Miracle-dz/UniFAR-FTUs huggingface dataset:
Hot spot recovery in object-oriented software with inheritance and composition template methods

The success of an object-oriented software development project highly depends on how well the designers can capture the Hot Spots of the application domain, that is, those aspects that should be kept flexible to accommodate reuse and change. Yet, all too often, Hot Spots are hardly documented and over years of software evolution, the source code that reifies them becomes increasingly entangled with the application specific code. This blurring of the flexible with the rigid parts makes an application hard to maintain, prone to unexpected change impact, and immobile for reuse in related areas. In this paper we apply SPOOL, our prototype environment for reverse engineering, to the recovery of Hot Spots in C++ software. We base the technique for Hot Spot recovery on the design concept of template methods. We present the approach and the interactive analysis capabilities of SPOOL to visualize browse, and inspect Hot Spots in both separate and contextual form. The findings are validated based on two industrial systems.
Event Detection through Differential Pattern Mining in Internet of Things

Detecting an event of interest, e.g., damage in aerospace vehicles from the continuous arriving data in Internet of Things (IoT) is challenging due to the detection quality. Traditional data mining schemes are employed to reduce data that often use metrics, association rules, and binary values for frequent patterns as indicators for finding interesting knowledge. However, these may not be directly applicable to the network due to certain constraints (communication, computation, bandwidth). We discover that, the indicators may not reveal meaningful information for event detection. In this paper, we propose a comprehensive data mining framework for event detection in IoT named DPminer, which functions in a distributed and parallel manner (data in a partitioned database processed by one or more sensor processors) and is able to extract a pattern of sensors that may have event information with a low communication cost. To achieve this, we introduce a new sensor behavioral pattern mining technique called differential sensor pattern (DSP) which considers different frequencies and values (non-binary) with a set of sensors. We present an algorithm for data preparation and then use a highly-compact data tree structure (called DP-Tree) for generating the DSP. Evaluation results show that DPminer can be very useful for networked sensing with a superior performance in terms of communication cost and detection quality compared to existing data mining schemes.
The No Child Left Behind Act: Accountability, High-Stakes Testing, and Roles for Sociologists

Central to sociology is the assumption that virtually all forms of social action and public policies have unanticipated consequences for their actors and social systems. As sociologists, we seek to explore these unanticipated consequences and delineate how they will affect people, policies, and practices. This essay focuses on the unanticipated consequences of the assessment and accountability mandates of the No Child Left Behind Act (NCLB) of 2001. Here, I suggest ways for sociologists to play significant roles in the states' implementation of their assessment and accountability systems. The key components of NCLB are not new (Mazzeo 2001), since the assessment of students is traceable to the post-Civil War era, and school accountability followed the publication of A Nation at Risk (National Commission on Excellence in Education
Drama Education: A ‘self-organising system’ in pursuit of learning

The pursuit of meaning in drama is part of a larger pursuit of the means by which meaning is created and shared. Through an inquiry into the making of meaning it is possible to gain greater insight into the learning contained in the processes of drama. In his inquiry into drama and learning the author has found the ‘system’a useful vehicle for engaging with the drama experience. ‘Systems theory’ offers a frame through which the drama experience can be interpreted, just as it does an opportunity to reflect upon the language systems through which meaning is held and communicated, in and through drama. ‘Self-organising systems theory’ extends this understanding by suggesting the processes through which explanations ‘feed back’ into the system and create opportunities to reflect on not only the experience, but the context of its occurrence. In the context of drama education, a systems analysis allows teachers, students and researchers to step back from the subject, to imagine, then construct connections more clearly (not the least being the researcher’s own connection to the subject). In this increasingly rewarding field, science meets poetry in an imaginative synthesis of research and learning. For this reason alone it is a useful tool in the attempt to find a language appropriate to a discussion of the learning made available through drama education.
Statistical Learning of Rational Wavelet Transform for Natural Images

Motivated with the concept of transform learning and the utility of rational wavelet transform in audio and speech processing, this paper proposes Rational Wavelet Transform Learning in the Statistical sense (RWLS) for natural images. The proposed RWLS design is carried out via lifting framework and is shown to have a closed form solution. The efficacy of the learned transform is demonstrated in the application of compressed sensing (CS) based reconstruction. The learned RWLS is observed to perform better than the existing standard dyadic wavelet transforms.
Using origami design principles to fold reprogrammable mechanical metamaterials

Folding robots and metamaterials The same principles used to make origami art can make self-assembling robots and tunable metamaterials—artificial materials engineered to have properties that may not be found in nature (see the Perspective by You). Felton et al. made complex self-folding robots from flat templates. Such robots could potentially be sent through a collapsed building or tunnels and then assemble themselves autonomously into their final functional form. Silverberg et al. created a mechanical metamaterial that was folded into a tessellated pattern of unit cells. These cells reversibly switched between soft and stiff states, causing large, controllable changes to the way the material responded to being squashed. Science, this issue p. 644, p. 647; see also p. 623 Origami folded sheets can be structurally altered by adding defects to control the mechanical properties. [Also see Perspective by You] Although broadly admired for its aesthetic qualities, the art of origami is now being recognized also as a framework for mechanical metamaterial design. Working with the Miura-ori tessellation, we find that each unit cell of this crease pattern is mechanically bistable, and by switching between states, the compressive modulus of the overall structure can be rationally and reversibly tuned. By virtue of their interactions, these mechanically stable lattice defects also lead to emergent crystallographic structures such as vacancies, dislocations, and grain boundaries. Each of these structures comes from an arrangement of reversible folds, highlighting a connection between mechanical metamaterials and programmable matter. Given origami’s scale-free geometric character, this framework for metamaterial design can be directly transferred to milli-, micro-, and nanometer-size systems.
A Dialogue Process for Choosing Value-Creating Strategies

A decision process has proven effective in three activities thatare key to value creation: choosing an excellent strategy, actually bringing about change, and operating effectively with the new strategy. The dialogue is between a decision board and the strategy team as they work through six steps of a decision process. This process is focused on alternatives and implementation and is founded in decision analysis. Strategy frame-works and structuring tools are key to assessing the business situation. Risk and value trade-offs are made explicit, leading to concrete proposals to add value and reduce risk. Explicit plans for action are developed as the strategic alternative is chosen. Companies have developed strategy insights using this process, as we illustrate with examples from the pharmaceutical industry.
Specification of the UFT Web-Based Fitness Tracking Software

The main components of the UML-based specification of the Ultimate Fitness Tracker (UFT) software are presented in this paper. The UFT is a web-based fitness tracking application that allows users to define and plan exercising programs and keep track of their progress. The application’s main functionality is outlined in the paper in terms of functional and non-functional requirements and samples of use case modeling, high-level design, and user interface are provided. The current status of the UFT application as well as several planned directions of further research and development are also presented in the paper. Key-Words: fitness tracking software, web application, requirements specification, use cases, scenarios, UML.
Characterization of human reflex tear proteome reveals high expression of lacrimal proline‐rich protein 4 (PRR4)

In‐depth studies on the proteome of reflex tears are still inadequate. Hence, further studies on this subject will unravel the key proteins which are conjectured to possess vital functions in the protection of the ocular surface. Therefore, this study investigated the differences in the expression levels in proteome of reflex compared to basal tears. Basal (n = 10) and reflex (n = 10) tear samples from healthy subjects were collected employing the capillary method, subsequently pooled and the proteomes were characterized employing 1DE combined with LC‐ESI‐MS/MS strategy for label‐free quantitative (LFQ) analysis. The differentially expressed proteins were validated by 2DE combined with LC‐ESI‐MS/MS and targeted‐MS approach called accurate inclusion mass screening (AIMS) strategies. The analysis of the reflex tear proteome demonstrated increased abundance in proline‐rich protein 4 (PRR4) and zymogen granule protein 16 homolog B (ZG16B) for the first time. Other abundant lacrimal proteins, e.g. lactotransferrin and lysozyme remained constant. Predominantly, the lacrimal gland‐specific PRR4 represents the major increased protein in reflex tears in an attempt to wash out irritants that come into contact with the eye. Conversely, decreased abundance in Ig alpha‐1 chain C, polymeric immunoglobulin receptor, cystatin S/SN, clusterin and mammaglobin were observed. This study had further unraveled the intricate proteome regulation during reflex tearing, especially the potential role of PRR4, which may be the key player in the protection and maintenance of dynamic balance of the ocular surface.
Real-Time, Transcranial Monitoring of Safe Blood-Brain Barrier Opening in Non-Human Primates

The delivery of drugs to specific neural targets faces two fundamental problems: most drugs do not cross the blood-brain barrier and those that do spread to all parts of the brain. To date there exists only one non-invasive methodology with the potential to solve these problems: selective blood-brain barrier disruption using micro-bubble enhanced focused ultrasound. We have recently developed a single-element 500 kHz spherical transducer ultrasound setup for use in the nonhuman primate. Here, we tested the accuracy of the system by targeting the caudate nucleus of the basal ganglia in two macaque monkeys. Our results show that average in-plane error of the system is on the order of 2 mm and targeting error in depth, i.e., along the ultrasound path, is even smaller averaging 1.2 mm. We have also developed a real-time treatment monitoring based on backscattered emissions spectral analyses. This technique helped us determining a safe and reliable acoustic parameters window for BBB opening.
Aging, female sex, migration, elevated HDL-C, and inflammation are associated with prevalence of metabolic syndrome among African bank employees

Background The objective of this study was to compare four different criteria for diagnosing metabolic syndrome (MS) and to correlate sociodemographic data, liver enzymes, lipids, inflammation, and insulin resistance with MS definitions. Methods This cross-sectional study included a random number of 126 African bank employees from Brazzaville, Congo. Results The prevalence of MS varied according to the different definitions used: 4.8% under World Health Organization (WHO) criteria, 8.7% under the National Cholesterol Education Program Adult Treatment Panel III (NECP-ATPIII) criteria, 14.3% under the International Diabetes Federation (IDF) for Europe, and 15.9% by the IDF for Central Africa. According to the IDF, specific cutoff points for the erythrocyte sedimentation rate, ≥13 mm at first hour and ≥30 mm at second hour, defined MS for Central Africa. The best agreement was observed between the IDF for Europe and the IDF for Central Africa (Kappa = 0.938; P < 0.0001) criteria. The worst agreements were between the WHO and IDF for Central Africa (Kappa = 0.419; P < 0.0001) criteria and between the WHO and IDF for Europe (Kappa = 0.462; P < 0.0001) criteria. The NECP-ATPIII criteria did not agree with either the IDF for Europe or the IDF for Central Africa criteria. There was a significant relationship between female sex, aging, elevated liver enzymes, elevated phospholipids, high homeostasis model assessment of insulin resistance, and MS defined by the IDF for Central Africa. Conclusion The IDF definition of the MS modified for Central Africa provides higher prevalence estimates of MS than the estimates based on the NECP-ATPIII and IDF for Europe criteria. Liver enzymes, phospholipids, and homeostasis model assessment of insulin resistance should be included in clinical practice to stratify cardiovascular disease risk among Africans.
Von Mises-Fisher Mean Shift for Clustering on a Hypersphere

We propose a method of clustering sample vectors on a hypersphere. Sample vectors are normalized in many cases, especially when applying kernel functions, and thus lie on a (unit) hypersphere. Considering the constraint of the hypersphere, the proposed method utilizes the von Mises-Fisher distribution in the framework of mean shift. It is also extended to the kernel-based clustering method via kernel tricks to cope with complex distributions. The algorithms of the proposed methods are based on simple matrix calculations. In the experiments, including a practical motion clustering task, the proposed methods produce favorable clustering results.
Short-term variation in sperm competition causes sperm-mediated epigenetic effects on early offspring performance in the zebrafish

The inheritance of non-genetic factors is increasingly seen to play a major role in ecology and evolution. While the causes and consequences of epigenetic effects transmitted from the mother to the offspring have received ample attention, much less is known about how variation in the condition of the father affects the offspring. Here, we manipulated the intensity of sperm competition experienced by male zebrafish Danio rerio to investigate the potential for sperm-mediated epigenetic effects over a relatively short period of time. We found that the rapid responses of males to varying intensity of sperm competition not only affected sperm traits as shown previously, but also the performance of the resulting offspring. We observed that males exposed to high intensity of sperm competition produced faster swimming and more motile sperm, and sired offspring that hatched over a narrower time frame but exhibited a lower survival rate than males exposed to low intensity of sperm competition. Our results provide striking evidence for short-term paternal effects and the possible fitness consequences of such sperm-mediated non-genetic factors not only for the resulting offspring but also for the female.
Motor unit synchronization in physiologic, enhanced physiologic, and voluntary tremor in man

Synchronization between pairs of single motor units simultaneously recorded from wrist extensor muscles was quantitated in 3 normal subjects during physiologic tremor (PT), beta‐adrenergically enhanced physiologic tremor (EPT), and fast voluntary wrist flexion‐extension movements mimicking tremor (VT). Cross‐correlation histograms generated from the two spike trains of each motor unit pair demonstrated central or paracentral peaks in 13/19 recording during PT, 22/36 during EPT, and 6/7 during VT. Relative peak area was used as a quantitative index of synchronization between the two motor units of each pair. It was lowest in PT, progressively increased in EPT as tremor amplitude increased, and highest in VT. In PT and lower amplitude EPT, the synchronization indexes were higher between motor units that discharged at the same or nearly the same frequency. In contrast, in higher amplitude EPT and VT, motor units with different firing frequencies were sometimes strongly synchronized as a consequence of double discharges in faster‐firing motor units that had burst repetition rates in the range of slower‐firing motor units discharging as singlets. Greater motor unit synchronization with increasing tremor amplitude in EPT may be secondary to a simultaneous increase in muscle spindle afferent activity from the tremulous muscle. Greatest synchronization in VT presumably reflects near maximal supraspinal and segmental common synaptic input onto motoneurons that generate VT. These results support a longstanding hypothesis that synchronization of motor units is the physiological basis for higher amplitude tremor.
Children's Understanding of Advertising: An Investigation Using Verbal and Pictorially Cued Methods.

Conflicting results on children's understanding of advertising may stem from differences in research methods. Most studies are conducted using interviewing techniques, employing only verbal questioning. In the present study, 136 children of two age groups (7 and 10 years) were first asked what advertising was for and, after responding, shown depictions of possible reasons. The results indicate that although older children are more likely than younger ones to understand that advertising seeks to promote selling, pictorial cues allow a much larger proportion of all children to indicate their understanding than verbal questioning does on its own, with younger children especially showing improvement. Thus, seven-year-olds seem to have an implicit understanding of the persuasive intent of advertising that they are unable to articulate in response to investigators' questions. Multiple methods appear to offer a means of evaluating the level of sophistication in children' understanding of advertising.
Entrevista de apego para niños (EAN): estudio exploratorio de un nuevo instrumento de evaluación del apego en población infantil de 3 a 7 años

This study analizes the psychometric properties of a new instrument about the working model of children´s attachment. The sample was composed of 60 subjects (30 from normal population and 30 from a social risk population). The age of children ranges from 3 to 7 years old. This instrument is an interview based on the completion story task, however it includes new contents as well as a new procedure in regarding to previous attachment measures. The findings show good validity and reliability. The found results are going to be the beginning of future studies.
Scaling and universality in continuous length combinatorial optimization

We consider combinatorial optimization problems defined over random ensembles and study how solution cost increases when the optimal solution undergoes a small perturbation δ. For the minimum spanning tree, the increase in cost scales as δ2. For the minimum matching and traveling salesman problems in dimension d ≥ 2, the increase scales as δ3; this is observed in Monte Carlo simulations in d = 2, 3, 4 and in theoretical analysis of a mean-field model. We speculate that the scaling exponent could serve to classify combinatorial optimization problems of this general kind into a small number of distinct categories, similar to universality classes in statistical physics.
Making sense of self‐care practices at the intersection of severe mental illness and physical health—An Australian study

The poor physical health of people who experience severe mental illness (SMI) is an important public health issue that has been acknowledged, yet not properly addressed. People who live with SMI perform a myriad of complex tasks in order to take care of their physical health, while receiving unpredictable levels of support and assistance from health professionals. In this qualitative study, we aimed to uncover the kinds of work people with SMI do in order to look after their physical health. In a metropolitan area in Queensland, Australia, 32 people with lived experience of SMI participated in semi-structured, face-to-face interviews. Data were digitally recorded, transcribed verbatim and open coded. They were then themed using a constant comparative process. We found that people with SMI were engaged in a "rhythm of life with illness" that consisted of relatively short, acute and chaotic cycles of mental and physical illness, accompanied by much longer mental and physical illness recovery cycles. Participants engaged in three specific types of health-related work to manage these cycles: discovery work (and the associated role of the health professional); sense-making work to meaningfully interpret health and illness; and embedding work to become engaged self-managers of illness and producers of health. We discuss how varying levels of support from health professionals impact consumers' self-management of their physical and mental health; how health professionals influence consumers' experience of treatment burden; and implications for practice.
Network routing capacity

We define the routing capacity of a network to be the supremum of all possible fractional message throughputs achievable by routing. We prove that the routing capacity of every network is achievable and rational, we present an algorithm for its computation, and we prove that every non-negative rational number is the routing capacity of some network. We also determine the routing capacity for various example networks. Finally, we discuss the extension of routing capacity to fractional coding solutions and show that the coding capacity of a network is independent of the alphabet used
Unsupervised Class Separation of Multivariate Data through Cumulative Variance-Based Ranking

This paper introduces a new extension of outlier detection approaches and a new concept, class separation through variance. We show that accumulating information about the outlierness of points in multiple subspaces leads to a ranking in which classes with differing variance naturally tend to separate. Exploiting this leads to a highly effective and efficient unsupervised class separation approach, especially useful in the difficult case of heavily overlapping distributions. Unlike typical outlier detection algorithms, this method can be applied beyond the `rare classes' case with great success. Two novel algorithms that implement this approach are provided. Additionally, experiments show that the novel methods typically outperform other state-of-the-art outlier detection methods on high dimensional data such as Feature Bagging, SOE1, LOF, ORCA and Robust Mahalanobis Distance and competes even with the leading supervised classification methods.