Miracle-dz/UniFAR-FTUs huggingface dataset:
Insulin Resistance as Estimated by Homeostasis Model Assessment Predicts Incident Symptomatic Cardiovascular Disease in Caucasian Subjects From the General Population

OBJECTIVE—The purpose of this study was to evaluate whether insulin resistance is associated to cardiovascular disease (CVD) and to understand whether this association can be explained by traditional and novel CVD risk factors associated with this metabolic disorder. RESEARCH DESIGN AND METHODS—We examined a sample representative of the population of Bruneck, Italy (n = 919; aged 40–79 years). Insulin-resistant subjects were those with a score in the top quartile of the homeostasis model assessment (HOMA) for insulin resistance (HOMA-IR). Risk factors correlated with insulin resistance included BMI, A1C, HDL cholesterol, triglycerides, blood pressure, high-sensitivity C-reactive protein (hsCRP), fibrinogen, oxidized LDL, vascular cell adhesion molecule-1 (VCAM-1), and adiponectin. Subjects without CVD at baseline were followed up for 15 years for incident CVD, a composite end point including fatal and nonfatal myocardial infarction and stroke, transient ischemic attack, and any revascularization procedure. RESULTS—During follow-up, 118 subjects experienced a first symptomatic CVD event. Levels of HOMA-IR were higher at baseline among subjects who developed CVD (2.8) compared with those remaining free of CVD (2.5) (P < 0.05). Levels of HOMA-IR also were significantly correlated (P < 0.05) with most CVD risk factors we evaluated. In Cox proportional hazard models, insulin-resistant subjects had an age-, sex-, and smoking-adjusted 2.1-fold increased risk (95% CI 1.3–3.1) of incident symptomatic CVD relative to non–insulin-resistant subjects. After sequential adjustment for physical activity and classic risk factors (A1C, LDL cholesterol, and hypertension) as well as BMI, HDL cholesterol, triglycerides, and novel risk factors, including fibrinogen, oxidized LDL, hsCRP, VCAM-1, and adiponectin, the association between HOMA-IR and incident CVD remained significant and virtually unchanged (hazard ratio 2.2 [95% CI 1.4–3.6], P < 0.001). CONCLUSIONS—HOMA-estimated insulin resistance is associated with subsequent symptomatic CVD in the general population independently of all classic and several nontraditional risk factors. These data suggest that insulin resistance may be an important target to reduce CVD risk.
The Effectiveness of the Pictorial Book to Improve the Understanding of Deaf Students About Nature and Environment in Elementary School

Delay in language development and communication of deaf children is a major problem for themselves and other people. Therefore, management of the education and habilitation needs to be prepared early with hoping that can increase language and communication skills through systematic learning and utilization of appropriate learning material (textbook). The purpose of this study is to describe the feasibility prototype of learning material to improve understanding about nature and the environment for deaf children in the elementary school. The results of the data analysis of this study concluded that the prototype of the pictorial book has contributed significantly to improving deaf children’s understanding of nature and its surroundings, particularly, through the ability to listen and understand meaning of language, ability to read and understand the meaning of language, the ability to write and understand the meaning of language, as well as a functional knowledge of the language.
Fusogenic Pairings of Vesicle-Associated Membrane Proteins (VAMPs) and Plasma Membrane t-SNAREs – VAMP5 as the Exception

Background Intracellular vesicle fusion is mediated by the interactions of SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) proteins on vesicles (v-SNAREs) and on target membranes (t-SNAREs). The vesicle-associated membrane proteins (VAMPs) are v-SNAREs that reside in various post-Golgi vesicular compartments. To fully understand the specific role of each VAMP in vesicle trafficking, it is important to determine if VAMPs have differential membrane fusion activities. Methodology/Principal Findings In this study, we developed a cell fusion assay that quantifies SNARE-mediated membrane fusion events by activated expression of β-galactosidase, and examined fusogenic pairings between the seven VAMPs, i.e., VAMPs 1, 2, 3, 4, 5, 7 and 8, and two plasma membrane t-SNARE complexes, syntaxin1/SNAP-25 and syntaxin4/SNAP-25. VAMPs 1, 2, 3, 4, 7 and 8 drove fusion efficiently, whereas VAMP5 was unable to mediate fusion with the t-SNAREs. By expressing VAMPs 1, 3, 4, 7 and 8 at the same level, we further compared their membrane fusion activities. VAMPs 1 and 3 had comparable and the highest fusion activities, whereas VAMPs 4, 7 and 8 exhibited 30–50% lower fusion activities. Moreover, we determined the dependence of cell fusion activity on VAMP1 expression level. Analysis of the dependence data suggested that there was no cooperativity of VAMP proteins in the cell fusion reaction. Conclusions/Significance These data indicate that VAMPs have differential membrane fusion capacities, and imply that with the exception of VAMP5, VAMPs are essentially redundant in mediating fusion with plasma membrane t-SNAREs.
Effect of His-Tag on Expression, Purification, and Structure of Zinc Finger Protein, ZNF191(243-368)

Zinc finger proteins are associated with hereditary diseases and cancers. To obtain an adequate amount of zinc finger proteins for studying their properties, structure, and functions, many protein expression systems are used. ZNF191(243-368) is a zinc finger protein and can be fused with His-tag to generate fusion proteins such as His6-ZNF191(243-368) and ZNF191(243-368)-His8. The purification of His-tag protein using Ni-NTA resin can overcome the difficulty of ZNF191(243-368) separation caused by inclusion body formation. The influences of His-tag on ZNF191(243-368) properties and structure were investigated using spectrographic techniques and hydrolase experiment. Our findings suggest that insertion of a His-tag at the N-terminal or C-terminal end of ZNF191(243-368) has different effects on the protein. Therefore, an expression system should be considered based on the properties and structure of the protein. Furthermore, the hydrolase activity of ZNF191(243-368)-His8 has provided new insights into the design of biological functional molecules.
“PolNet - Polish WordNet” project: PolNet 2.0 - a short description of the release

In December 2011/January 2012 we have released the main deliverable of the project "PolNet Polish WordNet". It was first presented and distributed (as PolNet 1.0) at the 5th Language and Technology Conference in Poznan (2011) and (informally, with kind permission of the organizers) distributed during the Global Wordnet Conference in Matsue, Japan, in January 2012. We intend to present to the participants of the GWC 2014 the characteristics of the new, extended release of PolNet.
Distributed exact shortest paths in sublinear time

The distributed single-source shortest paths problem is one of the most fundamental and central problems in the message-passing distributed computing. Classical Bellman-Ford algorithm solves it in O(n) time, where n is the number of vertices in the input graph G. Peleg and Rubinovich, FOCS'99, showed a lower bound of Ω(D + √n) for this problem, where D is the hop-diameter of G. Whether or not this problem can be solved in o(n) time when D is relatively small is a major notorious open question. Despite intensive research that yielded near-optimal algorithms for the approximate variant of this problem, no progress was reported for the original problem. In this paper we answer this question in the affirmative. We devise an algorithm that requires O((n logn)5/6) time, for D = O(√n logn), and O(D1/3 #183; (n logn)2/3) time, for larger D. This running time is sublinear in n in almost the entire range of parameters, specifically, for D = o(n/log2 n). We also generalize our result in two directions. One is when edges have bandwidth b ≥ 1, and the other is the s-sources shortest paths problem. For the former problem, our algorithm provides an improved bound, compared to the unit-bandwidth case. In particular, we provide an all-pairs shortest paths algorithm that requires O(n5/3 #183; log2/3 n) time, even for b = 1, for all values of D. For the latter problem (of s sources), our algorithm also provides bounds that improve upon the previous state-of-the-art in the entire range of parameters. From the technical viewpoint, our algorithm computes a hopset G″ of a skeleton graph G′ of G without first computing G′ itself. We then conduct a Bellman-Ford exploration in G′ ∪ G″, while computing the required edges of G′ on the fly. As a result, our algorithm computes exactly those edges of G′ that it really needs, rather than computing approximately the entire G′.
A process metrics based framework for Aspect Oriented Software to predict software bugs and maintenance

The quality evaluation of software products, e.g., defect measuring and identification approaches of individual versions, gains importance with higher use of software applications. Process metrics are considered as the main predictor of defect prediction and software maintenance in numerous empirical studies for the software product. In addition to that, there are few models, consider process metrics as an indicator of software quality too. The prime objective of this paper is to design of process metrics framework for Aspect Oriented Software. This framework can be extended for defect prediction and quality evaluation of aspect oriented software.
QoS level estimation for web service composition in an Environmental Assessment system

In the Intelligent Distributed Environmental Assessment (IDEA) [3] system, sensors are used to measure noise and air pollution. The architecture is service-oriented, allowing application architects to combine services provided by the system platform in order to satisfy application needs. A typical user application may require a set of those services. Because of the sensor nodes' resource limitation, some services may not keep Quality of Service (QoS) levels stable over a long period, which could lead to Service Layer Agreement (SLA) violations. To maintain SLA, QoS levels must be estimated so that services can be properly invoked and combined to satisfy the user's QoS requirements. This paper proposes a novel approach to estimate QoS levels of web services. On the basis of monitored values of QoS parameters, a Naïve Bayes estimation model is developed to select the best-suited services. This paper also presents approaches adopted to monitor QoS levels of web services in the IDEA environment.
Deadlock-Free Adaptive Routing in Meshes with Fault-Tolerance Ability Based on Channel Overlapping

A new deadlock-free routing scheme for meshes is proposed based on a new virtual network partitioning scheme, called channel overlapping. Two virtual networks can share some common virtual channels based on the new virtual network partitioning scheme. The deadlock-free adaptive routing method is then extended to deadlock-free adaptive fault-tolerant routing in 3D meshes still with two virtual channels. A few faulty nodes can make a higher dimensional mesh unsafe for fault-tolerant routing methods based on the block fault model, where the whole system (n-dimensional space) forms a fault block. Planar safety information in meshes is proposed to guide fault-tolerant routing and classifies fault-free nodes inside 2D planes. Many nodes globally marked as unsafe in the whole system become locally enabled inside 2D planes. This fault-tolerant deadlock-free adaptive routing algorithm is also extended to the one in an n-dimensional meshes with two virtual channels. Extensive simulation results are presented and compared to previous methods.
F Fermi National Accelerator Laboratory FERMILAB-Pub-98 / 082-T Implications of Hadron Collider Observables on Parton Distribution Function Uncertainties

Standard parton distribution function sets do not have rigorously quanti ed uncertainties. In recent years it has become apparent that these uncertainties play an important role in the interpretation of hadron collider data. In this paper, using the framework of statistical inference, we illustrate a technique that can be used to e ciently propagate the uncertainties to new observables, assess the compatibility of new data with an initial t, and, in case the compatibility is good, include the new data in the t.
Detection of Motor Changes in Huntington's Disease Using Dynamic Causal Modeling

Deficits in motor functioning are one of the hallmarks of Huntington's disease (HD), a genetically caused neurodegenerative disorder. We applied functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to assess changes that occur with disease progression in the neural circuitry of key areas associated with executive and cognitive aspects of motor control. Seventy-seven healthy controls, 62 pre-symptomatic HD gene carriers (preHD), and 16 patients with manifest HD symptoms (earlyHD) performed a motor finger-tapping fMRI task with systematically varying speed and complexity. DCM was used to assess the causal interactions among seven pre-defined regions of interest, comprising primary motor cortex, supplementary motor area (SMA), dorsal premotor cortex, and superior parietal cortex. To capture heterogeneity among HD gene carriers, DCM parameters were entered into a hierarchical cluster analysis using Ward's method and squared Euclidian distance as a measure of similarity. After applying Bonferroni correction for the number of tests, DCM analysis revealed a group difference that was not present in the conventional fMRI analysis. We found an inhibitory effect of complexity on the connection from parietal to premotor areas in preHD, which became excitatory in earlyHD and correlated with putamen atrophy. While speed of finger movements did not modulate the connection from caudal to pre-SMA in controls and preHD, this connection became strongly negative in earlyHD. This second effect did not survive correction for multiple comparisons. Hierarchical clustering separated the gene mutation carriers into three clusters that also differed significantly between these two connections and thereby confirmed their relevance. DCM proved useful in identifying group differences that would have remained undetected by standard analyses and may aid in the investigation of between-subject heterogeneity.
Map-aided indoor mobile positioning system using particle filter

A framework for positioning and tracking problems in indoor environments using particle filters has been developed and applied to a WLAN location determination technique. The use of particle filtering represents an interesting way to handle the variations of the signal strength measurements. It can also aggregate in a simple way different information like signal strength and the map of a building. This type of information is very useful to obtain correct trajectories without wall-crossings. Constraining this filter on a Voronoi diagram of the building decreases the complexity of the method and improves its stability as the particles cannot be trapped in a room. In this paper, particle filtering and its constraint on a Voronoi diagram are presented, with their performances in indoor environments by combining WLAN signal strength and fingerprinting.
DOES FINGER POINTING TOWARD DRUG NAMES PREVENT CONFUSION BETWEEN SIMILAR NAMES DURING RAPID SEARCH

It is customary for Japanese healthcare workers to use finger pointing toward drugs and prescriptions when they prepare and administer medication to patients, which is believed to be effective to avoid medication errors. The present study investigated whether finger pointing would be effective to avoid confusion errors and anchoring of the gaze on the word pointed to would be a plausible explanation for the potential effects. Sixteen participants observed four drug names with or without pointing with the index finger and determined whether the target drug name was present or not as quickly and accurately as possible (i.e., a choice reaction-time task). The number of similar drug names with the target word was manipulated. The results showed that finger pointing was effective to reduce the error rate when only single similar word existed. Analyses of gaze behavior showed that the fixation duration and number of fixations per drug name increased under finger pointing condition. These results suggest that finger pointing is likely to be effective to fixate a target drug name for a longer time; the effects on error prevention seem to be evident when the error rate itself is relatively high.
Overlapping trend detection and application in prediction

Traditional time series studies pay more attention to the representation effect of original sequence rather than to the trend contained in it. And overlapping trends are ignored because of the usual way for extracting trend from time series is decomposition or segmentation. A sufficient long sequence is also required when doing prediction with trend analysis, or only disappointing results would be gotten. This paper introduces sliding window to improve the inertia test based trend detection algorithm. The data of experiments show that the improved algorithm gets the target of overlapping trend detection and short sequence prediction.
Positive arts interventions: creative clinical tools promoting psychological well-being

ABSTRACT Since ancient times, the arts have been used by humans across the globe as healing methods and vehicles for communication. The arts are increasingly becoming clinical tools to promote health and psychological well-being in individuals. This clinical paper features positive arts interventions which positive arts therapists, positive psychologists and positive psychotherapists can administer in their clinical practice for individuals of all ages to creatively tap into their imagination, reflect upon life goals, gain insight into their character strengths, activate their positive emotions, determine their sources of life meaning and explore spiritual avenues. The following positive arts interventions will be described in great detail: Scribble Drawing, My Strengths Collage, Bridge Drawing with Path (BDP), A Favourite Kind of Day (AFKD), Tree of Life, My Sources of Meaning and Spiritual Pathway. To illustrate these positive arts-based activities, the authors share clinical case examples from Australia, Canada and Ukraine.
Early Practise and Integration : The Key to Teaching Difficult Subjects

Software Engineering is a young area compared to other engineering disciplines. The subject is rapidly moving and more questions than answers seem to appear. Usually, Software Engineering projects involve several people for a prolonged time. Large projects range over several months or years and involve considerable groups of people developing massive systems. Such systems are complex because of their size, and because they need to be regularly modified in order to meet new and changed customer requirements, and because of the need to correct faulty products. We have found it very important to highlight as many questions as possible that appear within Software Engineering already in the education programme. The strategy is to provide as much practical experience from projects as possible, and to let the students be aware of questions and problems before they get possible answers and solutions to those questions. In order to have the right practical training, you have to initiate active tasks on the courses. Some parts come automatically from initiatives from students, but some parts need to be coerced by the teachers. We have noticed that it is important to introduce specific fields in Software Engineering, with a successively increasing emphasis. To achieve high understanding, the order and emphasis need to be carefully considered. This paper describes five fields that we think should be emphasized in this way. These fields are specification, system decomposition, planning, tracking and verification.
A preliminary evaluation of 3D mesh animation coding techniques

This paper provides an overview of the state-of-the-art techniques recently developed within the emerging field of dynamic mesh compression. Static encoders, wavelet-based schemes, PCA-based approaches, differential temporal and spatio-temporal predictive techniques, and clustering-based representations are considered, presented, analyzed, and objectively compared in terms of compression efficiency, algorithmic and computational aspects and offered functionalities (such as progressive transmission, scalable rendering, computational and algorithmic aspects, field of applicability.). The proposed comparative study reveals that: (1) clustering-based approaches offer the best compromise between compression performances and computational complexity; (2) PCA-based representations are highly efficient on long animated sequences (i.e. with number of mesh vertices much smaller than the number of frames) at the price of prohibitive computational complexity of the encoding process; (3) Spatio-temporal Dynapack predictors provides simple yet effective predictive schemes that outperforms simple predictors such as those considered within the interpolator compression node adopted by the MPEG-4 within the AFX standard; (4) Wavelet-based approaches, which provide the best compression performances for static meshes show here again good results, with the additional advantage of a fully progressive representation, but suffer from an applicability limited to large meshes with at least several thousands of vertices per connected component.
The Trouble With Risk Matrices

Risk matrices are used in many organizations as a basis for risk management decisions. They are easy-to-use and have intuitive appeal. They are often defended as the only avenue of approach to risk management because quantitative information is “scarce or nonexistent”. Unfortunately their theoretical basis is superficial and the validity of the qualitative information they employ is highly suspect. Assessments of the likelihood of occurrence and their impacts suffer all the shortcomings associated with subjective assessment. These all combine to produce a less than useful portayal of risk management information. The true value of subject matter experts (SME) is in aiding the devlopemnt of quantitative models representing the inter-relations between variables that ultimately determine the outcome of interest for the decision maker.
A Review of Machine Learning Solutions to Denial-of-Services Attacks in Wireless Sensor Networks

Wireless sensor networks (WSNs) are used in various fields where remote data collection is necessary, such as environment and habitat monitoring, military applications, smart homes, traffic control, and health monitoring etc. Since WSNs play a crucial role in various domains and the sensors are constrained by resources, they are vulnerable to different types of attacks. One of the main attack types that threaten WSNs is Denial-of-Service (DoS) attacks. DoS attacks can be carried out at various layers of the network architecture. In this paper, we review the DoS attacks at each layer of TCP/IP protocol stack. Among them we focus on the network layer attacks because they are more diverse than other layer attacks. We review a number of studies proposing machine learning solutions pertaining to network layer DoS attacks in WSNs. We also provide some comparative conclusions to aid researchers studying in this field.