Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring happiness in large population

The ability to know emotional states for large number of people is important, for example, to ensure the effectiveness of public policies. In this study, we propose a measure of happiness that can be used in large scale population that is based on the analysis of Indonesian language lexicons. Here, we incorporate human assessment of Indonesian words, then quantify happiness on large-scale of texts gathered from twitter conversations. We used two psychological constructs to measure happiness: valence and arousal. We found that Indonesian words have tendency towards positive emotions. We also identified several happiness patterns during days of the week, hours of the day, and selected conversation topics.
Targeted Projection Pursuit Tool for Gene Expression Visualisation

Summary A tool is introduced that uses a novel technique to enable users to explore two-dimensional views of high dimensional gene expression data sets. Unlike other such tools, the interface is intuitive and efficient, allowing the user to easily select views that meet their requirements. The tool is tested on publicly available gene expression data sets and demonstrated to find views that show the seperation of gene expression data sets into classes more effectively than standard dimension-reduction methods.
An OFDM Symbol Design for Reduced Complexity MMSE Channel Estimation

In this paper we revisit the minimum mean square error (MMSE) pilot-aided channel estimation for broadband orthogonal frequency division multiplexing (OFDM) systems. The careful design of OFDM symbol leads to the proposal of a simplified time-domain (TD) MMSE estimator. By exploring the Fourier properties of the symbol, the investigated method eliminates the need to use direct or inverse discrete Fourier transforms (DFT/IDFT) before the channel estimation, by using the TD received symbol samples as the input to the MMSE filter. Moreover, performing the estimation in TD (where the channel impulse response (CIR) energy is mainly limit to a small set of samples), makes way to a simple, nonetheless efficient estimation of the filter parameters. The performance of the channel estimation scheme, using the estimated parameters, presents a tolerable degradation when compared with the ideal situation (a-priori knowledge of the channel correlation and noise variance), while exhibiting a reduced computational load. The feasibility of the investigated method is substantiated by system simulation using indoor and outdoor wireless channel models.
Linguistic Variation, Cultural Influence and Identity Building in Ethiopian Trade Center Towns: the Case of Maichew

There are societies where their community reflects a language as well as culture of two or more societies. These kinds of situations are more found in places that are mostly used as trade centers. Practically, trade centers are areas where various people come from different places to exchange goods and services, however, trade centers are also center to people’s exchange of various social, political, and linguistic features. Thus, owing to social factors such like intermarriage, people may start to permanently live in the towns. As a result, as the new arrivals start to share their various cultural practices, linguistic elements and attitudes with the original community, there may appear a language and culture that reflects the influence of others. Therefore, the intention of the researcher was to show, in trade center towns like Maichew, how the presence of various ethnic groups contributed to the language and culture of the community and to look into the attributes of identity that are used by the community members to define their individual and group identity. The researcher incorporated participants using a convenience sampling and used a qualitative method to delve the core features the language undergoes as to vary from the standard Tigrigna, probe the cultural practices of the community which are peculiar and reengineered for the purpose of harmonization and inquire the attributes of identity and their level of importance to define individuals and group. Furthermore, a quantitative method is used to look into the distribution of ethnic groups in the community. As a result, as the language maintains phonetic feature variation, undergoes a phonological process for variation purpose, shows a lexical and structural variation from the standard Tigrigna, the culture of the community harmonizes cultural practices that can be traced to the Agaw, Amhara, Oromo, Tigray: particularly the Agame and Afar ethnic groups. The study also found out that the community members use several attributes to define their individual identity considering the importance of attributes but use the language which is different from the standard Tigrigna as means of their group identity. Generally, the study confirms that identity is an ongoing process in which the attributes used to construct are determined by those values and elements society regards most. iii
Review article The role of basal ganglia in controlling cognitive functions

According to current knowledge, basal ganglia are no longer solely associated with movement control. Due to the complex structural and functional connections of basal ganglia with widespread regions of the cortex, especially with associative prefrontal cortex, the basal ganglia contribute to many functions, including: selective gating function, selecting between competing actions, maintaining information in the working memory, goal selection, planning and sequencing of behavioural acts. This does not mean that the basal ganglia play that role themselves, but rather that the basal ganglia complement the role of the frontal cortex. To simplify, we can say that the role of the basal ganglia with respect to the frontal cortex is initiation of movement and cognitive actions. The basal ganglia in collaboration with the frontal cortex play a role in the decision-making process, in selecting motion and cognitive acts, in set shifting and working memory. A common source of knowledge on the role of the basal ganglia in cognitive regulation is provided by the numerous recently developed neurocomputational models attempting to reproduce the relation between the basal ganglia and the frontal cortex in controlling higher cognitive functions. Another source of knowledge is constituted by data resulting from neuroimaging studies enabling one to detect the activity of selected structures of the basal ganglia during performance of specific cognitive tasks, as well as by anatomical data.
Design of Steerable Linear and Planar Array Geometry with Non-uniform Spacing for Side-Lobe Reduction

In this paper, we present a noble pattern synthesis method of linear and planar array antennas, with non-uniform spacing, for simultaneous reduction of their side-lobe level and pattern distortion during beam steering. In the case of linear array, the Gauss-Newton method is applied to adjust the positions of elements, providing an optimal linear array in the sense of side-lobe level and pattern distortion. In the case of planar array, the concept of thinned array combined with non-uniformly spaced array is applied to obtain an optimal two dimensional (2-D) planar array structure under some constraints. The optimized non-uniformly spaced linear array is extended to the 2-D planar array structure, and it is used as an initial planar array geometry. Next, we further modify the initial 2-D planar array geometry with the aid of thinned array theory in order to reduce the maximum side-lobe level. This is implemented by a genetic algorithm under some constraints, minimizing the maximum side-lobe level of the 2-D planar array. It is shown that the proposed method can significantly reduce the pattern distortion as well as the side-lobe level, although the beam direction is scanned.
Text Retrieval with External Information

Aimof this paper is to propose a statistical strategy based on the Partial Least Squares Regression (PLSR) in order to exploit external information in Text Mining processes. We focus on Text Retrieval, a procedure aimed at finding interesting information in large textual collections. In order to exploit external information, often available in collections, we assume a dependence structure between two sets of textual variables. By means of PLSR a latent structure taking into account word similarities and external information is obtained. Projection of documents and queries on the obtained latent structure allows effective document retrieval. The suggested strategy is applied to data which consist of two sets of variables: words of journal article abstracts and their respective keywords. The investigated approach enables more effective documents retrieval, as it takes into account the external information given by the
Varieties of universalism: post-1990s developments in the initial school-based model of VET in Finland and Sweden and implications for transitions to the world of work and higher education

Abstract The Nordic countries are often referred to as a group even though their education systems and training models are very different. The aim of this study is to advance understanding of those differences and compare the developments and organisation of initial vocational education and training (IVET) in Finland and Sweden since the 1990s as examples of school-based models of IVET in statist regimes. The research questions address the following: how these two countries have institutionalised school-based IVET since the 1990s; the kinds of legislative reforms that have been decisive for the construction of school-based IVET; and how the models of school-based IVET in these two countries allow access to higher education and the world of work. The analysis shows the heterogeneity of the statist model of school-based IVET systems in two Nordic countries and underlines differences with respect to school-to-work transitions between IVET and different labour market sectors.
Deoxycholic Acid Could Induce Apoptosis and Trigger Gastric Carcinogenesis on Gastric Epithelial Cells by Quantitative Proteomic Analysis

Background. Pathologic duodenogastric reflux can induce or aggravate gastritis because of the presence of bile acids. Bile reflux has been generally considered to be associated with intestinal metaplasia and gastric cancer. However, the pathogenic mechanisms of the effects of bile acids on gastric mucosa are still unknown. Methods. To explore the mechanisms by which bile acids induce gastric mucosal lesions, we examined cell apoptosis in the gastric epithelial cell line GES-1 and investigated the changes in protein profiles of GES-1 cells in response to a bile acid deoxycholic acid using a proteomics approach. Changes in the profiles of the differently expressed proteins were analyzed using the DAVID and STRING programs. Results. We found apoptosis was significantly induced in GES-1 cells by deoxycholic acid. Using liquid chromatographic/tandem mass spectrometric (LC-MS/MS) methods, 134 upregulated proteins and 214 downregulated proteins were identified in the bile acid treated GES-1 cells. Bioinformatics analysis revealed the interactions and signaling networks of these differentially expressed proteins. Conclusion. These findings may improve the understanding of the molecular mechanisms underlying the pathogenicity of bile acids on gastric mucosa.
High Performance and Low-Power Full Adder

Full adders (FAs) are essential for digital circuits including microprocessors, digital signal processors, and microcontrollers . Both the power consumption and the reliability of FAs are crucial as they directly affect: arithmetic logic units, floating-point units, as well as memory address calculations. This paper studies the effect threshold voltage (VTH) variations play on the reliability of a classical 28- transistor FA, and shows that reliability can be enhanced without increasing the occupied area, and while also reducing power consumption. An enabling transistor sizing scheme is used to improve on reliability without increasing power consumption (as reducing and limiting currents). The proposed FA in 16nm predictive technology model (PTM) is significantly more reliable (six orders of magnitude in case of Cout, and three orders of magnitude in case of Sum at 10% input variations) and dissipates 38× less than a classical FA, while being 6× slower.
Autonomy in Paid Work and Employee Subjective Well-Being

This article explores the relationship between different forms of autonomy, categorized into “job control” and “schedule control,” and measures of subjective well-being, using UK panel data from Understanding Society. Levels of autonomy differ considerably among UK employees. Managers report the greatest autonomy. Professionals, especially women, and less skilled occupations report substantially less. Panel probit, analysis of covariance, and change-score analysis evidence not only the positive impact of autonomy but also the differentiated and gendered relationship between autonomy and subjective well-being measures. Job control, including over tasks and pace of work, increases job and leisure satisfaction. Autonomy over work manner increases leisure and life satisfaction, but only among women. Informal schedule control has positive impacts on job (men and women) and life (men only) satisfaction.
A Novel approach for Detection of Distributed Denial of Service attack in VANET

Vehicular ad hoc Networks (VANETs) are new upcoming technology providing appropriate communication to the vehicles as well as passengers with no fixed infrastructure. In today’s life, maintaining the heavy traffic is very difficult that gives bad impact to roads safety and throughput of network. Researchers have done a lot of work in VANET, but still the security got affected from malicious attacks. To maintain the availability, network must be available at the time when vehicles interact with each other. This paper introduces a scheme to detect DDoS attack, as this attack gives adverse effect to network availability. According to our scheme, a Local Protection Node (LPN) is selected from the hierarchical architecture. PDR value and the threshold value has been compared, when these two values become equal a Monitor mode message is to be transmitted by LPN to other vehicles in the network for the purpose of sensing. Any vehicle that injects large number of false packets will be detected as an attacker and thus packets from evil node will be discarded. The proposed scheme is very simple and efficient. General Term Security
Twisted bundles on noncommutative T 4 and D-brane bound states

We construct twisted quantum bundles and adjoint sections on noncommutative $T^4$, and investigate relevant D-brane bound states with non-Abelian backgrounds. We also show that the noncommutative $T^4$ with non-Abelian backgrounds exhibits SO$(4,4|Z)$ duality and via this duality we get a Morita equivalent $T^4$ on which only D0-branes exist. For a reducible non-Abelian background, the moduli space of D-brane bound states in Type II string theory takes the form $\prod_a (T^4)^{q_a}/S_{q_a}$.
Anycast Routing in Probabilistically Contacted Delay Tolerant Networks

Delay tolerant networks (DTNs) experience frequent and long lasting network disconnection due to various reasons such as mobility, sleep scheduling, etc. Anycast routing is an important and challenging problem in DTNs. In this paper, we study the single-copy message anycast routing problem in probability-contacted DTNs. We first define a novel metric MDRA (Maximum Delivery Rate for Anycast) to indicate the maximum successful probability of anycast routing, and then propose the MDRA routing algorithm based on this metric. Rigorous theoretical analysis shows that such a anycasting strategy is the optimal. Moreover, we propose an efficient algorithm to compute the MDRA values of all nodes. The computation overhead of this algorithm only is O(|S|^2|T|) where |S| is the number of nodes in the network and |T| is the TTL (Time To Live) value of messages. In addition, through extensive simulations based on real DTN traces, we demonstrate that our algorithms can significantly perform better than the previous ones.
Protein Secondary Structure Prediction Using Support Vector Machines (SVMs)

Bioinformatics or computational biology is field of science in which biology, computer science and information technology merges into a single discipline. In modern computation biology, protein secondary structure prediction is a major problem. Secondary structure prediction is depends on its amino acid sequence. Current studies prefer machine learning techniques for classification and regression task. Recently many researchers used various data mining and machine learning tool for protein structure prediction. Our intention is to use model based (i.e., supervised learning) approach for protein secondary structure prediction and our objective is to enhance the prediction of 2D protein structure problem using advance machine learning techniques like, linear and non-linear support vector machine with different kernel functions. The datasets used for this problem are Protein Data Bank (PDB) sets, which is based on structural classification of protein (SCOP), RS126 and CB513.
Local Flaps: A Real-Time Finite Element Based Solution to the Plastic Surgery Defect Puzzle

One of the most fundamental challenges in plastic surgery is the alteration of the geometry and topology of the skin. The specific decisions made by the surgeon concerning the size and shape of the tissue to be removed and the subsequent closure of the resulting wound may have a dramatic affect on the quality of life for the patient after the procedure is completed. The plastic surgeon must look at the defect created as an organic puzzle, designing the optimal pattern to close the hole aesthetically and efficiently. In the past, such skills were the distillation of years of hands-on practice on live patients, while relevant reference material was limited to two-dimensional illustrations. Practicing this procedure on a personal computer [1] has been largely impractical to date, but recent technological advances may come to challenge this limitation. We present a comprehensive real-time virtual surgical environment, based on finite element modeling and simulation of tissue cutting and manipulation. Our system demonstrates the fundamental building blocks of plastic surgery procedures on a localized tissue flap, and provides a proof of concept for larger simulation systems usable in the authoring of complex procedures on elaborate subject geometry.
Decision making with long delays using networks of flip-flop neurons

Decision making tasks that involve processing of sequential stimuli with long delays pose a significant challenge to modeling using current methods in neural networks. However, decision making in animals involves storage of salient stimuli over long periods of time, robust maintenance of this information in the presence of noisy input, and subsequent recall and processing at the time of final decision. In the field of digital design, a new element that appears in sequential networks, an element that is absent in static, combinatorial logic networks, is the flip-flop. Taking cue from this aspect of digital design, we propose to design neural networks with flip-flop neurons, to address problems involving storage and recognition of stimuli for long time durations. We simulate two kinds of flip-flops the SR flip-flop and the T flip-flop using dynamic neurons. We construct multilayer neural architectures in which a layer of flip-flop neurons is sandwiched between two multilayer perceptrons (MLPs). We then derive gradient-descent-based training rules for these hybrid networks. Several benchmark tasks in sequential processing were successfully learnt and solved by the proposed network architectures. These tasks include the 2-sequence task, 1-2-AX-BY task and the Parity problem. Performance of the network compares favorably with existing sequential neural networks models applied to the same problems. Finally, we discuss the limitations of networks based on the type and number of flip-flops present in the network.
Friendly prodding and other sources of change in Cuba

L'A. rappelle que Cuba a connu une crise economique grave entre 1990 et 1993 apres l'effondrement du monde communiste. Il montre que ce pays a entrepris un certain nombre de reformes economiques pour pallier cette situation. Il met en relief l'impact economique de l'embargo decrete par les Etats-Unis. Il examine, dans un premier temps, les reformes entreprises dans ce pays. Il souligne que les structures economiques, les strategies economiques de type socialistes et de type privees semblent entrer en conflit. Il pose le probleme de l'insertion de Cuba dans le cadre de l'economie internationale. Il examine les relations economiques de Cuba avec le Canada, le Mexique, l'Union Europeenne ainsi qu'avec les autres pays d'Amerique latine et des Caraibes
A Normative Database for Quantitative Motor Assessment

We created a Quantitative Motor Assessment (QMA) to assess neuromuscular health and to identify motor deficits that affect human performance. Using custom software and an inexpensive novel motion capture sensor, we adapted and automated traditional subjective motor assessments in an integrated system that is quick, lowcost, and highly sensitive. We administered the QMA to 104 (53 males and 51 females) healthy individuals 18-50 years old in order to establish a normative database of unimpaired motor behavior. We expect that the sensitivity, objectivity, low cost, portability, and ease of use make the QMA a beneficial and accessible tool to clinicians as well as researchers.
Detecting Drowsy Drivers Using Machine Learning Algorithms

Driver drowsiness contributes to many car crashes and fatalities in the United States. Machine learning algorithms have shown to help in detecting driver drowsiness. We try different machine learning algorithms on a dataset collected by the NADS-1 [1] simulator to detect driver drowsiness. We generate different aggregation features on the time-series data and evaluate the performance of the feature sets. We find that aggregation at the more fine-grained “per-event” level improves the outcome of classification compared to the high-level “per-run” aggregation.
Lac repressor hinge flexibility and DNA looping: single molecule kinetics by tethered particle motion

The tethered particle motion (TPM) allows the direct detection of activity of a variety of biomolecules at the single molecule level. First pioneered for RNA polymerase, it has recently been applied also to other enzymes. In this work we employ TPM for a systematic investigation of the kinetics of DNA looping by wild-type Lac repressor (wt-LacI) and by hinge mutants Q60G and Q60 + 1. We implement a novel method for TPM data analysis to reliably measure the kinetics of loop formation and disruption and to quantify the effects of the protein hinge flexibility and of DNA loop strain on such kinetics. We demonstrate that the flexibility of the protein hinge has a profound effect on the lifetime of the looped state. Our measurements also show that the DNA bending energy plays a minor role on loop disruption kinetics, while a strong effect is seen on the kinetics of loop formation. These observations substantiate the growing number of theoretical studies aimed at characterizing the effects of DNA flexibility, tension and torsion on the kinetics of protein binding and dissociation, strengthening the idea that these mechanical factors in vivo may play an important role in the modulation of gene expression regulation.