Current Equipment Research Articles

Temperature Distribution and Equipment Layout in a Deep Chamber: A Case Study of a Coal Mine Substation

With the gradual depletion of shallow resources, the process of resource exploitation is being transferred to greater depths. The temperature of the surrounding rock increases gradually in the process of deep mining, and the temperature of the underground substation chambers often exceeds the normal working temperature in summer. In this paper, the equipment layout and ventilation conditions of the deep substation chamber of the Jiangxi Qujiang Mining Company were selected as the research subjects, and numerical simulation software was used to study the temperature distribution within the chamber under different conditions by changing the combinations of the wind velocity and air temperature of the inlet air of the chamber. The study showed that, under the conditions of the current equipment layout and air door size, the equipment temperature was prone to being too high in the summer. Therefore, the layout of the equipment was optimized based on the simulation results. The transformer equipment was changed from the original serial mode to the juxtaposed mode, and the size of the air door was increased, which effectively reduced the disturbance of the air flow and the length of the air flow path in the chamber. This meant that the high temperature area of the chamber was at the end of the chamber, which efficiently reduced the area of the high temperature zone and ensured that the equipment was in a lower temperature environment. This method can be used as a reference for temperature distribution, layout, and temperature control measures within buildings.

Treatment planning for Flash radiotherapy: General aspects and applications to proton beams.

The increased radioresistence of healthy tissues when irradiated at very high dose rates (known as the Flash effect) is a radiobiological mechanism that is currently investigated to increase the therapeutic ratio of radiotherapy treatments. To maximize the benefits of the clinical application of Flash, a patient-specific balance between different properties of the dose distribution should be found, that is, Flash needs to be one of the variables considered in treatment planning. We investigated the Flash potential of three proton therapy planning and beam delivery techniques, each on a different anatomical region. Based on a set of beam delivery parameters, on hypotheses on the dose and dose rate thresholds needed for the Flash effect to occur, and on two definitions of Flash dose rate, we generated exemplary illustrations of the capabilities of current proton therapy equipment to generate Flash dose distributions. All techniques investigated could both produce dose distributions comparable with a conventional proton plan and reach the Flash regime, to an extent that was strongly dependent on the dose per fraction and the Flash dose threshold. The beam current, Flash dose rate threshold, and dose rate definition typically had a more moderate effect on the amount of Flash dose in normal tissue. A systematic estimation of the impact of Flash on different patient anatomies and treatment protocols is possible only if Flash-specific treatment planning features become readily available. Planning evaluation tools such as a voxel-based dose delivery time structure, and the inclusion in the optimization cost function of parameters directly associated with Flash (e.g., beam current, spot delivery sequence, and scanning speed), are needed to generate treatment plans that are taking full advantage of the potential benefits of the Flasheffect.

A Comparative Study of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): From Convolutional Neural Networks to Visual Transformers.

In recent years, deep learning has made brilliant achievements in Environmental Microorganism (EM) image classification. However, image classification of small EM datasets has still not obtained good research results. Therefore, researchers need to spend a lot of time searching for models with good classification performance and suitable for the current equipment working environment. To provide reliable references for researchers, we conduct a series of comparison experiments on 21 deep learning models. The experiment includes direct classification, imbalanced training, and hyper-parameters tuning experiments. During the experiments, we find complementarities among the 21 models, which is the basis for feature fusion related experiments. We also find that the data augmentation method of geometric deformation is difficult to improve the performance of VTs (ViT, DeiT, BotNet, and T2T-ViT) series models. In terms of model performance, Xception has the best classification performance, the vision transformer (ViT) model consumes the least time for training, and the ShuffleNet-V2 model has the least number of parameters.

Current Inhalation Equipment for Analgesia with the Inert Gas Xenon

Current Inhalation Equipment for Analgesia with the Inert Gas Xenon

Inspection of Synchronous Belt in Lifting Appliances

Introduced the inspection requirements of the main transmission components in the hoisting machinery in the current special equipment regulation; Checked the technical requirements related to safety in the relevant standards of the synchronous belt. Based on the physical structure, failure mode and regulatory standard requirements of the synchronous belt, summarized the inspection method of the synchronous belt.

Hydro electroactive Cu/Zn coated cotton fiber nonwovens for antibacterial and antiviral applications

In this study, Cu/Zn galvanic electrodes were sputtered on the two surfaces of hydrophilic cotton fiber nonwovens (Cotton) to prepare hydro electroactive Cu/Cotton/Zn composites. When the Cu/Cotton/Zn was used as a functional layer in the face mask, the Cu/Zn galvanic electrodes can be spontaneously activated by water vapor molecules exhaled by the human body and generate galvanic current. Based on this, the hydro electroactive Cu/Cotton/Zn demonstrated excellent antibacterial activity against Escherichia coli and Staphylococcus aureus and could deactivate Enterovirus 71 (EV71) virions transmitted through the respiratory tract by 97.72% after 15 min of contact. Moreover, the Cu/Cotton/Zn did not affect the particle filtration efficiency and breathability of the face mask's polypropylene (PP) melt-blown layer. Furthermore, the cytotoxicity assessment of Cu/Cotton/Zn showed no cytotoxicity, indicating good biological security. Overall, the Cu/Cotton/Zn may provide a new approach to increase the antibacterial and antiviral performance of current personnel protective equipment on the market.

A Real-Life Reproducibility Assessment for NMR Metabolomics.

Nuclear magnetic resonance (NMR) metabolomics is currently popular enough to attract both specialized and non-specialized NMR groups involving both analytical trained personnel and newcomers, including undergraduate students. Recent interlaboratory studies performed by established NMR metabolomics groups demonstrated high reproducibility of the state-of-the-art NMR equipment and SOPs. There is, however, no assessment of NMR reproducibility when mixing both analytical experts and newcomers. An interlaboratory assessment of NMR quantitation reproducibility was performed using two NMR instruments belonging to different laboratories and involving several operators with different backgrounds and metabolomics expertise for the purpose of assessing the limiting factors for data reproducibility in a multipurpose NMR environment. The variability induced by the operator, automatic pipettes, NMR tubes and NMR instruments was evaluated in order to assess the limiting factors for quantitation reproducibility. The results estimated the expected reproducibility data in a real-life multipurpose NMR laboratory to a maximum 4% variability, demonstrating that the current NMR equipment and SOPs may compensate some of the operator-induced variability.

A Wearable and Real-Time Pulse Wave Monitoring System Based on a Flexible Compound Sensor.

Continuous monitoring of pulse waves plays a significant role in reflecting physical conditions and disease diagnosis. However, the current collection equipment cannot simultaneously achieve wearable and continuous monitoring under varying pressure and provide personalized pulse wave monitoring targeted different human bodies. To solve the above problems, this paper proposed a novel wearable and real-time pulse wave monitoring system based on a novel flexible compound sensor. Firstly, a custom-packaged pressure sensor, a signal stabilization structure, and a micro pressurization system make up the flexible compound sensor to complete the stable acquisition of pulse wave signals under continuously varying pressure. Secondly, a real-time algorithm completes the analysis of the trend of the pulse wave peak, which can quickly and accurately locate the best pulse wave for different individuals. Finally, the experimental results show that the wearable system can both realize continuous monitoring and reflecting trend differences and quickly locate the best pulse wave for different individuals with the 95% accuracy. The weight of the whole system is only 52.775 g, the working current is 46 mA, and the power consumption is 160 mW. Its small size and low power consumption meet wearable and portable scenarios, which has significant research value and commercialization prospects.

An Immersible Microgripper for Pancreatic Islet and Organoid Research.

To improve the predictive value of in vitro experimentation, the use of 3D cell culture models, or organoids, is becoming increasingly popular. However, the current equipment of life science laboratories has been developed to deal with cell monolayers or cell suspensions. To handle 3D cell aggregates and organoids in a well-controlled manner, without causing structural damage or disturbing the function of interest, new instrumentation is needed. In particular, the precise and stable positioning in a cell bath with flow rates sufficient to characterize the kinetic responses to physiological or pharmacological stimuli can be a demanding task. Here, we present data that demonstrate that microgrippers are well suited to this task. The current version is able to work in aqueous solutions and was shown to position isolated pancreatic islets and 3D aggregates of insulin-secreting MIN6-cells. A stable hold required a gripping force of less than 30 μN and did not affect the cellular integrity. It was maintained even with high flow rates of the bath perfusion, and it was precise enough to permit the simultaneous microfluorimetric measurements and membrane potential measurements of the single cells within the islet through the use of patch-clamp electrodes.

Transmission modes of severe acute respiratory syndrome coronavirus 2 and implications for infection control: a review.

The complete picture regarding transmission modes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unknown. This review summarises the available evidence on its transmission modes, our preliminary research findings and implications for infection control policy, and outlines future research directions. Environmental contamination has been reported in hospital settings occupied by infected patients, and is higher in the first week of illness. Transmission via environmental surfaces or fomites is likely, but decontamination protocols are effective in minimising this risk. The extent of airborne transmission is also unclear. While several studies have detected SARS-CoV-2 ribonucleic acid in air samples, none has isolated viable virus in culture. Transmission likely lies on a spectrum between droplet and airborne transmission, depending on the patient, disease and environmental factors. Singapore's current personal protective equipment and isolation protocols are sufficient to manage this risk.

Novel Vote Scheme for Decision-Making Feedback Based on Blockchain in Internet of Vehicles

Obtaining timely and accurate traffic information is one of the most important problems in intelligent transportation system, which will make vehicles run smoothly, avoid road congestion, save road running time and reduce vehicle energy consumption. In the current Internet of Vehicles system, the traffic management center can learn from the feedback information of all vehicles to improve the ability of decision-making and traffic command. However, the existing feedback mechanism does not respond to the spatial-temporal characteristics of data in time, due to the lack of communication capability of the current equipment. So, it cannot meet the requirements of ultra-low delay, high reliability and high security in the Internet of Vehicles. To solve this problem, this paper proposes a blockchain-based proxy vote and revocation scheme for decision feedback in Internet of Vehicles, which allows the intelligent system to ignore the unevenness and heterogeneity in the 6G technology. In addition, blockchain technology notarizes the vote data of vehicles and outsources microservices. Secondly, we use the attributes of decision-related nodes instead of their identities to enable anonymous vote. Smart contracts can automatically expand the scalability of outsourced microservices. Finally, the security proof of the proposed scheme ensures the security and consistency of outsourced microservices. The simulation results also show that our scheme greatly improves the efficiency of voting feedback.

Passion as a Determinant in Sport Consumption: the Case of Amateur Cyclists

This paper analyses sport passion as a possible determinant for sport consumption. The purpose of this research, after defining the concept of passion for cycling, is to understand the existing relations between the latter and the costs incurred to practice this sport at an amateur level. This research is exploratory in nature and uses a qualitative mix-method approach. Given the need to isolate individual dynamics of cyclists from socio-cultural influences, the interviewees were selected from a restricted and homogeneous geographical area: the Umbria Region (Italy). The study is structured in two phases: in the first phase 22 in-depth interviews were carried out; in the second phase a group interview was preferred. In order to guarantee transparency e verifiability of the results, the answers were handled with the help of a word processing software (NVIVO). The results of this research suggest that cyclists’ consumption models are instrumentally influenced by the passion for cycling, more than other characteristics previously studied in sport management literature. This study provides useful indications on how to develop new forms of market segmentation. It also offers an approach for the operationalization of the level of passion for cycling, which enriches the current equipment of sports management researchers, who can also use the work in other contexts of free time consumption. This work highlights the key role of passion as a determinant for sport consumption and represents an original connection between psychological studies on sport passion and economic studies on sport consumption.

Techno-economic analysis of solar energy system for electrification of rural school in Southern Ethiopia

To provide rural communities with low-cost electricity, innovative off-grid renewable energy producing techniques have emerged. The International Energy Agency estimates that around 45% of Ethiopia’s total population have access to electricity. Nearly 85% of Ethiopia’s urban population has access to public electricity, but this figure is only 29% for the rural population. This study examines the feasibility of using combined photovoltaic (PV)/diesel/battery systems to power a remote rural school in southern Ethiopia. The performance of various hybrid systems was assessed using techno-economic and environmental analyses, and the optimal solution was chosen using the Hybrid Optimization Model for Electric Renewable (HOMER) analytic tool. The evaluation criteria include net present cost (NPC), cost of energy (COE) and emissions. The results indicate that PV/DG/battery hybrid energy system (HES) with a 7.5 kW PV, 7.3 kW DG, 6.60 kW converter, and 11 units of batteries (case I) is the most feasible, optimized, cost-effective and environmentally friendly system among the systems considered. This system has a Net Present Cost (NPC) of $32,019 and a Cost of Energy (COE) of $0.254/kWh, as computed using current equipment values. The optimized system is also environmentally benign, emitting 793 kg of carbon dioxide per year, about 91% less than the PV/diesel combination (worst case IV). Furthermore, sensitivity analysis was performed to examine the impacts of altering factors such as solar radiation, fuel price, and battery minimum state of charge (SOCmin) on system cost and performance. We believe that the information given in this paper will shed light on the current state and future prospects for renewable energy deployment in Ethiopia, and also show that, if policymakers create the necessary investment environment, such projects can be a viable alternative to rural electrification.

IMPLEMENTASI STOP KONTAK PINTAR PADA LAMPU TAMAN DENGAN MENGGUNAKAN MIKROKONTROLLER WEMOS D1 R1 BERBASIS IOT

The socket is an electrical installation that functions as a liaison between electric current and electrical equipment, one example is a garden lamp. To be able to turn on, you need a power outlet, but manual sockets are considered less effective due to the development of human habits leaving the house with the lights still on. With current technological developments, namely utilizing internet of things (IoT) technology, a smart socket is made that can be controlled remotely via a smartphone. The smart socket is made using Wemos D1 R1 as the microcontroller and is equipped with a raindrop sensor as a safety where the system will turn off the electricity automatically when the sensor detects water and a notification will appear on the smartphone as if water has been detected, so users don't have to worry about leaving the house. with a state of forgetting not to turn off the garden lights.

The Effect of Covid-19 Pandemic on Current and Future Endoscopic Personal Protective Equipment Practices: A National Survey of 77 Endoscopists.

IntroductionThe COVID-19 pandemic has raised awareness about the importance of personal protective equipment (PPE). We aimed to study and compare PPE practices among Canadian endoscopists before and after the COVID-19 pandemic.MethodsA 74-item questionnaire was emailed from June 2020 to September 2020 to practicing endoscopists in Canada. Survey questions collected basic demographics and differences between PPE practices pre- and post-COVID-19. PPE practices were categorized into four endoscopic procedure types including upper or lower endoscopy and diagnostic or interventional. Outcomes for specific procedures were reported as rates, with ranges shown when evaluating all procedure types together.ResultsA total of 77 respondents completed the survey with the majority of respondents aged 40 to 49 (44%) and identifying as Gastroenterologists (70%). Gender was evenly split (49% females versus 51% males). In the pre-pandemic era, the majority of endoscopists wore gowns (91 to 94%) and all endoscopists wore gloves (100%). However, the majority of endoscopists did not wear surgical masks (21 to 31%), face shields (13 to 34%), eye protection (13 to 21%), hair protection (11 to 13%), or N95 respirators (2 to 3%). In the post-pandemic era, more surgeons plan on wearing face shields (33 to 47%, P = 0.001 to 0.045), goggles (38.5 to 58.7%, P < 0.001), hair protection (33 to 36%, P = 0.011 to 0.024), and a trend suggests more surgeons will wear surgical masks (51 to 61%, P = 0.163 to 0.333). More endoscopists also plan on wearing N95 respirators during lower endoscopy (6 to 7%, P < 0.005).ConclusionThe COVID-19 pandemic has changed the attitudes of many endoscopists regarding future PPE use in routine endoscopy. Ongoing studies are needed to inform new post-pandemic PPE consensus guidelines.

Regression and Classification Model Based Predictive Maintenance of Aircrafts Using Neural Network

One of the key objectives of today's businesses and mills is to predict machine problems. Failures must be avoided, because downtimes represent expensive expenses and a loss of productivity. This is why the number of remaining cycles (RULs) until the failure occurs is vital in machine maintenance. The estimations of the RUL should be based on earlier observations, whenever possible under the same conditions. In the research of RUL estimates, the creation of systems that monitor current equipment conditions is becoming crucial. I employed Long Short Term Memory (LSTM) in my project to determine an aircraft's remaining usable lives. The aircraft's functioning condition is also forecast. The former is done by a regression method, using a classification methodology predicted by working circumstances. In order to estimate operating conditions and remaining usable life of the aircraft, data utilized for LSTM models training are derived from 21 aircraft sensor readings located at different locations with three distinct settings.

Deep learning-based system development for black pine bast scale detection

The prevention of the loss of agricultural resources caused by pests is an important issue. Advances are being made in technologies, but current farm management methods and equipment have not yet met the level required for precise pest control, and most rely on manual management by professional workers. Hence, a pest detection system based on deep learning was developed for the automatic pest density measurement. In the proposed system, an image capture device for pheromone traps was developed to solve nonuniform shooting distance and the reflection of the outer vinyl of the trap while capturing the images. Since the black pine bast scale pest is small, pheromone traps are captured as several subimages and they are used for training the deep learning model. Finally, they are integrated by an image stitching algorithm to form an entire trap image. These processes are managed with the developed smartphone application. The deep learning model detects the pests in the image. The experimental results indicate that the model achieves an F1 score of 0.90 and mAP of 94.7% and suggest that a deep learning model based on object detection can be used for quick and automatic detection of pests attracted to pheromone traps.

Study of Generator Set Overload Protection System in Power Generation Units

The need for electrical energy in an industry is very important for the production process to run. To meet the demand for electrical energy, one can use a power source from PLN or use an independent power source by establishing a power plant. The Power Plant Unit is a unit that functions to provide electrical energy needs for the production process at PPSDM Migas. Electricity generation in the Power Plant Unit, namely Pembangkit Listrik Tenaga Diesel (PLTD) using a generator set that uses diesel fuel. A generator set or generator is a generator that has been equipped with a prime mover. Gensets that work continuously are certainly inseparable from disturbances such as the occurrence of overloads. Overload disturbance occurs because the amount of load power supplied by the generator is greater than the capacity of the working generator. Air Circuit Breaker (ACB) is one of the protective equipment used to protect generator sets. Inside the ACB there is Over Current Trip equipment that will work if there is an overload on the generator. The capacity of the generator used is 1000kVA/400V with a nominal generator current of 1443.38 A. Under normal load conditions, the installed load power is 354.5 kW with a load current of 639.6 A. Then at peak load conditions, the installed load power is 510,3 kW with a load current of 920.7 A. In both conditions, the load current does not exceed the nominal current of the generator so Over Current Trip does not instruct ACB to trip. However, it is possible for overload disturbances to occur if there is no coordination between the operator at the power plant and the load operator (refinery &amp; utilities) so that the operation of the load is not controlled.

Development of Ocean Current Power Generation Equipment as Learning Materials

The purpose of this study is to develop teaching materials and teaching tools for raising the ability to think and judge scientifically and to evaluate and utilize them, while encouraging the understanding according to the developmental stage, taking energy situation and environmental problem of Japan and the world which are tense recently as a subject. In this study, the development of the ocean current power generation equipment is proposed with the aim of scientifically recognizing the necessity of the introduction of the renewable energy and technical problems in proportion to the developmental stage, and acquiring the ability to appropriately evaluate and utilize the technology. The developed equipment is composed of a hull and a power generation turbine. On the hull, the hull stabilization is attempted by arranging two floats made of foamed polystyrene side by side. The turbine was designed by 3D CAD and fabricated by 3D printer. Created. On the power generation turbine, after the students themselves designed it using simple 3DCAD and printed it by 3D printer, they intend to improve it so that it becomes more efficient through experiment and measurement in this experimental equipment.

Airway consideration in cleft patients-challenges and approaches

Over the last few decades, there is a paramount shift in the implementation of pediatric anesthesia. Although for most of the time, difficult airway scenarios are well-planned and executed, occasionally an unanticipated difficult situation may still arise. This is more common in patients with orofacial anomalies such as cleft lip and palate which constitute one of the most common craniofacial anomalies. Various approaches to difficult airway management in an infant undergoing cleft repair have been described in the literature. However, no approach is considered ideal. It depends on age, associated anomalies, at hand resources, and the skill of the anesthesiologist. The unique anatomical and physiological features of pediatric airways impose additional challenges. The evolution of advanced airway modalities such as video laryngoscopes (VLs) and fiber-optic bronchoscopes had a major impact on the practice of anesthesia and the management of difficult airway scenarios in children and neonates. This article focuses on airway assessment and various current techniques and equipment used in airway management of cleft anomalies. Pediatric airway devices such as supraglottic airways, VLs, and fiber-optic bronchoscopes are briefly discussed with the benefits and limitations of each device. Recent studies describe specific problems as well as advantages with the usage of these devices.