Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantitative Determination of Expression of the Prostate Cancer Protein (cid:1) -Methylacyl-CoA Racemase Using Automated Quantitative Analysis (AQUA) A Novel Paradigm for Automated and Continuous Biomarker Measurements

Despite years of discovery and attempts at validation, few molecular biomarkers achieve acceptance in the clinical setting. Tissue-based markers evaluated by immunohistochemistry suffer from a high degree of inter- and intraobserver variability. One recent advance in this field that promises to automate this process is the development of AQUA, a molecular-based method of quantitative assessment of protein expression. This system integrates a set of algorithms that allows for the rapid, automated, continuous, and quantitative analysis of tissue samples, including the separation of tumor from stromal elements and the subcellular localization of signals. This study uses the AQUA system to assess a recently described prostate cancer biomarker, (cid:1) -methylacyl-CoA-racemase (AMACR), and to determine the effectiveness of the quantitative measurement of this marker as a means for making the diagnosis of prostate cancer. Using a prostate cancer progression tissue microarray containing a wide range of prostate tissues, AQUA was directly compared to standard immunohistochemical evaluation for AMACR protein expression using the p504s monoclonal antibody. Both methods produced similar results showing AMACR protein expression to be stron-gest in the clinically localized prostate cancer, followed by the metastatic tumor samples. Benign prostate tissue was categorized as negative for most tissue samples by immunohistochemistry. localization of signals. Proof of principle experiments validated this approach using estrogen receptor and Her2-neu analysis in breast carcinoma and showed that this technology was able to discover relationships between expression and outcome that were impossible for con-ventional pathologist-based immunohistochemical methods. 6,7 Automated analysis and subcellular localization of (cid:2) -catenin in colon cancer identified two novel, prognos-tically significant tumor subsets, not detected by tradi-tional pathologist-based scoring. 6 From the perspective of screening novel biomarkers the system promises to make the process more objective and quantitative.
Active Learning for News Article’s Authorship Identification

Over time, the amount of textual data has increased drastically, especially due to the publication of articles. As a consequence, there has been a rise in anonymous content. Research is being conducted to determine alternative methods for identifying unknown text authors. To this end, a system has to be developed to accurately determine the author of unknown texts, given a group of writing samples. Active Learning is utilized in this study because it iteratively selects the most informative samples to include in the training set, which enables a more precise and accurate authorship identification approach with fewer examples. Makes it useful for analyzing the rising amount of anonymous content and identifying unknown text authors. This study proposes a novel approach that utilizes active learning (AL) based machine models, namely Logistic Regression (AL-LR), Random Forest (AL-RF), XGboost (AL-XGB), and Multilayer Perceptron (AL-MLP) for authorship identification. The proposed approach extracts valuable characteristics of the writer using the Term Frequency-Inverse Document Frequency (TF-IDF). This study’s selected comprehensive dataset, “All the news,” is divided into three subsets: Article 1, Article 2, and Article 3. We have restricted the dataset’s scope and selected the top 50 authors for our experimentation. The experimental outcomes reveal that the proposed AL-XGB model achieves superior performance on Article 1 of the “All the news” dataset. Further, the AL-LR model performed well on Article 2, and the AL-MLP performed well on Article 3. The results suggest using the proposed approach for authorship identification.
Health-related Quality of Life Measurement Tools for Lymphedema: A Review of the Literature

Background: Lymphedema can significantly affect patients’ health-related quality of life (HRQoL). Various quality of life scales have been developed to assess the extent of the disease burden. The purpose of this study is to review various HRQoL instruments that have been used in lymphedema studies and compare their qualities against the COSMIN checklist. Methods: A systematic literature review search was conducted for clinical lymphedema studies published between January 1, 1984, and February 1, 2020, using Pubmed database. All clinical lymphedema studies which used HRQoL instruments as outcome measures were identified. Results: One thousand seventy-six studies were screened—of which, 288 studies were individually assessed. Thirty-nine HRQoL instruments were identified in these clinical lymphedema studies. Of these, there are eight lymphedema-specific questionnaires that cover all HRQoL domains, all of which have been validated for use in lymphedema. We contrasted the two most popular questionnaires [LYMQOL and Upper Limb Lymphedema (ULL)-27] and compared their features. Conclusion: There is currently no ideal lymphedema HRQoL measurement tool available based on the COSMIN criteria. However, our review suggested that LYMQOL and ULL-27 are the most used and most validated instruments at present, but each has their own limitations. We recommend the use of LYMQOL and ULL-27 for future studies to allow direct HRQoL comparison to current literature. Further research is required to develop an optimal HRQoL questionnaire that can ultimately become the gold standard HRQoL instrument for lymphedema.
Sigmoid Function Model for a PWM DC–DC Converter

Considering the presence of switching devices, a pulse-width modulation (PWM) dc–dc converter is a piecewise smooth switching system that causes difficulties in stability analysis and controller design. Hence, a new modeling method that employs a sigmoid function is proposed to approximate the switching transition of a power device to construct a smooth continuous-time system model for a converter. This study adopts the equivalent circuit modeling method of a three-terminal switch to establish the sigmoid function model of the basic dc–dc converter and zero-current switching quasi-resonant dc–dc converter. The proposed sigmoid function models are simulated and experimentally verified. Furthermore, the simulation speed and accuracy of the proposed model are compared with the state-space averaged model. The results of this study are consistent with the Simulink circuit simulation results and experimental results. In addition, the proposed model improves accuracy and does not result in a significant loss in simulation speed. The model possesses various advantages: first, based on the model, the stability analysis and control theory for smooth continuous-time systems can be directly applied to PWM dc–dc converters; second, the model can present a unified description of the continuous conduction mode and discontinuous conduction mode for converters.
Identification of spatial variability and heterogeneity of the Culebra dolomite at the Waste Isolation Pilot Plant site

The Culebra dolomite is a heterogeneous, locally fractured medium whose transmissivity varies over seven orders of magnitude in the vicinity of the Waste Isolation Pilot Plant site in southeastern New Mexico, USA. The spatial distribution of hydraulic properties within the Culebra has been defined by performing 150 hydraulic tests at 41 well locations. Different scales of tests are performing 150 hydraulic tests at 41 well locations. Different scales of tests are performed to provide data for different purposes. Small-scale tests such as drillstem tests and slug tests, and short, intermediate-scale pumping tests provide point data useful in developing initial parameters for numerical modeling. Large-scale pumping tests provide information on the distribution of fractures between widely spaced wells, and also provide data for model calibration. Tracer tests provide data on transport mechanisms needed for transport modeling. 16 refs., 7 figs.
MicroRNA-21a-5p-modified macrophage exosomes as natural nanocarriers promote bone regeneration by targeting GATA2

Abstract Bone immune responses based on macrophages are critical in the osteogenesis of bone abnormalities. In general, M2 macrophage facilitate the promotion of osteogenesis, as well, M1 macrophage play an important role in early bone healing, as confirmed by previous studies. However, it is not clear how M1 macrophage are involved in the bone immune response. MiR-21a-5p is a highly expressed microRNA in M1 macrophage in contrast to M2. Therefore, the current work sought to ascertain the influence of M1 macrophage on bone healing via exosomal miR-21a-5p and the probable mechanism. We discovered that injecting M1 macrophage exosomes overexpressing miR-21a-5p into bone defect locations enhanced bone regeneration in vivo. Furthermore, by directly targeting GATA2, miR-21a-5p accelerated MC3T3-E1 osteogenic differentiation. Our findings showed that exosomal miR-21a-5p from M1 macrophage may be transported to osteoblasts and target GATA2 to enhance bone defect healing.
Mobile robotics in smart farming: current trends and applications

In recent years, precision agriculture and smart farming have been deployed by leaps and bounds as arable land has become increasingly scarce. According to the Food and Agriculture Organization (FAO), by the year 2050, farming in the world should grow by about one-third above current levels. Therefore, farmers have intensively used fertilizers to promote crop growth and yields, which has adversely affected the nutritional improvement of foodstuffs. To address challenges related to productivity, environmental impact, food safety, crop losses, and sustainability, mobile robots in agriculture have proliferated, integrating mainly path planning and crop information gathering processes. Current agricultural robotic systems are large in size and cost because they use a computer as a server and mobile robots as clients. This article reviews the use of mobile robotics in farming to reduce costs, reduce environmental impact, and optimize harvests. The current status of mobile robotics, the technologies employed, the algorithms applied, and the relevant results obtained in smart farming are established. Finally, challenges to be faced in new smart farming techniques are also presented: environmental conditions, implementation costs, technical requirements, process automation, connectivity, and processing potential. As part of the contributions of this article, it was possible to conclude that the leading technologies for the implementation of smart farming are as follows: the Internet of Things (IoT), mobile robotics, artificial intelligence, artificial vision, multi-objective control, and big data. One technological solution that could be implemented is developing a fully autonomous, low-cost agricultural mobile robotic system that does not depend on a server.
NeuroBridge: a prototype platform for discovery of the long-tail neuroimaging data

Introduction Open science initiatives have enabled sharing of large amounts of already collected data. However, significant gaps remain regarding how to find appropriate data, including underutilized data that exist in the long tail of science. We demonstrate the NeuroBridge prototype and its ability to search PubMed Central full-text papers for information relevant to neuroimaging data collected from schizophrenia and addiction studies. Methods The NeuroBridge architecture contained the following components: (1) Extensible ontology for modeling study metadata: subject population, imaging techniques, and relevant behavioral, cognitive, or clinical data. Details are described in the companion paper in this special issue; (2) A natural-language based document processor that leveraged pre-trained deep-learning models on a small-sample document corpus to establish efficient representations for each article as a collection of machine-recognized ontological terms; (3) Integrated search using ontology-driven similarity to query PubMed Central and NeuroQuery, which provides fMRI activation maps along with PubMed source articles. Results The NeuroBridge prototype contains a corpus of 356 papers from 2018 to 2021 describing schizophrenia and addiction neuroimaging studies, of which 186 were annotated with the NeuroBridge ontology. The search portal on the NeuroBridge website https://neurobridges.org/ provides an interactive Query Builder, where the user builds queries by selecting NeuroBridge ontology terms to preserve the ontology tree structure. For each return entry, links to the PubMed abstract as well as to the PMC full-text article, if available, are presented. For each of the returned articles, we provide a list of clinical assessments described in the Section “Methods” of the article. Articles returned from NeuroQuery based on the same search are also presented. Conclusion The NeuroBridge prototype combines ontology-based search with natural-language text-mining approaches to demonstrate that papers relevant to a user’s research question can be identified. The NeuroBridge prototype takes a first step toward identifying potential neuroimaging data described in full-text papers. Toward the overall goal of discovering “enough data of the right kind,” ongoing work includes validating the document processor with a larger corpus, extending the ontology to include detailed imaging data, and extracting information regarding data availability from the returned publications and incorporating XNAT-based neuroimaging databases to enhance data accessibility.
Haplotype analysis and marker development of five salt-tolerant–related genes in rice (Oryza sativa L.)

Salinity stress is a great threat to the growth and productivity of crops, and development of salt-tolerant crops is of great necessity to ensure food security. Although a few genes with natural variations that confer salt tolerance at germination and seedling stage in rice have been cloned, effective intragenic markers for these genes are awaited to be developed, which hinder the use of these genes in genetic improvement of salt tolerance in rice. In this study, we first performed haplotype analysis of five rice salt-tolerant–related genes using 38 rice accessions with reference genome and 4,726 rice germplasm accessions with imputed genotypes and classified main haplotype groups and haplotypes. Subsequently, we identified unique variations for elite haplotypes reported in previous studies and developed 11 effective intragenic makers. Finally, we conducted genotyping of 533 of the 4,726 rice accessions from worldwide and 70 approved temperate geng/japonica cultivars in China using the developed markers. These results could provide effective donors and markers of salt-tolerant–related genes and thus could be of great use in genetic improvement of salt tolerance in rice.
Serum Adiponectin Levels as an Independent Marker of Severity of Psoriasis: A Cross-Sectional Analysis

Background Adiponectin is an adipokine, having anti-inflammatory properties, the levels of which are reduced in metabolic syndrome. In psoriasis, it plays a preventive role by inhibiting the differentiation and proliferation of keratinocytes and decreasing the levels of the signature cytokine, IL-17. Aims and objectives To find a correlation between serum adiponectin levels and the severity of psoriasis and to compare these levels amongst patients with parameters of metabolic syndrome vs those without it. Materials and methods This was a cross-sectional observational study consisting of 60 cases of chronic plaque type psoriasis and 20 controls. Mild, moderate and severe disease was defined based on Psoriasis Area Severity Index (PASI). Serum samples were analyzed for fasting serum adiponectin levels. Results The mean serum adiponectin level among cases (16.07 ± 8.55 μg/ml) was significantly lower than controls (21.65 ± 8.07 μg/ml, P = .012). It was not only lower among cases with MetS (14.28 ± 7.95 μg/ml), but also in patients without MetS (17.35 ± 8.83 μg/ml). Serum adiponectin levels were negatively correlated to age, Body Mass Index (BMI), PASI, disease duration and Erythrocyte Sedimentation Rate(ESR). However, only the negative correlation with PASI (P = .000), duration (P = .005) and ESR (P = .010), was statistically significant. Conclusion Serum adiponectin is decreased in psoriasis, independent of metabolic syndrome and is negatively correlated with disease severity and duration. Limitations Analysis on a larger sample size and response to treatment could not be assessed.
Physical layer security based on full duplex and half-duplex multi relay assisted OFDM system

ABSTRACT Broadcasting in wireless channels causes security vulnerabilities since both the intended receiver and the eavesdropper may receive the information. Physical layer security (PLS) ensures the confidentiality of information transmitted wireless medium, even in the presence of eavesdroppers, without relying on cryptographic techniques implemented at higher layers. A PLS method for cooperative relay based Orthogonal Frequency Division Multiplexing (OFDM) with optimal relay selection and power optimization is proposed. In order to increase the overall system’s secrecy rate, a hybrid relaying and water filling based optimal power allocation is performed for multi-relay assisted OFDM-based wireless networks. By changing the eavesdroppers’ distances, the performance efficiency of the proposed system is verified. The analysis is carried out for both Full Duplex (FD) and Half Duplex (HD) systems and their performances are compared with existing equal power allocation technique. The proposed method combines relay selection and novel power optimization process to improve secrecy rate than the existing power allocation methods for both HD and FD systems.
A Data-Driven Maneuvering Target Tracking Method Aided With Partial Models

Target tracking plays a vital role in both civil and military fields. Traditional radar point (maneuvering) target tracking methods always require a prior kinematic model to match the target motion. In fact, it is hard to satisfy this requirement in practice, especially when sudden maneuvering happens for non-cooperative target tracking, which leads to an undesirable tracking peak error. Motivated by this, a new data-driven maneuvering target tracking method aided with partial models is proposed in this article to suppress this peak error. Here, since the historical target tracks include as many kinds of sudden maneuvers as possible, a data-driven learning-based network is trained to obtain high-precision state estimate when the target makes unpredictable maneuvers. Meanwhile, when the target has weak or no sudden maneuver, state estimate with satisfying accuracy is still obtained via prior kinematic models, where the Kalman filtering gain and model parameters are learned through the designed network to further promote its adaptivity. In particular, the kinematic modeling-based estimation also maintains the tracking robustness in the absence of representative training data. In addition, a discriminant network of evolution models is constructed to decide the dominant model (i.e. data-driven evolution model or one of the kinematic models) online based on radar measurements in the sliding window, which actually outputs the weights to make the final estimate as a weighted combination of the data-driven learning-based estimate and the kinematic modeling-based estimate. The proposed method is discussed in detail from the perspectives of tracking precision comparison, timeliness analysis, and noise analysis. The results show that the algorithm can ensure the timeliness of calculation and has a certain robustness under different noises. And most importantly, it has higher tracking precision when target maneuver happens suddenly.
Estimating the production of withaferin A and withanolide A in Withania somnifera (L.) dunal using aquaponics for sustainable development in hill agriculture

Introduction Humanity is suffering from huge and severe difficulties, including changes in climate, soil degradation, scarcity of water and the security of food and medicines, among others. The aquaponics system acts as a closed loop consisting of aquaculture elements and hydroponics, which may contribute to addressing these problems. The aquaponics method is quickly expanding as the requirement to increase the production of sustainable herbal products, including medicinal compounds and foods, in freshwater systems and replenish phosphorous reserves shrinks. Methods The current work is designed to increase the production of the antioxidants withaferin A and withanolide A in two varieties (Jawahar-20 and Poshita) of W. somnifera using the aquaponics technique. Total 100 seedlings (one month old) grown in soil initially were taken to be grown in aquaponics for a time period of 6 months.And 100 seedlings were placed in pots containing soil as control for study after six months. Results It was observed that the higher content of withaferin A was analyzed in the root and stem samples of Jawahar-20 and Poshita from the six-month-old plant of W. somnifera. The maximum content of withanolide A was examined in the root samples of the six month-old plants of Poshita (1.879 mg/g) and Jawahar-20 (1.221 mg/g). While the 6 month old Poshita seedling grown in soil recorded less withaferin A (0.115 ± 0.009b) and withanolide A (0.138 ± 0.008d). Discussion It is concluded that Poshita was found to be more promising for the enhanced production of withaferin A and withanolide A in the aquaponics system. Moreover, the root was observed as the best source for the production of withaferin A and withanolide A and the best age of the plant is 2 years for the production compounds in medicinal plants with futuristic perspective to hill agriculture integrated farming. compounds. Thus aquaponics can be an effective approach with enhanced yield of bioactive compounds in medicinal plants with futuristic perspective to hill agriculture and integrated farming.
ANALYZING THE SOCIO-ECONOMIC IMPACTS OF URBAN HIGHWAYS

THE METHODOLOGY IS DISCUSSED OF A SOCIO-ECONOMIC ANALYSIS OF THE INNER BELT HIGHWAY AND CONNECTED RADIALS IN THE BOSTON METROPOLITAN AREA. THE PLANNERS HAD TWO TASKS: (1) TO RECOMMEND ALIGNMENTS FOR SEVERAL ROUTES UNDER STUDY, AND (2) TO SUBMIT A PRIORITY PROGRAM OF HIGHWAY CONSTRUCTION. STEPS UNDERTAKEN IN THE ANALYSIS WERE: (1) ASSESSMENT OF PHYSICAL IMPACTS, A FIELD SURVEY, TABULATION, AND ACTOR ANALYSIS, AND (2) ASSESSMENT OF FUNCTIONAL IMPACTS, POPULATION AND EMPLOYMENT FORECASTS, POPULATION AND EMPLOYMENT DISTRIBUTIONS. UNDER THE LATTER CATEGORY, SEVERAL ASSUMPTIONS WERE CONSIDERED: NO HIGHWAYS - MEDIAN FORECAST, ALL HIGHWAYS BUILT SIMULTANEOUSLY -- HIGH ECONOMIC FORECAST, ALL HIGHWAYS BUILT SIMULTANEOUSLY - MEDIAN EMPLOYMENT FORECAST, ALL HIGHWAYS BUILT SIMULTANEOUSLY - LOW ECONOMIC FORECAST, AND HIGHWAYS CONSTRUCTED ACCORDING TO GIVEN PRIORITIES - MEDIAN ECONOMIC FORECAST.