Miracle-dz/UniFAR-FTUs huggingface dataset:
Immunological detection of nitrosative stress-mediated modified Tamm–Horsfall glycoprotein (THP) in calcium oxalate stone formers

Abstract The generation of reactive oxygen species (ROS) and reactive nitrogen species (RNS) in hyperoxaluric condition has been proved experimentally. This may result in the formation of the cytotoxic metabolite peroxynitrite, which is capable of causing lipid peroxidation and protein modification. The presence of nitrotyrosine in proteins has been associated with several pathological conditions. The present study investigated the presence of nitrotyrosine in the stone formers Tamm–Horsfall glycoprotein (THP). In vitro nitration of control THP was carried out using peroxynitrite. New Zealand white rabbits were immunized with peroxynitrated THP at 15-day intervals. Antisera collected following the third immunization were assayed for antibody titres using solid-phase ELISA. Antibodies were purified by affinity chromatography. The carbonyl content of control, stone formers and nitrated THP were determined. Western blotting was carried with control, stone formers and nitrated THPs. Immunodiffusion studies demonstrated cross-reaction with nitrated bovine serum albumin. Significant amounts (p<0.001) of carbonyl content were present in both stone formers and nitrated THPs. Western blot analysis confirmed the presence of nitrated amino acid 3-nitrotyrosine in stone formers, which could bring about structural and functional modifications of THP in hyperoxaluric patients. A cross-reaction with nitrated bovine serum albumin confirms that the raised antibody has certain paratopes similar to the epitope of nitrated protein molecules. Detection of 3-nitrotyrosine in stone formers THP indicates that it is one of the key factors influencing the conversion of THP to a structurally and immunologically altered form during calcium oxalate stone formation.
Application of data mining in agriculture.

MiloviC, B. and v. RadojeviC, 2015. application of data mining in agriculture. Bulg. J. Agric. Sci., 21: 26-34 Today, agricultural organizations work with large amounts of data. Processing and retrieval of significant data in this abun - dance of agricultural information is necessary. Utilization of information and communications technology enables automation of extracting significant data in an effort to obtain knowledge and trends, which enables the elimination of manual tasks and easier data extraction directly from electronic sources, transfer to secure electronic system of documentation which will enable production cost reduction, higher yield and higher market price. Data mining in addition to information about crops enables agricultural enterprises to predict trends about customer’s conditions or their behavior, which is achieved by analyzing data from different perspectives and finding connections and relationships in seemingly unrelated data. Raw data of agricultural enterprises are very ample and diverse. it is necessary to collect and store them in an organized form, and their integration enables the creation of agricultural information system. Data mining in agriculture provides many opportunities for exploring hidden patterns in these collections of data. These patterns can be used to determine the condition of customers in agricultural organizations.
Learning Goal Seeking and Obstacle Avoidance using the FQL Algorithm

In this article, we are interested in the reactive behaviours navigation training of a mobile robot in an unknown environment. The method we will suggest ensures navigation in unknown environments with presence off different obstacles shape and consists in bringing the robot in a goal position, avoiding obstacles and releasing it from the tight corners and deadlock obstacles shape. This is difficult to do manually in the case of FIS with a large rule base. In this framework, we use the reinforcement learning algorithm called Fuzzy Q-learning, based on temporal difference prediction method. The application was tested in our experimental PIONEER II platform.
Localized QoS Routing Algorithm Based on Residual Bandwidth

The biggest contemporary drawback in the maintenance and distribution of the global state is the increase in communication overheads. Localized routing is the method to avoid this problem. New localized routing algorithms called Highest Minimum Bandwidth routing (HMB) is introduced in this paper. The new algorithm is compared under different traffic loads and network topologies to the existing localized Credit Based Routing (CBR) and the global WSP routing algorithm. New algorithm shows better performance without undue increase in complexity. The selection of disjoint paths and recalculation of the set of candidate paths, which assist both existing localized routing and our novel algorithm to achieve superior performance, are also described.
Forgot your password: Correlation dilution

We consider the problem of diluting common randomness from correlated observations by separated agents. This problem creates a new framework to study statistical privacy, in which a legitimate party, Alice, has access to a random variable X, whereas an attacker, Bob, has access to a random variable Y dependent on X drawn from a joint distribution pX,Y. Alice's goal is to produce a non-trivial function of her available information that is uncorrelated with (has small correlation with) any function that Bob can produce based on his available information. This problem naturally admits a minimax formulation where Alice plays first and Bob follows her. We define dilution coefficient as the smallest value of correlation achieved by the best strategy available to Alice, and characterize it in terms of the minimum principal inertia components of the joint probability distribution pX,Y. We then explicitly find the optimal function that Alice must choose to achieve this limit. We also establish a connection between differential privacy and dilution coefficient and show that if Y is ε-differentially private from X, then dilution coefficient can be upper bounded in terms of ε. Finally, we extend to the setting where Alice and Bob have access to i.i. d. copies of (Xi, Yi), i = 1, . , n and show that the dilution coefficient vanishes exponentially with n. In other words, Alice can achieve better privacy as the number of her observations grows.
Agonistic screams differ among four species of macaques: the significance of motivation-structural rules

We compared screams of four species of macaques (rhesus monkey, Macaca mulatta; pigtailed monkey, M. nemestrina; Sulawesi crested black macaque, M. nigra; stumptailed macaque, M. arctoides) with respect to predictions of Morton's motivation-structural rules (Morton 1977, American Naturalist, 111, 855-869). We examined screams produced by victims of attack that involved contact aggression (pulling, pushing, slapping, grappling and biting) from a higher-ranking opponent. For each macaque species, we digitized 100 screams from females 3 years of age or older and measured acoustic features of each call. We used discriminant function analysis to determine whether the 400 vocalizations could be assigned to the correct caller species on the basis of their acoustic structure. Calls were assigned to the correct species at a significantly higher rate (93.5%) than expected by chance (25%). Each of the four macaque species used acoustically distinct screams in a shared context. While the differences in the macaque species' vocalizations suggest no simple correlation between immediate context and the acoustic forms of screams, there was general correspondence between the acoustic structure predicted by motivation-structural rules and inferences about the internal state of the vocalizer derived from the typical intensity of aggressive patterns that characterize each of the four species. Copyright 2000 The Association for the Study of Animal Behaviour.
Leptospirosis Outbreak during Rice Harvesting Season in Kebumen, Central Java Indonesia (The First Case Report in Kebumen)

Leptospirosis, a public health problem in Indonesia, has never been reported in Kebumen before, but Kebumen Public Health Office reported several new leptospirosis cases in this regency during paddy harvesting season in February 2017. A descriptive cross-sectional study was conducted to investigate leptospirosis epidemiology (eg, the reservoir animals, the geographical distribution, and specific populations at risk) in Kebumen on March 2017. Thirty febrile patients were enrolled in Public Health Services and tested for leptospirosis using Leptotek. The positive cases were investigated by interview and site inspection to assess environmental risks. Rat traps were set randomly at housing areas near the positive cases's house in Kuwarasan and Buayan subdistricts. Kidneys were removed from rats and analysed using PCR assay for pathogenic Leptospira detection. Thirteen positive leptospirosis cases out of 30 febrile patients were found in 6 subdistricts consisted of Kuwarasan (30.7%), Buayan (30.7%), Karanganyar (7.7%), Gombong (7.7%), Sempor (7.7%) and Sruweng (15.4%). 92, 31% of the patients were farmers, indicating occupational exposures at paddy fields. Most of the case were in the age group of 31–40 years (53, 85%). High vulnerability among males due to activities in outdoor settings was revealed from male to female ratio (12: 1). Clinical symptoms consisted of calf muscle pain (100%), jaundice (84.6%), oliguria (38.5%) and renal failure (15.4%), with case fatality rate was 23, 08%. Rats (Bandicotta indica) with positive Leptospira were found at Kuwarasan subdistrict (6.25%). Based on the results of this study, paddy harvesting season is a critical period associated with leptospirosis transmission in Central Java. Indeed, preventive efforts should be done to avoid leptospirosis outbreak
Parallel Multi-Proposal and Multi-Chain MCMC for calculating P-Value of genome-Wide Association Study

In this paper, by the novel idea of integrating multiple-proposal algorithm and multiple-chain algorithm by parallel computing, we develop a highly efficient sampler for approximating statistical distributions: parallel Multi-proposal and Multi-chain Markov Chain Monte Carlo (pMPMC3), and we illustrate the high performance of this sampler by calculating P-value (odds ratio significance) for Genome Wide Association Study (GWAS). Computational results show that, by setting the convergence condition as the standard deviation of P-value is less than 10−3, pMPMC3 with 4 proposals and 4 chains obtains a convergent P-value within 106 iterations, while the conventional method Monte Carlo simulation does not obtain convergent P-values even in 107 iterations. We also test pMPMC3 by changing the number of chains, the number of proposals and the size of the dataset on a cluster with maximum 600 processes, the algorithm scales well.
Optimizing Repetitive Computations of Database Triggers within a Transaction

We study the problem of optimizing costly repetitive evaluations of database triggers within a transaction. We first show that well known incremental rule evaluation algorithms such as RETE or TREAT are inappropriate for that because they do not consider how repetitive triggerings of rules can be caused by the structure of transaction programs. Therefore, their decision of precomputing and caching some expressions in rule conditions for a later reuse can be erroneous. We assume that transaction programs are represented by their flow graph. We then propose an algorithm that, given a transaction's flow graph, and a set of triggers, constructs a compact data structure called a triggering graph. First, for each possible transaction execution, this graph indicates which rules may be triggered. Second, for every rule $r$ capable of being triggered and fired several times, the graph represents the real «influence» of both the transaction and the rules on $r$. This provides the necessary information for deciding which subexpressions of $r$ are most profitable to cache for the considered transaction.
Simvastatin induces the apoptosis of normal vascular smooth muscle through the disruption of actin integrity via the impairment of RhoA/ Rac-1 activity

Summary Statins, lipid-lowering agents for the prevention of atherosclerosis and fatal coronary heart diseases, have pleiotropic modalities on the function and physiology of vascular smooth muscle that include anti-contractile and pro-apoptotic effects. These effects were suggested to stem from the inhibition of small GTPase Rho A, but they are largely regarded as distinct and unrelated. Recently, we discovered that simvastatin causes both contractile dysfunction and apoptosis of vascular smooth muscle cells (VSMCs), reflecting that they may be closely related, yet their connecting link remains unexplained. Here, we elaborated the mechanism underlying simvastatin-induced apoptosis of normal VSMCs in connection with contractile dysfunction. Repeated oral administration of simvastatin to rats in vivo resulted in contractile dysfunction and apoptosis of vascular smooth muscle, of which pattern was well reproduced in rat VSMCs in vitro. Of note, contractile dysfunction and apoptosis occurred in concerted manners both in vivo and in vitro in the aspects of time course and dose of exposure. In rat VSMCs, simvastatin impaired the activation of small GTPases, RhoA along with Rac-1, which resulted in the disruption of actin integrity, a pivotal factor both for the generation of contractile force and survival of VSMCs. In line with the disruption of actin integrity, Bmf, a pro-apoptotic factor bound to intact actin, dissociated and translocated into mitochondria, which corresponded well with the dissipation of mitochondrial membrane potential, caspase-3 activation and ultimately apoptosis. These events were all rescued by an actin stabilisation agent, jasplakinolide as well as geranylgeraniol, indicating that damages of the actin integrity from disrupted activation of RhoA/ Rac-1 lies at the center of simvastatin-induced contractile dysfunction and apoptosis in vascular smooth muscle. Supplementary Material to this article is available online at www.thrombosis-online.com.
MMSE of probabilistic low-rank matrix estimation: Universality with respect to the output channel

This paper considers probabilistic estimation of a low-rank matrix from non-linear element-wise measurements of its elements. We derive the corresponding approximate message passing (AMP) algorithm and its state evolution. Relying on non-rigorous but standard assumptions motivated by statistical physics, we characterize the minimum mean squared error (MMSE) achievable information theoretically and with the AMP algorithm. Unlike in related problems of linear estimation, in the present setting the MMSE depends on the output channel only trough a single parameter - its Fisher information. We illustrate this striking finding by analysis of submatrix localization, and of detection of communities hidden in a dense stochastic block model. For this example we locate the computational and statistical boundaries that are not equal for rank larger than four.
Pinocchio's Pupil: Using Eyetracking and Pupil Dilation to Understand Truth-Telling and Deception in Sender-Receiver Game

We report experiments on sender-receiver games with an incentive for senders to exaggerate. Subjects "overcommunicate" -- messages are more informative of the true state than they should be, in equilibrium. Eyetracking shows that senders look at payoffs in a way that is consistent with a level-k model. A combination of sender messages and lookup patterns predicts the true state about twice as often as predicted by equilibrium. Using these measures to infer the state would enable receiver subjects to hypothetically earn 16-21 percent more than they actually do, an economic value of 60 percent of the maximum increment. (JEL C72, C91, D82, Z13)
PORT-BASED ONTOLOGY SEMANTIC SIMILARITIES FOR MODULE CONCEPT CREATION

The modularity indicates a one-to-one mapping between functional concepts and physical components. It can allow us to generate more product varieties at lower costs. Functional concepts can be described by precise syntactic structures with functional terms. Different semantic measures can be used to evaluate the strength of the semantic link between two functional concepts from port ontology. In this paper, different methods of modularity based on ontology are first investigated. Secondly, the primitive concepts are presented based on port ontology by using natural language, and then their semantic synthesis is used to describe component ontology. The taxonomy of port-based ontology are built to map the component connections and interactions in order to build functional blocks. Next, propose an approach to computing semantic similarity by mapping terms to functional ontology and by examining their relationships based on port ontology language. Furthermore, several modules are partitioned on the basis of similarity measures. The process of module construction is described and its elements are related to the similarity values between concepts. Finally, a case is studied to show the efficiency of port ontology semantic similarity for modular concept generation. © 2009 ASME
Attacking Signed Binaries

The digital verification of binaries at the kernel level has been proposed as a method to prevent trojaned programs and unauthorised execution. However, the nature of attacks which various signed binary schemes seek to prevent vary quite considerably. Further, unrealistic assumptions are often made as to the security of the environment in which the verification takes place. In this paper, the authors explore one such kernel-level verification tool, DigSig, and show how the security assumptions that DigSig makes are too broad. Various attacks which succeed given a reduced set of assumptions are then demonstrated. A number of recommendations are made, which alleviate most attacks described without requiring a vastly more complex system.
Metric cotype

We introduce the notion of <i>metric cotype</i>, a property of metric spaces related to a property of normed spaces, called <i>Rademacher cotype</i>. Apart from settling a long standing open problem in metric geometry, this property is used to prove the following dichotomy: A family of metric spaces <i>F</i> is either almost universal (i.e., contains any finite metric space with any distortion > 1), or there exists α > 0, and arbitrarily large <i>n</i>-point metrics whose distortion when embedded in any member of <i>F</i> is at least Ω((log <i>n</i>)<sup>α</sup>). The same property is also used to prove strong non-embeddability theorems of <i>L</i><inf><i>q</i></inf> into <i>L</i><inf><i>p</i></inf>, when <i>q</i> > max{2, <i>p</i>}. Finally we use metric cotype to obtain a new type of isoperimetric inequality on the discrete torus.
Marine Fish Proteins and Peptides for Cosmeceuticals: A Review

Marine fish provide a rich source of bioactive compounds such as proteins and peptides. The bioactive proteins and peptides derived from marine fish have gained enormous interest in nutraceutical, pharmaceutical, and cosmeceutical industries due to their broad spectrum of bioactivities, including antioxidant, antimicrobial, and anti-aging activities. Recently, the development of cosmeceuticals using marine fish-derived proteins and peptides obtained from chemical or enzymatical hydrolysis of fish processing by-products has increased rapidly owing to their activities in antioxidation and tissue regeneration. Marine fish-derived collagen has been utilized for the development of cosmeceutical products due to its abilities in skin repair and tissue regeneration. Marine fish-derived peptides have also been utilized for various cosmeceutical applications due to their antioxidant, antimicrobial, and matrix metalloproteinase inhibitory activities. In addition, marine fish-derived proteins and hydrolysates demonstrated efficient anti-photoaging activity. The present review highlights and presents an overview of the current status of the isolation and applications of marine fish-derived proteins and peptides. This review also demonstrates that marine fish-derived proteins and peptides have high potential for biocompatible and effective cosmeceuticals.
Forecasting Wheat Price Using Backpropagation And NARX Neural Network

--------------------------------------------------ABSTRACT-------------------------------------------------------This study aims to investigate suitable model and forecast future wheat price using backpropagation neural network (BPNN) and nonlinear autoregressive models with exogenous inputs (NARX) networks. The price of wheat was estimated using prices of 3 types of grains widely used in agriculture which are oats, barley and soybeans. The analysis was conducted using historical data on the prices from 1978 until 2012. Artificial neural networks are non-parametric statistical estimators, and thus have potential for use in estimation modeling. The variables selection criteria procedures are also developed to select a significance explanatory variable. The methods are compared to obtain the best model for predicting wheat price. Based on the results, the NARX model with 8 nodes in hidden layer and 4 tapped delay lines can be used as an alternative model predict wheat price.
Implementation of Surface Gratings for Reduced Coupling Noise in Silicon-on-Insulator Circuits

Coupling light into a silicon-on-insulator photonic chip has always been the first hurdle to overcome when using photonic integrated circuits. For applications that require robust, low-noise performance, and high degree of multiplexing, flood illuminating an array of vertical grating couplers is a promising approach to couple input light into the chip waveguides. This technique provides a very high alignment tolerance and allows simultaneous excitation of multiple waveguides for rapid parallel readout. However, parasitic reflections of the coupled light on the chip substrate introduce interferences and limit the device performance. We investigate the use of grating structures implemented on the chip surface to limit these parasitic signals and demonstrate a significant reduction of the coupling noise.
Vegetation versus man-made object detection from imagery for unmanned vehicles in off-road environments

There have been several major advances in autonomous navigation for unmanned ground vehicles in controlled urban environments in recent years. However, off-road environments still pose several perception and classification challenges. This paper addresses two of these challenges: detection and classification of vegetation vs. man-made objects. In order for a vehicle or remote operator to traverse cross-country terrain, automated decisions must be made about obstacles in the vehicle's path. The most common obstacle is vegetation, but some vegetation may be traversable, depending on the size of the vehicle and the type of vegetation. However, man made objects should generally be detected and avoided in navigation. We present recent research towards the goal of vegetation and man-made object detection in the visible spectrum. First, we look at a state-of-the-art approach to image segmentation and image saliency using natural scene statistics. Then we apply recent work in multi-class image labeling to several images taken from a small unmanned ground vehicle (UGV). This work will attempt to highlight the recent advances and challenges that lie ahead in the ultimate goal of vegetation and man-made object detection and classification in the visual spectrum from UGV.