Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Variation in Osteopontin Gene Is Associated with Susceptibility to Sarcoidosis in Slovenian Population

Sarcoidosis is a systemic inflammatory disease characterised by appearance of granulomas. Precise etiology has not been elucidated. Osteopontin (Opn) is a Th1 cytokine whose levels have been found increased in granulomas and serum samples from patients with sarcoidosis. We investigated whether genetic variation in Osteopontin gene (OPN) gene contributes to susceptibility to sarcoidosis. Haplotype-block structure in the OPN gene region was investigated using data from HapMap project. Three representative SNPs have been selected from each block of SNPs in linkage disequilibrium (rs11730582-C/T, rs11728697-C/T and rs4754-C/T). Genotyping was performed using TaqMan SNP Genotyping Assays on a sample of 165 patients and 284 controls. Statistical analyses of association were performed using Chi-Square test and algorithms implemented in the haplo.stats and PHASE packages. Genotyping analysis revealed a significant difference in genotype frequencies at rs4754 polymorphism in groups of patients and controls under recessive genetic model (p=0.036, OR=1.99, 95%CI=1.04-3.82), CC homozygotes being significantly over-represented in the patients group. However these results failed to reach significance after correction for multiple testing (p=0.25). The frequencies of predicted haplotypes differed between patient and control groups, frequency of TTT haplotype was found to be significantly decreased in the group of patients with sarcoidosis (p=0.014, OR=0.40, 95%CI=0.20-0.79). Our results suggest that variation in the OPN gene might be significantly associated with sarcoidosis and that the TTT haplotype in OPN may act as a protective factor in sarcoidosis.
A taste of Capsicum

Capsicum is a lightweight operating system (OS) capability and sandbox framework planned for inclusion in FreeBSD 9. Capsicum extends, rather than replaces, UNIX APIs, providing new kernel primitives (sandboxed capability mode and capabilities) and a userspace sandbox API. These tools support decomposition of monolithic UNIX applications into compartmentalized logical applications, an increasingly common goal that is supported poorly by existing OS access control primitives. We demonstrate our approach by adapting core FreeBSD utilities and Google's Chromium Web browser to use Capsicum primitives, and compare the complexity and robustness of Capsicum with other sandboxing techniques.
Non-volatile Content Addressable Memory for Computing Acceleration

Associative memory, as a form of computing-with-memory, reduces energy of the processing elements by eliminating redundant computations [2], [8], [11]–[15], [17]–[20]. An associative memory can quickly recall responses of a function for a subset of input patterns to save energy by avoiding the actual function execution on the processing element. An associative memory is typically composed of a ternary content-addressable memory (TCAM) to store input patterns and an output memory to return the pre-stored output. The operation of a TCAM goes beyond retrieving logic “0” and “1” and it has capability to store and search wildcard [5]. This feature opens the application of the TCAMs for approximate computing domain, and a wide range of applications in query processing [2], [14], text processing [26], search engine [9], [28], image processing [1], [7], [16], pattern recognition and classification [10], [21], [23]. Associative memories can be implemented on both software and hardware. Software solutions are based on hashing where a frequent data can be stored and retrieved from hash function by keys [3], [22]. In hardware, the associative memory is being implemented by TCAMs. Conventional TCAM with two SRAM cells suffers from high power dissipation and low density [? ], [6]. The cost perbit of CMOS-based TCAM is 8× more than SRAM [4]. These limit the application of TCAMs to network applications [24]. Low leakage power of non-volatile memory make them appropriate as a replacement for CMOS-based TCAMs [29].
A Radio Resource Management Framework for IEEE 802.16-Based OFDM/TDD Wireless Mesh Networks

We present a radio resource management framework for the IEEE 802.16-based OFDM/TDD wireless mesh networks. The major components of the framework, namely, subchannel allocation, admission control, and route selection schemes are developed so that the quality of service (QoS) can be guaranteed on a per-connection basis. We formulate a tandem queueing model to obtain the in-connection performance measures such as average delay and packet data unit (PDU) dropping probability for relay connections in an end-to-end basis. The same formulation can be used to obtain the performance measures such as the average transmission delay for a PDU and the PDU dropping probability at a mesh-node (i.e., IEEE 802.16 base station) for local connections. Two subchannel allocation algorithms, namely, the optimal and the iterative subchannel algorithms, are proposed. The admission control and route selection schemes for relay connections are based on the performance measures obtained from the tandem queueing model. In particular, a new connection is accepted if the packet delay requirements corresponding to that connection can be satisfied and the route that provides the smallest delay is selected for routing packets through the network to the Internet gateway. The performances of the proposed radio resource management schemes are evaluated by simulations.
BBRC Crystal structure of rubredoxin from Desulfovibrio gigas to ultra-high 0 . 68 Å resolution q

Rubredoxin (D.g. Rd) is a small non-heme iron–sulfur protein shown to function as a redox coupling protein from the sulfate reducing bacteria Desulfovibrio gigas. The protein is generally purified from anaerobic bacteria in which it is thought to be involved in electron transfer or exchange processes. Rd transfers an electron to oxygen to form water as part of a unique electron transfer chain, composed by NADH:rubredoxin oxidoreductase (NRO), rubredoxin and rubredoxin:oxygen oxidoreductase (ROO) in D.g. The crystal structure of D.g. Rd has been determined by means of both a Fe single-wavelength anomalous dispersion (SAD) signal and the direct method, and refined to an ultra-high 0.68 Å resolution, using X-ray from a synchrotron. Rd contains one iron atom bound in a tetrahedral coordination by the sulfur atoms of four cysteinyl residues. Hydrophobic and p–p interactions maintain the internal Rd folding. Multiple conformations of the iron–sulfur cluster and amino acid residues are observed and indicate its unique mechanism of electron transfer. Several hydrogen bonds, including NAH SG of the iron–sulfur, are revealed clearly in maps of electron density. Abundant waters bound to CAO peptides of residues Val8, Cys9, Gly10, Ala38, and Gly43, which may be involved in electron transfer. This ultrahigh-resolution structure allows us to study in great detail the relationship between structure and function of rubredoxin, such as salt bridges, hydrogen bonds, water structures, cysteine ligands, iron–sulfur cluster, and distributions of electron density among activity sites. For the first time, this information will provide a clear role for this protein in a strict anaerobic bacterium. 2006 Elsevier Inc. All rights reserved.
Mitigation of Greenhouse Gas Emissions by Fly Ash Stabilization and Sisal Fibre Reinforcement of Clay Subgrade for Road Construction

Construction of bituminous pavements forms a major source of greenhouse gas emissions. In order to mitigate this effect, the research study proposes use of fly ash and sisal fibre in stabilization of clay soil for the pavement subgrade. The test specimens were impregnated with fly ash contents of 10%, 20%, 30% and 40% and fibre contents of 0.25% 0.50%, 0.75% and 1.0% of the dry soil mass and different geotechnical characteristics of the stabilized soils namely maximum dry density (MDD), optimum moisture content (OMC), California bearing ratio (CBR) and unconfined compressive strength (UCS) values were determined. Additionally, scanning electron microscopy tests were also carried out on the stabilized soil samples to know their surface morphology. Bituminous pavements sections with stabilized and non-stabilized subgrades were designed for 50 million standard axles traffic intensity in accordance with the standard codal provisions. The greenhouse gas emissions associated with construction of bituminous pavements were evaluated using standard inventories of carbon coefficients for road materials. The results indicated that key strength parameters of soil subgrade i.e. CBR and UCS were significantly enhanced with the use of fly ash and sisal fibre. The soil stabilization treatment significantly reduced the layer thickness eventually leading to reduction in the associated greenhouse gas emissions for the designed pavements. The results obtained are indicative of the potential utilization of fly ash and sisal fibre in building sustainable and durable bituminous pavements with reduced greenhouse gas emissions.
Interleaver-Division Multiple Access on the OR Channel

The OR channel provides an unusual opportunity where single-user decoding permits operation at about 70% of the full multiple-access channel sum capacity. The interleaverdivision multiple access technique applied in this paper can approach that performance with turbo and LDPC solutions. The current paper focuses on very low latency codes with simple Viterbi decoding, intended for very high speed (gigabits per second) applications. Namely, it focuses on nonlinear trellis codes that provide about 30% of the full multiple-access sum capacity at high speeds and with very low latency. These trellis codes are designed specifically for the Z-channel that arises in a multipleuser OR channel when the other users are treated as noise. In order to optimize the sum-capacity of the OR-MAC, the trellis code transmits codewords with a ones density much less than 50%. Also, a union bound technique that predicts the performance of these codes is presented. Results from simulations and an award-winning FPGA implementation are shown.
An Anti-VEGF-B Antibody Fragment Induces Regression of Pre-Existing Blood Vessels in the Rat Cornea.

Purpose We tested the ability of an antibody fragment with specificity for vascular endothelial growth factor-B (VEGF-B) to regress nascent and established corneal blood vessels in the rat. Methods A single chain variable antibody fragment (scFv) with specificity for VEGF-B was engineered from the 2H10 hybridoma. Binding to rat, mouse, and human VEGF-B was confirmed by surface plasmon resonance. Activity of the anti-VEGF-B scFv on developing and established corneal blood vessels was assessed following unilateral superficial cautery in male and female outbred Sprague Dawley rats. Groups (untreated, control scFv-treated, or anti-VEGF-B scFv-treated) comprised 6 to 22 rats. Treatment consisted of 5 μL scFv, 1 mg/mL, applied topically five times per day for 14 days, or two subconjunctival injections, 50 μg scFv each, applied 7 days apart, or combined topical and subconjunctival treatment. Corneal vessel area was quantified on hematoxylin-stained corneal flat-mounts, and groups were compared using the Mann-Whitney U test, with post hoc Bonferroni correction. Immunohistochemistry for cleaved caspase-3 was performed. Results Topical anti-VEGF-B scFv therapy alone did not regress corneal blood vessels significantly (P > 0.05). Subconjunctival injection and combined treatment regressed 14-day established corneal blood vessels (25% reduction in vessel area [P = 0.04] and 37% reduction in vessel area [P < 0.001], respectively, compared to results in untreated controls). Cleaved caspase-3 was identified in vascular endothelial cells of anti-VEGF-B scFv-treated corneas. In scFv-treated rats, corneal endothelial cell function was maintained to 12 weeks after treatment and a normal blink reflex was present. Conclusions The anti-VEGF-B scFv significantly regressed established but not developing corneal blood vessels in rats.
EfficientNet-based vehicle damage insurance verification

The purpose of this study is to develop a new approach to expedite the vehicle insurance claims process by utilizing the power of EfficientNet, a state-of-the-art deep learning model. Vehicle damage assessments have traditionally been hampered by manual inspections, which result in delays and increased administrative costs. The proposed system, which utilizes EfficientNet as part of its deep learning model, shows unparalleled accuracy when analyzing and verifying vehicle damage in real time using advanced deep learning models trained on extensive datasets. Using a combination of computer vision and image recognition technology, our solution significantly reduces claims assessment time and resources. According to our experimental results, EfficientNet consistently outperformed other algorithms in accurately analyzing and verifying vehicle damage. Its superior accuracy and efficiency make it the ideal choice for expediting the vehicle insurance claims process and reducing administrative costs.
Safety Assessment of Bacillus subtilis G8 Isolated from Natto for Food Application

Various bacteria are widely used as food-fermenting agents, including Lactobacillus, Bifidobacterium, and Bacillus. Despite they are generally recognized as safe to be consumed by humans, those bacteria could potentially cause antibiotic resistance as they could acquire and transfer antibiotic resistance genes from or to other microbes within the human gastrointestinal tract. Profiling antibiotic resistance pattern in those bacteria is therefore important to control the spread of antibiotic resistance. In this study, antibiotic resistance profile of Bacillus subtilis G8 was assessed. B. subtilis G8 had been isolated from commercialised Japanese natto in Indonesia and had been previously reported for its fibrinolytic characteristics. The antibiotic resistance phenotype and genotype of B. subtilis G8 were assessed through the Kirby-Bauer disk diffusion method and whole-genome analysis, respectively. B. subtilis G8 exhibited resistance towards Oxacillin, Lincomycin and Tiamulin-Lefamulin. The bioinformatics analysis indicated several responsible genes mediating those resistance, i.e., ybxI (for Oxacillin), lmrB (for Lincomycin) and vmlR (for Lincomycin and Tiamulin-Lefamulin). All identified genes were found in the chromosomal DNA. Further analysis found no mobile genetic elements within the genome, therefore reducing a risk of resistance gene transfer via plasmid and subsequently supporting safety profile of B. subtilis G8 in food fermentation usage.
Protein-ligand interaction prediction: an improved chemogenomics approach

Motivation: Predicting interactions between small molecules and proteins is a crucial step to decipher many biological processes, and plays a critical role in drug discovery. When no detailed 3D structure of the protein target is available, ligand-based virtual screening allows the construction of predictive models by learning to discriminate known ligands from non-ligands. However, the accuracy of ligand-based models quickly degrades when the number of known ligands decreases, and in particular the approach is not applicable for orphan receptors with no known ligand. Results: We propose a systematic method to predict ligand–protein interactions, even for targets with no known 3D structure and few or no known ligands. Following the recent chemogenomics trend, we adopt a cross-target view and attempt to screen the chemical space against whole families of proteins simultaneously. The lack of known ligand for a given target can then be compensated by the availability of known ligands for similar targets. We test this strategy on three important classes of drug targets, namely enzymes, G-protein-coupled receptors (GPCR) and ion channels, and report dramatic improvements in prediction accuracy over classical ligand-based virtual screening, in particular for targets with few or no known ligands. Availability: All data and algorithms are available as Supplementary Material. Contact: laurent.jacob@ensmp.fr Supplementary information: Supplementary data are available at Bioinformatics online.
Blockchain-Based Fintech Architecture for Enhanced Interoperability in Health Insurance

Health Insurances play vital role in one’s life to bear costly medical services and delays in payments from insurer to service providers causes chaotic to insureds seeking immediate treatment for their diseases. Almost every stakeholder in this ecosystem is equipped with his own significantly efficient independent information systems usually known as Management Information Systems (MIS) which most of the times remain sufficient for their internal business needs but apart from so much technical advancements, the inter-communication of these stakeholders for up-to-date status of insurer, insured, and health service provider is still missing in various scenarios which causes distress to all stakeholders and patients. In this paper, we have proposed a Blockchain based data sharing solution among all the stakeholders to fast up the processes and smoothness of network along with a concept of Insurance e-Wallet for insured entities where they can have summary of all their purchased Insurance plans, their processed or pending claims, remaining limits, and upcoming changes in their policies from insurance vendors. Apart from interoperability, the second most important aspect this architecture addresses the avoiding of redundant paper work that every stakeholder manages to maintain their day-to-day activity records, these are almost the same set of documents regarding an insurance claim that a service provider, insurer, and a patient maintains. To avoid this redundancy, we made use of IPFS as the decentralized repository for such documents which makes Blockchain solution cost effective and light weight as just the reference or the hash ID is put in Blockchain instead of whole document in binary format. A prototype is developed based on suggested architecture and two experiments are performed on implemented prototype, first one for measuring expected growth rate of Blockchain based on routine appendment of data and second for measuring document access time required to access files from IPFS server. Lastly the paper concludes with some prominent implementation challenges that stakeholders may face during Blockchain ’s implementation to achieve transformation in this industry.
Branch prediction based on universal data compression algorithms

Data compression and prediction are closely related. Thus prediction methods based on data compression algorithms have been suggested for the branch prediction problem. In this work we consider two universal compression algorithms: prediction by partial matching (PPM), and a recently developed method, context tree weighting (CTW). We describe the prediction algorithms induced by these methods. We also suggest adaptive algorithms variations of the basic methods that attempt to fit limited memory constraints and to match the non-stationary nature of the branch sequence. Furthermore, we show how to incorporate address information and to combine other relevant data. Finally, we present simulation results for selected programs from the SPECint95, SYSmark/32, SYSmark/NT, and transactional processing benchmarks. Our results are most promising in programs with difficult to predict branch behavior.
Simple Yet Effective Methods for Cross-Lingual Link Discovery (CLLD) - KMI @ NTCIR-10 CrossLink-2

Cross-Lingual Link Discovery (CLLD) aims to automatically find links between documents written in different languages. In this paper, we first present a relatively simple yet effective methods for CLLD in Wiki collections, explaining the fndings that motivated their design. Our methods (team KMI) achieved in the NTCIR-10 CrossLink-2 evaluation the best overall results in the English to Chinese, Japanese and Korean (E2CJK) task and were the top performers in the Chinese, Japanese, Korean to English task (CJK2E)1 [Tang et al.,2013]. Though tested on these language combinations, the methods are language agnostic and can be easily applied to any other language combination with sufficient corpora and available pre-processing tools. In the second part of the paper, we provide an in depth analysis of the nature of the task, the evaluation metrics and the impact of the system components on the overall CLLD performance. We believe a good understanding of these aspects is the key to improving CLLD systems in the future.
Software Evolution Of A Hexapod Robot Walking Gait

This paper describes the process of evolving a Hexapod Robot walking gait within a simulated software environment. Initially a 3D mathematical model of the robot was created using Matlab, simulating full motion of each the robot's six legs. Each leg has three degrees of freedom (DOF), allowing the robot to move in both lateral and rotational directions. The simulation allows the robot's movements to be determined, based on a repeated sequence of static leg positions, and was used with a genetic algorithm (GA) to evolve walking gaits for the robot. The walking gait is described by a chromosome which is an 18times9 look up table (LUT) that lists the angular position of all eighteen servo motors over a sequence of nine discrete static positions, which will describe the walking gait. Each position in the LUT has twenty discrete states ranging from -45deg to +45deg, allowing a flexible range of achievable motions, while maintaining sensible evaluation limits. Successful evolution of these gaits was performed within 700 generations.
Disturbance and delay robustness of gradient feedback systems based on static noncooperative games with application to PEV charging

This paper considers interconnected dynamical systems derived from static noncooperative games. Designing such a gradient-type feedback aims at robustly driving state variables to the vicinities of Nash equilibria in the presence of uncertainty and variation. A recently-developed small-gain framework for integral input-to-state stable systems is employed to investigate global robustness of the gradient-type dynamical system with respect to disturbances and time-delays. Stability and robustness criteria are presented, and Lyapunov-Krasovskii functionals are constructed. The developed theory is applied to the plug-in electric vehicles charging problem of allocating the charging activities to the overnight electric demand valley for reducing the impact on the electric grid. A decentralized charging scheme with guaranteed robustness is proposed. Its usefulness is illustrated by numerical simulations.
Experience in measuring backbone traffic variability: models, metrics, measurements and meaning

Understanding the variability of Internet traffic in backbone networks is essential to better plan and manage existing networks, as well as to design next generation networks. However, most traffic analyses that might be used to approach this problem are based on detailed packet or flow level measurements, which are usually not available throughout a large network. As a result there is a poor understanding of backbone traffic variability, and its impact on network operations (e.g. on capacity planning or traffic engineering). This paper introduces a metric for measuring backbone traffic variability that is grounded on simple but powerful traffic theory. What sets this metric apart, however, is that we present a method for making practical measurements of the metric using widely available SNMP traffic measurements. Furthermore, we use a novel method to overcome the major limitation of SNMP measurements -- that they only provide link statistics. The method, based on a "gravity model", derives an approximate traffic matrix from the SNMP data. In addition to simulations, we use more than 1 year's worth of SNMP data from an operational IP network of about 1000 nodes to test our methods. We also delve into the degree and sources of variability in real backbone traffic, providing insight into the true nature of traffic variability.