Miracle-dz/UniFAR-FTUs huggingface dataset:
RECORDS OF PHARMACEUTICAL AND BIOMEDICAL SCIENCES Therapeutic efficacy of Ganoderma Lucidum on Thioacetamide- Induced Hepatic Fibrosis through Inhibition of TGF-β1 signaling in Male Rats

The anti-fibrosis efficacy of Ganoderma lucidum (GL) was investigated on thioacetamide (TAA)-induced liver fibrosis. Experimental fibrosis was induced by (200 mg/kg TAA, i.p.) twice weekly for 6 weeks in male Sprague-Dawley rats. GL was administered to TAA rats, either as (250/500 mg/kg, i.p) daily for further 3 weeks. Repeated administration of TAA caused liver fibrosis evidenced by significant elevation of hepatic TGF-β1 accompanied by an increase in the hydroxyproline content, oxidative stress levels and liver biomarkers. Contrarily, GL treatment significantly reduced ALT, AST, total bilirubin, MDA, NO concentrations and restored SOD activity. H & E and Masson trichrome staining confirmed that GL suppressed liver fibrosis, inflammation and attenuated the histopathological alterations. GL also elicited a statistical decrease in TGF-β1 level and hydroxyproline content with a concomitant decline in NF-kB and α-SMA immunoexpression in the TAA treated rats. Furthermore, GL downregulated TNF-α and IL-1β levels in TAAtreated rats compared to the control group. Conclusion: GL possesses a pronounced protective activity against TAA-induced fibrosis in rats; It significantly inhibits oxidative stress, inflammation and diminishes fibrosis by: inhibiting NF-kB activation, reducing TGF-β mediated by PI3K-AKT pathway thus restoring the liver function, the effect was in a dose dependent manner.
Size‐Controlled Colloidal Pd(II) Catalysts for Electroless Ni Deposition in Nanolithography Applications

A new Pd(II) electroless metal deposition catalyst dispersion, PD2, prepared by quenching a PdCl 4 2 solution with HCl and excess NaCl following rapid hydrolysis at pH ∼ 7 and ∼0.8 mM NaCl is described. The precursors to the catalytic Pd(0) species are shown to be chloride-rich Pd(II) colloidal particles having negative surface charge by x-ray photoelectron spectroscopy, UV-visible spectroscopy, centrifugation, and chemical tests. The particles bind selectively and covalently at ligand-modified surfaces with complete surface coverage occurring for treatment times ≥2 min. Atomic force microscopy indicates that the average and maximum sizes of the bound particles are 9 ± 3 and 18 nm, respectively. A correspondingly narrow distribution (15 to 33 nm) of Ni particles of average size 21 ± 5 nm is obtained following metallization of catalyzed surfaces. The ability to control Ni particle morphology using PD2 is successfully exploited in the selective metallization of ∼15 nm features patterned by scanning tunneling microscopy. Metallization occurs with minimal distortion of feature geometries and no pattern degradation due to Ni overgrowth or bridging of adjacent features. Catalyst behavior is well described by a model in which domination of particle nucleation events and dispersion medium chemistry during colloid formation determine particle surface binding, stability, size, and dispersity
Photodegradation Products of Polycyclic Aromatic Hydrocarbons in Water and Their Amenability to Biodegradation

Saturated water solutions of anthracene, pyrene, benz[ a ]anthracene, and dibenz[ a,h ]anthracene were UV-irradiated in the presence of oxygen and their photodegradation products were identified. The products were then individually photolyzed. Several products of photolysis were identified chromatographically. Furthermore, the biodegradation of two photoproducts, 9,10-anthracenedione and benz[ a ]anthracene-7,12-dione, was studied separately and in the presence of the original polycyclic aromatic hydrocarbons (PAHs). The irradiation of anthracene first produced 9,10-anthracenedione and continuous illumination yielded additionally 1-hydroxy-9,10-anthracenedione, 1,4-dihydroxy-9,10-anthracenedione, 9-anthrone, and 1(3H)-isobenzofuranone. Photolysis of benz[ a ]anthracene produced benz[ a ]anthracene-7,12-dione and 1(3H)-isobenzofuranone. By irradiation of pyrene and dibenz[ a,h ]anthracene mainly diones of the original compounds were formed. In batch vial experiments, the biodegradation of 9,10-anthracenedione alone started with no lag phase whereas biodegradation of anthracene alone had a lag of 40 days. The lag for benz[ a ]anthracene biodegradation was, in the presence and absence of benz[ a ]anthracene-7,12-dione, 17 and 35 days, respectively.
An efficient methodology for the synthesis of 3-styryl coumarins

Foi desenvolvida a arilacao de Heck, regiosseletiva e altamente eficiente, de 3-vinil-6,7dimetoxicumarina, para a obtencao de 3-estiril cumarinas com bons a excelentes rendimentos. O aumento da conjugacao nos produtos sintetizados reflete na absorvância, revelando todos desvios batocromicos pronunciados e efeitos hipercromicos. Regioselective and highly efficient Heck arylation of 3-vinyl-6,7-dimethoxycoumarin has been developed to afford 3-styryl coumarins in good to very high yields. The increase in conjugation reflects on the absorbance of the synthesized compounds revealing all pronounced bathochromic shifts and hyperchromic effects.
Predicting the spatial distribution of soil organic carbon stock
in Swedish forests using remotely sensed and site-specific
variables

Abstract. The status of the SOC stock at any position in the landscape is subject to a complex interplay of soil-state factors operating at different scales and regulating multiple processes resulting either in soils acting as a net sink or net source of carbon. Forest landscapes are characterized by high spatial variability and key drivers of SOC stock might be specific for subareas compared to those influencing the whole landscape. Consequently, separately calibrating models for subareas (local models) that collectively cover a target area can result in different prediction accuracy and SOC stock drivers compared to a single model (global model) that covers the whole area. The goal of this study was therefore to (1) assess how global and local models differ in predicting the humus layer, mineral soil and total SOC stock in Swedish forests, (2) identify the key factors for SOC stock prediction and their scale of influence. We use the Swedish National Forest Soil Inventory (NFSI) database and a digital soil mapping approach to evaluate the prediction performance using Random Forest modelling calibrated locally for the northern, central and southern Sweden (local models) and for the whole Sweden (global model). Models were built by considering (1) only site characteristics which are recorded on the plot during NFSI, (2) remotely sensed variables and (3) both site characteristics and remotely sensed variables. Local models are generally more effective for predicting SOC stock after testing on independent validation data. Using remotely sensed variables together with NFSI data indicates that such covariates have limited predictive strength but that site specific variables from the NFSI covariates show better explanatory strength for SOC stocks. The most important covariates that influence the humus layer, mineral soil and total SOC stock were related to the site characteristic covariates and include the soil moisture class, vegetation type, soil type and soil texture. Future studies could focus in mapping these influential site covariates which have potential for future SOC stock prediction models.
NATIONAL INSTITUTE FOR HEALTH AND CARE EXCELLENCE INTERVENTIONAL PROCEDURES PROGRAMME Interventional procedure overview of platelet-rich plasma injections for knee osteoarthritis

s were excluded where no clinical outcomes were reported, or where the paper was a review, editorial, or a laboratory or animal study. Conference abstracts were also excluded because of the difficulty of appraising study methodology, unless they reported specific adverse events that were not available in the published literature. Patient Patients with osteoarthritis of the knee. Intervention/test Platelet-rich plasma injections as standalone therapy. Outcome Articles were retrieved if the abstract contained information relevant to the safety and/or efficacy. Language Non-English-language articles were excluded unless they were thought to add substantively to the English-language evidence base. List of studies included in the IP overview This IP overview is based on 2,717 patients from 3 systematic reviews and meta-analyses and 5 randomised controlled trials (RCTs). Other studies that were considered to be relevant to the procedure but were not included in the main extraction table (table 2) are in the appendix.
Analysis of Student Procrastinatory Behavior in Virtual Learning Environments Using Machine Learning

: Virtual Learning Environments (VLEs) are increasingly being used due to the uncertain global situation caused by COVID-19. Some major impacts of the pandemic are lockdowns and social distancing. This has led to academia taking measures to normalize the increased use of VLEs for teaching. However, this shift from face-to-face to online environments comes with many concerns—one of which is student procrastination. Procrastination is an observed student behavior of delaying tasks, which results in poor learning and can adversely affect student performance. Hence, is it essential to analyze student procrastination and determine the factors that cause this behavior whilst learning in VLEs. In this study, we present our findings on the impact of VLEs on student procrastination. We also analyze the performance of machine learning approaches to avoid manual intervention. We initially performed data collection, producing a dataset which was annotated by an expert, allowing us to visualize the pattern of student procrastination. Results confirmed the application of machine learning techniques for analysis for student’s behavior. The results demonstrated the effectiveness of supervised approaches with an accuracy of up to 83%. In contrast, unsupervised approaches do not seem appropriate for this task. We hope that future work based on this study will allow automatic data annotation based on a trained machine learning model. The findings of our work will help identify students prone to procrastinating and allow intervention to maintain their academic performance. The expected implication of the presented study is an improvement of educational practices, helping teachers and demonstrators to gain a better understanding of students’ behaviors.
RoboAssist: Simulation of an ROS based Robot for Assisting Old and Differently abled

-This paper presents an intelligent 7-DOF Android Robot to be used for assisting old and differently abled in homes and in their day to day lives. The robot utilizes a special OpenCV script that detects the host and registers them as master. The robot then continuously monitors the registered master and serves them as required. Some motions such as falling and fainting has been pre-recorded which when detected initializes the Emergency Service of the Robot. The open-source meta operating system ROS (Robot Operating System) has been used to develop the framework. The designed robot is simulated in Gazebo.
Serum Homocysteine as One of the Risk Factors of Cerebral Small Vessel Disease in Chinese Patients

Objective: This study aimed to determine the risk factors of cerebral small vessel disease (CSVD) from different variables including serum homocysteine (Hcy) in a group of Chinese patients. Methods: A total of 139 patients with CSVD admitted to the affiliated hospital of Xuzhou Medical University from July 2017 to July 2018 were enrolled. Fifty healthy individuals were selected as controls. According to the diagnostic criteria, the CSVD patients were divided into three groups, namely, lacunar infarction (LI) group (n=59), white matter lesion (WML) group (n=46), and LI+WML group (n=34). The serum Hcy levels of the three groups were observed and compared. Multivariate logistic regression was performed to determine whether a number of variables including serum Hcy level are the risk factors of CSVD. Results: Hypertension, systolic blood pressure (SBP), diastolic blood pressure (DBP), low-density lipoprotein cholesterol (LDL-C), triglycerides (TGs), fasting blood glucose (FBG), and Hcy were significantly higher in CSVD group than the control group (P < 0.05). The age, gender, SBP, platelet, TG, and Hcy were significantly different between the LI group, WML group, and LI+WML groups (P<0.05). The age and Hcy level of patients in LI+WML group were higher than those of the LI group and WML group, and the difference was statistically significant (P < 0.05). The level of SBP was higher in the LI group than the WML group (P < 0.05). The Hcy level of patients in the LI group was higher than that in the WML group, but there was no significant difference (P > 0.05). The platelet and TG were significantly higher in WML group than LI group and LI+WML group (P < 0.05). Controlling the influence of sex and age, multivariate logistic regression analysis revealed that the Hcy levels were correlated with the incidence of the CSVD. Conclusion: Serum Hcy level is a risk factor for CSVD. Regular detection of serum Hcy level and timely intervention may effectively prevent and control the occurrence and development of CSVD.
License Plate Localization for Low Computation Resources Systems Using Raw Image Input and Artificial Neural Network

License Plate localization using Computer Vision needs a lot of computation resources. Thus, it is hard to deploy it on small systems. This paper presents an efficient license plate localization method using raw image input and artificial neural network. This is achieved by eliminating feature extraction stage and try to use as minimum as possible neural network architecture. Raw image input in dataset is cropped and labelled manually from random car images and video frames. The minimum architecture of the model has only three layers and 32,770 neurons. This is feasible to be deployed in today most single chip systems. The results, from various experiments, yield more than 90% of localization accuracy. Keywords— computer and information processing, image analysis, image processing, object detection, license plate localization Abstrak— Nomor plat kendaraan bermotor yang diperoleh dengan menggunakan Computer Vision membutuhkan banyak daya komputasi. Hal ini menyebabkan implementasinya ke dalam sistem minimum yang sederhana menjadi tidak mudah. Dalam penelitian ini, dikembangkan sebuah metoda untuk mendapatkan plat nomor kendaraan bermotor yang effisien menggunakan masukan langsung tanpa ektraksi ciri dan jaringan saraf tiruan. Penghematan daya komputasi dicapai dengan cara menghilangkan tahap ekstraksi ciri dan penggunaan arsitektur jaringan saraf tiruan yang seminimum mungkin. Citra masukan diperoleh dengan cara memotong dan memberi label gambar mobil dan frame video yang diperoleh secara acak. Arsitektur minimum yang dihasilkan berupa model yang hanya terdiri dari tiga lapisan dan 32,770 neuron. Model ini cukup fisibel untuk diterapkan pada kebanyakan system on a chip yang ada pada saat ini. Tingkat akurasi model dalam menemukan lokasi nomor kendaraan dari berbagai eksperimen berhasil mencapai lebih dari 90%. Kata Kunci— pemrosesan informasi dan komputer, analisis citra, pemrosesan citra, deteksi objek, ekstraksi plat nomor kendaraan bermotor
Error sources in the force mode of the “PB2” Planck-Balance

The PB2 Planck-Balance is a table-top Kibble balance, that is designed for the calibration of class E2 weights in a range of 1 mg up to 100 g. This work presents typical systematic errors which have to be considered during the calibration and will show results for measurements with small masses.
Genetic Analysis of Diallel Crosses in Wheat under Drought and Normal Irrigation Treatments

Seven bread wheat genotypes were crossed in a7x7half diallel scheme in 2017/2018.Parents and their 21 F1 crosses were evaluated under normal and stress conditions during 2018/2019 in two field experiments. The results of analysis of variance were significant for all studied traits. The highest mean values were detected by parents P1, P1,P2, P3,P2 and p2 for plant height, spike length, No of spikes/ plant, 1000-kernel weight, biological yield/ plant and grain yield/ plant, respectively. While, the highest mean values were recorded with crosses P3xP5 for biological yield/ plant and grain yield / plant. Mean squares for both general (GCA) and specific (SCA) combining ability estimates were highly significant for most studied traits. The ratios between GCA and SCA exceeded the unity for all studied traits, except biological yield/ plant under drought, revealing that additive and additive x additive types of gene action are more important than non-additive gene action in controlling these traits. P6 exhibited positive and significant ĝi effects for biological yield/ plant. P7 gave positive and significant combiner for spike length, No of spikes/ plant and grain yield/ plant. The highest desirable SCA effects were obtained with P1 x P6, P1 x P7, P2 x P7, P3 x P5 and P4 x P7for grain yield/ plant which exhibited significant and positive ŝij effects Foreign Agricultural Service / USDA Office of Global Analysis http://www.pecad. fas.usda. gov (1 metric ton per hectare = 100 grams per square meter, 1 hectare (ha) = 10,000 square meters).
Experimental Detection of Preferred or Universal Reference Frame

The dimensional parameters of permittivity ε0 and permeability μ0 associated with empty space characterize the velocity of light propagation c in vacuum, thereby implying the notion of an Absolute reference frame with respect to which c is measured. Even before the null result of Michelson-Morley experiment, Physicists had persistently felt the necessity of detecting this Universal or Absolute reference frame. It was the failure of all attempts to detect a Universal reference frame that prompted Albert Einstein to declare the absence of such a frame and propounded his special theory of relativity. In this paper we have shown through a detailed analysis that by making use of modern advancements in technology, we can determine the absolute velocity of an object with respect to a Preferred or Universal reference frame in real time, with an accuracy of a few meters per second. It involves a precise measurement of propagation time of a few signal pulses. That means we can experimentally detect and establish an Absolute reference frame, which had been postulated to be non-existent in SR. With the experimental establishment of an Absolute reference frame, the hitherto discredited notion of Aether again comes into focus of scientific investigation.
Malaria: A Global Health Disparity Challenge from a Nursing Perspective

Malaria is a life-threatening disease that disproportionately impacts children under the age of five [1]. Globally, children under five constitute 67% of all malaria deaths [1]. Currently, inadequate education on malaria prevention and management is evident in both low-income countries such as Nigeria and high-income countries such as Canada, implying an urgent need for a greater effort to address this global issue [1-5]. The purpose of this paper is to highlight the impact of malaria education on children at risk of exposure to malaria. Specifically, this review will identify how countries, such as Canada, may learn from endemic countries, such as Nigeria, to tackle malaria from a social determinants of health approach. Since the promotion of global health and equity is a fundamental nursing mandate, this paper also aims to bring a nursing perspective to addressing malaria education.
Exploring the Impacts of Stakeholder Pressures and Green Manufacturing on Environmental, Operational and Financial Performance

Due to growing environmental concerns, organisations are subjected to pressures from various stakeholders to reduce their negative impact on the environment. As a result, concepts such as Green Manufacturing (GMfg) are gaining increasing attention. Since GMfg implementation requires significant resource investments, there is a need to investigate impacts on performance outcomes and provide suggestions for implementation strategies. This research explored the effects of market and regulatory stakeholder pressures on the adoption of GMfg practices (Environmental Management, product stewardship and process stewardship) and examined the impacts of GMfg on environmental, operational and financial performance. A multi-industry survey study conducted in 155 manufacturing companies in Europe showed that market pressure had a significant positive impact on the adoption of Environmental Management (EM), which positively affected financial and operational performance through improved environmental performance. Product stewardship was found to have a direct positive impact on operational performance. The impact of EM on product stewardship was mediated by process stewardship, suggesting a staged implementation of these three elements. Regulatory pressures were found to have a direct negative impact on environmental performance. Finally, a moderation analysis showed no significant effects of GMfg on firm performance, when groups of companies were compared based on the time that had passed since they first started implementing GMfg practices.
The Preparation and Structure of Platinum Metal Nanosheets between Graphite Layers

Platinum chloride−graphite intercalated compounds (PtCl4−GICs) with a stage three structure were produced by mixing platinum tetrachloride and graphite at 723 K under 0.3 MPa of chlorine atmosphere. Two-dimensional platinum nanosheets with a thickness of 2−3 nm and a width of 5−300 nm were formed between graphite layers by hydrogen reduction of PtCl4−GICs at 573 K. The sheets had a number of hexagonal holes and edge angles of 120°, owing to the limited aggregation of the intercalated platinum chloride molecules to platinum sheets along regular hexagonal nets of carbon atoms between graphite layers.
An efficient logistic regression and ant colony optimization-based object-oriented quality prediction

In this paper an efficient logistic regression and ant colony optimization-based object-oriented quality prediction has been presented. The dataset has been considered based on the object-oriented codes. The code considered here are completely equipped with object-oriented features for the complete analysis. The major parameters considered for the experimentation are class, object, inheritance and dynamic behavior. Class and objects have been considered for the class labels and memory requirements checking with the proper stack call and constructor invocation. Inheritance has been considered for the code reusability testing. Dynamic behavior has been tested for the runtime allocation. Then clustering algorithm is used for the parameter preprocessing and grouping based on the parameters. For data filtration chi-square testing has been applied. Then logistic regression and ant colony optimization (LR-ACO) have been considered for the final classification. Then F-Measure, Odd Ratio and Power have been considered for the analysis of the classification based on LR-ACO. The result after LR-ACO shows better accuracy as comparison to the previous methods.