The plastic deformation behavior of 3Y-TZP with weak electric current in oxygen-lean atmosphere was investigated. An electrochemical reduction reaction, induced by the electric current, can significantly promote the plastic deformation of 3Y-TZP at furnace temperature of 1200 °C and a strain rate of 6.67 × 10−4 s−1. Especially, a remarkable variation of the electrical property and grain growth were observed in 3Y-TZP during the deformation. The stress exponent ranging within 2~3 indicated that the deformation was dominated by grain boundary sliding. The applied electric current decreased the apparent activation energy Q of the deformation from 465 kJ mol-1 to 315 kJ mol-1, resulting in a transition of the diffusion mechanism from the lattice diffusion to the grain boundary diffusion. These phenomena were mainly attributed to the enhancement of the cation diffusion caused by the electrochemical reduction reaction, which induced by the electric current in oxygen-lean atmosphere.

(1) Background: COVID-19 had devastating effects on both physical and mental well-being, prompting the need for interventions. This study aimed to explore the impact of mindfulness-based stress reduction on mental health, mindfulness, and sleep disorders in COVID-19 survivors.; (2) Methods: In this interventional parallel study, the sample was selected university students in nursing and midwifery faculties using total population sampling. The intervention included providing counseling on mindfulness methods by trained experts. General health, mindfulness and sleep quality questionnaires were used for data collection. Data were analyzed using SPSS22, descriptive and interferential statistic. A significance level of 0.05 was considered; (3) Results: In this study, the mean age of the students was 20.29 ± 2.03 years. 69.5% of the participants were female and 96% were single. 71.3% were studying nursing and 67% had a history of Corona infection. The intervention was only effective on general health questionnaire and the mean score of this questionnaire was 1.7 higher than the control group; (4) Conclusions: the study indicated that MBSR intervention improves mindfulness, mental health, and sleep quality in COVID-19 survivors. Regular assessment and use of this intervention can help address long-term challenges and improve overall well-being.

The complex progression, specialized care, and comorbidities of chronic diseases place a financial and health burden on society. In some instances, the high hospital readmission rate is also a result of chronic diseases. The readmission rates can be decreased if the quality of life for patients is increased and healthcare costs are reduced through effective management and preventive measures. As a result, healthcare professionals, service providers, and policy-makers are looking for innovative approaches to reduce healthcare costs while enhancing the quality of care. There is an emerging trend in deploying technological advancements like artificial intelligence (AI), the Internet of Things (IoT), sensors, wearables, social media, mobile apps, and genomics to decrease hospital readmissions. In some instances, predictive analytics, early warning systems, personal-ized care management, remote monitoring and Telehealth, decision support systems, patient education and engagement, and other areas of artificial intelligence and machine learning have outperformed traditional approaches in lowering hospital readmissions. Although AI effectively reduces readmission, there are potential risks if it is not combined with efficient interventions. Therefore, real-time monitoring and intervention are required for AI systems to increase patient safety and decrease hospital readmissions. To achieve autonomy, prevent harm, achieve fairness, and achieve explicability, the ethical principles relating to AI systems should be taken into ac-count. This study examines the significant impact on health and the economy of hospital read-missions for chronic diseases and the role of AI in reducing readmissions.

High surface area carbon was obtained from -carrageenan – urea cryogels doped with 1.25 – 5 wt% graphene oxide (GO). Incorporation of GO resulted in multifaceted modification in the textural and chemical properties of the carbon cryogel. The thermal decomposition of GO facilitated the formation of micropores resulted in a substantial increase in the apparent surface area (up to 1780 m2/g). The annealing at 1000 °C removed part of the heteroatoms but left behind a high number of defects. While the volatile thermal degradation products of GO affected the porous texture and the surface chemistry in a complex way, its reduced residue resulted in a gradually increasing electrical conductivity. The influence of GO was studied in oxygen reduction reaction (ORR) and in Li-ion storage application. GO affected the electron transfer mechanism in the ORR tests and challenged the stability of the electrodes. Even if the electrode has been stabilized under oxygen-free conditions, later may undergo destabilization processes during the ORR. The 5 wt% GO doped sample was the most sensitive under oxidative conditions, but finally it exhibited the highest capacitance. In the Li-ion battery tests the coulombic efficiency of all the samples was consistently above 98 %, indicating the great potential of such carbons for efficient Li-ion insertion and reinsertion during the charge – discharge process, thereby providing a promising alternative for graphite-based anodes. The cell from the 1.25% sample showed an initial discharge capacity of 313 mAh/g, 95.1 % capacity retention and 99.3 % coulombic efficiency after 50 charge – discharge cycles.

This study investigates via Lie symmetry analysis the Hunter-Saxton equation, an equation relevant to the theoretical analysis of nematic liquid crystals. We employ the multiplier method to obtain conservation laws of the equation derived from first-order multipliers. Conservation laws of the Hunter-Saxton equation, in combination with the Lie point symmetries of the equation, enable us to perform symmetry reductions through employment of the double reduction method. The method exploits the relationship between Lie point symmetries and conservation laws to effectively reduce both the number of variables and the order of the equation. Five nontrivial conservation laws of the Hunter-Saxton equation are derived, four of which are found to have associated Lie point symmetries. Applying the double reduction method to the Hunter-Saxton equation results in a set of first-order ordinary differential equations, the solutions of which represent invariant solutions for the equation.

Earth Observation (EO) techniques have significantly evolved over time, covering a wide range of applications in different domains. The scope of this study is to review the research conducted on EO in the Eastern Mediterranean, Middle East, and North Africa (EMMENA) region and to identify the main knowledge gaps. We searched through the Web of Science database for papers published between 2018 and 2022 for EO studies in the EMMENA. We categorized the papers in the following thematic areas: Atmosphere, Water, Agriculture, Land, Disaster Risk Reduction (DRR), Cultural Heritage, Energy, Marine Safety and Security (MSS) and Big Earth Data (BED); 6647 papers were found with the highest number of publications in the thematic areas of BED (27%) and Land (22%). Most of the EMMENA countries are surrounded by sea, yet there was a very small number of studies on MSS (0.9% of total number of papers). This study detected a gap in fundamental research in the BED thematic area. Other future needs identified by this study are the limited availability of very high resolution and near real time remote sensing data, the lack of harmonized methodologies and the need for further development of models, algorithms, early warning systems and services.

In this study, our primary objective was to analyze the tradeoff between accuracy and complexity in machine learning models, with a specific focus on the impact of reducing complexity and entropy on the production of landslide susceptibility maps. We aimed to investigate how simplifying the model and reducing entropy can affect the capture of complex patterns in the susceptibility maps. To achieve this, we conducted a comprehensive evaluation of various machine-learning algorithms for classification tasks. We compared the performance of these algorithms in terms of accuracy and complexity, considering both "before" and "after" scenarios of dimensionality reduction using Principal Component Analysis (PCA). Our findings revealed that reducing complexity and lowering entropy can lead to an increase in model accuracy. However, we also observed that this reduction in complexity comes at the cost of losing important complex patterns in the produced landslide susceptibility maps. By simplifying the model and reducing entropy, certain intricate relationships and uncertain patterns may be overlooked, resulting in a loss of information and potentially compromising the accuracy of the susceptibility maps. The analysis encompassed a diverse range of machine learning algorithms, including Random Forest (RF), Extra Trees (EXT), XGboost, LightGBM, Catboost, Naive Bayes (NB), K-Nearest Neighbors (KNN), Gradient Boosting Machine (GBM), and Decision Trees (DT). Each algorithm was evaluated for its strengths and limitations, considering the tradeoff between accuracy and complexity. Before dimensionality reduction, the algorithms demonstrated promising results, with RF exhibiting excellent AUC/ROC scores and average accuracy. However, computational costs were noted as a potential drawback for RF, especially when dealing with large datasets. EXT showcased robust performance and good accuracy, while XGboost demonstrated its ability to handle complex relationships within large datasets, albeit requiring careful hyperparameter tuning. The efficiency and scalability of LightGBM made it a suitable choice for large datasets, although it displayed sensitivity to class imbalance. Catboost excelled in handling categorical features, but longer training times were observed for larger datasets. NB showcased simplicity and computational efficiency but assumed independence among features. KNN, known for its capability to capture local patterns and spatial relationships, was found to be sensitive to the choice of distance metric. GBM, while capturing complex relationships effectively, was prone to overfitting without proper regularization. DT, with its interpretability and ease of understanding, faced limitations in terms of overfitting and limited generalization. After dimensionality reduction, certain algorithms exhibited improvements in their AUC/ROC scores and average accuracy, including RF, EXT, XGboost, and LightGBM. However, for a few algorithms, such as NB and DT, a decrease in performance was observed. This study provides valuable insights into the performance characteristics, strengths, and limitations of various machine learning algorithms in classification tasks. Researchers and practitioners can utilize these findings to make informed decisions when selecting algorithms for their specific datasets and requirements. We also aim to identify the potential factors contributing to the high accuracy rates obtained from these ensembled algorithms and explore possible shortcomings of non-ensembled algorithms that may result in lower accuracy rates. By conducting a comprehensive analysis of these algorithms, we seek to provide valuable insights into the benefits and limitations of ensembled approaches for landslide susceptibility mapping. Our study sheds light on the challenges faced when balancing accuracy and complexity in machine learning models for landslide susceptibility mapping. It emphasizes the importance of carefully considering the level of complexity and entropy reduction in relation to the specific patterns and uncertainties present in the data. By providing insights into this tradeoff, our research aims to assist researchers and practitioners in making informed decisions regarding model complexity and entropy reduction, ultimately improving the quality and interpretability of landslide susceptibility maps.

Microarray gene expression-based detection and classification of medical conditions have been prominent in research studies over the past few decades. However, extracting relevant data from the high-volume microarray gene expression with inherent nonlinearity and inseparable noise components raises significant challenges during data classification and disease detection. So, this paper proposes a two-level strategy involving feature extraction and selection methods before the classification step. The feature extraction step utilizes Short Term Fourier Transform (STFT), and the feature selection step employs Particle Swarm Optimization (PSO) and Harmonic Search (HS) metaheuristic methods. The classifiers employed are Non-Linear Regression, Gaussian Mixture Model, Softmax Discriminant, Naive Bayes, SVM (Linear), SVM (Polynomial), and SVM (RBF). The two-level extracted relevant features are compared with raw data classification results, including Convolutional Neural Network (CNN) Methodology. Among the methods, STFT with PSO feature selection and SVM (RBF) classifier produced the highest accuracy of 94.47%.

Bimetallic Ni/Cu core-shell and Cu-Ni heterostructural micro- and nanoparticles were prepared using two simple successive reduction procedures. Monometallic Ni and Cu particles were synthesized for comparison. The phase constitutions and morphological features of the particles were studied by means of X-ray diffraction, energy-dispersive X-ray spectroscopy and scanning electron microscopy methods. All the obtained mono- and bimetallic particles were applied as electrocatalysts in the electrohydrogenation of p-nitrophenol (p-NPh). An additional electrochemical reduction of copper cations during the hydrogen saturation of Cu-containing particles was established. Some of the prepared particles exhibited high catalytic activity with an increase in the hydrogenation rate of p-NPh by more than 3 times compared to its electrochemical reduction on the non-activated cathode, and p-NPh conversion yielded the maximum values. The main product of p-NPh electrocatalytic hydrogenation over Ni-Cu particles is p-aminophenol, which is an intermediate in the synthesis of many drugs. p-Aminophenol formation is confirmed by UV-Vis spectra.

Reactive oxygen species and reactive nitrogen species in semen are both essential for fertilization process; however, they become harmful at excessive levels, causing oxidative stress and nitrosative stress, respectively. Recently, oxidation–reduction potential (ORP) has been used as a marker for measuring oxidative stress, and this study investigated the possibility of comprehensively evaluating nitrosative stress. The correlation between standardized ORP (sORP) and 8-hydroxy-2′-deoxyguanosine (8-OHdG) and NOx per unit sperm was tested. Based on the previously reported cutoff value, samples were classified into oxidative stress-positive and negative groups. Thereafter, a receiver operating characteristic curve was drawn on 8-OHdG and NOx, and each optimal cutoff value was determined. Both standardized 8-OHdG and NOx significantly correlated with sORP. Although both correlated significantly with sORP in the oxidative stress group, no correlation was found in the nonoxidative stress group. The optimal standardized 8-OHdG level to determine oxidative stress status was 0.52 ng/106 spermatozoa, and the standardized NOx was 0.17 µM/106 spermatozoa/mL. The ORP is a simpler and quicker assay that can comprehensively assess oxidative and nitrosative stresses. Optimal cutoff values for both stresses were established in this study.

Metal organic frameworks (MOFs) are used in catalysis due to their high specific surface area and porous structure. The dispersed active sites and limited reaction space render MOFs have the potential for highly selective electrocatalytic CO2 reduction reaction (ECO2RR). Meanwhile, formic acid (HCOOH) is attracting attention as a liquid product with high economic benefits. This review summarizes the MOFs and their derivatives applied for ECO2RR into HCOOH products. The preparation methods of MOFs as electrocatalysts and their unique advantages are discussed. A series of MOFs, and MOFs derivatives obtained by electrochemical reduction or carbonization processes are highlighted, including metal nanomaterials, carbon-based nanocomposites, single-atom catalysts, and bimetallic nanocomposites. Depending on the MOFs building units (metal ions and organic linkers) and the reaction conditions of derivatization, MOFs-based catalysts exhibit rich diversity and controllable modulation of catalytic performance. Finally, the challenges encountered at this stage and the future research directions of MOFs-based catalysts are proposed.

Since Hydrogen Sulfide (H2S) was recognized as a gas transmitter, its detection and quantifica-tion have become a hot research topic among chemists and biologists. In this area. fluorescent probes have shown great advantages: fast and strong responds, low detection limit and easy ma-nipulation. Here we developed a new fluorescent probe that detected H2S selectively among various bioactive and inorganic salts. This probe was based on the core structure of fluorescein and reacted with H2S through azide-reduction. Great linearity was achieved correlating fluores-cence intensity and H2S concentrations in solution. The detection of H2S in cancer cells was also achieved.

This comprehensive study focused on the standard taxi sign used in Ireland, its impact on drag production, fuel expenses, and CO2 emissions. Experimental analysis revealed that the conventional taxi sign significantly increased drag, especially when mounted on streamlined vehicles such as saloon cars, due to flow separation issues on the rear roof and rear windshield. Longitudinal reorientation of the sign offered a 14-fold reduction in drag increase compared to the traditional placement. It was found that positioning the sign in the middle of the roof offered the greatest fuel efficiency. Furthermore, the study estimated that implementing longitudinal repositioning on all Irish taxi signs could save drivers approximately 832 per year and reduce national CO2 emissions by a substantial 22,464 tonnes annually. Comparative analyses with international taxi signs demonstrated that the Irish sign had significantly larger drag contributions, emphasizing the need for improved aerodynamics. To address the inherent drag issue, the study explored novel appendable devices and proposed alternative taxi sign designs. Among the tested solutions, a magnet-mounted front ramp proved the most effective, reducing total drag by nearly 30%. Additionally, a motorized flip-up taxi sign design demonstrated a remarkable 40% reduction in drag. Finally, a newly proposed taxi sign design, featuring longitudinal positioning and pointed triangular front and rear faces, resulted in a minimal 4.3% increase in vehicle drag compared to the baseline car.

In this paper, we introduce as a pedagogical strategy an internal division-free, straightforward, and symmetrically progressing algorithm in manually computing matrix inverse and solving systems of linear equations by revisiting the application of elementary row operations in the Gauss-Jordan reduction method and connecting it to the determinant method. The proposed cross-multiplication-flip (CMF) algorithm employs cross-multiplication similar to the butterfly movement in computing determinants as a strategic application of elementary row operations to efficiently reduce the rows and then applies flipping of rows and entries to put an upper triangular matrix into lower triangular form to continue the reduction process.

This paper explores the challenges faced by blue-collared international migrants in adapting to new and unfamiliar climates while pursuing job opportunities, with a focus on poverty alleviation. Drawing on existing research and empirical evidence, the study investigates the trials encountered by these migrants as they navigate climate shocks and assesses the potential impacts on poverty reduction efforts. The findings underscore the significant difficulties blue-collared migrants experience when confronted with abrupt changes in climate conditions, adversely affecting their physical and mental well-being, as well as their employment prospects. The process of adjustment involves not only acclimating to new climate patterns but also navigating cultural nuances and social dynamics, exacerbating stress and feelings of isolation. Consequently, these challenges can perpetuate poverty by disrupting employment stability and limiting opportunities for career advancement. To address these issues, the paper proposes comprehensive support measures, including targeted pre-departure training programs, access to retraining opportunities, and assistance in securing sustainable livelihoods. By prioritizing climate resilience and empowering blue-collared migrants to adapt effectively to new climates, it becomes possible to enhance their livelihood prospects, reduce poverty levels, and foster sustainable development. The paper concludes by highlighting the significance of integrating climate adaptation strategies with poverty alleviation efforts to create a more inclusive and resilient future for blue-collared migrants in their pursuit of sustainable livelihoods.

Delay in data transmission is one of key performance indicators (KPIs) of a network. The planning and project value of delay in network management is of crucial importance for the optimal allocation of network resources and their performance focuses. To create optimal solutions, predictive models, which are currently most often based on machine learning (ML), are used. This paper aims to investigate the training, testing and selection of the best predictive delay model for a VoIP service in an Long Term Evolution (LTE) network using three ML techniques - Neural Networks (NN), Support Vector Machines (SVM) and k-Nearest Neighbors (k-NN). The space of model input variables is optimized by dimensionality reduction techniques: RReliefF algorithm, Backward selection via the recursive feature elimination algorithm and the Pareto 80/20 rule. A three-segment road in the geo-space between the cities of Banja Luka (BL) and Doboj (Db) in the Republic of Srpska (RS), Bosnia and Herzegovina (BiH), covered by the cellular network (LTE) of the M:tel BL operator was chosen for the case study. The results show that, in all three optimization approaches, the k-NN model is selected as the best solution. For the RReliefF optimization algorithm, the best model has 6 inputs and minimum relative error (RE), RE=0.109; for the Backward selection via the recursive feature elimination algorithm, the best model has 4 inputs and RE=0.041; and for the Pareto 80/20 rule, the best model has 11 inputs and RE= 0.049. The comparative analysis of the results concludes that according to observed criteria for the selection of the final model, the best solution is an approach to optimizing the number of predictors based on the Backward selection via the recursive feature elimination algorithm.

Abstract: Based on the survey data of 5 large grain-producing provinces in China, this paper studies the effect of agricultural production trusteeship on agricultural carbon emission reduction by using a propensity score matching method. The empirical results show that the carbon emission of wheat reduces by 7.107kg/mu, with a decrease rate of 15.5% after participating in agricultural production trusteeship. Among them, chemical fertilizers, manpower input, agricultural chemicals and diesel oil respectively reduces with rates of 14.2%, 27.7%, 14.1%, and 6%. However, there are differences in the facilitation effects of different trusteeship services, with the best promotion effect of field management services, followed by cultivation, planting and harvest services, and then agricultural material supply services, the ATT is -6.160, -5.732 and -5.530, respectively. Meanwhile, there are differences in the promotion effects for farm households with different factor endowments. The promotion effect is better for small farm households with 1 type of agricultural machinery or less, and an operation scale of 7 mus or less. Therefore, in order to better play the role of agricultural production trusteeship on agricultural carbon emission reduction, the government should vigorously support its development and guide more smallholders to choose agricultural production trusteeship.

Drafting formations have been long recognized as highly effective for reducing drag and enhancing athletic performance, particularly in race walking events. The precise spacing and positioning of the race walkers are critical to optimizing the effectiveness of drafting. In this study, the drag reduction of 15 drafting formations is investigated using wind-tunnel experiments and CFD numerical simulations. The results show excellent consistency in drag reduction rate between the two methods, with differences being within 10%. This can be attributed to spacing replacing body shape differences as the primary factor influencing drag reduction. Optimal double, triple, and quadruple drafting formations produce the same results in both wind-tunnel experiments and CFD simulation, resulting in drag reductions of 67%, 66%, and 81% (wind-tunnel) and 65%, 72%, and 85% (CFD). The sources of drag differences in the two methods are discussed from various aspects. The flow field obtained through CFD analysis is used to examine the mechanism of drag reduction, revealing that drafting formations have a significant shielding effect on incoming air, which reduces the number and speed of airflow impacting the core race walker. This shielding effect is identified as the primary cause of drag reduction. Using an empirical model for mechanical power output, optimal double, triple, and quadruple drafting formations enhance sport economy (4.4-5.7%), speed (3.61-4.67%), and performance (173.8-223.3s) compared to race walking alone. The findings can serve as a reference for race walkers' positioning strategy and provide insights for considering drafting formations in various running events.

The utilization of wind energy has become increasingly popular in the United States and many European countries due to its abundant natural source and optimized design. While existing wind turbines are predominantly large-scale and not suitable for standalone or distributed power production, Lubbock County in West Texas offers a diverse range of renewable energy options to meet its energy needs. The region relies heavily on utility-scale wind energy sources to supply power to the Texas Grid, replacing conventional fossil fuel-based systems. Currently, standalone solar PV systems are the preferred choice for renewable energy generation. However, West Texas possesses an ample supply of wind energy that can be harnessed to establish a microgrid and provide standalone power to rural communities. By employing the latest technology and optimizing efficiency, even in low-scale generation, a 6 kW permanent magnet alternator-based distributed wind turbine has been designed. This paper focuses on analyzing the techno-economic aspects of implementing this wind turbine in a real-world scenario, taking into account wind attributes such as velocity and available power at the specific location.

The high level of noise in helicopter cabins considerably compromises the comfort and safety of the pilot and passengers. To verify the feasibility and effectiveness of microperforated panel composite sound absorption structures for noise suppression in helicopter cabins, simulation and experimental studies were conducted on a model of a light helicopter cabin. First, three microperforated composite sound absorption structures for the helicopter cabin wall panel were designed. Then, a finite element model of the main gear/body acoustic vibration coupling was established to obtain the target frequencies of the microperforated composite sound absorption structures; the acoustic effect was verified by simulation. Finally, a model helicopter cabin equipped with the three microperforated composite sound absorption structures was built, and a cabin noise test was performed. The test results showed that the combined microperforated panel acoustic structure and microperforated panel–porous material composite structure realized an overall cabin sound pressure level attenuation of 8–10 dB, on average, in the wide frequency range of 500–2000 Hz, with an amplitude of more than 20 dB. The microperforated panel–acoustic supermaterial composite structure achieved low-frequency sound absorption in the frequency range of 300–450 Hz. The sound absorption effect reached 50%, and it also exhibited good noise reduction effects in the middle- and high-frequency bands.

This paper presents a new methodology to evaluate the performance of an electric vehicle hybrid power system consisting of a fuel cell and a supercapacitor. The study compares the results with those obtained for a battery-electric vehicle. The methodology extends to three driving modes, ECO, NORMAL, and SPORT, corresponding to conservative, moderate, and aggressive acceleration, and three driving conditions, low, medium, and high energy demand. We develop a simulation process to evaluate the energy consumption and the energy rate of a specific electric vehicle used as a prototype for the study. The methodology applies to a driving route that includes acceleration, deceleration, braking, and constant speed segments reproducing standard driving conditions in urban journeys. The proposed method considers combined driving modes, ECO, NORMAL, and SPORT, in each acceleration process, with variable fractions, 0% to 100%, for each mode. This methodology optimizes the simulation results as it fits the current driving way in urban environments. The simulation results show an average reduction in energy consumption of 37% and 27.1% in vehicle weight, contributing to lower energy use. The study concludes that using a hybrid power system, fuel cell/supercapacitor, instead of a battery in electric vehicles is beneficial, especially in journeys with frequent acceleration processes.

Hydrogen powered vehicles use high-pressure reservoirs from which the gas is transferred to the low-pressure fuel-cell via a classical pressure reduction valve. In these systems no expansion work is recovered and the question is addressed of the potential to increase the global efficiency by using an expansion machine between the reservoir and the electrochemical reactor. This paper investigates the feasibility of such an expansion machine, evaluates the mechanical constraints in terms of forces, torques and produced power by numeric simulation. It further evaluates the energetic contribution to the whole conversion chain from the hydrogen reservoir to the common electrical network on board. A low energy contribution of the expansion system addresses the question of the real benefit of such an investment.

In today's society, mankind is confronted with two major problems: the energy crisis and the greenhouse effect. The artificial photosynthesis can use solar energy to convert greenhouse gas CO2 into high-value compounds, which is an ideal solution to alleviate the energy crisis and solve the problem of global warming. The combination of ZnO and polythiophenes (PTh) can make up for each other's drawbacks, thus improving the photoresponse behavior and separation efficiency of photogenerated carriers. PTh layer can transfer photogenerated electrons to ZnO, thereby extending the lifetime of photogenerated charges. The production rate of CH4 from photoreduction of CO2 with ZnO/PTh10 is 4.3 times that of pure ZnO, and the selectivity of CH4 is increased from 70.2% to 92.2%. The conductive PTh can absorb photons to induce π–π* transition, the photogenerated electrons can transfer from LUMO to the conduction band (CB) of ZnO, thus more electrons involve in the reduction of CO2.

Diabetes becomes a life threatening non-communicable disease in the world, according to International Diabetic Federation (IDF) in 2023, an estimated 537 million adults (20-79 years) are living with diabetes, which is equivalent to 9.3% of the global adult population. This number is predicted to rise to 643 million by 2030 and 783 million by 2045. Over 3 in 4 adults with diabetes live in low- and middle-income countries. Diabetes is a persistent metabolic condition marked by increased levels of glucose in the bloodstream. It is a significant global health concern, affecting millions of individuals worldwide. It having the symptoms of drowsiness for the whole day if not properly examined or treated well. It is targeted to spread over the younger age community and the number is growing in the exponential fashion. Even day to day many advancements have come from the researcher to diagnose, to find solutions to prevent from newer entry. Authors have taken a dataset with 57 non diabetic and 20 diabetic patients with the total 28735 micro array gene to undergone pre-processing process and reduced up to 22960 gene data using Dimensionality Reduction (DR) such as Detrend Fluctuation Analysis (DFA), Chi square probability density function (Chi2PDF), Firefly algorithm Cuckoo search were used in this research. Meta heuristic algorithms like Particle swarm Optimization (PSO) and Harmonic Search (HS) are used for feature selection. Further seven classification techniques such as Non-Linear Regression (NLR), Linear Regression (LR), Logistics Regression (LoR), Gaussian Mixture Model (GMM), Bayesian Linear Discriminant Classifier (BLDC), Softmax Discriminant Classifier (SDC), Support Vector Machine – Radial Basis Function (SVM-RBF) are using to make a decision, predictive analysis and segregate the data according to the level of blood glucose as Diabetic Patient (DP) and Non-Diabetic Patient (NDP).

This article offers a theoretical framework to contextualise the concept of "Safety Culture" in the field of public safety and Disaster Risk Reduction (DRR), with the aim of supporting its understanding and measurement in our communities and finally attaining more disaster resilient societies. The work discusses the role of cultural dimensions in risk management and DRR and highlights the relevance of building knowledge and practices based on the consideration of culture and cultural variability in all phases of the risk management process. After an overview of the Safety Culture concept, including its origins, developments and applications, the text explores the transferability of this concept to the context of public safety. Then, based on the existing Safety Culture models, metrics and indicators from other sectors, the paper proposes an original definition of Safety Culture for the DRR context, shaped on a series of elements and dimensions specifically outlined for this context. Finally, the expected benefits of the application of Safety Culture concepts and techniques for further advances in DRR is discussed.

Electrical rotating machines like Induction Motors (IMs) are widely used in several industrial applications since their robust elements, provide high efficiency and give versatility in industrial applications. Nevertheless, the occurrence of faults in IMs is inherent to their operating conditions, hence, Inter-turn short-circuit (ITSC) is one of the most common failures that affect IMs and its appearance is due to electrical stresses leads to the degradation of the stator winding insulation. In this regard, this work proposes a diagnosis methodology for the assessment and detection of incipient ITSC in IMs, the proposed method is based on the processing of vibration, stator currents and magnetic stray-flux signals. Certainly, the novelty and contribution include the characterization of different physical magnitudes by estimating a set of statistical time domain features, as well as, their fusion and reduction through the Linear discriminant Analysis technique within a feature-level fusion approach. Furthermore, the fusion and reduction of information from different physical magnitudes leads to perform the automatic fault detection and identification by a simple Neural-Network (NN) structure. The proposed method is evaluated under a complete set of experimental data and the obtained results demonstrate that the fusion of information from different sources (physical magnitudes) allows to improve the accuracy during the detection of ITSC in IMs , the results make this proposal feasible to be incorporated as a part of condition-based maintenance programs in the industry.

Concept sustainable of banking is based on principle realization growth and profit for the bank and shareholders, but only with achievement social goals, as and care for conservation life environment. Providing new ones banking service and creation new ( green ) banking jobs, except for _ profitable, they achieve and spreads social and ecological goals, chances are with creation competitive advantages, both in countries Western Balkans observed in the work, so and in all countries of the world In this one work we will focus on analysis macroeconomic parameters in countries Western Balkans works tests influence selected indicators on performance banking system, with special in retrospect on social and component protection life environment. The results indicate that rate unemployment the most significant indicator potentially risky events for bankers, as and banks they are not recognized in national conservation strategies _ life environment which are in WB countries currently on strength. Accordingly, the former is necessary to carry out education foreign affairs, and in parallel to promote green loans like they live and in the long term more favorable of traditional loans, with update the existing one regulatory frame in the domain protection life environment.

The Bayer process is the maim method of alumina production worldwide. The use of low-quality bauxites for alumina production results in the formation of a significant amount of technogenic waste - bauxite residue (BR). The Bayer reductive method is one possible way to eliminate BR stockpiling, but it requires high-pressure leaching at temperatures higher than 220 °C. In this research, the possibility of boehmitic bauxite atmospheric pressure leaching at both the first and second stages or high-pressure leaching at the second stage with the simultaneous reduction of hematite was investigated. Bauxite and solid residue after NaOH leaching were characterized using XRD, SEM-EDS, and Mössbauer spectroscopy methods. The first stage of leaching under atmospheric pressure with the addition of Fe(II) species in a strong alkali solution (330-400 g L–1 Na2O) results in a partial reduction of the iron minerals and an extraction of more than 60% of Si and 5-25% of Al (depending on caustic modulus of solution) after 1 h. The obtained desilicated bauxite was subjected to atmospheric leaching at 120 °C in a strong alkali solution (350 g L-1) or high-pressure leaching at 160-220 °C using the Bayer process mother liquor in order to obtain a concentrate with a magnetite content higher than 83 wt. %.

Concern about the planet's future has motivated governments around the world to adopt policies that promote more responsible energy consumption. Reducing emissions of the principal cause of climate change man-made greenhouse gases requires greater system efficiency and the utilization of renewable energy sources. The generation of electricity is the single largest source of hazardous pollutants, followed by the transportation sector. This is true due to the extreme reliance on petroleum and its derivatives that these industries have. Electric mobility is receiving more attention from businesses, governments, and academic institutions as a means to reduce the negative impacts of current energy consumption. Without measures to address common technical issues, electric vehicles would strain electrical infrastructure. In order to determine the best strategy for switching operations and feeder reconfiguration, this research presents a helpful hybrid genetic algorithm particle swarm optimization (HGAPSO) method. Meet transmission limits while decreasing real power losses and enhancing the system's bus voltage profile. The effects of HGAPSO on power losses and voltage distributions in the network are analyzed. Then, a report is produced contrasting GA and PSO. This cross-breeding of GA and PSO led to HGAPSO. This important problem can be solved more effectively with the use of new or improved algorithms. To find the optimal reconfiguration and properly rearrange transmission network interconnection, it employs a plethora of heuristic optimization algorithms. The objective is to limit bus voltage variations while maintaining the system's radial topology and minimizing power usage. The reliability and performance of the procedure were evaluated using MATLAB's IEEE 33-bus communication network. The outcomes demonstrate the effectiveness of the proposed technique, which cuts down on power waste during standalone runs and speeds up the processing time.

Symmetry concepts in parametrized dynamical systems may reduce the number of external parameters by a suitable normalization prescription. If, under the action of a symmetry group G, parameter space A becomes a (locally) trivial principal bundle, A ~ A/G x G, then the normalized dynamics only depends on the quotient A/G. In this way, the dynamics of fractional variables in homogeneous epidemic SI(R)S models, with standard incidence, absence of R-susceptibility and compartment independent birth and death rates, turns out to be isomorphic to (a marginally extended version of) Hethcote's classic endemic model, first presented in 1973. The paper studies a 10-parameter master model with constant and I -linear vaccination rates, vertical transmission and a vaccination rate for susceptible newborns. As recently shown by the author, all demographic parameters are redundant. After adjusting time scale, the remaining 5-parameter model admits a 3-dimensional abelian scaling symmetry. By normalization we end up with Hethcote's extended 2-parameter model. Thus, in view of symmetry concepts, reproving theorems on endemic bifurcation and stability in such models becomes needless.

A high perovskite activity is sought for use in magnetic applications. In this paper, we present the simple synthesis of (2.5 and 5%) Tellurium-impregnated-LaCoO3 (Te-LCO), Te and LaCoO3 (LCO) by using a ball mill, chemical reduction, and hydrothermal synthesis, respectively. We also explored the structure stability along with the magnetic properties of Te-LCO. Te has a rhombohedral crystal structure, whereas Te-LCO has a hexagonal crystal system. The reconstructed Te was imbued with LCO that was produced by hydrothermal synthesis; as the concentration of the imbuing agent grew, the material became magnetically preferred. According to the X-ray photoelectron spectra, the oxidation state of the cobaltite is one that is magnetically advantageous. As a result of the fact that the creation of oxygen-deficient perovskites has been shown to influence the mixed (Te4+/2-) valence state of the incorporated samples, it is abundantly obvious that this process is of utmost significance. The TEM image confirms the inclusion of Te in LCO. The samples start out in a paramagnetic state (LCO), but when Te is added to the mixture, the magnetic state shifts to a weak ferromagnetic one. It is at this point that hysteresis occurs due to the presence of Te. Despite being doped with Mn in our prior study, rhombohedral LCO retains its paramagnetic characteristic at room temperature (RT). As a result, the purpose of this study was to determine the impacts of RT field dependency of magnetization (M-H) for Te-impregnated LCO in order to improve the magnetic properties of RT because it is a low-cost material for advanced multi-functional and energy applications.

Emerging infectious disease threats are becoming more frequent due to various social, political and geographical pressures including increased human-animal contact, global trade, transportation and changing climate conditions. As a result, the threat that emerging agents can be spread by blood contact or transfusion of blood products also becomes increasingly problematic. Blood transfusion is essential in treating patients with anemia, blood loss, and other medical conditions. However, these lifesaving components can become a vector for spreading diseases, particularly to vulnerable populations. New methods have been implemented on a global basis for prevention of transfusion transmission via plasma, platelet, and whole blood products. Implementing proactive pathogen reduction methods can significantly reduce the likelihood of disease transmission via blood transfusion, even for newly emerging agents whose transmissibility and susceptibility are still being evaluated as they emerge. In this review, we consider the Mirasol PRT system for blood safety which is based on a photochemical method involving Riboflavin and UV light. We provide examples of how emerging threats such as Ebola, SARS-CoV-2, Hepatitis E, monkeypox and other agents have been evaluated in real time regarding effectiveness of this method for reducing the likelihood of disease transmission via transfusion. Keywords: transfusion; blood; pathogen reduction; emerging infectious diseases.

To accomplish IMO's emissions reduction targets, the Chinese government has established emission control areas and implemented strict sulfur limitation policies. Faced with the downturn in the shipping industry and the challenge of insufficient supply of compliant fuel, Hong Kong and Shenzhen in China have implemented different low-sulfur fuel subsidy policies. Therefore, it is particularly important to study the air pollution control mechanism considering low sulfur fuel subsidy policy. Firstly, the non-cooperative game models considering low-sulfur fuel subsidies are constructed. Secondly, the mechanisms of various factors affecting port pricing, throughput and profit are analyzed. Then, a case study is conducted by using AIS data of container ships in Shanghai Port and Ningbo Zhoushan Port. The study reveals that whether the container service price of the leader port increases or decreases, the follower port always take corresponding follow-up measures. In both sequential and simultaneous game, the profit difference of the leader port is positively related to the subsidy ratio of the port’s own and negatively related to the coefficient of the competitor's subsidy. In conclusion, the low-sulfur fuel subsidy policy has a significant positive impact on the step-by-step implementation of more stringent pollution reduction policies in port waters.

This article purposed to examine the impact of integration between Lean accounting (LA) tools & Just in Time (JIT) technique on Cost Reduction (CR) in modern manufacturing environment in Saudi establishments, these two variable moderated by Ethical Standards (ESs). A quantitative methodology was used for realizing the study objectives and answering study questions, the main tool exercised for producing the incipient data was a fully-structured questionnaire with closed ended questions, which was designed and passed around online among a selected sample of (109) managers and accountants in Saudi manufacturing firms. Descriptive and deductive statistics adopted to derive the findings, wherefore the compiled responses analyzed by SPSS & AMOS and the results showed that there is direct and indirect effect of LA tools & JIT technique on CR in Saudi industrial companies, especially when using ESs. These findings could provide decision makers in Saudi manufacturing companies with the acuity of adopting both methods in a combined way to maximize the profits of these firms. The results of this study also suggest that the application of LA tools & JIT technique has a positive effect on the promotion of sustainable manufacture and consequent achievement of high sustainable performance.

The rapid development of electrochemical CO2 reduction offers a promising route to convert in-termittent renewable energy into products of high value-added fuels or chemical feedstocks. However, low faradaic efficiency, low current density, and a narrow potential range still limited the large-scale application of CO2RR electrocatalyst. Herein, monolith 3D bi-continuous nano-porous Bismuth (np-Bi) electrodes are fabricated via a simple one-step electrochemical dealloying strategy from Pb-Bi binary alloy. The unique bi-continuous porous structure ensures highly effective charge transfer, meanwhile the controllable millimeter-size geometric porous structure enables easy catalyst adjustment to expose highly suitable surface curvatures with abundant reactive sites. This results in a high selectivity of 92.6% and superior potential window (400 mV, selectivity >88%) for electrochemical reduction of carbon dioxide to formate. Our scalable strategy provides a feasible pathway for mass-producing high-performance and versatile CO2 electrocatalysts.

A scientific carbon accounting system can help enterprises reduce carbon emissions. This study took the enterprise in the Yangtze River basin as a case study. The accounting classification of carbon emissions in the life cycle of lime production was assessed, and the composition of the sources of carbon emission was analyzed, covering mining explosives, fuel (diesel, coal), electricity and high temperature limestone decomposition. Using the IPCC emission factor method, a carbon life cycle emission accounting model for lime production was established. We determined that a total of 354,200 tons of carbon emissions were generated from producing 321,000 tons of lime in a year. The decomposition of limestone at a high temperature was the largest carbon emission source, accounting for 62.34% of the total carbon emission. Coal combustion was also an important source of carbon emissions, accounting for 32.66% of total carbon emissions. The carbon emission for one ton of activated lime was 1.46kg, 1.49kg, 1100kg and 1102.95kg respectively for the open-pit, mining stage, crushing stage, and the calcination stage. Based upon the main sources of carbon emission for lime production, carbon emission reduction should focus on CO2 capture technology, fuel optimization and energy control. Using our analysis of carbon emissions, the carbon emission factor of producing unit quicklime of the lime enterprise in the Yangtze River basin was determined. Furthermore, the research into carbon emission reduction for lime production can provide a point of reference for the promotion of carbon neutrality in the same industry.

This study investigated the possible usage of beeswax oleogels instead of milk fat as a fat source in ice cream production and konjac gum as a stabilizer instead of salep. For this aim, 12 different ice cream samples were prepared using various fat and oil sources (milk fat and oleogel), stabilizers (salep and konjac gum), and emulsifiers (monoglyceride (MG), palsgaard (PG), and none emulsifier emulsifier-free (NE)). It was determined that the overrun ratio in ice cream samples containing milk fat was higher than in oleogel and the viscosity of the ice cream mix containing palsgaard and oleogel was greater than that of the other treatments (milk fat, MG, and NE). While the first dripping time of the samples with PG and konjac gum was longer compared to the samples without emulsifier (NE) and Monoglyceride (MG), the complete melting times of the samples were close to each other. Whereas the dissolution rate of the samples with salep was higher than that of konjac gum, the fat destabilization ratios of the samples with oleogel and konjac gum were lower than those of milk fat and salep. The fat destabilization ratio of samples containing PG as an emulsifier was statistically higher (p <0.01) than that of samples containing MG and NE. It was found that the unsaturated fatty acid (C18:1, C18:2, and C18:3) content of the samples containing oleogel was significantly higher (p <0.01) than that of the samples containing milk fat. However, butyric and caproic acids, which are aliphatic fatty acids, were found to be deficient in the samples to which oleogel was added instead of milk fat. As to the microscopic appearance, while water and oil particles were not homogeneously dispersed in the ice cream samples with oleogel, they were fully homogeneously dispersed in the milk fat-added ice cream samples. In addition, it was determined that panelists preferred the C samples (milk fat as fat source, salep and PG as emulsifier).Among the samples with added oleogel as oil source, they liked the J sample more (oleogel as fat source,conjak gum and none emulgator). Therefore, the C and J samples can be recommended for consumption

The reckless use of non-replenishable fuels by the growing population for energy and the resultant incessant emission of hazardous gases and waste products into the atmosphere insisted scientists to fabricate materials capable of managing these global threats at once. In recent studies, photo-catalysis employed focus on utilizing renewable solar energy to initiate chemical processes with the aid of semiconductors and highly selective catalysts. A wide range of nanoparticles have showcased promising photocatalytic properties. Ultrasmall metal nanoclusters (MNCs) with sizes below 2 nm, stabilized by ligands shows discrete energy levels, exhibits unique optoelectronic properties which are vital to photocatalysis. In this review, we intend to compile information on varying photocatalytic efficiency of metal NCs with respect to changes in their properties. Review discusses about the photocatalytic activity of atomically precise ligand-protected MNCs and its hybrids in the domain of in energy conversion processes like photodegradation of dyes, Oxygen Evolution Reaction (ORR), Hydrogen Evolution Reaction (HER) and CO2 Reduction Reaction (CO2RR), and photosensitizer in solar cell.

The effects of global warming combined with the progressive expansion of urbanization have considerably increased exposure to urban flooding and runoff widespread erosion risk, also causing shallow landslides and mud flows, respectively in urbanized areas of lowland and hill/foothill environments. Increasing urban flooding resilience has become a priority at virtually all levels of governance. The analysis of a different hazard scenarios, in which various hydro-meteorological conditions and management alternatives are examined, should act as the basis for the effective design and evaluation of interventions to improve urban flooding resilience. Turin Metropolitan Area (TMA), located in north-western Italy, represents a unique case due to its complex orography, with a mountainous sector in the west side and a flat or hilly part in the east side. During the warm season, these environmental conditions make the urban area prone to severe atmospheric convection causing frequent hailstorms and rainstorms of high intensity that may impact on urban infrastructures (i.e., drainage system and road network), thus requiring an adequate management as a key factor to reducing risk and losses. The urban areas of TMA are monitored by polarimetric Doppler weather radars and by a dense rain gauges network. Analyzing several case studies of urban flooding, this research work assesses the feasibility of a meteorological radar early warning system based on the identification of rainfall thresholds that characterize urban flooding, occurring in the lowlands, and the runoff erosion phenomena affecting the urbanized hills and foothills.

Twin pregnancies are highly undesirable in dairy cattle; they compromise the health and wellbeing of a cow, and its incidence dramatically impairs the farm economy. Recently, a genomic prediction for twin pregnancies has been developed. The objective of this study was to assess cow, environmental and management risk factors affecting the incidence of twin pregnancies in high-producing dairy cows in their first lactation, with special emphasis placed on the genomic prediction values for twin pregnancy. Our study population of primiparous cows proved valuable in identifying factors other than genomic predictive values influencing the twin pregnancy rate. The odds ratio for twin pregnancy was 0.85 (p &lt;0.0001) for each unit of a prediction value increase, 3.5 (p = 0.023) for cows becoming pregnant during the negative photoperiod, and 0.33 (p = 0.016) for cows producing ≥42 kg of milk at AI, compared to the remaining cows producing &lt;42kg of milk. As a general conclusion, the practical implication of our findings is that genomic prediction values can identify the risk of twin pregnancy at herd level. Given the cumulative effect of genomic selection, selecting for animals with reduced genetic risk of twin pregnancies can contribute to reduce its incidence in dairy herds.

In the era of big data, feature engineering has proved its efficiency and importance in dimensionality reduction and useful information extraction from original features. Feature engineering can be expressed as dimensionality reduction and is divided into two types of methods such as feature selection and feature extraction. Each method has its pros and cons. There are a lot of studies to combine these methods. Sparse autoencoder (SAE) is a representative deep feature learning method that combines feature selection with feature extraction. However, existing SAEs do not consider the feature importance during training. It causes extracting irrelevant information. In this paper, we propose a parallel guiding sparse autoencoder (PGSAE) to guide the information by two parallel guiding layers and sparsity constraints. The parallel guiding layers keep the main distribution using Wasserstein distance which is a metric of distribution difference, and it suppresses the leverage of guiding features to prevent overfitting. We perform our experiments using four datasets that have different dimensionality and number of samples. The proposed PGSAE method produces a better classification performance compared to other dimensionality reduction methods.

Various species of plants, bacteria, fungi, insects, invertebrates, and vertebrate animals produce unique small molecules, peptides, or proteins (biomolecules) for their defensive purposes. These biomolecules, also known as toxins, are poisonous (toxic) to humans and could be misused due to relatively easy accessibility and affordability. Toxins are not contagious and replicative; their effect or symptoms depend on their concentration (dose), which can take hours to days after exposure. Furthermore, for nefarious actors, preparing low-effort homemade explosives (HMEs) using household items or easily accessible chemical precursors is not difficult. To mitigate the biosecurity risks, biological scientists, law enforcement investigators, and public health response professionals should be aware of the new threats and challenges posed by low-effort toxins and HMEs. The chemical and biological investigation, evidence, and countermeasures training program was aimed at preparing biological scientists, law enforcement investigators, and public health representatives to mitigate the biosecurity risks from low-effort toxins and HMEs. The tailor-made eight-day training program containing lectures, round table discussions, immersion scenarios, practical exercises, practical assessment, and tabletop exercises helped participants to understand and close their skill gaps. The training also covered various elements associated with chemical, biological, radiological, nuclear, and explosive (CBRNE) threats from nefarious individuals and groups. Some highlights of the training are reported in this report.

The battery energy storage systems (BESS) are most promising solution for increasing efficiency and flexibility of distribution networks (DNs) with significant penetration level of photovoltaic (PV) systems. There are various issues related to the optimal operation of DNs with integrated PV sys-tems and BESS that need to be addressed to maximize DN performance. This paper deals with the day-ahead optimal active-reactive power dispatching in unbalanced DNs with integrated sin-gle-phase PV generation and BESSs. The objectives are the minimization of cost for electricity, en-ergy losses in the DN and voltage unbalance at three-phase load buses by optimal managing of active and reactive power flows. To solve this highly constrained nonlinear optimization problem, a hybrid particle swarm optimization with sigmoid-based acceleration coefficients (PSOS) and cha-otic gravitational search algorithm (CGSA), called PSOS-CGSA algorithm, is proposed. A scenario based approach encompassing the Monte Carlo simulation (MCS) method with the simultaneous backward reduction algorithm is used for the probabilistic assessment of the uncertainty of PV generation and power of loads. The effectiveness of the proposed procedure is evaluated through the series test cases in a modified IEEE 13-bus feeder.

: Polymer single screw extrusion is a major industrial processing technique used to obtain plastics products. To assure high outputs, tight dimensional tolerances, and excellent product performance, extruder screws may show different design characteristics. Barrier screws, which contain a second flight in the compression zone, have become quite popular as they promote and stabilize polymer melting. Therefore, it is important to design efficiently extruder screws and decide whether a conventional screw will do the job efficiently, or a barrier-screw should be considered instead. This work uses multi-objective evolutionary algorithms to design conventional and barrier screws (Maillefer screws will be studied) with optimized geometry. Processing of two polymers, Low Density Polyethylene and Polypropylene, is analyzed. A methodology based on the use of Artificial Intelligence (AI) techniques, namely data mining, decision making and evolutionary algorithms, is presented and utilized to obtain results with practical significance, based on relevant performance measures (objectives) used in the optimization. For the various case studies selected, Maillefer screws were generally advantageous for processing LDPE, while for PP the use of both types of screws would be feasible.

EMG analysis is becoming increasingly important in many research and clinical applications, including muscle fatigue detection, control of robotic mechanisms and prostheses, clinical diagnosis of neuromuscular diseases and quantification of force. However, electromyographic signals can be contaminated by various types of noise, interference and artifacts, which can lead to misinterpretation of the data acquired using this method. Even assuming best practices, the collected signal may still be altered by such contaminants. The aim of this paper is to review methods employed to reduce contamination of single channel EMG signals. This review is limited to methods performed directly on the measured EMG signal and those that allow total reconstruction of the EMG signal. Subtraction methods used in the time domain, denoising methods performed after signal decomposition and hybrid methods are assessed. It is defended that individual methods may be more or less suitable for a particular application depending on contaminant(s) present in the signal and on the specific requirements of the application.

Human perception of nature and God have always been inextricably linked. In order to understand nature and its inherent processes, including various natural hazards, the reasons for their origin were often attributed to God's will, suffering for sin and the similar. Fear of material and human losses prompted a man to pray and offer sacrifices/gifts and other rituals to appease the "wrath of the gods". The progress of civilization and technology has not alleviated the destruction and trauma that natural disasters inflict on all aspects of social life. A major obstacle to this is the exponential population growth in vulnerable areas. The frequency of natural disasters and the fatalistic attitudes that limit the effective fight against them have motivated religious communities and individuals to cooperate with international and international organizations and institutions to reduce the risk of local disasters. Believers thus receive the necessary psychological and financial assistance and support from religious communities during all phases of disaster management. Therefore, the subject of this paper is a comprehensive examination relationship between the degree of religiosity of the population and how this connection impacts the policy of reducing disaster risk. The aim of the research is to scientifically describe the nature of the relationship between the degree of religiosity of citizens and different segments of disaster risk reduction.

The global transport sector of the world economy contributes about 15% of the Greenhouse Gas (GHGs) emissions in the world today. The University of Saskatchewan has pursued the green energy transition over the years. They have spearheaded diverse sustainability projects and agendas, due to the importance of curbing climate change and advancing sustainability. The transport system in the university campus is one area of focus where the Sustainability Office plans to introduce some innovations, as a way of curbing GHG emissions while also advancing sustainability practice in the university campus. The study carried out an economic benefit analysis on the campus fleet (consisting of 91 ICE vehicles) to determine if it is economically or financially feasible to transition from Internal Combustion Engine (ICE) or PVs (Petrol Vehicles) to Electric Vehicles (EVs). The analysis used RETScreen Expert software for analyzing renewable energy technology projects. The variables of Payback Period (PBP), cash flow projections, savings made from transitioning (fuel cost savings and energy cost savings), Benefit-Cost-ratio, GHG emission reduction potential, etc. were analyzed. The findings revealed that the GHG emission from the campus fleet will be reduced by 100% (this will result in the removal of about 298.1 tCO₂ from the environment). Also, the fleet manager will save approximately $129,049 (88.9%) in fuel costs. Apart from these, the return on investment will be achieved in year 5 (all things being equal), but can be reduced to year 2 if the vehicles are put into constant and active use (eliminating most idle times. Also, the Sustainability Office will be making a GHG reduction revenue of $14,906.

Variational Auto-Encoders (VAEs) are deep generative models used for unsupervised learning, however their standard version is not topology-aware in practice since the data topology may not be taken into consideration. In this paper, we propose two different approaches with the aim to preserve the topological structure between the input space and the latent representation of a VAE. Firstly, we introduce InvMap-VAE as a way to turn any dimensionality reduction technique, given an embedding it produces, into a generative model within a VAE framework providing an inverse mapping into original space. Secondly, we propose the Witness Simplicial VAE as an extension of the Simplicial Auto-Encoder to the variational setup using a witness complex for computing the simplicial regularization, and we motivate this method theoretically using tools from algebraic topology. The Witness Simplicial VAE is independent of any dimensionality reduction technique and together with its extension, Isolandmarks Witness Simplicial VAE, preserves the persistent Betti numbers of a data set better than a standard VAE.

Background and purpose: Total elbow arthroplasties (TEA) aim to replicate anatomy and provide stability in the treatment of distal fractures of the humerus. In the presence of an aging population with higher functional demand, improving patients’ well-being is crucial. This study aimed to analyze patients’ reported outcomes and functional outcomes for TEA in comminuted fractures of the distal humerus and to compare these outcomes with their counterpart patients who have been treated with open reduction and internal fixation (ORIF). In addition, this study aims to compare the secondary procedures rate between the two groups.Patients and Methods: Eligible patients were those who underwent TEA or ORIF of the distal humerus and completed several patient-reported outcome (PRO) questionnaires including the Disabilities of the Arm, Shoulder, and Hand (DASH) questionnaire, 12-Item Short Form Health Survey Physical and Mental components (SF-12 P and SF-12 M, respectively) scores, visual analog scale (VAS) score for pain, and patient satisfaction ratings (1-5). A physical examination including range of motion, instability, and strength was performed for all patients. Results: This study found that patients following TEA have shown significantly lower pain levels (TEA: 3.72±2.8; ORIF 5.2±2.98, P=0.019) and higher satisfaction levels (TEA: 4.18±1.17; ORIF 3.57±1.46, P=0.035) compared with patients following ORIF. DASH score (TEA: 33.7±29.4; ORIF 39.75±24.6, P=0.31) and SF-12 score (TEA: 31.7±9.67; ORIF 31.25±10.2, P=0.85) were not statistically different between TEA and ORIF.Patients following TEA have demonstrated an advantage in flexion compared with patients following ORIF (P=0.045). Both patients following TEA and ORIF demonstrated no statistically significant difference in pronation and supination of the operated elbow compared to the contralateral side. Although, a decreased range in extension and flexion of the operated elbow compared with the contralateral side was demonstrated in both groups (extension P=0.005, flexion P<0.001). The grip Test showed no significant difference between the patients who were treated by TEA or ORIF (P=0.99). Moreover, ORIF in comminuted fractures of the distal humerus in elders may be associated with a higher complication rate compared with TEA.Conclusion: TEA following comminuted fractures of the distal humerus is associated with favorable satisfaction, pain levels, and range of motion in flexion compared with patients following ORIF of the distal humerus. Additionally, TEA may be associated with a lower rate of secondary procedures.

The validity of our universe as a three-dimensional space (3+1 in relativity) is considered a fundamental fact in physics. In this study, we show that our observed world is thus the output of a prior fundamental operator referred to as an organizer. The organizer is an expansion of projecting operators. It is been shown that identical weighted projecting operators, which are associated with identical particles, generate subspaces of entangled states, whereas groups of unequal weighted coefficients are responsible for finite-size subspaces that are associated with unidentical particles. Considering 3D-subspaces as evidence of the coefficients’ arrangement in our universe, we implement our formalism to describe the implacable vectors, location, momentum, and force within each 3D subspace. By implementing the Heisenberg relation, we drive both the classical and quantum expressions for the laws of motion.

Quantum mechanics introduces the concept of an observer who selects a measuring device and reads the outputs. This measurement process is irreversible. Lately, scholars on quantum collapse phenomena have presented a quantum-like formalism describing the measurement results as an interpretation of the measured object. Note that an observer must read the interpretation results after the interpretation process. Therefore, we propose that the definition of the concept of life should be expanded based on the following concept: A living system decreases entropy, measured results are interpreted, and an internal observer reads the commentary.

We propose a forward-only multi-layer encoding-decoding framework based on the principle of Maximal Coding Rate Reduction (MCR$^2$), an information-theoretic metric that measures a statistical distance between two sets of feature vectors up to the second moment. The encoder directly transforms data vectors themselves via gradient ascent to maximize the MCR$^2$ distance between different classes in the feature space, resulting in class-wise mutually orthogonal subspace representations. The decoder follows a process symmetric to the encoder, and transforms the subspace feature vectors via gradient descent to minimize the MCR$^2$ distance between the reconstructed data and the original data. We show that the encoder transforms data to linear discriminative representations without breaking the higher-order manifolds, and the decoder reconstructs the data with high fidelity.

As China put forward its “carbon emissions peak and carbon neutrality” goals, how to achieve carbon reduction had become a key for China’s goal. The manufacturing industry is an important source of carbon dioxide emissions. For a manufacturing country like China, adjustments in various aspects of the industry would have a huge impact on carbon emissions. As an important reform of contemporary production mode, the process of production automation in China will inevitably affect China's carbon emissions. Therefore, the analysis of the impact of production automation on carbon dioxide emissions was an important basis for judging the future carbon reduction in China. Refer to the traditional study of carbon Kuznets curve, this paper analyzed the impact of average wage on production automation and the role of production automation in the carbon Kuznets curve(CKC). This paper proposed that production automation plays a mediating role in the process of carbon emissions, and gives a verification model of the mediating role. By analyzing the relationship between average wage and production automation process, the U-shaped curve relationship between them was verified. By examining the relationship between carbon dioxide emission data and production automation industry in China, we verified that production automation plays a partial mediating role in the change of carbon Kuznets curve. Combined with the analysis of the two parts, this paper believed that with the continuous development of China's intelligent manufacturing industry, China's carbon reduction prospects were more optimistic, and there was a good industrial foundation to achieve the “carbon peaking and carbon neutrality” goals. Finally, this paper proposes policy suggestions as increase research investment in production automation, help promote the application of production automation, encourage the research and application development of low-carbon technology, especially encourage modular design, so as to give full play to the role of production automation in the process of carbon neutrality in China.

The electrochemical CO2 reduction reaction can lead to high value-added molecules production while helping decrease anthropogenic CO2 emissions. Copper can reduce CO2 to more than thirty different hydrocarbons and oxygenates, but it lacks the required selectivity. We present a computational investigation of the role of nano-structuring and alloying in Cu-based catalysts on the activity and selectivity of CO2 reduction to one-carbon products: carbon monoxide, formic acid, formaldehyde, methanol, and methane. The adsorption, activation, and conversion of CO2 were computed on monometallic and bimetallic (decorated and core-shell) 55-atom Cu-based clusters. The dopant metals considered were Ag, Cd, Pd, Pt, and Zn, located at different coordination sites. The relative binding strength of the intermediates at different applied potentials were used to identify the optimal catalyst for the selective CO2 conversion to one carbon products. It was discovered that single atom doping with Cd and Zn is optimal for the CO2 to carbon monoxide conversion. The core-shell models with Ag, Pd, and Pt provided higher selectivity for formic acid and formaldehyde. The Cu-Pt and Cu-Pd showed lowest overpotential for methane formation.

Malware complexity is rapidly increasing, causing catastrophic impacts on computer systems. Memory dump malware is gaining increased attention due to its ability to expose plaintext passwords or key encryption files. This paper presents an enhanced classification model based on One class SVM (OCSVM) classifier that can identify any deviation from the normal memory dump file patterns and detect it as malware. The proposed model integrates OCSVM and Principal Component Analysis (PCA) for increased model sensitivity and efficiency. An up-to-date dataset known as “MALMEMANALYSIS-2022” was utilized during the evaluation phase of this study. The accuracy achieved by the traditional one-class classification (TOCC) model was 55%, compared to 99.4% in the one-class classification with PCA (OCC-PCA) model. Such results have confirmed the increased performance achieved by the proposed model.

Nearly 15 million patients undergo cosmetic surgery in the United States each year, with breast augmentations such as implants, lifts, or reductions being some of the most common procedures. The most common complications of these procedures are scarring and infection at the incision site, which often necessitates expensive corrective surgery. After significant weight loss, the patient in this study underwent an elective lower body lift in conjunction with a breast reduction and nipple-areolar transplant. An autologous skin graft was used at the transplant donor site. The skin graft unfortunately necrosed, warranting the need for rapid wound closure to avoid further pain and infection. The patient was treated for eight weeks with conservative measures. After eight weeks of failed attempts to close her wound, she was referred for specialist care. Upon initial examination, the donor site wound measured 3.5 cm x 3.5 cm with no sign of epithelialization. The patient received a single dose of Wharton’s jelly flowable perinatal tissue allograft and five hyperbaric oxygen therapy treatments over seven weeks. Upon inspection at the final examination, the wound was closed entirely with 100% epithelialization overlying granulation tissue. This case study demonstrates a precedent for the application of Wharton’s jelly flowable allografts in complicated cosmetic post-surgical wounds. Future efforts will be directed at applying Wharton’s jelly allografts on a preventative basis. Preventative applications could be in stage 2 pressure sores or intra-operatively to decrease potential patient suffering, prevent emotional distress, and reduce unnecessary healthcare expenses.

This study aimed to investigate the effect of reducing the amount of organic waste on the weight of cats in Tehran. The weight of 4192 cats was measured from spring 2016 to the end of winter 2020. They were classified into 6 age groups, 2 gender groups, and 13 geographical areas. Their weight was measured for 48 months (16 seasons). The statistical parameters analysis showed no weight loss in 2017, but since 2018, cats have been losing weight every year. They had lost about 178g of their weight in 2018. The sharpest annual decrease was observed in 2019 when about 301g of weight loss was recorded. In the winter of 2020, 115g of weight loss took place. In the spring of 2017, no weight change was observed, but in the spring of 2018, the cats lost 155g of their weight. Their weight loss intensified in the spring of 2019 and about 299g of weight loss was observed. In the summer of 2017, as in the spring of the same year, no weight loss was recorded, but for the summer of 2018, the weight loss was evident and about 205g of the weight of the cats had been reduced. The weight loss in the summer of 2019 not only continued but intensified and about 304g of weight loss was recorded for cats. Weight change was not observed in the fall of 2017 as in the spring and summer of the same year. In the fall of 2018, weight loss was recorded for cats. They had lost about 324g of their weight in the fall of 2018. Also, they experienced a weight loss of about 218g in the fall of 2019. During the spring, summer, and autumn of 2017, no weight loss was observed in the cats for the winter of 2018, but in the winter of 2019, the cats faced the most severe weight loss (seasonally). They lost about 401g of weight in the winter of 2019. Of course, in the winter of 2020, about 186g of weight loss was observed in cats. The results showed that female cats did not lose weight in 2017 but experienced weight loss in 2018 with a weight loss of 181g. The weight loss of females intensified in 2019 and 294g of weight loss was recorded. Female cats lost 186g of their weight in the winter of 2020. Male cats did not lose weight like female cats in 2017. But in 2018, a weight loss of 166g was observed in male cats. The weight loss of male cats continued in 2019 and 311g of weight loss was recorded for them. However, in 2020, unlike females, weight loss was not observed in male cats. It can be said that both sexes lost more weight in the winter of 2019 than in other seasons. In 2017, weight loss was observed only for the region of 10, and in the same year, weight gain was recorded for the region of 15. But in 2018, except for regions 3, 4, 15, and 19, weight loss was observed in other regions. In 2019, the weight loss of cats spread and weight loss was observed in all regions except the region of 12. In winter 2020, weight loss was recorded only in the region of 4. In the end, it can be concluded that the weight of cats has decreased since the spring of 2018 because the beginning of the decrease in the amount of organic waste has been recorded since the winter of 2018. So, there is a direct relationship between the weight of cats and the amount of organic waste (access to food). The amount of garbage has been decreasing since the winter of 2018, and the average weight of cats has also been decreasing since the spring of 2018 due to the decrease in access to food.

Recent wastewater testing suggests the poliovirus is reemerging, raising questions about the efficacy of the current inactivated polio vaccine and mass vaccination to eradicate poliomyelitis. The present study reassessed reported outcomes from the placebo-control study of the 1954 Salk inactivated poliomyelitis vaccine field trial, which studied a population of 1,829,916 U.S. school children from the first three grades. The placebo-control study of the trial reported that the polio vaccine was 80% to 90% effective in reducing cases of laboratory confirmed paralytic poliomyelitis, 60% to 70% effective against type 1 of the virus, and greater than 90% effective against types 2 and 3 of the poliovirus. However, these outcomes are reported as relative risk reductions, and the absolute risk reductions of the 1954 polio vaccine field trial were never reported to the public. The present paper’s analysis reveals to the public for the first time that the inactivated poliomyelitis vaccine's absolute risk reduction of laboratory confirmed paralytic poliomyelitis in the placebo-control study is 0.01% to 0.02%, an extraordinarily low clinical effect that impugns the Salk polio vaccine’s reported effectiveness. Furthermore, absolute risk reductions for the three poliovirus types are 0.01%, 0.00%, and 0.01%, respectively. Outcome reporting bias in the 1954 inactivated poliomyelitis vaccine field trial casts doubt on eradication of the poliovirus through mass vaccination.

Electronic structure calculations have been carried out to examine the effect of protonation and water molecules on the heme group of peroxidases in different redox (ferric, ferrous, compounds I and II) and spin states. Shared geometries, spectroscopic properties at Soret region, and thermodynamics of peroxidases are discussed. B3LYP and M06-2X density functionals with different basis sets were employed on a common molecular model of the active site (Fe-centred porphine and proximal imidazole). Computed Gibbs free energies indicate that the corresponding aquo complexes are not thermodynamically stable, supporting the five-coordinate Fe(III) centre in native ferric peroxidases, with a water molecule located at a non-bonding distance. Protonation of the ferryl oxygen of compound II is discussed in terms of thermodynamics, Fe–O bond distances, and redox properties. It is demonstrated that this protonation is necessary to account for the experimental data and computed Gibbs free energies that reveal pKa values of compound II about 8.5 – 9.0. Computation suggests that the origin of the general oxidative properties of peroxidase species, as well as their reactivity towards water and protons and Soret spectral properties, mostly resides on the iron porphyrin and its proximal ligand histidine.

The prospects of processing blast furnace and steelmaking sludge using Waelz process in a laboratory rotary kiln is shown. The influence of varying thermal treatment modes, furnace atmosphere and type of reducing agents on the level of zinc reduction from sludges was analyzed. In general, the blast furnace sludge contains a high portion of iron (approx.48 wt. %) and can be reused as a charge after satisfactory zinc reduction. It was found that N- atmosphere and high content of the graphite or coke oven reducing agent in combination with high temperature can reduce the content of Zn in the sludge to 0.08 wt. % at 1200 °C for mixture of steelmaking and blast furnace sludge. A significant reduction in the Zn content to 0.66 wt. % occurs at 1100 °C. The content and type of reducing agent play an important role; graphite has shown a better reducing ability compared to coke oven dust. When nitrogen is used, zinc is reduced even without an additional reducing agent, since the carbon contained in the sludge is made use of for the reduction. In an air atmosphere, without the use of a reducing agent, there was no reduction in the Zn content.

Cardiac monitoring based on wearable photoplethysmography (PPG) is widespread because of its usability and low cost. Unfortunately, PPG is negatively affected by various types of disruptions, which could introduce errors to the algorithm that extracts Pulse Rate Variability (PRV). This study aims to identify the nature of such artifacts caused by various types of factors under the conditions of precisely planned experiments. We also propose methods for their reduction based solely on the PPG signal while preserving the frequency content of PRV. The accuracy of PRV derived from PPG was compared to Heart Rate Variability (HRV) derived from the accompanying recorded ECG. The results indicate that filtering PPG signals using the Discrete Wavelet Transform and its inverse (DWT/IDWT) is suitable for removing slow components and high-frequency noise. Moreover, the main benefit of amplitude demodulation is better preparation of the PPG to determine the duration of pulse cycles and reduce the impact of some other artifacts. Postprocessing applied to HRV and PRV indicates that the correction of outliers based on local statistical measures of signals and the AR model is only important when PPG is of low-quality and has no effect under good signal quality. The main conclusion is that DWT/IDWT, followed by amplitude demodulation, enables the proper preparation of the PPG signal for the subsequent use of PRV extraction algorithms. However, postprocessing in the proposed form should be applied more in the situations of observed strong artifacts than in motionless laboratory experiments.

In Qinglong ore field, paleo-oil reservoir is found to be associated with antimony deposits, and they have close genetic relationship. In this study, aromatics geochemistry of paleo-oil reservoir bitumen was studied to further discuss the thermochemical sulfate reduction (TSR) reaction and the mechanism of antimony mineralization. A total of 124 aromatic compounds were identified by Gas chromatography-mass spectrometry (GC–MS) analysis in bitumen samples, including abundant phenanthrene series, dibenzothiophene series, fluoranthene series, chrysene series, and a small number of fluorene series, naphthalene series, dibenzofuran series, biphenyl series, triaromatic steroid series. Aromatic parameters such as trimethylnaphthalene index (TMNr), methylphenanthrene index (MPI), methylphenanthrene distribution fraction (MPDF, F1 and F2), methyldibenzothiophene parameter (MDR), C28TAS-20S/(20R+20S), and benzofluoranthene/benzo[e]pyrene indicate Qinglong paleo-oil reservoir is in over maturity level. The abundance of phenanthrene and chrysene aromatic compounds and a small amount of naphthalene series, benzofluoranthene, fluoranthene, pyrene, anthracene, retene, perylene and biphenyl suggest that the parent material of the paleo-oil reservoir was mainly low aquatic organisms, mixed with a small amount of higher plant. The detected a certain number of compounds, such as retene, triaromatic steroid series and perylene, the ternary diagram of DBF–DBT–F and binary plot of Pr/Ph–DBT/P, DBT/(F+DBT)–DBF/(F+DBF) and Pr/Ph–DBT/DBF reveal that the source rock of the paleo-oil reservoir was formed in the marine environment of weak oxidation and weak reduction. The comprehensive analysis shows that the Qinglong paleo-oil reservoir originated from Devonian source rocks, just like other paleo-oil reservoirs and natural gas reservoirs in the Nanpanjiang basin. Abundant dibenzothiophene series were detected, indicating that the paleo-oil reservoir underwent a certain degree of TSR reaction. We believe that the paleo-gas reservoir formed by the evolution of paleo-oil reservoir participated in antimony mineralization, that is, hydrocarbon organic matter acted as reducing agent and transformed SO42− in oilfield brine into H2S through TSR, providing reduced sulfur and creating environmental conditions for mineralization.

Background Nitrous Oxide (N₂O) is a dissociative anaesthetic that is sometimes used recreationally. The prevalence of N₂O use is difficult to quantify but appears to be increasing. Research on N₂O harms and application of harm reduction strategies are limited. The aim of this mixed method systematic review was to collate and synthesise the disparate body of research on recreational nitrous oxide use to inform harm reduction approaches tailored for young people. Methods To identify publications reporting recreational use of N₂O, a search of public health, psychology and social science databases was conducted. Databases included PubMed, CIHNAL, PsycINFO, Scopus and Web of Science. Gray literature and Google advanced search were also used. Due to limited published literature on the recreational use of N₂O, no limit was placed on publication date or study type. A thematic synthesis extracted descriptive and analytical themes from the selected studies. Quality appraisal was conducted using the CASP Tool for Qualitative studies and the Joanna Briggs Institute case report assessment tool Results The search retrieved 407 reports. Thirty-four were included in the final analysis including sixteen case reports. The included studies were primarily concerned with raising awareness of the apparently increasing use and subsequently increasing harms of recreational N₂O use. There was limited reference to policy or legislative responses in any published studies, no suggestions for harm reduction strategies or application of service level responses. In general, individuals lack awareness of N2O related harms. Conclusion The review found three key areas that deserve further consideration including: 1) policy, 2) service delivery, and 3) harm associated with N₂O use. We recommend a top-down (policy) and bottom-up (services delivery/services users) approach to harm reduction for N₂O use which also includes further consultation and research with both groups. Future research could explore young people’s experience of N₂O use including benefits and problems to inform contextually relevant harm reduction strategies.

Digital twins are the foundation of autonomous off-road vehicles. Dynamic reduction methods are one of several ways to develop digital twins for off-road vehicles. The article commences with a comprehensive overview of the most widely used dynamic reduction methods and then introduces performance metrics for assessing their efficacies in the context of digital twins. The paper additionally includes a detailed mathematical derivation of the state-space representation for reduced-order finite element models. The state-space representation of the reduced finite element models facilitates their export to problem-solving environments for dynamic analysis. The state-space models are eventually solved utilizing the built-in libraries of numerical solvers in textual and graphical programming platforms. In addition, the article identifies the set of solvers that best suit the simulation of virtual models for off-road vehicles. This article also includes an evaluation of the simulation results of digital models with modes ranging from 0 to 30 Hz. In addition, the article demonstrates the lower bound of the frequency range necessary and sufficient to be retained in off-road vehicle virtual models. Finally, the paper presents the simulation outcomes for digital models of commercial off-road vehicles with custom-built control, electrical, and control systems.

This transdisciplinary review of research about international cooperation on social and environmental change builds the case for replacing Sustainable Development as the dominant framework for an era of increasing crises and disasters. The review is the output of an intentional exploration of recent studies in multiple subject areas, based on the authors’ decades of work in related fields since the Rio Earth Summit 30 years ago (rather than a keyword search of databases). It summarizes the research which documents failure to progress towards the Sustainable Development Goals (SDGs). Consequently, the extensive scholarship critiquing the conceptual framework behind those ‘Global Goals’, and the economic ideology they arose from and support, is used to explain that failure. Although the pandemic set back the SDGs, it further revealed the inappropriate strategy behind those goals. This suggests the Global Goals constitute an ‘own-goal’ scored against people and nature. From this conclusion, alternative frameworks for organizing action on social and environmental issues become more important and are therefore briefly reviewed. It is argued that such a future framework must relate a new eco-social contract between citizen and state, and engage existing organizations and capabilities that are relevant to an increasingly disrupted world. Therefore, the case is made for considering an upgraded form of Disaster Risk Management (DRM) as an overarching framework. The proposed upgrades include detaching from economic ideologies, and recognizing that a wider metadisaster from climate chaos may reduce the future availability of external support. Therefore, self-reliant resilience and locally-led adaptation are identified as important to the future of DRM. Some options for professionals continuing to use the term sustainability, such as this journal, are discussed.

This paper presents a study on the idle vibration reduction of a diesel sport utility vehicle (SUV). To reduce idle vibration, the transmission paths of vibration from the engine to the driver seat floor were investigated with the vehicle components related to idle vibration. Furthermore, operational deflection shape (ODS) tests were conducted to visualize the vibration shapes during engine idling. Experimental modal analyses were performed to obtain the natural frequencies and mode shapes. Through the ODS and modal tests, the vibration characteristics of the diesel SUV during idling were identified. Considering these vibration characteristics, a multi-body dynamic model for the diesel SUV described by differential equations of motion was established to evaluate the idle vibration. To implement the dynamic model effectively, the equivalent stiffnesses and damping coefficients included in the model were determined experimentally or analytically. The established dynamic model was verified by comparing the natural frequencies and idle vibration levels between simulations. Using this dynamic model, we analyzed the effects of various design variables on idle vibration and obtained an optimal design for reducing the idle vibration level. Finally, we present a design guide to reduce the idle vibration for diesel SUVs.

This work discussed the advantages of reducing copper in molten copper slag with low S content. FactSage calculated the distribution of copper at equilibrium under different sulfur content. The effect of sulfur content on copper recovery under different oxygen partial pressures was pointed out. The effect of sulfur content on copper recovery in the actual reduction process was explored through experimental research. Under the condition of low sulfur, the Recovery of copper and the stability of the experiment have an ideal results.

Hazelnut is a widespread nut species, especially in Europe, that can be consumed raw or roasted, due to its pleasant taste and nutritional properties. Despite the renowned beneficial properties, hazelnuts contain several proteins capable of inducing food allergy in sensitized individuals such as Cor a 2 (profilin), Cor a 8 (lipid transfer protein), Cor a 9 (11S seed storage globulin, legumin-like) and Cor a 11 (7S seed storage globulin, vicilin-like). In the present paper we investigated the effectiveness of autoclave based treatments in decreasing the allergic potential of hazelnut as also assessed by submitting the treated material to in vivo skin prick test and to in vitro immunoblot analysis with sera of allergic individuals exposed to the treated food material. This preliminary analysis shows that autoclave treatment, preceded by hydration and/or followed by drying, seems to be a promising approach and appears to be effective in reducing the allergenicity of hazelnut in most patients, probably due to the denaturation of most major and minor allergenic proteins. This work will open to the opportunity to produce, in perspective, hypoallergenic hazelnut derivatives tolerated by the allergic subjects.

Recently, electrocatalysts for oxygen reduction reactions (ORRs) as well as oxygen evolution reactions (OERs) hinged on electrospun nanofiber composites have attracted wide research attention. Transition metal elements and heteroatomic doping are important methods used to enhance their catalytic performances. Lately, the construction of electrocatalysts based on metal-organic framework (MOF) electrospun nanofibers has become a research hotspot. In this work, bimetallic NixCoy-ZIF nanocrystals were synthesized in an aqueous solution, followed by NixCoy-ZIF/PAN electrospun nanofiber precursors, which were prepared by a simple electrospinning method. Bimetal (Ni-Co) porous carbon nanofiber catalysts doped with nitrogen, oxygen, and sulfur elements were obtained at high-temperature carbonization treatment in different atmospheres (Ar, Air, and H2S), respectively. The morphological properties, structures, and composition were characterized by SEM, TEM, SAED, XRD, and XPS. Also, the specific surface area of materials and their pore size distribution was characterized by BET. Linear sweep voltammetry curves investigated catalyst performances towards oxygen reduction and evolution reactions. Importantly, Ni1Co2-ZIFs/PAN-Ar yielded the best ORR activity, whereas Ni1Co1-ZIFs/PAN-Air exhibited the best OER performance. This work provides significant guidance for the preparation and characterization of multi-doped porous carbon nanofibers carbonized in different atmospheres.

Fibroepithelial lesions (FL) of the breast, in particular Phyllodes tumors (PT) and fibroadenomas, pose a significant diagnostic challenge. There are no generally accepted criteria that distinguish benign, borderline, malignant PT, and FA. Combined genome-wide DNA methylation and copy number variant (CNV) profiling is an emerging strategy to classify tumors. We compiled a series of patient-derived archival biopsy specimens reflecting the FL spectrum and histological mimickers including clinical follow-up data. DNA methylation and CNVs were determined by well-established microarrays. Comparison of the patterns with a pan-cancer dataset assembled from public resources including "The Cancer Genome Atlas" (TCGA) and "Gene Expression Omnibus" (GEO) suggests that FLs form a methylation class distinct from both control breast tissue as well as common breast cancers. Complex CNVs were enriched in clinically aggressive FLs. Subsequent fluorescence in situ hybridization (FISH) analysis detected respective aberrations in the neoplastic mesenchymal component of FLs only, confirming that the epithelial component is non-neoplastic. Of note, our approach could lead to the elimination of the diagnostically problematic category of borderline PT and allow for optimized prognostic patient stratification. Furthermore, the identified recurrent genomic aberrations such as 1q gains (including MDM4), CDKN2a/b deletions and EGFR amplifications may inform therapeutic decision-making.

Environmental tax is the climate policy that offers, in theory, the easiest way for carbon reduction. But in practice, implementation has proven complicated despite public demand for policy action on climate change. This research investigates to reframe environmental taxes in ways more personally engaging to create a moral foundation, and massive participation. As people show rising demand, we aimed to design a tool that responds to public expectations and operates directly at source on emission reducers, viz the trees. Drawing on research from environmental taxes and the evidence of measures taken, we reasoned that an environmental fiscal policy may not intend necessarily to punish the “bads”, but rather might reward the positive attitude and direct it to act. Consequently, we focused on tax reliefs and designed Green Aid, that can address people’s attitude to take active participation into account by incorporating virtuous behaviours into tax relief. Green Aid Tax relief works embedded in the Green Aid Participation Scheme that bears directly on a source of environmental recovery and organizes the global call to public action in a sustained, structured, and collective participation to forestation. Green Aid bridges the action of contributing to carbon reduction with immediate, tangible, and direct benefits. It can be an alternative environmental tax, able to address and operate directly at source on emission reducers and secure effectiveness in carbon reduction and efficiency in terms of public acceptance and viability at a global level.

Research for a theory of quantum gravity has recently led to the use of presheaf topos. Quantum uncertainty is linked to the truth values of intuitionistic logic. This paper proposes transposing this model into a classic probability context, that of conditional mathematical expectations. A simulation of Brownian motion is offered for illustrative purposes.

This study investigated the development of Aedes aegypti density in houses of the urban locality of Poblado Miguel Alemán Valdes, in the Sonora state of Mexico, after application of 1% propoxur paint as full wall coverage (IP) and targeted indoor painting (IP 1m) in comparison to IRS with propoxur 70% WP (full wall coverage). The 1% propoxur paint was applied by the homeowners by brushing and rolling at the recommended dose of 1L/8 m², equivalent to 1.5 g a.i./m², while IRS was conducted by professionals with Propoxur 70% WP at a dose of 1 g a.i./m². Adult mosquito surveys were conducted in a random sample of houses in each block one week before the interventions and at week 1, month 1 to 4, month 6, month 9 and month 12 post-interventions. All three propoxur based treatments provided similar reductions (43.7%, 44.9% and 41.3% for IP, IP 1m and IRS respectively) in the fraction of houses positive in female Aedes aegypti resting indoor and outdoor as one year average of 8 follow up surveys. Indoor resting density of Aedes females during the one-year evaluation was reduced by 77.5% through IP followed by IP 1m with 64.2% reduction and 30% reduction with IRS. Culex mosquitoes’ interior density was affected as well by the insecticide treatments with similar average reductions for IP 1m (50.0%) and IRS (57.8%) in comparison with control. Aedes breeding was impacted by the insecticide paint in similar extent for both interventions, expressed by a substantial reduction of the House Index (20.1% IP, 31.2% IP 1m) and especially the Container Index (51.8% IP, 61.7% IP 1m) during the one-year surveys in comparison to control. In contrast, IRS treated block experienced an increase in both indexes. However, despite IP and IP 1m impacted in Aedes adult and immature indexes with noticeable reductions, the differences in all cases were not significative among the different insecticide treatments. The low sample size and mosquito population levels may have influenced the statistical outcomes. More than 80% of the interviewed residents were satisfied with the effectiveness of the paint and IRS treatments. The determination of the blood cholinesterase activity of tested individuals after the use of the carbamate paint and IRS in this study did not exceed acceptable inhibition limits. This study suggests that the application of propoxur paint by homeowners as full house coverage or as targeted indoor painting can be a safe and accepted intervention method for density reduction of Aedes aegypti populations in urban environments.

Abstract: Urban regeneration decision-making is a complex process, as it involves a wide range of decision-makers, public-private partnerships in finance and implementation, including the inevitable considerable amount of risk on a long-term basis. There are a multitude of stakeholders, the citizens being the key stakeholders. It is necessary to involve the citizens in the planning process. Such involvement allows the communities to express their needs and aspirations, which is useful in the policymaking, delivery of planning programs, and in the monitoring process. In such a context, Factor analysis was the statistical technique used (1) Carry out factor analysis based on the principal component analysis method using the software XLSTAT 2021.4.1.1205 - (2) Construct a factor model of Urban Regeneration. (3) Interpret and label the factor dimensions. The results of the analysis indicated that the first two principal components accounted for 60.04% of the total variance of the original dataset. All variables seemed to be, positively correlated to each other and contributed similarly to principal components PC1 &PC2. The observations were well clustered; except for very few outliers. The limitation of the work was that the perceptions of the citizens were limited to the variables derived by the researcher.

This paper presents three types of sliding mode controllers for a magnetic levitation system. First, a proportional-integral sliding mode controller (PI-SMC) is designed using a new switching surface and a proportional plus power rate reaching law. The PI-SMC is more robust than a feedback linearization controller in the presence of mismatched uncertainties and outperforms the SMC schemes reported recently in the literature in terms of the convergence rate and settling time. Next, to reduce the chattering phenomenon in the PI-SMC, a state feedback-based discrete-time SMC algorithm is developed. However, the disturbance rejection ability is compromised to some extent. Furthermore, to improve the robustness without compromising the chattering reduction benefits of the discrete-time SMC, mismatched uncertainties like sensor noise and track input disturbance are incorporated in a robust discrete-time SMC design using multirate output feedback (MROF). With this technique, it is possible to realize the effect of a full-state feedback controller without incurring the complexity of a dynamic controller or an additional discrete-time observer. Also, the MROF-based discrete-time SMC strategy can stabilize the magnetic levitation system with excellent dynamic and steady-state performance with superior robustness in the presence of mismatched uncertainties. The stability of the closed-loop system under the proposed controllers is proved by using the Lyapunov stability theory. The simulation results and analytical comparisons demonstrate the effectiveness and robustness of the proposed control schemes.

(1) Background: We reviewed the logistics of the implementation of pathogen inactivation (PI) using the INTERCEPT Blood System™ for platelets and the experience with routine use and clinical outcomes in the patient population at the Sírio-Libanês Hospital of São Paulo, Brazil. (2) Methods: Platelet concentrate (PC), including pathogen reduced (PR-PC) production, inventory management, discard rates, blood utilization, and clinical outcomes were analyzed over the 40 months before and after PI implementation. Age distribution and wastage rates were compared over the 10 months before and after approval for PR-PC to be stored for up to 7 days. (3) Results: A 100% PR-PC inventory was achieved by increasing double apheresis collections and production of double doses using pools of two single apheresis units. Discard rates decreased from 6% to 3% after PI implementation and further decreased to 1.2% after 7-day storage extension for PR-PCs. The blood utilization remained stable, with no increase in component utilization. A significant decrease in adverse transfusion events was observed after the PI implementation. (4) Conclusion: Our experience demonstrates the feasibility for Brazilian blood centers to achieve a 100% PR-PC inventory. All patients at our hospital received PR-PC and showed no increase in blood component utilization and decreased rates of adverse transfusion reactions.

Compared with precious metal catalysts, non-platinum catalysts have the advantages of low cost and high performance. Among them, the activated carbon (AC) with a large specific surface area (SSA) can be used as a carrier or as a carbon source of nonprecious metal/carbon system catalyst at the same time. Therefore, this paper uses cheap pine peel bio-based materials to prepare large surface area activated carbon and then compound with cobalt phthalocyanine (CoPc) to obtain a high-performance cobalt/nitrogen/carbon catalyst. The merits include AC@CoPc composite catalysts are prepared by precisely controlling the composite proportion of AC and CoPc, the atomically dispersed Co nanoparticles form and synergistically with N promote the exposure of CoNx active sites, and the Eonset of the catalyst treated with a composite proportion of AC and CoPc of 1 to 2 at 800 °C (AC@CoPc-800-1-2) is 1.01 V, which is higher than Pt/C (20 wt%) catalyst. Apart from this, the stability is 87.8% in 0.1 M KOH after 20000 s testing in compared with other AC@CoPc series catalysts and Pt/C (20 wt%) catalyst. Considering from the performance and price of the catalyst in practical application, these composite catalysts combine biomass carbon materials with phthalocyanine series, which will be widely used in the area of nonprecious metal catalysts.

Under the goal of carbon peak and carbon neutrality, the carbon emission reduction of the automobile industry has attracted more and more attention in recent years. Electric vehicle has the dual attributes of power load and energy storage unit. With the increase of the number of electric vehicles, reducing carbon emissions through the collaborative interaction between electric vehicle and power network will become an important way to control carbon emissions in the automotive field. In this study, an optimization model of emission reduction benefits based on integrated development of electric vehicle and power grid is proposed, which explores the best technical way of synergy between power grid and electric vehicle, achieves the best carbon reduction effect and provides a model basis for large-scale demonstration application. Numerical simulations based on the real case in Beijing are conducted to validate the effectiveness of the proposed method.

Improving the operational reliability of nuclear power plants, combined heat and power plants (CHP), as well as oil and gas pipelines is a priority task in the development of a variable-speed drive for lock valves used at these facilities. The paper analyzes technical requirements for such devices; the motor has been selected, its electrical equilibrium and moment equations have been obtained; recommendations for the selection of the kinematic drive scheme have been formulated. Based on the theoretical data obtained, a prototype has been developed, manufactured and tested.

In this manuscript we use an exactly solvable stochastic binary model for regulation of gene expression to analyse the dynamics of response to a treatment aiming to modulate the number of transcripts of RKIP gene. We demonstrate the usefulness of our method simulating three treatment scenarios aiming to reestablish RKIP gene expression dynamics towards pre-cancerous state: i. to increase the promoter’s ON state duration; ii. to increase the mRNAs’ synthesis rate; iii. to increase both rates. We show that the pre-treatment kinetic rates of ON and OFF promoter switching speeds and mRNA synthesis and degradation will affect the heterogeneity and time for treatment response. Hence, we present a strategy for reducing drug dosage by simultaneously targeting multiple kinetic rates. That enables a reduction of treatment response time and heterogeneity which in principle diminishes the chances of emergence of resistance to treatment. This approach may be useful for inferring kinetic constants related to expression of antimetastatic genes or oncogenes and on the design of multi-drug therapeutic strategies targeting master regulatory genes.

This paper focuses on parametric model order reduction (PMOR) of guided ultrasonic wave propagation and its interaction with damage in a fiber metal laminate (FML). Structural health monitoring in FML seeks to detect, localize and characterize the damage with high accuracy and minimal use of sensors. This can be achieved by the inverse problem analysis approach which employs the signal measurement data recorded by the embedded sensors in the structure. The inverse analysis requires to solve the forward simulation of the underlying system several thousand times. These simulations are often exorbitantly expensive and triggered the need for improving their computational efficiency. A PMOR approach hinged on the proper orthogonal decomposition method is presented in this paper. An adaptive parameter sampling technique is established with the aid of a surrogate model to efficiently update the reduced-order basis in a greedy fashion. A numerical experiment is conducted to illustrate the parametric training of the reduced-order model. The results show that the reduced-order solution based on the PMOR approach is accurately complying with that of the high fidelity solution.

Steels studs are an inevitable part of drywall construction as they are lightweight and offer the required structural stability. However, the studs act as sound bridges between the plasterboards reducing the overall sound insulation of the wall. Overcoming this often calls for wider cavity walls and complex stud decoupling fixtures that increase the installation cost while reducing the floor area. As an alternative approach, this research reveals the potential of perforated studs to improve the acoustic insulation of drywall partitions. The acoustic and structural performance is characterized using a validated finite element model that acted as a prediction tool in reducing the number of physical tests required. The results established that an acoustic numerical model featuring fluid-structure-interaction can predict the weighted sound reduction index of a stud wall assembly at an accuracy of ±1 dB. The model was used to analyze six perforated stud designs and found to outperform the sound insulation of non-perforated drywall partitions by reducing the sound bridging. Overall, the best performing perforated stud design was found to offer improvements in acoustic insulation of up to 4 dB, while being structurally compliant.

The current paper is devoted to the introduction of simpler Eulerian variational principles from which all the relevant equations of non-barotropic stationary magnetohydrodynamics can be derived for magnetic fields which lie on surfaces. A variational principle is given in terms of three independent variables for stationary non-barotropic magnetohydrodynamic flows. This is a smaller number of variables than the eight variables which appear in the standard equations of non-barotropic magnetohydrodynamics which are the magnetic field, the velocity field, the specific entropy and the density. We further investigate the case in which the flow along magnetic lines is not ideal.

Understanding of the decisive role of the interaction mechanism and kinetics in the combustion processes is highly relevant for the elaboration of optimal conditions for obtaining Mo-Cu composite powders. From this perspective, the efficient delivery of the reduction mechanism of copper and molybdenum oxides with combined Mg + C reducing agents at high heating rates is crucial to develop a valuable approach for the combustion synthesis of Mo-Cu composite powders. Herein, we shed light on the mechanism of the reactions in all the studied binary, ternary and quaternary systems contemporaneously demonstrating the effect of the heating rate on the conversion degree. The combination of two highly exothermic and speedy reactions (MoO3+3Mg and CuO+Mg vs MoO3+CuO+4Mg) led to a slow interaction with weak self-heating (dysynergistic effect) due to a change in the reaction mechanism. On the other hand, it has been shown that during the simultaneous utilization of the Mg and C reducing agents, the process begins exclusively with carbothermic reduction, and at relatively high temperatures it continues with magnesiothermic one. The effective activation energy values of the magnesiothermic stages of the studied reactions were determined by Kissinger isoconversional method.

Pulsed thermography is a commonly used non-destructive testing method, and is increasingly studied for advanced materials such as carbon fiber-reinforced polymer (CFRP) evaluation. Different processing approaches are proposed to detect and characterize anomalies that may be generated in structures during the manufacturing cycle or service period. In this study, we used a type of matrix decomposition using Robust-PCA via Inexact-ALM in our experiment. We investigate this method as a pre-and post-processing method on thermal data acquired by pulsed thermography. We employed state-of-the-art methods, i.e., PCT, PPT, and PLST, as the main process. The results indicate that pre-processing on thermal data can elevate the defect detectability while post-processing, in some cases, can deteriorate the results.

As a result of rapid population growth, an exponentially growing human population, and industrial expansion, it has become increasingly difficult to manage municipal solid wastes throughout the world. Decentralized waste management systems have created difficult situations in developing countries such as Malaysia. Wastes generated in the country, due to various cultural, social, and religious activities, organic and contributing to environmental pollution (air, water, and soil) and human health troubles. A questionnaire survey was participated by 220 construction professionals in Malaysia using structured and semi-structured methods. The framework was assessed using A partial least square structural equation modeling (PLS-SEM) to target sustainable development goals (SDG). Statistical analysis results indicate a significant effect between SCW management, since(r(270)=.687, P&lt;0.001). Improving factors has strong relationship with SCW management, since(r(270)=.723, P&lt;0.001). The mediation results also suggested a significant indirect positive effect of improving factors drivers on SCW management through policy-related factors sinceβ=0.688, t=8.254, P&lt;0.001, 95% CI for β=0.536,0.866. Finally, policy-related factors construct has a strong relationship with SCWM) management, since(r(270)=.811, P&lt;0.001) With the R Square of 0.787 and 0.785. The developed framework can improve construction waste management in the construction industry and enhance construction waste management to achieve global sustainable development goals. The findings show that one of the most critical issues of enhancing profitability is using preventive policies to reduce construction waste. This study could guide construction industry stakeholders in identifying the different waste management features during a building project's construction and design stage

This paper aims to delve into how gender dimensions observed before, during and after a disaster, have been addressed in two internationally recognised frameworks developed for reducing risks of disasters: Hyogo Framework Action (2005-2015) and Sendai Framework for Disaster Risk Reduction (2015-2030). Building on a systematic review, we evaluate 33 scholarly peer-reviewed journal articles, including book chapters and websites in areas of gender, disaster risk reduction and vulnerability. This study documents a comparative picture of these two frameworks and shows the practical implications of the Sendai Framework for Disaster Risk Reduction (SFDRR) by addressing women’s empowerment in the light of their active participation in disaster risk reduction process. The findings of the study suggest that the frameworks have discussed the reduction of women’s socioeconomic vulnerabilities, as well as encouraged their empowerment. Comparing the two frameworks, it appears in the current study that there has been a significant gap in the existing literature that does not explicitly document comparing and contrasting features of a gender lens in the policy documents.

This work is driven by a practical question, corrections of Artificial Intelligence (AI) errors. Systematic re-training of a large AI system is hardly possible. To solve this problem, special external devices, correctors, are developed. They should provide quick and non-iterative system fix without modification of a legacy AI system. A common universal part of the AI corrector is a classifier that should separate undesired and erroneous behavior from normal operation. Training of such classifiers is a grand challenge at the heart of the one- and few-shot learning methods. Effectiveness of one- and few-short methods is based on either significant dimensionality reductions or the blessing of dimensionality effects. Stochastic separability is a blessing of dimensionality phenomenon that allows one-and few-shot error correction: in high-dimensional datasets under broad assumptions each point can be separated from the rest of the set by simple and robust linear discriminant. The hierarchical structure of data universe is introduced where each data cluster has a granular internal structure, etc. New stochastic separation theorems for the data distributions with fine-grained structure are formulated and proved. Separation theorems in infinite-dimensional limits are proven under assumptions of compact embedding of patterns into data space. New multi-correctors of AI systems are presented and illustrated with examples of predicting errors and learning new classes of objects by a deep convolutional neural network.

Background: This article evaluates the perception of drug use control and strategies in Valencia City (Spain) in a general and clinical population, in two independent studies. Material and Methods: 1071 people participated. In the Study 1 (n= 924) the entire sample came from general population (GP), and in the Study 2 (n=147), 68 were drug users being treated in an Addictive Behaviors Unit (ABU), and 79 people of the GP. The drug use control perception and strategies in both subgroups were compared. The participants filled in the Drug Use Strategies Scale and a Drug Use Survey. Results: A high level of perception of drug control in GP was obtained (72,7% in the Study 1 and 67,5% in the Study 2), and 32.5% in ABU subgroup. People in the PG and drug users in treatment differ in some control strategies. A predictive profile of the perception of control was obtained for the Study 2. Conclusion: The high degree of perception of controlling drug use in the GP, and partially in drug users being treated, and the specific control strategies reported suggests that moderate use and drug control strategies are a great value alternative to bear in mind compared to abstinence.

Sulfur dioxide (SO2) reduction remains an area of global necessity further enhanced by the current international focus on pandemic diseases mitigation, elimination of air pollution, and promotion of renewable green energy. The dynamics of chemical bond-strength breaking and reformation in the transition state (TS) is a fundamental process in the reduction of SO2 by CO. Density Functional Theory (DFT) has been used to determine optimal TS reaction pathway via a novel triple-hybrid catalyst utilizing doubly-charged negative atomic V, Mn, and Au. The triple-hybrid catalyst is furthermore tailored to the subsequent minimization of each individual step of the 3-Step SO2 reduction by CO chemical reaction. Each optimized step 1, 2, and 3 is minimized with doubly-charged V, Mn, and Au, respectively, with TS barrier reductions ranging from 1.18 eV to 0.002 eV. Super-benzene, armchair (6, 6) single wall carbon nanotube, and fullerene TS reaction pathways have also been calculated to compare the nanoscale catalytic effectiveness with that of the atomic scale transition metals.

People living in areas of significant seismic risk seldom undertake sufficient preparations to safeguard their family. This is most problematic in remote communities such as those along the Dead Sea Fault, Israel, where self-reliance is a key factor in coping with disasters. To facilitate individual and familial involvement in earthquake preparedness in remote areas, we designed a tool for self-assessment of risk and preparedness. The personalized risk assessment is based on national hazard and building standards, and on personal input regarding structure characteristics. The risk and preparedness evaluations enhance awareness and provide immediate feedback to help users improve familial preparedness. Spatial analysis of the data collected is used to form high-resolution maps that expose specific challenges for emergency response. A study conducted in the town of Mitzpe Ramon exposed neighborhoods with relatively high risk of damage and low preparedness. Integrating these results with seasonal stress-factors such as peak tourism and extreme weather, provides new and important insights on the ability of the local community and emergency forces to cope with multi-hazard situations. Analysis of the heterogeneous distribution of expected hardship within a community should be implemented world-wide to improve risk mitigation.

Slope failures pose a substantial threat to mining activity due to their destructive potential and high probability of occurrence on steep slopes close to limit equilibrium conditions, often found both in open pits and in waste and tailing disposal facilities. The development of slope monitoring and modeling programs usually entails the exploitation of in situ and remote sensing data together with the application of numerical modeling, and it plays an important role in the definition of prevention and mitigation measures aimed at minimizing the impact of slope failures in mining areas. Here we present a new methodology combining satellite radar interferometry and 2D finite element modeling for slope stability analysis at a regional scale, applied within slope unit polygons. We studied a former mining area in southeast Spain, and the method proved useful in detecting and characterizing a considerably large number of unstable slopes. Out of 1,959 slope units used for the spatial analysis of the radar interferometry data, 43 were unstable, with varying values of safety factor and landslide size. Out of the 43 active slope units, 21 exhibited line of sight velocities greater than the maximum error obtained through the validation analysis (2.5 cm/year). Eventually, this work discusses the possibility of using the results of the proposed approach to devise a proxy for landslide hazard. The proposed methodology can help to provide non-expert final users with intelligible, clear and easily comparable information to analyze slope instabilities in different settings, not limited to mining areas.

The energy crisis and environmental problems are becoming more and more severe due to the long-term consumption of fossil fuels. Therefore, energy conversion devices with high energy density and environmental friendliness (such as fuel cells, metal-air batteries, etc.) have been ex-pected to be reliable alternatives to traditional fossil energy. However, due to the inevitable use of precious metals as the electrode catalysts for these devices, the popularization of these alternatives is seriously hindered. Transition metal nitrides (TMNs) exhibit similar surface and adsorption properties to noble metals since the atomic distance between metal atoms increases and the d-band center of metal atoms downshift after the nitrogen atoms enter the metal lattice. TMNs have become one of the best electrode materials to replace noble metal electrocatalysts in energy storage and conversion devices. In this review, the latest development in the electrocatalytic ap-plication of TMNs nanocrystalline is covered. Firstly, we briefly discuss the structure and activity origin of TMNs and introduce the common physical and chemical methods for the preparation of TMNs. Subsequently, we illustrate the applications of unary TMNs and multivariate TMNs in oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Finally, we summarize the challenges and problems of TMNs encountered at the present stage, and expect its future de-velopment.

The dilatometer curves of continuous cooling transformation of 12Mn steel were measured with Formastor-FⅡthermal mechanical simulator．The steel's undercooled austenite phase continuous cooling transformation curves ( CCT curves) were established by means of the dilatometer method and the metallographic-hardness measurement method． The effect of cooling rate on microstructure and hardness of the steel was studied． CCT curve of test steel was simulated by JMatPro. The results show that the Ac1 and Ac3 of the experimental steel are 692 ℃ and 855 ℃ ; the microstructure obtained is made of ferrite，pearlite and bainite．The ferrite transformation and pearlite transformation occur at a slower cooling rate，in which the ferrite is dominant. When the cooling rate is greater than 4.25 ℃ / s bainite transformation happens．As the cooling rate increases，microstructure or grains become finer．The hardness of the tested steel with increasing cooling rate shows a trend of first fast increase and soon decrease．The simulation results are consistent with the measured CCT law. The high temperature mechanical properties of 12mn steel round billet were tested by gleeble-1500d thermal / mechanical simulator. The tensile strength, reduction of area and stress-strain curves of the billet were obtained in the range of 600-1300 ℃.

A highly efficient reduction process of Cr (VI) with biochar was conducted in this paper. The results showed that nearly 100% Cr (VI) was reduced at selected reaction conditions: the dosage of biochar at m (C)/m(Cr) = 3.0, reaction temperature of 90 ℃, reaction time at 60 min and concentration of H2SO4 of 20 g/L, respectively. The reduction kinetics analysis demonstrated that the reduction of Cr (VI) fitted well with the pseudo-first-order model and the apparent activation energy was calculated to 40.24 kJ/mol. Response surface methodology confirmed that all the experimental parameters had positive effect on the reduction of Cr (VI). The influence of each parameter on the reduction process followed the order: dosage of biochar> Concentration of H2SO4 > Reaction Temperature > Reaction Time. This paper provided a versatile strategy for treatment of wastewater containing Cr (VI) and showed a bright tomorrow for wastewater treatment.

Given a polynomial $P(x_{1}, x_{2}, \ldots, x_{n})$ which is the sum of terms, where each term is a product of two distinct variables, then the problem $APSS$ consists in calculating the total sum value of $\sum_{\forall U_{i}} P(u_{1}, u_{2}, \ldots, u_{n})$, for all the possible assignments $U_{i} = \{u_{1}, u_{2}, ... u_{n}\}$ to the variables such that $u_{j} \in \{0, 1\}$. $APSS$ is the abbreviation for the problem name Algebraic Polynomial Sum Solver Over $\{0, 1\}$. We show that $APSS$ is in $\#L$ and therefore, it is in $FP$ as well. The functional polynomial time solution was implemented with Scala in \url{https://github.com/frankvegadelgado/sat} using the DIMACS format for the formulas in $\textit{MONOTONE-2SAT}$.

Increasing the quality factor (Q) of an optical resonator device has been a research focus to be utilized in various applications. Higher Q-factor means light is confined in a longer time which will produce a shaper peak and higher transmission. In this paper, we introduce a novel technique to increase further the Q-factor of a one-dimensional photonic crystal (1D PhC) cavity device by using an end loop-mirror (ELM). The technique utilizes and recycles the light transmission from the conventional 1D PhC cavity design. The design has been proved to work by using the 2.5D FDTD simulation with Lumerical FDTD and MODE softwares. By using the ELM technique, the Q- factor of a 1D PhC design has been shown to have increased up to 79.53 % from the initial Q value without the ELM. This novel design technique can be combined with any high Q-factor and very high Q-factor designs to increase more the Q-factor value of a photonic crystal cavity devices or any other suitable optical resonator devices. The experimental result shows that the device is measurable by adding a Y-branch component to the one-port structure and able to get the high-Q result.

Red mud is a hazardous waste of alumina industry that contains high amounts of iron, aluminum, titanium and REEs. One of the promising methods for the extraction of iron from red mud is car-bothermic reduction with the addition of sodium salts. This research focuses on the process of hy-drochloric high-pressure acid leaching using 10–20% HCl of two samples of non-magnetic tailings obtained by 60-minute carbothermic roasting of red mud at 1300 °C and the mixture of 84.6 wt. % of red mud and 15.4 wt. % Na2SO4 at 1150 °C, respectively, with subsequent magnetic separation of metallic iron. An influence of temperature, leaching duration, solid-to-liquid-ratio and acid con-centration on dissolution behavior of Al, Ti, Mg, Ca, Si, Fe, Na, La, Ce, Pr, Nd, Sc, Zr were studied. Based on the investigation of the obtained residues, mechanism of passing of valuable elements into the solution was proposed. It has shown that 90% Al, 91% Sc and above 80% of other REEs can be dissolved under optimal conditions; Ti can be extracted into the solution or the residue depending on the leaching temperature and acid concentration. Based on the research results, novel flowsheets for red mud treatment were developed.

Chemotherapy is a standard therapeutic option for triple-negative breast cancer (TNBC); however, its effectiveness is often compromised by drug-related toxicity and resistance development. Herein, we aimed to evaluate whether an improved antineoplastic effect could be achieved in vitro and in vivo in TNBC by combining dovitinib, a multi-kinase inhibitor, with calcitriol, a natural anti-cancer hormone. In vitro, cell proliferation and cell-cycle distribution were studied by sulforhodamine B-assays and flow cytometry. In vivo, dovitinib/calcitriol effects on tumor growth, angiogenesis and endothelium activation were evaluated in xenografted mice by caliper measures, Itgb3-immunohistochemistry and 99mTc-RGD2-tumor uptake. The drug combination elicited a synergistically improved antiproliferative effect in TNBC-derived cells, which allowed a 7-fold dovitinib dose-reduction. Mechanistically, the co-treatment induced cell death and accumulation in S and G2/M phases, while inhibited tumor growth to a greater extent than each compound alone. Tumor uptake of 99mTc-RGD2 was reduced by dovitinib, suggesting angiogenesis inhibition, which was corroborated by decreased endothelial cell growth and tumor vessel density. In summary, calcitriol synergized dovitinib anticancer effects in vitro and in vivo, allowing for a significant dose-reduction of dovitinib, while maintaining its antiproliferative potency. Our results suggest the beneficial convergence of independent antitumor mechanisms of dovitinib and calcitriol to inhibit TNBC-tumor growth.

Cultivated land plays an important role in water and soil loss in the earth-rocky mountainous region, northern China, however, its responses to soil control measures and rainfall characteristics are still not fully understood. In this study, 85 erosive rainfall events in 2011-2019 were grouped into three types, and the responses of runoff and soil loss on five cultivated plots with different slopes in the upstream catchment of the Miyun Reservoir to soil conservation measures and rainfall regimes were evaluated. Results found that event-averaged runoff depths and soil loss rates on the five plots ranged from 7.05 mm to 0.03 mm and from 300.51 t km-2 to 0.37 t km-2 respectively, depending on rainfall regimes, soil conservation measures, and slope gradients. The high occurring frequency (i.e., 72.94%) rainfall regime A with short rainfall duration (RD), low rainfall amount (P), and high mean rainfall intensity (Im) yielded lower runoff depth and higher soil loss rate. Rainfall regime B with longer RD, and higher P and Im, however, produced higher rainfall depth and lower soil loss rate. Terraced plot had the highest runoff and soil loss reduction efficiencies of over 96.03%. Contour tillage had comparable sediment reduction efficiency to that of the terraced plot on gentle slopes (gradient less than 11.0%), while its runoff reduction efficiency was less than 13.11%. This study implies that in the Miyun Reservoir catchment and similar regions in the world, contour tillage should be promoted on gentle slopes, and terrace construction should be given enough attention since it can greatly reduce water quantity and cause water shortage in downstream catchments.