Miracle-dz/UniFAR-FTUs huggingface dataset:
Rhamnocitrin Attenuates Ovarian Fibrosis in Rats with Letrozole-Induced Experimental Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) is a common endocrine-related cause of infertility in women and has an unknown etiology. Studies have shown that rhamnocitrin (Rha) exhibits positive effects on the reproductive system. This study investigated Rha's antifibrotic effects on PCOS rats and revealed its underlying mechanisms. Female SD rats were randomized into 4 groups (n = 8, each); the control group received tea oil by intraperitoneal injection and 1% w/v CMC by oral gavage; the PCOS group received letrozole (1 mg/kg); the PCOS+Rha group received letrozole and Rha (5 mg/kg); the PCOS+Met group received letrozole and Met (265 mg/kg) for 21 days. At the study end, Rha treatment restored letrozole-induced alterations in the relative ovarian weights, body weight, and relative weights of uterine and visceral adipose tissues. Histological observation showed that Rha ameliorates ovarian structure and fibrosis in PCOS. Administration of Rha reduced letrozole-induced metabolic dysfunction by ameliorating the levels of TC, TG, and HDL-C in the PCOS rats. Rha treatment also modulated the serum levels of sex hormones, which decreased T, E2, and LH and increased FSH in PCOS rats. In addition, Rha treatment modulated insulin resistance and increased gene expression of antioxidant enzymes (Cat, Sod2, Gpx3, Mgst1, Prdx3, Gsta4, Gsr, and Sod1) in the ovaries of the PCOS rats. Finally, Rha treatment appeared to increase the activity of PPAR-γ and inhibit the TGF-β1/Smad pathway in the ovaries of the PCOS rats. Our findings suggest that Rha significantly ameliorated metabolic disturbances and ovarian fibrosis in the PCOS rats. Rha perhaps is an effective compound for preventing ovarian fibrosis in the future.
A novel needle probe for deeper photoacoustic viscoelasticity measurement

We present for the first time, to the best of our knowledge, a needle probe for photoacoustic viscoelasticity (PAVE) measurements at a depth of 1 cm below the sample surface. The probe uses a gradient index rod lens, encased within a side-facing needle (0.7 mm outer diameter), to direct excitation light (532 nm) and detection light (1325 nm) focused on the sample, collecting and directing the returned detection light in a spectral domain low coherence interferometry system, which allows for obtaining optical phase differences due to photoacoustic oscillations. The feasibility of needle probe for PAVE depth characterization was investigated on gelatin phantoms and invitro biological tissues. The experimental results in an invivoanimal model predict the great potential of this technique for invivotumor boundary detection.
Antioxidant and Antibacterial Influences of some Plant Leaves Cell sap

Plant waste is of great importance from an environmental and economic perspective, and therefore they benefit from these secondary metabolites that these plant wastes contain, such as pomegranate leaves, moringa leaves, and olive leaves, which contain many important secondary metabolic products that play many important roles for the plant and also from terms of medical or nutritional roles. The total phenolic compounds in the cell juices of the studied plant leaves were estimated, and the results were as follows: Moringa leaf juice (MLE), olive leaf juice (OLE), and pomegranate leaf juice (PLE), respectively, (780, 698, 650 μg/g). Fractionation was carried out by HPLC to obtain the components of phenolic compounds from phenolic acids, phenols, or polyphenolic compounds "flavonoids". The evaluation of the activities of the studied plant juices for the antioxidant activity was carried out by two methods DPPH (2,2-diphenyl-1-picrylhydrazyl), and rancimat, which are three levels of concentrations of Moringa, olive, and pomegranate (200, 400 and 800 ppm) compared with BHT (Butylated hydroxytoluene) (200 ppm) and the results proved that for the three juices and the study examined the antioxidant activity because it contains phenolic compounds, which are attributed to this antioxidant activity. The antibacterial activity was also tested in some types of pathogenic bacteria, which are ( listeria spp – Bacillus subtitles – staphylococcus aureus ).
Dense connected convolution neural network for land cover classification

Hyperspectral Imaging is employed to monitor the earth regions on basis of spectral continuous data ranges initializing from visible wave infrared region to short wave infrared region of the electromagnetic spectrum. It authorizes the detailed recognition and classification of land cover on account of spectral feature space. Hyperspectral images seemed to be presented by employing traditional unsupervised and supervised classifier with regards to classification. Various problems seemed to cause Hughes phenomenon as it represents the curse of dimensionality issues. In spite of mitigating those challenges, a deep ensemble classification model seemed to be proposed in this work. It process the data features using various convolution layers of the network along modelling the activation function as a simple structure for classification of the hyperspectral data based on the spectral values using Softmax layer and error function to minimize the losses. Dense Connected Convolution Neural Network projected in this work as it has high potential to effectively classify the spectral features with learnt weights from one individual convolution layer to convolution layers. The main idea of Dense Convolution Neural Network is to produce discriminative classification results and to enhance the accuracy and diversity of a classifier simultaneously.
Length-weight relationship, growth pattern and condition factor of four indigenous cypriniform Schizothorax species from Vishav Stream of Kashmir Himalaya, India

The indigenous Schizothorax spp. in the valley of Kashmir are facing constant threats and decline in their overall population. The current aim was to analyse the comparative length-weight relationship (LWRs) and condition factor (K) of 350 specimens belonging to four Schizothorax spp. (S. plagiostomus, S. esocinus, S. labiatus and S. curvifrons) from the Vishav Stream of Kashmir Himalaya, India. The fish specimens were sampled for a period of one year from April 2018 to March 2019. The results revealed that the growth coefficient ‘b’ in all the four Schizothorax spp. was found very close to 3, indicating an isometric growth pattern. No significant difference in the ‘b’ values of four Schizothorax spp. was found when compared with the isometric value (t-test: p > 0.05). The mean value of the ‘K’ for S. plagiostomus, S. esocinus, S. curvifrons and for S. labiatus were 0.81 ± 0.07, 0.80 ± 0.08, 0.85 ± 0.08 and 0.88 ± 0.12 respectively. The mean condition factor did not vary across four species (ANOVA: p > 0.05). The present findings could serve as baseline information for the management, stock assessment and future studies of indigenous capture fishery resources of the Vishav Stream and other similar habitats.
Experiments with Externally Prestressed Continuous Composite Girders

Steel-concrete composite girders have attractive potentials when applied in bridge construction. The serviceability performance of continuous composite girders is becoming more and more a deterministic parameter in the design of this type of structures. An effective method for improving this performance is to apply prestressing to control or completely eliminate concrete deck cracking caused by static and time dependent actions. Little literature has been found addressing the experimental analysis of continuous girders prestressed by means of external deviated tendons. The current research aims to investigate the behavior of a double-span steel composite beam externally prestressed by means of continuous tendons in terms of cracking characteristics, load deflection response, and load carrying capacity. The efficiency of prestressing is evaluated by comparing the results to those of a non-prestressed beam with similar cross sections and spans.
Maternal reports of morbidity during the index ALSPAC pregnancy

Within the ALSPAC (Avon Longitudinal Study of Parents and Children) resource, information concerning the health of the mother during pregnancy is available from three sources: (i) computerised data collected by midwives after the birth of the baby, known as the STORK database; (ii) data abstracted by ALSPAC staff from detailed medical obstetric records, and (iii) reports by mothers during pregnancy, and shortly after the birth using structured questionnaires completed at home. In this Data Note we focus on source (iii), and detail the information obtained from these mothers concerning their health, signs and symptoms together with medications and supplements taken during pregnancy. We also describe how the data can be accessed.
Reducing loss and crosstalk in two-mode ridge waveguide bend by step-like thickness structuring

We proposed a simple method of reducing bend-related loss and inter-mode crosstalk in two-mode ridge waveguide by step-like thickness structuring of bent section. It is already known that the effect of bend can be compensated by linear variation of the waveguide thickness or effective index, however, fabrication of such waveguides requires complicated technologies, which limits mass applications of such structures. We show that the two-step like structuring of the ridge waveguide thickness is sufficient to significantly reduce pure bending loss, bend-related inter-mode crosstalk and excess loss at the interface between straight and bent waveguides sections. Based on the rigorous numerical simulation conducted using transformation optics formalism, we determined the thickness change required to compensate for bend-induced effects and confirmed effectiveness of the proposed approach.
Optimization of HD-sEMG-Based Cross-Day Hand Gesture Classification by Optimal Feature Extraction and Data Augmentation

Human–machine interaction requires accurate recognition of human intentions (e.g., via hand gestures). Here, we assessed the cross-day robustness of widely used hand gesture classification techniques applied to high-density surface electromyogram (HD-sEMG) signals (256 channels). Our evaluation covered techniques in each stage of the classification framework: first, 50 temporal-spectral-spatial domain features, second, 15 feature optimization techniques, and third, seven classifiers. Moreover, although HD-sEMG provides sufficient neuromuscular information, some of the channels may present low signal-to-noise ratio and should therefore be treated as outliers. Accordingly, we performed our evaluation with, first, all outlier channels retained, and second, removal of the features corresponding to poor-quality channels and substitution with interpolated values from neighbor channels. The impact of sliding window and data augmentation was also investigated. We examined the results on a 35-gesture classification task using HD-sEMG acquired from 20 subjects on two sessions in separate days. The results showed that interpolation of features from outlier channels significantly improved the performance in most cases. Use of a sliding window and of data augmentation contributed to a higher classification accuracy. For the classification of 11 selected gestures of common daily use, the support vector machine classifier achieved the highest classification accuracy of 91.9% in a cross-day validation protocol using an optimal combination of 13 features (each extracted from sliding windows), feature optimization by linear discriminant analysis, and data augmentation. Our work can serve as a technique-screening tool on cross-day applications of human–machine interactions.
Trace metal contents of autotrophic flagellates from contrasting open‐ocean ecosystems

Nano‐ and picophytoplankton are a major component of open‐ocean ecosystems and one of the main plankton functional types in biogeochemical models, yet little is known about their trace metal contents. In cultures of the picoeukaryote Ostreococcus lucimarinus, iron limitation reduced iron quotas by 68%, a fraction of the plasticity known in diatoms. In contrast, a commonly co‐occurring cyanobacterium, Prochlorococcus, showed variable iron contents with iron availability in culture. Synchrotron X‐ray fluorescence was used to measure single‐cell metal (Mn, Fe, Co, Ni, Zn) quotas of autotrophic flagellates (1.4–16.8‐μm diameter) collected from four ocean regions. Iron quotas were tightly constrained and showed little response to iron availability, similar to cultured Ostreococcus. Zinc quotas also did not vary with zinc availability but appeared to vary with phosphorus availability. These results suggest that macronutrient and metal availability may be equally important for controlling metal contents of small eukaryotic open‐ocean phytoplankton.
Effect of Feeding High-alpha Linolenic Acid Flaxseed Oil to Broilers and Layers on Liver Biosynthesis of Total Very Long Chain Omega-3 Fatty Acids

Omega-3 fatty acids (n-3 FA) are known to possess beneficial effects on human health especially the long chain members (>20C; VLC n-3 FA). High- α linolenic acid flaxseed oil (FLAX oil) is known to be the richest plant source with n-3 FA (58% ALA vs 50% in regular flaxseed oil). Broilers and layers were fed FLAX oil in order to assess their ability to enrich the breast tissues with n-3 FA. In the broilers experiment, FLAX oil was added at a level of 2.25% of the diet while in laying hens, was added at 4% of the diet. The growth performance was not affected by the dietary treatments in both broilers and layers. The fatty acid profile of the liver was affected by the dietary treatments where the total n-3 FA was higher in laying hens, but the total VLCn-3 FA was greater in broilers.
Deep Mutual Information Subspace Clustering Network for Hyperspectral Images

Hyperspectral image (HSI) clustering has attracted a great deal of attention, owing to lower cost and higher application prospects. Deep subspace clustering has been proved to be an effective method to explore the sample relationship of HSI clustering. However, due to the complex distribution of HSI data, the problem of data cluster overlap occurs frequently. In the actual sample distribution, a sample may belong to multiple subspaces. The complex sample distribution brings challenges to subspace clustering. In this letter, we propose a deep mutual information subspace clustering (DMISC) network to find a more intuitive feature space for nonlinear subspace clustering. Technically, we maximize the mutual information between the samples and their generated features to enlarge the interclass dispersion and intraclass compactness. The deep subspace method can find a more suitable nonlinear intrinsic relationship, benefitting from the generated feature distribution. We evaluate DMISC on four HSI datasets and compare the performances with 12 popular clustering methods. The experimental results demonstrate that our method outperforms many prior unsupervised methods.
Model‐driven engineering of safety and security software systems: A systematic mapping study and future research directions

This article presents a systematic mapping study on the model‐driven engineering of safety and security concerns in software systems. Combined modeling and development of both safety and security concerns is an emerging field of research as both concerns affect one another in unique ways. Our mapping study provides an overview of the current state of the art in this field. This study carefully selected 143 publications out of 27,259 relevant papers through a rigorous and systematic process. This study then proposes and answers questions such as frequently used methods and tools and development stages where these concerns are typically investigated in application domains. Additionally, we identify the community's preference for publication venues and trends. The discussion on obtained results also features the gained insights and future research directions.
Flight Demonstration of Net Electric Charge Control of Aircraft Using Corona Discharge

This article reports on a flight experiment demonstrating the ability to control the net electrical charge of a small unmanned aircraft using ion emission from a corona discharge. The charging mechanism is based on the advection of ions produced by the corona discharge, leaving charge of the opposite polarity on the aircraft. An onboard high voltage power supply of up to $\pm$15 kV was remotely operated to control the level of charging. The high voltage terminal of the power supply was connected to two thin corona wires placed above the aft surface of the wing in the spanwise direction, whereas the low voltage terminal was connected to the conductive airframe. Using this strategy, electric potentials of up to −30 and +23 kV relative to the environment were acquired by the aircraft, using positive and negative corona discharges, respectively. The study addresses the dependencies with power supply bias and wind speed. Possible applications of net charge control include risk reduction of aircraft-triggered lightning strikes, as explored by the authors in prior work, as well as a means of compensating for precipitation static and other sources of charging.
Objective Evaluation Method of Broadcasting Vocal Timbre Based on Feature Selection

Broadcasting voice is used to convey ideas and emotions. In the selection process of broadcasting and hosting professionals, the vocal timbre is an important index. The subjective evaluation method is widely used, but the selection results have certain subjectivity and uncertainty. In this paper, an objective evaluation method of broadcasting vocal timbre is proposed. Firstly, the broadcasting vocal timbre database is constructed on Chinese phonetic characteristics. Then, the timbre feature selection strategy is presented based on human vocal mechanism, and the broadcast timbre characteristics are divided into three categories, which include source parameters, vocal tract parameters, and human hearing parameters. Finally, the three models of hidden Markov model (HMM), Gaussian Mixture Model-General Background Model (GMM-UBM), and long short-term memory (LSTM) are exploited to evaluate the timbre of the broadcast by extracting timbre features and four timbre feature combinations. The experiments show that the selection of timbre features is scientific and effective. Moreover, the accuracy of the LSTM network using the deep learning algorithm in the objective evaluation of the broadcast timbre is better than the traditional HMM and GMM-UBM, and the proposed method can achieve about 95% accuracy rate in our database.
Potential Application of Rhamnolipid-Silica Nanoparticle Complex for Enhanced Oil Recovery Studied with Molecular DynamicsSimulations

Biosurfactants are used as a solution to the use of synthetic surfactants in Enhance Oil Recovery (EOR) process which are not safe for environment. One of the requirements for biosurfactants in EOR is having the ability to reduce the value of the interfacial tension (IFT) to a minimum of 10-3 mN/m. To meet the requirement, the performance of biosurfactants can be improved by having it interact strongly with nanosized support material. In this study, the stability of the free monorhamnolipids (without silica) and the monorhamnolipids-silica nanoparticle complexes at the decane-water interface at 300 K was studied by in silico method. Component density analysis shows that monorhamnolipids and monorhamnolipids-silica nanoparticle complexes diffuse to the decane-water interface. Trajectory analysis of the simulation boxes showed that the complexes were more stable at the decane-water interface. Based on the interaction analysis of the hydrophilic groups as well as hydrogen bonding, the complexes stability on the interface is caused by the strong hydrogen interaction between monorhamnolipids and silica that have more stable properties at the decane-water interface. This causes the complexes are more effective in reducing the IFT of decane and water with a decrease of up to 1.6 mN/m.
Endocrine Late Effects in Childhood Cancer Survivors

Simple Summary Recent advances in cancer treatment have led to improved survival, with an exponential increase in sequelae among survivors. Around 50% of survivors will experience at least one hormonal disorder, with radiotherapy, hematopoietic stem cell transplantation, and alkylating chemotherapy being the most frequently related. Therefore, lifelong monitoring of childhood cancer survivors at risk is paramount. With this review, we describe in detail the most prevalent endocrine sequelae, considering new approaches such as proton beam therapy and immune-related endocrinopathies with the advent of precision oncology treatment. We hope to encourage oncologists and endocrinologists to develop early detection guidelines that minimize sequelae and have a positive impact on their quality of life. Abstract Childhood cancer management has improved considerably over the years, leading to a significant improvement in survival of up to 80%. However, childhood cancer survivors are at the highest risk of developing sequelae resulting from treatment, with endocrine complications being frequently observed among survivors. Multiple predisposing factors for endocrine sequelae have been identified, including age at diagnosis, treatment received, radiation, tumor type, and genetic polymorphisms, which could explain the individual predisposition to develop drug toxicity. Novel agents targeting tumor growth and immune checkpoint inhibitors have recently become the cornerstone for the treatment of different cancers, triggering a myriad of immune-related endocrinopathies. Endocrine sequelae of cancer therapy will have an impact on not only childhood but also on the survival and quality of life of these highly complex patients. Therefore, lifelong monitoring of childhood cancer survivors at risk of endocrine diseases is paramount. Encouraging oncologists and endocrinologists to develop new follow-up and early detection guidelines that minimize sequelae among these patients has become a priority, promoting integration between pediatric and adult units since many sequelae may manifest only after years to decades of follow-up.
Development and Validation of Simulation-Based Instructional Materials on Central Dogma of Molecular Biology for Senior High School

Despite the advantages proffered by technology in science education, little has been done to develop and validate innovative technology-based instructional materials on Central Dogma of Molecular Biology. It is imperative to test any newly generated instructional materials to validate their quality before being widely used. Hence, this study aimed to validate the developed simulation-based instructional materials on Central Dogma of Molecular Biology for Senior High School. This study utilized Research and Development (RD) design involving 50 Grade 12 STEM learners and 15 Biology education experts chosen through purposive sampling. Results revealed that experts strongly agreed that the developed simulation-based instructional materials on Central Dogma of Molecular Biology have content, technical, and instructional qualities. Meanwhile, the pretest and posttest results revealed that the learners demonstrated significant conceptual improvement from approaching proficiency to advanced mastery level in Central Dogma of Molecular Biology concepts. Further, the learners' pretest and posttest mean scores on the concepts differed significantly (p0.05). Therefore, it is recommended that the developed simulation-based instructional materials be used to complement in teaching Central Dogma of Molecular Biology.