Miracle-dz/UniFAR-FTUs huggingface dataset:
Statement of Research Interests

“Connect” may be the best keyword of the last decades. Beyond the barriers of age, gender, race, geography, and many others, people who used to be separated are connected online. These connections are bringing about huge changes in how we create, consume, and disseminate information online. The impact of an individual can be massively and swiftly amplified by the connected others (e.g., viral retweets in Twitter) [1, 2]. This fact that an individual’s voice can reach the whole population prompts an important question: Why can’t the online space become the ideal space for democracy?
Relationship Between Perceived Organizational Support and Organizational Citizenship Behavior; a Study of Employees in National Highway Authority of Pakistan

The purpose of this study was to explore the relationship between perceived organizational support and organizational citizenship behavior of the employees in NHA (National Highway Authority) of Pakistan. Data was collected through questionnaires distributed in a survey and overall 200 useable filled questionnaires were received. Convenience sampling technique was applied for the selection of sample and SPSS 16 was used for the analysis of the data. Results indicate that positive environment, organizational resources, the behavior of the employees, organizational environment, and other related factors are all linked to organizational citizenship behavior positively. This paper also provides the implications of the study for human resource managers and tries to find out how to improve organizational citizenship behavior in the organizations by providing organizational support to the employees.
7 Year Follow up of Renal Artery Stenosis due to Fibromuscular Dysplasia

Case Presentation A 23 years old absolutely alright one month back when he developed high grade fever, consulted some General practitioner at Multan and was found hyper-tensive during his routine check-up. His routine lab investigation showed persistent hypokalemia. He was referred to cardiology OPD with uncontrolled hyper-tension. He was given ACE inhibitor and beta blocker were given but the hypertension remain uncontrolled. His serum urea 20 mg/dl (15 - 45 mg/dl) Serum creati-nine 0.8 mg/dl (0.4 - 1.4 mg/dl). Urine examination: Unremarkable. Abdominal Ultrasound: Right kidney slightly small-ler. Compensatory hypertrophy of left kidney. Renal Scan: Slightly reduced functioning left kidney. Reduced functioning small sized, right kidney. Echocardiography: Normal, with normal ejection fraction. Angiography was planned which shows right sided renal artery stenosis. Angioplasty was done on 11/07/2001 with TIMI grade III adequate post stenting blood flow. After the angioplasty patient remain nor-motensive without antihypertensive medication. Follow up angiography was done on 26/3/2003 whi-ch shows normal functioning patent right renal artery stent. Complete blood count urea creatinine, within normal limit. 2007 patient Color Doppler of renal artery was done which shows normal patent renal arte-ries and no antihypertensive medication was given to this patient in these 8 years. So angioplasty with stent-ing is the treatment of choice for renal artery stenosis due to fibromuscular dysplasia.
Argumentation as a Tool to Understand Complexity of Knowledge Integration

Science literacy is a central concern for public discussion of socio-scientific issues related to STEM. Such issues are increasingly present in the school curriculum and places greater responsibility on teachers to be knowledgeable about STEM and especially about how to engage in socio-scientific discussion. This paper reports research conducted with undergraduate teacher education students at the beginning of a course dealing with science literacy at a Canadian university. Groups of 4-5 students engaged in a discussion of one of two topics, one was current and controversial, the other less contentious. Transcripts of the verbal interactions were analyzed using a coding scheme adapted from Duschl (2008) based on the presumptive argumentation schemes of Walton, Reed and Macagno (2008). Results indicated that argument from personal or reported experiences predominated both topics but otherwise different argument schemes were utilized. Social dimensions of a topic were discussed just as often as arguing from evidence even though students had been directed to briefly research the assigned topic before the discussion. The group discussing the less contentious issue was able to adjust their points-of-view and arrive at a consensual solution. The group discussing the more contentious topic was less inclined to change perspectives and failed to achieve a collective position. Moreover, only this group expressed concern over bias in the scientific evidence uncovered in their research. Implications for understanding the integration of knowledge sources and argumentation schemes are discussed in relation to controversial socio-scientific issues.
Antihyperglycaemic, antioxidative activities of a formulated polyherbal drug MTEC (Modified) in streptozotocin-induced diabetic rat.

Musa paradisiaca belongs to the family of Musaceae and is distributed throughout India and Malaysia. The plant has medicinal value as antidiabetic agent. Seeds of Tamarindus indica of Caesalpiniaceae family used as traditional medicine for the management of diabetes mellitus found throughout India. Eugenia jambolana an evergreen tree of Myrtaceae family is used as traditional medicine for the management of diabetes in India. Coccinia indica of Cucurbitaceae family is distributed widely all over India and its medicinal value as antidiabetic agent is well recognized. The diabetic therapeutic efficacy of a formulated polyherbal drug (abbreviated form MTEC), constituted with n-hexane fractions of the hydromethanol extract of root of M. paradisiaca, seed of T. indica, seed of E. jambolana and leaf of C. indica at specific ratio was investigated in streptozotocin-induced diabetic rats. Streptozotocin-induced diabetic state was confirmed here by the monitoring of increased level of fasting blood glucose, decreased glycogen level in liver and skeletal muscle along with elevation in the activities of glucose-6phosphatase and lactate dehydrogenase and diminution in the activities of hexokinase as well as glucose-6-phosphate dehydrogenase in liver, skeletal muscle and cardiac muscle. Oral administration of MTEC (modified) at a dose of 100 mg/5 ml of olive oil/Kg body weight daily to the diabetic rats significantly (P<0.05) corrected fasting blood glucose level, glycogen contents of liver and skeletal muscle along with said carbohydrate metabolic enzyme activities in liver, skeletal and cardiac muscles in diabetic rat towards the control levels. Diabetes mellitus induced oxidative stress was also corrected significantly (P<0.05) by the treatment of this polyherbal drug (modified MTEC) to the diabetic rat. Results of the present study support the therapeutic potentiality of this polyherbal drug MTEC for the management of diabetes.
Influence of structural organization on the electronic properties of organic photovoltaic materials

First principles DFT calculations have been used to investigate the electronic properties of donor-acceptor blend of regioregular head-to-tail poly-3-hexylthiophene (RR-PHT) and C60. We found that the different order parameters investigated for the RR-P3HT/C60 blend induce a significant variation of the electronic properties of the system, such as a decreasing band gap with an improving molecular packing.
Quality of Life Outcomes after Robotic Thyroid Surgery

Copyright c 2015, the Korean Thyroid Association. All rights reserved. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. 경액와 액와부 접근법 로봇 갑상선 수술 후 삶의 질 변화
LINGUISTIC AND GENETIC RELATIONSHIPS IN NORTHERN CAMEROON

Cameroon, (Central Africa), has about 270 languages, which belong to three linguistic families. In Northern Cameroon alone, there are over 100 languages spoken, and the differences among the languages are quite significant. The object of this feasibility study was to collect DNA in the field and determine the degree of genetic diversity among individuals comprising six language groups in Northern Cameroon: Hdi (N=30), Mafa (31), Mina (29), and Gidar (30) (all Central Chadic); Peve (31) (Masa, Chadic); and Mambay (31) (Niger Congo). DNA samples were collected on buccal swabs and sent to Institute of Behavioral Genetics for analysis. Here we report the preliminary analysis of data from genotyping 20 unlinked Short Tandem Repeat (STR, microsattelite) markers across the genome with average heterozygosities greater than 0.70. Data were analyzed using the program structure (Pritchard et al, 2000, Falush et al, 2003). Results from structure indicated that the genotype of an individual can be considered to be drawn from their respective subgroup (alpha = 0.0491). Furthermore, there is genetic differentiation across language groups (FST range: 0.0003-0.1229). Our ability to predict language subgroup membership based on genetic information was modest, but our results indicate that 6 disparate language groups exhibit genetic divergence and vary in genetic diversity. Whether the diversity within language groups resulted from six separate founding populations or from dispersion and isolation of the language groups from ancestral sources remains an open question. Efforts are in progress to genotype 12 Y-chromosome STR loci, and mitochondrial DNA typing is planned to address the question of ancestral origin of the genetic diversity among the six language groups. This study demonstrates the feasibility of DNA collection in these populations and our analyses suggest the potential value of more extensive genotyping of these samples and more extensive studies of the relationship between genetic and linguistic diversity in this region.
Magnetic MnxGe1-x Dots for Spintronics Applications

Dilute magnetic semiconductors (DMSs) attract tremendous interest as emerging candidates for the microelectronics industry due to their uniqueness in exhibiting spin dependent magneto-electro-optical properties. Their distinctive material characteristics such as spin dependent coupling between semiconductor bands and the localized states promises magnetoelectric effect the modulation of magnetic properties by an applied electric field in semiconductors (Kulkarni et al., 2005, Ohno et al., 2000). Thus, a wide variety of semiconductor devices can be envisaged (Brunner, 2002a), such as spin polarized lightemitting diodes, lasers (Schulthess and Butler, 2001, Schilfgaarde and Mryasov, 2001) and spin transistor logic devices (Chen et al., 2005, Brunner, 2002b, Ohno et al., 2000). The development of these devices is considered as a possible route for extending the semiconductor scaling roadmap to spin-added electronics (Liu et al., 2005).
The interrelationships between rhizobacteria and arbuscular mycorrhizal fungi and their importance in the integrated management of nematodes and soilborne plant pathogens

The interrelationships between rhizobacteria and arbuscular mycorrhizal fungi and their importance in the integrated management of nematodes and soilborne plant pathogens A total of 62 bacterial isolates were isolated from surface sterilized AMF (arbuscular mycorrhizal fungi) spores, which were previously extracted from tomato fields in Nakhon Ratchasima Province of Thailand. These spore-associated bacteria were tested for their antagonistic potential against the root-knot nematode Meloidogyne incognita and the soilborne plant pathogens Fusarium oxysporum, Pythium aphanidermatum, Pythium ultimum and Rhizoctonia solani. A high percentage of the bacterial isolates (14,5%) reduced nematode penetration of tomato roots in repeated experiments. Two of these antagonistic bacteria were further tested in a long-term experiment, either alone or in combination with Glomus intraradices. Single inoculations resulted in low or even no biological control, but both dual inoculations reduced gall and egg mass production. Twelve bacteria (19,4%) inhibited fungal growth of at least one pathogen in vitro and six isolates showed antagonistic potential against all pathogens tested. The seven isolates that inhibited growth of Fusarium oxyporum in vitro were tested in vivo against the same pathogen. Three of these seven bacteria reduced the reisolation rate of the pathogen and therefore inhibited fungal spread in the tomato stem. The PHPR Rhizobium etli G12, inducing resistance against M. incognita, was found to promote establishment of G. intraradices on three different tomato cultivars. The bacterium appears to accelerate AMF colonization of the root, and therefore should be regarded a Mycorrhiza helper bacterium (MHB). In in vitro studies, R. etli stimulated AMF sporulation and hyphal branching, the latter of which is an important prerequisite for penetration of the host roots. This direct effect of the bacterium on fungal morphology is one explanation for the increased mycorrhiza establishment, but a plant-mediated effect cannot be excluded. The combination of G. intraradices with R. etli enhanced biocontrol of M. incognita on tomato, in comparison to single inoculations. The better mycorrhization of the young transplants and the combination of different modes of action could be the explanations of the increased antagonistic potential.
DESIGN OF AN ELECTRICAL MACHINE FOR AN INTEGRATED MAGNETOCALORIC COOLING SYSTEM

The magnetocaloric effect, and particularly its application to the production of cold at room temperature remain a scientific and technologic challenge. Magnetic refrigeration offers a good energy efficiency. This paper deals with the design and implementation of a magnetic refrigerator prototype. The particularity of our prototype is to integrate a magnetocaloric regenerator in the air gap of a Permanent Magnet Synchronous Machine.
Improving Movement Prediction of Traffic Actors using Off-road Loss and Bias Mitigation

There is a significant amount of recent literature in the domain of self-driving vehicles (SDVs), with researchers focusing on various components of the SDV system that have the potential to improve on-street performance. This includes work exploring improved perception of the SDV surroundings, or proposing algorithms providing better short-term prediction of nearby traffic actor behavior. However, in most cases, the authors report only aggregate metrics computed on the entire data, and often do not fully consider the bias inherent in the traffic data sets. We argue that this practice may not give a full picture of the actual performance of the prediction model, and in fact, may mask some of its problem areas (e.g., handling turns). We analyze the amount of bias present in traffic data and explore the ways to address this issue. In particular, we propose to use a novel off-road loss and standard bias mitigation techniques that result in improved performance. We further propose to avoid aggregate metrics and instead analyze performance on relevant subsets of the data, thus better capturing actual model capabilities. Moreover, we propose to measure a novel off-road error to complement commonly used prediction metrics. Extensive analysis of real-world data suggests benefits of the proposed approach for improving the performance of SDV technology.
Kerberos Authorization with Hybrid Access Control Model in Public Cloud

Access control and Data confidentiality are key technology to ensure the security of system and to protect the privacy of the users. The modified Collaborative Trust Enhanced Security (CTES) model has an inbuilt access control mechanism for Kerberos protocol itself to enforce the access control policy directly into the Client system node. This paper explains the hybrid access control model with Role Based Access Control (RBAC) and Attribute Based Access Control (ABAC) for modified CTES framework through Kerberos protocol. Hence, it retains the concept of “role”, “group” and “attributes” for the user which are necessary to protect data privacy in the system. Data confidentiality for the stored data in Cloud is achieved by cryptographic techniques. Gnu Privacy Guard (GnuPG) based certificate is capable enough to verify the identity of the correspondent in information exchange as well as the information integrity. It is a strongest authentication technique where the user is asked to provide his/her digital ID for validation in the Server and enables Single sign-on services for Kerberos Authorization in modified CTES model. In this paper, it is proposed for a new Kerberos Authorization with Hybrid Access Control Model (KAHAC) for single-domain systems and multi-domain systems in Public Cloud based on roles, attributes, groups, access modes and the type of resources.
A Novel High-Efficiency Double-Input Bidirectional DC/DC Converter for Battery Cell-Voltage Equalizer with Flyback Transformer

Large-scale battery cells are connected in series, which inevitably leads to a phenomenon that the cell voltage is unbalanced. With a conventional equalizer, it is challenging to maintain excellent characteristics in terms of its size, design cost, and equalization efficiency. In order to improve the defects in the above equalization circuit, a novel voltage equalization circuit is designed, which can work in two modes. A bidirectional direct current–direct current (DC–DC) equalization structure is adopted, which can quickly equalize two high or low-power batteries without using an external energy buffer. In order to verify the effectiveness of the proposed circuit, a 12-cell battery 2800-MAh battery string was applied for experimental verification. Computer monitoring (LabVIEW) was adopted in the whole system to intelligently adjust the energy imbalance of the battery pack. The experimental results showed excellent overall performance in terms of equalization was achieved through the newly proposed method. That is, the circuit equalization speed, design cost, and volume have a good balance performance.
The Effects of the LDA Topic Model on Sentiment Classification

Online reviews are a feedback to the product and play a key role in improving the product to cater to consumers. Online reviews that rely heavily on manual categorization are time consuming and labor intensive.The recurrent neural network in deep learning can process time series data, while the long and short term memory network can process long time sequence data well. This has good experimental verification support in natural language processing, machine translation, speech recognition and language model.The merits of the extracted data features affect the classification results produced by the classification model. The LDA topic model adds a priori a posteriori knowledge to classify the data so that the characteristics of the data can be extracted efficiently.Applied to the classifier can improve accuracy and efficiency. Two-way long-term and short-term memory networks are variants and extensions of cyclic neural networks.The deep learning framework Keras uses Tensorflow as the backend to build a convenient two-way long-term and short-term memory network model, which provides a strong technical support for the experiment.Using the LDA topic model to extract the keywords needed to train the neural network and increase the internal relationship between words can improve the learning efficiency of the model. The experimental results in the same experimental environment are better than the traditional word frequency features.
Melodic Pattern Recognition of songs based on Raga Music for Content-based Music Retrieval

Melodic Pattern Recognition of songs based on Raga Music for Content-based Music Retrieval Makarand Velankar, Amod Deshpande, Dr. Parag Kulkarni Faculty Cummins College of Engineering and Ph.D. Research Scholar PICT, Pune SPPU Consonance Acoustics, Aurangabad. Chief Scientist and CEO, Kvinna Limited. Pune. E-mail: makarand.velankar@cumminscollege.in, amod.deshpande@live.com, parag.acad@gmail.com ABSTRACT
Impact of the spatial variability of daily precipitation on hydrological projections: A comparison of GCM- and RCM-driven cases in the Han River basin, Korea

Hydrological Processes. 2019;1–18. Abstract In this study, we investigate the impact of the spatial variability of daily precipitation on hydrological projections based on a comparative assessment of streamflow simulations driven by a global climate model (GCM) and two regional climate models (RCMs). A total of 12 different climate input datasets, that is, the raw and bias‐ corrected GCM and raw and bias‐corrected two RCMs for the reference and future periods, are fed to a semidistributed hydrological model to assess whether the bias correction using quantile mapping and dynamical downscaling using RCMs can improve streamflow simulation in the Han River basin, Korea. A statistical analysis of the daily precipitation demonstrates that the precipitation simulated by the GCM fails to capture the large variability of the observed daily precipitation, in which the spatial autocorrelation decreases sharply within a relatively short distance. However, the spatial variability of precipitation simulated by the two RCMs shows better agreement with the observations. After applying bias correction to the raw GCM and raw RCMs outputs, only a slight change is observed in the spatial variability, whereas an improvement is observed in the precipitation intensity. Intensified precipitation but with the same spatial variability of the raw output from the bias‐corrected GCM does not improve the heterogeneous runoff distributions, which in turn regulate unrealistically high peak downstream streamflow. GCM‐simulated precipitation with a large bias correction that is necessary to compensate for the poor performance in present climate simulation appears to distort streamflow patterns in the future projection, which leads to misleading projections of climate change impacts on hydrological extremes.
ThRift: An omnidirectional image based virtual reality system

Virtual reality (VR) is collecting attention thanks to the progress of hardware such as head-mounted displays (HMD) and 3D graphics chips. Because most of the systems, however, are based on computer graphics (CG), they require a significant amount of time and energy to build 3D models manually. One solution is to build them automatically from images, but the display quality lacks realism due to low resolution and some artifacts. We propose a system based on image-based rendering that can provide the user with a photo realistic and immersive walk-through experience. Depending on the user’s location, we switch images. Although the time consuming part is image acquisition, it takes less than an hour for 30 images by a consumer omnidirectional camera. The user is able to walk around in a room interactively in realtime, while looking in any direction with a wide-angle HMD.
Floating Ground-truth Labels

The reliability of ground-truth labels is very important in supervised image classification problems. Although a large amount of images are collected, if the amount of noisy labels is high, deep neural networks cannot learn the discriminative visual properties between the target classes; this results in underfitting. In real-world applications, this situation frequently occurs. Regardless of the number of noise labels because of unclear visual patterns and subjective (floating) labeling criterion, deep networks should maintain high performance. In this paper, we describe this problem in detail and introduce a related application. To apply the existing deep learning based algorithms to large-scale, realworld image data, it is important to address the noisy label problem.