Miracle-dz/UniFAR-FTUs huggingface dataset:
HDLs and alimentary lipemia. Studies in men with previous myocardial infarction at a young age.

The plasma concentration, particle size, and chemical composition of high density lipoproteins (HDLs) are associated with the metabolism of triglyceride-rich lipoproteins (TGRLs). During alimentary lipemia there is active exchange of lipids and apolipoproteins between HDL and apolipoprotein B-containing lipoproteins. Whereas HDL has been assigned a protective role against the development of atherosclerosis, alimentary lipemia has been proposed to represent a potentially atherogenic state. We examined plasma HDL concentration, particle size, and composition and their relations to postprandial TGRLs in 32 postinfarction patients and 10 healthy control subjects after intake of a standardized oral fat load of a mixed-meal type. All patients had undergone coronary angiographies in connection with the myocardial infarction and around 5 years thereafter. The plasma HDL cholesterol concentration decreased significantly in response to the oral fat load, particularly in hypertriglyceridemic patients, with a concomitant increase of HDL triglycerides. A limited and reversible yet consistent increase of HDL particle size (1-2%) was seen 6 hours after intake of the oral fat load on nondenaturing gradient gel electrophoresis (GGE) in both patients and control subjects. Virtually no changes in the plasma concentration of HDL GGE subclasses, lipoproteins containing apolipoprotein A-I but no apolipoprotein A-II (LpA-I), or lipoproteins containing both apolipoproteins A-I and A-II (LpA-I:A-II) were induced in the postprandial state despite massive increases of large very low density lipoprotein (VLDL) and large chylomicron remnant levels (determined as apolipoproteins B-100 and B-48 on sodium dodecyl sulfate-polyacrylamide gel electrophoresis). Strong inverse correlations with fasting plasma HDL cholesterol and the larger HDL GGE subspecies were found for large postprandial VLDL and large chylomicron remnants, whereas the corresponding relations for small VLDL and small chylomicron remnants were weaker. The relations of both large and small VLDL and chylomicron remnants to HDL cholesterol were confined to subjects in the lower fasting plasma HDL cholesterol range (< 1.2 mmol/l). None of the HDL parameters measured, either in the fasting or in the postprandial state (HDL cholesterol, HDL triglycerides, HDL GGE subclasses, LpA-I, and LpA-I:A-II), were related to the development of coronary atherosclerosis, whereas the postprandial plasma levels of small chylomicron remnants, which showed weak negative correlations with HDL, related positively to the progression of coronary atherosclerosis. (ABSTRACT TRUNCATED AT 400 WORDS)
Veteran, Primary Care Provider, and Specialist Satisfaction With Electronic Consultation

Background Access to specialty care is challenging for veterans in rural locations. To address this challenge, in December 2009, the Veterans Affairs (VA) Pittsburgh Healthcare System (VAPHS) implemented an electronic consultation (e-consult) program to provide primary care providers (PCPs) and patients with enhanced specialty care access. Objective The aim of this quality improvement (QI) project evaluation was to: (1) assess satisfaction with the e-consult process, and (2) identify perceived facilitators and barriers to using the e-consult program. Methods We conducted semistructured telephone interviews with veteran patients (N=15), Community Based Outpatient Clinic (CBOC) PCPs (N=15), and VA Pittsburgh specialty physicians (N=4) who used the e-consult program between December 2009 to August 2010. Participants answered questions regarding satisfaction in eight domains and identified factors contributing to their responses. Results Most participants were white (patients=87%; PCPs=80%; specialists=75%) and male (patients=93%; PCPs=67%; specialists=75%). On average, patients had one e-consult (SD 0), PCPs initiated 6 e-consults (SD 6), and VAPHS specialists performed 17 e-consults (SD 11). Patients, PCPs, and specialty physicians were satisfied with e-consults median (range) of 5.0 (4-5) on 1-5 Likert-scale, 4.0 (3-5), and 3.5 (3-5) respectively. The most common reason why patients and specialists reported increased overall satisfaction with e-consults was improved communication, whereas improved timeliness of care was the most common reason for PCPs. Communication was the most reported perceived barrier and facilitator to e-consult use. Conclusions Veterans and VA health care providers were satisfied with the e-consult process. Our findings suggest that while the reasons for satisfaction with e-consult differ somewhat for patients and physicians, e-consult may be a useful tool to improve VA health care system access for rural patients.
Search Space Extension and PGAs: A Comparative Study of Parallelization Schemes to Genetic Algorithms using the TSP

Parallel genetic algorithms (PGAs) have been developed to reduce the execution time of serial genetic algorithms (SGA) and to solve larger problems. They typically find better solutions, as they are likely to be more resistant to premature convergence to local minima compared to serial genetic algorithms. This paper presents a comparative study of four different PGAs using the traveling salesman problem (TSP) as the case application in order to quantify their performance on the basis of small initial populations. Besides the well-known parallelization approaches, a new parallelization scheme is considered which combines iterative data exchanges and new solutions generation, thus extending a search space during the evolution. To make the comparison fair, all PGAs are using the same baseline serial genetic algorithm, started from the same set of initial populations and tested on the same known instances from the TSPLIB-archive.
On the Proximity Factors of Lattice Reduction-Aided Decoding

Lattice reduction-aided decoding (LRAD) features reduced decoding complexity and near-optimum performance in multiinput multioutput communications. In this paper, a quantitative error-rate analysis of LRAD is presented. To this aim, the proximity factors are defined to measure the worst-case losses in decoding distances associated with the decision region relative to infinite lattice decoding (ILD), namely, closest point search in an infinite lattice. Upper bounds on the proximity factors are derived, which are functions of the dimension n of the lattice alone. The study is then extended to the dual-basis reduction. It is found that the bounds for dual basis reduction may be smaller. Reasonably good bounds are derived in many cases. Proximity factors not only imply the same diversity order in fading channels, but also relate the error probabilities of ILD and LRAD.
On Consideration of Content Preference and Sharing Willingness in D2D Assisted Offloading

Device-to-device (D2D) assisted offloading heavily depends on the participation of human users. The content preference and sharing willingness of human users are two crucial factors in the D2D assisted offloading. In this paper, with consideration of these two factors, the optimal content pushing strategy is investigated by formulating an optimization problem to maximize the offloading gain measured by the offloaded traffic. Users are placed into groups according to their content preferences and share content with intergroup and intragroup users at different sharing probabilities. Although the optimization problem is nonconvex, the closed-form optimal solution for a special case is obtained, when the sharing probabilities for intergroup and intragroup users are the same. Furthermore, an alternative group optimization (AGO) algorithm is proposed to solve the general case of the optimization problem. Finally, simulation results are provided to demonstrate the offloading performance achieved by the optimal pushing strategy for the special case and AGO algorithm. An interesting conclusion drawn is that the group with the largest number of interested users is not necessarily given the highest pushing probability. It is more important to give high pushing probability to users with high sharing willingness.
Laser-ultrasonic sensing of surface temperature distribution of a material being heated

A new non-contact method with a laser ultrasonic technique for measuring surface temperature distribution of a material being heated is presented. The principle of the surface temperature measurement is based on temperature dependence of the velocity of the surface acoustic wave (SAW) propagating on a material surface. An effective method consisting of a SAW velocity measurement and an inverse analysis coupled with a one-dimensional finite difference calculation has been developed to determine surface temperature distributions quantitatively. In order to demonstrate the practical feasibility of the method, surface temperature distributions of a steel and aluminium plates are examined. The SAW of each plate is measured during heating using a laser ultrasound interferometer based on photorefractive two-wave mixing. The surface temperature distributions determined by the ultrasonic method almost agree with those measured using an infrared camera.
A Conserved Behavioral State Barrier Impedes Transitions between Anesthetic-Induced Unconsciousness and Wakefulness: Evidence for Neural Inertia

One major unanswered question in neuroscience is how the brain transitions between conscious and unconscious states. General anesthetics offer a controllable means to study these transitions. Induction of anesthesia is commonly attributed to drug-induced global modulation of neuronal function, while emergence from anesthesia has been thought to occur passively, paralleling elimination of the anesthetic from its sites in the central nervous system (CNS). If this were true, then CNS anesthetic concentrations on induction and emergence would be indistinguishable. By generating anesthetic dose-response data in both insects and mammals, we demonstrate that the forward and reverse paths through which anesthetic-induced unconsciousness arises and dissipates are not identical. Instead they exhibit hysteresis that is not fully explained by pharmacokinetics as previously thought. Single gene mutations that affect sleep-wake states are shown to collapse or widen anesthetic hysteresis without obvious confounding effects on volatile anesthetic uptake, distribution, or metabolism. We propose a fundamental and biologically conserved concept of neural inertia, a tendency of the CNS to resist behavioral state transitions between conscious and unconscious states. We demonstrate that such a barrier separates wakeful and anesthetized states for multiple anesthetics in both flies and mice, and argue that it contributes to the hysteresis observed when the brain transitions between conscious and unconscious states.
Classification by Discriminative Regularization

Classification is one of the most fundamental problems in machine learning, which aims to separate the data from different classes as far away as possible. A common way to get a good classification function is to minimize its empirical prediction loss or structural loss. In this paper, we point out that we can also enhance the discriminality of those classifiers by further incorporating the discriminative information contained in the data set as a prior into the classifier construction process. In such a way, we will show that the constructed classifiers will be more powerful, and this will also be validated by the final empirical study on several benchmark data sets.
Has Anyone Seen My Goose? Social Network Services in Developing Regions

In developing regions, Internet connectivity is extremely poor, while mobile phone penetration is much higher. The inhabitants of developing countries still rely on traditional social mechanisms, such as word-of-mouth, to gather most information that they use in everyday life. In this paper, we propose Goose, a Social Network Service (SNS) architecture for developing regions, which provides services including friend searching, resource sharing and information seeking. Goose uses both the limited GSM coverage and Delay Tolerant Networking (DTN) technology on mobile phones, to enable social information exchange even without cellular data coverage.
On Spatial Fairness of the 802.11 DCF Protocol and the Role of Directional Antenna

The IEEE 802.11 DCF protocol suffers from the spatial fairness problem where different nodes achieve different throughput due to their topological distributions. In this paper we extend Bianchi's Markov model of the DCF protocol to multihop WLANs with some simple topologies and study the behavior of the binary exponential backoff (BEB) algorithm under heavy load conditions. Our study is focused on the interaction between the BEB processes of nodes at different locations. We identified several courses of the fairness problem, and found the BEB processes of some nodes have significant advantage over some other nodes. The BEB algorithm provides an undesired positive feedback and worsens the fairness problem. We further study directional antenna as a means to improve network fairness, and find that fairness can be improved significantly with directional antenna without changing the BEB algorithm.
The Development of WLAN-based Indoor Positioning Systems for Aerospace Engineering Education Improvement Programs

Aerospace engineering education improvement program sponsored by Advisor Office, Ministry of Education in Taiwan aims to improve the capability of undergraduate students to design and conduct experiments as well as to obtain hands-on experience in a variety of aerospace engineering such as flight dynamics, control, navigation, global positioning, and wireless communication. In a four-year aerospace engineering education improvement project (2001-2004), we establish a laboratory to develop WLAN-based indoor positioning systems. In general, it is difficult for undergraduate students to have the opportunities of obtaining hands-on experience on the surveillance/navigation of aerospace systems due to the highly complex features of the real systems. In order to simulate this surveillance/navigation scenario, we develop an indoor positioning system to explore ways of simulating next-generation GPS-aided surveillance/navigation systems. Indoor positioning also plays an essential role in the area of automation systems. There are many indoor positioning-related problems such as product tracking in the manufacturing process, navigation of mobile robots, real-time positioning and tracking of patients in hospitals, and sensor network consisting of various types of sensors. With the rapid growth of the Internet, more and more wireless local area network (WLAN) has been installed on campus, in company, and at home. This project develops an IEEE 802.11-based indoor positioning system. The main idea behind the proposed indoor positioning system is to calculate the position using the probabilistic model and measurement of received signal strength. The proposed methodology can position and track the mobile device by integrating the maximum-likelihood estimate of the position and measurement-based Artificial Neural Network-trained RF map. We develop positioning software and implement the positioning algorithm in an IEEE 802.11 WLAN to validate the proposed indoor positioning methods.
WhatIF Application: Moving Electrically without an Electric Vehicle

According to several recent studies, the overhead caused by charging operations to the users' daily activities constitutes one of the main issues discouraging the purchasing of an Electric Vehicle (EV). At present, multiple factors contribute to such overhead, including the limited EV range, the duration of the charging phase, and the non-uniform coverage of the Equipment Vehicle Service Stations (EVSSs) in most areas of the world. Although the situation is going to improve in the long term thanks to the technological advances of the EVs and of the charging infrastructures, ICT-based solutions are needed to minimize the overhead in the short term. To this aim, in this paper we propose the WhatIF application, a software that allows the planning and simulation of EV-related scenarios. Through a mobile client, the users of our system can register their daily journeys, including driving activities and planned stops. A back-end module allows verifying the feasibility of a journey with an EV, scheduling the (eventual) recharging operations during the planned stops. A feasibility energy-optimal algorithm minimizing the overall charged energy is proposed. The performance of the WhatIF application has been tested over a large-scale simulated EV scenario (i.e. the Italian Emilia-Romagna region), considering realistic road topology, EVSSs locations, EV battery models and mobility patterns. Simulation results indicate that 76\% of the EVs are able to complete their journeys when scheduling charging operations during the stops, hence confirming the effectiveness of the WhatIF application in mitigating the overhead of EV mobility.
SIRT1 Suppresses the Senescence-Associated Secretory Phenotype through Epigenetic Gene Regulation

Senescent cells develop a pro-inflammatory response termed the senescence-associated secretory phenotype (SASP). As many SASP components affect surrounding cells and alter their microenvironment, SASP may be a key phenomenon in linking cellular senesence with individual aging and age-related diseases. We herein demonstrated that the expression of Sirtuin1 (SIRT1) was decreased and the expression of SASP components was reciprocally increased during cellular senescence. The mRNAs and proteins of SASP components, such as IL-6 and IL-8, quickly accumulated in SIRT1-depleted cells, and the levels of these factors were also higher than those in control cells, indicating that SIRT1 negatively regulated the expression of SASP factors at the transcriptional level. SIRT1 bound to the promoter regions of IL-8 and IL-6, but dissociated from them during cellular senescence. The acetylation of Histone H3 (K9) and H4 (K16) of the IL-8 and IL-6 promoter regions gradually increased during cellular senescence. In SIRT1-depleted cells, the acetylation levels of these regions were already higher than those in control cells in the pre-senescent stage. Moreover, these acetylation levels in SIRT1-depleted cells were significantly higher than those in control cells during cellular senescence. These results suggest that SIRT1 repressed the expression of SASP factors through the deacetylation of histones in their promoter regions.
Experimental Evaluation of Memory Management in Content-Centric Networking

Content-Centric Networking is a new communication architecture that rethinks the Internet communication model, designed for point-to-point connections between hosts, and centers it around content dissemination and retrieval. Most of the issues faced by the current IP infrastructure in terms of mobility management, security, scalability, which are accrued by today's Internet trends, find a natural solution in CCN shift from IP addresses to named data. In this paper we explore the impact of storage management on the performance of multiple applications sharing the same CCN infrastructure and we quantify the effectiveness of static storage partitioning and dynamic management techniques in providing service differentiation. To this purpose, we implement a set of storage management techniques in the open source CCNx prototype and perform extensive experiments in a real testbed under fairly realistic network conditions. Our experimental results allow to clarify the relation between CCN chunk-level caching and Quality of Experience (QoE) perceived by end users.
Biosensor for detection of selective anticancer drug gemcitabine based on polyaniline-gold nanocomposite

Electrochemical biosensor is an effective tool for pharmaceutical analysis due to its simplicity, specificity, sensitivity, fast, cost- effective and repetitive measurements with miniaturized and portable devices. The paper illustrates the detail methodology for development of an amperometric biosensor based on polyaniline-gold nanocomposite film modified horseradish peroxidase for anticancer drug gemcitabine in bulk and in parenteral formulation. Scanning Electron Microscopy, Cyclic Voltammetry, Fourier Transform Infra Red Spectroscopy and Electrochemical Impedance Spectroscopic studies of the electrodes and after immobilizing of HRP shows the successful formation of a selectivity of the electrode. The proposed polyaniline-gold nano- composite based biosensor allow quantitation over the range 0.10 to 1.10 ngmL −1 with detection limit of 0.031 ngmL −1 , biosensor sensitivity of 2.934 µAng mL -1 has distinct advantages over other existing methods. Precision and accuracy were also checked and were within the limits. The procedure has been applied to the assay of the drug in dosage form with mean percentage recoveries of 99.00±0.08%. The suggested biosensor method can be successfully applied to the detection and determination of anticancer drug gemcitabine in different drug formulations. Copyright © 2015 VBRI press.
Survey and Proposal on Binary Search Algorithms for Longest Prefix Match

The IP address lookup has been a major challenge for Internet routers. This is accompanied with a background of advances in link bandwidth and rapid growth in Internet traffic and the number of networks. This survey paper explores binary search algorithms as a simple and efficient approach to the IP address lookup problem. Binary search algorithms are categorized as algorithms based on the trie structure, algorithms performing binary search on prefix values, and algorithms performing binary search on prefix lengths. In this paper, algorithms in each category are described in terms of their data structures, routing tables, and performance. Performance is evaluated with respect to pre-defined metrics, such as search speed and memory requirement. Table update, scalability toward large routing data, and the migration to IPv6 are also discussed. Simulation results are shown for real routing data with sizes of 15000 to 227000 prefixes acquired from backbone routers. Suggestions are made for the choice of algorithms depending on the table size, routing data statistics, or implementation flexibility.
A Deep Learning Frame-Work for Recognizing Developmental Disorders

Developmental Disorders are chronic disabilities that have a severe impact on the day to day functioning of a large section of the human population. Recognizing developmental disorders from facial images is an important but a relatively unexplored challenge in the field of computer vision. This paper proposes a novel framework to detect developmental disorders from facial images. A spectrum of disorders constituting of Autism Spectrum Disorder, Cerebral Palsy, Fetal Alcohol Syndrome, Down syndrome, Intellectual disability and Progeria have been considered for recognition. The framework relies on Deep Convolutional Neural Networks (DCNN) for feature extraction. A new data-set comprising of images of subjects with these disabilities was built for testing the performance of the frame work. This model has been tested on different age groups, individual disabilities and has also been compared to a similar model that uses human intelligence to identify different developmental disorders. The results indicate that the model performs better than average human intelligence in terms of differentiating amongst different disabilities and is able to recognize subjects with these developmental disorders with an accuracy of 98.80%.
Special values of generalized log-sine integrals

We study generalized log-sine integrals at special values. At π and multiples thereof explicit evaluations are obtained in terms of Nielsen polylogarithms at ±1. For general arguments we present algorithmic evaluations involving Nielsen polylogarithms at related arguments. In particular, we consider log-sine integrals at π/3 which evaluate in terms of polylogarithms at the sixth root of unity. An implementation of our results for the computer algebra systems Mathematica and SAGE is provided.