Energy Conservation Techniques Research Articles

Experimental investigation of pulp dewatering by high vacuum suction boxes

AbstractReducing energy consumption by industrial processes has become imperative because of rising energy costs and efforts toward decarbonisation. The continuous manufacturing of paper is energy intensive due in part to the water removal process required to convert pulp slurries to valuable paper products. This necessitates the development of energy conservation techniques, while simultaneously ensuring the quality of the product. A pilot-scale test unit was developed to quantify the effects of dwell time, vacuum pressure, and refining energy on the achievable pulp concentration or dryness level of three pulp types utilised in paper machines. Pulp dry matter was investigated as a means of gauging vacuum consumption and hence energy utilisation in paper machines, which could potentially reduce utility consumption of the overall drying process. A novel approach to simulate the pulsating high vacuum zone in the forming section of a paper machine was implemented, allowing the development of statistical correlations to explore vacuum dewatering conditions that may lead to energy efficiency. Bleached hardwood, mechanical/groundwood and recycled pulp were characterised to determine the effects of refining energy on fibre morphology and their drainage behaviour in pulp slurries. A dryness level of 21.8% at − 55 kPa gauge was achieved for bleached hardwood, whereas lower values of 19.8 and 18.3% were observed for recycled and mechanical pulps, respectively. This behaviour was attributed to the differences in drainability and morphology of the pulps due to their respective unique properties, further exaggerated by refining.

Effect of 4-Week Pulmonary Rehabilitation on Dyspnea, Fatigue, Quality of Life and Radiological Findings in a Patient with Pulmonary Renal Syndrome Suffering from Pneumonia - A Case Study

Background: Pulmonary renal syndrome (PRS) is a rare, autoimmune disease, defined as combination of pulmonary symptoms (cough, chest pain and dyspnea- at acute stage) and rapidly progressive glomerulonephritis. Pneumonia is an inflammatory condition caused by infectious agents leading to fever, cough and shortness of breath. We report a case of a 42 years old female suffering from PRS and recently diagnosed with bacterial pneumonia. Medically she was managed through antibacterial and oral corticosteroids. At initial encounter of pneumonia, she was in intensive care unit and had cough, dyspnea, pyrexia and fatigue with oxygen saturation (SpO2) of 94% on 15 liters of oxygen via non rebreathable mask. Her chest x-ray demonstrated lobar pneumonia involving right upper lobe. Even after the resolution of pneumonia, she had fatigue, dyspnea and baseline SpO2 of 90-92% on room air. Thus, all the above traits were treated by pulmonary rehabilitation. Purpose: To study the effect of tailor-made pulmonary rehabilitation in pneumonia along with PRS. Method: Physiotherapy was divided into 2 phases: (1) Acute phase: chest physiotherapy (breathing exercises, nebulization, bronchial hygiene, percussion and vibration) (2) Subacute and Late phase: dyspnea management, energy conservation techniques, early mobilization, exercise training (aerobic and strength) Result: 4 weeks of pulmonary rehabilitation resulted in significant improvement in radiological finding, St. George’s respiratory questionnaire (85.39 to 15.53), SpO2 at room air (90% to 99%), Modified Medical Research council score (4 to 1), fatigue severity scale (43 to 21) with an improved inspiratory capacity measured by incentive spirometer. Conclusion: Pulmonary rehabilitation is a structured and multifaceted approach which improves respiratory function, enhance physical fitness, reduces fatigue and the length of hospital stay, prevent recurrence and optimize overall quality of life. Our findings underscore the pivotal role of pulmonary rehabilitation in the treatment of pneumonia alongside Pulmonary Renal Syndrome. Keywords: pulmonary rehabilitation, pneumonia, pulmonary renal syndrome

Occupational therapy and chronic pain - the didactic experience at academic pain league at the University of São Paulo medical school

Occupational Therapy interventions for people with chronic pain focus on promoting independence/autonomy and rescuing meaningful activities (interrupted after the limitations brought about by illness). Various strategies can be used, such as: guidance on energy conservation and joint protection techniques, prescription and/or manufacture of positioning devices, prescription and/or manufacture of assistive technology equipment, development of creative and expressive activities, training activities of daily living, environmental assessment, guidance for family members and caregivers. This article aims to present the implementation of the Occupational Therapy Service at the FMUSP Pain League, developed since 2023. The work focused on implementing Occupational Therapy as one of the professions that make up the FMUSP Pain League, on a permanent and continuous basis; and, in addition, allow undergraduates teaching opportunities (theoretical and practical) related to the multidisciplinary care of people with chronic pain, as well as promoting research actions in the area of ​​Occupational Therapy and Chronic Pain. In OT, a student and the supervising teacher work, together with the multidisciplinary team. Activities are weekly and take place at night. Remote and in-service supervision is carried out. The implementation took place in 3 stages. In the first stage, we sought to understand the dynamics of the league, as well as characterize the patients and their specific demands, through participant observation. The second stage was structured around the specific OT intervention; evaluations of league users were carried out, with the application of evaluation and recording instruments. The third stage focused on monitoring patients and families, with new assessments carried out when necessary. Interventions follows through individual plan care, family guidance, development of educational material, prescription and/or production of assistive technology devices. The service uses a specific evolution form and the data feeds into a service database. We consider that the results obtained are satisfactory, as theoretical and practical learning was possible for the participating student. Currently, Occupational Therapy is already part of the League's routine activities, with participation in the Introductory Course, in the Board of Directors and in planning activities for 2024.

Eco-Friendly Energy Efficient Classrooms and Sustainable Campus Strategies: A Case Study on Energy Management and Carbon Footprint Reduction

This research paper presents a comprehensive study on energy management and carbon footprint reduction in an educational institutional campus. It focuses on implementing energy-efficient technologies and practices to minimize energy consumption and environmental impact. The study encompasses four cases, each addressing different aspects of energy use in a university setting, including the installation of LED lighting, programmable remote switches, and high-efficiency air conditioning systems. The methodology involves a detailed analysis of energy consumption patterns, using smart energy meters and theoretical calculations. Case I establishes a baseline energy consumption, while subsequent cases implement energy-saving measures. Case II involves replacing traditional tube lights with energy-efficient LED lights, resulting in considerable energy savings. Case III extends these savings further by integrating programmable remote switches mapped with student timetables. Finally, Case IV proposes the replacement of older air conditioning units with 25 SEER models, leading to significant reductions in energy use. The results highlight the effectiveness of these interventions. Case II achieves a 66.67% energy saving, while Case III yields up to 77.78% energy saving in lighting and 33.34% in air conditioning. In Case IV, the adoption of high-efficiency air conditioners can result in a 52% energy saving during teaching weeks. The economic benefits of these measures are substantial, with cost savings per classroom ranging from 7.65% in Case II to 53.46% in Case IV. Moreover, the environmental impact of these energy conservation techniques is substantial. The study reports reductions in carbon emissions from 14.71metric tons of carbon dioxide equivalent (MT CO2e) in base Case I to 6.85 MT CO2e in Case IV. The overall carbon emission reductions for Cases II, III, and IV are 7.61%, 36.37%, and 53.43%, respectively. This study demonstrates the profound impact of integrated energy management strategies in reducing the carbon footprint and energy consumption in educational institutions, offering a model for sustainable and economically viable operations.

Energy-efficient scheduling for parallel applications with reliability and time constraints on heterogeneous distributed systems

Reliability is a crucial index of the system, and many safety-critical applications have reliability requirements and deadline constraints. In addition, in order to protect the environment and reduce system operating costs, it is necessary to minimize energy consumption as much as possible. This paper considers parallel applications on heterogeneous distributed systems and proposes two algorithms to minimize energy consumption for meeting the deadline and satisfying the reliability requirement of the applications. The first algorithm is called minimizing scheduling length while satisfying the reliability requirement (MSLSRR). It first transforms the reliability requirement of the application into the reliability requirement of the task and then assigns the task to the processor with the earliest finish time. Since the reliability generated by MSLSRR is often higher than the reliability requirement of the application, and the scheduling length is also less than the deadline, an algorithm called improving energy efficiency (IEE) is designed, which redefined the minimum reliability requirement for the task and applied dynamic voltage and frequency scaling (DVFS) technique for energy conservation. The proposed algorithms are compared with existing algorithms by using real parallel applications. Experimental results demonstrate that the proposed algorithms consume the least energy.

Comparison of Joint Mobilization and Energy Conservation Technique in Rheumatoid Arthritis Patients in Hand Joints

Background: Rheumatoid arthritis is an auto-immune inflammatory condition that affects the hand, wrist,andknee joints.Joint mobilization is frequently used in RA patients. This study was to find the effectiveness of Jointmobilization and Energy conservation technique using range of motion measurement and Sollerman handfunction test in hand joints.Purpose: This study is to find the effect of Joint mobilization and Energy conservation technique which is a noninvasiveprocedure on Rheumatoid arthritis patients.Materials and Methods: A group of 60 Rheumatoid arthritis patients were selected according to inclusion andexclusion criteria from Saveetha medical college and hospital and SAGA Rehabilitation centre.they were dividedinto Joint mobilization group: (n=30) the subjects were treated with Joint mobilization and taught exercises to gainstrength and mobility for 3 days a week for 4 weeks for 15-30 minutes and Energy conservation group: (n=30) thesubjects are taught pacing the activities, prescribing assistive devices, foam-covered handles, wide grip handlesusing large joints to lift objects, teaching Proper body mechanics and Ergonomic considerations to be followed for4 weeks.Study period: November 2022 to April 2023.Result: A statistically significant difference between Joint Mobilization and Energy conservation technique groupsreveals that Joint mobilization has significant effects in lowering stiffness and pain and improving ROM of handjoints.Conclusion: Joint mobilization worked more effectively than energy conservation techniques in RA patients.

Nonintrusive Load Monitoring (NILM) Using a Deep Learning Model with a Transformer-Based Attention Mechanism and Temporal Pooling

Nonintrusive load monitoring (NILM) is an important technique for energy management and conservation. In this paper, a deep learning model based on an attention mechanism, temporal pooling, residual connections, and transformers is proposed. This article presents a novel approach for NILM to accurately discern energy consumption patterns of individual household appliances. The proposed method entails a sequence of layers, including encoders, transformers, attention, temporal pooling, and residual connections, offering a comprehensive solution for NILM while effectively capturing appliance-specific energy usage in a household. The proposed model was evaluated using UK-DALE, REDD, and REFIT datasets in both seen and unseen cases. It shows that the proposed model in this paper performs better than other methods stated in other papers in terms of F1-score and total error of the results (in terms of SAE). This model achieved an F1-score equal to 92.96 as well as a total SAE equal to −0.036, which shows its effectiveness in accurately diagnosing and estimating the energy consumption of individual home appliances. The findings of this research show that the proposed model can be a tool for energy management in residential and commercial buildings.

Ab. No. 32 Effect of 4-Week Pulmonary Rehabilitation on Dyspnoea, Fatigue, Quality of Life and Radiological Findings in a Patient of Pulmonary Renal Syndrome Suffering from Pneumonia- A Case Study

Introduction: Pulmonary renal syndrome (PRS) is a rare, autoimmune disease, defined as combination of pulmonary symptoms (cough, chest pain and dyspnoea- at acute stage) and rapidly progressive glomerulonephritis. Pneumonia is an inflammatory condition caused by infectious agents leading to fever, cough and shortness of breath. We report a case of 42 years old female suffering from PRS and recently diagnosed with bacterial pneumonia. Medically she was managed through antibacterial and oral corticosteroids. At initial encounter of pneumonia, she was in intensive care unit and had cough, dyspnoea, pyrexia and fatigue with oxygen saturation (SpO2) of 94% on 15 litres of oxygen via non-re-breathable mask. Her chest x-ray demonstrated lobar pneumonia involving right upper lobe. Even after the resolution of pneumonia, she had fatigue, dyspnoea and baseline SpO2 of 90-92% on room air. Thus, all the above traits were treated by pulmonary rehabilitation. The study aims to find the effect of tailor-made pulmonary rehabilitation in pneumonia along with PRS. Methods: Physiotherapy was divided into 2 phases: (1) To treat pneumonia- chest physiotherapy (breathing exercises, nebulization, bronchial hygiene, percussion, and vibration) (2) After resolution of pneumonia: dyspnoea management, energy conservation techniques, early mobilization, exercise training (aerobic and strength) Result: 4 weeks of pulmonary rehabilitation resulted in significant improvement in radiological findings, St. George’s respiratory questionnaire (85.39 to 15.53), SpO2 at room air (90% to 99%), Modified Medical Research council score (4 to 1), fatigue severity scale (43 to 21) with an improved inspiratory capacity measured by incentive spirometer. Conclusion: Our results underline pulmonary rehabilitation as an important pillar in the treatment of pneumonia with PRS.

Enhancing Next-Generation Wireless Networks Using Preemptive Energy Conservation Technique

Enhancing Next-Generation Wireless Networks Using Preemptive Energy Conservation Technique

Distributionally robust deep network based on [formula omitted]-divergence for non-intrusive load monitoring

Non-Intrusive Load Monitoring (NILM) is a crucial technique for energy conservation as it provides detailed energy consumption data for individual household appliances, leading to targeted energy saving strategies. In practice, the startup phase of appliances is more significant than the shutdown phase, especially when predicting appliance-level consumption. When implementing Sequence-to-Point (S2P) based network models, where each appliance is trained separately, the primary source of training error comes from state transitions during startup, particularly those involving other appliances. These transitions can be mistakenly learned by the network as spurious correlations. This paper presents a method for effectively filtering such samples, and extracting features that are more resistant to spurious correlation confusion. We propose a Distributionally Robust Deep Network (DRDN) model grounded in ϕ-divergence, to address the NILM disaggregation problem. Our model incorporates an adaptive loss-scaled robust parameter to enable sample selection and improve decision-making. Our experimental results on the REDD and UK-DALE datasets demonstrate that DRDN models exhibit superior transferability and effectiveness in solving domain generalization problem compared to traditional deep learning approaches across different buildings.

Energy Consumption Reduction in Wireless Sensor Network-Based Water Pipeline Monitoring Systems via Energy Conservation Techniques

In wireless sensor network-based water pipeline monitoring (WWPM) systems, a vital requirement emerges: the achievement of low energy consumption. This primary goal arises from the fundamental necessity to ensure the sustained operability of sensor nodes over extended durations, all without the need for frequent battery replacement. Given that sensor nodes in such applications are typically battery-powered and often physically inaccessible, maximizing energy efficiency by minimizing unnecessary energy consumption is of vital importance. This paper presents an experimental study that investigates the impact of a hybrid technique, incorporating distributed computing, hierarchical sensing, and duty cycling, on the energy consumption of a sensor node in prolonging the lifespan of a WWPM system. A custom sensor node is designed using the ESP32 MCU and nRF24L01+ transceiver. Hierarchical sensing is implemented through the use of LSM9DS1 and ADXL344 accelerometers, distributed computing through the implementation of a distributed Kalman filter, and duty cycling through the implementation of interrupt-enabled sleep/wakeup functionality. The experimental results reveal that combining distributed computing, hierarchical sensing and duty cycling reduces energy consumption by a factor of eight compared to the lone implementation of distributed computing.

Energy efficiency in healthcare institutions

AbstractThe Environmental Protection Agency classifies healthcare as one of the leading energy-consuming industries. Extensive energy is needed around the clock in healthcare institutions for lighting, ventilation, and operating medical equipment. However, there is a growing concern over the sustainability of energy utilization by healthcare institutions worldwide. This narrative review thus seeks to examine energy efficiency and utilization in healthcare institutions and energy management and conservation techniques and make recommendations for future optimal usage. The paper notes that healthcare institutions use different quantities of energy from diverse sources, including hydropower, biomass, solar energy, and wind power. However, energy consumption varies from one institution to another, with the number of beds and intensity of healthcare operations, with an average of 0.27 MWh m−2. Moreover, this review also identified various techniques and measures to enhance energy efficiency, such as the variant refrigerant flow technology and the combination of renewable energy sources with diesel generators to reduce the cost of electricity. Overall, healthcare institutions need energy management systems such as automated energy monitoring technologies, to check the systems' efficiency. The same techniques can also help Middle Eastern healthcare institutions with efficient energy utilization. Ultimately, the literature review aims to introduce an approach that focuses on reducing site-level consumption of energy while increasing the quality of the energy used and hence, helping reduce energy costs while conserving the environment.

Six Principles Energy Conservation Techniques for Respiratory Frequency and Oxygen Saturation in COPD Patients

Background: Chronic obstructive pulmonary disease refers to chronic diseases, such as emphysema, chronic bronchitis, asthma, or a combination of them. The observed symptoms of chronic obstructive pulmonary disease include breathlessness, wheezing, repeated respiratory tract infection, losing weight, and prolonged fatigue.
 Objectives: This research determined the influence of a 6-principle energy conservation technique on the respiratory frequency and oxygen saturation of COPD patients.
 Methods: This quasi-experimental research applied one group pretest-posttest design. The research design was useful to measure the respiratory rate and oxygen saturation before and after the implementation of 6-principle energy conservation. The researcher involved 29 respondents taken by accidental sampling.
 Results: The result showed the frequency mean before the intervention was 26.34 times per minute and after the intervention was 23.83 times per minute. The oxygen saturation, SpO2, before the intervention, was 97.17% while after the intervention was 96.76%. The Wilcoxon test found the influence of a 6-principle energy conservation technique toward the respiratory rate, a p-value of 0.000. On the other hand, the researcher did not find the influence of the 6-principle energy conservation technique on the COPD patient (p-value 0.944).
 Conclusion: The researcher recommends the implementation of 6-principle energy conservation as the non-pharmacological intervention alternative to manage the abnormal respiratory rate of COPD patients.

Preoperative pulmonary rehabilitation in medical inoperable patients with early stage non-small cell lung cancer and postoperative results

Aims: The impact of postoperative complications after surgery for lung cancer is substantial, with the increasing age of patients and the presence of comorbidities. Impairment in exercise capacity is a potential modifiable risk factor for postoperative complications. This study aimed to assess the contribution of preoperative pulmonary rehabilitation (PR) for increasing operability conditions in non-small cell lung cancer (NSCLC) for patients with limited pulmonary functions and postoperative results.
 Methods: The patients with NSCLC who had preoperative pulmonary rehabilitation and underwent surgical resection in our clinics between 2010-2019 were evaluated retrospectively. The patients enrolled in a comprehensive, multidisciplinary, supervised outpatient 10-day duration PR program preoperatively, consisting of bronchial hygiene, breathing control, energy conservation techniques, exercise training (endurance and strength), psychological support, and nutritional support. Exercise capacity and VO2 peak were evaluated by using an incremental shuttle walk test (ISWT).
 Results: Eighteen patients who underwent surgery due to NSCLC and had a pre-operative pulmonary rehabilitation program were evaluated. All the cases were male; the mean age was 66.2 (53-77) years. The squamous cell/adenocarcinoma ratio was 2.6 (13:5), and the mean tumor size was 4.6 (8-18) cm. The postoperative hospital stay was 12.7 (4-42) days, and they were followed up for an average of 30.2 (2-83) months. 
 Conclusion: Complete surgical resection is the most effective curative treatment for lung cancer. However, many patients with lung cancer also have severe COPD, increasing their risk of postoperative complications and their likelihood of being considered "inoperable." Preoperative pulmonary rehabilitation (PR) has been proposed as an intervention for risk modification and to decrease surgical morbidity and mortality. The results of our study also revealed the importance of preoperative pulmonary rehabilitation in centers where lung cancer surgery was performed.

Energy Conservation Techniques in Tropical Climate - A Comprehensive Review and Adaptation of the Lamin House for Nusantara

Energy Conservation Techniques in Tropical Climate - A Comprehensive Review and Adaptation of the Lamin House for Nusantara

Numerical simulation study on the effects of co-injection of pulverized coal and SPL (Spent Pot-Lining) into the blast furnace

This study investigated the potential use of spent pot-lining (SPL) as a supplementary fuel in blast furnaces (BFs) to replace coke or pulverized coal (PC). A numerical model was established to study the combustion behavior of mixed fuel (MF) containing 80 % PC and 20 % SPL in the raceway of BF. The study focused on the effects of blast velocity, temperature, injection rate, and oxygen content on combustion. Results showed that the burnout rate has a positive relationship with blast velocity and oxygen content, and decreases with the increase of blast temperature and injection volume. To obtain a high temperature zone, it is recommended to increase the oxygen content and air volume of the blast, and the blast temperature (1473 K) and injection volume (169 kg/t) maintain the basic operating conditions. These results can provide insights into the potential use of SPL as a waste resource in iron-making processes, which can promote the substitution of industrial waste SPL for PC in high-energy-consuming industries, contribute to the development of green metallurgical technology, and advance global energy conservation and emission reduction techniques.

Energy centric reputation index and fuzzy-based clustering for wireless sensor networks

Energy conservation is essential for a wireless sensor network to enhance its network lifetime. Clustering is one of the most important energy conservation techniques that prolong the WSN by providing balanced energy depletion across the network. Various clustering strategies have been proposed in the past to enhance the efficiency of the network till now. In the last two decades, fuzzy inference system based clustering solution has been proven to provide promising solutions. The existing fuzzy-based clustering algorithms consider the naïve network parameters as input that saves only a limited amount of energy in the network. However, in wireless sensor networks, the requirement is to make them highly energy efficient through an effective clustering strategy. To achieve effective clustering there is a need for energy-centric network parameters for the clustering instead of naïve network parameters. In this article, a novel energy-centric reputation index is proposed in which the naïve network parameters are unified with energy parameters in the background. Further, the reputation index scores are passed into a fuzzy-based approach to obtain the fitness value of the node chosen as the cluster head. Thus, in this paper, an energy-centric reputation index and fuzzy-based clustering(ECRIF) model is proposed for wireless sensor networks. The proposed model provides a highly energy-efficient wireless sensor network and is designed to work in two phases. In phase 1, three reputation indexes concerning internodal distance, distance to the sink, and the degree of the node is calculated while considering their energy consumption pattern in the background. In phase 2, the three reputation indexes are passed onto the fuzzy system as fuzzy input parameters to obtain the fitness value of the nodes for cluster head selection. Simulation results confirm that the proposed protocol enhances the overall lifetime of the network on an average by 70% in terms of the first node dies, 61% in terms of half node dies, and 78% in terms of the last node dies when compared with two other existing clustering models.

Advanced Active and Passive Methods in Residential Energy Efficiency

Energy efficiency in buildings is very important since it contributes significantly to fossil fuel consumption and consequently climate change. Several approaches have been taken by researchers and the industry to address the issue. These approaches are classified as either passive or active approaches. The purpose of this review article is to summarize a number of the technologies that have been investigated and/or developed. In this technical review paper, the more commonly used active and passive building energy conservation techniques are described and discussed. The pros and cons of both the active and passive energy techniques are described with appropriate reference citations provided. This review article provides a description to give an understanding of building conservation approaches. In the active classification, several methods have been reviewed that include earth-to-air heat exchangers, ground-source and hybrid heat pumps, and the use of new refrigerants, among other methods. In the passive classification, methods such as vegetated roofs, solar chimneys, natural ventilation, and more are discussed. Often, in a building, multiple passive and active methods can be employed simultaneously.

A Health App for Post-Pandemic Years (HAPPY) for people with physiological and psychosocial distress during the post-pandemic era: Protocol for a randomized controlled trial.

This article describes a protocol for a randomized controlled trial to evaluate the effects of a three-level Health App for Post-Pandemic Years (HAPPY) on alleviating post-pandemic physiological and psychosocial distress. Convenience and snowball sampling methods will be used to recruit 814 people aged 18+ with physiological and/or psychosocial distress. The experimental group will receive a 24-week intervention consisting of an 8-week regular supervision phase and a 16-week self-help phase. Based on their assessment results, they will be assigned to receive interventions on mindfulness, energy conservation techniques, or physical activity training. The waitlist control group will receive the same intervention in Week 25. The primary outcome will be changes in psychosocial distress, measured using the Kessler Psychological Distress Scale (K10). Secondary outcomes will include changes in levels of fatigue (Chinese version of the Brief Fatigue Inventory), sleep quality (Chinese version of the Pittsburgh Sleep Quality Index), pain intensity (Numeric Rating Scale), positive appraisal (Short version of the 18-item Cognitive Emotion Regulation Questionnaire), self-efficacy (Chinese version of the General Self-efficacy Scale), depression and anxiety (Chinese version of the 21-item Depression Anxiety Stress Scale), and event impact (Chinese version of the 22-item Impact of Event Scale-Revised). All measures will be administered at baseline (T0), Week 8 after the supervision phase (T1), and 24 weeks post-intervention (T2). A generalized estimating equations model will be used to examine the group, time, and interaction (Time × Group) effect of the interventions on the outcome assessments (intention-to-treat analysis) across the three time points, and to compute a within-group comparison of objective physiological parameters and adherence to the assigned interventions in the experimental group. The innovative, three-level mobile HAPPY app will promote beneficial behavioral strategies to alleviate post-pandemic physiological and psychosocial distress. ClinicalTrials.gov, NCT05459896. Registered on 15 July 2022.

Energy Conservation Techniques for Manufacturing Industries

Energy Conservation Techniques for Manufacturing Industries