Miracle-dz/UniFAR-FTUs huggingface dataset:
Live View Car Surveillance System

Today we are living in the 21st century where with the increase in technological advancements and IOT, human race is facing a large breakdown in security issues. With the fast-technological advancement, we face certain problems in our daily life. Vehicle security is one of the major issues in the current era.Car automation and surveillance is an escalating trend in this decade. The vehicle security has become a need of the time. In this paper we propose a real-time security system with a live 360-degree view of the vehicle and intelligence to the system made through using various sensors to pin point the area of contact to the vehicle which will be added advantage to the owner of the vehicle. We are using a security system which senses the motion, sends a notification to the owner, and the owners can also see the video through camera in their mobile phone app. The system works on the principle of real-time camera surveillance system. Moreover, the proposed system can also be extended to inculcate the concept of Ad-hoc networking in intelligent cars, to send a warning to the car at the back, in case of an accident which will press the brakes of car to stop at a safe distance. This paper lies in the field of Internet of things (IOT), Block chain, Smart cities, Data analytics, Mobile application, Knowledge management, Digital transformation, Networking, Wireless/Mobile Communication, Statistics in Society Signal Processing using smart cars using Raspberry pi, Sensors, Cameras, GPRS, GPS.
Body Odor Disgust Sensitivity Predicts Moral Harshness Toward Moral Violations of Purity

Detecting pathogen threats and avoiding disease is fundamental to human survival. The behavioral immune system (BIS) framework outlines a set of psychological functions that may have evolved for this purpose. Disgust is a core emotion that plays a pivotal role in the BIS, as it activates the behavioral avoidance motives that prevent people from being in contact with pathogens. To date, there has been little agreement on how disgust sensitivity might underlie moral judgments. Here, we investigated moral violations of “purity” (assumed to elicit disgust) and violations of “harm” (assumed to elicit anger). We hypothesized that individual differences in BIS-related traits would be associated with greater disgust (vs. anger) reactivity to, and greater condemnation of Purity (vs. Harm) violations. The study was pre-registered (https://osf.io/57nm8/). Participants (N = 632) rated scenarios concerning moral wrongness or inappropriateness and regarding disgust and anger. To measure individual differences in the activation of the BIS, we used our recently developed Body Odor Disgust Scale (BODS), a BIS-related trait measure that assesses individual differences in feeling disgusted by body odors. In line with our predictions, we found that scores on the BODS relate more strongly to affective reactions to Purity, as compared to Harm, violations. In addition, BODS relates more strongly to Moral condemnation than to perceived Inappropriateness of an action, and to the condemnation of Purity violations as compared to Harm violations. These results suggest that the BIS is involved in moral judgment, although to some extent this role seems to be specific for violations of “moral purity,” a response that might be rooted in disease avoidance. Data and scripts to analyze the data are available on the Open Science Framework (OSF) repository: https://osf.io/tk4x5/. Planned analyses are available at https://osf.io/x6g3u/.
Biochemical Pathways Triggered by Antipsychotics in Human Oligodendrocytes: Potential of Discovering New Treatment Targets

Schizophrenia is a psychiatric disorder that affects more than 21 million people worldwide. It is an incurable disorder and the primary means of managing symptoms is through administration of pharmacological treatments, which consist heavily of antipsychotics. First-generation antipsychotics have the properties of D2 receptor antagonists. Second-generation antipsychotics are antagonists of both D2 and 5HT2 receptors. Recently, there has been increasing interest in the effects of antipsychotics beyond their neuronal targets and oligodendrocytes are one of the main candidates. Thus, our aim was to evaluate the molecular effects of typical and atypical drugs across the proteome of the human oligodendrocyte cell line, MO3.13. For this, we performed a mass spectrometry-based, bottom-up shotgun proteomic analysis to identify differences triggered by typical (chlorpromazine and haloperidol) and atypical (quetiapine and risperidone) antipsychotics. Proteins which showed changes in their expression levels were analyzed in silico using Ingenuity® Pathway Analysis, which implicated dysregulation of canonical pathways for each treatment. Our results shed light on the biochemical pathways involved in the mechanisms of action of these drugs, which may guide the identification of novel biomarkers and the development of new and improved treatments.
High-Spectral-Efficiency 600-Gbps/Carrier Transmission Using PDM-256QAM Format

High-capacity carrier signals with high-order modulation are being considered for data center interconnection (DCI) applications as they can reduce the cost per bit by decreasing the number of devices and increasing fiber capacity. However, signal quality degradation due to device imperfections affecting the frequency response has limited the capacity per carrier of PDM-256QAM signals to under 400 Gbps. Here, it is possible to use a calibration method for dealing with device imperfections wherein a fixed equalizer separately calibrates the frequency response of the transmitter and receiver. Our previous study showed that PDM-256QAM signals at up to 48 GBaud could be transmitted over 100 km, while it used an experimental setup with total 3-dB analog bandwidth of 13 and 20 GHz for transmitter and receiver, respectively. A micro-integrable tunable laser assembly with a typical linewidth of 20 kHz, maximum under 100 kHz. Actual DCI applications, however, are expected to use dense wavelength division multiplexing (WDM), so in this study, we examined transmission of 10-WDM 48-GBaud PDM-256QAM signals in a 50-GHz grid and evaluated the WDM penalties. The resulting spectral efficiency of 600-Gbps/carrier WDM transmissions was as high as 12.02 bit/s/Hz.
Assessing Executive Function in Adolescence: A Scoping Review of Existing Measures and Their Psychometric Robustness

Background: There is much research examining adolescents' executive function (EF) but there is little information about tools that measure EF, in particular preference of use, their reliability and validity. This information is important as to help both researchers and practitioners select the most relevant and reliable measure of EF to use with adolescents in their context. Aims: We conducted a scoping review to: (a) identify the measures of EF that have been used in studies conducted among adolescents in the past 15 years; (b) identify the most frequently used measures of EF; and (c) establish the psychometric robustness of existing EF measures used with adolescents. Methods: We searched three bibliographic databases (PsycINFO, Ovid Medline, and Web of Science) using key terms “Adolescents,” “Executive Functions,” and “measures”. The search covered research articles published between 1st January 2002 and 31st July 2017. Results: We identified a total of 338 individual measures of EF from 705 eligible studies. The vast majority of these studies (95%) were conducted in high income countries. Of the identified measures, 10 were the most used frequently, with a cumulative percent frequency accounting for nearly half (44%) the frequency of usage of all reported measures of EF. These are: Digit Span (count = 160), Trail Making Test (count = 158), Behavior Rating Inventory of Executive Function (count = 148), Wisconsin Card Sorting Test (count = 140), Verbal Fluency Tasks (count = 88), Stroop Color-Word Test (count = 78), Classical Stroop Task (count = 63), Color-Word Interference Test from Delis-Kaplan battery (count = 62), Rey-Osterrieth Complex Figure Test (count = 62), and Original Continuous Performance Test (count = 58). In terms of paradigms, tasks from Span (count = 235), Stroop (count = 216), Trails (count = 171), Card sorting (count = 166), Continuous performance (count = 99), and Tower (count = 94) paradigms were frequently used. Only 48 studies out of the included 705 reported the reliability and/or validity of measures of EF used with adolescents, but limited to studies in high income countries. Conclusion: We conclude that there is a wide array of measures for assessing EF among adolescents. Ten of these measures are frequently used. However, the evidence of psychometric robustness of measures of EF used with adolescents remains limited to support the validity of their usage across different contexts.
Integrated Reconfigurable Silicon Photonics Switch Matrix in IRIS Project: Technological Achievements and Experimental Results

This paper reports the performances of a silicon photonics optical switch matrix fabricated by using large-scale three-dimensional (3-D) integration. The wavelength selective optical switch consists of a photonic integrated circuit (PIC), with 1398 circuit elements, interconnected in a 3-D stack with its control electronic integrated circuit (EIC). Each PIC element can be trimmed or reconfigured by using metallic heaters. The EIC is designed to drive the heaters and to read the signal of monitor photodiodes integrated into the PIC. Small footprint and high energy efficiency are achieved in the PIC and the EIC. Automatic wavelength alignment of the optical circuits in the PIC to the ITU grid and fine temperature tuning of each photonic element to optimize the switch insertion losses are obtained by an optimization routine. A fully packaged switch with input/output fibers is tested both for optical and electrical characteristics as well as for the system performances. Fiber-to-fiber insertion losses of about 20 dB and channel isolation of −35 dB are achieved. Bit error rate characteristics at 25 Gb/s are evaluated. Perspective applications of the optical switch in optical transport and intra-data center networks are discussed.
Tunable Neuron With PWL Approximation Based on the Minimum Operator

In this brief, hardware implementation of a novel tunable neuron is proposed based on choosing the minimum operator to generate the piecewise linear approximation of the neuron’s transfer function. The proposed structure is compatible with analog and mixed-signal neural networks. An accurate model of the sigmoid function is developed by using minimum operator. Moreover, if required, the activation function of the neuron can be adjusted during the training to provide various maximal slope <inline-formula> <tex-math notation="LaTeX">$ {sigmoid}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$ {hard}$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">$ {limit}$ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$ {linear}$ </tex-math></inline-formula> functions. The shape and the slope of the transfer function can be controlled by a 2-bit digital to analog converter. This allows the neuron to have different transfer functions based on the network requirements and during the training.
An Exhaustive Survey on Security Concerns and Solutions at Different Components of Virtualization

Virtualization is a key enabler of various modern computing technologies. However, it brings additional vulnerabilities that can be exploited to affect the availability, integrity, and confidentiality of the underlying resources and services. The dynamic and shared nature of the virtualization poses additional challenges to the traditional security solutions. This article explores the vulnerabilities, threats, and attacks relevant to virtualization. We analyze the existing security solutions and identify the research gaps that can help the research community to develop a secured virtualization platform for current and future computing technologies.
ARPM: Additive, Retentive Penalty Method for Multidimensional NILM Algorithms

Nonintrusive load monitoring (NILM) algorithms may suggest different approaches for solving the NILM problem: the disintegrating of total power consumption to the discrete appliances comprising it. All of these algorithms incorporate some cost function to discriminate between the possible options at each sample time. For the estimation process of such algorithms, and the selection of the most likely possibility, we propose a new formulation of a family of cost functions, on the set of the possible assertions per each appliance. The proposed design, abbreviated ARPM (Additive, Retentive Penalty Method), emphasizes two major properties that were discovered to be significant when performing real-time estimation in a NILM system. The first is a granular calculation of Hamming distances between possibilities, and the second is the processing of the changes in the measured power consumption, rather than the consumption value itself. This design consists of a low number of free parameters, and can be integrated additively and seamlessly with existing cost functions already embedded in NILM systems. It had been evaluated with a series of experiments and proven to enhance the success rate by all measured criteria and on various datasets, with no parameter adjustments.
CENTAURO: A Hybrid Locomotion and High Power Resilient Manipulation Platform

Despite the development of a large number of mobile manipulation robots, very few platforms can demonstrate the required strength and mechanical sturdiness to accommodate the needs of real-world applications with high payload and moderate/harsh physical interaction demands, e.g., in disaster-response scenarios or heavy logistics/collaborative tasks. In this letter, we introduce the design of a wheeled-legged mobile manipulation platform capable of executing demanding manipulation tasks, and demonstrating significant physical resilience while possessing a body size (height/width) and weight compatible to that of a human. The achieved performance is the result of combining a number of design and implementation principles related to the actuation system, the integration of body structure and actuation, and the wheeled-legged mobility concept. These design principles are discussed, and the solutions adopted for various robot components are detailed. Finally, the robot performance is demonstrated in a set of experiments validating its power and strength capability when manipulating heavy payload and executing tasks involving high impact physical interactions.
Sparse Representation-Based Intuitionistic Fuzzy Clustering Approach to Find the Group Intra-Relations and Group Leaders for Large-Scale Decision Making

In this paper, a sparse representation-based intuitionistic fuzzy clustering (SRIFC) approach is presented for solving the large-scale decision making (LSDM) problem. It consists of two algorithms: the sparse representation-based intuitionistic fuzzy clustering-exactly precision algorithm (which is presented for an exactly precision requirement), and the sparse representation-based intuitionistic fuzzy clustering-soft precision and scalable algorithm (which is proposed for soft precision and scalable requirements). In the proposed SRIFC approach, decision makers are clustered into several interest groups according to their interest preferences and relation sparsity of their intuitionistic fuzzy assessment information. The purpose of the presented SRIFC approach is to investigate the group intra-relations among DMs and to detect the group leaders for each interest group during the clustering process. According to the illustrative experiment results, the presented SRIFC approach is an adaptive and the unsupervised clustering method and presents more robust and efficient for LSDM problems.
SPARSE AND LOW-RANK OPTIMIZATION FOR PLIABLE INDEX CODING

In this paper, we investigate the pliable index coding problem, where clients are interested in receiving any messages (instead of specific messages) that they do not have. The motivating applications including caching networks, recommendation systems and distributed computing systems, where the clients are happy to receive any messages not available in them. However, the pliable index coding problem turns out to be computationally intractable, for which we propose a novel sparse and low-rank optimization framework to assist efficient algorithms design in real field, thereby minimizing the number of channel uses for message delivery. To address the nonconvex challenges in this framework, we further propose the alternating projection algorithm to solve the sparse and low-rank optimization problem with local convergence guarantees. Simulation results demonstrate that the number of channel uses can be significantly reduced for message delivery via the sparse and low-rank optimization.
Comparing Lean Management Principles and Evolutionary Design in Nature

Evolutionary design is defined as a gradual process in which something changes into a different and usually more complex or better form. This process is apparent in nature where it is evolving towards the optimum solution. Lean is defined as a philosophy that aims at eliminating waste in production processes without compromising value. The two concepts appear in the literature as independent with little attempts to study a possible relation between them. The purpose of this paper is to explore synergies between the two seemingly distinct systems. This is performed by studying each notion on its own through breaking it down to its dynamic functional systems, and comparing the functions of each against one another. Findings reveal that the development of lean since its inception is comparable to the natural mechanisms of evolutionary design in nature. Findings suggest that lean is the natural course of evolution of construction management systems towards more optimal systems. Constructal Law provides us with a perspective about the concept of evolution and the direction of these evolutionary changes with time. The continuous evolution of everything is never out of control. Plotting the history of the covered territory against time shows an S-shaped curve. Every spreading flow has an S-shaped history of growth. It starts with an initial slow growth, followed by a much faster growth and a slow growth again.
Drosophila melanogaster: A Model Organism to Study Cancer

Cancer is a multistep disease driven by the activation of specific oncogenic pathways concomitantly with the loss of function of tumor suppressor genes that act as sentinels to control physiological growth. The conservation of most of these signaling pathways in Drosophila, and the ability to easily manipulate them genetically, has made the fruit fly a useful model organism to study cancer biology. In this review we outline the basic mechanisms and signaling pathways conserved between humans and flies responsible of inducing uncontrolled growth and cancer development. Second, we describe classic and novel Drosophila models used to study different cancers, with the objective to discuss their strengths and limitations on their use to identify signals driving growth cell autonomously and within organs, drug discovery and for therapeutic approaches.
SINGLE IMAGE SUPER-RESOLUTION USING A NON-LOCAL 3D CONVOLUTIONAL NEURAL NETWORK

Single image super-resolution (SR), which intends to recover a high-resolution (HR) image from a single low-resolution (LR) image, has attracted increasing attentions with a wide range of applications. In this paper, we propose a novel non-local scheme based on a 3D convolutional neural network (3DCNN) for image super-resolution. Different from most previous methods, our scheme takes the inherent non-local self-similarity property of natural images into account. Specifically, the non-local similar patches are searched and extracted from low-resolution images. Then a 3DCNN is constructed to jointly sharpen these non-local patches, which can make full use of the non-local similarity in natural images. Finally, the super-resolved image is reconstructed from the sharpened patches. Experiments show that the proposed non-local method achieves the superior reconstruction accuracy compared with several state-of-the-art methods.
Efficient Autonomous Exploration Planning of Large-Scale 3-D Environments

Exploration is an important aspect of robotics, whether it is for mapping, rescue missions, or path planning in an unknown environment. Frontier Exploration planning (FEP) and Receding Horizon Next-Best-View planning (RH-NBVP) are two different approaches with different strengths and weaknesses. FEP explores a large environment consisting of separate regions with ease, but is slow at reaching full exploration due to moving back and forth between regions. RH-NBVP shows great potential and efficiently explores individual regions, but has the disadvantage that it can get stuck in large environments not exploring all regions. In this letter, we present a method that combines both approaches, with FEP as a global exploration planner and RH-NBVP for local exploration. We also present techniques to estimate potential information gain faster, to cache previously estimated gains and to exploit these to efficiently estimate new queries.
A 1.2 V–20 V Closed-Loop Charge Pump for High Dynamic Range Photodetector Array Biasing

Ultra-high dynamic range optical sensing is achieved by operating a CMOS photodiode or imager alternately in linear and single-photon avalanche modes, which requires reverse bias from low voltage to above junction breakdown voltage for the process. To address this need, this brief presents a reconfigurable, closed-loop charge pump generating regulated output voltage from 1.2 to 20 V fabricated in a standard 0.18-<inline-formula> <tex-math notation="LaTeX">${\mu }\text{m}$ </tex-math></inline-formula> CMOS process. The dual-mode dc–dc converter architecture demonstrates maximum efficiency of 34% in high-voltage mode (>10 V) and 56% in low-voltage mode (<5 V) to provide efficient detector bias for both linear and single-photon operation. The charge pump demonstrates 960 ns recovery of 60 mV voltage droop at 11.9 V when biasing a CMOS-integrated single-photon avalanche diode device with an emulated array capacitance equivalent of 68 pF.
Voids in Kesterites and the Influence of Lamellae Preparation by Focused Ion Beam for Transmission Electron Microscopy Analyses

Kesterite solar cells based on Cu2ZnSnS4 and Cu2ZnSnSe4 (CZTSe) are potential future candidates to be used in thin-film solar cells. The technology still has to be developed to a great extent and for this to happen, high levels of confidence in the characterization methods are required, so that improvements can be made on solid interpretations. In this study, we show that the interpretations of one of the most used characterization techniques in kesterites, scanning transmission electron microscopy (STEM), might be affected by its specimen preparation when using focused ion beam (FIB). Using complementary measurements based on scanning electron microscopy and Raman scattering spectroscopy, compelling evidence shows that secondary phases of ZnSe mixed in the bulk of CZTSe are the likely cause of the appearance of voids in STEM lamellae. Sputtering simulations support this interpretation by showing that Zn in a ZnSe matrix is preferentially sputtered compared with any metal atom in a CZTSe matrix.