Miracle-dz/UniFAR-FTUs huggingface dataset:
A Combined Approach for Ab Initio Construction of Low Resolution Protein Tertiary Structures from Sequence

An approach to construct low resolution models of protein structure from sequence information using a combination of different methodologies is described. All possible compact self-avoiding C alpha conformations (approximately 10 million) of a small protein chain were exhaustively enumerated on a tetrahedral lattice. The best scoring 10,000 conformations were selected using a lattice-based scoring function. All-atom structures were then generated by fitting an off-lattice four-state phi/psi model to the lattice conformations, using idealised helix and sheet values based on predicted secondary structure. The all-atom conformations were minimised using ENCAD and scored using a second hybrid scoring function. The best scoring 50, 100, and 500 conformations were input to a consensus-based distance geometry routine that used constraints from each the conformation sets and produced a single structure for each set (total of three). Secondary structures were again fitted to the three structures, and the resulting structures were minimised and scored. The lowest scoring conformation was taken to be the "correct" answer. The results of application of this method to twelve proteins are presented.
The Emerging Role of The Eosinophil and Its Measurement in Chronic Cough

Although the aetiology of chronic cough in guidelines is clearly stated as asthma and related syndromes, gastro-oesophageal reflux disease (GORD), and upper airways disease, the inflammatory mechanisms underlying these conditions differ. Recent studies on asthma have increasingly focused on its molecular phenotypes instead of clinical characteristics. Here, we proposed the hypothesis that divides cough into two groups; the eosinophilic and neutrophilic. This division will enhance our ability to recognise the type of airway inflammation which, as a consequence will lead us to more targeted and personalized treatment approaches.
A control method for steering individual particles inside liquid droplets actuated by electrowetting.

An algorithm is developed that allows steering of individual particles inside electrowetting systems by control of actuators already present in these systems. Particles are steered by creating time varying flow fields that carry the particles along their desired trajectories. Results are demonstrated using an experimentally validated model developed in ref. We show that the current UCLA electro-wetting-on-dielectric (EWOD) system contains enough control authority to steer a single particle along arbitrary trajectories and to steer two particles, at once, along simple paths. Particle steering is limited by contact angle saturation and by the small number of actuators that are available to actuate the flow in practical electrowetting systems.
Human dendritic cells subsets as targets and vectors for therapy

The skin immune system includes a complex network of dendritic cells (DCs). In addition to generating cellular and humoral immunity against pathogens, skin DCs are involved in tolerogenic mechanisms that maintain immune homeostasis and in pathogenic chronic inflammation in which immune responses are unrestrained. Harnessing DC function by directly targeting DC‐derived molecules or by selectively modulating DC subsets is a novel strategy for ameliorating inflammatory diseases. In this short review, we discuss recent advances in understanding the functional specialization of skin DCs and the potential implication for future DC‐based therapeutic strategies.
ARTransform : Visualization of Three Dimensional Geometric Transformations in Augmented Reality Environment

Three dimensional (3D) geometric transformations are basic and important skills when working in computer graphics related areas. Traditional ways in learning the skills include forcing the 3D results to be demonstrated on 2D output media thus challenge the imaginations of the viewers. This paper presents ARTransform – an augmented reality (AR) application for 3D geometric transformations analysis. ARTransform animates 3D geometric transformations in real environment, which enables the viewers to move around the transforming objects and make closer observations. Graphical user interface control panels are developed to provide userspecified geometric transformations and animations. ARTransform adopts the concept of keeping the learning curve gentle to enable the viewers to spend more time in transformation analysis, thus, user interaction is achieved by conventional input devices via keyboard and mouse. ARTransform is still at its infancy and much work remains to be done. User-test on the application will be carried out when more features are added to the application.
Representation without taxation: what makes GUI good

In the proposed work, research in cognitive science and display-based HCI is synthesized and brought to bear on the question of "what makes GUI good? ". A two-phase approach is outlined. The empirical phase will build upon a foundation laid by display-based HCI research. The computational modeling phase will be informed by the empirical phase and previous modeling efforts. The primary goal is to be able to explicate conditions under which a user will rely on external display components vs. internal knowledge structures to control task performance.
SDCTune: A model for predicting the SDC proneness of an application for configurable protection

Silent Data Corruption (SDC) is a serious reliability issue in many domains, including embedded systems. However, current protection techniques are brittle, and do not allow programmers to trade off performance for SDC coverage. Further, many of them require tens of thousands of fault injection experiments, which are highly time-intensive. In this paper, we propose an empirical model to predict the SDC proneness of a program's data called SDCTune. SDCTune is based on static and dynamic features of the program alone, and does not require fault injections to be performed. We then develop an algorithm using SDCTune to selectively protect the most SDC-prone data in the program subject to a given performance overhead bound. Our results show that our technique is highly accurate at predicting the relative SDC rate of an application, and outperforms full duplication by a factor of 0.83 to 1.87x in efficiency of detection (i.e., ratio of SDC coverage provided to performance overhead).
Architecture for computer vision application development within the HORUS system

An integrated program development environment for computer vision tasks is presented. The first component of the system is concerned with the visualization of 2-D image data. This is done in an object-oriented manner. Programming of the visualization process is achieved by arranging the representations of iconic data in an interactively customizable hierarchy that establishes an intuitive flow of messages between data representations seen as objects. The visualization objects, called displays, are designed for different levels of abstraction, starting from direct iconic representation down to numerical features, depending on the information needed. Two types of messages are passed between these displays (update and result messages), which yield a clear and intuitive semantics. The second component of the system is an interactive tool for rapid program development. It helps the user in selecting appropriate operators in many ways. For example, the system provides context sensitive selection of possible alternative operators as well as suitable successors and required predecessors. For the task of choosing appropriate parameters several alternatives exist. For example, the system provides default values as well as lists of useful values for all parameters of each operator. To achieve this, a knowledge base containing facts about the operators and their parameters is used. Second, through the tight coupling of the two system components, parameters can be determined quickly by data exploration within the visualization component.
Shrinkage Properties of Wool Treated with Ionic Liquid and Chitosan Biopolymer

In order to improve the shrinkage resistance of wool fabrics, a new method that combine ionic liquid and chitosan was researched in this paper. Wool fabric was first pretreated with 1 - butyl - 3 - methyl bromination imidazole([Bmim]Br）, and subsequently was treated with chitosan. Pretreatment temperature and time, and chitosan concentration of post-treatment were studied in this paper. Results showed that wool fabrics treated with [Bmim]Br at 80°C for 2 hours and post-treated in 1.0% chitosan acetic acid solution exhibit good shrinkage resistance. In addition, SEM images of ionic liquid treated wool fiber indicates that the scales have been destroyed, and the surface is covered with a layer of film after post-treated with chitosan.
A Novel Method for Intelligence of Sensors Modeling

For the complexity of the automation system roll on, sensors should have to be more intelligent. Recently, Neural Network is widely used to intelligentize sensors for its well performance on capturing the information of the data. But due to its intrinsic linear character, it doesn't perform well in nonlinear data processing. In this paper, RNN with Kernel Principal Component Analysis (KPCA) and Principal Component Analysis (PCA) as the feature extraction is introduced in as comparison. And then an experimental system is set up with pressure sensor. By examining the data of the example, it is shown that the proposed methods can both achieve good performance comparing with NN method. And the KPCA method performs better than the PCA method.
Financial Reporting of Intellectual Capital and Company's Performance in Indian Information Technology Industry

This paper examines the relationship between Financial Reporting of Intellectual Capital and Companyâ€™s Performances in Indian Information Technology Industry. For the purpose of this study, sixty companies listed on NSE were taken for a period of 1999-00 to 2008-09. Value Added Intellectual Co-efficient (VAICTM) method developed by Pulic (1998) was used for the analysis of the data. The present study uses VAICTM model and regression equation for the evaluation of intellectual capital and their relationship with productivity, profitability, and market valuation of the companies. The result of the study supports the hypothesis that profitability of the company can be explained by the intellectual capital. However, there is no significant association of intellectual capital with productivity and market capitalization of the companies for the selected time period of year 1999-00 to 2008-09.
Subjectively Interesting Alternative Clusters

We deploy a recently proposed framework for mining subjectively interesting patterns from data [3] to the problem of clustering, where patterns are clusters in the data. This framework outlines how subjective interestingness of patterns (here, clusters) can be quantified using sound information theoretic concepts. We demonstrate how it motivates a new objective function quantifying the interestingness of (a set of) clusters, automatically accounting for a user's prior beliefs and for redundancies between the clusters. Directly searching for the optimal set of clusters defined in this way is hard. However, the optimization problem can be solved to a provably good approximation if clusters are generated iteratively, paralleling the iterative data mining setting discussed in [3]. In this iterative scheme, each subsequent cluster is maximally interesting given the previously generated ones, automatically trading off interestingness with non-redundancy. Thus, this implementation of the clustering approach can be regarded as a method for alternative clustering. Although generating each cluster in an iterative fashion is computationally hard as well, we develop an approximation technique similar to spectral clustering algorithms. We end with a few visual demonstrations of the alternative clustering approach to artificial datasets.
PCTCP: per-circuit TCP-over-IPsec transport for anonymous communication overlay networks

Recently, there have been several research efforts to design a transport layer that meets the security requirements of anonymous communications while maximizing the network performance experienced by users. In this work, we argue that existing proposals suffer from several performance and deployment issues and we introduce PCTCP, a novel anonymous communication transport design for overlay networks that addresses the shortcomings of the previous proposals. In PCTCP, every overlay path, or circuit, is assigned a separate kernel-level TCP connection that is protected by IPsec, the standard security layer for IP. To evaluate our work, we focus on the Tor network, the most popular low-latency anonymity network, which is notorious for its performance problems that can potentially deter its wider adoption and thereby impact its anonymity. Previous research showed that the current transport layer design of Tor, in which several circuits are multiplexed in a single TCP connection between any pair of routers, is a key contributor to Tor's performance issues. We implemented, experimentally evaluated, and confirmed the potential gains provided by PCTCP in an isolated testbed and on the live Tor network. We ascertained that significant performance benefits can be obtained using our approach for web clients, while maintaining the same level of anonymity provided by the network today. Our realistic large-scale experimental evaluation of PCTCP shows improvements of more than 60% for response times and approximately 30% for download times compared to Tor. Finally, PCTCP only requires minimal changes to Tor and is easily deployable, as it does not require all routers on a circuit to upgrade.
Acidianus Brierleyi is the Dominant Thermoacidophile in a Bioleaching Community Processing Chalcopyrite Containing Concentrates at 70°C

Bioleaching test work was performed in continuously operated multi-stage reactor systems at 70°C using a thermophilic culture treating an Aguablanca Ni-Cu concentrate from Spain and a blend of Cu concentrates from Bor, Serbia. The copper in both these concentrates occurs as chalcopyrite and therefore the use of thermophiles was applied, which resulted in copper recoveries of over 95%. Qualitative assessment of the microbial community in the bioreactors was performed by terminal restriction enzyme fragment length polymorphism (T-RFLP) and clone library analysis of the 16S rRNA genes amplified by PCR. T-RFLP analysis revealed that only archaea were present, and that the communities in both the Aguablanca and Bor systems consisted of two different microorganisms. A 16S rRNA gene clone library using DNA from the Aguablanca system was constructed and screened. Again, two archaea were detected in similar relative abundance in the population as found by T-RFLP analyses. The sequences of these two cloned genes revealed that the dominant archaeon (up to 98% of the total archaea detected) was Acidianus brierleyi, and the other was Metallosphaera sedula. Quantitative assessment of the microbial community was performed by Q-PCR and confirmed the dominance of archaea in the system with Acidianus being the dominant strain (98-99% of the total population) and a minor part of the population (1-2%) consisted of Metallosphaera. Additionally, very small amounts of Sulfolobus spp. were detected. This study, along with other recent studies on the diversity of thermoacidophiles involved in the solubilization of copper from chalcopyrite concentrates, revealed that a wider variety of thermoacidophiles are involved in bioprocessing of metal sulfides, and showed that A. brierleyi should be considered an important biomining acidophile.
“Look at this!” learning to guide visual saliency in human-robot interaction

We learn to direct visual saliency in multimodal (i.e., pointing gestures and spoken references) human-robot interaction to highlight and segment arbitrary referent objects. For this purpose, we train a conditional random field to integrate features that reflect low-level visual saliency, the likelihood of salient objects, the probability that a given pixel is pointed at, and - if available - spoken information about the target object's visual appearance. As such, this work integrates several of our ideas and approaches, ranging from multi-scale spectral saliency detection, spatially debiased salient object detection, computational attention in human-robot interaction to learning robust color term models. We demonstrate that this machine learning driven integration outperforms the previously reported results on two datasets, one dataset without and one with spoken object references. In summary, for automatically detected pointing gestures and automatically extracted object references, our approach improves the rate at which the correct object is included in the initial focus of attention by 10.37% in the absence and 25.21% in the presence of spoken target object information.
Injectable Hydrogels for Spinal Cord Repair: A Focus on Swelling and Intraspinal Pressure

Spinal cord injury (SCI) is a devastating condition that leaves patients with limited motor and sensory function at and below the injury site, with little to no hope of a meaningful recovery. Because of their ability to mimic multiple features of central nervous system (CNS) tissues, injectable hydrogels are being developed that can participate as therapeutic agents in reducing secondary injury and in the regeneration of spinal cord tissue. Injectable biomaterials can provide a supportive substrate for tissue regeneration, deliver therapeutic factors, and regulate local tissue physiology. Recent reports of increasing intraspinal pressure after SCI suggest that this physiological change can contribute to injury expansion, also known as secondary injury. Hydrogels contain high water content similar to native tissue, and many hydrogels absorb water and swell after formation. In the case of injectable hydrogels for the spinal cord, this process often occurs in or around the spinal cord tissue, and thus may affect intraspinal pressure. In the future, predictable swelling properties of hydrogels may be leveraged to control intraspinal pressure after injury. Here, we review the physiology of SCI, with special attention to the current clinical and experimental literature, underscoring the importance of controlling intraspinal pressure after SCI. We then discuss how hydrogel fabrication, injection, and swelling can impact intraspinal pressure in the context of developing injectable biomaterials for SCI treatment.
School Start Times for Adolescents

The American Academy of Pediatrics recognizes insufficient sleep in adolescents as an important public health issue that significantly affects the health and safety, as well as the academic success, of our nation’s middle and high school students. Although a number of factors, including biological changes in sleep associated with puberty, lifestyle choices, and academic demands, negatively affect middle and high school students’ ability to obtain sufficient sleep, the evidence strongly implicates earlier school start times (ie, before 8:30 am) as a key modifiable contributor to insufficient sleep, as well as circadian rhythm disruption, in this population. Furthermore, a substantial body of research has now demonstrated that delaying school start times is an effective countermeasure to chronic sleep loss and has a wide range of potential benefits to students with regard to physical and mental health, safety, and academic achievement. The American Academy of Pediatrics strongly supports the efforts of school districts to optimize sleep in students and urges high schools and middle schools to aim for start times that allow students the opportunity to achieve optimal levels of sleep (8.5–9.5 hours) and to improve physical (eg, reduced obesity risk) and mental (eg, lower rates of depression) health, safety (eg, drowsy driving crashes), academic performance, and quality of life.
Thermoelectric and structural properties of high-performance In-based skutterudites for high-temperature energy recovery

The temperature-dependent thermoelectric (TE) and structural properties of n-type filled skutterudites were measured from 300–625 K. In_0. 2Co_4Sb_12, and In_0. 2Ce_0. 05Yb_0. 1Co_4Sb_12 exhibited figure of merit (ZT) values as high as 1.2 at 625 K and In_0. 2Ce_0. 15Co_4Sb_12 showed ZT values of ∼1.4 at 625 K. The room temperature Young’s modulus, Poisson’s ratio, and coefficient of thermal expansion (at 298–673 K) of In_0. 2Ce_0. 15Co_4Sb_12, In_0. 2Co_4Sb_12, and In_0. 2Ce_0. 05Yb_0. 1Co_4Sb_12 compositions were found to be lower than that for the unfilled Co_4Sb_12 skutterudite material. It was discovered that thermal cycling of n-type In_0. 15Ce_0. 1Co_4Sb_12 and In_0. 2Ce_0. 17Co_4Sb_12 materials from 323–673 K (200 cycles) actually increased their power factors by 13.6–36% at 510–525 K without appreciably changing the Young’s modulus or the Poisson’s ratio. The transport and structural properties characterized in this work are critical to transitioning these materials into operating TE devices and systems.
The morphology of layer-by-layer films of polymer/polyelectrolyte studied by atomic force microscopy

Layer-by-layer (LBL) films of a semiconducting polymer (POMA) alternated with a polyelectrolyte (PVS), adsorbed onto silicon oxide, mica, ITO/glass, Au/Cr/glass, hydrophilic and hydrophobic glass were studied by atomic force microscopy (AFM). The samples were characterized LBL with the AFM operating in the contact, friction and tapping modes, which allowed us to determine their morphological surface properties such as roughness, mean grain size, grain boundaries and power spectrum density. Their film thickness was measured by AFM using the tip as a scraping tool. Surface roughness increases with the number of bilayers until a constant value is reached. This is in agreement with the observed increase in the adsorbed amount (per layer) of POMA as the number of bilayers is increased, which also saturates after several bilayers. It is shown that the 3D growth behaviour indicates a similar microscopic mechanism for all systems under study, pointing to a stochastic growth process of the Eden model type, but strongly influenced by initial roughness and water affinity of the virgin substrates. The crystalline or amorphous nature of the substrates does not seem to influence the growth process.
Tracking of Nonholonomic Control Systems Based on Visual Servoing Feedback

This paper investigated the visual servoing tracking of nonholonomic mobile robots. Nonholonomic kinematic systems with visual feedback are uncertain and more involved in comparison with common kinematic systems. Barbalat theorem and two-step techniques were exploited to craft a robust controller that enables the mobile robot image pose and the orientation tracking despite the lack of depth information and the lack of precise visual parameters. The most interesting feature of this paper is that the problem was discussed in the image frame and the inertial frame, which made the problem easy and useful. The convergence of the error system by using the proposed method was rigorously proved. The simulation was given to show the effectiveness of the presented controllers.