Miracle-dz/UniFAR-FTUs huggingface dataset:
An overview of program slicing

MARK HARMAN and ROBERT HIERONS review three semantic paradigms for slicing — static, dynamic and conditioned; and two syntactic paradigms — syntax-preserving and amorphous. Slicing has been applied to many software development problems including testing, reuse, maintenance and evolution. This paper describes the main forms of program slice and some of the applications to which slicing has been put. Copyright © 2001 John Wiley & Sons, Ltd.
Evaluating the process of wisdom in wise political leaders using a developmental wisdom model

Wise leadership is increasingly attracting attention in organizational, management and leadership literature (Mumford 2011). However, the notion of wisdom is still diverse and ambiguous. Determining what constitutes wisdom turns us in the directions of psychology and philosophy: Rooney, McKenna and Liesch (2010) claim that there is considerable overlap between Aristotelian philosophy and the work of contemporary wisdom psychological theorists. While some may find it inappropriate, incommensurate, even disturbing to attempt to measure a concept like wisdom because of its ineffable and transcendent quality (Case and Gosling 2007), there is considerable evidence to show that people believe that they ‘know’ wisdom when they see it (Pasupathi and Staudinger 2001). We propose, then, that to attempt to find human characteristics that might predict the likelihood of wisdom is not an inappropriate practice. For example, most would agree that a reasonable level of intelligence and knowledge is needed to be wise, although all the major wisdom theorists (Sternberg, Berlin School, Ardelt and so on) would strongly argue that it is a necessary, but not sufficient, condition.
GPU-CC: a reconfigurable GPU architecture with communicating cores

GPUs have evolved to programmable, energy efficient compute accelerators for massively parallel applications. Still, compute power is lost in many applications because of cycles spent on data movement and control instead of computations on actual data. Additional cycles can be lost as well on pipeline stalls due to long latency operations. To improve performance and energy efficiency, we introduce GPU-CC: a reconfigurable GPU architecture with communicating cores. It is based on a contemporary GPU, which can still be used as such, but also has the ability to reorganize the cores of a GPU in a reconfigurable network. In GPU-CC data movement and control is implicit in the configuration of the communication network. Additionally each core executes a fixed instruction, reducing instruction decode count and increasing energy efficiency. We show a large performance potential for GPU-CC, e.g. 1.9x and 2.4x for a 3x3 and 5x5 convolution application. The hardware cost of GPU-CC is mainly determined by the buffers in the added network, which amounts to 12.4% of extra memory space.
Single-plasmon interferences

The wave-particle duality of single surface plasmons is demonstrated using a plasmonic beam splitter on a flat gold device. Surface plasmon polaritons are electromagnetic waves coupled to collective electron oscillations propagating along metal-dielectric interfaces, exhibiting a bosonic character. Recent experiments involving surface plasmons guided by wires or stripes allowed the reproduction of quantum optics effects, such as antibunching with a single surface plasmon state, coalescence with a two-plasmon state, conservation of squeezing, or entanglement through plasmonic channels. We report the first direct demonstration of the wave-particle duality for a single surface plasmon freely propagating along a planar metal-air interface. We develop a platform that enables two complementary experiments, one revealing the particle behavior of the single-plasmon state through antibunching, and the other one where the interferences prove its wave nature. This result opens up new ways to exploit quantum conversion effects between different bosonic species as shown here with photons and polaritons.
Sedation with dexmedetomidine in the intensive care setting

Dexmedetomidine is an α-2 agonist that produces sedation and analgesia without compromising the respiratory drive. Use of dexmedetomidine as a sedative in the critically ill is associated with fewer opioid requirements compared with propofol and a similar time at goal sedation compared with benzodiazepines. Dexmedetomidine may produce negative hemodynamic effects including lower mean heart rates and potentially more bradycardia than other sedatives used in the critically ill. Recent studies have demonstrated that dexmedetomidine is safe at higher dosages, but more studies are needed to determine whether the efficacy of dexmedetomidine is dose dependent. In addition, further research is required to define dexmedetomidine’s role in the care of delirious critically ill patients, as many, but not all, studies have indicated favorable outcomes.
Chapter 3 Graph-Theoretic Analysis of Multistability and Monotonicity for Biochemical Reaction Networks

Mathematical models of biochemical reaction networks are usually high dimensional, nonlinear, and have many unknown parameters, such as reaction rate constants, or unspecified types of chemical kinetics (such as mass-action, Michaelis-Menten, or Hill kinetics). On the other hand, important properties of these dynamical systems are often determined by the network structure, and do not depend on the unknown parameter values or kinetics. For example, some reaction networks may give rise to multiple equilibria (i.e., they may function as a biochemical switch) while other networks have unique equilibria for any parameter values. Or, some reaction networks may give rise to monotone systems, which renders their dynamics especially stable. We describe how the species-reaction graph (SR graph) can be used to analyze both multistability and monotonicity of networks.
Design and analysis of algorithms: course notes

Preface These are my lecture notes from CMSC 651: Design and Analysis of Algorithms. This course has been taught several times and each time the coverage of the topics differs slightly. Here I have compiled all the notes together. The course covers core material in data structures and algorithm design, and also helps students prepare for research in the field of algorithms. The reader will find an unusual emphasis on graph theoretic algorithms, and for that I am to blame. The choice of topics was mine, and is biased by my personal taste. The material for the first few weeks was taken primarily from the textbook on Algorithms by Cormen, Leiserson and Rivest. In addition, I have used material from several other books such as the Combinatorial Optimization book by Papadimitriou and Steiglitz, as well as the Network Flow book by Ahuja, Magnanti and Orlin and the edited book on Approximation Algorithms by Hochbaum. A few papers were also covered, that I personally feel give some very important and useful techniques that should be in the toolbox of every algorithms researcher.
De novo Assembly and Analysis of the Northern Leopard Frog Rana pipiens Transcriptome

The northern leopard frog Rana (Lithobates) pipiens is an important animal model, being used extensively in cancer, neurology, physiology, and biomechanical studies. R. pipiens is a native North American frog whose range extends from northern Canada to southwest United States, but over the past few decades its populations have declined significantly and is now considered uncommon in large portions of the United States and Canada. To aid in the study and conservation of R. pipiens, this paper describes the first R. pipiens transcriptome. The R. pipiens transcriptome was annotated using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Eukaryotic Orthologous Groups (KOG). Differential expression analysis revealed universal and tissue specific genes, and endocrine-related genes were identified. Transcriptome assemblies and other sequence data are available for download.
Sustainability Reporting in Higher Education: Interconnecting the Reporting Process and Organisational Change Management for Sustainability

Although there has been a considerable increase in the publication of sustainability reports in the corporate world in the last decade, sustainability reporting in higher education institutions is still in its early stages. This study’s aim was to explore the relationship between sustainability reporting and organizational change management for sustainability in higher education. A survey was sent to higher education institutions worldwide that have published sustainability reports in the last ten years. The survey was answered by 23 institutions out of a total of 64. The findings showed that sustainability reporting has been predominantly driven by internal motivations, and that the sustainability reporting process leads to incremental changes, such as an increase in awareness of sustainability and improvements in communication with internal stakeholders. Some factors impeding change are the absence of an external stakeholder engagement process, the lack of inclusion of material impacts in reports, and the lack of institutionalization of sustainability reporting in the higher education system. The paper proposes that higher education institutions need to consider sustainability reporting as a dynamic tool to plan sustainability changes, and not just as a communication activity.
Greed is Good: Optimistic Algorithms for Bipartite-Graph Partial Coloring on Multicore Architectures

In parallel computing, a valid graph coloring yields a lock-free processing of the colored tasks, data points, etc., without expensive synchronization mechanisms. However, coloring is not free and the overhead can be significant. In particular, for the bipartite-graph partial coloring (BGPC) and distance-2 graph coloring (D2GC) problems, which have various use-cases within the scientific computing and numerical optimization domains, the coloring overhead can be in the order of minutes with a single thread for many real-life graphs. In this work, we propose parallel algorithms for bipartite-graph partial coloring on shared-memory architectures. Compared to the existing shared-memory BGPC algorithms, the proposed ones employ greedier and more optimistic techniques that yield a better parallel coloring performance. In particular, on 16 cores, the proposed algorithms perform more than 4x faster than their counterparts in the ColPack library which is, to the best of our knowledge, the only publicly-available coloring library for multicore architectures. In addition to BGPC, the proposed techniques are employed to devise parallel distance-2 graph coloring algorithms and similar performance improvements have been observed. Finally, we propose two costless balancing heuristics for BGPC that can reduce the skewness and imbalance on the cardinality of color sets (almost) for free. The heuristics can also be used for the D2GC problem and in general, they will probably yield a better color-based parallelization performance especially on many-core architectures.
Independent genetic loci for sensorimotor gating and attentional performance in BXD recombinant inbred strains

A startle reflex in response to an intense acoustic stimulus is inhibited when a barely detectable pulse precedes the startle stimulus by 30–500 ms. It has been theorized that this phenomenon, named prepulse inhibition (PPI) of a startle response, is an automatic early‐stage gating process contributing to the ability to focus attention. Deficits in PPI may therefore contribute to deficits in attentional processing. Both deficits are observed in schizophrenia spectrum disorders. Here, we investigated whether there is overlap in genetic control of PPI and attentional processing phenotypes in the panel of BXD recombinant inbred strains of mice. Using an individually titrated prepulse intensity to handle differences in perceived prepulse intensities among strains, we identified a significant quantitative trait locus (QTL) for PPI at the mid‐distal end of chromosome 17. A measure of attentional processing in the five‐choice serial reaction time task, response variability, mapped to a different locus on proximal‐mid chromosome 16. In addition, the estimated genetic and environmental correlations between PPI and several attentional phenotypes were low and not significant. Taken together, the observation of separate genetic loci for PPI and attention and the absence of genetic and environmental correlations indicate that differences in sensorimotor gating do not contribute to differences in attentional performance. Therefore, it is worth pursuing the causative genes residing in both attention and PPI QTL, as these may contribute to separate molecular pathways implicated in neuropsychiatric diseases, such as schizophrenia.
Research of android malware detection based on network traffic monitoring

With Android terminal into the life of people, the spread of Android malware seriously affected people's life. As a result of the Android security flaws, attackers can easily collect private information of users, and the information can be utilized in APT attacks. It is not only a threat to the end user, but also poses a threat to industrial control systems and mobile Internet. In this paper, we propose a network traffic monitoring system used in the detection of Android malware. The system consists of four components: traffic monitoring, traffic anomaly recognition, response processing and cloud storage. The system parses the protocol of data packets and extracts the feature data, then use SVM classification algorithm for data classification, determine whether the network traffic is abnormal, and locate the application that produced abnormal through the correlation analysis. The system not only can automatic response and process the malicious software, but also can generate new security policy from existing information and training data; When training data is reaching a certain amount, it will trigger a new round of training to improve the ability of detection. Finally, we experiment on the system, the experimental results show that our system can effectively detect the Android malware and control the application.
Sarcopenia is associated with Framingham risk score in the Korean population: Korean National Health and Nutrition Examination Survey (KNHANES) 2010–2011

Background Sarcopenia is a risk factor for metabolic disorders and cardiovascular disease, but the association between sarcopenia and cardiovascular risk factors according to age and obesity status in the general population remains unknown. We thus investigated these associations in the Korean population. Methods We included 8,958 and 8,518 subjects from the fifth Korean National Health and Nutrition Examination Survey (KNHANES) (from 2010 and 2011, respectively). The study was restricted to participants ≥ 20 years old who had completed the health examination survey, including whole body dual-energy X-ray absorptiometry scans. After exclusion, 7,366 subjects (3,188 men, 4,178 women) were included in our final analysis. Age was categorized according to three age groups (20–39, 40–59, and ≥ 60 years), and subjects were categorized according to their sarcopenic and obesity status. Cardiovascular risk was assessed with Framingham risk score (FRS). Results The sarcopenic obese group had a higher FRS than the non-sarcopenic obese group, which had a higher FRS than the non-sarcopenic non-obese group. Age-wise, the 20–39 year-old group showed a non-significant association between sarcopenia and FRS. In the 40–59 year-old group, regardless of obesity status, sarcopenic subjects had a higher FRS than non-sarcopenic subjects. In the ≥ 60 year-old group, sarcopenic subjects had a higher FRS than non-sarcopenic subjects for the non-obese group. Conclusions Sarcopenia was associated with cardiovascular disease and may be an early predictor of its susceptibility in both elderly and middle-aged subjects. Thus, management of sarcopenia is necessary to prevent cardiovascular disease.
Endogenous Serotonin Contributes to a Developmental Decrease in Long-Term Potentiation in the Rat Visual Cortex

The primary visual cortex shows synaptic plasticity during a postnatal “critical period,” and its plasticity declines with development. Indeed, we found a developmental decrease in the induction of long-term potentiation (LTP) in the rat visual cortex. In visual cortex slices obtained from 2- to 3-week-old rats, tetanic stimulation (100 Hz for 1 sec, twice at an interval of 30 sec) of the white matter reproducibly induced LTP of field potentials in layer II/III. However, in slices from 5-week-old rats, the same tetanic stimulation failed to induce LTP. We hypothesized that endogenous serotonin (5-HT) is responsible for the developmental decrease in visual cortex LTP, because the induction of visual cortex LTP was suppressed by the addition of exogenous 5-HT (10 μm) and because the amount of 5-HT in the visual cortex increased during development. To test this hypothesis, we investigated the effect of methysergide, a 5-HT receptor antagonist, on the induction of visual cortex LTP. When visual cortex slices from 5-week-old rats were perfused with 50 μmmethysergide, tetanic stimulation of the white matter induced robust LTP in layer II/III. Furthermore, serotonergic neurons were lesioned by intracerebroventricular injection of 5,7-dihydroxytryptamine (5,7-DHT). LTP was induced in visual cortex slices from 5,7-DHT-treated, 5-week-old rats. These results suggest that the induction of visual cortex LTP in 5-week-old rats is suppressed by endogenous 5-HT. 5-HT may be a factor that determines a critical period for synaptic plasticity in the rat visual cortex.
DCloud: Deadline-Aware Resource Allocation for Cloud Computing Jobs

With the tremendous growth of cloud computing, it is increasingly critical to provide quantifiable performance to tenants and to improve resource utilization for the cloud provider. Though many recent proposals focus on guaranteeing job performance (with a particular note on network bandwidth) in the cloud, they usually lack efficient utilization of cloud resource, or vice versa. In this paper we present DCloud, which leverages the (soft) deadlines of cloud computing jobs to enable flexible and efficient resource utilization in data centers. With the deadline requirement of a job guaranteed, DCloud employs both time sliding (postponing the launching time of a job) and bandwidth scaling (adjusting the bandwidth associated with VMs) in resource allocation, so as to better match the resource allocated to the job with the cloud's residual resource. Extensive simulations and testbed experiments show that DCloud can accept much more jobs than existing solutions, and significantly increase the cloud provider's revenue with less cost for individual tenants.
Building damage detection from post-earthquake aerial images using watershed segmentation in Golcuk, Turkey

The collapsed buildings due to earthquake were detected from post-event aerial images using watershed segmentation algorithm. The objective was to detect the collapsed buildings based on the analysis of the cast shadows. The building boundaries were available and stored in a GIS as vector polygons. The building polygons were utilized to perform assessments in a building specific manner. The approach was implemented in a selected urban area of Golcuk. The shadows cast by the buildings were detected using the watershed segmentation algorithm. The shadow casting edges of the buildings were identified and a buffer zone was generated for each building polygon along these edges. Then, the initial points falling within the buffer zone were selected from both inside and outside the building polygons to start the watershed segmentation. The shadow regions were detected using a watershed segmentation algorithm. This was followed by measuring the agreement between the shadow producing edges of the buildings and the corresponding shadows based on the percentage of the shadow pixels. Of the 284 buildings analyzed, 229 were correctly labeled as collapsed or un-collapsed providing an overall accuracy of 80%. The results prove that the collapsed buildings caused by the earthquake can be successfully detected from post-event aerial images.
A Direct-Construction Based Fuzzy Support Vector Classifier

This study presents a novel direct-construction based fuzzy multiclass support vector classifier based on previous multi-class classification method by Crammer and Singer (2001). In our proposed method, the membership degree is computed by fuzzy c-means clustering, the optimal problem and its constraints of multi- class classification are reconstructed and its corresponding Lagrangian formula is re-deduced. Experimental comparison with the previous study indicates that our method can obtain better classification ratio.
Interdependence in Comparative Politics

Interdependence is ubiquitous and often central across comparative politics. Indeed, as the authors show first, theoretically, any situation involving externalities from one unit's actions on others' implies interdependence. Positive or negative externalities induce negative or positive interdependence, which spurs competitive races or free riding, with corresponding early or late-mover advantages, and thus strategic rush to act or delay and inaction. The authors show next how to model interdependent processes empirically, how not doing so risks omitted-variable biases favoring domestic and exogenous-external accounts over interdependence, but how doing so naïvely risks simultaneity biases with the opposite substantive implications. They then discuss how to estimate properly specified interdependence models and, finally, how to interpret and present estimated spatio-temporally dynamic effects, response paths, and long-run steady-states, with associated standard errors. They illustrate by replicating a noteworthy earlier, nonspatial study of capital tax competition. Web appendices contain further technical details, literature survey, data, statistical software code, and spreadsheet templates for all suggested procedures.
LVCSR-based language identification

Automatic language identification is an important problem in building multilingual speech recognition and understanding systems. Building a language identification module for four languages we studied the influence of applying different levels of knowledge sources on a large vocabulary continuous speech recognition (LVCSR) approach, i.e. phonetic, phonotactic, lexical, and syntactic-semantic knowledge. The resulting language identification (LID) module can identify spontaneous speech input and can be used as a front end for the multilingual speech-to-speech translation system JANUS-II. A comparison of five LID systems showed that the incorporation of lexical and linguistic knowledge reduces the language identification error for the 2-language tests up to 50%. Based on these results we build a LID module for German, English, Spanish, and Japanese which yields 84% identification rate on the spontaneous scheduling task (SST).