Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of the brainstem in sleep disturbances and chronic pain of Gulf War and Iraq/Afghanistan veterans

Introduction Gulf War Illness is a type of chronic multisymptom illness, that affects about 30% of veterans deployed to the 1990–91 Persian Gulf War. Veterans deployed to Iraq/Afghanistan after 2000 are reported to have a similar prevalence of chronic multisymptom illness. More than 30 years after the Persian Gulf War, Gulf War Illness still has an unexplained symptom complex, unknown etiology and lacks definitive diagnostic criteria and effective treatments. Our recent studies have found that substantially smaller brainstem volumes and lower fiber integrity are associated with increased sleep difficulty and pain intensity in 1990–91 Persian Gulf War veterans. This study was conducted to investigate whether veterans deployed to Iraq/Afghanistan present similar brainstem damage, and whether such brainstem structural differences are associated with major symptoms as in Gulf War Illness. Methods Here, we used structural magnetic resonance imaging and diffusion tensor imaging to measure the volumes of subcortices, brainstem subregions and white matter integrity of brainstem fiber tracts in 188 veterans including 98 Persian Gulf War veterans and 90 Iraq/Afghanistan veterans. Results We found that compared to healthy controls, veterans of both campaigns presented with substantially smaller volumes in brainstem subregions, accompanied by greater periaqueductal gray matter volumes. We also found that all veterans had reduced integrity in the brainstem-spinal cord tracts and the brainstem-subcortical tracts. In veterans deployed during the 1990–91 Persian Gulf War, we found that brainstem structural deficits significantly correlated with increased sleep difficulties and pain intensities, but in veterans deployed to Iraq/Afghanistan, no such effect was observed. Discussion These structural differences in the brainstem neurons and tracts may reflect autonomic dysregulation corresponding to the symptom constellation, which is characteristic of Gulf War Illness. Understanding these neuroimaging and neuropathological relationships in Gulf War and Iraq/Afghanistan veterans may improve clinical management and treatment strategies for modern war related chronic multisymptom illness.
The Effect of Return on Asset (RoA), Earning Management and Audit Committee on Audit Delay with Managerial Ownership as a Moderating Variable

This study looks into the effects of return on asset (RoA), earnings management, and the audit committee on audit delay, with managerial ownership acting as a moderating variable. Committee of AuditsBetween 2020 and 2022, this study was carried out at property and real estate companies that were listed on Indonesia's stock exchange. Audited financial accounts serve as the source of secondary data that is used. Partial Least Square Structural Equation Modeling (SEM-PLS) is the data analysis method used. The findings demonstrated that, although profitability and earning management had a major impact on audit delay, the Committee on Audit had no discernible impact and was bolstered by managerial ownership as a mitigating factor.
A Low Sidelobe W-Band Antenna Sparse Array Based on GA Optimization

A low sidelobe W-band antenna sparse array is proposed in this paper. Unlike the conventional sparse ways, extracting units from full array, the presented sparse antenna array is based on completely random unit arrangement with genetic algorithm (GA) optimization. The minimum spacing between antenna units satisfies Euclidean spatial constraint. During beam scanning range from 0° to 30°, the sidelobe level in whole space is less than −12dB while the sparse ratio is higher than 85.2%.
Exploration of phyto-beneficial traits of halophilic rhizobacteria isolated from the mangrove halophyte Avicennia marina

Abstract The salinity of the soil exerts an adverse effect on plant development and yield. However, amid saline stress, certain halophilic bacteria enhance the growth of plants. In this investigation, the mangrove halophyte Avicennia marina’s (A. marina) rhizosphere soil was used as the source for the isolation of halophilic bacteria. The isolates’ growth capacity at different pH, salinity, temperature, and polyethylene glycol (PEG) was assessed, and it was found that 56% showed growth in media supplemented with 2–7.5% NaCl; 50% showed efficient growth at pH 6–8, 62% grow optimally at temperature 25–35 °C, and about 88% showed growth in media with 5% PEG. The isolates possess growth-promoting traits evidenced by nitrogen fixation (18%), ammonia production (31%), phosphate solubilization (88%), zinc solubilization (44%), and indole acetic acid (IAA) (88%) production. The isolates can produce extracellular enzymes, viz., protease (88%), amylase (62%), cellulase (56%), and lipase (31%). The bacterial isolate S1B1 that displayed maximum plant growth-promoting traits was selected as the potent and subjected to plant growth promotion studies. The potent isolate S1B1 enhances Solanum lycopersicum’s germination under different salinity compared to untreated seeds with germination of 64% at the maximum concentration of 2% NaCl. The potential halophilic plant growth-promoting rhizobacteria (PGPR) isolate was determined as Rossellomorea aquimaris (R. aquimaris) by 16s rRNA analysis. The results demonstrated that R. aquimaris recovered from the rhizosphere of halophyte A. marina found possible applications for enhancing plant development and productivity in salinity-affected soils.
NEW DISTRIBUTION AREAS OF SOME VASCULAR PLANTS FOR THE FLORA OF AZERBAIJAN

: Information is provided on new habitats for 44 taxa, based on the results of field studies from 2008 to 2023, supplementing data on individual botanical and geographical regions of Azerbaijan. For 20 species, new places of distribution were identified in the botanical-geographical region of the Greater Caucasus (GC) Guba part, 16 species were found in the eastern GC and two species in the western GC, four species ‒ in the Samur-Devechi lowland, one species each ‒ in Gobustan, Absheron, Lankaran and Caspian lowlands. Some taxa were identified both in the Guba and eastern part of GC. Among these plants six are endemics of the Caucasus ( Aquilegia olympica , Galanthus alpinus var. alpinus , Hedera pastuchovii , Senecio pojarkovae , Tulipa undulatifolia var. undulatifolia ( T. eichleri Regel), Ziziphora clinopodioides subsp. clinopodioides ( Z. serpyllacea M. Bieb.)), two endemics of Azerbaijan ( Iris schischkinii , Rosa azerbaidshanica ), five rare and endangered taxa ( Aquilegia olympica , Ophrys sphegodes subsp. mammosa , Ophrys oestrifera , Rosa azerbaidshanica , Tulipa schmidtii ). The data obtained expand scientific knowledge about endemic, rare and endangered species of the flora of Azerbaijan, included in the Red Books of the Republic of Azerbaijan (1989, 2013, 2023), are important for the development of measures to ensure their safety. This source of information is necessary for the compilation of the new edition of “Flora of Azerbaijan”. To a certain extent, this study also echoes other works and the brief results of the taxonomic composition study of the republic flora.
ACCELERATE THE CLOUD TASK SCHEDULING WITH ANT COLONY OPTIMIZATION

Cloud computing is a type of parallel and distributed system consisting of interconnected physical and virtual machines. One of the fundamental issues in this environment is related to job scheduling. This work is a nondeterministic polynomial time-hard optimization problem, and many meta-heuristic algorithms have been proposed to solve it. A good task scheduler should adapt its planning strategy to the dynamic environment and the types of assignments. In this paper, the modified ant colony optimization to deal with cloud task scheduling is offered and compared to different algorithms such as First Come First Serve or Round Robin. The main goal of adjustment is to enhance the performance of ant colony optimization algorithm and apply it to minimizing the makespan of a given task set in Clouds. The improved algorithm is going to be deployed in the CloudSim toolkit where Round Robin pre-installed. The experimental results show that the suggested approach outperforms the preset one.
Bacteriology of chicken meat samples from Bharatpur, Chitwan, Nepal

Many food-borne diseases are associated with the consumption of chicken meat and thus are of public health significance worldwide. A cross-sectional study was done to isolate, identify, and characterize bacteria from chicken meat samples of Bharatpur, Chitwan. A total of 102 samples were randomly collected and processed at the Microbiology laboratory of Birendra Multiple Campus, Chitwan for three months (May-July 2016). One gram of each sample was crushed on 9 ml distilled water in a sterile mortar pestle followed by serial dilution and inoculation of 0.1 ml sample into suitable culture media and incubated at 37 оC for 24 hours. Identification of the isolates was done by microscopic examination and biochemical tests and the antimicrobial susceptibility pattern of the isolates was determined by the Kirby Bauer disc diffusion method. Out of 102 meat samples, the growth positivity rate was 94.0% (n = 96/102) on all of the culture media. 26/48 fresh and 44/54 frozen samples gave positive growth with 36 isolates from fresh and 60 isolates from frozen meat samples, with the occurrence of Staphylococcus aureus 26(27.08%), Pseudomonas spp 6(6.25%), Proteus spp 4(4.16%), Escherichia coli 22(22.91%), Salmonella spp 16(16.66%), Citrobacter spp 8(8.33), Acinetobacter spp 8(8.33%), Streptococcus spp 2(2.08%), Shigella spp 4(4.16%) and Vibrio spp 2(2.08%). Cefalexin (92.85%) was the most effective antibiotic against Gram-positive bacteria followed by Amoxicillin (71.42%) and Methicillin (64.28%). The least effective antibiotic was Ampicillin (50%). Similarly, Gentamicin (76.47%) followed by Nalidixic acid (41.47%) were effective against Gram-negative bacteria, while some showed resistance to all three classes of drugs exhibiting MDR.
A Review: On Smart Materials Based on Some Polysaccharides; within the Contextual Bigger Data, Insiders, “Improvisation” and Said Artificial Intelligence Trends

Smart Materials are along with Innovation attributes and Artificial Intelligence among the most used “buzz” words in all media. Central to their practical occurrence, many talents are to be gathered within new contextual data influxes. Has this, in the last 20 years, changed some of the essential fundamental dimensions and the required skills of the actors such as providers, users, insiders, etc.? This is a preliminary focus and prelude of this review. As an example, polysaccharide materials are the most abundant macromolecules present as an integral part of the natural system of our planet. They are renewable, biodegradable, carbon neutral with low environmental, health and safety risks and serve as structural materials in the cell walls of plants. Most of them are used, for many years, as engineering materials in many important industrial processes, such as pulp and papermaking and manufacture of synthetic textile fibres. They are also used in other domains such as conversion into biofuels and, more recently, in the design of processes using polysaccharide nanoparticles. The main properties of polysaccharides (e.g. low density, thermal stability, chemical resistance, high mechanical strength…), together with their biocompatibility, biodegradability, functionality, durability and uniformity, allow their use for manufacturing smart materials such as blends and composites, electroactive polymers and hydrogels which can be obtained 1) through direct utilization and/or 2) after chemical or physical modifications of the polysaccharides. This paper reviews recent works developed on polysaccharides, mainly on cellulose, hemicelluloses, chitin, chitosans, alginates, and their by-products (blends and composites), with the objectives of manufacturing smart materials. It is worth noting that, today, the fundamental understanding of the molecular level interactions that confer smartness to polysaccharides remains poor and one can predict that new experimental and theoretical tools will emerge to develop the necessary understanding of the structure-property-function relationships that will enable polysaccharide-smartness to be better understood and controlled, giving rise to the development of new and innovative applications such as nanotechnology, foods, cosmetics and medicine (e.g. controlled drug release and regenerative medicine) and so, opening up major commercial markets in the context of green chemistry.
Evolución de la presencia y éxito de las candidatas en elecciones en Chile, 1989-2009

espanolEste articulo presenta las explicaciones que pueden dar cuenta de la presencia de mujeres en cargos de representacion popular. Sobre esta base, analizamos lo que ha ocurrido en Chile entre el retorno de la democracia en 1989 y 2009. Usamos los datos de 17 elecciones, con 37.487 candidatos. De ellos, el 19,4% fueron mujeres. De los 12.161 candidatos electos al Congreso o a gobiernos municipales, solo el 16,3% fueron mujeres. El numero de mujeres que se presenta a cargos de eleccion y su tasa de exito ha aumentado, especialmente en elecciones locales. Tambien mostramos que en elecciones con menor proporcionalidad —como alcaldes, diputados y senadores— hay menos mujeres candidatas y electas. Aunque los partidos de izquierda presentan mas candidatas, los partidos de derecha logran un mayor numero de mujeres electas. Finalmente, mostramos que la eleccion de la primera mujer presidenta, Michelle Bachelet, no tuvo un efecto sobre las tasas de participacion de mujeres como candidatas, ni sobre su exito electoral en las municipales de 2008 y legislativas de 2009. Las variables institucionales dan cuenta del porque compiten mas mujeres en elecciones mas proporcionales y porque tienen mas exito en contiendas de mayor representacion proporcional y de caracter loca EnglishThis article introduces the explanations that are likely to account for the presence of women in elected offices. Based on them, we analyze the evolution of women in elected office in Chile between the return of democracy in 1989 and 2009. We use data from 17 elections and 37.487 candidates. 19,4 percent of them, were women. And only 16,3 percent of the 12.161 candidates elected to either the legislature or local governments were women. The number of female candidates and their success rate have increased, especially in local elections. Moreover, we show that in elections with lower levels of proportionality —as mayors, deputies and senators— there are fewer female candidates and winners. Left-wing parties present more female candidates, whereas right-wing parties manage to get a higher rate of their female candidates elected. Finally, we show that the election of Michelle Bachelet as Chile’s first woman president did not have an impact on the number of female candidates or on their electoral success in the municipal elections of 2008 or the legislative elections of 2009. Institutional variables account for the higher number of female candidates in more proportional elections as well as their higher success rate both in local elections and elections with higher proportional representation
Automatic microseismic denoising and onset detection using the synchrosqueezed continuous wavelet transform

ABSTRACTTypical microseismic data recorded by surface arrays are characterized by low signal-to-noise ratios (S/Ns) and highly nonstationary noise that make it difficult to detect small events. Currently, array or crosscorrelation-based approaches are used to enhance the S/N prior to processing. We have developed an alternative approach for S/N improvement and simultaneous detection of microseismic events. The proposed method is based on the synchrosqueezed continuous wavelet transform (SS-CWT) and custom thresholding of single-channel data. The SS-CWT allows for the adaptive filtering of time- and frequency-varying noise as well as offering an improvement in resolution over the conventional wavelet transform. Simultaneously, the algorithm incorporates a detection procedure that uses the thresholded wavelet coefficients and detects an arrival as a local maxima in a characteristic function. The algorithm was tested using a synthetic signal and field microseismic data, and our results have been compared wit.
Innovative Application Contexts for Focusing Devices based on Leaky Waves

Nowadays, there exist many kinds of devices capable to generate focused electromagnetic radiation with reduced diffraction in the near field, such as Bessel beams. Among them, those based on leaky waves, also known as Bessel-beam launchers (BBLs), have attracted much attention thanks to their low-profile, low-cost, and design flexibility. While the design rules of different kinds of BBLs have been already presented in the literature, their performance when used for transmitting either power or information is scarcely reported. The aim of this work is to comprehensively review and explain their implementation and design principles through a simple, analytical, yet effective leaky-wave approach. Furthermore, their performance in wireless power transfer scenarios is reported showing promising results. Finally, their potential use in secure near-field point-to-point communications is investigated, thus paving the way for future research and development in this rapidly evolving area.
A Review of Deep Learning Strategies for Enhancing Cybersecurity in Networks

Rapid technological improvements have brought significant hazards to sensitive data and information. Cyberspace has connected various data structures, ranging from private communications/transactions to government activities. Cyberattacks are growing more complex which emphasizes the need to improve cybersecurity. Cyber security is more crucial as everything becomes more digital and as the number of connected devices keeps increasing. Cyber security techniques are used to keep networks, applications, and devices safe from intruders. Cloud and IoT technologies have expanded the complexity of computing, communication, and networking infrastructures, making cybercrime prevention more difficult. It takes a long time to develop threat recognition algorithms by the existing methods. Innovative strategies, like employing deep learning tools for cybersecurity, are anticipated to provide a solution to the issue. Deep learning approaches have many benefits which include the ability to solve complex problems quickly, high levels of automation, the best use of informal information, the capacity to generate excellent results at a lower cost, and the ability to recognize complex interactions. A diverse range of applications can be employed in deep learning models to make decisions based on predictions in the daily routine. The significant benefits of deep learning-enabled cyber security have improved security and reduced risks. The intensity of this systematic study provides consolidated knowledge about recent trends and serves as a foundation for future research in Deep learning-enabled Cybersecurity. This paper highlights the potential challenges and current cybersecurity issues with cutting-edge Deep Learning technologies.
Design, Optimization, and Experimental Evaluation of Slow Light Generated by π-Phase-Shifted Fiber Bragg Grating for Use in Sensing Applications

This paper describes design, theoretical analysis, and experimental evaluation of a π-Phase-Shifted Fiber Bragg Grating (π-PSFBG) inscribed in the standard telecom fiber for slow light generation. At first, the grating was designed for its use in the reflection mode with a central wavelength of 1552 nm and a pass band width of less than 100 pm. The impact of fabrication imperfections was experimentally investigated and compared to model predictions. The optical spectra obtained experimentally show that the spectral region used for slow light generation is narrower (less than 10 pm), thus allowing for too-low levels of slow light optical-output power. In the next step, the optimization of the grating design was conducted to account for fabrication errors, to improve the grating’s spectral behavior and its temporal performance, and to widen the spectral interval for slow light generation in the grating’s transmission mode. The targeted central wavelength was 1553 nm. The π-PSFBG was then commercially fabricated, and the achieved parameters were experimentally investigated. For the region of (1551–1554) nm, a 15-fold increase in the grating’s pass band width was achieved. We have shown that a pair of retarded optical pulses were generated. The measured group delay was found to be ~10.5 ps (compared to 19 ps predicted by the model). The π-PSFBG operating in its transmission mode has the potential to operate as tunable delay line for applications in RF photonics, ultra-fast signal processing, and optical communications, where tunable high precision delay lines are highly desirable. The π-PSFBG can be designed and used for the generation of variable group delays from tens to hundreds of ps, depending on application needs.
Exploring physical education teachers’ experiences with incorporating technology into instruction

Keeping up with evolving concepts and teaching new knowledge require individuals to adapt to 21st century abilities in order to be future-ready and versatile in keeping up with the trends of an ever-changing educational landscape. Technology integration is a huge assist in offering meaningful and creative quality education services. The purpose of this study is to acquire an in-depth undertanding of physical education teachers' experiences with integrating ICT into lesson delivery. The study utilized qualitative study which employs a phenomenological approach. Purposive sampling was utilized in the study to fulfill the study's purpose of answering research concerns where 7 physical education teachers participated the study. Codes and themes were used in the study. Three themes emerged in the study: dynamic teaching and learning experiences, lack of access, and health problems. This study intends to highlight the significance of adopting and integrating technology into the current teaching and learning process, which highlights the significance of teaching of physical education teachers’ with showcasing the technical capabilities and skills. Additionally, by incorporating ICT, the study will highlight its beneficial outcomes and serves as a strategy will be developed to deal with the difficulties instructors have faced by creating policies for improving teachers’ technological skills as a result of these difficulties. The use of ICT to give instruction in physical education classes will highlight the study's beneficial effects. Every physical education teacher who uses ICT to give lessons in concepts, principles, and teaching and learning will benefit from the clarity this study will bring.