Miracle-dz/UniFAR-FTUs huggingface dataset:
Absorption and metabolism of glucose by the mesenteric-drained viscera of sheep fed on dried-grass or ground, maize-based diets

1. Sheep fitted with re-entrant canulas in the proximal duodenum and terminal ileum were used to determine the amount of α-glucoside entering, and apparently disappearing from, the small intestine when either dried-grass or ground maize-based diets were fed. The fate of any α-glucoside entering the small intestine was studied by comparing the net disappearance of such a-glucoside from the small intestine with the absorption of glucose into the mesenteric venous blood. 2. Glucose absorption from the small intestine was measured in sheep equipped with catheters in the mesenteric vein and carotid artery. A continuous infusion of [6-3H]glucose was used to determine glucose utilization by the mesenteric-drained viscera and the whole-body glucose turnover rate (GTR). 3. The amounts of α-glucoside entering the small intestine when the dried-grass and maize-based diets were given were 13.9 (SE 1.5) and 95.4 (SE 16.2) g/24 h respectively; apparent digestibilities of such α-glucoside in the small intestine were 60 and 90% respectively. 4. The net absorption of glucose into the mesenteric venous blood was —2.03 (SE 1.20) and 19.28 (SE 0.75) mmol/h for the dried-grass and maize-based diets respectively. Similarly, total glucose absorption amounted to 1.52 (SE 1.35) and 23.33 (SE 1.86) mmol/h (equivalent to 7 and 101 g/24 h respectively). These values represented 83 and 11 1% of the a-glucoside apparently disappearing from the small intestine, determined using the re-entrant cannulated sheep. 5. Total glucose absorption represented 8 and 61% of the whole-body GTR for the dried-grass and maize-based diets respectively. Endogenous glucose production was significantly lower when the sheep were fed on the maize-based diet compared with the dried-grass diet. 6. The mesenteric-drained viscera metabolized a small amount of glucose, equivalent to 234 and 17% of the total glucose absorbed for the dried-grass and maize-based diets respectively. 7. It is concluded that a large proportion of the starch entering the small intestine of sheep given a maize-based diet is digested and absorbed as glucose, and thus contributes to the whole-body GTR.
Methods for Growing and Titrating African Swine Fever Virus: Field and Laboratory Samples

Growing African swine fever virus (ASFV) isolates obtained mainly from the field, but also engineered in the laboratory, is a critical step for diagnosis, titration, or virus infection studies. This unit describes a set of methods and protocols to produce and titrate any ASFV strain in cell cultures. The procedures include (1) basic techniques to prepare virus‐sensitive target cells; (2) strategies for growth, concentration, and purification of virus stocks; and (3) the semi‐quantitative (end dilution) and quantitative (plaque) assays for the determination of viral titers, and the use of different ASFV‐sensitive cells as targets for virus production and titration. Curr. Protoc. Cell Biol. 53:26.14. 1‐26.14. 25. © 2011 by John Wiley & Sons, Inc.
Topological large-scale off-road navigation and exploration RAVON at the European Land Robot Trial 2008

A large-scale navigation system for autonomous off-road robots is presented which uses a topological map to navigate to a previously unseen target location. During path traversal, the system relies on a local navigation layer to avoid obstacles not modeled in the map. Data from this local layer is abstracted to learn both realistic topological edge cost measures and local traversability maps which allow more efficient route selection during topological exploration. On the topological level, a technique to handle impassable route segments in the map is presented and an exploration strategy that allows to discover new routes to the goal is introduced. The performance of the proposed concept is experimentally validated on the robot RAVON at the 2nd Military European Land Robot Trial 2008.
Limiting Absorption Principle and Perfectly Matched Layer Method for Dirichlet Laplacians in Quasi-cylindrical Domains

We establish a limiting absorption principle for Dirichlet Laplacians in quasi-cylindrical domains. Outside a bounded set these domains can be transformed onto a semi-cylinder by suitable diffeomorphisms. Dirichlet Laplacians model quantum or acoustically-soft waveguides associated with quasi-cylindrical domains. We construct a uniquely solvable problem with perfectly matched layers of finite length. We prove that solutions of the latter problem approximate outgoing or incoming solutions with an error that exponentially tends to zero as the length of layers tends to infinity. Outgoing and incoming solutions are characterized by means of the limiting absorption principle.
How to Keep a Secret: Leakage Deterring Public-key Cryptography

How is it possible to prevent the sharing of cryptographic functions? This question appears to be fundamentally hard to address since in this setting the owner of the key is the adversary: she wishes to share a program or device that (potentially only partly) implements her main cryptographic functionality. Given that she possesses the cryptographic key, it is impossible for her to be prevented from writing code or building a device that uses that key. She may though be deterred from doing so. We introduce leakage-deterring public-key cryptographic primitives to address this problem. Such primitives have the feature of enabling the embedding of owner-specific private data into the owner’s publickey so that given access to any (even partially functional) implementation of the primitive, the recovery of the data can be facilitated. We formalize the notion of leakage-deterring in the context of encryption, signature, and identification and we provide efficient generic constructions that facilitate the recoverability of the hidden data while retaining privacy as long as no sharing takes place.
Clustering-Based Adaptive Crossover and Mutation Probabilities for Genetic Algorithms

Research into adjusting the probabilities of crossover and mutation pm in genetic algorithms (GAs) is one of the most significant and promising areas in evolutionary computation. px and pm greatly determine whether the algorithm will find a near-optimum solution or whether it will find a solution efficiently. Instead of using fixed values of px and pm , this paper presents the use of fuzzy logic to adaptively adjust the values of px and pm in GA. By applying the K-means algorithm, distribution of the population in the search space is clustered in each generation. A fuzzy system is used to adjust the values of px and pm. It is based on considering the relative size of the cluster containing the best chromosome and the one containing the worst chromosome. The proposed method has been applied to optimize a buck regulator that requires satisfying several static and dynamic operational requirements. The optimized circuit component values, the regulator's performance, and the convergence rate in the training are favorably compared with the GA using fixed values of px and pm. The effectiveness of the fuzzy-controlled crossover and mutation probabilities is also demonstrated by optimizing eight multidimensional mathematical functions
Linear Concurrent Constraint Programming: Operational and Phase Semantics

In this paper we give a logical semantics for the class CC of concurrent constraint programming languages and for its extension LCC based on linear constraint systems. Besides the characterization in intuitionistic logic of the stores of CC computations, we show that both the stores and the successes of LCC computations can be characterized in intuitionistic linear logic. We illustrate the usefulness of these results by showing with examples how the phase semantics of linear logic can be used to give simple “semantical” proofs of safety properties of LCC programs.
A Novel Method to Determine the Assembling Space between Two Protein Subunits

It is thought that proteins recognize their partners by complementarity. The parameters for the charge complementarity and many analyses have been reported not only in small ligand to protein interactions but also protein-protein interactions. However, there have been few reports about shape complementarity, especially for the protein-protein interfaces. The SC program [1] may be the only method available to describe shape complementarity previously reported. However, this method is based on the surface shape. To assess the shape complementarity, we propose to calculate the volume between two protein subunits and thereby facilitate estimation of shape complementarity independently of the surface shape.
System identification using binary sensors

System identification is investigated for plants that are equipped with only binary-valued sensors. Optimal identification errors, time complexity, optimal input design, and impact of disturbances and unmodeled dynamics on identification accuracy and complexity are examined in both stochastic and deterministic information frameworks. It is revealed that binary sensors impose fundamental limitations on identification accuracy and time complexity, and carry distinct features beyond identification with regular sensors. Comparisons between the stochastic and deterministic frameworks indicate a complementary nature in their utility in binary-sensor identification.
Non-cooperative target assignment using regret matching

In this paper, we have adopted a game theoretic approach to consider optimal assignment of targets to vehicles. We have taken optimality to mean that the cost of vehicle-target assignment is minimized where the cost is the sum of the Euclidean distances between a vehicle and its assigned target. This occurs when the set of targets is assigned to their nearest vehicles. In other words, each vehicle should assign themselves to a target located within the Voronoi region associated with the vehicle. Standard schemes require vehicle-vehicle communication at least to rank the targets according to the nearest neighbour rule. In our proposed model, there is no need for communication among the vehicles and only limited communication between the targets and the vehicles is required. Specifically, we have introduced an appropriate utility function which depends on the distance between the vehicles and targets and the number of vehicles engaging a particular target. The vehicles negotiate their choice of targets via regret matching. We present simulations which demonstrate that vehicles select targets that fall within their Voronoi region. For vehicles that do not have any targets within their Voronoi region, they select their nearest unassigned target. We also present analysis of how the designed utility function causes convergence of the vehicle-target assignment using regret matching.
Construction of Deliberation Structure in E‐Mail Communication

We propose a model, called a deliberation structure model, that represents streams of relevant messages in email communication. The deliberation structure model treats e‐mail messages that include several topics and uses tree structure, called deliberation trees, that are based on Clark's contribution trees to represent message structure. Deliberation trees are useful to visualize the message structure. A method for constructing the deliberation structure is showed.
Propelinear structure of Z_{2k}-linear codes

Let C be an additive subgroup of Z nk for any k � 1. We define a Gray map � : Z nk ! Z kn such that �(C) is a binary propelinear code and, hence, a Hamming-compatible group code. Moreover, � is the unique Gray map such that �(C) is Hamming-compatible group code. Using this Gray map we discuss about the nonexistence of 1-perfect binary mixed group code.
Keyword query cleaning using hidden Markov models

In this paper, we consider the problem of keyword query cleaning for structured databases from a probabilistic approach. Keyword query cleaning consists of rewriting the user query, segmenting the keywords, matching each segment to database items, and finally tagging the segments by their meta-data information. We present an efficient and robust solution using Hidden Markov Models (HMM). By modeling user keyword queries using a generative probabilistic HMM-based model, we construct a HMM from the user specified keyword query (and the database instance). The optimal statistical keyword cleaning is computed as the most likely path of the constructed HMM. Furthermore, we demonstrate how the optimal HMM-based keyword cleaning algorithm can be generalized to compute a stream of clean queries ranked from the most likely clean query to the least likely clean query. Finally, we present the implementation of the proposed system and its preliminary performance.
Regulation of Heat Shock Proteins 27 and 70, p-Akt/p-eNOS and MAPKs by Naringin Dampens Myocardial Injury and Dysfunction In Vivo after Ischemia/Reperfusion

Naringin has antioxidant properties that could improve redox-sensitive myocardial ischemia reperfusion (IR) injury. This study was designed to investigate whether naringin restores the myocardial damage and dysfunction in vivo after IR and the mechanisms underlying its cardioprotective effects. Naringin (20–80 mg/kg/day, p.o.) or saline were administered to rats for 14 days and the myocardial IR injury was induced on 15th day by occluding the left anterior descending coronary artery for 45 min and subsequent reperfusion for 60 min. Post-IR rats exhibited pronounced cardiac dysfunction as evidenced by significantly decreased mean arterial pressure, heart rate, +LVdP/dt max (inotropic state), -LVdP/dt max (lusitropic state) and increased left ventricular end diastolic pressure as compared to sham group, which was improved by naringin. Further, on histopathological and ultrastructural assessments myocardium and myocytes appeared more normal in structure and the infarct size was reduced significantly in naringin 40 and 80 mg/kg/day group. This amelioration of post-IR-associated cardiac injury by naringin was accompanied by increased nitric oxide (NO) bioavailability, decreased NO inactivation to nitrotyrosine, amplified protein expressions of Hsp27, Hsp70, β-catenin and increased p-eNOS/eNOS, p-Akt/Akt, and p-ERK/ERK ratio. In addition, IR-induced TNF-α/IKK-β/NF-κB upregulation and JNK phosphorylation were significantly attenuated by naringin. Moreover, western blotting and immunohistochemistry analysis of apoptotic signaling pathway further established naringin cardioprotective potential as it upregulated Bcl-2 expression and downregulated Bax and Caspase-3 expression with reduced TUNEL positivity. Naringin also normalized the cardiac injury markers (lactate dehydrogenase and creatine kinase-MB), endogenous antioxidant activities (superoxide dismutase, reduced glutathione and glutathione peroxidase) and lipid peroxidation levels. Thus, naringin restored IR injury by preserving myocardial structural integrity and regulating Hsp27, Hsp70, p-eNOS/p-Akt/p-ERK signaling and inflammatory response.
Articulatory VCV Synthesis from EMA Data

This paper reports experiments in synthesizing VCV sequences with French unvoiced stop or fricative consonants, using a time-domain simulation of the vocal-tract system. The necessary dynamics of the vocal-tract shape are derived in two steps: first, time-varying parameters of an articulatory model are calculated automatically from electromagnetic articulography (EMA) data, using a method previously published by the first author; second, semi-automatic corrections are applied to properly account for consonantal events. Time-varying characteristics of the glottis are set using empirical rules. Friction noise is generated along the length of the whole vocal-tract instead of locally at the narrowest constriction. Spectrogams of satisfactory synthesis results are presented alongside those of real speech recorded simultaneously with the articulatory data. Corresponding audio files are available online.
Prototyping a three-link robot manipulator

In this paper we present the stages of designing a three link robot manipulator pro totype that was built as part of a research project for establishing a prototyping en vironment for robot manipulators Building this robot helped determine the required subsystems and interfaces for building the prototyping environment and provided hands on experience for real problems and di culties that are addressed and solved using this environment Also this robot is used as an educational tool in robotics and control classes
Cooperative Strategies for Energy-Aware Ad Hoc Networks: A Correlated-Equilibrium Game-Theoretical Approach

Energy efficiency is a crucial requirement for energy-aware ad hoc networks. Cooperative communications can be applied to significantly reduce and balance energy consumption. However, this advantage mainly depends on efficient cooperative strategies, i.e., the joint issue of relay node selection and transmit power control. In this paper, we propose a cooperative behavior control scheme, which determines cooperative strategies by using the correlated equilibrium (CE). Specifically, we first model a cooperative behavior control game where the individual utility function is derived from the energy efficiency in terms of the global max-min fairness with the outage performance constraint. Since the CE can achieve better performance by helping the noncooperative players to coordinate their strategies, we employ the CE to analyze the proposed game. Next, we derive the condition under which the CE is Pareto optimal and employ linear programming duality to show its closed-form expression. Furthermore, we design a linear programming method and a distributed learning algorithm based on the regret matching procedure to achieve the CE, respectively. Simulation results demonstrate that our scheme achieves good convergence, Pareto optimality, and max-min fairness.
Interactive Texture Segmentation using Random Forests and Total Variation

Hypothesis The segmentation quality depends on a strong description for F and B. In order to model hypotheses based on different high-level features, we need an efficient learning algorithm capable of handling arbitrary input data. Random Forests (RFs) are fast to compute while yielding state-of-the-art performance in machine learning and vision problems. Their parallel structure dedicates them to GPU implementations. Recently, an online version of RFs has been proposed [2], which renders retraining of the whole forest upon additional user input unnecessary.
Sliding mode control for trajectory tracking of nonholonomic wheeled mobile robots

Nonholonomic mobile robots have constraints imposed on the motion that are not integrable, i.e., the constraints cannot be written as time derivatives of some function of the generalized coordinates. The position control of nonholonomic mobile robots has been an important class of control problems. In this paper, we propose a robust tracking control of nonholonomic wheeled mobile robots using sliding mode. The posture of a mobile robot is represented by polar coordinates and the dynamic equation of the robot is feedback-linearized by the computed-torque method. A novel sliding mode control law is proposed for asymptotically stabilizing the mobile robot to a desired trajectory. It is shown that the proposed scheme is robust to bounded external disturbances. Experimental results demonstrate the effectiveness of accurate tracking capability and the robust performance of the proposed scheme.
Molecular, Cellular and Functional Effects of Radiation-Induced Brain Injury: A Review

Radiation therapy is the most effective non-surgical treatment of primary brain tumors and metastases. Preclinical studies have provided valuable insights into pathogenesis of radiation-induced injury to the central nervous system. Radiation-induced brain injury can damage neuronal, glial and vascular compartments of the brain and may lead to molecular, cellular and functional changes. Given its central role in memory and adult neurogenesis, the majority of studies have focused on the hippocampus. These findings suggested that hippocampal avoidance in cranial radiotherapy prevents radiation-induced cognitive impairment of patients. However, multiple rodent studies have shown that this problem is more complex. As the radiation-induced cognitive impairment reflects hippocampal and non-hippocampal compartments, it is of critical importance to investigate molecular, cellular and functional modifications in various brain regions as well as their integration at clinically relevant doses and schedules. We here provide a literature overview, including our previously published results, in order to support the translation of preclinical findings to clinical practice, and improve the physical and mental status of patients with brain tumors.
An integrated collision avoidance system for autonomous underwater vehicles

This paper presents an integrated approach to the design of an obstacle avoidance system for autonomous underwater vehicles. A type of incremental stochastic algorithm known as rapidly-exploring random tree (RRT) is merged with a manoeuvre automaton (MA) representation to form the motion planner. The improved planner is not only capable of taking into account the dynamics of the system, but it also allows complex non-linear manoeuvres to be performed. In addition, it is highly computationally efficient. This paper also extends it to take into account dynamic targets. The output trajectory from the planner is then tracked using a kinematic based state-dependent Riccati equation (SDRE) controller. In other words, by omitting the requirement of a dynamic model of the system, one can extend the application to a more encompassing types of vehicle whilst reducing the number of tuning parameters. Detailed simulation studies are conducted using a non-linear AUTOSUB model to investigate the feasibility of the proposed methods.
Heterogeneity in mouse spasmolytic polypeptide-expressing metaplasia lineages identifies markers of metaplastic progression

Objectives Spasmolytic polypeptide-expressing metaplasia (SPEM) develops as a preneoplastic lesion in the stomachs of mice and humans after parietal cell loss. To identify the commonalities and differences between phenotypic SPEM lineages, SPEM were studied from three different mouse models of parietal cell loss: with chronic inflammation with Helicobacter felis infection; with acute inflammation with L635 treatment; and without inflammation following DMP-777 treatment. Design RNA transcripts from laser capture microdissected normal chief cells and SPEM lineages were compared using gene microarray. Alterations in transcripts were validated by quantitative real-time PCR. Clusterin and cystic fibrosis transmembrane conductance regulator (CFTR) were selected for immunohistochemical analysis in all mouse models as well as in human SPEM, intestinal metaplasia and gastric cancer. Results Transcript expression patterns demonstrated differences among the phenotypic SPEM models. Clusterin expression was significantly upregulated in all three mouse SPEM models as well as in human SPEM. The highest clusterin expression in human gastric cancers correlated with poor survival. Conversely, CFTR expression was upregulated only in SPEM with inflammation in mice. In humans, intestinal metaplasia, but not SPEM, expressed CFTR. Conclusions While markers such as clusterin are expressed in all phenotypic SPEM lineages, distinct patterns of upregulated genes including CFTR are present in murine metaplasia associated with inflammation, indicative of progression of metaplasia towards a more intestinalised metaplastic phenotype.