Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the effect of meta-individual values on management of software development using Schwartz's model: A case of Thai IT professionals

The management of software development is a vital factor which leads to the success of the software project. The most important component involved in the project is the team members. Meta-individual values of Thai IT professionals should affect the software development management practices. In this research, we found that self-transcendence and openness to change have influence on every software development practice. However, conflicting meta-individual value is also involved. Mixed meta-individual values are required for the smooth performing and conducting software development management practices. Moreover, Thai IT professionals are influenced by national culture.
Collaboration on Social Media: Analyzing Successful Projects on Social Coding

Social Coding Sites (SCSs) are social media services for sharing software development projects on the Web, and many open source projects are currently being developed on SCSs. One of the characteristics of SCSs is that they provide a platform on social networks that encourages collaboration between developers with the same interests and purpose. For example, external developers can easily report bugs and improvements to the project members. In this paper, we investigate keys to the success of projects on SCSs based on large data consisting of more than three hundred thousand projects. We focus on the following three perspectives: 1) the team structure, 2) social activity with external developers, and 3) content developed by the project. To evaluate the success quantitatively, we define activity, popularity and sociality as success indexes. A summary of the findings we obtained by using the techniques of correlation analysis, social network analysis and topic extraction is as follows: the number of project members and the connectivity between the members are positively correlated with success indexes. Second, projects that faithfully tackle change requests from external developers are more likely to be successful. Third, the success indexes differ between topics of softwares developed by projects. Our analysis suggests how to be successful in various projects, not limited to social coding.
Indigenous Practices of Water Management for Sustainable Services

This article explores the possibility of incorporating traditional water management experiences into modern water management. After the literature review, two case studies are presented from Borana and Konso communities in southern Ethiopia. The study was conducted through interviews, discussions, and observations. The two cases were selected due to their long existence. Both communities have their own water source types, depending on local hydrogeological conditions. Borana is known for the so-called Ella (wells) and Konso for Harta (ponds), which have been managed for more than five centuries. All government and development partners strive to achieve sustainable services in water supply and sanitation. Therefore, they design various management packages to engage the communities and keep the systems sustainable. However, the management components are often designed with little attention to local customs and traditions. The cases in the two communities show that traditional knowledge is largely ignored when replaced by modern one. However, the concepts of cost recovery, ownership experience, equity, enforcement, integrity, and unity, which are highly pronounced in modern systems, can also be found in the traditional water managements of Borana and Konso. Naturally, one shoe never fits all. Borana and Konso experiences are working for their own community. This research implies that when we plan a project or a program for a particular community, the starting point should be the indigenous practices and thoughts on life.
Foundations and Trends Pointer Analysis

Pointer analysis is a fundamental static program analysis, with a rich literature and wide applications. The goal of pointer analysis is to compute an approximation of the set of program objects that a pointer variable or expression can refer to. We present an introduction and survey of pointer analysis techniques, with an emphasis on distilling the essence of common analysis algorithms. To this end, we focus on a declarative presentation of a common core of pointer analyses: algorithms are modeled as configurable, yet easy-to-follow, logical specifications. The specifications serve as a starting point for a broader discussion of the literature, as independent threads spun from the declarative model. Y. Smaragdakis and G. Balatsouras. Pointer Analysis. Foundations and Trends © in Programming Languages, vol. 2, no. 1, pp. 1–69, 2015. DOI: 10.1561/2500000014.
Hubungan dukungan sosial dan trait kecemasan dengan trauma pada korban perdagangan manusia

Perdagangan manusia masih marak terjadi dan memberikan dampak negatif yang berpengaruh pada kehidupan para korban. Secara psikis para korban rentan mengalami stres, depresi dan trauma. Tujuan dilakukannya penelitian ini untuk mengetahui hubungan dukungan sosial dan trait kecemasan dengan trauma pada korban perdagangan manusia. Penelitian melibatkan 112 individu yang menjadi korban perdagangan manusia. Pengambilan data menggunakan instrumen Interpersonal Support Evaluation List Shortened Version-12 Item (ISEL), State-Trait Anxiety Scale Inventory (STAI), dan The Posttraumatic Stress Disorder Checklist (PCLS-S). Uji signifikansi memperlihatkan F hitung 31.810 (sig. 0,000<0,05), kesimpulannya model ini signifikan dan dapat digunakan memprediksi trauma melalui dukungan sosial dan trait kecemasan sebagai moderator. Hasil penelitian menunjukkan bahwa trauma pada korban perdagangan manusia dapat dijelaskan secara bersama-sama antara dukungan sosial sebagai variabel independen dan trait kecemasan sebagai moderator sebesar 45,4%.
MIREX 2012 SUBMISSION AUDIO CLASSIFICATION USING SPARSE FEATURE LEARNING

We present a training/test framework for automatic audio annotation and ranking using learned feature representations. Commonly used audio features in audio classification, such as MFCC and chroma, have been developed based on acoustic knowledge. As an alternative, there is increasing interest in learning features from data using unsupervised learning algorithms. In this work, we apply sparse Restricted Boltzmann Machine to audio data, particularly focusing on learning high-dimensional sparse feature representation. Our evaluation results on two music genre datasets show that the learned feature representations achieve high accuracy.
Ca2+-Dependent Desensitization of TRPV2 Channels Is Mediated by Hydrolysis of Phosphatidylinositol 4,5-Bisphosphate

TRPV2 is a member of the transient receptor potential family of ion channels involved in chemical and thermal pain transduction. Unlike the related TRPV1 channel, TRPV2 does not appear to bind either calmodulin or ATP in its N-terminal ankyrin repeat domain. In addition, it does not contain a calmodulin-binding site in the distal C-terminal region, as has been proposed for TRPV1. We have found that TRPV2 channels transiently expressed in F-11 cells undergo Ca2+-dependent desensitization, similar to the other TRPVs, suggesting that the mechanism of desensitization may be conserved in the subfamily of TRPV channels. TRPV2 desensitization was not altered in whole-cell recordings in the presence of calmodulin inhibitors or on coexpression of mutant calmodulin but was sensitive to changes in membrane phosphatidylinositol 4,5-bisphosphate (PIP2), suggesting a role of membrane PIP2 in TRPV2 desensitization. Simultaneous confocal imaging and electrophysiological recording of cells expressing TRPV2 and a fluorescent PIP2-binding probe demonstrated that TRPV2 desensitization was concomitant with depletion of PIP2. We conclude that the decrease in PIP2 levels on channel activation underlies a major component of Ca2+-dependent desensitization of TRPV2 and may play a similar role in other TRP channels.
Investigation of PHY, MAC and APP Layers for Adaptive and Cross-Layer Optimization in IEEE802.11 WLAN

Due to huge popularity of portable terminals based on Wireless LANs and increasing demand for multimedia services from these terminals, the earlier structures and protocols are insufficient to cover the requirements of emerging networks and communications. Most research in this field is tailored to find more efficient ways to optimize the quality of wireless LAN regarding the requirements of multimedia services. Our work is to investigate the effects of modulation modes at the physical layer, retry limits at the MAC layer and packet sizes at the application layer over the quality of media packet transmission. Interrelation among these parameters to extract a cross-layer idea will be discussed as well. We will show how these parameters from different layers jointly contribute to the performance of service delivery by the network. The results obtained could form a basis to suggest independent optimization in each layer (an adaptive approach) or optimization of a set of parameters from different layers (a cross-layer approach). Our simulation model is implemented in the NS-2 simulator. Throughput and delay (latency) of packet transmission are the quantities of our assessments.
The Protein Data Bank: unifying the archive

The Protein Data Bank (PDB; http://www.pdb.org/) is the single worldwide archive of structural data of biological macromolecules. This paper describes the progress that has been made in validating all data in the PDB archive and in releasing a uniform archive for the community. We have now produced a collection of mmCIF data files for the PDB archive (ftp://beta.rcsb.org/pub/pdb/uniformity/data/mmCIF/). A utility application that converts the mmCIF data files to the PDB format (called CIFTr) has also been released to provide support for existing software.
Maintaining Consistency between Caches to Improve Overall Performance in Wireless Sensor Networks

Sensor Network (WSN) is an application based network. Wireless Sensor Network has a wide range of potential, practical and useful applications. Majority of such applications require an optimization to the communication among the sensors, so as to serve data in short latency and with minimal energy consumption. The sensor nodes in WSN are battery powered devices that consumes energy during data transmission and processing. Sink node send query messages in network, nodes may or may not reply back to the sinks query messages, but battery dissipates due to processing. Data transmission in WSN consumes more energy than processing therefore it is appropriate to exploit the benefits of caching. Cooperative caching is used for the reduction in the state of non utility of data and decreases the requirement of wireless bandwidth and energy. Cooperative caching which secure sharing of data among various nodes reduces the number of communications over the wireless channels and thus enhances the overall lifetime of a wireless sensor network. To overcome problem of cooperative cache a new technique is proposed which gives better results than existing one. Network simulator NS-2 is used for the simulations. Wireless sensor offers impressive computational resources for processing data. Wireless Sensor networks are self organizer and are deployed in ad-hoc systems. Each node in wireless sensor is consist of multiple types of memory and processing elements, RF transceiver, a power source, sensors and actuators. Wireless Sensor Network is a distributed real time systems. Wireless Sensor Network is a latest technology that has an ability to coordinate a large network into a single network. It is also consist of large number of low cost devices. Wireless Sensor Network is a Light weighted distributed system. There is no need of external infrastructures in wireless sensor network to communicate with other devices. The sensor in wireless sensor networks deployed are self organized and multi hop in nature. The wireless sensor networks consume a lots of energy while transfer data from one device to other. There is need to adjust transfer and sensing rate to avoid energy consumption in wireless sensor networks (5).
Large-scale application of formal verification: From fiction to fact

Formal verification has matured considerably as a verification discipline in the past couple of decades, becoming a mainstream technology in industrial design and verification methodologies and processes. In this paper we chronicle the evolution of formal verification at IBM from being a specialized side activity with a narrow focus, to achieving a broad-based usage as a core verification technology helping to significantly improve design and verification productivity. We showcase what is possible in the application of formal verification in a commercial/industrial setting by highlighting the success we had in leveraging the technology extensively on IBM's POWER7™ microprocessor and systems. We touch upon the methodology and execution aspects of the unprecedented use of formal verification on the POWER7 program, and depict ways in which the technology positively impacted pre-silicon design quality and facilitated root causing of bug escapes to silicon. Furthermore, we outline where we see applied formal verification evolving towards at IBM, and the challenges thereof.
Job recommendation based on factorization machine and topic modelling

This paper describes our solution for the RecSys Challenge 2016. In the challenge, several datasets were provided from a social network for business XING. The goal of the competition was to use these data to predict job postings that a user will interact positively with (click, bookmark or reply). Our solution to this problem includes three different types of models: Factorization Machine, item-based collaborative filtering, and content-based topic model on tags. Thus, we combined collaborative and content-based approaches in our solution. Our best submission, which was a blend of ten models, achieved 7th place in the challenge's final leader-board with a score of 1677 898.52. The approaches presented in this paper are general and scalable. Therefore they can be applied to another problem of this type.
Correction: Thermodynamics of Random Reaction Networks

Reaction networks are useful for analyzing reaction systems occurring in chemistry, systems biology, or Earth system science. Despite the importance of thermodynamic disequilibrium for many of those systems, the general thermodynamic properties of reaction networks are poorly understood. To circumvent the problem of sparse thermodynamic data, we generate artificial reaction networks and investigate their non-equilibrium steady state for various boundary fluxes. We generate linear and nonlinear networks using four different complex network models (Erdős-Rényi, Barabási-Albert, Watts-Strogatz, Pan-Sinha) and compare their topological properties with real reaction networks. For similar boundary conditions the steady state flow through the linear networks is about one order of magnitude higher than the flow through comparable nonlinear networks. In all networks, the flow decreases with the distance between the inflow and outflow boundary species, with WattsStrogatz networks showing a significantly smaller slope compared to the three other network types. The distribution of entropy production of the individual reactions inside the network follows a power law in the intermediate region with an exponent of circa −1.5 for linear and −1.66 for nonlinear networks. An elevated entropy production rate is found in reactions associated with weakly connected species. This effect is stronger in nonlinear networks than in the linear ones. Increasing the flow through the nonlinear networks also increases the number of cycles and leads to a narrower distribution of chemical potentials. We conclude that the relation between distribution of dissipation, network topology and strength of disequilibrium is nontrivial and can be studied systematically by artificial reaction networks.
Ccq1-Tpz1TPP1 interaction facilitates telomerase and SHREC association with telomeres in fission yeast

Through characterization of ccq1 mutants that disrupt Ccq1-Tpz1TPP1 interaction, the authors establish that Ccq1-Tpz1TPP1 interaction contributes to optimal binding of the Ccq1-SHREC complex and is required for Ccq1 Thr93 phosphorylation and telomerase recruitment.
GALNT2 suppresses malignant phenotypes through IGF-1 receptor and predicts favorable prognosis in neuroblastoma

Aberrant expression of the simple mucin-type carbohydrate antigens such as Tn antigen is associated with malignant transformation and cancer progression. N-acetylgalactosaminyltransferase 2 (GALNT2), one of the enzymes that mediate the initial step of mucin-type O-glycosylation, is responsible for forming Tn antigen. GALNT2 is expressed differentially in nervous tissues during mouse embryogenesis; however, the role of GALNT2 in neuroblastoma (NB) remains unclear. Here we showed that increased GALNT2 expression evaluated using immunohistochemistry in NB tumor tissues correlated well with the histological grade of differentiation as well as younger age at diagnosis, early clinical stage, primary tumor originated from the extra-adrenal site, favorable INPC histology, and MYCN non-amplification. Multivariate analysis showed that GALNT2 expression is an independent prognostic factor for better survival for NB patients. GALNT2 overexpression suppressed IGF-1-induced cell growth, migration, and invasion of NB cells, whereas GALNT2 knockdown enhanced these NB phenotypes. Mechanistic investigations demonstrated that GALNT2 overexpression modified O-glycans on IGF-1R, which suppressed IGF-1-triggered IGF-1R dimerization and subsequent downstream signaling events. Conversely, these properties were reversed by GALNT2 knockdown in NB cells. Our findings suggest that GALNT2 regulates malignant phenotypes of NB cells through the IGF-1R signaling pathway, suggesting a critical role for GALNT2 in the pathogenesis of NB.
Analyzing Word-Of-Mouth In Social Media: The Impact And Generation Patterns

Online word-of-mouth (WOM) has been recognized as an important information source in influencing consumer purchase decisions in literature. WOM can influence product sales through both awareness effect and persuasive effect. The explosive growth of social media which allows the creation and exchange of user-generated content (including WOM) is changing the way consumers search for information and communicate with each other. Analyzing the impact of WOM and the generation patterns in the context of social media becomes important. Social broadcasting network is an important type of social media, and user generated contents such as tweets in social broadcasting system have become an important source of WOM. In a social broadcasting system, the awareness effect of WOM is strengthened by the rapid information diffusion, and the persuasive effect of WOM is influenced by social interactions. In my dissertation, I try to investigate the impact of WOM from tweets on product sales while controlling for other WOM sources such as product reviews and blogs. My second research question is the generation patterns of WOM. Generation pattern in my study refers to some specific characters of the rating sequence for a given product. Extant research typically examined the relationship between WOM and product sales by using aggregated WOM data, which ignored the dynamics of WOM generation. In fact, WOM of a product changes from time to time. For two products which have the same aggregated ratings and the same aggregated volumes of ratings, information included in the rating sequence might be different. In my dissertation, I want to identify different patterns of WOM generation, and further to investigate the impact of WOM generation pattern on product sales. To achieve these objectives, I collect data of sales, tweets, reviews, and blogs for a book list from the on-sale calendar of Publishers Weekly. This book list includes all adults’ books which published during the period from October 2011 to December 2011. For the methodology, I propose to use data mining tools such as text mining and clustering to extract information in tweets and reviews. Panel data are analysed for the impact of tweets, and time series are used to identify generation patterns.
The per-sample capacity of zero-dispersion optical fibers

The capacity of the channel defined by the stochastic nonlinear Schrödinger equation, which includes the effects of the Kerr nonlinearity and amplified spontaneous emission noise, is considered in the case of zero dispersion. For the first time, the exact capacity subject to peak and average power constraints is numerically quantified using dense multiple ring modulation formats. It is shown that, for a fixed noise power, the per-sample capacity grows unbounded with input signal power. A distribution with a half-Gaussian profile on amplitude and uniform phase is shown to provide a lower bound to the capacity which is simple and asymptotically optimal at high SNRs.
Capacity and Coverage Enhancements of MIMO WLANs in Realistic Environments

Recently, there has been an explosion of growth in research on MIMO systems, but little has been published characterising performance in realistic environments. This paper quantifies the performance of MIMO WLANs in outdoor environments, and compares performance between spatial multiplexing and space time block coding processing approaches. Packet Error Rate (PER) and throughput performance results are presented under different channel conditions. A WLAN physical layer simulator employing MIMO techniques and a propagation modelling tool are combined in order to evaluate the coverage and throughput enhancements of WLANs for the 2×2 and 4×4 MIMO cases.
Annotation as Process, Thing, and Knowledge: Multi-domain studies of structured data annotation

Following Buckland’s (1991) work on the nature of information, this paper characterizes the multi-faceted concept of ‘annotation’ as process, thing, and knowledge. This typology is then used to enumerate general research questions for the exploration of annotation in arbitrary domains. Our research team’s investigation of annotation of structured data in specific domains and user groups is described, including library catalogers, musicians, historical geographers, web users, statistical analysts, and biomedical researchers.
Distributed Circular Formation Stabilization for Dynamic Unicycles

This paper investigates the problem of designing distributed control laws making a group of dynamic unicycles converge to a common circle of prespecified radius, whose center is stationary but dependent on the initial conditions, and travel around the circle in a desired direction. The vehicles are required to converge to a formation on the circle, expressed by desired separations and ordering of the unicycles. The information exchange between unicycles is modelled by a directed graph which is assumed to have a spanning tree. A hierarchical approach is proposed which simplifies the control design by decoupling the problem of making the unicycles converge to a common circle from the problem of stabilizing the formation.
Management Reform in Flemish Local Authorities: Testing the Institutional Framework

This research empirically examines the process of organisational change through management reform (New Public Management) by an examination of the level of compliance with the reformed management regulations. A management index is constructed and applied on a sample of 100 Flemish local governments using a questionnaire, their annual accounts and interviews. The institutional framework proves to be a useful base for considering the level of adoption and testing cross-sectional differences on a number of explanatory factors. This study reveals that in practice the level of adoption of the governmental reform is restricted and mediated by both local organisational aspects and wider institutional influences.