Miracle-dz/UniFAR-FTUs huggingface dataset:
Food Anticipatory Activity on Circadian Time Scales Is Not Dependent on Central Serotonin: Evidence From Tryptophan Hydroxylase-2 and Serotonin Transporter Knockout Mice

A number of studies implicate biogenic amines in regulating circadian rhythms. In particular, dopamine and serotonin influence the entrainment of circadian rhythms to daily food availability. To study circadian entrainment to feeding, food availability is typically restricted to a short period within the light cycle daily. This results in a notable increase in pre-meal activity, termed “food anticipatory activity” (FAA), which typically develops within about 1 week of scheduled feeding. Several studies have implicated serotonin as a negative regulator of FAA: (1) aged rats treated with serotonin 5-HT2 and 3 receptor antagonists showed enhanced FAA, (2) mice lacking for the 2C serotonin receptor demonstrate enhanced FAA, and (3) pharmacologically increased serotonin levels suppressed FAA while decreased serotonin levels enhanced FAA in mice. We sought to confirm and extend these findings using genetic models with impairments in central serotonin production or re-uptake, but were surprised to find that both serotonin transporter (Slc6a4) and tryptophan hydroxylase-2 knockout mice demonstrated a normal behavioral response to timed, calorie restricted feeding. Our data suggest that FAA is largely independent of central serotonin and/or serotonin reuptake and that serotonin may not be a robust negative regulator of FAA.
Mutagenic mechanisms of cancer-associated DNA polymerase ϵ alleles

A single amino acid residue change in the exonuclease domain of human DNA polymerase ε, P286R, is associated with the development of colorectal cancers, and has been shown to impart a mutagenic phenotype. Perhaps unexpectedly, the corresponding Pol ε allele in the yeast Saccharomyces cerevisiae (pol2-P301R), was found to drive greater mutagenesis than exonuclease-deficient Pol ε (pol2-4), a phenotype sometimes termed ultra-mutagenesis. By studying the impact on mutation frequency, type, replication-strand bias, and sequence context, we show that ultra-mutagenesis is commonly observed in cells carrying a range of cancer-associated Pol ε exonuclease domain alleles. Similarities between mutations generated by these alleles and those generated in pol2-4 cells indicate a shared mechanism of mutagenesis that yields a mutation pattern similar to cancer Signature 14. Comparison of POL2 ultra-mutator with pol2-M644G, a mutant in the polymerase domain decreasing Pol ε fidelity, revealed unexpected analogies in the sequence context and strand bias of mutations. Analysis of mutational patterns unique to exonuclease domain mutant cells suggests that backtracking of the polymerase, when the mismatched primer end cannot be accommodated in the proofreading domain, results in the observed increase in insertions and T>A mutations in specific sequence contexts.
The effect of response biases on resolution thresholds of Sloan letters in central and paracentral vision

Purpose Letter resolution depends on three factors: perceivability, response bias, and similarity. The aim of the present study was to investigate the effect of response bias (the sensory-independent factor) on resolution thresholds of Sloan letters in central and paracentral vision. Methods Nine subjects with normal ocular health were recruited for this study. Using the method of constant stimuli, individual Sloan letters resolution thresholds were measured at 0° (central) and at ±3° eccentricity along the vertical meridian of the visual field. Response biases and letter similarities were computed using Luce’s choice model. Results Results showed that the differences in resolution thresholds of individual Sloan letters were significant at the central (F (9, 80) =5.02, p<. 001), the upper (χ2 (9) = 50.38, p<. 05) and the lower (χ2 (9) = 56.32, p<. 05) visual field locations. Unlike letter similarity measures, response biases showed significant correlations to the differences in thresholds at the central (r = −0.83, p<.05), the upper (r = - 0.73, p<.05) and the lower (r = −0.70, p<.05) visual field locations. Conclusions Our findings suggest that response biases have a significant effect on resolution of Sloan letters that could result in overestimating resolution acuity in central and paracentral visual field locations.
The dedicated iron deficiency anaemia clinic: a 15-year experience

Objective To report our cumulative experience from a dedicated iron deficiency anaemia (IDA) clinic over the last 15 years—with particular emphasis on referral rate, uptake of investigation, impact on endoscopy services, diagnostic yield of gastrointestinal (GI) investigation and the issue of recurrent IDA. Method A series of analyses of a register of 2808 referrals to the Poole IDA clinic between 2004 and 2018. Results The study population of 2808 had a sex ratio of 1.9 (female/male ratio) and a median age of 72 years (IQR: 60–79). A rising referral rate over the study period appears to be plateauing at around 2 cases per 1000 population per annum. On the basis of a snapshot audit, investigation of IDA may now account for over 20% of all diagnostic endoscopies. Overall, 86% of cases underwent examination of the upper and lower GI tract. Significant GI pathology was identified in 27% of the investigated cohort. Adenocarcinoma of the upper or lower GI tract was found in 8.3%, the majority in the right colon. The prevalence of recurrent IDA was estimated at 12.4%, and the results of investigation of this subgroup are reported. Conclusion Unexplained IDA is common, particularly in those over 60 years, and may be the first indication of underlying GI malignancy in over 8% of cases. Unresolved challenges include accommodating the resulting endoscopy workload, establishing a risk/benefit ratio for investigating those with major comorbidities and the management of recurrent IDA.
OptoSense

Ubiquitous computing requires robust and sustainable sensing techniques to detect users for explicit and implicit inputs. Existing solutions with cameras can be privacy-invasive. Battery-powered sensors require user maintenance, preventing practical ubiquitous sensor deployment. We present OptoSense, a general-purpose self-powered sensing system which senses ambient light at the surface level of everyday objects as a high-fidelity signal to infer user activities and interactions. To situate the novelty of OptoSense among prior work and highlight the generalizability of the approach, we propose a design framework of ambient light sensing surfaces, enabling implicit activity sensing and explicit interactions in a wide range of use cases with varying sensing dimensions (0D, 1D, 2D), fields of view (wide, narrow), and perspectives (egocentric, allocentric). OptoSense supports this framework through example applications ranging from object use and indoor traffic detection, to liquid sensing and multitouch input. Additionally, the system can achieve high detection accuracy while being self-powered by ambient light. On-going improvements that replace Optosense's silicon-based sensors with organic semiconductors (OSCs) enable devices that are ultra-thin, flexible, and cost effective to scale.
Robotic Inner Signal Propagation and Random Access over Hybrid Access Scheme

This paper proposes a Hybrid Access Scheme (HAS) aiming to convert a future robot’s backend communication system by a finite number of sensors instead of using a lot of wires. To replace this communication, the HAS needs to assure higher reliability within stringent low latency packet transmission. In this paper, the HAS utilizes the packet diversity principle and forward multiple copies of the same packet over the massive number of subcarrier channels. The HAS assigns the random accessing to select a subcarrier channel for general packet transmitting sensors. The audio and video sensors transmit packets over the dedicated channels to avoid collisions. The HAS system allows transmitting audio, video and general sensors simultaneously. The minimum number of subcarriers to satisfy theURLLC reliability requirement of 99.999% is evaluated for different packet duplications over different arrival condition.The HAS system’s reliability and collision probability are evaluated in MATLAB simulator for different packet duplication over different arrival condition. Moreover, the signal propagation expressions are captured using ANSYS HFSS software for rectangular and circular transmission medium over the 900 MHz, 2.4 GHz, 24 GHz, and 55 GHz frequency bands for differentstructural configurations.
16-Port Non-Planar MIMO Antenna System With Near-Zero-Index (NZI) Metamaterial Decoupling Structure for 5G Applications

In this article, a low-cost 16-port non-planar Multiple-Input-Multiple Output (MIMO) antenna system is proposed for future 5G applications. The non-planar MIMO antenna system is established around a 3D-octagonal-shape polystyrene block. The MIMO elements are arranged on the eight-sides of octagonal-shape block, whereas bottom and top faces of polystyrene block are left void. The single antenna element comprises of slotted microstrip patch with a stepped chamfered feed line and defected ground plane. Each MIMO element is designed on FR-4 substrate with a size of 22 mm $\times20$ mm, to cover the frequency band of 3.35 GHz to 3.65 GHz for the fifth-generation (5G) applications. The isolation between array elements is improved by using a meander-lines based near-zero-index epsilon-negative (NZI-ENG) metamaterial decoupling structure. The array elements are placed on the top-layer, whereas common connected ground plane and decoupling structure is placed on the bottom-layer. The metamaterial-based decoupling structure offers an isolation of more than 28 dB for antenna elements arranged in across and side-by-side configuration. Moreover, simulated and measured MIMO performance parameters i.e. Total Active Reflection Coefficient (TARC) <−18 dB, Envelop correlation coefficient (ECC) < 0.1 and Channel capacity loss (CCL) < 0.3 are in acceptable limits. The proposed non-planar 3D-MIMO antenna system can be employed for indoor localization systems and wireless personal area network applications, where different 5G devices are wirelessly linked to a centralized server. Moreover, a good agreement between simulated and measured results is achieved for the non-planar MIMO antenna system.
Optimal Non-convex Combined Heat and Power Economic Dispatch Using Particle Swarm Optimization

The economic scheduling of Combined Heat and Power (CHP) systems is a very hard and complex problem. With a rise in the number of operational units and related constraints, the conventional mathematical techniques cannot be used for optimization and optimal scheduling of the CHP units. This problem aims to simultaneously minimize the overall cost of operation of the electrical generator, CHP and heat generator units with the consideration of various operational constraints. This problem is very challenging and difficult to solve since the objective function is nonconvex and has nonlinear characteristics. A popular optimization technique, the Particle Swarm Optimization (PSO) is used in this paper to solve CHPED problem. The algorithm mimics the social behaviour and the food searching strategy of birds or fishes, which usually move in groups in search of food. To demonstrate the algorithm's superiority in handling different related constraints and the ability to produce better results, it is implemented on three different test systems. The results obtained by PSO on all the test systems are compared with the results obtained using some of the latest published techniques, which highlights the superiority of the PSO algorithm.
An Evaluation Framework for Assessing the Impact of Location Privacy on Geospatial Analysis

The need for addressing geoprivacy in location based services has increased the offer of mechanisms that protect location information, however, these algorithms are not always developed to ensure the usability of the data and therefore, their adoption is not wide. In this work, a framework is presented to evaluate the effects of geoprivacy mechanisms on the quality of geodata to provide insights into how the data is affected for geospatial analysis. For this purpose, a toolkit of indices was developed to evaluate different characteristics of the data before and after a geoprivacy mechanism is implemented, providing a criterion to select one of them. The indices measure the changes in the presence of clusters through the quantification of hotspots in hotspot analysis and the difference observed in heatmaps of the concentration of the geodata. Variations in global indices like the Nearest Neighbor Index (NNI) and the orientation of the standard deviational ellipse are also measured. For demonstration, the data of crime arrests in New York was used for the month of January in 2017 and 2018. Five mechanisms were tested with different settings, resulting with the NRand-K algorithm producing fewer alterations to the reference data, preserving its initial characteristics better than the other mechanisms.
A Review of Solid-State Circuit Breakers

Although conventional electromechanical circuit breakers have a proven record as effective and reliable devices for circuit protection, emerging power distribution technologies and architectures, such as dc microgrids, require improved interruption performance characteristics (e.g., faster switching speed). The need for faster switching operation, in combination with the latest developments of advanced power semiconductor technologies, has spurred an increase in the research and development in the area of solid-state circuit breakers. This article provides a comprehensive review of various solid-state circuit breaker technologies that have been reported in the literature during recent years. First, we categorize solid-state circuit breakers based on key features and subsystems, including power semiconductor devices, main circuit topologies, voltage clamping methods, gate drivers, fault detection methods, and commutation methods for power semiconductor devices. Second, we discuss the various challenges associated with the design of solid-state circuit breakers from the perspective of generic applications and provide a comparison of several solid-state breaker technologies based on key metrics. Finally, we provide a useful framework and point of reference for future development of solid-state circuit breakers for many emerging power distribution applications.
Design of expert system for predicting and evaluating centrifugal pump operation based on GRU-BP neural network

At present, in actual factory production, the running status of the equipment will affect the quality and output of the product. The timely and effective prediction of the running status to the equipment in Short-term can improve the stability and reliability of production. Firstly, a Gated Recurrent Unit (GRU) model is proposed to deal with the prediction of the future short-term operation status. Secondly, through the idea of combining neural network and expert system, an expert system model based on Gated Recurrent Unit-Back Propagation (GRU-BP) Neural Network is designed to evaluate the short-term running state of the centrifugal pump in the future. After the simulation results of field equipment operation parameters, it is verified that the GRU-BP model can not only judge the running state of the machine pump, but also predict the state of the machine pump in a short period of time with high accuracy, and has a great potential in the direction of pump state prediction.
Depth cameras calibration for obstructive sleep apnea diagnostic support

In our research, we use depth cameras to obtain precise 3D models of patients’ heads and faces. Visual system based on these cameras is basic element of developed screening tool for obstructive sleep apnea. Decreasing of scanning time plays key role mainly for pediatric patients and suppresses generation of motion artifacts in 3D models. Used Time of Flight sensors are relatively non-expensive solution, especially in our case (parallel usage of several cameras). To obtain accurate models, the step of camera calibration is very important. In this article, we bring detailed look on geometrical distortion (radial and tangential) of used cameras and also methods for spatial calibration of system composed from three cameras. As software tool, we used Camera Calibrator implemented in MATLAB. As result of mentioned research, we found suitable multi-camera calibration method and set of parameters related to our visual system (given topology and geometrical properties of scanning cabin). Calibration decreased average distance error (measured using Hausdorff distances) from ca. 3 mm before calibration to ca. 2 mm after calibration and made easier the registration of partial models to the resulting one. Designed visual system based on depth cameras with proper calibration and interference suppression seems to have big potential for obstructive sleep apnea screening not only in pediatrics.
Personal Trusted Platform Module for the Multi-Core System of 5G Security and Privacy

The article is devoted to the choice of personal means of the 5G defense in dependence of hard- and software available to the user. The universal module MS 127.04 and its software compatible unit can be universally configured for use. An intelligent hardware and software platform is proposed for multi-core setting of policies for the automatic encryption of confidential data and selective blocking related to the implementation of computing security and confidentiality of data transfer, using such additional specially. A platform that resists the external influences is described. The platform is based on a universal module MS 127.05 (produced in Russia), that is a heterogeneous multiprocessor system on a chip), the system features 16 processor cores (NeuroMatrix Core 4) and five ARM Cortex-A5 units (ULSI 1879VM8Ya.
Intelligent Adaptive Routing Algorithm in Software Defined Networks with Quality of Service

Currently, the most popular approach in information technology and computer networks is technology of software defined networks (SDN). Its main feature is separation of data plane and control plane levels, as well as support of specified requirements for the quality of service (QoS) of network applications. The aim of this work is the development of intelligent adaptive routing algorithm in SDN with support QoS. Proposed algorithm based on using a composite LARAC metric in that the bandwidth can be constant and the effect of transmission delay varies depending on the control coefficient. To implement the algorithm comparative analysis and experimental research of different neural network architectures were carried out. Also a model that allows the highest accuracy of optimal routes search in SDN with support multiple QoS parameters was developed.
A Framework for Subgraph Detection in Interdependent Networks via Graph Block-Structured Optimization

As the backbone of many real-world complex systems, networks interact with others in nontrivial ways from time to time. It is a challenging problem to detect subgraphs that have dependencies on each other across multiple networks. Instead of devising a method for a specific scenario, we propose a generic framework to discover subgraphs in multiple interdependent networks, which generalizes the classical subgraph detection problem in a single network and can be applied to more practical applications. Specifically, we propose the Graph Block-structured Gradient Hard Thresholding Pursuit (GB-GHTP) framework to optimize interdependent networks with block-structured constraints, which enjoys 1) a theoretical guarantee and 2) a nearly linear time complexity on the network size. It is demonstrated how our framework can be applied to three practical applications: 1) evolving anomalous subgraph detection in dynamic networks, 2) anomalous subgraph detection in networks of networks, and 3) connected dense subgraph detection in dual networks. We evaluate our framework on large-scale datasets with comprehensive experiments, which validate our framework’s effectiveness and efficiency.
Comparative study of fault estimation for 3-DOF helicopter

Fault estimation plays an important role in health monitoring as well as fault tolerant control, which can help ensure the reliability and safety of helicopter system. As the helicopter is a typical nonlinear, strong coupling and unstable system, its fault estimation design is challenging. Besides, it is also of great risk and cost to conduct experimental validation of different fault estimation schemes for real helicopter system. Thus, this paper is intended to conduct comparative research of fault estimation for helicopter system with table-mount experimental platform. Based on helicopter’s dynamic model, four observer-based fault estimation approaches are presented, in which Luenberger observer, Kalman filter, unknown input observer, and modified proportional-integral-derivative observer design are adopted separately. For the modified proportional-integral-derivative observer based fault estimation design, measurement noise is specifically considered. Based on Quanser’s 3-DOF helicopter system, both simulation and experimental tests are carried out to show the performance differences of these fault estimation approaches.
Underwater Image Restoration Using Geodesic Color Distance and Complete Image Formation Model

Underwater images suffer from different types of quality degradation, including haze, blur, low contrast, and color distortion, owing to light scattering and absorption. This article proposes a novel underwater image restoration algorithm based on the complete underwater image formation model (UIFM). Although the majority of the existing methods consider the direct transmission and backward scattering components only, this study, in addition, includes forward scattering in the UIFM. We estimate the transmission map based on the observation that the scene distance is inversely proportional to the geodesic color distance from the background light. We also approximate the point spread function in the forward scattering term to estimate the scene radiance more faithfully. Moreover, we obtain the optimal parameters of the UIFM required for transmission estimation and scene radiance restoration by minimizing a cost function composed of the sharpness, information loss, and dark background prior. The experimental results confirm that the proposed algorithm considerably improves the quality of the estimated transmission maps and restores scene radiance compared with the existing state-of-the-art methods.
Decentralized Control of Networked Systems with Unknown Control Directions and Uncertainties

In this paper, we investigate the decentralized control of networked agents with unknown control directions, i.e., the sign of high-frequency-gain in agent’s dynamics is unknown. Meanwhile, uncertain nonlinearity also appears in agent’s dynamics. A Nussbaum-type adaptive controller is designed with the aid of nonlinear damping technique for each agent such that consensus of the network can be achieved while all signals in the overall system maintain bounded. The controller for each agent is composed by a Nussbaum-type item which seeks the control direction adaptively and a distributed item to drive the system to consensus state, in which a nonlinear damping item is added. It is proved that consensus of the network can be realized via the proposed controller. Moreover, the final consensus state is indicated, which is significant for consensus of networked nonlinear systems. Simulation results are presented to verify the effectiveness of the proposed controllers.