Miracle-dz/UniFAR-FTUs huggingface dataset:
Type inference for JavaScript

Object-oriented scripting languages like JavaScript are popular, in part because of their dynamic features. These include the runtime modification of objects and classes, through addition of fields or updating of methods. These features make static typing difficult and usually dynamic typing is used. Consequently, errors such as access to non-existent members, are not detected until runtime. We provide a static type system that can cope with dynamic features such as member addition, while providing the usual safety guarantees. Since the structure of objects may change over time, we employ a structural type system to track the changes. We show how type inference can be used to infer the structure of objects and give corresponding structural types. Therefore, the programmer can enjoy the safety offered by static typing, without having to give explicit types in their programs. We develop JS0, a formalisation of JavaScript with features including dynamic addition of fields and updating of methods. We give an operational semantics and static type system for JS0 using structural types. Our types allow objects to evolve in a controlled manner by classifying members as definite or potential. A member is potential until it has been assigned to and then it becomes definite. We prove that our type system is sound. We develop a type inference algorithm for JS0 based on a system of constraints between type variables. We define a translation between constraints and types that allows us to generate a type annotated JS0 program from an untype JS0 program. We prove that the constraints are sound with respect to the type system and that our translation is deterministic. We define a well-formedness criterion on constraints and conjecture that well-formed constraints are satisfiable. Therefore, combined with the soundness of constraints and the soundness of the type system, we conjecture that programs that generate well-formed constraints will not get stuck.
Common mental disorders among patients in primary health care in Greenland

Introduction. There are many indications that mental health in Greenland is endangered and needs more attention. Study design. A two-stage study of the prevalence of common mental disorders among a sample of primary health care patients. Methods. 376 randomly selected patients from general consultations in two Greenlandic towns were screened with 12 questions from the General Health Questionnaire. From these patients, a sample of 100 patients, including more high-than low-scorers, was interviewed using the SCAN (Schedules for Clinical Assessment in Neuropsychiatry) Present Examination psychiatric interview. Results. Estimated prevalence for the total study population of at least one psychiatric diagnosis was 49.3% (95% CI 39.7–59.0%). Most diagnoses were in the group of anxieties, somatoform disorders and depressive disorders. Many patients had more than one diagnosis. Lack of education and poor proficiency in Danish, as well as growing up in a family with severe alcohol problems, were high risk factors for a psychiatric diagnosis. Patients and physicians seemingly agreed on focusing on physical disorders at the consultation, and only a minority of mental disorders was recognised and treated as such by the physicians. Conclusion. Mental disorders are prevalent but not sufficiently recognised and treated among patients in primary health care in Greenland. Their association with social and economic conditions calls for attention from the health services as well as from social and educational institutions.
Sparse Named Entity Classification using Factorization Machines

Named entity classification is the task of classifying text-based elements into various categories, including places, names, dates, times, and monetary values. A bottleneck in named entity classification, however, is the data problem of sparseness, because new named entities continually emerge, making it rather difficult to maintain a dictionary for named entity classification. Thus, in this paper, we address the problem of named entity classification using matrix factorization to overcome the problem of feature sparsity. Experimental results show that our proposed model, with fewer features and a smaller size, achieves competitive accuracy to state-of-the-art models.
Selective Transurethral Resection of the Prostate Combined with Transurethral Incision of the Bladder Neck for Bladder Outlet Obstruction in Patients with Small Volume Benign Prostate Hyperplasia (BPH): A Prospective Randomized Study

Purpose Transurethral resection of the prostate (TURP) has a high failure rate in patients with small volume benign prostate hyperplasia (BPH) with bladder outlet obstruction (BOO). We describe and report the results of an alternative surgical method, selective transurethral resection of the prostate (STURP) in combination with transurethral incision of the bladder neck (TUIBN). Methods Patients were randomized to receive TURP or STRUP+TUIBN in combination with TUIBN. Maximum urinary flow rate (Qmax), voided volume, and post voiding residual volume (PVR) were assessed at baseline and at 1, 3, and 6 months after surgery. Efficacy of treatment was assessed by lower urinary tract symptoms and IPSS. Results Sixty three patients received STRUP+TUIBN and 61 received TURP. Surgical time, amount of prostate tissue resected, and blood loss was the same in both groups (all, p>0.05). The mean duration of follow-up was 9.02 and 8.53 months in patients receiving TURP and STRUP+TUIBN, respectively. At 6 months postoperatively, IPSS was 4.26±1.22 and 4.18±1.47 in patients receiving TURP and STRUP+TUIBN, respectively (p>0.05), and the Qmax in patients receiving STRUP+TUIBN was markedly higher than in those receiving TURP (28.28±6.46 mL/s vs. 21.59±7.14 mL/s; p<0.05). Bladder neck contracture and urinary tract infections were observed in 3 and 5 patients receiving TURP, respectively, and none in STURP. Conclusions STRUP+TUIBN may offer a more effective and safer alternative to TURP for small volume BPH patients.
Intelligent Detection System framework using Mobile agents

An intrusion detection system framework using mobile agents is a layered framework mechanism designed to support heterogeneous network environments to identify intruders at its best. Traditional computer misuse detection techniques can identify known attacks efficiently, but perform very poorly in other cases. Anomaly detection has the potential to detect unknown attacks; however, it is a very challenging task since its aim is to detect unknown attacks without any priori knowledge about specific intrusions. This technology is still at its early stage. The objective of this paper is that the system can detect anomalous user activity. Existing research in this area focuses either on user activity or on program operation but not on both simultaneously. In this paper, an attempt to look at both concurrently is presented. Based on an intrusion detection framework [1], a novel user anomaly detection system has been implemented and conducted several intrusion detection experiments in a simulated environment by analyzing user activity and program operation activities. The proposed framework is a layered framework, which is designed to satisfy the core purpose of IDS, and allows detecting the intrusion as quickly as possible with available data using mobile agents. This framework was mainly designed to provide security for the network using mobile agent mechanisms to add mobility features to monitor the user processes from different computational systems. The experimental results have shown that the system can detect anomalous user activity effectively.
PARTICULARITIES REGARDING THE COMPREHENSIVE REHABILITATION OF THE REVASCULARIZED DIABETIC PATIENTS Part II

Comprehensive rehabilitation is a concept developed in order to limit the physiopathologic and psychosocial consequences of the cardiac events and aims at limiting the risk of infract and sudden death, at improving the cardiac symptomathology, at delaying or determining the reversion of the atherosclerotic process and at reintegrating the cardiac patients within their family and professional activity with a proper functional status.
A Framework of Spatial Sensor Web

Sensor networks can be used to sense, collect and process information of monitored objects and transfer the information to users. It has been applied in many domains, such as military, environment observation, calamity forecasting, geo-spatial explore. A sensor Web refers to web accessible sensor networks and archived sensor data that can be discovered and accessed using standard protocols and application program interfaces (APIs). The sensor Web achieves the cooperation, series, harmony and consistency of data acquisition, abstraction and distribution. It is web-centric, open, interoperable, smart, and dynamical and is a new fashion of sensor deployment, data acquisition and information abstraction. In this paper, a framework of spatial sensor Web is designed. This framework includes SOS, SPS and some other services and integrates geographic information systems (GIS) which has the abilities of spatial locating and spatial analysis. The framework follows the sensor Web specifications defined by OGC and can accommodate and receive all kinds of sensor services and data. It enables the interoperability between different sensors, sensor systems and users and "plug-and-play" web-based sensor systems. A prototype of spatial sensor Web has been developed which integrates a sensor network of weather station to sensor web and GIS.
Robust nonlinear unmixing of hyperspectral images with a linear-mixture/nonlinear-fluctuation model

Hyperspectral data unmixing has attracted considerable attention in recent years. Hyperspectral data may however suffer from varying levels of signal-to-noise ratio over spectral bands. In this paper, we investigate a robust approach for nonlinear hyperspectral data unmixing. Each observed pixel is modeled as a linear mixing of endmember spectra with nonlinear fluctuations embedded in a reproducing kernel Hilbert space. Welsch M-estimator is considered for reducing the sensitivity of the unmixing process. Experimental results, with both synthetic and real data, illustrate the effectiveness of the proposed scheme.
On Issues with Software Quality Models

Software metrics and quality models play a pivotal role in measurement of software quality. A number of well-known quality models and software metrics are used to build quality software both in industry and in academia. However, during our research on measuring software quality using design patterns, we faced many issues related to existing software metrics and quality models. In this position paper, we discuss some of these issues and present our approach to software quality assessment
WSN18-4: Integrated Backup Topology Control and Routing of Obscured Traffic in Hybrid RF/FSO Networks

We propose a framework for providing instantaneous backup to traffic in a hybrid RF/FSO mesh network. Free space optical (FSO) links have high bandwidth and security, making them suitable for use in backbone networks. RF links have low bandwidth, but offer high reliability in conditions where FSO links are obscured. Thus, RF links are primarily used to provide instantaneous backup to traffic flowing on FSO links. We propose a framework to model FSO link failures due to obscuration, and propose algorithms for integrated topology control of RF links and routing for maximizing the backup provided. We do extensive simulations to demonstrate that the performance of RF topology and routing computed using our algorithms is much better than the case of having the same RF and FSO topologies and routes.
Full-Duplex MIMO Small-Cell Networks With Interference Cancellation

Full-duplex (FD) technology is envisaged as a key component for future mobile broadband networks due to its ability to boost the spectral efficiency. FD systems can transmit and receive simultaneously on the same frequency at the expense of residual self-interference (SI) and additional interference to the network compared with half-duplex (HD) transmission. This paper analyzes the performance of wireless networks with FD multi-antenna base stations (BSs) and HD user equipments (UEs) using stochastic geometry. Our analytical results quantify the success probability and the achievable spectral efficiency and indicate the amount of SI cancellation needed for beneficial FD operation. The advantages of multi-antenna BSs/UEs are shown and the performance gains achieved by balancing desired signal power increase and interference cancellation are derived. The proposed framework aims at shedding light on the system-level gains of FD mode with respect to HD mode in terms of network throughput, and provides design guidelines for the practical implementation of FD technology in large small-cell networks.
Auditory Perception: A New Analysis and Synthesis

Preface 1. Sound and the auditory system 2. Spatial localization and binaural hearing 3. Perception of acoustic repetition: pitch and infrapitch 4. Judging auditory magnitudes: the Sone scale of loudness and the Mel scale of pitch 5. Perception of acoustic sequences 6. Perceptual restoration of missing sounds 7. Speech 8. The relation of hearing to perception in general References Index.
Self-contained indoor pedestrian navigation by means of human motion analysis and magnetic field mapping

In the case of disasters such as fires, floods and earthquakes, effective and rapid rescue operations have to be carried out by first responders. Rescue operations inside of large-scale office buildings, shopping malls and public buildings are a major challenge in terms of positioning and guidance. Global navigation satellite systems (GNSS) and terrestrial radio navigation systems such as global positioning system (GPS), wireless local area network (WLAN), ultra-wideband (UWB) and radio frequency identification (RFID) are either not fully operative inside of buildings or require a costly system infrastructure. Hence, this paper deals with autonomous or self-contained and semi-autonomous positioning for pedestrians based on low-cost inertial measurement units (IMU). A novel combination of improved movement recognition or human motion analysis and magnetic field mapping for absolute repositioning is proposed. This combination allows for a low error of position and the minimization of the IMU-typically drift, respectively. Therefore in this paper several methods for human motion analysis as well as for magnetic field mapping are assessed. Furthermore a number of meaningful results are shown.
Autosomal recessive congenital cataract linked to EPHA2 in a consanguineous Pakistani family

Purpose To investigate the genetic basis of autosomal recessive congenital cataracts in a consanguineous Pakistani family. Methods All affected individuals underwent a detailed ophthalmological and clinical examination. Blood samples were collected and genomic DNAs were extracted. A genome-wide scan was performed with polymorphic microsatellite markers. Logarithm of odds (LOD) scores were calculated, and Eph-receptor type-A2 (EPHA2), residing in the critical interval, was sequenced bidirectionally. Results The clinical and ophthalmological examinations suggested that all affected individuals have nuclear cataracts. Genome-wide linkage analyses localized the critical interval to a 20.78 cM (15.08 Mb) interval on chromosome 1p, with a maximum two-point LOD score of 5.21 at θ=0. Sequencing of EPHA2 residing in the critical interval identified a missense mutation: c.2353G>A, which results in an alanine to threonine substitution (p.A785T). Conclusions Here, we report for the first time a missense mutation in EPHA2 associated with autosomal recessive congenital cataracts.
Estimation of multivariate models for time series of possibly different lengths

We consider the problem of estimating parametric multivariate density models when unequal amounts of data are available on each variable. We focus in particular on the case that the unknown parameter vector may be partitioned into elements relating only to a marginal distribution and elements relating to the copula. In such a case we propose using a multi-stage maximum likelihood estimator (MSMLE) based on all available data rather than the usual one-stage maximum likelihood estimator (1SMLE) based only on the overlapping data. We provide conditions under which the MSMLE is not less asymptotically efficient than the 1SMLE, and we examine the small sample efficiency of the estimators via simulations. The analysis in this paper is motivated by a model of the joint distribution of daily Japanese yen-US dollar and euro-US dollar exchange rates. We find significant evidence of time variation in the conditional copula of these exchange rates, and evidence of greater dependence during extreme events than under the normal distribution. Copyright © 2006 John Wiley & Sons, Ltd.
Question identification on Turkish tweets

Question identification is a field Natural Language Processing and also Information Extraction. The aim of work is detecting Turkish tweets which are including question expressions. The application contains three stages: applying some pre-processing steps to data set for cleaning unnecessary data like Retweet, determining candidate tweets via a rule-based method and extracting tweets which are really include questions using Conditional Random Fields. For this purpose one million tweets were collected and labeled. Tweets are ungrammatical data type. According to results; the model developed has been largely successful on tweets. Additionally, it is a first study about identifying questions on Turkish tweets.
Individual Differences in Anterior EEG Asymmetry in Children with High Functioning Autism

of a dissertation at the University of Miami. Dissertation supervised by Professors Peter Mundy and Heather Henderson. No. of pages in text. (128) This study examined the moderating role of motivational tendencies for social approach and avoidance behavior, as measured by anterior EEG asymmetry, on symptom expression. In particular, this study aimed to replicate and extend previous findings that measures of anterior EEG asymmetry provide an important marker of subgroups of HFA children that significantly differ from each other, and controls, on measures of social communication impairment. EEG data were collected across two occasions on 51 HFA and 44 non-HFA children. EEG asymmetry was computed for homologous electrode pairs (e.g., lnF4-lnF3). More positive scores were indicative of relative left frontal asymmetry. Data on social and behavioral functioning were collected via parentand self-report. Results of this short-term longitudinal study revealed moderate test-retest reliability for midfrontal asymmetry, r (65) = . 39, p < . 01. Results supported previous research demonstrating the differential relation of EEG asymmetry to symptom impairment among HFA children, such that parents of LFA-HFA children reported lower levels of impairment than RFA-HFA children on the SCQ Total Score, F (3, 47) = 3.58, p = . 065, and Social Interaction Domain, F (3, 47) = 4.59, p < . 05. Results also indicated that parents of LFA-HFA children reported higher levels of general communicative competence on the CCC-2, GCC, F (3, 47) = 6.83, p = . 01, but greater impairment in pragmatic communication when compared to RFA-HFA children, SIDC, F (3, 47) = 4.41, p < . 05. Additional analyses indicated that RFA was associated with early and more confident recognition of atypical (and stereotypically autistic) development based on retrospective parent-report (ADI-R #86), while LFA was associated with early, but less unambiguously autistic impairment, X (51) = 3.75, p = . 05. This study demonstrates that anterior EEG asymmetry subgroups are reliable and useful markers of phenotypic variability that are meaningfully related to the experience and expression of symptoms of core autism impairment.
Involvement of membrane calcium in the response of rabbit neutrophils to chemotactic factors as evidenced by the fluorescence of chlorotetracycline

We have utilized the fluorescent chelate probe chlorotetracycline to investigate the possible involvement of membrane calcium in the response of rabbit peritoneal neutrophils to chemotactic factors. Two chemotactic factors, the small molecular weight fragment of the fifth component of complement C5a and the synthetic peptide formyl-methionyl- leucyl-phenylalanine (F-Met-Leu-Phe), were tested and found to decrease the fluorescence of cell-associated chlorotetracycline in a manner strongly suggesting stimulus-induced displacement of membrane calcium. The time-course, concentration dependence, and receptor specificity of the calcium redistribution induced by the stimuli are consistent with its early role in the initiation of the various neutrophil functions. F- Met-Leu-Phe and C5a appear to interact with the same pool of membrane calcium and to release it to the cytoplasmic side of the plasma membrane. Intracellular calcium then binds back to the membrane(s) from where it can be displaced by additional stimulation. The release of membrane calcium, experimentally defined here, appears to play a central role in the initiation of the various neutrophil functions.
Adaptive Neuro-Fuzzy Extended Kaiman Filtering for robot localization

Extended Kaiman Filter (EKF) has been a popular approach in localization of a mobile robot. However, the performance of the EKF and the quality of the estimation depends on the correct a priori knowledge of process and measurement noise covariance matrices (Qk and RK, respectively). Imprecise knowledge of these statistics can cause significant degradation in performance. In this paper, the Adaptive Neuro-Fuzzy Inference System (ANFIS) supervises the performance of the EKF with adjusting the matrix Qk and RK. The ANFIS is trained using the steepest gradient descent (SD) to minimize the differences between the outputs of ANFIS and desired outputs. The simulation results show the effectiveness of the proposed algorithm.