Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy of Partially Purified Soybean Protease Inhibitor on The Development of Cotton Leafworm, Spodoptera littoralis (Bosid.)

Plant protease inhibitors) PIs) are one of the plant strategies to maintain favorable growth and survival. Soybean trypsin inhibitor is the most well-known of the plant serine proteinase. The present study aims to detect the inhibitory activity of two concentrations of partially purified trypsin inhibitors from seeds of soybean(Glycine max). Comparing the results of feeding larvae on partially purified soybean inhibitors with control, revealed that the larval weight reduction caused by soybean PI was noticed after seven days of treatment. The highest larval weight reduction was obtained due to treatment with SPI at levels SPI 30% and SPI 60%, and there was no significant difference between the two levels. Feeding larvae on SPI 60% caused higher larval mortality about 20% than the control followed by SPI 30% which caused 16% larval mortality. The pupation in treated larvae was delayed two days by comparing to control. The highest weight reduction in pupal weight was 3.5± 0.3 gm at SPI 60% compared with control. Besides, the pupation rate decreased from 83% at SPI 60% to 80% at SPI 30%. Also, the reduction in adult emergency % was recorded at SPI level 30% by 41% and at SPI level 60% by 16% compared with the control. Results reveal that soybean protease inhibitors inhibit the growth and development of S. littoralis, and may be used in integrated pest control strategies.
Hadoop MapReduce Performance Improvement In Distributed System - IRE Journals

-MapReduce is currently a parallel computing framework for distributed processing of large-scale data intensive application. The most important performance metric is job execution time but it can be seriously impacted by straggler machines. Speculative execution is a common approach for this problem by backing up slow tasks on alternative machines. Some schedulers with speculative execution have been proposed but they have some weaknesses:(i) they cannot calculate the progress rate accurately because the progress scores of the phases are set to constant values which may be totally different for heterogeneous environment, (ii) they define the stragglers by specifying a static threshold value which calculates the temporal difference between an individual task and the average task progression. To get the better performance, this paper proposes an algorithm identifying the stragglers by the more accurate progress of each job based on its own historical information and using a dynamic threshold value adjusting the continuously varying environment automatically.
A Comprehensive Review of Multimodal Medical Image Fusion Techniques

The multimodal image fusion is the process of combining relevant information from multiple imaging modalities. A fused image which contains recovering description than the one provided by any image fusion techniques are most widely used for real-world applications like agriculture, robotics and informatics, aeronautical, military, medical, pedestrian detection, etc. We try to give an outline of multimodal medical image fusion methods, developed during the period of time. The fusion of medical images in many combinations assists in utilizing it for medical diagnostics and examination. There is an incredible progress within the fields of deep learning, AI and bio-inspired optimization techniques. Effective utilization of these techniques is often used to further improve the effectiveness of image fusion algorithms.
Direct-writing of circuit interconnects on cellulose paper using ultra-long, silver nanowires based conducting ink

A highly stable conducting nanoink based on silver ultra-long nanowires (Ag ULNWs) was developed by a self-seeding polyol method with controlled doping of silver acetate for flexible electronics applications. Ionic diffusion followed by the reduction of Ag+ ions was found to have a significant role on the network conductivity by reducing the contact resistance of the conducting patterns. Crack-free, bendable conductive patterns could be produced by a direct-writing approach with superior conductivity. The electrical properties of the nanowire ink patterns have been analysed with respect to pattern length, time and temperature. A two dimensional (2D) rectangular resistive network model has been adopted to depict the role of network density, percolation density and contact resistance of these conducting nanowire networks. Further, various electronic arts and circuit interconnects were drawn on cellulose paper substrates using a direct-writing approach and their performances have been successfully manifested.
"One Firm Spot": The Role of Homework as Lever in Acquiring Conceptual and Performance Competence in College Chemistry

While learning at the K�12 level is a well-characterized process, how learning occurs in college is still underspecified. We report in this paper how different learning opportunities affect achievement in a large college chemistry class that makes use of authentic problem-solving activities supported by scenarios and virtual laboratories. Our study reveals that: (a) a significant portion of the learning takes place in the self-directed study the last few days before the exams; (b) authentic problem-solving activities have an important mediating effect in learning; (c) self-directed study and homework are the most relevant learning opportunities, explaining 48% of the course achievement in this course; (d) study and carefully planned homework activities can overcome the initial differences in prior knowledge.
A review on dynamic capacities in strategic management

Objective: The essence of strategic management in every enterprise is targeted at creating value and adding competitive advantage for food and beverage enterprise. In the rapidly changing and complex environment, dynamic capacities play an important role in achieving and sustaining competitive advantage. The main aim of this article is to identify the nature and components of dynamic capacities that have significant effect on strategic management. Research Design & Methods: The research method is based on both theoretical and empirical review of literature. The theoretical review of literature is focusing on dynamic capacities and strategic management. Findings: From the empirical review, it was revealed that dynamic capacities and strategic management are very associated as they are embedded in each other. Also, the organizations should take cognizance of innovation and efficient decision making which are revealed to be critical dynamic capacities that do enhance value creation and competitive advantage (strategic management). The aftermath of this is the inevitability of organizational profit. Contribution & Value Added: The organizations should focus on product innovation and efficient decision making to enhance value creation and competitive advantage over their competitors. Future studies may examine the performance of dynamic capacities on enterprise in a technology turbulent situation vis-a-vis the proposition of happenings in the Industry 5.0.
Short Update on Bisphenol A Exposure and Type 2 Diabetes: Focus on Workers

Type 2 diabetes mellitus (T2DM) is one of the most prevalent metabolic disorders, characterized by impaired metabolism of carbohydrates, lipids and proteins [1,2]. The prevalence of diabetes worldwide has grown from about 108 million adults (4.7% of population) in 1980 [3] to 463 million (9.3%) in 2019 [4] and it is estimated that it will rise to 700 million by 2045 [4]. Diabetes leads to hyperglycemia, which results from defective insulin secretion, insulin resistance or a combination of both [5]. The etiology of this type of diabetes involves different factors, with a clear genetic background but also linked to possible environmental chemical exposure [6,7].
Convenient and accurate discretized path integral methods for equilibrium quantum mechanical calculations

In the path integral representation of quantum theory, a few body quantum problem becomes a classical many body problem. To exploit this isomorphism, it becomes necessary to develop methods by which degrees of freedom can be explicitly removed from consideration. The interactions among the remaining relevant variables are described by effective interactions. In this paper, we present a general methodology to carry out the reduction in numbers of degrees of freedom. Certain path integral algorithms are shown to correspond to reference systems for the full isomorphic classical many body problem. The correspondence allows one to determine systematic corrections to the algorithms by low order perturbation approximations familiar in the theory of simple classical fluids. We show how to use discretized path integrals to compute rigorous upper and lower bounds to the free energy for nontrivial quantum systems, and we discuss how to optimize the upper bounds with variational theories. Several illustrative example.
On the Dynamic Modelling of a Novel Serial-parallel Robot

This paper addresses the kinematic and dynamic modelling of a novel serial-parallel robot arm which has been designed and implemented for hot press forging industry in Vietnam. The robot is capable of replacing workers for transferring hot and heavy billets between a heating furnace and a hydraulic press machine of a forging station. To meet all functional requirements of the forging process automation, the robot was designed with a particular architecture of five DOFs, which combines a serial-link robot arm and some local closed chain mechanisms. All the active joints of the robot are actuated by hydraulic cylinders. The control system of the robot was designed mainly based on the industrial PLC units, which also plays a role as a central control unit controlling all the components of the entire forging station. Since some local closed mechanisms are added to the main kinematic chain of the robot, the number of the generalized coordinates of the mechanical system is increased, and the mathematical modelling for the robot is more complex that requires a formulation of constraint equations with respect to the local closed chains. By using the Lagrangian formulation with Lagrangian Multipliers, the dynamic equations are first derived with respect to all extended generalized coordinates. Then a compact form of the dynamic equations is yielded by cancelling the Multipliers. Since the obtained dynamic equations are expressed in terms of independent generalized coordinates which are selected according to active joint variables of the arm, the equations could be best suitable for control law design and implementation. The simulation of the forward and inverse kinematics and dynamics of the arm demonstrates the motion behavior of the robot system.
Fungal mycotoxins and natural antioxidants: Two sides of the same coin and significance in food safety

Fungi have a long and intimate connection with humankind, particularly at the chemical level as a source of both harmful and beneficial compounds. Their worldwide occurrence in various food and feeds poses a major health threatening risk for human and animal and, as a consequence, mycotoxins represent an economic burden. Fortunately, not all fungal secondary metabolites are toxic to humankind such as; antibiotics, phytotoxines, enzymes and antioxidants, which represent the other side of the coin. Endophytes are now considered as an important component of biodiversity, and act as reservoirs of novel bioactive secondary metabolites, such as alkaloids, flavanoids, phenols, phenolic acids, quinones, steroids, saponins, tannins, terpenoids, isocoumarin derivatives, peptides and enzymes, beside their ability to produce the same or similar kind of compounds of their host plants. Today’s world challenge is ensuring the safety of food, which has been a major focus of international and national action over the last years. Legislative limits for a range of mycotoxins continue to develop worldwide, due to being carcinogenic to animals and humans, resulting in an increased number of official controls monitoring in the food supply chain deriving from national food safety plans and for food trade purposes. This review brings about the harmful (mycotoxins) and beneficial (antioxidants, antibiotics, enzymes) fungal metabolites in industrial and pharmaceutical applications. It also provides a perspective about mechanism of how can endophytic fungi metabolites play a reverse role as one of the main strategies of mycotoxin deactivation and prevention representing the other side of the coin.
Rotigotine protects dopaminergic neurons through dopamine D2 receptor
 against 6-hydroxydopamine

Dopamine (DA) receptor (D1 and D2-like receptors) agonists are known to affect expression levels of DA receptors. Rotigotine, a DA D2-like receptor agonist, has been developed for treating Parkinson’s disease (PD). However, its role in PD by acting through DA D2-like receptors has not been fully understood yet. The purpose of this study was to investigate neuroprotective effects of rotigotine through DA D2 and D3 receptors in 6-hydroxydopamine (6-OHDA) induced mouse model of PD. Expression level of tyrosine hydroxylase (TH) was examined using immunohistochemistry and Western blot analysis. Results revealed that unilateral injection of 6-OHDA into the midbrain caused significant loss of TH positive cells in the substantia nigra, whereas rotigotine inhibited such loss of TH cells in 6-OHDA-induced mouse model of PD. In vitro experiments demonstrated that rotigotine increased expression levels of TH against 6-OHDA-induced toxicity. The expression level of TH after treatment with L’741,626, a D2 receptor antagonist was decreased more than that after treatment with GR 103691, a D3 receptor antagonist. These results suggest that rotigotine can protect DA neurons against 6-OHDA induced toxicity and that the protective effect of rotigotine for DAergic neurons through a DA D2 receptor is stronger than that through a DA D3 receptor.
Climate change impacts on vegetation and agricultural drought in the basin of Panjshir River in Afghanistan

The agricultural drought, severely affecting human life, occurs unpredictably at different times with different intensities. The conventional methods for assessing drought often relay on indices obtained using meteorological data, but due to the low spatial coverage, incompleteness and inaccuracy of these data, meteorological indices cannot be considered as a comprehensive method. Therefore, it is suggested that remote sensing constitute more versatile approach, as it allows to assess the drought using the adequate spatial and temporal coverage for the study area. In the study, performed for the Panjshir river basin in Afghanistan, the 2010-2019 period is used to evaluate vegetation rate using NDVI data from MODIS. To calculate agricultural drought indices (DSI, VCI and TCI), May and June were selected, as the peak vegetation time occurs for these months. On the base of the remote sensing indicators it was shown that during the study period the drought conditions were normal in the region, except for 2011, 2017, and 2018, which were the driest years, and for 2019, which was the wettest year. Agricultural drought indices were compared to SPI index calculated using winter and spring precipitation data recorded at the meteorological stations. It was observed that the remote sensing indices showed the highest correlation with data from Kabul meteorological station, which is located at the same altitude and climate as the dense vegetation zone. Furthermore, the comparison showed that the ground precipitation data is characterized by higher amplitudes than the remote sensing data. From the above it steams that the vegetation in the Panjshir basin is influenced by both seasonal rainfall and rivers that continuously flood the area.
Simulating IEEE 802.15.6 based Wireless Body Area Network Interference using NS2 Platform for Indian Scenario

A recent data suggest that currently there are more than 485 million wearable sensors or gadgets users in the world and expected to increase in the near future. The communication technologies used in these gadgets are either Wi-Fi or Blue-Tooth. These wireless technologies have inherent limitations to be used in Health Monitoring. Also, these technology gadgets are not being considered and accepted by medical practitioners for e-health monitoring. To address this issue, in 2012 IEEE 802.15. 6 standard has been introduced to develop future of e-health monitoring which paves its way to Wireless Body Area Networks (WBAN) developments. India, being populated country, WBAN can be extremely useful technology to reduce burden on health care system. WBAN research has gained importance in India, where most of the research is focussed on sensor development and monitoring. The network level studies focusing on interference phenomenon are rare to find. In this paper, a focus is on developing an interference scenario in simulation environment. This interference study provided deep insight into the dynamics of co-existing WBANs where its adverse effects are observed on energy consumption, delay and throughput.
A SECURITY AWARE FOR PERSONAL DATA STORAGE IN CLOUD

- Recently, Personal Data Storage (PDS) has inaugurated a substantial change to the way people can store and control their personal data, by moving from a service centric to a user-centric model. PDS offers individuals the capability to keep their data in a unique logical repository, that can be connected and exploited by proper analytical tools, or shared with third parties under the control of end users. Up to now, most of the research on PDS has focused on how to enforce user privacy preferences and how to secure data when stored into the PDS. In contrast, in this paper we aim at designing a Privacy-aware Personal Data Storage (P-PDS), that is, a PDS able to automatically take privacy-aware decisions on third parties access requests in accordance with user preferences. The proposed P-PDS is based on preliminary results presented in, where it has been demonstrated that semi-supervised learning can be successfully exploited to make a PDS able to automatically decide whether an access request has to be authorized or not .
Newcastle disease virus Genotype VII in Chicken Flocks in Dakahlia Governorate and the Effectiveness of some Vaccines

Out of fifteen chicken flocks, ten were tested Newcastle Disease Virus (NDV) positive by RTPCR. Two selected NDV isolates from previously vaccinated flocks were selected for further investigation. The isolates were proofed negative for the presence of either infectious bronchitis virus (IBV) or avian influenza virus (AIV) genome. The mean death time and intracerebral pathogenicity indices as well as the presence of 112RRQKRF117 motif at the F gene cleavage site were indicative for the virulence of the investigated strains. The phylogenetic analysis showed that the velogenic genotype isolate clustered with published class II genotype VII and closely related to Middle East isolates. In vivo protection assay revealed that vaccination with live and/or inactivated ND vaccines induced sufficient protection ranged between 86.7 % and 100 % against morbidity and mortality as judged by HI titers and challenge test with NDV genotype VII.
Plant Leaf Diseases Prediction and Classification Using Optimization Based Convolution Neural Network

Plant leaf diseases and ruinous bugs are a significant test in the horticulture area. Quicker and an exact forecast of leaf diseases in plant could assist with building up an early treatment strategy while extensively decreasing financial misfortunes. Current progressed advancements in profound learning permitted analysts to amazingly improve the presentation and exactness of article identification and acknowledgment frameworks. A profound learning-based way to deal with recognize leaf illnesses in various plants utilizing pictures of plant leaves. The picture handling ventures for plant illness recognizable proof incorporate obtaining of pictures, pre-preparing, division and highlight extraction. Focus in predominantly on the most used order systems in illness location of plants, for example, Convolutional Neural Network, Support Vector Machine, KNearest Neighbor, and Artificial Neural Network. It has been seen from the examination that advancement Convolutional Neural Network approach gives better precision contrasted with the conventional methodologies. Optimization based CNN convolution neural network the proposed framework can viably recognized various sorts of diseases with the capacity to manage complex situations from a plant's region.
Phytochemical analysis and antibacterial activity of organic extract of Catharanthus RoseusL. flower against gram-positive and gram-negative bacteria

Antibacterial, Phytochemical, Antibiotics, Gram-positive, Gram-negative, Catharanthus roseus Plant extracts especially medicinal plants used as alternative treatment due to minimal side effect and danger to human health. The present study focuses on the phytochemical analysis and antimicrobial properties of medicinally recognized known plant of Catharanthus roseus. In this research, the bioactive secondary metabolites and antimicrobial activities of organic extracts of C. roseus flowers parts were investigated. The phytochemical screening of both ethanol and ethyl acetate plant extracts revealed the presence of various secondary metabolites such as alkaloids, flavonoids, protein, phenol, saponins and other phytochemicals. However, agar well diffusion method was used for antimicrobial testing of organic extracts against multidrug resistant (MDR) foodborne Gram-positive (Staphylococcus hominis) and Gram-negative (Citrobacter freundii, Escherichia coli and Aeromonas caviae) bacteria. The study revealed that the flower extracts of C. roseus showed highest (15.5± 0.50 mm) antibacterial activity against Citrobacter freundii BTGE-K_4 but the lowest (5.67± 0.58 mm) antibacterial activity against S hominis BTGE-K_11. Moreover, the lowest minimum inhibitory concentration (MIC) value was 125 μg/mL which showed against the tested MDR bacteria. Moreover, this study supports the importance of using medicinal plants as an alternative source for the treatment of bacterial diseases and other pharmaceutical purposes such as preservatives due to minor side effects, cost effectiveness and development of resistance to antibiotics.
Development of narrative macrostructure in monolingual preschoolers in Germany and impact of socio-economic status and home literacy environment

The aim of this paper is to analyse the development of narrative macrostructure and the impact of socio-economic status (SES) and home literacy environment (HLE) on the narrative macrostructure of monolingual preschoolers in Germany when retelling and telling a story. The analysis of narrative macrostructure includes three components: story structure, story complexity, and story comprehension. Oral narratives were elicited via Multilingual Assessment Instrument for Narratives (LITMUS-MAIN). 198 monolingual children between age 4;6 and 5;11 participated (M=63 months, SD=5 months). The comparison of narrative macrostructure in three age groups (4;6 to 4;11 years, 5;0 to 5;5 years, 5;6 to 5;11 years) illustrate significant age effects in story structure, story complexity and story comprehension skills. There were weak significant positive correlations of some of these skills with aspects of socio-economic status and home literacy environment, for example between story comprehension skills and the educational background, the frequency and duration of the child’s exposure to books and the number of books in the household.