Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparative Study between Total Laparoscopic Hysterectomy and Non-Descent Vaginal Hysterectomy for the Treatment of Benign Diseases of the Uterus

: Background: According to NCBI data, the prevalence of hysterectomy performed in married women is 17 per 1000 married women 1 . The number of women undergoing hysterectomy ranges from 2 to 63/1000 across different states. A little more than one-third of women who had undergone hysterectomy were under the age of 40 years 2. We aim to compare between non-descent vaginal mode of hysterectomy and the total laparoscopic mode of hysterectomy in the treatment of Benign diseases of the uterus. Methods: This was a Cross-sectional comparative study. Patients who underwent non-decent vaginal hysterectomy (NDVH) and Total laparoscopic hysterectomy (TLH) at our tertiary care Hospital during the study period were enrolled.120 cases were randomized equally into two surgical procedure groups of NDVH and TLH with 60 cases in each group. Results: The financial burden was less In the NDVH procedure. The length of hospital stay was significantly less in NDVH. Blood loss during surgery was significantly more in NDVH. The mean drop in hemoglobin was significantly more in NDVH. Mean ambulation time was significantly less in TLH. The mean VAS score on different days was significantly less in TLH. Conclusions: When both surgical approaches are feasible, VH should remain the surgery of choice for benign hysterectomy
Alternanthera Sessilis Leaf Extract-Derived Green Synthesised Zinc Oxide Nanoparticles Antibacterial Activity Against Infections In Freshwater Fish

- Biological reductants continue to be studied worldwide to reduce the harmful effects of toxic chemicals used to create nanoparticles. Utilizing an aqueous leaf extract of Alternanthera sessilis , this study analyzed the effects of bio-synthesized ZnO nanoparticles(As-ZnO NPs). Zinc acetate dihydrate was employed as the precursor, and the leaf extract was used as a biological reductant to produce zinc oxide nanoparticles. The synthesis conditions, such as heat, p H, and mixing time, were optimized for the synthesis of ZnO nanoparticles. The obtained nanopowder was characterized using several analytical methods and was kept in a dry state. The As-ZnO nanoparticles were characterized using UV-Vis Spectroscopy, Scanning Electron Microscope, Energy Dispersive X-ray analysis, Powder X-ray diffraction and FT-IR Spectroscopy. The synthesized As-ZnO NPs exhibited a peak at 333 nm in the UV-Vis spectroscopy analysis. According to Scanning Electron Microscope, the structure of nanoparticles showed a hexagonal wurtzite shape. The crystalline nature of the nanoparticles was validated by Powder X-ray diffraction. The synthesized nanoparticles were tested for their antibacterial potential against the main aquatic pathogens such as Enterococcus faecalis , Staphylococcus aureus , Streptococcus pyogenes , Aeromonas hydrophilia , Klebsiella pneumonia and Pseudomonas aeruginosa . This study reported an efficient green method for synthesising zinc oxide nanoparticles with antibacterial properties against freshwater fish pathogens.
New geometric restriction for the displacement-constraint points in discontinuous deformation analysis

AbstractA displacement-based seismic discontinuous deformation analysis (DDA) considers the influence of an earthquake by applying a time-dependent displacement constraint to simulate time-dependent ground movement of the base rock. However, unexpected variations of the base block stress and the block area in a seismic DDA may affect the block contacts with another block. This study theoretically clarifies the mechanism that causes unwanted base block distortion in a seismic DDA. A new geometric restriction is proposed for the assignment of displacement–constraint points to simulate the ground movement of two-dimensional (2D) and three-dimensional (3D) convex and concave blocks without changing the DDA algorithm. Additionally, the Daguangbao rock avalanche triggered by the Wenchuan earthquake in China is considered as a case study to demonstrate the capability of the new geometric restriction in a DDA to solve practical problems.
Variability in ecological attributes of abundant species increases with taxonomic diversity: insights for assembly mechanisms of Neotropical bat communities

Understanding the mechanisms shaping species composition of assemblages is critical for incorporating ecological and evolutionary perspectives into biodiversity conservation. Thus, we quanti�ed the relative support of community assembly mechanisms by assessing how species richness relates to the functional and phylogenetic biodiversity of Neotropical bat assemblages. We assessed the association of functional diversity for functional categories and phylogenetic diversity with species richness for 20 assemblages of Neotropical bats. In addition, we contrasted functional and phylogenetic diversity against null models to determine the mechanisms that structure the assemblages. Functional divergence increased with species richness, indicating that the variability in ecological attributes among abundant bats increases as the assemblages contain more species. Taxa were more distantly related as richness increases, but distances among closely related species remain constant. We found a consistent tendency of clustering of functional traits in site assemblages, particularly in abundant species. We proposed competition between clades as a possible mechanism modulating the community structure in Neotropical bats assemblages. Our results suggest that decreasing overlap in functional traits between abundant species could promote coexistence with rare species that can buffer ecosystem function due to species loss.
MIT Open Access

An approach-avoidance (Ap–Av) conﬂict arises when an individual has to decide whether to accept or reject a compound offer that has features indicating both reward and punishment. During value judgments of likes and dislikes, arousal responses simultaneously emerge and inﬂuence reaction times and the frequency of behavioral errors. In Ap–Av decision-making, reward and punishment differentially inﬂuence valence and arousal, allowing us to dissociate their neural processing. The primate caudate nucleus (CN) has been implicated in affective judgment
Short-term variability and mass loss in Be stars

Context. In early-type Be stars, groups of nonradial pulsation (NRP) modes with numerically related frequencies may be instrumental for the release of excess angular momentum through mass-ejection events. Difference and sum/harmonic frequencies often form additional groups. Aims. The purpose of this study is to find out whether a similar frequency pattern occurs in the cooler third-magnitude B7-8 IIIe shell star ν Pup. Methods. Time-series analyses were performed of space photometry with BRITE-Constellation (2015, 2016/17, and 2017/18), SMEI (2003–2011), and HIPPARCOS (1989–1993). Two IUE SWP and 27 optical echelle spectra spanning 20 years were retrieved from various archives. Results. The optical spectra exhibit no anomalies or well-defined variabilities. A magnetic field was not detected. All three photometry satellites recorded variability near 0.656 c/d which is resolved into three features separated by ∼0.0021 c/d. Their first harmonics and two combination frequencies form a second group, whose features are similarly spaced by 0.0021 c/d. The frequency spacing is very nearly but not exactly equidistant. Variability near 0.0021 c/d was not detected. The long-term frequency stability could be used to derive meaningful constraints on the properties of a putative companion star. The IUE spectra do not reveal the presence of a hot subluminous secondary. Conclusions. ν Pup is another Be star exhibiting an NRP variability pattern with long-term constancy and underlining the importance of combination frequencies and frequency groups. This star is a good target for efforts to identify an effectively single Be star.
Algebraic Tunnelling Algebraic Tunnelling

We study the quantum phenomenon of tunnelling in the framework of algebraic quantum theory, motivated by the tunnelling aspects of false vacuum decay. We see that resolvent C*-algebra, proposed relatively recently by Buchholz and Grundling rather than Weyl algebra provides an appropriate framework for treating the dynamics of non-free quantum mechanical system as an algebraic automorphism. At the end, we propose to investigate false vacuum decay in algebraic quantum field theoretic setting in terms of the two-point correlation function which gives us the tunneling probability, with the corresponding C*-algebraic construction
Dairy Feed Quality and Feeding Practices in Selected Urban and Peri-Urban Areas of Nekemte and Nedjo, Western Oromia

: Dairy feed quality and feeding practice was studied in urban and peri-urban selected areas of Nekemte and Nedjo in Western Oromia, Ethiopia. This study was conducted with the objectives of investigating feed resources, assessing feeding practice and determining nutritional qualities of major dairy feeds. Purposive sampling technique was employed to select target dairy farms. A total of 60 dairy farms were selected from Nekemte (30) and Nedjo (30) to gather data through semi-structure questionnaire and field observation. Farmers were stratified into medium holders and small holders based on herd size. Samples of major feeds from both study sites were collected and analysis for chemical composition and in vitro - dry matter digestibility (IVDMD). The results of the study showed that natural pasture hay and crop residue were the major feed resources in both study sites. Stall feeding and semi-grazing feeding systems were practiced by 78.4 % and 21.6% of respondents respectively. Major feed samples were analyzed for ash, neutral detergent fiber (NDF), acid detergent fiber (ADF), crude protein (CP) and IVDMD. The ash contents of feeds samples varied significantly (P<0.05) from 44±1.8 g/kg DM (Teff straw) to 105±0.5 g/kg DM (Noug cake). The CP contents of feeds significantly (P<0.05) varied from 357±0.8 g/kg DM (Noug cake) to 50.3±0.32 g/kg DM (Teff straw). The NDF contents of feeds range from 184±0.17g/kg DM (Maize flour) to 774±0.17 g/kg DM (Teff straw). The IVDMD of sample feeds significantly varied (P < 0.05) with a range of 43.9±3.8 to 83.4±0.4 for hay and maize flour respectively. Teff straw had highest IVDMD value among roughage feeds. Therefore, the present study concluded that the quality of feeds were low in quality hence supplementation of energy and protein feeds is essential. Strategic energy and protein rich feed for supplementation, sensitizing farmers to use of other optional available feeds resources like hulls of pea, fruit wastes and technical intervention of pre-harvest and post-managements are paramount to increase dairy cattle milk productivity.
ACADEMICS’ BEHAVIORAL INTENTION AND USAGE OF IOT IN E-LEARNING: MODERATION OF GENDER AND EXPERIENCE

As the world shifts to e-learning, IoT is becoming increasingly important in the learning and teaching environment. The key concerns are the elements that influence academics’ behavioral intention to adopt IoT, and how the whole operation affects their performance. However, there is a research gap in past studies that have not addressed this issue sufficiently. As a result, this study employed the Unified Theory of Acceptance and Use of Technology (UTAUT) as a guideline to examine the factors that influence academics’ behavioral intentions to use IoT. Furthermore, the moderating effects of both gender and level of experience on this relationship were inspected. The structural models were validated, and the predefined hypotheses were presented (n = 321). The results from the Structural Equation Modeling approach using Amos 26 indicate that performance expectancy, social influence, and effort expectancy directly influenced behavioral intentions to utilize IoT. The findings also showed that facilitating conditions were the most important determinant of academics’ actual usage of IoT. The structural model was further investigated according to the experiences of the male and female academic groups. The findings revealed a different pattern of strength and significant relationships between groups with the overall model, implying that gender and experience act as moderators. This study provides a wealth of antecedents from which to construct a thorough theory of IoT adoption. The theory explores the elements that influence academics’ willingness to utilize IoT from the standpoints of the technology itself, social context, and individual user characteristics. By employing the proposed approach, Universities can modify their EL strategies to make the most of their resources and in turn improve efficiency.
Serum peptides as candidate biomarkers for relapsing polychondritis

Background: For relapsing polychondritis (RP), no useful biomarkers have yet been identi�ed. We analyzed serum peptide pro�les to identify candidate biomarkers. Methods: Patients with RP or rheumatoid arthritis (RA) and healthy control (HC) subjects were divided into training set (RP, n=19; RA, n=21; HC, n=17) and testing set (RP, n=18; RA, n=21; HC, n=18). Seven patients demonstrating granulomatosis with polyangiitis (GPA) were used for validation. The ion intensity of serum peptides was comprehensively measured by matrix-assisted laser desorption/ionization time-of-ight/time-of-ight mass spectrometry. Results: One hundred sixty serum peptides were detected. In the RP group of the training set, 24, 8, and 7 peptides showed a ³1. 2-fold difference in ion intensity in comparison to the HC, RA, and HC+RA (non-RP) groups, respectively (p<0.05). Based on a supervised multivariate analysis of the ion intensity of 160 peptides, we generated 3 models that completely discriminated the RP group from the HC, RA, and non-RP groups (RP/HC-160P model, RP/RA-160P model, and RP/nonRP-160P model; AUROC, 1.000). By selecting 11, 9, and 14 peptides, the RP group was also completely discriminated from the 3 groups (RP/HC-11P model, RP/RA-9P model, and RP/nonRP-14P model; AUROC, 1.000). We attempted to identify the peptides with a ³1. 2-fold difference in ion intensity between the RP group and one of the 3 groups and the peptides comprising the RP/HC-11P, RP/RA-9P or RP/nonRP-14P models. Nineteen peptides were identi�ed. Most were fragments of proteins associated with coagulation. To obtain biomarker models for RP which consists of a few peptides
An empirical Performance evaluation and comparison of different classifiers on standard datasets

— Supervised Machine Learning (SML) refers to the mapping of the input variable to output variable using an algorithm. The correctness of learning is the number of correct predictions/classifications after training a model. This study shows the behavior of different supervised classifiers namely distance-based non-parametric algorithm KNN, statistical-based Naïve Bayes classifier, parametric method SVM, and Neural Network on linear and non-linear data. The performance of the algorithms is evaluated for accuracy score parameter on some authentic dataset repository of UCI Machine Learning Repository and compared to find out which algorithm is best suitable for which type of data sets. One of the important steps is also included before analyzing the accuracy score. This is calculated using Standard scalar libraries present within Anaconda software
Opleiding Informatica Functional profiling of Alzheimer’s through a consensus network

Alzheimer’s is a neurodegenerative disease, causing memory and cognitive skill problems. There is currently no effective drug or treatment and the assumption is that the number of patients with AD will only increase. Therefore research in AD is of great importance. The main objective of this research is to identify the molecular functions and biological processes which are differentially expressed in AD by means of a consensus network. Datasets from STRING, WikiPathway and KEGG have been combined into a consensus protein-protein interaction network (PPIN). Overlaying these networks with gene expression data allows for identification of differentially expressed proteins present in these PPINs. From these data the essential proteins APP, APOE, Beta-amyloid and Tau are not statistically significant and thus not differentially expressed, which was not as expected. After further research, the top three differentially expressed proteins are MPO, SELE and ERG1. With further analysis and functional enrichment analysis it can be concluded that the molecular function protein binding and the biological process response to organic substance contain the most differentially expressed proteins. Further research such as proteomics, GWAS and TWAS will allow to validate these gene expression results.
Determining what happens to the genes FOXP3, ROR γ t, SOCS1, STAT3, STAT5, and SMAD3 in patients with ankylosing spondylitis who received anti-TNF therapy

Background/Objective: Ankylosing spondylitis (AS) is a common in�ammatory rheumatic disease that affects the axial skeleton, causing characteristic in�ammatory back pain. We aim to examine the genes FOXP3, ROR γ t, SOCS1, STAT3, STAT5, and SMAD3 in patients with ankylosing spondylitis who receive anti-TNF therapy to understand the progression of the disease in a clinically improved or failed response to anti-TNF treatment. Method: A prospective case-control study was conducted at Basrah Teaching Hospital in southern Iraq. Eighty-one AS patients were divided into two groups: 67 were treated with anti-TNF therapy; 14 were newly diagnosed patients as positive controls, and 65 were healthy individuals. Disease activity was assessed using the AS Bath Disease Activity Index (BASDAI). Conventional radiography and MRI are used to measure the severity of the disease. Blood samples were homogenized, and mRNA was isolated using a total RNA extraction kit. Reverse transcription (RT) was performed. The gene expression of ROR γ t, FOXP3, SOCS1, SAMD1, SMAD3, STAT3, and STAT5 was detected by implementing a real-timePCR system. Result: There was signi�cant downregulation of the FOXP3 gene in anti-TNF-treated AS patients and biologically naïve AS patients compared to healthy control people, which may be due to how the disease affects the expression and activity of the FOXP3 gene, which does not change with the type of therapy (P = 0.001). ROR γ t expression was higher in both established and newly diagnosed AS patients (p 0.001) than in healthy controls. The SOCS1 gene was expressed at a low level in patients with AS and positive control patients compared to the SOCS1 gene in healthy control individuals (p 0.780). STAT3 expression was lower in established and biologically naïve AS patients than in healthy subjects. Simultaneously, biologically normal AS patients had higher levels of STAT5 in this group. SMAD3 was underexpressed in established and biologically naïve AS patients compared to healthy subjects. Conclusion: The progression of AS in patients treated with anti-TNF therapy is linked to a secondary change in the expression of the genes FOXP3, ROR γ t, SOCS1, STAT3, STAT5, and SMAD3 that leads to the induction of exTh17cells
Brain MRI Technics Images Translation by Generative Adversarial Network

One of the most critical problems in medical imaging is having high-quality data on healthy and sick patients. Also, gathering and creating a useful dataset is very time-consuming and is not always cost-effective. Machine learning methods are the newest methods in image processing, especially in medical image processing for classi�cation, segmentation, and translation. GAN (Generative Adversarial Networks) is a class of machine learning frameworks that we consider a solution to image-to-image translation problems and augmentation. One of GAN's applications is generating more realistic data for training and validation to improve the performance of the algorithm and evaluation. In this paper, we propose a high-quality image-to-image translation framework based on CycleGAN in a paired and unpaired model of translation from T1 (or T2) to T2 (or T1) weighted MRI (Magnetic Resonance Imaging) of brain images. For evaluation, we used a dataset that consisted of T1 and T2 images acquired using the 3D structural MRI modality in four training and testing categories, which included 1113 structural MRI scans of large amounts of neuroimaging data.
Synthesis of a monodisperse well-defined core–shell magnetic molecularly-imprinted polymer prior to LC-MS/MS for fast and sensitive determination of mycotoxin residues in rice

Correction for ‘Synthesis of a monodisperse well-defined core–shell magnetic molecularly-imprinted polymer prior to LC-MS/MS for fast and sensitive determination of mycotoxin residues in rice’ by Sheng-Dong Pan et al., Anal. Methods, 2017, 9, 5281–5292.
Campylobacter fetus Invasive Infections and Risks for Death, France, 2000–2021

Campylobacter fetus accounts for 1% of Campylobacter spp. infections, but prevalence of bacteremia and risk for death are high. To determine clinical features of C. fetus infections and risks for death, we conducted a retrospective observational study of all adult inpatients with a confirmed C. fetus infection in Nord Franche-Comté Hospital, Trevenans, France, during January 2000–December 2021. Among 991 patients with isolated Campylobacter spp. strains, we identified 39 (4%) with culture-positive C. fetus infections, of which 33 had complete records and underwent further analysis; 21 had documented bacteremia and 12 did not. Secondary localizations were reported for 7 (33%) patients with C. fetus bacteremia, of which 5 exhibited a predilection for vascular infections (including 3 with mycotic aneurysm). Another 7 (33%) patients with C. fetus bacteremia died within 30 days. Significant risk factors associated with death within 30 days were dyspnea, quick sequential organ failure assessment score >2 at admission, and septic shock.
A FRAMEWORK FOR DEVELOPING SECURE INTERNET OF MEDICAL THINGS: A COMPREHENSIVE ROADMAP FROM AN ARTIFICIAL INTELLIGENCE PERSPECTIVE

The Internet of Medical Things (IoMT) has gained an extensive reputation in many applications within medical sectors. The late expansion of using these technologies has helped many organizations to progress well by delivering high-quality services. Such advancements and developments wouldn’t hide the fact that such technologies also have many risks associated with their usage. Such risks vary in their severity depending on many factors, including the type of services IoMT provides and the customers it serves. However, the most important risks these systems are lately facing are related to their security. Therefore, any IoMT has to be secure enough in order to gain the trust and credibility of its clients. Although the IoMT security issues have been considered in several studies, enough attention has not been given to the best practices for developing secure applications. In fact, not following a precise and well-structured framework for developing secure IoMT applications has lately resulted in many cyber incidents directed toward such IoMT applications. The novelty of this work is to develop a framework that resolves such issues from the early stages of development. The main purpose of this framework is to provide a roadmap consisting of several strategic approaches for developing secure IoMT applications that take into consideration the advancements in artificial intelligence. The framework will also guide IoMT developers on how to mitigate and detect vulnerabilities, and hence the cyberattacks associated with each layer of a specific IoMT, using relevant machine/deep learning methods.