Pancreatic cancer presents formidable challenges due to rapid progression and resistance to conventional treatments. Oncolytic viruses (OVs) selectively infect cancer cells and cause cancer cells to lyse, releasing molecules that can be identified by the host’s immune system. Moreover, OV can carry immune-stimulatory payloads such as interleukin-12 which when delivered locally can enhance immune system-mediated tumor killing. OV’s are very well tolerated by cancer patients due to their ability to selectively target tumors without affecting surrounding normal tissues. OV’s have recently been combined with other therapies including chemotherapy and immunotherapy to improve clinical outcomes. Several OVs including adenovirus, herpes simplex viruses (HSV), vaccinia virus, parvovirus, reovirus, and measles virus have been evaluated in preclinical and clinical settings for the treatment of pancreatic cancer. We evaluated the safety and tolerability of a replication-competent oncolytic adenoviral vector carrying two suicide genes (thymidine kinase, TK; and cytosine deaminase, CD) and human interleukin-12 (hIL12) in metastatic pancreatic cancer patients in a phase 1 trial. This vector was found to be safe and well-tolerated at the highest doses tested without causing any significant adverse events (SAE). Moreover, long-term follow-up studies indicated an increase in the overall survival (OS) in subjects receiving the highest dose of the OV. Our encouraging long-term survival data provide hope for patients with advanced pancreatic cancers, a disease that has not seen a meaningful increase in OS in the last five decades. In this review article, we highlight several preclinical and clinical studies and discuss future directions for optimizing OV therapy in pancreatic cancer. We envision OV-based gene therapy to be a game changer in the near future with the advent of newer generation OVs that have higher specificity and selectivity combined with personalized treatment plans developed under AI guidance.

The past 40 years have seen automotive Electronic Control Units (ECUs) move from being purely mechanical controlled to being primarily digital controlled. While there has been significant improvements in terms of passenger safety and vehicle efficiency including optimised fuel consumption, rising ECU numbers have resulted in increased vehicle weight, greater demands placed on power,more complex hardware and software, ad-hoc methods for updating software, and subsequent rise in costs for both vehicle manufacturer and consumer. To address these issues, the research presented in this paper proposes virtualisation technologies to be applied within automotive Electrical/Electronic (E/E) architecture. To proposed approach is evaluated through a comprehensive study of the CPU and memory resource requirement in order to support container-based ECU automotive functions. This comprehensive performance evaluation reveals that lightweight container virtualisation has the potential to welcome a paradigm shift in the E/E architecture, promoting consolidation and enhancing the architecture through power, weight and cost savings. Container based virtualisation will also enable a robust mechanism to facilitate online dynamic software updates throughout the lifetime of a vehicle.

A recently published article posited the use of polymer matrix composites (PMCs) as a replacement material for low-carbon steel (LCS) in large power transformer (LPT) tanks [1]. PMCs offer potential advantages such as weight reduction, corrosion prevention, and self-healing of the tank material which may not be achievable with traditional LCS. LCS can arrest ballistic projectiles at relatively low velocities, but at higher velocities, penetration can occur leading to a potential major transformer failure. Numerical simulations of steel projectile impacts upon LCS plates and glass and/or carbon fiber polymer composite laminates showed that with sufficient thickness both could prevent projectile penetration. This prevention was especially efficient when the plates were coated with a high strain rate sensitive material such as polyurea (PU). Our simulations show that the addition of a 3 mm coating of PU to a standard 10 mm thick LCS plate used in LPT tanks could prevent penetration of a 400 m/s steel projectile. For PMC plates, the simulations with the same projectile velocity showed three times faster deceleration with a 3 mm PU coating than without the coating. Thus, two realistic approaches to improving the ballistic protection of LPTs are presented. In addition to their other advantages, this research clearly shows that PMCs with the coating could provide significant ballistic protection for the next generation of LPT tanks.

The accelerated development of AI technology has brought about revolutionary changes in various fields of society. Recently, it has been emphasized that Fairness, Accountability, Transparency, Ethics (Explainability) (FATE) should be considered to support the reliability and validity of AI-based decision-making. However, in the case of autonomous driving technology, which is directly related to human life and requires real-time adaptation and response to various changes and risks in the real world, environmental adaptability must be considered in a more comprehensive and converged manner. In order to derive definitive evidence for each object in a convergent autonomous driving environment, it is necessary to transparently collect and provide various types of road environment information for driving objects and driving assistance, and to construct driving technology that is adaptable to various situations by considering all uncertainties in the real-time changing driving environment.This allows unbiased and fair results based on flexible contextual understanding, even in situations that do not conform to rules and patterns, by considering the convergent interactions and dynamic situations of various objects that are possible in a real-time road environment. The transparent, environmentally adaptive, and fairness-based outcomes provide the basis for the decision-making process and support clear interpretation and explainability of decisions. All of these processes enable autonomous vehicles to draw reliable conclusions and take responsibility for their decisions in autonomous driving situations. Therefore, this paper proposes an Adaptability, Fairness, Transparency, Explainability and Accountability (AFTEA) Framework to build a stable and reliable autonomous driving environment in dynamic situations. This paper explains the definition, role, and necessity of AFTEA in artificial intelligence technology and highlights its value when applied and integrated into autonomous driving technology. The AFTEA framework with environmental adaptability will support the establishment of a sustainable autonomous driving environment in dynamic environments, and aims to provide a direction for establishing a stable and reliable AI system that adapts to various real-world scenarios.

This study examines the latest innovation in wooden pile foundation models using a combination of wood and concrete materials for house construction on swampy land. The focus of the research is on developing joints and materials that enhance the load-bearing capacity and stability of building structures on swampy terrain. The methods used include field observations, laboratory experiments, and descriptive analysis. The results show that the combination of wood and concrete in foundation piles can increase structural strength, reduce deformation, and extend the service life of buildings. The new joint techniques developed in this research are effective in improving structural integrity and minimizing the negative impacts of soft soil conditions. The conclusion emphasizes the importance of material innovation and joint techniques in construction on swampy land, providing practical guidance for construction practitioners and researchers in this field.

The theory says that number interacts with spaces based on the meaning of mathematics, in this way it is possible to obtain numerical knowledge. The theory shows the possibility of using spaces related to each other to efficiently discover whether results and origins are even or odd, but always applying rules to make this work. the study uses equivalent representations of odd and even numbers. Thus, it is possible to discover the possibilities of origins and their results.

This research aims to analyze the impact of Social Responsibility on the performance of 216 European companies during the years 2017 to 2021. The objective of this research is to determine how the operational, financial and market performance of companies is influenced by social responsibility practices. The methodology adopted is quantitative in nature, using the estimation of dynamic models for panel data. To quantify corporate performance, this study will use, the return on assets, the return on equity and finally the Tobin's Q ratio. On the other hand, ESG (Environment, Social and Government) scores and GC Score scores will be used in order to quantify SR. The results show that SR presents not only a negative influence on the financial and operational performance of companies, but also a positive impact on market performance. This influence is even greater when distinguishing the best from the worst scores. The environment, social and government dimension shows a negative relationship with ROA and ROE, and a positive one with Tobin's Q. On the other hand, the anti-corruption and environment dimension of the GC Score, relates negatively with Tobin's Q, the human rights dimension relates negatively with ROE and ROA, and finally, the labor law dimension presents a positive relationship with ROE. Importantly, firm size positively influences this relationship, while age has a negative influence. This research offers important contributions to the literature, since from the ESG scores and the GC Score, a complete analysis of the impact of social responsibility on corporate performance is developed.

The development requirements for reusable liquid rocket engines have set higher standards for the reliability design of turbopump structures. To address the issue of bearing failure in turbopumps under harsh conditions such as low temperature, high speed, heavy load, and repeated start-stop cycles, this paper proposes replacing ball bearings with thrust foil bearings. We used liquid nitrogen instead of liquid hydrogen and liquid oxygen to simulate the ultralow temperature and low viscosity operating environment of turbopumps, evaluating the potential feasibility of using thrust foil bearings in this context. The numerical calculations primarily include the formulation of the foil deformation equations based on the link-spring model for the wavy foil and the thin plate finite element model for the top foil. These equations are solved by coupling the Reynolds lubrication equation, the fluid film thickness equation, and the foil deformation equations using the finite difference method, Newton-Raphson method, and finite element method. A detailed analysis is conducted on the effects of rotational speed, fluid film thickness, thrust disk inclination angle, and wavy foil interface friction coefficient on the static and dynamic characteristics of thrust foil bearings. The research findings provide guidance for the application of thrust foil bearings in liquid rocket turbopumps.

Robot manipulators are robotic systems that are frequently used in automation systems and able to provide increased speed, precision and efficiency in the industrial applications. Due to their nonlinear and complex nature, it is crucial to optimize the robot manipulator systems in terms of trajectory control. In this study, positioning analysis based on artificial neural networks (ANN) were performed for robot manipulator systems used in the textile industry and the optimal ANN model for the high-accuracy positioning was improved. The inverse kinematic analysis of a 6 degree of freedom (DOF) industrial denim robot manipulator were carried out via 4 different learning algorithms of Delta-Bar-Delta (DBD), Online Back Propagation (OBP), Quick Back Propagation (QBP) and Random Back Propagation (RBP) for proposed neural network predictor. From the results obtained, it was observed that QBP based 3-10-6 type ANN structure produced the optimal results in terms of estimation and modelling of trajectory control. In addition, 3-5-6 type ANN structure was also improved and its Root Mean Square Error (RMSE) and statistical R2 performances were compared to that of 3-10-6 ANN structure. Consequently, it can be concluded that the proposed neural predictors can successfully be employed in real-time industrial applications for robot manipulator trajectory analysis.

The use of didactic and interactive materials is essential in generating interest among students and teachers in utilizing mathematical models and digital technologies for the educational process. These materials create a dynamic and engaging learning environment that promotes a deeper understanding of complex concepts and fosters a passion for learning. Additionally, integrating interactive materials into pilot courses can assist teachers in better assessing student learning and adjusting the teaching strategies accordingly and the teachers can receive valuable insights into students' strengths and weaknesses, allowing them to provide targeted support and intervention when needed. In this context, the purpose of this paper is to introduce an approach for solving mathematics problems embedded in technical scenarios within the defense and security fields with the aid of digital technology. In this way, students can visualize abstract concepts, experiment with different scenarios, and receive instant feedback on their understanding. This paper helps to reinforce key concepts and enhance problem-solving skills, sparking curiosity, creativity, and encouraging active participation and collaboration. Throughout the development of this proposal, good practices are adopted, and advice for improvement is collected while having a wide range of users, giving feedback, discussions, and testing (pilot) short-term learning/teaching/training activities.

The unprecedented production and sharing of data, opinions, and comments among people on social media and the Internet in general has highlighted sentiment analysis as a key machine learning approach in scientific and market research. Sentiment analysis can extract sentiments and opinions from user-generated text, providing useful evidence for new product decision-making and effective customer relationship management. However, there are concerns about existing standard sentiment analysis tools regarding the generation of inaccurate sentiment classification results. The objective of this paper is to determine the efficiency of off-the-shelf sentiment analysis APIs in recognizing low-resource languages, such as Greek. Specifically, we examined whether sentiment analysis performed on 300 online ordering customer reviews using the Meaning Cloud web-based tool produced meaningful results with high accuracy. According to the results of the study, we found low agreement between the web-based and the actual raters in the food delivery services related data. However, the low accuracy of the results highlights the need for specialized sentiment analysis tools capable of recognizing only one low-resource language. Finally, there is a significant need for the creation of industry-specific lexical resources that provide decision-makers with valuable insights.

In the light of almost a century of struggle to make (common) sense of Quantum Mechanics and to reconcile it with General Relativity, it is proposed to (for some time) forget about quantizing gravity or striving for one Theory of Everything or “Weltformel”, which would describe the whole of reality without any joints or suture marks. Instead of one single monolithic formalism, a three-legged compound approach is argued for. Quantum Mechanics, Relativity and Thermodynamics are proposed as the main pillars of reality, each with its well-defined realm, specific features, and clearly marked interfaces between the three of them. Not only classical reality, which is rather directly accessible to us, is then comprehensively modelled by their encompassing combination. Quantum phenomena are understood as undoubtedly lying at the bottom of classical physics and at the same time, they become “fully real” only when embedded in classical frames between preparation and measurement in time. It is then where thermodynamics steps in and provides the mediating glue. The aim of this short contribution is not to deliver novel quantitative results but rather to propose a comprehensive research program and to coarsely lay out a very roughly coherent self-referential sketch starting from the beginning of the one universe, which we inhabit.

In this paper we introduce an ODE system to model the interaction between nature resources and human exploitation in a rich consumeristic society. In this model the rate of change of population depends on wealth per capita, and the rate of consumption has a quadratic growth with respect to population and wealth. As in our previous work \cite{BaCra_1}, we distinguish between renewable and non renewable resources, and we introduce a replenishment term for non renewable resources. We first get some information on the asymptotic behaviour of wealth and population, then we compute all the equilibria of the system and we study their stability when the parameter of exploitation of resources is small. Some numerical simulations confirm the theoretical results, and give suggestions for future research.

An electrothermal analysis for barium titanate based ceramics is presented combining the Heywang–Jonker model for the electric resistivity with a heat dissipation mechanism based on natural convection and radiation in a one dimensional model on the device level with voltage as the control parameter. Both PTC and NTC effects are accounted for through the double Schottky barriers at the grain boundaries of the material. The problem formulated in this way admits uniform and non–uniform multiple steady state solutions that do not depend on the external circuit. The numerical bifurcation analysis reveals that the PTC effect gives rise to several multiplicites above the Curie point, whereas the NTC effect is responsible for the thermal runaway (temperature blowup). The thermal runaway phenomenon as a potential thermal shock could be among the possible reasons for the observed thermomechanical failures (delamination fracture). The theoretical results for the NTC regime and the thermal runaway are in agreement with experimental flash sintering results obtained for 3% and 8% yttria stabilized zirconia.

The design is described of a readily useable technology for routine paddock-scale soil porosity estimation. The method is non-contact (proximal) and typically from sensors mounted on a small farm vehicle around 1 m above the soil surface. Challenges arise from the need to have a compact low-power rigid structure and to allow for pasture cover and surface roughness. The high-frequency regime for acoustic reflections from a porous material is a function of the porosity , the tortuosity , and the angle of incidence . There is no dependence on frequency, so measurements must be conducted at two or more angles of incidence in order to obtain two or more equations in the unknown soil properties and . A system requiring a single transmitter/receiver pair to be moved from one angle to another is not viable for rapid sampling. Therefore, the design includes at least two transmitter/reflector pairs placed at identical distances from the ground so that they would respond identically to power reflected from a perfectly reflecting surface. A single 25 kHz frequency is a compromise which allows for the frequency-dependent signal loss from a natural rough agricultural soil surface. Multiple-transmitter and multiple-microphone arrays are described which give a good signal to noise ratio while maintaining a compact system design. The resulting arrays have a diameter of 100 mm. Pulsed ultrasound is used so that the reflected sound can be separated from sound travelling directly through the air horizontally from transmitter to receiver. The average porosity estimated for soil samples in the laboratory and in the field is found to be within around 0.04 of the porosity measured independently. This level of variation is consistent with uncertainties in setting the angle of incidence, although assumptions made in modelling the interaction of ultrasound with the rough surface no doubt also contribute.

(1) Background: Burnout syndrome results from chronic stress in the work-place. The COVID-19 pandemic has imposed a heavy workload on health professionals, doctors and nurses to respond to first-line health care during the first two years of an emergency caused by this virus. The aim of this study was to evaluate the prevalence of burnout in healthcare personnel, doctors and nurses during the COVID-19 pandemic. (2) Methods: This was a review of reviews on the prevalence of professional burnout syndrome in healthcare personnel, doctors and nurses before or during the COVID-19 pandemic, without language restrictions or missing data from the Cochrane Library electronic databases. In total, 48,657 articles were obtained from Pub-Med/MEDLINE and the Web of Science. (3) Results: After completing the examination, 20 articles were included in the review. Of these articles, 7% included nurses in their study population, 72% interviewed doctors from different specialties, and the remaining 21% reported personnel data. Healthcare as a whole: In total, 624 articles with 233,087 participants were included. Regarding the prevalence by subscale, a PD of 33% (95% CI; 33%- 34%), an AE of 37% (95% CI; 37%- 37%) and a PR of 29% (95% CI) were found. %; 29% and 29%). ; (4) Conclusions: The incidences of DP and AE are high, and that of RP is low. These findings demonstrate the high prevalence of burnout according to subscale. Burnout is a problem of great magnitude, and as such, interventions must be implemented immediately at the individual and group levels by institutions and health systems.

The arguments on the origin and evolution of the evergreen broad-leaved forest in eastern Asia, especially in the evolutionary process, exist generally, even contrary in some cases. The origin and evolution of the flora of eastern Asia, the formation time of Asian monsoon, and the implications from phylogenetic and molecular biogeographic studies in some important taxa, as well as in palaeobotanical evidences, are debatable. Most researches from different disciplines suggested that the monsoon in Miocene is a key to diversification of eastern Asian flora and its evergreen broad-leaved forest. The common view is that the evergreen broad-leaved forest of East Asia is closely related to the monsoon intensity and developments, which are caused by the uplift of Himalaya-Tibet, during or after the mid-Miocene. The analysis on the floristic elements show that the present subtropical evergreen broad-leaved forest in eastern Asia could have an early or ancient tropical origin and a tropical Asian affinity, but their species are dominated by the Chinese endemic or eastern Asian distribution, many of which are the tropical sister ones. The time of Himalayan uplift and intensity of monsoon climate is believed the key for the formation of the evergreen broad-leaved forest in eastern Asia. Combined existing palaeobotanical findings, the uplift of Himalayas and the formation of monsoon climate, as well as floristic elements of the subtropical evergreen broad-leaved forest, we believe that it was evolved from a Asian tropical rain forest after mid-Miocene in southeastern region of eastern Asia, while the ancient subtropical evergreen broad-leaved forests in southwestern region continuously evolved into the present subtropical ones.

The aim of this retrospective study was to identify myocardial injury after COVID-19 inflamation and to explore whether myocardial damage could be a possible cause of the persistent symptoms following COVID-19 infection in previously healthy individuals. The study included 139 patients who were enrolled between January-June 2021, mean age 46.7±15.2 years, 68 were men, 71 were women without known cardiac or pulmonary diseases. All patients underwent clinical work up, lab. analyses, cardiac ultrasound, and CMR on 1.5 T scanner using a recommended protocol for morphological and functional assessment before and after contrast media application with multi-parametric sequences. In 39% of patients late gadolinium enhancement (LGE) was found as a sign of myocarditis. Fibrinogen was statistically significantly higher in patients with LGE than in those without LGE, (4.3±0.23 vs 3.2±0.14g/L, p<0.05; respectively), as well as D-dimer (1.8±0.3 vs 0.8±0.1 mg/L FEU). Also troponin was statistically significantly higher in patients with myocardial LGE (13.1±0.4ng/L) compared to those with normal myocardium (4.9±0.3ng/L, p<0.001). We demonstrated chest pain, fatigue and elevated troponin to be independent predictors for LGE. Septal LGE was shown to be predictor for arrhythmias. The use of CMR is a potential risk stratification tool in evaluating outcomes following COVID-19 myocarditis.

Background: Delivery of quality family planning services depends on availability of skilled health care providers, which is often a challenge in Low- and middle-income countries. This study evaluates the effects of a targeted training program on family planning services delivered by the Lady Health Workers (LHWs) in six districts of Punjab, Pakistan. The primary goal was to enhance the quality and accessibility of family planning services, recognizing the pivotal role of LHWs in community health. Methods: Using a robust panel data difference-in-differences (DiD) approach, we analyzed the electronic medical records (EMR) of 1,410 LHWs over a nine-month period. This timeframe in-cluded both pre-training (July to December 2022) and post-training (April to June 2023) phases. Our assessment focused on the impact of training on five outcome variables: the number of follow-up clients, the number of Intrauterine Contraceptive Device (IUCD) clients, the number of condom clients, the number of modern method clients, and the number of injection clients. We also con-sidered control variables such as LHW age, LHW education, the number of eligible couples in each LHW's catchment area, and a categorical variable for the districts. Results: The positive and statistically significant (p<0.05) coefficients across various service cat-egories – Follow Up Clients [Coeff: 1.00, CI: (0.30 - 1.70)], IUCD Clients [Coeff: 0.23, CI: (-0.01 - 0.46)], Condom Clients [Coeff: 1.41, CI: (0.97 – 1.86)], Modern Method Clients [Coeff: 1.82, CI: (0.96 – 2.68)], and Injection Clients [Coeff: 0.32, CI: (0.14 – 0.50)]. These findings indicate enhanced productivity among LHWs who have received training, with results significant at the 95% con-fidence interval (CI). Conclusion: The study highlights the effectiveness of targeted training programs in boosting family planning services at the community level and offers insightful implications for policy-makers and health practitioners. While focused on six districts in Punjab, these promising results emphasize the need for ongoing training and support for frontline health workers to bolster family planning initiatives.

The emergence of digital twins (DTs) represents a recent advancement in technological processes that support the planning, construction, and oversight of constructed assets. A DT is essentially a digital model that facilitates simulations and two-way information exchange with its real-world counterpart (a physical twin), creating opportunities for data-driven decision-making. Despite the promising prospects of DTs, both the technology and the methodologies for developing them, as well as their potential applications, remain not fully understood in both academic and industrial contexts. This research explores the applications of DTs for the management of existing assets within the AEC/FM industry. The study presents the results of a comprehensive literature review that explores existing knowledge in this domain. The findings reveal that procedures for creating DTs are still in their early stages, emphasizing potential applications in asset management throughout their lifespan, facilitating sustainability upgrades, and supporting the maintenance and restoration of heritage assets. The review concludes by providing recommendations for future research in this evolving field.

In this study, the pristine MgO, MgO/CNT and Ni-MgO/CNT nanocomposites were processed by the impregnation and chemical vapour deposition methods and analyzed for hydrogen evolution (HER) via electrochemical water splitting process. Furthermore, effect of nickel on the deposited carbon was systematically elaborated in this study. The highly conductive carbon nanotubes (CNTs) deposited on the metal surface of the Ni-MgO nanocomposite heterostructure provides the robust stability and superior electrocatalytic activity. The optimized Ni-MgO/CNT nanocomposite exhibited hierarchical helical-shaped carbon nanotubes adorned on the surface of the Ni-MgO flakes, forming a hybrid metal-carbon network structure. The HER catalytic reaction was carried out in 1M alkaline KOH electrolyte, and the optimized Ni-MgO/CNT nanocomposite achieves the low 117 mV overpotential value (ɳ) at the 10 mA cm-2 and needs low 116 mV/dec Tafel value denoted Volmer-Heyrovsky pathway. Also, high electrochemical active surface area (ECSA) value of Ni-MgO/CNT nanocomposite acquires 515 cm2, which is favorable for the generation of abundant electro-active species and the prepared electrocatalyst durability was also performed by chronoamperometry test for prolonged duration of 20 h at 10 mA cm-2 and exhibits the good stability with 72% retention. Hence, obtained results demonstrated that the optimized Ni-MgO/CNT nanocomposite is highly active and cost-effective electrocatalyst towards hydrogen energy production.

Abstract: In the past years, lithium-ion solid-state batteries demonstrated significant advancements regarding such properties as safety, long-term endurance, and energy density. The properties of these depend on solid-state electrolytes and especially ionic transport interfacial transport with cathode or anode materials. Solid-state electrolytes based on lithium halides offer new opportunities due to their unique features such as broad electrochemical stability window, high lithium-ion conductivity, and elasticity at close to melting point temperatures that help to improve lithium-ion transport at interfaces. A comparative study of lithium indium halide (Li3InCl6) electrolytes syn-thesized by a mechano-thermal method using different optimization parameters revealed a signif-icant effect of ball-milling time, temperature, and pressure on lithium-ion transport. Based on the Electrochemical Impedance Spectroscopy (EIS) data in the temperature range of 25-100 °C, the optimized Li3InCl6 electrolyte phase demonstrates high ionic conductivity reaching 0.98 mS cm−1 at room temperature. However, at 70 °C, phase transformation was observed leading to significant changes in the activation energy for lithium-ion transport. In-situ X-ray diffraction and in-situ/operando X-ray photoelectron spectroscopy techniques confirmed the tempera-ture-dependent behavior of Li3InCl6 synthesized. These observations provide critical information for practical applications of solid-state electrolytes and nanocomposites based on Li3InCl6 within the broad temperature range for lithium-ion solid-state batteries with improved morphology, chemical interactions, and structural integrity.

In the field of maneuvering target tracking, the combined observations of azimuth and Doppler may cause weak observation or non-observation in the application of traditional target tracking algorithms. Additionally, traditional target-tracking algorithms require pre-defined multiple mathematical models to accurately capture the complex motion states of targets, while model mismatch and unavoidable measurement noise lead to significant errors in target state prediction. To address those above challenges, in recent years, the target-tracking algorithms based on neural networks, such as recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and Transformer architectures, have been widely used for their unique advantages to achieve accurate predictions. To better model the nonlinear relationship between the observation time series and the target state time series, as well as the contextual relationship among time series points, we present a deep learning algorithm called recursive downsample-convolve-interact neural network (RDCINN) based on convolutional neural network (CNN) that downsamples time series into sub-sequences and extracts multi-resolution features to enable the modeling of complex relationships between time series, which overcomes the shortcomings of traditional target-tracking algorithms in using observation information inefficiently due to weak observation or non-observation. The experimental results show that our algorithm outperforms other existing algorithms in the scenario of strong maneuvering target tracking with the combined observations of azimuth and Doppler.

In this study, cotton fabric reinforced phenolic resin (CPF) composites were modified by adding four two-dimensional fillers: graphitic carbon nitride (g-C3N4), graphite (Gr), molybdenum disulfide (MoS2), and hexagonal boron nitride (h-BN). The tribological properties of these modified materials were investigated under dry friction and water lubrication conditions. CPF/ Gr composite exhibits significantly better tribological performance than the other three fillers modified CPF composites under dry friction, with a 24% reduction in friction coefficient and a 78% reduction in wear rate compared to unmodified CPF composite. Under water lubrication conditions, all four fillers did not significantly alter the friction coefficient of the CPF composite. However, except for an excessive amount of Gr, the other three fillers can reduce the wear rate. Particularly, in the case of 10% MoS2 content, the wear rate decreased by 56%. Scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS) were employed for the analysis of the morphology and composition of the transfer films. Additionally, molecular dynamics (MD) simulations were conducted to investigate the adsorption effects of Gr, MoS2, and PF on the counterpart surface under both dry friction and water lubrication conditions. The difference in the adsorption capacity of Gr and MoS2 on the counterpart, as well as the resulting formation of transfer films, accounts for the variation in tribological behavior between CPF/Gr and CPF/MoS2 composites. By combining the lubrication properties of MoS2 and Gr under dry friction and water lubrication conditions, using them as co-fillers can achieve a synergistic lubrication effect.

Corynebacterium glutamicum is prominent for the industrial production of secreted amino acids. Notably, it naturally accumulates the carotenoid pigment decaprenoxanthin in its membranes. Metabolic engineering enabled production of astaxanthin. Here, a bioprocess for astaxanthin production in lab-scale stirred bioreactors was established by a DoE-guided approach to optimize the basic process parameters pH, rDOS, aeration rate as well as inoculation cell density. The DoE-guided approach from 2 L scale cultivation revealed that the pH showed the strongest effect on the product formation. Subsequently, an optimum at pH 8, an aeration rate of 0.25 vvm, 30 % rDOS and an initial optical density of 1 was established that allowed production of 7.6±0.6mg L-1 astaxanthin in batch mode. These process conditions were successfully transferred to a fed-batch process resulting in a high cell density cultivation with up to 60 g CDW L-1 biomass and 64 mg L-1 astaxanthin and thus demonstrating an about 9-fold improvement compared to optimal batch conditions. Moreover, pH shifts experiments indicate that the cells can quickly adapt to a change from pH 6 to 8 and start producing astaxanthin showing the possibility of a biphasic bioprocesses for astaxanthin production.

Veganism and the interest towards a plant-based diet are experiencing exponential growth worldwide, and in Italy more and more individuals and families are adopting this lifestyle and diet, too.Such a change in eating habits also imperatively implies the support and expertise of medical and health care professionals, who to date are still often unprepared and skeptical about this dietary pattern, despite scientific evidence.

The development of the additive manufacturing (AM) technology proffers challenging requirements for forming accuracy and efficiency. In this paper, a hybrid additive manufacturing technology combining fusion-based selective laser melting (SLM) and solid-state cold spraying (CS) was proposed in order to enable the fast production of near-net-shape metal parts. The idea is to fabricate a bulk deposit with a rough contour first via “fast” CS process and then add fine structures and complex features through “slow” SLM. The experimental results show that it is feasible to deposit SLM part onto CS part with good interfacial bonding. However, the CS parts must be subject to heat treatment to improve their cohesion strength before being sending for SLM processing. Otherwise, the high tensile residual stress generated during SLM process will cause fracture and cracks in the CS part. After heat treatment, pure copper deposited by CS undergoes grain growth and recrystallization, resulting in improved cohesive strength and release of the residual stress in the CS parts is released. The tensile test on the SLM/CS interfacial region indicates that the bonding strength increased by 38% from 45±7 MPa to 62±1 MPa after the CS part is subject to heat treatment, and the SLM/CS interfacial bonding strength is higher than the CS parts. This study demonstrates that the proposed hybrid AM process is feasible and promising for manufacturing free-standing SLM-CS components.

This study aims to explore predictors of the foreign investment from China coming into Rwanda. One of the components of Rwanda’s economy is the investment it receives from other countries. In order to achieve these objectives, the study gathers econometric secondary data from 2007 to 2020 quarterly which were availably provided by National Statistics of China, World Bank, UNCTAD, National Institute of Statistics of Rwanda, and the National bank of Rwanda. From literature and based on the availability of data, market size, trade openness, infrastructure, and human capital were measured as predictors of Chinese FDI. The data is analyzed using linear regression in Stata. The finding of the study showed that variables have a positive effect on FDI from China, and it found that though FDI had an effect on overall economy of Rwanda, the effect was not statistically significant. The study suggested that Rwanda’s policy on foreign investment should aim to attract and encourage Chinese investment to increase the economy of Rwanda. To encourage more FDI, the Rwandan government can offer Chinese investors greater ownership, locational, and internalization benefits. It also should continue to strengthen economic policy transparency since it lowers transaction costs and hence improves incentives for foreign investment.

E-commerce recommendation systems usually deal with massive customer sequential databases, such as historical purchase or click stream sequences. Recommendation systems’ accuracy can be improved if complex sequential patterns of user purchase behavior are learned by integrating sequential patterns of customer clicks and/or purchases into the user-item rating matrix input of collaborative filtering. This reviews focuses on algorithmic techniques of existing E-commerce recommendation systems that are sequential pattern based such as ChoRec05, ChenRec09, HuangRec09, LiuRec09, ChoiRec12, Hybrid Model RecSys16, Product RecSys16, SainiRec17, HPCRec18 and HSPCRec19. It provides a comprehensive and comparative performance analysis of these systems, exposing their methodologies, achievements, limitations, and potentials for solving more important problems in this domain. The review showed that integrating sequential pattern mining of historical purchase and/or click sequences into user-item matrix for collaborative filtering (i) improved recommendation accuracy (ii) reduced user-item rating data sparsity (iii) increased novelty rate of recommendations and (iv) improved scalability of the recommendation system.

The use of bioethanol in cooking is not new, but until recently its application has been confined exclusively to small scale projects. However, a new bioethanol cooking utility in Kenya has now reached mass market adoption, serving more than 950,000 households with cooking fuel since launching in late 2019. Its success was made possible by a significant investment in technology to facilitate safe, convenient and affordable fuel distribution. It is funded by climate finance which is based on bioethanol fuel replacing charcoal used for cooking, a leading cause of African defor-estation. This development has been so recent that it has not widely been discussed in the academic literature. More broadly, the health, environmental and economic impacts of bioethanol for cooking have not been systematically assembled in one place. This article details what is known about the impact of bioethanol for cooking, how and why bioethanol for cooking was able to suddenly reach commercially viable scale in spite of the challenges it faced. It also discusses implications for further scaling of clean cooking fuel solutions.

The metaphor of being touched by music is widespread and almost universal. The tactile experience, moreover, has received growing interest in recent years. There is, however, a need to go beyond a mere metaphorical use of the term, by positioning the tactile experience within the broader frame of embodied cognition and the experiential turn in cognitive science. This article explores the possible contribution of a science of touch by defining music as a vibrational art that impinges upon the body and the senses. It takes as a starting point the clinical findings on the psychological and physiological value of tender touch with a special focus on the method of kangaroo mother care, which is a method for holding the baby against the chest of the mother, skin-to-skin. It is seen as one of the most basic affiliative bonding with stimuli that elicit reward. Via an extensive review of the research literature, it is questioned to what extent this rationale can be translated to the realm of music. There are, in fact, many analogies, but a comprehensive theoretical framework is still lacking. This article aims at providing at least some preparatory groundwork to fuel more theorizing about listening and its relation to the sense of touch.

The epidemiological and clinical pathological aspects of polioencephalomalacia (PEM) in five buffaloes (buffaloes 01 to 05) in the amazon biome are described. Epidemiological data were obtained during the clinical visit in which the animals with clinical signs compatible with polioencephalomalacia were submitted to a general and specific clinical examination of the nervous system. During the necropsy of the five animals, the intensity and location of the lesions were evaluated and fragments from different organs were collected and fixed in 10% buffered formalin and sent to the Pathological Anatomy Sector of the Federal Rural University of Rio de Janeiro for histopathological examination. Of the five studied animals, all were of the Murrah breed, four male and one female, with ages ranging from two months to one year. Two buffaloes (buffalo 01 and 02) were from the municipality of Castanhal, Pará, kept in an extensive breeding system on Urochloa brizantha pasture. Buffaloes 03 and 04 belonged to a property located in the municipality of Cachoeira do Arari, Marajó Island, Pará, and buffalo 05 was from a property located in the municipality of Itaubal, state of Amapá, all of them were raised in an extensive system in flooded of native pasture. At the clinical examination, all buffaloes had a body score between 2.5 and 3 (scale from 1 to 5), and there was noted decreased alertness, postural changes, marked hypermetria when stimulated to move, total or partial blindness demonstrated by colliding to the corral structures, head pressing and circumduction of the hindquarters when supported on the forelimbs, opisthotonos, muscle tremors, convulsions, paddling movements, sialorrhea, decrease in palpebral and pupillary reflexes and eyeball rotation placing the pupillary slit in a vertical position. At necropsy, mild lesions characterized by edema and flattening of the cerebral convolutions were observed. Histopathological examination showed laminar necrosis of the cerebral cortex. The diagnosis of polioencephalomalacia was based on epidemiological, clinical-pathological, and histopathological findings, similar to findings in other ruminants. The cause of polioencephalomalacia in the studied buffaloes was not established, which indicates the need for further studies to elucidate this disease in the species, mainly in the Amazon region.

This article explores matter collineations (MCs) of static plane-symmetric spacetimes, considering the stress-energy tensor in its contravariant and mixed forms. We solve the MC equations in two cases: when the energy-momentum tensor is nondegenerate and degenerate. For the case of degenerate energy-momentum tensor, we employ a direct integration technique to solve the MC equations, which leads to an infinite-dimensional Lie algebra. On the other hand, when considering the nondegenerate energy-momentum tensor, the contravariant form results in a finite-dimensional Lie algebra with dimensions of either 4 or 10. However, in the case of the mixed form of the energy-momentum tensor, the dimension of the Lie algebra is infinite. Moreover, the obtained MCs are compared with those already found for covariant stress-energy.

Despite the important role of offshore renewable energies in the energy transition, the economical viability is still unclear. Therefore, an appropriate site selection is crucial. Besides the energy potential, the impact of operation and maintenance (O&M) aspects on the location can be critical. Traditional accessibility assessment metrics do not allow a comprehensive evaluation. Therefore, the present paper suggests a novel, technology-informed metric, incorporating the overall set of most critical aspects, i.e. metocean conditions, visibility due to sunlight and sea fog, system failures, and O&M logistics. Among the different aspects, limited visibility is shown to be highly relevant with a reduction of up to 60% in accessibility. The study assesses accessibility in 5 different locations across Europe. On the one hand, accessibility is shown to be less sensitive to long-term resource variations with a reduction of 5% in the last 6 decades. On the other hand, accessibility is shown to be inversely proportional to the energy potential overall, meaning that as energy potential increases, accessibility is reduced, increasing downtime, reducing final energy generation and increasing the final cost of energy. As a consequence, site selection should combine energy potential and accessibility assessments, which is enabled by the technology-informed metric presented here.

In this study, the gravimetric characterization and analysis of the solubilized extract of the organic fraction of Urban Household Solid Waste (RSDU) from the municipality of Belém do Pará was carried out in order to obtain the composition of the collected materials and the characteristics of the liquid resulting from the solubilization of these materials . The waste used to carry out this research was collected door-to-door, in which the points and neighborhoods served were determined through the sectorization of these locations and representative statistical sampling. For the sectorization of neighborhoods, family income values ​​were considered as the main parameter. After collecting the solid waste, the material was sent to the facilities of the Federal University of Pará (FUPa), where the waste was classified into paper, cardboard, tetrapak, rigid plastic, soft plastic, metals, glass, organic matter, waste toilets, fabrics and others. The organic fraction of solid waste was separated and sent to the drying, crushing and packaging processes. Subsequently, the solubilized extract of the organic fraction of solid waste was obtained, following the methodology recommended by NBR standard nº 10.006/2004, of the Brazilian Association of Technical Standards and the values ​​obtained were compared with Ordinance GM/MS nº 888/2021 and CONAMA Resolution nº 357/2005, in addition to results obtained by other authors. After carrying out the gravimetric characterization, it was possible to obtain the average proportions of 5.09% paper, 3.20% cardboard, 0.94% tetrapak, 3.58% rigid plastic, 9.97% soft plastic, 2.00% metals, 55.57% organic matter, 1.86% glass, 14.26% sanitary waste, 3.23% fabrics and 3.00% other waste. High values ​​of organic residues were found in the gravimetric composition, which can be explained by the collection method used and the high humidity of the organic solid residues. In the analyzes of the solubilized extract, values ​​of Hp (3.69 to 4.92), Turbidity (791 to 1,733 uT), Apparent Color (8,500 to 12,500 uC), True Color (6,000 to 14,000 uC), Total Dissolved Solids (5,330 to 8,040 mg/L), Total Nitrogen (201.80 to 359.90 mg/L), Ammoniacal Nitrogen (161 to 289 mg/L), Nitrate (10 to 40 mg/L), Total Phosphorus (52.30 to 166.80 mg/L) and Chemical Oxygen Demand (28,701 mg/L to 38,608 mg/L), in addition to other measured parameters, in which such information makes it possible to check the similarities of the waste solubilization conditions to that of leachates from landfills, in addition to not being in compliance with environmental and health legislation, demonstrating risks to the local environment and public health.

The four-way reversing valve is a key component determining whether a heat pump air conditioning system can work. Studying the four-way reversing valve is of great significance for improving the performance of the heat pump air conditioning system. In this paper, the control equation of the sliding block movement process is constructed to simulate the reversing process of the four-way reversing valve in fluid mechanics, and a detailed study is carried out from the sliding block speed, sliding block acceleration, sliding block force, refrigerant leakage, and other aspects. Research has shown that optimizing the structure of the slider can greatly improve the working performance of the four-way reversing valve. Increasing the height of the slider not only improves the pressure relief ability of the four-way reversing valve and prevents the slider from being damaged by high-pressure gas impact, but also reduces the leakage of refrigerant during the directional process; When reducing the length of the slider, although it will improve the pressure relief capacity of the four-way reversing valve, it also increases the amount of refrigerant leakage. The research results provide a theoretical basis and improvement direction for designers to improve the performance of four-way reversing valves.

Ketogenic dietary therapies (KDTs) are an effective and safe non-pharmacological treatment for drug-resistant epilepsy, but adherence can be challenging for both patients and caregivers. In Europe, there are no adequate tools to measure it other than monitoring ketosis. This study aimed to adapt and validate the Brazilian adherence questionnaire, Keto-check, into the Italian version: iKetoCheck. Using the Delphi technique, 12 judges validated the contents through agreement rate and the Content Validity Index (CVI). The iKetocheck was self-completed electronically by drug-resistant epilepsy or GLUT1 deficiency patients within an interval of 15 days to measure its reproducibility. Test-retest reliability was evaluated using Pearson correlation and relative significance test. Exploratory and confirmatory factorial analyses were made using Factor software. The final tool, iKetoCheck, consists of 10 questions with 5-point Likert scale answers. It evaluates various aspects such as informing caregivers about the diet, organization of meals, measurement of ketosis, weighing food consumed, diet negligence, use of carbohydrate-free medications, attending follow-up visits, reading food labels, consulting an expert for dietary concerns, and cooking at home. The factorial analysis resulted in three factors: "attention," "organization," and "precision," with satisfactory results for indices in exploratory and confirmatory analyses. Although higher mean values of ketonemia measurement were observed in patients with a higher adherence score, these values were not statistically significant (p=0.284). In conclusion, iKetoCheck is a valid tool for evaluating KDTs' adherence in Italian drug-resistant epilepsy or GLUT1 deficiency patients. It can provide valuable information to improve patient management and optimize the effectiveness of KDTs.

Formation of the excited doublet (D) and quartet (Q) states of free radicals under their photoexcitation is discussed. Relative positions of D and Q states are compared to the positions of photoexcited states of organic molecules (Jablonsky diagram). A number of representative cases of the detected by emission or absorption excited is presented. A special case of the population lowest Q-state in some radicals of is discoursed. Spin-statistical factor in the reactions of Q and D is debated.

The dynamic response of a Bell-and-Bloom magnetometer to a parallel (to the bias field) time-dependent field is modelled beyond the commonly assumed quasi-static regime. The results unveil features that are related to the parametric nature of the considered system. It is shown that a for low-amplitude time-dependent field different operating conditions are possible and that, beside the commonly reported low-pass-filter behaviour, a band-pass response emerges. Moreover, we numerically show that for larger field amplitude the system, due to its parametric nature, has a kind of ``non-linear'' response.

This paper addresses the issue of the automatic identification of river reaches and their planform type, given the (observed) set of geomorphic elements and units. It introduces further advances with respect to the original proposal by Nardini and Brierley. And it explores explicitly the ability of the algorithm and associated tools to work properly on significantly different rivers while adopting a given same parametrization. This was indeed an envisaged ability speculated as a challenging conclusion of the previous work. The Duqueco, Laja and Biobío rivers (Chile) are analyzed for this purpose. The conclusion is definitely positive, what opens future promising application horizons.

In the last decades, consumers are increasingly interested in organic products and they strongly demand for reliability of the traceability of the organic products they use to buy and eat. Different researches have been carried out over the years to investigate on new and reliable systems to test the authenticity of products obtained using organic cultivation methods. The monitoring of some chemical components, derived from primary and/or secondary metabolism, in horticultural organic and conventional products, has highlighted the diversity induced by the two production techniques while the difference in fertilization practices has been shown to impact on the isotopic distribution of some elements, with particular reference to nitrogen. An integrated system is proposed to validate, through the acquisition of isotopic data and other chemical and biochemical parameters, the authenticity of organic products. This approach is intended to be coupled to the application of chemometric multivariate analysis of isotopic data combined with other quality and nutraceutical parameters, giving the possibility to discriminate organic from conventional products, thanks to the different isotopic signature impressed by the different nitrogenous source combined with the qualitative pattern of the crops, significantly affected by the different treatments. The main perspectives of the presented integrated approach, based on the combined use of chemometric and analytical tools, are linked to the feasibility of applying a reliable system to authenticate productions obtained with organic fertilizers (organic agriculture) respect to those obtained with the use of synthetic fertilizers (conventional agriculture), protect and valorize virtuous farmers and support political stakeholders and decision makers to counteract food fraud.

Land’s basic metric is soil organic carbon (SOC) yet global estimates range 1,417–15,000 Gt C. Erosion of ancient topsoil and loss of soil taxa are most urgent of all context-triage concerns, and most ignored. Re-evaluation of topographical terrain on a non-flat Earth increases most soil dynamic inventories. Carbon credits of our neglected and disappearing SOC stocks are enumerated for mineral soils (~4,100 Gt C plus ca. 20–30% glomalin), Permafrost (>4,200 Gt C), peat (1,123 Gt C), plant roots (916 Gt C), litter (600 Gt C), microbes (200 Gt C), fungi (30 Gt C), biocrust (10–20 Gt C), earthworms (2.3–3.6 Gt C), termites (0.15 Gt C), nematodes (0.06 Gt C), ants (0.024 Gt C), and soil viruses (0.02–4.0 Gt C). Net contribution to atmospheric CO₂ is more from biotic topsoil loss (>10 Gt C/yr) than fossil fuels (<10 Gt C/yr). Although higher CO₂ results in a terrestrial greening effect with Net Primary Productivity (NPP) now ~220 Gt C/yr (cf. ~20 Gt C/yr Ocean NPP), this is arguably offset by topsoil erosion, desert expansion, plus fire at net ~16–20 Gt C/yr lost due, in part, to extravagant meat-eating with unsupportable, humus-depleting farm management. In particular, excess synthetic Nitrogen acidifies topsoil and destroys the natural SOC biota. Review shows critical topsoil loss up to 20,000 tonnes per second and, when soil microbes/invertebrates are properly considered, extinctions as high as 23 taxa per second. Sustainable Development Goals (SDGs) fail without solid soil foundation. Rather, heritage farm-data points to resolution in organic husbandry. Remedy via natural vermi-compost, 100% organic farming and practical Permaculture is under a simple premise that the Problem (i.e., SOC loss) is the Solution (viz., SOC restoration).

Accumulating reports have suggested that an inability to clear dead cells is a cause of inflammation and cancer and that the fascia is associated with cancer metastasis. Novel corpuscle-connected filiform structures (CCFSs) entangled on the fascia of the internal organs of rats were selectively visualized with high repeatability (93%) under vital staining with Janus Green B (JGB). Serial sections of CCFSs stained with haematoxylin and eosin and with Mattson Trichrome were microscopically examined. In parallel, the immunohistochemistry with CD31, Lyve 1, scanning electron microscopy, and transmission electron microscopy (TEM) were also used to investigate the novel properties of the CCFSs. All of the CCFSs enclosed JGB-stained granules, which was verified by the impromptu coupling of stereo and light microscopes and fluorescence-activated cell sorting. The functions of the CCFSs were discovered under fluorescence microscopy and confocal laser scanning microscopy to be implicated in cell death: fragmented DNAs and f-actins with extracellular DNAs. The dead cells in the CCFSs were verified by using terminal deoxynucleotidyl transferase dUTP nick end labelling and TEM. Moreover, the CCFS had a relatively-high concentration of calcium, a main element for cell death in tissue, which was measured in 2-dimensionally images using time-of-flight secondary ion mass spectrometry. Taken these results, we report for the first time that novel reticular CCFSs are widely entangled on the fascia of the internal organs of rats with the implication for cell death.

In this paper, we introduce a model for the automatic generation of literary sentences in French. It is based on algorithms that we have previously used to generate sentences in Spanish and Portuguese, and on a new corpus consisting of literary texts in French that we have constructed, called [FR]. Our automatic text generation algorithm combines language models, shallow parsing and deep learning, artificial neural networks. We have also proposed and implemented a manual evaluation protocol to assess the quality of the artificial sentences generated by our algorithm, by testing if they fulfill four simple criteria. We have obtained encouraging results from the evaluators for most of the desired features of our artificially generated sentences.

Head and neck squamous cell carcinoma (HNSCC) arise from the mucosal epithelium in the oral cavity, pharynx, sino-nasal region, and larynx. Laryngeal squamous cell carcinoma (LSCC) represents one-third of all head and neck cancers. Dysregulated RNA-related pathways define an important molecular signature in this aggressive carcinoma. The Survival Motor Neuron (SMN) protein regulates fundamental aspects of the RNA metabolism but, curiously, its role in cancer is virtually unknown. For the first time, here we focus on SMN in cancer context. We conducted a pilot study in a total of 20 patients with LSCC where SMN was found overexpressed at both the protein and transcript levels. By a cellular model of human laryngeal carcinoma, we demonstrated that SMN impacts cancer-relevant behaviors and perturbs key players of cell migration, invasion, and adhesion. Furthermore, in LSCC we showed a physical interaction between SMN and the epidermal growth factor receptor (EGFR), whose overexpression is an important feature in these tumours. This study candidates SMN as novel therapeutic target in LSSC, and likely in the whole spectrum of HNSCC. Overall, we provide the first analysis of SMN in human cancer.

Food security is a matter of global concern, as the supply of food is one of the basic needs, ensuring the survival of the species. The trend of globalization and development of the global economy has shifted the responsible, local consumption patterns towards an increased homogeneity of diets, with food products being disconnected from their source, leading to two major results: (1) increased global consumption, driven by the extensive availability of affordable seasonal foods throughout the year and (2) increased uncertainty in the supply chain – susceptible to disruptions, causing food insecurity. To determine what the nutritional model is in the case of the present study – Romania – we developed a questionnaire of 32 questions and distributed it to 1,053 respondents from Romania. The survey was conducted during 2021 and 2022, both in urban and rural areas with the aim of investigating the consumption pattern of the population. The analysis of the questionnaire data reveals overconsumption of animal products, starchy vegetables and bread and pastry products. This nutritional pattern with a high intake in animal protein, correlated with a lack of diversification, is extremely unsustainable, having a negative impact on human health and environmental health.behaviour towards a careful approach to food, environment and personal health, aims to identify consumption patterns that have the potential to increase the sustainability of the food system and a positive correlation with food security. Adopting sustainable dietary patters, based on short supply chains and mindful consumption, has great potential in restoring food security and resilience to adversity.

Micro-level language policy and planning (LPP) primarily concerns local actors' decision-making on matters in relation to language(s) and its users. Despite a growing body of literature focusing on micro language planning in educational settings, there is a scarcity of research examining early childhood education settings such as micro-level LPP context for young English language learners. By adopting a case study approach, the present study examined the educators' enactment of agency in micro-planning the English language education policy (LEP) in one Chinese kindergarten and the associated factors shaping their agency. Our study revealed that the sustainable implementation of the kindergarten English LEP depended on the principal, native English-speaking teachers, and the Chinese assistant teachers' different degrees of agency. Also, the research findings indicated an array of contextual and individual factors nested in a hierarchical structure that facilitated, guided, and constrained the educators' agency in a role-and circumstance-dependent manner. This study contributes to the pertinent literature by casting nuanced light on the different educators' contributions to the micro-level LPP against a national policy that does not endorse early-year English language education.

In heterogeneous networks, the random walks based on meta-path requires prior knowledge and lacks flexibility. And the random walks based on non-meta-path only considers the number of node types, but does not consider the influence of schema and topology between node types in real networks. To solve the above problems, this paper proposes a novel model HNE-RWTIC (Heterogeneous Network Embedding Based on Random Walks of Type & Inner Constraint). Firstly, to realize the flexible walks, we design a Type strategy, which is the node type selection strategy based on the co-occurrence probability of node types. Secondly, to achieve the uniformity of node sampling, we design an Inner strategy, which is the node selection strategy based on the adjacency relationship between nodes. The Type & Inner strategy can realize the random walks based on meta-path, the flexibility of the walks, and can sample the node types and nodes uniformly in proportion. Thirdly, based on the above strategy, a transition probability model is constructed; then, we obtain the nodes embedding based on the random walks and Skip-Gram. Finally, in classification and clustering tasks, we conducted a thorough empirical evaluation of our method on three real heterogeneous networks. Experimental results shown that F1-Score and NMI of HNE-RWTIC outperform state-of-the-art approaches.

Food security is a matter of global interest, as the provision of food resources is the primary determinant of human existence. Food is one of the basic needs, ensuring the survival of the species. The trend of globalization and development of the global economy has shifted the responsible local consumption patterns to an increased homogeneity of diets, food products being disconnected from their source. This disconnection led to two major results: (1) increased global consumption, with seasonal foods now available throughout the year, and a decrease in food prices on the global market, and (2) increased uncertainty in the supply chain, susceptible to disruptions, as was the case during the Covid-19 pandemic. The present study, based on the research and analysis of third-party data on food security, sustainable diets, consumption patterns and recommended actions to change the current unsustainable consumer behaviour towards a careful approach to food, environment and personal health, aims to identify consumption patterns that have the potential to increase the sustainability of the food system and a positive correlation with food security. Adopting sustainable dietary patters, based on short supply chains and mindful consumption, has great potential in restoring food security and resilience to adversity.

An electrocardiograph (ECG) reflects the health of the human heart and is used to help diagnose arrhythmia and myocardial infarction(MI) in clinical practice. Early diagnosis of arrhythmia helps implement preventive measures and plays a crucial role in saving a patient's life. With the increasing demand of clinicians for ECG analysis technology, intelligent detection and diagnosis of ECG signals has become a more efficient means to assist physicians in diagnosing cardiovascular diseases. This paper introduces an ECG diagnosis approach based on an ensemble deep learning combination of CNN(convolutional neural network) and SLAP(stacked-long short term memory architecture for prediction) architecture. ECG data is denoised and further divided into single heartbeats to achieve data standardization and sample diversity. Adam optimizer and BCEwithlogitsloss multi-classification loss function were used to enhance the model effect, and the system achieved the classification effect of 99.3% average accuracy, 99.0% F1-value, and 99.2% sensitivity in MIT-BIH standard database classification. It also shows good generalization ability on the Tianchi data set.

Independent Learning Independent Campus (MBKM) is a program to develop an educational ecosystem that is in harmony with learning in higher education and the needs of industry. The limited link and match between universities and the business and industrial world in Indonesia are obstacles in realizing Indonesia as a developed country in the Industrial Revolution 4.0 era. The purpose of this study is to analyze the impact of the Independent Learning Independent Campus (MBKM) program on improving the performance of Ibn Khaldun University Bogor. The method used in this study is descriptive statistics with quantitative analysis. The sample that participated in this study consisted of all active students, lecturers, and administration staff. The research data was obtained through distribution to 6100 students, 233 lecturers, and 150 education staff. The research stages include socializing the understanding of MBKM, filling out the survey, calculating the distribution of respondents' filling, and concluding the assessment category using the weighted mean score (WMS) method. Based on the result, the implementation of MBKM in University of Ibn Khaldun Bogor based on all indicators can conclude that MBKM improve the performance of Ibn Khaldun Bogor University in the good category with an average percentage assessment criteria above 75%

The capabilities of a quadcopter in the hover mode for low-altitude sensing of atmospheric turbulence with high spatial resolution in urban areas characterized by complex orography are investigated. The studies were carried out in different seasons (winter, spring, summer, and fall), and the quadcopter hovered in the immediate vicinity of ultrasonic weather stations. The DJI Phantom 4 Pro quadcopter and AMK-03 ultrasonic weather stations installed in different places of the studied territory were used in the experiment. The smoothing procedure was used to main regularities in the behavior of the longitudinal and lateral spectra of turbulence in the inertial and energy production ranges. The longitudinal and lateral turbulence scales were estimated by the least-square fit method with the von Karman model as a regression curve. It is shown that the turbulence spectra obtained with DJI Phantom 4 Pro and AMK-03 generally coincide with minor differences observed in the high-frequency region of the spectrum. In the inertial range, the behavior of the turbulence spectra shows that they obey the Kolmogorov-Obukhov “5/3” law. In the energy production range, the longitudinal and lateral turbulence scales and their ratio measured by DJI Phantom 4 Pro and AMK-03 agree to a good accuracy. Discrepancies in the data obtained with the quadcopter and the ultrasonic weather stations at the territory with complex orography are explained by the partial correlation of the wind velocity series at different measurement points and the influence of the inhomogeneous surface.

This paper investigates the path following control problem for a unmanned surface vehicle (USV) in the presence of unknown disturbances and system uncertainties. The simulation study combines two different types of sliding mode surface based control approaches due to its precise tracking and robustness against disturbances and uncertainty. Firstly, an adaptive linear sliding mode surface algorithm is applied, to keep the yaw error within the desired boundaries and then an adaptive integral non-linear sliding mode surface is explored to keep an account of the sliding mode condition. Additionally, a method to reconfigure the input parameters in order to keep settling time, yaw rate restriction and desired precision within boundary conditions is presented. The main strengths of proposed approach is simplicity, robustness with respect to external disturbances and high adaptability to static and dynamics reference courses without the need of parameter reconfiguration.

Eating disorders (ED) are characterized by alterations in eating behavior. The genetic factors shared between ED diagnoses have been underexplored. The present study aimed to perform a genome-wide association study on individuals with disordered eating behaviors in the Mexican population, blood methylation quantitative trait loci (blood-meQTL) analysis, and in silico function prediction by different algorithms. The analysis included a total of 1803 individuals. Genome-wide association study and blood-meQTL analysis were performed by logistic and linear regression. In silico functional variant prediction, phenome-wide, and transcriptome-wide association studies by different algorithms were analyzed. In the genome-wide association study, we identified 44 single-nucleotide polymorphisms (SNP) associated at a nominal value and 7 blood-meQTL at a genome-wide umbral. The SNPs were enriched in genome-wide associations of the metabolic and immunologic domains. In the in silico analysis, the SNP rs10419198 located on an enhancer mark could change the expression of PRR12 on blood, adipocytes, and brain areas that regulate food intake. The present study supports the previous associations of genetic variation in the metabolic domain with ED.

Our study provides guidelines on how to build long-term customer relationship in the non-contract mechanism context. More specifically, the findings show that special, social, and core benefits influence calculative commitment, and operational and special benefits influence affective commitment. This study also supports that calculative and affective commitment play a crucial role in understanding multi-channel agencies’ loyalty. In sum, this study revealed that calculative and affective commitment can be considered as partial or full mediators in the relationship between RBs (relational benefits) and loyalty. This study not only contributed to the existing SET (social exchange theory) and RBs paradigm but also provided practical implications for food distribution management.

The ryanodine receptor (RyR) is a Ca2+ release channel in the sarcoplasmic reticulum of skeletal and cardiac muscles and plays a key role in excitation-contraction coupling. The activity of the RyR is regulated by many intracellular factors such as divalent cations (Ca2+ and Mg2+), nucleotides, associated proteins, and reactive oxygen species. Since these intracellular factors change depending on the condition of the muscle, e.g., exercise, fatigue, or disease states, the RyR channel activity will be altered accordingly. In this review, we describe how the RyR channel is regulated under various conditions and discuss the possibility that the RyR acts as a sensor for change in the cellular environment of muscles.

Microfluidic lab-on-chip devices are widely being developed for chemical and biological studies. One of the most commonly used types of these chips is perfusion microwells for culturing multicellular spheroids. The main challenge in such systems is the formation of substantial necrotic and hypoxic zones within the cultured spheroids. Herein, we propose a novel acoustofluidic integrated platform to tackle this bottleneck problem. We show that such an approach enhances cell viability and shrinks necrotic and hypoxic zones in these spheroid-on-a-chip platforms without the need to increase the flow rate, leading to a significant reduction in costly reagents' consumption. Proof-of-concept, designing procedures, and finite element numerical simulation are discussed in details. Also, the effects of acoustic and hydrodynamic parameters on the cultured cells are investigated. The results show that by increasing acoustic boundary displacement amplitude (d0), the spheroid’s proliferating zone enlarges greatly. Moreover, it is shown that by implementing d0=0.5 nm, the required flow rate to maintain the necrotic zone below 13% will be decreased 12 times compared to non-acoustic chips.

Although chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) have distinct clinical features, both diseases may coexist in a patient because they share similar risk factors such as smoking, male sex, and old age. Patients with both emphysema in upper lung fields and diffuse ILD are diagnosed with combined pulmonary fibrosis and emphysema (CPFE), which causes substantial clinical deterioration. Patients with CPFE have higher mortality compared with patients who have COPD alone, but results have been inconclusive compared with patients who have idiopathic pulmonary fibrosis (IPF). Poor prognostic factors for CPFE include exacerbation, lung cancer, and pulmonary hypertension. The presence of interstitial lung abnormalities, which may be an early or mild form of ILD, is notable among patients with COPD, and is associated with poor prognosis. Various theories have been proposed regarding the pathophysiology of CPFE. Biomarker analyses have implied that this pathophysiology may be more closely associated with IPF development, rather than COPD or emphysema. Patients with CPFE should be advised to quit smoking and undergo routine lung function tests, and pulmonary rehabilitation may be helpful. Various pharmacologic agents may be beneficial in patients with CPFE, but further studies are needed.

Clinical education is a method that is applied to formal nurse education as a step to provide real and direct learning experiences in the nursing environment correctly and effectively. The success of education in a clinical setting certainly requires the support of teaching nurses (clinical instructors) who have credibility and competence in terms of knowledge, attitudes and skills and are actively involved in professional activities. The diversity of backgrounds of nurses and students, including patients, certainly contributes to a shift in paradigms and perspectives for the nursing environment both in education and in clinical settings in health services. Responding to this cultural diversity, it is important to prepare knowledge and understanding related to transcultural nursing issues, intercultural communication and clinical education which explores the socio-cultural elements in the implementation of staff, students and patients. Purpose: The purpose of this literature review is to identify the extent to which nurse educators play a role by including socio-cultural and transcultural aspects in efforts to develop the quality of education in clinical practice environments in the millennium era. Method: The method of writing this article uses 11 literature review, the publication year period 2019,2020 and 2021 with sources from 4 databases such as science Direct, Scopus, ProQues and Elsevier. The review guidelines used are based on Prisma and the Joanna Briggs Institutute. The level of eligibility is identified through the title, abstract, research methodology as well as the type of scholarly journal and full text. Results: The results of the reviews found are presented in a narrative form. The results of the review study found that there were 11 articles explaining the competence of clinical education based on the socio-cultural approach, which is an educational strategy in the clinical area that integrates transcultural elements of nursing, intercultural communication, collaboration, self-directed with the principles of openness, honesty, and mutual respect in the implementation of team interaction and collaboration. The development of interpersonal relationships is also an important role that educators must have in helping to introduce the nurse orientation process to the organizational environment and other professional teams so that the achievement of satisfaction with clinical education is able to improve the performance of nurses and students perfectly. Conclusion: Clinical education which is supported by the competence of nurse educators (clinical instructors) who have individual and professional competences has a role to play in improving clinical learning outcomes by both students and nurses with a socio-cultural and transcultural strategic approach that will create satisfaction with the achievement of clinical competence and performance effectively.

With the continuous development of the mining industry, the world's major mines have gradually entered the intelligent stage. In the intelligent underground mine, the operation road of the underground transportation equipment is very complicated, and the monitoring and control of the underground traffic has become a problem to be solved in the intelligent underground mine. Therefore, on the basis of solving the practical problems of underground mines, the concept paper discusses the possibility of the rail transit monitoring system being applied to underground mines through the summary and induction of the related literature and propose the design for the CBTC system to solve the problems in the underground mine rail transportation. As the mining engineers, we put forward the concept of this design for the CBTC system in this concept paper, but we need to continue to work hard for the future development of the underground mines. And the concept paper serves as a guide to the Tossing out a brick to get a jade gem, has implications for the development and the future of the underground mine transportation.

Four new zoonotic coronaviruses outbreak occurred in the past two decades. The first coronavirus outbreak happened in 2003 and was named Severe Acute Respiratory Syndrome Coronavirus-1 (SARS-CoV-1), followed by Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in 2013, and by Swine Acute Diarrhoea Syndrome (SADS) in 2017. In late December 2019, a patient from Wuhan Seafood Wholesale Market, China, was admitted to Huang's hospital with respiratory distress syndrome (RDS) of apparently unknown etiology, which later was diagnosed with SARS-CoV-2-induced coronavirus disease-19 (COVID-19). SARS-CoV-2 was identified from another clade within the subgenus Sarbecovirus of the genus Betacoronavirus. This new CoV variant showed 96.2% similarity at whole-genome level to bat coronavirus. Based on genetic studies, pangolin, bats, and snakes are suspected to be a possible intermediate host of this virus, but further research is in progress to determine how this virus appeared and what is the exact source of infection. The SARS-CoV-2 outbreak has higher transmissibility, contagiosity and pathogenicity compared to that of SARS-CoV-1 and MERS-CoV. SARS-CoV-2 swiftly spread from continent to continent and is persistently causing a shocking global public health concern albeit the rate of infected cases and mortality is relatively decreasing over time. In this review, we provide an update on the origin, transmissibility, etiology, epidemiology, and evolution of COVID-19. We also highlight the current diagnostics, therapies, and prognostics for SARS-CoV-2. Eventually, we report and provide our humble opinion about the preventive strategies to control the ongoing related pandemic situation at global and individual levels, considering the international public health emergency and possible future epidemics and pandemics.

In MBSE there is yet no converged terminology. The term ’system model’ is used in different contexts in literature. In this study we elaborated the definitions and usages of the term ’system model’, to find a common definition. 104 publications have been analyzed in depth for their usage and definition as well as their meta-data e.g., the publication year and publication background to find some common patterns. While the term is gaining more interest in recent years it is used in a broad range of contexts for both analytical and synthetic use cases. Based on this three categories of system models have been defined and integrated into a more precise definition.

In this article, the geometry of pseudoparallel, Ricci-generalized pseudoparallel and 2-Ricci-generalized pseudoparallel invariant submanifolds of an almost $\alpha$-cosymplectic $(\kappa,\mu,\nu)$ space has been searched under the some conditions. We also give some characterizations for such submanifolds. I think that obtained new results contribute to differential geometry.

Reliable prediction of sustainable energy consumption is the key to designing environmental friend buildings. In this study, two novel hybrid intelligent methods, namely grasshopper optimization algorithm (GOA), wind-driven optimization (WDO), and biogeography-based optimization (BBO) is employed to optimize the multitarget prediction of heating loads (HLs) and cooling loads (CLs) in heating ventilation and air conditioning (HVAC) systems. Concerning the optimization of applied hybrid algorithms, a series of swarm-based iteration is performed, and the best structure for the abovementioned methods are proposed. Besides, through sensitivity analyzing the relationship between the HLs and CLs and influential factors are highlighted. In other words, the GOA, WDO, and BBO algorithm are mixed with a class of feedforward artificial neural networks (ANN), which called MLP (multi-layer perceptron) to predict the HLs and CLs. According to the provided sensitivity analysis, the WDO with swarm size = 500 proposes the most proper-fitted terms after it has been combined with optimized MLP. The proposed WDO-MLP (training (R2 correlation=0.977 and RMSE error=0.183) and testing (R2 correlation=0.973 and RMSE error=0.190)) provided accurate prediction in the heating load and (training (R2 correlation=0.99 and RMSE error=0.147) and testing (R2 correlation=0.99 and RMSE error=0.148)) presents the most-fit prediction in the cooling load.

Conformal radiotherapy is a primary treatment in head and neck cancer, which putative adverse effects depend on relatively low doses of radiation delivered to increased volumes of normal tissues. Systemic effects of such treatment include radiation-induced changes in serum lipid profile, yet dose- and volume-dependence of these changes remain to be established. Here we analyzed levels of choline-containing phospholipids in serum samples collected consecutively during the radiotherapy used as the only treatment modality. The LC-MS approach applied in the study enabled the detection and quantitation of 151 phospholipids, including (lyso)phosphatidylcholines and sphingomyelins. No statistically significant differences were found in the pre-treatment samples from patients with different location and stage of cancer. To compensate for potential differences between schemes of radiotherapy the biologically effective doses were calculated and used in the search of correlations with specific lipid levels. We found that the levels of several phospholipids depended on the maximum dose delivered to the gross tumor volume and total radiation energy absorbed by the patient’s body. Increased doses correlated with increased levels of sphingomyelins and reduced levels of phosphatidylcholines. Noteworthy, serum phospholipid levels were associated mainly with volumes of normal tissues irradiated with relatively low doses (i.e., total accumulated dose 20 Gy), which indicated the importance of such effects on the systemic response of the patient’s organism to IMRT.

Temperature is one of the most important range-limiting factors for many seaweeds. Driven by the recent climatic changes, rapid northward shifts of species’ distribution ranges can potentially modify the phylogeographic signature of Last Glacial Maximum such as increased genetic diversity at lower latitudes. To explore this question in detail in the kelp Saccharina latissima, we used microsatellites and double digest RAD-sequencing derived SNPs on S. latissima sporophytes sampled within 11 sites spanning the entire European Atlantic latitudinal range of this species. In addition, we checked for statistical correlation between genetic marker allele frequencies and three environmental proxies (sea surface temperature, salinity, and water turbidity). Our findings revealed that genetic diversity was significantly higher for the northern localities compared to the southern ones in contrast to the expected phylogeographic pattern. This suggests that the southernmost S. latissima populations are negatively affected by the recent climatic changes but also that the recolonization of S. latissima range following the LGM may have occurred from northerly refugia. Seven SNPs and 12 microsatellite alleles were found to be significantly associated with at least one of the three environmental variables. We discuss the potential adaptive functions of the genes associated with the outlier markers and the importance of these markers for successful conservation and aquaculture strategies for S. latissima in this age of rapid global change.

The dynamics involving market competition and the challenges of dealing with empowered customers, means that creating and delivering relevant customer experience (CX) of service, is as important as creating product or services. Several studies have treated customer experience as though a front-desk, sales-point affair with the customer in the retailing environment, negating the critical role of organization-wide efforts in the overall customer experience management sequence. This review, however, adopts customer-centricity, as a theoretical lens to underscore the [re]configuration of organizational-level factors that are critical to adopting a high customer-experienced centred organization. Based on the review, we highlight conditions for adopting high customer experience management organization: (1) developing an integrated CX strategy, (2) CX-based knowledge management, (3) organizational re-design that supports CX-management, (4) top management commitment, (5) integrated CX IT systems, and (6) CX-oriented HR policies. These practices are only necessary conditions, but not sufficient, for creating, delivering, relevant and sustainable customer experience. However, more robust empirical studies are needed to advance the application of organization-wide customer experience management, which vary across industry, products/services, and sector.

Greek yogurt (GY), a high-protein-low-fat dairy product, particularly prized for its sensory and nutritional benefits, revolutionized the North American yogurt market in less than a decade, bringing with it new sustainability challenges. The standard production of GY generates large volumes of acid whey, a co-product that is a potential source of environmental pollution if not recovered. This study aims to assess the environmental performance of different technologies and identify the main factors for improving GY production. A complete life cycle assessment (LCA) was performed to compare the standard technology (centrifugation) with two new technologies (fortification and ultrafiltration) to reduce acid whey volumes. Three milk protein concentrate alternatives were also assessed. Results show that the technology choice is not a clear discriminant factor. However, minimizing losses and wastage (accounting for 23 to 25% of the environmental impacts for all indicators) beyond the processing plant and selecting milk ingredients (accounting for 63 to 67% of the impacts) with low environmental impacts are key factors in improving the environmental performance of GY systems. From a methodological perspective, the results also highlight a shortcoming in the current International Dairy Federation LCA guidelines (2015) for treating the multifunctionality of GY systems.

Breast cancer develops from cells lining the milk ducts and slowly grows into a lump or a tumour. Breast cancer may be invasive or non-invasive. Invasive cancer spreads from the milk duct or lobule to other tissues in the breast, whereas, non-invasive ones lack the ability to invade other breast tissues. Non-invasive breast cancer is called in situ and may remain inactive for entire lifetime. Due to heterogeneity nature of breast, density as well as masses is variable in size and shape. A dataset of 18056 patients are collected from 20 Government Hospitals and 50 Private Hospitals in West Bengal before COVID-19 and after COVID-19. The classification of patients are made on three classes- Normal, Sign of Abnormality and Abnormality. The reports of MRIs of patients in January 2020 and February 2020 are collected from different hospitals. It is treated as dataset before COVID-19 . MRIS of patients in April 2020 and May 2020 are dataset during COVID-19. The entire datasets are accumulated for testing of any change in patients MRIS after the official announcement of new virus COVID-19 in March 2020. The aim of the paper is to make a comparison of any change in size and shape of masses of MRIs of patients before and after COVId-19. All collected MRIs reports are diagnosed by radiologists of hospitals.

COVID-19, caused by SARS-CoV-2, is responsible for widespread mortality and economic loss across almost 212 countries. The distribution of disease prevalence is, however, uneven and likely dependent on the range of human behavior and/or the pathogen and environmental variables. Here in this research we examined the correlation between daily and total COVID-19 case reports from Bangladesh and meteorological variables (average temperature, average humidity, and average wind speed) against one another using Spearman rank and Kendall correlation tests to highlight significant meteorological variables in relation to COVID-19. The tests revealed that both temperature and humidity had a non-significant correlation with COVID-19 transmission amid epicenter (EC) and non-epicenter (NEC) areas. However, a weak (KCC: 0.168, p < 0.05; SCC: 0.271, p < 0.05) correlation was found for temperature in ECs. Wind speed showed moderate to strong correlation in ECs with a very high statistical significance to both daily new cases [(KCC: 0.494, p < 0.01); (SCC: 0.689, p < 0.01)] and total cases [(KCC: 0.426, p < 0.01); (SCC: 0.617, p < 0.01)]. The COVID-19 transmission was found to have a weak (KCC: 0.354, p < 0.01) to moderate (SCC: 0.465, p < 0.01) correlation with daily new cases; however, a moderate (KCC: 0.497, p < 0.01) to strong (SCC: 0.712, p < 0.01) correlation with total cases was found in NECs. The results suggest that temperature and humidity have little influence on COVID-19 transmission, but wind speed may have some influence. Countries should prioritize social engineering to modify human behavior in order to combat the spread of COVID-19 and future pandemics.

Corporate sustainability reporting, also known as Triple-bottom-line reporting, involves reporting nonfinancial and financial information to a broader set of stakeholders than just shareholders and seek to fortify an organization’s ability to manage key risks. The current case is that, the quality, rigor, and utility of sustainability reporting remains contentious with concerns about the suitability of the criteria or standards used to prepare the reports. Despite the rapid increase in the number of companies around the world adopting Global Reporting Initiative standards, little is known about the extent of practice of corporate sustainability reporting in public universities in Kenya. The study selected five universities that had their 2017-18 audited financial reports available online for the readers, which served as the main source of secondary data. The guidelines on corporate sustainability reporting was derived from literature review, which provided key indicators upon which the data from each university was evaluated. It was observed that almost all the institutions recognize the critical role of both internal and external independent audit of financial statements. In conclusion, financial reporting sustainability is guided by strict compliance to the factors of sustainability.

The formation of sinkholes in Winkler County, Texas is concerning due to the amount of oil and gas infrastructure and the potential for catastrophic losses. Evidences of new and potential sinkholes have been documented, and determining the cause of these sinkholes is paramount to mitigate the devastating consequences thereof. Studies shown that the Wink sinkholes result from both natural and anthropogenic influences. Data depicting land-cover changes, alterations in the hydrologic systems, climate changes, and oil and gas activity were analyzed in an effort to better understand the link between these processes and sinkhole formation. Results indicate that the combination of these processes lead to the current state; Land cover changes were highest in shrub versus grasses, undeveloped to developed and croplands. Rises in temperature and a decrease in precipitation indicate a shift towards a more arid climate. Changes to the hydraulic system are a direct result of these land cover changes while the groundwater quality depict an environment prone to dissolution. Historical oil and gas activities have created pathways of meteoric water infiltration to the underlying limestone and evaporite formation. The combination of these processes create an environment that accelerates sinkhole formations. Understanding these processes allows for the development and implementation of better land practices, better groundwater protections, and the need for monitoring and maintaining aging oil and gas infrastructure.

The purpose of this systematic review is to provide second language acquisition (SLA) researchers with an overview of research trends in this field in the last ten years (2009-2019). In doing so, three international peer-reviewed journals, Studies in Second Language Acquisition, Language Teaching Research, and The Modern Language Journal, were selected. 150 articles were systematically selected and analyzed. The analysis of data resulted in identifying six descriptive themes. Results showed that some areas of second language acquisition still need further exploration while some areas are of great interest for researchers. Some suggestions for future research as well as implications of the study were discussed in detail.

Purpose: Localization and mapping with LiDAR data is a fundamental building block for autonomous vehicles. Though LiDAR point clouds can often encode the scene depth more accurate and steadier compared with visual information, laser-based Simultaneous Localization And Mapping (SLAM) remains challengeable as the data is usually sparse, density variable and less discriminative. The purpose of this paper is to propose an accurate and reliable laser-based SLAM solution. Design/methodology/approach: The method starts with constructing voxel grids based on the 3D input point cloud. These voxels are then classified into three types to indicate different physical objects according to the spatial distribution of the points contained in each voxel. A global environment model with Partition of Unity (POU) implicit surface is maintained along the process and located voxels are merged into it from stage to stage, through scan-to-model matching implemented by Levenberg-Marquardt method. Findings: We find a laser-based SLAM method. The method uses POU implicit surface representation to build the model and is evaluated on the KITTI odometry benchmark without loop closure. Experimental results indicate that the method achieves accuracy comparable to the state-of-the-art methods. Originality/value: We propose a novel, low-drift SLAM method, which falls into a scan-to-model matching paradigm, operates on point clouds obtained from Velodyne HDL64. The method is of value to researchers developing SLAM systems for autonomous vehicles.

The technique of obtaining information or data about any feature or object from afar, called in technical parlance as remote sensing, has proven extremely useful in diverse fields. In the ecological sphere, especially, remote sensing has enabled collection of data or information about large swaths of areas or landscapes. Even then, in remote sensing the task of identifying and monitoring of different water reservoirs has proved a tough one. This is mainly because getting correct appraisals about the spread and boundaries of the area under study and the contours of any water surfaces lodged therein becomes a factor of utmost importance. Identification of water reservoirs is rendered even tougher because of presence of cloud in satellite images, which becomes the largest source of error in identification of water surfaces. To overcome this glitch, the method of the shape matching approach for analysis of cloudy images in reference to cloud-free images of water surfaces with the help of vector data processing, is recommended. It includes the database of water bodies in vector format, which is a complex polygon structure. This analysis highlights three steps: First, the creation of vector database for the analysis; second, simplification of multi-scale vector polygon features; and third, the matching of reference and target water bodies database within defined distance tolerance. This feature matching approach provides matching of one to many and many to many features. It also gives the corrected images that are free of clouds.

We report on the field testing datasets and performance evaluation results obtained from a commercial property-based visually-clear solar window installation site in Perth-Australia. This installation was fitted into a refurbished shopping centre entrance porch, and showcases the potential of glass curtain wall-based solar energy harvesting in built environments. In particular, we focus on photovoltaic (PV) performance characteristics such as the electric power output, specific yield, day-to-day consistency of peak output power, and the amounts of energy generated and stored daily. The dependencies of the generated electric power and stored energy on multiple environmental and geometric parameters are also studied. An overview of the current and future application potential of high-transparency, visually-clear solar window-based curtain wall installations suitable for practical building integration is provided.

In this paper, we introduce the Prognostics and Health Management of gear bearing system using autoencoder neural networks. Bearings and gears are the most common mechanical components in rotating machines, and their health conditions are of great concern in practice. This study presents an outlier modeling method for forecasting the gear bearing system failure using the health indicators constructed from mechanical signal processing and modeling. Outlier modeling aims to find patterns in data that are significantly different from what is defined as normal. In the unsupervised outlier modeling setting, prior labels about the anomalousness of data points are not available. In such cases, the most common techniques for scoring data points for outlyingness include distance-based methods density-based methods, and linear methods. The conventional outlier modeling methods have been used for a long time to detect anomalous observations in data. However, this paper shows that autoencoders are a very competitive technique compared to other existing methods. The developed method is demonstrated using the IMS bearing data from NASA Acoustics and Vibration Database.

Attitudes and behaviours towards the natural environment have been extensively studied in certain cultural settings during the last 40 years. In education, the teacher's ability to grasp the fundamentals of an academic subject may define his or her own attitudes towards that discipline; certainly the reverse is also valid. The correlations between affective and cognitive domains appear to play a significant role in teaching-learning dynamics. In this study we seek to assess whether the affective posture towards school sciences of a cohort of teachers in rural communities shows an association with their cognitive competence in the disciplines. The results of this study provide evidence that there is a statistically significant correlation between the cognitive and affective domains for in-service teachers. The affective domain, therefore, could serve as a predictor for cognitive competency and self-efficacy expectancies with respect to both content and career fulfilment.

As a holistic medical school, Iranian traditional medicine (ITM) considers the human body as a dynamic and intricate network of interconnecting processes. Currently, systems biology and more precisely systems medicine and pharmacology can be an aid in providing rationalizations for many traditional medications and treatments and elucidating a great deal of knowledge they can offer to guide future research in medicine. Therefore, re-organization and standardization of traditional medicine data are requested more than ever before. To address this issue, we have constructed UNaProd, a Universal Natural Product database for materia medica of ITM. Primarily based on Makhzan al-Advieh, which is the most recent encyclopedia of materia medica in ITM with the largest number of monographs, this database was created using both text mining methods and manual editing. UNaProd is currently hosting to 2696 monographs from herbal to animal to mineral compounds in 16 diverse attributes such as origin and scientific name. In the current version, UNaProd is hyperlinked to IrGO and CMAUP databases for Mizaj and molecular features respectively and it is freely available at http://jafarilab.com/unaprod/.

Nowadays, the development or improvement of actuation mechanisms is a crucial topic for the achievement of dextrous manipulation using soft robots. Then, a primary target of research is the design of actuation and driving devices. Consequently, in this paper, we introduce a soft driving epicyclical mechanism that mimics human muscle behavior and fulfills motion requirements to achieve grasping gestures using a robotic finger. The prototype is experimentally assessed, and results show that our approach has enough performance for the implementation in grasping tasks. Furthermore, we introduce the basis for a new soft epicyclical mechanism merger with shape memory alloys to allow active stiffness control of the mechanism.

In this paper, we propose a novel approach of video skimming by exploiting the fusion of video temporal information and keyword information representation extracted from multi-model video information including audio, text and visual indices. In addition, we introduce the brand-safe filtering and sentiment analysis in order to only reserve the user-friendly content in the video skim. In the experiment by using the videos from YouTube-8M dataset, we have proved that the semantic conservation in the video skim from the proposed approach highly outperforms the approaches by only partial information of the video in conserving the semantic content of the video.

We investigate the value distribution of dierence polynomials of entire and meromorphic functions, which can be viewed as the Hayman's conjecture. And we also study the uniqueness of dierence polynomials sharing a common value.

This case study assessed marketing arrangements used by small scale farmers in the Lake Basin and Lower Eastern bean corridors of Kenya to determine which markets work for rural producers and what changes are needed to produce and supply sufficient quantities for trade. Using exploratory research, data was collected through focus group discussions with six farmer groups representing a total of 1255 bean farmers and key informant interviews with extension staff. The results indicated that 94% of the farmers produced beans before identifying buyers with only 6% participating in group marketing. Though spot-market transactions with brokers and traders provided ready cash for the farmers, formal buyers were perceived to be more reliable but difficult to find and, operated stringent requirements which were a barrier to entry. A theory of change to integrate smallholders into formal markets to sustainably produce and supply sufficient volumes for trade should entail a transformation agenda at four levels of the value chain: intensification of production through pure stand models with greater use of certified high yielding varieties; stable price guarantees; a market-driven research and extension service and; an enabling political, policy and business environment in the bean value chain. Further research is needed to pilot these changes in a case control study.

This brief review highlights some current issues in Galactic stellar nucleosynthesis, and some recent laboratory studies by the Wisconsin atomic physics group that have direct application to stellar spectroscopy, in order to advance our understanding of the chemical evolution of our Galaxy. The relevant publication history of the lab studies are summarized, and investigations into the abundances of neutron-capture and iron-peak elements in low metallicity stars are described. Finally, new initatives in near-infrared spectroscopy are briefly explored.

This paper describes a case study for applying of hybrid-electric propulsion system for a general aviation aircraft. The work was performed by a joint team of CIRA and the Department of Industrial Engineering of the University of Naples “Federico II”. Electric and hybrid electric propulsion for aircraft has gained widespread and significant attention over the past decade. The driver for industry interest has principally been the need to reduce emissions of combustion engine exhaust products and noise, but increasingly studies revealed potential for overall improvement in energy efficiency and mission flexibility of new aircraft types. The project goal was to demonstrate feasibility of aeronautic parallel hybrid-electric propulsion for a Light aircraft varying the mission profiles and the electric configuration. Through a creation, and application, of a global model, with software AMESim^®, in which it can be represented everything about the components chosen by the industrial partners, some interesting considerations are carried out. In particular, it was confirmed that with the only integration of state of the art technologies, for some particular missions, the advantages of aircraft hybrid-electric propulsion, for light aircraft, are notable.

Recent advances in sensor and platform technologies such as satellite systems, unmanned aerial vehicles (UAV), manned aerial platforms, and ground-based sensor networks have resulted in massive volumes of data is produced and collected about the earth. Processing, managing, and analyzing these data is one of the main challenges in 3D synthetic representation used in modeling and simulation (M&S) of the natural environment. M&S devices, such as flight simulators, traditionally require a variety of different databases to provide a synthetic representation of the world. M&S often requires integration of data from a variety of sources stored in different formats. Thus, for simulation of a complex synthetic environment, such as a 3D terrain model, tackling interoperability among its components (geospatial data, natural and man-made objects, dynamic and static models) is a critical challenge. Conventional approaches used local proprietary data models and formats. These approaches often lacked interoperability and created silos of content within the simulation community. Therefore, open geospatial standards are increasingly perceived as a means to promote interoperability and reusability for 3D M&S. In this paper, the Open Geospatial Consortium (OGC) CDB Standard is introduced. “CDB” originally refers to Common DataBase which is currently considered as a name with no abbreviation in the OGC community. The OGC CDB is an international standard for structuring, modeling, and storing geospatial information required in high performance modeling and simulation applications. CDB defines the core conceptual models, use cases, requirements, and specifications for employing geospatial data in 3D M&S. The main features of the OGC CDB Standard are described as run-time performance, full plug-and-play interoperable geospatial data store, usefulness in 3D and dynamic simulation environment, ability to integrate proprietary and open-source data formats. Furthermore, compatibility with the OGC standards baseline reduces the complexity of discovering, transforming, and streaming geospatial data into the synthetic environment and makes them more widely acceptable to major geospatial data/software producers. This paper includes an overview of OGC CDB version 1.0 which defines a conceptual model and file structure for the storage, access, and modification of a multi-resolution 3D synthetic environment data store. Finally, this paper presents a perspective of future versions of the OGC CDB and what the steps are for humanizing the OGC CDB standard with the other OGC/ISO standards baseline.

Glacier dynamics play an important role in the mass balance of many glaciers, ice caps and ice sheets. In this study we exploit Radarsat-2 (RS-2) Wide Fine (WF) data to determine the surface speed of Svalbard glaciers in the winters of 2012/2013 and 2013/2014 using Synthetic Aperture RADAR (SAR) offset and speckle tracking. The RS-2 WF mode combines the advantages of the large spatial coverage of the Wide mode (150 x 150 km) and the high pixel resolution (9m) of the Fine mode and thus has a major potential for glacier velocity monitoring from space through offset and speckle tracking. Faster flowing glaciers (1.95 m d^-1 - 2.55 m d^-1) which are studied in detail are Nathorstbreen, Kronebreen, Kongsbreen and Monacobreen. Using our Radarsat-2 WF dataset, we compare the performance of two SAR tracking algorithms, namely the GAMMA Remote Sensing Software and a custom written MATLAB script (GRAY method) that has primarily been used in the Canadian Arctic. Both algorithms provide comparable results, especially for the faster flowing glaciers and the termini of slower tidewater glaciers. A comparison of the WF data to RS-2 Ultrafine and Wide mode data reveals the superiority of RS-2 WF data over the Wide mode data.

In May of 2022, millions of U.S. parents faced uncertainty in safely feeding their infants due to the infant formula shortage. Methods: An anonymous, electronic, cross-sectional, retrospective survey was used. Results: U.S. parents (n =187) whose infants were 10.2 weeks old during the short-age completed the survey. Eighty-one percent of parents switched formulas during the shortage, 87% switched because they could not find the formula they typically used, 34% switched 3-5 times, 29% of parents visited ≥ 4 stores/24 hours and 26% of parents traveled >20 miles/24 hours to purchase formula. Use of infant formula increased (p< 0.01); in infants requiring specialty for-mula, use of intact cow’s milk formula increased (p < 0.05) and use of premature infant formulas decreased (p < 0.05). Infants relying on specialty formulas experienced at least one undesirable outcome compared with non-specialty users. Parents used social media, relatives/friends, and healthcare providers for support during the shortage, but their helpfulness scores were suboptimal. Parents reported needs for greater infant formula availability, free prenatal lactation education and postpartum lactation support. Conclusions: Government, regulatory and healthcare policy oversight are needed to protect the infant feeding system, including more commercially available products, access to banked donor milk and lactation support.

The persistence of geographic inequities in vaccination coverage often evidences the presence of zero-dose and missed communities and vulnerabilities to vaccine-preventable diseases. These inequities were exacerbated in many places during the COVID-19 pandemic, due to severe disruptions to vaccination services. Understanding changes in zero-dose prevalence and associated risk factors in the context of the COVID-19 pandemic is, therefore, critical to designing effective strategies to reach vulnerable populations. Using data from nationally representative household surveys conducted before the COVID-19 pandemic in 2018 and during the pandemic in 2021 in Nigeria, we fitted Bayesian geostatistical models to map the distribution of three vaccination coverage indicators: receipt of DTP1, MCV1 and any of the four basic vaccines (BCG, OPV0, DTP1 and MCV1), and corresponding zero-dose estimates independently at 1x1 km resolution and the district level during both time periods. We also explored changes in the factors associated with non-vaccination at the national and regional levels using multilevel logistic regression models. Our results revealed no increases in zero-dose prevalence due to the pandemic at the national level, although considerable increases were observed in a few districts. We found substantial subnational heterogeneities in vaccination coverage and zero-dose prevalence both before and during the pandemic, showing broadly similar patterns in both time periods. Areas with relatively higher zero-dose prevalence occurred mostly in the north and a few places in the south in both time periods. We also found consistent areas of low coverage and high zero-dose prevalence using all three zero-dose indicators, revealing areas in greatest need. At the national level, risk factors related to socioeconomic/ demographic status (e.g., maternal education), maternal access to and utilization of health services and remoteness were strongly associated with the odds of zero dose in both time periods, while those related to communication were mostly relevant before the pandemic. These associations were also supported at the regional level, but we additionally identified risk factors specific to zero dose in each region; for example, communication and cross-border migration in the northwest. Our findings can help guide tailored strategies to reduce zero-dose prevalence and boost coverage levels in Nigeria.

Piezoelectric ultrasonic motors (USMs) are actuators that use ultrasonic frequency piezoelectric vibration generated waves to transform electrical energy into rotary or translating motion. USMs are paid more attention because they offer distinct qualities over traditional magnet-coil-based motors, such as miniaturization, great accuracy, speed, non-magnetic nature, silent operation, straightforward construction, broad temperature operations, and adaptability. This review study focuses on the principle of USMs and their classifications, characterization, fabrication methods, applications, and future challenges. Firstly, the classifications of USMs, especially, standing wave, traveling wave, hybrid mode, multi degree of freedom USMs are summarized, and their respective functioning principles are explained. Secondly, the finite element modelling analysis for design and performance predictions, the conventional and nano/micro fabrication methods, and, the various characterization methods are presented. Thirdly, their advantages, such as high accuracy, small size, and silent operation and their benefits over conventional motors for the different specific applications are examined. In addition, the substantial contributions to a variety of tech-nical fields like surgical robots, industrial, aerospace, and biomedical applications are introduced. Finally, their future prospects and challenges in USMs development, with an emphasis on downsizing, increasing efficiency, and new materials are outlined.

This paper presents a method of fusion of identification (attribute) information provided by two types of sensors: combined primary and secondary (IFF) surveillance radars and ESM (Electronic Support Measures). In the first section, the basic taxonomy of attribute identification is adopted in accordance with the standards of STANAG 1241 ed. 5 and STANAG 1241 ed. 6 (draft). These standards provide the following basic values of the attribute identifications: FRIEND, HOSTILE, NEUTRAL, UNKNOWN and additional values: ASSUMED FRIEND and SUSPECT. The basis of theoretical considerations is Dezert-Smarandache theory (DSmT) of inference. The paper presents and practically uses for combining identification information from different ESM sensors and radars six information fusion rules proposed by DSmT - the Proportional Conflict Redistribution rules (PCR1, PCR2, PCR3, PCR4, PCR5 and PCR6). In the paper, rules of determining attribute information by ESM sensor equipped with the data base of radar emitters are presented. It was proposed that each signal vector sent by the ESM sensor contained an extension specifying a randomized identification declaration (hypothesis) - basic belief assignment (BBA). The paper also presents a model for determining the basic belief assignment for a combined primary and secondary radar. Results of the PCR rules of sensor information combining for different scenarios of radio-electronic situation (deterministic and Monte Carlo) are presented in the final part of the paper. They confirm the legitimacy of the use of Dezert-Smarandache theory into information fusion for primary radars, secondary radars and ESM sensors.

Celiac disease (CD) is a genetically conditioned autoimmune process that appears in susceptible people. It can affect people of any age, and slightly predominates in females. It has a fairly homogenous global distribution, with an average prevalence of 1-2%, the frequency having increased in recent decades. The only effective treatment is a strict and permanent gluten-free diet (GFD), although the level of compliance with it is poor, at about 50% of cases. To monitor the effectiveness of the GFD, several procedures involving various approaches are employed: a) periodic interviews by nutritionists; b) clinical follow-up; c) serological controls of specific antibodies; d) endoscopies with collection of duodenal biopsies; e) structured questionnaires; f) determination of gluten peptides derived from gluten in feces and/or urine. All of these procedures are useful when applied, alone or in combination, depending on the cases. Some patients will only need to consult to their doctors, while others will require a multidisciplinary approach to assess their compliance with the GFD. In children, normalization of duodenal mucosa was achieved in 95% of cases within 2 years, while it is more delayed in adults, whose mucosa take longer to heal completely.

In this paper, we make an attempt to estimate the famous Avogadro number with programming logics written in Python associated with advanced nuclear binding energy formulae. Average rest mass of nucleon, nuclear binding energy per nucleon and electron rest mass seem to play a vital role in estimating the unified atomic mass unit and Avogadro number. Interesting point to be noted is that, Avogadro number seems to be the inverse of the Unified atomic mass unit. With further study, it seems possible to estimate the unified atomic mass unit and Avogadro number accurately. Our interesting observation is that, short range strong nuclear force seems to have a vital role in deciding the accuracy of Avogadro number. For that purpose one may consider AI techniques along with newly observed atomic nuclides and their nuclear binding energies. For Z=6 to 118 and A_low=2Z and A_upper=3.5Z, estimated average value of Avogadro number is $N_{Average} \cong 6.01938 \times 10 ^{26}$. Considering the saturation of nuclear binding energy, at Z=26, $N_{Z=26} \cong \left(6.02229 \textrm{to} 6.02285\right) \times 10 ^{26}$. At academic level, our proposal can be given a chance as a case study. It is planned to develop a web application for this purpose.

The water resources carrying capacity (WRCC) system comprises multiple complex and nonlinear interactions related to society, economy, water resources and the water environment. A full understanding of its internal mechanism is conducive to the further improvement of the regional WRCC. This article focuses on the temporal and spatial variability of WRCC to explore a method of dynamic successive assessment. Firstly, the Pressure-State-Response (PSR)framework is used to develop a systematic and causal indicator system. Then, The Variable Fuzzy Pattern Recognition (VFPR) model and an analytic hierarchy process-entropy (AHP-E) model are combined to successively and dynamically assess WRCC. The proposed method is applied to the dynamic successive assessment of WRCC in Hebei Province, and it is obtained that the poor water resources carrying capacity in Hebei Province is mainly due to the basic attribute of the decision of the water resources shortage, but Hebei Province actively adopts a variety of measures to save water and pressurize mining, which makes the province's water resources carrying capacity have a tendency to become better gradually. At the same time, the system dynamics model (SD) of water resources carrying capacity based on the analysis of the model structure was established. Moreover, three scenarios were designed, including existing continuation, high-efficiency water-saving, cross-regional water transfer and coordinated development, each scenario divided into high and low-speed economic development and population growth schemes, then total 6 schemes between 2023 and 2030 were simulated and predicted respectively. The results indicate that if the current development model is adopted, the water resource carrying capacity will continue to maintain low levels. It was concluded that the high-speed development of economy and population, the efficient water conservation and inter-basin transfer scenario (scenario 2 with high-speed) is the best choice for sustainable development of water resources and social economy in Hebei.

Peptides of hydrolysates of food proteins are an easily digestible source of amino acids necessary for the body to adapt to physical stress. Commercially significant hydrolysates include whey protein, casein, and other animal proteins. Hydrolysates of plant proteins are gaining popularity, but they are less common, then animal ones. Soy protein isolate is promising for obtaining the hydrolysates due to its affordable price and balanced amino acid profile. However, there are no direct studies showing an improvement in the result of physical activity when eating soy protein isolate hydrolysate (SPIH). In this work, for the first time, the study was conducted on the safety and efficacy of SPIH during physical load on model animals (rats). It was shown that the hydrolysate did not lead to pathological changes in the viscera, food intake, and weight of animals did not differ from the control group (animals consumed whey protein). Under physical load rats enteral fed SPIH showed a tendency to adapt more quickly to physical stress than the control group and the group of animals that was fed by free amino acids. The metabolites of animal blood serum were studied by NMR spectroscopy. It was shown that by the 95th minute after feeding in the group of rats receiving SPIH, the difference of proteinogenic amino acids concentrations in blood between individuals was significantly less than in the groups receiving whey protein or a mixture of amino acids. In other words, individual biochemical and physiological characteristics of individuals did not affect the assimilation of amino acids of hydrolysate.

Eco-innovation denotes developing green practices using environmentally friendly innovative approaches or technologies. Although, eco-innovation has been broadly applied in different in-dustries, such as low-carbon production and manufacturing, how to implement such innovation in education for sustainable development (ESD) has rarely been studied. Therefore, this research considered a reflective and cooperative learning approach to science, technology, engineering, arts, and math (STEAM) education. A case study examined Wanluan Township of Pingtung County in southern Taiwan. Four departments’ students and teachers at Meiho University were involved in situated learning. Students of hospitality management played farm owners who en-gaged in organic agriculture to produce food and beverages. These agricultural products were farm-to-table, cooked and served for customers in a natural dining setting through the students’ teamwork. Students of tourism, sports & leisure management, and food science & nutrition played tourists in a self-guided travel context, who engaged in acts such as visiting buildings to understand heritage while observing that the houses were still in use a dwelling. This encouraged reflection on the importance of cultural preservation. According to the results from the role-play farm owners and tourists, eco-innovation can represent a sustainable marketing strategy for im-proving the local-community economy and can be implemented in a practical situation in STEAM. The goal of ESD for 2030 — societal transformation — is to foster students’ responsible behavior and attitudes in a personally authentic manner, thereby fostering sustainability learning and understanding.

Melting phase relations of the diamond-forming system olivine (Ol) – jadeite (Jd) – diopside (Di) – (Mg, Fe, Ca, Na)-carbonates (Carb*) – (C-O-H-fluid) are studied in experiments at 6.0 GPa in the polythermal section Ol74Carb*18.5(C-O-H)7.5 - Omp74Carb*18.5(C-O-H)7.5, where Ol = Fo80Fa20, Omp (omphacite) = Jd62Di38 and Carb* = (MgCO3)25(FeCO3)25(CaCO3)25(Na2CO3)25. Peritectic reaction of olivine and jadeite-bearing melt with formation of garnet has been determined as a physico-chemical mechanism of ultrabasiс-basiс evolution of the diamond-forming system. In the process CO2-component of the supercritical C-O-H-fluid can react with silicate components to form additional carbonates of Mg, Fe, Ca and Na. Solidus temperature of the diamond-forming system is depressed to 1000-1020°C by joint effect of the H2O-fluid and carbonate constituents thereof. The experimentally recognized peritectic mechanism of ultrabasiс-basiс evolution of the diamond-forming system explains the origin of the associated paragenetic inclusions of peridotite and eclogite minerals in diamonds as well as the xenoliths of diamond-bearing peridotites and eclogites of the kimberlitic deposits of diamond. The diamond-forming systems have formed with the use of material of the upper mantle native peridotite rocks. In this case the capacity of the rocks to run the peritectic reaction of olivine was transmitted with silicate components to the diamond-forming systems.

The stimulus-secretion coupling of glucose-induced release is generally attributed to the metabolism of the hexose in the β-cells in the glycolytic pathway and the citric acid cycle. Glucose metabolism generates an increased cytosolic concentration of ATP and of the ATP/ADP ratio that closes the ATP-dependent K+-channel at the plasma membrane by the interaction of ATP with the regulatory Kir6.2 channel subunit The resultant depolarization of the β-cells opens voltage-dependent Ca2+-channels at the plasma membrane that allow an increase of the cytosolic cation concentration that triggers the exocytosis of insulin secretory granules. The resultant secretory response evolves in time as a biphasic secretion with a first and transient peak of approximately 10 minutes duration followed by a sustained phase of secretion lasting as long as the stimulus. Whereas the first transient peak can be reproduced by a simple depolarization of β-cells with high extracellular KCl maintaining the KATP-channels open with diazoxide, the sustained phase is agreed to depend on the participation of some metabolic signal that remains to be determined Our group has been investigating for several years the participation of β-cell GABA metabolism, together with that of glucose (the β-cell “specific” nutrient secretagogue) and some other “metabolic” secretagogues (branched-chain alpha-ketoacids and a mixture of L-Leucine + L-glutamine, at supraphysiological concentrations) in their mechanism of stimulation of insulin secretion. All three types of stimuli promote the flux in the GABA shunt of rat islets by different metabolic pathways that end in the production of α-ketoglutarate. This citric acid cycle intermediary is preferentially derived to the GABA shunt instead of its continuous oxidation in the citric acid cycle. Islet content of GABA is significantly suppressed by all the stimuli and blocking the GABA shunt with gabaculine, or ϒ-vinyl-GABA (GABAT inhibitors), diminish the insulin secretory responses as well as total ATP and the ATP/ADP ratio. It is concluded that GABA metabolism is increased in parallel to glucose metabolism and is significantly contributing to the magnitude of the insulin secretory response. Its possible implication in β-cells degradation in type-2 (perhaps also in type 1) diabetes is suggested.

The study presented hereafter shows a new methodology to reveal traces of polyethylene (the most common microplastic particles, known as a structure of C2H4) in a sample of ocean water by the irradiation of a 50 keV, 1 µA electron beam. This is performed by analyzing the photon (produced by the electrons in water ) fluxes and spectra (i.e. fluxes as a function of photon energy) at different types of contaminated water with an adequate device and in particular looking at the peculiar interactions of electrons/photons with the potential abnormal atomic hydrogen (H), oxygen (O), carbon (C), phosphorus (P) compositions present in the water, as a function of living and not living organic organisms with a PO4 group RNA/DNA strands in a cluster configuration through a volumetric cells grid.

Teachers’ time resources are becoming increasingly scarce and time poverty will have a direct impact on the long-term sustainability of their professional development. However, the current state of teachers’ time poverty and its potential harmful consequences are unclear. Therefore, this research conducts two cross-sectional studies to investigate the current situation and group differences in time poverty among Chinese teachers (Sample 1), as well as the influence of teachers’ time poverty on job burnout (Sample 2). The results indicate that: (1) there is a high level of time poverty among teachers; (2) there is no significant difference in gender, teaching years, or teaching section, and there is a significant difference in teaching responsibilities; (3) time poverty could positively and significantly predict job burnout, and job burnout could positively and significantly predict mental health; (4) mental health factors (including depression, anxiety and stress) play the mediating role in the relationship between teachers’ time poverty and job burnout. To create a sustainable development environment for teachers, it is suggested that teachers improve time management skills and establish a self-regulation mechanism; schools should clarify the boundaries of teachers’ work and respect their right to rest; and society should provide positive and adequate spiritual support.