Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient protocol design for dynamic tag population monitoring in large‐scale radio frequency identification systems

As radio frequency identification (RFID) tags become more ubiquitously available, they will stay in dynamic environments where tags can freely enter or leave RFID readers' interrogation range. With such a dynamic tag population, there arises a problem of population monitoring, whose purpose is to identify the missing tags that have departed from the reading range and the new tags that have newly entered. This problem is a new problem which cannot be well solved by the conventional tag identification protocols. In this paper, we first show that this traditional approach is inefficient, because it collects all the tag IDs in each scan and ignores the ready‐for‐use knowledge of the tag population in a previous scan. To be more efficient, we present three protocols: (i) a baseline protocol that improves the traditional tag identification protocol by optimizing its length of random number used for collision detection; (ii) a novel one‐phase protocol with easy labor to identify exactly the new tags and the missing tags by fully utilizing the knowledge of previous tag population; and (iii) a hybrid protocol that smartly combines the baseline protocol and the one‐phase protocol. Its purpose is to deal with the situation that the knowledge of previous tag population is highly inconsistent with the current tag population. This hybrid protocol, as shown by our analysis, can improve the tag monitoring accuracy by 25%, and improve the time efficiency by 55.3%, as compared with a recent work (called two‐phase protocol), which also identifies the population changes. Copyright © 2012 John Wiley & Sons, Ltd.
Prevalence of Coxsackievirus A6 and Enterovirus 71 in Hand, Foot and Mouth Disease in Nanjing, China in 2013

Background: Although hand, foot and mouth disease (HFMD) has been strongly associated with enterovirus 71 (EV71), coxsackievirus A16 (CVA16) and other enteroviruses, studies regarding coxsackievirus A6 (CVA6) infection in HFMD are limited. The aim of this study was to identify the major etiological agents causing HFMD in Nanjing in 2013 and explore the clinical and genetic characteristics of the prevalent enterovirus (EV) types in HFMD. Methods: A total of 394 throat swabs were collected from hospitalized children diagnosed with HFMD from April to July 2013. EVs were detected by reverse transcription polymerase chain reaction of 5′ UTR sequences. Genotyping and phylogenetic analysis were based on VP4 sequences. Demographic and clinical data were obtained. Results: Of the specimens, 68.5% (270/394) were positive for EVs. The genotypes and detection rates were CVA6, 30.00% (81/270); EV71, 17.41% (47/270); HRV, 11.11% (30/270); CVA10, 3.33% (9/270); CVA2, 1.11% (3/270); CVA16, 0.74% (2/270); EV68, 0.37% (1/270); echovirus 6, 0.37% (1/270); echovirus 9, 0.37% (1/270), respectively. Patients infected with CVA6 displayed symptoms atypical of HFMD, including larger vesicles on their limbs and buttocks. Phylogenetic analysis revealed 2 genetically distinct CVA6 strains that circulated independently within the region. Patients infected with CVA6 were more likely to have abnormal periphery blood white blood cell and C-reactive protein levels, while EV71 was more likely to infect the central nervous system, as indicated by clinical manifestations and white blood cell analysis of cerebrospinal fluid. Conclusions: Multiple EV genotypes contributed to HFMD in Nanjing in 2013, and CVA6 was the dominant genotype. The clinical presentation of CVA6 infection differs from that of EV71 infection in HFMD.
AOI‐cast in distributed virtual environments: an approach based on delay tolerant reverse compass routing

This paper presents a novel Area Of Interest (AOI)‐cast algorithm for distributed virtual environments targeted to Delaunay‐based P2P overlays. The algorithm exploits the mathematical properties of Delaunay triangulations to build a spanning tree supporting the notification of the events generated by a peer to the other ones located in its AOI. The spanning tree is computed by the reversing compass routing, a routing algorithm proposed for geometric networks. Our approach presents a set of novel features. First, it requires only the knowledge of the peer's neighbors, so that the amount of traffic load on the P2P overlay is minimized. Second, we prove that, for circular shaped AOI, the algorithm builds a spanning tree covering all and only the peers of the AOI. Finally, our approach takes into account the possible inconsistencies among the local views of the peers, because the network latency, by introducing a tolerance threshold in the reverse compass routing. We present a set of simulations considering both synthetic data and real data traces taken from a real multiplayer game, which show the effectiveness of our proposal. Copyright © 2012 John Wiley & Sons, Ltd.
Outreach programmes for health improvement of Traveller Communities: a synthesis of evidence

The term ‘Traveller Communities’ refers to a complex population group encompassing Romani Gypsies, Irish Travellers, Welsh Travellers, Scottish Travellers, Roma, New Travellers, Travelling Showpeople, Circus People and Boat Dwellers. A lack of reliable demographic data combined with nomadic lifestyles leads to potential invisibility in health service planning and results in unmet needs.Outreach has been utilised as a key strategy to engage Traveller Communities in health improvement interventions.
SaC‐FRAPP: a scalable and cost‐effective framework for privacy preservation over big data on cloud

Big data and cloud computing are two disruptive trends nowadays, provisioning numerous opportunities to the current information technology industry and research communities while posing significant challenges on them as well. Cloud computing provides powerful and economical infrastructural resources for cloud users to handle ever increasing data sets in big data applications. However, processing or sharing privacy‐sensitive data sets on cloud probably engenders severe privacy concerns because of multi‐tenancy. Data encryption and anonymization are two widely‐adopted ways to combat privacy breach. However, encryption is not suitable for data that are processed and shared frequently, and anonymizing big data and manage numerous anonymized data sets are still challenges for traditional anonymization approaches. As such, we propose a scalable and cost‐effective framework for privacy preservation over big data on cloud in this paper. The key idea of the framework is that it leverages cloud‐based MapReduce to conduct data anonymization and manage anonymous data sets, before releasing data to others. The framework provides a holistic conceptual foundation for privacy preservation over big data. Further, a corresponding proof‐of‐concept prototype system is implemented. Empirical evaluations demonstrate that scalable and cost‐effective framework for privacy preservation can anonymize large‐scale data sets and mange anonymous data sets in a highly flexible, scalable, efficient, and cost‐effective fashion. Copyright © 2013 John Wiley & Sons, Ltd.
Assessment of Prime-boost Vaccination Using an AS03B-adjuvanted Influenza A (H5N1) Vaccine: A Randomized Trial in Children of Three to Less Than Eighteen Years of Age

Background: Heterologous prime-boost vaccination is a pandemic response strategy utilizing subtype-matched vaccine at pandemic onset followed by strain-matched vaccine once available. Persistence of immune response and safety of influenza A (H5N1) vaccine adjuvanted with adjuvant system containing &agr;-tocopherol and squalene in an oil-in-water emulsion (AS03B) were evaluated. Methods: An open phase 3 active-controlled study (www.clinicaltrials.gov NCT01379937) assessed immunogenicity and reactogenicity of a heterologous booster dose of A/turkey/Turkey/1/2005–H5N1–AS03B in children 3 to <18 years of age, given 6 months after 2-dose priming with A/Indonesia/05/2005–H5N1–AS03B (H5N1(2) –H5N1 group) compared with a single dose of A/turkey/Turkey/1/2005–H5N1–AS03B in unprimed subjects (hepatitis A vaccine (HAV)–H5N1 group). Hemagglutinin inhibition responses and microneutralization antibodies were assessed to 6 months after booster vaccination. Results: Hemagglutinin inhibition antibody responses against A/turkey/Turkey/1/2005–H5N1 were superior in the H5N1(2)–H5N1 versus the hepatitis A vaccine–H5N1 group overall and in each age strata (3 to <10 and 10 to <18 years). Anamnestic immune responses were demonstrated against vaccine-homologous/heterologous strains in the H5N1(2)–H5N1 group. Injection site pain and fever increased with consecutive doses for children <6 years (H5N1(2)–H5N1). Immune responses to vaccine-homologous/heterologous strains persisted to 6 months after booster vaccination in the H5N1(2)–H5N1 group. Conclusions: Heterologous H5N1–AS03B-adjuvanted booster vaccination in children/adolescents was immunogenic for vaccine-homologous and heterologous strains following 2-dose priming, with immune persistence for at least 6 months. Prime-boost strategies using H5N1–AS03 could be effectively employed in this age group.
Dietary Protein's and Dietary Acid Load's Influence on Bone Health

A variety of genetic, mechano-response-related, endocrine-metabolic, and nutritional determinants impact bone health. Among the nutritional influences, protein intake and dietary acid load are two of the factors most controversially discussed. Although in the past high protein intake was often assumed to exert a primarily detrimental impact on bone mass and skeletal health, the majority of recent studies indicates the opposite and suggests a bone-anabolic influence. Studies examining the influence of alkalizing diets or alkalizing supplement provision on skeletal outcomes are less consistent, which raises doubts about the role of acid–base status in bone health. The present review critically evaluates relevant key issues such as acid–base terminology, influencing factors of intestinal calcium absorption, calcium balance, the endocrine-metabolic milieu related to metabolic acidosis, and some methodological aspects of dietary exposure and bone outcome examinations. It becomes apparent that for an adequate identification and characterization of either dietary acid load's or protein's impact on bone, the combined assessment of both nutritional influences is necessary.
Altered white matter integrity in temporal lobe epilepsy: Association with cognitive and clinical profiles

Purpose: Diffusion tensor imaging (DTI) studies have reported substantial white matter abnormalities in patients with temporal lobe epilepsy (TLE). However, limited data exist regarding the extent of white matter tract abnormalities, cognitive effects of these abnormalities, and relationship to clinical factors. The current study examined these issues in subjects with chronic TLE.
The Bioactivity and Toxicological Actions of Carvacrol

Carvacrol is a monoterpenic phenol produced by an abundant number of aromatic plants, including thyme and oregano. Presently, carvacrol is used in low concentrations as a food flavoring ingredient and preservative, as well as a fragrance ingredient in cosmetic formulations. In recent years, considerable research has been undertaken in an effort to establish the biological actions of carvacrol for its potential use in clinical applications. Results from in vitro and in vivo studies show that carvacrol possess a variety of biological and pharmacological properties including antioxidant, antibacterial, antifungal, anticancer, anti-inflammatory, hepatoprotective, spasmolytic, and vasorelaxant. The focus of this review is to evaluate the existing knowledge regarding the biological, pharmacological, and toxicological effects of carvacrol.
Mung Bean: Technological and Nutritional Potential

Mung bean (Vigna radiata (L.) R. Wilczek) has been intensively researched; scattered data are available on various properties. Data on physical, chemical, food processing, and nutritional properties were collected for whole mung bean grains and reviewed to assess the crop's potential as food and to set research priorities. Results show that mung bean is a rich source of protein (14.6–33.0 g/100 g) and iron (5.9–7.6 mg/100 g). Grain color is correlated with compounds like polyphenols and carotenoids, while grain hardness is associated with fiber content. Physical properties like grain dimensions, sphericity, porosity, bulk, and true density are related to moisture content. Anti-nutrients are phytic acid, tannins, hemagglutinins, and polyphenols. Reported nutrient contents vary greatly, the causes of which are not well understood. Grain size and color have been associated with different regions and were used by plant breeders for selection purposes. Analytical methods require more accuracy and precision to distinguish biological variation from analytical variation. Research on nutrient digestibility, food processing properties, and bioavailability is needed. Furthermore, the effects of storage and processing on nutrients and food processing properties are required to enable optimization of processing steps, for better mung bean food quality and process efficiency.
Discovery of biological networks using an optimized partial correlation coefficient with information theory algorithm on Stampede's Xeon and Xeon Phi processors

The partial correlation coefficient with information theory (PCIT) method is an important technique for detecting interactions between networks. The PCIT algorithm has been used in the biological context to infer complex regulatory mechanisms and interactions in genetic networks, in genome wide association studies, and in other similar problems. In this work, the PCIT algorithm is re‐implemented with exemplary parallel, vector, input/output (I/O), memory, and instruction optimizations for today's multi‐core and many‐core architectures. The evolution and performance of the new code targets the processor architectures of the Stampede supercomputer but will also benefit other architectures. The Stampede system consists of an Intel Xeon E5 processor base system with an innovative component consist of Intel Xeon Phi Coprocessors. Optimized results and an analysis are presented for both the Xeon and the Xeon Phi. Copyright © 2014 John Wiley & Sons, Ltd.
Narrowing of the Diagnostic Gap of Acute Gastroenteritis in Children 0–6 Years of Age Using a Combination of Classical and Molecular Techniques, Delivers Challenges in Syndromic Approach Diagnostics

Background: Twenty-five percent to 50% of acute gastroenteritis (AGE) cases remain etiologically undiagnosed. Our main aim was to determine the most appropriate list of enteric pathogens to be included in the daily diagnostics scheme of AGE, ensuring the lowest possible diagnostic gap. Methods: Two hundred ninety seven children ⩽6 years of age, admitted to hospital in Slovenia, October 2011 to October 2012, with AGE, and 88 ⩽6 years old healthy children were included in the study. A broad spectrum of enteric pathogens was targeted with molecular methods, including 8 viruses, 6 bacteria and 2 parasites. Results: At least one enteric pathogen was detected in 91.2% of cases with AGE and 27.3% of controls. Viruses were the most prevalent (82.5% and 15.9%), followed by bacteria (27.3% and 10.2%) and parasites (3.0% and 1.1%) in cases and controls, respectively. A high proportion (41.8%) of mixed infections was observed in the cases. For cases with undetermined etiology (8.8%), stool samples were analyzed with next generation sequencing, and a potential viral pathogen was detected in 17 additional samples (5.8%). Conclusions: Our study suggests that tests for rotaviruses, noroviruses genogroup II, adenoviruses 40/41, astroviruses, Campylobacter spp. and Salmonella sp. should be included in the initial diagnostic algorithm, which revealed the etiology in 83.5% of children tested. The use of molecular methods in diagnostics of gastroenteritis is preferable because of their high sensitivity, specificity, fast performance and the possibility of establishing the concentration of the target. The latter may be valuable for assessing the clinical significance of the detected enteric, particularly viral pathogens.
Online hot event discovery based on Association Link Network

Online hot event discovery has become a flourishing frontier where online document streams are monitored to discover newly occurring events or assigned to previously detected events. However, hot events have the nature to evolve, and their inherent topically related words are also likely to evolve. It makes event discovery a challenging task for traditional‐mining approaches. Combining word association and semantic community, Association Link Network (ALN) organizes the loosely distributed associated resources. This paper presents an ALN‐based novel online hot event discovery approach. Technically, this approach is enacted around three stages. In the first stage, we extract significant features to represent the content of each document from the online document stream. During the second stage, we classify the online document stream into topically related detected events considering event evolution in the form of ALN. At the third stage, we create an ALN‐based event detection algorithm, which is used to timely discover newly occurring hot events. The online datasets used in our empirical studies are acquired from Baidu News, which spans a range of 1315 hot events and 236,300 documents. Experimental results demonstrate the hot events discovery ability with respect to high accuracy, good scalability, and short runtime. Copyright © 2014 John Wiley & Sons, Ltd.
Interest prediction in social networks based on Markov chain modeling on clustered users

Effective user interest prediction is significant for service providers in a set of application scenarios such as user behavior analysis and resource recommendation. However, existing approaches are either incomplete or proprietary. In this paper, user interest prediction based on the Markov chain modeling on clustered users is proposed with the following procedure: collect dataset from 4613 users and more than 16 million messages from Sina Weibo; obtain each user's interest eigenvalue sequence and establish single‐Markov chain model; and implement user clustering algorithm for the multi‐Markov chain construction in order to divide users into a set of predefined interest categories. The proposed solution is capable of predicting both long‐term and short‐term user interests based on a suitable selection of the initial state distribution, λ. The proposed solution also proves that short‐term interests are consistent with long‐term interests if the influences of social or user‐related events that cause interruptions (e.g., earthquake and birthday) are not considered. Furthermore, experiments show that the proposed solution is feasible and efficient and can achieve a higher accuracy of prediction than that of the other approaches such as Support Vector Machine (SVM) and K‐means. Copyright © 2015 John Wiley & Sons, Ltd.
Most Common Foodborne Pathogens and Mycotoxins on Fresh Produce: A Review of Recent Outbreaks

ABSTRACT Every year millions of people are affected and thousands of them die due to infections and intoxication as a result of foodborne outbreaks, which also cause billions of dollars' worth of damage, public health problems, and agricultural product loss. A considerable portion of these outbreaks is related to fresh produce and caused by foodborne pathogens on fresh produce and mycotoxins. Escherichia coli O104:H4 outbreak, occurred in Germany in 2011, has attracted a great attention on foodborne outbreaks caused by contaminated fresh produce, and especially the vulnerability and gaps in the early warning and notification networks in the surveillance systems in all around the world. In the frame of this paper, we reviewed the most common foodborne pathogens on fresh produce, traceback investigations of the outbreaks caused by these pathogens, and lastly international early warning and notification systems, including PulseNet International and Rapid Alert System for Food and Feed, aiming to detect foodborne outbreaks.
A novel application classification attack against Tor

Tor is a famous anonymous communication system for preserving users' online privacy. It supports TCP applications and packs upper‐layer application data into encrypted equal‐sized cells with onion routing to hide private information of users. However, we note that the current Tor design cannot conceal certain application behaviors. For example, P2P applications usually upload and download files simultaneously, and this behavioral feature is also kept in Tor traffic. Motivated by this observation, we investigate a new attack against Tor, application classification attack, which can recognize application types from Tor traffic. An attacker first carefully selects some flow features such as burst volumes and directions to represent the application behaviors and takes advantage of some efficient machine‐learning algorithm (e.g., Profile Hidden Markov Model) to model different types of applications. Then he or she can use these established models to classify target's Tor traffic and infer its application type. We have implemented the application classification attack on Tor using parallel computing, and our experiments validate the feasibility and effectiveness of the attack. We argue that the disclosure of application type information is a serious threat to Tor users' anonymity because it can be used to reduce the anonymity set and facilitate other attacks. We also present guidelines to defend against application classification attack. Copyright © 2015 John Wiley & Sons, Ltd.
Impact of Diet Composition on Blood Glucose Regulation

Nutritional management of blood glucose levels is a strategic target in the prevention and management of type 2 diabetes mellitus (T2DM). To implement such an approach, it is essential to understand the effect of food on glycemic regulation and on the underlying metabolic derangements. This comprehensive review summarizes the results from human dietary interventions exploring the impact of dietary components on blood glucose levels. Included are the major macronutrients; carbohydrate, protein and fat, micronutrient vitamins and minerals, nonnutrient phytochemicals and additional foods including low-calorie sweeteners, vinegar, and alcohol. Based on the evidence presented in this review, it is clear that dietary components have significant and clinically relevant effects on blood glucose modulation. An integrated approach that includes reducing excess body weight, increased physical activity along with a dietary regime to regulate blood glucose levels will not only be advantages in T2DM management, but will benefit the health of the population and limit the increasing worldwide incidence of T2DM.
State of the Art Reviews: Smoking Cessation

Smoking cessation continues to be an area of great concern for public health. Smoking status and willingness to quit should be assessed at every patient visit. A variety of nonprescription and prescription pharmacotherapy options exist for those willing to quit. Medications currently approved by the Food and Drug Administration for smoking cessation include nicotine replacement therapy (gum, lozenge, patch, inhaler, and nasal spray), bupropion sustained release, and the newly approved varenicline. Nortriptyline and clonidine are not indicated for smoking cessation but have been used as second-line agents. This review focuses on each treatment option, including precautions, proper dosing and duration, adverse effects, and medication delivery issues. Attention is also given to individual patient considerations such as combination therapy, pregnancy, postcessation weight gain, and effects of cessation on the current medication regimen.