Miracle-dz/UniFAR-FTUs huggingface dataset:
On secure transmission in hybrid satellite‐terrestrial cooperative network with untrusted energy harvesting relay and imperfect channel estimation

In this paper, the security performance of a hybrid satellite‐terrestrial cooperative network (HSTCN) with untrusted energy limited relay and imperfect channel state information (CSI) is investigated. The satellite and terrestrial links are assumed to follow Shadowed‐Rician fading and Rayleigh fading distributions respectively. The amplify‐and‐forward energy‐limited relay node employs power splitting relaying mode to scavenge energy from its received signals. By considering imperfect CSI between the relay and destination link, maximum ratio combining (MRC) and selection combining (SC) diversity schemes are utilized at the destination to enhance the quality of received signal‐to‐noise ratio (SNR) and aid jamming signal to prevent the untrusted relay from intercepting the satellite confidential data. Thus, to evaluate the HSTCN security performance, the exact analytical closed‐form expressions for the security outage probability (SOP) and connectivity outage probability (COP) are derived for each of the diversity combining techniques. Owing to trade‐off between SOP and COP, the effective secrecy throughput (EST) expression is obtained for the considered diversity schemes with a view to examine the security and reliability performance of the concerned system. Moreover, the impact of system parameters such as transmit SNR, channel coefficient, energy harvesting coefficient, and number of antennas are evaluated. In addition, the results reveal that the MRC has better SOP, COP, and EST performance compare with the SC. Also, it is found that the system EST degrades at high transmit SNR when the number of antennas at satellite is higher. The accuracy of the derived analytical expressions is confirmed by using Monte‐Carlo simulations.
A detailed introduction of different beamforming techniques used in 5G

The arrival of high‐speed internet facility such as the mmWave system or more commonly known as 5G wireless network is a prime impetus that is expected to be the driver for radical transformation in current communication methods. Apart from the numerous applications, an area where 5G is expected to be a game‐changer is the vehicle‐to‐everything or V2X network. This technology uses a road side unit (RSU) which provides wireless connectivity to vehicles, pedestrians, and so on, which may be either stationary or mobile so that their exact location can be known in real time. Researchers have demonstrated experimentally that 4G connectivity with such RSUs can provide a reliable low latency network for certain applications. For instance, for near‐perfect localization of each connected objects on the map, there is a need to stream GPS data, process semantic information from videos continually using computer vision. While these are simply for locating vehicles in real time so that road accident can be prevented. They are also the host of other features such as entertainment, health monitors, and mobile office that can be integrated inside a moving vehicle. To address the issues massive multi‐input multi‐output (MIMO), communication can be realized by using hybrid transceivers which uses a setup consisting of high‐dimensional analog phase shifters and power amplifier with dimensional digital signal processing units having low power. It is therefore vital to choose an apt beamforming design that will run on low energy. A comparison of different varieties of beamforming methodologies for determining the most efficient massive MIMO network is carried out here.
Prediction of Liver Disease using Regression Tree

Abstract— Data Mining plays a decisive role especially in medical domain. Decision trees are predominant model in machine learning. Decision trees are simple and very effective classification approach. The decision tree identifies the utmost prime features of a given problem. One of the most common disease in India is Liver Cirrhosis. It is distinctly difficult to uncover Liver Cirrhosis in its initial stage. However early diagnosis of Liver Cirrhosis is highly important.The liver disease data set has a collection of distinguishing features that affect the healthy state of a patient. Machine Learning methods enable knowledge acquisition in early stages and use of this acquired knowledge plays an important role in solving problems like suppose if we want to predict whether the patient with the Liver Cirrhosis has also been suffering from Hepatitis C or not. In order to easily arrive at this knowledge certainly there is a need for fully integrated system. In this paper the collected Liver disease data set is analyzed and prognosticated whether the patient is suffering from liver cirrhosis or not.
Graph traversal aided detection in uplink MBM massive MIMO based on socio‐cognitive knowledge of swarm optimization

Media‐based modulation (MBM) plays a crucial role in enhancing the spectral efficiency and energy efficiency of massive MIMO (mMIMO) systems for 5G and beyond wireless communications. In MBM, multiple parasitic elements, also termed as radio frequency (RF) mirrors, are placed near the transmit antennas for generating different channel fade realizations. These realizations are obtained by ON/OFF switching of RF mirrors. One of those channel fade realizations is selected (using a part of the incoming information bits) for transmitting a part of the information bits utilizing a symbol chosen from the conventional constellation set (using another part of the incoming information bits). Transmission of a symbol through one of the available channel realizations constitutes a sparse transmit vector for each user in MBM‐mMIMO. The sparse nature of transmitted symbols from multiple users and inter‐user interference makes the symbol detection in uplink MBM‐mMIMO challenging. Therefore, in this article, the problem of symbol detection in MBM‐mMIMO is analyzed from a graph‐theoretical point of view, and a graph‐traversal aided low‐complexity symbol detection algorithm is proposed inspired by socio‐cognitive learning of swarm optimization. Also, the convergence characteristic of the proposed technique is investigated theoretically. Further, an analytical expression of upper bound on bit error rate performance is derived and corroborated through simulations. Viability and robustness of the proposed technique are also justified through simulations over state‐of‐art detection techniques, under both perfect and imperfect channel state information scenarios.
CHEAP: An Efficient Localized Area Coverage Maintenance Protocol for Wireless Sensor Networks

Over the course of operation, a wireless sensor network can experience failures that are detrimental to the underlying application’s objectives. In this paper, we address the problem of restoring coverage ratio of a damaged area ( hole ) using only the neighboring nodes. Most existing solutions fail to simultaneously prevent new holes formation, collisions, oscillations, cascaded movements, and overlapped areas. To do this, we propose an intersection points-based strategy to properly locate and characterize any type of coverage hole. Then, we allow nodes, whether or not redundant, to coordinate their movements and ranges in order to effectively eliminate the detected hole. We suggest for that purpose, a tabu search based optimization scheme along with a location-allocation model through a mixed integer linear program. Simulation results show that our protocol significantly increases the network’s resilience
Prospective Randomized Controlled Study on an Innovative Mini-open Technique Versus Standard Percutaneous Technique to Avoid Sural Nerve Injury During Acute Achilles Tendon Repair

Percutaneous and mini-open repair of the tendo-Achilles have proved good results according to several authors. However, sural nerve injury is one of the most important complications that may be associated with this technique because of either entangling the nerve inside the suture laterally or piercing the nerve with the needle. The authors present a simple and reproducible technique to avoid injury of the sural nerve with the mini-open repair of the Achilles tendon. The patients were split into 2 groups, each consisted of 20 patients. They were randomly allocated using identical envelopes to either treatment by the new modified technique of surgical repair. The study group, and the conventional mini-open technique; the control group. The patients were assessed clinically at 1, 6, 12 months, and at the end of follow-up postoperatively. The outcome was assessed using the Weber Modification of Thermann score. The demographic data and the gap size were comparable between both groups with no statistical significance. The mean Weber Modification of Thermann score For the study group was 86 (range, 80 to 95; SD, 5.062). It was better than that for the control group (mean, 83.25; range, 75 to 90; SD, 4.375). This was statistically significant (P=0.036). None of the cases in group I developed sural nerve injury, whereas 7 cases (35%) in group II developed sural nerve injury, and this was statistically significant (P=0.003*). None of the patients in both groups developed rerupture, surgical site tenderness, or skin-related complications. Our innovative surgical technique permitted avoidance of injury of the sural nerve during mini-open Achilles tendon repair, meanwhile retained all the advantages of the mini-open repair. Level of Evidence: Level I—a prospective randomized clinical trial.
Carbon support films for electron microscopy by deposition on an organic glass

The making of carbon films, mainly for use in electron microscopy, by evaporation on to a supercooled organic glass is described. The substrate is dibenzylamine tartrate, with an additive. When molten, standard support grids can be floated on it, so that the substrate is automatically flush with the upper surface of the grids. Large batches of grids can be made in this way without individual handling. Some of the physical properties of evaporated carbon films are discussed.
Force Measurements between Bacteria and Poly(ethylene glycol)-Coated Surfaces

The atomic force microscope (AFM) was used to directly measure the forces of interaction between E. coli D21 bacteria and hydrophilic glass or hydrophobic N-octadecyltrichlorosilane (OTS)-treated glass substrates coated with the block copolymers, poly(ethylene glycol) (PEG)−lysine dendron or Pluronic F127 surfactant, respectively. Short-range repulsive interactions between bacterial cells and substrates coated with the block copolymers were detected by the AFM over distances of separation comparable to the extended length of the PEG polymer chains. In contrast, glass and OTS-treated glass devoid of PEG−lysine dendron or Pluronic F127 exerted long-range attractive forces on E. coli D21 bacteria. Thus, polymeric brush layers appear to not only block the long-range attractive forces of interaction between bacteria and substrates but also introduce repulsive steric effects.
Reduction of Graphite Oxide with a Grignard Reagent for Facile In Situ Preparation of Electrically Conductive Polyolefin/Graphene Nanocomposites

A Grignard reagent, n-BuMgCl, is found to be able to reduce graphite oxide to form loosely aggregated graphene sheets immobilized with few Mg–Cl species. Further complexing with TiCl4 leads to a graphene-based supported catalyst that is ready for in situ olefin polymerization to access electrically conductive polyolefin/graphene nanocomposites. PP/graphene nanocomposites thus prepared possess a rather low electrical percolation threshold (approximately 0.2 vol%) and high conductivities (e.g., 3.92 S·m−1 at 1.2 vol%, 28.5 S·m−1 at 4.1 vol%, and 163.1 S·m−1 at 10.2 vol%).
Short title: Inferring probe shape and molecular structure from AFM images

Atomic force microscopy (AFM) can visualize functional biomolecules near the physiological condition, but the observed data are limited to the surface height of specimens. Since the AFM images highly depend on the probe tip shape, for successful inference of molecular structures from the measurement, the knowledge of the probe shape is required, but is often missing. Here, we developed a method of the rigid-body fitting to AFM images, which simultaneously finds the shape of the probe tip and the placement of the molecular structure via an exhaustive search. First, we examined four similarity scores via twin-experiments for four test proteins, finding that the cosine similarity score generally worked best, whereas the pixel-RMSD and the correlation coefficient were also useful. We then applied the method to two experimental high-speed-AFM images inferring the probe shape and the molecular placement. The results suggest that the appropriate similarity score can differ between target systems. For an actin filament image, the cosine similarity apparently worked best. For an image of the flagellar protein FlhAC, we found the correlation coefficient gave better results. This difference may partly be attributed to the flexibility in the target molecule, ignored in the rigid-body fitting. The inferred tip shape and placement results can be further refined by other methods, such as the flexible fitting molecular dynamics simulations. The developed software is publicly available.
BOPE: Boundary Order-Preserving Encryption Scheme in Relational Database System

Recently, researchers are being more interested in performing operations directly on the encrypted database with the help of the <inline-formula> <tex-math notation="LaTeX">$O$ </tex-math></inline-formula>rder-<inline-formula> <tex-math notation="LaTeX">$P$ </tex-math></inline-formula>reserving <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>ncryption (OPE) scheme. This mechanism enables executing many types of queries efficiently, such as range query and comparison, since it can preserve the relative order of underlying plaintext on ciphertexts. However, traditional OPE schemes cannot achieve ideal security against IND-OCPA (<italic>IND</italic> istinguishability under <inline-formula> <tex-math notation="LaTeX">$O$ </tex-math></inline-formula>rdered <inline-formula> <tex-math notation="LaTeX">$C$ </tex-math></inline-formula>hosen-<inline-formula> <tex-math notation="LaTeX">$P$ </tex-math></inline-formula>laintext <inline-formula> <tex-math notation="LaTeX">$A$ </tex-math></inline-formula>ttack) in a linear length of static encoding. Popa’s mutable scheme (namely, mOPE) is an effective solution to perform the range query in the database environment. In this paper, we propose a novel scheme, <inline-formula> <tex-math notation="LaTeX">$B$ </tex-math></inline-formula>oundary <inline-formula> <tex-math notation="LaTeX">$O$ </tex-math></inline-formula>rder-<inline-formula> <tex-math notation="LaTeX">$P$ </tex-math></inline-formula>reserving <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>ncryption (BOPE), to achieve high performance under ideal security. BOPE comprises two algorithms. One is a searching algorithm in which we propose a data structure, the boundary tree, to optimize the algorithm by cutting the scope of each iteration and reducing the rounds of interaction. The second algorithm is an updating algorithm for stale encoding, which determines whether to update the lookup table according to the type of each query, in order to avoid the time cost of redundant updates. We implemented and evaluated BOPE on a practical environment where we have achieved a performance increase of more than 10% from mOPE.
A Versatile Pneumatic Actuator Based on Scissor Mechanisms: Design, Modeling, and Experiments

A new versatile pneumatic actuator called a scissor-mechanism-based vacuum powered artificial muscle (SMVAM) is proposed in this letter. The actuator is composed of a soft airtight skin and a scissor structural skeleton, and based on the types of scissor units in the skeleton, the actuator can be designed into linear or curvilinear types. The principal motion of the actuator is the contraction process driven by negative pressure to generate a large force and considerable contraction ratio, and the extension process of the actuator driven by positive pressure is the restoration motion of the actuator. The design method for SMVAMs and a quasi-static model to estimate the blocked force of the actuators are developed. Based on the experimental results, the actuators can generate a maximum contraction ratio of 80% and a large force of approximately 300 N in the vertical direction and can also achieve contraction and extension routines in a nonvertical manner with a tip payload. Furthermore, the case study has shown the promise of the actuator for different applications.
A Lumped-Parameter Equivalent Circuit Model for Perovskite Solar Cells’ S-Shaped I-V Kinks

A lumped-parameter circuit model is proposed to describe the S-shaped I-V characteristics with current kinks exhibited in perovskite solar cells (PSCs). The physics-based model represents the electrical effect of the electrode contact interface. A Difference-Microvariation (DM) principle is used to derive the explicit solution of the model, which gives accurate and efficient descriptions for the current kinks of PSCs in a single-piece formula. The good agreement between our proposed model and numerical iteration results or reconstructed experimental data proves its validity. We believe that, the improved model can provide optimization direction for device process. Meanwhile, the proposed DM principle can perform as an efficient and serviceable tool to implement the lumped-parameter model compactly into TCAD simulators of PSCs.
Soil Moisture Estimation for Wheat Crop Using Dual-Pol L-Band SAR Data

Soil moisture retrieval over the vegetated soil surfaces using Synthetic Aperture Radar (SAR) data is a challenging issue. Presence of vegetation over soil surface makes the interaction of the radar signal with the soil more complex. Several studies used the Water Cloud Model (WCM) to separate vegetation effect on the soil backscatter while estimating the soil moisture. The general form of WCM utilizes one or two vegetation descriptors (e.g., Vegetation Water Content (VWC) and Leaf Area Index (LAI)) in determining the vegetation contribution. Eventually, these descriptors replaced by vegetation metric derived from ancillary sources (e.g., Normalized Difference Vegetation Index-NDVI). This ancillary data may not be available close to the date of SAR data acquisition due to several reasons. To circumvent these challenges, we use SAR derived vegetation descriptors in estimating soil moisture over wheat fields. We studied the performance of four different descriptors (viz., VWC, NDVI, cross-pol ratio (CPR), Dual-pol Radar Vegetation Index (DpRVI)) for estimating soil moisture using WCM. SAR derived vegetation descriptors for dual-pol data provided a reliable accuracy with a r value of 0.86 and RMSE of 5.9% (DpRVI-VV) as compared to NDVI. HH polarisation outperformed VV polarisation agreeing with the fact that vertically oriented crops less affects horizontally polarized signal.
A Distributed System for Multiscale Feature Extraction and Semantic Classification of Large-Scale Lidar Point Clouds

Managing and processing large-scale point clouds are much needed for the exploration and contextual understanding of the data. Hence, we explore the use of a widely used big data analytics framework, Apache Spark, in distributed systems for large-scale point cloud processing. To effectively use Spark, we propose to use its integration with Cassandra for persistent storage, and to appropriately partition the point cloud across the nodes in the distributed system. We use this integrated framework for multiscale feature extraction and semantic classification using random forest classifier. We have shown the efficacy of our proposed application through our results in the DALES aerial LiDAR point cloud.
Reducing Dynamism in DRAM With Bistable MEMS Switch as Sleep Transistor

We demonstrate the bistable microelectromechanical system (MEMS) sleep-transistor for CMOS integrated circuits (ICs). The sleep transistor has infinite sleep mode resistance and ~2.5-<inline-formula> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula> resistance in active mode. The hold bias in active mode is zero for the bistable MEMS sleep transistor. The proposed bistable MEMS switch is an ideal candidate for gating the power-hungry digital circuits. The dynamic random access memory (DRAM) supply rails gated with bistable MEMS sleep transistors offer ~6 order reduction in refresh rate. This article also reports on the design guidelines for the CMOS compatible fabrication of bistable MEMS sleep transistor. Only ~0.31 pJ of energy is consumed, in toggling between the modes of bistable MEMS sleep transistor. The MEMS gate can drive large area CMOS circuit blocks with fuse current density of ~0.5 mA/<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}^{{2}}$ </tex-math></inline-formula>. Furthermore, the fabrication of the bistable MEMS sleep transistor is critical in the aspect that its design is a play between restoring and adhesion forces.
Q-learning in Continuous Action Space by Extending EVA

Today, in order to use reinforcement learning in the real world, we need to improve the efficiency of reinforcement learning in continuous action spaces. In this study, we propose Q-learning in continuous action space based on an agent’s past series of experiences (i.e., trajectory information). We evaluate the effectiveness of our proposed method by conducting comparative experiments on several tasks.
Multi-Objective Online Task Allocation in Spatial Crowdsourcing Systems

In this work we aim to provide an efficient solution to the problem of online task allocation in spatial crowdsourcing systems. We focus on the objectives of platform utility maximization and worker utility maximization, yet the proposed schema is generic enough to accommodate more objectives. The goal is to find an allocation of tasks to workers that maximizes the platform’s profit and reliability of the results, while simultaneously assigns tasks based on the users’ interests to increase user engagement and hence the probability that the users will complete the tasks on time. Our scheme works well in highly fluctuating environments where the tasks to be executed require that the workers meet certain criteria of expertise, availability, reliability, etc. Our detailed experimental evaluation illustrates the benefits and practicality of our approach and demonstrates that our approach outperforms its competitors.
Dual Buffer Layers for Developing Electrochemical Metallization Memory With Low Current and High Endurance

In this letter, the dual buffer layers of AgInSbTe (AIST) and monolayer defective graphene (DG) are introduced into amorphous carbon (a-C)-based electrochemical metallization (ECM) type memristor. The advantages of promoting Ag dissolution and localizing cation diffusion region of AIST and DG layers can effectively suppress the well-known current overshoot issue and break the current-retention dilemma. Compared with its counterpart without buffer layer (Ag/a-C/Pt), the device with dual buffer layers (Ag/AIST/DG/a-C/Pt) presents excellent resistive switching (RS) performance, such as lower forming voltage with reduced overshoot current, smaller parameter fluctuations, and better cycling endurance. More importantly, the nonvolatile RS with low operation current of 10 <inline-formula> <tex-math notation="LaTeX">$\mu \text{A}$ </tex-math></inline-formula> and remarkable endurance (<inline-formula> <tex-math notation="LaTeX">$> {3.1}\times {10}^{{7}}$ </tex-math></inline-formula> cycles) is realized, which is among the best of reported a-C-based ECM memories. Benefit from the low operation current, the device also shows the capacity of multilevel memory with six nonvolatile resistance states through regulating the compliance current.