Miracle-dz/UniFAR-FTUs huggingface dataset:
Occurrence and Distribution of Microbiological and Physico-Chemical Indicators in Ground Water Contaminated by Drainages, North India

The aim of this study was to undertake an assessment of the groundwater quality near city drainages of the Meerut region. Groundwater samples collected from different locations in winter and summer at increasing distances (5 to 70 m) from the drainages were assessed for their suitability for human consumption. The samples were analyzed for various bacteriological parameters including total viable count (TVC), total coliforms (TC), faecal coliforms (FC) and faecal streptococci (FS). Additionally, physico-chemical [pH, dissolved oxygen (DO), biological oxygen demand (BOD) and chemical oxygen demand (COD)] were assessed. Heavy metals like Al was detected in 83% and Cd, Cu, Zn in 75% and Pb in 41% water samples in winter while during summer season the percentage was slightly higher. Total viable as well as coliforms count exceeded the maximum permissible limits in most water samples irrespective of distance from drainages. The higher most probable number (MPN) values and presence of antibiotic resistant faecal coliforms and streptococci in the water samples suggest the presence of pathogenic microorganisms, heavy metals as well as organic load decreased with increase in distance.
Research on Wireless Coverage Performance of LTE-V2X in Urban Scenario

As a ubiquitous connection scenario, IoV is the infrastructure and technical path to realize intelligent transportation. With the development of communication technology, more and more entities are added to the communication network and become the elements of the network. How to reasonably deploy the devices according to the scenario characteristics has become the key point of the development of V2X technology. In this paper, comparison between Uu communication and PC5 communication in LTE-V2X as well as the classiﬁcation of LTE-V2X are ﬁrst introduced. Moreover, typical scenarios of V2X communication are analyzed. Finally, test and evaluation work for V2X network quality are conducted and recommendations are made for RSU deployment. It can be concluded that in the urban scenario, the effective coverage distance is about 400 to 500 meters. Surrounding trees and buildings have obvious shielding effect on LTE-V2X signals, and therefore, RSUs cannot cover the next intersection. In actual deployment, some roads should supplement more RSUs to satisfy the coverage requirements. Recommendations for deployment scheme in urban scenarios are also presented.
Review for Role of Nutraceuticals in Neurodegenerative Diseases

The neurodegenerative disorder NDDs includes Parkinson’s Disease (PD), Alzheimer’s Disease (AD), Huntington’s Disease (HD), prion disease; Motor Neuron Disease (MND) characterized by intense memory loss enough to interfere with social and occupational execution. It is the most general form of dementia, affecting more than 20 million people worldwide. Posed lifestyle changes are associated with drastically increased risk of chronic illness and diseases, posing a substantial healthcare and financial burden to society globally. The treatments of neurodegenerative disorder are through cholinesterase inhibitors or NMDAreceptor antagonists, while doubts remain about the therapeutic efficacy of these nutraceutical product such as fruits, vegetables, grains, meat, fish, eggs, minerals, carbohydrates, Flavonoids, Carotenoids, Crocin, Cyanidin, Luteolin, Quercetin and Kaempferol, Withanine, Asiatic Acid, Bhilavanol A and Bhilavanol B, vitamin B3, vitamin B9 or folate, vitamin B12, vitamin B6, vitamin D, vitamin E, and vitamin C, Omega-3 Fatty Acid Molecules, N-acetyl Cysteine, S-adenosyl Methionine, L-Tryptophan/5-HTP, Zinc and amino acid-based compounds, as the origin for every nutraceutical is different depending on the natural source and this phytochemical have been used in the treatments neurodegenerative diseases. The demand of nutraceuticals is widely increasing to combat neurological interventions. An association between food habits and the individual lifestyle with neurodegeneration has been manifested, thereby proposing the role of nutraceuticals as prophylactic treatment for neurological interventions. The current review covers some of the major neurological disorders and nutraceutical therapy in the prevention of disease.
Efficacy of bupivacaine infiltration on pain control in standard percutaneous nephrolithotomy: a meta-analysis of randomized controlled trials

Introduction: The efficacy of bupivacaine infiltration to control pain for standard percutaneous nephrolithotomy remains controversial. We conduct a systematic review and meta-analysis to explore the influence of bupivacaine infiltration on pain control for standard percutaneous nephrolithotomy. Methods: We search PubMed, EMbase, Web of science, EBSCO, and Cochrane library databases through January 2018 for randomized controlled trials (RCTs) assessing the effect of bupivacaine infiltration on pain control in standard percutaneous nephrolithotomy. Meta-analysis is performed using the random-effect model. Results: Six RCTs involving 337 patients are included in the meta-analysis. Overall, compared with control group for standard percutaneous nephrolithotomy, bupivacaine infiltration can significantly reduce VAS at postoperative 12 h (Std. MD=-0.87; 95% CI=-1.27 to -0.48; P < 0.0001) and 24 h (Std. MD=-0.78; 95% CI=-1.24 to -0.32; P=0.0008), as well as prolong the time of first an= algesic demand (Std. MD=1.02; 95% CI=0.43 to 1.62; P=0.0008), but has no remarkable influence on VAS at postoperative 6 h (Std. MD=-0.33; 95% CI=-0.81 to 0.15; P=0.18), doses of analgesic usage (Std. MD=-0.50; 95% CI=-1.24 to 0.24; P=0.18), operative time (Std. MD=0.13; 95% CI=-0.14 to 0.40; P=0.33), hospital stay (Std. MD=0.07; 95% CI=-0.30 to 0.45; P=0.70), nausea/vomiting (RR=0.52; 95% CI=0.27 to 1.00; P=0.05). Conclusions: Bupivacaine infiltration has important ability to alleviate the pain and prolong the time of first analgesic demand for standard percutaneous nephrolithotomy.
Anthropometric, biochemical, and nutritional risk factors for osteoporosis in Korean adults based on a large cross-sectional study

Background Osteoporosis a common bone disorder characterized by decreases in bone mass, tension, and strength. Although many previous studies worldwide have sought to identify the risk factors for osteoporosis, studies that simultaneously examine a variety of factors, such as biochemical, anthropometric and nutritional components, are very rare. Therefore, the objective of this study was to simultaneously examine the association of osteoporosis with biochemical profiles, anthropometric factors, and nutritional components in a large-scale cross-sectional study. Method This cross-sectional study was based on data from the Korea National Health and Nutrition Examination Survey (KNHANES VI-VII) from 2015 to 2018. Based on data from 16,454 participants, logistic regression was used to examine the association between various parameters in a crude analysis and in models adjusted for confounders. Results In men, osteoporosis was significantly associated with the anthropometric variables height and weight; the biochemical components hemoglobin, hematocrit, urea nitrogen and urine pH and creatinine; and the nutritional components total food intake, energy, water, protein, phosphorus, and kalium. However, these associations disappeared in adjusted model 2. In women, osteoporosis was significantly related to the anthropometric measures height, weight, and systolic blood pressure; the biochemical components hemoglobin, hematocrit and urine pH; and the nutritional components total food intake, water, calcium, phosphorus, and kalium. Most of these associations were maintained in the adjusted models. Conclusion Osteoporosis was linked to various anthropometric, biochemical and urine and nutritional components in Korean women, but the association between osteoporosis and risk factors differed according to sex.
Preparation and Characterization of Thermoplastic Elastomers/Plasticizer-Compatibilizer/Organoclay Nanocomposites by Reactive Extrusion System

Polymer layered silicate nano-composites were prepared in melt by reactive extrusion (25:1 21 mm Rondol twinscrew compounding line) using poly(ethylene-co-propyleneco-ethylidenenorbornene) terpolymer (EPDM) as a matrx polymer, PP-g-MA and poly[(maleic anhydride-alt-1-octadecene)-g-PEO (poly(MA-alt-OD)-g-PEO) as functionalized polymer compatibilizer-internal plasticizer, octadecyl amine-montmorillonite (ODA-MMT) and dimethyldidodecyl ammonium -MMT (DMDA-MMT) as reactive and non-reactive nano-fillers, respectively. The formation of nano structural fragments, polymer blend composition-properties (thermal behavior and morphology) was studied using FTIR, XRD, TGA-DTG and DSC analysis methods. It was found that intercalation/exfoliation degree of EPDM macromolecules significantly depends on the origin and content of organoclays. Better results were obtained for nanocomposites prepared in the presence of reactive organo-filler (ODA-MMT) and PEO grafted alternating copolymer. The results of FTIR (chemical structure) and XRD (physical structure and exfoliation degree) analyses indicate that amidization of anhydride copolymer with alkyl amine groups of organo-filler and esterification of alternating copolymer with α -hydroxyω -methoxyPEO occur in melt compounding in situ processing in the chosen extrusion conditions (barrel temperature: 120, 130, 140 and 145°C, twin-screw speed around 30-40 mrp). The glass-transition (Tg), melting (Tm) and recrystallization (Tc) temperatures strongly depend on the origin and content of organoclay and PEO-grafted copolymer-compatibilizer, respectively. Thermal behavior, crystallinity and thermostability of nanocomposites were significantly improved as compared with pristine EPDM terpolymer. *Corresponding author: Mostafa AD, Division of Nanotechnology and Nanomedicine, Institute of Science and Engineering, Hacettepe University, Beytete, Turkey, Tel: +903124444444; E-mail: cavusogluilayda@gmail.com Received July 13, 2017; Accepted July 20, 2017; Published September 13, 2017 Citation: Mostafa AD, Zakir MOR, Erdoğan A (2017) Preparation and Characterization of Thermoplastic Elastomers/Plasticizer Compatibilizer/ Organoclay Nanocomposites by Reactive Extrusion System. Chem Sci J 8: 166. doi: 10.4172/2150-3494.1000166 Copyright: © 2017 Mostafa AD, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Determining Regulatory Sequences of the ATF3 Promoter within the Integrated Stress Response Pathway

ii Acknowledgements . iii List of Figures . iv List of Tables . v Introduction . 1 Materials and Methods . 8 1. Cell Culture . 8 2. Site Directed Mutagenesis . 8 3. Luciferase Reporter Assay . 8 4. Polymerase Chain Reaction (PCR) . 9 5. Molecular Cloning . 9 6. Gibson Assembly . 10 7. Bacterial Transformation . 10 8. Quantitative Reverse Transcription Polymerase Chain Reaction (RT-qPCR) . 10 9. Data Analysis . 11 Results . 12 Discussion.26 References . 34 Appendix . 39
International Journal of Instruction

Based on the problem that the teacher's commitment to the profession is still not as expected, this study aims to find ways to improve teacher commitment to the profession by examining the influence of transformational leadership, self-efficacy, and job satisfaction. The methodologies used are the Path method and Sitorem method. The study population was 1307 Non-Civil Servant, middle school teachers in Cirebon District, Indonesia with a research sample of 136 teachers. The NonCivil Servant middle school teachers are teachers who are not paid by the government but by the foundation. The results showed that the Teacher's Commitment to the Professionals could be increased through strengthening Transformational Leadership, Self-Efficacy, and Job Satisfaction. The strengthening of variables is carried out by correcting the weak indicators based on Sitorem's analysis, so that the priority order for handling the improvement of indicators is carried out as follows: 1. Strength of self-confidence, and 2. Announcement of self-confidence for Self-Efficacy variables, 3. Salary received, 4 Promotion, and 5. Supervision of Supervisors for the Job Satisfaction variable, 6. The job itself, 7. Surviving in the Organization, and 8. Establishing Professional Values for the Teacher Commitment variable towards the Profession. This main contribution of our research to provide empirical evidence that the Path Analysis and Sitorem Analysis methods are very good to be used to analysed the factors that influence the strengthening of the Teacher's commitment to his professionalism.
A cutting sequencing approach to modular manufacturing

In this study, a two‐stage algorithm is developed for the cutting sequencing problem in a modular manufacturing system consisting of four basic workstations. Since the flexibility of the system is dependent upon the cutting stage of raw materials, the study focuses particularly on this workstation. In the first stage of the algorithm, an integer linear programming model is used to determine the number of hardboards that will be cut. The model is tested with two different objective functions. In the second stage, a heuristic which takes into account the due date of the products is developed to obtain the real‐time sequencing of these cutting patterns on the shop floor. The algorithm is further implemented in a furniture manufacturer that operates on a make‐to‐order basis. The results of the existing and proposed system are compared, and the proposed algorithm is found to provide a useful tool in such a real‐life planning problem.
Effects of losses on signals in PWB's

This paper shows data that demonstrates the effects of dielectric and conductor losses on signals propagating in a printed wiring board (PWB). These losses vary with frequency (increasing as frequency increases), and depend on the geometry and size of the conductors involved, and on the materials used. Some determination of the significance of these effects on system performance is made. Limits on signal speed, PWB size, and conductor density where these effects become non-negligible in CMOS based digital computers are estimated. >
Ordered Object Segmentation Based on Machine Learning Algorithms

The 7th International Workshop on Advanced Computational Intelligence and Intelligent Informatics (IWACIII2021) Beijing, China, Oct.31-Nov.3, 2021 1 Abstract: The conventional automatic drug dispenser can significantly contribute to numerous services such as medicine industries, pharmacy shops and medical assistance by reducing the workload of medical workers and allowing patients to take their timely medication. In this paper, we use a segmentation technique to identify the location of drug pillboxes from the medicine shelves with the automatic counting of spiral pillboxes. The proposed method is a solution to a dynamic segmentation framework for recognizing objects from large datasets. Firstly, the picture is filtered to remove the noise to recognize the boundary line. Following that, projection lines are drawn in the center to divide the segments of pillboxes by utilizing the midpoint formula, which supports smooth counting of line detection among objects. Besides, we applied the Mean shift method to accumulate the intersection points. The key role of clustering is to collect intersection midpoints data. The proposed framework identifies the existing area from medicine pillbox images and detects the specific segmentation line that automatically allocates the pillboxes. Furthermore, we obtain 99.83% accuracy and successfully detect pillboxes, which aids in the improvement of segmentation, filtering and clustering algorithms. Such techniques assist us in recognizing the most appropriate segmentation boundary lines for further discoveries in the future.
Joint Modeling of Visual Objects and Relations for Scene Graph Generation

An in-depth scene understanding usually requires recognizing all the objects and their relations in an image, encoded as a scene graph. Most existing approaches for scene graph generation ﬁrst independently recognize each object and then predict their relations independently. Though these approaches are very efﬁcient, they ignore the dependency between different objects as well as between their relations. In this paper, we propose a principled approach to jointly predict the entire scene graph by fully capturing the dependency between different objects and between their relations. Speciﬁcally, we establish a uniﬁed conditional random ﬁeld (CRF) to model the joint distribution of all the objects and their relations in a scene graph. We carefully design the potential functions to enable relational reasoning among different objects according to knowledge graph embedding methods. We further propose an efﬁcient and effective algorithm for inference based on mean-ﬁeld variational inference, in which we ﬁrst provide a warm initialization by independently predicting the objects and their relations according to the current model, followed by a few iterations of relational reasoning. Experimental results on both the relationship retrieval and zero-shot relationship retrieval tasks prove the efﬁciency and efﬁcacy of our proposed approach.
DESIGN OF A PRINTED LOG-PERIODIC DIPOLE ARRAY FOR ULTRA-WIDEBAND APPLICATIONS

A printed Log-periodic dipole array (LPDA) is presented, operating over the C, X and Ku bands. The antenna feeding structure consists of two coaxial cables, in order to realize an inflnite balun which provides the required broadband input matching. The second coaxial cable mirrors the flrst one, connected to the antenna input, and is capable of both stabilizing the antenna phase center and improving the radiation pattern. The antenna has been designed using CST Microwave Studio, with an useful frequency range of 4{18GHz. Moreover, both simulated and measured results show that the proposed LPDA can be successfully used as an Ultra Wideband Antenna in the range 4.25{13.25GHz, in which its phase center remains stable.
Stress Analysis under Cu Bump Bonding Process

The copper wire has some advantages in thermal performance, mechanical performance, and low cost, which make it can provide the lowest cost flip-chip(FC) package for low I/O density device. The 2D Cu stud bump finite element model was set up by using ANSYS/LS-DYNA with LOLID162 element to dynamic simulate the Cu stud bump bonding shaping process. The stress distribution in the Cu stud bump and the pad during the bonding process were studied, and the influence of pad thickness on the stress distribution of Si chip was also analyzed. The results shows that under the bonding process the Cu bump height is mainly influenced by the bonding pressure and the top shape of the Cu bump is influenced by ultrasonic energy, the increase of pad thickness results in reducing stress concentration inside the Si chip.
Intermodulation distortion in Kahn-technique transmitters

The Kahn Envelope Elimination and Restoration (EER) technique implements a linear RF power amplifier (PA) by combining nonlinear, but efficient, RF and AF power amplifiers. For signals with high peak-to-average ratios, the average efficiency of a Kahn-technique transmitter can be three to four times that of a transmitter that employs conventional linear RP PAs. Since switching-mode amplifiers are employed, the linearity of an EER transmitter depends upon parameters such as the bandwidth of the envelope modulator and the differential delay between envelope and phase signals. This paper determines the relationship between these parameters and IMD levels and verifies the predictions by laboratory measurements. The results can be used to determine the requirements for the components of a Kahn-technique transmitter.
A Functional Taxonomy of Visual Augmented Reality for Human-Robot Interaction

—Augmented reality (AR) technologies are today more frequently being introduced to Human-Robot Interaction to mediate the interaction between human and robot. Indeed, better technical support and improved framework integration allow the design and study of novel scenarios augmenting interaction with AR. While some literature reviews have been published, so far no classiﬁcations have been devised for the role of AR in HRI. AR constitutes a vast ﬁeld of research in HCI, and as it is picking up in HRI, it is timely to articulate the current knowledge and information about the functionalities of AR in HRI. Here we propose a multidimensional taxonomy for AR in HRI that distinguishes the type of perception augmentation, the functional role of AR, and the augmentation artifact type. We place sample publications within the taxonomy to demonstrate its utility. Lastly, we derive from the taxonomy some research gaps in current AR-for-HRI research and provide suggestions for exploration beyond the current state-of-the-art.
Feedforward fuzzy logic control for permanent magnet synchronous motor drive

In this paper, a fuzzy logic speed controller in combination with feedforward fuzzy logic current controller is designed and modelled to control a permanent magnet synchronous motor (PMSM) drive for high performance drive applications. The fundamentals of fuzzy logic based control algorithms are illustrated in brief. The detailed performance of PMSM drive is studied applying various mechanical disturbances such as starting, speed reversal, flux weakening and load perturbations.
Workplace travel plans: can they be evaluated effectively by experts?

Employers are regularly involved in transport planning and characteristic workplace-oriented tools include: (1) travel plans for building projects, (2) mandatory travel plans, (3) subsidies to employers with an advanced travel plan and (4) best travel plan awards. In all cases, experts judge the level of car use. We argue that decision-makers might benefit from a multiple regression-based benchmark modelling tool that estimates the expected share of the car. In this paper, we estimate the share of car users in the commuting modal split at workplaces. However, since the amount of information available to experts differs, we gradually add information to the model to measure the impact of data availability. Without historic data on modal split, the current share can only be predicted moderately well, i.e. within a 20% range. Besides adding the past, results improve by using homogenous and regional subsamples. Nevertheless, quantitative analyses do not make expert knowledge obsolete.
Multi-objective Path Planning Based on An Improved GWO-WOA Method

The problem of multi-objective path planning for robots is to ﬁnd the shortest, smoothest and safest path in the presence of obstacles, which can be proposed as a multi-objective optimization problem with generous constraints. In this paper, an improved GWO-WOA method is proposed achieve the solution, which mainly consists the following two improvements: First, a tent chaos mechanism is used to improve the initial population quality of grey wolf optimizer (GWO). Second, the hunting mechanism of the whale optimizer algorithm (WOA) is replaced to the hunting strategy of GWO, which can improve the tracking performance of the optimal global exploration searching solutions and avoid falling into the local optimization. Then, a smooth path is calculated based on the proposed hybrid GWO-WOA with spline interpolation method. To further reduce the computing burden, an one-dimensional search method for iteration process is proposed and compared with two-dimensional search method. Finally, simulation experiments demonstrate the feasibility and effectiveness of the proposed algo-rithm under different environments.