Miracle-dz/UniFAR-FTUs huggingface dataset:
Tracking Design Smells: Lessons from a Study of God Classes

"God class" is a term used to describe a certain type of large classes which "know too much or do too much". Often a God class (GC) is created by accident as functionalities are incrementally added to a central class over the course of its evolution. GCs are generally thought to be examples of bad code that should be detected and removed to ensure software quality. However, in some cases, a GC is created by design as the best solution to a particular problem because, for example, the problem is not easily decomposable or strong requirements on efficiency exist. In this paper, we study in two open-source systems the "life cycle" of GCs: how they arise, how prevalent they are, and whether they remain or they are removed as the systems evolve over time, through a number of versions. We show how to detect the degree of "godliness" of classes automatically. Then, we show that by identifying the evolution of "godliness", we can distinguish between those classes that are so by design (good code) from those that occurred by accident (bad code). This methodology can guide software quality teams in their efforts to implement prevention and correction mechanisms.
Modeling spatial variation in the relationships between violence and alcohol and drug use : A comparison of geographically weighted regression and Bayesian spatially varying coefficient process models

Previous studies consistently indicate measurable local associations between alcohol and drug usage and the incidence of violence, which reveal the importance of spatial analysis in the study of alcohol, drugs, and violence. While studies increasingly incorporate spatial correlation among model residuals to improve model performance, many analyses assume associations that are constant across a study area, an assumption that has come under scrutiny in the statistics and geography literature. In this paper, we compare and contrast two approaches for the estimation of potentially spatially varying regression effects. Specifically, we provide a comparison of a geographically weighted regression (GWR) model with a Bayesian spatially varying coefficient process model, where comparable spatial dependence functions are used. We compare the approaches with respect to conceptual structures, computational implementation, and inferential output. We apply both approaches to model the relationships of violent crime with illegal drug arrest and alcohol sales data from Houston, Texas and compare their results. We also present results of diagnostic tools for
TSC22D4 is a molecular output of hepatic wasting metabolism

In mammals, proper storage and distribution of lipids in and between tissues is essential for the maintenance of energy homeostasis. Here, we show that tumour growth triggers hepatic metabolic dysfunction as part of the cancer cachectic phenotype, particularly by reduced hepatic very‐low‐density‐lipoprotein (VLDL) secretion and hypobetalipoproteinemia. As a molecular cachexia output pathway, hepatic levels of the transcription factor transforming growth factor beta 1‐stimulated clone (TSC) 22 D4 were increased in cancer cachexia. Mimicking high cachectic levels of TSC22D4 in healthy livers led to the inhibition of hepatic VLDL release and lipogenic genes, and diminished systemic VLDL levels under both normal and high fat dietary conditions. Liver‐specific ablation of TSC22D4 triggered hypertriglyceridemia through the induction of hepatic VLDL secretion. Furthermore, hepatic TSC22D4 expression levels were correlated with the degree of body weight loss and VLDL hypo‐secretion in cancer cachexia, and TSC22D4 deficiency rescued tumour cell‐induced metabolic dysfunction in hepatocytes. Therefore, hepatic TSC22D4 activity may represent a molecular rationale for peripheral energy deprivation in subjects with metabolic wasting diseases, including cancer cachexia.
Factors affecting space use overlap by white-tailed deer in an urban landscape

Variation in the size and overlap of space use by white-tailed deer (Odocoileus virginianus) has broad implications for managing deer–human conflicts and disease spread and transmission in urban landscapes. Understanding which factors affect overlap of home range by various segments (i.e., age, sex) of an urban deer population has implications to direct contact between deer on disease epidemiology. We assessed size of home range and overlap of space use using the volume of intersection index (VI) for deer in an urban landscape by sex, age, season, and time of day. We found mean space use was larger for males than for females, for males <3 years old than for males ≥3 years old, and during nocturnal hours compared with diurnal hours. We also identified larger space use by both sexes during the nongrowing than the growing season. Overlap of space use for female and male deer in our urban landscape differed considerably depending on demographic (i.e., age) and environmental variables (i.e., time, season). For example, highest mean VIs occurred between 6-year-old females (mean = 0.51 ± 0.10) and 5- and 6-year-old males (mean = 0.49 ± 0.14); no mean VI was greater than 0.31 between females and males for any age combination. Variation in overlap of space use for urban deer provides new information for managing deer–human conflicts and direct transmission of disease between various segments of a deer population in an urban landscape.
Spatially Varying Blur Recovery - Diagonal Approximations in the Wavelet Domain

Restoration of images degraded by spatially varying blurs is an issue of increasing importance. Many new optical systems allow to know the system point spread function at some random locations, by using microscopic luminescent structures. Given a set of impulse responses, we propose a fast and efficient algorithm to reconstruct the blurring operator in the whole image domain. Our method consists in finding an approximation of the integral operator by operators diagonal in the wavelet domain. Interestingly, this method complexity scales linearly with the image size. It is thus applicable to large 3D problems. We show that this approach might outperform previously proposed strategies such as linear interpolations (Nagy and O'Leary, 1998) or separable approximations (Zhang et al., 2007). We provide various theoretical and numerical results in order to justify the proposed methods. We also show preliminary deblurring results illustrating the relevance of our formalism.
Reenement and State Machine Abstraction Reenement and State Machine Abstraction

Most SVRC technical reports are available via anonymous ftp, from svrc.it. uq.edu. au in the directory /pub/techreports. Abstracts and compressed postscript les are available via Abstract Precise module interface speciications are essential in modular software development. The role of state in these speciications has been the issue of some debate and is central to the notion of data reenement. In previous work, Hooman and Strooper introduce a state-abstraction lattice that deenes a partial order on speciications for deterministic and complete languages. They use this lattice to deene a notion of state abstractness and show that this intuitive notion corresponds to the use of the terms \abstract" and \concrete" as used in data-reenement proofs. In this paper, we extend this work for a class of speciications and languages that we call demonic and semi-deterministic. We also introduce a notion of backward reenement and prove that backward reenement together with the common forward reenement of VDM and Z form a sound and complete reenement technique with respect to a partial order on languages deened by demonic speciications. We illustrate the ideas using simple languages and speciications.
Infants’ and Children’s Salt Taste Perception and Liking: A Review

Sodium is an essential nutrient for the human body. It is widely used as sodium chloride (table salt) in (processed) foods and overconsumed by both children and adults, placing them at risk for adverse health effects such as high blood pressure and cardiovascular diseases. The current review focusses on the development of salt taste sensitivity and preferences, and its association with food intake. Three -to- four month old infants are able to detect and prefer sodium chloride solutions over plain water, which is thought to be a biological unlearned response. Liking for water with sodium chloride mostly decreases when infants enter early childhood, but liking for sodium chloride in appropriate food contexts such as soup and snack foods remains high. The increased acceptance and preference of sodium chloride rich foods coincides with infants’ exposure to salty foods, and is therefore thought to be mostly a learned response. Children prefer higher salt concentrations than adults, but seem to be equally sensitive to salt taste. The addition of salt to foods increases children’s consumption of those foods. However, children’s liking for salt taste as such does not seem to correlate with children’s consumption of salty foods. Decreasing the exposure to salty tasting foods during early infancy is recommended. Salt plays an important role in children’s liking for a variety of foods. It is, however, questionable if children’s liking for salt per se influences the intake of salty foods.
Joining: Mechanical Fastening of Polymers, Composites, and Polymer–Metal Hybrid Structures

The development of new materials and fabrication techniques has become a matter of success for the industry. Polymers, polymeric composites, and polymer–metal structures are being increasingly employed in several products mainly because of the associated weight savings. Mechanical fastening is one of the main joining methods for polymer and polymeric composites along with adhesive bonding and welding. On the other hand, polymer–metal structures are more difficult to join by traditional joining methods, mostly because of their strong dissimilar physical-chemical features. Constant efforts on developing improved alternative joining techniques for these hybrid structures, such as the FricRiveting, injection clinching joining (ICJ), collar joining, and injection over molding, have contributed to the dissemination of such structures in industrial applications. This article intends to tackle the basic principles of the mechanical fastening for polymers, composites, and polymer–metal hybrid structures, with emphasis on the description of the main mechanical fastening techniques available for this category of materials as well as on recent developments with future short to medium term potential of industrial application. Finally, this work intends to show that the field of mechanical fastening of polymers, polymeric composites, and polymer–metal hybrid structures for industrial applications is still a growing research and development area. This is due to the increasing aspirations for more environmental friendly technologies and lightweight materials. Keywords: mechanical fastening; fabrication; polymers; composites; polymer–metal hybrid structures
Goal-directed attention alters the tuning of object-based representations in extrastriate cortex

Humans survive in environments that contain a vast quantity and variety of visual information. All items of perceived visual information must be represented within a limited number of brain networks. The human brain requires mechanisms for selecting only a relevant fraction of perceived information for more in-depth processing, where neural representations of that information may be actively maintained and utilized for goal-directed behavior. Object-based attention is crucial for goal-directed behavior and yet remains poorly understood. Thus, in the study we investigate how neural representations of visual object information are guided by selective attention. The magnitude of activation in human extrastriate cortex has been shown to be modulated by attention; however, object-based attention is not likely to be fully explained by a localized gain mechanism. Thus, we measured information coded in spatially distributed patterns of brain activity with fMRI while human participants performed a task requiring selective processing of a relevant visual object category that differed across conditions. Using pattern classification and spatial correlation techniques, we found that the direction of selective attention is implemented as a shift in the tuning of object-based information representations within extrastriate cortex. In contrast, we found that representations within lateral prefrontal cortex (PFC) coded for the attention condition rather than the concrete representations of object category. In sum, our findings are consistent with a model of object-based selective attention in which representations coded within extrastriate cortex are tuned to favor the representation of goal-relevant information, guided by more abstract representations within lateral PFC.
Determination of DMMP Using a Polymer Coated QCM Sensor

A quartz crystal microbalance (QCM) modified with a thin layer of fluorinated polymer was utilized to determine dimethylmethyl phosphonate (DMMP). Determination was based on the frequency shifts due to the adsorption and desorption of the compound at the surface of modified quartz crystal electrode. Fluorosiloxane was utilized onto the surface of the sensor. The frequency shifts were linear against the concentration of DMMP within the concentration range of 30~210mg•m-3. Good selectivity and sensitivity were obtained with the sensor for DMMP. The detection limit was 10.1 mg•m-3.
Depth Map Upsampling via Compressive Sensing

We propose a new method to enhance the lateral resolution of depth maps with registered high-resolution color images. Inspired by the theory of Compressive Sensing (CS), we formulate the up sampling task as a sparse signal recovery problem. With a reference color image, the low-resolution depth map is converted into suitable sampling data (measurements). The signal recovery problem, defined in a constrained optimization framework, can be efficiently solved with variable splitting and alternating minimization. Experimental results demonstrate the effectiveness of our CS-based method: it competes favorably with other state-of-the-art methods with large up sampling factors and noisy depth inputs.
Mobile Sensing at the Service of Mental Well-being: a Large-scale Longitudinal Study

Measuring mental well-being with mobile sensing has been an increasingly active research topic. Pervasiveness of smartphones combined with the convenience of mobile app distribution platforms (e.g., Google Play) provide a tremendous opportunity to reach out to millions of users. However, the studies at the confluence of mental health and mobile sensing have been longitudinally limited, controlled, or confined to a small number of participants. In this paper we report on what we believe is the largest longitudinal in-the-wild study of mood through smartphones. We describe an Android app to collect participants' self-reported moods and system triggered experience sampling data while passively measuring their physical activity, sociability, and mobility via their device's sensors. We report the results of a large-scale analysis of the data collected for about three years from 18,000 users. The paper makes three primary contributions. First, we show how we used physical and software sensors in smartphones to automatically and accurately identify routines. Then, we demonstrate the strong correlation between these routines and users' personality, well-being perception, and other psychological variables. Finally, we explore predictability of users' mood using their passive sensing data. Our findings show that, especially for weekends, mobile sensing can be used to predict users' mood with an accuracy of about 70%. These results have the potential to impact the design of future mobile apps for mood/behavior tracking and interventions.
Simulating Quantum Computation by Contracting Tensor Networks

The treewidth of a graph is a useful combinatorial measure of how close the graph is to a tree. We prove that a quantum circuit with $T$ gates whose underlying graph has a treewidth $d$ can be simulated deterministically in $T^{O(1)}\exp[O(d)]$ time, which, in particular, is polynomial in $T$ if $d=O(\log T)$. Among many implications, we show efficient simulations for log-depth circuits whose gates apply to nearby qubits only, a natural constraint satisfied by most physical implementations. We also show that one-way quantum computation of Raussendorf and Briegel (Phys. Rev. Lett., 86 (2001), pp. 5188-5191), a universal quantum computation scheme with promising physical implementations, can be efficiently simulated by a randomized algorithm if its quantum resource is derived from a small-treewidth graph with a constant maximum degree. (The requirement on the maximum degree was removed in [I. L. Markov and Y. Shi, preprint:quant-ph/0511069].)
Fast Exact Computation of betweenness Centrality in Social Networks

Social networks have demonstrated in the last few years to be a powerful and flexible concept useful to represent and analyze data emerging form social interactions and social activities. The study of these networks can thus provide a deeper understanding of many emergent global phenomena. The amount of data available in the form of social networks data is growing by the day, and this poses many computational challenging problems for their analysis. In fact many analysis tools suitable to analyze small to medium sized networks are inefficient for large social networks. The computation of the betweenness centrality index is a well established method for network data analysis and it is also important as subroutine in more advanced algorithms, such as the Girvan-Newman method for graph partitioning. In this paper we present a new approach for the computation of the betweenness centrality, which speeds up considerably Brandes' algorithm (the current state of the art) in the context of social networks. Our approach exploits the natural sparsity of the data to algebraically (and efficiently) determine the betweenness of those nodes forming trees (tree-nodes) in the social network. Moreover, for the residual network, which is often of much smaller size, we modify directly the Brandes' algorithm so that we can remove the nodes already processed and perform the computation of the shortest paths only for the residual nodes. Tests conducted on a sample of publicly available large networks from the Stanford repository show that improvements of a factor ranging between 2 and 5 are possible on several such graphs, when the sparsity, measured by the ratio of tree-nodes to the total number of nodes, is in a medium range (30% to 50%). For some large networks from the Stanford repository and for a sample of social networks provided by Sistemi Territoriali with high sparsity (80% and above) tests show that our algorithm consistently runs between one and two orders of magnitude faster than the current state of the art exact algorithm.
Association between cortisol awakening response and memory function in major depression

Background While impaired memory and altered cortisol secretion are characteristic features of major depression, much less is known regarding the impact of antidepressant medication. We examined whether the cortisol awakening response (CAR) is increased in depressed patients with and without medication compared with healthy controls (HC) and whether CAR is associated with memory function in each group. Method We examined 21 patients with major depression without medication, 20 depressed patients on antidepressant treatment, and 41 age-, sex- and education-matched healthy subjects. We tested verbal (Auditory Verbal Learning Task) and visuospatial (Rey figure) memory and measured CAR on two consecutive days. Results Patient groups did not differ in severity of depression. We found a significant effect of group (p = 0.03) for CAR. Unmedicated patients exhibited a greater CAR compared with medicated patients (p = 0.04) with no differences between patient groups and HC. We found a significant effect of group for verbal (p = 0.03) and non-verbal memory (p = 0.04). Unmedicated patients performed worse compared with medicated patients and HC in both memory domains. Medicated patients and HC did not differ. Regression analyses revealed a negative association between CAR and memory function in depressed patients, but not in HC. Conclusions While in unmedicated depressed patients the magnitude of CAR is associated with impaired memory, medicated patients showed a smaller CAR and unimpaired cognitive function compared with HC. Our findings are compatible with the idea that antidepressants reduce CAR and partially restore memory function even if depressive psychopathology is still present.
Voice Activity Detection using Temporal Characteristics of Autocorrelation Lag and Maximum Spectral Amplitude in Sub-bands

A robust voice activity detection (VAD) is a prerequisite for many speech based applications like speech recognition. We investigated two VAD techniques that use time domain and frequency domain characteristics of speech signal. The temporal characteristic of the autocorrelation lag is able to discriminate speech and nonspeech regions. In the frequency domain, peak value of the magnitude spectrum in different sub-bands is used for VAD. Performance of the proposed methods are evaluated on TIMIT database with noises from NOISEX-92 database at various signal-to-noise ratio (SNR) levels. From the experimental results, it is observed that VAD based on autocorrelation lag is working consistently better than the maximum peak value of the autocorrelation function based method. However, it performs inferior compared to our second approach and AMR-VAD2. Our second approach i.e., VAD based on maximum spectral amplitude in sub-bands out-performs AMR-VAD2 and Sohn VAD for some noise conditions. Moreover, it is shown that a threshold independent of noises and their levels can be selected in the proposed method
Challenges for Asynchronous Collaboration in Augmented Reality

Collaboration is a promising area of investigation for Augmented Reality (AR) applications. While there have been numerous examples of co-located and remote synchronous collaborative AR applications, there has not been the same interest in pursuing asynchronous interfaces. Asynchronous processes differ from their synchronous counterparts due to the collaboration occurring over a period of time, without the requirement of all parties being present simultaneously. For AR applications, asynchronous collaboration is typically considered to be the combination of drawn registered annotations, and their review at a later time. The potential on offer far exceeds this stance. This paper uncovers a unique opportunity for pursuing asynchronous collaboration support in AR, identifies how communications can be enhanced, and discusses the research challenges unique to asynchronous collaboration in AR.
Effects of Polymorphisms in Pepsinogen (PEP), Amylase (AMY) and Trypsin (TRY) Genes on Food Habit Domestication Traits in Mandarin Fish

Mandarin fish (Siniperca chuatsi) have a peculiar feeding habit of only accepting live fish prey and refusing dead prey and artificial diets. However, previous research has shown that some individuals accept dead prey after gradual domestication. Digestive enzymes are correlated with feeding habits in fish. In the current study, SNPs in the mandarin fish genes for pepsinogen (PEP), amylase (AMY), and trypsin (TRY) were evaluated for associations with feeding habits in domesticated mandarin fish by scanning their complete genomic sequence. In total, two SNPs were found in PEP, one was found in TRY, and none were found in AMY. The D1(CTCC) and D5(TTTT) diplotypes in the PEP gene tended to show strong effects on the feeding habits of domesticated fish (p < 0.01). The results indicate that PEP may be associated with the genetic mechanism for feeding habits in mandarin fish, and the D1(CTCC) and D5(TTTT) diplotypes in the PEP gene may be useful markers for selecting mandarin fish with appropriate feeding habits for domestication.