Miracle-dz/UniFAR-FTUs huggingface dataset:
Histological and immunohistochemical study of the protective effect of virgin coconut oil on cyclophosphamide-induced immunotoxicity of the spleen and peyer’s patches

Introduction: Virgin coconut oil (VCO) is an edible oil extracted from the meat of mature coconuts. It is also known for its health and therapeutic benefits, mainly attributed to its polyphenols and medium-chain fatty acid contents The immunomodulatory effects of VCO have not been extensively investigated. The aim of the present study was to investigate the effects of VCO on cyclophosphamide (CY)-induced immunotoxicity of peripheral lymphoid tissues. Methods: Forty Wistar rats were divided into five groups of eight rats each. Group 1 served as the normal control, while the other groups were all given 10 mg/kg of CY orally once daily for 4 weeks. Group 2 received CY served as the negative control. Group 3 rats were treated with levamisole (LMS) for 6 weeks, while Groups 4A and 4B were given VCO at 10 mL/kg and 15 mL/kg, respectively, for 6 weeks. The spleen and ileum sections were subjected to routine histological examination and immunohistochemical evaluation for T and B lymphocytes. Results: Histologically, the spleen and Peyer’s patches (PPs) of the ileum exhibited a significant reduction in the lymphoid cellularity following daily administration of 10 mg/kg CY for 4 weeks.
BP Neural Network for Predicting the Heat Exchanger Performance and Pressure Drop Characteristics of Plate Heat Exchanger

The method of neural network was used to establish a new model of predicting the heat exchanger performance and pressure drop characteristics of plate heat exchanger.The function fitting ability of BP neural network was utilized by fitted specific isoperimetric,such as nominal plate area,plate thickness,chevron depth,normal pitch,plate chevron angle,and so on.This method was used to predict the heat exchanging modulus K,pressure drops of both cold and hot sides and rule equation in plate heat exchangers.It provided a new higher precision method for evaluating the synthesis performance of plate heat exchanger.
The dark side of I2P, a forensic analysis case study

ABSTRACT File sharing applications, which operate as a form of Peer-to-Peer (P2P) network, are popular amongst users and developers due to their heterogeneity, decentralized approach and rudimentary deployment features. However, they are also used for illegal online activities and often are infested with malicious content such as viruses and contraband material. This brings new challenges to forensic investigations in detecting, retrieving and examining the P2P applications. Within the domain of P2P applications, the Invisible Internet Project (IP2) is used to allow applications to communicate anonymously. As such, this work discusses its use by network node operators and known attacks against privacy or availability of I2P routers. Specifically, we investigate the characteristics of I2P networks in order to outline the security flaws and the issues in detecting artefacts within the I2P. Furthermore, we present a discussion on new methods to detect the presence of I2P using forensic tools and reconstruct specific I2P activities using artefacts left over by network software.
The Role of Virtual Try-On Technology in Online Purchasing Decision

Today, with the intensive use of internet technologies, the concept of e-commerce became a focused channel to understand the customer behavior and purchasing processes for different product categories. Several methods are used to enable users to conclude their surf with the purchase and up-to-date technologies are contributed to positively nudging their purchasing tendencies. In this study, the impact of one of these technologies, virtual try-on (VTO), in terms of the customer experience was investigated. According to the results, the desire to use this technology again has been determined and it has also been seen that VTO technology had increased users’ purchase intention. Plus, two different user groups with different characteristics were identified according to their perceptions towards VTO technology. It is recommended that firms offering this technology seek to differentiate ways in their promotion and communication with designated groups
Efficient dead pine tree detecting method in the Forest damaged by pine wood nematode (Bursaphelenchus xylophilus) through utilizing unmanned aerial vehicles and deep learning-based object detection techniques

Abstract Pine wood nematode (Bursaphelenchus xylophilus) is an invasive pathogen in South Korea, where it has caused pine wilt disease (PWD) with extremely high mortality of native pine species (Pinus densiflora, Pinus thunbergii, and Pinus koraiensis). Since the disease spreads by its vectors, native pine sawyer beetles (Monochamus alternatus and Monochamus saltuarius), the cost of monitoring the expansion has been rapidly increasing. Furthermore, it is even more costly to eliminate new and isolated infections since unremoved infected trees act as new sources of infection through the preferred oviposition of the beetles on such trees. The methodology of combining unmanned aerial vehicle (UAV) and object detection based on deep learning provides the opportunity to solve such problems, as UAV with RGB camera can provide high spatial resolution aerial image and digital surface model (DSM), which can be used for object detection with excellent results. In this study, we evaluated the performance of this method to detect dead pine trees in PWD-damaged areas. In particular, to ensure low omission error of monitoring, YOLOv3 was employed for object detection as the model design is focused on minimizing the omission error. We also modified the model so that the positions and crown diameter could be estimated. Four detection models were trained using four different combinations between aerial images (R, G, B) and DSM from UAV. Among them, the model from RGB showed the highest performance (recall: 0.9909, precision: 0.8438) and was selected as the optimal model. Our results suggest that our method can contribute to low-cost and effective monitoring of the dead pine trees while maintaining low omission error, which is critical for PWD management.
Ionic Liquid@Metal-Organic Framework as a Solid Electrolyte in a Lithium-Ion Battery: Current Performance and Perspective at Molecular Level

Searching for a suitable electrolyte in a lithium-ion battery is a challenging task. The electrolyte must not only be chemically and mechanically stable, but also be able to transport lithium ions efficiently. Ionic liquid incorporated into a metal–organic framework (IL@MOF) has currently emerged as an interesting class of hybrid material that could offer excellent electrochemical properties. However, the understanding of the mechanism and factors that govern its fast ionic conduction is crucial as well. In this review, the characteristics and potential use of IL@MOF as an electrolyte in a lithium-ion battery are highlighted. The importance of computational methods is emphasized as a comprehensive tool to investigate the atomistic behavior of IL@MOF and its interaction in electrochemical environments.
Evaluation of entrepreneurial behavior of technology-based companies in stages of the business life cycle

Purpose: The purpose of this paper is to evaluate the entrepreneurial behavior of managers of technology-based companies in specific stages of the business life cycle.Design/methodology/approach: Structured questionnaire based on the entrepreneurial behavior characteristics was applied to the thirty-one managers of the technology-based companies mapped for the paper. The collected data were processed by the Hierarchical Process Analysis (AHP) technique in a multicriterial approach to measure the entrepreneurial behavior according stages of the business life cycle. Findings: The results of the paper show that the level of entrepreneurial behavior of managers follows the development of the company. Managers working in technology-based companies at later stages of the business life cycle showed more entrepreneurial characteristics. The results showed that the experience that the manager acquires as the company evolves influences his or her behavior and consequently the company's performance. Moreover, certain characteristics could be related to the particularities of each stage of the business life cycle. Originality: The results of this paper can provide managers with understanding of how entrepreneurial behaviors diversify according to the stage of the technology-based company. Since both entrepreneurial behavior and the stages of the business life cycle influence the performance of technology-based companies, the results provide important knowledge for managers to improve their businesses. These managers can use the contributions of the paper as a management practice throughout the stages of their existence, which may provide the adoption of more appropriate strategies, being a connection between the theory studied and the business practices.
ELECTRIC VEHICLE CHARGER MANAGEMENT SYSTEM FOR INTEROPERABLE CHARGING FACILITIES

This paper designs and develops a real-time charger management system which keeps collecting the status information from chargers and converts control messages from the total operation center to a command predefined for charger control. RF cards complete the service chain from electric vehicles to the operation center, making the information flow bidirectional. The extended coverage of the operation control over the charging infrastructure allows an easy payment for the charging fee, based on the membership management and personalized services. A web application is implemented on the digital map of the target city for users to retrieve necessary information from the system and find the best service and chargers. The massive amount of real-time charger monitoring data is being accumulated in the database, and big data analysis will allow us to make intelligent plans for future smart grid city services.
The Development of the NCEP Global Ensemble Forecast System Version 12

The Global Ensemble Forecast System (GEFS) is upgraded to version 12, in which the legacy Global Spectral Model (GSM) is replaced by a model with a new dynamical core - the Finite Volume Cubed-Sphere Dynamical Core (FV3). Extensive tests were performed to determine the optimal model and ensemble configuration. The new GEFS has cubed-sphere grids with a horizontal resolution of about 25-km and an increased ensemble size from 20 to 30. It extends the forecast length from 16 days to 35 days to support subseasonal forecasts. The stochastic total tendency perturbation (STTP) scheme is replaced by two model uncertainty schemes: the Stochastically Perturbed Physics Tendencies (SPPT) scheme and Stochastic Kinetic Energy Backscatter (SKEB) scheme. Forecast verification is performed on a period of more than two years of retrospective runs. The results show that the upgraded GEFS outperforms the operational-at-the-time version by all measures included in the GEFS verification package. The new system has a better ensemble error-spread relationship, significantly improved skills in large-scale environment forecasts, precipitation probability forecasts over CONUS, tropical cyclone track and intensity forecasts, and significantly reduced 2-m temperature biases over Northern America. GEFSv12 was implemented on September 23, 2020.
Deblurring X-ray Transmission Images Using Convolutional Neural Networks to Achieve Fast CT Scanning

X-ray computed tomography (CT) allows for visualization of the interior of solid objects in a non-destructive and non-invasive manner. However, producing high-precision measurements takes a long time because thousands of sharp transmission images are required to reconstruct CT volumes. To address this problem, we propose a CT measurement method based on Convolutional Neural Networks (CNNs) that yields sharp transmission images by deblurring blurry ones. In this method, ﬁrst, blurry images are obtained in a short measurement time, then they are deblurred by CNNs with ﬁne-tuning and integrated by linear interpolation. This method shortens the measurement time indirectly because the process related to the CNNs is fast with GPUs and the blurry images with low levels of noise intensity do not require a long time. Besides, the ﬁne-tuning may improve the output images’ sharpness. According to our experimental results, the proposed method is fast and can maintain the quality of data to a certain extent.
Fast development Extreme Programming (XP)

Developing software has always been a great challenge. Proof of this are the numerous methodological proposals that transgress in the various areas of the process. On the one hand, we find more traditional proposals focused on controlling the process, closely establishing the activities involved, the artefacts and tools, as well as the notations to be used. These approaches have proven effective and useful in countless projects, but have also exhibited problems in others. An accepted refinement is to include more activities, artefacts and constraints in the development processes, based on the weaknesses observed. However, the end result would be a much more problematic development process and may restrict the team's own ability to deliver the project. Another approach is to focus on other dimensions, such as human resources or the software product. Agile methodologies are based on this ideology, which place greater value on the individual, customer support and incremental software development, using very short iterations. This approach is proving its worth in projects with changing requirements and when there is a tendency to reduce development times, without neglecting the final quality of the product. Agile methodologies are setting trends in software production, and at the same time creating a deep debate between their followers and those who, due to certainty or distrust, do not perceive them as possible alternatives to traditional methodologies. This paper summarizes the emergence of agile methodologies, their values, principles and some comparisons with traditional methodologies. At the same time, eXtreme Programming (XP), the most popular agile methodology today, is described almost in cellular form.
Alignment-Augmented Consistent Translation for Multilingual Open Information Extraction

Progress with supervised Open Information Extraction (OpenIE) has been primarily limited to English due to the scarcity of training data in other languages. In this paper, we explore techniques to automatically convert English text for training OpenIE systems in other languages. We introduce the Alignment-Augmented Constrained Translation (AACTrans) model to translate English sentences and their corresponding extractions consistently with each other — with no changes to vocabulary or semantic meaning which may result from independent translations. Using the data generated with AACTrans, we train a novel two-stage generative OpenIE model, which we call Gen2OIE, that outputs for each sentence: 1) relations in the first stage and 2) all extractions containing the relation in the second stage. Gen2OIE increases relation coverage using a training data transformation technique that is generalizable to multiple languages, in contrast to existing models that use an English-specific training loss. Evaluations on 5 languages — Spanish, Portuguese, Chinese, Hindi and Telugu — show that the Gen2OIE with AACTrans data outperforms prior systems by a margin of 6-25% in F1.
In Vivo and In Vitro Evaluation of Ethanol Extract of Alphonsea sclerocarpa for Antidiabetic Properties in Wistar Rats Induction of diabetes mellitus in experimental animals

Objective : The purpose of the current investigation was to investigate in vivo and in vitro anti-diabetic potentials of ethanol extract of Alphonsea sclerocarpa leaves against alloxan-induced diabetes in albino rats. Methods : Two in vivo and one in vitro method were performed for the evaluation of ethanol extract for antidiabetic activity. For in-vivo evaluation, diabetes was induced in albino rats by administering a single dose of alloxan. The study was designed to test the acute effect of ethanol extract of Alphonsea sclerocarpa (EEAS) to reduce blood glucose in OGTT. The chronic study of 21 days was performed against diabetic rats and blood glucose was determined on the 1 st , 7 th , 14 th, and 21 st days. In chronic in vivo study, serum parameters insulin, urea, creatinine, total cholesterol, triglycerides, ALT, and AST were also estimated on the 21 st day to determine the effects of ethanol and ethanol extracts on complications of diabetes mellitus. Glucose uptake by hemidiaphragm assay was performed to test the ability of the extract to utilize glucose. Results: In Oral Glucose Tolerance Test, standard glibenclamide and ethanol extract (200 mg/kg and 400 mg/kg) treated animals have shown a significant reduction in blood glucose at 90 mins but at 120 mins. In the chronic model, the ethanol extract effectively reduced blood glucose levels (P<0.001) on the 14 th and 21 st day of study in therapeutic groups and the effect was comparable to that of standard. The extract could also significantly (P<0.001) reduce concentrations of SGOT, triglycerides, cholesterol, and urea in serum and significantly (P<0.001) increase the insulin level in blood which proves beneficial effects of the extract in diabetes. The change in concentrations of SGPT and urea was less significant (P>0.01). The presence of extract in glucose uptake assay could significantly increase the utilization of the glucose by rat hemidiaphragm. Conclusion: The ethanol extract of Alphonsea sclerocarpa possesses significant antidiabetic properties against alloxan-induced diabetic animals.
IS 3D TRANSTHORACIC PLANIMETRY STILL SUPERIOR OVER 2D ECHO IN RHEUMATIC MITRAL STENOSIS WHEN BOTH AREA AND HEMODYNAMIC PARAMETERS OF SEVERITY ARE IN QUESTION?

Objectives: The objective of the study was to compare transthoracic 3D planimetry to 2D planimetry in calculating mitral valve area along with correlation of various echocardiographic parameters of severity of mitral stenosis among these modalities. Methodology: Patients with (RMS) were enrolled. Keeping 2D PHT as reference mitral valve area (MVA) was calculated and it was compared to the results derived by transthoracic 2D and 3D planimetry. Agreement between the 2D and 3D methods was assessed by measuring the intraclass correlation coefficient (ICC). Results: 51 patients were included. 36 (70.6%) were females; mean age was 33 ± 6 years. Mean gradient was 14.5 ± 3.9 mmhg while mean Pulmonary artery systolic pressure (PASP) was 31.6 ± 6 mmhg. MVA’s derived by PHT, 3D planimetry, and 2D were 1.04 ± 0.24, 1.07 ± 0.24, 1.21 ± 0.27 cm2 respectively. 3D obtained areas were significantly lower compared to 2D (p< 0.001) and insignificantly greater from PHT (p = 0.18). 3D demonstrated best agreement with MVA PHT (95% limits of agreement: 0.67 to 0.92; ICC 0.84). MVA 3D planimetry and MVA 2D correlated well with PASP and mean pressure gradient but showed weak correlation with left atrium size. Conclusion: 3D planimetry derived mitral area compared to 2D echocardiography are more in line with PHT calculated area and correlates well to hemodynamic parameters of severity.
Measuring More to Learn More From the Block Design Test: A Literature Review

The block design test (BDT), in which a person has to recreate a visual design using colored blocks, is notable among cognitive assessments because it makes so much of a person’s problem-solving strategy “visible” through their ongoing manual actions. While, for decades, numerous pockets of research on the BDT have identified certain behavioral variables as being important for certain cognitive or neurological hypotheses, there is no unifying framework for bringing together this spread of variables and hypotheses. In this paper, we identify 25 independent and dependent variables that have been examined as part of published BDT studies across many areas of cognitive science and present a sample of the research on each one. We also suggest variables of interest for future BDT research, especially as made possible with the advent of advanced recording technologies like wearable eye trackers.
Molecular characterization and deployment of the high-temperature adult plant stripe rust resistance gene Yr36 ( WKS1 ) from wheat

: Stripe rust, caused by Puccinia striiformis f. sp. tritici is one of the most destructive fungal diseases of wheat. Virulent races that appeared within the last decade caused drastic cuts in yields. The incorporation of genetic resistance against this pathogen is the most cost-effective and environmentally friendly solution to this problem. However, race specific seedling resistance genes provide only a temporary solution because fungal populations rapidly evolve to overcome this type of resistance. In contrast, high temperature adult plant (HTAP) resistance genes provide a broad spectrum resistance that is partial and more durable. The cloning of the first wheat HTAP stripe rust resistance gene Yr36 ( Science 2009, 323:1357 ), funded by our previous (2007-2010) BARD grant, provided us for the first time with an entry point for understanding the mechanism of broad spectrum resistance. Two paralogous copies of this gene are tightly linked at the Yr36 locus ( WKS1 and WKS2 ). objectives study characterize Yr36 ( WKS) resistance mechanism and to identify and characterize alternative WKS genes in wheat and wild relatives. We report here that the protein coded by Yr36 , designated WKS1, that has a novel architecture with a functional kinase and a lipid binding START domain, is localized to chloroplast. Our results suggest that the presence of the START domain may affect the kinase activity. We have found that the WKS1 was over-expressed on leaf necrosis in wheat transgenic plants. When the isolated WKS1.1 splice variant transcript was transformed into susceptible wheat it conferred resistance to stripe rust, but the truncated variant WKS1.2 did not confer resistance. WKS1.1 and WKS1.2 showed different lipid binding profiling. WKS1.1 enters the chloroplast membrane, while WKS1.2 is only attached outside of the chloroplast membrane. The ascorbate peroxidase (APX) activity of the recombinant protein of Tm t APX was found to be reduced by WKS1.1 protein in vitro . The WKS1.1 mature protein in the chloroplast is able to phosphorylate cDNA showed partial resistance to stripe rust, similar to the response conferred by TdWKS1 . Quantitative PCR indicated that the AcWKS2 is expressed 3-5 folds higher than the nonfunctional WKS2 in RSL65 and that the expression can be up-regulated by higher temperature and PST-inoculation. Furthermore, transgenic Bobwhite lines containing WKS1 were crossed with AcWKS2 Bobwhite transgenes. Plants with WKS1 , AcWKS2 , WKS1 × AcWKS2 (F 1 ), or no transgene were compared for the levels of resistance to stripe rust. Our results indicate that plants with WKS1 × WKS2 - Ae showed enhanced resistance to stripe rust than the plants with one gene alone.
MilliCloud: beyond vision PCD generation using millimeter-wave

Existing 3D Point Cloud Data (PCD) generation systems based on RGB-D and LiDAR sensors require robust lighting and unobstructed field of views of target scenes. So, they cannot work properly under challenging environmental conditions. Recently, millimeter-wave (mmWave) based imaging systems have raised a huge interest due to their ability to see-through obstacles and work in dark environments. But the resolution and quality of the PCDs from traditional imaging algorithms are very poor. This work proposes and preliminary validates MilliCloud, a deep-learning based system for generating high-quality indoor PCDs using handheld mmWave devices.