Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical research Interleukin-1β gene polymorphism is associated with skin photosensitivity

Introduction: Ultraviolet radiation (UVR) exerts both beneficial and harmful effects on humans. Scarce data indicate that cytokine gene polymorphism might determine personal response to UVR. The aim of the study was to analyze the association between polymorphisms in the IL-1β gene and individual photosensitivity in healthy volunteers to ultraviolet B radiation. Material and methods: The study group consisted of 234 healthy Caucasian volunteers (119 F, 115 M) with either II or III skin phototype. In each volunteer phototesting was undertaken and then 24 h later minimal erythema dose (MED) was determined. Three known dimorphic sites within the IL-1β gene were analyzed using RFLP-PCR technique: T→C (promoter region) at position-511 (rs16944), G→A (intron 4) known in literature as 5810 (rs1143633) and C→T (exon 5) known in literature as +3953 or 5887 (rs1143634). Results: The mean value of MED in 234 volunteers was 0.156 J/cm 2 . A statistically significant difference was found between MED in subjects with skin phototype II and skin type III: 0.13 vs. 0.17 J/cm 2 , P<10 –5 . A significant association between phototypes and the 5887 (rs1143634) polymorphism was found. Phototype III occurred significantly more often among carriers of the CC genotype; OR (95% CI) = 2.1 (1.2-3.9). Moreover, carriers of the T allele had lower MED as compared to the CC genotype; 0.15 vs. 0.17 J/cm 2 , P=0.016. Conclusions: The obtained results demonstrate the role of genetic factors in skin phototype and individual photosensitivity. It indicates that individual susceptibility to UVB radiation needs to be considered when studying the effects of UVB in humans.
A pilot phase II study of valproic acid for treatment of low-grade neuroendocrine carcinoma.

INTRODUCTION Notch1 has been shown to be a tumor suppressor in neuroendocrine tumors (NETs). Previous in vitro studies in NET cell lines have also suggested that valproic acid (VPA), a histone deacetylase inhibitor, can induce Notch1 and that Notch1 activation correlates with a decrease in tumor markers for NETs. Thus, this study aimed to evaluate the role of VPA in treating NETs and to determine whether VPA induced the Notch signaling pathway signaling in vivo. PATIENTS AND METHODS Eight patients with low-grade NETs (carcinoid and pancreatic) were treated with 500 mg of oral VPA twice a day with dosing adjusted to maintain a goal VPA level between 50 and 100 μg/mL. All patients were followed for 12 months or until disease progression. RESULTS Notch1 signaling was absent in all tumors prior to treatment and was upregulated with VPA. One patient had an unconfirmed partial response and was noted to have a 40-fold increase in Notch1 mRNA levels. Four patients had stable disease as best response. Tumor markers improved in 5 out of 7 patients. Overall, treatment with VPA was well tolerated. CONCLUSION . VPA activates Notch1 signaling in vivo and may have a role in treating low-grade NETs.
An agile optimization algorithm for vitality management along with fusion of sustainable renewable resources in microgrid

ABSTRACT This article presents a residential microgrid consisting of hybrid wind–solar energy to meet residential local demand. Due to the random and intermittent characteristics of renewable energy, new challenges arise for the reliable operation of microgrids such as loss of power, decrease in performance, reduction in quality of power, etc. Hence, a novel hybrid galactic–swarm optimization (GSO with point estimation method that utilizes renewable energy resources such as wind and solar energy for energy management is proposed in this article. The point estimation method models the uncertainties of energy resources and also provides optimal power flow from wind and solar. Then, GSO algorithm concludes the optimal amount of output power to avoid supplementary generation with proper scheduling and also the amount of exchanging energy with load and main grid during the operating period. Based on the power supply form the hybrid energy resources to load, the load shifting is done during peak hours using ant–lion Optimization Algorithm. The proposed method manages the processes in power distribution system for controlling power stability and power loss. The proposed work is implemented in the working platform of MATLAB and the effectiveness of the proposed is demonstrated.
Optimum Network Coding for Delay Sensitive Applications in WiMAX Unicast

MAC layer random network coding (MRNC) was proposed in (1) as an alternative to HARQ for reliable data transmission in WiMAX unicast. It has been shown that MRNC achieves a higher transmission efficiency than HARQ as it avoids the problem of ACK/NAK packet overhead and the additional re- dundancy resulting from their loss. However, (1) did not address the problem of restricting the number of transmissions to an upper bound which is important for delay sensitive applications. In this paper, we investigate a more structured MAC layer coding scheme that achieves the optimum performance in the delay sensitive traffic context while achieving the same overhead level as MRNC. We first formulate the delay sensitive traffic satisfaction, in such an environment, as a minimax optimization problem over all possible coding schemes. We then show that the MAC layer Systematic Network Coding (MSNC), which transmits the packets once uncoded and employs random network coding for retransmissions, achieves the optimum performance for delay sensitive applications while achieving the same overhead level as MRNC. Index Terms—WiMAX, MAC Layer Random Network Coding, Delay Sensitive Applications.
Graph-aware linear mixed effects models for brain connectivity networks

Neuroimaging data on functional connections in the brain are frequently represented by weighted networks. These networks share the same set of labeled nodes corresponding to a fixed atlas of the brain, while each subject's network has their own edge weights. We propose a method for modeling such brain networks via linear mixed effects models, which takes advantage of the community structure, or functional regions, known to be present in the brain. The model allows for comparing two populations, such as patients and healthy controls, globally, at functional systems level, and at individual edge level, with systems-level inference in particular allowing for a biologically meaningful interpretation. We incorporate correlation between edge weights into the model by allowing for a general variance structure, and show this leads to much more accurate inference. A thorough study comparing schizophrenics to healthy controls illustrates the full potential of our methods, and obtains results consistent with the medical literature on schizophrenia.
In vitro and in vivo studies of sustained-release floating dosage forms containing salbutamol sulfate.

Peroral sustained-release floating capsules containing salbutamol sulfate were formulated using different combinations of hydrocolloids of natural and semi-synthetic origin. The floating properties and release rate characteristics were determined for the capsules in simulated gastric fluid USP XXI and HCl (0.1 mol.l-1) as dissolution media. Also, a marketed sustained-release non-floating capsule containing salbutamol sulfate was studied for its release rate characteristics. The floating capsule formulated showed a Higuchian release profile while the marketed product released only about 80% of the total dose in the stipulated 12 h in the dissolution medium. In vivo X-ray studies of the abdomen were carried out to locate the floating and non-floating (fabricated) dosage forms at various time intervals of uniform duration. The floating capsule definitely indicated a residence time (up to 8-9 h) in the stomach greater than for the non-floating capsule.
Pollution going multimodal: the complex impact of the human-altered sensory environment on animal perception and performance

Anthropogenic sensory pollution is affecting ecosystems worldwide. Human actions generate acoustic noise, emanate artificial light and emit chemical substances. All of these pollutants are known to affect animals. Most studies on anthropogenic pollution address the impact of pollutants in unimodal sensory domains. High levels of anthropogenic noise, for example, have been shown to interfere with acoustic signals and cues. However, animals rely on multiple senses, and pollutants often co-occur. Thus, a full ecological assessment of the impact of anthropogenic activities requires a multimodal approach. We describe how sensory pollutants can co-occur and how covariance among pollutants may differ from natural situations. We review how animals combine information that arrives at their sensory systems through different modalities and outline how sensory conditions can interfere with multimodal perception. Finally, we describe how sensory pollutants can affect the perception, behaviour and endocrinology of animals within and across sensory modalities. We conclude that sensory pollution can affect animals in complex ways due to interactions among sensory stimuli, neural processing and behavioural and endocrinal feedback. We call for more empirical data on covariance among sensory conditions, for instance, data on correlated levels in noise and light pollution. Furthermore, we encourage researchers to test animal responses to a full-factorial set of sensory pollutants in the presence or the absence of ecologically important signals and cues. We realize that such approach is often time and energy consuming, but we think this is the only way to fully understand the multimodal impact of sensory pollution on animal performance and perception.
Improving Memory in Outpatients with Neurological Disorders Using a Group-Based Training Program

Abstract Memory problems are common in patients with a range of neurological conditions, but there have been few attempts to provide and evaluate the usefulness of memory training for groups of neurological outpatients. We used a waitlist-controlled trial design to assess the effectiveness of a newly created, 6-session intervention, which involved training in the use of compensatory strategies as well as education regarding memory function, neurological damage, sleep and lifestyle factors that have an impact on memory. Fifty-six patients with neurological conditions (e.g., stroke, epilepsy) and memory complaints completed the training and assessments. Outcomes were evaluated in terms of reported strategy use as well as objective and subjective measures of anterograde and prospective memory. Training resulted in significant improvements on number of strategies used, scores on the Rey Auditory Verbal Learning Test (total learning and delayed recall) and self-report on the Comprehensive Assessment of Prospective Memory. Improvements were stable at 3-month follow-up. Better individual outcomes were related to lower baseline memory scores, fewer symptoms of depression and greater self-awareness of memory function. Overall the study provides encouraging results to indicate that patients with neurological conditions such as stroke and epilepsy can show improvements in memory after a relatively short group-based intervention. (JINS, 2012, 18, 1–11)
Bioinformatics Analysis of the Effects of Tobacco Smoke on Gene Expression

This study was designed to explore the effects of tobacco smoke on gene expression through bioinformatics analyses. Gene expression profile GSE17913 was downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) in buccal mucosa tissues between 39 active smokers and 40 never smokers were identified. Gene Ontology (GO) and pathway enrichment analyses of DEGs were performed, followed by protein-protein interaction (PPI) network, transcriptional regulatory network as well as miRNA-target regulatory network construction. In total, 88 up-regulated DEGs and 106 down-regulated DEGs were identified. Among these DEGs, cytochrome P450, family 1, subfamily A, polypeptide 1 (CYP1A1) and CYP1B1 were enriched in the Metabolism of xenobiotics by cytochrome P450 pathway. In the PPI network, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta (YWHAZ), and CYP1A1 were hub genes. In the transcriptional regulatory network, transcription factors of MYC associated factor X (MAX) and upstream transcription factor 1 (USF1) regulated many overlapped DEGs. In addition, protein tyrosine phosphatase, receptor type, D (PTPRD) was regulated by multiple miRNAs in the miRNA-DEG regulatory network. CYP1A1, CYP1B1, YWHAZ and PTPRD, and TF of MAX and USF1 may have the potential to be used as biomarkers and therapeutic targets in tobacco smoke-related pathological changes.
An Exploratory Analysis of Multi-Class Uncertainty Approximation in Bayesian Convolutional Neural Networks

Neural networks are an important and powerful family of models, but they have lacked practical ways of estimating predictive uncertainty. Recently, researchers from the Bayesian machine learning community developed a technique called Monte Carlo (MC) dropout which provides a theoretically grounded approach to estimating predictive uncertainty in dropout neural networks [Gal and Ghahramani, 2016]. Some researchers have developed ad hoc approximations of these uncertainty estimates for use in convolutional neural networks [Feinman et al., 2017; Leibig et al., 2017]. We extend their research to a multi-class setting, and find that ad hoc approximations of predictive uncertainty in some cases provides useful information about a model’s confidence in its predictions. Furthermore, we develop a novel approximation of uncertainty that in some respects performs better than those currently being used. Finally, we test these approximations in practice and compare them to other methods suggested in the literature. In our setting we find that the ad hoc approximations perform adequately, but not as well as those already suggested by experts.
Stable and Secure AODV protocol for MANET

This paper presents a new Stable and Secure Routing Strategy for AODV protocol. This has been designed to overcome the flaws in basic AODV protocol. The proposed scheme is based on modifications to existing AODV. Two parameters have been used, one for stability and other for security. Security has been achieved using one-way hash chains and stability by using Hello packets. Thus this strategy ensures stable and secure routing over the MANET. Keywords: MANET, Routing, Secured, Stable
ALFRED: the ALelle FREquency Database. Update

Elaboration of ALFRED (http://alfred.med.yale.edu) is being continued in two directions. One of which is developing tools for efficiently annotating the entries and checking the integrity of the data already in the database while the other is to increase the quantity and accessibility of data. Information contained in ALFRED such as, polymorphic sites, number of populations and frequency tables (one sample typed for one site) has significantly increased.
Bioflavonoid quercetin inhibits mitosis and apoptosis of glomerular cells in vitro and in vivo.

Bioflavonoids have been regarded as therapeutic agents for a wide range of disease including inflammation. In this report, we investigated effects of bioflavonoid quercetin on mitosis and apoptosis of glomerular cells in vitro and in vivo. Serum-stimulated rat mesangial cells were treated with or without quercetin, and total cell number, percentages of mitotic cells, and incorporation of [(3)H]-thymidine were evaluated. All three assays showed that mitogenic activity of mesangial cells was markedly attenuated by quercetin. To examine the effect of quercetin on apoptosis, mesangial cells were pretreated with or without quercetin and stimulated by hydrogen peroxide or tumor necrosis factor-alpha. Hoechst staining and DNA ladder assay showed that both apoptotic responses were dramatically inhibited by quercetin. We further investigated effects of quercetin on in vivo mitosis and apoptosis of glomerular cells. Rats were administered with or without quercetin intraperitoneally, and nephrotoxic serum nephritis was induced. Immunohistochemical analyses showed that treatment with quercetin significantly reduced the number of proliferating cell nuclear antigen (+) cells and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (+) cells in the glomerulus. These data suggested that quercetin has the potential for inhibiting mitosis and apoptosis of glomerular cells both in vitro and in vivo.
Visually lossless adaptive compression for medical images with JPEG 2000

A novel technique for visually lossless medical image compression is presented Visually lossless compression is defined as removing visually insignificant information without evoking any degradation in image quality, through the suppression of visual distortions. An advanced perceptual distortion metric is adapted into the JPEG 2000 coding framework, whilst maintaining bit-stream compliance. Current simulation results have shown superior compression gains over that of the state of the art JPEG-LS and JPEG 2000 Lossless coders, without any visible distortions.
Spectral root homomorphic deconvolution system

In this paper, we develop a new homomorphic deconvolution system that is useful when the signal to be deconvolved is a convolution of two components, one of which is a train of pulses and for the other we have some a priori information on its approximate number of poles and zeros. The system that we develop is essentially the same as the logarithmic homomorphic deconvolution system (LHDS) [1]-[3] except that the logarithmic and exponential operations are replaced with ( )γand ( )1/γoperations. By theoretical and/or empirical results, we illustrate that under appropriate conditions, the new system with the proper choice of γ can potentially yield a better result than the LHDS and that the results obtained by the new system with the value of γ close to 0 are essentially the same as those obtained by the LHDS. As a potential area of practical application, a new speech analysis/ synthesis system is developed based on the new homomorphic deconvolution system discussed in this paper. Some preliminary results on the performance of such a system are also discussed.
Perirhinal Cortex Ablation Impairs Visual Object Identification

Impairments in both recognition memory and concurrent discrimination learning have been shown to follow perirhinal cortex ablation in the monkey. The pattern of these impairments is consistent with the hypothesis that the perirhinal cortex has a role in the visual identification of objects. In this study we compared the performance of a group of three cynomolgus monkeys with bilateral perirhinal cortex ablation with that of a group of three normal controls in two tasks designed to test this hypothesis more directly. In experiment 1 the subjects relearned a set of 40 familiar concurrent discrimination problems; the stimuli in each trial were digitized images of real objects presented in one of three different views. After attaining criterion they were tested on the same problems using similar, but previously unseen, views of the objects. In experiment 2 the subjects were tested on their ability to perform 10 of these familiar discriminations with each problem presented in the unfamiliar context of a digitized image of a unique complex scene. The subjects with ablations were significantly impaired on both tasks. These results demonstrate that the role of the perirhinal cortex is not restricted to memory, and they support the hypothesis that the perirhinal cortex is involved in visual object identification. We suggest that the perirhinal cortex is crucially involved in processing coherent concepts of individual objects. A deficit of this nature could underlie the pattern of impairments that follow perirhinal cortex damage in both visual object recognition memory and visual associative memory.
ACT-R/E

We present ACT-R/E (Adaptive Character of Thought-Rational / Embodied), a cognitive architecture for human-robot interaction. Our reason for using ACT-R/E is two-fold. First, ACT-R/E enables researchers to build good embodied models of people to understand how and why people think the way they do. Then, we leverage that knowledge of people by using it to predict what a person will do in different situations; e.g., that a person may forget something and may need to be reminded or that a person cannot see everything the robot sees. We also discuss methods of how to evaluate a cognitive architecture and show numerous empirically validated examples of ACT-R/E models.
Instruction Set Extension for Long Integer Modulo Arithmetic on RISC-Based Smart Cards

Modulo multiplication of long integers (≥ 1024 bits) is the major operation of many public-key cryptosystems like RSA or Diffie-Hellman. The efficient implementation of modulo arithmetic is a challenging task, in particular on smart cards due to their constrained resources and relatively slow clock frequency. In this paper we present the concept of an application-specific instruction set extension (ISE) for long integer arithmetic. We introduce an optimized multiply-andaccumulate (MAC) unit that makes it possible to compute a×b+c+d with only one instruction, whereby a,b,c,d are single-precision words (unsigned integers). This additional instruction is simple to incorporate into common RISC architectures like the MIPS32. Experimental results show that the inner-product operation of a multiple-precision multiplication can be accelerated by a factor of two without increasing the processor’s clock frequency. We also estimate the execution time of a 1024-bit modulo exponentiation assuming that this special MAC instruction was made available. The proposed ISE is an alternative solution to a crypto co-processor, especially for multi-application smart cards (e.g., Java cards) with an embedded 32-bit RISC core.
HAWAII: a domain-based approach for supporting mobility in wide-area wireless networks

Mobile-IP is the current standard for supporting macro-mobility of mobile hosts. However, in the case of micro-mobility support, there are several competing proposals. In this paper we present the design, implementation, and performance evaluation of HAWAII: a domain-based approach for supporting mobility. HAWAII uses specialized path setup schemes which install host-based forwarding entries in specific routers to support intra-domain micro-mobility. These path setup schemes deliver excellent performance by reducing mobility related disruption to user applications. Also, mobile hosts retain their network address while moving within the domain, simplifying QoS support. Furthermore, reliability is achieved through maintaining soft-state forwarding entries for the mobile hosts and leveraging fault detection mechanisms built in existing intra-domain routing protocols. HAWAII defaults to using Mobile IP for macro-mobility, thus providing a comprehensive solution for mobility support in wide-area wireless networks.