The combined heat and power system is based on the principle of "cascade utilization of thermal energy" for system integration and optimization. The rational utilization of energy, as well as the rational arrangement of energy flow and the process optimization combination of the overall system are taken into account in order to achieve multifunctional goals in the field of thermal engineering. The present paper presents a detailed assessment of combined heat and power systems from above standpoints. This article is divided into two parts “CHP based on thermo-dynamic cycles” and “CHP based on non-thermodynamic cycles”. Each part is then classified based on power subsystem energy consumption efficiency (high or low), including Rankine cycle, ORC, Stirling cycle, gas turbine, reciprocating engine, PVT and fuel cell. The present paper also helps identify the research gaps in this area and provides direction on future studies on combined heat and power systems.

This paper is about energy as viewed through an integrated model that links energy with environment, technology and urbanisation as related areas. Our goal is to empirically investigate the (in)efficient energy use across 30 developed OECD member states during the period from 2001 to 2018. For that purpose, we set up an output-oriented BCC data envelopment analysis that employs a set of input variables with non-negative values to calculate the efficiency scores on minimising energy use and losses as well as environmental emissions. We develop a couple of baseline models for primary energy and secondary energy (electricity) in which we find that countries have mean inefficiency margins of 16.1 per cent for primary energy and from 10.8 to 13.5 per cent for electricity. Then, we extend the baseline models by adding environment as an important closely related concept and confirm the consistency of the baseline findings. In the context of this analysis, however, the inefficiency scores, on the one hand, point out to a mismatch in the utilisation of the inputs to produce efficiency but, on the other hand, they uncover a hidden potential to increasy efficiency through re-allocation under constant inputs.

Although energy management of a microgrid is generally performed using a day-ahead scheduling method, its effectiveness has been questioned by the research community due to the existence of high uncertainty in renewable power generation, power demand and electricity market. As a result, real-time energy management schemes are recently developed to minimise the operating cost of a microgrid while high uncertainty presents in the network. This paper develops modified particle swarm optimisation (MPSO) algorithms to solve optimisation problems of energy management schemes for a community microgrid and proposes a scheduling approach after taking into consideration high uncertainty to effectively minimise the operational cost of the microgrid. The optimisation problems are formulated for real-time and scheduling approaches, and solution methods are developed to solve the problems. It is observed that the scheduling program demonstrates superior performance in all the cases, including uncertainty in prediction, as compared to the other energy management approaches, although solutions have significant deviations due to prediction errors.

This paper presents an in-depth contextualized tutorial on Agricultural IoT (Agri-IoT), covering the fundamental concepts, assessment of routing architectures and protocols, and performance optimization techniques via systematic survey and synthesis of related literature. The negative impacts of climate change and the increasing global population on food security and unemployment threats have motivated the adoption of the wireless sensor network (WSN)-based Agri-IoT as an indispensable underlying technology in precision agriculture and greenhouses to improve food production capacities and quality. However, most related Agri-IoT testbed solutions have failed to achieve their performance expectations due to the lack of an in-depth and contextualized reference tutorial that provides a holistic overview of communication technologies, routing architectures, and performance optimization modalities based on users’ expectations. Thus, although IoT applications are founded on a common idea, each use case (e.g., Agri-IoT) varies based on specific performance and users expectations as well as its technological, architectural, and deployment requirements. Likewise, the agricultural setting is a unique and hostile area where conventional IoT technologies do not apply, hence the need for this tutorial. Consequently, this tutorial addresses these via the following contributions: (1) a systematic overview of the fundamental concepts, technologies, and architectural standards of WSN-based Agri-IoT, (2) an evaluation of the technical design requirements of a robust, location-independent, and affordable Agri-IoT, (3) a comprehensive survey of the benchmarking fault tolerance techniques, communication standards, routing and medium access control (MAC) protocols, and WSN-based Agri-IoT testbed solutions, and (4) an in-depth case study on how to design a self-healing, energy-efficient, affordable, adaptive, stable, autonomous, and cluster-based WSN-specific Agri-IoT from a proposed taxonomy of multi-objective optimization (MOO) metrics that can guarantee an optimized network performance. Furthermore, this tutorial established new taxonomies of faults, architectural layers, and MOO metrics for cluster-based Agri-IoT (CA-IoT) networks and a 3-tier objective framework with remedial measures for designing an efficient associated supervisory protocol for cluster-based Agri-IoT networks.

The growing urgency for sustainable energy solutions necessitates a deeper understanding of the environmental impacts of renewable technologies. This article aims to synthesize and analyze Life Cycle Assessments (LCA) in this domain, providing a comprehensive perspective. We systematically categorize 2,923 articles into four communities: (1) Photovoltaic systems, (2) Wind energy systems, (3) Materials for auxiliary industry of photovoltaic and wind systems, and (4) Solar thermal systems. A comparative analysis is conducted to identify methodological consistencies and disparities across these communities. The findings reveal diverse methodological approaches and a range of environmental impacts, highlighting the complexities in assessing renewable energy systems. The article underscores the significance of material selection in photovoltaic and wind systems, providing a critical overview of the current state of LCA research in renewable energy and stressing the need for standardized methodologies. It also identifies gaps in recent research, offering insights for future studies focused on integrating environmental, economic, and social considerations in renewable energy assessments.As a case study, an LCA was used to evaluate two energy supply methods for a sensor network: one connected to the public grid and another powered by a photovoltaic panel. The off-grid system, while more environmentally friendly by reducing reliance on non-renewable energy sources, posed challenges due to the high environmental impact of battery production and disposal. Integrating environmental assessments provides a robust framework for making informed decisions on sustainable technologies. The findings are critical for projects that balance technological needs with sustainability goals.

The energy efficiency of existing buildings is a crucial factor in addressing Europe’s energy con-sumption challenges, accounting for nearly 40% of the total energy usage. The ongoing energy crisis, driven by the reliance on fossil fuels and increasing prices, has underscored the urgency of adopting sustainable and energy efficient practices especially to the existing building stock. Cyprus is par-ticularly vulnerable due to its heavy dependence on imported fuels for electricity generation and faces significant challenges in transforming its existing building stock into energy-efficient and sustainable structures. Extensive focus has been made by the government on the energy-efficient retrofit of non-residential public buildings. This study examines an existing cultural hall. The case study of the Cultural Hall represents the building stock before 2010 which is lacking thermal in-sulation, double glazing and any energy efficient element. It then offers an ideal case study to ex-plore sustainable solutions which can be easily adopted from the construction industry and from the building owners. The primary objective of this research is twofold: first, to develop a comprehensive retrofit plan to transform the cultural hall into a net-zero energy building; and second, to explore how this transformation can give value back to the local community. After running two simulation scenarios and providing two energy performance certificates, one with at the existing state and one with the intended retrofit measures, it is clear that the building can be a net zero energy consump-tion building. Some interesting results derived, present also how this building can provide value back to the community i.e. through solar carports for EV charging.

Installations of decentralised Renewable Energy Systems (RES) are becoming increasing popular as governments introduce ambitious energy policies to curb emissions and slow surging energy costs. This work presents a novel model for optimal sizing for decentralised renewable generation and hybrid storage system to create a Renewable Energy Community (REC), developed in Python. The model implements PV Solar and Wind Turbines combined with a hybrid battery and Regenerative Hydrogen Fuel Cell (RHFC). The electrical service demand is derived using real usage data from a rural island case study location. Cost remuneration is managed with an REC virtual trading layer, ensuring fair distribution among actors in accordance with the European RED(III) policy. A multi-objective Genetic Algorithm (GA) stochastically determines the system capacities such that the inherent trade-off relationship between project cost and decarbonisation can be observed. The optimal design results in an LCOE of 0.15€/kWh, reducing costs by over 50% compared with typical EU grid power, with a project IRR of 10.8%, simple return of 9.6%/year, and ROI of 9 years. Emissions output from grid only use is reduced by 72% to 69 gCO2e/kWh. Further research of lifetime economics and additional revenue streams in combination with this work could provide a useful tool for users to quickly design and prototype future decentralised REC systems.

In contrast to physical sustainable measures carried out in homes, such as insulation, the installation of a Home Energy Management System (HEMS) has no direct and immediate energy-saving effect. A HEMS gives insight into resident behaviour regarding energy use. When this is linked to the appropriate feedback, the resident is in a position to change his or her behaviour. This should result in reduced gas and/or electricity consumption. The aim of our study is to contribute towards the effective use of home energy management systems (HEMS) by identifying types of homeowners in relation to the use of HEMS. The research methods used were a literature review and the Q-method. A survey using the Q-method was conducted among 39 owners of single-family homes in various Rotterdam neighbourhoods. In order to find shared views among respondents, a principal component analysis (PCA) was performed. Five different types of homeowner could be distinguished: the optimists, the privacy-conscious, the technicians, the sceptics, and the indifferent. Their opinions vary as regards the added value of a HEMS, what characteristics a HEMS should have, how much confidence they have in the energy-saving effect of such systems, and their views on the privacy and safety of HEMS. The target group classification can be used as input for a way in which local stakeholders, e.g. a municipality, can offer HEMS that is in line with the wishes of the homeowner.

In this paper we present a city-scale (possibly global) air pollution network made of low-cost sensors for particulate matter concentration in the air. The components of presented system are based on our research and experience from previous studies focused on air quality instruments and sensors for addressing urban air pollution. Sensor nodes are produced locally and distributed over a city of Sarajevo, Bosnia and Herzegovina. The system collects, calibrates and displays particulate metal concentrations in real-time. In comparison to the available measurements from governmental institutions, our system demonstrated good agreement of measured parameters, with several advantages including: higher resolution in space and time, lower costs, both horizontal and vertical measurements and many more. One of the capabilities of the system is the real-time air pollution city map with animations. By installing multiple sensor nodes over a slope (cable car), we receive vertical measurements of temperature, humidity and particulate matter concentration in real time, which gives a valuable insight into the dynamics of temperature inversion episodes and air pollution below the inversion layer.

This paper describes different variants of broadband and simple attenuator modules for beamforming applications, based on Radio Frequency Micro Electro-Mechanical Systems (RF-MEMS), framed within Coplanar Waveguide (CPW) structures. The modules proposed in the first part of this work differ in their actuation voltage, topology, and desired attenuation level. Fabricated samples of basic 1-bit attenuation modules, characterized by a moderate footprint of 690 x 1960 µm2 and aiming at attenuation levels of -2, -3 and -5 dB in the 24.25-27.5 GHz range, are presented in their variants featuring both low actuation voltages (5-7 V) as well as higher values (~ 45V), the latter ones ensuring larger mechanical restoring force (and robustness against stiction). Beyond the fabrication non-idealities that affected the described samples, the substantial agreement between simulations and measurement outcomes proved that the proposed designs could provide precise attenuation levels up to 40 GHz, ranging up to nearly -3 dB and -5 dB for the series and shunt variants, respectively. Moreover, they could be effective building blocks for future wideband and reconfigurable RF-MEMS attenuators. In fact, in the second part of this work, combinations of the discussed cells and other configurations meant for larger attenuation levels will be investigated.

The COVID-19 pandemic halted progress in global vaccine coverage and disrupted routine childhood vaccination practices worldwide. While there is ample evidence of vaccination declines experienced during the pandemic, it is less clear how low-income countries were affected. We executed a systematic review to synthesize the current literature on impacts to routine childhood vaccinations in low-income countries from January 1, 2020 to February 8, 2023. We collected data using an extraction form on Covidence and assessed the quality of studies included in the review using the Risk of Bias in Non-Randomized Studies of Interventions (ROBINS-I) tool. Effect estimates for changes in vaccination during the pandemic were reported and summarized. Factors that influenced changes were grouped into descriptive themes. Thirteen studies, encompassing 18 low-income countries and evaluating 15 vaccines at varying doses, were included in the final review. We found that routine childhood vaccinations during the COVID-19 pandemic varied considerably by vaccine type, location, and phase of the pandemic. Nine different themes were identified as factors that influenced changes in vaccination. Documenting past experiences and lessons learned is crucial for informing preparedness efforts in anticipation of future public health emergencies. Failure to effectively address these things in the next public health emergency could result in a recurrence of declining routine childhood vaccinations.

Abstract: Efforts for carbon emission reduction have been identified as a major climate change mitigation target in the Paris Agreement. The 26th Conference of Parties to the United Nations Framework Convention on Climate Change highlighted the worldwide effort for cleaner and greener mining, urging the mineral industry to embrace greener operational emissions reduction technologies and strategies. Ghana pledged at the Paris Conference to reduce CO2 emissions by 15% and increase renewable energy share to 10% of the national energy mix. Here the fundamental question is how Ghana’s mining industry can contribute to CO2 emission reduction efforts. This paper investigates barriers to low-carbon emission policy implementation among mining companies in Ghana. The questionnaire survey was conducted among Ghana’s four large-scale gold mining companies. As the sample number of available companies is limited, we used a descriptive analysis to assess the responses. The results show that the companies expressed widely different ways to respond to the issues of cost, a government policy/regulations for carbon emission reduction, and the adoption/acquisition of low-carbon technologies. Those companies that are relatively less prepared for this endeavor emphasized the uncertainties of securing sufficient energy in case of using low-carbon technologies. They also expressed a need for more trained workers to handle low-carbon technologies. All companies agreed with a expected high cost of adopting low-carbon options. There was a communication gap with the relevant government ministry about low-carbon mining options where the government should be able to facilitate the involvement of othe low technology providers, such as solar PV installation.

Amidst escalating environmental concerns, short natural fiber thermoplastic (SNFT) biocomposites have emerged as sustainable materials for the eco-friendly production of mechanical components. However, their limited durability has prompted research into the experimental evaluation of the deterioration of the mechanical characteristics of SNFT biocomposites, particularly under the influence of ultraviolet rays. However, conducting tests to evaluate the mechanical properties can be time-consuming and expensive. In this study, an artificial neural network (ANN) model was employed to predict the mechanical properties (tensile strength) and the impact performance (resistance and absorbed energy) of polypropylene reinforced with 30 wt.% short flax or wood pine fibers (referred to as PP30-F or PP30-P, respectively). Eight parameters were collected from experimental studies. The ANN input parameters comprised nondestructive test results, including mass, hardness, roughness, and natural frequencies, while the output parameters were the tensile strength, the maximum impact load and absorbed energy. The model was developed using the ANN toolbox in MATLAB. The linear coefficient of correlation and mean squared error were selected as the metrics for evaluating the performance function and accuracy of the ANN model. They calculate the relationship and the average squared difference between the predicted and actual values. The data analysis conducted by the models demonstrated exceptional predictive capability, achieving an accuracy rate exceeding 96%, which was deemed satisfactory. For both the PP30-F and PP30-P biocomposites, the ANN predictions deviated from the experimental data by 3, 5, and 6% about the impact load, absorbed energy, and tensile strength, respectively.

Low-cost monitors have made possible for the first time measurements of long-term (months to years) potential indoor exposures to fine particles. Indoor and outdoor measurements made over nearly 5 years (2017-2021) by the largest network of low-cost monitors in the United States (PurpleAir) are compared to the prevalence of adult smokers in 1650 Zip codes within the three West Coast states of California, Oregon, and Washington. The results show that mean indoor exposures above the 75th percentile of adult smoking prevalence are more than 50% higher than those below the 25th percentile. Mean outdoor concentrations are also elevated, but by a smaller amount (20%). Both comparisons are significant at the p<0.001 level. The elevation of the PM2.5 concentrations with increasing smoking prevalence is evidence of environmental disparities in income, education, and other socioeconomic indices..

Background and objectives: Musculoskeletal (MSK) pain significantly impacts physical activity and quality of life in the elderly, potentially influencing mortality. This study explored the relationship between MSK pain, physical activity, muscle mass, and mortality among older adults. Material and Methods: We studied 1000 participants of the Korean Longitudinal Study on Health and Aging (KLoSHA), a prospective, population-based cohort study of people aged 65 years or older. Survival status was tracked over a 5-year period. Correlations between Low back pain (LBP), knee pain, regular exercise, appendicular skeletal muscle mass (ASM), and other variables were analyzed. Logistic regression analyzes were used to identify independent risk factors for mortality. Results: Of the total participants, 829 (82.9%) survived after a 5-year period. Survivors tended to be younger, had a higher BMI, and were more active in regular exercise. In contrast, non-survivors exhibited a higher prevalence of both LBP and knee pain, along with increased instances of multiple MSK pain. Lower ASM correlated moderately with LBP and knee pain, whereas higher ASM was associated with regular exercise Lower ASM was moderately associated with LBP and knee pain, while higher ASM correlated with engagement in regular exercise. There was a moderate correlation between LBP and knee pain, both of which were associated with a lack of regular exercise. Age, sex, ASM, and regular exercise were significant predictors, even though MSK pain itself did not directly predict all-cause mortality. Conclusions: This study demonstrated the independent association between ASM, regular exercise, and mortality. Although MSK pain did not directly correlate with all-cause mortality, the non-survivor group had higher levels of both single and multiple MSK pain. Recognizing the interplay of MSK pain, physical activity, and muscle mass for older adults, the research underscores the need for holistic strategies to enhance health outcomes in older individuals with MSK pain.

Through long-term Rayleigh lidar observations during 2010-2022, atmospheric gravity wave (AGW) activities in the middle atmosphere (30–65 km) are statistically investigated at Haikou (110.3°E, 19.9°N) in China. In total, 827 quasi-monochromatic AGW events are identified from the lidar dataset, and the vertical wavelength, observed wave period, and vertical propagation direction of dominant waves are extracted for each AGW event by analyzing the power spectra of wave-induced temperature perturbations. It is revealed that 81.7% of all AGW events were associated with upward-propagating waves, and the proportion of upward-propagating AGWs reached a maximum in autumn and a minimum in winter. The most common vertical wavelengths and wave periods were 6–11 km and 4–10 hours, respectively. In particular, 68 AGW events associated with simultaneous upward and downward propagating waves were observed by lidar, corresponding to 8.2% of the events. The occurrence of such special AGW phenomena is qualitatively discussed, and multiple formation mechanisms may exist. Comparisons are made with previously reported lidar observation results, and the statistical features of AGW activity in the low-latitude middle atmosphere may vary over a relatively wide range depending on the location and altitude. However, a majority of AGWs propagate upward in the middle atmosphere.

Understanding the evolution patterns in patients diagnosed with acute myeloid leukemia (AML) after therapy is relevant due to the dismal outcome still present in refractory or relapsed AML patients. We performed a retrospective, single-center study to evaluate the mutation profile in paired samples obtained at the time of diagnosis and at the onset of progressive or refractory disease in patients diagnosed with AML through a commercial next-generation sequencing (NGS) panel. In total, 62 patients were analyzed. Of these, 28 patients received ICT, and 34 patients underwent low-intensity treatments. In LIT patients, there were emergent mutations at progressive disease in a 64% (22/34) of the patients. Emergent mutations in the RAS-MAPK signaling pathway were observed in 35.9% (12/34) , corresponding to 54.5% of all patients with emergent mutations (12/22). These were found in 12/22 patients that received venetoclax in combination with hypomethylating agents. Six presented mutations in genes related to the RAS-MAPK pathway. Emerging mutations are frequently observed at progressive AML disease after therapy. In patients treated with LIT, mutations in RAS-MAPK signaling pathway might have a key role on the secondary clinical resistance, not only if they are present at diagnosis, becoming a potential target for the development of new drugs.

A problem of efficacy of crystal growth methods for crystallization from solution or melt has been investigated. Axial vibrational control (AVC) technique was considered as a perspective method to manage both heat-mass transfer and chemical component composition of the melts in the case of crystallization of complex chemical compounds. Numerical modeling and the search for generalized dependencies made it possible to predict the AVC parameters that provide optimal heat and mass transfer modes for creating flat liquid-solid interfaces, as well as the component composition of dissociated melts of various chemical compounds – Ge, NaNO3, CdTe.

The airflow carried by artificial aeration provides oxidant O2 for microbial growth and mineral dissolution in heap bioleaching. To investigate the effect of forced aeration rate on bioleaching of low-grade copper sulfide ores, column bioleaching experiments with six columns were conducted in the aeration range of 0~150 L/h at 30~45 ℃. The results showed that when the aeration rate was higher than 95 L/h, the proportions of heap settlement and fine particles mass were much greater than that without aeration. The final total Fe concentration and bacterial cell numbers in pregnant leach solution increased with the increase of aeration rate.The final concentrations of Cu2 + in the mother liquor under aeration conditions of 60-150 L / h were 1.411, 1.432, 1.498, 1.491 and 1.583 g / L, respectively, which were higher than 1.345 g / L under non-aeration conditions. When the aeration rate was 150 L / h, the final Cu leaching rate was 80.1 %, which was 11.4 % higher than that without aeration ( 68.7 % ). Furthermore, in the early stage of leaching, copper leaching rate with 95 L/h aeration rate remained the highest. 结论Artificial aeration accelerates the bioleaching of low-grade copper sulfide ores by improving porosity structure, temperature range of bacterial activity and microbial catalyzed dissolution of targeted minerals.

Background: Very low-calorie ketogenic diet (VLCKD) is associated with improvement of metabolic and cardiovascular disorders. We aimed to evaluate the effects of VLCKD in patients with Cushing’s disease (CD) as adjunctive therapy to treatment for primary disease. Methods: We evaluated clinical, hormonal and metabolic parameters in 15 patients with CD and 15 controls at baseline and after 1 week and 3 weeks of VLCKD and further 2 weeks of low-carbohydrate ketogenic diet (LCKD). Results: After 5 weeks of diet a significant decrease in BMI (p=0.002), waist circumference (WC) (p=0.024), systolic (p=0.015) and diastolic blood pressure (p=0.005), ACTH (p=0.026), cortisone (p=0.025), total (p=0.006) and LDL cholesterol (p=0.017), triglycerides (p=0.016), alkaline phosphatase (p=0.008) and a significant increase in HDL cholesterol (p=0.017), vitamin D (p=0.015) and oral disposition index (Dio)(p=0.004) was observed in CD. A significant decrease in BMI (p=0.003), WC (p=0.002), systolic (p=0.025) and diastolic (p=0.007) blood pressure and total cholesterol (p=0.026) and increase in HDL cholesterol (p=0.001) and DIo (p<0.001) was observed in controls. Conclusions: The current study confirms that ketogenic diet is effective in improving metabolic disorders and shows that a nutritional approach may be combined with conventional CD therapy in order to improve metabolic and cardiovascular comorbidities.

FeZnNa@SiO2-C catalyst with graphitized carbon (GC) modified mesoporous SiO2 support metal nanoparticles was prepared by sol-gel method. The effect of adding metal Na and Zn promoters as a dispersion on the CO2 hydrogenation to low olefins was systematically studied. The results showed that Zn-Na, as a combination, promoted the absorption of CO2 and improved the conversion rate of CO2. Na as an alkaline substance can improve the absorption of more acidic CO2, improving the conversion rate of CO2 to 59.03%. Meanwhiles, addition of secondary metal Zn into Fe-based catalysts to form a surface alloy could alter the adsorption of CO2 and the activation of C-O bonds, inhibit the subsequent hydrogenation of olefins to paraffins, facilitate the reduction of Fe2O3 and the formation of active Fe5C2 species. From TEM and XRD, the formation of active Fe5C2 species was found, the selectivity of the target product was 41.07%. The deep hydrogenation of olefins is inhibited, by inhibiting their deep hydrogenations, the STY of C2=-C4= was raised again, up to 0.0436. However, the corresponding STY does not increase infinitely with the increase of Na content, and when the Na content to 6.4%, which can be shown higher CO2 hydrogenation catalytic performance. Compared with Fe@SiO2-C catalyst, Na and Zn promoted Fe-based catalysts prepared by modified sol-gel method, can be used directly for highly efficient CO2 hydrogenation to low olefins and thus will be more promising in the future.

The vibration response of soil is a key property in the field of agricultural soil tillage. Vibration components of tillage machinery are generally used to reduce tillage resistance and improve work efficiency, the pressure variation under low-frequency vibration will affect the fragmentation and dispersion of farmland soil. However, the gradient of pressure variation, frequency domain response, and effective transmission range are unclear. A new method based on DEM (Discrete Element Method) is presented to study the vibration response and pressure transmission under low-frequency vibration. Bench test results showed that peak pressure positively correlates with the vibration frequency and attenuates rapidly at the vibration distance of 100 to 250 mm. The results data were also selected to determine the simulation model parameters. Amplitude, vibration frequency, and soil depth were used as test factors in single-factor simulation tests, and their effects on the peak pressure, frequency domain response, and effective transmission distance were analyzed. The results showed a positive relationship between the peak pressure and the test factors. The peak pressure increases with a maximum gradient of 19.02 kPa/mm at a vibration distance of 50 mm. The amplitude, vibration frequency, and soil depth positively correlate with the dominant frequency amplitude. The main frequency is independent of amplitude and soil depth. At the vibration distance of 250 mm, the dominant frequency is approximately twice the vibration frequency at 7–11 Hz and approximately equal to the vibration frequency at 13–15 Hz. Multiple exponential functions were used to fit the peak pressure attenuation function, obtaining an effective transmission distance range of 347.15 to 550.37 mm for the 5kPa cut-off pressure. For a soil depth of 300 mm, the vertical shear wave diffusion angle is greater than the horizontal shear wave diffusion angle. The study clarifies the vibration response of soil under low-frequency vibration, which helps to design vibration type soil-engaging components of tillage machinery and match vibration parameters for energy saving and resistance reduction in soil tillage.

Background: Spinal pain is highly prevalent and in Spain it produces a very high economic cost and the scientific evidence supporting treatments shows low to moderate evidence for exercise. Therefore, the aim of this study was to assess the effectiveness of a therapeutic group exercise protocol in reducing pain intensity and disability in patients with spinal pain in primary health care setting. Methods: A total sample of 149 patients who suffered from chronic non-specific spinal pain. Patients received a therapeutic exercise protocol, including exercises of auto-mobilization of the neck and lumbar regions, as well as core stabilization exercises. Pain intensity and disability were evaluated before and after the therapeutic exercise protocol. Results: Statistically significant differences (P<0.05) were shown for pain intensity and disability of patients with neck and low back pain with an effect size from moderate to large. Conclusions: A therapeutic exercise protocol may provide beneficial effects on disability and pain intensity in patients with chronic non-specific spinal pain, including neck and low back pain conditions. Clinicians should consider the use of self-administered exercise protocols, demonstrate great effectiveness, and be less costly.

The increase and diversity of low-cost Air Quality (AQ) sensors, as well as their flexibility and low power consumption, offers us the opportunity to integrate them into a broad AQ wireless sensor networks with the aim of enabling real-time monitoring and higher spatial sampling density of pollution in all parts of the cities. Considering that the vast majority of the population lives in these cities and the increase in respiratory/allergic problems in a large part of the population, it is of great interest to offer services and applications to improve their quality of life. In the ECO4RUPA project we focus on this kind of service, proposing an inclusive and intelligent routing ecosystem carried out by using a network of low-cost AQ sensors with the support of 5G communications along with official AQ monitoring stations, assisted with artificial intelligence to improve the AQ monitoring data and by spatial interpolation techniques to enhance its spatial resolution. The goal of this service is to calculate healthy walking and/or cycling routes according to the particular citizen’s profile and needs. We provide and analyse the results of the proposed route planner under different scenarios (different time tables, congestion road traffic and routes) and different user’s profiles, with special interest on citizens with asthma and pregnant women, since both require special needs. In summary, our approach can lead to an approximately average reduction in pollution exposure of 17.82%, while experiencing an approximately average increase in distance travelled of 9.8 %.

(1) Background: This study aimed to evaluate whether the implementation of a modified blood sampling protocol, which focused on need-based laboratory testing and minimized venous sampling by replacing it with point-of-care testing (POCT) via capillary puncture, successfully reduced iatrogenic blood loss, incidence of anemia, and frequency of blood transfusion in extremely low birth weight infants (ELBWIs) without negatively affecting neonatal outcomes. (2) Methods: A retrospective analysis was conducted on 313 ELBWIs of gestational age (GA) between 23 and 28 weeks, born between 2013 and 2019. The infants were divided into two groups: before (period I) and after (period II) the implementation of the modified blood sampling protocol in January 2016. Propensity score matching was conducted to minimize selection bias. Clinical data, including the frequency and amount of blood sampling, frequency and volume of blood transfusion, and clinical characteristics, such as gestational age, birth weight, and neonatal outcome data, were collected and compared between the two groups. (3) Results: No significant differences in the GA or birth weight between the two periods were observed. The total sampling volume during a month after birth (16.7 ± 4.1 mL vs. 15.6 ± 4.4 mL, P=0.03) and total sampling volume during hospital days (51.4 ± 29.7 mL vs. 44.3 ± 27.5 mL, P=0.04) in period II were significantly lower than that in period I. There were no differences in the mortality or morbidity between the two periods. Although the transfusion frequency and amount did not have significant differences between the periods, we observed a positive correlation between the transfusion frequency and sampling volume (coefficient: 0.09, 95% CI: 0.08–0.11). (4) Conclusions: The modified blood sampling protocol effectively reduced the iatrogenic blood loss without negatively affecting the neonatal outcomes.

Chondrosarcoma, represents approximately 0.1% of all neoplasms of the head and neck, being considered a rare disease, but with a relatively good prognosis. The 5-year overall survival (OS) rate is estimated at 70-80%, being considered a disease with a low growth rate. About 13% of all cases of chondrosarcoma, are located in the region of the head and neck. We present the case of a young patient treated multimodally, lost from the oncological records less than two years after the diagnosis, without evidence of disease progression. The early loss from the oncological follow-up programs of patients with a lower risk of early repalpse, without evidence of a recurrence or metastasis could be the consequence of a major complication among which we could assume an aspiration pneumonia secondary to a dysphagia, associated with an aggressive multidisciplinary treatment. Large tumor size and positive resection margins (R1 resection) are risk factors that support an intensive adjuvant approach in order to reduce the risk of recurrence, but the low grade of tumor, associating a lower risk of recurrence as well as the adverse events (AE) of adjuvant radiotherapy and chemotherapy justifies a more reserved therapeutic approach. Taking into account the longer life expectancy of these patients, it is recommended to use a more conformal irradiation technique in order to reduce doses to radiosensitive structures as well as to omit elective neck irradiation, taking into account the lower risk of lymph node involvement. The lack of guidelines that include very rare tumors including low grade chondrosarcoma of head and neck make a unified approach difficult, but the data presented even in case reports could contribute to choosing the regimen that offers the best therapeutic ratio.

With the rapid development of electronic and communication technology in military radar, the demand for microwave absorbing materials in low-frequency with thin layer is growing increasingly. In this study, flexible Co3O4/CC (carbon cloth) composites derives from Co-MOFs (metal-organic frameworks)/CC are prepared by hydrothermal and thermal treatment processes. The flexible precursors of Co-MOFs/CC are calcined with different calcination temperatures, which the material structure, dielectric properties and microwave absorption performance are changed. With the increase of calcination temperature, the minimum reflection loss of the corresponding Co3O4/CC composites gradually moves to the lower frequency with thinner thickness. In addition, the Co3O4/CC composites with 25 wt% filler loading ratio exhibit the minimum reflection loss (RL) of -46.59 dB at 6.24 GHz with 4.2 mm thickness. When the thickness is 3.70 mm, the effective absorption bandwidth is 3.04 GHz from 5.84 to 8.88 GHz. This study not only proves that the composite Co3O4/CC is a kind of outstanding microwave absorbing material with better flexibility, but also provides a useful inspiration for the low frequency and broadband microwave absorbing material.

Graphene quality for use in biosensors was assessed in fabricated chips by a set of methods that includes atomic force microscopy (AFM), Raman spectroscopy, and low-frequency noise. It is shown that local areas of residues on the graphene surface, which arisen due to the interaction of graphene with a photoresist at the initial stage of chips development, leads to a spread of chips resistance (R) within 1-10 kΩ and to an increase in the root mean square (RMS) roughness up to 10 times that can significantly impair reproducibility of graphene parameters in biosensors chips. It was observed that the control of the photoresist residues after photolithography (PLG) by AFM and subsequent additional cleaning allow reducing the spread of R values in chips to 1–1.6 kΩ and obtaining RMS roughness similar to the roughness in pristine graphene before PLG. Monitoring of the spectral density of low-frequency voltage fluctuation (SU), which provides integral information about the defect system and quality of the material, makes it possible to identify chips with low graphene quality and with inhomogeneously distributed compressive stresses areas by the type of frequency dependence SU (f).

The Brazilian livestock is predominantly extensive, with approximately 90% of the production being sustained on pasture, which occupies around 20% of the territory. In the current climate change scenario and where cropland is becoming a limited resource, there is a growing need for a more efficient land use and occupation. It is estimated that more than half of the Brazilian pastures have some level of degradation; however there is still no mapping of the quality of pastures on a national scale. In this study, we mapped and evaluated the spatio-temporal dynamics of pasture quality in Brazil, between 2010 and 2018, considering three classes of degradation: Absent (D0), Intermediate (D1), and Severe (D2). There was no variation in the total area occupied by pastures in the evaluated period, in spite of the accentuated spatial dynamics, with a retraction in the center-south and expansion to the north, over areas of ​​native vegetation. The percentage of non-degraded pastures increased ~12%, due to the recovery of degraded areas and the emergence of new pasture areas as a result of the prevailing spatial dynamics. However, about 44 Mha of the pasture area is currently severely degraded. The dynamics in pasture quality were not homogeneous in property size classes. We observed that in the approximately 2.68 million properties with livestock activity, the proportion with quality gains was twice as low in small properties compared to large ones, and the proportion with losses was three times greater, showing an increase in inequality between properties with more and less resources (large and small, respectively). The areas occupied by pastures in Brazil present an unique opportunity to increase livestock production and make available areas for agriculture, without the need for new deforestation in the coming decades.

Background: Simulation plays a crucial role in health studies, as it helps medical students apply their theoretical knowledge in real-life situations. Moulage is one of the techniques that helps in making simulation more realistic or high-fidelity. It uses special effects to emulate wounds for a better understanding of what the wound is like visually. Still, moulage is expensive, time-consuming, resource-intensive, and requires the training of staff, which is why we need to find low-cost substitutes for moulage materials. Method: When searching the database “PubMed” for the terms “Low-cost and Medical moulage”, we retrieved 222 studies, out of which when excluding results not related to low-cost, we obtained 62 studies, from which when removing studies that do not contain information regarding moulage, we found two papers, after referring to citations and cited articles of those papers, we ended up with six studies. Based on the selected articles and additional articles sourced from their reference list, a total of 11 studies were included in the review. Results: We understand that moulage is a technique that helps make simulations come alive, but the resources required to use it are at times, expensive, which is why we need to find methods to do low-cost moulage, and many studies address that it can be as simple as using homemade ingredients. Students from a previous study have talked about their opinions regarding the realistic component of moulage and whether if it is any different from other moulages. Most of the students agreed that the moulage ranked well in face and content validity. However, further innovations must be introduced in the field to be widely spread and lead to newer opportunities. Conclusion: Although the research done under moulage is limited, it is accepted that moulage is helpful for simulation-based studies and that low-cost moulage can help make medical studies a better experience for students studying it. Students have a favorable opinion on the realistic aspect of the low-cost moulage applied to them. Newer methods can be introduced to moulage, and it can be implemented in low-income countries.

Background: Simulations have historically aided training programs by providing a realistic and holistic replication of professional scenarios and procedures. Simulations have developed over the past 40 years to include varying fidelities and modalities of simulation. Learning in a simulation-centered environment has benefits, ranging from improved patient care to specific skills acquisition while catering to students’ numerous and varied learning approaches. Simulation is a multifaceted field that benefits all parties, the teachers, the learners, and the patients. The application of simulation to medical education and its amalgamation with other modes and substitutes allows for a more integrated learning and testing curriculum that advances the current trajectory of medical education. Such developments, however, are limited to resource rich areas, leaving behind low-middle income countries to use traditional, less evolved methodologies and practices. This review aimed to explore different aspects of simulation and focus specifically on low-cost task trainers and their accessibility. Method: The purpose of the study was to assess the accessibility of low-cost task trainers in terms of cost-effectiveness, distribution, validation, and frequency within specific specialties. To do so, 84 PubMed publications have been screened, and 39 filtered research studies have collected the necessary data. After analyzing the papers, we classified the following information – process, specialization, validation (y/n), costs, development location, and year of publication. Results: After carefully analyzing the accumulated data from the selected 39 publications, we found that most studies (i.e., 6 out of 39) were published in 2020. Emergency Medicine was the most common specialty for which low-cost trainers were developed (9 out of 39 procedural simulators); Otolaryngology followed this with 8 out of 39 trainers and general surgery with 7/39 of the task-trainers. The price ranges fluctuated and fell within the price bracket of USD 0 to USD 400 collectively. Our review also uncovered the concentration of development of such innovations solely in high income countries (HICs). Conclusion: Simulation is an invaluable tool applicable to a diverse range of phases of medical education. Future conjunction of simulation with low-cost substitutes along with increased encouragement and enthusiasm towards developing cost effective simulation-based learning environments (SBLEs) with the reserves and requirements of these areas in mind may prove to be a reliable option for low and middle resource settings

The term low-resourced has been tossed around in the field of natural language processing to a degree that almost any language that is not English can be called "low-resourced"; sometimes even just for the sake of making a mundane or mediocre paper appear more interesting and insightful. In a field where English is a synonym for language and low-resourced is a synonym for anything not English, calling endangered languages low-resourced is a bit of an overstatement. In this paper, I inspect the relation of the endangered with the low-resourced from my own experiences.

Abstract: Imaging devices of less than 300,000 pixels are mostly used for sewage conduit exploration due to the petty nature of the survey industry in Korea. P articular ly , devices of less than 100,000 pixels are still widely used, and the environment for image processing is very bitter . Since the sewage conduit image s covered in this study ha ve a very low resolution (240 × 320 = 76,800 pixels), it is very difficult to detect cracks. Because most of the resolution of the sewe r conduit images are very low in Korea, this problem of low resolution was selected as the subject of study. Cracks were detected through a total of six steps of improving the crack in Step 2, finding the optimal threshold value in Step 3, and applying an algorithm to detect cracks in Step 5. Cracks were effectively detected by the optimal parameters in Steps 2 and 3 and the user algorithm in Step 5. Desp ite the very low resolution, the cracked image s showed 96.4% accuracy of detection, and the non cracked image s showed 94.5% accuracy . Moreover, the analysis was excellent in quality , also . It is believed that the findings of this study can be effectively u sed for crack detection with low resolution images.

Biosensors are essential tools which have been traditionally used to monitor environmental pollution, detect the presence of toxic elements and biohazardous bacteria or virus in organic matter and biomolecules for clinical diagnostics. In the last couple of decades, the scientific community has witnessed their widespread application in the fields of military, health care, industrial process control, environmental monitoring, food-quality control, and microbiology. Biosensor technology has greatly evolved from the in vitro studies based on the biosensing ability of organic beings to the highly sophisticated world of nanofabrication enabled miniaturized biosensors. The incorporation of nanotechnology in the vast field of biosensing has led to the development of novel sensors and sensing mechanisms, as well as an increase in the sensitivity and performance of the existing biosensors. Additionally, the nanoscale dimension further assists the development of sensors for rapid and simple detection in vivo as well as the ability to probe single-biomolecules and obtain critical information for their detection and analysis. However, the major drawbacks of this include, but are not limited to potential toxicities associated with the unavoidable release of nanoparticles into the environment, miniaturization induced unreliability, lack of automation, and difficulty of integrating the nanostructured-based biosensors as well as unreliable transduction signals from these devices. Although the field of biosensors is vast, we intend to explore various nanotechnology enabled biosensors as part of this review article and provide a brief description of their fundamental working principles and potential applications.

Cuticular waxes are a mixture of hydrophobic very-long-chain fatty acids and their derivatives accumulated in the plant cuticle. Most studies define the role of cuticular wax largely based on reducing non-stomatal water loss. The present study investigated the role of cuticular wax in reducing both low-temperature and dehydration stress in plants using Arabidopsis thaliana mutants and transgenic genotypes altered in the formation of cuticular wax. cer3-6, a known Arabidopsis wax-deficient mutant (with distinct reduction in aldehydes, n-alkanes, secondary n-alcohols, and ketones compared to wild type (WT)), was most sensitive to water loss; while dewax, a known wax overproducer (greater alkanes and ketones compared to WT), was more resistant to dehydration compared to WT. Furthermore, cold-acclimated cer3-6 froze at warmer temperatures, while cold-acclimated dewax displayed freezing exotherms at colder temperatures compared to WT. GC-MS analysis identified a characteristic decrease in the accumulation of certain waxes (e.g. alkanes, alcohols) in Arabidopsis cuticles under cold acclimation, which was additionally reduced in cer3-6. Conversely, the dewax mutant showed a greater ability to accumulate waxes under cold acclimation. FTIR spectroscopy also supported observations in cuticular wax deposition under cold acclimation. Our data indicate cuticular alkane waxes along with alcohols and fatty acids can facilitate avoidance of both ice formation and leaf water loss under dehydration stress, and are promising genetic targets of interest.

Purpose: Novel coronavirus disease (COVID-19) is the current global concern. Radiotherapy (RT), commonly employed in cancer management, has been considered one of the potential treatments for COVID-19 pneumonia. Here, we present the final report of the pilot trial evaluating the efficacy and safety of low-dose whole-lung irradiation (LD-WLI) in patients with COVID-19 pneumonia. Methods and Materials: We enrolled patients with moderate COVID-19 pneumonia who were older than 60 years. Participants were treated with LD-WLI in a single fraction of 0.5 or 1.0Gy along with the national protocol of COVID-19. The primary endpoints were improvement of SpO₂, the number of hospital/ICU stay days, and the number of intubations after RT and the secondary endpoints were alterations of the c-reactive peptide, interleukin-6, ferritin, procalcitonin, and D-dimer. The response rate (RR) was defined as a rise in SpO₂ upon RT with rising or constant trend in the next two days, and clinical recovery (CR) included patients who were discharged from the hospital or acquired SpO₂ ≥93% on room air. Results: Between 21 May 2020 and 2 July 2020, ten patients were enrolled. The median age was 75 years, 80% were male, and 80% had comorbidities. The first five patients received a single 0.5Gy-WLI, and others received 1.0Gy. Patients were followed for 2-14 days (median 5.5 days). Following one day, nine patients experienced an improvement in SpO₂. Five patients were discharged (median 6^th day, range 2^nd-14^th day), and four patients died (median 7^th day, range 3^rd-10^th day). Overall, the RR and CR were 60.0% and 55.5%, respectively. The RR and CR rates of 0.5- and 1.0Gy group were 80% vs 40% and 75% vs 40%, respectively. No acute radiation-induced toxicity was recorded. Conclusions: LD-WLI with a single 0.5Gy fraction seems to be a more appropriate dose to warrant further evaluation in a large-scale, randomized trial.

We review a number of preconditioners for the advection-diffusion operator and for the Schur complement matrix which in turn constitute the building blocks for Constraint and Triangular Preconditioners to accelerate the iterative solution of the discretized and linearized Navier-Stokes equations. An intensive numerical testing is performed onto the driven cavity problem with low values of the viscosity coefficient. We devise an efficient multigrid preconditioner for the advection-diffusion matrix which, combined with the commuted BFBt Schur complement approximation, and inserted in a 2 x 2 block preconditioner, provides convergence of the GMRES method in a number of iteration independent of the meshsize for the lowest values of the viscosity parameter. The low-rank acceleration of such preconditioner is also investigated showing its great potential.

The concept of using special electrical circuit design realize a "cold resistors", that is, an active resistor circuitry with lowered effective noise temperature, was first introduced about 80 years ago. Later on, various kinds of artificial resistors were applied in different research areas, such as gravitational wave detection, photo-amplifiers and quartz oscillators. Their proofs of concepts were experimentally proved. Unfortunately, the complete theory was not found even though several attempts had been published, sometimes with errors. In this paper, we describe a correct and complete circuit theoretical model of a cold resistor system. The results are confirmed by computer simulations. A design tools for this circuit is also shown.

Number of confirmed cases of COVID-19 caused by SARS-CoV-2 exceeded 5 million as of May 21, 2020. Global average of the case fatality rate of COVID-19 is about 7% so far. There exist variations in case fatality rates among countries. Particularly, Singapore and Qatar have exceptionally low case fatality rates with 0.1% while France’s rate is almost 20%. Since no magic bullet treatment for COVID-19 exists, we investigated SARS-CoV-2 strains specific to Singapore in this study to identify a clade with low pathogenicity. Variant analysis revealed that a clade with variants ORF1ab L3606F, A4489V, S2015R, T2016K, and N P13L is common in Singapore. Based on our analysis of variants and historical case statistics, the clade is dominant in a recent surge. Therefore, we suggest that low case fatality rate of Singapore possibly is attributed to the clade. Although contribution of each variant to the low pathogenicity is not clear, L3606F alone does not accomplish such low pathogenicity from the comparison with case fatality data from Japan, where L3606F is dominant. Further investigation is necessary to conclude to validate this finding.

We report the negative effective mass metamaterials based on the electro-mechanical coupling exploiting plasma oscillations of a free electron gas. The negative mass appears as a result of vibration of a metallic particle with a frequency of ω which is close the frequency of the plasma oscillations of the electron gas m_2 relatively to the ionic lattice m_1. The plasma oscillations are represented with the elastic spring k_2=ω_p^2 m_2, where ω_p is the plasma frequency. Thus, the metallic particle vibrated with the external frequency ω is described by the effective mass m_eff=m_1+(m_2 ω_p^2)/(ω_p^2-ω^2 ) , which is negative when the frequency ω approaches ω_p from above. The idea is exemplified with two conducting metals, namely Au and Li.

In the last years, the development of low-cost GNSS sensors allowed monitoring in a continuous way movement related to natural processes like landslides with increasing accuracy and limited efforts. In this work, we present the first results of an experimental low-cost GNSS continuous monitoring applied to the unstable slope affecting the Madonna del Sasso Sanctuary (NW Italy). The courtyard of Sanctuary is built of two unstable blocks delimited by high cliff. Previous studies and non-continuous monitoring showed that blocks suffer a seasonal cycle of thermal expansion and long-term trend to downslope of few millimeters per year. The presence of continuous monitoring solution, could be an essential help to better understand the kinematics of unstable slope and to recognize the beginning of a possible paroxysm phase that could end with a failure of the unstable area. We tested the accuracy of the instruments and the first year of experimental measurements are presented. We also propose a methodological approach that considers the use of automatized procedures for the identification of anomalous trends and a risk communication strategy based on monitoring data.

A hydrothermal pretreatment of the microalga Nannochloropsis gaditana at mild temperatures has been studied in order to reduce N and O content in the biocrude obtained by hydrothermal liquefaction (HTL). The work is focused on the evaluation of temperature, reactor loading and time (factors) to maximize the yield of the pretreated biomass and the heteroatom contents transferred from the microalga biomass to the aqueous phase (responses). The study followed the factorial design and response surface methodology. An equation for every response has been obtained, which leads to the accurate calculation of the operating conditions required to obtain a given value of these responses. Temperature and time are critical factors with a negative effect on the pretreated biomass yield, but a positive one on the N and O recovery in the aqueous phase. The slurry concentration has to be low to increase heteroatom recovery and high to maximize the pretreated microalga yields

Over half of adult Americans now have diabetes or prediabetes and worse, this epidemic is now world-wide and shows no signs of slowing, with rates of both diabetes and diabetes-related health complications still rising. When advising patients with diabetes on food choices, many providers rely on nutrition guidelines provided by the American Diabetes Association (ADA), and these guidelines influence other recommendations across the globe. Given the alarming trends in diabetes, it is paramount to review the treatment guidelines to ensure they are based on rigorous and accepted scientific methods. Our review included the evidence cited by the ADA in support of its claims and recommendations for eating patterns to combat diabetes (see Description of Eating Patterns, Supplemental Appendix), as presented in the most current edition of the annual ADA’s Standards of Medical Care in Diabetes (2018 Standards). Our review also includes sources cited in the latest edition of the ADA’s Nutrition Therapy Recommendations for Adults with Diabetes (2014 Recommendations), which also informed the 2018 Standards. In October 2018 low carbohydrate was named as a recommended eating pattern by the ADA and European Association for the Study of Diabetes (EASD)⁵but only citations from the 2014 and early 2018 ADA documents were reviewed.

MEMThe PdNi film hydrogen sensors with Wheatstone bridge structure were designed and fabricated by the micro-electro-mechanical system (MEMS) technology. The integrated sensors consisted of four PdNi alloy film resistors. The interval two of them were shielded with silicon nitride film and used as reference resistance, while the others were used for hydrogen sensing. The PdNi alloy films and SiN films were deposited by magnetron sputtering. The morphology and microstructure of the PdNi films were characterized with X-ray diffraction (XRD). The output resistance signal was converted to millivolt output voltage signal for easy data acquisition. Hydrogen (H2) sensing properties of PdNi film hydrogen sensor with Wheatstone bridge structure was investigated under different temperatures (30℃, 50℃ and 70℃) and H2 concentrations (from 10 ppm to 0.4%). The hydrogen sensor demonstrated good response at different hydrogen concentrations and high repeatability in cycle testing under 0.4% H2 concentration. Under 10ppm hydrogen, the PdNi film hydrogen sensor had evident and collectable output voltage of 600 μV.

The beginning of industrialization human being has observed a variety of environmental troubles in the world. This industrialization has not only brought growth and affluence but ultimately troubled the ecosystem. One of the crashes is visible, in form of water contamination. Here the current study heavy metal contamination of water body has been discussed. Effluents from a great number of industries viz., tannery, textile, pigment & dyes, paint, wood processing, petroleum refining, electroplating, leather etc., have a major amount of heavy metals in their wastewater. The conventional technique of handling heavy metal pollution includes chemical oxidation, chemical precipitation, ion exchange, reverse osmosis, membrane separation, electrodialysis etc. These processes are expensive, energy intensive and frequently related with generation of poisonous by-product. Therefore, the adsorption has been examined as a cost-efficient technique of elimination of heavy metals from wastewater. In the current study different low-cost adsorbent has been a review as an abatement of heavy metal contamination from wastewater. These adsorbent comprise materials of natural origin like peat moss, zeolites, clay, and chitin are found to be an effective agent for removal of deadly heavy metals like Pb, Cd, Zn, Cu, Ni, Hg, Cr etc. Separately from these, a variety of agricultural wastes like rice husk, waste tea, neem bark, black gram; Turkish coffee, walnut shell etc. were also known as a powerful adsorbent for heavy metal removal. at the side of that low-cost industrial byproduct like fly ash, lignin, iron (III) hydroxide and red mud, coffee husks, Areca waste, tea factory waste, sugar beet pulp, battery industry waste, blast furnace sludge, waste slurry, sea nodule remains and grape stalk wastes have been discovered for their technical possibility to eliminate toxic heavy metals from impure water.

Computational Fluid Dynamics (CFD) is utilized to study entropy generation for the rarefied steady state laminar 2-D flow of air-Al2O3 nanofluid in square cavity equipped with two solid fins at the hot wall. Such flows are of great importance in industrial applications, such cooling of the electronic equipment’s and nuclear reactors. In the current study, effects of Knudsen number (Kn), Rayleigh number (Ra) and the nano solid particles volume fraction (ϕ) on the entropy generation are investigated. The values of parameters considered in this work are as follows: 0≤Kn≤0.1, 〖10〗^3≤Ra≤〖10〗^6,0≤ϕ≤0.2. Length of the fins (LF) is considered to be fixed and equals to 0.5 m, whereas the location of the fins with respect to the lower wall (HF) is set to 0.25 and 0.75 m. Simulations demonstrate that there is an inverse direct effect of Kn on the entropy generation. Moreover, it is found that when Ra is less than 104, the entropy generation, due to the flow, increases as ϕ increases. In addition, the entropy generation due to the flow will decrease at Ra greater than 104 as ϕ increases. Moreover, the entropy generation due to heat will increase as both the ϕ and Ra increase. In addition, a correlation model of the total entropy generation as a function of all of the investigated parameters in this study is proposed. Finally, an optimization technique is adapted to find out the conditions at which the total entropy generation is minimized

Recent advances in single-atom catalysis resulted in readily accessible materials whose application in most catalytic reactions mediated by conventional nanoparticle-based catalysts often results in higher activity and selectivity. Can we expect catalysis by atomically dispersed atoms to find practical applications? Which are the hurdles to be overcome prior to widespread uptake of atomically dispersed metals in industrial synthetic processes and in hydrogen fuel cells?

A The agri-food sector is in full renovation, continuously demanding new systems that allow farmers to facilitate their work. Efficient agricultural practices are essential for increasing farm profitability. Efficient agricultural practices can be increased by understanding and managing water neeeds. However, real-time monitoring of water needs is currently slow, and irrigation decisions are based on previous data or physical evidence. Furthermore, the prices of automatic systems for collecting data from several sources (soil and climate) are expensive and the autonomy is very low. Emerging Internet of Things (IoT) technologies such as wireless sensor networks can be used to collect vast amounts of data recorded via apps. By means of an LPWAN communication the farmer can know in real time the state of his crops thanks to a large number of sensors connected wirelessly and distributed across his farm. This paper presents a low consumption solution based on LoRaWAN technology. The wireless sensor node, called BoX, exhibits very low power since it has been optimized both in terms of hardware and software. The result is a higher degree of autonomy than commercial motes. That will allow the farmer to have all the information necessary to achieve an efficient management of his crops with full autonomy.

An ultra-low anti-reflection optical coating on both surfaces of a plastic cover slip was studied for use in confocal image measurement. The optical reflectance at a wavelength of 632.8 nm was less than 0.1% when the coated sample was placed in a liquid having a refractive index of 1.34 close to the aqueous solution of the biomaterial. The high- and low-index coating films, Substance-2 (PrTiO3) and silicon dioxide (SiO2), were measured by an ellipsometer to determine their optical refraction indices and extinction coefficients. Theoretically, when the two layer thicknesses are designed using the optical admittance diagram of the cover slip to approach the equivalent index of 1.34, a reflectance of 1.6×10-5% in the liquid could be obtained. Experimentally, the reflectance of the sample deposited on the two faces of the cover slip was 4.223±0.145% as measured in the air; and 0.050±0.002% as measured by a He-Ne laser in the liquid.

The atherosclerosis, a chronic and inflammatory disease that occurs when there are high levels of low-density lipoprotein (LDL) on plasma. This important risk factor for development of cardiovascular disease (CVD) is the main cause of death worldwide. MicroRNAs have recently emerged as potential biomarkers and therapeutic target for lipid metabolism disorders. In this review, we will provide profile of surrounding miRNAs that have demonstrated being regulators of PCSK9, LDLR and APOB100 genes. Recent work has identified the mir-148, mir-128, mir-27a/b, mir-185, mir-301, mir-130 as important regulators of this pathway because they decrease supply of LDL receptors through interaction with PCSK9. Inhibition of LDLR expression cause elevation of plasma LDL levels which induces atherosclerosis. While mir-30c, mir-122, mir-34 decrease MTTP, which promotes degradation of APOB100 preventing assembly and secretion of VLDL. We conclude that, when overexpressed, mir-148a, mir128 and mir-27a/b, mir-122 and mir-34 are related to decrease in LDLR, facilitating occurrence of atherosclerosis. While mir-30 has been linked to decreased atherosclerosis. Detection of miRNAs profile could be used in the future as a biomarker for disturbs linked to c-LDL uptake and in future anti-miRNAs therapies may be used in the treatment of atherosclerosis.

This paper seeks to model the crack propagation in of AAs (aluminum-alloys) 2524-T3 and 7050-T7452 subjected to fatigue loading at low temperature. Fatigue crack growth tests were performed on AAs 2524-T3 and 7050-T7452 subjected to constant-amplitude and actual random-spectra loading histories at room temperature of about 25 °C and at cryogenic temperature of -70 °C, respectively, to determine their crack growth properties and residual lives. The interaction mechanisms between cryogenic temperature and the fatigue load were deduced on the basis of the results of fractographic analysis. Temperature-dependent residual lives under actual random-spectrum load history were modeled based on a modified accumulation damage rule by accounting for the load interaction. Good correlation was achieved between the predictions and actual experiments, demonstrating the practical and effective use of the proposed method.

Free and open source hardware (FOSH) development has been shown to increase innovation and reduce economic costs. This article reviews the opportunity to use FOSH like a sanction to undercut imports and exports from a target criminal country. A formal methodology is presented for selecting strategic national investments in FOSH development to improve both national security and global safety. In this methodology, first the target country that is threatening national security or safety is identified. Next, the top imports from the target country as well as potentially other importing countries (allies) are quantified. Hardware is identified that could undercut imports/exports from the target country. Finally, methods to support the FOSH development are enumerated to support production in a commons-based peer production strategy. To demonstrate how this theoretical method works in practice it is applied as a case study to the current criminal military aggressor nation, who is also a fossil fuel exporter. The results show there are numerous existing FOSH and opportunities to develop new FOSH for energy conservation and renewable energy to reduce fossil fuel energy demand. Widespread deployment would reduce the concomitant pollution, human health impacts, and environmental desecration as well as cut financing of military operations.

The Smart Energy Research Lab (SERL) Observatory dataset described here comprises half-hourly and daily electricity and gas data, SERL survey data, Energy Performance Certificate (EPC) input data and 24 local hourly climate reanalysis variables from the European Centre for Medium-Range Weather Forecasts (ECMWF) for over 13,000 households in Great Britain (GB). Participants were recruited in September 2019, September 2020 and January 2021 and their smart meter data are collected from up to one year prior to sign up. Data collection will continue until at least August 2022, and longer if funding allows. Survey data relating to the dwelling, appliances, household demographics and attitudes was collected at sign up. Data are linked at the household level and UK-based academic researchers can apply for access within a secure virtual environment for research projects in the public interest. This is a data descriptor paper describing how the data was collected, the variables available and the representativeness of the sample compared to national estimates. It is intended as a guide for researchers working with or considering using the SERL Observatory dataset, or simply looking to learn more about it.

The planning and decision-making for a distributed energy supply concept in complex actor structures like in districts calls for the approach to be highly structured. Here, a strategy with strong use of energetic simulations is developed, the core elements are presented and research gaps are identified. The exemplary implementation is shown using the case study of a new district on the former Oldenburg airbase in northwestern Germany. The process is divided into four consecutive phases, which are carried out with different stakeholder participation and use of different simulation tools. Based on a common objective, a superstructure of the applicable technologies is developed. Detailed planning is then carried out with the help of a multi-objective optimal sizing algorithm and Monte Carlo based risk assessment. The process ends with the operating phase, which is to guarantee a further optimal and dynamic mode of operation. The main objective of this publication is present the core elements of the planning processes and decision-making framework based on the case study and to find and identify research gaps that will have to be addressed in the future.

This paper develops a novel energy universal service bus system (EUSBS) based on emerging energy Internet (E-net) technologies. This EUSBS is a unified identification and plug-and-play interface platform to which high penetration distributed energy and equipment (DEE), including photovoltaic (PV), fans, electric vehicle charging stations (EVCSs), energy storage equipment (ESE), and commercial and residential users (CRUs), can access in a coordinated control and optimized utilization mode. First, the functions design, overall framework and topology architecture design of the EUSBS are expounded, among which the EUSBS is mainly composed of a hardware system and a software platform. Moreover, several future application scenarios are presented. Then, the hardware part of EUSBS is designed and developed, including the framework design of this hardware subsystem, and development of the hardware equipment for PV access, fans access, EVCS access, ESE access, and CRU access. The hardware subsystem consists of smart socket, and household/floor/building concentrators. Based on this, the prototypes development of EUSBS hardware equipment is completely demonstrated. Third, the software part of the EUSBS is developed as a cloud service platform for electricity use data analysis of DEE. This software subsystem contains the power quality & energy efficiency analysis module, optimization control module, information and service module, and data monitoring and electricity behavior analysis module. Based on this design, the software interfaces are developed. Finally, an application study on energy management and optimization of a smart commercial building is conducted to evaluate the functions and practicality of this EUSBS. The EUSBS developed in this paper is able to overcome difficulties in big data collection and utilization on sides of distribution network and electricity utilization, and eventually implement a deep information-energy fusion and a friendly supply-demand interaction between the grid and users. This contribution presents a detailed and systematic development scheme of the EUSBS, and moreover, the laboratory prototypes of the hardware and software subsystems have been developed based on E-net technologies. This paper can provide some thoughts and suggestions for the research of active distribution network and comprehensive energy management and optimization in power systems, as well as references and guidance for researchers to carry out research regarding energy management, optimization and coordinated control of the smart buildings.

This randomized control trial aims to test the hypothesis that twice-daily nurse-administered saline enema(SE) is comparable to physician-administrated SE in very low birth weight infants (VLBW) with meconium obstruction of prematurity (MOP). MOP is defined as no bowel opening for 48 h, and treatment failure is defined as the need for additional intervention and safety. Twice-daily SE was administered by accredited nurses, surgeons/neonatologists using standardized protocols. The outcomes were comparability of nurse to physician-administered SE in terms of frequency of administration, catheter insertion length and volume of enema, daily maximum meconium output, and treatment failure, defined as the need for additional intervention. Safety outcomes were evaluated. Twenty-eight infants were managed with SE. 389 SE were administered, 96 and 293 in 750-999g and 1000-1500g birth weight groups, respectively. Nurses administered 72.9% and 81.5% of SE in 750-999g and 1000-1500g birth weight groups, respectively. Physicians performed the rest of the SE. Daily meconium output was comparable in nurse and physician-administered SE in both groups. There were no treatment failures or adverse events in both SE group. SE administered by nurses was found to be comparable in terms of safety, efficacy, and frequency of administration to that of physician-administered SE.

The use of energy resources is essential to the survival and development of human civilization. However, inefficient energy use not only has an impact on the economy, but it also has a significant impact on climate change. Studying and analyzing the factors that increase energy consumption is crucial for improving energy management. The aim of this study is to analyze the factors influencing energy savings in a building taken as a study model under two different climatic conditions. Measurements of the building's energy performance were carried out using the EnergyPlus calculation engine, which enabled us to analyze the strengths of building parameters such as the number of lights, the equipment used, occupancy, temperature and the relationships between the factors influenced. EnergyPlus is an important software tool in the field of building energy efficiency, enabling the precise simulation of building energy consumption. Simulation scenarios based on actual consumption data carried out by researchers have made it possible to develop energy management strategies in buildings in order to optimize energy efficiency, and in particular to promote the thermal performance of these buildings. In the present work, EnergyPlus building energy simulation software is used to simulate the energy consumption of the building of the Faculty of Electrical Engineering at the "Gheorghe Asachi" Technical University in Iasi, in order to determine the factors influencing building energy consumption. It has been shown that occupancy and heating and cooling systems are the key factors influencing energy consumption in buildings. The advantage of this study is that it can be used to model the most influential factors in predicting future energy consumption in buildings.

In response to escalating global concerns regarding climate change, nations worldwide have been undertaking structural adjustments in their energy sectors to promote diversification and decarbonization. This study conducts a comparative analysis of the policies and measures adopted by major economies, including the United States, the United Kingdom, Japan, Germany, and France, focusing on climate change, energy structural adjustments, and carbon emission reduction. By analyzing recent carbon emission and highlighting achievements in renewable energy promotion, green industry development, industrial restructuring, and energy production decarbonization, this study aims to provide valuable insights and formulate strategies for constructing an innovative energy system that ensures economic and social development while facilitating rapid growth and wide applications of low-carbon energy sources.

The Internet of Things (IoT) is experiencing exponential growth, revolutionizing various industries with its ability to connect devices and enable advanced applications. In the realm of energy production, IoT offers significant potential for optimizing processes and improving efficiency. This study presents a comprehensive monitoring and energy management strategy for the University of Cuenca's microgrid photovoltaic (PV) system, utilizing IoT and ThingSpeak as key technologies. The proposed strategy leverages intelligent environments and utilizes ThingSpeak as a robust platform for data presentation and analysis. By integrating IoT devices and sensors, real-time monitoring of PV system parameters such as solar radiation and temperature is achieved. The collected data is then analyzed using advanced algorithms and visualized through ThingSpeak, enabling effective energy management and decision-making. The developed monitoring system was rigorously tested in a laboratory microgrid setting, where the PV system is interconnected with other generation and storage systems, as well as the electrical grid. Through the seamless integration of these components, the monitoring system provides enhanced visibility and control over the microgrid's energy production. The results demonstrate the successful implementation of the monitoring system, showcasing its ability to improve the supervision, automation, and analysis of daily energy production. By leveraging IoT technologies and ThingSpeak, stakeholders can access real-time data, analyze performance trends, and optimize energy resources.

$\phi$CDM models provide an alternative to the standard $\Lambda$CDM paradigm, while being physically better motivated. These models lead to a time-dependent speed of sound for dark energy that is difficult to replicate by $w$CDM parametrizations. We review the most up-to-date status of observational evidence for the $\phi$CDM models in this paper. We start with an overview of the motivation behind these classes of models, the basic mathematical formalism, and the different classes of models. We then present a compilation of recent results of applying different observational probes to constraining $\phi$CDM model parameters. Over the last twenty years, the precision of observational data has increased immensely, leading to ever tighter constraints. A combination of the recent measurements favors the spatially flat $\Lambda$CDM model, but a large class of $\phi$CDM models is still not ruled out.

Τhe building automation control is a crucial factor for improving buildings energy efficiency and management, as well as improving the electricity grid's reliability indices. This paper presents the methodology, describes the necessary technology requirements and presents the decentralized building automation novel algorithm for Efficient demand side management in a building. All these are applied in an experimental university microgrid and the results are presented in terms of energy saving in kWh, money in € and working hours.

Energy keeps the global economy alive, whereas it is extensively exposed to various climate change impacts. In this context, severe business competition (e.g., the building sector) and the unwise use of natural resources and ecosystem services (e.g., fossil fuel energy sources) seem to sharpen the relevant effects of climate change. Indicatively, contemporary issues at the interface of building energy performance and environmental quality levels include consequences from global warming, increasing releases of carbon dioxide to peak electrical loads, power grid and building planning, and energy demand and supply issues. In light of such concerns, the present review paper attempts to disclose the multifaceted and multidisciplinary character of building energy use at the interface of the economy, the environment, and society against climate change. This review highlights energy efficiency concepts, production, distribution, consumption patterns, and relevant technological improvements. Interestingly, the reviewed contributions in relevant literature reveal the need and necessity to alter the energy mix used and relevant energy use issues. These include developments in climate-proof and effective systems regarding climate change impacts and shocks. Practical implications indicate that the sustainable development goals for clean energy and climate action should be followed if we wish to bring a sustainable future closer and faster to our reality.

This study investigates the relationship between clean and dirty energy markets, specifically focusing on clean energy stock indexes and their potential as hedging assets and safe havens during periods of global economic uncertainty. The research analyzes five clean energy indexes and five dirty energy indexes from May 2018 to May 2023, considering events like the global pandemic and the Russian invasion of Ukraine. The main objective is to examine the causal relationship among different stock indexes pertaining to dirty and clean energy by using the Granger causality test (VAR Granger Causality/Block Exogeneity Wald Test) to determine whether clean energy indexes can predict future prices of dirty energy indexes. However, the findings reveal that clean and dirty energy indexes do not exhibit hedging characteristics or serve as safe havens during times of economic uncertainty, rejecting the research question. These results have important implications for investment strategies, as assets lacking safe haven characteristics may not preserve portfolio efficiency in uncertain times. The study's insights provide valuable guidance for investors, poli-cymakers, and participants in energy financial markets. It highlights the need to adapt investment approaches and seek alternative options to navigate uncertain economic conditions effectively.

The spiral tube heat exchange is widely used in large-scale liquefaction process. However, the research on the friction pressure drop of the two-phase flow in the spiral tube is limited, especially for the offshore sloshing condition. In this paper, an experimental system is designed and built, and the effects of sloshing form (roll, pitch, heave), sloshing period (5-15s), mass flux (200-800 kg/(m2·s)), vapor quality (0.3-0.9) and operating pressure (2-4 MPa) on friction pressure drop of methane/ethane (C1/C2) mixture in spiral tube are studied. The result shows that the growth rate of time-averaged friction pressure drop during condensation under sloshing condition is less than 0, which indicates that sloshing will lead to drag reduction. And under the three sloshing parameters, the growth rate of time-averaged friction pressure drop of C1/C2 is reduced by-5.99%%, 5.97% and -6.70% respectively.

In this study, a multiobjective, multiperiod, global optimization for design, sizing and dispatch of an islanded, hybrid microgrid was performed using a model built in MATLAB. The system was simulated over one year for sizing and over one day for dispatch, both using hourly time steps. The model minimized lifecycle levelized costs, emissions, lost load and dumped power while maximizing penetration of clean, renewable sources in the microgrid. This found optimal capacities of the renewable, energy storage and backup generation components which provide the best combination of affordability, sustainability, reliability and efficiency. After experimenting with several global solvers, it was determined that particle swarm optimization is most well-suited to solving the sizing optimization problem. The PV-wind microgrid using Li-ion batteries along with diesel engines was found to perform best among all the combinations considered. It was found that in spite of including additional objectives, monetary costs are the primary driver while allocating generation capacity between different renewable sources like wind versus solar PV. Furthermore, the sizing of PV, wind and battery storage depends strongly on the rating of the standby distributed generator, mainly due to reliability consideration. Generating Pareto-optimal sets revealed interesting relationships between different input variables (i.e. PV, wind and battery capacities) as well as trade-offs that arise while pursuing different objectives. Pursuing cost-minimization alone may lead to sub-optimal outcomes in terms of environmental impact, reliability and excess energy production. A sensitivity analysis was also conducted to understand the effects of various parameters like fuel price and energy storage costs on the optimal system's design and operation. Such accurate sizing programs help reduce the extent of oversizing of sub-systems during the design and planning stage, which is usually needed to achieve high reliability with distributed and decentralized energy systems like off-grid microgrids. This reduces the upfront capital investment needed to build the system, making clean electricity access affordable in the short term. The economic-environmental dispatch produced day-ahead scheduling strategies to meet the above mentioned objectives. The system was found to be relatively robust to short-term uncertainties and disturbances in renewable generation and load, although this does cause sub-optimal performance due to increased reliance on fossil fuels. It was found that dispatching of the batteries and backup generators is most critical in minimizing impacts of such events. However, the response to longer-term disturbances still remains to be assessed. The study also includes a comprehensive literature review of tools available for microgrid design as well as different optimization algorithms that have been used to solve microgrid sizing, dispatch and scheduling problems. Additionally, an overview is provided of various control strategies that can be used to improve robustness and resiliency of microgrids.

Renewable Energy Communities (RECs) are emerging as an effective concept and model to empower the active participation of citizens on the energy transition, not only as energy consumers, but also as promoters of environmentally friendly energy generation solutions. This paper aims to contribute to the management and optimization of individual and community Distributed Energy Resources (DER). The solution follows a price and source-based REC management program, in which consumers day-ahead flexible loads (Flex Offers) are shifted according to electricity generation availability, prices and personal preferences, to balance the grid and incentivize user participation. The heuristic approach used in the proposed algorithms allows the optimization of energy resources in a distributed edge and fog approach with a low computational overhead. The simulations performed using real world energy consumption and flexibility data of a REC with 50 dwellings show an average cost reduction of 10.6% and an average increase of 11.4% in individual self-consumption. Additionally, the case-study demonstrates promising results regarding grid load balancing and the introduction of intra-community energy trading.

Explaining the emergence of behavior and understanding on the basis of neuronal mechanisms is still elusive. One renowned proposal is the Free Energy Principle (FEP), which uses an information-theoretic framework derived from thermodynamic considerations to describe how behavior and understanding would emerge. FEP starts from a whole organism approach, based on mental states and phenomena, mapping them into the neuronal substrate. An alternative approach, the Energy Homeostasis Principle (EHP), initiates a similar explanatory effort, but starting from single neuron phenomena and building up to the whole organism’s behavior and understanding. In this work, we develop the EHP as an alternative but complementary vision to FEP and try to explain how behavior and understanding would emerge from the local requirements of the neurons. Based on EHP and a strict naturalist approach that sees living beings as physical and deterministic systems, we explain scenarios where learning would emerge without the need for volition or goals. Given these starting points, we state several considerations of how we see the nervous system, particularly the role of function, purpose, and the conception of goal-oriented behaviors. We problematize these conceptions, giving an alternative teleology-free framework in which behavior and, ultimately, understanding would still emerge. We reinterpret neural processing explaining basic learning situations up to simple anticipatory behavior. Finally, we end the work with an evolutionary perspective of how this non-goal-oriented behavior appears. We acknowledge that in the current form of our proposal, we are still far from explaining the emergence of understanding. Still, we set the ground for an alternative neuron-based framework to ultimately explain understanding.

During the last two decades, energy poverty has captured a growing attention of researchers and policymakers due to its strong association with economic poverty and poor economic performance. This study uses a broad set of macro level indicators and makes the first attempt to measure energy poverty and its impact on economic growth of Pakistan over the period 1990 to 2017. In particular, our energy poverty indicator considers four main dimensions of energy poverty, namely, energy services, clean energy, energy governance and energy affordability. Our main results show that though the overall energy poverty has reduced in Pakistan during the selected sample period, the country shows an increasing dependence on polluted energy supply in order to meet its growing demand of energy. In second stage of the investigation, we test the neoclassical growth theory where we incorporate energy poverty along with human capital as source of economic growth. Our cointegration results reveal a strong relationship between energy poverty and economic growth that is also dynamically stable in short run. These strong negative linkages between energy poverty with economic growth for the sample economy complement the previous literature on the subject.

All over the world energy is used for different purposes and hence its continuous high demand which has brought about an increase in crisis and prices of energy. Ghana has faced a lot of supply and high electricity consumption challenges over a period of time. The Energy Commission of Ghana has developed regulations and guidelines to help reduce high consumption challenges among users, these included the replacement of incandescent bulbs with fluorescent bulbs, ban of importation of low energy efficient appliances. In spite of the effort to reduce electricity wastage, there is still a high increase in electricity consumption. The research investigated what contributed to electricity consumption in Kwame Nkrumah University of Science and Technology with the lecture halls as the main focus, the research also analyzed the current occupant behavior characterized by the electrical energy consumption practices. And investigated how the contemporary theories for reducing energy consumption was used in the lecture halls. A questionnaire survey was conducted to investigate occupants on their energy use practices in lecture halls that causes wastages, observation was made to establish relevant data on the use of contemporary theories for energy reduction in lecture halls. In a total of 110 occupants that responded to the questionnaire, 79 occupants almost always turn off electrical fitting and fixtures when not in use. From the responses, a majority of the occupants claimed to comply to best practices of energy use. The research concluded that some contemporary theories to reduce energy consumptions was not used and considered in the lecture halls.

This study aimed to focus on how to design a low-cost greenhouse for the cultivation of crops, to propose the cost-effectiveness analysis of small agribusiness, and to promote sustainable agricultural production during and after the COVID-19 crisis for helping grassroots and anyone who lost their job. This article is qualitative engineering research, studying of literature reviews of greenhouse farming concept and Micro, Small and Medium Enterprises, then, designing low-cost greenhouse model which was preliminarily adapted for hot climate countries. Three plants that were selected as representative plants of this model include sunflower, water spinach, and wheat. The greenhouse model, measuring 5 x 7 x 4 m (W x L x H), was designed for this mission. The total cost of one building is approximately 97,994 THB. For the worthiness of the investment, farmers should build at least three greenhouse buildings, which will return total income to farmers approximately 34,666.09 THB per month. The suggestion includes further knowledge and financial supports from the government sectors among farmers, then, boost them up using high-level technology and also planting high-price agribusiness production to promote the local economy to be strong and sustainable.

Background: The frequency of visits to restaurants has been suggested to contribute to the pandemic of obesity. However, few studies have examined how individual use of these restaurants is related to BMI using new technology of reminding to avoid memory error. Aim: To investigate the association between the usage of different types of food outlets and BMI among adults in Scotland. Method: The study was cross-sectional. Participants (n = 681) completed an online survey for seven consecutive days where all food purchased at food outlets was reported each day. We explored the relationship between BMI and usage of these restaurants using auto-reminder text system. Results: Body Mass Index (BMI) of both males and females was not related to frequency of use of Full-Service Restaurants (FSRs), Fast Food Restaurants (FFRs), delivery or takeaways, when assessed individually, or combined (TFO= Total Food Outlet). Conclusion: These data do not support the widespread belief that consumption of food out of the home at fast-food and full-service restaurants, combined with that derived from deliveries and takeaways, is a major driver of obesity in UK.

Great Britain’s stocks of coal, natural gas, and petroleum have seen major changes to the levels of stored energy over the years 2005 to 2019, a reduction of 200 TWh (35%) from 570 TWh to 370 TWh. The transformation of its electrical system over this timeframe saw a reduction in coal generation, leading to a corresponding reduction of the levels of stockpiled coal of 85 TWh (68%), partially offset by an increase in the stocks of biomass for electrical generation. The reduction in natural gas storage of 24 TWh (44%) was primarily due to the closure of Britain’s only long-term seasonal natural gas storage facility in January 2018. This was partially offset by the construction of medium-term natural gas storage facilities and the use of LNG storage in the years preceding its closure. For stocks of crude oil and oil products the reduction was 35 TWh (21%), linked to the overall reduction in demand.

Natural gas combined cycle power plants (CCPPs) are widely used to meet peak loads in electric energy production. Continuous monitoring of the output electrical power of CCPPs is a requirement for power performance. In this study, the role of ambient temperature change having the greatest effect on electric production is investigated for a natural gas CCPP. The plant has generated electricity for fourteen years and setup at 240 MW in Aliağa, İzmir, Turkey. Depending on the seasonal temperature changes, the study data were obtained from each gas turbine (GT), steam turbine (ST) and combined cycle blocks (CCBs) in the ambient temperature range of 8-23°C. It has been found that decreases of the electric energy in the GTs because of the temperature increase and indirectly diminishes of the electricity production in the STs. As a result, the efficiency of each GT, ST and CCB reduced, although the quantity of fuel consumed by the controllers in the plant was decreased. As a result of this data, it has been recommended and applied that additional precautions have been taken for the power plant to bring the air entering the combustion chamber to ideal conditions and necessary air cooling systems have been installed.

In a vacuum tube, two identical and parallel Ag-O-Cs surfaces, A and B, with a work function of 0.8eV, ceaselessly emit thermal electrons at room temperature. The thermal electrons are controlled by a static uniform magnetic field (a magnetic demon), and the number of electrons migrate from A to B exceeds the one from B to A, (or vice versa). The net migration from A to B quickly results in a charge distribution: A charged positively and B negatively. A potential difference between A and B emerges, and the tube outputs ceaselessly an electric current and a power to a resistance (a load) and cools itself slightly. The ambient air is a single heat reservoir in the experiment, and all the heat extracted by the tube from the air is converted into electric energy without producing other effect. We believe the experiment is in contradiction to the Kelvin statement of the second law.

The process of modelling energy systems is accompanied by challenges inherently connected with mathematical modelling. However, due to modern realities in the 21st century, existing challenges are gaining in magnitude and are supplemented with new ones. Modellers are confronted with a rising complexity of energy systems and high uncertainties on different levels. In addition, interdisciplinary modelling is necessary for getting insight in mechanisms of an integrated world. At the same time models need to meet scientific standards as public acceptance becomes increasingly important. In this intricate environment model application as well as result communication and interpretation is also getting more difficult. In this paper we present the open energy modelling framework (oemof) as a novel approach for energy system modelling and derive its contribution to existing challenges. Therefore, based on literature review, we outline challenges for energy system modelling as well as existing and emerging approaches. Based on a description of the philosophy and elementary structural elements of oemof, a qualitative analysis of the framework with regard to the challenges is undertaken. Inherent features of oemof such as the open source, open data, non-proprietary and collaborative modelling approach are preconditions to meet modern realities of energy modelling. Additionally, a generic basis with an object-oriented implementation allows to tackle challenges related to complexity of highly integrated future energy systems and sets the foundation to address uncertainty in the future. Experiences from the collaborative modelling approach can enrich interdisciplinary modelling activities. Our analysis concludes that there are remaining challenges that can neither be tackled by a model nor a modelling framework. Among these are problems connected to result communication and interpretation.

Integrating a grid-connected battery into a Renewable Energy Community boosts Collective-Self-Consumption of photovoltaic produced energy and allow to perform Energy Arbitrage in the day-ahead and intraday electricity market. However, is it a cost-effective investment? The proposed analysis relay on Net Present Value assessment. Ageing affects are integrated and sensitivity analyses are conducted: considering community customers number, electricity mar-ket prices, battery cost, size and the decision to engage in energy arbitrage. Each scenario under-goes a 20-year hourly simulation using an ageing aware rolling-horizon 24-hours-looking-ahead scheduling, optimized with Mixed-integer linear Programming. Forecast errors, provid-ing of ancillary services, real time control and grid constrains are not taken into account. Simulations conducted on the Italian market indicates that a battery dedicated solely to collec-tive self-consumption is not economically appealing. However, integrating Energy Arbitrage, despite impact on battery lifespan, halves the payback period and enhances the attractiveness of larger battery investments. The Net Present Value is contingent upon battery size, customer number and market prices. However, if battery cost does not exceed 200 €/kWh the investment become cost-effective across all scenarios.

The transition to sustainable energy systems in the Middle East and North Africa (MENA) region addresses critical challenges of environmental protection, energy security, and socio-economic resilience. Using neo-institutional theory, this paper examines the intricate relationship between formal and informal institutions and their significant impact on the region’s energy transition. Despite the MENA region’s abundant renewable energy resources, numerous institutional barriers, such as governance inefficiencies, regulatory inconsistencies, and entrenched socio-cultural norms, significantly hinder this transition. Through a review of existing literature, this study presents a comprehensive analytical framework designed to overcome these barriers, with a focus on the Just and Sustainable Energy Transition model. This strategic model emphasizes equity, sustainability, and inclusive governance as pillars for reform. The study offers detailed recommendations for institutional change and underscores the importance of collaborative efforts among governments, industry stakeholders, and international partners to unlock the MENA region’s renewable energy potential, advance global sustainability goals, and ensure a more secure and resilient energy future.

Urban wind energy has emerged as an attractive source of distributed generation in cities to achieve sustainable development goals. The advance in technologies for the use of urban wind energy has turned this source into an attractive alternative for the decarbonization of cities and the energy transition. The objectives of this work are (1) to identify the potential of wind energy through numerical weather prediction (NWP) data tools and (2) to identify the roles and responsibilities of the stakeholders involved in the decision-making process. A methodology was developed in two phases and applied to a case study in the Dominican Republic. The first phase consisted of estimating the wind energy potential for the 32 provinces at a height of 10 m using open-access geographic reference systems tools provided by NASA. In the second phase, 28 stakeholders were identified through snowball sampling. The Responsible, Accountable, Consult, and Informed (RACI) matrix tool was applied to identify the roles of the 28 institutions addressed at the country level as relevant in the decision-making process for the energy sector. The annual average wind speed and energy potential for each province were determined. It was found 24 provinces have poor potential, below <4.5 m/s. In the northwest and east is where there is the greatest potential, between 4.83 - 6.63 m/s. The population density was established and was observed that the provinces with greater potential are less densely populated. Through 59 interviews 28 institutions were identified and evaluated due to their relevance in decision-making for the implementation of energy projects. The MEM has strongly categorized as “A”, electricity distribution companies as “R”, energy associations and universities as “C”, and educational and justice institutions as “I”.

Energy poverty is a severe electrification challenge in Nigeria that has affected the country's economic development. The gap between electricity demand and supply continues to increase, and a large percentage of the populace affected are rural dwellers. With the prevailing electricity inaccessibility in rural, renewable energy sources (RES) present viable option for addressing rural electrification challenge. However, RES like solar have intermittency challenges since they are weather dependent. Thus, a hybrid microgrid system (HMS) comprising solar, hydropower and battery storage was sized as a feasible solution for electrifying rural areas in Nigeria. For the HMS sizing, a site was selected, whose residential load demand was estimated. The renewable energy generation potential for the selected resources at the site as well as grid reliability were assessed. Hybrid Optimisation Model for Multiple Energy Resources (HOMER) was used to size the HMS. An economic analysis was performed to determine the levelised cost of energy (LCOE) and net present cost (NPC). For the sized HMS, two scenarios were considered: off-grid and grid-connected HMS configurations. The results showed that the LCOE of the off-grid and grid-connected configurations are $0.101/kWh and $0.046/kWh, respectively. The NPC of the off-grid and grid-connected configurations are $227,307 and $145,282, respectively.

This research paper presents a comprehensive study on the optimal planning and design of hybrid renewable energy systems for microgrid (MG) applications at Oakland University. The HOMER Pro platform analyzes the technical economic and environmental aspects of integrating renewable energy technologies. The research also focuses on the importance of addressing unmet load in the MG system design to ensure the university's electricity demand is always met. By optimizing the integration of various renewable energy technologies, such as solar photovoltaic (PV), energy storage system (ESS), combined heat and power (CHP), and wind turbine energy (WT), the study aims to fulfill the energy requirements while reducing reliance on traditional grid sources and achieving significant reductions in greenhouse gas emissions. The proposed MG configurations are designed to be scalable and flexible, accommodating future expansions, load demands changes, and technological advancements without costly modifications or disruptions. By conducting a comprehensive analysis of technical, economic, environmental factors, and addressing unmet load, this research contributes to the advancement of renewable energy integration within MG systems. It offers a complete guide for Oakland University and other institutions to effectively plan, design and implement hybrid renewable energy solutions, fostering a greener and more resilient campus environment. The findings demonstrate the potential for cost-effective and sustainable energy solutions, providing valuable guidance for Oakland University in its search of energy resilience and environmental surveillance which has a total peak load of 9.958MW. The HOMER simulation results indicate that utilizing all renewable resources, the estimated net present cost (NPC) is a minimum of 30M$, with a levelized energy cost (LCOE) of 0.00274$/kWh. In addition, the minimum desired load will be unmeted on some days of September.

A high-performance Lead-free Piezoelectric Energy Harvester (LPEH) based on a Ba0.85Ca0.15Ti0.90Zr0.10O3 + CuO 0.3 wt% (BCTZC0.3) composite was fabricated by sintering at 1450℃. The BCTZC0.3 composite, which has an enhanced high-energy-conversion constant (〖d_33×g〗_33), shows improved piezoelectric power-generation performance when compared with conventional piezoelectric energy harvesters. The BCTZC0.3-based LPEH produces instantaneous maximum power of 8.2 mW and an energy density of 107.9 mW/cm3 in a weak magnetic field of 250 μT. This energy harvester can be used to charge a capacitor and operate a wireless sensor network (WSN) system to provide temperature sensing and radio-frequency (RF) transmission in a 250 μT magnetic field. The proposed LPEH is a promising green-energy device for potentially self-powering WSN systems when applied.

Sector coupling is one of the emerging topics in recent energy and climate change policy discussions. It can play a significant role in creating the pathway of a renewable-based energy system in the European energy sector. The North Sea region is very likely to play a key role in the transition to a sustainable energy system. Though different energy modelling approaches allow a versatile use, they lead to the problem of an unclear understanding of specific aspects of sector coupling, and the relevance of existing tools and techniques to model and analyze such a system. This paper is aimed at providing a comprehensive understanding of sector coupling and its incorporation in energy system models. Followed by a thorough literature review on sector coupling and energy system modelling, the paper outlines an approach to select an appropriate tool based on the specific rationales of the research. The paper also presents ‘Oemof’ as an open model tool to address the complex challenges of energy systems. The conclusions from the literature review provide a detailed understanding of the concept of sector coupling and indicate that it can be advantageous from the viewpoints of decarbonization, flexibility, network optimization, and system efficiency. To solve the coupling barriers, diversified techno-socio-economic circumstances should be taken into account through the use of model collaboration. It is also demonstrated how a list of appropriate tools for model collaboration can be picked up methodologically from an available wide range of models. Finally, ‘Oemof’ is hypothesized as a progressive tool to design a sector-coupled and renewable-based energy system in the North Sea region.

Since the discovery of the human epidermal growth factor receptor 2 (HER2) as an oncogenic driver in a subset of breast cancers and the development of HER2 directed therapies, the prognosis of HER2 amplified breast cancers has increased meaningfully. Next to monoclonal anti-HER2 antibodies and tyrosine kinase inhibitors, the antibody-drug conjugate T-DM1 is a pillar of targeted treatment of advanced HER2-positive breast cancers. Currently, several HER2 directed antibody-drug conjugates are under clinical investigation for HER2 amplified but also HER2 expressing but not amplified breast tumors. In this article, we review the current preclinical and clinical evidence of the investigational drugs A166, ALT-P7, ARX788, DHES0815A, DS-8201a, RC48, SYD985, MEDI4276 and XMT-1522.

This paper introduces an innovative energy circuit that challenges conventional understandings of energy conservation, marking a significant departure from traditional frameworks. Seeking to enhance energy generation within existing paradigms, this innovation holds promise for addressing pressing global issues such as the energy crisis and environmental sustainability, while also stimulating scientific inquiry. In contrast to prevalent misconceptions rooted in philosophical and scientific constraints, this study refutes the notion of generating energy from nothing and questions the viability of perpetual motion machines as conceptual models. Instead, it proposes a novel circuit design derived from an unconventional electrical short circuit, which is shown to disrupt the established principles of energy conservation. This circuit offers a transformative approach with diverse applications, including self-recharging capabilities for electric vehicles, bolstering microgrid infrastructure, and facilitating the integration of renewable energy sources. Transcending conventional scientific boundaries, this paper prompts philosophical reflections on the evolving nature of scientific exploration. Ultimately, the energy circuit represents a pivotal step towards mitigating the global energy crisis by reducing reliance on finite resources and fostering sustainability. The paper concludes by illustrating the circuit's potential to revolutionize energy systems and contribute to a more resilient and sustainable future.

The COST Action ‘PED-EU-NET’, JPI Urban Europe, IEA EBC Annex 83 and EERA JP Smart Cities can be considered as the main promoters and pioneer initiatives of the research on Positive Energy Districts (PEDs), that collaborated to develop a tool called 'PED Database'. The tool aims to map, filter, sort, and compare PED experiences, providing a balanced overview of the technological and non-technological solutions adopted in different PED projects and case studies around Europe and beyond. The paper aims to present the collaborative step-by-step process leading to the PED DB implementation, describing the adopted methodology, the current results and potentials of the online version platform and introducing its future possible developments towards a more user-friendly and stakeholders-tailored tool.

The Covid-19 pandemic and the subsequent implementation of lockdown measures have significantly impacted global electricity consumption, necessitating accurate energy consumption forecasts for optimal energy generation and distribution during a pandemic. In this study, we propose a new forecasting model called the Multivariate Multilayered LSTM with Covid-19 case injection ($\proposedModel$) for improved energy forecast during the next occurrence of a similar pandemic. We utilize data from commercial buildings in Melbourne, Australia during the Covid-19 pandemic to predict energy consumption and evaluate the model's performance against commonly used methods such as LSTM, Bi-LSTM, Linear Regression, Support Vector Machine and the previously published work of Multilayered LSTM (M-LSTM). The proposed forecasting model was analyzed using the following metrics of mean percent absolute error (MPAE), normalized root mean square error (NRMSE), and $R^2$ score values. The model $\proposedModel$ demonstrates superior performance, achieving the lowest MPAE values of 0.061, 0.093, and 0.158 for data sets from 3 different buildings, respectively. Our results highlight the improved precision and accuracy of the model, providing valuable information for energy management and decision-making during the challenges posed by the occurrence of a pandemic like Covid-19 in the future.

: Electric air conditioning and heating systems capacity is growing rapidly. So does the nameplate capacity of PV power plants. While demand in cooling has a positive correlation with solar irradiationirradiance, the demand in heating has an opposite relation. In this study, different approaches of to design (aggregation; energy storagethermal, battery and implicit systems storage) and control (frequency conversion; variable and adaptive load) and their effects on the efficiency of an off-grid active thermal stabilisation system based on a solar-powered heat pump are analysed. The case considered is permafrost thermal stabilisation system in Norway. It is shown that proper layout and control of the system with an adaptive load can reduce the capital expenses expenditures and the total cost of ownership by 30-40%. Increase in the efficiency capacity factor and cooling stability of the systems with the aggregated and threshold power consumervariable load due to the principle of aggregation is studied. The downside of that is the increase in compressors operation time by 50% with variable load and by 25% per unit with aggregation which means more frequent replacement in terms of motor-hours. But The the feasibility of this approaches considered are applicable for a wide range of solar-powered facilities, but the results are is quite case sensitive and depends on the prices for low-power heat pumps. The prospects of using the excess refrigerant and soil for thermal energy storage instead of traditional electrochemical batteries are considered.

Canada has committed to reducing greenhouse gas (GHG) emissions by increasing the non-emitting share of electricity generation to 90% by 2030. As solar energy costs have plummeted, agrivoltaics (co-development of solar photovoltaic (PV) systems and agriculture) provide an economic path to these goals. This study quantifies agrivoltaic potential in Canada by province using geographical information system analysis of agricultural areas and numerical simulations. Systems modeled would enable conventional farming of field crops to continue (and potentially increase yield) by using bifacial PV for single-axis tracking and vertical system configurations. Between a quarter (vertical) to more than one third (single axis tracking) of Canada’s electrical energy needs can be provided solely by agrivoltaics using only 1% of current agricultural lands. These results show that agrivoltaics could be a major contributor to sustainable electricity generation and provide the ability for Canada to render the power generation sector net zero/GHG emission free. It is clear that the potential of agrivoltaic-based solar energy production in Canada far outstrips current electric demand and can thus be used to electrify and decarbonize transportation, heating, expand economic opportunities by powering the burgeoning computing sector, and export green electricity to the U.S. to help eliminate their dependence on fossil fuels.

The hybrid system is analyzed and optimized to produce electric energy in Non-Interconnected Zones in the Colombian Caribbean region, contributing both to the improvement in the reduction of greenhouse gas emissions and to the rational use of energy. A comparative analysis of the performance of these systems was carried using a dynamic model in real wind and solar data. The model is integrated by a Southwest Wind Power Inc. wind turbine. AIR 403, a proton exchange fuel cell (PEM), an electrolyze, a solar panel and a charge regulator based on PID controllers to manipulate oxygen and hydrogen flows in the cell. The transient responses of the cell voltage, current, and power were obtained for the demand of 200 W for changes in solar radiation and wind speed for all days of the year 2013 in the Ernesto Cortissoz airport, Puerto Bolívar, Alfonso Lopez airport and Simon Bolívar airport, by regulating the flow of hydrogen and oxygen into the fuel cell. The maximum contribution of power generation from the fuel cell was presented for the Simon Bolívar airport in November with a value of 158,358W (9.45%). A multi-objective design optimization under a Pareto front is presented for each place studied to minimize the Levelized Cost of Energy and CO₂ emission, where the objective variables are the number of panel and stack in the PV system and PEM.

Physics behind collimated highly directional nature of lasers, and factors that keep the seven coloured waves that form white light together during their journey from Sun to Earth, in the face of the natural disruptive forces, is not fully understood. Energy levels were measured, in terms of alterations in induced current and voltage, in beams from a red laser, white LED light and the Sunlight before and during their disruption by diffusers (frosted glass for the lasers) and diffractors (diffraction grating for the white light) using a photovoltaic solar cell panel attached to a digital multimeter. Results show that disruption of the beams results in release of extra energy named as ‘Latent Light Binding’ Energy’. It is hypothesized that the ‘binding’ energy keeps laser waves firmly bound together both end-on and side-on enabling laser beams to travel long distances in collimated manner. Likewise, the 7 coloured waves that constitute white light are kept together, probably side-on, in their journey from the Sun to the Earth. The observation that diffraction of sunbeam is associated with increased power generation provides a new lead to improve harnessing of solar energy, where, currently, the focus is mainly on improving efficiency of photovoltaic cell.

Exercise facilitates weight control, partly through effects on appetite regulation. Single bouts of exercise induce a short-term energy deficit without stimulating compensatory effects on appetite, whilst limited evidence suggests that exercise training may modify subjective and homeostatic mediators of appetite in directions associated with enhanced meal-induced satiety. However, large variability in responses exists between individuals. This article reviews the evidence relating to how adiposity, sex and habitual physical activity modulate exercise-induced appetite, energy intake and appetite-related hormone responses. The balance of evidence suggests that adiposity and sex do not modify appetite or energy intake responses to acute or chronic exercise interventions, but individuals with higher habitual physical activity levels may better adjust energy intake in response to energy balance perturbations. The effect of these individual characteristics and behaviours on appetite-related hormone responses to exercise remains equivocal. These findings support the continued promotion of exercise as a strategy for inducing short-term energy deficits irrespective of adiposity and sex, as well as the ability of exercise to positively influence energy balance over the longer term. Future well-controlled studies are required to further ascertain potential mediators of appetite responses to exercise.

The growing interest in benchtop NMR systems is visible in a vast number of applications in science and industry. Low-field nuclear magnetic resonance (LF-NMR) became an instant in technologies that productions are dependent on the reliable structure identification, grade and purity control, chemical process inspection or reaction monitoring. Beyond the benefits of being cost-, space-, maintenance- and user friendly, insufficient sensitivity and low signal resolution are the main drawbacks, due to which the low-field NMR (LF-NMR) in the fields of organic chemistry and synthesis remains limited to solely academic teaching purposes. Herein, we discuss the possibilities of LF-NMR for the needs of organic chemistry and synthesis on a set of compounds 1-4 achieved as the products of student’s laboratory course and organic derivatives 5-8 that are from our research interests. Chemical structure determination of all compounds 1-8 presented herein was performed using the benchtop-type NMR instrument operating at 60 MHz (Pulsar Oxford Ltd.). Structure of novel compounds 5-7 prepared under the aims of our research was characterized by combined 1H/19LF-NMR and compared with an appropriate high-field NMR data from Bruker Ascend Instrument (400 MHz). Finally, possibilities of the low-field NMR as an analytical tool for the research purposes in the fields of organic chemistry and synthesis are documented on a set of 1H and 2D 1H-1H COSY for azomethine 8.

Cement production contributes to about 7% of CO2 emissions into the atmosphere. Despite our best efforts, we cannot find a competitive substitute that is both reliable and environmentally friendly. The simplest way to solve the problem is to rationalize the resources and try to minimize its use by substitute them with other materials. A concrete that contains a substantial amount of fly ash is already available, but its use is limited by the current shortage in the market and reduced initial resistance. In this context, ternary mixtures have been used to conduct an experiment. A significant volume of cement has been replaced with fly ash and metakaolin, which serves as a correction factor for the performance. In this work the main advantages and disadvantages of the simultaneous use of these two additions, which may reveal to be very interesting with high volumes of substitution will be presented. The performance of this ternary mixture is very promising. Provide a wide range of possibilities for replacing cement, maintaining or even improving its mechanical and durability properties. A solution for an ecological concrete with enhanced performance for general use in construction as an alternative to conventional concrete.

Utilizing NCEP/NCAR monthly reanalysis data alongside precipitation observations from 1936 monitoring stations across China spanning from 1966 to 2022, this study establishes a location index for the thermal low-pressure center situated over the Qinghai–Tibet Plateau. Temporal variations in the location index and summer (July) precipitation patterns in China were studied. Over the past six decades, thermal low-pressure centers have been predominantly positioned near 90°E and 32.5°N on the plateau, with their distribution extending from east to west rather than from south to north. The longitudinal and latitudinal position indices exhibit contrasting linear trends, with a positive trend observed during the 1970s and early 21st century and a negative trend in subsequent decades. Mutation analysis highlights pronounced weakening mutations occurring in 1981 and 1973, with the longitudinal index transitioning from an inter-annual cycle of approximately 6-8 years, while the latitudinal index displays quasi-cyclic oscillations of 5 and 8 and 12-14 years. Strong negative correlations are evident between the location indices and precipitation along the southeastern edge of the Qinghai–Tibet Plateau and in Southern China, contrasting with the positive correlations observed in the central-eastern plateau, northwest China, North China, and the Huang-Huai region. The influence of southerly airflow predominates over much of China east of the plateau, while northwest China experiences convergence between northerly and southerly airflow. Higher location indices correspond to weaker surface cold air masses and strengthened Western Pacific Subtropical and South Asian Highs south of the Yangtze River Basin, resulting in significantly reduced rainfall in the southern Yangtze River region and increased rainfall in northwest China.

Abstract: Purpose: High-grade isthmic spondylolisthesis (HGISL) is a severe condition, associated with low-back pain (LBP) and radiculopathies. The present study is a monocentric prospective observational study investigating the clinical-radiological outcomes of a bilateral minimally invasive TLIF (bm-TLIF) for HGISL. Material and Methods: Patients who underwent bm- TLIF for HGISL at our institution, were considered for inclusion. Clinical-radiological outcomes and complications were collected. Results: Twenty-one patients (14M:7F) were included and the mean clinical follow-up (FU) time was 27(±6) months. There was a significative improvement of the mean VAS-back, VAS-legs, ODI, and SF-36 PCS scores, comparing pre- and last FU measurements. The mean pelvic tilt (p0,05). The univariate analysis showed that residual slip angle (> or  10°) may independently influence VAS-b (p

As a major coal country, China faces the issue of significant gas emissions during the coal mining process. This study aims to improve the utilization efficiency of mine gas, reduce greenhouse gas emissions, and promote the low-carbon and green transformation of the coal industry. A 10kW gas regenerative thermal oxidation (RTO) experimental system was constructed. The effects of initial methane concentration, low-temperature flue gas proportion, and operating load on combustion temperature, methane oxidation rate, high-temperature flue gas energy, and system thermal efficiency were studied. The results show that when the combustion temperature is below 600°C, the CH4 combustion reaction cannot proceed effectively, and the system temperature continuously decreases and cannot be maintained stable. The experiment determines the stable operating methane concentration range of RTO. In this experimental system, the lower limit of the initial methane concentration is 0.28%, corresponding to an 86% methane oxidation rate. As the initial methane concentration decreases, the combustion temperature also decreases, and the methane oxidation rate follows suit. The higher the low-temperature flue gas proportion, the higher the combustion temperature, and the system thermal efficiency and output heat decrease with the increase of the low-temperature flue gas proportion. This experiment explores multiple factors affecting regenerative thermal oxidation, providing an basis for ensuring the safe and stable operation of the system and optimization. Improving the thermal insulation and heat exchange performance of the storage body can expand the lower limit of the initial methane concentration, thereby increasing the stability and thermal efficiency of the system.

In recent years, researches on combining wavelet decomposition and convolutional neural network (CNN) together to classify hyperspectral images (HSI) have emerged, and some effective classification models have been proposed and achieved good classification results. However, there are two problems for most of the proposed models. One is the heavy training parameters and the other is that there is no distinction between the classification effectiveness of low frequency and high frequency features after wavelet decomposition. In this paper, a new light-weighted HSI classification model (LLFWCNN) is proposed, which performs multi-layer wavelet decomposition for HSI after dimensionality reduction, and only arranges the low frequency features in a specific stack mode, then classifies them through a well-designed convolutional neural network. Compared with other classification models, the number of parameters is only 2.5% of that of other models. And only the low frequency features after wavelet decomposition are used, while the high frequency features are abandoned. The results showed that compared with the state-of-the-art classification models, LLFWCNN could obtain the same or even better classification results with fewer network parameters and proved that the low frequency features after wavelet decomposition provide LLFWCNN with more favorable information for HSI classification as well.

A multicenter, prospective cohort study conducted in 5 physiotherapy clinics in the UAE from January 2021 to March 2023 to assess coronal lumbar spine radiographic parameters as a predictor of conservative therapy outcomes in patients suffering from low back and leg pain due to lumbar disc herniation (HNP). Ninety patients (mean age 44 yrs., 54% male) with lumbar HNP underwent conservative therapy. All participants received lumbar spine MRI and radiography to assess spine alignment. Interventions included specific exercises, diathermy, traction, education, a home-based exercise pro-gram, and medications. Detailed demographic data was collected. Follow-up was 6-months after discharge. A successful outcome was based on a minimum of the following four outcomes: (1) reduction of pain by 17.5 points (0–100 NRS); (2) fatigue reduction by 7.5 points; (3) distress reduction by 5 points; and (4) interference reduction by 9.5 points. At 6-month follow-up it was found that patient age, education, and radio-graphic determined lumbosacral angle measures significantly affected the odds of a successful outcome. Increasing age 1-year significantly decreased the odds of success of improving pain, fatigue (OR = 0.85, p = 0.016) and interference scores (OR = 0.89, p = 0.042) by 15%, 15%, and 11% respectively. Lower education significantly increased the odds of success for improving pain, fatigue, and interference by 26.18, 26.18, and 7.5 (p = 0.006, = 0.006, and = 0.029 respectively). Increasing (worsening) the radiographic lumbosacral angle by each 1° significantly reduced the odds of success for improving pain, fatigue, distress, and interference by 3.52, 3.52, 27.99, and 2.55, respectively (p < 0.001, < 0.001, = 0.003, = 0.001). Our findings indicate that younger age, less education, and better coronal radiological lumbar spine alignment all had a substantial impact on the likelihood of success of 6-month outcomes in patients suffering from chronic lower back pain and radiculopathy due to HNP.

Greenhouse gas (GHG) emissions from human activities have climbed significantly above pre-pandemic levels and reached record highs that unequivocally accelerate global warming. Industry has a significant impact on climate change, emitting at least 21 % of global GHGs and making little overall progress toward its reduction until now. Reducing industry’s emissions requires coordinated action along the value chains in order to promote mitigation options, such as energy and material efficiency, circular material flows, and transformative changes within production processes. The authors analyzed the GHG emissions generated during the manufacturing of three different products of automotive suppliers located in Austria. Despite previous efforts toward an environmentally compatible fabrication, additional and significant reduction potentials were identified. These measures for product carbon footprint (PCF) reduction included the sourcing of low-carbon materials (which are already available on the market), more extensive use of renewable energy, and changes towards more resource efficient manufacturing processes and machinery. Depending on the materials used, the PCF can be reduced by up to 80 %. The findings serve to prepare for future PCF reporting regulations and illustrate reduction potentials to achieve future market advantages, especially when PCFs become an awarding criterion.

Previous studies on the mechanisms underlying willed actions reported that the premotor cortex may be involved in the construction of motor awareness. However, its exact role is still under investigation. Here we investigated the role of the dorsal premotor cortex (PMd) in motor awareness by modulating its activity applying inhibitory rTMS to PMd, before a specific motor awareness task (under three conditions: without stimulation, after rTMS and after sham stimulation). During the task, subjects had to trace straight lines to a given target, receiving a visual feedback of the line trajectories on a computer screen. Crucially, in most trials the trajectories on the screen were deviated and to produce straight lines, subjects had to correct their movements towards the opposite direction. After each trial, participants were asked to judge whether the line seen on the computer screen corresponded to the line actually drawn. Results show that participants in the no stimulation condition did not recognize the perturbation until 14 degrees of deviation. Importantly, active, but not sham, rTMS significantly modulated motor awareness, decreasing the amplitude of the angle at which participants became aware of the trajectory correction. These results suggest that PMd plays a crucial role in action self- monitoring.