Industrial wireless sensor and actuator networks in industry 4.0: Exploring requirements,protocols, and challenges—A MAC survey

The vision to connect everyday physical objects to the Internet promises to create the Internet of Things (IoT), which is expected to integrate the diverse technologies such as sensors, actuators, radio frequency identification, communication technologies, and Internet protocols. Thus, IoT promises to transfer traditional industry to advance digital industry known as the Industry 4.0. At the core of the Industry 4.0 are the wireless sensor networks (WSNs) and wireless sensor and actuator networks (WSANs) that led to the development of industrial wireless sensor networks (IWSNs) and industrial wireless sensor and actuator networks (IWSANs). These networks play a central role of connecting machines, parts, products, and humans and create a diverse set of new applications to support intelligent and autonomous decision making. The IWSAN is a promising technology for numerous industrial applications because of their several potential benefits such as simple deployment, low cost, less complexity, and mobility support. However, despite such benefits, they impose several unique challenges at different layers of the protocol stack when deploying them for various monitoring and control applications in the Industry 4.0. In this article, we explore IWSAN, its applications, requirements, challenges, and solutions in the context of industrial control applications. Our main focus is on the medium access control (MAC) layer that can be exploited to satisfy such requirements. Our discussion presents extensive background study of the MAC schemes and it reviews the MAC protocols of the existing wireless standards and technologies. A number of application‐specific MAC protocols developed to support industrial applications, which are not part of these standards, are also elaborated. We rationalize to what extent the existing standards and protocols help in solving such requirements as laid down by the Industry 4.0. In the end, we emphasize on existing challenges and present important future directions.     

Covalent 0D–2D Heterostructuring of Co9S8–MoS2 for Enhanced Hydrogen Evolution in All pH Electrolytes

Ultrasmall Co₉S₈ nanoparticles are introduced on the basal plane of MoS₂ to fabricate a covalent 0D–2D heterostructure that enhances the hydrogen evolution reaction (HER) activity of electrochemical water splitting. In the heterostructure, separate phases of Co₉S₈ and MoS₂ are formed, but they are connected by Co–S–Mo type covalent bonds. The charge redistribution from Co to Mo occurring at the interface enhances the electron‐doped characteristics of MoS₂ to generate electron‐rich Mo atoms. Besides, reductive annealing during the synthesis forms S defects that activates adjacent Mo atoms for further enhanced HER activity as elucidated by the density functional theory (DFT) calculation. Eventually, the covalent Co₉S₈–MoS₂ heterostructure shows amplified HER activity as well as stability in all pH electrolytes. The synergistic effect is pronounced when the heterostructure is coupled with a porous Ni foam (NF) support to form Co₉S₈–MoS₂/NF that displays superior performance to those of the state‐of‐the‐art non‐noble metal electrocatalysts, and even outperforms a commercial Pt/C catalyst in a practically meaningful, high current density region in alkaline (>170 mA cm^?2) and neutral (>60 mA cm^?2) media. The high HER performance and stability of Co₉S₈–MoS₂ heterostructure make it a promising pH universal alternative to expensive Pt‐based electrocatalysts for practical water electrolyzers.     

Efficient Hydrogen Evolution Reaction Catalysis in Alkaline Media by All‐in‐One MoS2 with Multifunctional Active Sites

MoS₂ becomes an efficient and durable nonprecious‐metal electrocatalyst for the hydrogen evolution reaction (HER) when it contains multifunctional active sites for water splitting derived from 1T‐phase, defects, S vacancies, exposed Mo edges with expanded interlayer spacings. In contrast to previously reported MoS₂‐based catalysts targeting only a single or few of these characteristics, the all‐in‐one MoS₂ catalyst prepared herein features all of the above active site types. During synthesis, the intercalation of in situ generated NH₃ molecules into MoS₂ sheets affords ammoniated MoS₂ (A‐MoS₂) that predominantly comprises 1T‐MoS₂ and exhibits an expanded interlayer spacing. The subsequent reduction of A‐MoS₂ results in the removal of intercalated NH₃ and H₂S to form an all‐in‐one MoS₂ with multifunctional active sites mentioned above (R‐MoS₂) that exhibits electrocatalytic HER performance in alkaline media superior to those of all previously reported MoS₂‐based electrocatalysts. In particular, a hybrid MoS₂/nickel foam catalyst outperforms commercial Pt/C in the practically meaningful high‐current region (>25 mA cm^?2), demonstrating that R‐MoS₂‐based materials can potentially replace Pt catalysts in practical alkaline HER systems.     

Bright,dark and dark-singular soliton solutions of nonlinear Schrödinger's equation with spatio-temporal dispersion

This article presents an analytical study of the propagation of solitons through optical fibres. We consider a nonlinear Schrödinger equation with spatio-temporal dispersion and quadratic–cubic nonlinearity. Jacobi elliptic functions are used as an ansatz to extract optical dark and bright solitons as well as Jacobi elliptic solutions. The extended direct algebraic method gives dark and dark-singular soliton solutions. The constraint conditions which guarantee the existence of soliton solutions are listed.     

Miniaturized,Battery‐Free Optofluidic Systems with Potential for Wireless Pharmacology and Optogenetics

Combination of optogenetics and pharmacology represents a unique approach to dissect neural circuitry with high specificity and versatility. However, conventional tools available to perform these experiments, such as optical fibers and metal cannula, are limited due to their tethered operation and lack of biomechanical compatibility. To address these issues, a miniaturized, battery‐free, soft optofluidic system that can provide wireless drug delivery and optical stimulation for spatiotemporal control of the targeted neural circuit in freely behaving animals is reported. The device integrates microscale inorganic light‐emitting diodes and microfluidic drug delivery systems with a tiny stretchable multichannel radiofrequency antenna, which not only eliminates the need for bulky batteries but also offers fully wireless, independent control of light and fluid delivery. This design enables a miniature (125 mm³), lightweight (220 mg), soft, and flexible platform, thus facilitating seamless implantation and operation in the body without causing disturbance of naturalistic behavior. The proof‐of‐principle experiments and analytical studies validate the feasibility and reliability of the fully implantable optofluidic systems for use in freely moving animals, demonstrating its potential for wireless in vivo pharmacology and optogenetics.     

Heat transfer analysis of Walters’-B fluid with Newtonian heating through an oscillating vertical plate by using fractional Caputo–Fabrizio derivatives

Mechanics of Time-Dependent Materials - This paper presents a study of Walters’-B fluid with Caputo–Fabrizio fractional derivatives through an infinitely long oscillating vertical plate...     

3D Semantic Deep Learning Networks for Leukemia Detection

White blood cells (WBCs) are a vital part of the immune system that protect the body from different types of bacteria and viruses. Abnormal cell growth destroys the body’s immune system, and computerized methods play a vital role in detecting abnormalities at the initial stage. In this research, a deep learning technique is proposed for the detection of leukemia. The proposed methodology consists of three phases. Phase I uses an open neural network exchange (ONNX) and YOLOv2 to localize WBCs. The localized images are passed to Phase II, in which 3D-segmentation is performed using deeplabv3 as a base network of the pre-trained Xception model. The segmented images are used in Phase III, in which features are extracted using the darknet-53 model and optimized using Bhattacharyya separately criteria to classify WBCs. The proposed methodology is validated on three publically available benchmark datasets, namely ALL-IDB1, ALL-IDB2, and LISC, in terms of different metrics, such as precision, accuracy, sensitivity, and dice scores. The results of the proposed method are comparable to those of recent existing methodologies, thus proving its effectiveness.     

Structure Preserving Algorithm for Fractional Order Mathematical Model of COVID-19

In this article, a brief biological structure and some basic properties of COVID-19 are described. A classical integer order model is modified and converted into a fractional order model with as order of the fractional derivative. Moreover, a valued structure preserving the numerical design, coined as Grunwald–Letnikov non-standard finite difference scheme, is developed for the fractional COVID-19 model. Taking into account the importance of the positivity and boundedness of the state variables, some productive results have been proved to ensure these essential features. Stability of the model at a corona free and a corona existing equilibrium points is investigated on the basis of Eigen values. The Routh–Hurwitz criterion is applied for the local stability analysis. An appropriate example with fitted and estimated set of parametric values is presented for the simulations. Graphical solutions are displayed for the chosen values of (fractional order of the derivatives). The role of quarantined policy is also determined gradually to highlight its significance and relevancy in controlling infectious diseases. In the end, outcomes of the study are presented.     

Conditional mean- and median-based cumulative sum control charts for Weibull data

This article deals with the monitoring of censored data using the cumulative sum (CUSUM) control charts for Weibull lifetimes under type-I censoring. To develop an efficient CUSUM structure for censored data, we use the conditional expected value (CEV) and conditional median (CM) approaches. In particular, we focus on the detection of shifts in the mean of Weibull lifetimes assuming censored data. In addition to fixed/known parameter values, the effect of estimation is assessed on the detection power of control charts. The performance of the proposed charts is evaluated by the average run length (ARL). Furthermore, the ARL performance of CUSUM charts is compared with CEV- and CM-based exponentially weighted moving average (EWMA) control charts. Besides an extensive simulation study, the significance of the current work is illustrated by a data set on the response time of a thermostat experiment.     

On increasing the sensitivity of moving average control chart using auxiliary variable

In the statistical process control, the most useful tool to monitor the manufacturing processes in the industries is the control chart. Quality practitioners always desire the charting structure that identifies sustainable changes in the monitoring processes. The sensitivity of the control chart is improved when additional correlated auxiliary information about the study variable is introduced. The regression estimate in the form of auxiliary and supporting variables presents an unbiased and efficient statistic of the mean of the process variable. In this study, auxiliary information-based moving average (AB-MA) control chart is designed for efficient monitoring of shifts in the process location parameter. The performance of the AB-MA control chart is evaluated and compared with existing charts using average run length and other run length characteristics. The comparison reveals that the AB-MA control chart outperforms the competitors in detecting the small and medium changes in the process location parameter. The application of the proposal is also provided to implement it in real situation.