Miracle-dz/UniFAR-FTUs huggingface dataset:
Safety-Critical Java Virtual Machine Services

To ensure that Safety-Critical Java (SCJ) programs run correctly and safely, the virtual machine they run on must be shown to operate correctly. To the best of our knowledge, however, currently we do not even have a clear specification of the requirements for such a virtual machine. In this paper, we present an identification of these requirements for the SCJ API and infrastructure, based on the requirements of the SCJ standard and on consideration of existing virtual machines for SCJ. Formal methods provide a powerful tool in modelling and eliciting requirements, and establishing correctness of implementations. We also present here a formal model of the requirements written in the Circus specification language, which has already been used in a technique for verification of SCJ programs. Our work is a contribution to establishing a framework for the development of fully verified systems using SCJ.
Community surveillance for cerebrovascular disease: the Framingham Cardiovascular Disease Survey.

To ESTIMATE CEREBROVASCULAR ACCIDENT (CVA) incidence in communities, reliable yet economical methods are needed by which the geographic and temporal patterns of CVA occurrence, as well as the effects of community hypertension detection and treatment programs, can be accurately assessed. The Framingham Cardiovascular Disease Survey (CVDS) was undertaken (a) to determine the accuracy of incidence rates generated from a short-term surveillance study of a defined community as compared with a longitudinal survey of a sample of the same population and (b) to investigate the methodological problems of such a short-term study. Our report deals with the results of the Framingham CVDS.
Congestion prediction in early stages of physical design

Routability optimization has become a major concern in physical design of VLSI circuits. Due to the recent advances in VLSI technology, interconnect has become a dominant factor of the overall performance of a circuit. In order to optimize interconnect cost, we need a good congestion estimation method to predict routability in the early designing stages. Many congestion models have been proposed but there's still a lot of room for improvement. Besides, routers will perform rip-up and reroute operations to prevent overflow, but most models do not consider this case. The outcome is that the existing models will usually underestimate the routability. In this paper, we have a comprehensive study on our proposed congestion models. Results show that the estimation results of our approaches are always more accurate than the previous congestion models.
Left/Right Brains, Teammates in Learning

Left/right brain research and its implications for teachers are highlighted. The medical and psychological research in asymmetry and the related attitudinal changes towards brain functioning over the last 150 years are reviewed. Strategies teachers may apply to classroom practice are abstracted from that research. Respect for the functioning of each hemisphere and the need for the “teaming” of both are emphasized.
Acute regulation of proximal tubule apical membrane Na/H exchanger NHE-3: role of phosphorylation, protein trafficking, and regulatory factors.

The mammalian proximal tubule reabsorbs approximately 80% of the NaHCO3 and approximately 50% of the filtered NaCl from the glomerular filtrate ([1][1],[2][2],[3][3]). All of the transcellular NaCl and two-thirds of the transcellular NaHCO3 absorption are mediated by the proximal tubule apical
Evaluation of evidence for autocorrelated data, with an example relating to traces of cocaine on banknotes

Much research in recent years for evidence evaluation in forensic science has focussed on methods for determining the likelihood ratio in various scenarios. The likelihood of the evidence is calculated under each of two propositions, that proposed by the prosecution and that proposed by the defence. The value of the evidence is given by the ratio of the likelihoods associated with these two propositions. The aim of this research is to evaluate this likelihood ratio under two scenarios. The first is when the evidence consists of continuous autocorrelated data. The second, an extension to this, is when the observed data are also believed to be driven by an underlying latent Markov chain. Four models have been developed to take these attributes into account: an autoregressive model of order one, a hidden Markov model with autocorrelation between adjacent data points and a nonparametric model with two different bandwidth selection methods. Application of these methods will be illustrated with an example where the data relate to traces of cocaine on banknotes as measured by the log peak area for the ion count for cocaine product ion m/z 105 in a mass spectrometer. The likelihood ratios using these four models will be calculated for these data, and the results compared.
Twenty Years of Clinical Experience with a New Modality of Vascular‐Targeted Photodynamic Therapy for Port Wine Stains

BACKGROUND Port wine stains (PWS) are congenital capillary malformations of the skin and are difficult to treat without scarring. Since January 1991, our group has performed a new modality of vascular‐targeted photodynamic therapy (PDT) for PWS treatment. OBJECTIVE To summarize our clinical experiences with vascular‐targeted PDT for PWS at Chinese PLA General Hospital. METHODS AND MATERIALS Our group has collected and reviewed retrospective clinical research data of vascular‐targeted PDT for treating PWS since January 1991. RESULTS Clinical studies showed that vascular‐targeted PDT is an effective treatment for all types of PWS. Repetitive treatment sessions were usually needed to obtain a better cosmetic effect. No recurrence was seen in patients followed up for longer than 19 years. There were no significant side effects or adverse reactions. CONCLUSION This new PDT is an effective, safe, and noninvasive modality with no recurrence for PWS, although the protocol for PDT requires further optimization. The authors have indicated no significant interest with commercial supporters.
The Causes and Consequences of Changes in Virulence following Pathogen Host Shifts

Emerging infectious diseases are often the result of a host shift, where the pathogen originates from a different host species. Virulence—the harm a pathogen does to its host—can be extremely high following a host shift (for example Ebola, HIV, and SARs), while other host shifts may go undetected as they cause few symptoms in the new host. Here we examine how virulence varies across host species by carrying out a large cross infection experiment using 48 species of Drosophilidae and an RNA virus. Host shifts resulted in dramatic variation in virulence, with benign infections in some species and rapid death in others. The change in virulence was highly predictable from the host phylogeny, with hosts clustering together in distinct clades displaying high or low virulence. High levels of virulence are associated with high viral loads, and this may determine the transmission rate of the virus.
Towards Next Generation Touring: Personalized Group Tours

Recommending and planning tour itineraries are challenging and time-consuming for tourists, hence they may seek tour operators for help. Traditionally tour operators have offered standard tour packages of popular locations, but these packages may not cater to tourist's interests. In addition, tourists may want to travel in a group, e.g., extended family, and want an operator to help them. We introduce the novel problem of group tour recommendation (GroupTourRec), which involves many challenges: forming tour groups whose members have similar interests; recommending Points-of-Interests (POI) that form the tour itinerary and cater for the group's interests; and assigning guides to lead these tours. For each challenge, we propose solutions involving: clustering for tourist groupings; optimizing a variant of the Orienteering problem for POI recommendations; and integer programming for tour guide assignments. Using a Flickr dataset of seven cities, we compare our proposed approaches against various baselines and observe significant improvements in terms of interest similarity, total/maximum/minimum tour interests and total tour guide expertise.
Comparison In Vitro of a High- and a Low-Abundance Chemoreceptor of Escherichia coli: Similar Kinase Activation but Different Methyl-Accepting Activities

ABSTRACT In Escherichia coli, high-abundance chemoreceptors are present in cellular amounts approximately 10-fold greater than low-abundance chemoreceptors. Cells containing only low-abundance receptors exhibit abnormally low tumble frequencies and do not migrate effectively in spatial gradients. These defects reflect an inherent activity difference between the two receptor classes. We used in vitro assays to investigate this difference. The low-abundance receptor Trg mediated an ∼100-fold activation of the kinase CheA, only twofold less than activation by the high-abundance receptor Tar. In contrast, Trg was less than 1/20 as active as Tar for in vitro methylation. As observed for high-abundance receptors, kinase activation by Trg varied with the extend of modification at methyl-accepting sites; low methylation corresponded to low kinase activation. Thus, in Trg-only cells, low receptor methylation would result in low kinase activation, correspondingly low content of phospho-CheY, and a decreased dynamic range over which attractant binding could modulate kinase activity. These features could account for the low tumble frequency and inefficient taxis exhibited by Trg-only cells. Thus, the crucial functional difference between the receptor classes is likely to be methyl-accepting activity. We investigated the structural basis for this functional difference by introducing onto the carboxy terminus of Trg a CheR-binding pentapeptide, usually found only at the carboxy termini of high-abundance receptors. This addition enhanced the in vitro methyl-accepting activity of Trg 10-fold.
Organizational effects of information and communication technology (ICT) in elderly homecare: a case study

The use of information and communication technology (ICT) to support integrated healthcare services in elderly homecare is becoming more established. In particular, ICT can enable information exchange, knowledge sharing and documentation at the point-of-care (POC). The aim of this study was to explore these effects using the Old@Home prototype. Old@Home was perceived to contribute in developing horizontal links for communication between individuals who work together, independent of geographical distance or organizational affiliation, and to contribute to increased work efficiency. The prototype was further seen to reduce professional isolation by providing a holistic overview of the care process. User centred design and implementation of Old@Home was considered key to facilitating acceptance of organizational changes. Participation of care professionals not only led to a better understanding of the needs of involved organizations, but also increased end-users' involvement and commitment, stimulating them to test and improve the prototype until the final version.
SET pulse-width measurement eliminating pulse-width modulation and within-die process variation effects

This paper presents a measurement circuit structure for capturing SET pulse-width suppressing pulse-width modulation and within-die process variation effects. For mitigating pulse-width modulation while maintaining area efficiency, the proposed circuit uses massively parallelized short inverter chains as a target circuit. Moreover, for each inverter chain on each die, pulse-width calibration is performed. In measurements, narrow SET pulses ranging 5 ps to 215 ps were obtained. We confirm that an overestimation of pulse-width may happen when ignoring die-to-die and within-die variation of the measurement circuit. Our evaluation results thus point out that calibration for within-die variation in addition to die-to-die variation of the measurement circuit is indispensable.
Voltage Control of Multiterminal VSC-HVDC Transmission Systems for Offshore Wind Power Plants: Design and Implementation in a Scaled Platform

This paper deals with multiterminal voltage source converter (VSC) HVDC transmission systems for the connection of offshore wind power plants to the main land ac grid. A droop-based control scheme is considered. The droop controllers have been designed base on a mixed sensitivity criterion by solving a convex optimization problem with linear matrix inequalities. The system is analyzed by means of simulations and experimentally in a scaled platform. Simulations show the control performance during a wind speed change and a voltage sag in the main ac grid. Experimental results include wind power changes (increase and decrease) and an eventual VSC loss (both considering grid-side and wind farm VSC loss). In all the cases, the simulation and the experimental results have shown a good system performance.
Verified Enforcement of Automaton-based Information Release Policies

Many organizations specify complex information release policies to describe the terms under which sensitive information may be released to organizations outside of their control. In this paper, we present AIR, a formal language for describing information release policies in terms of security automata. Each automaton’s state transitions correspond to conditions that must be satisfied before information may be released, and released information may be optionally downgraded. We give a semantics to AIR policies by translating them into an API for programs written in λAIR, a core formalism for a purely functional programming language. Through its use of dependent, singleton, and affine types, λAIR’s type system assists in the proof that programs use an AIR policy API correctly. Our work takes an important step toward building software, such as so-called cross-domain guards, that can be verified to correctly enforce high-level information release policies.
EFFECT OF BODY MASS INDEX, WAIST HIP RATIO AND WAIST CIRCUMFERENCE ON COGNITIVE FUNCTIONS IN PERIMENOPAUSAL WOMEN

Cognitive performance is predictive of subsequent dementia; the assessment of risk factors might have a protective or detrimental effect on cognitive performance in perimenopausal women.The objective of the present study was to elucidate the effect of BMI, waist circumference and waist hip ratio on various cognitive function parameters such as Mini Mental Scale examination (MMS-E), Orientation, Attention, Memory, Visuo Spatial ability, Verbal Fluency and Language in perimenopausal age women.The present study included a total of 60 healthy women (40-60 years). Participants were categorized into control group and overweight/obese groups based on the body mass index . The results of the present study showed a significant decrease (P<0.05) in all the cognitive parameters in the overweight/obese group when compared to the control group. In conclusion the present study suggest that increased waist circumference, waist hip ratio and BMI are the risk factor for cognitive impairment in perimenopausal women.
Reducing the complexity of k-nearest diverse neighbor queries in medical image datasets through fractal analysis

Content-Based Image Retrieval (CBIR) Systems allow the search of images by similarity employing a numeric representation automatically or semi-automatically obtained from them to perform the search. Nevertheless, the query result does not always bring what the user expected. In this sense, CBIR systems face the semantic gap problem. One way of overcoming this problem is by the addition of diversity in query execution, so that the user can ask the system to return the most varied images regarding some similarity criteria. However, applying diversity on large datasets has a prohibitive computational cost and, moreover, the result often differs from the expected with a resulting subset that has images with high dissimilarity to the query image. In this paper we propose an approach to reduce the computational cost of Content-Based Image Retrieval systems regarding similarity and diversity criteria. The proposed approach employs dataset fractals analysis to estimate a suitable radius for a database subset to perform a similarity query regarding diversity. It selects closer images to the query center and applies the diversity factor to the subset, providing not only a better comprehension of the impact of the diversity factor to the query result, but also an improvement in execution time.
An Emerging Era in the Management of Parkinson's Disease: Wearable Technologies and the Internet of Things

Current challenges demand a profound restructuration of the global healthcare system. A more efficient system is required to cope with the growing world population and increased life expectancy, which is associated with a marked prevalence of chronic neurological disorders such as Parkinson's disease (PD). One possible approach to meet this demand is a laterally distributed platform such as the Internet of Things (IoT). Real-time motion metrics in PD could be obtained virtually in any scenario by placing lightweight wearable sensors in the patient's clothes and connecting them to a medical database through mobile devices such as cell phones or tablets. Technologies exist to collect huge amounts of patient data not only during regular medical visits but also at home during activities of daily life. These data could be fed into intelligent algorithms to first discriminate relevant threatening conditions, adjust medications based on online obtained physical deficits, and facilitate strategies to modify disease progression. A major impact of this approach lies in its efficiency, by maximizing resources and drastically improving the patient experience. The patient participates actively in disease management via combined objective device- and self-assessment and by sharing information within both medical and peer groups. Here, we review and discuss the existing wearable technologies and the Internet-of-Things concept applied to PD, with an emphasis on how this technological platform may lead to a shift in paradigm in terms of diagnostics and treatment.
Face normalization using multi-scale cortical keypoints

Empirical studies concerning face recognition suggest that faces may be stored in memory by a few canonical representations. Models of visual perception are based on image representations in cortical area V1 and beyond, which contain many cell layers for feature extractions. Simple, complex and end-stopped cells tuned to different spatial frequencies (scales) and/or orientations provide input for line, edge and keypoint detection. This yields a rich, multi-scale object representation that can be stored in memory in order to identify objects. The multi-scale, keypoint-based saliency maps for Focus-of-Attention can be explored to obtain face detection and normalization, after which face recognition can be achieved using the line/edge representation. In this paper, we focus only on face normalization, showing that multi-scale keypoints can be used to construct canonical representations of faces in memory.
A study of towel folding by a robot arm - Spreading and vertex detection using image processing

In this study, we aim to construct a sequence of towel folding operations by a robot arm. In this paper, we propose the methods for spreading a towel and detecting the grasp positions. For the easy spreading of the towel, we propose how to put the towel on the table. The proposed method lifts one vertex of the towel, and detects the shadow part by using a camera image for recognizing the overlapped condition of the towel. For the folding motion of the towel, we set the vertices of the towel edges as grasping positions. So, we propose the way to detect the vertices of the towel correctly by generating a rectangle which includes all feature points of the towel by using image processing.
Automatic Discrimination of the Geographical Origins of Milks by Excitation-Emission Fluorescence Spectrometry and Chemometrics

This paper presents the automatic discrimination of geographical origins of milks from Western Yunnan Plateau areas and eastern China by excitation-emission fluorescence spectrometry and chemometrics. Genuine plateau milks (n = 60) and milks from eastern China (n = 89) are scanned in the regions of 180–300 nm for excitation and 200–800 nm for emission. Different options of data analysis are investigated and compared in terms of their performance in discriminating milks of different geographical origins: (1) two-way partial least squares discriminant analysis (PLSDA) based on excitation and emission spectra, respectively; (2) two-way PLSDA based on fusion of excitation and emission spectra; (3) three-way PLSDA based on excitation-emission matrix spectra. The two-way PLSDA methods with excitation spectra, emission spectra, and fusion of excitation and emission spectra correctly classify 91.3%, 88.6%, and 95.3% of the milk samples, respectively; while the total accuracy of three-way PLSDA is 96.0%. The results demonstrate the two-way data combining excitation and emission spectra are sufficient to characterize and identify the plateau milks. Considering both model accuracy and the analytical time required, two-way PLS-DA with fusion of excitation and emission spectra is recommended as a reliable and quick method to discriminate plateau milks from ordinary milks.
THE ORMATION OF VACUOLES DUE TO BACILLUS TYPHOSUS IN THE CELLS OF TISSUE CULTURES OF THE INTESTINE OF THE CHICK EMBRYO

The introduction of Bacillus typhosus into the hanging drop of a tissue culture of the intestine of a chick embryo leads to the rapid vacuolation of the cells of the tissues which comprise the growth of the cultures. The cells of the connective tissue, the endodermal membrane, the mesothelium, and also the clasmatocytes exhibit the ability to ingest Bacillus typhosus in the cultures.
Detecting Anomalies in Massive Traffic Streams Based on S-Transform Analysis of Summarized Traffic Entropies

Detecting traffic anomalies is an indispensable component of overall security architecture. As Internet and traffic data with more sophisticated attacks grow exponentially, preserving security with signaturebased traffic analyzers or analyzers that do not support massive traffic are not sufficient. In this paper, we propose a novel method based on combined sketch technique and S-transform analysis for detecting anomalies in massive traffic streams. The method does not require any prior knowledge such as attack patterns and models representing normal traffic behavior. To detect anomalies, we summarize the entropy of traffic data over time and maintain the summarized data in sketches. The entropy fluctuation of the traffic data aggregated to the same bucket is observed by S-transform to detect spectral changes referred to as anomalies in this work. We evaluated the performance of the method with real-world backbone traffic collected at the United States and Japan transit link in terms of both accuracy and false positive rates. We also explored the method parameters’ influence on detection performance. Furthermore, we compared the performance of our method to S-transform-based and Wavelet-based methods. The results demonstrated that our method was capable of detecting anomalies and overcame both methods. We also found that our method was not sensitive to its parameter settings. key words: anomaly detection, sketch, entropy, time-frequency analysis, S-transform