Miracle-dz/UniFAR-FTUs huggingface dataset:
Discovering and Representing Logical Structure in Code Change

There is a significant gap between how programmers think about code change and how change is represented in most software engineering tools. Programmers often think about code change in terms of structure: which code elements changed and how their structural dependencies are affected by the change. By reasoning about structural information within and around changed code, they recognize high-level systematic changes such as refactorings and crosscutting changes. Yet, most software engineering tools are based on a textual representation of code change. To bridge this gap, we propose a novel rule-based delta representation that explicitly and concisely captures systematic changes to a program’s structure, along with an engine that automatically infers such rules. Our logical structural delta (LSD) can complement existing uses of textual deltas: e.g., understanding another programmer’s modification, reviewing a patch before submission, and writing change documentation. We believe that LSD may serve as a basis for many software engineering tools that can benefit from explicit logical structure in code change: a bug finding tool, a refactoring reconstruction tool, a dependency removal checker, etc.
Church in the Round: Feminist Interpretation of the Church

Ideas of the Christian church are changing, and Letty Russell envisions its future as partnership and sharing for all members around a common table of hospitality. Russell draws on her pastorate in Harlem, her classes in theology, and many ecumenical conversations to help the newly emerging church face the challenges of liberation for all people.
TIFAflow: enhancing traffic archiving system with flow granularity for forensic analysis in network security

The archiving of Internet traffic is an essential function for retrospective network event analysis and forensic computer communication. The state-of-the-art approach for network monitoring and analysis involves storage and analysis of network flow statistic. However, this approach loses much valuable information within the Internet traffic. With the advancement of commodity hardware, in particular the volume of storage devices and the speed of interconnect technologies used in network adapter cards and multi-core processors, it is now possible to capture 10 Gbps and beyond real-time network traffic using a commodity computer, such as n2disk. Also with the advancement of distributed file system (such as Hadoop, ZFS, etc.) and open cloud computing platform (such as OpenStack, CloudStack, and Eucalyptus, etc.), it is practical to store such large volume of traffic data and fully in-depth analyse the inside communication within an acceptable latency. In this paper, based on well- known TimeMachine, we present TIFAflow, the design and implementation of a novel system for archiving and querying network flows. Firstly, we enhance the traffic archiving system named TImemachine+FAstbit (TIFA) with flow granularity, i.e., supply the system with flow table and flow module. Secondly, based on real network traces, we conduct performance comparison experiments of TIFAflow with other implementations such as common database solution, TimeMachine and TIFA system. Finally, based on comparison results, we demonstrate that TIFAflow has a higher performance improvement in storing and querying performance than TimeMachine and TIFA, both in time and space metrics.
EMG-to-force estimation with full-scale physiology based muscle model

EMG-to-force estimation for voluntary muscle contraction has many applications in human-machine interaction, motion analysis, and rehabilitation robotics for prosthetic limbs or exoskeletons. EMG-based model can account for a subject's individual activation patterns to estimate muscle force. For the estimation, so-called Hill-type model has been used in most of the cases. It already has shown its promising performance, but it is still known as a phenomenological model considering only macroscopic physiology. We have already developed the physiological based muscle model for the use of functional electrical stimulation (FES) which can render the myoelectrical property also in microscopic scale. In this paper we discuss EMG-to-force estimation based on this full physiological based muscle model in voluntary contraction. In addition to Hill macroscopic structure, a microscopic physiology originally designed by Huxley is integrated. It has significant meaning to realize the same kind of EMG-to-force estimation with a physiological based model not with a phenomenological model, because it brings the understanding of the internal biophysical dynamics and new insights about neuromuscular activations. Using same EMG data of isometric muscle contraction, the force estimation results are shown by classical approach and new physiological based approach. Its interpretation is also discussed.
Investigation of Saturable and Reverse Saturable Absorptions for Graphene by Z-Scan Technique

The optical nonlinear absorption (NLA) property of multilayer graphene was investigated by Z-scan technique with picosecond laser pulse of 532-nm wavelength. Graphene samples were fabricated by chemical vapor deposition (CVD) with different number of layers, which were 1-, 8-, and 16-layer. The dependence of NLA coefficient α(I) on number of layers was investigated under the laser intensity of 7-80 GW/cm2. The results showed that α(I) increased as the number of layer increased, and decreased as the laser intensity increased. Nonlinearities of graphene were mainly caused by saturable absorption (SA) effect. The 1-, 8-, and 16-layer graphene exhibited SA nonlinearity. However, reversed SA (RSA) nonlinearity was observed for 16-layer graphene only. The RSA was resulted from two-photon absorption due to layer stacking-induced bandgap opening, confirmed by the α(I) measurement. The RSA may reduce the stability of mode-locking and therefore, it suggests that the lower layer stacking in CVD fabricated graphene is preferable to use as saturable absorbers in laser mode-locking.
Genetic influences on the circulating cytokines involved in osteoclastogenesis

It has been shown that compared with healthy subjects or patients with other types of tumour, patients with myeloma bone disease have lower OPG levels in their serum (or within the bone microenvironment), and that these low OPG serum levels are inversely correlated with the severity of the disease. One study even suggests that serum levels of OPG could serve as a cardiovascular risk factor. 11 Further support for OPG being a vascular regulator comes from an epidemiological study conducted by Browner and colleagues, 12
Using randomization in the teaching of data structures and algorithms

We describe an approach for incorporating randomization in the teaching of data structures and algorithms. The proofs we include are quite simple and can easily be made a part of a Freshman-Sophomore Introduction to Data Structures (CS2) course and a Junior-Senior level course on the design and analysis of data structures and algorithms (CS7/DS&amp;A). The main idea of this approach is to show that using randomization in data structures and algorithms is safe and can be used to significantly simplify efficient solutions to various computational problems. We illustrate this approach by giving examples of the use of randomization in some traditional topics from CS2 and DS&amp;A.
Java Virtual Machine monitoring for dependability benchmarking

A monitoring infrastructure is a key component in each task aimed at evaluating the dependability of a system. This paper presents a monitoring infrastructure for the Java Virtual Machine (JVM), which is starting to be employed in mission and safety critical application, often with real-time requirements. This infrastructure, named JVMMon, collects data about both the state and the failures of the monitored Virtual Machine. The state of the JVM was defined according to the Java Virtual Machine specification. JVMMon is constituted by three components: a monitoring agent which collects data from the monitored VM; a local monitor daemon that receives data from such agent and updates the state of the JVM; a data collector, which stores events and state snapshots in a database. The impact on the performance of the JVM has been evaluated running the SPEC JVM98 benchmark suite
An Infrastructure Approach to Context-Aware Computing

The Context Toolkit (Dey, Abowd, and Salber, 2001 [this special issue]) is only one of many possible architectures for supporting context-aware applications. In this essay, we look at the tradeoffs involved with a service infrastructure approach to context-aware computing. We describe the advantages that a service infrastructure for context awareness has over other approaches, outline some of the core technical challenges that must be addressed before such an infrastructure can be built, and point out promising research directions for overcoming these challenges.
Altered Glutamate Reuptake in Relapsing-Remitting and Secondary Progressive Multiple Sclerosis Cortex: Correlation With Microglia Infiltration, Demyelination, and Neuronal and Synaptic Damage

Cortical involvement in multiple sclerosis (MS) is emerging as an important determinant of disease progression. The mechanisms responsible for MS cortical pathology are not fully characterized. The objective of this study was to assess the role of excitotoxicity in MS cortex, evaluating excitatory amino acid transporter (EAAT) expression and its relationship with demyelination, inflammation, gliosis, and neuronal and synaptic pathology. EAATs are essential in maintaining low extracellular glutamate concentrations and preventing excitotoxicity. Ten MS brains (3 relapsing-remitting MS cases and 7 secondary progressive MS cases) were evaluated by immunohistochemistry for myelin basic protein, CD68, HLA-DR, EAAT1, EAAT2, glial fibrillary acidic protein, phosphorylated c-Jun N-terminal kinase (pJNK), synaptophysin, and neurofilaments. Cortical lesions were frequently observed in MS brains in variable numbers and extensions. In cortical lesions, activated microglia infiltration correlated with focal loss of EAAT1, EAAT2, and synaptophysin immunostaining, and with neuronal immunostaining for pJNK, a protein involved in response to excitotoxic injury. No reduction of EAATs or synaptophysin immunostaining was observed in demyelinated cortex in the absence of activated microglia. Alterations of the mechanisms of glutamate reuptake are found in cortical MS lesions in the presence of activated microglia and are associated with signs of neuronal and synaptic damage suggestive of excitotoxicity. Excitotoxicity may be involved in the pathogenesis of demyelination and of neuronal and synaptic damage in MS cortex.
Sociological and Philosophical Aspects of Human Interaction with Technology: Advancing Concepts

Anabela Mesquita is a professor at the Institute of Administration and Accountancy (ISCAP)/Polytechnic School of Porto (IPP), Portugal. She is also an invited researcher at the Algoritmi R & D Center, Information Systems Group, at the University of Minho (Portugal). She lectures courses related to business communication, information society, and digital storytelling. Dr. Mesquita’s research interests include knowledge and innovation management, impact of information systems in organization, life long learning at higher education levels, and e-learning. She also has been involved in several European and national research projects. Dr. Mesquita has published numerous papers in various international journals and conference proceedings. She has been a member of the programme committee and scientific committee of several national and international conferences, in most cases also serving as referee. She serves as Member of the Editorial Board and referee for IGI Global. She also serves as Associate Editor of the Information Resources Management Journal. She serves as referee for the Journal of Cases of Information Technology. She has also been evaluator and reviewer for European commission projects. Anabela Mesquita (ISCAP/IPP and Algoritmi Centre, University of Minho, Portugal)
GaN nanowire tips for nanoscale atomic force microscopy

Imaging of high-aspect-ratio nanostructures with sharp edges and straight walls in nanoscale metrology by atomic force microscopy (AFM) has been challenging due to the mechanical properties and conical geometry of the majority of available commercial tips. Here we report on the fabrication of GaN probes for nanoscale metrology of high-aspect-ratio structures to enhance the resolution of AFM imaging and improve the durability of AFM tips. GaN nanowires were fabricated using bottom-up and top-down techniques and bonded to Si cantilevers to scan vertical trenches on Si substrates. Over several scans, the GaN probes demonstrated excellent durability while scanning uneven structures and showed resolution enhancements in topography images, independent of scan direction, compared to commercial Si tips.
Integration of text- and data-mining using ontologies successfully selects disease gene candidates

Genome-wide techniques such as microarray analysis, Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS), linkage analysis and association studies are used extensively in the search for genes that cause diseases, and often identify many hundreds of candidate disease genes. Selection of the most probable of these candidate disease genes for further empirical analysis is a significant challenge. Additionally, identifying the genes that cause complex diseases is problematic due to low penetrance of multiple contributing genes. Here, we describe a novel bioinformatic approach that selects candidate disease genes according to their expression profiles. We use the eVOC anatomical ontology to integrate text-mining of biomedical literature and data-mining of available human gene expression data. To demonstrate that our method is successful and widely applicable, we apply it to a database of 417 candidate genes containing 17 known disease genes. We successfully select the known disease gene for 15 out of 17 diseases and reduce the candidate gene set to 63.3% (±18.8%) of its original size. This approach facilitates direct association between genomic data describing gene expression and information from biomedical texts describing disease phenotype, and successfully prioritizes candidate genes according to their expression in disease-affected tissues.
Epidemiology, diagnosis and management of hirsutism: a consensus statement by the Androgen Excess and Polycystic Ovary Syndrome Society.

BACKGROUND Hirsutism, defined by the presence of excessive terminal hair in androgen-sensitive areas of the female body, is one of the most common disorders in women during reproductive age. METHODS We conducted a systematic review and critical assessment of the available evidence pertaining to the epidemiology, pathophysiology, diagnosis and management of hirsutism. RESULTS The prevalence of hirsutism is ~10% in most populations, with the important exception of Far-East Asian women who present hirsutism less frequently. Although usually caused by relatively benign functional conditions, with the polycystic ovary syndrome leading the list of the most frequent etiologies, hirsutism may be the presenting symptom of a life-threatening tumor requiring immediate intervention. CONCLUSIONS Following evidence-based diagnostic and treatment strategies that address not only the amelioration of hirsutism but also the treatment of the underlying etiology is essential for the proper management of affected women, especially considering that hirsutism is, in most cases, a chronic disorder needing long-term follow-up. Accordingly, we provide evidence-based guidelines for the etiological diagnosis and for the management of this frequent medical complaint.
Structured Best Arm Identification with Fixed Confidence

We study the problem of identifying the best action among a set of possible options when the value of each action is given by a mapping from a number of noisy micro-observables in the so-called fixed confidence setting. Our main motivation is the application to the minimax game search, which has been a major topic of interest in artificial intelligence. In this paper we introduce an abstract setting to clearly describe the essential properties of the problem. While previous work only considered a two-move game tree search problem, our abstract setting can be applied to the general minimax games where the depth can be non-uniform and arbitrary, and transpositions are allowed. We introduce a new algorithm (LUCB-micro) for the abstract setting, and give its lower and upper sample complexity results. Our bounds recover some previous results, which were only available in more limited settings, while they also shed further light on how the structure of minimax problems influence sample complexity.
Blood Viscosity in Subjects With Normoglycemia and Prediabetes

OBJECTIVE Blood viscosity (BV) is higher in diabetic patients and might represent a risk factor for the development of insulin resistance and type 2 diabetes. However, data in subjects with normal glucose or prediabetes are missing. In the current study, we evaluated the relationship between BV and blood glucose in subjects with normal glucose or prediabetes. RESEARCH DESIGN AND METHODS Enrolled subjects were divided into three groups according to blood glucose: group A (n = 74), blood glucose <90 mg/dL; group B (n = 96), blood glucose ranging from 90 to 99 mg/dL; and group C (n = 94), blood glucose ranging from 100 to 125 mg/dL. BV was measured at 37°C with a cone-plate viscometer at shear rates ranging from 225 to 22.5 s−1. RESULTS Blood pressure, blood lipids, fibrinogen, and plasma viscosity were similar in the three groups. BMI and waist circumference were significantly increased in group C. Hematocrit (P < 0.05) and BV (P between 0.01 and 0.001) were significantly higher in groups B and C compared with group A. Blood glucose was significantly and inversely correlated with HDL cholesterol and directly with BMI, waist, hematocrit (r = 0.134), and BV (from 225 s−1 to 22.5 s−1; r ranging from 0.162 to 0.131). BV at shear rate 225 s−1 was independently associated with blood glucose. CONCLUSIONS The current study shows a direct relationship between BV and blood glucose in nondiabetic subjects. It also suggests that, even within glucose values considered completely normal, individuals with higher blood glucose levels have increased BV comparable with that observed in subjects with prediabetes.
Localization and organization of protein factors involved in chromosome inheritance in Dictyostelium discoideum

Abstract Heterochromatin protein 1 (HP1) proteins are highly conserved heterochromatin components required for genomic integrity. We have previously shown that the two HP1 isoforms expressed in Dictyostelium, HcpA and HcpB, are mainly localized to (peri-)centromeric heterochromatin and have largely overlapping functions. However, they cause distinct phenotypes when overexpressed. We show here that these isoforms display quantitative differences in dimerization behavior. Dimerization preference, as well as the mutant phenotype in overexpression strains, depends on the C-terminus containing the hinge and chromo shadow domains. Both Hcp proteins are targeted to distinct subnuclear regions by different chromo shadow domain-dependent and -independent mechanisms. In addition, both proteins bind to DNA and RNA in vitro and binding is independent of the chromo shadow domain. Thus, this DNA and/or RNA binding activity may contribute to protein targeting. To further characterize heterochromatin, we cloned the Dictyostelium homolog of the origin recognition complex subunit 2 (OrcB). OrcB localizes to distinct subnuclear foci that were also targeted by HcpA. In addition, it is associated with the centrosome throughout the cell cycle. The results indicate that, similar to Orc2 homologs from other organisms, it is required for different processes in chromosome inheritance.
Iterative exact global histogram specification and SSIM gradient ascent: a proof of convergence, step size and parameter selection

The SSIM-optimized exact global histogram specification (EGHS) is shown to converge in the sense that the first order approximation of the result's quality (i.e., its structural similarity with input) does not decrease in an iteration, when the step size is small. Each iteration is composed of SSIM gradient ascent and basic EGHS with the specified target histogram. Selection of step size and other parameters is also discussed.
Single-Wafer Pressure Capacitive Sensor

A novel manufacturing process for pressure sensor without the need of wafer bonding is presented. Its main advantages are a simple fabrication process and an efficient integr ability with other devices. The sensor is composed of a polysilicon membrane that deflects due to the pressure difference applied over it. Two operation regions are observed: a non-linear sensitivity region at low pressure (0-30 kPa) and a linear one (30-200 kPa) in touch mode. A capacitance-to-frequency conversion circuitry is designed and validated to provide a sensitive sensing module. Experimental results show a sensitivity of 28.7 fF/kPa and of 13.93 Hz/kPa in the nonlinear region. Among the most significant features of this device are versatility, high reliability, integrability and high sensivity.
Discovering Latent Structures for Activity Recognition in Smart Environments

Activity recognition is of great importance for a variety of context-aware applications and especially for assistance provided for independent living of the elderly. One of the factors that has impact on the activity recognition accuracy is feature representation. Many approaches have been proposed to select the most discriminative subset of features for activity recognition, but they are data-dependent and related to real numbers gathered from wearable sensors/devices. However, feature representation and transformation in smart environments, in which the data is very often a discrete sensor reading, has not been fully explored. In this paper, we map the activity model in a smart environment to a topic model and leverage the hierarchical Dirichlet process (HDP) to discover hidden structures from the sensor reading sequences. We use a hybrid approach: we combine the discovered latent structures with discriminative classifier such as support vector machines (SVMs), and demonstrate, through comparison studies, its effectiveness in improving activity recognition accuracy and the robustness to sensor noises. The comparison studies are carried out on three publicly available datasets from smart environments.
Benzyl 5-hydroxy-4-oxapentacyclo[5.4.1.02,6.03,10.08,11]dodecane-3-carboxylate

The title compound, C19H18O4, exhibits a long C—C bond [1.575 (2) Å] in the cage structure. In the crystal, pairs of O—H⋯O hydrogen bonds link the molecules into centrosymmetric dimers. C—H⋯O interactions also occur.