some of the antifungal cyclic peptides isolated from bacteria, fungi, and plants, taking into consideration the progress made in peptide research. Additionally, it provides a summary of synthetic cyclic peptides with antifungal activity and discusses the potential future of utilizing combinations of antifungal peptides from different sources. The review underscores the need for further exploration of the novel therapeutic applications of these abundant and diverse cyclic peptides.
CoSOV1Net: Cone- and Spatial-Opponency Primary Visual Cortex-Inspired Neural Network for Lightweight Salient Object Detection
Authors: Ndayikengurukiye Didier , Mignotte Max
Published: June 2023

Computer vision models of salient object detection attempt to mimic the ability of the human visual system to select relevant objects in images. To this end, the development of deep neural networks on high-end computers has recently made it possible to achieve high performance. However, it remains a challenge to develop deep neural network models of the same performance for devices with much more limited resources. In this work, we propose a new approach for a lightweight salient object detection neural network model, inspired by the cone and spatial opponent processes of the primary visual cortex (V1), that inextricably link color and shape in human color perception. Our proposed model, namely CoSOV1net, is trained from scratch, without using backbones from image classification or other tasks. Experiments, on the most widely used and challenging datasets for salient object detection, show that CoSOV1Net achieves competitive performance (i.e. Fβ=0.931 on the ECSSD dataset) with state-of-the-art salient object detection models, while having low number of parameters (1.14M), low FLOPS (1.4G) and high FPS (211.2) on GPU (nvidia Geforce RTX 3090 TI) compared to the state-of-the-art in the salient object detection or lightweight salient object detection task. Thus, CoSOV1net turns out to be a lightweight salient object detection that can be adapted to mobile environments and resource-constrained devices.
Wavelet Transforms and Machine Learning Methods for the Study of Turbulence
Authors: Alam Jahrul M
Published: June 2023

This article examines the wavelet transforms and the machine learning methods in accelerating large eddy simulations of turbulent flows. An overarching challenge of large eddy simulations is to accurately represent the cascade of kinetic energy across the cut-off length scale. Taylor hypothesis suggests that the energy cascade occurs through the process of vortex stretching. However, Richardson hypothesis assumes the self-amplification of the strain field and a hierarchical break down of large eddies lead the energy cascade. The large eddy simulations typically employs the self-amplification of the strain in formulating subgrid models. However, several studies also proposed subgrid models based on vortex stretching. The wavelet-based coherent vortex simulation of turbulence directly accounts for vortex stretching in overall forward scatter of energy, while allowing local backscatter. The wavelet-based large eddy simulation adapts the grid to capture the creation of small-scale eddies, while adopting subgrid models based on the self-amplification of strain. The advancement of artificial intelligence in turbulence modelling is currently evolving around accelerating the numerical simulations of turbulent flow. However, there is a clear connection between the application of wavelet transfroms and neural networks for directly solving the Navier-Stokes equation, indicating some potential benefits of wavelet methods over the neural networks.
Recent Advances on Electrospun Fibers for Biological Applications
Authors: Fromager Bénédicte , Marhuenda Emilie , Louis Benjamin , Bakalara Norbert , Cambedouzou Julien , Cornu David
Published: June 2023

Electrospinning is a simple versatile method to generate nanofibres. Remarkable progress has been made in the development of electrospinning process. The production of nanofibers is affected by many parameters, which influence the final material properties. Electrospun fibers have a wide range of applications such as energy storage and biomedical scaffolds. Polyacrylonitrile (PAN) has been widely used in the production of carbon nanofibers. PAN has received increasing interest in recent years, due to its excellent characteristics, such as spinnability, biocompatibility, and commercial viability, opening new applications in the biotechnological field. This paper provides an overview of the electrospinning process, its main parameters, and operation modes that affect nanofibers fabrication. A review of their biological applications is proposed. A focus is made on PAN fibers formation, functionalization, and application as scaffolds to allow cell growth. Overall, nanofibre scaffolds, made of stabilized PAN, appear as a powerful tool in medical applications needing controlled cell culture.
A Blockchain-based Continuous Micropayment Scheme Using Lockable Signature
Authors: Wang Wennan , Chen Guoxin , Chu Chiawei , Lan Wusong
Published: June 2023

A blockchain-based continuous micropayment is a crucial component of the digital economy as it facilitates transactions and promotes small purchases. However, due to the throughput limitations of blockchain, payment channels (PC) are often used to process a large volume of transactions through an off-chain mode. Nevertheless, the introduction of PC requires a trusted third party to ensure transaction security, which creates an additional security assumption since only the first and last transactions can be witnessed by other system users. To address this issue, we propose a novel micropayment scheme based on lockable signatures. All transactions in the PC form a continuous microtransaction hash-chain (CMHC) to prevent malicious users from obtaining transaction information during the process. Furthermore, all locks in the CMHC are invisible during the entire transaction process, and all information is transferred in a tamper-resistant manner. We provide corresponding security analysis and conduct a series of evaluations. The results show that the proposed scheme performs better than the state-of-the-art solutions in terms of transaction time and verification costs. This lockable signature-based micropayment scheme not only guarantees security but also improves transaction speed and efficiency, thereby promoting the development of the digital economy.
The Impact of Bloody Amniotic Fluid on Delivery and Early Neonatal Outcomes
Authors: Schreiber Hanoch , Cohen Gal , Shalev Hila , Farladansky-Gershnabel Sivan , Weitzner Omer , Biron-Shental Tal , Kovo Michal , Arnon Shmuel , Markovitch Ofer
Published: June 2023

Information on the effect of bloody amniotic fluid during labor at term is scarce. This study assessed risk factors and obstetrical outcomes in labors complicated by bloody amniotic fluid. All nulliparas with singleton pregnancy, who underwent a trial of labor ≥37 weeks of gestation, in a single tertiary center, over six years were included. Obstetrical, delivery and neonatal outcomes were compared between deliveries with bloody amniotic fluid or clear amniotic fluid. Overall, 11,252 women were included. Among them, 364 (3.2%) had bloody amniotic fluid and 10,888 (96.7%) had clear amniotic fluid. Women with bloody amniotic fluid were characterized by shorter duration of the second stage of labor and higher rate of cesarean delivery due to non-reassuring fetal heart rate. The rates of cord pH < 7.1 and NICU admissions were also higher. In multivariate logistic regression analysis, cesarean delivery, cord blood pH < 7.1 and NICU admission were independently associated with increased odds ratio for bloody amniotic fluid. Bloody amniotic fluid at term is associated with adverse outcomes and must be considered during labor.
Identification of Subgroups within a Japanese Older Adult Population for whom Statin Therapy is Effective in Reducing Mortality
Authors: Funaki Daito , Kaneda Hideaki , Miyakoshi Akinori , Saito Kohei , Hatoko Sasaki , Nakatani Eiji
Published: June 2023

The effects of statin use for primary prevention in reducing mortality among older adults in Asian populations are unknown. This study aimed to determine whether use of statins for primary prevention was associated with a decreased risk of all-cause mortality in a Japanese older adult population. A regional, population-based, longitudinal cohort study was conducted using the Shizuoka Kokuho Database (SKDB). Data were compared between the statin-treated group and a non-statin-treated (control) group using the inverse probability of treatment weighting (IPTW) method. In the SKDB cohort aged ≥65 years, new statin use was associated with a decreased risk of all-cause mortality (hazard ratio, 0.40; 95% confidence interval [CI], 0.33–0.48) after IPTW adjustment. The risk difference for mortality at 5 years in the statin-treated group (7.9%) compared with that in the control group (92.1%) was 0.05 (95% CI, 0.04–0.06), and the number needed to treat was 21.20 (95% CI, 18.10–24.70). In conclusion, statin use for primary prevention in older adults may reduce the risk of all-cause mortality in the population without atherosclerotic disease. Furthermore, statin use for primary prevention is feasible in patients aged 75 to <85 years and in patients with comorbidities such as diabetes, or dementia.
Spatial Analysis of Influence Factors Associated With Liver Fluke (Opisthorchis viverrini) Infection in Small Sub-Watershed Using GWR Modeling
Authors: Pumhirunroj Benjamabhorn , Littidej Patiwat , Boonmars Thidarut , Bootyothee Kanokwan , Artchayasawat Atchara , Wongkalasin Attasit , Lertsiriudom Eksakol , Khamphilung Phusit , Slack Donald
Published: June 2023

Infection of liver flukes (Opisthorchis viverrini) is partly due to their suitability for habitats in sub-basin areas, which causes the intermediate host to remain in the watershed system in all seasons. Spatial monitoring of fluke infection at the small -basin analysis scale is important because this can enable analysis at the level of the spatial factors involved and influencing infections. A geographic weighted regression model was developed to analyze the spatial characteristics of liver fluke infection, aiming to 1. analyze the spatial factors associated with human liver fluke infection according to sub-basin boundaries and 2. generate an alternative model for enhancing the effectiveness of preventive public health management to reduce the risk of liver fluke infection in humans. The number of infected persons was obtained from local authorities and converted into a percentage of infected people and generated as raster data with a heat map so that the data were continuous and defined as dependent variables. The independent set consisted of nine variables, both vector and raster data, that correlated the location with the village location of an infected person. The results showed that the variables X5stream, X7ndmi, and X9savi were statistically significantly correlated to the percentage of infected people, with the t-stat and p-value being (-2.068, 1.875, and -2.661) and (0.048, 0.034, and 0.021), respectively. The GWR model was able to increase accuracy more than the comparable models such as OLS, in all tests of the four alternative models, with an accuracy increase in R2 of 7.69% (0.576 to 0.624). This study confirms that the development of spatial models with GWR models can screen for factors associated with liver fluke infection at the level of small spatial units such as sub-basins.
Postoperative Survival Effect of Examined Lymph Node Count in Node-Negative Esophageal Carcinoma
Authors: Li Zhiyu , He Wenwu , Li Changding , Nie Xin , Ni Kunhan , Leng Xuefeng , Li Kunzhi , Liu Kun , Tu Deyao , Han Yongtao
Published: June 2023

Background
A limited lymphadenectomy may make patients with esophageal squamous cell carcinoma (ESCC) at risk for missing occult nodal disease. This study aimed to determine an effective threshold of lymph nodes (LNs) for evaluation of the quality of lymphadenectomy and discuss the impact of adjuvant chemotherapy on pN0 patients.
Methods
Patients treated surgically for ESCC between 2010 and 2018 in Sichuan Cancer Hospital were included. NPV (Negative Predictive Value) based on a beta-binomial distribution was developed to assess the confidence of node-negative disease. Kaplan-Meier curves were plotted to compare survival differences among groups.
Results
When patients had >21 LNs examined, the probability of false-negative findings was estimated at <10%, and NPV was estimated at a high level (>86.5%). For patients with LNs removed ≤21, 5-year OS (or DFS) in postoperative chemotherapy group vs that in surgery group was 65.3% vs 54.6%, p = 0.041 (or 59.2% vs 46.6%, p = 0.033). But for patients with >21 LNs, there were no statistical differences (p = 0.683 for OS or p = 0.942 for DFS).
Conclusion
Only pN0 patients who were at high risk of occult lymph node metastasis (examined LNs ≤21) could benefit from postoperative chemotherapy.
A Global Review of Invasive Haemophilus influenzae disease from 2000-2023: Current Status, Challenges and Future Perspectives
Authors: Abdi Abas Mahammed , Yehualaw Desta Damtie , Kebede Tirusew Sema , Darod Ziad Abdilahi
Published: June 2023

Haemophilus influenzae is one of causative agent of invasive bacterial pathogen that affects both children and adults. Haemophilus influenzae is a pleomorphic gram-negative coccobacillus and it is a common commensal of the upper respiratory tract. It is a human-only pathogen that can cause severe invasive diseases. These bacterial infections can range from mild, such as ear infections, to severe, such as bloodstream infections. The infections typically affect children younger than 5 years old and old age person older than 65 years. They also affect people who are immunocompromised, such as those with certain medical conditions. The highest incidence rates of invasive Haemophilus influenzae disease have recently been discovered in various nations, including North America, Canada, and parts of Europe. In order to monitor the evolving nature of invasive Haemophilus influenzae disease critically reviewed data is required to capture the true status of invasiveness of the Haemophilus influenza diseases. Developing new vaccines against Haemilus influenzae is a potential solution to protect some vulnerable populations against the invasive disease due to this bacterial species. This review article thoroughly investigate recent and up-to-date biomedical science perspective development, innovation, findings, publications and current areas of scientific interest and gap including pathogenicity, diagnosis, multidrug-resistance, Molecular characterization and genetic evolution, epidemiology and immunological characteristics of Haemophilus influenzae, including specific current issues that are affecting the research and development of vaccines to treat Haemophilus influenzae non serotype b diseases and providing insight into how these problems may be overcome.
Ramon Syndrome: A Rare Case of Cherubism with Gingival Fibromatosis in an Adult Female
Authors: Assimi Sihame , Cherkaoui Amine
Published: June 2023

Abstract: Cherubism is a rare genetic disorder characterized by painless bilateral expansion of the mandible and maxilla. We present an unusual case of a 50-year-old female patient with Ramon syndrome, a rare variant of cherubism, accompanied by gingival fibromatosis. The patient exhibited symptoms of short stature, mental retardation, rheumatoid arthritis, epilepsy, hirsutism, and gingival enlargement. Clinical examination revealed generalized gingival inflammation with plaque and attachment loss. Radiographically, bilateral defined multilocular radiolucencies were observed in the mandibular body and ramus. The patient underwent a non-surgical phase, including oral hygiene motivation and periodontal debridement, followed by a surgical phase involving gingivoplasty and internal bevel gingivectomy with open flap debridement. Histopathological analysis confirmed the presence of fibroblasts, multinucleated giant cells, and fibrous connective tissue. The patient's son also presented with bilateral facial swelling and similar radiographic findings, indicating familial inheritance of cherubism. The case demonstrates the clinical, radiographic, and histopathological features of cherubism associated with gingival fibromatosis and highlights the challenges in diagnosis and management. Regular follow-up and maintenance are essential for long-term stability and prevention of recurrence. This report contributes to the limited literature on cherubism in older patients and emphasizes the importance of early identification and intervention in affected individuals.
Investigation of Single Event Upset in Graphene Nano-Ribbon FET SRAM Cell
Authors: Adesina Naheem Olakunle
Published: June 2023

In recent years, graphene has received so much attention because of its superlative properties and its potential to revolutionize electronics especially in VLSI. This study analyzes the effect of single event upset (SEU) in SRAM cell which employs metal-oxide semiconductor type graphene nano-ribbon field effect transistor (MOS-GNRFET) and compares the results respectively with another SRAM cell designed in PTM 10nm FinFET node. Our simulation show there is a change in data stored in the SRAM after heavy ion strike. However, it recovers from radiation effects after 0.46 ns for GNRFET and 0.51 ns for FinFET. Since the degradation observed in Q and Qb of GNRFET SRAM are 2.7X and 2.16X as compared to PTM nano-MOSFET, we can conclude that GNRFET is less robust to single effect upset. In addition, the stability of SRAM can be improved by increasing the supply voltage VDD.
Autism spectrum disorder pathogenesis – a cross-sectional literature review
Authors: Horecka-Lewitowicz Agata , Adamczyk-Gruszka Olga , Kozieł Dorota , Lim Hyebin , Lewitowicz Wojciech , Lewitowicz Piotr
Published: June 2023

The etiology of autism spectrum disorder (ASD) has not yet been completely elucidated. Through time, multiple attempts have been made to uncover the causes of ASD. Different theories have been proposed, such as that it is caused by “Gods Wrath,” alternations in the gut–brain axis with an emphasis on gut dysbiosis, post vaccine complications, and genetic or even autoimmune causes. In this review we present data covering over 170 000 participants at age ranging from 2 to 14 years focusing on human cell changes rather than using animal models found in previous studies. The male/female ratio was 4:1. Data collection occurred in many countries covering ethnically diversified subjects. Moreover, we aim to show how the progress in genetic techniques influence the explanation found in medical White Papers based on the human genetic samples we have observed from our studies
Comparison of Transfer Learning and Established Calibration Transfer Methods for Metal Oxide Semiconductor Gas Sensors
Authors: Robin Yannick , Amann Johannes Felix , Schneider Tizian , Schütze Andreas , Bur Christian
Published: June 2023

With metal oxide semiconductors being a promising candidate for accurate indoor air quality assessments, multiple drawbacks of the gas sensors prevent their widespread use. Examples include poor selectivity, instability over time, and sensor poisoning. Complex calibration methods and advanced operation modes can solve some of those drawbacks. However, this leads to long calibration times, which are unsuitable for mass production. In recent years, multiple attempts to solve calibration transfer have been made with the help of direct standardization, orthogonal signal correction, and many more methods. Besides those, a new promising approach is transfer learning from deep learning. This article will compare different calibration transfer methods, including direct standardization, piecewise direct standardization, transfer learning for deep learning models, and global model building. The machine learning methods to calibrate the initial models for calibration transfer are feature extraction, selection, and regression (established methods) and a custom convolutional neural network TCOCNN. It is shown that transfer learning can outperform the other calibration transfer methods regarding the root mean squared error, especially if the initial model is built with multiple sensors. It was possible to reduce the number of calibration samples by up to 99.3 % (from 10 days to approximately 2 hours) and still achieve an RMSE for acetone of around 18 ppb (15 ppb with extended individual calibration) if six different sensors were used for building the initial model. Furthermore, it was shown that the other calibration transfer methods (direct standardization and piecewise direct standardization) also work reasonably well for both machine learning approaches, primarily when multiple sensors are used for the initial model.
Application Study of YOLOv5 Algorithm on Automotive Wheel Surface Defect Detection
Authors: Xia Xiuye , Zhang Zhenyu , Liu Fucai
Published: June 2023

Surface defect detection is a crucial step in the process of automotive wheel production. However, the task possesses challenges due to complex background and a wide range of defect types. In order to detect the defects on the wheel surface accurately and quickly, this paper proposes a YOLOv5-based algorithm for automotive wheel surface defect detection. The algorithm trains and tests the YOLOv5s model using the self-created automotive wheel surface defect dataset, which contains four kinds of defects: linear, dotted, sludge, pinhole. The extensive experimental results demonstrate that the deep learning network trained by our method can achieve an average accuracy of 71.7% and 57.14 FPS. Our findings prove that this detection algorithm performs better than other common target detection algorithms and meets the real-time requirements of industrial applications.
Landscape Evolution Modelling of a Post-mining Catchment for Long-term Simulations
Authors: Nair Devika , Evans Dr.Ken , Bellairs Dr.Sean
Published: June 2023

Landform Evolution Modelling (LEM) provides an avenue for simulating how a landscape may evolve over extended time periods of thousands of years. The CAESAR-Lisflood LEM that includes a hydrologic model (TOPMODEL) and a hydraulic model (Lisflood) can be used to assess the proposed final landform morphology of a mine site by simulating how the mine landform and the landscape would evolve over a 1,000-year period. The accuracy of future simulations depends on the calibration and validation of the model to the past and present events. Calibration and validation of the model involves finding a combination of parameters of the model which when applied and simulated gives model outputs similar to those observed for the real site scenario for corresponding input data. Calibrating the sediment output of the CAESAR-Lisflood model at the catchment level and using it for studying the equilibrium conditions of the landform is an area yet to be explored. Therefore, the aim of this study was to calibrate the CAESAR-Lisflood model and then validate it. To achieve this, the model was run for a rainfall event with a set of parameters, plus discharge and sediment data for the input point of the catchment, to analyze how similar the model output would behave when compared with the discharge and sediment data for the output point of the catchment. The model parameters were then adjusted until the model closely approximate the real site values of the catchment. It was then validated by running the model for a different set of events and checking that the model gave similar results to the real site values. The outcomes demonstrated that while the model can be calibrated to a greater extent for hydrology (discharge output) throughout the year, the sediment output calibration may be slightly improved by having the ability to change parameters to take into account the seasonal vegetation growth during the start and end of the wet season. This study is important for designing and testing post-mining rehabilitated landscape systems that assess hydrology and sediment movement in seasonal biomes.
Development of an Automatic Robot To Save Labor in Longline Fishing
Authors: Shiraishi Haruhiro , Shiraishi Hajime
Published: June 2023

Most of the fishing currently practiced in Japan is done by small vessels with a small number of fishermen (one or two). One of the most common fishing methods is longline fishing. However, this method requires the vessel to operate at a constant low speed because the depth of the hook must be kept constant while adjusting the speed of the fishing boat to the tidal current. In addition, because the vessel must maneuver and fish at the same time, automation is desired. Thus, we propose a robotic system that can control the depth of the trap at a constant depth even when the speed of the vessel and the current change, and that can successfully fish without the need for skilled fishermen. Fishing can be conducted regardless of the speed of the vessel, whereas currently it is controlled by the speed of the vessel and the tidal current. Therefore, it may contribute to proposing new fishing methods as well as the existing ones. This can contribute to the shortage of successors to the fishing industry and to the revitalization of the fishing industry.
Enhancing the Anti-Leukemic Potential of Thymoquinone- SBE-β-CD Inclusion Complex
Authors: EID ELTAYEB E.M. , Alshehade Salah Abdalrazak , Almiman Amer A. , Kamran Sareh , Lee Vannajan Sanghiran , Alshawsh Mohammed Abdullah
Published: June 2023

Leukemia, characterized by abnormal blood cell proliferation, remains a significant challenge in cancer treatment. Thymoquinone (TQ), a bioactive compound derived from black seed, has demonstrated anticancer properties, including telomerase inhibition and induction of apoptosis. However, TQ's poor solubility and limited bioavailability hinder its clinical application. This study explores the use of SBE-β-CD, a cyclodextrin derivative, to enhance the solubility and stability of TQ for leukemia treatment. SBE-β-CD offers low hemolytic activity and has been successfully employed in controlled drug release systems. The study investigates the formation of inclusion complexes between TQ and SBE-β-CD and assesses their effects on leukemia cell growth. Results indicate that the TQ/SBE-β-CD complex exhibits improved solubility and enhanced cytotoxic effects compared to TQ alone, suggesting the potential of SBE-β-CD as a drug delivery system for TQ. Annexin V-FITC tests demonstrate increased apoptosis and reduced telomerase activity in leukemia cells treated with TQ/SBE-β-CD, supporting its anti-leukemic potential. Molecular docking analysis reveals a strong binding affinity between TQ and telomerase. However, further research is needed to optimize the apoptotic effects and minimize necrosis induction. In conclusion, TQ/SBE-β-CD shows promise as a novel strategy for leukemia treatment by targeting telomerase and enhancing the cytotoxic effects of TQ, offering a potential solution to overcome the limitations of TQ's poor solubility and bioavailability.
Assessing the FDI- Load Capacity Factor relationship in Spain: an ARDL approach
Authors: Hernandez Soto Gonzalo
Published: June 2023

This work discusses the relationship between foreign direct investment (FDI) and pollution in Spain using an autoregressive distributed lag regression model (ARDL) from 1961 to 2018. The authors apply the theoretical context of pollution haven/halo and conclude that FDI in Spain does not contribute to the transfer of green technologies for cleaner production, despite being included within the European environmental regulatory framework. The authors also verify the adequacy of the environmental Kuznets curve (EKC) and the Load Capacity Curve hypothesis (LCC) in the Spanish environmental context and find that income per capita has a positive effect on environmental sustainability and quality. In this sense, the further development of an efficient renewable energy infrastructure could efficiently drive to a better standards all pollution indexes in Spain, including nuclear energy production, contributing the emissions neutrality aimed by the EU by 2050.