Miracle-dz/UniFAR-FTUs huggingface dataset:
Sexy selfie of hijabed women: Objectification of women's bodies in Instagram account @jilbabootd

Women with hijab often generate a controversy. Hijabed women in a sexy selfie are one example of it. The action of selfie photo becomes a new trend in line with the popularity of visual-based social media like Instagram. Taking and uploading selfie photos on Instagram seems to be indispensable for some people, including hijabed women. This paper is aimed to examine photos of sexy selfie of hijabed women uploaded in Instagram account @jilbabootd. The purpose of this paper is to reveal the practice of objectification of a women’s bodies by analyzing the comments raised by followers of account @jilbabootd. This study is framed by Lacan's psychoanalytic theory of desire, lack, and pleasure. The @jilbabootd account is intentionally created for the purpose of the self-certified sexy self-certified photo shoot. Women who become an admin in the @jilbabootd account reproduce the discourse of male gaze. Women who become followers in this account also perpetuate the male domination of women by giving comments that the language is very male (manly). The hijabed women who send sexy selfie photos are "willingly" expose their bodies to become objects of male fantasy, gaze, and pleasure. They get their own pleasure by becoming the objects of gaze.
The effects of oral administration of Croton penduliflorus seed oil and Depo provera on liver and kidney functions of pregnant Dutch-white rabbits.

This study investigated the effects of oral administration of Croton penduliflorus seed oil (CSPO) and Depo provera on liver and kidney function of pregnant rabbits. Graded doses of CSPO were suspended in 5% Tween 20 solution. Twenty-five pregnant Dutch-white rabbits at mid–gestation were allocated into 5 groups. Group 1 animals served as control and received 1ml daily of 5% Tween 20 while groups 2-4 received 50, 100 or 150 mg/kg body weight oral dose of CPSO for 10 consecutive days. Animals in group 5 received one intramuscular injection of 2.73 mg/kg of Depo provera. Withdrawal of treatment was followed by 18 hrs fast, and then sacrificed. Blood samples from fasted animals were collected from all groups and analyzed for liver and kidney function parameters. CSPO caused significant (P © 2010 International Formulae Group. All rights reserved. Keywords: Croton penduliflorus , Depo provera, biliary obstruction.
Community detection in dynamic networks

A reasonable representation of some complex systems such as social and biological systems is a network topology that allows its components and interactions among them to change over time. Understanding the time-dependence of these networks can lead to invaluable insight about characteristics and structure of time-varying networks. In this thesis, several classes of static and dynamic clustering algorithms and ideas are reviewed. A challenge arising in dynamic clustering schemes is that the detected communities are not independent over time and the identified clusters at one point of time should not dramatically deviate from the results of previous timesteps. It is especially important to reduce large short term variations and ensure that communities smoothly change over time. Here we present a novel method which is built upon a probabilistic generative Bayesian model to address the problem of identifying consistent and stable overlapping communities in dynamic networks. Synthetic and real networks are used to evaluate the performance with respect to different parameter settings, the model order selection, and the run-time of the proposed algorithm. Performance analysis indicates thatthe algorithm proposed in this thesis outperforms several other state-of-the-art algorithms and provides valuable insights into the evolution and underlying structure. %%%%Une representation raisonnable de certains systemes complexes tels que les systemes sociaux et biologiques est une topologie de reseau qui permet a ses composants et les interactions entre eux de changer au fil du temps. Comprendre la dependance temporelle de ces reseaux, conduire a de precieux renseignements sur les caracteristiques et la structure de variables dans le temps des reseaux. Dans cette these, plusieurs classes d'algorithmes de clustering statiques et dynamiques et des idees sont passees en revue. Un defi se pose dans des plans de regroupement dynamiques est que les communautes detectees ne sont pas independants dans le temps et les grappes fondees a un moment donne du temps ne doit pas s'ecarter de facon spectaculaire a partir des resultats de pas de temps precedents. Specialement, il est de l'importance de diminuer de fortes variations a court terme et d'assurer que les communautes progressivement changer au fil du temps. Ici, nous presentons une nouvelle methode qui repose sur un modele bayesien generatif probabiliste pour resoudre le probleme de l'identification des communautes stables et coherentes qui se chevauchent dans les reseaux dynamiques. Reseaux synthetiques et reelles sont utilisees pour evaluer la performance par rapport a differents parametres, la selection pour modele, et le moment de l'execution de l'algorithme propose. Analyse de la performance indique quel'algorithme propose dans cette these surpasse plusieurs autres algorithmes et revele l'apercu inestimable d'un reseau e-mail reelle.
SYMPHONY : a controller for hybrid software defined networks

Software Defined Networks (SDN) is currently an active area of research. As enterprises migrate to SDN, an inevitable network transitional state is a brownfield state, where both Software Defined and Legacy networks coexist. To achieve interoperability between legacy and Software Defined Networks and to leverage the existence of OpenFlow devices in the traditional network to improve existing network state, a Hybrid SDN controller is a desirable addition to any brownfield deployment of SDN.The thesis of this work aims to further the knowledge in the area of Hybrid Software Defined Networks by highlighting the requirements and challenges to be addressed while integrating legacy and Software Defined Networks. The requirements and challenges discussed in this thesis focus on path computation, packet forwarding, and centralised policy application. This is achieved by building a Hybrid SDN Controller. The main controller components controller application that runs on POX, a route server to store legacy network information, a next-hop module, a path discovery module and a policy module. We also discuss three use cases of SYMPHONY hybrid SDN controller to demonstrate the controller's application and usefulness. We also perform few key tests to determine the efficiency of deploying a hybrid SDN controller in a network.
PENGARUH METODE PRAKTEK TERHADAP BELAJAR LAY UP SHOOT DALAM PEMBELAJARAN BOLA BASKET (Peserta ekstrakulikuler siswa SMK Pasundan Subang)

Bola basket termasuk jenis olahraga yang kompleks gerakannya. Artinya gerakannya terdiri dari gabungan unsur-unsur gerak yang terkoordinasi rapi. Untuk itu seorang pemain harus menguasai semua teknik dasar bola basket khususnya teknik lay up shoot karena kelihatannya mudah dilakukan, hal ini tidak semudah itu. Dapat disimpulkan bahwa latihan menggunakan metode praktek dapat menjadi salah satu solusi untuk mempelajari dan meningkatkan hasil lay up shoot bagi pemain basket pemula. Penelitian ini bertujuan untuk mengetahui pembelajaran metode praktek dapat memberikan peningkatan terhadap hasil belajar lay up shoot pada siswa peserta ekstrakulikuler bola basket SMK Pasundan Subang. Penelitian ini merupakan penelitian eksperimen dengan memberikan perlakuan (treatment) pada kelompok eksperimen, dengan membagi menjadi dua kelompok, yaitu kelompok eksperimen A dengan perlakuan latihan metode praktek dan kelompok eksperimen B sebagai kelompok control. Populasi dalam penelitian ini adalah keseluruhan siswa peserta ekstrakulikuler bola basket SMK Pasundan Subang yang berjumlah 20 siswa. Sampel yang diambil dengan total sampling berjumlah 20 siswa. Instrumen yang digunakan adalah tes lay up shoot dari Imam Sodikun dengan validitas tes 0,509 dan reliabilitas tes 0,675. Analisis data menggunakan uji prasyarat, dan uji t. Hasil analisis menunjukan ada pengarah yang signifikan hasil dari latihan Metode Praktek pada kelompok eksperimen, dengan t hitung= 4,389> t tabel= 2,101 dan nilai signifikansi p sebesar 0,000< 0,05. Oleh karena itu dapat ditarik sebuah kesimpulan bahwa latihan metode praktek dapat memberikan hasil yang signifikan terhadap peningkatan belajar lay up shoot bola basket peserta ekstrakulikuler bola basket SMK Pasundan Subang.
Scalable and Efficient Algorithms for Unstructured Mesh Computations

The growing need for numerical simulations results in larger and more complex computing centers and more HPC softwares. Actual HPC system architectures have an increasing requirement for energy efficiency and performance. Recent advances in hardware design result in an increasing number of nodes and an increasing number of cores per node. However, some resources do not scale at the same rate. The increasing number of cores and parallel units implies a lower memory per core, higher requirement for concurrency, higher coherency traffic, and higher cost for coherency protocol. Most of the applications and runtimes currently in use struggle to scale with the present trend. In the context of finite element methods, exposing massive parallelism on unstructured mesh computations with efficient load balancing and minimal synchronizations is challenging. To make efficient use of these architectures, several parallelization strategies have to be combined together to exploit the multiple levels of parallelism. This P.h. D. thesis proposes several contributions aimed at overpassing this limitation by addressing irregular codes and data structures in an efficient way. We developed a hybrid parallelization approach combining the distributed, shared, and vectorial forms of parallelism in a fine grain taskbased approach applied to irregular structures. Our approach has been ported to several industrial applications developed by Dassault Aviation and has led to important speedups using standard multicores and the Intel Xeon Phi manycore.
Distributed energy efficient backbone construction utilizing particle swarm optimization algorithm in wireless sensor networks with bidirectional links

— Connected dominating set (CDS) problem is the most widely used method for backbone formation in wireless sensor networks. To date, numerous algorithms have been proposed for backbone construction on minimum CDS (MCDS) problem in unit disk graphs (UDG); however, only a few algorithms have been proposed on MCDS problem in disk graphs with bidirectional links (DGB) and on degree-constrained minimum-weight CDS (DC-MWCDS) problem in UDG. To the best of our knowledge, no work has been done on DC-MWCDS problem in DGB. In this paper, we present the OEDC-MWCDS problem (optimal energy and degree constrained minimum-weight connected dominating set) for energy efficient backbone construction in wireless sensor networks. Then, we model a wireless sensor network as a disk graph with bidirectional links and propose a backbone construction algorithm called EBC-PSO (energy efficient backbone construction utilizing particle swarm optimization algorithm) to obtain a CDS with the minimum weight subject to the optimal energy and degree constraints. The main objective of the proposed algorithm is to find the optimal values of energy and degree constraint to maximize network lifetime. In the proposed algorithm, optimal coefficients of minimum remaining energy and maximum degree of nodes are determined utilizing PSO algorithm. Then, in the selection of DS nodes, these coefficients are used. Simulation results verify the performance of the proposed algorithm in terms of network lifetime and backbone size.
Polychlorinated biphenyl congeners as markers of toxic equivalents of polychlorinated biphenyls, dibenzo-p-dioxins and dibenzofurans in breast milk.

In breast milk, concentrations of polychlorinated biphenyls (PCBs) are higher than those of polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs), making PCB analyses less time-consuming and expensive. We searched for PCB "markers" of PCDD/DF concentrations, by studying associations between concentrations of PCB and PCDD/DFs (expressed as toxic equivalents, TEQs) in breast milk from 27 women (primiparas, 22-35 years). These women donated breast milk in 1996-1999 together with 183 other primiparas from Uppsala County, Sweden. Regression analyses showed that both dioxin-like and non-dioxin-like penta- to hepta-chlorinated PCBs could be used as markers of TEQ concentrations in this group of women, in some cases after age adjustment of the regressions. The strong positive association between concentrations of dioxin-like PCB/DD/DFs and non-dioxin-like PCBs will in future epidemiological studies make it difficult to separate Ah receptor-dependent effects from non-Ah receptor-dependent effects. With the use of regression equations and concentrations in breast milk samples collected in 1994, TEQ concentrations were estimated in the 1994 samples. Comparisons between estimated and measured concentrations indicated that associations between concentrations of marker substances and TEQs should be determined separately within each study population, in order to obtain reliable TEQ exposure assessments from PCB markers.
A Theme-Context Mixture Model for Personalized Search in Social Network

Nowadays, social network technology provided a lot of ways for users to express their emotions and attitudes online. How to model user preferenced information and provide personalized service is a crucial problem in big data era. In this paper, a new probabilistic model be proposed to model and analysis topic trends in personalized search. The model extended the Latent Dirichlet Allocation (LDA) model by introducing context variables, through which we can detect and analysis topic trends according to contextual information. The core idea of proposed probabilistic model is to learn a finite Dirichlet mixture model, and then adopt Bayesian discriminant to detect topic and topic trends analysis. Experimental results show that the proposed probabilistic mixture model can detect topics and discover topic trends effectively.
Modeling units of study from a pedagogical perspective: the pedagogical meta-model behind EML

This text is a short summary of the work on pedagogical analysis carried out when EML (Educational Modelling Language) was being developed. Because we address pedagogical meta-models the consequence is that I must justify the underlying pedagogical models it describes. I have included a (far from complete) list with literature used in the pedagogical analysis. I am sorry for its length, but for every pedagogical meta-model it is crucial to define the space of models where it is ‘meta’ to. As an aid to comprehension, I will use UML diagrams to express static and dynamic relationships when appropriate. All diagrams are drawn from a conceptual perspective and not from an implementation perspective. This paper is provided as input for the IMS Learning Design group. Please mail comments, questions and any other reactions to: rob.koper@ou.nl With thanks to Adrian Rawlings for reviewing this version.
Preliminary Work Towards Development of a Dynamic Job Shop Scheduling Model

This paper presents a preliminary work on a development of dynamic job shop scheduling model. The motivation of the study comes from an urgent need for practical procedures to enable easier and accurate feedback at operational level particularly related to job shop in small and medium-sized companies. A spreadsheet-based scheduling template is formulated and modeled using Microsoft Excel. A job shop benchmark case study available in OR-Library has been chosen to demonstrate the applicability of the basic model. The preliminary result indicating that the proposed spreadsheet model needs further refinement through incorporation of dynamic factors to be obtained from industrial practitioners.
Scalable monitoring for multiple virtualized infrastructures for 5G services

— This paper presents the high level architecture and functionality details of the monitoring framework that has been implemented and integrated within the SONATA project, in order to support the management of 5G services under the SDN/NFV paradigm. The innovative framework, extending the functionality of Prometheus.io, is unique in its support for multiple types of virtualized infrastructure, supporting multiple Points of Presence (PoP), is extensible using Websockets, and is fully available in open-source.
Effect of progressive resistance exercise training on hepatic fat in Asian Indians with non-alcoholic fatty liver disease.

Introduction: Nonalcoholic fatty liver disease (NAFLD) is closely associated with obesity and insulin resistance and lifestyle measures form the cornerstone of therapy. Objective: To study the effect of progressive resistance training (PRT) on hepatic fat Research Article British Journal of Medicine & Medical Research, 4(1): 114-124, 2014 115 content, body composition and insulin sensitivity in patients with NAFLD. Methods: This study included 24 adult patients with NAFLD diagnosed on ultrasonography. Subjects with alcohol intake >140 gm/week and any secondary cause of fatty liver were excluded. Patients underwent thrice weekly sessions (40 minutes each) of resistance exercises including flexion at biceps, triceps, and hip flexion, knee extension and heel rise for 12 weeks. Preand post-intervention evaluation included anthropometry, BIA analysis, short insulin tolerance test (SITT), lipid profile and hepatic fat quantification by MRI. Results: Twenty four patients (17 males, 7 females, mean age 39.8±10.5 yrs) completed the study protocol with 78.7% compliance to PRT protocol. There was significant decrease in waist, hip and mid-thigh circumferences and skinfold thicknesses at biceps, triceps, subscapular and suprailiac regions (p<0.05), with no significant change in BMI and WHR. Insulin sensitivity improved significantly at 12 weeks as indicated by increase in k-value (rate of change of glucose) on SITT (0.84 vs 1.3, p=0.002). A decrease in total cholesterol and LDL-c with increase in HDL-c was noted after 12 weeks (p<0.05). Hepatic fat content also decreased at 12 weeks (22.3±3.9 vs 21.4±4.0 %, p=0.01). Conclusion: Moderate intensity PRT is associated with significant improvement in hepatic fat, truncal subcutaneous fat and insulin sensitivity in patients with NAFLD.
Machine Learning Methods for Life Sciences: Intelligent Data Analysis in Bio- and Chemoinformatics

In the past few years, experimental techniques in the life sciences have undergone a rapid progress. Moreover, the integration of methods from different disciplines has led to the formation of new fields of research, like imaging genetics, molecular medicine and biological psychology. The experimental progress has come along with an increasing need for intelligent data analysis, which aims at analyzing a given dataset in the most promising way taking domain knowledge into account. This includes the representation of the data, the choice of variables, the preprocessing, the handling of missing values, the model assumptions, the choice of methods for prediction, model selection and regularization, as well as the interpretation of the results. The topic of this thesis is intelligent data analysis in the fields of bioinformatics and chemoinformatics using machine learning techniques. The goal of imaging genetics is to gain insight into genetically determined psychiatric diseases by association studies between potentially relevant genetic variants and endophenotypes. In this thesis, two different methods for an exploratory analysis are developed: The first method is based on P-SVM feature selection for multiple regression and models additive and multiplicative gene effects on an endophenotype using a sparse regression model. The second method introduces a new learning paradigm called target selection to model the association between a single genetic variable and a multidimensional endophenotype. Often, several different models for genetic association are suggested in the literature, and the question is how much evidence a measured dataset provides for each of them. For this purpose, a method for model comparison in imaging genetics is suggested in this thesis, which is based on the use of information criteria. The aim of quantitative structure activity relationship (QSAR) analysis is to predict the biological activity of compounds from their molecular structure. Traditionally, QSAR methods are based on extracting a set of molecular descriptors and using them to build a predictive model. In this thesis, a descriptor-free method for 3D QSAR analysis is proposed, which introduces the concept of molecule kernels to measure the similarity between the 3D structures of a pair of molecules. The molecule kernels can be used together with the P-SVM, a recently proposed support vector machine for dyadic data, to build explanatory QSAR models which do not require an explicit descriptor construction. The resulting models make direct use of the structural similarities between the compounds which are to be predicted and a set of support molecules. The proposed method is applied to QSARand genotoxicity datasets.
Ejective harmony in Lezgian

This paper contributes to the typology of laryngeal harmony by analysing an unusual case of long-distance laryngeal co-occurrence restrictions and alternations in Lezgian. This pattern, previously unmentioned in the phonological literature, is the first known case of alternations involving ejective harmony. In Lezgian, local processes mask the interaction of ejectives and plain voiceless stops. This is robustly supported by our dictionary analysis, which reveals a ban on the co-occurrence of ejectives and plain voiceless stops within the foot. Both harmony alternations and static co-occurrence restrictions are sensitive to foot structure, unlike previous cases of consonant harmony. Harmony also interacts opaquely with vowel syncope, and certain co-occurrences of plain and ejective stops are resolved with dissimilation rather than harmony, showing a conspiracy to avoid co-occurrences. We demonstrate an account within the Agreement by Correspondence framework and discuss implications for the typology and analysis of consonant harmony.
Short Communication Stereo inverse perspective mapping: theory and applications

This paper discusses an extension to the inverse perspective mapping geometrical transform to the processing of stereo images and presents the calibration method used on the ARGO autonomous vehicle. The article features also an example of application in the automotive field in which the stereo inverse perspective mapping helps to speed up the process. q 1998 Elsevier Science B.V. All rights reserved.
Ergoferon and improvement of etiopathogenetic therapy of influenza and acute respiratore viral infection in adults

The therapeutic efficacy and tolerance of ergoferon, an antiviral medication combining anti-inflammatory and antihistaminic actions were estimated in the treatment of adult patients with influenza and acute respiratory viral infection. Ergoferon was shown to stimulate production of endogenous interferon-alpha and interferon-gamma and to normalize the T-lymphocyte subpopulation composition and histamine level, that made it possible to lower the time of the disease clinical signs development and to prevent typical complications and chronic somatic pathology exacerbation.