Miracle-dz/UniFAR-FTUs huggingface dataset:
Differences among Obese versus Nonobese Patients undergoing total Laparoscopic Hysterectomy. A single Center Experience

Aim of the study: The main aim of this study is to analyze the influence of obesity over the intraoperative and post-operative evolution, in the context of total laparoscopic hysterectomy. Material and Methods: The study developed in the II nd Surgical Clinic of the “Pius Brinzeu” County Emergency Hospital Timișoara between 1st of January 2017 – 1st of January 2019 and it was applied to a general batch of 29 women patients diagnosed with benign pathology of the uterus and adnexa. Results: The general batch we considered necessary some type of categorization of the women patients based on the BMI: Group A: BMI = 19.5-24,9kg/m2; Group B: BMI = 25-29.9 kg/m2; Group C: BMI> 30kg/m2. A positive moderated co-relation between the number of the comorbidities and the BMI (r=0.493, p˂0.05). Somehow self-explanatory, it was emphasized the fact that group B and C which contained mostly patients with the BMI limit over the usual one, it was remarked a proportional increase of the comorbidities at the same time with the increase of the BMI. A strong positive co-relation between the BMI and the intervention time (p=0.047), therefore, those two being tied by proportional increase relation. In this way we obtained a statistically significant co-relation between BMI and the post-operative complications (p˂0.05) but with a low number of major complication on the general batch. Conclusions: By analyzing the comorbidities and the post-operative evolution, minor differences were encountered between the study groups, and it was demonstrated that there is no reason to see a high BMI level as an obstacle in performing TLH.
The Difference of Gut Microbiota and Their Correlations With Urinary Organic Acids Between Autistic Children With and Without Atopic Dermatitis

Autism is a kind of biologically based neurodevelopmental condition, and the coexistence of atopic dermatitis (AD) is not uncommon. Given that the gut microbiota plays an important role in the development of both diseases, we aimed to explore the differences of gut microbiota and their correlations with urinary organic acids between autistic children with and without AD. We enrolled 61 autistic children including 36 with AD and 25 without AD. The gut microbiota was sequenced by metagenomic shotgun sequencing, and the diversity, compositions, and functional pathways were analyzed further. Urinary organic acids were assayed by gas chromatography–mass spectrometry, and univariate/multivariate analyses were applied. Spearman correlation analysis was conducted to explore their relationships. In our study, AD individuals had more prominent gastrointestinal disorders. The alpha diversity of the gut microbiota was lower in the AD group. LEfSe analysis showed a higher abundance of Anaerostipes caccae, Eubacterium hallii, and Bifidobacterium bifidum in AD individuals, with Akkermansia muciniphila, Roseburia intestinalis, Haemophilus parainfluenzae, and Rothia mucilaginosa in controls. Meanwhile, functional profiles showed that the pathway of lipid metabolism had a higher proportion in the AD group, and the pathway of xenobiotics biodegradation was abundant in controls. Among urinary organic acids, adipic acid, 3-hydroxyglutaric acid, tartaric acid, homovanillic acid, 2-hydroxyphenylacetic acid, aconitic acid, and 2-hydroxyhippuric acid were richer in the AD group. However, only adipic acid remained significant in the multivariate analysis (OR = 1.513, 95% CI [1.042, 2.198], P = 0.030). In the correlation analysis, Roseburia intestinalis had a negative correlation with aconitic acid (r = -0.14, P = 0.02), and the latter was positively correlated with adipic acid (r = 0.41, P = 0.006). Besides, the pathway of xenobiotics biodegradation seems to inversely correlate with adipic acid (r = -0.42, P = 0.18). The gut microbiota plays an important role in the development of AD in autistic children, and more well-designed studies are warranted to explore the underlying mechanism.
Dietary Inflammation Index and Its Association with Long-Term All-Cause and Cardiovascular Mortality in the General US Population by Baseline Glycemic Status

Dietary inflammatory potential has been proven to be correlated with the incidence of diabetes and cardiovascular diseases. However, the evidence regarding the impact of dietary inflammatory patterns on long-term mortality is scarce. This cohort study aims to investigate the dietary inflammatory pattern of the general US individuals by baseline glycemic status and to estimate its association with long-term mortality. A total of 20,762 general American adults with different glycemic statuses from the National Health and Nutrition Examination Survey were included. We extracted 24-h dietary information, and the dietary inflammatory index (DII) was calculated. The outcomes were defined as 5-year all-cause and cardiovascular mortality. Compared with the normoglycemia group, individuals with prediabetes and type 2 diabetes had higher DII scores (overall weighted p < 0.001). Compared with low DII scores, participants with high DII scores were at a higher risk of long-term all-cause mortality (HR: 1.597, 95% CI: 1.370, 1.861; p < 0.001) and cardiovascular mortality (HR: 2.036, 95% CI: 1.458, 2.844; p < 0.001). The results were stable after adjusting for potential confounders. Moreover, the prognostic value of DII for long-term all-cause mortality existed only in diabetic individuals but not in the normoglycemia or prediabetes group (p for interaction = 0.006). In conclusion, compared to the normoglycemia or prediabetes groups, participants with diabetes had a higher DII score, which indicates a greater pro-inflammatory potential. Diabetic individuals with higher DII scores were at a higher risk of long-term all-cause and cardiovascular mortality.
MULTIMODAL EVENT DETECTION IN BIG DATA USING MULTI-LEVEL FUSION CLASSIFIER

Deep learning-based multimodal event detection using the Multi-Level Fusion Classifier (MLFC) model is proposed to overcome these complexities. The data are gathered from the multimodal data, including text, images and audio placed in the Hadoop platform for storage. The data are fed to MLFC, and the modals of text, image and audio are generated through various approaches. The text modal is generated through pre-processing, Enhanced Term frequency - Inverse document frequency (TF-IDF) and attention-based BiLSTM (Attn_BiLSTM). The image modal is generated through the Improved Capsule Network (I-CapsNet). The audio modal is generated by extracting low-level, mid-level and high-level features directed to Convolutional Neural Network _Opposition Salp swarm Algorithm (CNN_OSA). The extracted features are fused through Deep FF (Feature Fusion) strategy, and the various events are classified through the SoftMax classifier. The overall accuracy obtained in classifying the multimodal events is 98.26% which outperforms better when compared to the existing approaches.
A GRAPH BASED APPROACH TO LEARNER PROFILING IN AN INTELLIGENT TUTORING SYSTEM

Learner profiling lays the foundations of the personalization that happens in adaptive educational applications and Intelligent Tutoring Systems (ITS). A learner’s level of knowledge on a topic is estimated from their performance on certain activities related to the topic. For this, researchers have devised many model extensions throughout the years that incorporate specific cognitive features into student profiling. In this paper, a new graph-based algorithm for learner profiling has been proposed that is able to adapt the course to the current knowledge level of the learner using the topic dependencies fed in by the subject experts and the past response data of learners who have taken this course in the past. This results in learner profiling with minimum number of assessment activities in the best case.
Linear Convergence of ADMM Under Metric Subregularity for Distributed Optimization

The alternating direction method of multipliers (ADMM) has seen much progress in the literature in recent years. Usually, linear convergence of distributed ADMM is proved under either second-order conditions or strong convexity. When both conditions fail, an alternative is expected to play the role. In this article, it is shown that distributed ADMM can achieve a linear convergence rate by imposing metric subregularity on a defined mapping. Furthermore, it is proved that both second-order conditions and strong convexity imply metric subregularity under reasonable conditions, e.g., the cost functions being twice continuously differentiable in a neighborhood. In addition, nonergodic convergence rates are presented as well for problems under consideration. Finally, simulation results are carried out to illustrate the efficiency of the proposed algorithm.
Shadows: Blockchain Virtualization for Interoperable Computations in IIoT Environments

In this work, we propose Shadows, a virtual blockchain (VC) for achieving parallel consensus and efficient management of data in industries by utilizing BC. Typically, industrial processes involve heterogeneous activities which require real-time consensus, managed execution, isolation, data sharing, accelerated computation, and efficient utilization of various computational resources such as CPU, RAM, and storage. Achieving these in real-time using a single conventional blockchain (BC) leads to the exertion of computational power. To achieve resource-efficient real-time consensus, we virtualize the nodes of the BC network and create different BC for various activities. Further, to virtualize BC and provide better access to data, we propose smart contracts liable for providing a unified view of a single BC, dynamically creating BCs, allocating resources to these, and making communication between the same. Through lab-scale experiments, we demonstrate that Shadows is capable of utilizing the resources efficiently and achieving real-time consensus. In particular, Shadows uses 18% CPU and 92% memory while reducing consensus time by 56%, compared to a single conventional BC. Shadows also accesses the data efficiently by utilizing smart contracts and dynamically balances the load by migrating the virtual nodes. Further, Shadows reduces the number of migrations to make the balance system by 67%.
AN EXTRACTION AND CLASSIFICATION BASED ON EMD AND LSSVM OF EPILEPTIC EEG

The epilepsy EEG signal with nonstationary and nonlinear characteristics is a typical electroencephalographic (EEG), which have been solved by the proposed method of using least squares support vector machine (LSSVM) as the classifiers and empirical mode decomposition (EMD) as the feature extraction methods to achieve epileptic seizure detection with signal analysis and processing. In this proposed method, EMD is used to select three intrinsic mode functions (IMF) with high correlation to replace the original signals, which has been employed to solve the nonlinear and nonstationary problems in feature extraction and infusion, and then, the feature can be employed to feed to the recognition engine named LSSVM, and its parameters is optimized by particle swarm optimization (PSO). The study uses publicly available EEG database from the University of Bonn (UoB), and there are 7960 EEG segments in the complete dataset, among which are nine recognition problems marked as Z-N, Z-F, Z-S, O-N, O-F,O-S N-S F-S and Z-O-N-F-S, the average classification accuracy of Z-N, Z-F, Z-S, O-N, O-F, O-S, N-S and F-S can be generally obtained as highly as 90%, the Z-O-N-F-S training set and test set classification accuracy are 98.8% and 88%, which had been used to verify the effectiveness and robustness of this proposed method on feature extraction, To the best of our knowledge, the excellent performance of the proposed method has shown that this method can be employed to track the patient’s healthy state and monitor the moment of epilepsy seizure.
Coexistence, Energy, and Trophic Cascade in a Three-Level Food Chain Integrating Body Sizes

Predation is a biological interaction that influences demographic patterns by modifying community structure. In the current ecological crisis, there is a need to better understand the conditions of coexistence between predators, prey and their resources. The body size is considered a key feature to explain community-scale phenomena, energetic, and evolutionary constraints. This raises the question of how species body size directly or indirectly affects the demographic patterns that enable coexistence. Considering the above, we conducted a theoretical study that implements a Rosenzweig-MacArthur type model, which represents a three-level chain that integrates body sizes and includes a Holling type I functional response. In this model, we characterize coexistence through body size-dependent net reproductive rates. Our results suggest that the body sizes of consumer species strongly affect the size-density relations and energy requirements. We obtain the negative relationship between body size and density of intermediate consumers and discuss the energy equivalence rule. Furthermore, larger predators have a more significant impact on the intensity of the trophic cascade than smaller predators. Finally, we discuss potential extensions and applications of our modeling approach.
A Combined Use of Rhizobacteria and Moringa Leaf Extract Mitigates the Adverse Effects of Drought Stress in Wheat (Triticum aestivum L.)

Less nutrient availability and drought stress are some serious concerns of agriculture. Both biotic and abiotic stress factors have the potential to limit crop productivity. However, several organic extracts obtained from moringa leaves may induce immunity in plants under nutritional and drought stress for increasing their survival. Additionally, some rhizobacterial strains have the ability to enhance root growth for better nutrient and water uptake in stress conditions. To cover the knowledge gap on the interactive effects of beneficial rhizobacteria and moringa leaf extracts (MLEs), this study was conducted. The aim of this experimental study was to investigate the effectiveness of sole and combined use of rhizobacteria and MLEs against nutritional and drought stress in wheat. Nitrogen-fixing bacteria Pseudomonas aeruginosa (Pa) (108 CFU ml–1) was inoculated to wheat plants with and without foliar-applied MLEs at two different concentrations (MLE 1 = 1:15 v/v and MLE 2 = 1:30 v/v) twice at 25 and 35 days after seed sowing (50 ml per plant) after the establishment of drought stress. Results revealed that Pa + MLE 2 significantly increased fresh weight (FW), dry weight (DW), lengths of roots and shoot and photosynthetic contents of wheat. A significant enhancement in total soluble sugars, total soluble proteins, calcium, potassium, phosphate, and nitrate contents validated the efficacious effect of Pa + MLE 2 over control-treated plants. Significant decrease in sodium, proline, glycine betaine, electrolyte leakage, malondialdehyde, hydrogen peroxide, superoxide dismutase (SOD), and peroxide (POD) concentrations in wheat cultivated under drought stress conditions also represents the imperative role of Pa + MLE 2 over control. In conclusion, Pa + MLE 2 can alleviate nutritional stress and drought effects in wheat. More research in this field is required to proclaim Pa + MLE 2 as the most effective amendment against drought stress in distinct agroecological zones, different soil types, and contrasting wheat cultivars worldwide.
Effect of Fans’ Placement on the Indoor Thermal Environment of Typical Tunnel-Ventilated Multi-Floor Pig Buildings Using Numerical Simulation

An increasing number of large pig farms are being built in multi-floor pig buildings (MFPBs) in China. Currently, the ventilation system of MFPB varies greatly and lacks common standards. This work aims to compare the ventilation performance of three popular MFPB types with different placement of fans using the Computational Fluid Dynamics (CFD) technique. After being validated with field-measured data, the CFD models were extended to simulate the air velocity, air temperature, humidity, and effective temperature of the three MFPBs. The simulation results showed that the ventilation rate of the building with outflowing openings in the endwall and fans installed on the top of the shaft was approximately 25% less than the two buildings with fans installed on each floor. The ventilation rate of each floor increased from the first to the top floor for both buildings with a shaft, while no significant difference was observed in the building without a shaft. Increasing the shaft’s width could mitigate the variation in the ventilation rate of each floor. The effective temperature distribution at the animal level was consistent with the air velocity distribution. Therefore, in terms of the indoor environmental condition, the fans were recommended to be installed separately on each floor.
Effect of Solution pH on the Photo-Oxidation of 4-Chlorophenol by Synthesized Silver-Zinc Oxide Photocatalyst

Due to its toxicity, 4-chlorophenol (4CP) must be removed from the wastewater before discharging into open water. In this work, ZnO and Ag-ZnO photocatalysts were prepared via a solvothermal method under mild conditions (150 °C), followed by calcination at 300 °C and then characterized. The addition of Ag resulted in a change of the ZnO morphologies, which exhibited wurtzite structure, from irregular to rod-like shape, lower bandgap energy, and a lower electron-hole recombination rate. The 0.6 Ag-ZnO catalyst showed the highest efficiency in the photooxidation of 4CP under UV irradiation. Molecular 4CP exists in acidic and near-neutral conditions (pH 4 and 6) and is stable towards UV irradiation. Photooxidation of 2.3 × 10–4 mol/L 4CP by 0.8 g of 0.6% Ag-ZnO resulted in 67% removal of molecular 4CP at pH 6 with a rate constant of 4.0 × 10–3 min–1. Under similar conditions, a complete photooxidation of the anionic 4CP was observed at pH 11 with a rate constant of 1.4 × 10–2 min–1. The holes and superoxide radicals are the species responsible for molecular 4CP photoooxidation, while hydroxyl radicals are the dominant species for anionic 4CP. The prepared Ag/ZnO photocatalyst exhibit good potential to efficiently oxidize 4CP in both acidic and alkaline conditions.
The Importance of Textbooks in Kinesiology

Physical education programs in the United States emerged in the late 1800s and early 1900s. Over time, physical education became the field of kinesiology with an established disciplinary base with multiple associated professions. Historical context is provided for five different eras. Textbooks, including those authored by National Academy of Kinesiology fellows, played an important role in the evolution of the field, providing direction, context, and content for both the subdisciplines and the professions. Arguments are offered for the value of textbooks as an important form of scholarship (the scholarship of integration), for the value of textbooks in providing visibility and real-world impact for the field of kinesiology, and for the value of associated textbook ancillary materials as teaching resources for faculty in institutions of higher learning.
Screening of Specific and Common Pathways in Breast Cancer Cell Lines MCF-7 and MDA-MB-231 Treated with Chlorophyllides Composites

Our previous findings have shown that the chlorophyllides composites have anticancer activities to breast cancer cell lines (MCF-7 and MDA-MB-231). In the present study, microarray gene expression profiling was utilized to investigate the chlorophyllides anticancer mechanism on the breast cancer cells lines. Results showed that chlorophyllides composites induced upregulation of 43 and 56 differentially expressed genes (DEG) in MCF-7 and MDA-MB-231 cells, respectively. In both cell lines, chlorophyllides composites modulated the expression of annexin A4 (ANXA4), chemokine C-C motif receptor 1 (CCR1), stromal interaction molecule 2 (STIM2), ethanolamine kinase 1 (ETNK1) and member of RAS oncogene family (RAP2B). Further, the KEGG annotation revealed that chlorophyllides composites modulated DEGs that are associated with the endocrine system in MCF-7 cells and with the nervous system in MDA-MB-231 cells, respectively. The expression levels of 9 genes were validated by quantitative reverse transcription PCR (RT-qPCR). The expression of CCR1, STIM2, ETNK1, MAGl1 and TOP2A were upregulated in both chlorophyllides composites treated-MCF-7 and MDA-MB-231 cells. The different expression of NLRC5, SLC7A7 and PKN1 provided valuable information for future investigation and development of novel cancer therapy.
Number of Bacteria in Saliva in the Perioperative Period and Factors Associated with Increased Numbers

Perioperative oral management is performed to prevent postoperative complications, but its indication and management method are unclear. This study aimed to investigate salivary bacterial counts pre-and postoperatively, and factors related to increased bacterial count postoperatively. We included 121 patients who underwent surgery under general anesthesia and perioperative oral management. The bacterial count in saliva was determined preoperatively, and first and seventh days postoperatively using the dielectrophoresis and impedance measurement methods. The relationships between salivary bacterial count and various variables were analyzed using one-way analysis of variance, Spearman’s rank correlation coefficient, and multiple regression analysis. The salivary bacterial count increased significantly on the first day postoperatively but decreased on the seventh day. Multivariate analysis showed that age (p = 0.004, standardized coefficient β = 0.283) and xerostomia (p = 0.034, standardized coefficient β = 0.192) were significantly correlated with increased salivary bacterial count preoperatively. Salivary bacterial count on the day after surgery was significantly increased in patients with a large number of bacterial counts on the day before surgery after preoperative oral care (p = 0.007, standardized coefficient β = 0.241) and postoperative fasting (p = 0.001, standardized coefficient β = −0.329). Establishing good oral hygiene before surgery and decreasing salivary bacterial count are necessary in patients with a high risk of postoperative surgical site infection or pneumonia, especially in older adults or postoperative fasting.