Miracle-dz/UniFAR-FTUs huggingface dataset:
S.P.O.O.F Net: Syntactic Patterns for identification of Ominous Online Factors

With more emphasis on internet as a primary mechanism for information access and communication, it is highly important that the platform stays safe and secure for anyone who uses it. Online scams and cybercrimes are becoming a common threat to the technology and systems that help mitigate these issues are in high demand. Businesses all over the world invest heavily to stay secure in the cyberspace and rely on security experts in defending their business from online threats. The immense scale of the internet and the dynamicity of the threat it holds forces the adoption of automated threat detection systems. Several cybersecurity use cases exist, but the two use cases discussed here are DGA detection and Malicious URL detection. This paper addresses the drawbacks of previous rulebased and machine learning based detection methods. Here, embedding concepts from NLP is incorporated into cybersecurity use cases to propose a new in house model christened S.P.O.O. F Net, which is a combination of a Convolutional Neural Network and Long Short Term Memory Network. The proposed model is benchmarked with machine learning algorithm incorporating bi-gram feature engineering techniques and also a conventional CNN with character level embedding (same as the one used for S.P.O.O.F Net). It was observed that S.P.O.O. F Net gave better performance over the aforementioned methods with accuracy scores of 98.3% for DGA detections and 99% for malicious URL detection. This work also aims to demonstrate the possibilities of incorporating NLP concepts to cybersecurity use cases and provide future researches a new thinking curve to develop systems in this domain.
Development of social systems neuroscience using macaques

This paper reviews the literature on social neuroscience studies using macaques in the hope of encouraging as many researchers as possible to participate in this field of research and thereby accelerate the system-level understanding of social cognition and behavior. We describe how different parts of the primate brain are engaged in different aspects of social information processing, with particular emphasis on the use of experimental paradigms involving more than one monkey in laboratory settings. The description begins with how individual neurons are used for evaluating socially relevant information, such as the identity, face, and focus of attention of others in various social contexts. A description of the neural bases of social reward processing and social action monitoring follows. Finally, we provide several perspectives on novel experimental strategies to help clarify the nature of interacting brains under more socially and ecologically plausible conditions.
Frequency-Selective Rasorber With Interabsorption Band Transparent Window and Interdigital Resonator

A novel frequency-selective rasorber (FSR) is proposed in this paper which has a nearly transparent window between two absorption bands. The FSR consists of a resistive sheet and a bandpass frequency-selective surface (FSS). The impedance conditions of absorption/transmission for both the resistive sheet and the bandpass FSS are theoretically derived based on equivalent circuit analysis. The insertion loss of FSR at the resonant frequency of lossless bandpass FSS is proven to be only related to the equivalent impedance of the resistive sheet. When the resistive sheet is in parallel resonance at the passband, a nearly transparent window can be achieved regardless of lossy properties. An interdigital resonator (IR) is designed to realize parallel resonance in the resistive element by extending one finger of a strip-type interdigital capacitor to connect the two separate parts of the capacitor. The IR is equivalent to a parallel LC circuit. Lumped resistors are loaded around the IR to absorb the incident wave at lower and upper absorption bands. With the bandpass FSS as the ground plane, the absorption performances at both the lower and upper bands around the resonant frequency are improved compared to a metal-plane-backed absorber structure. The FSR passband is designed at 10 GHz with an insertion loss of 0.2 dB. The band with a reflection coefficient below −10 dB extends from 4.8 to 15.5 GHz. A further extension to dual-polarized FSR is designed, fabricated, and measured to validate the proposed design.
A Machine Learning Approach to Leverage Individual Keyboard and Mouse Interaction Behavior From Multiple Users in Real-World Learning Scenarios

There is strong evidence that emotions influence the learning process. For this reason, we explore the relevance of individual and general mouse and keyboard interaction patterns in real-world settings while learners perform free text tasks. To this end, we have modeled users’ mouse movements and keystroke dynamics with data mining techniques, building on previous related research and extending it in terms of some critical modeling issues that may have an impact on detection results. Inspired by practice in affective computing where physiological sensors are used, we argue for the creation of an interaction baseline model, as a reference point in the way how learners interact with the keyboard and mouse. To make the proposed affective model feasible, we have adopted a simplified 2-D self-labeling approach for labeling the users’ affective state. Our approach to affect detection improves results when there is a small amount of data instances available and does not require additional affect-oriented tasks from the learners. Specifically, learners are only asked to self-reflect their emotional state after finishing the tasks and immediately selecting two values in the affect scale. The approach we have followed aims to distill two types of interaction patterns: 1) within-subject patterns (from a single participant) and 2) between-subject patterns (across all participants). Doing this, we aim to combine both the approaches as modeling factors, thus taking advantage of individual and general interaction patterns to predict affect.
SIW-Based Quad-Beam Leaky-Wave Antenna With Polarization Diversity for Four-Quadrant Scanning Applications

A novel polarization diverse substrate integrated waveguide (SIW)-based leaky-wave antenna (LWA) is proposed for larger radiation coverage by frequency beam scanning in X-band. For feeding purpose, the SIW-based power divider, the directional coupler, and the 180° power splitter are used in the design. For radiation, +45°/−45° tilted slots are etched on top and bottom faces of the structure such that the radiated quad beam scans all the four quadrants. By varying the means of excitation at two input ports, multiple polarization states are realized. The antenna shows ±45° dual polarization (+45° and −45° are co-existing), horizontal and vertical polarization, and two types of circular dual-polarization (left handed and right handed simultaneously). The proposed antenna is capable of scanning in each of the four quadrants simultaneously with the scanning range of 62° having the maximum gain of 12.6 dBi and an improved cross-polarization level better than −20 dB. The quad beam covers overall scanning range of 248° with different polarization states. The S-parameters, radiation patterns, gain, and axial ratio are calculated and demonstrated. The proposed LWA shows desirable advantages, such as simultaneous four-quadrant frequency beam scanning having polarization diversity capabilities, which leads to a flexible design for practical utilization.
BehaviorKI: Behavior Pattern Based Runtime Integrity Checking for Operating System Kernel

Kernel rootkits pose a serious threat to system security by tampering with the state of operating system inconspicuously. To ensure operating system kernel integrity, Virtual Machine Monitor (VMM) based approaches have been proposed. Most of these approaches use snapshot-based or event-triggered techniques. However, snapshot-based techniques have been suffering from missing transient attacks or significant performance overhead, while event-triggered methods are facing with heavy workload as integrity checking might be triggered by any suspicious actions. In this paper, we propose a novel solution which is a behavior-triggered integrity checking approach named BehaviorKI. By analyzing attacking processes, BehaviorKI can extract a set of behavior patterns which characterize malicious behaviors. BehaviorKI will trigger integrity checking with kernel invariants when a malicious behavior pattern detected. In this way, our approach can alleviate the performance burden by reducing the frequent kernel integrity checking. The experiment results show that Be-haviorKI outperforms existing snapshot-based and event-triggered approaches.
The PREHydrA: A Passive Return, High Force Density, Electro-Hydrostatic Actuator Concept for Wearable Robotics

This letter presents the Passive Return Electro-Hydrostatic Actuator (PREHydrA), an actuator for use in wearable robotics. It eliminates conventional hydraulic systems’ fluid supply and valves, potentially making it lighter, more efficient, and simpler. It also avoids the configuration-dependent friction of Bowden cable transmissions. A physical port-based network model was created of the PREHydrA that predicts force tracking with a maximum error of about 4 N. Closed loop output force control was used in experiments to obtain a mean absolute tracking error below 4 N for force references from 300 N amplitude at 0.5 Hz to 20 N amplitude at 10 Hz. These forces, frequencies, and corresponding velocities (up to 0.47 m/s) demonstrate that the PREHydrA's performance is sufficient for many wearable applications.
A Digitally Interfaced Analog Correlation Filter System for Object Tracking Applications

This paper reports a <inline-formula> <tex-math notation="LaTeX">$24\times 57$ </tex-math></inline-formula> correlation filter system for object tracking applications. While digital interfacing of the input and output data enabled a standard and flexible way of communication with pre- and post-processing digital blocks, the multiply-accumulate (MAC) operations were performed in the analog domain to save power and area. The proposed system utilizes non-volatile floating-gate memories to store filter coefficients. The chip was fabricated in a 0.13-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS process and occupies 3.23 mm<sup>2</sup> of silicon area. The system dissipates 388.4 <inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> of power at a throughput of 11.3 kVec/s, achieving an energy efficiency of 25.2 pJ/MAC. Experimental results for a custom filter designed to detect vehicles are presented.
Design of a Bioinspired Robotic Hand: Magnetic Synapse Sensor Integration for a Robust Remote Tactile Sensing

Integrating tactile sensors into robotic applications is still a challenge because of sensor interconnection and various form factors. Newly developed magnetic synapse sensors have high sensitivity and remote sensing capability, but integration with a robotic finger is an issue because of the air-transmitting tubes that need to be connected from the sensor to the remotely located base unit. This study proposes an integrated design of a multijoint robotic finger with magnetic synapse sensors inspired by the human's joint structure and synapse system. The joint unit inspired by human's finger joints for the usage of the magnetic synapse sensors can easily has hollow channels and insert air-transmitting tubes through a rotating joint compared to the traditional pin joint. The rolling contact joint also minimizes the length variation of the tube when the joint rotates because the center of rotation changes. Modularized sensor units capable of changing the sensor sensitivity and sensing range have been developed and applied to the remote tactile sensing system. A three-finger gripper with three joints per finger with an integrated three-tactile sensor array was prototyped to explore the feasibility of the units. The sensor sensitivity was 0.016 mV/kPa and the sensing range was 350 kPa. The robotic fingers integrated with a high-sensitivity sensor array can grasp objects with various shapes and compliance (i.e., artificial flowers, paper cups, and wine glasses) without damaging the objects using tactile feedback.
Implementation of Multioperations in Thick Control Flow Processors

Multioperations are primitives of parallel computation for which processors perform a reduction, e.g. addition, on values provided by multiple threads into a single value in a constant number of steps. Algorithmically, multioperations can speed up execution by a logarithmic factor over their single operation counterparts. In this paper, we propose an architectural technique for realizing multioperations in thick control flow processors. Thick control flows (TCF) are computational constructs that simplify parallel programming by bundling a number of homogeneous threads following the same control path into universalized vector-like entities. The elements of TCFs are called fibers to distinguish them from ordinary threads having their own individual control. Processors designed for executing TCFs feature a unique frontend-backend structure to provide low-latency processing of TCF-common computations and high-throughput execution of data parallel fibers. Our proposal relies on step caches and equally sized multioperation scratchpads, while on the memory side, we make use of active memory modules. The idea is to compute partial results in backend units to reduce the traffic to the referred shared memory location. The final result is then computed in the active memory unit of the target memory module. According to the evaluation made with our TCF-aware processor equipped with multioperation scratchpads and active memory units, it indeed executes certain N data element-algorithms log N times faster than the baseline processor. The cost of the implementation is preliminarily evaluated.
The Performance Analysis of Cache Architecture Based on Alluxio over Virtualized Infrastructure

In the cloud computing architecture, the decoupled computing and storage architecture have been gradually accepted by the major public cloud vendors due to its flexibility and low cost. However, this architecture has a certain performance loss that it has a large delay in accessing data as it has to access the data through the network. In order to make up for this shortcoming, a variety of performance optimization schemes have been proposed. Most of these schemes accelerate the I/O operations by caches, which consist of the fast storage media such as memory, SSD, etc. Although different architecture designs have been proposed, they paid little attention to the cost incurred. However, the cost reduction plays a critical role in practical application in the real world. In this paper, we explore the caching design through the experiments while taking the cost performance into account. We also summarize the performance differences between various caching architectures in specific application scenario, and propose suggestions on caching design according to the scenario.
Long noncoding RNA GAS5 regulates the proliferation, migration, and invasion of glioma cells by negatively regulating miR‐18a‐5p

Long noncoding RNAs, transcribed from a recently discovered class of noncoding genes, may play a critical role in regulating cellular processes, such as cell proliferation and apoptosis, as well as in cancer progression and metastasis. We previously detected the induction of growth arrest–specific 5 (GAS5) during glioma cell death. However, the function and underlying mechanism of GAS5 in human gliomas remain to be elucidated.
Risk Assessment and Risk-Adapted Treatment Selection: A Case-Based Approach for Chronic Lymphocytic Leukemia

Selected Patient Cases From the APSHO Regional Lecture Series INTRODUCTION As the official publication of the Advanced Practitioner Society for Hematology and Oncology (APSHO), JADPRO is pleased to offer Part 3 of an accredited educational activity based on the recently concluded APSHO Regional Lecture Series. Hosted in collaboration with major cancer centers around the country, the APSHO Regional Lecture Series brought case-based didactic presentations and skills workshops to advanced practitioners. In the spirit of JADPRO, three accredited Grand Rounds articles by Beth Eaby-Sandy, MSN, CRNP, OCN® (non–small cell lung cancer) and Sandra Kurtin, PhDc, ANP-C, AOCN® (multiple myeloma and chronic lymphocytic leukemia)—program chairs for the regional lecture series—offer the same practice-changing information and strategies for advanced practitioners. In this Grand Rounds article, program chair Sandra Kurtin reviews the prognosis, risk assessment, and treatment for patients with chronic lymphocytic leukemia and assesses four case studies. You can read Parts 1 and 2 in previous issues of JADPRO or online at advancedpractitioner.com. Check out apsho.org/lectures for information on registering for upcoming JADPRO Regional Lectures this year at a location near you.
Synthesis of Sparse Linear Array for Directional Modulation via Convex Optimization

The design of a directional modulation (DM) signal by a phased array is one of the important topics in the field of physical layer security communication. In this paper, we synthesize a sparse array for DM based on convex optimization. The main idea is that a nonconvex optimization problem associated with <inline-formula> <tex-math notation="LaTeX">$\ell _{0}$ </tex-math></inline-formula>-norm is formulated for synthesizing a sparse array. To solve this nonconvex optimization problem, two different solutions are employed to relax the nonconvex optimization problem in a convex way: one is based on iterative reweighted <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula>-norm resulting in a superdirective array, the other is based on mixed integer programming resulting in a nonsuperdirective array. Furthermore, multiple important metrics of a DM transmitter, such as power efficiency, information beamwidth, and dynamic DM signal, are also considered in the optimization problem to achieve better performance of the DM signal via a sparse array. Simulation results show that the proposed synthesis method provides greater flexibility of controlling the security performance, power efficiency, and static or dynamic DM signal while the number of excitations is less than the uniformly spaced linear array in the benchmark problems.
Evaluation of Gastric Disease with Capsule Endoscopy

The clinical indication for capsule endoscopy has expanded from small bowel evaluation to include esophagus or colon evaluation. Nevertheless, the role of capsule endoscopy in evaluation of the stomach is very limited because of the large volume and surface. However, efforts to develop an active locomotion system for capsule manipulation in detailed gastric evaluation are ongoing, because the technique is non-invasive, convenient, and safe, and requires no sedation. Studies have successfully reported gastric evaluation using a magnetic-controlled capsule endoscopy system. Advances in technology suggest that capsule endoscopy will have a major role not only in the evaluation of gastric disorders but also in the pathologic diagnosis, intervention, and treatment of any gastrointestinal tract disorder.
A Set-Aware Key-Value Store on Shingled Magnetic Recording Drives with Dynamic Band

Key-value (KV) stores play an increasingly critical role in supporting diverse large-scale applications in modern data centers hosting terabytes of KV items which even might reside on a single server due to virtualization purpose. The combination of ever growing volume of KV items and storage/application consolidation is driving a trend of high storage density for KV stores. Shingled Magnetic Recording (SMR) represents a promising technology for increasing disk capacity, but it comes at a cost of poor random write performance and severe I/O amplification. Applications/software working with SMR devices need to be designed and optimized in an SMR-friendly manner. In this work, we present SEALDB, a Log-Structured Merge tree (LSM-tree) based key-value store that is specifically optimized for and works well with SMR drives via adequately addressing the poor random writes and severe I/O amplification issues. First, for LSM-trees, SEALDB concatenates SSTables of each compaction, and groups them into sets. Taking sets as the basic unit for compactions, SEALDB improves compaction efficiency by mitigating random I/Os. Second, SEALDB creates varying size bands on HM-SMR drives, named dynamic bands. Dynamic bands not only accommodate the storage of sets, but also eliminate the auxiliary write amplification from SMR drives. We demonstrate the advantages of SEALDB via extensive experiments in various workloads. Overall, SEALDB delivers impressive performance improvement. Compared with LevelDB, SEALDB is 3.42 times faster on random load due to improved compaction efficiency and eliminated auxiliary write amplification on SMR drives.
Dietary Protein and Energy Balance in Relation to Obesity and Co-morbidities

Dietary protein is effective for body-weight management, in that it promotes satiety, energy expenditure, and changes body-composition in favor of fat-free body mass. With respect to body-weight management, the effects of diets varying in protein differ according to energy balance. During energy restriction, sustaining protein intake at the level of requirement appears to be sufficient to aid body weight loss and fat loss. An additional increase of protein intake does not induce a larger loss of body weight, but can be effective to maintain a larger amount of fat-free mass. Protein induced satiety is likely a combined expression with direct and indirect effects of elevated plasma amino acid and anorexigenic hormone concentrations, increased diet-induced thermogenesis, and ketogenic state, all feed-back on the central nervous system. The decline in energy expenditure and sleeping metabolic rate as a result of body weight loss is less on a high-protein than on a medium-protein diet. In addition, higher rates of energy expenditure have been observed as acute responses to energy-balanced high-protein diets. In energy balance, high protein diets may be beneficial to prevent the development of a positive energy balance, whereas low-protein diets may facilitate this. High protein-low carbohydrate diets may be favorable for the control of intrahepatic triglyceride IHTG in healthy humans, likely as a result of combined effects involving changes in protein and carbohydrate intake. Body weight loss and subsequent weight maintenance usually shows favorable effects in relation to insulin sensitivity, although some risks may be present. Promotion of insulin sensitivity beyond its effect on body-weight loss and subsequent body-weight maintenance seems unlikely. In conclusion, higher-protein diets may reduce overweight and obesity, yet whether high-protein diets, beyond their effect on body-weight management, contribute to prevention of increases in non-alcoholic fatty liver disease NAFLD, type 2 diabetes and cardiovascular diseases is inconclusive.