Nuclear export of viral mRNAs, is an essential step in the HIV replication cycle. This role is played by a small regulatory protein of HIV-1 called Rev.The N-terminal region of Rev contains an arginine-rich sequence. The arginine-rich motif (ARM) is located between amino acids 38-50 and forms an alpha-helical secondary structure. Expression of the structural proteins of human immunodeficiency virus type 1 requires the direct interaction of multiple copies of the viral Rev protein with its highly structured RNA target sequence, the Rev Response element (RRE). The major viral proteins are not produced if this transport of RNA is stopped. Therefore, knowledge of Rev structure is essential for understanding of its cooperative binding to the RRE, for understanding the mechanism of HIV infection and for the development of antiviral drugs that interfere with Rev’s essential functions and for acknowledgment of good candidate drugs for treatment of AIDS. To understand how REV interact with RRE element of HIV-RNA and its formation of oligomeric complex it is better to characterize the domain wise structure of REV with regard in function of each domain. Due to lack of structural data on Rev no single compound is reported as inhibitor of REV expect antiviral drugs. Identification of a high-affinity RNA-binding site for the human immunodeficiency virus type 1 Rev Protein is much more important. The ARM is a highly specific sequence which allows for the multimerization of Rev and also binding of REV with RNA. Here we are first time exploring the structural characteristics of REV protein both in free form and in complex with RNA at domain function level especially explore the role of ARM motif in REV HIV-1 protein as RNA binding sites by molecular dynamics (MD) simulation and homology modeling studies. Results indicate that the arginine-rich motif (ARM) is crucial in stability of this complex. The residues ARG38, 39, 41, 43, 44, 48, 50, and ASN40 are most interacting with nucleobases of RRE in Crystal structure of Rev and Rev-response-element RNA complex. Our study plays a major role in elaboration of binding of RNA with REV and pave the way for further investigation for therapeutically agent for HIV.

Human factors are the most relevant issues contributing to adverse events in obstetrics. Specific training of Crisis Resource Management (CRM) skills (i.e., problem solving and team management, resource allocation, awareness of environment, and dynamic decision-making) are now widespread and are often based on High Fidelity Simulation. In order to be used as a guideline in simulated scenarios, they need to be translated into specific and observable behavioral markers. To this purpose, we developed a set of observable behaviors related to the main elements of CRM in the delivery room. The observational tool was then adopted in a two-days seminar on obstetric hemorrhage where teams working in obstetric wards of six Italian hospitals took part to simulations. The tool was used as guide for the Io and as a peer-to-peer feedback. It was then rated for its usefulness in facilitating the reflection upon one’s own behavior, its ease of use, and its usefulness for the peer-to-peer feedback. The ratings were highly positive, around 4 in a 5-point scale. The CRM observational tool is therefore a useful, quick and easy solution to facilitate the debriefing, the peer-to-peer feedback and, most of all, the transfer of safe behavior from simulation to everyday practice.

Fiber-metal laminates (FMLs) such as Kevlar reinforced aluminum laminate (ARALL), Carbon reinforced aluminum laminate (CARALL), and Glass reinforced aluminum laminate (GLARE) offer great potential for weight reduction applications in automobile and aerospace construction. In order to investigate the feasibility for utilizing such materials in the form of laminates, sheet hydro-bulging tests are studied under the condition of uniform blank holder force for three-layered aluminum and aluminum-composite laminates using orthogonal carbon and Kevlar as well as glass fiber in the middle. The experimental results validate the finite element results and they exhibited that the forming limit of glass fiber in the middle is the highest among the studied materials, while carbon fiber material performs the worst. Furthermore, the crack modes are different for the three kinds of fiber materials investigated in the research. This study provides fundamental guidance for the selection of multi-layer sheet materials in the future manufacturing field.

The future of machine tools will be dominated by highly flexible and interconnected systems, in order to achieve the required productivity, accuracy and reliability. Nowadays, distortion and vibration problems are easily solved in labs for the most common machining operations by using models based on equations describing the physical laws of the machining processes; however additional efforts are needed to overcome the gap between scientific research and the real manufacturing problems. In fact, there is an increasing interest in developing simulation packages based on “deep-knowledge and models” that aid machine designers, production engineers or machinists to get the best of the machine-tools. This article proposes a methodology to reduce problems in machining by means of a simulation utility, which uses the main variables of the system&process as input data, and generates results that help in the proper decision-making and machining planification. Direct benefits can be found in a) the fixture/clamping optimal design, b) the machine tool configuration, c) the definition of chatter-free optimum cutting conditions and d) the right programming of cutting toolpaths at the Computer Aided Manufacturing (CAM) stage. The information and knowledge-based approach showed successful results in several local manufacturing companies and are explained in the paper.

The next future using machine tools will be dominated by highly flexible and interconnected systems, in order to achieve the required productivity, accuracy and reliability. Nowadays, distortion and vibration problems are easily solved for the most common cases by sing models based on equations describing the physical laws dominating the machining process; however additional efforts are needed to overcome the gap between scientific research and the real manufacturing problems. In fact, there is an increasing interest in developing simulation packages based on “deep knowledge and models” that aid the machine designer, the production engineer, or machinists to get the best of their machines. This article proposes a systematic methodology to reduce problems in machining by means of a simulation utility, which recognizes, collects and uses the main variables of the system/process as input data, and generates objective results that help in the proper decision-making. Direct benefits by such an application are found in a) the fixture/clamping optimal design, b) the machine tool configuration, c) the definition of chatter free optimum cutting conditions and the right programming of cutting tool path at the Computer Aided Manufacturing (CAM) stage. The information and knowledge-based approach showed successful results in several local manufacturing companies.

Some of the barriers preventing Virtual Reality (VR) from being widely adopted are the cost and unfamiliarity of VR systems. Here we propose that in many cases the specialized controllers shipped with most VR head-mounted displays can be replaced by a regular smartphone, cutting the cost of the system, and allowing users to interact in VR using a device they are already familiar with. To achieve this, we developed SmartVR Pointer, an approach that uses smartphones as a replacement for the specialized controllers for two essential operations in VR: selection and navigation by teleporting. In SmartVR Pointer a camera mounted on the head-mounted display (HMD) is tilted downwards so that it points to where the user will naturally be holding their phone in front of them. SmartVR Pointer supports three selection modalities: tracker-based,gaze-based, and combined/hybrid. In the tracker-based SmartVR pointer selection we use image-based tracking to track a QR code displayed on the phone screen and them map the phone’s position to a pointer shown within the field of view of the camera in the Virtual Environment. In the gaze-based selection modality the user places the pointer using their gaze and taps on the phone for selection. The combined technique is a hybrid between head-gaze-based interaction in VR and smartphone-based Augmented Reality. It allows the user to control a VR pointer that behaves like a mouse pointer by moving their smartphone to select objects within the virtual environment, and to interact with the selected objects using the smartphone’s touch screen. The touchscreen is used for selection and dragging. SmartVR Pointer is simple and requires no calibration and no complex hardware assembly or disassembly. We demonstrate successful interactive applications of SmartVR Pointer in a VR environment with a demo where the user navigates in the virtual environment using teleportation points on the floor and then solves a Tetris-style key-and-lock challenge.

The human mind is multimodal. Yet most behavioral studies rely on century-old measures of behavior—task accuracy and latency (response time). Multimodal and multisensory analysis of human behavior creates a better understanding of how the mind works. The problem is that designing and implementing these experiments is technically complex and costly. This paper introduces versatile and economical means of developing multimodal-multisensory human experiments. We provide an experimental design framework that automatically integrates and synchronizes measures including electroencephalogram (EEG), galvanic skin response (GSR), eye-tracking, virtual reality (VR), body movement, mouse/cursor motion and response time. Unlike proprietary systems (e.g., iMotions), our system is free and open-source; it integrates PsychoPy, Unity and Lab Streaming Layer (LSL). The system embeds LSL inside PsychoPy/Unity for the synchronization of multiple sensory signals—gaze motion, electroencephalogram (EEG), galvanic skin response (GSR), mouse/cursor movement, and body motion—with low-cost consumer-grade devices in a simple behavioral task designed by PsychoPy and a virtual reality environment designed by Unity. This tutorial shows a step-by-step process by which a complex multimodal-multisensory experiment can be designed and implemented in a few hours. When conducting the experiment, all of the data synchronization and recoding of the data to disk will be done automatically.

There is a lot of pressures from organizations to continually redesign the business processes and the technology infrastructure to support the organization, but to also help organizations manage competing stakeholder needs, changing objectives and behaviour, and so on. A key part of this is making sure that all their activities in the different components of the business are interconnected and that they are moving in the same direction. Enterprise Architecture (EA) is an effective way of dealing with the challenge of designing business activities and supporting IT. This paper will summarize the organization of EA and look more closely at some major components of EA: governance architecture, business architecture, information architecture and technical architecture and consider the overlap and constructive interaction involved. Enterprise Architecture can be best understood through business process redesign. So, it is useful to briefly review the leading frameworks for business process redesign, including COBIT from ISACA, LEAN from the Toyota Group, TOGAF from the Object-Management Group, and the Capgemini Integrated Architecture Framework (IAF). All these frameworks allow us to more successful transformation, to return to the central idea of this paper.

Over 2.2 billion people across the globe face significant barriers to accessing essential ophthalmic care, with elderly, rural, and refugee populations being disproportionately affected. These obsta-cles deepen existing disparities in eye care. 3D printing is a novel technology that has the potential to transform the field and improve access through alleviating many patient-specific barriers. This article delves into the evolution of 3D printing within ophthalmology, highlighting its current ap-plications and future potential. It explores various 3D printing techniques and biomaterials, dis-cussing their effectiveness in creating advanced solutions such as bioengineered corneas, ocular prosthetics, and innovative treatments for dry eye syndrome. Additionally, 3D printing has rev-olutionized drug delivery systems for conditions like glaucoma, retinal diseases, and for ocular brachytherapy. Despite its promise, the integration of 3D printing into clinical practice presents challenges, which the article addresses alongside strategies for overcoming them. By mapping out the technological advancements and challenges, this review offers a roadmap for enhancing global eye care accessibility and improving patient outcomes on a global scale.

Hydrogen mobility embodies a promising solution to address the challenges posed by traditional fossil-fuel-based vehicles. The use of hydrogen in small heavy duty road vehicles based on internal combustion engines (ICEs) may be appealing for two fundamental reasons: direct electrification seems less promising in heavy duty transport systems and fuel cell-based hydrogen vehicles implementation may not proceed at the expected pace due to higher investment costs compared to ICEs. On the other hand, hydrogen combustion is gaining attractiveness and relies on robust and cheap technologies, but it is not the only renewable solution. In this framework, this work presents a methodology to assess Weel-to-Whell primary energy consumption and CO2 emissions of small heavy-duty vehicles. The methodology is applied in a real case-study, namely a passenger coach travelling on a 100 km-mission in non-optimized conditions. Therefore, the suitability of hydrogen is compared with standard diesel and other alternative diesel-type fuels (biodiesel and synthetic diesel types). Hydrogen shows competitivity with standard diesel from the point of view of CO2 emission reduction (-29%) while it hides a higher primary energy consumption (+40%). Nonetheless, HVO brings the highest benefits both from the point of view of primary energy consumption and emission reduction, namely -35% and 464-634 kgCO2/100km avoided compared to hydrogen.

Background: The Government of Bangladesh is currently providing COVID-19 vaccines free of cost, but for a massive population, the free vaccination program’s sustainability is challenging. In this regard, assessing willingness to pay can help to explore vaccine pricing, subsidizing strategy, and vaccine demand. The study aimed to evaluate the prevalence of willingness to pay (WTP) for the COVID-19 vaccine and its associated factors to ensure the sustainability of the vaccination program. Methods: A cross-sectional research design was adopted to collect data from 1497 respondents through online and face-to-face interviews. Data were analyzed using the chi-square test and point-biserial correlation for descriptive statistical analysis, and multiple logistic regression analysis was also used to identify the factors associated with the dependent variable in the study. Results: The prevalence of WTP towards a COVID-19 vaccine was 50.9 %, and mean and median WTP were respectively 754.55 BDT (US$ 8.93), 300 BDT (US$ 3.55). WTP of other religions was significantly higher than Muslims (aOR=1.5, P=0.037). WTP was also higher among Graduate (aOR=2.2, P=0.007), Masters & MPhil/PhD (aOR=2, P=0.030), higher family income group (aOR=1, P=0.039) and respondents with higher knowledge about the vaccine (aOR=1.1, P=0.003), behavioral practice (aOR=1.1, P< 0.001), higher subjective norms (aOR=1.2, P=0.009), higher anticipated regret (aOR=1.2, P=0.005) and higher perceived benefits from the vaccine (aOR=1.1, P=0.029). On the contrary, WTP is lower among respondents who had a higher negative attitude toward vaccines (aOR= 0.9, P<0.001) and higher behavioral control (aOR=0.9, P=0.006). The participants who had experienced severe morbidity and who belonged to a higher income group, they have highly tended to WTP's highest amount of money for the COVID-19 vaccine. Conclusion: The study found that nearly half of the respondents were not interested in paying for the COVID-19 vaccine. It emphasizes higher education, proper knowledge dissemination about the COVID-19 vaccine, positive behavioral practice, reducing negative attitudes towards it, and higher household income to increase WTP for the COVID-19 vaccine. Health promotion materials should be developed to improve COVID-19 vaccine knowledge and reduce negative attitudes regarding vaccines. A subsidized scheme for lower-income groups should be initiated to minimize the catastrophic income challenge regarding WTP for the COVID-19 vaccine.

This study explores the effects of powder-to-liquid ratio on the performance characteristics of lost foam casting coatings. The investigation focuses on how variations in this ratio affect key properties including apparent viscosity, shear thinning behavior, coating weight, and surface morphology. Through a series of controlled experiments, coatings were prepared with different powder-to-liquid ratios and assessed for their physical and application properties. The results indicate that increasing the powder-to-liquid ratio raises the apparent viscosity and modifies shear thinning behavior. Notably, ratios exceeding 2.0 result in a sharp increase in viscosity that impedes coating application. The optimal powder-to-liquid ratio was determined to be between 2.0 and 2.2, where coatings demonstrated enhanced uniformity, improved particle distribution, and superior surface morphology. Coating weight increased up to a ratio of 2.2 but decreased beyond this threshold due to excessive viscosity. Both microscopic and macroscopic analyses confirmed that a ratio of 2.0 to 2.2 strikes the best balance for coating performance. These findings underscore the importance of precise powder-to-liquid ratio control to optimize the quality of lost foam casting coatings, offering valuable insights for refining coating formulations and application techniques in industrial contexts.

Background and Objective: To examine the effect of ordered subset expectation maximization (OSEM) parameters on the quantitative image quality of cardiac SPECT images in two different frequently used SPECT cameras and determine the optimal settings for producing images of best diagnostic quality. Another objective was to assess if different cameras produced a significant change in optimal parameters and levels of detectability. Methods: The optimization of OSEM iterative reconstruction algorithm was carried out by comparing image quality metrics, namely, contrast-to-noise ratio (CNR) and defect contrast across 12 OSEM subset-iteration combinations to find the best choice for cardiac perfusion SPECT images. Eight frames were reconstructed using the SIMIND Monte Carlo Simulation package. An activity of 370 MBq (10mCi) and projection acquisition interval of 20 seconds per projection were used. Attenuation (AC) and scatter corrections (SC) were performed in this study for all images. Results: The 16-2 subset-iteration combination yielded the highest CNR and defect contrast values for both cameras. The difference between CNR values for two cameras was found to be around 5% only. Conclusions: Monte Carlo simulations can be useful to investigate how quantitative image quality behaves with respect to reconstruction parameters and correction algorithms in a controlled environment. The found optimum is similar to values reported in previous findings. In this study, the use of different camera brands did not affect the optimum. The quantitative detectability measures were also very similar.

Individuals may exhibit altered foot mechanics, in this case foot pronation, only when fatigue sets in. Therefore, a more evidence-based understanding of these fatigue-induced changes may be helpful for future gait analysis and return to play tests, since fatigue could provide new insights that might explain a person’s complaints. Methods: 25 healthy test persons (24.3±2.7 years, BMI: 22.7±2.8) participated in this controlled non-randomized study of unilateral fatigue of the right foot stabilizing muscles with regard to the pronation of the foot, measured by navicular drop (ND) in a static (statND) und dynamic (dynND) state. The left foot served as a control. Surface electromyography was used to verify fatigue. Results: While statND didn’t change, the dynND increased significantly by 1.44±2.1 mm (= 22.3 %) after fatigue of the foot stabilizing muscles. No correlation was found between statND and dynND. Conclusion: Muscular fatigue can affect foot pronation. The dynND appears to be more representative of the loads in everyday life, whereby most studies work with the statND.

The study looks at how joining live video chats with native English speakers on TikTok helps people who are learning English feel more ready to talk in English and less nervous about it. This study looks at EFL students who join TikTok live sessions. The researcher wants to understand how confident and nervous the students feel when they communicate. He uses qualitative research methods to do this. The study shows that using TikTok in a fun and calming way could help people learn a new language and reduce feelings of worry. This is helpful for teachers and language experts who want to use social media to help people learn languages.

: This study aimed to validate the effects of self-compassion-based forest healing therapy as an intervention for reducing stress and promoting coping resources. Therefore, we investigated the effects of self-compassion-based forest healing therapy on stress, self-compassion, and connectedness to nature. A total of 30 participants were divided into an experimental and control group. Two sessions of forest healing meditation activities were held at the Forest of Healing every two weeks between October and November 2023. As a repeated measures experiment, data were collected before the intervention, after the first intervention, and after the second intervention. Perceived stress, positive and negative affect, and salivary cortisol were measured to assess physiological and psychological stress in participants. Connectedness to nature and self-compassion were measured to evaluate stress-coping resources. The results showed that the forest healing program had significant positive effects on stress and emotional states in the experimental group after the intervention. Further, there was a significant incremental effect on connectedness to nature and self-compassion in the experimental group. Therefore, self-compassion meditation-based forest healing therapy is a feasible and efficient approach for facilitating stress management and coping resource building.

Despite significant prevention efforts, the numbers of physically inactive individuals, chronic illnesses, exhaustion syndromes and sick leaves are increasing. A still unresolved problem with exercise promotion is the low participation of sedentary persons. This collective term covers heterogeneous subgroups. Their engagement with movement campaigns and resistance to change are influenced by numerous factors. Our aim was to analyse survey data on health, performance, lifestyle habits and the approachability to physical activity campaigns obtained from the Germany-wide ActIv survey. From 2,888 study participants aged 50-60 years, 668 persons were categorised into the subgroups "never-athletes", "sports-dropouts", "always-athletes" and "sports-beginners". Large and significant group differences were found for BMI, assessment of quality of life, health and fitness, risk factors and health problems. 42.5% of "never-athletes" and 32.5% of "sports-dropouts" did not state any barriers to sport. There are substantial disparities between the non-athlete groups in terms of their motivation to exercise. In contrast, there are comparatively minor differences in motivation between "sports-dropouts" and "sports-beginners", whose health and fitness are the primary motivators for sport. Our analyses suggest that (i) negative health and performance trends cannot be compensated by appeals for voluntary participation in exercise programmes and (ii) powerful incentive systems are required.

Litsea martabanica root's antioxidant and AChE activity showed promise as a pesticide detoxification agent in our previous study. In addition to roots, its leaves can help mitigate pesticide exposure, although there is limited scientific evidence supporting their efficacy. However, the use of roots in many countries, such as Thailand, could contribute to environmental degradation, as highland communities traditionally cut down whole trees to obtain them. This study aims to evaluate the antioxidant activity and anti-pesticide potential of water extracts from L. martabanica leaves instead of its roots through in vitro and in vivo investigations. The findings showed that L. martabanica water extracts and fractions demonstrated varied antioxidant activity. The water extract, obtained using traditional extraction methods, was chosen for in vivo experiments. Rats received the extract followed by chlorpyrifos exposure for 16 days. Results indicated reduced acetylcholinesterase activity in chlorpyrifos-exposed rats, while treatment with leaf extract led to increased activity, suggesting its potential as a detoxifying agent. Histopathological examination revealed no liver cell necrosis and showed liver cell regeneration, indicating potential protection against free radical-induced liver damage without affecting rat liver weight or biochemical profiles. Utilizing L. martabanica leaves for healthcare purposes holds promise without negative environmental impact.

Single-phase-to-ground fault in non-effectively grounded systems poses serious public safety concern. Along with increasing deployment of low-voltage (LV) sensors, new opportunities and ways are created for solving this traditional problem in distribution systems. A new approach, identifying primary single-phase-to-ground line fault and locating it through measurement data from smart sensors deployed in the secondary side of distribution transformers, is proposed in this paper. When a fault occurs in primary distribution feeder, the transient aerial mode voltage (AMV) of each LV smart sensor is calculated. The fault line can be identified by an abrupt change value of AMV at LV side. Next, by finding the position of the maximum value of this AMV from LV sensors on the fault line, the fault location can be pinpointed to two neighboring distribution transformers. The proposed method has been proven to be efficient and reliable by simulation studies.

Iron deficiency in the fetal and neonatal period (perinatal iron deficiency) bodes poorly to neuro-development. Given its common occurrence and the negative impact on brain development, a screening and treatment strategy that is focused on optimizing brain development in perinatal iron deficiency is necessary. Pediatric societies currently recommend a universal iron supple-mentation strategy for full-term and preterm infants that does not consider individual variation in the body iron status and could lead to under-treatment or over-treatment. Moreover, the focus is on hematological normalcy and not optimal brain development. Several serum iron indices and hematological parameters in the perinatal period are associated with risk of abnormal neurodevelopment, suggesting their potential use as biomarkers for screening and monitoring treatment in infants at risk for perinatal iron deficiency. A biomarker-based screening and treatment strategy that is focused on optimizing brain development will likely improve outcome in perinatal iron deficiency.

The aim of the study was to identify factors associated with non-adherence to tuberculosis (TB) preventive treatment among contacts with latent TB infection of new cases of pulmonary TB cases reported in Catalonia in 2019-2021. All contacts aged 18 years or older with a latent TB infection who received a TB preventive treatment were included in the study. The Chi square test and the odds ratios (OR) were used to assess the association between non-adherence to TB preventive treatment and the study variables, considering a p < 0.05 as statistically significant. Multiple logistic regression analysis was used to detect the in-dependent factors associated with TB preventive treatment non-adherence, considering a p < 0.05 as statistically significant. The percentage of non-adherence to TB preventive treatment found in this study was 23.7%. A multivariable logistic regression analysis determined that the following factors were significantly associated with TB preventive treatment non-adherence among adult contacts: “exposure at school or workplace” (aOR = 3.34), “exposure to an index case without laboratory confirmation of TB” (aOR = 2.07), “immigrant contact” (aOR = 1.81), “male gender” (aOR = 1.75) and “exposure duration <6 hours per week or sporadic exposure” (aOR = 1.60). By contrast, the factor “short-term TB preventive treatment regimen” (aOR = 0.38) was significantly associated with a lower treatment non-adherence. Adherence to TB preventive treatment should be improved among adult contacts of TB pulmonary cases with latent TB infection by recommending short-term treatment regimens and by developing health education activities, with a greater focus on contacts with factors associated with treatment non-adherence.

Disulfiram (DSF), an anti-alcoholism medicine, exerts treatment effects in patients suffering from persistent Borreliosis and also exhibits anti-cancer effects by its copper chelating derivatives. Since chronic/persistent borreliosis is characterized by increased amounts of proinflammatory macrophages, this study investigated opsonin-independent phagocytosis, migration and surface marker expression of in vivo activated human monocyte-derived macrophages and dendritic cells with and without DSF treatment. Phagocytosis of non-opsonized Dynabeads® M-450 and migration of macrophages and dendritic cells were monitored using live cell analyzer Juli™ Br for 24h by imaging every 3.5 min. Results were analyzed by a newly developed software based on the differential phase contrast images of cells before and after ingestion of Dynabeads bearing an electron dense iron core. As a control, phagocytosis was also monitored by visual counting of ingested beads. DSF decreased the phagocytic capacities exhibited by global macrophages and dendritic cells. DSF also impaired the migration of human monocyte-derived macrophages and dendritic cells (hMDMD) and significantly reduced the expression densities of surface antigens CD45 and CD14. In cells consisting of anti-inflammatory M2 macrophages, DSF led to a remarkable cell death and also increased oxidative stress as determined by MitoSox staining. Mitochondrial oxidative stress was a prominent feature in M2 macrophages which were more sensitive to DSF-induced cytotoxicity.

Energy transition is one of the greatest challenges facing humanity today. All micro, small, medium and large enterprises in operation will have to face it, and some can al-ready boast the first successes in this regard. This paper focuses on the involvement of these smallest players in energy transition. Micro and small entities are the largest part of the economy, having a great influence on its development. Looking at the wide scale of their activities, these entities are distinguished by a specific owner-manager relationship. This means that the final decision-making is influenced by business goals, but also by the manager's approach, their awareness of changes, and personal and other factors. Based on a structured and standardized survey questionnaire, the research was carried out using the Computer-Assisted Telephone Interviewing technique between April and May 2022 among owners of micro and small enterprises operating in Poland. The survey showed that active engagement of micro and small enterprises in energy efficiency initiatives is related to their market success and financial health.

Internet of Things (IoT) is what we have as a great breakthrough in 5G network. Although 5G network can support several Internet of Everything (IoE) services, 6G is the network to fully support that. This paper is a survey research presenting the 5G and IoT technology and the challenges coming, with the 6G network being the new alternative network coming to solve these issues and limitations we are facing with 5G. A reference to the Control Plane and User Plane Separation (CUPS) is made with IPv4 and IPv6 addressing which is the foundation of the Network Slicing for the 5G core network. Comparing to other related papers, we provide in depth information on how the Internet of Things (IoT) is going to affect our lifes and how this technology is handled as Internet of Everything (IoE) in 6G network. Finally, a full reference is made to the 6G network with its challenges comparing to the 5G network.

In this study, an analysis was conducted on 16 durum wheat genotypes cultivated under seven different crop management systems. The purpose was to investigate the influence of Genotype (G), Environment (E), and Genotype by Environment interactions (GxE) on the content of total free phenolic compounds (TPC) and the antioxidant capacity (AC) of durum wheat in Mediterranean environments and identify their adaptability in climatic change. Additionally, possible correlations between TPC and AC with protein content (PC), and vitreous-kernel percentage (VKP) of the samples were examined. The results indicated significant impacts from E, G, and GxE on both TPC and AC. Among the E, the mean values for TPC, ABTS, DPPH, and FRAP values were recorded at 48.8 mg TE/100 g dw, 121.3 mg TE/100 g dw, 23.0 mg TE/100 g dw, and 88.4 mg TE/100 g dw, respectively. Environments subjected to splitting topdressing N fertilization consistently showed low values, while the late sowing ones possessed high values. The Organic environment maintained a stable position in the middle across all measurements. The predominant influence was attributed to GxE, as indicated by the order GxE &gt;E&gt;G for ABTS, DPPH, and FRAP while for TPC was E&gt;GxE&gt;G. A comprehensive exploration of GxE interaction holds the potential to improve the total free phenolics content and antioxidant capacity of durum wheat within wheat farming systems. Achieving this enhancement involves the meticulous selection of cultivars that not only display high values but also exhibit stability across diverse conditions. Noteworthy genotypes for TPC include G5, G7 and G10, for ABTS include G3, G5 and G7, and for protein include G1, G9, and G16. G7 and G5 had high presence of frequency with G7 being the closest genotype to the ideal for both TPC and ABTS. These results suggest that the cultivation period as well as the nitrogen fertilization and its application method have a significant impact on the various antioxidant properties of durum wheat. This study holds significant importance as it represents the first comprehensive exploration of the impact of various E on the TPC and AC in durum wheat, with a special emphasis on the crop management. Notably, the significance of several statistical tools is also highlighted, such as the GGE biplot, Pi, and KR, in identifying superior genotypes, with the GGE biplot being highly valuable since it offers a visual representation of the study's outcomes.

According to official sources, the numbers of children-to-parent violence (CPV) in the most advanced countries have been on an increasing trend for more than a decade, which generates great social concern. This phenomenon has also aroused enormous interest among researchers, who have identified risk and protective factors related to adolescent CPV in numerous studies. To contribute to a better explanation of CPV, the aim of the present study was to analyze the relationship between family communication problems and CPV, through psychosocial adjustment variables -psychological distress and positive attitude toward the transgression of social norms- in schooled adolescents. The sample consisted of 8115 adolescents enrolled in schools in the State of Nuevo León (Mexico) (51.5% boys, 49.5% girls), whose ages ranged from 11 to 16 years (M = 13.34, SD = 1.04). Structural equation modeling was performed using Structural Equation Modeling Software (EQS). The results showed that family communication problems have a direct and signif-icant relationship with CPV. It was also observed that there is an indirect relationship between both variables, through the relationships of psychological distress and positive attitude towards the transgression of social norms. The multigroup analysis performed showed gender differences in some of these relationships. Finally, the results and their implications in the field of family intervention are discussed.

Consuming fish sustainably means consuming less and better, considering environmental, social, and economic impacts. This demands more knowledge to make informed decisions. In this study, the main goal was to understand how sustainability education can be used as a tool to raise awareness and promote new habits regarding the sustainable consumption of fish in 4th-grade students at primary school. During the COVID-19 pandemic, face-to-face and online learning methodologies were used in two different groups of students to understand whether the teaching method impacted learning. A sequential explanatory mixed methodology was applied, with a pre-test/post-test design, combined with focus group sessions. Between the pre and post-tests three learning modules were performed. The results showed that the students were unaware of many aspects related to fish sustainable consumption, but the developed activities significantly increased their knowledge of the subject and impacted students to change their consumption behaviours. It was also found that the construction of knowledge by the students after the activities was achieved either by face-to-face or online learning. Interviews from focus group sessions showed that students got to know new fish species, learned about the concept of minimum landing size and closure season and that fish are labelled like other types of food.

Finnish government's carbon neutrality goal by 2035 requires integration of renewable energy sources into the power grid. Considering the stochasticity of these resources, additional sources of flexibility are necessary to balance supply and demand in the power grid. District heating network (DHN) operators in Finland plan to shut down fossil-fuel-based combined heat and power plants and electrify heating systems by deploying heat pumps (HPs) and electric boilers. Techno-economic analysis and optimal operation of DHN-connected HPs and electric boilers in providing ancillary balancing services considering the 15-minute granularity in the balancing markets in Finland were investigated. The objective was to maximize the potential revenue for DHN operators gained from the day-ahead electricity market and frequency containment reserve (FCR) balancing markets. Three inter-connected DHNs in the Helsinki metropolitan area were optimized considering the reference year 2019 and each operator's decarbonization strategies for 2025. HPs could gain the highest profit from FCR-D up-regulation market, while the electric boiler may gain considerable profits from FCR-D down-regulation market. Compared to other balancing markets studied, the FCR-N market had a limited profit margin. Sensitivity analysis indicated that spot electricity prices and CO2 emission allowance prices have a significant impact on the profit from balancing markets.

Chronic Kidney Disease (CKD) is a major public health concern with an increasing proportion of sufferers progressing to renal replacement therapy (RRT). Early identification of those at risk of disease progression could be key in improving outcomes. We hypothesise that urinary liver-type fatty acid binding protein (uL-FABP) may be a suitable biomarker for CKD progression and can add value to currently established biomarkers such as urinary protein to creatinine ratio (uPCR) 583 participants with CKD 1-5 (not receiving renal replacement therapy) entered a 2-yr prospective longitudinal study. UPCR and uL-FABP were measured at baseline and CKD progression was defined as either i) a decline in eGFR of >5ml/min/1.73m2 or an increase in serum creatinine by 10% at 1-yr or ii) a decline in eGFR of >6 ml/min/1.73m2, or an increase in serum creatinine by 20% at 2-yrs or iii) the initiation of RRT. A combined outcome of initiating RRT or death was also included. Approximately 40% of participants showed CKD progression. UL-FABP predicted CKD progression at both years 1 and 2 (OR 1.01, p<0.01). Sensitivity and specificity were comparable to those of uPCR (AUC 0.623 v 0.706) and heat map analysis suggested that uL-FABP in the absence of significant proteinuria can predict an increase in serum creatinine of 10% at 1yr and 20% at 2yr. The risk of the combined outcome of initiating RRT or death was 23% higher in those with high uL-FABP (p<0.01) independent of uPCR. UL-FABP appears to be a highly sensitive and specific biomarker of CKD progression. The use of this biomarker could enhance the risk stratification of CKD and its progression and should be assessed further.

: Ovarian cancer has a dismal prognosis. Standard treatment following surgery relies on platinum-based chemotherapy. However, sizeable percentages of patients are unresponsive. Identification of markers predicting response to chemotherapy might help select eligible patients while sparing unresponsive ones treatment-associated toxicity. Cancer/testis antigens (CTA) are expressed by healthy germ cells and malignant cells of diverse histological origin. This expression profile identifies them as attractive targets of cancer immunotherapies. We analyzed correlations between expression of MAGE-A10 and New York esophageal-1 cancer (NY-ESO-1) CTAs at protein level and effectiveness of platinum-based chemotherapy in patients with advanced-stage high-grade serous ovarian carcinoma (HGSOC). MAGE-A10 and NY-ESO-1 protein expression was analyzed by immunohistochemistry (IHC) in formalin-fixed, paraffin-embedded samples from 93 patients with advanced-stage HGSOC treated at our institutions between January 1996 and December 2013. Correlation between expression of these markers and response to platinum-based chemotherapy, evaluated according to RECIST 1.1 criteria, platinum sensitivity, measured as platinum free interval (PFI), progression free (PFS) and overall survival (OS) was explored. MAGE-A10 protein expression predicts unresponsiveness to platinum-based chemotherapy (p=0.005), poor platinum sensitivity (p<0.001), and poor PFS (p<0.001) and OS (p<0.001). Multiva-riate analysis identifies MAGE-A10 protein expression as independent predictor of poor platinum sensitivity (p=0.005) and shorter OS (p<0.001). Instead, no correlation was observed between NY-ESO-1 protein expression and response to platinum-based chemotherapy (p=0.832), platinum sensitivity (p= 0.168), PFS (p=0.126) and OS (p=0.335). MAGE-A10 protein expression reliably identifies advanced-stage HGSOC unresponsive to platinum-based chemotherapy. Targeted im-munotherapy could represent an important alternative therapeutic option in these cancers.

This paper examines the importance of choice of cooking fuels in wellbeing, analysing relationships between the proportion of population with primary reliance on different types of fuels for cooking (predictor variable), and key wellbeing indices (outcome variables) - Personal Health, Social Life, Civic Engagement, Life Evaluation, Negative Experience. By combining two global datasets from Gallup and WHO, the study adds to current evidence by taking a global perspective. Controlling for demographic factors such as income per capita, age, education level, employment, etc., regression modelling of these relationships show that clean cooking fuels are influential in all of the key wellbeing indices with the exception of the Life Evaluation Index. Among the key wellbeing indices, Personal Health and Negative Experience Indices are the most strongly influenced by choice of clean cooking fuels. By adding access to electricity as an additional predictor variable, the analysis highlights the potential for integrating eCooking into national electrification plans as part of sustainable energy transitions, given that health outcomes (Personal health and Negative experience indices) appear to be as closely linked to choice of cooking fuels as to access to electricity.

Abstract: Urban population growth and the expansion of the built environment, pollution, overexploitation of water, inequality in water distribution, and the impacts of climate change in future availability of water, are all elements that jeopardize urban water security. Due to the complexity of urban water systems and their relevance for urban life, a holistic and integrative perspective is therefore needed to address such challenges. In this paper, Urban Water Metabolism (UWM) has been used for comprehensively understanding water (in)security in the City of Puebla (Mexico) and its metropolitan area. Water inflows and outflows have been estimated using a Material Flow Analysis (MFA) method with data either obtained from official sources or simulated with the Monte Carlo method. Our findings show that the UWM configuration in the City of Puebla and its metropolitan area is effective for generating profits to service providers and water related business, yet ineffective to guarantee citizens’ Human Right to Water and Sanitation (HRWS), a right recognized in the Constitution of Mexico. We conclude that to advance towards an inclusive and sustainable provision of water, economic interests must be reconsidered and therefore adjusted so they can be in line with such aspirational socioecological goals. UWM accounting can therefore inform new water governance arrangements, those based on both the best available knowledge and a vibrant participation of all relevant stakeholders.

Soil salinity is a limiting factor in crop productivity. Inoculating crops with microorganisms adapted to salt stress is an alternative to increasing plant salinity tolerance. Few studies have simultaneously propagated arbuscular mycorrhizal fungi (AMF) and dark septate fungi (DSF) using different sources of native inoculum from halophyte plants, and evaluated their effectiveness. This study selected, in alfalfa plants as trap culture, the infectivity of 38 microbial consortia native from rhizospheric soil (19) or roots (19) coming from six halophyte plants, as well as their effectiveness in mitigating salinity stress. Inoculation with soil resulted in 26%-56% colonization by AMF and 12%-32% by DSF. Root inoculation produced 10%-56% and 8%-24% of colonization, respectively. There was no difference in the number of spores of AMF produced with both inoculum types. The effective consortia were selected based on low Na but high P and K shoot concentrations which is relevant for plant nutrition but more for salt stress mitigation. The microbial consortia selection is presented in a more novel and applicable context, which would allow for the production of native microbial inoculants adapted to salinity to diminish the harmful effects of salinity stress in glycophyte plants in the context of sustainable agriculture.

Non-normal mode stability analysis has long been employed to study linear transient characteristics of wall bounded shear flows. However, the application of this approach to investigate shear flows with stratified thermal conditions (STCF) has received limited attention. This paper examines thermal effects on Taylor-Couette flow. The results in this study indicate the possibility of a subcritical bifurcation in stratified Taylor-Couette flow.

LSUs (RESPONSE TO LOW SULFUR) are plant-specific proteins of unknown function that were initially identified during transcriptomic studies of the sulfur deficiency response in Arabidopsis. Recent functional studies have shown that LSUs are important hubs of protein interaction networks with potential roles in plant stress responses. In particular, LSU proteins have been reported to interact with members of the brassinosteroid, jasmonate signaling, and ethylene biosynthetic pathways, suggesting that LSUs may be involved in response to plant stress through modulation of phytohormones. Furthermore, in silico analysis of the promoter regions of LSU genes in Arabidopsis has revealed the presence of cis-regulatory elements that are potentially responsive to phytohormones such as ABA, auxin, and jasmonic acid, suggesting crosstalk between LSU proteins and phytohormones. In this review, we summarize current knowledge about the LSU gene family in plants and its potential role in phytohormone responses.

Aiming at the problem of low charging efficiency caused by the scattered sensor nodes in traditional wireless rechargeable sensor networks (WRSNs), a UAV-assisted WRSN Online Charging Strategy Based on Dynamic Queue and Improved K-means (UOCS) is proposed. The scheme assumes that the energy consumption of nodes is unpredictable, and only generates charging requests when the energy is lower than a threshold, and performs on-demand responses to nodes that issue charging requests. The scheme combines the characteristics of one-to-one charging of UAVs, the selection and allocation timing of waiting queues and the number of UAVs, and the improved K-means partitioning based on space-time coordination(SPKM), which simplifies the problem of coordinated charging of multiple UAVs and maximizes energy. Using the efficiency and charging success rate, the optimal charging trajectory can be found under the constraint that the node will not starve to death due to power shortage. Finally, a simulation comparison experiment is carried out with the existing UAV charging scheduling strategy. UOCS achieves the optimal node survival rate with low algorithm complexity.

The dynamic response of structural elements subjected to blast loading is a problem of growing interest in the field of defense and security. In this work, a novel computational tool for the rapid evaluation of the effects of explosions, hereafter referred as SimEx, is presented and discussed. The classical correlations for the reference chemical (1 kg of TNT) and nuclear (106 kg of TNT) explosions, both spherical and hemispherical, are used together with the blast wave scaling laws and the International Standard Atmosphere (ISA) model to compute the dynamic response of Single-Degree-of-Freedom (SDOF) systems subject to blast loading. The underlying simplifications in the analysis of the structural response follow the directives established by UFC 3-340-02 and the Protective Design Center Technical Reports of the US Army Corps of Engineers, which offer useful estimates with a low computational cost, enabling in particular the computation of damage diagrams in the Charge Weight-Standoff distance (CW-S) space for the rapid screening of component (or building) damage levels. SimEx is a computer application based on Matlab and developed by the Fluid Mechanics Research Group at University Carlos III of Madrid (UC3M), which has been successfully used for both teaching and research purposes in the Degree in Security Engineering, taught to the future Guardia Civil officers at the Spanish University Center of the Civil Guard (CUGC). This dual use has allowed the development of the application well beyond its initially objective, testing on one hand the implemented capacities by undergraduate cadets with end-user profile, and implementing new functionalities and utilities by Masters and PhD students. With this experience, the application has been continuously growing since its initial inception in 2014 both at a visual and a functional level, including new effects in the propagation of the blast waves, such as clearing and confinement, and incorporating new calculation assistants, such as those for the thermochemical analysis of explosive mixtures; crater formation; fragment mass distributions, ejection speeds and ballistic trajectories; and the statistical evaluation of damage to people due to overpressure, body projection, and fragment injuries.

Detector-based spectral CT offers the possibility of obtaining spectral information from which discrete acquisitions at different energy levels can be derived, yielding so-called virtual monoenergetic images (VMI). In this study, we aimed to develop a jointly optimized deep learning framework based on dual-energy CT pulmonary angiography (DE-CTPA) data to generate synthetic monoenergetic images (SMI) for improving automatic pulmonary embolism (PE) detection in single-energy CTPA scans. For this purpose, we used two data sets: our institutional DE-CTPA data set D1 comprising polyenergetic arterial series and the corresponding VMI at low-energy levels (40 keV) with 7,892 image pairs, and a 10% subset of the 2020 RSNA Pulmonary Embolism Detection Challenge data set D2, which consisted of 161,253 polyenergetic images with dichotomous slice-wise annotations (PE/no PE). We trained a fully convolutional encoder-decoder on D1 to generate SMI from single-energy CTPA scans of D2, which were then fed into a ResNet50 network for training of the downstream PE classification task. The quantitative results on the reconstruction ability of our framework revealed high-quality visual SMI predictions with reconstruction results of 0.984 ± 0.002 (structural similarity) and 41.706 ± 0.547 dB (peak-signal-to-noise ratio). PE classification resulted in an AUC of 0.84 for our model, which achieved improved performance compared to other naive approaches with AUCs up to 0.81. Our study stresses the role of using joint optimization strategies for deep learning algorithms to improve automatic PE detection. The proposed pipeline may prove to be beneficial for computer-aided detection systems and could help rescue CTPA studies with suboptimal opacification of the pulmonary arteries from single-energy CT scanners.

Given the increasing public interest in how ingredients are processed and the growing demand for organic food products, it is critical to understand consumers’ expectations about the process-related quality of organic products. Consumers perceive organic food to be nutritious, healthy and either natural or less processed, as they are afraid of the loss of nutrients and other natural properties of the food products. However, emerging food processing technologies might generate healthy and safe food options with nutritional quality properties. Simplified communication schemes might help to overcome this barrier. The main objective of this paper is to propose a working definition of "careful processing" for organic products and test its consistency while being used in scoring different processing methods by consumers. Results show that the proposed definition allows to consistently rate alternative processing methods. Consumers tend to score novel processing methods such as pulsed electric fields and microwave as less careful, supporting the idea that organic consumers want the least man-made interference with their food products. Results show that a simple but effective definition of careful processing may help consumers to distinguish further organic food products from conventional ones, no matter which communication scheme is used.

The energy sector plays an important role in Mexico’s development trajectory. Mexico makes an interesting case study, because it shows how difficult it is to reduce fossil energy dependence despite geographic and climatic conditions that favour renewable energy deployment and use. Resolving path dependencies and the related carbon lock-in are key to Mexico’s sustainable energy transition. This case study aims to identify and discuss how carbon lock-in affects Mexico’s sustainable energy transition. Mexico’s carbon lock-in involves oil and oil-run power plants that are costly to build but relatively inexpensive to operate. This case study identifies potential entry points for transitioning towards sustainable energy in Mexico – resources that can promote the use of clean energy despite carbon lock-in. For example, focusing on electrification – particularly of the carbon-intensive sectors – can help Mexico transit towards sustainable energy despite institutional constraints. Complementing this case study is a teaching guide with recommendations for using Mexico’s energy transition in courses on sustainability. It introduces a “learning activation framework” to identify emerging opportunities that can advance sustainable energy transitions in different cases of carbon lock-in. Finally, the framework also gives students a chance to help dismantle or cope with carbon lock-ins.

Background: A large majority of primary school pupils fail to achieve 30-minutes in-school moderate-to-vigorous physical activity (MVPA). The aim of this study was to investigate MVPA accumulation and subject frequency during academic lesson segments and the broader segmented school day. Methods: 122 children (42.6% boys; 9.9±0.3yrs) from six primary schools in North East England, wore uniaxial accelerometers for eight consecutive days. Subject frequency was assessed by teacher diaries. Multilevel models (children nested within schools) examined significant predictors of MVPA across each school-day segment (lesson one, break, lesson two, lunch, lesson three). Results: Pupils averaged 18.33±8.34 minutes of in-school MVPA and 90.2% failed to achieve the in-school 30-minute MVPA threshold. Across all school-day segments, MVPA accumulation was typically influenced at the individual level. Lesson one and two - dominated by Math and English - were less active than lesson three. Break and lunch were the most active segments. Conclusion: This study breaks new ground, revealing MVPA accumulation and subject frequency varies greatly during different academic lessons. Morning lessons were dominated by the inactive delivery of Math and English, whereas afternoon lessons involved a greater array of subject delivery that resulted in marginally higher levels of MVPA.

The Standard Model (SM) fails to account for either the triplication of fermion families or chiral symmetry breaking in the electroweak sector. Here we show that both phenomena arise from the approach to chaos of quantum theory near the Fermi scale.

Windows account for a significant proportion of the total energy lost in buildings. The interaction of window type, Window-to-Wall Ratio (WWR) scheduled and window placement height would influence the natural lighting and heat transfer through windows. This is a pressing issue for non-tropical regions considering their high emissions and distinct climatic characteristics. A limitation exists in the adoption of common simulation-based optimisation approaches in the literature, which are hardly accessible to practitioners. This article develops a numerical-based window design optimisation model using a common Building Information Modelling (BIM) platform adopted throughout the industry, focusing on non-tropical regions of Australia. Three objective functions are proposed; the first objective is to maximize the available daylight, and the other two emphasize on the undesirable heat transfer through windows in summer and winter respectively. The developed model is tested on a case study located in Sydney, Australia, and a set of Pareto-optimum solutions is obtained. Through the use of the proposed model, energy savings of up to 16.43% are achieved. Key findings on the case example indicate that leveraging winter heat gain to reduce annual energy consumption should not be the top priority when designing windows for Sydney.

Acknowledging the diverse perceptions about science-religion relationships among learners who come from various religious environments may increase learners’ willingness to learn about evolution. This study is based on a zoology course designed for in-service teachers, which aimed to provide basic scientific knowledge about evolution using the Religious Cultural Competence in Evolution Education framework. The study explores whether learners who were resistant to evolution modify their attitudes and willingness to learn about it, and whether they develop respect toward learners who hold contradicting views. Using qualitative methods, the findings indicate that using the Religious Cultural Competence in Evolution Education framework increased some formerly "resistant" learners’ willingness to learn about evolution and include it in their own teaching, albeit in varying degrees and with various reservations. The learners appreciated the freedom to express their challenges concerning evolution learning or teaching and became more willing to respect opposing perspectives, even though not all the religious learners accepted evolution as an explanation for the development of organisms. This study has international implications for bridging the gap between science and religion, thus reducing resistance to learning and teaching about evolution.

We present and benchmark FilterNet, a flexible deep learning architecture for time series classification tasks, such as activity recognition via multichannel sensor data. It adapts popular CNN and CNN-LSTM motifs which have excelled in activity recognition benchmarks, implementing them in a many-to-many architecture to markedly improve frame-by-frame accuracy, event segmentation accuracy, model size, and computational efficiency. We propose several model variants, evaluate them alongside other published models using the Opportunity benchmark dataset, demonstrate the effect of model ensembling and of altering key parameters, and quantify the quality of the models’ segmentation of discrete events. We also offer recommendations for use and suggest potential model extensions. FilterNet advances the state of the art in all measured accuracy and speed metrics on the benchmarked dataset, and it can be extensively customized for other applications.

Ground-level ozone (O3) increases in the northeastern part of Eurasia, where larch species are dominant trees and have been planted intensively. The Japanese larch (Larix kaempferi; hereafter larch) is classified as the tree species most of its sensitive to O3 based on data from long-shoot needles of seedlings. This criterion should be reconsidered based on O3 uptake, which is strongly depended on stomatal conductance (Gs) of adult trees through the difference in relevant needle traits. Because Gs is closely correlated with photosynthetic activity, we measured the in situ seasonal and yearly change in photosynthetic function, needle mass per area (LMA) and nitrogen (N) content of both short- and long-shoot needles of the canopy of larch trees over successive 3 years. No difference was observed in the in light saturated photosynthetic rate at ambient CO2 (Psat) between needles of hetero types of shoot in the latter part of the growing season, but clear differences were found within a specific year, indicating that seasonal changes in climatic factors determine Psat in the long term. The Psat-N relations differed significantly between the needle types. However, Psat at saturated CO2 (Pmax)-N was quite similar, implying that the CO2 diffusion difference between short- and long-shoots is responsible for the differing Psat -N. In conclusion, seasonal and yearly variations in photosynthetic capacity are mainly determined mainly by climatic variations, whereas shoot type determined the traits of photosynthetic N utilization as well as Gs regulation.

Glioblastoma (GBM) is the most lethal form of brain tumor, characterized by rapid growth and surrounding tissue invasion. The current standard treatment is surgery followed by radiotherapy, and concurrent chemotherapy, typically with temozolomide. Although extensive research has been performed over the past years to develop an effective therapeutic strategy for the treatment of GBM, efforts have not provided major improvements in the overall survival of patients with GBM. Thus, new therapeutic approaches are urgently needed. A major challenge in the development of therapies for central nervous system (CNS) disorders is overcoming the blood–brain barrier (BBB). In this context, the intranasal (IN) route of drug administration has been proposed as a non-invasive alternative route to directly targeting the CNS. In fact, this route of drug administration may bypass the blood-brain barrier and reduce systemic side effects. Recently, formulations have been developed to further enhance nose-to-brain transport, mainly with the use of nano-sized and nanostructured drug delivery systems. The focus of this review will be on the strategies developed to deliver a number of anticancer compounds for the treatment of GBM using the nasal administration. In particular, the specific properties of nanomedicines proposed for the nose-to-brain delivery will be critically evaluated. The number of preclinical and clinical data reviewed support the idea that nasal delivery of anticancer drugs might represent a breakthrough advancement in the fight against GBM.

Background: Mitigating climate change requires fundamentally redesigned energy systems in which renewable energy sources ultimately replace fossil fuels such as natural gas. In this context, the question how and to which extent the gas sector can contribute to an increasingly climate-neutral future EU energy system is heavily debated among scholars, energy industry experts and policy makers. Methods: We take a two-step approach: We begin with a review of studies from energy industry and academia to discuss potential gas sector contributions from a holistic energy system design point of view; this is followed by a comprehensive discussion of technical potentials, micro-economic conditions and societal implications of renewable gas. We then enrich our findings with the results of an empirical focus group process. Results: The gas sector can not only contribute to balancing volatile renewable energy production but also enable the supply of renewable energy to end-users in gaseous form; based on existing infrastructure. This could reduce costs for society, increase public acceptance and ultimately speed up the energy system transformation. There is the theoretical technical potential to substitute major parts of natural gas with renewable gas of biogenic and synthetic nature. This, however, crucially requires a supportive policy framework like the one established for renewable electricity. Conclusion: Given the societal benefits and the competitiveness of renewable gas as compared to renewable alternatives, energy policy makers should incorporate renewable gas and the existing gas infrastructure in the future energy system framework. The objective should be an optimized interplay of various energy vectors and their infrastructure along the entire energy supply chain. This requires a level playing field for different renewable technologies across different policy areas and a form of public support that strikes the balance between facilitating the gradual substitution of natural gas by renewable gas while maintaining public acceptance for this transformation despite higher costs for end-users.: Given the societal benefits and the competitiveness of renewable gas as compared to renewable alternatives, energy policy makers should incorporate renewable gas and the existing gas infrastructure in the future energy system framework. The objective should be an optimized interplay of various energy vectors and their infrastructure along the entire energy supply chain. This requires a level playing field for different renewable technologies across different policy areas and a form of public support that strikes the balance between facilitating the gradual substitution of natural gas by renewable gas while maintaining public acceptance for this transformation despite higher costs for end-users.

Modified FOLFIRINOX is effective for advanced pancreatic cancer but frequently causes severe neutropenia. The present study was designed to investigate the influence of severe neutropenia on clinical outcomes in advanced pancreatic cancer patients receiving modified FOLFIRINOX. Fifty-one advanced pancreatic cancer patients who received modified FOLFIRINOX during January 2014 and May 2018 were subjects of the present study. Adverse events, including neutropenia, were graded according to the Common Terminology Criteria for Adverse Events, version 4.0. Median overall survival (OS) was determined as the primary endpoint, while median time to treatment failure (TTF), overall response rate (ORR), and the incidence of other adverse events were measured as secondary endpoints. Severe neutropenia (grade≥3) occurred in 39 patients (76.4%), in which high level of total bilirubin (>0.6mg/dL) was a significant risk as assessed by a multivariate logistic regression analysis. Median duration of OS was significantly longer in patients with severe neutropenia than in those without it (15.2 months versus 7.2 months, P=0.032). Moreover, there was a significant correlation between OS and the grade of neutropenia (R=0.306, P=0.029). ORR tended to be higher, though not significantly, in patients with severe neutropenia. In contrast, the incidence rates of other adverse events were not different between the two groups. Severe neutropenia is an independent predictor of prognosis in advanced pancreatic cancer patients received modified FOLFIRNOX therapy.

In this paper, we prove some random fixed point theorems for generalized random $\alpha-\psi-$contractive mappings in a Polish space and, as some applications, we show the existence of random solutions of second order random differential equation.

The separation of sister chromatids during anaphase is the culmination of mitosis and one of the most strikingly beautiful examples of cellular movement. It consists of two distinct processes: Anaphase A, the movement of chromosomes toward spindle poles via shortening of the connecting fibers, and anaphase B, separation of the two poles from one another via spindle elongation. I focus here on anaphase A chromosome-to-pole movement. The chapter begins by summarizing classical observations of chromosome movements, which support the current understanding of anaphase mechanisms. Live cell fluorescence microscopy studies showed that poleward chromosome movement is associated with disassembly, or ‘melting’ of the kinetochore-attached microtubule fibers that link chromosomes to poles. Microtubule-marking techniques established that kinetochore-fiber disassembly often occurs through a ‘pac-man’ mechanism, where tubulin subunits are lost from kinetochore-attached plus ends and the kinetochore appears to consume its microtubule track as it moves poleward. In addition, kinetochore-fiber disassembly in many cells occurs partly through ‘flux’, where the microtubules flow continuously toward the poles and tubulin subunits are lost from minus ends. Molecular mechanistic models for how load-bearing attachments are maintained to disassembling microtubule ends, and how the forces are generated to drive pac-man and flux-based movements, are discussed.

GaN ultraviolet photodetector with metal-semiconductor-metal structure is achieved by growing on a periodic trapezoid column-shape patterned sapphire substrate using metalorganic chemical vapor deposition. Under 5-V reverse bias, the photodetector fabricated on such patterned sapphire substrate exhibits a lower dark current, a higher photocurrent, and a 476 % enhancement in the maximum responsivity as compare with those of the photodetector fabricated on conventional flat sapphire substrate. It is also found that the much larger UV-to-visible rejection ratio and the fact that responsivity drops in a smaller cut-off region are observed from photodetector fabricated by using a periodic trapezoid column-shape patterned sapphire substrate. These phenomena may all be attributed to the reduction of threading dislocation density and the improved quality of GaN film, as well as the internal reflection and/or scattering effect on the interface between GaN film and the periodic trapezoid column-shape pattern of the substrate.

Background: The research is conducted against the backdrop of the rising incidence of diabetes and the demand for novel approaches to improve patient outcomes. With the goal of revolutionizing conventional methods and addressing the changing healthcare landscape, the study concentrated on the application of AI technology in diabetes treatment. Objective: Examining the various ways AI can be used in diabetes care and assessing how it can enhance automated screenings, tailored treatment recommendations, predictive modeling, and patient self-management were the main goals of the study. Result: The findings demonstrated how well AI works to anticipate a patient's unique reaction to a therapy, assist medical personnel in making decisions, and give patients more control over their own care. Artificial intelligence (AI)-powered solutions showed promise in improving real-time monitoring and encouraging patient adherence, supporting a comprehensive strategy for managing diabetes. Conclusion: The research indicates that artificial intelligence (AI) has great potential to change the way diabetes is treated. However, it also highlights the need for more research, ethical issues, and validation of AI. The results advocate for joint efforts to ensure responsible and patient-centered technology innovation in diabetes care and encourage the integration of AI with new technologies.

Infill drilling is one of the most effective methods to improve the performance of poly-mer flooding. The difficulties related to infill drilling are determining the optimal numbers and placements of infill wells. In this study, an improved archimedes optimization algorithm with Halton sequence (HS-AOA) was proposed to overcome the aforementioned difficulties. First, to optimize the infill well placement for polymer flooding, an objective function that considered the economic influence of infill drilling was developed. Then, the novel optimization algorithm (HS-AOA) for infill well placement was developed by combining the AOA with the Halton se-quence. The codes were developed in MATLAB and connected to a commercial reservoir simula-tor CMG STARS to carry out the infill well placement optimization. Finally, the HS-AOA was compared to the basic AOA to confirm its reliability and then used to optimize the infill well placements for polymer flooding in a typical offshore oil reservoir. The results showed that the introduction of the Halton sequence into AOA effectively increased the diversity of the initial ob-jects in the AOA and avoided the HS-AOA trapping into the local optimal solutions. The HS–AOA outperformed the AOA. It was an effective approach to optimize the infill well placement for polymer flooding processes. In addition, infill drilling could effectively and economically im-prove the polymer flooding performance in offshore oil reservoirs. The NPV of the polymer flooding case with infill wells determined by HS-AOA reached 3.5 × 108 $, which was an increase of 7% over that of the polymer flooding case. This study presents an effective method for opti-mizing infill well placement for polymer flooding processes. It also can serve as a valuable refer-ence for other optimization problems in the petroleum industry, such as joint optimization of well control and placement.

Carbon capture, utilization, and storage (CCUS) considered a the key strategy for reducing the emissions of anthropogenic carbon dioxide from power generation plants, can be achieved by three main technologies: oxy-fuel combustion, pre-combustion, and post-combustion capture. Post-combustion carbon capture (PCC), where CO2 is removed after the fuel burning, is a crucial solution for reducing greenhouse gas emissions from natural gas power plants (NGPPs). However, high costs and energy penalties associated with PCC technologies hinder their widespread adoption. Recent advancements in hybrid PCC configurations have shown promise in improving efficiency and reducing costs. In effect, six PCC hybrid configurations below were identified as feasible process routes: • 2S-AB +AD: Two-stage Absorption + Adsorption hybrid • 2S-AB +MB: Two-stage Absorption + Membrane hybrid • 2S-AD +AB: Two-stage Adsorption + Absorption hybrid • 2S-AD +MB: Two-stage Adsorption + Membrane hybrid • 2S-MB +AB: Two-stage Membrane + Absorption hybrid • 2S-MB +AD: Two-stage Membrane + Adsorption hybrid Each hybrid has its own technical and economic challenges that need to be investigated in order to identify the best technique for carbon capture. In this paper, we performed Aspen Hysys design simulation of the six hybrids PCC configurations and also their economic evaluations using parameters like investment costs, operating costs, net present value, and rate of return, culminating in the use of three assessment parameters namely, levelized cost of electricity (LCOE), carbon emission intensity (CEI) and cost of carbon avoidance (COA), to evaluate the six hybrids PCC configurations and to determine the most viable option. Overall, it was found by dimensional analysis that the post combustion carbon capture using 2S-MB +AB: Two-stage Membrane + Absorption hybrid is the most viable for capturing CO2 from power generation plants and is hereby recommended. However, the choice of materials (membranes and absorbents) needs to be evaluated so as determined the best optimal configuration for commercialization.

Psychiatric disorders, characterized by complex and fluctuating patterns of thoughts, emotions, and behaviors, can be effectively modeled and visualized using mathematical wave equations. This study explores the representation of three major psychiatric conditions— Psychosis, Bipolar Disorder and Obsessive Compulsive Disorder (OCD)—through the application of differential equations, damping factors, and noise perturbations. Psychosis is modeled using Lissajous figures with high-frequency components, damping, and noise, symbolizing the irregular and erratic thought patterns characteristic of this condition. The inclusion of random perturbations and varying frequencies illustrates the chaotic and unpredictable nature of psychotic episodes, while damping effects reflect the temporary reductions in symptom intensity. For bipolar disorder, a system of partial differential equations simulates the cyclical nature of manic and depressive episodes. The model captures high-energy manic phases with periodic disturbances and the subsequent transition to lower-energy depressive states through damping effects. This representation highlights the oscillatory behavior and recurring episodes inherent to bipolar disorder. OCD is represented with Circumferential Complex Equations in Mult directions. The resulting graphical representations provide intuitive visual insights into the dynamics of these psychiatric disorders. By leveraging wave equations and mathematical modeling, this approach offers a novel perspective on understanding and analyzing the complex behaviors associated with OCD, bipolar disorder and psychosis. This method not only aids in the conceptualization of psychiatric phenomena but also underscores the potential of mathematical tools in the study of mental health conditions.

This study examines geothermal energy extraction potential from the basement rock within the Denver-Julesburg (DJ) Basin, focusing on flow performance and heat extraction efficiency of different geothermal well configurations. It specifically compares U-Shaped, V-Shaped, Inclined V-Shaped, and Pipe-in-Pipe configurations against Enhanced Geothermal Systems (EGS) setups. Through numerical modeling, we evaluated the thermal behavior of these systems under various operational scenarios and fracture conditions. Results suggest that while closed-loop systems offer moderate temperature increases, EGS configurations show substantial potential for high-temperature extraction. This underscores the importance of evaluating well configurations in complex geological settings like the DJ Basin. The insights from this study aid in strategic geothermal energy planning and development, marking significant advancements in geothermal technology and setting a foundation for future explorations and optimizations.

The installation of electric vehicle supply equipment (EVSE) increases demand and peak loads, potentially straining existing energy distribution infrastructure. Dispersed and inadequately planned placement of charging points (CPs) can disrupt the electrical grid, surpass contracted demand thresholds, and require infrastructure upgrades, thereby incurring unfeasible costs for Distribution System Operators (DSOs). In this context, it is necessary to recognize the role of business models in enabling effective electrification of the transportation sector. In response to these challenges, this paper introduces a novel e-mobility hub management strategy, tailored for implementation in the Brazilian context. The proposed strategy revolves around a microgrid configuration encompassing dispatchable and photovoltaic generation, a battery energy storage system (BESS), EVSE infrastructure, and local loads. Moreover, this centralized controller facilitates the implementation of dynamic pricing and demand-response mechanisms, integral to business models seeking to integrate EVSE into the distribution grid. To validate the efficacy of the proposed solution, hardware-in-the-loop (HIL) simulations of the microgrid system are conducted. These simulations, incorporating the centralized controller, serve as a tool for assessing system performance and viability before on-site equipment deployment. Finally, this paper concludes with the insights gleaned from test analysis and its discussion through a selection of the most expressive scenarios, including islanded and connected operation modes.

Addressing the significant challenge in high-speed cotton dibbling operations in Xinjiang—specifically, the duck bill’s ("Duck bill" is a type of duck-billed bunch planting mechanism or component). shortened opening duration leading to seed throwing and floating—a new crawler-type delayed hole-forming mechanism has been designed. This mechanism extends the duck bill horizontally, thereby prolonging its opening time, enabling cotton sowing speeds of up to 6 km/h. Following agronomic principles for cotton planting, the overall layout of the crawler-type hole-forming mechanism, the structural parameters of the key components and the trajectory of the hole-forming are determined. We use the Discrete Element Method (DEM) and multi-body dynamics coupling method to simulate and analyze the motion process of the device. The fixed the tilt angle of the duck bill α(A), the depth of the duck bill hole-forming into the soil h(B), and the angle of rotation of the moving duck bill β(C) were taken as the experimental factors, with the longitudinal length of cotton seed hole (Y1) and the hole-forming depth of cotton seed hole (Y2) as the response values. The parameter range of each factor and the preliminary influence on the response value were determined through pre-experiments and single-factor simulation test. Based on RecurDyn-EDEM coupling, a quadratic regression orthogonal rotation combination simulation test was carried out. The results show that the order of the primary and secondary factors affecting the Y1 of the time-lapse hole-forming device was: A > C > B. The order of primary and secondary factors affecting the Y2 of the delayed hole forming device was: B > C > A. When the A was 2.4 °, the B was 42.4 mm, and the C was 30.5 °, the performance of the hole-forming was the best, and the Y1 was 26.4 mm, and the Y2 was 25.0 mm. The bench verification test results show that under the optimized combination of operating parameters, the average Y1 was 29.1 mm, and the average Y2 was 23.2 mm. Compared with the results of the previous coupled simulation model, the average relative errors of the two are 7.23 % and 4.36 %, respectively, indicating the accuracy and effectiveness of the established DEM simulation model and virtual test analysis. The hole-forming area and the opening time of the duck bill after the stable operation of the machine were recorded and measured. The calculated hole dislocation rate Hc was 4.33 %, which did not exceed the national standard requirement of 6 %. The qualified rate of hole distance Hx was 94.33 %, which was much higher than the national standard requirement of 80 %. The average opening time of the duck bill at a speed of 6 km/h is 0.45 s, which is much longer than the time required for cotton seeds to fall from the duck bill 0.11 s. It meets the requirements of high-speed cotton planting in China and facilitating advancements in future high-speed planter technology.

Based on the goals of "high reliability, high frequency, rapid launch, and low cost" for space launch site, and drawing inspiration from the design principles of SpaceX's Starship launch test facility, an integrated dual-sided deflector system for convective cooling and thermal protection is presented. The interaction process between the gas jet and liquid water jet and its effect on the flow field environment are thoroughly studied using numerical calculation methods. Furthermore, Regarding the phase-change heat transfer issue in a compressible gas-liquid two-phase flow and the varying distribution of different bubble shapes and sizes at the gas-liquid interface, a modified Lee model is derived. The rationality and accuracy of the phase-change mass-transfer coefficient values can be improved by adjusting the equivalent diameter and shape factor of the bubbles. The research results demonstrate that compared to the classical Lee model, the modified Lee model can achieve a higher numerical accuracy in predicting the heat and mass transfer processes in gas-liquid two-phase flows. Through comparative analysis with traditional dual-sided deflector and conventional cooling system, the integrated dual-sided deflector system for convective cooling and thermal protection exhibits significant performance advantages in gas flow regulation, flow field environment improvement and erosion protection in the near-ground region of the launch site. Particularly, regarding the thermal environment of the dual-sided deflector, it not only achieves effective flow deflection, but also mitigates the degree of erosion caused by the gas jet on the deflector. This conclusion can provide theoretical references for the thermal protection design of commercial launch vehicle system at space launch site.

The fitting and modeling of skewed, complex, symmetric, and asymmetric datasets is an exciting research topic in many fields of applied sciences, notably lifetime, medical, and financial sciences. The Heavy tailed Nadarajah Haghighi model is introduced by compounding the heavy tailed family and Nadarajah Haghighi distribution in this paper. The so obtained model has three parameters accounting for the scale and shape of the distribution. The proposed distribution's fundamental characteristics such as probability density, cumulative distribution, hazard rate, and survival functions are provided, and several key statistical properties are established, and several entropy information measures are proposed. The estimation of model parameter is performed via the ML procedure. Further, different simulation experiments are conducted to demonstrate the performance of proposed estimator’s using some measure, like the average estimate, the average bias, and associated mean square error. Finally, we are applied our proposed model to analyze three different real datasets. In our illustration, we are compared the practicality of the recommended model with several well-known competing models.

The research work explores the impact of temperature on Silicon photovoltaic (PV) panels considering Nigeria as case study. It is found that high solar radiation in Nigeria increases surface temperature of PV panel above 25oC of optimal operating temperature of PV panels. Redundant energy gain from incident solar energy is dissipated at the rear of PV panels as heat, which reduces the efficiency of PV panel. Cooling mechanism is needed to cool the PV panels to increase the efficiency. In this study we demonstrated a unique design of a bifunctional photovoltaic-thermal (PVT) system by employing heat exchanger at the rear of PV panel and water is used as a working fluid that is circulated through the heat exchanger to remove the excess heat. It is observed from the simulation results that Maiduguri peak annual electrical power output gives 1907kWh/kWp which is the highest, because of high solar radiation average of 727W/m2 in a year. And for Makurdi the peak annual electrical power output of 1542kWh/kWp while for Port Harcourt the peak power output of 1355kWh/kWp respectively. Interestingly, Polycrystalline Si-PV surface temperature decrease from 49.25oC to 38.38oC. Electrical power increased from 1526.83W to 1566.82W in a day and efficiency increase from 13.99% to 15.01%.

Dysregulation of the Cyclin-dependent kinase 8 (CDK8) activity has been associated to many diseases including the colorectal and breast cancer. As usual in the CDK family, the activity of CDK8 is controlled by a regulatory protein called cyclin C (CycC). But while human CDK family members are generally activated in two steps that is, the binding of the cyclin to CDK and the phosphorylation of a residue in the CDK activation loop, CDK8 does not require the phosphorylation step to be active. Another peculiarity of CDK8 is its ability to be associated to CycC while adopted an inactive form. These specificities raise the question of the role of CycC in the complex CDK8-CycC, which appears to be more complex than for the other members of CDK family. Through MD simulations and binding free energy calculations, we investigated the effect of CycC on the structure and dynamics of CDK8 on the one hand, and the structural molecular basis of the protein-protein interaction between the two partners on the other hand. We found that CycC has a stabilizing effect on CDK8 and identified specific interaction hotspots within its interaction surface compared to other human CDK/Cyc pairs. Targeting these specific interaction hotspots could be a promising approach in terms of specificity, to effectively disrupt the interaction between CDK8. The simulation of the conformational transition from the inactive to the active form of CDK8 suggests that the residue Glu99 of the CycC may assume the role of the missing phosphorylation step in the activation mechanism of CDK8. In a more general view, these results point the importance of keeping the CycC in computational studies when studying the human CDK8 protein in both the active and the inactive form.

Electrical contacts are important circuit components with diverse industrial applications, and their failure can lead to multiple unwanted effects. Hence, the behavior of electrical contacts is a widely studied topic in scientific literature based on various approaches, tools, and techniques. The present study proposes a numerical modeling and simulation approach based on the Holm contact theory to study the dependence between the electric potential and the temperature within an electrical contact. Structured in 5 sections, the research was conducted using COMSOL Multiphysics software and its solid-state mechanics, electric current, and heat transfer modules in order to highlight contact behavior from mechanical, electrical and thermal points of view: the von Mises stress, contact force, the electric field amplitude, the variation of the electrical potential along the current path, the temperature gradient, and dependence of temperature along the contact elements edges were obtained by simulation and graphically represented. The results are in line with the expectations and with past research that was studied in the literature review.

: This study presents energy and exergy analyses conducted on a Gifford-McMahon cycle refriger-ator. Through detailed numerical simulations, the performance of the refrigerator is thoroughly assessed, with a particular focus on energy and exergy losses. The obtained results are compared with Sankey and Grassman diagrams, providing visual representations of energy and exergy flows within the system. The localization of exergy losses is carefully analysed to identify key areas for optimization aimed at enhancing efficiency and power output. By pinpointing sources of ex-ergy destruction, targeted improvements can be implemented to maximize the overall perfor-mance of the refrigerator. Overall, this research contributes to a deeper understanding of the thermodynamic behaviour of Gifford-McMahon cycle refrigerators and provides valuable insights for optimizing their performance in practical applications.

The research on the excavation mechanical properties of underpass tunnels has already had certain results, but fewer of them consider the effects of dynamic and static loads on the excavation mechanical properties of underground tunnels at the same time, especially the lack of research cases of double-line highway tunnels with angled underpasses of existing railway tunnels. In this paper, based on the tunnel project of the new double-line Shiqian Highway Tunnel passing under the Hurong Railway at an oblique angle, the mechanical parameters of the rock body in the cross-tunneling area under the influence of static and dynamic load coupling are obtained by using the disturbance quantification coefficients and the Hoek-Brown criterion based on the method of over-advanced geological prediction and the investigation of the surrounding rock on the palisade face, and the engineering-scale finite element model is constructed and the mechanical characteristics of the excavation in the tunnel of the double-lane highway tunnel passing under the existing railroad under the influence of the static and dynamic loads are analyzed. The results show that: the new tunnel rock movement law for the top of the arch sinking, bottom plate bulging, side wall to move outward, the height and width of the arch and bottom plate arch with the tunnel excavation and increase, the side wall rock displacement effect is smaller; left and right lines of the tunnel disturbed area of the rule of change is similar; the existing tunnel bottom plate displacement is more than the top plate and the left and right side walls by the excavation of the time step influence is larger. Typical profile displacement is mainly determined by the distance from the excavation surface; the new tunnel in the four types of calculation conditions of the rock disturbance angle is the same; the existing tunnel roof and side wall Von Mises stress extreme occurs in the tunnel structure, the bottom plate there are pressure relief and pressure-bearing areas; based on the displacement control criteria, the recommended upper and lower step blasting method.

The early detection of small cracks in large structures is a crucial requirement for the implementation of structural health monitoring (SHM) system with a low transducer density. This work presents the results of the analysis of scattering of a submillimeter notch type defect with semielliptical shape with a groove at constant width 100µm in a 4.1mm thick aluminum plate. The defect is investigated with an ultrasonic guided wave (UGW) A0 mode at 550 kHz to cover long range in a thick plate. The mode selection is obtained by interdigital transducers designed to operate with 5mm central wavelength. The novel contribution is the assessment of the scattering amplitudes at different orientations of the defect when the distance is large as 35 cm in pulse-echo mode or 70 cm in pitch-catch mode. The system model is based on Finite Element Model (FEM) simulations and the results are in good agreement with experimental tests. The detection of the defect is obtained by comparing the scattered signals from the defect with base line signals of the pristine laminate. The analysis of scattering features and the efficient excitation with a probing UGW show the potential implementation in real structural health monitoring (SHM) systems.

This paper presents a mathematical modeling approach utilizing a fuzzy modeling framework for fixed wing aircraft systems with the goal of creating a highly desirable mathematical representation for model-based control design applications. The starting point is a mathematical model comprised of fifteen non-linear ordinary differential equations representing the dynamic and kinematic behavior applicable to a wide range of fixed wing aircraft systems. Here the proposed mathematical modeling framework is applied to the AIRBUS A310 model developed by ONERA. The proposed fuzzy modeling framework takes advantage of sector non-linearity techniquesto recast all the non-linear terms from the original model to a set of combined fuzzy rules. The result of this fuzzification is a more suitable mathematical description from the control system design point of view. Therefore, the combination of this fuzzy model and the wide range of control techniques available in the literature for such kind of models will enable us to avoid common control design methods, such as gain scheduling, where stability issues can be extremely challenging.

Generalized distributions have been studied a lot recently because of their flexibility and relia-bility in modeling lifetime data. The two-parameter exponentially-modified logistic distribution is a new flexible modified distribution that was introduced recently. It is regarded as a strong competitor for widely used classical symmetrical and non-symmetrical distributions such as normal, logistic, lognormal, and log-logistic. In this study, the unknown parameters of the dis-tribution are estimated using the maximum likelihood method. The Grey Wolf Optimization al-gorithm, which is a new meta-heuristic algorithm, is applied in order to solve the nonlinear like-lihood equations of the study model. The performance of the Grey Wolf Optimization method is compared to that of the other meta-heuristic algorithms used in this study, which include the Whale Optimization Algorithm, the Sine Cosine Algorithm, and the Particle Swarm Optimiza-tion Algorithm. The efficiencies of maximum likelihood estimates for all algorithms are com-pared via an extensive Monte-Carlo simulation study. The likelihood estimates for the location α and scale β parameters of the exponentially-modified logistic distribution developed with the Grey Wolf Optimization algorithm are the most efficient among others, according to simulation findings. Four real datasets are analyzed to show the flexibility of this distribution.

In response to growing industrial demands, necessitated by larger ships and increased cargo volumes, many port authorities worldwide are undertaking a significant expansion of their infrastructure to increase their capacity. Significant expansion raises challenges such as potential congestion and environmental concerns, especially for port located in urban area as the case study explored in this paper. To address these issues, the study employs a combination of scenario analysis developed in collaboration with the port authority and logistic system simulation. This approach assesses the capacity of existing access gates to handle the increased trucking traffic and optimizes the unloading process of construction trucks at a new terminal. Key findings suggest that while the current gate capacities are adequate, optimizing unloading times at the new terminal is critical to prevent road congestion in urban area before the gate and reduce negative impacts such as sound and atmospheric pollution. The study advocates for an appointment system during peak hours to manage traffic flow effectively and underscores the importance of collaboration between the city and port authorities in managing truck traffic to mitigate congestion on the city side. Nonetheless, the study recognizes certain constraints, including the incomplete evaluation of the influence of intermodal transport on truck traffic. Furthermore, the study emphasizes the need for future research to consider the correlation between vehicle numbers and service levels, aiming to effectively adjust the time in the system.

In several emergency situations, during natural or human-caused disasters, frontline responders need to be able to communicate and collaborate to properly carry out the relief mission. Some countries are building their national Public Safety Mobile Broadband based on cellular LTE technology to provide fast, safe, and secure emergency services. Otherwise, in several emergency situations, the cellular antennas can be overloaded or partially damaged in manner to affect the group communication services. Since few last years, direct device-to-device (D2D) communications have been proposed by 3GPP as an underlay to Long Term Evolution (LTE) networks based on proximity, reuse, and hop gains. This paper focuses on the loosely coupled model based on D2D direct communication for Public Safety context. Many scenarios related to user membership and network management are detailed. Both “less cost” and “optimized tree” approaches are proposed, implemented, and their performance evaluated in terms of network updates number and resulting average Channel Quality Indicator (CQI). Other optimization approaches with different CQI threshold and optimization interval values have been implemented, simulated and their performance are compared with the “optimized tree”.

Eruca sativa is a commonly used edible plant in Italian cuisine. E. sativa 70% ethanol extract (ES) was fractionated with five organic solvents. Ethyl acetate fraction(EEA) had the highest antioxidant activity, which was correlated with the total polyphenol and flavonoid content. ES and EEA acted as PPAR-α ligands by PPAR-α competitive binding assay. EEA significantly increased cornified envelope formation as a keratinocyte terminal differentiation marker in HaCaT cells. Further, it significantly reduced nitric oxide and pro-inflammatory cytokines in lipopolysaccharide-stimulated RAW 264.7 cells. The main flavonol forms detected in high amounts from EEA are mono-, and di-glycoside of each aglycone. Flavonol mono-glycosides were shown to be a potent PPAR-α ligand using molecular docking simulation and showed the inhibition of nitric oxide. These results suggest that E. sativa is suitable for use in improving skin barrier function and inflammation in skin disorders, such as atopic dermatitis.

(1) Background: OCT imaging has been used to assess enamel demineralization in dental research but is not yet developed enough to qualify as a diagnostic technique in clinics. The current capabilities of most commercial acquisition software allow for visual and qualitative assessment. There is a need for a fast and verified batch-processing algorithm for segmenting and analyzing the de-mineralized enamel. This study suggests a GUI MATLAB algorithm for processing and quantitative analysis of the demineralized enamel. (2) Methods: A group of artificially demineralized human enamels was in vitro scanned under the OCT, and ROI frames were extracted. By using a selected intensity threshold colormap, inter- (Ie) and intra- (Ia) prismatic demineralization can be segmented. A set of quantitative measurements for average demineralized depth, average line profile, and integrated reflectivity can be obtained for an accurate assessment. Real and simulated OCT frames were used for algorithm verification. (3) Results: A strong correlation between automated and known Excel measurements for the average demineralization depth was found (R² > 0.97). (4) Conclusions: OCT image segmentation and quantification of the enamel demoralization zones are possible. The algorithm can assess the future development of a real-time assessment of dental diagnostics using an oral probe OCT.

Agricultural drainage canals that connect upstream fish spawning areas to downstream rivers and lakes serve as crucial habitats for migrating fish. However, disconnections, such as drops and chutes, have been constructed in these canals due to agricultural modernization and flood control measures, hindering the movement of fish with limited swimming abilities. Portable fishways offer a promising solution to reconnect water bodies in agricultural canals, as they can be easily removed during high water discharges to avoid impeding the canals' drainage function. In addition to experimental assessments of fishway functionality, employing a hydrodynamic model to explore effective placement strategies for portable fishways is essential to maximize their effectiveness. This study presents a method to determine the best horizontal location of a portable fishway in an agricultural drainage canal using two-dimensional hydrodynamic simulations within the specified cases. The applicability of this method is demonstrated by addressing the positioning challenge of a portable fishway on a chute in an agricultural drainage canal in Japan. Results indicate that the proposed method allows for the selection of a suitable location, considering preferable hydraulic conditions both within the portable fishway and around its entrance.

Cycle times at workstations in offsite construction factories fluctuate widely due to various influencing factors. Consequently, relying on average rates, such as length per unit of time, for estimating cycle times proves to be inaccurate, often leading to significant deviations between production schedules and actual operations. To address this issue, this study proposes an estimation system that leverages machine-learning-based prediction, statistical methods, 3D simulation, and computer vision to predict cycle times at the workstation level. Testing of the system on a semi-automated wood-wall framing workstation in a panelized construction factory shows that it reduces the mean absolute error and sum of errors by approximately 36% and 68%, respectively, compared to the fixed rate method. The results also highlight the efficacy of using computer vision data for training machine-learning models for cycle time estimation, the importance of identifying and understanding the factors influencing cycle times, and the impact of random delays on the accuracy of cycle time estimation systems.

In recent years, the genesis of natural gas and the definition of major gas source rocks in the Baiyun Sag of the Pearl River Mouth Basin have attracted extensive attention from scholars. There is still considerable controversy over the genesis and the main gas source rocks of natural gas. In this study, the chemical kinetics method of natural gas generation and carbon isotope fractionation was used to study the generation history and isotope evolution history of Paleogene natural gas in the Y5 well area located on the north slope of Baiyun Sag. And other geochemical discriminant methods were applied simultaneously to determine the type and source rocks of natural gas. The results show that the natural gas in the Y5 well area on the northern slope of Baiyun Sag is mainly kerogen degradation gas, mixed with a small amount of oil cracking gas. The mixture of kerogen degradation gas and a small amount of crude oil cracking gas caused the inversion of the carbon isotope sequence of ethane and propane. The natural gas in the Y5 well area mainly comes from delta–shallow lacustrine facies source rock. The high–quality reservoirs in the shallower strata accumulate natural gas generated in the early stage, and the tight reservoirs in the deeper strata mainly accumulate natural gas generated in the late stage.

One of the rapidly developing research areas in the power system is the integration of distributed generation (DG) with the distribution system. The size and location of DG sources had a considerable impact on power system networks. Artificial intelligence (AI) techniques can be used to address multidimensional problems relating to DG size and location in distribution systems. Heuristic optimization offers a reliable and effective method for solving complicated real-world problems. This work focuses on a hybrid approach that combines the two heuristic optimization methods i.e., Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) for the optimal siting and sizing of DG in distribution systems. This hybrid approach combines ideas from GA and PSO and generates individuals in a new generation using both PSO mechanisms and the procedures found in GA. An extensive performance analysis of the IEEE 14 busbar standard test system is conducted to demonstrate the viability of the suggested methodologies. In the designated locations, DG is placed, and the outcomes have been verified. The results indicated that the right placement of DG injection enhances the voltage profile and lowers the distributed system’s power losses. These techniques offer unique methods for determining the location of the DG unit, demonstrating the potential of such a computational techniques to reduce computing time and complexity while simultaneously reducing human errors associated with hit-and-trail methods.

Polo-like kinase 1 (PLK1) plays a pivotal role in cell division regulation and emerges as a promising therapeutic target for cancer treatment. Consequently, the development of small-molecule inhibitors targeting PLK1 has become a focal point in contemporary research. The adenosine triphosphate (ATP)-binding site and the polo-box domain in PLK1 present crucial interaction sites for these inhibitors, aiming to disrupt the protein's function. However, designing potent and selective small-molecule inhibitors can be challenging, requiring a deep understanding of protein-ligand interaction mechanisms at these binding sites. In this context, our study leverages the fragment molecular orbital (FMO) method to explore these site-specific interactions in-depth. Through the FMO approach, we used the FMO method to elucidate the molecular mechanisms of small-molecule drug binding to these sites to design PLK1 inhibitors that are both potent and selective. Our investigation further entailed a comparative analysis of various PLK1 inhibitors, each characterized by distinct structural attributes. This comparison enhanced our understanding of the structure-activity relationships of these inhibitors, underscoring the efficacy of the FMO method in identifying critical binding features and predicting binding modes for small-molecule ligands. Furthermore, Our research spotlighted "hot spot" residues instrumental for selective and robust PLK1 binding. Our findings offer profound insights, priming the rational design of innovative potential PLK1 inhibitors with significant implications for developing anticancer therapeutics.

The production of anatase titanium dioxide particles plays a crucial role in the sulfate process used for manufacturing white pigment. A key factor in improving the quality of white pigments is enhancing the thermal mixing process within the precipitation tank. This improvement ensures the uniform dispersion of seed particles instead of their agglomeration, leading to the formation of particles with uniform sizes. The objective of this study was to enhance three-phase CFD simulations involving the mixing process of H₂SO₄ solution, steam as a gas phase, and solid seed particles. By analyzing the trajectories of the seed particles using CFD, the optimal injection position for the seed particles within the mixing process was determined. Subsequently, lab scale test and real field test were conducted based on the insights gained from the CFD simulations. The particle size distribution of two different types of seed inlets was analyzed and compared using Transmission Electron Microscopy (TEM). The findings of this study demonstrate that the developed multi-phase CFD simulation can be effectively utilized to enhance the precipitation process for the production of anatase titanium dioxide particles.

Variations in threshold voltage (VTH) and charge distributions in noncircular cells of three-dimensional (3D) NAND flash memory are investigated. The electric field difference in the circular and spike regions causes nonuniform trapped electron density in the charge trap layer (CTL) and influences the VTH variation. Such less-trapped electron (LT) regions in CTL between the circular and spike regions exhibit a lower electric field during the program, resulting in a higher current flow through that region. For the two-spike cells, the charge distribution and VTH variation are analyzed at different heights (HSpike) and angles between spikes. These irregular cells decrease VTH as the HSpike increases.

The entry and exit method is a simple and practical method to determine the critical slip surface of slope. However, it has the drawback of sacrificing computational efficiency to improve search accuracy. To solve this problem, this paper proposes an improved entry and exit method to search for the critical slip surface. Based on the random fields generated by using Karhunen–Loève expansion method, the simplified Bishop’s method combined with the improved entry and exit method is used to determine the critical slip surface and its corresponding minimum factor of safety. Then, the failure probability is calculated by conducting Monte Carlo simulation. Two examples are reanalyzed to verify the accuracy and efficiency of the proposed method. Meaningful comparisons are made to demonstrate the calculating accuracy and calculating efficiency of the improved entry and exit method in searching for the minimum safety factor of slope, based on which the effect of the reduced searching range on slope reliability was explored. The results indicate that the proposed method provides a practical tool for evaluating the reliability of slopes in spatially variable soils. It can greatly improve the computational efficiency in relatively high-computational accuracy of slope reliability analysis.

In this paper, possibilities for the bandwidth and wavelength utilization in future next-generation passive optical networks are presented and reasons for realizing and utilizing of extended dynamic wavelength and bandwidth algorithms for NG-PON2 networks are analyzed. Next, principles of the effective dynamic bandwidth allocation are introduced in details, focused on the importance of the decision criterion optimization. For achieving better bandwidth utilization of dedicated wavelengths, this paper is focused on the novel effective dynamic bandwidth allocation algorithm with adaptive allocation of wavelengths to ONU units and on the optimization of the decision criterion. For analyzing the novel extended DWBA algorithm utilizing for various wavelength allocation cases possible in NG-PON2 networks, a simulation program with the enhancement of the EDBA algorithm is realized. Finally, an optimization of the decision criterion defining a minimum bandwidth utilization of the actual wavelength is executed for NG-PON2 networks based on the hybrid TWDM technique.

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

The ultrasonic vibration assisted pressing process can improve the fluidity, the uneven distribution of density and particle size of WC-Co powder. However, the microscopic mechanism of ultrasonic vibration on the powder remains unclear. In this paper, WC and Co particles are simulated by three-dimensional spherical models of two particle sizes with the aide of the secondary development of Python. At the same time, the forming process of powder at mesoscale is simulated in the virtue of the finite element analysis software ABAQUS. The influence of vibration amplitude on the fluidity, the filling density and the stress distribution of WC-Co powder is investigated when the ultrasonic vibration is applied to the conventional pressing process. From simulation results, the ultrasonic vibration amplitude has great influences on the density of the compact. With the increase of the ultrasonic amplitude, the compact density also increases gradually. At the initial stage of the compaction, the particles move violently under the action of ultrasonic vibration, the fluidity is obviously enhanced, the arch bridge effect between particles is destroyed, the fine particles quickly fill the pores between the large particles, which increase the density, and the residual stress in the billet decreases after the compaction. From the experimental results, the size distribution of the billet is more uniform, the elastic aftereffect is reduced, the dimensional instability is improved, and the density curves obtained by experiment and simulation are within a reasonable error range.

Being one of the most critical phases of a flight, landing deserves specific attention, especially when the aircraft is subject to external disturbances such as wind. A notable concern associated with touchdown events, especially when crosswind is present is tire wear. This work is aimed first at developing a nonlinear flight simulator able to handle the entire landing maneuver in non-null wind conditions, considering the airborne phase, ground run, and the transition between them. Then, the simulator is included in an optimal process to define the landing technique associated with the minimum tire wear. The methodology is tested in a simulation environment with a realistic model of a reference aircraft, showing that a significant reduction of tire wear can be obtained by optimizing the sideslip angle at touchdown and the lateral-directional controls after the airplane touches the runway with both legs of the main landing gear.

To obtain a given structure in 3D building-up modes, it is necessary to use optimal surfacing modes that determine the amount of heat input in local areas. For this purpose, aluminum bronze was surfacing onto a deformed base and the structure and its characteristics in the surfacing and heat-affected zones were studied by the EBSD method. The heterogeneity of the formation of the structure in each selected zone is established, which indicates the heterogeneity of heat input in local areas of the material in one mode of surfacing. For typical cases of crystallization, a molecular dynamics simulation of crystallization processes with different heat input to the base with characteristics specified based on experimental data was carried out. It has been established that the amount of heat input determines the degree of melting and the inherited defectiveness of growing crystals. The formation of misorientation boundaries and crystallization centers of new grains is determined by the conditions of joint growth of grains with given crystallographic parameters of the computational model. Numerical calculations agree with the experimentally observed results.

Accurate analysis of continuous-wave electron spin resonance (cw ESR) spectra of biological or organic free-radicals and paramagnetic metal complexes is key to understand their structure-function relationships and electrochemical properties. Current method of analysis based on simulations often fail to extract the spectral information accurately. In addition, such analyses are highly sensitive to spectral resolution and artifacts, users’ defined input parameters and spectral complexity. We introduce a simulation-independent spectral analysis approach that enables broader application of ESR. We use a wavelet packet transform-based method for extracting g values and hyperfine (A) constants directly from cw ESR spectra. We show that our method overcomes the challenges associated with simulation-based methods for analyzing poorly / partially resolved and unresolved spectra, which is a common in most cases. The accuracy and consistency of the method are demonstrated on a series of experimental spectra of organic radicals and copper-nitrogen complexes. We showed that for a two-component system, the method identifies their individual spectral features even at a relative concentration of 5% for the minor component.

Phthalate esters (PAEs) are a ubiquitous kind of environmental endocrine-disrupting chemicals, causing environmental and health issues. EstJ6 is an effective phthalate-degrading hydrolase, and its mutant with a combination of three non-conservative distal mutations has an improved activity against PAEs with unknown molecular mechanisms. Herein, we attempt to fill the significant gap between distal mutations and the activity of this enzyme using computational approaches. We find mutations result in a redistribution of enzyme’s preexisting conformational states and dynamics changes of key functional regions, especially the lid over the active site. The outward motion of the lid upon mutations should make it easier for substrates or products to enter or exit. Additionally, the stronger substrate binding affinity and conformational rearrangements of catalytic reaction-associated residues in mutant, accompanied by the strengthened communication within the protein, might contribute to the elevated catalytic efficiency. Finally, an attempt has been done to improve the thermostability of EstJ6 upon introducing a distal disulfide bond between residues A23 and A29, and the simulation results are as expected. Together, our work explored the allosteric effects caused by distal mutations, which could provide insights into the rational design of esterases for industrial applications in the future.

By employing a variation of the polyamidation method using in situ silylated diamines and acid chlorides, it has been possible to obtain a rod-type polyamide: poly(p-phenylene terephthalamide) (PPTA, a polymer used in the high value-added material Kevlar), with a molecular weight much higher than that obtained with the classical, and industrial, polyamidation method. The optimization of the method has consisted in using, together with the silylating agent, a mixture of pyridine and a high pKa tertiary amine. The research has been complemented by a combination of nuclear magnetic resonance and molecular simulation studies, which have determined that the improvements in molecular weight derive mainly from the formation of silylamide groups in the growing polymer.

Digital Elevation Model (DEM) is a representation of elevation data that represent terrain with or without overlaying objects of the Earth. It is the ideal and most widely used method for determining topography. DEMs are generated from various techniques such as traditional Surveying, Photogrammetry, InSAR, LiDAR, Clinometry and radargrammetry. It has been observed that mostly LiDAR-generated DEMs provide the best accuracy. The unavailability of LiDAR data in most of the region restricts global researchers from high-resolution and accurate DEMs. The recent launch of ICESat-2 with a 13m beam footprint and 0.7m pulse interval, promises elevations at high orbital precision. Its accuracy is of the order of few centimeters in complex topography, because of this ICESat-2 proves to be a good source to generate high-accuracy DEMs. ICESat-2 provides discrete photon data with elevations of points on the Earth’s surface. Traditional interpolation techniques tend to over-smooth the estimated space and still are unable to justify the complicated continuity in the topographical data. Machine learning algorithms are widely being used to extract patterns and spatial extent in geographic data. To estimate a DEM from ICESat-2 LiDAR point data, machine learning regression algorithms are implemented in this study. The present study has been performed for a plain region of Ghaziabad, Uttar Pradesh, India. Studies have shown that Cartosat-1 DEM V3 R1 product provides an accuracy of the order of 2m in predominantly plain regions, hence taken for this region. Current work focuses on comparing various regression-based machine-learning techniques to interpolate DEM from ICESat-2 data The RMSE of the interpolated DEM resulted from the Gradient Boosting Regressor, Random Forest Regressor, Decision Tree Regressor, and Multi-Layer Perceptron Regressor was 7.13m, 7.01m, 7.15m, and 3.76m, respectively when evaluated against the TANDEM-X DEM of the same region. The MLP Regressor is found to perform the best among the four algorithms tested.

The stick-free flight stability is an old-fashioned and non-progressive issue; nevertheless, it is still existent, and of significant importance to the design of aircraft whose control system is reversible. The problem’s existence necessitates a deep assessment of stick-free flight stability throughout the aircraft design. Up to now, this problem has been addressed using either analytical approaches, which are only related to the static stability evaluation, or performing flight tests. In this study, the problem is handled in its entirety, from static and dynamic flight stability assessment to design criteria with a comprehensive perspective. Moreover, it is also exhibited that contrary to what has been generally proposed in the literature, limiting the problem of stick-free flight stability through static stability assessment is far from the main challenge. As a brief scope, the derivation of the control surface dynamics, a stick-free trim algorithm, and assessment rationale of the stick-free static and dynamic flight stability using a simulation approach are proposed. As a consequence, the aim is to set a broad understanding for designers related to this phenomenon and add adjunct design criteria in the design optimization process by approaching it in terms of modeling, simulation, and flight test perspective.

Recently, there has been increasing attention toward inhaled nanoparticles (NPs) to develop in-halation therapies for diseases associated with the pulmonary system and investigate the toxic ef-fects of hazardous environmental particles on human lung health. Taking advantage of microfluidic technology for cell culture applications, lung-on-a-chip devices with great potential in replicating the lung air-blood barrier (ABB) have opened new research insights in preclinical pathology and therapeutic studies associated with aerosol NPs. Surprisingly, the air interface in such devices, which makes them tremendously unique among the other common liquid-based cellular mi-crosystems and enables exposure of cultivated cells to the drug/toxic aerosols, has been largely disregarded. Accordingly, there exists a significant research gap in the comprehensive under-standing of the NPs’ dynamics in the lung-on-a-chip devices, which is momentous to control the injection of aerosols to the target area and attain a desired physiochemical efficacy. To address this research gap, a numerical parametric study is presented to provide a deep insight into the dynamic behavior of the airborne NPs in a gas-liquid dual-channel lung-on-a-chip device with a porous membrane separating the channels. A finite element multi-physics model is developed to enable a particle tracing investigation simultaneously in both air and medium phases to replicate the in vivo conditions avoiding laborious and costly experimental trials. The results include the impact of fluid flow as well as geometrical properties on the distribution, deposition, and translocation of the NPs with diameters ranging from 10 nm to 900 nm in the lung-on-a-chip. The obtained results strongly suggest the aerosol injection of NPs instead of the aqueous solution for more efficient deposition on the substrate of the air channel and higher translocation to the media channel. The current study proposes to optimize the affecting parameters to control the injection and delivery of aerosol par-ticles into the lung-on-chip device depending on the objectives of biomedical investigations and provides optimized values for some specific cases. Therefore, this study can assist scientists and researchers in complementing their experimental investigation in future preclinical studies on pulmonary pathology associated with inhaled hazardous and toxic environmental particles, as well as therapeutic studies for developing inhalation drug delivery.

This paper focuses on the combination of the method of moments and the wire-grid approximation as an effective computational technique for modeling symmetrical antennas with low computational cost and quite accurate results. The criteria and conditions for the use of wire-grid surface approximation from various sources are presented together with new recommendations for modeling symmetrical antenna structures using the wire-grid approximation. These recommendations are used to calculate the characteristics of biconical and horn antennas at different frequencies. The results obtained using different grid and mesh settings are compared to those obtained analytically. Moreover, the results are compared to those obtained using the finite difference time domain numerical method, as well as the measured ones. All results are shown to be in a good agreement. The used recommendations for building a symmetrical wire-grid of those symmetrical antenna elements provided the most advantageous parameters of the grid and mesh settings and the wire radius, which are able to give a quite accurate results with low computational cost. Additionally, the known equal area rule was modified for a rectangular grid form. The obtained radiation patterns of a conductive plate using both the original rule and the modified one are compared with the electrodynamic analysis results. It is shown that the use of the modified rule is more accurate when using a rectangle grid form.

Finite element (FE) modeling is commonly used as a method to investigate the influence of medical devices, such as implants and screws and their effects on the biomechanical behavior of the spine. Another simulation method is a multi-body simulation (MBS), where the model is composed of several non-deformable bodies. MBS solvers generally require a very short computing time for dynamic tasks compared to an FE analysis. Considering this computational advantage, in this study, we examine whether parameters whose values are not known a priory can be determined with sufficient accuracy using MBS model. Therefore, we propose a Many-at-a-time sensitivity analysis method that allows approximating these a priory unknown parameters without requiring long simulation times. This method enables a high degree of MBS model optimization to be achieved in an iterative process. The sensitivity analysis method is applied to a simplified screw-vertebra model, consisting of an anterior anchor implant screw and vertebral body of C4. An experiment described in the literature is used as a basis for developing and assessing the potential of the method for sensitivity analysis and to validate the models action. The optimal model parameters for the MBS model were determined to be c=823224N/m for stiffness and d=488Ns/m for damping. The presented method of parameter identification can be used in studies including more complex MBS spine models or to set initial parameter values that are not available as initial values for FE models.

Damage in concrete structures initiates as the growth of diffuse microcracks that is followed by damage localisation and eventually leads to structural failure. Weak changes such as diffuse microcracking processes are failure precursors. Identification and characterisation of these failure precursors at an early stage of concrete degradation and application of suitable precautionary measures will considerably reduce the costs of repair and maintenance. To this end, a reduced order multiscale model for simulating microcracking-induced damage in concrete at the mesoscale levelis proposed. The model simulates the propagation of microcracks in concrete using a two-scale computational methodology. First, a realistic concrete specimen that explicitly resolves the coarse aggregates in a mortar matrix was generated at the mesoscale. Microcrack growth in the mortar matrix is modelled using a synthesis of continuum micromechanics and fracture mechanics. Model order reduction of the two-scale model is achieved using clustering technique. Model predictions are calibrated and validated using uniaxial compression tests performed in the laboratory.

Ocean surface waves have been utilized as fundamental information in various fields of oceanic research. In this paper, we suggest a simulation and modelling technique for generating an ocean surface wave using an inverse Fast Fourier Transform (iFFT), and we subsequently verify the wave’s accuracy. The conventional method, linear superposition, requires recursive calculation because of the double summation and the time variable; to circumvent this issue, the new algorithm is presented. The Joint North Sea Wave Project (JONSWAP) spectrum is utilized for the ocean surface wave simulation example, and the parameters are the significant wave height (HS) and the zero-crossing wave period (TZ). A coordinate transform for the wavenumber domain was used to apply the inverse FFT algorithm. To verify the accuracy of the simulation result, the relative error between the input condition and the analysis result was calculated. The result for TZ is below 4% relative error, and the maximum relative error for HS is 7%. To avoid the Nyquist frequency for wave-field analysis and simulation, the minimum grid size was calculated by twice applying the maximum wavenumber.

The matrix converter converts the input line voltage into a variable voltage with an unrestricted output frequency without using an intermediate circuit, dc link circuit. A pure sine in and pure sine out is the unique feature of the matrix converter. This research paper also analyzes the basic operating principle and the simulation modeling of the direct matrix converter, which is controlled by the Space Vector Pulse Width Modulation technique by using the software which is known as MATLAB/Simulink. The most desirable features in the power frequency changes can be fulfilled by using the matrix converters, and this is the reason for the tremendous interest in the topology. Since the power electronic circuits which is known as the motor drives are used to operate the AC motors at the frequencies other than that of the supply.

In this note, I analyze the data generated by M. Fodje's (2013) simulation programs "epr-simple" and "epr-clocked". They were written in Python and published on Github. Inspection of the program descriptions shows that they make use of the detection-loophole and the coincidence-loophole respectively. I evaluate them with appropriate modified Bell-CHSH type inequalities: the Larsson detection-loophole adjusted CHSH, and the Larsson-Gill coincidence-loophole adjusted CHSH (NB: its correctness is conjecture, we do not have proof). The experimental efficiencies turn out to be approximately eta = 81% (close to optimal) and gamma = 55% (far from optimal). The observed values of CHSH are, as they should be, within the appropriately adjusted bounds. Fodjes' detection-loophole model turns out to be very, very close to Pearle's famous 1970 model, so the efficiency is close to optimal. The model has the same defect as Pearle's: the joint detection rates exhibit signaling. Fodje's coincidence-loophole model is actually a clever modification of his detection-loophole model. Because of this, however, it cannot lead to optimal efficiency.

Infection of hosts by morbilliviruses is facilitated by the interaction between viral hemagglutinin (H-protein) and the signaling lymphocytic activation molecule (SLAM). Recently, the functional importance of the N-terminal region of human SLAM as a measles virus receptor was demonstrated. However, the functional roles of this region in the infection process by other morbilliviruses and host range determination remain unknown partly because this region is highly flexible, which has hampered accurate structure determination of this region by X-ray crystallography. In this study, we analyzed the interaction between the H-protein from canine distemper virus (CDV-H) and SLAMs by a computational chemistry approach. Molecular dynamics simulations and fragment molecular orbital analysis demonstrated that the unique His28 in the N-terminal region of SLAM from Macaca is a key determinant that enables formation of a stable interaction with CDV-H, providing a basis for CDV infection in Macaca. The computational chemistry approach presented should enable determination of molecular interactions involving regions of proteins that are difficult to predict from crystal structures because of their high flexibility.

A humidity-sensitive demand-controlled ventilation system is known for many years. It has been developed and commonly applied in regions with an oceanic climate. Some attempts were made to introduce this solution in Poland in a much severe continental climate. The article evaluates this system's performance and energy consumption applied in an 8-floor multi-unit residential building, virtual reference building described by the National Energy Conservation Agency NAPE, Poland. The simulations using the computer program CONTAM were performed for the whole hating season for Warsaw's climate. Besides passive stack ventilation that worked as a reference, two versions of humidity-sensitive demand-controlled ventilation were checked. The difference between them lies in applying the additional roof fans that convert the system to hybrid. The study confirmed that the application of demand-controlled ventilation in multi-unit residential buildings in a continental climate with warm summer (Dfb) leads to significant energy savings. However, the efforts to ensure acceptable indoor air quality require hybrid ventilation, which reduces the energy benefits. It is especially visible when primary energy use is analyzed.