Miracle-dz/UniFAR-FTUs huggingface dataset:
COVERAGE BASED TEST SUITE AUGMENTATION TECHNIQUES-A SURVEY

Regression testing is the activity of retesting a program so as to ensure that no new errors have been introduced into the previously tested code. However this activity does not involve rerunning the entire test suite but selecting only a few test cases that exercise the changes. Suppose there is a program P and P’ is it’s modified version. The regression test suite so selected must be able to reveal the differences between P and P’ that would help the developer discover errors caused by changes. More and more emphasis has been laid in identifying the regression test suites and ordering them. However, less focus have been laid on the effectiveness of regression test suite in response to changes. While performing regression testing we also need to check whether the existing test suites are sufficient for handling the changes that are introduced. If they are not adequate then providing guidance for creating the new test cases that would be targeting the changed behavior of the program. This problem is called as test suite augmentation. Many test suite augmentation techniques have been proposed in this regard. The main aim of this paper is to explain the concept of test suite augmentation and review the existing techniques based on coverage criteria.
Validity and Reliability of Finnish Version of WHOQOL-Bref on Adult Population in Finland

The aim of this paper is to determine the WHOQOL-Bref population norms and describe the psychometric properties of the Finnish WHOQOL-Bref in relation to construct validity, discriminatory power and internal consistency in the general population. The data is from the Finnish HYPA survey, which combines telephone and personal visits interviews. Telephone interviews and posted questionnaires and register-based data were used for 18-79 year olds and face to face interviews with register data at age group over 79 years olds. The Cronbachs alpha, confirmatory factor and regression analysis show that the internal consistency and validity of the two general questions, and physical and psychological domain to be sufficient for research and QoL measurement purposes. The internal consistency of the domains in the sample for the physical, psychological, social relationships and environmental domains were 0.83; 0.78; 0.69; 0.67 respectively measured by alpha. The internal consistency for total scale was 0.89 which was near excellent (> 0.90).
The Relationship between Commitment Forms and Work Outcomes: A Comparison of Three Models

This study examined three models of the relationships between commitment foci and work outcomes such as turnover intentions, actual turnover, and absenteeism. The first is based on the traditional literature that argues that the relationship between commitment foci and outcomes is direct. The second is based on Morrow's model of universal forms of work commitment. According to this model, job involvement mediates the relationship between the other commitment foci and outcomes. The third model is based on the conceptualization proposed by Randall and Cote. According to their model organizational commitment and occupational commitment should mediate the relationship between commitment foci and out-comes. In the study 283 nurses from three small hospitals in Israel were surveyed with a response rate of 62 percent. The results of path analysis (LISREL VIII) showed a better fit to the data of the Randall and Cote model. The article concludes with implications regarding the continuing assessment of Morrow's conceptualization to establish an acceptable definition and measurement of universal forms of work commitment.
A UWB Radar Signal Processing Platform for Real-Time Human Respiratory Feature Extraction Based on Four-Segment Linear Waveform Model

This paper presents an ultra-wideband (UWB) impulse-radio radar signal processing platform used to analyze human respiratory features. Conventional radar systems used in human detection only analyze human respiration rates or the response of a target. However, additional respiratory signal information is available that has not been explored using radar detection. The authors previously proposed a modified raised cosine waveform (MRCW) respiration model and an iterative correlation search algorithm that could acquire additional respiratory features such as the inspiration and expiration speeds, respiration intensity, and respiration holding ratio. To realize real-time respiratory feature extraction by using the proposed UWB signal processing platform, this paper proposes a new four-segment linear waveform (FSLW) respiration model. This model offers a superior fit to the measured respiration signal compared with the MRCW model and decreases the computational complexity of feature extraction. In addition, an early-terminated iterative correlation search algorithm is presented, substantially decreasing the computational complexity and yielding negligible performance degradation. These extracted features can be considered the compressed signals used to decrease the amount of data storage required for use in long-term medical monitoring systems and can also be used in clinical diagnosis. The proposed respiratory feature extraction algorithm was designed and implemented using the proposed UWB radar signal processing platform including a radar front-end chip and an FPGA chip. The proposed radar system can detect human respiration rates at 0.1 to 1 Hz and facilitates the real-time analysis of the respiratory features of each respiration period.
Temporal-related Convolutional-Restricted-Boltzmann-Machine capable of learning relational order via reinforcement learning procedure?

In this article, we extend the conventional framework of convolutional-Restricted-Boltzmann-Machine to learn highly abstract features among abitrary number of time related input maps by constructing a layer of multiplicative units, which capture the relations among inputs. In many cases, more than two maps are strongly related, so it is wise to make multiplicative unit learn relations among more input maps, in other words, to find the optimal relational-order of each unit. In order to enable our machine to learn relational order, we developed a reinforcement-learning method whose optimality is proven to train the network.
On the maximum Doppler diversity of high mobility systems with imperfect channel state information

This paper studies the maximum Doppler diversity order of high mobility systems operating in the presence of imperfect channel state information (CSI). High mobility of wireless terminals causes large Doppler spread, which provides Doppler diversity. However, channel estimation errors are usually inevitable in such systems due to fast time-varying fading caused by large Doppler spread, and they will negatively impact system performance. We study the fundamental tradeoff between Doppler diversity and channel estimation errors by identifying the exact analytical expression of the maximum Doppler diversity order achievable in the presence of imperfect CSI. The analytical study is enabled by a simple repetition code at the transmitter and a new optimum diversity receiver, which is developed by analyzing the statistical properties of channel estimation errors. The analytical results show that if the energy of pilot symbols scales linearly with that of data symbols, then systems with imperfect CSI can achieve the same Doppler diversity order as those with perfect CSI. A non-linear scaling between the energy of pilot and data symbols always results in a loss of Doppler diversity for systems with imperfect CSI.
Preventing gastrointestinal complications of NSAIDs

PREVIEW In the United States, gastrointestinal complications induced by nonsteroidal anti-inflammatory drugs (NSAIDs) cause more than 100,000 hospitalizations and an estimated 16,500 deaths annually. Because serious gastrointestinal events can occur without warning, prevention measures must not rely on warning signs alone. This article discusses the epidemiology of NSAID- induced toxic episodes, reviews the risk factors for these occurrences, and offers strategies for minimizing the risk among long-term NSAID users.
A Writing Assignment Extended: An Occasion for Young People to Construct Writer Identities

Becoming a successful writer is an important skill for the young because it predicts academic success, supports and extends learning, provides opportunities to participate in civic and community life and fulfils expectations of the workforce to create clear and concise documents. Many secondary students in the US, however, struggle to gain basic academic literacy skills that meet the demands of higher education and the workforce. This qualitative study explored how a specific writing genre, occasional papers, opened opportunities for students to situate themselves and each other as authors in an 11th-grade English classroom. The paper argues that high school students need more opportunities to construct their identities as lifelong authors, who write to make sense of themselves and the world around them and write to promote dialogue with an audience if they are to succeed at high-stakes exams and writing as a member of the workforce. Suggestions for how to integrate such writing within a standardized curriculum are discussed.
Novel Verification Framework Combining Structural and OBDD Methods in a Synthesis Environment

This paper presents a new methodology for formal logic verification for combinational circuits. Specifically, a structural approach is used, based on indirect implications derived by using Recursive Learning. This is extended to formulate a hybrid approach where this structural method is used to reduce the complexity of a subsequent functional method based on OBDDs. It is demonstrated how OBDD-based verification can take great advantage of structural preprocessing in a synthesis environment. The experimental results show the effective compromise achieved between memory-efficient structural methods and functional methods. One more advantage of these methods lies in the fact that resources that go into logic synthesis can effectively be reused for verification purposes.
Exploring Eyes-free Interaction with Wrist-Worn Deformable Materials

Recent work has explored how on-the-wrist devices can be augmented with displays, sensors, and aesthetics to produce a new genre of wearable, digital jewelry. Most often, these devices are augmented with hardware (e.g., touch-screens, gyroscopes) to receive wearer input. Breakthroughs in sensing materials allow novel inputs such as squeeze, bend, and stretch, which may be more suited to interaction with a discreet wearable. We explore interactions with a flexible bracelet that can be manipulated through bend, stretch, and touch. We discuss the process involved in fabricating materials that convert these actions into measurable parameters. We particularly focus on eyes-free interactions with bracelets that take advantage of the tactile feedback from the act of deformation, and demonstrate some early, low-fidelity prototype concepts.
Cosmic microwave background temperature and polarization pseudo-Cl estimators and covariances

We develop the pseudo-Cl method for reconstructing the cosmic microwave background (CMB) temperature and polarization auto- and cross-power spectra, and estimate the pseudo-Cl covariance matrix for a realistic experiment on the cut sky. We calculate the full coupling equations for all six possible CMB power spectra, relating the observed pseudo-Cl values to the underlying all-sky Cl values, and test the reconstruction on both full-sky and cut-sky simulated CMB data sets. In particular we consider the reconstruction of the Cl from upcoming ground-based polarization experiments covering areas of a few hundred deg2 and find that the method is fast, unbiased and performs well over a wide range of multipoles from l= 2 to l= 2500. We then calculate the full covariance matrix between the modes of the pseudo-temperature and polarization power spectra, assuming that the underlying CMB fields are Gaussian randomly distributed. The complexity of the covariance matrix prohibits its rapid calculation, required for parameter estimation. Hence we present an approximation for the covariance matrix in terms of convolutions of the underlying power spectra. The coupling matrices in these expressions can be estimated by fitting to numerical simulations, circumventing direct and slow calculation, and further, inaccurate analytic approximations. We show that these coupling matrices are mostly independent of cosmology, and that the full covariance matrix for all six pseudo-Cl power spectra can be quickly and accurately calculated for any given cosmological model using this method. We compare these semi-analytic covariance matrices against simulations and find good agreement, the accuracy of which depends mainly on survey area and the range of cosmological parameters considered.
Detailed Analysis of Nearby Bulgelike Dwarf Stars. II. Lithium Abundances

Li abundances are derived for a sample of bulgelike stars with isochronal ages of 10-11 Gyr. These stars have orbits with pericentric distances, Rp, as small as 2-3 kpc and Zmax < 1 kpc. The sample comprises G and K dwarf stars in the metallicity range -0.80 ≤ [Fe/H] ≤ +0.40. Few data on Li abundances in old turnoff stars (≥4.5 Gyr) within the present metallicity range are available. M67 (4.7 Gyr) and NGC 188 (6 Gyr) are the oldest studied metal-rich open clusters with late-type stars. Li abundances have also been studied for a few samples of old metal-rich field stars. In the present work, a high dispersion in Li abundances is found for bulgelike stars with all metallicity ranges, comparable with values in M67. The role of metallicity and age on a Li depletion pattern is discussed. The possible connection between Li depletion and oxygen abundance due to atmospheric opacity effects is investigated.
Energy Efficient Routing Protocols in WSN: A Review Paper

Wireless sensor networks with hundreds of sensor nodes have emerged in recent years as important platforms for a wide spectrum of monitoring tasks ranging from environmental to military applications. A sensor network is a static ad hoc network which consists of hundreds of sensor nodes that can be deployed on the fly operation being not attended so the main design issue for a sensor network must be conservation of the energy available at each sensor node. Wireless Sensor Network depends on nodes have limited energy, computational power, memory , range and it is important to increase energy efficiency by saving the battery power so as to extend the life time of the given WSN deployment. Different protocols are used for energy consumption, in wireless sensor network. LEACH, TEEN, APTEEN, PEGASIS ,DEEC, DDEEC, EDEEC, BEENISH are energyefficient protocols that balances the energy expense, saves the node energy and hence prolongs the lifetime of the network. This paper presents a detailed review and analysis of these energy efficient protocols.
Ultra Low Voltage Synthesizable Memories: A Trade-Off Discussion in 65 nm CMOS

In this study, design considerations for ultra low voltage (ULV) standard-cell based memories (SCM) are presented. Trade-offs for area cost, leakage power, access time, and access energy are discussed and realized using different read logic styles, latch architecture designs, and process options. Furthermore, deployment of multiple threshold voltages (Vth) options in a single standard-cell/bitcell enables additional architectural choices. Silicon measurements from five memory designs, optimized at the transistor level in conjunction with gate-level optimizations, are considered to demonstrate the different trade-off corners. Measurements show that substituting the storage element in an SCM with a D-latch using transistor stacking and channel length stretching results in lowest leakage power. Alternatively, a pass- transistor based latch as storage element reduces the area footprint at a cost of reduced access speed, which can be compensated by using a lower-Vth pass-transistor. However, relatively high speed (tens of MHz) in the near- to subthreshold (sub-Vth) region is achievable if general purpose transistors are used instead of low power transistors. A discussion is included to illustrate when to implement ULV memories using SCMs and when to choose sub-Vth SRAMs. The discussion shows that the border is between 4-6 kb, depending on the number of words and the wordlength configuration.
Nomenclature for factors of the HLA system, update July 2016

The following sequences have been submitted to the Nomenclature Committee since the June 2016 nomenclature update and, following agreed policy, have been assigned official allele designations (Marsh et al., 2010). Full details of all sequences will be published in a forthcoming report. Below are listed the newly assigned sequences (Table 1) and confirmations of previously reported sequences (Table 2). The accession number of each sequence is given, and these can be used to retrieve the sequence files from the EMBL, GenBank or DDBJ data libraries. Although accession numbers have been
A Motivational Model of Information Processing Intensity

A general theory of motivation, derived from Tolman and Atkinson and his associates is applied to message processing. The model explains a person's tendency to process a message and his resultant information processing intensity in terms of his need for information on the given topic, his expectancy that processing the message will lead to information relevant to the need and his evaluation of the particular message as a source of information.
Analysis of the proteome in the human pituitary

The pituitary is the master endocrine gland responsible for the regulation of various physiologic and metabolic processes. Proteomics offers an efficient means for a comprehensive analysis of pituitary protein expression. This paper reports on the application of proteomics for the mapping of major proteins in a normal (control) pituitary. Pituitary proteins were separated by two‐dimensional gel electrophoresis with immobilized pH 3–10 gradient strips. Major protein spots that were visualized in the two‐dimensional gel by silver staining were excised, and the proteins in these spots were digested with trypsin. The tryptic digests were analyzed by mass spectrometry, and the mass spectrometric data were used to identify the proteins through searches of the SWISS‐PROT or NCBInr protein sequence databases. The majority of the proteins were identified on the basis of peptide mass fingerprinting data obtained by matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry. Several proteins were also characterized based on product‐ion spectra measured by post‐source decay analysis and/or liquid chromatography‐electrospray‐quadrupole ion trap mass spectrometry. To date, 62 prominent protein spots, corresponding to 38 different proteins, were identified. The identified proteins include important pituitary hormones, structural proteins, enzymes, and other proteins. The protein identification data were used to establish a two‐dimensional reference database of the human pituitary, which can be accessed over the Internet (http://www.utmem.edu/proteomics). This database will serve as a tool for further proteomics studies of pituitary protein expression in health and disease.
Identifying the Associations between Child Temperament and Father Involvement: Theoretical Considerations and Empirical Evidence

Using a sample of resident fathers (either married or cohabiting) from the Fragile Families and Child Wellbeing Study (N = 2,213), this study assessed the relationship between child temperament and father involvement. The direct effects of child temperament on father involvement, as well as its moderating effect on the association between other predictor variables and father involvement were measured. A two-equation model was estimated, using a two-stage least squares (2SLS) regression procedure. Findings suggest that fathers are less involved with temperamentally difficult children than with temperamentally easy children. Further, temperament moderated the strength of the association between parental relationship quality and father involvement for married fathers. Implications for intervention programs targeted at increasing paternal involvement are discussed.
The Social and Cultural Predictors of Generosity in Marriage

This study focuses on the social and cultural sources of an important dimension of solidarity in contemporary marriages: marital generosity. Marital generosity is defined here as freely giving to one’s spouse by regularly engaging in small acts of service, forgiving one’s spouse, and displaying high levels of affection and respect. Using recent data from a national sample, the Survey of Marital Generosity (N = 1,368 couples), we explored the associations between gender egalitarianism, familism, religiosity, and generous behavior among spouses aged 18 to 45. Our results suggest that domestic gender egalitarianism—where spouses reported sharing housework and child care—is linked to greater reports of marital generosity. Religiosity is also positively associated with marital generosity. Finally, the most potent predictor of generosity in this study is commitment, where spouses are personally dedicated to their partner and to continuing the relationship.
USING MULTIMEDIA SOCIAL STORIES TO INCREASE APPROPRIATE SOCIAL ENGAGEMENT IN YOUNG CHILDREN WITH AUTISM

The purpose of this study was to examine the effectiveness of the multimedia social stories on the duration of appropriate social engagement of 3 young children with autism. Using a multiple-baseline-across-participants design, the multimedia social stories were implemented, and observations of 10-min play sessions were conducted three times per week. Study results showed an increase in the duration of appropriate social engagement for all participants and two participants also showed generalization to a classroom setting. The results from the study provide support for the use of the multimedia social stories without additional behavioral management techniques in increasing the social engagement of children with autism. Recommendations for future research and potential benefits of the multimedia social story interventions are discussed.
Recommendation via matrix completion using Kolmogorov complexity

A usual way to model a recommendation system is as a matrix completion problem. There are several matrix completion methods, typically using optimization approaches or collaborative filtering. Most approaches assume that the matrix is either low rank, or that there are a small number of latent variables that encode the full problem. Here, we propose a novel matrix completion algorithm for recommendation systems, without any assumptions on the rank and that is model free, i.e., the entries are not assumed to be a function of some latent variables. Instead, we use a technique akin to information theory. Our method performs hybrid neighborhood-based collaborative filtering using Kolmogorov complexity. It decouples the matrix completion into a vector completion problem for each user. The recommendation for one user is thus independent of the recommendation for other users. This makes the algorithm scalable because the computations are highly parallelizable. Our results are competitive with state-of-the-art approaches on both synthetic and real-world dataset benchmarks.