Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation into experimental toxicological properties of plant protection products having a potential link to Parkinson's disease and childhood leukaemia

Abstract In 2013, EFSA published a literature review on epidemiological studies linking exposure to pesticides and human health outcome. As a follow up, the EFSA Panel on Plant Protection Products and their residues (PPR Panel) was requested to investigate the plausible involvement of pesticide exposure as a risk factor for Parkinson's disease (PD) and childhood leukaemia (CHL). A systematic literature review on PD and CHL and mode of actions for pesticides was published by EFSA in 2016 and used as background documentation. The Panel used the Adverse Outcome Pathway (AOP) conceptual framework to define the biological plausibility in relation to epidemiological studies by means of identification of specific symptoms of the diseases as AO. The AOP combines multiple information and provides knowledge of biological pathways, highlights species differences and similarities, identifies research needs and supports regulatory decisions. In this context, the AOP approach could help in organising the available experimental knowledge to assess biological plausibility by describing the link between a molecular initiating event (MIE) and the AO through a series of biologically plausible and essential key events (KEs). As the AOP is chemically agnostic, tool chemical compounds were selected to empirically support the response and temporal concordance of the key event relationships (KERs). Three qualitative and one putative AOP were developed by the Panel using the results obtained. The Panel supports the use of the AOP framework to scientifically and transparently explore the biological plausibility of the association between pesticide exposure and human health outcomes, identify data gaps, define a tailored testing strategy and suggests an AOP's informed Integrated Approach for Testing and Assessment (IATA).
A Review of Focused Crawler Approaches

Focused Crawler main aim is to selectively seek out pages that are relevant to pre-define set of topic rather than to exploit all regions of web. In this paper a review of focused crawler approaches have been presented which is classify in to five categories: Priority base crawler, Structured base crawler, Leaning base crawler, Context base crawler and Other focused crawler. Priority base crawler assign priority values to URL’s which have been crawled. Structured base crawler uses web pages structure to calculate the page relevance. Learning base crawler uses classifier to determine whether page is relevant or not. Context base crawler also considers context related with topic keyword. Other Focused Crawler can not be classified to one of the previously focused crawler approaches. Keywords-Crawler; Focused Crawler; Structured base crawler; Learning base crawler; Context base crawler
Impact of frailty on outcomes in elderly patients with acute myocardial infarction who undergo percutaneous coronary intervention.

AIMS Frailty is characterized by reduced biological reserves and weakened resistance to stressors, and is common in older adults. This study evaluated the prognostic implications of frailty at hospitalization in elderly patients with acute myocardial infarction (AMI) who undergo percutaneous coronary intervention (PCI). METHODS AND RESULTS We prospectively analyzed 546 AMI patients aged ≥80 years undergoing PCI from 2009 to 2017. Frailty was classified based on impairment in walking (unassisted, assisted, wheelchair/non-ambulatory), cognition (normal, mildly impaired, moderately to severely impaired), and basic activities of daily living. Impairment in each domain was scored as 0, 1, or 2, and patients were categorized into the following 3 groups based on total score: no frailty (0), mild frailty (1 to 2), moderate-to-severe frailty (≥3). The median follow-up period was 589 days. Of the 546 patients, 27.8% were frail (mild or moderate-to-severe), and this proportion significantly increased to 35.5% at discharge (P<0.001). Compared to non-frail patients, frail patients were older, less likely to be male, and had a higher rate of advanced Killip class. Major bleeding (no frailty, 9.6%; mild frailty, 16.9%; moderate-to-severe frailty, 31.8%; P<0.001) and in-hospital mortality (no frailty, 8.4%; mild frailty, 15.4%; moderate-to-severe frailty, 27.3%; P<0.001) increased as frailty worsened. After adjusting for confounders, frailty was independently associated with higher mid-term all-cause mortality (hazard ratio, 1.81; 95% confidence interval, 1.23-2.65; P=0.002). CONCLUSIONS Frailty in AMI patients aged ≥80 years undergoing PCI was associated with major bleeding, in-hospital death, and mid-term mortality.
Comparison of Classification Algorithms to Predict Students’ Post Graduation Course in Weka Environment

— Decision Tree is the most prominent classification algorithm in Data Mining. It can be implemented through various algorithms like J48, Simple CART / CART, Random Tree, ID3 etc depending on the types of data and requirements of applications. Here in this paper we have compared different algorithms of decision tree induction on the basis of different parameters. In this paper, we have selected three algorithms for comparison which are theoretically better as compare to other decision tree induction algorithm. We compare these three algorithms using open source data mining tool Weka & present the result. We found that J48 classification algorithm works better for the Prediction of Post-Graduation Course than other Decision Tree Induction classification algorithms.
Verification and Innovation of Neighbor Positions in MANETs

-In this paper generally MANETs are self-configuring autonomous networks that do not need any central authority to control and coordinate the network. In this neighborhood discovery (ND) is the process of discovering the devices that are directly reachable for communication or in physical proximity. So it becomes a fundamental requirement and building block for various other applications. It is very easy to abuse ND and there by compromise the overlying protocols and applications. Thus, providing methods to mitigate this vulnerability and secure ND is essential. This paper uses the directional antenna algorithm called as scanning based direct discovery algorithm to discover the neighbors, and location awareness is an important asset in mobile systems and many protocols require knowledge of position of the participating nodes. To allow cooperative working of the variety of distributed protocols we use trust system to provide the trust level of various nodes, thereby enhancing the cooperation amongst the nodes. This paper uses distributed hybrid trust algorithm and as well uses relationship maturity concept to compute the trust of the nodes. This paper demonstrates that Trust systems are better than already existing cryptographic techniques.
POWER OPTIMIZATION USING BODY BIASING METHOD FOR DUAL VOLTAGE FPGA

- Dual supply voltage is a mature low power technique that has already been widely used in application-specific integrated circuit (ASIC). It has also been introduced into field programmable gate array (FPGA) where non-critical blocks are configured to work at unsettled low voltage level, so as to reduce dynamic power. These supply voltage optimizations decreases the computation time, delay and power.In existing method a model design of Dual Voltage Supply for FPGA blocks to reduce the dynamic power in FPGA's. The particular model is designed to work in Vdd1 and others in Vdd2. The proposed system will be developed by using Dual Mode Logic Switches and Body Biasing method to reduce the power reduction ratio.The design can be simulated using back end low power tools available in Tanner EDA .
Engineering Computations Discovering Optimal Services with Multi Criteria based Analysis on Social Network Reviews

The social networks are build to share the user reviews, photos, videos and opinions on products and locations. The geographical location information are collected with smart phone based applications. The check in and user posting details are maintained under the Location Based Social Networks (LBSN). The huge volume of data values are processed with the big data environment. The big data values are processed with the support of the cloud resources. The user spatial parameters and review information are utilized in the service rating prediction operations. The Location Based Rating Prediction (LBRP) algorithm is applied for the service rating prediction process. The LBRP uses the three measurements for the prediction process. The user-item geographical connections, user-user geographical connections and interpersonal interest similarity measures are estimated for the rating prediction process. The user – item geographical connection indicates the distance between the user ratings and the user – item geographical locations. The user – user geographical connection indicates the user rating differences and the user – user geographical location distances. The optimal service discovery operations are carried out with user behavior discovery and service score index methods. The user behavior estimation process is carried out with multi activity centers. The service score estimation and index operations are performed with the attributes of the Point of Interests (POI). The user recommendation task is integrated with the system to suggest better services with reference to the user behavior and ratings. The user category, region and seasonal aspects are employed in the multi criteria based recommendation process.
A THREE PHASE GRID CONNECTED PHOTOVOLTAIC INVERTER WITH DC CURRENT SUPPRESSION FEATURE

The Photo Voltaic inverters without the isolation transformer become more attractive due to higher efficiency and lower weight and other offered mentioned advantages. However, it may have dc offset current while injecting generated AC to the grid which is critical to the power system. In this paper, a simplified control strategy of suppressing dc current injection to the grid connected for PV inverters is analyzed using MATLAB simulink software. It is based on the idea of accurately sensing the dc offset voltage of PV inverter output which is fed to Grid. Since dc component of the inverter output can be eliminated, dc injection to the grid can be effectively suppressed. To show the effectiveness of the proposed method FFT analysis has implemented to the proposed method.
Acupuncture for insomnia with short sleep duration: protocol for a randomised controlled trial

Introduction Insomnia with short sleep duration has a more serious negative impact on patient health. The existing literature suggests that medication therapy is more effective for this phenotype of insomnia compared with cognitive–behavioural therapy. However, the potential side effects of hypnotic medications hinder their clinical application. Acupuncture has been widely used in the treatment of insomnia, but it remains unclear whether it has therapeutic efficacy for insomnia with short sleep duration. The purpose of this trial is to evaluate the efficacy and safety of acupuncture for insomnia with short sleep duration. Methods and analysis This study is designed as a randomised, single-centre, single-blinded, placebo acupuncture controlled trial involving 152 participants. Eligible patients will be divided into two groups according to the objective total sleep time: insomnia with normal sleep duration group and insomnia with short sleep duration group. Then, patients in each group will be randomly assigned to two subgroups, the treatment group (acupuncture) and the control group (placebo acupuncture), in a 1:1 ratio with 38 subjects in each subgroup. The primary outcome is the Pittsburgh Sleep Quality Index and the Insomnia Severity Index. Secondary outcomes are actigraphy, the Beck Anxiety Inventory, the Beck Depression Inventory and the Fatigue Severity Scale. All adverse effects will be assessed by the Treatment Emergent Symptom Scale. Outcomes will be evaluated at baseline, post treatment, as well as at 1-week and 1-month follow-up. Ethics and dissemination This protocol has been approved by the ethics committee of Yueyang Hospital of Integrated Traditional Chinese and Western Medicine (no. 2019-17). Written informed consent will be obtained from all participants. The results will be disseminated through peer-reviewed journals for publications. Trial registration number ChiCTR1900023473; Pre-results.
Supplementation with Seabuckthorn Oil Augmented in 16:1n-7t Increases Serum Trans-Palmitoleic Acid in Metabolically Healthy Adults: A Randomized Crossover Dose-Escalation Study.

BACKGROUND In animal models cis-palmitoleic acid (9-hexadecenoic acid; 16:1n-7c), a lipokine, improves insulin sensitivity, inflammation, and lipoprotein profiles; in humans trans-palmitoleic acid (16:1n-7t) has been associated with lower incidence of type 2 diabetes. The response to dose-escalation of supplements containing cis- and trans-palmitoleic acid has not been evaluated. OBJECTIVES We examined dose-escalation effects of oral supplementation with seabuckthorn oil and seabuckthorn oil augmented in 16:1n-7t on serum phospholipid fatty acids (PLFAs). METHODS Thirteen participants (7 women and 6 men; age 48 ± 16 y, BMI 30.4 ± 3.7 kg/m2) participated in a randomized, double-blind, crossover, dose-escalation trial of unmodified seabuckthorn oils relatively high in 16:1n-7c (380, 760, and 1520 mg 16:1n-7c/d) and seabuckthorn oils augmented in 16:1n-7t (120, 240, and 480 mg 16:1n-7t/d). Each of the 3 escalation doses was provided for 3 wk, with a 4-wk washout period between the 2 supplements. At the end of each dose period, fasting blood samples were used to determine the primary outcomes (serum concentrations of the PLFAs 16:1n-7t and 16:1n-7c) and the secondary outcomes (glucose homeostasis, serum lipids, and clinical measures). Trends across doses were evaluated using linear regression. RESULTS Compared with baseline, supplementation with seabuckthorn oil augmented in 16:1n-7t increased phospholipid 16:1n-7t by 26.6% at the highest dose (P = 0.0343). Supplementation with unmodified seabuckthorn oil resulted in a positive trend across the dose-escalations (P-trend = 0.0199). No significant effects of either supplement were identified on blood glucose, insulin, lipids, or other clinical measures, although this dosing study was not powered to detect such effects. No carryover or adverse effects were observed. CONCLUSIONS Supplementation with seabuckthorn oil augmented in 16:1n-7t and unmodified seabuckthorn oil moderately increased concentrations of their corresponding PLFAs in metabolically healthy adults, supporting the use of supplementation with these fatty acids to test potential clinical effects in humans.This trial was registered at clinicaltrials.gov as NCT02311790.
Phosphate application influences the initial growth and accumulation of phosphorus and nitrogen in UMBU (Spondias

The objective of the current work is to evaluate the influence of phosphorus (P) on the accumulation of dry matter as well as the nitrogen (N) and P uptake by the umbu. The experiment was conducted under greenhouse conditions and seeds were placed in a 3-liter pot containing Yellow Latosol soil. The experimental design was entirely randomized, employing different P levels (0; 8; 16; 32 and 64 mg kg-1 of soil). The experiment was concluded 108 days post planting, and the characteristics of growth as well as the N and P uptake were evaluated. The P was found to be significant as it promoted an increase in stem diameter, which could improve grafting and establishment of the plants in the field. The least value of Total Dry Mass (TDM) was obtained when the plants were cultivated in the absence of P. Up to the dose of 32 mg of P the increase in the accumulation of Dry Mass by Absorbing Root (DMAR) was slow and gradual; however, between the doses of 32 and 64 mg of P, a substantial accumulation of dry mass in this plant region was observed. The deficiency of P significantly reduced the uptake of P and N, although it did not change the N: P ratio. Phosphorus fertilization allowed greater growth of the xylopodium, local where water and nutrients storage ocurrs; therefore, P fertilization may contribute to increased drought tolerance of this specie. The concept of P-fertilization is highly significant for the growth of the umbu. * Corresponding Author: Jailson Lopes Cruz  jailson.cruz@embrapa.br International Journal of Agronomy and Agricultural Research (IJAAR) ISSN: 2223-7054 (Print) 2225-3610 (Online) http://www.innspub. net Vol. 5, No. 1, p. 101-109, 2014
Reference Broadcast Time Synchronization in WSN

-Sensor nodes are deployed randomly in an Wireless Sensor Network (WSN). Sensor nodes should be arranged and communicate with ad-hoc manner in order to monitor the area/target . Energy Conservation is the most critical issue in sensor network due to size and weight of sensor Nodes. In this context synchronization is achieved by using Flooding Time Synchronization Protocol (FTSP). Speed of Propagation is slow because each node wait for waits for a given time period to propagate time information about Reference node. Rapid flooding will overcome these drawbacks and also increase the scalability of the network. Gradient Time synchronization Protocol (GTSP) is used to optimize the local skew in wsn. GTSP is a completely decentralized protocol since each sensor node synchronizes to its neighboring nodes . GTSP fails to maintain synchronize nodes in the network when external node crashes. Reference Broadcast Time Synchronization (RBSP) chooses the reference node by agreement algorithm and broadcast time information about the object in a network.
INVESTIGATING EFL STUDENT TEACHERS’ LEARNING PERFORMANCE, ATTITUDES AND PEER INTERACTION IN FLIPPED CLASSROOM

This mixed–method research design examined the influence of Flipped Classroom Intervention (FCI) on the learning performance of pre-service EFL female teachers, along with their related attitudes and peer interaction. The study sample consisted of thirty-eight pre-service EFL females in Saudi Arabia. The research design was a one-group pre-posttest, with data collected by means of twenty items gathered preand post-test to measure learning performance. In addition, the attitudes and peer interaction of the participants were explored through the use of two Likert-scale questionnaires and their reflections were examined by means of semi-structured focusgroup interviews. The results of the paired-samples t-test revealed a statistically significant improvement in participants’ learning performance (t=-7.459, p<.0005) in favor of the post-test. The results also revealed that the participants held positive attitudes towards FCI for all items within the three dimensions, giving highly confident responses regarding their views on peer interaction during FCI. Similarly, the findings of the semi-structured focus-group interviews revealed that FCI proved effective in raising the levels of: (1) the teacher’s performance; (2) the classroom environment; (3) teamwork; and (4) the students’ learning skills.
Summarization using Fuzzy Relational Clustering Algorithm

1 CSE Department, MIT College, Aurangabad, Maharashtra, India. 2 CSE Department, MIT College, Aurangabad, Maharashtra, India. Emailsakinariwala@gmail.com, kbhushanm@gmail.com ABSTRACT: The amount of stored data is increasing day by day. The automatic document summarization is used to solve the problem of information overload. The general technique to generate the summary is to use clustering, where sentence clustering plays vital role. For clustering sentence level text fuzzy relational clustering algorithm is used. It considers graphical representation of data and graph centrality is used as likelihood; with the help of Expectation Maximization framework it determines cluster membership values and mixing coefficients. The results of algorithm when applied to sentence clustering task show that it is able to identify overlapping clusters of sentences which are related semantically. The output cluster membership values of the algorithm can be used to generate extractive summary of text. Experimental results on quotation dataset show that the algorithm performs far better as compare to the K-medoids algorithm. The summary produce by the fuzzy relational clustering algorithm is able to capture the main idea of the original text and it provides useful information to users.
A Review on Privacy Preserving Data Mining Techniques

Data mining is a computational process of analyzing and extracting the knowledge from large useful datasets. Most data mining applications operate under the assumption that all the data is available at a single central repository, called a data warehouse. This poses a huge privacy problem because violating only a single repository’s security exposes all the data. Privacy preserving data mining techniques are introduced with the aim of extracting the relevant knowledge from the large amount of data while protecting the sensible information at the same time. People today have become well aware of the privacy intrusions of their sensitive data and are very reluctant to share their information. The major area of concern is that non-sensitive data even may deliver sensitive information, including personal information, facts or patterns. Several techniques of privacy preserving data mining have been proposed in literature. In this paper, we have studied all these state of art techniques. A tabular comparison of work done by different authors is presented. In our future work we will work on a hybrid of these techniques to preserve the privacy
Effective Range of Unmanned Aerial Vehicle (UAV) in the Malaysian Army Tactical Operations

Unmanned Aerial Vehicle (UAV) has been used in military application even during the conflicts in World War II. The utilization of UAV was further expanded during the Vietnam War and the role of “eye in the sky” has seen UAV became the ultimate ISTAR (Intelligence, Surveillance, Target Acquisition and Reconnaissance) tool for almost all conflicts. The evolution of UAV in various sizes and features will see UAV saturating the battlefield theater’s cloud in the future. This paper is to present the concept of operations of UAV in the military, segmented by units in battle to enable researchers to concentrate their research on types of UAV to suit the needs of the Malaysian Army. Using effective firepower range of all Malaysian Army arsenals and the commonality in terms of tasking, this study is able to establish the classes in terms of range needed for UAV in the Malaysian Army. From the observation, it is clear that the majority of the intended UAV will be operating in the less than 3 km combat radius.