Miracle-dz/UniFAR-FTUs huggingface dataset:
Gut Microbial Diversity Analysis of Different Native Chickens and Screening of Chicken-Derived Probiotics

Simple Summary The gut microbiota plays a vital role in the growth and development of chickens, while environmental and host factors can influence its composition. This study sheds light on the variations in gut microbial diversity and structural composition among native chickens from different geographical environments, as well as different breeds of broiler and laying hens, revealing the presence of distinct microbial communities. Additionally, our investigation into chicken-derived probiotics, specifically Lactobacillus agilis MH1 and Lactobacillus salivarius ZJ1, uncovered their probiotic properties, favorable genomic profiles, and their ability to alleviate enteritis in mice. These findings provide a critical theoretical foundation for the study of native chickens and offer valuable guidance for the subsequent development and formulation of chicken-derived probiotics. Abstract The gut microbiota plays a critical role in the growth, development, nutritional digestion, and overall health of chickens. Furthermore, certain probiotics isolated from poultry intestines have demonstrated the potential to enhance immune function and production performance in chickens. To investigate the differences in gut microbiota among chickens from various geographical environments and different breeds of broiler and laying hens, we conducted 16S rRNA sequencing on the fecal microbiota of 140 Chinese native chickens and ten Roman layers. In addition, we isolated and screened the potential probiotics to examine their biological characteristics, genome profiles, and functionality in animals. Our findings revealed the significant variations in gut microbiota composition and structure between Tibetan chickens (ZJ), which reside in high-altitude regions, and Meihua chickens (MH) and Xuhai chickens (XH), which inhabit low-altitude regions. Specifically, Cupriavidus and Candidatus_Bacilloplasma were identified as unique microbial communities in high and low altitudes, respectively. Notably, among regions with similar altitudes, Luning chickens (LN) exhibited the lowest α diversity, accompanied by a remarkably high relative abundance of Firmicutes and Lactobacillus. Conversely, Wugu chickens (WGs) and Yaoshan chickens (YSs) displayed similar gut microbiota profiles. Furthermore, distinctive gut microbiota patterns were observed between the different breeds of broilers and laying hens. Commercial Roman layers (LMs) exhibited significantly lower alpha diversity compared to native chickens, and broilers and laying hens predominantly harbored Firmicutes, Bacteroidota, and Proteobacteria. Of particular interest, the probiotics Lactobacillus agilis MH1 and Lactobacillus salivarius ZJ1, derived from chicken feces, exhibited favorable genomic profiles, and demonstrated anti-colitis effects and immunomodulatory functions. These findings provide a crucial theoretical foundation for native chicken research and offer insights for the future development and formulation of chicken-derived probiotics.
Optimization Accuracy of CNN Model by Utilizing CLAHE Parameters in Image Classification Problems

This study aims to optimize popular Convolutional Neural Network (CNN) models, such as ResNet50, InceptionV4, VGG19, MobileNetV1, MobileNetV2, MobileNetV3 Small, and MobileNetV3 Large, by utilizing the CLAHE (Contrast Limited Adaptive Histogram Equalization) parameter. This research focuses on the problem of classifying retinal fundus images, which have challenges in analyzing the structure and features of the picture. This study compared the performance of CNN models, which were optimized using the CLAHE method as image pre-processing. The fundus retinal image data used is a publicly available dataset. The optimization process is done by changing the parameters in the CNN model and applying the CLAHE technique to improve image quality before the classification process. The results showed that using the CLAHE parameter significantly contributed to improving the performance of the CNN model in classifying retinal fundus images. Some CNN models optimized with CLAHE produce better accuracy than the unoptimized models. There are also variations in performance between the different models, with some models providing better results in classifying retinal fundus images. This study provides new insights regarding using CLAHE parameters in optimizing the CNN model for retinal fundus image classification problems. The results of this research can be the basis for further development in medical image processing and pattern recognition for more accurate and practical diagnostic applications.
Simulating the Sandwaves Moving with a Ultra-High Resolution Three Dimensional Hydrodynamic Model

An ultra-high horizontal resolution (about 200m) three-dimensional ocean model is developed to simulate the bottom current of observation area with size of 40 kilometers. The model takes tidal force, surface wind and baroclinic effect into account and adopts grid-nesting technique to achieve the horizontal resolution level. With the current simulated, a sediment transport model is developed and applied in the prediction of small scale sandwaves migration in study area of Beibu Gulf, South China Sea. The migration directions both on the ridge back and the ridge groove that are opposite are successfully predicted.n
3D indoor modeling and game theory based navigation for pre and post COVID-19 situation

The COVID-19 pandemic has greatly affected human behavior, creating a need for individuals to be more cautious about health and safety protocols. People are becoming more aware of their surroundings and the importance of minimizing the risk of exposure to potential sources of infection. This shift in mindset is particularly important in indoor environments, especially hospitals, where there is a greater risk of virus transmission. The implementation of route planning in these areas, aimed at minimizing interaction and exposure, is crucial for positively influencing individual behavior. Accurate maps of buildings help provide location-based services, prepare for emergencies, and manage infrastructural facilities. There aren’t any maps available for most installations, and there are no proven techniques to categorize features within indoor areas to provide location-based services. During a pandemic like COVID-19, the direct connection between the masses is one of the significant preventive steps. Hospitals are the main stakeholders in managing such situations. This study presents a novel method to create an adaptive 3D model of an indoor space to be used for localization and routing purposes. The proposed method infuses LiDAR-based data-driven methodology with a Quantum Geographic Information System (QGIS) model-driven process using game theory. The game theory determines the object localization and optimal path for COVID-19 patients in a real-time scenario using Nash equilibrium. Using the proposed method, comprehensive simulations and model experiments were done using QGIS to identify an optimized route. Dijkstra algorithm is used to determine the path assessment score after obtaining several path plans using dynamic programming. Additionally, Game theory generates path ordering based on the custom scenarios and user preference in the input path. In comparison to other approaches, the suggested way can minimize time and avoid congestion. It is demonstrated that the suggested technique satisfies the actual technical requirements in real-time. As we look forward to the post-COVID era, the tactics and insights gained during the pandemic hold significant value. The techniques used to improve indoor navigation and reduce interpersonal contact within healthcare facilities can be applied to maintain a continued emphasis on safety, hygiene, and effective space management in the long term. The use of three-dimensional (3D) modeling and optimization methodologies in the long-term planning and design of indoor spaces promotes resilience and flexibility, encouraging the adoption of sustainable and safe practices that extend beyond the current pandemic.
Aplastic Anemia Mimicking Myelofibrosis: A Diagnostic Dilemma

Hematological disorders pose a diagnostic challenge due to overlapping clinical features, as demonstrated by the difficulty in differentiating between aplastic anemia (AA) and primary myelofibrosis (PM). Myeloproliferative disorders, characterized by aberrant proliferation of bone marrow stem cells, present complexities in diagnosis, often requiring a comprehensive evaluation to distinguish between disorders with similar manifestations. The distinctions between myelofibrosis and AA lie not only in clinical presentations but also in genetic and molecular markers, necessitating a nuanced diagnostic approach. We present a case of a 37-year-old male initially diagnosed with myelofibrosis based on a history of pancytopenia, warm submandibular and submental swelling, and negative BCR-ABL and JAK2 mutations. Further examination revealed empty fragmented cells, hypoplastic bone marrow, and suppressed erythropoiesis and myelopoiesis. Subsequent core biopsy showed increased megakaryocytes, prompting a revised diagnosis of AA. This case underscores the importance of a meticulous diagnostic journey, incorporating physical examination, genetic testing, and advanced imaging to unravel the complexities of hematological disorders. The intricacies of this case prompt a reevaluation of diagnostic paradigms, highlighting the limitations of relying solely on specific mutations for diagnosis. The absence of BCR-ABL and JAK2 mutations in AA raises questions about its genetic landscape, necessitating further exploration. Immunological considerations, given the immune-mediated nature of AA, provide a foundation for future research into immune dysregulation and potential therapeutic interventions. The clinical management challenges posed by AA underscore the need for personalized treatment strategies, guided by a deeper understanding of its underlying pathophysiology. Advanced imaging techniques, in conjunction with traditional diagnostic methods, emerge as crucial tools for enhancing diagnostic accuracy in hematological disorders. This case serves as a paradigm for ongoing medical education, multidisciplinary collaboration, and innovative approaches in the evolving landscape of hematology, emphasizing the imperative for continuous refinement in diagnostic strategies and patient care.
Role of Endothelial Nitric Oxide in Control of Peripheral Vascular Conductance 1 During Muscle

24 The muscle metaboreflex is a powerful pressor reflex induced by the activation of 25 chemically sensitive muscle afferents as a result of metabolite accumulation. During 26 submaximal dynamic exercise, the rise in arterial pressure is primarily due to increases 27 in cardiac output as there is little systemic vasoconstriction. Indeed, in normal animals 28 we have often shown a small, but significant, peripheral vasodilation during 29 metaboreflex activation, which is mediated, at least in part, by release of epinephrine 30 and activation of vascular β2 receptors. We tested whether this vasodilation is in part 31 due to increased release of nitric oxide caused by the rise in cardiac output eliciting 32 endothelium-dependent. flow-mediated vasodilation. The muscle metaboreflex was 33 activated via graded reductions in hindlimb blood flow during mild exercise with and 34 without nitric oxide synthesis blockade (L-nitroarginine methyl ester (L-name); 5mg/kg). 35 We assessed the role of increased cardiac output in mediating peripheral vasodilation 36 via the slope of the relationship between the rise in non-ischemic vascular conductance 37 (conductance of all vascular beds excluding hindlimbs) vs. the rise in cardiac output. L38 name increased mean arterial pressure at rest and during exercise. The metaboreflex39 induced increases in mean arterial pressure were unaltered by L-name; whereas, the 40 increases in cardiac output and non-ischemic vascular conductance were attenuated. 41 However, the slope of the relationship between non-ischemic vascular conductance and 42 cardiac output was not affected by L-name indicating that the rise in cardiac output did 43 not elicit vasodilation via increased release of nitric oxide. Thus, although nitric oxide is 44 intrinsic to the vascular tonus, endothelial-dependent flow-mediated vasodilation plays 45 little role in the small peripheral vasodilation observed during muscle metaboreflex 46 activation. 47
Fragmentary Models for Some Classes of Vehicle Routing Problems

Most of the optimization problems related to the delivery of goods belong to the class of nondeterministic polynomial time hard (NPH) problems. For such problems, the use of various metaheuristics is justified. However, the presence of a large number of constraints, first, significantly complicates the construction of the corresponding mathematical model, and, second, makes the method of solving the problem individual, applicable to a rather narrow class of applied problems. The authors have shown that a fragmentary model can be built for many classes of logistics problems. This allows them to reduce the optimization problem of the corresponding class to an unconstrained optimization problem on a set of permutations. The authors propose a method for constructing universal hybrid algorithms for finding suboptimal solutions for certain classes of vehicle routing problems based on a combination of fragmentary and well-known metaheuristics.
EVALUATION OF DETERMINANTS OF TOURISM DESTINATION’S COMPETITIVENESS ON CUSTOMER LOYALTY

The purpose of the study sought to evaluate the influence of determinants of tourism destination competitiveness on customer loyalty. The study evaluated by the fact many tourism destinations competitiveness in Kenya are silent to domestic tourism due to lack of customer loyalty. The specific objective was to evaluate the effects of destination attractiveness, to establish the effect of auxilary factors, to determine the influence of destination management and to establish the moderating role of situational condition in sanctuaries. The study would of significance to the management of tourism destinations. The study adopted Michael porter theory of competitive advantage. The study used descriptive research design. The study used a sample size of 233 respondents from tourist destinations. The target population was 466 respondents from the two sanctuaries. Stratified sampling techniques were used to select 233 respondents from Assistant warden ii, sergeant education warden, customer care officers, supervisors, animal keepers, tour guides, rangers, cage attendants, research scientist, and corporal discipline officers. The tool for data collection was research questionnaire. Validity of research instruments were measured by supervisor’s opinion and relevant research experts. Reliability of research instruments were determined by use of Crobach alpha coefficients. The data collected was analyzed by use of descriptive statistics involving percentage, mean, and standard deviations. The results were presented by use of charts, figures, graphs and tables. The findings from the study were of significance to the management of tourism destinations, policy makers, academicians and researchers who would use relevant knowledge to do further research. The destination management affects attractiveness. Development in the destination should be responsive to visitor needs, Marketing of Tourist attractions should seek to increase resident awareness and reputation of domestic holidays, There’s need to engage domestic tourists through social networks such as you tube, twitter, facebook, whatsapp, etc to ensure efficient communication, Planning and development should focus on the uniqueness of the destination.
Prevalence of Occupational Injuries of the Oral and Maxillofacial Region and Their Covariates Among Building Construction Workers in Chennai

Background and aim With many risky environmental conditions, civil construction sites are prone to physical injuries, especially those pertaining to the oral and maxillofacial regions. The current study was an effort to assess the magnitude and pattern of such oral and maxillofacial injuries and the factors associated with them. Methodology This descriptive study was carried out on 524 construction workers, of whom 254 met the inclusion criteria related to work site injuries. An interviewer-administered proforma with basic demographic details is used in conjunction with an intraoral examination to classify the dental injury. Descriptive statistics were done to evaluate the frequency of injury occurrence, while inferential statistics, including the chi-square test and regression analysis, were done to evaluate the association between injury and the variable under concern. Result The study includes a total of 254 participants, with ages ranging from 20 to above 50 years, of whom 230 (91%) were males and 24 (9.4%) were females. The majority, 200 (78.7%), were unskilled laborers, and 195 (76.7%) were migrant workers with language barriers. It was found that 95 (76.7%) had a history of dental injury alone, while 59 (23.2%) had a history of oral maxillofacial injury. Among the reasons for injury, the increased odds ratios (OD) were noted in the collapse of the surrounding area as 0.050 (0.029-0.075), rainy season 1.001 (0.891-1.281), unskilled labor 1.020 (0.910-1.30), and migrants 1.010 (0.901-1.200). The OD for males is 2.052 (1.941-2.101). Conclusion The current study confirms that the magnitude of workplace-related injuries is significant, and the majority of them stem from basic language barriers among migrant workers and a lack of knowledge to adhere to safety protocols and instructions given.
Closure of the Global Overturning Circulation Through the Indian, Pacific, and Southern Oceans: Schematics and Transports

This paper applies several novel statistical methods to assess the extent and variability of the ocean's three major "high-nutrient / low-chlorophyll" (HNLC) regions. Its novel contributions include articulating a new definition of HNLC in terms of the ratio NO3/Chl, and identifying new linkages between HNLC extent and some climate variability indices.
Effect of Natural Variation and Rootstock on Fruit Quality and Volatile Organic Compounds of ‘Kiyomi tangor’ (Citrus reticulata Blanco) Citrus

In this study, we compared the fruit quality and color of ‘Kiyomi’ (WT) and its mutant (MT) grafted on Ziyang xiangcheng (Cj) (WT/Cj, MT/Cj), and the MT grafted on Trifoliate orange (Pt) (MT/Pt). The differences in sugar, organic acid, flavonoids, phenols, and volatile substances of the three materials were also analyzed by high performance liquid chromatography (HPLC) and headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC–MS). The results showed significant differences in the appearance of WT/Cj, MT/Cj, and MT/Pt. MT/Pt, compared to WT/Cj, MT/Cj, had lower sugar, acid, phenol and flavonoid contents in the pulp. However, MT/Pt pulp was higher in vitamin C (VC), and the peel had significantly higher total phenol and flavonoid contents. In terms of pulp, WT/Cj had the greatest diversity of volatile organic compounds (VOCs). 4-methyl-1-pentanol was significantly higher in MT/Cj pulp, while MT/Pt pulp had a unique octanoic acid, methyl ester. VOCs were more diverse in the peels of the three materials. β-Myrcene and valencen were significantly higher in MT/Cj peels. In contrast, 16 unique VOCs were detected in MT/Pt, and D-limonene content was significantly higher than in WT/Cj and MT/Cj. The results suggest Trifoliate orange is a suitable rootstock for MT.
Antibacterial Potential of Ethanol Extract of Marigold (Tagetes erecta L.)

Antimicrobial resistance is a pandemic which affects the therapeutic options of many people in need by rendering most known antibacterial agents ineffective. The answer to the problem may be found in the old books written by ancient philosophers who used various plants to treat the sick. Our objective was to study the antibacterial properties of the commonly found plant, Tagetes erecta L. , and to determine the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the crude ethanol extract. A maceration protocol was used to obtain crude ethanol extract of dried aerial parts of T. erecta and broth microdilution method to test the antibacterial activity of the extract against selected Gram-positive and Gram-negative bacteria. The inhibitory effect of the T. erecta extract was documented with MICs for Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus being 368 mg/ml and 182 mg/ml for Enterococcus faecalis. The MBCs for all bacterial species were 368 mg/ml. The current study demonstrates the antibacterial properties of T. erecta and its potential use as a source of antibacterial compounds.
Enhancing Plant Disease Identification through Innovative Image Synthesis: A Study of InstaGAN and Data Augmentation in Agriculture

This study explores the growing implementation of artificial intelligence (AI) technology, particularly in agriculture, where AI-driven object detection enhances efficiency. Deep learning's potential for plant disease identification is hampered by data scarcity. To address this, data augmentation techniques like Generative Adversarial Networks (GANs) are employed, with models like InstaGAN contributing to image synthesis. InstaGAN's innovative approach, integrating instance information and contextual preservation, is examined using the "Plant Village" dataset. The study underscores the value of InstaGAN in mitigating data limitations through synthesized image augmentation, showcasing promising outcomes in comparison to alternative models.
Carga cognitiva y realidad mixta (aumentada y virtual)

: Technological progress has led to the emergence of cutting-edge tools that enrich the physical environment by incorporating virtual elements. In the field of education, this technological immersion offers learning experiences that guarantee greater optimisation in the acquisition of knowledge through a lower cognitive load. These technologies have the capacity to create and add information developed in virtual environments
Implementation and Testing of MP-TCP ATSSS in a 5G Multi-Access Configuration

5G represents the latest currently available and the state of the art of mobile cellular networks. 5G is defined on the basis of new concepts like Software Defined Network (SDN), Network Function Virtualization (NFV) and Network Slicing, enabling a wide set of use-cases and applications. An innovative feature introduced in 5G since 3GPP Release 16 is Access Traffic Steering, Splitting and Switching (ATSSS), which gives the possibility to the user equipment (UE) connected to a 5G network using a 3GPP link (i.e., the gNB New Radio access) and a non-3GPP one (e.g., a public WLAN access point) to access 5G services using both links simultaneously. ATSSS can improve the user-experience, maximizing the throughput and improving resilience to network faults by downloading or uploading data using both channels at the same time or selecting the best link where to transmit for each data flow. In this paper, we analyze in depth the ATSSS functionality and the associated Multipath TCP (MP-TCP) mode in a Linux simulation testbed, including an Open Source 5G Core Network, with the full implementation of the User Plane and 3GPP and non-3GPP access links, using Free5GC, UERANSIM and a custom implementation of N3IWF. In this testbed setup, we run real traffic and assess the MP-TCP configuration and performance in realistic conditions, when the non-3GPP access is performed wither via terrestrial wireless or a high latency satellite link.