Miracle-dz/UniFAR-FTUs huggingface dataset:
A Combination of Behavioral and Physiological Indicators for Assessing Pig Welfare on the Farm

The purpose of this research was to identify pig welfare indicators that could help in recognizing stressful practices on farm. The study evaluated behavioral and physiological indicators (cortisol and negative acute phase proteins) in 2 groups of 20 female pigs 4 months old after a 48-hr transport. The first group (A) was transported at the end of May, the second (B) in June. Behavioral observations and blood collection occurred at arrival (D1) and 28 days later (D28). Compared with within-animal control samples obtained 28 days later, pigs of Group A had increased cortisol levels and decreased albumin concentrations after arrival. As demonstrated by lesion and behavior observations, the effect on cortisol and albumin was higher in Group B pigs after a tail-biting episode occurred. The study has reported no evidence of Retinol Binding Protein (RBP) in pigs. A method developed for swine RBP quantification found RBP strongly reduced in D28 samples of Group B, confirming it to be a negative protein in pigs. The suggested combination of physiological and behavioral indicators could provide useful information on the welfare state of an animal.
Learning Qualitative Metabolic Models

The ability to learn a model of a system from observations of the system and background knowledge is central to intelligence, and the automation of the process is a key research goal of Artificial Intelligence. We present a model-learning system, developed for application to scientific discovery problems, where the models are scientific hypotheses and the observations are experiments. The learning system, QoPH learns the structural relationships between the observed variables, known to be a hard problem. QoPH has been shown capable of learning models with hidden (unmeasured) variables, under different levels of noise, and from qualitative or quantitative input data.
The Potential of GMP-Compliant Platelet Lysate to Induce a Permissive State for Cardiovascular Transdifferentiation in Human Mediastinal Adipose Tissue-Derived Mesenchymal Stem Cells

Human adipose tissue-derived mesenchymal stem cells (ADMSCs) are considered eligible candidates for cardiovascular stem cell therapy applications due to their cardiac transdifferentiation potential and immunotolerance. Over the years, the in vitro culture of ADMSCs by platelet lysate (PL), a hemoderivate containing numerous growth factors and cytokines derived from platelet pools, has allowed achieving a safe and reproducible methodology to obtain high cell yield prior to clinical administration. Nevertheless, the biological properties of PL are still to be fully elucidated. In this brief report we show the potential ability of PL to induce a permissive state of cardiac-like transdifferentiation and to cause epigenetic modifications. RTPCR results indicate an upregulation of Cx43, SMA, c-kit, and Thy-1 confirmed by immunofluorescence staining, compared to standard cultures with foetal bovine serum. Moreover, PL-cultured ADMSCs exhibit a remarkable increase of both acetylated histones 3 and 4, with a patient-dependent time trend, and methylation at lysine 9 on histone 3 preceding the acetylation. Expression levels of p300 and SIRT-1, two major regulators of histone 3, are also upregulated after treatment with PL. In conclusion, PL could unravel novel biological properties beyond its routine employment in noncardiac applications, providing new insights into the plasticity of human ADMSCs.
Glimepiride: evidence-based facts, trends, and observations

Type 2 diabetes mellitus is characterized by insulin resistance and progressive β cell failure; therefore, β cell secretagogues are useful for achieving sufficient glycemic control. Glimepiride is a second-generation sulfonylurea that stimulates pancreatic β cells to release insulin. Additionally, is has been shown to work via several extra pancreatic mechanisms. It is administered as monotherapy in patients with type 2 diabetes mellitus in whom glycemic control is not achieved by dietary and lifestyle modifications. It can also be combined with other antihyperglycemic agents, including metformin and insulin, in patients who are not adequately controlled by sulfonylureas alone. The effective dosage range is 1 to 8 mg/day; however, there is no significant difference between 4 and 8 mg/day, but it should be used with caution in the elderly and in patients with renal or hepatic disease. In clinical studies, glimepiride was generally associated with lower risk of hypoglycemia and less weight gain compared to other sulfonylureas. Glimepiride use may be safer in patients with cardiovascular disease because of its lack of detrimental effects on ischemic preconditioning. It is effective in reducing fasting plasma glucose, post-prandial glucose, and glycosylated hemoglobin levels and is a useful, cost-effective treatment option for managing type 2 diabetes mellitus.
Gemini H-Band Imaging of the Field of a z = 10 Candidate

We present a deep H-band image of the field of a candidate z = 10 galaxy magnified by the foreground (z = 0.25) cluster A1835. The image was obtained with NIRI on Gemini-North to better constrain the photometry and investigate the morphology of the source. The image is approximately 1 mag deeper and has better spatial resolution (seeing was 0.″4-0.″5) than the existing H-band image obtained with ISAAC on the Very Large Telescope by Pelló et al. The object is not detected in our new data. Given the published photometry (HAB = 25.0), we would have expected it to have been detected at more than ~7 σ in a 1. ″4 diameter aperture. We obtain a limit of HAB > 26.0 (3 σ) for the object. A major part of the evidence that this object is at z = 10 was the presence of a strong continuum break between the J and H bands, attributed to absorption of all continuum shortward of 1216 Å in the rest frame of the object. Our H-band nondetection substantially reduces the magnitude of any break and therefore weakens the case that this object is at z = 10. Without a clear continuum break, the identification of an emission line at 1.33745 μm as Lyα at z ≈ 10 is less likely. We show that the width and flux of this line are consistent with an alternative emission line such as [O III] λ5007 from an intermediate-redshift H II/dwarf galaxy.
Motility-based coverage enhancement in directional sensor networks

Random deployment may cause to the overlapped areas in directional sensor networks. The proposed algorithm Weighted Attraction Forces of Uncovered Points (W-AFUP), aims at both minimizing the overlapped areas and facing the working directions towards the area of interest. W-AFUP is a distributed iterative algorithm which exploits motility capability of the nodes. The proposed algorithm finds the appropriate working direction for each sensor node by using the repel forces exerted by the uncovered points around the sensor nodes. W-AFUP improves the coverage by %19-%37 after the initial deployment.
Sustainable Change Sequence: a framework for developing behavior change interventions for patients with long-term conditions

Objective Interactive interventions are increasingly advocated to support behavior change for patients who have long-term conditions. Such interventions are most likely to achieve behavior change when they are based on appropriate theoretical frameworks. Developers of interventions are faced with a diverse set of behavioral theories that do not specifically address intervention development. The aim of our work was to develop a framework to guide the developers of interactive healthcare interventions that was derived from relevant theory, and which guided developers towards appropriate behavior change techniques. Methods We reviewed theories that inform behavior change interventions, where relevant to the management of long-term conditions. Theoretical constructs and behavior change techniques were grouped according to similarity in aims. Results We developed a logic model that operationalizes behavior change theories and techniques into five steps likely to lead to sustained behavior change. The steps are: 1) create awareness of need; 2) facilitate learning; 3) enhance motivation; 4) prompt behaviour change; and 5) ensure sustainability of behaviour change. Conclusion and Practice implications A framework that sequences behavioural change techniques along a sustainability model provides a practical template for the developers of interactive healthcare applications and interventions.
H-Infinity gain scheduling design for the meridian UAS for a broader range of operation and for fault tolerant applications

This paper describes the design of a MIMO H-infinity gain schedule for the Meridian UAS and illustrates its application for an extended operational range and for a moderate fault tolerant capability. The gain scheduling concept is based on smooth interpolation between two H-infinity controllers, covering a broad range of trim conditions. This interpolation is provided by the homogeneous design of the controllers by using the same augmented model structure within the H-infinity algorithm. The scheduling variable is defined as the commanded airspeed, acting as an exogenous variable, driving a smooth transition between the current and the next controller. The utilization of an exogenous signal avoids the occurrence of hidden coupling effects, typical in gain scheduling applications. Also, a new procedure is defined to adapt the controller when a failure or a significant dynamic change in the UAS takes place. Using the best knowledge of the failure the H-infinity controller is calculated. This controller is computed with a predefined gamma value, avoiding iterations, generating the new controller instantaneously.
Modelling Human Reliability in Air Traffic Management

This paper outlines how the human information processing model of Wickens is combined with Hollnagel’s cognitive control mode model and human error models for application within the context of conventional Air Traffic Management (ATM). The aim of this model-based approach is to enable the evaluation of both accident risk and aspects like cognitive workload and reliability of the human controller in managing air traffic situations safely. The combined model has been integrated with models for pilot, aircraft and other ATM elements and a comparison with available statistical data is made through running Monte Carlo simulations with the integrated model.
Using OTP with PAKE: An Optimized Implementation of a Synchronization Window

Authentication has been a cornerstone of computer security for decades. A considerable number of authentication protocols have been specified and implemented. This paper compares most common families of client-server authentication protocols and shows the benefits of the combined use of One Time Password (OTP) with Password Authenticated Key Exchange (PAKE) protocols. Then, the paper addresses a particular issue inherited from this combination which consists in the synchronization between the client and the server. We propose an optimized implementation for a synchronization mechanism based on the use of a synchronization window. The optimized synchronization has been implemented and the simulation results show that our proposal significantly reduces the computations needed at the client side to select the current password.
A MILP Formulation for Setwise Max-Margin Learning

In max-margin learning, the system aims at establishing a solution as robust as possible. In this paper we extend the idea of max-margin learning to cases where the goal is to produce a set of solutions, instead of a single one. In particular, we focus on the problem of preference elicitation, but we believe our idea could be adapted to other situations. We present a MILP formulation for our “setwise” max margin learner and discuss current ongoing works. 1 Max-margin Learning for Preference Optimization The notion of margin is important in several machine learning algorithms. By maximizing the margin, the learner ensures robustness in the solution. In particular, a max-margin approach has been proposed for optimization with a partially specified preference profile and elicitation of further preferences [2]. Automatic assessment of preferences is an important component of many artificial intelligence systems [3]. In this paper, we show how to extend the idea of maxmargin for optimizing a set and we provide a MILP formulation. The result of the computation can be used to generate a set of recommendations and to generate a “diverse” set of feasible utility functions. This can be useful for further elicitation as we may ask the user a choice query based on this set (“Among these items, which one do you prefer ? ”). First of all, we review the standard (singleton) max-margin learning problem. We assume a multi attribute feature space X (we assume possible options are specified by configuration constraints) and that the user preferences are encoded by a vector of weights w = (w1, ., wm); the utility of an option y is then w · y. The weight vector w is unknown but we are given constraints (that encode a “feasible region”). A pairwise comparison between a more preferred product y+ and a less preferred product y− is encoded by a constraint w · (y+ − y−) ≥ 0. Given a number of such pairwise comparisons, represented by a set D (the “learning set”), and, possibly, other additional constraints (representing some kind of “prior” knowledge, as for example w2 > 0.3) we want to find a vector w of parameters such that all constraints are satisfied and does that by the largest margin. As shown by [2] the problem can be easily formulated as a linear program. The shared margin is represented by the decision variable M , that we want to maximize. We require, 1 Aalborg University, Denmark, email: paolo@cs.aau. dk for each pairwise statement in D, to have w · (y +−y −) ≥M .
Acquisition of Complement Inhibitor Serine Protease Factor I and Its Cofactors C4b-Binding Protein and Factor H by Prevotella intermedia

Infection with the Gram-negative pathogen Prevotella intermedia gives rise to periodontitis and a growing number of studies implies an association of P. intermedia with rheumatoid arthritis. The serine protease Factor I (FI) is the central inhibitor of complement degrading complement components C3b and C4b in the presence of cofactors such as C4b-binding protein (C4BP) and Factor H (FH). Yet, the significance of complement inhibitor acquisition in P. intermedia infection and FI binding by Gram-negative pathogens has not been addressed. Here we show that P. intermedia isolates bound purified FI as well as FI directly from heat-inactivated human serum. FI bound to bacteria retained its serine protease activity as shown in degradation experiments with 125I-labeled C4b. Since FI requires cofactors for its activity we also investigated the binding of purified cofactors C4BP and FH and found acquisition of both proteins, which retained their activity in FI mediated degradation of C3b and C4b. We propose that FI binding by P. intermedia represents a new mechanism contributing to complement evasion by a Gram-negative bacterial pathogen associated with chronic diseases.
Scene Memory Is More Detailed Than You Think

Observers can store thousands of object images in visual long-term memory with high fidelity, but the fidelity of scene representations in long-term memory is not known. Here, we probed scene-representation fidelity by varying the number of studied exemplars in different scene categories and testing memory using exemplar-level foils. Observers viewed thousands of scenes over 5.5 hr and then completed a series of forced-choice tests. Memory performance was high, even with up to 64 scenes from the same category in memory. Moreover, there was only a 2% decrease in accuracy for each doubling of the number of studied scene exemplars. Surprisingly, this degree of categorical interference was similar to the degree previously demonstrated for object memory. Thus, although scenes have often been defined as a superset of objects, our results suggest that scenes and objects may be entities at a similar level of abstraction in visual long-term memory.
Quantitative imaging of solute transport in an unsaturated and undisturbed soil monolith with 3‐D ERT and TDR

Electrical resistivity tomography (ERT) has proved to be a valuable tool for imaging solute transport processes in the subsurface. However, a quantitative interpretation of corresponding ERT results is constrained by a number of factors. One such factor is the nonuniqueness of the ERT inverse problem if no additional constraints are imposed. In the vadose zone, further problems arise from the general ambiguity of the imaged bulk electrical conductivity in terms of water content and solute concentration. In this study we address these issues in detail for a solute tracer experiment conducted in an undisturbed unsaturated soil monolith where the tracer transport was monitored by means of 3‐D smoothness‐constrained ERT and time domain reflectometry (TDR) measurements. The experimental design allowed the determination of solute tracer concentrations directly from imaged bulk electrical conductivity. Independent TDR data and effluent tracer concentrations provided a “ground truth” for the ERT‐derived apparent convection‐dispersion equation transport parameters. The apparent transport velocity calculated from the ERT results was consistent with that based on TDR data and the sampled effluent, independent of the degree of smoothness imposed in the ERT inversion. On the other hand, the apparent dispersivity calculated from the ERT results was larger than that estimated from TDR data but smaller than that estimated from the sampled effluent, with the magnitude of deviations dependent on the degree of smoothing. Importantly, no mass balance problems were observed in the ERT results. We believe that this is largely a consequence of the uniform application of the tracer as a front and of the configuration of the electrode array with respect to the main transport direction. In conclusion, the study demonstrates that ERT can yield unprecedented quantitative information about local‐ and column‐scale solute transport characteristics in natural soils.
Study on test generation and diagnosis optimization algorithm for wiring interconnects

With the increasing number of chips with boundary-scan structure, boundary-scan technique becomes a new and effective way of test and design-for-testability for VLSI circuits. Because of the serial nature of the boundary scan tests, it is important to minimize the test size while maintaining diagnosability. This paper analyzes the advantages and deficiencies of traditional test generation and diagnosis algorithm for wiring interconnects. In addition, we present an optimal algorithm, Equal-Weight & Min-Distance Algorithm. It achieves a good trade-off between test compactness and diagnosability. It can effectively reduce test time and improve fault diagnosability.
Layered routing algorithm for sustainable MANET operation

In this paper a routing algorithm for MANETs is presented, based on the formation of servicing zones and determination of nodes in these zones as default gateways. The idea behind this approach is to gain power efficiency and sustainability of the network. The proposed approach reduces the overall number of broadcasts in the network and ensures a reliable and energy efficient connection, by balancing the load among the nodes. The algorithm could be considered as a hybrid type of routing mechanism, incorporating multipath hop-by-hop distributed routing. We apply a time slot based self-organizing and self-routing approach by the application of a network model with universal basic node properties. For each node we define two functional and one generic property. The algorithm has the logic of non-cooperative routing based on the evaluation of the defined basic properties of the nodes. The major advantages of the algorithm are related to the complexity and the reduced overall routing cost, especially in higher density networks.
A novel segmentation correction method for fusion of vision and laser

In this paper, a method is proposed to solve the displacements and distortions, which are caused by inaccurate calibration in the low-level fusion. Compared with existing methods, the proposed method does not rely on any specified environmental feature and can be applied to a variety of scenarios. To implement it, twice clustering processes are applied to segment the input point cloud, and an iterative closest point (ICP) algorithm is used to iterate and correct the corresponding partitions. Furthermore, we also quantify an index to evaluate the result of correction and provide some simplified constraints to improve the measurement accuracy. Finally, the effectiveness of the proposed methods is verified by the result of 3D reconstruction.
FPGA Based Intelligent Co-operative Processor in Memory Architecture

In a continuing effort to improve computer system performance, Processor-In-Memory (PIM) architecture has emerged as an alternative solution. PIM architecture incorporates computational units and control logic directly on the memory to provide immediate access to the data. To exploit the potential benefits of PIM, a concept of Co-operative Intelligent Memory (CIM) was developed by the intelligent system group of University of Hertfordshire, based on the previously developed Co-operative Pseudo Intelligent Memory (CPIM). This paper provides an overview on previous works (CPIM, CIM) and realization of CPIM over two scenarios, cumulative successive addition, and non-cumulative successive addition, using Nexar 2004 EDS tool as a design environment to target device (SPARTAN II, XC2S300E-6PQ208C). The performance (speedup) is then measured against an SISD without significant performance acceleration methods to ensure a speedup assessment obtained against base-line architecture.
Rain evaporation and moist patches in tropical boundary layers

Moist patches are areas in the subcloud layer characterized by a positive water vapor anomaly compared to the environment and are considered important in triggering new convective cells. A correct understanding of the origin of the water vapor in these patches is, thus, essential to improving existing convective parameterizations. Recent studies have addressed this problem and have shown that contrary to what was previously thought, the main source of water vapor in moist patches are surface latent heat fluxes, instead of rain evaporation. This manuscript offers a different perspective to the topic, focusing on the origin only of the water vapor that makes moist patches anomalously moist when compared to the environment. It is found that near the surface, rain evaporation contributes half as much as latent heat fluxes, implying that a parameterization of the thermodynamic forcing should be more sensitive to environmental variables, like relative humidity, than recently suggested.