Miracle-dz/UniFAR-FTUs huggingface dataset:
Time-Dependent MHD Flow of Non-Newtonian Generalized Burgers' Fluid (GBF) Over a Suddenly Moved Plate With Generalized Darcy's Law

Time-dependent magnetohydrodynamic (MHD) motion of a generalized Burgers' fluid (GBF) is investigated in this article. GBF is a highly complicated non-Newtonian fluid and is of highest degree in the class of rate type fluids. GBF is taken electrically conducting by using the restriction of small magnetic Reynolds number. Darcy's law has been used here in its generalized form using the GBF constitutive relation; hence, the medium is made porous. The impulsive motion in the fluid is induced due to sudden jerk of the plate. Exact expressions for velocity as well as for shear stress fields are obtained using the Laplace transform method. The solutions for hydrodynamic fluid (absence of MHD) in a non-porous medium as well as those for a Newtonian fluid (NF) executing a similar motion are also recovered. Results are sketched in terms of several plots and discussed for embedded parameters. It is found that the Hartmann number and porosity of the medium have strong influence on the velocity and shear stress fields.
Distribution and Expression of Vimentin and Desmin in Broiler Pectoralis major Affected by the Growth-Related Muscular Abnormalities

Desmin (DES) and Vimentin (VIM) exert an essential role in maintaining muscle cytoarchitecture and since are considered reliable markers for muscle regeneration, their expression has been extensively investigated in dystrophic muscles. Thus, exhibiting features similar to those of human dystrophic muscles, the present study aimed at assessing the distribution of VIM and DES proteins and the expression of the corresponding genes in Pectoralis major muscles affected by white striping (WS), wooden breast (WB), and spaghetti meat (SM) abnormalities as well as in those having macroscopically normal appearance (NORM). For this purpose, 20 Pectoralis major muscles (5/group) were collected from the same flock of fast-growing broilers to perform immunohistochemistry, immunoblotting and gene expression. Immunohistochemical analyses showed an increased number of fibers immunoreactive to both VIM and DES in WS and WB, while only a few immunoreactive fibers were observed in NORM. Concerning the protein level, if compared with NORM, a 55% increase in VIM content was found in WB affected cases (P < 0.05) thus suggesting the development of intense regenerative processes in an early-stage within these muscles. The significantly higher amount of DES (+53%) found in WS might be attributed to a progression of the regenerative processes that require its synthesis to preserve the structural organization of the developing fibers. On the other hand, significantly lower VIM and DES contents were found in SM. About gene expression, VIM mRNA levels gradually increased from the NORM to the SM group, with significantly higher gene expressions in WB and SM samples compared to the NORM group (P = 0.009 for WB vs. NORM and P = 0.004 for SM vs. NORM). Similarly, the expression of DES gene showed an increase from the NORM to WB group (P = 0.05). Overall, the findings of the present study suggest that intense regenerative processes take place in both WB and WS muscles although a different progression of regeneration might be hypothesized. On the other hand, the lack of correspondence between VIM gene expression and its protein product observed in SM suggests that VIM may also exert a role in the development of the SM phenotype.
O6-Methylguanine-DNA Methyltransferase (MGMT): Challenges and New Opportunities in Glioma Chemotherapy

Chemoresistance has been a significant problem affecting the efficacy of drugs targeting tumors for decades. MGMT, known as O6-methylguanine-DNA methyltransferase, is a DNA repair enzyme that plays an important role in chemoresistance to alkylating agents. Hence, MGMT is considered a promising target for tumor treatment. Several methods are employed to detect MGMT, each with its own advantages and disadvantages. Some of the detection methods are; immunohistochemistry, methylation-specific PCR (MSP), pyrophosphate sequencing, MGMT activity test, and real-time quantitative PCR. Methylation of MGMT promoter is a key predictor of whether alkylating agents can effectively control glioma cells. The prognostic value of MGMT in glioma is currently being explored. The expression of MGMT gene mainly depends on epigenetic modification–methylation of CpG island of MGMT promoter. CpG island covers a length of 762 bp, with 98 CpG sites located at the 5' end of the gene, ranging from 480 to 1,480 nucleotides. The methylation sites and frequencies of CpG islands vary in MGMT-deficient tumor cell lines, xenografts of glioblastoma and in situ glioblastoma. Methylation in some regions of promoter CpG islands is particularly associated with gene expression. The change in the methylation status of the MGMT promoter after chemotherapy, radiotherapy or both is not completely understood, and results from previous studies have been controversial. Several studies have revealed that chemotherapy may enhance MGMT expression in gliomas. This could be through gene induction or selection of high MGMT-expressing cells during chemotherapy. Selective survival of glioma cells with high MGMT expression during alkylating agent therapy may change MGMT status in case of recurrence. Several strategies have been pursued to improve the anti-tumor effects of temozolomide. These include the synthesis of analogs of O6-meG such as O6-benzylguanine (O6-BG) and O6-(4-bromothenyl) guanine (O6-BTG), RNAi, and viral proteins. This review describes the regulation of MGMT expression and its role in chemotherapy, especially in glioma. Targeting MGMT seems to be a promising approach to overcome chemoresistance. Further studies exploring new agents targeting MGMT with better curative effect and less toxicity are advocated. We anticipate that these developments will improve the current poor prognosis of glioma patients.
CONTEMPORARY SOCIAL PROCESSES

Introduction Institutionally complex, multifaceted and diverse world of contemporary societies shows different communication mechanisms to solve problems that are widespread. Migration belongs to these problems and is caused by military operations in the country that forces its citizens to relocate to safer regions. This requires new approaches to identifying and defining the ways to prevent negative social consequences that migration leads in a crisis society. S. Moiseev shows anxiety concerning the ambiguity of interpretation of the term “mass” in the social sciences and offers a “rehabilitation” of this term through the generalised definition of the mass. This researcher offers to consider the concept of “mass” as an “ideal type”, which is not limited to specific empirical phenomena. We do not share the opinion of S. Mooiseev a coherent sociological conceptualisation of the term “mass” can be formed. In explaining the mechanism of conversion mass into collective, we rely on a combination of situational, process and system approaches, not the ideal types of mass. The demand for conceptualisation of the term “mass” is largely due to the formation of mass society, mass culture and mass communication. In this article, we base on the fact that internal migration can be seen as a mass phenomenon, when it covers a large number of people and brings together their common characteristics. By the characteristics of internal migrants from the area ATO in Ukraine (2014-2016 years.) we classified as follows: 1. Massivity. Large numbers of people (both organized and unorganized) have left the ATO area alone or with the help of volunteers at the same time. They searched for a shelter in other regions of Ukraine and abroad. 2. Being in a critical condition. The mass movement of Ukrainian citizens from the ATO area that are taking place during the 2014-2016 are generated by the crisis and set themselves domestic workers
Spun Carbon Nanotube Fibres and Films as an Alternative to Printed Electronic Components

Current studies of carbon nanotubes have enabled both new electronic applications and improvements to the performance of existing ones. Manufacturing of macroscopic electronic components with this material generally involves the use of printed electronic methods, which must use carbon nanotube (CNT) powders. However, in recent years, it has been shown that the use of ready-made self-standing macroscopic CNT assemblies could have considerable potential in the future development of electronic components. Two examples of these are spun carbon nanotube fibers and CNT films. The following paper considers whether these spun materials may replace printed electronic CNT elements in all applications. To enable the investigation of this question some practical experiments were undertaken. They included the formation of smart textile elements, flexible and transparent components, and structural electronic devices. By taking this approach it has been possible to show that CNT fibres and films are highly versatile materials that may improve the electrical and mechanical performance of many currently produced printed electronic elements. Additionally, the use of these spun materials may enable many new applications and functionalities particularly in the area of e-textiles. However, as with every new technology, it has its limitations, and these are also considered.
Web Content Mining: Tool, Technique & Concept

Today the evolution of the World Wide Web has brought us enormous and ever growing amounts of data and information. The web is full of structured or unstructured information which is directly or indirectly influencing society or people in every day life. Due to huge data available with the web it has become a challenge for people with interest in utilizing this information. For mining the huge available data on web in the form of frequently used patterns and log files for meaning use is considered in this paper. The paper presents a preliminary review of Web content mining contributions in the field of web mining and the prominent successful algorithms and some tools.
Final Report A SVM Model for Relation Classification of Noun Phrases based on the NELL Database

The Never Ending Language Learning (NELL) project has produced considerable corpus statistics describing subject-verb-object triples, as well as instances of hundreds of relations. This paper presents RECSVM, a relation classification model for noun phrase (NP) pairs based on the NELL knowledge base, which is capable of predicting whether a given pair of noun phrases satisfies a certain relation in NELL, but it is also capable of determining the most probable relation given the input NP pair. Features employed to build the SVM model include categories of NPs, distributions of word occurrences, contexts of NPs as well as results of shallow parsing, which are proved to be effective in classifying the relations of noun phrase pairs.
An analytical accumulation mode SOI pMOSFET model for high-temperature analog applications

An accumulation mode SOI pMOSFET model for simulation of analog circuits meant for high-temperature applications is presented in the paper. The model is based on explicit expressions for the drain current with an infinite order of continuity what assures smooth transitions between different operation regimes of the transistor. This model is valid for all regimes of normal operation, demonstrates proper description of high-temperature behavior of the subthreshold and off-state current. The model characteristics show a good agreement with the experimental data for temperatures up to 300 °C.
Full-Band Music Genres Interpolations with Wasserstein Autoencoders

We compare different types of autoencoders for generating interpolations between four-instruments musical patterns in the acid jazz, funk, and soul genres. Preliminary empirical results suggest the superiority of Wasserstein autoencoders. The pro-cess of generation produces musically sound and creative transitions between different genres and can be of interest to practitioners in the ﬁeld.
COMBINING AUGMENTED REALITY AND SIMULATION-BASED OPTIMIZATION FOR DECISION SUPPORT IN MANUFACTURING

Although the idea of using Augmented Reality and simulation within manufacturing is not a new one, the improvement of hardware enhances the emergence of new areas. For manufacturing organizations, simulation is an important tool used to analyze and understand their manufacturing systems; however, simulation models can be complex. Nonetheless, using Augmented Reality to display the simulation results and analysis can increase the understanding of the model and the modeled system. This paper introduces a decision support system, IDSS-AR, which uses simulation and Augmented Reality to show a simulation model in 3D. The decision support system uses Microsoft HoloLens, which is a head-worn hardware for Augmented Reality. A prototype of IDSS-AR has been evaluated with a simulation model depicting a real manufacturing system on which a bottleneck detection method has been applied. The bottleneck information is shown on the simulation model, increasing the possibility of realizing interactions between the bottlenecks.
Using Physical Activity to Enhance Health Outcomes Across the Life Span

Physical activity has been widely recognized as one of the primary determinants that proliferates positive psychophysiological health in individuals. Despite the numerous benefits of engaging in physical activity, a majority of the global population continues to be physically inactive or sedentary. The aim of this brief commentary is to capture the benefits of engaging in regular physical activity across the life span. In particular, this paper will highlight the benefits of engaging in regular physical activity with respect to age, gender, atypical populations, and lifestyle. Future research and recommendations have also been addressed.
A Software Tool for the Design of Critical Robot Missions with Performance Guarantees

Deploying a robot as part of a counter-weapons of mass destruction mission demands that the robotic software operates with high assurance. A unique feature of robotic software development is the need to perform predictably in a physical environment that may only be poorly characterized in advance. In this paper, we present an approach to building high assurance software for robot missions carried out in uncertain environments. The software development framework and the verification algorithm, VIPARS, are described in detail. Results are presented for missions including motion and sensing uncertainty, interaction with obstacles, and the use of sensors to guide behavior. © 2013 The Authors. Published by Elsevier B.V. Selection and/or peer-review under responsibility of Georgia Institute of Technology.
Parametric tracking across multiple cameras

This paper presents a tracking method based on parameters between colour blobs. The colour blobs are obtained from segmenting the overall target into multiple colour regions. The colour regions are segmented using EM method that determines the normal colour distributions from the overall colour pixel distribution. After segmenting into different regions on the different colour layers, parameters can be generated between colour regions of interest. In this instance, the colour regions of interest are the top and bottom colour regions. The parameters that are generated from these colour regions are the vector magnitude, vector angle and the value difference between colour regions. These parameters are used as a means for tracking targets of interest. These parameters are used for tracking the target of interest across an array of cameras which in this instance are three cameras. Three cameras have been set up with different background and foreground conditions. The summarised results of tracking targets across three cameras have shown that the consistency of colour regions across different cameras and different background settings provided sufficient parameters for targets to be tracked consistently. Example of tracking performance across three cameras were 0.88, 0.67 and 0.55. The remaining tracking performances across three cameras are shown in Table 2. The tracking performance indicate that the parameters between colour regions were able to be used for tracking a target across different cameras with different background scenarios. Based on results obtained, parameters between segmented colour regions have indicated robustness in tracking target of interest across three cameras.
DeepProbLog: Integrating Logic and Learning through Algebraic Model Counting

The overall goal of neuro-symbolic computation is to integrate high-level reasoning with low-level perception. With DeepProbLog, we show how such an integration can be achieved by using algebraic model counting. Furthermore, we argue that 1) neuro-symbolic computation should integrate neural networks with the two most prominent methods for reasoning, that is, logic and probability, and that 2) neurosymbolic integrated methods should have the pure neural, logical and probabilistic methods as edge cases. We examine the state-of-the-art with regard to these claims and position our own contribution DeepProbLog in this perspective.1
Socially intelligent task and motion planning for human-robot interaction

As social beings, much human behavior is predicated on social context - the ambient social state that includes cultural norms, social signals, individual preferences, etc. In this paper, we propose a socially-aware task and motion planning algorithm that considers social context to generate appropriate and effective plans in human social environments (HSEs). The key strength of our proposed approach is that it explicitly models how potential actions not only affect objective cost, but also transform the social context in which it plans and acts. We investigate strategies to limit the complexity of our algorithm, so that our planner will remain tractable for mobile platforms in complex HSEs like hospitals and factories. The planner will also consider the relative importance and urgency of its tasks, which it uses to determine when it is and is not appropriate to violate social expectations to achieve its objective. This social awareness will allow robots to understand a fundamental rule of society: just because something makes your job easier, does not make it the right thing to do! To our knowledge, the proposed work is the first task and motion planning approach that supports socially intelligent robot policy for HSEs. Through this ongoing work, robots will be able to understand, respect, and leverage social context accomplish tasks both acceptably and effectively in HSEs.
A Survey on Low Power High Speed Domino Circuit in Low Power VLSI Design

Increased number of transistor count and reduced device size is main reason behind scaling and this incorporates leakage current also in other hand battery technology is growing very slowly hence we need low power circuit so that we can enhance overall performance of device. After evolution of CMOS circuit the scientist moved on static and dynamic circuit design. In static CMOS there are various limitations like no. of transistor count, power dissipation, slow speed, hence to overcome these limitation a new circuit pseudo NMOS is used. It exist somewhere between static and dynamic circuit. We have seen that FinFET technology is simulated by BISM4 model using HSPICE at 32nm process technology at 250C with CL=1pF at 100MHz frequency. When CMOS is compared with FinFET for 8 and 16 input OR gate we save average power 15.46%, 21.34% SFLD, 57.37%, 20.12% HSD, 30.90%, 42.46% CKD respectively.
Vehicle Routing Problem with Time Windows Variants and its Application in Distribution Optimization

Salah satu topik penerapan teori graph adalah Vehicle Routing Problem (VRP) dan variannya. Topik ini merupakan combinatorial optimization problem yang dapat diaplikasikan pada masalah optimalisasi distribusi. Pada optimalisasi distribusi, tambahan batasan (constraints) time windows merupakan bahasan yang penting untuk dianalisa. VRPTW adalah varian VRP dengan tambahan constraints berupa time windows. Identifikasi perbedaan contrains pada varian VRPTW, deskripsi formulasi varian VRPTW, dan metode/algoritma untuk menyelesaikannya merupakan isu yang penting untuk dibahas. Rancangan kajian ini adalah deskriptif kualitatif dengan mengidentifikasi datadata berupa titik graph sebagai depot atau costumer, bobot sisi graph sebagai jarak depot ke costumer atau antar costumer, banyak kendaraan, kapasitas kendaraan, dan time windows masing-masing costumer. Selanjutnya dilakukan identifikasi data dengan varian yang bersesuaian, mendiskripsikan formulasi matematikanya, memecahkan masalah dengan algoritma, menganalisa hasil pemecahan masalah dan menginterpretasikan hasilnya. Varian VRPTW yang dibahas adalah VRPBTW, CVRPTW, SDVRPTW, MTSDVRPTW, VRPSPDTW, VRPPDTW, dan MDVRPPDTW. Pemecahan masalah varian VRPTW dengan algoritma sequential insertion dan implementasinya dalam program komputer dengan bahasa Delphi dikaji pada studi ini. Mengetahui perbedaan varian ini diperlukan dalam memodelkan masalah nyata ke dalam formulasi matematika dan bermanfaat pada penyelesaian masalah optimalisasi distribusi. Implikasi hasil pembahasan diperlukan mahasiswa yang sedang melaksanakan PKL di Industri.
Principal Component Analysis (PCA) of Body Measurements and Body Indices in the Pasundan Cows

Principal component analysis (PCA) is important for describing the body conformation in livestock. Total of seven body measurements and thirteen body indices parameters from 144 heads of Pasundan cow (average 3 years age) at West Java Province of Indonesia were used in this study for PCA analysis. The body measurements in this study consisted of withers height (WH), body length (BL), chest girth (CG), chest width (CW), rump height (RH), rump width (RW) and rump length (RL). Therefore the body indices in this study consisted of height slope (HS), width slope (WS), body index (BI), area index (AI), rump length index (RLI), conformation index (CI), length index (LI), body ratio (BR), proportionality (Pr), thoracic development (TD), pelvic index (PI), transverse pelvic (TP) and longitudinal pelvic (LP). The highest of Pearson’s coefficient of correlations (r) value in body measurements was showed between WH and RH (0.93). Hence, the highest r value in body indices was showed between WS and TP (0.86). The PCA for body measurements and body measurements was revealed two factors of PC1 (WH, BL, RH) and PC2 (CG, CW, RW, RL) that explained about 73.36% of the total variation. Meanwhile, the PCA for body indices was revealed four factors of PC1 (BI, AI, RLI, LI, Pr, LP), PC2 (CI, TD), PC3 (WS, PI, TP) and PC4 (HS, BR) that explained about 89.38% of the total variation. It was concluded that the seven body measurements is important for describing body conformation of Pasundan cows such as body size (PC1) and body shape (PC2).
Energy Savings with Thin Gauge Silicon-Iron

With rising energy costs, increased regulatory pressure, and ongoing environmental concerns, there is renewed interest in higher performance materials that offer energy savings for electrical equipment. The poten al for improving energy efficiency in produc on, transmission and use makes thin gauge Silicon-iron (Si-Fe) increasingly a rac ve as an alterna ve for components and machinery that use electrical steel.
Analysis of CloudStack Platform Suitability for Management of Different Cloud Infrastructure Configurations

This article discusses suitability of CloudStack platform for different configurations. In this paper we review cases of platform usage in commercial and non-commercial organizations. We summarized CloudStack out of the box functionality and rated functionality extension possibility based on public information resources. Also, we estimated possible expenses related to this platform usage. As the result, different cases of CloudStack suitability have been determined.