Miracle-dz/UniFAR-FTUs huggingface dataset:
How Can a Touch-Screen Based Visual Discrimination Help to Better Characterize Rodent Models of Schizophrenia?

Existing in many forms, two of the most commonly used cognition paradigms in the rodent are rule acquisition and reversal learning (e.g. swim mazes, operant tasks, T-mazes). Despite the wide spread use of these simple assays, interpretation is often not straightforward and important controls are commonly over looked. For example, when acquiring a simple discrimination (a response to stimulus “A” is rewarded, whereas a response to stimulus “B” is not), necessary for many forms of operant learning, the animal must learn several concepts. Rodents must (1) learn to distinguish the stimuli, (2) learn that only one of the stimuli is associated with reward, (3) and that earning a reward is dependent upon their own behavior. Accordingly an impairment in task acquisition could be caused by a failure in any one of these processes or other non-specific effects, like alterations in motoric abilities. Reversal learning has similar, but unique, difficulties in interpretation. In rodents, reversal learning paradigms can take days, and are often split into three distinct phases. Early reversal is the first stage of the process, occurring immediately after the switch in rule contingencies associated with reward. The rodent’s behavior is capable of earning a reward, but its current behavior is not; it must learn the new contingency. Until this occurs, the animal will consistently perform below chance. As it comes to understand this change, the animal will begin to experiment with other responses to see if they earn a reward (middle reversal), and their accuracy will begin to increase towards chance level performance. Finally, as the animal learns that it can still earn a reward, it must learn which stimuli is now associated with a reward, a stage called late reversal. Depending upon the stage reversal learning does require different neurobiological and psychological processes (for example see Bussey et al., 1997, Chudasama and Robbins, 2003), some of which may overlap with acquisition learning. Considering the numerous processes involved in acquisition of a discrimination, and the overlap between reversal learning and acquisition of a discrimination, it is important to understand the psychological process impaired, not just the stage impaired (i.e. visuo-perceptual changes will impair acquisition, but this does not mean the animal is impaired at learning).
Using simplified meshes for crude registration of two partially overlapping range images

We present an efficient algorithm for crude registration of two partially overlapping range images. The central focus of our work is how to filter out the wrong pairs efficiently in order to reduce the search space. Motivated by the availability of robust and efficient mesh simplification algorithms, such as the QSLIM software package, which preserve the main characteristics of the surface shape, we propose to find a good initial transformation estimate on the basis of the vertices of simplified meshes, instead of the original dense sets of range data. Promising results, that make the iterative closest point matching procedure converges to a correct final alignment, are provided.
The Application of Telepresence and Virtual Reality to Subsea Exploration

The operation of remote science exploration vehicles ben-eﬁts greatly from the application of advanced telepresence and virtual reality operator interfaces. Telepresence, or the projection of the human sensory apparatus into a remote location, can provide scientists with a much greater intuitive understanding of the environment in which they are working than simple camera-display systems. Likewise virtual reality, or the use of highly interactive three-dimensional computer graphics, can both enhance an operator’s situational awareness of an environment and also compensate (to some degree) for low bandwidth and/or long time delays in the communications channel between the operator and the vehicle. These advanced operator interfaces are important for terrestrial science and exploration applications, and are critical for missions involving the exploration of other planetary surfaces, such as on Mars. The undersea environment provides an excellent terrestrial analog to science exploration and operations on another planetary surface.
Efficient network formation by distributed reinforcement

We consider the problem of efficient network formation in a distributed fashion. Network formation is modeled as an evolutionary process, where agents can form and sever unidirectional links and derive direct and indirect benefits from these links. We formulate and analyze an evolutionary model in which each agent¿s choices depend on its own previous links and benefits, and link selections are subject to random perturbations. Agents reinforce the establishment of a link if it was beneficial in the past, and suppress it otherwise. We illustrate the flexibility of the model to incorporate various design criteria, including dynamic cost functions that reflect link establishment and maintenance, and distance-dependent benefit functions.We show that the evolutionary process assigns positive probability to the emergence of multiple stable configurations (i.e., strict Nash networks), which need not emerge under alternative processes such as best-reply dynamics. We analyze the specific case of so-called frictionless benefit flow, and show that a single agent can reinforce the emergence of an efficient network through an enhanced evolutionary process known as dynamic reinforcement.
Transforming Growth Factor B1 Stimulated DNA Synthesis in the Granulosa Cells of Preantral Follicles: Negative Interaction with Epidermal Growth Factor1

Abstract EGF or TGFB1 alone stimulates but together attenuate granulosa cell DNA synthesis. Intact preantral follicles from hamsters were cultured with TGFB1, EGF, or both to reveal the mechanisms of such unique regulation. Follicular CCND2 (also known as cyclin D2), CDKN1B (also known as p27kip1), and the involvement of appropriate signaling intermediaries and kinases were examined. TGFB1, acting via SMAD2 and SMAD3, antagonized the degradation of CCND2 protein by blocking its phosphorylation. In contrast, TGFB1 supported CDKN1B degradation by involving MAPK14 (also known as p38 Map Kinase) and PKC, resulting in CDK4 activation and DNA synthesis. EGF via MAPK3/1 maintained functional levels of CCND2 through CCND2 synthesis as well as degradation. EGF and TGFB1 together inhibited CDK4 activation and DNA synthesis. EGF attenuated TGFB1 stimulated phosphorylation of SMAD3, TGFB1-induced activation of MAPK14 and PKC, and TGFB1 suppression of CCND2 degradation. In contrast, TGFB1 suppressed EGF-induced increase in CCND2 mRNA levels. The final outcome was CCND2 degradation without replenishment and decreased activities of MAPK14 and PKC leading to suppression of CDK4 activation. The results indicate that each growth factor involves a separate mechanism to maintain an effective level of CCND2 in granulosa cells for the activation of CDK4 and induction of DNA synthesis. However, their simultaneous action is inhibitory to follicular DNA synthesis because they counteract each other's activity by interfering at specific sites. Because both EGF and TGFB1 are present in granulosa cells, this mechanism may explain how their effects are temporally modulated for granulosa cell proliferation and folliculogenesis.
Molecular and Structural Changes in Chlamydomonas under Limiting CO2 (A Possible Mitochondrial Role in Adaptation)

When Chlamydomonas reinhardtii cells are transferred to limiting CO2, one response is the induction of a CO2-concentrating mechanism (CCM) with components that remain to be identified. Characterization of membrane-associated proteins induced by this transfer revealed that synthesis of the 21-kD protein (LIP-21) was regulated at the level of translatable message abundance and correlated well with the induction of CCM activity. Phase partitioning of LIP-21 and the previously characterized LIP-36 showed that both appeared to be peripherally associated with membranes, which limits their potential to function as transporters of inorganic carbon. Ultrastructural changes that occur when cells are transferred to limiting CO2 were also examined to help form a model for the CCM or other aspects of adaptation to limiting CO2. Changes were observed in vacuolization, starch distribution, and mitochondrial location. The mitochondria relocated from within the cup of the chloroplast to between the chloroplast envelope and the plasma membrane. In addition, immunogold labeling demonstrated that LIP-21 was localized specifically to the peripheral mitochondria. These data suggest that mitochondria, although not previously incorporated into models for the CCM, may play an important role in the cell's adaptation to limiting CO2.
A hybrid method based on genetic algorithm, self-organised feature map, and support vector machine for better network anomaly detection

Anomaly-based network intrusion detection techniques are a valuable technology to shield our systems and networks against the malicious activities. Anomaly detection is done by soft margin Support Vector Machine(SVM), which classify the input into any one of the label (normal and anomalous) category with respect to its anomalous behavior. SVM gives much better classification, out of wide variety of class discrimination algorithms which deals with huge collection of data. Here genetic algorithm (GA) and self-organised feature map (SOFM) are used to enhance the feature and information extraction from a huge dataset similar to KDD99. GA gives us the most prominent features contributing to the anomalous behaviour of a connection and SOFM helps to identify similar groups from the dataset by using the similarity metric. These two machine learning algorithms help to reduce the volume of dataset and features to train SVM. The proposed framework GSS (GA-SOFM-SVM) has 10% increase in detection rate and 50% reduction in false positive and false negative rate compared to soft margin SVM.
Highly Selective Microstrip Bandpass Filters in Ka-Band

Highly selective microstrip bandpass filters in Ka-band are developed by suitably inserting the attenuation poles in an edge-coupled structure. The attenuation poles at the high and low passband edges are introduced by adding a capacitively coupled gap and tapped open stubs in the conventional microstrip edge-coupled filter. In this study, the improved filters with center frequencies at 28 GHz and 38 GHz are fabricated on Teflon and Al2O3 substrates. Both filters have better selectivity and occupy the same area when compared with the conventional edge-coupled filter.
Anticipating Dormant Functionality in Malware: A Semantics Based Approach

One of the challenges in malware analysis has been finding out the dormant functionality of the malware. Requirement of manual analysis along with code obfuscation and encryption rules out static analysis as it may not be effective and scalable in the face of continuously rising number of malware produced daily. Dynamic analysis on the other hand relies on the exhibited behavior of the malware, which may not exhibit the true functionality of the malware, as malware may sense the analysis environment or performs differently under different circumstances (User interaction, logic bombs and specific target etc). Finding out the complete function of a malware in case of Advanced Persistent Threat (APT) becomes imperative, to know the potential target of the APT and techniques being used by the malware authors, so that appropriate defense can be mounted proactively. Various approaches have been used to extract the dormant functionality of malware such as multiple runs and multipath or forced execution, but they have not been effective due to rigorous and exponential increase in number of paths required to be analyzed and thus are not scalable. They are costlier in terms of processing and are significantly constrained to analyze large numbers of malware samples being found daily. Structural attributes of the disassembled code may be analyzed to predict the dormant behavior but same functionality may be implemented using different structures and this approach will not be effective then. Semantics based formal techniques have a potential to identify and classify both hidden and exhibited malware behavior as they refer to a high level view of the malware attributes and behavior and are not dependent upon signature based models and even analyze new and unseen malware effectively. This paper presents a review of all efforts at adopting semantics based models for automated malware analysis and defines future work directions of the research.
Ultra-Low-Energy Mixed-Signal IC Implementing Encoded Neural Networks

Encoded Neural Networks (ENNs) associate low-complexity algorithm with a storage capacity much larger than Hopfield Neural Networks (HNNs) for the same number of nodes. Moreover, they have a lower density than HNNs in terms of connections, allowing a low-complexity circuit integration. The implementation of such a network requires low-complexity elements to take complete advantage of the assets of the model. This paper proposes an analog implementation of the ENNs. It is shown that this type of implementation is suitable for building network of thousands of nodes. To validate the proposed implementation, a prototype ENN of 30 computation nodes is designed, fabricated and tested on-chip for the ST 65-nm 1-V supply complementary metal-oxide silicon (CMOS) process. The circuit shows decoding performance similar to that of the theoretical model, and decodes a message in 58 ns. Moreover, the entire network occupies a silicon area of 16470 μm2 and consumes 145 μW, yielding a measured energy consumption per synaptic event per computation node of 68 fJ.
PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows

Computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Thus, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation and data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.
Nutrition and Bone: It is More than Calcium and Vitamin D

Unlike pharmacological agents that are taken for proscribed periods of time, food and nutrient intakes have the possibility of affecting bone health over the entire lifespan. While deficiencies or excesses of individual nutrients have been shown to affect bone, it is likely that individual foods or dietary patterns have important effects related to skeletal health. While biochemical mechanisms exist to relate a deficiency of vitamin K to altered bone metabolism, clinical trials related to supplementation of this nutrient have been confusing. It is likely that these disparate results are related to the fact that interactions of nutrients have not been considered or the possibility that suboptimal nutrient status is a marker of poor nutritional status. Vitamin A excess has been postulated to be related to high fracture risk; however, it is likely that retinol is not the best marker for the proposed interaction. Altering whole food patterns, such as the Dietary Approaches to Stop Hypertension diet, have demonstrated beneficial effects on bone metabolism. Individuals who select some vegetarian patterns may need to consider supplementation with nutrients such as calcium and protein. Future studies should center on whole food and dietary patterns and their relationship to bone metabolism and fracture risk.
Transient Behavior Study of Thermoelectric Generators through an Electro-thermal Model Using SPICE

A thermoelectric generator (TEG) usually works in dynamic operating conditions due to the time change, in real applications, of the electric load and hot or cold temperatures. Thus understanding transient thermal and electrical behavior of the device, besides the steady-state behavior, is important in order to investigate the global device performance. The major objective of this work is to describe the transient behavior of TEG operating in high temperature environments through a SPICE model based on an electrothermal analogy. The SPICE model presented is derived from a one dimensional (1-D) heat transfer differential equation. An important feature of the model is its ability to calculate the temperature profile taking the real temperature dependence of the materials properties into account. This feature is essential in simulating TEG exposed to a large temperature difference. In combination with considering the finite heat transfer rate at the interface between TEG and thermal ambient, the model is able to reflect the thermo-electric coupled multi-field system effect of TEG. A test rig is developed for verifying the proposed model. Commercially available TEG is tested with respect to stabilizing time under sharply changed electric load. The preliminary results of experiments and modeling are analyzed. It is expected that the model presented can assist, not only in the optimal design of TEG itself, but also in the evaluation of the whole energy system
Role of Features and Second-order Spatial Relations in Face Discrimination, Face Recognition, and Individual Face Skills: Behavioral and Functional Magnetic Resonance Imaging Data

We compared the contribution of featural information and second-order spatial relations (spacing between features) in face processing. A fully factorial design has the same or different features (eyes, mouth, and nose) across two successive displays, whereas, orthogonally, the second-order spatial relations between those features were the same or different. The range of such changes matched the possibilities within the population of natural face images. Behaviorally, we found that judging whether two successive faces depicted the same person was dominated by features, although second-order spatial relations also contributed. This influence of spatial relations correlated, for individual subjects, with their skill at recognition of faces (as famous, or as previously exposed) in separate behavioral tests. Using the same repetition design in functional magnetic resonance imaging, we found feature-dependent effects in the lateral occipital and right fusiform regions. In addition, there were spatial relation effects in the bilateral inferior occipital gyrus and right fusiform that correlated with individual differences in (separately measured) behavioral sensitivity to those changes. The results suggest that featural and second-order spatial relation aspects of faces make distinct contributions to behavioral discrimination and recognition, with features contributing most to face discrimination and second-order spatial relational aspects correlating best with recognition skills. Distinct neural responses to these aspects were found with functional magnetic resonance imaging, particularly when individual skills were taken into account for the impact of second-order spatial relations.
Field-portable reflection and transmission microscopy based on lensless holography

We demonstrate a lensfree dual-mode holographic microscope that can image specimens in both transmission and reflection geometries using in-line transmission and off-axis reflection holography, respectively. This field-portable dual-mode holographic microscope has a weight of ~200 g with dimensions of 15 x 5.5 x 5cm, where a laser source is powered by two batteries. Based on digital in-line holography, our transmission microscope achieves a sub-pixel lateral resolution of ≤2 µm over a wide field-of-view (FOV) of ~24 mm2 due to its unit fringe magnification geometry. Despite its simplicity and ease of operation, in-line transmission geometry is not suitable to image dense or connected objects such as tissue slides since the reference beam gets distorted causing severe aberrations in reconstruction of such objects. To mitigate this challenge, on the same cost-effective and field-portable assembly we built a lensless reflection mode microscope based on digital off-axis holography where a beam-splitter is used to interfere a tilted reference wave with the reflected light from the object surface, creating an off-axis hologram of the specimens on a CMOS sensor-chip. As a result of the reduced space-bandwidth product of the off-axis geometry compared to its in-line counterpart, the imaging FOV of our reflection mode is reduced to ~9 mm2, while still achieving a similar sub-pixel resolution of ≤2 µm. We tested the performance of this compact dual-mode microscopy unit by imaging a US-air force resolution test target, various micro-particles as well as a histopathology slide corresponding to skin tissue. Due to its compact, cost-effective, and lightweight design, this dual-mode lensless holographic microscope might especially be useful for field-use or for conducting microscopic analysis in resource-poor settings.
A generalized reduced fluid model with finite ion-gyroradius effects

Reduced fluid models have become important tools for studying the nonlinear dynamics of plasma in a large aspect‐ratio tokamak. A self‐consistent nonlinear reduced fluid model, with finite ion‐gyroradius effects is presented. The model is distinctive in being correct to O(( ρi/a)2) and in satisfying an exact, relatively simple energy conservation law.
A novel high-voltage half-bridge converter with phase-shifted active rectifier

The half-bridge converter with phase-shifted active rectifier allows us to avoid drawbacks of the traditional hard-switched half-bridge converter with a diode rectifier, such as high semiconductor losses and parasitic oscillations in the inverter. This paper introduces a novel improved control algorithm for a full-bridge phase-shifted active rectifier, allowing reduction of the energy circulation during its operation. The advantages of the algorithm are verified with a small-scale converter prototype. The experimental results were found in full accordance with expected waveforms.
Quasi-Monte Carlo Global Light Tracing with Inﬁnite Number of Rays

: The paper presents an efﬁcient method to solve the general rendering equation, using a combined ﬁnite element and quasi-random walk approach. Applying ﬁnite element techniques, the surfaces are decomposed into planar patches that are assumed to have position independent, but not direction independent (that is non-diffuse) radiance. The direction dependent radiance function is then computed by quasi-random walk. Since quasi-Monte Carlo quadrature is applied here to an integrand of ﬁnite variation, this method can take advantage of the superior convergence of quasi-Monte Carlo integration