Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanism of sinus bradycardia in carriers of the 1795insD mutation in the SCN5A gene

The SCN5A gene encodes the pore-forming α-subunit of the cardiac fast sodium channel (INa channel). Carriers of the 1795insD mutation in SCN5A show sinus bradycardia, with a mean heart rate of 70 bpm in mutation carriers vs. 77 bpm in non-carriers from the same family (lowest heart rate 41 vs. 47 bpm). We assessed the mechanism by which the 1795insD mutation causes sinus bradycardia by incorporating the mutation-induced changes in INa into the comprehensive computational model of a single human sinoatrial node cell that was recently developed by Fabbri et al. The 1795insD mutation reduced the beating rate of the model cell from 74 to 69 bpm (from 49 to 43 bpm in the presence of 20 nM acetylcholine). The mutation-induced persistent INa per se resulted in a large increase in beating rate. This gain-of-function effect was almost completely counteracted by the loss-of-function effect of the reduction in INa amplitude. The further loss-of-function effect of the shifts in (in)activation resulted in an overall loss-of-function effect of the 1795insD mutation. We conclude that the experimentally identified mutation-induced changes in INa can explain the clinically observed sinus bradycardia. Furthermore, we conclude that the Fabbri et al. model may prove a useful tool in understanding cardiac pacemaker activity in human.
An Improved Closed-Loop Switched Capacitor Capacitance-to-Frequency Converter and Its Evaluation

This paper presents a new capacitance-to-frequency converter (CFC) with high linearity and accuracy. In the CFC, the capacitance-to-frequency conversion is achieved using a negative feedback mechanism. In the feedback, the output frequency controls the charge injected by a switched-capacitor (SC) network such that the difference error is automatically minimized. The feedback mechanism ensures that the final output is insensitive to the nonlinearity errors of the units employed to realize the forward path, namely, a capacitance-to-voltage converter and a voltage-to-frequency converter. A simple error correction mechanism employed ensures that the digital output obtained is insensitive to the number of nonideal circuit parameters. The proposed converter uses a dc reference voltage for the excitation and helps to achieve high accuracy. A prototype of the improved CFC has been developed and tested for sensor capacitance <inline-formula> <tex-math notation="LaTeX">$C_{x}$ </tex-math></inline-formula> in the range of 5–25 pF. A prototype of the conventional open-loop CFC was also developed, and the linearity has been evaluated. The proposed closed-loop approach has lower (0.1%) nonlinearity error compared to the conventional CFC (0.8%). This improvement is achieved without the use of any error-compensating schemes, and hence the complexity level of the system remains the same as that of any typical CFC. The response time of the CFC designed is about <inline-formula> <tex-math notation="LaTeX">$400~\mu \text{s}$ </tex-math></inline-formula> for a 5–25 pF step change in <inline-formula> <tex-math notation="LaTeX">$C_{x}$ </tex-math></inline-formula>. The results obtained from the prototype CFC confirmed its usefulness.
Constructing lightweight and flexible pipelines using Plugin-Based Microbiome Analysis (PluMA)

Motivation Software pipelines have become almost standardized tools for microbiome analysis. Currently many pipelines are available, often sharing some of the same algorithms as stages. This is largely because each pipeline has its own source language and file formats, making it typically more economical to reinvent the wheel than to learn and interface to an existing package. We present Plugin-Based Microbiome Analysis (PluMA), which addresses this problem by providing a lightweight back end that can be infinitely extended using dynamically loaded plugin extensions. These can be written in one of many compiled or scripting languages. With PluMA and its online plugin pool, algorithm designers can easily plug-and-play existing pipeline stages with no knowledge of their underlying implementation, allowing them to efficiently test a new algorithm alongside these stages or combine them in a new and creative way. Results We demonstrate the usefulness of PluMA through an example pipeline (P-M16S) that expands an obesity study involving gut microbiome samples from the mouse, by integrating multiple plugins using a variety of source languages and file formats, and producing new results. Availability and implementation Links to github repositories for the PluMA source code and P-M16S, in addition to the plugin pool are available from the Bioinformatics Research Group (BioRG) at: http://biorg.cis. fiu.edu/pluma.
The algorithm to generate color point-cloud with the registration between panoramic image and laser point-cloud

Laser point cloud contains only intensity information and it is necessary for visual interpretation to obtain color information from other sensor. Cameras can provide texture, color, and other information of the corresponding object. Points with color information of corresponding pixels in digital images can be used to generate color point-cloud and is conducive to the visualization, classification and modeling of point-cloud. Different types of digital cameras are used in different Mobile Measurement Systems (MMS). the principles and processes for generating color point-cloud in different systems are not the same. The most prominent feature of the panoramic images is the field of 360 degrees view angle in the horizontal direction, to obtain the image information around the camera as much as possible. In this paper, we introduce a method to generate color point-cloud with panoramic image and laser point-cloud, and deduce the equation of the correspondence between points in panoramic images and laser point-clouds. The fusion of panoramic image and laser point-cloud is according to the collinear principle of three points (the center of the omnidirectional multi-camera system, the image point on the sphere, the object point). The experimental results show that the proposed algorithm and formulae in this paper are correct.
Electrical Unmanned Vehicle Architecture for Precision Farming Applications

This paper describes the development of a control architecture for electrical unmanned vehicles aimed at precision farming applications. The whole architecture is introduced, with particular attention to draw the highlights of the design process, and preliminary experimental results are reported. The design of ROBI', a prototype small-sized electrical mobile manipulator whose aim is to support development and testing of new architectures and control algorithms, is introduced as well.
A novel reduction strategy of standby power loss in the multi-oscillated current resonant DC-DC converter considering acoustic noise compatibility

The current resonant type DC-DC converter employs generally the pulse frequency modulation and its magnetizing inductance is set relatively low. For this reason, the magnetizing current through the converter causes a power loss under the light load condition. To solve this problem, a multi-oscillated current resonant type DC-DC converter has been proposed and then the advantage of its control method has been clarified, which can reduce power loss under light load condition and keep low switching noise. This paper deals with a novel reduction strategy of standby power consumption of the converter. As a result, the standby power consumption under no load condition is achieved below 60mW at 100V AC input and 150mW at 240V AC input, respectively. Furthermore, it is clarified that the slope of the resonant current envelope at soft start and end function in the standby mode influence the acoustic noise from the converter.
Para-catadioptric camera auto-calibration from epipolar geometry

We present a method for a para-catadioptric camera auto-calibration from point correspondences in two views based on the epipolar constraint. Besides rigidity, no assumptions about the scene are made (e.g. presence of a calibration object). The method leads to a closed form solution-to a polynomial eigenvalue problem and therefore no iterative minimizing process has to be used. The closed form solution allows to apply a 9-point RANSAC robust estimation technique and thus use automatically established point correspondences contaminated by mismatches. As a result of the calibration method, the calibrated camera, the estimated essential matrix, and the outliers in point matches are obtained. We demonstrate our method in experiments with commercially available parabolic mirror. Moreover, we show that the para-catadioptric camera model can be used in RANSAC to solve correspondence problem for a larger class of cata-dioptric cameras.
Do Unto Others: On the Importance of Reciprocity in Public Administration

There is an extensive literature across the humanities and social sciences on reciprocity as a fundamental driver of human behavior, and yet attempts to bring the main arguments from the diverse literatures together in a single interdisciplinary space remain scarce. This article aims to collate many of the main arguments from these literatures with the intention of speculating how reciprocity might be used to inform institutional structures, management practices, and public policy. This is significant, because the recent literature on public sector policy design tends to attach import to entirely self-regarding and/or altruistic motivations as fundamental drivers of human action, but, with some notable exceptions, says little directly on the role that reciprocity might have to play in motivating performance improvements. The lack of attention paid to reciprocity in the literature on human motivation and public policy design is problematic if one concludes that reciprocating behaviors are a major determinant of group cooperation and success.
RRT∗N: An improved rapidly-exploring random tree approach for reduced processing times

In this paper, we aim to improve on the processing time taken to run the Rapidly-Exploring Random Tree Star (RRT∗) algorithm with no regard for the path length. By restricting the area or volume in which the algorithm's nodes can be generated, a net improvement of the speed is observer. A further step is taken where the restriction is controller to either be in the form of a normal probability distribution or a uniform probability distribution. Both modifications are presented with the normal distribution resulting in significant improvements in the processing times.
Energy-Efficient NOMA Enabled Heterogeneous Cloud Radio Access Networks

H-CRANs are envisioned to be promising in 5G wireless networks. H-CRANs enable users to enjoy diverse services with high energy efficiency, high spectral efficiency, and low-cost operation, which are achieved by using cloud computing and virtualization technologies. However, H-CRANs face many technical challenges due to massive user connectivity, increasingly severe spectrum scarcity, and high penetration of energy-constrained devices. These challenges may significantly degrade network performance and user quality of service if not properly tackled. NOMA schemes exploit non-orthogonal resource sharing among multiple users and have received tremendous attention due to their great potential to improve spectral and energy efficiency in 5G networks. This article focuses on the energy efficiency study in a NOMA enabled H-CRAN. Key 5G technologies that can be applied in NOMA H-CRANs to improve energy efficiency are presented. Challenges to implement these technologies and open research issues are discussed. The performance study shows that using NOMA enabled H-CRANs together with the key presented technologies can greatly improve overall system energy efficiency.
Driving Style Comparison of City Buses: Electric vs. Diesel

The key issues of transportation today are pollution and energy, which both need to be minimized. In addition to the development of emerging technologies such as electric vehicles, reducing unnecessary energy consumption is equally important. This paper focuses on the driving style differences between electric and diesel city buses. The tools used for comparing driving styles are real-world measurements, literature review and driver survey. The study shows that the electric city buses are driven more aggressively and faster on average. The difference is due to electric powertrain's low-level noise feedback and superior power at low speeds.
SNARE complex in axonal guidance and neuroregeneration

Through complex mechanisms that guide axons to the appropriate routes towards their targets, axonal growth and guidance lead to neuronal system formation. These mechanisms establish the synaptic circuitry necessary for the optimal performance of the nervous system in all organisms. Damage to these networks can be repaired by neuroregenerative processes which in turn can re-establish synapses between injured axons and postsynaptic terminals. Both axonal growth and guidance and the neuroregenerative response rely on correct axonal growth and growth cone responses to guidance cues as well as correct synapses with appropriate targets. With this in mind, parallels can be drawn between axonal regeneration and processes occurring during embryonic nervous system development. However, when studying parallels between axonal development and regeneration many questions still arise; mainly, how do axons grow and synapse with their targets and how do they repair their membranes, grow and orchestrate regenerative responses after injury. Major players in the cellular and molecular processes that lead to growth cone development and movement during embryonic development are the Soluble N-ethylamaleimide Sensitive Factor (NSF) Attachment Protein Receptor (SNARE) proteins, which have been shown to be involved in axonal growth and guidance. Their involvement in axonal growth, guidance and neuroregeneration is of foremost importance, due to their roles in vesicle and membrane trafficking events. Here, we review the recent literature on the involvement of SNARE proteins in axonal growth and guidance during embryonic development and neuroregeneration.
Targeting Pattern Recognition Receptors (PRRs) in Nano- Adjuvants: Current Perspectives

DOI: 10.2174/22135294026661606011251 59 Abstract: Enormous progress in the field of vaccine development has moved the area from traditional vaccines using whole microorganisms to subunit vaccines containing only purified or modified antigenic proteins. The low immunogenic potentials of subunit vaccines compared to live attenuated pathogens, have prompted the research towards developing new adjuvants with the ability to mimic and enhance the innate and adaptive immune responses. Novel adjuvants formulations based on the discovery of pattern recognition receptors (PRRs), the main class of innate immunity sensors have recently gained interest. The major family of PRRs called Toll-like receptors (TLRs), which are expressed by a variety of cells and capable to induce innate immune responses and effective stimulation of transition from innate immune responses to adaptive immune responses. PRR ligands of natural and synthetic origin have been evaluated as potential adjuvants in a variety of applications including vaccine formulations. Apart from this, for generating effective and protective immune responses, targeted delivery of vaccine antigens along with PRR agonists to the desired cells is of great importance. New strategy of delivering vaccine antigens along with adjuvants using proper nano-sized materials has gained much attention during the recent years. Here we review the recent advances regarding PRR-based nano-adjuvants developments, focusing on current nano-materials based delivery system and their applications in biomedical sciences.
Inspiration and expiration dynamics in acute emotional stress assessment

Relationships between inspiration and expiration times, T<inf>in</inf> and T<inf>ex</inf>, and inter-breath interval (BB) were analyzed in a database composed by 120 young healthy volunteers undergoing a session divided in different stages aimed to induce relax and emotional stress, where respiration was recorded with a chest band. T<inf>in</inf> and T<inf>ex</inf> were represented as a function of BB so that two regression lines were obtained. The slopes of both regression lines, α<inf>Tin</inf> and α<inf>Tex</inf>, as well as the angle formed by them, θ, were used to characterize respiratory dynamics during each stage. Moreover, mean respiratory frequency in each stage was calculated. Statistical significant differences (p < 0.001) were obtained when comparing relax and stress stages, with increased α<inf>Tex</inf> and θ, and reduced α<inf>Tin</inf> during stress. Also differences between distinct stress stages were found. Results suggest that inspiration and expiration patterns, and hence respiratory dynamics, are different under stress, so its analysis could be useful for stress assessment.
Biomimetic Tactile Sensor for Control of Grip

We are developing a novel, robust tactile sensor array that mimics the human fingertip and its distributed set of touch receptors. The mechanical components are similar to a fingertip, with a rigid core surrounded by a weakly conductive fluid contained within an elastomeric skin. It uses the deformable properties of the finger pad as part of the transduction process. Multiple electrodes are mounted on the surface of the rigid core and connected to impedance measuring circuitry within the core. External forces deform the fluid path around the electrodes, resulting in a distributed pattern of impedance changes containing information about those forces and the objects that applied them. Here we report preliminary results with prototypes of the sensor, and we propose strategies for extracting features related to the mechanical inputs and using this information for reflexive grip control.
Contrast enhancement of low-light image using histogram equalization and illumination adjustment

Low-light image contains compressed dynamic range that can be enhanced for knowing detail information. Contrast enhancement of low-light image is a challenging task in image processing field. In this paper, we enhance the different type of low-light image by using histogram equalization (HE) and illumination adjustment. We present a method to detect different types of low-light images. Then, we apply the HE on V channel of input low-light image after converting the color space from RGB to HSV. After that, we enhance the contrast of V by adjusting intensity (V) of low-light image with adopting gamma correction. We evaluate our low-light enhanced method by naturalness image quality evaluator (NIQE) and colorfulness-based patch-based contrast quality index (CPCQI) and also compare our proposed method with typical HE method by measuring quality of images.
Lower Body Pose Estimation in Team Sports Videos Using Label-Grid Classifier Integrated with Tracking-by-Detection

We propose a human lower body pose estimation method for team sport videos, which is integrated with tracking-by-detection technique. The proposed Label-Grid classifier uses the grid histogram feature of the tracked window from the tracker and estimates the lower body joint position of a specific joint as the class label of the multiclass classifiers, whose classes correspond to the candidate joint positions on the grid. By learning various types of player poses and scales of Histogram-of-Oriented Gradients features within one team sport, our method can estimate poses even if the players are motion-blurred and low-resolution images without requiring a motion-model regression or part-based model, which are popular vision-based human pose estimation techniques. Moreover, our method can estimate poses with part-occlusions and non-upright side poses, which part-detector-based methods find it difficult to estimate with only one model. Experimental results show the advantage of our method for side running poses and non-walking poses. The results also show the robustness of our method for a large variety of poses and scales in team sports videos.
CBR Engine KB Manager Module Knowledge Base WordNet Server

Helping software designers in their task implies the development of tools with intelligent reasoning capabilities. One such capability is the integration of Natural Language Processing (NLP) in Computer Aided Software Engineering (CASE) tools, thus improving the designer/tool interface. In this paper, we present a Case Based Reasoning (CBR) approach that enables the generation of Unified Modeling Language (UML) class diagrams from natural language text. We describe the natural language translation module and provide an overview of the tool in which it is integrated. Experimental results evaluating the retrieval and adaptation mechanisms are also presented.
iReplayer: in-situ and identical record-and-replay for multithreaded applications

Reproducing executions of multithreaded programs is very challenging due to many intrinsic and external non-deterministic factors. Existing RnR systems achieve significant progress in terms of performance overhead, but none targets the in-situ setting, in which replay occurs within the same process as the recording process. Also, most existing work cannot achieve identical replay, which may prevent the reproduction of some errors. This paper presents iReplayer, which aims to identically replay multithreaded programs in the original process (under the "in-situ" setting). The novel in-situ and identical replay of iReplayer makes it more likely to reproduce errors, and allows it to directly employ debugging mechanisms (e.g. watchpoints) to aid failure diagnosis. Currently, iReplayer only incurs 3% performance overhead on average, which allows it to be always enabled in the production environment. iReplayer enables a range of possibilities, and this paper presents three examples: two automatic tools for detecting buffer overflows and use-after-free bugs, and one interactive debugging tool that is integrated with GDB.
Data Are Not Enough-Hurray For Causality!

A response is offered to an article by author Miguel A. Hernan in the issue on causal inference concerning the cause of diseases within the field of public health epidemiology. An overview of the use of observational research in epidemiology, including in regard to the formation of causal questions through observational data, is provided. Statistical association's relationship with causation is discussed.
Epidemiology of Puerperal Psychoses

Computer linkage of an obstetric register and a psychiatric case register made it possible to investigate the temporal relationship between childbirth and psychiatric contact in a population of 470 000 people over a 12-year period resulted in 54 087 births: 120 psychiatric admissions within 90 days of parturition. The ‘relative risk’ of admission to a psychiatric hospital with a psychotic illness was extremely high in the first 30 days after childbirth, particularly in primiparae, suggesting that metabolic factors are involved in the genesis of puerperal psychoses. However, being unmarried, having a first baby, Caesarian section and perinatal death were all associated with an increased risk of psychiatric admission or contact, or both, suggesting that psychological stresses also contribute to this high psychiatric morbidity. Women with a history of manic depressive illness, manic or depressive, had a much higher risk of psychiatric admission in the puerperium than those with a history of schizophrenia or depressive neuroses, and the majority of puerperal admissions met Research Diagnostic Criteria for manic or depressive disorder. Probably, therefore, puerperal psychoses are manic depressive illnesses and unrelated to schizophrenia.