bluuebunny/crossref_metadata_2025 huggingface dataset:
Peptides with Dual Antimicrobial–Anticancer Activity: Strategies to Overcome Peptide Limitations and Rational Design of Anticancer Peptides
Authors: Liscano Yamil , Oñate-Garzón Jose , Delgado Jean Paul
Published: September 2020

Peptides are naturally produced by all organisms and exhibit a wide range of physiological, immunomodulatory, and wound healing functions. Furthermore, they can provide with protection against microorganisms and tumor cells. Their multifaceted performance, high selectivity, and reduced toxicity have positioned them as effective therapeutic agents, representing a positive economic impact for pharmaceutical companies. Currently, efforts have been made to invest in the development of new peptides with antimicrobial and anticancer properties, but the poor stability of these molecules in physiological environments has triggered a bottleneck. Therefore, some tools, such as nanotechnology and in silico approaches can be applied as alternatives to try to overcome these obstacles. In silico studies provide a priori knowledge that can lead to the development of new anticancer peptides with enhanced biological activity and improved stability. This review focuses on the current status of research in peptides with dual antimicrobial–anticancer activity, including advances in computational biology using in silico analyses as a powerful tool for the study and rational design of these types of peptides.
Shape-Memory Polymeric Artificial Muscles: Mechanisms, Applications and Challenges
Authors: Chen Yujie , Chen Chi , Rehman Hafeez Ur , Zheng Xu , Li Hua , Liu Hezhou , Hedenqvist Mikael S.
Published: September 2020

Shape-memory materials are smart materials that can remember an original shape and return to their unique state from a deformed secondary shape in the presence of an appropriate stimulus. This property allows these materials to be used as shape-memory artificial muscles, which form a subclass of artificial muscles. The shape-memory artificial muscles are fabricated from shape-memory polymers (SMPs) by twist insertion, shape fixation via Tm or Tg, or by liquid crystal elastomers (LCEs). The prepared SMP artificial muscles can be used in a wide range of applications, from biomimetic and soft robotics to actuators, because they can be operated without sophisticated linkage design and can achieve complex final shapes. Recently, significant achievements have been made in fabrication, modelling, and manipulation of SMP-based artificial muscles. This paper presents a review of the recent progress in shape-memory polymer-based artificial muscles. Here we focus on the mechanisms of SMPs, applications of SMPs as artificial muscles, and the challenges they face concerning actuation. While shape-memory behavior has been demonstrated in several stimulated environments, our focus is on thermal-, photo-, and electrical-actuated SMP artificial muscles.
Five Novel Non-Sialic Acid-Like Scaffolds Inhibit In Vitro H1N1 and H5N2 Neuraminidase Activity of Influenza a Virus
Authors: Márquez-Domínguez Luis , Reyes-Leyva Julio , Herrera-Camacho Irma , Santos-López Gerardo , Scior Thomas
Published: September 2020

Neuraminidase (NA) of influenza viruses enables the virus to access the cell membrane. It degrades the sialic acid contained in extracellular mucin. Later, it is responsible for releasing newly formed virions from the membrane of infected cells. Both processes become key functions within the viral cycle. Therefore, it is a therapeutic target for research of the new antiviral agents. Structure–activity relationships studies have revealed which are the important functional groups for the receptor–ligand interaction. Influenza virus type A NA activity was inhibited by five scaffolds without structural resemblance to sialic acid. Intending small organic compound repositioning along with drug repurposing, this study combined in silico simulations of ligand docking into the known binding site of NA, along with in vitro bioassays. The five proposed scaffolds are N-acetylphenylalanylmethionine, propanoic 3-[(2,5-dimethylphenyl) carbamoyl]-2-(piperazin-1-yl) acid, 3-(propylaminosulfonyl)-4-chlorobenzoic acid, ascorbic acid (vitamin C), and 4-(dipropylsulfamoyl) benzoic acid (probenecid). Their half maximal inhibitory concentration (IC50) was determined through fluorometry. An acidic reagent 2′-O-(4-methylumbelliferyl)-α-dN-acetylneuraminic acid (MUNANA) was used as substrate for viruses of human influenza H1N1 or avian influenza H5N2. Inhibition was observed in millimolar ranges in a concentration-dependent manner. The IC50 values of the five proposed scaffolds ranged from 6.4 to 73 mM. The values reflect a significant affinity difference with respect to the reference drug zanamivir (p < 0.001). Two compounds (N-acetyl dipeptide and 4-substituted benzoic acid) clearly showed competitive mechanisms, whereas ascorbic acid reflected non-competitive kinetics. The five small organic molecules constitute five different scaffolds with moderate NA affinities. They are proposed as lead compounds for developing new NA inhibitors which are not analogous to sialic acid.
The Physiochemical Properties and Adsorption Characteristics of Processed Pomelo Peel as a Carrier for Epigallocatechin-3-Gallate
Authors: Wu Liangyu , Zhang Guoying , Lin Jinke
Published: September 2020

The NaOH-HCl- and ethanol-pretreated pomelo peel samples were prepared to apply to the batch adsorption for epigallocatechin-3-gallate (EGCG). The characteristics of peel samples were determined by Fourier transform infrared spectroscopy, scanning electron microscopy and a laser particle analyzer. The results of the physiochemical properties of the peel samples demonstrate that these peel samples have a promising adsorption capacity for EGCG, because of the increased potential binding sites on the surface compared with those of untreated peel samples. These two peel samples showed enhanced adsorption capacities of EGCG compared with that of unmodified peel in terms of the isothermal adsorption process, which could be described by both Langmuir and Freundlich models, with the theoretical maximum adsorption capacity of 77.52 and 94.34 mg g−1 for the NaOH-HCl and ethanol-treated peel samples, respectively. The adsorption kinetics demonstrated an excellent fitness to pseudo-second-order, showing that chemisorption was the rate-limiting step. The thermodynamics analysis revealed that the adsorption reaction was a spontaneous and endothermic process. This work highlights that the processed pomelo peels have outstanding adsorption capacities for EGCG, which could be promising candidates for EGCG delivering in functional food application.
Study of Antioxidant Properties of Agents from the Perspective of Their Action Mechanisms
Authors: Ivanova Alla , Gerasimova Elena , Gazizullina Elena
Published: September 2020

The creation and analysis of a large variety of existing methods for the evaluation of integrated antioxidant properties are quite relevant in connection with a range of biological mechanisms of the antioxidants (AO) action. In this work, the existing methods are correlated with mechanisms of antioxidant action. It is shown that the results obtained by various methods are mainly incomparable. This can be connected with the implementation of various mechanisms of antioxidant action in methods. The analysis of the literature data presented in this review indicates the difficulty of creating a universal method and the feasibility of using integrated approaches based on the use of several methods that implement and combine various mechanisms of the chemical conversion of antioxidants. This review describes methods for studying the chelating ability of antioxidants, except for methods based on electron and hydrogen atom transfer reactions, which are currently not widely covered in modern literature. With the description of each mechanism, special attention is paid to electrochemical methods, as the interaction of active oxygen metabolites of radical and non-radical nature with antioxidants has an electron/proton/donor-acceptor nature, which corresponds to the nature of electrochemical methods and suggests that they can be used to study the interaction.
Solid Circulating Velocity Measurement in a Liquid–Solid Micro-Circulating Fluidised Bed
Authors: do Nascimento Orlando L. , Reay David A. , Zivkovic Vladimir
Published: September 2020

Liquid–solid circulating fluidised beds (CFB) possess many qualities which makes them useful for industrial operations where particle–liquid contact is vital, e.g., improved heat transfer performance, and consequent uniform temperature, limited back mixing, exceptional solid–liquid contact. Despite this, circulating fluidised beds have seen no application in the micro-technology context. Liquid–solid micro circulating fluidised bed (µCFBs), which basically involves micro-particles fluidisation in fluidised beds within the bed of cross-section or inner diameter at the millimetre scale, could find potential applications in the area of micro-process and microfluidics technology. From an engineering standpoint, it is vital to know the solid circulating velocity, since that dictates the bed capability and operability as processing equipment. Albeit there are several studies on solid circulating velocity measurement in CFBs, this article is introducing the first experimental study on solid circulating velocity measurement in a CFB at micro-scale. The experimental studies were done in a novel micro-CFB which was fabricated by micro milling machining 1 mm2 cross-section channels in Perspex and in a 4 mm2 cross-section micro-CFB made by additive manufacturing technology. Soda-lime glass and polymethyl methacrylate (PMMA) micro-particles were employed as solid materials and tap water as the liquid medium. The digital particle image velocimetry (PIV) method was used as a measurement technique to determine the particle velocity in the micro-CFB system and validated by the valve accumulation technique using a novel magnetic micro-valve. The measured critical transition velocity, Ucr, is comparable to the particle terminal velocity, i.e., the normalised transition velocity is approximately 1 in line with macroscopic systems results and our previous study using simple visual observation. As in macroscopic CFB systems, Ucr decreased with solid inventory (1–9%) and finally becomes stable when the solid inventory is high enough (10–25%) and it increases with a reduction in particle size and density.
Validating the Efficiency of the FeS2 Method for Elucidating the Mechanisms of Contaminant Removal Using Fe0/H2O Systems
Authors: Xiao Minhui , Cui Xuesong , Hu Rui , Gwenzi Willis , Noubactep Chicgoua
Published: September 2020

There is growing interest in using pyrite minerals (FeS2) to enhance the efficiency of metallic iron (Fe0) for water treatment (Fe0/H2O systems). This approach contradicts the thermodynamic predicting suppression of FeS2 oxidation by Fe0 addition. Available results are rooted in time series correlations between aqueous and solid phases based on data collected under various operational conditions. Herein, the methylene blue method (MB method) is used to clarify the controversy. The MB method exploits the differential adsorptive affinity of MB onto sand and sand coated with iron corrosion products to assess the extent of Fe0 corrosion in Fe0/H2O systems. The effects of the addition of various amounts of FeS2 to a Fe0/sand mixture (FeS2 method) on MB discoloration were characterized in parallel quiescent batch experiments for up to 71 d (pH0 = 6.8). Pristine and aged FeS2 specimens were used. Parallel experiments with methyl orange (MO) and reactive red 120 (RR120) enabled a better discussion of the achieved results. The results clearly showed that FeS2 induces a pH shift and delays Fe precipitation and sand coating. Pristine FeS2 induced a pH shift to values lower than 4.5, but no quantitative MB discoloration occurred after 45 d. Aged FeS2 could not significantly shift the pH value (final pH ≥ 6.4) but improved the MB discoloration. The used systematic sequence of experiments demonstrated that adsorption and coprecipitation are the fundamental mechanisms of contaminant removal in Fe0/H2O systems. This research has clarified the reason why a FeS2 addition enhances the efficiency of Fe0 environmental remediation.
Identification of Motor and Mental Imagery EEG in Two and Multiclass Subject-Dependent Tasks Using Successive Decomposition Index
Authors: Sadiq Muhammad Tariq , Yu Xiaojun , Yuan Zhaohui , Aziz Muhammad Zulkifal
Published: September 2020

The development of fast and robust brain–computer interface (BCI) systems requires non-complex and efficient computational tools. The modern procedures adopted for this purpose are complex which limits their use in practical applications. In this study, for the first time, and to the best of our knowledge, a successive decomposition index (SDI)-based feature extraction approach is utilized for the classification of motor and mental imagery electroencephalography (EEG) tasks. First of all, the public datasets IVa, IVb, and V from BCI competition III were denoised using multiscale principal analysis (MSPCA), and then a SDI feature was calculated corresponding to each trial of the data. Finally, six benchmark machine learning and neural network classifiers were used to evaluate the performance of the proposed method. All the experiments were performed for motor and mental imagery datasets in binary and multiclass applications using a 10-fold cross-validation method. Furthermore, computerized automatic detection of motor and mental imagery using SDI (CADMMI-SDI) is developed to describe the proposed approach practically. The experimental results suggest that the highest classification accuracy of 97.46% (Dataset IVa), 99.52% (Dataset IVb), and 99.33% (Dataset V) was obtained using feedforward neural network classifier. Moreover, a series of experiments, namely, statistical analysis, channels variation, classifier parameters variation, processed and unprocessed data, and computational complexity, were performed and it was concluded that SDI is robust for noise, and a non-complex and efficient biomarker for the development of fast and accurate motor and mental imagery BCI systems.
A Novel NiFe2O4/Paper-Based Magnetoelastic Biosensor to Detect Human Serum Albumin
Authors: Guo Xing , Liu Rong , Li Hongmei , Wang Jingzhe , Yuan Zhongyun , Zhang Wendong , Sang Shengbo
Published: September 2020

For the first time, a novel NiFe2O4/paper-based magnetoelastic (ME) biosensor was developed for rapid, sensitive, and portable detection of human serum albumin (HSA). Due to the uniquely magnetoelastic effect of NiFe2O4 nanoparticles and the excellent mechanical properties of the paper, the paper-based ME biosensor transforms the surface stress signal induced by the specific binding of HSA and antibody modified on the paper into the electromagnetic signal. The accumulated binding complex generates a compressive stress on the biosensor surface, resulting in a decrease in the biosensor’s static magnetic permeability, which correlates to the HSA concentrations. To improve the sensitivity of the biosensor, the concentration of NiFe2O4 nanofluid and the impregnated numbers of the NiFe2O4 nanofluid-impregnated papers were optimized. The experimental results demonstrated that the biosensor exhibited a linear response to HSA concentrations ranging from 10 μg∙mL−1 to 200 μg∙mL−1, with a detection limit of 0.43 μg∙mL−1, which is significantly lower than the minimal diagnosis limit of microalbuminuria. The NiFe2O4/paper-based ME biosensor is easy to fabricate, and allows the rapid, highly-sensitive, and selective detection of HSA, providing a valuable analytical device for early monitoring and clinical diagnosis of microalbuminuria and nephropathy. This study shows the successful integration of the paper-based biosensor and the ME sensing analytical method will be a highly-sensitive, easy-to-use, disposable, and portable alternative for point-of-care monitoring.
Catalytic Gold Deposition for Ultrasensitive Optical Immunosensing of Prostate Specific Antigen
Authors: Cid-Barrio Laura , Ruiz Encinar Jorge , Costa-Fernández José Manuel
Published: September 2020

A major challenge in the development of bioanalytical methods is to achieve a rapid and robust quantification of disease biomarkers present at very low concentration levels in complex biological samples. An immunoassay platform is presented herein for ultrasensitive and fast detection of the prostate-specific antigen (PSA), a well-recognized cancer biomarker. A sandwich type immunosensor has been developed employing a detection antibody labeled with inorganic nanoparticles acting as tags for further indirect quantification of the analyte. The required high sensitivity is then achieved through a controlled gold deposition on the nanoparticle surface, carried out after completing the recognition step of the immunoassay, thus effectively amplifying the size of the nanoparticles from nm to µm range. Due to such an amplification procedure, quantification of the biomolecule could be carried out directly on the immunoassay plates using confocal microscopy for measurement of the reflected light produced by gold-enlarged nanostructures. The high specificity of the immunoassay was demonstrated with the addition of a major abundant protein in serum (albumin) at much higher concentrations. An extremely low detection limit for PSA quantification (LOD of 1.1 fg·mL−1 PSA) has been achieved. Such excellent LOD is 2–3 orders of magnitude lower than the clinically relevant PSA levels present in biological samples (4–10 ng·mL−1) and even to monitor eventual recurrence after clinical treatment of a prostate tumor (0.1 ng·mL−1). In fact, the broad dynamic range obtained (4 orders of magnitude) would allow the PSA quantification of diverse samples at very different relevant levels.
Cognitive Radio Networks for Internet of Things and Wireless Sensor Networks
Authors: Yu Heejung , Zikria Yousaf Bin
Published: September 2020

Recent innovation, growth, and deployment of internet of things (IoT) networks are changing the daily life of people. 5G networks are widely deployed around the world, and they are important for continuous growth of IoT. The next generation cellular networks and wireless sensor networks (WSN) make the road to the target of the next generation IoT networks. The challenges of the next generation IoT networks remain in reducing the overall network latency and increasing throughput without sacrificing reliability. One feasible alternative is coexistence of networks operating on different frequencies. However, data bandwidth support and spectrum availability are the major challenges. Therefore, cognitive radio networks (CRN) are the best available technology to cater to all these challenges for the co-existence of IoT, WSN, 5G, and beyond-5G networks.
Spatial Modulation and MP-WFRFT-Aided Multi-Beam Wireless Communication Scheme Based On Random Frequency Diverse Array
Authors: Gao Jianbang , Qiu Bin , Zhou Jing
Published: September 2020

A security-enhanced, spectral-efficient, and power-efficient multi-beam wireless communication scheme based on random frequency diverse array (RFDA) is proposed in this paper. (AN)-aided directional modulation (DM) schemes. Furthermore, with the aid of spatial modulation (SM) technology and cooperative legitimate users (LUs), we can transmit more information bits by the use of LU number informations than the single modulation symbols. Unlike conventional zero-forcing (ZF) beamforming for multi-beam DM, we design a FDA beamforming vector for each LU based on the minimum transmit power method. Numerical simulations show that (1) the proposed scheme is power-efficient compared to the conventional schemes, (2) the proposed scheme can transmit more information bits than the conventional schemes, and (3) the proposed scheme can ensure communication security when eavesdroppers (Eves) are proximal to LUs or even in same locations.
Ultrasonic Guided Wave Testing on Cross-Ply Composite Laminate: An Empirical Study
Authors: Aranguren Gerardo , Etxaniz Josu , Cantero-Chinchilla Sergio , Gil-Garcia Jose M. , Malik Muhammad Khalid
Published: September 2020

Structural health monitoring comprises a set of techniques to detect defects appearing in structures. One of the most viable techniques is based on the guided ultrasonic wave test (UGWT), which consists of emitting waves throughout the structure, acquiring the emitted waves with various sensors, and processing the waves to detect changes in the structure. The UGWT of layered composite structures is challenging due to the anisotropic wave propagation characteristics of such structures and to the high signal attenuation that the waves experience. Hence, very low amplitude signals that are hard to distinguish from noise are typically recovered. This paper analyzes the propagation of guided waves along a cross-ply composite laminate following an empirical methodology. The research compares several implementations for UGWT with piezoelectric wafer active sensors. The reference for comparison is set on a basic mode, which considers the application of nominal voltage to a single sensor. The attenuation and spreading of the waves in several directions are compared when more energy is applied to the monitored structure. In addition, delayed multiple emission is also considered in multisensor tests. The goal of all the UGWT configurations is to transmit more energy to the structure such that the echoes of the emission are of greater amplitude and they ease the signal processing. The study is focused on the realization of viable monitoring systems for aeronautical composite made structures.
NAS-HRIS: Automatic Design and Architecture Search of Neural Network for Semantic Segmentation in Remote Sensing Images
Authors: Zhang Mingwei , Jing Weipeng , Lin Jingbo , Fang Nengzhen , Wei Wei , Woźniak Marcin , Damaševičius Robertas
Published: September 2020

The segmentation of high-resolution (HR) remote sensing images is very important in modern society, especially in the fields of industry, agriculture and urban modelling. Through the neural network, the machine can effectively and accurately extract the surface feature information. However, using the traditional deep learning methods requires plentiful efforts in order to find a robust architecture. In this paper, we introduce a neural network architecture search (NAS) method, called NAS-HRIS, which can automatically search neural network architecture on the dataset. The proposed method embeds a directed acyclic graph (DAG) into the search space and designs the differentiable searching process, which enables it to learn an end-to-end searching rule by using gradient descent optimization. It uses the Gumbel-Max trick to provide an efficient way when drawing samples from a non-continuous probability distribution, and it improves the efficiency of searching and reduces the memory consumption. Compared with other NAS, NAS-HRIS consumes less GPU memory without reducing the accuracy, which corresponds to a large amount of HR remote sensing imagery data. We have carried out experiments on the WHUBuilding dataset and achieved 90.44% MIoU. In order to fully demonstrate the feasibility of the method, we made a new urban Beijing Building dataset, and conducted experiments on satellite images and non-single source images, achieving better results than SegNet, U-Net and Deeplab v3+ models, while the computational complexity of our network architecture is much smaller.
Prediction of End-Of-Season Tuber Yield and Tuber Set in Potatoes Using In-Season UAV-Based Hyperspectral Imagery and Machine Learning
Authors: Sun Chen , Feng Luwei , Zhang Zhou , Ma Yuchi , Crosby Trevor , Naber Mack , Wang Yi
Published: September 2020

Potato is the largest non-cereal food crop in the world. Timely estimation of end-of-season tuber production using in-season information can inform sustainable agricultural management decisions that increase productivity while reducing impacts on the environment. Recently, unmanned aerial vehicles (UAVs) have become increasingly popular in precision agriculture due to their flexibility in data acquisition and improved spatial and spectral resolutions. In addition, compared with natural color and multispectral imagery, hyperspectral data can provide higher spectral fidelity which is important for modelling crop traits. In this study, we conducted end-of-season potato tuber yield and tuber set predictions using in-season UAV-based hyperspectral images and machine learning. Specifically, six mainstream machine learning models, i.e., ordinary least square (OLS), ridge regression, partial least square regression (PLSR), support vector regression (SVR), random forest (RF), and adaptive boosting (AdaBoost), were developed and compared across potato research plots with different irrigation rates at the University of Wisconsin Hancock Agricultural Research Station. Our results showed that the tuber set could be better predicted than the tuber yield, and using the multi-temporal hyperspectral data improved the model performance. Ridge achieved the best performance for predicting tuber yield (R2 = 0.63) while Ridge and PLSR had similar performance for predicting tuber set (R2 = 0.69). Our study demonstrated that hyperspectral imagery and machine learning have good potential to help potato growers efficiently manage their irrigation practices.
Towards an Ultra Sensitive Hybrid Mass Sensor Based on Mode Localization without Resonance Tracking
Authors: Humbert Claude , Walter Vincent , Kacem Najib , Leblois Thérèse
Published: September 2020

We present a mode localized mass sensor prototype based on a hybrid system excited at a fixed frequency slightly below the resonances. Indeed, we show, both theoretically and experimentally, that this condition yields higher sensitivities and similar sensitivity ranges than that of resonance peak tracking while being less time consuming than a classical open-loop configuration due to the absence of frequency sweep. The system is made of a quartz resonator and a hardware that includes a resonator and the coupling. The digital aspect allows maximum sensitivity to be achieved with a fine tuning of the different parameters and the implementation of a coupling, regardless of the physical resonator geometry. This allows the generation of mode localization on shear waves resonant structures such as the quartz cristal microbalance widely used in biosensing. This solution has been successfully implemented using resin micro balls depositions. The sensitivities reach almost their maximum theoretical values which means this fixed frequency method has the potential to reach lower limit of detection than the open loop frequency tracking method.
Tracking the Insider Attacker: A Blockchain Traceability System for Insider Threats
Authors: Hu Teng , Xin Bangzhou , Liu Xiaolei , Chen Ting , Ding Kangyi , Zhang Xiaosong
Published: September 2020

The insider threats have always been one of the most severe challenges to cybersecurity. It can lead to the destruction of the organisation’s internal network system and information leakage, which seriously threaten the confidentiality, integrity and availability of data. To make matters worse, since the attacker has authorized access to the internal network, they can launch the attack from the inside and erase their attack trace, which makes it challenging to track and forensics. A blockchain traceability system for insider threats is proposed in this paper to mitigate the issue. First, this paper constructs an insider threat model of the internal network from a different perspective: insider attack forensics and prevent insider attacker from escaping. Then, we analyze why it is difficult to track attackers and obtain evidence when an insider threat has occurred. After that, the blockchain traceability system is designed in terms of data structure, transaction structure, block structure, consensus algorithm, data storage algorithm, and query algorithm, while using differential privacy to protect user privacy. We deployed this blockchain traceability system and conducted experiments, and the results show that it can achieve the goal of mitigating insider threats.
Resistance of IoT Sensors against DDoS Attack in Smart Home Environment
Authors: Huraj Ladislav , Šimon Marek , Horák Tibor
Published: September 2020

Smart devices along with sensors are gaining in popularity with the promise of making life easier for the owner. As the number of sensors in an Internet of Things (IoT) system grows, a question arises as to whether the transmission between the sensors and the IoT devices is reliable and whether the user receives alerts correctly and in a timely manner. Increased deployment of IoT devices with sensors increases possible safety risks. It is IoT devices that are often misused to create Distributed Denial of Service (DDoS) attacks, which is due to the weak security of IoT devices against misuse. The article looks at the issue from the opposite point of view, when the target of a DDoS attack are IoT devices in a smart home environment. The article examines how IoT devices and the entire smart home will behave if they become victims of a DDoS attack aimed at the smart home from the outside. The question of security was asked in terms of whether a legitimate user can continue to control and receive information from IoT sensors, which is available during normal operation of the smart home. The case study was done both from the point of view of the attack on the central units managing the IoT sensors directly, as well as on the smart-home personal assistant systems, with which the user can control the IoT sensors. The article presents experimental results for individual attacks performed in the case study and demonstrates the resistance of real IoT sensors against DDoS attack. The main novelty of the article is that the implementation of a personal assistant into the smart home environment increases the resistance of the user’s communication with the sensors. This study is a pilot testing the selected sensor sample to show behavior of smart home under DDoS attack.
Women Trading Sex in a U.S.-Mexico Border City: A Qualitative Study of the Barriers and Facilitators to Finding Community and Voice
Authors: Gonzalez Claudia , Brouwer Kimberly C. , Reed Elizabeth , Nicholls Melanie J. , Kim Jessica , Gonzalez-Zuniga Patricia E. , Gaeta-Rivera Andrés , Urada Lianne A.
Published: September 2020

Poverty and income inequality can increase a woman’s decision to engage in risky transactional sex, and may lead to unimaginable harms, such as violence, substance use, and human trafficking. This study examines the facilitators and barriers to finding community and voice among women trading sex in Tijuana, Mexico, and what factors, such as socio-structural support, violence, and substance use, may impact their potential to engage with others, including human service providers. Sixty qualitative in-depth interviews were conducted with women trading sex in Tijuana, Mexico. Researchers met with participants for in-depth-face-to-face structured interviews. Data were coded using ATLAS.ti. Participants were aged 19–73 (mean: 37), 98% were of Mexican nationality, 90% reported trading sex independent of the control of others, with 58% identified as independent and street-based. Thirty percent of women trading sex reported substance use (excluding marijuana) and 20% reported injection drug use within 30 days. The majority reported no involvement in mobilization activities, but 85% expressed interest. However, barriers included stigma, cultural gender norms, partner violence, and privacy in regards to disclosure of sex trade involvement, moral conflict (revealing one’s involvement in sex trade), involvement in substance use, human trafficking, and feeling powerless. Facilitators were having a safe space to meet, peer support, self-esteem, feeling heard, knowledge of rights, economic need to support families, and staying healthy. Findings imply the potential to go beyond mobilizing limited groups of women in the sex trade and instead involve whole community mobilization; that is, to reach and include the more vulnerable women (substance use, trafficked) in supportive services (social services, exit strategies, better healthcare opportunities, and/or education for healthcare providers to help break societal stigmas regarding women in the sex trade) and to change the status of women in society in general.
Deep MLP-CNN Model Using Mixed-Data to Distinguish between COVID-19 and Non-COVID-19 Patients
Authors: Ahsan Md Manjurul , E. Alam Tasfiq , Trafalis Theodore , Huebner Pedro
Published: September 2020

The limitations and high false-negative rates (30%) of COVID-19 test kits have been a prominent challenge during the 2020 coronavirus pandemic. Manufacturing those kits and performing the tests require extensive resources and time. Recent studies show that radiological images like chest X-rays can offer a more efficient solution and faster initial screening of COVID-19 patients. In this study, we develop a COVID-19 diagnosis model using Multilayer Perceptron and Convolutional Neural Network (MLP-CNN) for mixed-data (numerical/categorical and image data). The model predicts and differentiates between COVID-19 and non-COVID-19 patients, such that early diagnosis of the virus can be initiated, leading to timely isolation and treatments to stop further spread of the disease. We also explore the benefits of using numerical/categorical data in association with chest X-ray images for screening COVID-19 patients considering both balanced and imbalanced datasets. Three different optimization algorithms are used and tested:adaptive learning rate optimization algorithm (Adam), stochastic gradient descent (Sgd), and root mean square propagation (Rmsprop). Preliminary computational results show that, on a balanced dataset, a model trained with Adam can distinguish between COVID-19 and non-COVID-19 patients with a higher accuracy of 96.3%. On the imbalanced dataset, the model trained with Rmsprop outperformed all other models by achieving an accuracy of 95.38%. Additionally, our proposed model outperformed selected existing deep learning models (considering only chest X-ray or CT scan images) by producing an overall average accuracy of 94.6% ± 3.42%.
An Experimental Study on the Water Hammer with Cavity Collapse under Multiple Interruptions
Authors: Zhao Li , Yang Yusi , Wang Tong , Han Wensheng , Wu Rongchu , Wang Pengli , Wang Qiaoning , Zhou Liang
Published: September 2020

Pressurized pipeline system damage is primarily caused by the highly destructive water hammer force. Currently, research on water hammer-caused collapse is mostly based on single-point collapse cases, but water hammer research, which involves multipoint collapse, is insufficient. Here, we establish an experimental platform to realize water hammers with multipoint collapse. With different schemes, i.e., various initial flow rates and valve closing speeds, we observed the hydraulic transient process with a high-speed camera, analyzed its characteristics and explained experimental phenomena with theoretical knowledge. Using experimental data analysis, we summarized the influencing factors and laws of the cavity length and water hammer pressure. Flow and pressure data for the different schemes were recorded to provide basic simulation data. Water column separation experimental phenomena were observed: completely atomized, completely cavitated and partially cavitated, and both cavitated and atomized. At the pump outlet, three hydraulic transition states occurred simultaneously in the horizontal pipe section: completely atomized, completely cavitated, and both cavitated and atomized. Two hydraulic transition states occurred in the knee region: completely and partially cavitated, and without atomization. The experimental results reveal that the initial flow rate and valve closing speed greatly affect the water hammer pressure rise and cavity length. The higher the initial flow rate and valve closing speed are, the larger the water hammer pressure rise and cavity length are.
Envolvimento dos hormônios tireoidianos no desenvolvimento e progressão da Doença de Alzheimer
Authors: De Sousa dos Reis Caroline , Loewen Savaris Julia , Moraes Marques Camila
Published: September 2020

Introdução. Os hormônios tireoidianos (HTs) são relatados como fatores associados às doenças neurodegenerativas, como a doença de Alzheimer (DA). Objetivo. Analisar a relação entre os hormônios tireoidianos na prevenção e desenvolvimento da doença de Alzheimer. Método. Trata-se de uma revisão integrativa, a partir do levantamento de informações nas bases de dados Science Direct e PubMed. As estratégias de busca estabelecidas foram fundamentais em suas combinações, na língua inglesa, para garantir busca mais ampla. Quanto aos critérios de inclusão para a seleção de artigos: artigos completos e disponíveis, publicados em inglês, entre o período de 2009 até 2020. Artigos incompletos e não disponíveis, publicados anteriormente ao ano de 2009, em outra língua que não o inglês, e artigos redundantes e que não apresentavam relação com o tema, foram excluídos. Resultados. A glândula tireoide e seus diversos distúrbios possuem íntima relação no funcionamento fisiológico e patológico cerebral, podendo estar relacionado ao desenvolvimento, progressão e tratamento de doenças neurodegenerativas, especialmente com a doença de Alzheimer (DA), apesar das atuais evidências ainda não serem claras. Conclusão. São necessárias mais pesquisas para desvendar o elo fisiopatológico causal exato entre a função da tireoide e a demência. Definir mecanismos fisiopatológicos causais não apenas fornece mais informações sobre o desenvolvimento da demência, como também pode descobrir possíveis triagens futuras ou novas opções de tratamento.
De La Garza Toledo, Enrique (compilador), Sindicatos y nuevos movimientos sociales en América Latina, 1ª ed., CLACSO, Buenos Aires, 2005
Authors: Martinelli Larisa
Published: September 2020

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Entre el mercado y el sistema punitivo. Trayectorias, proyectos de movilidad social y criminalización de mujeres en el contexto de la campaña anti-trata
Authors: Varela Cecilia
Published: September 2020

En este trabajo, me propongo analizar algunos de los efectos de la implementación de la ley de trata en la Argentina. A partir de una pregunta inicial en torno a la alta criminalización de mujeres identificada en los expedientes judiciales relevados por infracción a la ley 26.364, exploro las modalidades de inserción de mujeres de sectores subalternos en el mercado sexual y sus trayectorias. En segundo lugar, exploro los procesos de reacomodamiento del mercado de departamentos privados de la CABA a partir del activo despliegue de las políticas anti-trata. Así, intento mostrar que en el contexto local los procesos judiciales abiertos por la ley 26.364 -y posteriormente por la ley 26.842- han criminalizado las trayectorias de mujeres que se han insertado en el mercado sexual inicialmente como trabajadoras y posteriormente desarrollado carreras en el sexo comercial. Discuto, así, los límites de los lenguajes legales para atender a la complejidad de las trayectorias en el mercado sexual.
Registrar y acompañar: acciones colectivas por el derecho al aborto en la ciudad de Neuquén
Authors: Burton Julia
Published: September 2020

En este trabajo se analizan las acciones colectivas con relación al reclamo por el derecho al aborto que desarrollan dos organizaciones feministas de la ciudad de Neuquén. La primera consiste en la elaboración de un archivo de historia oral basado en relatos de vida de mujeres que abortaron en Argentina y es realizado por la organización Sin Cautivas Feministas por la Resistencia. La segunda de las acciones analizadas es el dispositivo de información y acompañamiento a mujeres que quieren abortar con medicamentos llevado adelante por la Colectiva Feminista La Revuelta, que enmarca su accionar en Socorristas en Red (feministas que abortamos). Interesa observar las modalidades en que estas acciones colectivas están organizadas y cuáles son algunos de los sentidos referidos al aborto que pretenden instalar.
“La Nuestra” y “Las Aliadas” Sistematización de una experiencia de fútbol femenino en la Villa 31
Authors: “La Nuestra Futbol Femenino” Asociación Civil , Co.Co.In Colectivo
Published: September 2020

La sistematización de la experiencia realizada por el colectivo Co.Co.In conjuntamente con la Asociación Civil “La Nuestra Futbol Femenino”, fue presentado en el Concurso Nacional de Proyectos de investigación y Sistematización de la experiencia Edición 2014, del Observatorio Nacional del Deporte y la Actividad Física, dependiente del Consejo Nacional de Políticas Sociales.  Dicha sistematización fue galardonada con el Primer Premio en la categoría “Sistematización de la experiencia” y mantiene las pautas de presentación solicitadas a esos efectos.
De pánicos sexuales y sus legados represivos
Authors: Daich Deborah
Published: September 2020

El discurso del combate a la trata ha servido como vehículo para unpánico sexual que claramente la excede, todo lo que se conecte conel mercado del sexo es pasible de ser leído en clave de “esclavitud” ypura violencia, pura explotación, y ha comenzado así una cruzada moralsalvacionista que no complejiza, no explica ni describe los fenómenos,sino que los valoran y los juzgan. Así, lo que hoy está en el ojo de latormenta es el sexo comercial y las mismas defi niciones de sexualidad.Me propongo seguir la propuesta de Janice Irvine (2006), quienseñala algunas características o recurrencias de la retórica delos pánicos sexuales. Así, pretendo delinear los pánicos sexualesconstruidos en torno a la trata de personas con fi nes de explotaciónsexual y al mercado del sexo atendiendo a sus legados represivos yde estigmatización.
Therapeutic Communications Phase In Children Down Syndrom: Case Study In Bantul, Yogyakarta
Authors: Adhea Rifty Suciati Bahar Sarro,
Published: September 2020

Therapeutic communication is an attempt at healing through communication. In the case of Down Syndrome child therapy, therapists are required to pay attention to factors that influence the implementation of therapy so that communication is carried out effectively so that healing goals can be achieved. This study intends to describe the therapeutic communication phase of therapists with children with Down syndrome in forming independence in SLBN 1 Bantul, Yogyakarta. This study uses a qualitative descriptive type with 2 (two) pairs of informants, PT and LN . Data obtained through interviews, observations, and documentation. Based on the results of the study, it can be concluded that there are four therapeutic communication phases which include the pre-interaction phase, the orientation phase, the work phase, and the termination phase. In the work phase, the therapist uses YouTube in play therapy. The use of this new media has been proven to improve children's moods and thus speed healing. The four phases of therapeutic communication have been carried out effectively by a therapist informant and it is proven that children with down syndrome can experience changes toward healing in increasing independence, interacting, and building caring attitudes. The other informants did not carry out the four phases of therapeutic communication to the maximum, causing children to be lazy to attend school and slow to develop towards a better direction.

Keywords: therapeutic communication, pre-interaction phase, orientation phase, work phase, termination phase
Efektivitas Komunikasi Google Classroom Sebagai Media Pembelajaran Jarak Jauh Pada Mahasiswa Ilmu Komunikai Universitas Negeri Jakarta Angkatan 2018
Authors: K.Y.S. Putri Wanda Hanifah,
Published: September 2020

ABSTRAK

Dalam menghadapi pandemi Covid-19, mahasiswa Ilmu Komunikasi di Universitas Negeri Jakarta melakukan Pembelajaran Jarak Jauh (PJJ) dengan menggunakan salah satu media pembelajaran online, yaitu google classroom. Dengan memanfaatkan google classroom ini maka dosen dan mahasiswa akan tersambung secara digital. Dalam melakukan kegiatan pembelajaran, terdapat proses komunikasi untuk menyampaikan pesan edukatif dari dosen kepada mahasiswa, hal itu bertujuan agar pesan yang disampaikan oleh dosen dapat diterima dengan baik sehingga mempengaruhi pengetahuan dan perubahan perilaku mahasiswa, maka itu kesuksesan suatu kegiatan pembelajaran sangat bergantung pada efektivitas proses komunikasi yang terjadi dalam pembelajaran. Oleh karena itu tujuan penelitian ini adalah untuk mengetahui efektivitas google classroom sebagai media pembelajaran jarak jauh pada mahasiswa Ilmu Komunikasi Universitas Negeri Jakarta angkatan 2018. Jenis penelitian ini adalah deskriptif dengan pendekatan kuantitatif. Populasi dari penelitian ini adalah mahasiswa Ilmu Komunikasi Universitas Negeri Jakarta angkatan 2018 yang berjumlah 37 orang dengan 34 responden. Penelitian ini memiliki satu variabel, yaitu efektivitas komunikasi. Hasil dari penelitian ini menyatakan bahwa keenam dimensi efektivitas komunikasi yaitu dimensi penerima pesan, dimensi isi pesan, dimensi media komunikasi, dimensi format pesan, dimensi sumber pesan dan terakhir yaitu dimensi ketepatan waktu, memperoleh nilai rata-rata diatas 2,5%. Hal ini menunjukkan bahwa google classroom sebagai media pembelajaran jarak jauh pada mahasiswa Ilmu Komunikasi Universitas Negeri Jakarta angkatan 2018 dinyatakan efektif.

Kata Kunci : Efektivitas Komunikasi, Google Classroom, Pembelajaran Jarak Jauh, Mahasiswa Ilmu Komunikasi Universitas Negeri Jakarta angkatan 2018
Analisis Harmonisasi Komunikasi Antara Nelayan Jaring Bobo Dalam Usaha Penangkapan Ikan Di Kabupaten Seram Bagian Barat (SBB)
Authors: Sanmas Masni
Published: September 2020

ABSTRAK

 

 

Nelayan merupakan bagian dari unit penangkapan ikan yang sangat berperan penting dalam operasi penangkapan ikan di laut. Produktivitas hasil tangkap yang dimiliki nelayan sangat ditentukan oleh baik buruknya kondisi alam, misalnya keadaan cuaca yang kurang baik, faktor lain yang sangat berpengaruh terhadap kurangnya produktivitas hasil tangkap juga disebabkan karena faktor internal dari kelompok nelayan itu sendiri. Faktor internal yang dimaksud ialah hubungan sosial di dalam kelompok jaring bobo. Penelitian ini bertujuan untuk menganalisis harmonisasi komunikasi antara nelayan dalam usaha penangkapan ikan di Kabupaten Seram Bagian Barat (SBB), dan mendeskripsikan upaya yang telah dilakukan untuk membangun komunikasi yang harmonis antar nelayan selama berlangsungnya proses penangkapan ikan di Kabupaten Seram Bagian Barat (SBB). Penelitian ini menggunakan pendekatan kualitatif dengan analisis deskriptif. Data diperoleh melalui observasi dan wawancara langsung terhadap 22 informan dan dianalisis menggunakan model interaktif Miles dan Huberman. Hasil penelitian menunjukan bahwa, nelayan di Kabupaten Seram Bagian Barat dalam menjalankan usaha jaring bobo sering terjadi konflik yng mengakibatkan komunikasi antar nelayan tidak berjalan harmonis, dan ada juga nelayan yang komunikasi mereka berjalan harmonis. Upaya yang di gunakan dalam membangun komunikasi yang harmonis dengan saling menghargai, kejujuran, kerjasama, dan adanya tanggung jawab. Serta Pentingnya harmonisasi dalam kelompok adalah untuk menciptakan adanya rasa nyaman diantara nelayan.  

 

Kata Kunci: Komunikasi Kelompok, Harmonisasi Komunikasi, Hasil Tangkapan