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We will discuss the automated electrical control panel in this project, with the primary goal of reducing road accidents and conserving electrical resources. I used a timer switch in the Electrical Control Panel, believing that this would enable the circuit to complete only at a specific time. If the time transfer is set to 7:00p.m., for example, the current would pass through the contactor at 7:00p.m. This breakthrough would aid in the reduction of energy waste. Because of workers incompetence, street lights are not turned on at the proper times, resulting in traffic accidents. This breakthrough would also help to minimise road accidents since it will turn on at a predetermined time, allowing drivers to see clearly on the road.

Light metals such as aluminum alloys which are being broadly used in automobile sideways, aerospace production as well as segments in military. A light-weight metals prominent for energy consume reduction, efficiency of gasoline and oil increment and superior security to environment. The main utilization of aluminum matrix alloy components have been manufactured by the appropriate behaviors of high tensile strength, hardness, decent machinability, great cast-ability and excessive resistance of corrosion. In the present investigation dealing with casting and heat treatment processes of aluminum alloys 6063 by two different methods such as Sand casting and Die casting. The characterization of AA6063 are analyzed with help of destructive and non-destructive techniques. Finally the results indicates that die casted material gives better results when it is heat treated than the sand casted material.

Idiyaapam Making Machine is used to make the favourite dish of Tamil Nadu idiyaapam automatically. Nowadays, in homes manual hand operated idiyaapam making machines are employed and it has string hopper to extrude idiyaapam flour. It takes more time to make the dish and it is hard to turn the hand lever when the density of rice flour mixture is high. This is an era of automation and needs simple and automatic idiyaapam maker in which it extrudes the flour in the form of strings. In this work, the fabrication of automatic idiyaapam maker is carried and the rice flour would be extruded. Initially the wet flour composition should be fed into the machine and a collecting plate is kept at proper place in which strings are extruded. While the machine gets started, the flour composition is extruded the flour strings are formed. While accumulating strings, the collecting plate should be rotated to avoid overlapping of strings. Whenever the plate is filled up to the required amount, further forming of the strings should be stopped. Then the plate with the flour strings is shifted away from the extruding unit.

Today our society needs more energy for day-to-day activities due to rapid globalization and industrialization. In order to minimize the stress and dependency on fossil fuel, the most sustainable way is to harness suns energy. Solar energy is characterized by low cost, environment friendly, does not require frequent maintenance and most importantly, negligible maintenance cost. However, there is a requirement of monitoring solar installation in order to maximize the output power by setting real-time angles with the suns position. This can be easily done by the adoption of IoT technologies. The Internet of Things is often utilized in the measurement of solar energy for efficiency. It's also utilized to maintain the solar plant's health. The cost of renewable energy technology is decreasing throughout the globe, which encourages the construction of large-scale solar plants. Automation of plant observation on such a large scale of preparatory deployments requires sophisticated systems reliant on Internet connections since the majority of field units are situated in isolated, remote locations and therefore are not overseen from a central office. The project is based on the use of the most up-to-date, cost-effective method for remotely monitoring a solar plant performance by the inclusion of IoT. It can assist with plant maintenance, problem diagnostics, and real-time monitoring.

This paper targets to transmit industrial data from one sensor node to another sensor node, wirelessly and securely. However as the nodes have Internet access and are typically positioned in an unsupervised context with minimal individual intervention; security and seclusion are the prime challenges in Industrial Wireless Sensor Networks (IWSN). To use IWSN, a user must be able to get real time information straight from the source nodes and this is accomplished by Radio Frequency Identification (RFID). It yields a cost-effective solution of identification problems, but it frequently suffers from diverse safety and privacy difficulties. This paper resolves the issues of RFID systems using Global System for Mobile Communications (GSM) module that generates a One-Time Password (OTP) for accessing the data, and thereby ensures user's privacy and security in Industrial Wireless Sensor Network. Furthermore, eight evaluation criteria have been met by the proposed system surpassing the existing systems.

Stealth aircraft use Stealth Technology in order to evade recognition by utilizing mix of highlights with the goal that Aircraft can invade with RADAR and furthermore decrease the deceivability in “radio frequency (RF) range”, sound and infrared visual. During the most recent decades, stealth technology has demonstrated to be one of the best methodologies to the extent the undertaking to escape radar systems is concerned. Stealth intends to evade the recognition or attempt to cover up, for planes, avoiding radar implied stealth. The idea utilized in the stealth innovation isn’t so difficult. It utilizes the guideline to retain and mirror the radar waves. Airplane redirects the radar waves in different ways and limits the radar waves which return back to radar. Another marvel which permits the air ship maintain completely the incoming radar wavelengths to inhabit the electromagnetic reincorporated energy in various way. The structure and material used to manufacture air ship choose the degree of stealth accomplish via air ship. The thought for the radar radio wire to release Radio energy that is then returned through any item that occurs to recognize. The time taken for the reflection to come is measure by the radar radio wire and it can tell how far off an object is.

The dominant characteristics of the human foot are its shock-absorbing capability during walking or gait cycle and its adaptation to uneven surfaces. On the stance phase of the gait, the foot has to be flexible at first for shock absorption and adapt to the terrain; whereas, during the propulsive phase, it has to be dynamically rigid to function as a lever. Foot flexibility and rigidity are mainly controlled at the subtalar and midtarsal joints by tendons and ligaments. The subtalar joint is part of the longitudinal arch, but the midtarsal joint along with the tarsometatarsal joint are components of the transverse arch. However, the existence and functional role of transverse arch in human was challenged by some authors. But recent studies have revealed that the transverse arch has a predominant role in midfoot stiffness (Venkadeshan et al., 2020, & Holowoka et al., 2017). This midfoot stiffness allows the human foot to store elastic energy at the time of heel strike, which is utilized during the push-off mechanism for propulsion, thus making bipedalism more energy-efficient. Moreover, the transverse arch allows the longitudinal arch to be flexible like a lever and, at the same time, makes the arch of the foot rigid to behave like a stiff spring lever. Understanding the role of the transverse arch is obligatory to study the biomechanics of foot injuries and Charcot or diabetic foot. Studies on diabetic foot have shown that the modulation of transverse arch biomechanics and off-loading modalities would improve outcomes in the form of wound-healing and prevention of re-ulceration.

The governmental subsidy is an important instrument for catalyzing the early adoption of Electric Vehicles (EVs)}. A sustainable subsidy policy must balance between promoting EVs and expanding the charging infrastructure. This paper proposes a dynamic game approach to accelerate the adoption of EV technology. The government observes two correlated processes - the penetration of the EV market and the expansion of the charging infrastructure. It finds an optimal strategy that maximizes the cumulative social benefit in the face of uncertainty. A case study of China's EV industry finds that \blue{the established EV subsidy policies are inadequate to support EVs' growth over the next decades}. In contrast, the optimal subsidies will achieve \blue{the target EV market share and ensure the accessibility to charging infrastructure by 2030}. This non-myopic strategy can prioritize the infrastructure expansion, eliminate policy enforcement's monitoring costs, prevent compensation evasion, and help achieve long-term targets by making proactive regulatory policies.

Deep learning-based methods have achieved remarkable success in object detection, but this success requires the availability of a large number of training images. Collecting sufficient training images is difficult in detecting damages of airplane engines. Directly augmenting images by rotation, flipping, and random cropping cannot further improve the generalization ability of existing deep models. We propose an interactive augmentation method for airplane engine damage images using a prior-guided GAN to augment training images. Our method can generate many types of damages on arbitrary image regions according to the strokes of users. The proposed model consists of a prior network and a GAN. The Prior network generates a shape prior vector, which is used to encode the information of user strokes. The GAN takes the shape prior vector and random noise vectors to generate candidate damages. Final damages are pasted on the given positions of background images with an improved Poisson fusion. We compare the proposed method with traditional data augmentation methods by training airplane engine damage detectors with state-of-the-art object detectors, namely, Mask R-CNN, SSD, and YOLO v5. Experimental results show that training with images generated by our proposed data augmentation method achieves a better detection performance than that by traditional data augmentation methods.

Statement of problem The light source stability of digital cameras and smartphones is important in shade matching in restorative and prosthetic dentistry to communicate objectively with the dental laboratory. Techniques that standardize the light source of such devices are lacking, and this limitation can lead to color mismatches, difficulties in color communication, and treatment documentation. Purpose The purpose of this clinical study was to compare the magnitude of color difference (ΔE) among 3 shade selection methods during the fabrication of ceramic crowns: visual shade selection with a shade guide, digital shade selection with a digital camera and cross-polarizing filter, and digital shade selection with a smartphone and a light-correcting device. Material and methods Forty-five patients in need of ceramic crowns were enrolled, and shade selection was evaluated according to different protocols: visual shade selection (A-D shade guide and IPS Natural Die Material Shade Guide, sent to the dental laboratory technician via a laboratory prescription); digital shade selection with a digital camera (D7000; Nikon Corp) with an 85-mm lens and wireless close-up flash, with and without a cross-polarizing filter (Polar eyes); and digital shade selection with a smartphone and a light-correcting device (iPhone XS attached to Smile Lite MDP, with and without its cross-polarizing filter accessory). Information from the smartphone was imported to an app (IPS e.max Shade Navigation App; Ivoclar Vivadent AG) that converted the reading to a shade and level of translucency for the ceramic restoration. For all photographs, a gray reference card with known color values was positioned by the mandibular teeth and was used for white balancing of the digital photographs with a software program. All photographs were edited and sent to the dental laboratory: white-balanced with the shade guide; white-balanced with the substrate shade guide; black and white; saturated; and cross-polarized. Ceramic crowns were made with the same lithium disilicate material (IPS e.max CAD; Ivoclar Vivadent AG) and cemented with the same resin cement (RelyX Ultimate Clicker, A3 shade; 3M). The ΔE values between the crown and the adjacent tooth were determined. The data were analyzed by using a 1-way analysis of variance (ANOVA) and Tukey posthoc tests (α=.05). Results The mean ΔE between a cemented ceramic crown and the adjacent tooth in the visual shade selection group was 5.32, significantly different than both digital camera (ΔE=2.75; P=.002) and smartphone (ΔE=2.34; P=.001), which were not different from each other (P=.857). Conclusions The digital shade selection with photographs acquired with both a digital camera and a smartphone with a light-correcting device showed a threshold within the acceptable values (ΔE 3.7). The use of a gray reference card helped standardize the white balance from the digital images.

Objectives The deviation in gait cycle due to trunk acceleration and muscle activity on even and uneven inclined planes should be analyzed for the design of lower limb exoskeletons. This study compares the gait variability of gastrocnemius and medial hamstring muscle activity variation of twenty young male adults on inclined even and uneven planes. Material and methods The individuals walked on a long, 10° inclined even and uneven plane in both up-the-plane and down-the-plane directions at their preferred speed (average speed is 1.2 m/s). Gait variability during walking was calculated using an average standard deviation of trunk acceleration and the significance of change was calculated using two-way-ANOVA. For studying the difference between integrated electromyography (IEMG) values of walking on even and uneven planes, two parameters Normalized IEMG Percentage (NIP) and IEMG Variation Percentage (IVP) were chosen for the analysis. Results The results strongly agree with the hypothesis that gait variability hikes in the vertical direction of subject with a p-value of 0.04. The IEMG range of medial-hamstring muscle while walking on even and uneven plane is not highly significant for swing (0.44) as well as stance phase (0.47). While walking on an inclined uneven plane, the response of gastrocnemius muscle indicated the variation of NIP between 14.31% to 64.63%. It was observed that NIP and IEMG values of medial-hamstring muscles during backward walking have a resemblance. Conclusion Trunk variability had a significant change in the vertical direction (V) and was insignificant in medial-lateral (ML) and anterior-posterior (AP) orientations for both even and uneven inclined planes during forward and reverse walking. The muscle activity of gastrocnemius and medial-hamstring muscles does not have sound variations while walking on the inclined uneven plane.

Today, the rapid growth of the internet and advancements in mobile technology and increased internet connectivity have brought us to a data-driven economy where an enormous amount of data is being used to train machine learning models to make strategic decisions. However, in the aftermath of a data breach by Facebook in 2018, there are some serious concerns over user data privacy and security being used to train the Machine Learning models. In this context, a new approach, Federated Machine Learning is now one of the most talked-about and recent approaches. Current research primarily focuses on Federated Learning's advantages over the traditional methods and/or its classification. However, being in a nascent stage of development as a method, certain challenges need to be addressed. This paper intends to address the totality of federated learning with a complete vulnerability assessment. During the study of the literature, it is found that security being promised as one of the key advantages of federated learning can still not be guaranteed because of some issues inherently present, and this can lead to poisoning, inference attacks and insertion of backdoors, etc. This paper intends to provide a complete picture by giving an in-depth and comprehensive analysis of Federated Learning and its taxonomy. It also provides a detailed vulnerability assessment and highlights the challenges faced in the current setting and future research directions to make federated learning a more functional, robust and secure method to train machine learning models.

Electrification of bus fleets in most cities is expected to rise due to its significant environmental benefits. However, electric buses have limited driving range and long recharging times. Additionally, electric buses require special charging infrastructure, which overall makes them less flexible than conventional diesel buses. Due to the limitations of the electric bus technologies, further adjustments have to be made to the current bus transport planning problems. The scheduling of electric vehicles is recognized as a fast-growing area of research. In this paper, we review 43 articles related to the electric bus technologies and give an overview of the different problems in the electric bus planning process (strategic, tactical and operational). The different problems are: 1) investment of electric bus fleet and charging infrastructure, 2) placement of charging infrastructure, 3) the electric vehicle scheduling problem (E-VSP) and 4) the charging scheduling problem. Given a set of timetabled trips and recharging stations, the E-VSP is concerned with finding a vehicle schedule that covers the trips and satisfies the driving range and recharging requirements of electric buses while minimizing operational cost. A detailed literature review of the constraints associated with the E-VSP and the solution approaches proposed to solve it is given. Rescheduling aspects or considerations of robustness for scheduling of electric vehicles is identified as a future area of research. Furthermore, integrated electric bus planning is considered as a crucial area of research and integrated approaches could further improve the efficiency of electric bus transport systems.

As the wind turbine operates in harsh conditions, numerous of its components are critical and present an important downtime for maintenance. In this paper, we propose a fault diagnosis algorithm to detect and locate the defects affecting the generator rotor and the pinion of the gearbox lay shaft in a real 750 kW wind turbine drivetrain. The induction generator was used as a fault sensor for gear teeth damage. Through the use of the wavelet packet transform, and the local mean decomposition combined with the Fast Fourier Transform, the detection of gear meshing frequency in the stator current reflects teeth faults. Hence, the principal component analysis of the stator current gives a suitable classification for the gearbox states under different working stages. The obtained results have been significant, despite the use of a short duration and a low sampling frequency of the experimental data.

Due to the resource-constraint nature and lack of lightweight computing solutions for diagnostic devices in healthcare IoT, provisioning time-critical responses is still challenging. In this paper, we propose DC-Health, a Dew Computing enabled IoT healthcare solution for offline and ultra-low latency decisions. The proposed solution connects a large number of healthcare devices and provisions user-specific services even when Internet connectivity is not available. The computation module is placed at the extreme edge rather than the cloud to reduce the complexity and to improve the user-specific services. In addition to the other computing facilities provided by the cloud, fog, and edge, our solution performs with a negligible dependency on the Internet. We develop a prototype of DC-Health, which monitors the heart condition using the ECG sensors with end-mile services, flexibility in terms of user-control, and mobility feature. The experimental implementations show that the proposed architecture minimizes the network response time by at least 92% and 98%, compared to the fog and cloud-based approaches, respectively. Along with this, the proposed technique also reduces the CPU and memory usages, and response time by around 30% compared to the conventional method.

BackgroundIn the context of the SARS-CoV-2 pandemic, reuse of personal protective equipment, specifically that of medical face coverings, has been recommended. The reuse of these typically single-use only items necessitates procedures to inactivate contaminating human respiratory and gastrointestinal pathogens. We previously demonstrated decontamination of surgical masks and respirators contaminated with infectious SARS-CoV-2 and various animal coronaviruses via low concentration- and short exposure methylene blue photochemical treatment (10 µM methylene blue, 30 minutes of 12,500-lux red light or 50,000 lux white light exposure).MethodsHere, we describe the adaptation of this protocol to the decontamination of a more resistant, non-enveloped gastrointestinal virus and demonstrate efficient photodynamic inactivation of murine norovirus, a human norovirus surrogate.ResultsMethylene blue photochemical treatment (100 µM methylene blue, 30 minutes of 12,500-lux red light exposure) of murine norovirus-contaminated masks reduced infectious viral titres by over four orders of magnitude on surgical mask surfaces.Discussion and ConclusionsInactivation of a norovirus, the most difficult to inactivate of the respiratory and gastrointestinal human viruses, can predict the inactivation of any less resistant viral mask contaminant. The protocol developed here thus solidifies the position of methylene blue photochemical decontamination as an important tool in the package of practical pandemic preparedness.

Currently, industrial robots are considered as an alternative towards traditional machine tools. Especially for the large-scale parts milling, robotic flexibility and low cost make it possess the irreplaceability. However, the milling chatter caused by its weak rigidity hampers robotic application and promotion severely in aviation industry. Rotary ultrasonic milling (RUM) technology with one-dimensional axial vibration has been proven and approved on avoiding robotic chatter. Based on this, the research of project team demonstrates that longitudinal-torsional composite ultrasonic milling (CUM-LT) involving separation characteristic has a greater advantage than RUM in terms of chatter suppression. Thereby, the CUM-LT as a new means is applied to avoid processing vibration of robotic milling system. And its influence mechanism on stability improvement of weak stiffness processing system is clarified. Meanwhile, the approaches to strengthen separation effect are provided innovatively. Moreover, a new analysis method of robotic CUM-LT (RCUM-LT) stability is proposed on the basis of ultrasonic function angles. The simulation and experimental results indicate that compared with robotic RUM (RRUM), stability regions of separated RCUM-LT (SRCUM-LT) and unseparated RCUM-LT (URCUM-LT) are improved by 124.42% and 39.20%, respectively. The addition of torsional ultrasonic energy has a wonderful effect on the milling chatter suppression of low stiffness robots.

OBJECTIVE: To assess the effectiveness of a 3D-printed custom mask fitter in lieu of N95 respirators among ophthalmologists and other eye care professionals who may not be prioritized to receive N95 respirators amidst the coronavirus disease 2019 pandemic. METHODS: This was a proof-of-concept study from a tertiary eye care center in Oakville, Canada. All participants underwent the N95 Qualitative Fit Test with a custom mask fitter secured over an American Society for Testing and Materials Level 3 face mask. Participants answered a 10-point Likert scale questionnaire on comfort, ease of use, and feasibility of the custom mask fitter, as well as comfort of a regular face mask. RESULTS: Twenty participants were recruited. Of the 20 recruited, 18 (90%) successfully passed the fit test. The median scores for comfort, ease of use, and everyday feasibility for the custom mask fitter were 3.5, 4.5, and 3, respectively, whereas the median score for comfort of a regular face mask was 8.5. CONCLUSION: A reusable, low-cost, 3D-printed custom mask fitter is a potential effective alternative to an N95 respirator among eye care professionals but may require improvement in its design and comfort. This is especially relevant in the context of a limited supply of N95 respirators amidst a global pandemic.

The era of the industrial revolution 4.0 was an era marked by the transition of information and communication technology that was able to create new technology-based investments. Internet of things (IoT), Big Data, and Cloud Computing are the foundations that underlie this 4.0 industrial revolution. Cloud Computing is a service that provides network storage space and computer resources using an internet connection as a medium of access. Cloud Service Providers (CSP) offer attractive services, making more and more companies want to migrate to the cloud. Sometimes the migration process to cloud computing faces problems or even failures, and this is certainly a risk for cloud service users. This study will identify the types of risks and risk components in cloud migration using the Systematic Literature Review (SLR) method. The databases used in selecting articles that match the criteria include: Emerald Online, IEEE Xplore, ScienceDirect, SpringerLink, and between 2015 and 2020. The results of this study, there were 74 articles selected according to the criteria and reviewed. The output of this study shows that there are 7 types of risk in cloud migration, namely information security risk, risk of losing data access, risk of using virtual machines, errors in choosing CSPs, risk of compliance with various laws and regulations, financial risk, and management failure, the weights of 25%, 21%, 18%, 14%, 11%, 7%, and 4% respectively, as well as 5 risk components, namely threats, impacts, risk factors, vulnerabilities, and damage with a weight of 33%, 27%, 20%, 13%, and 7%.

We consider a general electric vehicle (EV) charging system with stochastic demand, demand request locations, and predetermined charging facilities (including charging station locations and charger capacities). The objective is to design a good routing strategy that accommodates well demand-request dynamics so as to satisfy the charging system’s stability constraints and also minimize the EV’s mean response time. We introduce a class of flexible and measurement-based routing policies called “partition-based random routing” (PBRR) and show that the performance measure of interest can be formulated as a constrained optimization problem with a convex objective function when the system is heavily loaded. This formulation enables us to establish strong theoretical results that are in aid of finding the optimal routing solution; however, in practice, finding this solution requires rather involved numerical calculations. To that end, we propose a surrogate, easy to design and implement, optimization algorithm for finding the desired optimal routing solution. Numerical work based on synthetic data shows that the performance of the developed routing strategy and its fast implementation is highly satisfactory for a number of system settings.

This study investigates the vast potential for space-based technologies and applications in supporting governance to strengthen civil society, bolster democratic processes, and allow for socio-economic development throughout Africa. It offers a comprehensive analysis of African governance levels, existing e-governance systems, African challenges relating to e-governance adoption, and how e-governance solutions can assist in realising the continent's development goals. First, the study explores the integral role of good governance in achieving the UN Agenda 2030 Sustainable Development Goals (SDGs) and the AU's Agenda 2063 aspirations. Subsequently, the existing African governance structures established at a continental level are described to provide an overview of the frameworks informing governance within Africa. Specific challenges that need to be overcome to ensure good governance are then addressed and the current governance levels in Africa are evaluated. An assessment of e-government readiness levels both globally and within Africa is offered through an examination of the United Nations E-Government Survey from 2018. Specific barriers to e-government, both abroad and within Africa, are then analysed along with the associated risks relating to e-government systems. It then investigates how digital divides and lack of internet connectivity within Africa can be addressed by new technologies and commitments from both terrestrial and space actors. The opportunities afforded by rapidly growing satellite constellations being deployed to increase connectivity levels and reduce the costs thereof are then analysed in detail and the various planned constellations are assessed on a technical level. Lastly, the potential for Earth Observation and remote sensing data to assist with e-governance activities across sectors including healthcare, education, agriculture, water and sanitation, and emergency responses is investigated.

In recent years, Chinese Long March (LM) launchers have experienced several launch failures, most of which occurred in their propulsion systems, and this paper studies Autonomous Mission Reconstruction (AMRC) technology to alleviate losses due to these failures. The status of the techniques related to AMRC, including trajectory and mission planning, guidance methods, and fault tolerant technologies, are reviewed, and their features are compared, which reflect the challenges faced by AMRC technology. After a brief introduction about the failure modes of engines that can occur during flight, and the fundamentals of trajectory planning and joint optimization of the target orbit and flight path, an AMRC algorithm is proposed for geostationary transfer orbit launch missions. The algorithm evaluates the residual performance onboard, and plans new objectives and corresponding flight path by iterative guidance mode or segmented state triggered optimization methods in real-time. Three failure scenarios that have occurred during previous LM missions are simulated to check the robustness of the algorithm: imminent risk of the boosters’ engines, thrust drop during the first stage of flight, and being unable to start the engine during the second stage. The payloads would fall from space according to the current design under these conditions, but they were saved with the AMRC algorithm in the simulations, which allowed the rocket to get into the target orbit as intended or the payloads were deployed in other orbits without crashing. Although spaceflight can be very unforgiving, the AMRC algorithm has the potential to avoid the total loss of a launch mission when faced with these kinds of typical failures.

Our regional burns service has gained experience in managing paediatric hand friction burns due to vacuum cleaners (VC). We aimed to evaluate our 10 year experience managing these injuries as well as reviewing national data trends in order to identify those at risk of injury. Materials and Methods A International Burns Injury Database (IBID) request was made to review the number of burn injuries recorded due to Vacuum cleaner injuries (VCIs). In addition, a local IBID request was made to identify the number of burn injuries managed within our regional burns service. Results We identified 288 VCIs which have increasingly occurred in England and Wales between 1996–2020 and 32 children who sustained these injuries within our regional burns service. A general theme from both national and local data highlighted that these injuries occurred in males (78%, n=25) with a mean age of 20 months (9 months–4.5 years) affecting children’s hands (94%). In 25 cases (78%) these injuries involved an interphalangeal joint. 85% (n = 27) of injuries were deep dermal/full thickness with eleven children (34%) undergoing surgical excision and skin grafts. Discussion Significant paediatric burn injuries can be sustained from VCs. Greater awareness is indicated for these injuries and legislation should be considered in order to improve the safety of vacuum cleaners. International burn societies are urged to collect data of these injuries in order to co-ordinate improved prevention strategies and change within the VC industry.

Container drayage operations with tractor-trailer distinction and trailer reposition exist widely in real-world logistics yet have seldom been reported in the literature. This paper studies a container drayage problem with trailer reposition (CDPTR), in which trailers might be provided at pickup locations and kept at delivery locations. A two-stage solution framework is adopted to solve the problem. The first stage generates tractor schedules to maximize profit, and the second stage aims to ensure sufficient trailers at each trailer depot during the container drayage operation. A hybrid large neighborhood search and tabu search (LNS-TS) heuristic is developed to solve the problem. We construct 72 instances with different characteristics, for example, time window duration, initial trailer resource and distribution, and the number of requests. Results show that our solutions outperform the solutions obtained from the solver. A detailed analysis of the results also reveals several insights for container drayage operators.

Despite the increased sensor-based data collection in Industry 4.0, the practical use of this data is still in its infancy. In contrast, academic literature provides several approaches to detect machine failures but, in most cases, relies on simulations and vast amounts of training data. Since it is often not practical to collect such amounts of data in an industrial context, we propose an approach to detect the current production mode and machine degradation states on a comparably small data set. Our approach integrates domain knowledge about manufacturing systems into a highly generalizable end-to-end workflow ranging from raw data processing, phase segmentation, data resampling, and feature extraction to machine tool anomaly detection. The workflow applies unsupervised clustering techniques to identify the current production mode and supervised classification models for detecting the present degradation. A resampling strategy and classical machine learning models enable the workflow to handle small data sets and distinguish between normal and abnormal machine tool behavior. To the best of our knowledge, there exists no such end-to-end workflow in the literature that uses the entire machine signal as input to identify anomalies for individual tools. Our evaluation with data from a real multi-purpose machine shows that the proposed workflow detects anomalies with an average F1-score of almost 93%.

Nowadays, people are taking soft drinks (carbonated nonalcoholic beverages) at an increasing rate. Health experts around the world have cautioned from time to time that these drinks lead to weight gain, raise the risk of non-communicable diseases, and so on. To develop consciousness among people, the present work describes an image-based tool to self-monitor the nutritional information of soft drinks by using a deep convolutional neural network (CNN) along with transfer learning. At first, a pre-processing function is done through noise reduction and contrast enhancement. Then the location of the drinks region is extracted through visual saliency and mean-shift segmentation technique. After removing backgrounds and segment out only the region of interest from the image a deep CNN-based transfer learning model is employed for the drink classification. Finally, the size of each drink bottle is estimated using the bag-of-feature (BoF) and distance ratio calculation to find the nutrition value from the nutrition fact table. To perform experimentation a dataset is built containing ten most consumed soft drinks in Bangladesh using images from the ImageNet dataset, internet sources and also self-capturing. The experiment confirms that our system can detect and recognize different types of drinks with an accuracy of 98.51%.

Friction self-piercing riveting (F-SPR) process based on a pip die has been invented to solve the cracking problems in riveting high-strength and low-ductility light metals, such as magnesium alloys, cast aluminum, and 7 series aluminum alloys. In this paper, in order to solve quality issues caused by the misalignment between rivet and pip-die in F-SPR, a flat-die based F-SPR process was proposed and employed to join 1.27 mm-thick AA6061-T6 to 3 mm-thick AZ31B. The results indicate that a 1.0 mm die distance is effective to avoid rivet upset and insufficient flaring. As the feed rate increases, the heat input in the whole process decreases, resulting in a larger riveting force, which in turn increases both the bottom thickness and interlock amount. Besides, solid-state bonding, including Al-Mg intermetallic compounds (IMCs), Al-Mg mechanical mixture, and Al-Fe atom interdiffusion was observed at the joint interfaces. The upper Al layer was softened, but the lower Mg layer was hardened, and both sheets exhibited a narrowed affected region with the increase of feed rate, while the rivet hardness shows no obvious change. Three fracture modes appeared accompanying the variations in lap-shear strength and energy absorption as the feed rate increased from 2 mm/s to 8 mm/s. Finally, the F-SPR process using a flat die was compared to those using a pip die and a flat bottom die to show the advantage of flat die on coping with the misalignment problem.

Multi-jet interactions are characterized by a number of shock and expansion waves, formation of turbulent shear layers and subsonic recirculation zones. The problem of the occurrence of unsteady, transient and oscillatory, processes arising in the nozzle devices of rocket engines at different flight modes is discussed. The main flow regimes, the sequence of their change and qualitative patterns of shock-wave structures that arise in each of the regimes are considered. The main emphasis is paid to the causes of occurrence and mechanisms of maintenance of low-frequency oscillations of the base pressure. The regularities of changes in the amplitude-frequency characteristics of oscillations are studied depending on the main parameters of the problem. Areas of existence of oscillatory processes are found, and a search is carried out for the ranges of design parameters, geometric characteristics of nozzle assemblies that provide a non oscillating flow of gas-dynamic processes. Hysteresis phenomena of shock-wave structure at increase or decrease in the reservoir total pressure is observed.

Numerical simulations of combustion processes in rocket engines requires a long run time of supercomputer systems even for a very short physical time. Therefore, creating digital twins of rocket engines needs enormous processor time, and is not very effective. This computational time surpasses the actual physical time of the process in many orders of magnitude. To speed up numerical simulations the paper presents a solution of the chemical kinetics problem using artificial neural network approach. Using the architecture of a multilayer neural network with bypass connections, namely residual network, it is possible to obtain a fast and reliable solution to the problem. The neural network is trained to predict the state of the system only one time step ahead. Using it in a recursive mode, it is possible to forecast for thousands of steps without loss of accuracy.

Masses of user-side smart meter data provide a foundation for utilities to acquire users’ electricity consumption patterns and promote refined energy management. Therefore, the charging load of electric vehicles can be identified non-intrusively through the smart meter data of residential users, which provides flexible resources for the demand side response of power grid enterprises and is beneficial to the power dispatching decision making. Meanwhile, revealing residential energy consumption behavior from smart meter data is treated as energy privacy leakage. Extensive data collection from smart meters has raised privacy risk, which could lead to the reduction of trust in utilities from households. Aiming at this problem, the paper proposes a non-intrusive method to extract residential electric vehicles, and on this basis, discusses the privacy protection. In this paper, DWT method is used to decompose the total power of smart meter to extract the charging load of electric vehicle, and similar charging load patterns are added to smart meter data to preserve the residential EV charging behavior privacy. Practical households with EVs are used to test the proposed method and the result shows its feasibility for the performance of privacy-preserving.

Background During shortages of filtering face pieces (FFP) in a pandemic, it is necessary to implement a method for safe reuse or extended use. Our aim was to develop a simple, inexpensive and ecological method for decontamination of disposable FFPs that preserves filtration efficiency and material integrity. Material and methods Contamination of FFPs (3M Aura 9320+) with SARS-CoV-2 (1.15 × 104 PFUs), Enterococcus faecium (>106 CFUs), and physiological nasopharyngeal flora was performed prior to decontamination by submersion in a solution of 6 % acetic acid and 6 % hydrogen peroxide (6%AA/6%HP solution) over 30 minutes. Material integrity was assessed by testing the filtering efficiency, loss of fit and employing electron microscopy. Results and Discussion Decontamination with the 6%AA/6%HP solution resulted in the complete elimination of SARS-CoV-2, E. faecium and physiological nasopharyngeal flora. Material characterization post-treatment showed neither critical material degradation, loss of fit or reduction of filtration efficiency. Electron microscopy revealed no damage to the fibers, and the rubber bands’ elasticity was not affected by the decontamination procedure. No concerning residuals of the decontamination procedure were found. Conclusion The simple application and widespread availability of 6%AA/6%HP solution for decontaminating disposable FFPs make this solution globally viable, including developing and third world countries.

Laser sintering devices have been increasingly used to fabricate the metal frameworks of metal-ceramic restorations. In the fabrication process, the sintering layer thickness is an important parameter; however, information on how it may affect the flexural strength of metal frameworks remains limited.The purpose of this in vitro study was to evaluate the flexural strength of 3-unit and 4-unit cobalt-chromium (Co-Cr) metal frameworks laser sintered with 20-μm, 30-μm, and 40-μm layer thicknesses.Three-unit and 4-unit master metal die models with premolar and molar abutments were prepared through direct metal laser sintering (DMLS). A total of 40 metal frameworks (n=10 for each metal die model) were fabricated by the lost-wax technique (group C, served as the control group) and through DMLS with 20-μm, 30-μm, and 40-μm layer thickness (experimental groups LS20, LS30, and LS40, respectively). Each metal framework was cemented to a master die with a polyvinyl siloxane impression material and then subjected to a 3-point bend test at a crosshead speed of 1 mm/min. The yield force of each metal framework was used to calculate the flexural strength. Data were statistically analyzed by using 1-way ANOVA followed by a Tukey honestly significant difference (HSD) test and an independent-samples t test (α=.05) The microstructure of the fracture surface was evaluated by scanning electron microscopy.Group C reported the lowest mean flexural strength (P.05), whereas group LS20 reported the highest mean flexural strength, although no significant difference (P.05) in flexural strength was observed among the DMLS groups. The 3-unit metal frameworks exhibited a statistically significant higher mean flexural strength than the 4-unit metal frameworks (P.05).The sintering layer thickness did not significantly affect the flexural strength of the laser-sintered metal frameworks. However, the DMLS groups reported a higher mean flexural strength than the cast group.

OBJECTIVE This study aimed to investigate nurses’ perceptions of oral healthcare provision to inpatients in Japanese hospitals and the infection control measures taken by them after the coronavirus disease 2019 (COVID-19) lockdown, to promote collaborative oral healthcare in hospitals. METHOD The participants were 1,037 nurses working in inpatient wards at four hospitals in Fukuoka Prefecture, Japan. Data were collected through a questionnaire survey, approximately six months after the COVID-19 lockdown. RESULTS More than 90% of the 734 nurses participating in this study positively perceived the preventive effect of oral healthcare on aspiration pneumonia, ventilator-associated pneumonia, and viral infection. However, approximately half of them had negative perceptions about their knowledge and confidence regarding the control of COVID-19 with oral healthcare provision, and 84.7% expected to be provided with the necessary information by oral health professionals. Further, 537 nurses (73.2%) provided oral healthcare to their patients; nine nurses (1.7%) responded that those patients who received oral healthcare decreased after the lockdown; and 12 (2.4%) responded that they could no longer collaborate with oral health professionals because of the lockdown. Additionally, 41.7 % of them used neither protective glasses nor face shields even after the lockdown. CONCLUSIONS This study showed that almost all the nurses positively perceived the effect of oral healthcare on the prevention of viral infection and pneumonia. However, some nurses perceived that their oral healthcare provision and collaborative oral healthcare were negatively affected. It also showed that most nurses’ knowledge, confidence, and use of infection control measures were insufficient. This study proposes that oral health professionals should support nurses in providing oral healthcare by providing them with information on COVID-19 infection control measures to prevent infection transmission through oral healthcare.

Focusing on the accurate size, direction and position of dynamic meshing impact, an innovative semi-finite element method (semi-FEM) forecasting model is proposed for spiral bevel gear transmission under both high speed and heavy load conditions. To distinguish with the traditional rotor dynamic analysis focusing on vibration effect for global system, a new dynamic loaded tooth contact analysis (DLTCA) focusing on loaded contact effect for local contact area is proposed for the geometric boundary forecasting. Where, DLTCA shows a systematically time-varying characteristics including the dynamic loaded contact pattern, pressure, transmission error. Considering tooth flank flexural behaviors, data-driven tooth flank simulation and finite element modeling is developed by using universal motion concept (UMC) machine settings. At each finite element in a local geometric boundary, the dynamic compatibility and equilibrium equations are established as a semi-FEM dynamic meshing impact forecasting model. Moreover, for a dynamic transmission system, a basic judgement criterion is firstly developed. Then, the improved simplex method is applied to solve the established model for the dynamic meshing impact size evaluations including transmission error, torque, angular velocity, and acceleration. Finally, numerical and test instances are provided to verify the proposed method.

In order to satisfy the machining requirements of aero-engine casing in modern aviation industry, this paper investigates three main issues during the design and development process of a five-axis machine tool with high accuracy, stiffness and efficiency, including whole structure design, key components design, and supporting stiffness design. First, an appropriate structure of five-axis machine tool is determined considering the processing characteristics of aero-engine casing. Then, a dual drive swing head and a compact motorized spindle are designed with enough drive capability and stiffness, and related structure, assembly method, cooling technology, and performance simulation are given in detail. Next, a design method of supporting stiffness of guide is proposed through the deformation prediction of the spindle end. Based on above work, a prototype of machine tool is developed, and some experiments are carried out, including performance tests of swing head and motorized spindle, and machining of a simulated workpiece of aero-engine casing. All experimental results show that the machine tool has satisfactory accuracy, stiffness and efficiency, which meets the machining requirements of aero-engine casing. The main work can be used as references for engineers and technicians, which are meaningful in practice.

PURPOSE To compare medial elbow stress during squatting throwing, standing throwing, and maximum effort throwing and to analyze its relationships with throwing variables and the hip joint internal rotation (IR) range of motion (ROM) in youth baseball catchers. METHODS Forty-five youth baseball catchers were recruited. Exclusion criteria included pain during throwing, history of surgery, or upper-extremity injuries within 12 months. Catchers performed 5 throws for each of the following throwing conditions: squatting throwing, standing throwing, and maximum effort throwing. Catchers were outfitted with a wearable sensor sleeve that recorded the medial elbow torque, arm speed, and shoulder rotation. Ball velocity was measured using a radar gun. RESULTS Final analysis included 42 catchers (mean age, 11.5 ± 1.2 years; mean catcher experience, 16.7 ± 10.3 months). The medial elbow torque was significantly greater during maximum effort throwing (19.0 ± 5.2 Nm) than during squatting throwing (14.3 ± 5.4 Nm) and standing throwing (15.7 ± 4.7 Nm) (both P < .001); there was no significant difference between squatting throwing and standing throwing. Multiple linear regression analysis showed that the ball velocity was significantly positively associated with the medial elbow torque during squatting throwing and standing throwing (P = .023 and P = .029, respectively). During squatting throwing, the hip IR ROM on the throwing side was significantly negatively associated with the medial elbow torque (P = .011). CONCLUSIONS The medial elbow torque during squatting throwing was equivalent to that during standing throwing. Increased medial elbow torque was associated with greater ball velocity during squatting throwing and standing throwing and with decreasing hip joint IR ROM on the throwing side during squatting throwing. Evaluation and stretching of the hip joint IR ROM on the throwing side may be important to decrease elbow stress during squatting throwing in youth baseball catchers. LEVEL OF EVIDENCE Level II, prospective comparative observational trial.

A high thrust liquid oxygen-kerosene fuelled engine is being developed for future launch vehicle applications. Comprehensive hot testing of engine at sea level conditions is required for qualification and acceptance of flight engine and launch vehicle stage. The engine and stage will be tested in a specialized rocket engine and stage hot test facility which deflects the flame safely to avoid any hazard to engine and adjoining mechanical structures. The facility is equipped with water jets to sufficiently cool the rocket plume before impinging on deflector pit walls. The high temperature and high-pressure rocket exhaust jet is cooled with sufficient quantity of water to maintain the impingement wall temperature within safe working limits. In this study, a multi-phase computational fluid dynamics (CFD) methodology is developed for design of water-cooling jet configuration of deflector facility. Multi-phase model validation study using full phase treatment and droplet assumption for water injection is performed prior to water jet optimization analysis of high thrust LOX-kerosene test facility. Validation studies based on simulation and analysis of existing test stand is developed. A discrete particle (DPM) based two phase methodology is chosen to model water injection in RANS framework. The optimum cooling configuration is determined iteratively through numerous multi-phase simulations. The multi-phase analysis showed ineffectiveness of initial water injection scheme which results in facility wall temperature above safe limit. A multi-plane water injection scheme is devised there on with provision of water injection at two axial locations from the nozzle exit. A detailed parametric multi-phase analysis is carried out for design optimization of multi-plane water injection scheme and to determine thermal condition of the test facility. Analysis showed effective rocket plume cooling and lower facility wall temperature with two plane water injection schemes in comparison to initial single plane design configuration. The study highlights the role of CFD based methodology to formulate an engineering solution for design optimization of LOX-kerosene engine hot test facility.

Recently, five-axis machining centers with non-orthogonal rotation axes have been developed to achieve a high stiffness and large machinable area. Although such machine tools can expand the manufacturing field, adopting not only orthogonal axes, but also non-orthogonal axes, requires generalization of conventional form-shaping theory. Moreover, since it is not possible to imagine simultaneous five-axis movement of machine tools with non-orthogonal axes, it is important to analyze the validity of the developed machine tools with non-orthogonal axes using generalized form-shaping theory by a structure analysis method. In the present paper, generalization of the form-shaping function is first performed, and the conditions whereby machining centers with non-orthogonal axes can achieve every position and posture are clarified for an index showing the validity of the machine tool structure. Finally, the machining feasibility is verified for a machine tool structure with non-orthogonal axes using the derived conditions.

A theoretical treatment on the oxide-controlled dwell fatigue crack growth of a γ’ strengthened nickel-based superalloys is presented. In particular, this study investigates the influence of an externally applied load and variations in the γ’ dispersion on the grain boundary oxide growth kinetics. A dislocation-based viscoplastic constitutive description for high temperature deformation is used to simulate the stress state evolution in the vicinity of a crack at elevated temperature. The viscoplastic model explicitly accounts for multimodal γ’ particle size distributions. A multicomponent mass transport formulation is used to simulate the formation/evolution of an oxide wedge ahead of the crack tip, where stress-assisted vacancy diffusion is assumed to operate. The resulting set of constitutive and mass transport equations have been implemented within a finite element scheme. Comparison of predicted compositional fields across the matrix/oxide interface are compared with experiments and shown to be in good agreement. Simulations indicate that the presence of a fine γ’ size distribution has a strong influence on the predicted ow stress of the material and consequently on the relaxation in the vicinity of the crack-tip/oxide wedge. It is shown that a unimodal dispersion leads to reduced oxide growth rates (parabolic behavior) when compared to a bimodal one. Stability conditions for oxide formation are investigated and is associated with the prediction of compressive stresses within the oxide layer just ahead of the crack tip, which become progressively negative as the oxide wedge develops. However, mechanical equilibrium requirements induce tensile stresses at the tip of the oxide wedge, where failure of the oxide is predicted. The time taken to reach this critical stress for oxide failure has been calculated, from which dwell crack growth rates are computationally derived. The predicted rates are shown to be in good agreement with available experimental data.

Accurate detection of mechanical components faults is an essential step for reduction of repair cost, human injury probability and loss of production. Using intelligent fault diagnosis systems in tractor could prevent secondary damage, thereby avoiding heavy consequences. In this study, fault diagnosis of tractor auxiliary gearbox is presented. Vibration signals of healthy and faulty pinions gear under three different operational conditions (Rotational speeds of 600 RPM, 1350 RPM and 2000 RPM) were collected, and discrete wavelet transform (DWT) was used as signal processing. Useful statistical features were calculated from collected signals. Correlation-based feature selection (CFS) method was used to find the best features. Random forest (RF) and multilayer perceptron (MLP) neural networks were employed to classify the data. The overall accuracy of RF classifier without using feature selection were 86.25%, at 600 RPM. The corresponding values of RF trained with the optimal 6 features by using CFS was 92.5%. The best results obtained at 1350 RPM, since the detection accuracy was 95%. The results of this study demonstrated the effectiveness and feasibility of the proposed method for fault diagnosis of tractor auxiliary gearbox.

Background The coronavirus disease 2019 pandemic prompted a surge in telemedicine, with the presumption that patients had computer and internet access. We sought to determine, in a population-based sample, how many Americans were using computers and the internet before the pandemic, and whether disparities existed in this. Methods The National Health Interview Survey is conducted annually by the Centers for Disease Control and Prevention and is representative of the entire United States civilian non-institutionalized population. In 2018, questions were fielded regarding computer and web utilization. We evaluated sociodemographic factors associated with this. Results Twenty-five thousand and forty-nine people, representing 245,842,992 in the population, responded to these questions. Of the responses, 19% stated they used a computer "never or almost never," 18% stated they did not use the internet, and 25% did not use email. Over the previous 12 months, 55% of responders stated they had looked up health information on the internet, 11% had filled a prescription online, 16% had scheduled a medical appointment on the internet, and 17% had communicated with a healthcare provider by email. Internet usage varied by region, age, race, education, family income, and insurance status, but not by gender. Conclusion As telemedicine becomes more prevalent, sociodemographic factors limiting computer and internet use may disadvantage certain segments of the population.

Aiming at the main problems in the design and analysis of well wall strengthening for fractured formations, a three-dimensional (3D) numerical simulation scheme is proposed. The three-dimensional finite element software is used to analyze the mechanical behavior of fractures and the pressure sealing process, and evaluate the stress cage effect. The main features of the model are as follows: (1) The equivalent fractures in the analytical model represents the function sum of the mechanical behavior of all fractures on the well wall, which is a functionally equivalent crack.(2) When evaluating the stress cage effect, the shape of the crack wedge filled with the plugging agent particles is formed by simulating the fractures opening process under the injection pressure, not a given regular shape.(3) In the model of calculating bull heading of block agent, the liquid pressure on the well wall is the injection pressure, which is a variation increased with time. The fluid pressure on the well wall in the stress cage calculation model is generated by the initial pore pressure. (4) The numerical evaluation of the stress cage effect is achieved by calculating the increase amplitude FX of the minimum hoop stress on the well wall. Using this model, several sets of injection pressure design values can be used for pressure plugging numerical simulation and stress cage effect evaluation calculation, and then the optimal and accurate quantitative value of “injection pressure, block agent particle size, safe mud window upper bound” are found through comparison. Finally, through an engineering example of horizontal well drilling pressure sealing in a shale gas reservoir developed by a fracture, we use the above theoretical tools to introduce the process and results of the numerical analysis of the extended mud window drilled by the shale gas fissure reservoir.

With the improvement of the accuracy of the inertial system, the influence of the disturbing gravity field on the accuracy of long-range rocket has become increasingly prominent. However, in actual engineering, there are problems of low accuracy and being time-consuming for disturbing gravity field compensation. In view of this, this paper proposes a set of online comprehensive solutions combining disturbing gravity reconstruction and stellar correction. According to the pre-launch binding parameters, the net function assignment method is used in the navigation system to calculate disturbing gravity in the boost phase online. In the guidance system, a closed-loop guidance online compensation method is proposed based on the state-space perturbation method for the disturbing gravity in the coast phase. At the same time, the vertical deflection can also be corrected by stellar guidance. The calculation results are simulated and verified under different circumstances. Simulation results show that the proposed online compensation algorithm has an accuracy improvement compared with the element compensation algorithm on ground. And the stellar guidance algorithm can further correct the impact deviation. The impact deviation after comprehensive compensation does not exceed 50 m, and the compensation percentage is greater than 65%.

Slip status of drill string is system generated binary value computed by comparison of sensor generated real time hook load value with a minimum threshold value of hook load stored in measurement system. This research article describes a novel method of slip status detection by machine vision technology which helps overcome the constraints of slip status detection with legacy measurement method. It also helps improve the real time drilling data quality and optimize and automate drilling operations. A method to detect drill string slip status with high-resolution digital camera installed on mast near rig floor is described along with backend vision processing and communication modules, which generate binary values of slip status. The binary values are transferred in real time to drilling measurement system of rig to compute other drilling parameters like bit depth, hole depth and stand counters. This method includes deploying active optical sensors at the rig floor, obtaining 1-D, 2-D, or 3D image data, and processing it to obtain the status of drill string. Reliable measurement of slip status by machine vision helps reduce non-productive time (NPT) by reliable real time surveillance of drilling operations.

Serverless computing, or Function as a Service (FaaS), represents a research trend where applications are built and deployed as a group of stateless functions. Although initially proposed for the cloud, serverless computing has also found its place on Internet of Things (IoT) while bringing functions closer to the devices, in order to reduce latency and avoid unnecessary energy and resource consumption. It is interesting that solutions can work in an integrated manner on edge, fog, and cloud layers. Mission-critical functions can be executed on edge and fog in order to benefit from low-latency responses, while heavy functions can be executed on the cloud to process huge amount of data produced by IoT sensors, as long as Internet connection is available. Existing surveys focus on serverless computing for specific layers and do not address a broad, integrated, and systematic vision regarding how IoT benefits from serverless on edge, fog, and cloud. With this in mind, this paper provides a comprehensive Systematic Literature Review that, after the selection process, covers 60 papers on the field of serverless computing for IoT on the three layers. This gives us insights about how functions are offloaded to different devices and how they interact with each other. We bring main components employed to incubate and execute functions, as well as the main challenges and open questions for this subject. Protocols, programming languages, and storage services related to the solutions are also presented. Finally, we show a rich taxonomy summarizing all characteristics in a single figure, along with a discussion about the overall architecture of serverless applications for IoT. We conclude that serverless computing is a promising technology for IoT applications, but several improvements still need to be made to popularize this concept and make it easier to use.

This paper presents the topic of using solid rocket propulsion for de-orbiting spacecraft, in order to fulfil space debris mitigation requirements. The benefits and disadvantages of using such means are discussed. A dedicated system can be implemented in the satellite design phase and shall be a key subsystem of platforms inserted into orbit. Uncontrolled, semi-controlled and controlled de-orbit can be completed using solid rocket motors. Their impact on the space debris environment is discussed. Specific requirements for dedicated propellants and systems are provided. While the majority of presently developed rocket systems worldwide require high burn rates, several applications, including de-orbiting, benefit from solid propellants with decreased regression rates. This allows limiting spacecraft accelerations and loads during de-orbit manoeuvres. Moreover, the requirement of minimising solid particle generation is presented. Heritage technology from the Mercury and Gemini human spaceflight programmes, where de-orbit motors were used, is shown. Historical Soviet, American and Chinese film-return-capsule solid propellant retrorockets, enabling de-orbit, are also presented. A detailed survey of current work worldwide on end-of-life disposal using solid propulsion is included. Challenges of developing dedicated systems are discussed. Finally, an outlook on solid rocket motor utilisation for space debris mitigation is provided.

This article investigates the asymmetric effect of internet access (index of the internet) on economic growth in 42 sub-Saharan African (SSA) countries over the period 2008-2018.The estimation procedure is obtained following a dynamic panel threshold regression technique via 1000 bootstrap replications and the 400 grids search developed by Hansen (1996, 1999, 2000). The investigation first explores the presence of inflection points in the relationship between internet access and economic growth through the application of Hansen's threshold models. The finding from the nonlinearity threshold model revealed a significant internet threshold-effect of 3.55 percent for growth. The article also examines the linear short-run effect of internet access on economic growth while controlling for the effects of private sector credit, trade openness, government regulation, and tariff regimes. The marginal effect of internet access is evaluated at the minimum, and the maximum levels of government regulation and tariffs regime are positive. On the other hand, the minimum and maximum levels of private sector credit and trade openness are negative via the interaction terms. The article advances the literature by its nonlinear transformation of the relevance of internet access on economic growth by exploring interactive mechanisms of internet access versus financial resource, internet access versus trade, internet access versus government regulation, and internet access versus the tariff regimes from end-user subscriptions. In policy terms, the statistical significance of the joint impact of government regulations and tariff regimes is relevant in the operation of the telecommunication industry in SSA countries.

At present, the surface precision requirements for mold and die parts are extremely high. Especially in the precision mold and die cavity for ELD lenses, several mirror surfaces for automotive lens parts, and general camera lenses that required a few tens or a single nano-level like a mirror-finished surface. This final process is difficult to achieve with the conventional cutting edge of ball-nose end mills. In addition, it is commonly performing a very long time by manual polishing of the skilled worker after machining. To the problem, we purposed to develop a sintered polycrystalline diamond (PCD) rotary tool with a simple spherical cutting part. This PCD tool is a novel method for the final process of the small molds and dies cavities with high precision. A distinctive feature of its cutting can achieve a mirror-finished surface by full automation on a CNC machining center. This study aims to clarify the basic machining characteristics and verify its effectiveness on the hardened stainless steel commercial STAVAX with the hardness of 54 HRC for small mold and die cavities. As a result, we can clarify the chip generation mechanism, finish surface accuracy, internal crystal structure state, and residual stress characteristic of this processing method. It also shows that the manual problems related to mirror finishing of the precision mold and die cavity can be solved under the actual mold manufacturing process by consecutive conditions.

This paper describes a technical feasibility study of on-board metal hydride storage systems. The main advantages of these systems would be that of being able to replace counterweights with the weight of the storage system and using the heat emissions of fuel cells for energy, making forklifts a perfect use case. The main challenge is designing a system that supplies the required energy for a sufficiently long period. A first draft was set up and analyzed to provide a forklift based on a fuel cell with hydrogen from HydralloyC5 or FeTiMn. The primary design parameter was the required amount of stored hydrogen, which should provide energy equal to the energy capacity of a battery in an electric vehicle. To account for highly dynamic system requirements, the reactor design was optimized such that the storage was charged in a short time. Additionally, we investigated a system in which a fixed amount of hydrogen energy was required. For this purpose, we used a validated simulation model for the design concepts of metal hydride storage systems. The model includes all relevant terms and parameters to describe processes inside the system's particular reactions and the thermal conduction due to heat exchangers. We introduce an embedded fuel cell model to calculate the demand for hydrogen for a given power level. The resulting calculations provide the required time for charging or a full charge depending on the tank's diameter and, therefore, the necessary number of tanks. We conclude that the desired hydrogen supply times are given for some of the use cases. Accordingly, the simulated results suggest that using a metal hydride system could be highly practical in forklifts.