N-methyl-D-aspartate receptors (NMDARs) are the main class of ionotropic receptor for the ex-citatory neurotransmitter glutamate. It plays a crucial role in the permeability of Ca2+ ions and excitatory neurotransmission in the brain. Being heteromeric receptors, they are composed of sev-eral subunits, including two obligatory GluN1 subunits (eight splice variants) and regulatory GluN2 (GluN2A~D) and/or GluN3 (GluN3A~B) subunits. Widely distributed in the brain, they regulate other neurotransmission systems and are therefore involved in essential functions such as synaptic transmission, learning and memory, plasticity, excitotoxicity. The present review will discuss the physiopathological impacts of NMDAR and particularly GluN2A and GluN2B subu-nits in cognitive processes and neurodegenerative diseases (Alzheimer's disease, Huntington's disease, Parkinson's disease). The pharmacology of different NMDAR antagonists and their po-tentialities will be presented. In particular, a focus will be given on fluoroethylnormemantine (FENM), an investigational drug with very promising developments as a tomography radiotracer for NMDARs, an anxiolytic in post-traumatic stress disorder and a neuroprotective agent in Alzheimer's disease.

Introduction: The academic landscape is increasingly recognizing the complex interplay of personal and professional responsibilities on scholarly productivity. For women scholars, particularly those with significant parenting duties, this balance is even more precarious. This study aims to explore how family responsibilities, personal vulnerabilities, and motivational theories such as Imposter Syndrome and Self-Determination Theory (SDT) influence the motivation to publish scholarly work. Understanding these dynamics is crucial for developing supportive mechanisms that can enhance academic productivity and personal fulfilment. Methods: Utilizing a Qualitative Evidence Synthesis (QES) framework, this study will systematically review and synthesize qualitative research on women scholars' experiences in academia, focusing on the challenges and motivators related to publishing. Data sources will include academic databases, grey literature, and first-hand narratives. Thematic analysis will be employed to identify key themes and patterns across the collected data. Results/Findings: Preliminary findings suggest that the dual demands of parenting—especially in extreme cases such as assuming responsibility for seven children—and academic work significantly impact women scholars' publishing activities. Personal vulnerabilities, including imposter syndrome and low self-efficacy, further exacerbate these challenges. However, the data also highlight resilience strategies and the potential for intrinsic and extrinsic motivational factors to mitigate these effects. Discussion: The study underscores the nuanced impact of familial and personal factors on academic motivation. The preliminary findings suggest that addressing imposter syndrome and enhancing self-determination could be pivotal in supporting women scholars. The role of institutional policies and academic culture in either exacerbating or alleviating these challenges is also discussed. Significance: By elucidating the specific challenges and motivators for women scholars in publishing, this study will contribute to the development of targeted interventions and policies that support work-life integration and promote academic productivity. The insights that will be gained could inform mentorship programs, institutional support systems, and policy reforms aimed at fostering a more inclusive and supportive academic environment.

Radish (Raphanus sativus L.), a root vegetable belonging to the Brassicaceae family, is considered as one of the representative crops displaying sporophytic self-incompatibility (SSI). The utilization of a self-incompatibility system in F1 breeding can improve the efficiency of cross combinations, leading to a reduction in breeding time and aiding in the development of novel F1 varieties. The successful implementation of this system necessitates the rapid and accurate identification of S haplotypes in parental lines. In this study, we identified a total of 9 S haplotypes among 22 elite radish lines through Sanger sequencing. Subsequently, we obtained sequences for showing 95% similarity to 9 S haplotypes, along with sequences identified by other researchers using BLAST. Following this, multiple sequence alignment (MSA) was conducted to identify SRK and SLG sequence similarities, as well as polymorphisms within the class I, II groups. Subsequently, S haplotype-specific marker sets were developed, targeting polymorphic regions of SRK and SLG alleles. These markers successfully amplified each of 9 S haplotypes. these markers will play a crucial role in the rapid and precise identification of parental S haplotypes in the radish F1 breeding process, proving instrumental in the radish F1 purity test.

Indigenous Peoples in Canada have shown great strength and resilience in maintaining their cultures and ways of life to date in the face of settler colonialism. Centering the water crises within Indigenous sovereignty and self-determination, we explore the impacts these crises are having on community members. Particularly, the continuous failure of the Canadian government to end the water crises in remote Indigenous communities, Star Blanket Cree Nation, is investigated in this paper. What implications have these water governance gaps had on Indigenous Peoples’ sovereignty and self-determination? We adopted an Indigenist theoretical framework to guide the study. Additionally, a community-based participatory research approach was adopted. To achieve our research goals of investigating the implications of the current water crises for Indigenous sovereignty and self-determination, specific methods of sharing circles were used to gather knowledge from community members, Elders, and knowledge keepers. The research findings strongly highlight the strength and resilience shown by remote Indigenous communities in the face of the current water crises and continuous government failure. Solving the current water crises will involve remote Indigenous communities taking charge of their own water governance through Indigenous-led water governance systems. Additionally, taking steps to rebuild trust through genuine reconciliation will be key. Therefore, listening to remote Indigenous communities and taking collaborative action is fundamental.

Children—Dependents in Social Construction Theory—are assessed within democracies regarding their ability to self-direct their behavior concerning their associated society. In this regard, childhood represents a lack of self-direction, a life period when people require the guidance and protection of adults. The assumed necessity of adults supervising children in democracies requires substantial social resources, reducing the self-direction of those charged with overseeing children. Given that self-direction defines the optimal experience of people within democratic society, finding ways to increase the self-direction of children is an individual and a social benefit. In this regard, smartphones have improved self-direction in children. How children have become empowered to self-direct their lives with smartphone use considering Social Construction Theory—as Advantaged, Contenders, or Deviants—is the focus of a scoping review conducted on “children, empowerment, smartphones” of the following databases: OVID, JSTOR, ProQuest, PubMed, Scopus, and Web of Science. The result is that children permitted to self-direct their activities aided by smartphone technology have comparable social behavior to adults positioned as Advantaged, Contenders, or Deviants and, as such they should be encouraged to utilize smartphone technology to improve their self-direction, as doing so will augment individual and caregiver self-direction, providing increased social benefit.

Wireless Sensor Networks (WSNs) are gaining traction in the realm of network communication, renowned for their adaptability, configuration, and flexibility. The forthcoming network traffic within WSNs can be forecasted through temporal sequence models. In this correspondence, We present a method (TSENet) that can accurately predict the traffic in the cellular network. TSENet is composed of transformers and self-attention network. We have designed a temporal transformer module specifically for extracting temporal features. This module accomplishes this by modeling the traffic flow within each grid of the communication network at both near-term and periodical intervals. Simultaneously, we amalgamate the spacial features of each grid with information from its correlated grids, generating spacial predictions within the spacial transformer. Furthermore, we employ self-attention aggregation to capture dependencies between external factor features and celluar data features. Empirical assessments performed on a genuine cellular traffic dataset offer compelling evidence substantiating the efficacy of TSENet.

For many engineering applications it is sufficient to use the concept of simple materials. However, higher gradients of the kinematic variables are taken into account to model materials with internal length scales as well as to describe localization effects using gradient theories in finite plasticity or fluid mechanics. In many approaches length scale parameter have been introduced that are related to a specific micro structure. An alternative approach is possible, if a thermodynamically consistent framework is used for material modelling as shown in the present contribution. However, even if sophisticated and thermodynamically consistent material models can be established there are still not yet standard experiments to determine higher order material constants. In order to contribute to this ongoing discussion system identification based on the method of self-adaptive filtering is proposed in this paper. To evaluate the effectiveness of this approach it has been applied to second-order gradient materials considering longitudinal vibrations. Based on thermodynamically consistent models that have been solved numerically it has been possible to prove that system identification based on self-adaptive filtering can be used effectively for both narrow-band and broadband signals in the field of second-order gradient materials. It has also been found that the differences identified for simple materials and gradient materials allow for condition monitoring and detection of gradient effects in the material behavior.

Self-esteem, the evaluation of one's own worth or value, is a critical aspect of psychological well-being and mental health. In this paper, we propose an active inference account of self-esteem, casting it as a sociometer, or an inferential capacity to interpret one's standing within a social group. This approach allows us to explore the interaction between an individual's self-perception and the expectations of their social environment.When there's a mismatch between these perceptions and expectations, the individual needs to adjust their actions or update their self-perception to better align with their current experiences. We also consider this hypothesis in relation to recent research on affective inference, suggesting that self-esteem enables the individual to track and respond to this discrepancy through affective states such as anxiety or positive affect. By acting as an inferential sociometer, self-esteem allows individuals to navigate and adapt to their social environment, ultimately impacting their psychological well-being and mental health.

Aging is the results of several complex and multifactorial processes, where several agents contribute to increase intrinsic vulnerability and susceptibility to age-related diseases. The hallmarks of aging are a set of biological mechanisms, finely regulated and strictly interconnected, initiating or contributing to biological changes anticipating several age-related diseases. The complex network of cellular and intercellular connections between the hallmarks might represent a possible target for the research of agents with pleiotropic affects. Vitamin D (VitD) is known to have positive impact not only on muscle and bone health, but also on several extra-skeletal districts, due to the widespread presence of VDRs (VDR). VitD and VDR could be molecules potentially targeting the hallmark of aging network. To date, evidence about the potential effect of VitD on the hallmark of aging is scarce in humans and mainly based on preclinical models. Although underpowered and heterogeneous, in-human studies seems to confirm the modulatory effect of VitD on some hallmarks aging and diseases. However, more investigations are needed to clarify the pleiotropic effects of VitD and its impact on the hallmark of aging, hopefully highlighting the courses for translational applications and potential clinical conclusions.

This study aims to analyse whether Chinese companies' R&D investment affects management innovation performance. Also, this dissertation defines management innovation as diversification strategies such as technology and industry diversification and analyzes the impact of these diversification strategies. In particular, this paper analyzes whether R&D investment leads to technology and industry diversification and whether technology diversification creates a mediating effect in the process of R&D investment leading to industry diversification. The analysis results can be summarized as follows: First, R&D investment showed a significant positive relationship with industry diversification. Second, R&D investment shows a significantly positive relationship with technology diversification. Third, technology and industry diversification showed a positive relationship. Fourth, this study examined the mediating role of technology diversification, and it was confirmed that technology diversification plays a mediating role in the effect of R&D investment on industry diversification. R&D investment and business innovation play a key role in the sustainable development of enterprises, and the findings of this paper have important reference value for enterprises' R&D investment decision-making. The results of this study provide the following implications that Chinese companies improve business innovation performance by increasing their R&D investment, promoting innovative R&D, and improving technology diversification and industry diversification strategies.

To resolve problems in the dietary life of university athletes, education is essential for enabling athletes to change their own dietary behavior. The purpose of this research, it was decided to verify the effectiveness of sports nutrition education based on self-determination theory (SDT). Methods, the subjects were thirty-six male university rowers. A stratified randomized comparison test was conducted by student year (SDT group and control group). Sports nutrition education was held three times, via an Internet conferencing system. Furthermore, group work over social media was used for the SDT group. Four evaluations were carried out based on anthropometric measurements, brief-type self-administered diet history questionnaire (BDHQ),sports nutrition knowledge (SNK), and treatment self-regulation questionnaire (TSRQ). Results, for the intra-group factor "Protein," a significant difference was evident in the self-determination theory group (50.0±28.5, 78.6±28.1, 81.0±21.5, p<0.000, units: %), and there were significant differences between after and before, and between three months after and before (p=0.002, p=0.002). For BDHQ, significant differences were evident for green/yellow vegetables, fruits, and dairy between after and before for the self-determination theory group (159.1±74.2-126.7±70.6, p=0.009, 306.0±196.2-195.2±146.1, p=0.020, 257.0±147.0-183.3±167.9, p=0.040, units: g). In conclusion, sports nutrition education based on SDT improved dietary knowledge and increased dietary intake.

This study proposed to use wearable EEG to study the impact of vipassana mindfulness practice on beginner's physiological and neurological responses. Mindfulness meditation has been shown to have numerous benefits, including stress reduction, improved attention and cognitive function, and enhanced emotional regulation. The roots of mindfulness meditation in Buddhism emphasize cultivating present-moment awareness and insight. However, the neural mechanisms together with physiological mechanism and their interaction underlying these benefits remain poorly understood. Method: One middle age man (50 years old) participated in this longitudinal study using wearable EEG to investigate the neurophysiological change during a one-month consecutive vipassana mindfulness practice. Both EEG and heart rate responses were recorded each time, before (5 minutes), during (20 minutes), and after (5 minutes) meditation sessions. The EEG and HR data were analyzed by Matlab and EEGlab to examine changes in brainwave activity and heart rate. Results: alpha peak frequency (APF) is significantly lower after mindfulness meditation, as shown by comparison of APF before mindfulness (pre-5) and during mindfulness practice (med-20), and comparison between APF of pre-5 and after mindfulness practice (post-5). The same is with the beta peak power. While for theta peak frequency, it is significant lower during mindfulness meditation (med-20), when comparing to either pre-5 or post-5. See figure 1a. However, peak power index is not so sensitive, and it is more obvious in theta wave band. That is, the theta power peak is significantly lower after meditation, as can be observed in comparison between pre-5 and med-20, also between pre-5 and med-20. See figure 1b. STATE Heart-mean (bpm) Heart-std(bmp) pre-5 69.88 3.88 med-20 68.36 2.81 post-5 69.55 4.13 t-value test (pre-med) 0.0694 0.0003 t-value test (pre-post) 0.7934 0.3656 t-value test (post-med) 0.3193 0.0001 Table 1. The difference of Heart rate (mean and SD) in before (pre-5), during (med-20) and after (post-5)mindfulness meditation. We find significant change in standard deviation (SD) of heart rate between meditation and non-meditation mental states, as shown in table 1. The study provides insights into the underlying neurophysiological mechanisms of mindfulness meditation using wearable EEG devices. It demonstrates that in term of EEG measurement, spectrum frequency can be more sensitive than spectrum power; also heart rate variability as measured by SD is more sensitive to mean of HR. The proposed study contributes to the literature by using wearable EEG devices to collect data in a more accessible and convenient manner.

Transformer models have emerged as frontrunners in the field of natural language processing, primarily due to their adept use of self-attention mechanisms to grasp the semantic linkages between words in sequences. Despite their strengths, these models often face challenges in single-task learning scenarios, particularly when it comes to delivering top-notch performance and crafting strong latent feature representations. This challenge is more pronounced in the context of smaller datasets and is particularly acute for under-resourced languages such as Arabic. In light of these challenges, this study introduces a novel methodology for text classification of Arabic texts. This method harnesses the newly developed Reverse Positional Encoding (RPE) technique. It adopts inductive-transfer learning (ITL) framework combined with a switching self-attention shared encoder, thereby increasing the model's adaptability and improving its sentence representation accuracy. The integration of Mixture of Experts (MoE) and Reverse Positional Encoding (RPE) techniques empowers the model to process longer sequences more effectively. This enhancement is notably beneficial for Arabic text classification, adeptly supporting both the intricate five-point and the simpler ternary classification tasks. The empirical evidence points to its outstanding performance, achieving accuracy rates of 87.20% for the HARD dataset, 72.17% for the BRAD dataset, and 86.89% for the LABR dataset, as evidenced by the assessments conducted on these datasets.

Artificial intelligence and Quantum science supports path-breaking technologies for main technological change. The investigation goal of this study is to examine their scientific and technological development to explain drivers of these disruptive technologies. Analyses of data, based on publications and patents in quantum science and artificial intelligence, with a technometric model show that that quantum science and technology has a growth rate of 1.07, artificial Intelligence ha a rate of growth of 1.37, whereas the interaction of quantum science and artificial intelligence generates a convergent technological trajectory that has an accelerated rate of growth of 1.58, higher than trends of these technologies taken individually. These findings here clarify one of the fundamental determinants of the evolution of path-breaking technologies that can support decision making of policymakers, technology analysts and R&amp;D managers to direct R&amp;D investments towards fruitful inter-relationships between radical technologies that foster scientific and technological change in knowledge economies.

The capacitor-mismatch among diverse defects caused by the manufacturing process variations significantly affects the linearity of capacitor-array used to implement the capacitive digital-to-analog converter (CDAC) in the successive-approximation-register (SAR) analog-to-digital converter (ADC). Accordingly, the linearity of the SAR ADC is limited by that of capacitor-array, resulting in serious yield loss. This paper proposes an efficient foreground self-calibration technique to enhance the linearity of the SAR ADCs by mitigating the capacitor-mismatch based on the split ADC architecture along with variable capacitors. In this work, two ADC channels (i.e., ADC1 and ADC2) for the split ADC architecture include their capacitive DACs (CDACs) whose binary-weighted capacitor-arrays consist of variable capacitors. A charge-sharing SAR ADC is used for each ADC channel. In the normal operation mode, their digital outputs are averaged to be the final ADC output, as in a conventional split ADC. In the calibration mode, every single binary-weighted capacitor for the two ADCs is sequentially calibrated by making parallel or/and antiparallel connection among two or thee capacitors from the two channels. For instance, because the capacitors of the CDACs ideally exhibit the binary-weighted relation as Cn=2×Cn−1, variable capacitor Cn of ADC1 can be updated to be closest to the sum of Cn−1 of ADC1 and Cn−1 of ADC2 for the calibration. For the process, the two capacitor-arrays of the two ADCs can be reconfigured to be connected to each other, so that Cn of ADC1 can be connected with two of Cn−1 of ADC1 and ADC2 in antiparallel. The two voltages at the top and the bottom plates of the CDAC are compared by a comparator of ADC1, and the comparison results are used to update Cn. This process is iterated, until Cn is in agreement with the sum of two of Cn−1. Finally, all the capacitors can be calibrated in this way to have the binary-weighted relation. The simulation results based on the proposed work with a split SAR ADC model verified that the proposed technique can be practically used, by showing that the total-harmonic-distortion and the signal-to-noise-and-distortion ratio were enhanced by 21.8-dB and 6.4-dB, respectively.

In order to improve real-time performance of gesture recognition by micro-Doppler map of mmWave Radar, the point cloud based gesture recognition for mmWave Radar is proposed in this paper.Two steps are carried out for mmWave Radar based gesture recognition. The first step is to estimate the point cloud of the gestures by 3D-FFT and the peak grouping. The second step is to train the TRANS-CNN model by combining the multi-head self-attention and the 1D-convolutional network, so as to extract the features in the point cloud data at a deeper level to categorize the gestures. In the experiments, TI mmWave Radar sensor IWR1642 is used as benchmark to evaluate the feasibility of the proposed approach. The results show that the accuracy of the gesture recognition reaches 98.5%. In order to prove the effectiveness of our approach, a simply 2Tx2Rx Radar sensor is developed in our lab and the accuracy of recognition reaches 97.1%. The results show that our proposed gesture recognition approach achieves the best performance in real-time with limited training data, in comparison with the existing methods.

Numerous elements, such as the composition and characteristics of carbon nanomaterials, the composition and characteristics of the matrix material, moisture levels, temperature, and loading circumstances, influence the piezoresistive behaviour of self-sensing cementitious composites. While some past research has explored the impact of some of these factors on the performance of self-sensing cementitious composites, additional investigations need to be conducted to delve into how loading conditions affect the sensitivity of self-sensing cement-stabilized composites. Therefore, this study explores the influences of various loading conditions (i.e., location of loading regarding the location of recording electrodes, and loading level) on the electromechanical performance of self-sensing cement-stabilized sand. To this end, firstly, the evaluation of the percolation threshold based on 10% cement-stabilized sand specimens containing various multiwall carbon nanotubes (MWCNTs) and graphene nanoplatelets (GNPs) was performed. Then, 10% cement-stabilized sand containing 4% MWCNTs/GNPs was tested under various cyclic compressive stresses. The results suggested that the distance between the loading area and the electrode location used for recording the electrical resistance significantly impacts the sensitivity of cement-stabilized sand. Optimal sensitivity was achieved when the electrodes were positioned directly beneath the loading area. Moreover, the study yielded that the stress sensitivity of self-sensing cement-stabilized sand increases proportionally with the stress level. Examination through scanning electron microscopy (SEM) demonstrated that the loading condition influences the bridging characteristics of carbon nanomaterials in cement-stabilized sand, leading to diverse electromechanical behaviors based on the loading condition. This study underscores the importance of considering specific parameters when designing the application of self-sensing cement-stabilized sand for practical field use.

Qualtra, an innovative 10 MW geothermal power plant proposal, employs a closed-loop design to mitigate emissions, ensuring no direct release into the atmosphere. A thorough assessment utilizing energy and exergy analysis, Life Cycle Assessment (LCA), Exergo-economic and Exergo Environmental Analysis (EevA) was conducted. The LCA results, utilizing the ReCiPe 2016 midpoint methodology, encompass all the spectrum of environmental indicators provided. The technology implemented makes it possible to totally avoid direct atmospheric emissions from the Qualtra plant, so the environmental impact is mainly due to indirect emissions over the life cycle. The results obtained for the Global Warming Potential indicator is about 6.6 g CO2/kWh, notably lower compared to other conventional systems. Contribution analysis reveals that the construction phase dominates, accounting for over 90% of the impact in all LCA MidPoint categories. At the component level, a single score calculation incorporating normalization and weighting was executed. The resulting single score is then used into Exergo-Environmental Analysis (EEvA), highlighting the well system as the most impactful contributor, constituting approximately 45% of the total impact. Other substantial contributions to the environmental impact include the condenser (21%), the turbine (17%), and the HEGeo (14%). The Exergo-Economic analysis assesses cost distribution across major plant components, projecting an electricity cost of about 8.3 c€/kWh.

Côte d’Ivoire has substantially neglected crop residues from farms in rural areas. This study aims to provide strategies for the sustainable conversion of crop residues to hydrogen. Using existing data and theoretical approaches, up to 16,801,306 tons of crop residues of 11 crop types were available in Côte d’Ivoire in 2019. A theoretical hydrogen potential of 1,296,424.84 tons was estimated from the crop residues. Technically, 907,497.39 tons of hydrogen is expected annually. Three scenarios of hydrogen project implementation developed indicated that the Ivorian industries can be supplied with 9,026,635 gigajoules of heat. Moreover, 17,910 cars and 4,732 buses can be supported in the transport sector. It is estimated that 817,293.95 tons of green ammonia for farmers can be supplied. Five million, seven hundred twenty-seven thousand, nine hundred ninety-two (5,727,992) households are expected to have access to 1,718.40 gigawatts of electricity. Due to these changes in transport, energy, industry, and agricultural sectors, a reduction of 1,644,722.08 tons of carbon dioxide per year can be achieved theoretically. With the scenarios, some 263,276.87 tons of hydrogen are exportable to other countries. Conversion of crop residues to hydrogen is a promising opportunity with environmental and socio-economic impact. Therefore, this study requires further extensive research.

Background: Breast cancer remains a significant health concern among women globally. Despite advancements in awareness and diagnostic techniques, it persists as a leading cause of death, with profound impacts on affected individuals' quality of life. Primary and secondary prevention, including regular screenings and practices like Breast Self-Examination (BSE), are pivotal in ensuring early diagnosis. The NHS in Italy offers screenings for women aged 50-69 every two years, managed by the Local Health Authority. However, the participation rates, especially among the Chinese female population residing in Italy, are not well-understood. Methods: Using a snowball method, we electronically disseminated a survey to investigate how Chinese women living in Italy engage with available NHS screening programs. The survey also explores their practice of BSE, the use and impact of technological tools on prevention, and aims to understand their depth of knowledge and misconceptions about breast cancer. Results: The data revealed a significant gap in breast cancer screening adherence and knowledge among Chinese women in Italy, with a notable discrepancy between the general population and those who have previously encountered cancer. Conclusions: The results highlight the urgent need for interventions that are culturally sensitive, stressing that these actions are not only desirable but essential.

(1) Background: Mindfulness-based interventions (MBIs) have shown interesting preliminary ef-fects over self-regulation processes in early adolescence. However, interventions usually integrate various types of practices with no clarity about the specific effect of each of them over attentional, emotional, and behavioral regulation. The objective of this research was to evaluate the effect of two MBIs, one focused on classic attentional practices and another one focused on the recognition and expression of emotions, over attentional, emotional, and behavioral self-regulation in early adolescents. (2) Method: An experimental method was carried out. A sample of 70 children be-tween 8 and 12 years old were randomized and assigned to three experimental conditions: 1) MBI with a focus on attentional practices, 2) MBI with a focus on recognition and expression of emotions, 3) control group, waiting list. The programs lasted 8 weeks, with a weekly 1-hour online synchronic session, plus home practices. Children were evaluated before starting the in-tervention and at the end of the 8-week program. The assessed variables were: 1) Mindfulness; 2) Emotional Regulation; 3) Attentional Regulation and 4) Behavioral regulation. (3) Results: Chil-dren that participated in both programs, increased their mindfulness and emotional and be-havioral regulation scores. Only children who participated in the program with a focus on at-tention showed significant changes in their ability to self-regulate attention. (4) Conclusions: online MBIs, with attention to external and internal stimuli practices, can be a good strategy to strengthen self-regulation skills of attention, emotions, and behavior in early adolescence.

Most of the educational interventions proposed so far in the field of mental well-being in education ‎usually address just students. In this study, we focused on teachers as the Covid-19 pandemic reiterated ‎the importance of their mental well-being during demanding times. We investigated whether ‎neurofeedback (NF) training can increase optimism, self-esteem, life satisfaction, and the ability to ‎cope with stressful events, reflecting on the research literature that emphasizes these four factors, ‎which affect the ability to be confident in dealing with uncertainty and distress. ‎ Forty teachers aged 35-55 participated in the study. The test group took part in 12 NF training sessions, ‎and the control group was not treated. Our findings indicate that compared to the control group, ‎measures of optimism, self-esteem, life satisfaction, and coping with stressful events improved ‎significantly in the test group.‎ To the best of our knowledge, this is the first attempt to test a mental welfare intervention program for ‎teachers through NF. This study responded to a call to develop teacher intervention programs using ‎physiological measurement and technological innovations to improve their mental health and allow ‎them to cope better with stressful teaching conditions.

Chipman contends, in stark contrast to the conventional view, that utility is not a real number but a vector and is inherently lexicographic in nature. According to these views, it will be proved that, for every preordered topological space (X,≾,t), the assumption t to be finer than the order topology t≾ on (X,t), i.e. t⊇t≾, and the assumption the quotient topology t∣∼≾ that is defined on the preordered set (X∣∼,≾∣∼) of indifference classes of ≾ to be Hausdorff imply that a cardinal number κ and a (complete) preorder ≲ on {0,1}κ that is coarser than the lexicographical ordering ≤lex on {0,1}κ, i.e. ≤lex⊂≲, can be chosen in such a way that there exists a continuous order-embedding ϑ:(X,≾,t)⟶({0,1}κ,≲,t≤lex). This theorem will be compared with a theorem that, in particular, describes necessary and sufficient conditions for ≾ to have a continuous multi-utility representation.

Human RAD51 protein (HsRad51)-promoted DNA strand exchange, a crucial step in homologous recombination, is regulated by proteins and calcium ions. The activator protein Swi5-Sfr1 and Ca2+ ions stimulate different reaction steps and induce a perpendicular orientation of DNA bases in the presynaptic complex. To investigate the importance of base orientation in the strand exchange reaction, we examined the Ca2+ concentration dependence of strand exchange activities and structural changes in the presynaptic complex. Our results show that optimal D-loop formation (strand exchange with closed circular DNA) requires Ca2+ concentrations greater than 5 mM, while 1 mM is sufficient for strand exchange between two oligonucleotides. The structural change, which is evidenced by an increase in fluorescence intensity of poly(dεA) (a poly(dA) analog), reaches a plateau at 1 mM Ca2+. Meanwhile, the linear dichroism signal intensity at 260 nm, which is indicative of rigid perpendicular DNA base orientation, requires >2 mM Ca2+ for saturation and thus correlates with the stimulation of D-loop formation. Therefore, Ca2+ exerts two different effects. Thermal stability measurements suggest that HsRad51 binds two Ca2+ ions with KD values of 0.3 mM and 2.5 mM, implying that one step is stimulated by one Ca2+ bond and the other by two Ca2+ bonds. We further discuss the parallels between Mg2+ activation of RecA and Ca2+ activation of HsRad51.

In the current work, the stable queueuing system's Generalised Z-Entropy (GZE) of Rényian formalism is examined in its fractal dimension. Notably, fractal dimension’s resulting behaviour that corresponds to the GZE parameters is examined through numerical tests. This research makes a substantial generalization in the literature by fusing fractal geometry and information theory to shed light on how entropy and complexity interact. More fundamentally, the significant role of fractal dimension to advance Big Data Analytics(BDAs) is highlighted. Closing remarks combined with open problems and the next phase of research are provided.

My innovative entropy measure, Ismail entropy, namely, (IE) is an ultimate generalization to numerous generalized entropies within the literature. The fractal dimension of IE is identified in this paper. On another applicative note, this paper offers some potential applications of fractal dimension to smart cities. The paper ends with closing remarks combined with some challenging open problems and the next phase of research.

Spiritual security should be a priority in our modern globalized society. Therefore, the study provides convincing evidence that it is important to develop a theoretical understanding of spiritual security. Several theoretical concerns regarding the establishment and maintenance of spiritual security are addressed in the article. He explores many ideas that are interrelated, including spiritual security, worldview, and spirituality. To ensure spiritual security, a practical analysis is carried out of the need to carry out various measures that strengthen the spiritual health of society.The article explains the methodology used in spiritual Security Investigations. According to the author, different levels of spiritual security can be analyzed using a structural-logical model and a dialectical method of cognition. Comparative analysis is also seen as a valuable tool. Spiritual intelligence is essential to overcome barriers, manage change, and ensure personal security and its impact on relationships. The process begins with introspection and evaluation, concluding with the ability to assess and understand the environment. By analyzing and understanding natural phenomena, it is possible to develop a sense of reality and a deeper appreciation of the nature of human existence. A person can feel spiritually safe if he adheres to his moral and spiritual beliefs and complies with the norms of society. It contains such things as worldview, social behavior, culture, research and social development. By expanding the spiritual point of view, the danger to the spiritual security of a person can be reduced.

This paper introduces an innovative nanotechnology-based approach that provides a pathway to enhance the energy release efficiency of nanoenergetic materials (nEMs) by harnessing self-synchronized collective atomic vibrations and phonon wave resonance within the transition domains between nanocomponents, without altering the material composition. The key innovation involves incorporating finely-tuned 2D-ordered linear-chain carbon-based multilayer nano-enhanced interfaces as programmable nanodevices into the transition domains using advanced multistage processing and assembly techniques. These programmable nanodevices enable precise control over self-synchronized collective atomic vibrations and phonon wave propagation, leading to synergistic effects. To activate and optimize these effects, a combination of various methods is employed, including energy-driven initiation of allotropic phase transformations, surface acoustic wave-assisted micro/nano-manipulation, heteroatom doping, directed self-assembly using high-frequency electromagnetic fields, and data-driven inverse design approaches. By leveraging a data-driven inverse design strategy and uncovering hidden structure-property relationships, we maximize energy release efficiency using the carbon nano-materials genome approach derived from multifactorial neural network-based predictive models. This approach not only unlocks new functionalities in nEMs but also improves environmental performance and safety levels. By pioneering transformative pathways for nEMs through harnessing phonon wave resonance in low-dimensional nanocarbon transition interfaces, this research brings significant advancements in the field.

Homochirality is an obvious feature of life on Earth. On the other hand, extraterrestrial samples contain largely racemic compounds. The same is true for any common organic synthesis. Therefore, it has been a perplexing puzzle for decades how these racemates could have formed enantiomerically enriched fractions as a basis for the origin of homochiral life forms. Numerous hypotheses have been put forward as to how preferentially homochiral molecules could have formed and accumulated on Earth. In this article, it is shown that homochirality of the abiotic organic pool at the time of formation of the first self-replicating molecules is not necessary and not even probable. It is proposed to abandon the notion of a molecular ensemble and to focus on the level of individual molecules. Although the formation of the first self-replicating, most likely homochiral molecule is a seemingly improbable event, on a closer look, it is almost inevitable that homochiral molecules have formed simply on a statistical basis. In this case, the non-selective leap to homochirality would be one of the first steps in chemical evolution directly out of a racemic “ocean”. Moreover, most studies focus on the chirality of the primordial monomers with respect to an asymmetric carbon atom. However, any polymer with a minimal size that allows folding to a secondary structure, would spontaneously lead to asymmetric higher structures (conformations). Most of the functions of these polymers would be influenced by this inherently asymmetric folding. To summarize, simple and universal mechanisms may have led to homochiral self-replicating systems in the context of chemical evolution. A homochiral monomer pool is deemed unnecessary and probably never existed on primordial Earth.

Vitamin D has important anti-inflammatory, anti-microbial properties and plays a central role in host immune response. Due to the crucial role of the kidneys in the metabolism of vitamin D, patients with chronic kidney disease (CKD), are prone to vitamin D deficiency. The resultant reduction in the production of calcitriol, the activated form of vitamin D in patients with CKD is responsible for exacerbating the existing renal impairment and periodontal inflammation. Recent evidence suggests a bidirectional, causal relationship between periodontitis and renal functional status. Both conditions have shared pathophysiologic mechanisms including oxidative stress, increases in the systemic inflammatory burden and impaired host response. This review explores the association between vitamin D, CKD and periodontitis. The review summarises the current evidence base for the classical and non-classical vitamin D metabolic pathways, the biological mechanisms linking vitamin D deficiency, CKD and periodontitis, as well as the bidirectional relationship between the two chronic inflammatory conditions. Finally, the paper explores the impact of vitamin D deficiency on CKD, periodontitis, and related co-morbidities.

The demand for precise indoor localization services is steadily increasing. Among various methods, fingerprint-based indoor localization has become a popular choice due to its exceptional accuracy, cost-effectiveness, and ease of implementation. However, its performance degrades significantly as a result of multipath signal attenuation and environmental changes. In this paper, we propose an indoor localization method based on fingerprints using self-attention and long short-term memory (LSTM). By integrating a self-attention mechanism and LSTM network, the proposed method exhibits outstanding positioning accuracy and robustness in diverse experimental environments. The performance of the proposed method is evaluated under two different experimental scenarios, which involve 2D and 3D moving trajectories, respectively. The experimental results demonstrate that our approach achieves an average localization error of 1.76 m and 2.83 m in the respective scenarios, outperforming the existing state-of-the-art methods by 42.67% and 31.64%.

With the development of artificial intelligence, the ability of capturing the background characteristics of hyperspectral imagery (HSI) is improved and promising performance in hyperspectral anomaly detection (HAD) tasks is yielded. However, existing methods proposed in recent years still suffer from certain limitations: 1) constraints are lacking in the deep feature learning process in terms of the issue for absence of prior background and anomaly information. 2) hyperspectral anomaly detectors with traditional self-supervised deep learning methods fail to ensure prioritized reconstruction of the background. 3) architectures of fully connected deep network in hyperspectral anomaly detectors lead to low utilization of spatial information and destruction for original spatial relationship of hyperspectral imagery, and disregard spectral correlation between adjacent pixels. 4) hypotheses or assumptions for background and anomaly distributions restrict the performance of many hyperspectral anomaly detectors because the distributions of background land covers are usually complex and not assumable in real-world hyperspectral imagery. With the consideration of above problems, in this paper, we propose a novel fully convolutional auto-encoder based on dual clustering and latent feature adversarial consistency (FCAE-DCAC) for HAD which is carried out in a self-supervised learning-based processing. Firstly, the density-based spatial clustering of applications with noise algorithm and connected component analysis are utilized for successive spectral and spatial clustering to obtain more precise prior background and anomaly information, which facilitates the separation between background and anomaly samples during the training of our method. Subsequently, a novel fully convolutional auto-encoder (FCAE) integrated with spatial-spectral joint attention (SSJA) is proposed to enhance the utilization of spatial information and augment feature expression. In addition, a latent feature adversarial consistency network is proposed to achieve pure background reconstruction with the ability of learning actual background distribution in hyperspectral imagery. Finally, a triplet loss is introduced to enhance the separability between background and anomaly, and the reconstruction residual serves as the anomaly detection result. We evaluate the proposed method on seven groups of real-world hyperspectral datasets, and the experimental results confirmed the effectiveness and superior performance of the proposed method versus nine state-of-the-art methods.

Organic light-emitting diodes (OLEDs) have garnered considerable attention in academic and industrial circles due to their potential applications in flat panel displays and solid-state lighting technologies, leveraging the advantages offered by organic electroactive derivatives over their inorganic counterparts. The thin and flexible design of OLEDs enables the development of innovative lighting solutions, facilitating the creation of customizable and contoured lighting panels. Among the diverse electroactive components employed in the molecular design of OLED materials, the benzophenone core has attracted much attention as fragment for synthesis of organic semiconductors. On the other hand, the benzophenone also functions as a classical phosphor with high intersystem crossing efficiency. This characteristic makes it as compelling candidate for effective reverse intersystem crossing, potentially leading to the development of thermally activated delayed fluorescent (TADF) emitters. These emitting materials witnessed a pronounced interest in recent years due to their incorporation in metal-free electroactive frameworks and the capability to convert triplet excitons into emissive singlet excitons through reverse intersystem crossing (RISC), consequently achieving exceptionally high external quantum efficiencies (EQEs). This review article comprehensively overviews the synthetic pathways, thermal characteristics, electrochemical behaviour and photo-physical properties of the derivatives based on benzophenone. Furthermore, we explore their applications in OLED devices, both as host materials and emitters, shedding light on the promising opportunities that benzophenone-based compounds present in advancing OLED technology.

Аннотация . Периодически развиваются самоподобные движения структурно-вещественных комплексов (СМК) из состава Солнечной системы в течение периода около 4,5 миллиардов лет земной коры, развития Земли в условиях самоорганизации. Синхронные или близкие во времени ряды генетических или парагенетических групп магматических, рудно-минеральных, метасоматических, осадочных образований, их структур и других сопутствующих им процессов, включают в себя каждый комплекс (ГМК). Каждый комплекс в его пределах ограничен во времени и пространстве, по причине признаков самопроизвольного динамического процесса; распространяется на территорию Земли в текущий исторический период; формирует состав и структуру земной коры на этом этапе, определяя ее полициклическое развитие. Количество циклов около 14,

This article delves into the complex tension between national self-rule and international involvement, in the context of global politics, examining the inherent challenges of upholding both principles when confronted with human rights abuses and the pursuit of global peace. The introduction presents the fundamental dilemma: self-governance versus moral obligations. The problem statement calls for a nuanced approach to address the intricate complexities of sovereignty and intervention, acknowledging the potential misuse by oppressive regimes and the ongoing challenges of determining when and how intervention is warranted. The article advocates for a more responsible and effective approach to global conflicts and human rights violations, balancing national sovereignty with judicious intervention when required. The methodology employs both literature review and case analysis to construct a framework for objectively assessing when international intervention is justified in instances of human rights abuses. The conclusion stresses the criticality of objective intervention criteria, transcending cultural, political, and economic biases, and advocates for a globally accepted approach that celebrates diversity while promoting global stability.

Brain-stimulation reward, also known as intracranial self-stimulation (ICSS), is a commonly used procedure for studying brain reward function and drug reward. In electrical ICSS, an electrode is surgically implanted into the medial forebrain bundle in the lateral hypothalamus or the ventral tegmental area in the midbrain. Operant lever responding leads to the delivery of electrical pulse stimulation. The alteration in the stimulation frequency-lever response curve is used to evaluate the impact of pharmacological agents on brain reward function. If a test drug induces a leftward or upward shift in the ICSS response curve, it implies a reward-enhancing or abuse-like effect. Conversely, if a drug causes a rightward or downward shift in the functional response curve, it suggests a reward-attenuating or aversive effect. A significant drawback of electrical ICSS is the lack of cellular selectivity in understanding the neural substrates underlying drug reward versus aversion. Excitingly, recent advancements in optical ICSS (oICSS) have facilitated the development of at least three cell type-specific oICSS models – dopamine-, glutamate-, and GABA-dependent oICSS. In these new models, a comparable frequency-rate response curve has been established and employed to study the substrate-specific mechanisms underlying brain reward function and a drug's rewarding versus aversive effects. In this review article, we summarize recent progress in this exciting research area. The findings in these new behavioral models have not only increased our understanding of the neural mechanisms underlying drug reward and addiction but have also introduced a novel experimental approach in preclinical medication development for treating substance use disorders.

We introduce a novel method for fabricating perovskite solar modules using selective spin-coating on various Au/ITO patterned substrates. These patterns were engineered for twofold purposes: (1) to enhance selectivity of monolayers primarily self-assembling on the Au electrode, and (2) to enable seamless interconnection between cells through direct contact of the top electrode and the hydrophobic Au connection electrode. Utilizing SAMs-treated Au/ITO, we achieved sequential selective deposition of the electron transport layer (ETL) and the perovskite layer on the hydrophilic amino-terminated ITO, while the hole transport layer (HTL) was deposited on the hydrophobic CH3-terminated Au connection electrodes. Importantly, our approach had negligible impact on the series resistance of the solar cells, as evidenced by the measured specific contact resistivity of the multilayers. A significant outcome was the production of a 6-cell series-connected solar module with a notable average PCE of 8.32%, providing a viable alternative to the conventional laser scribing technique.

In recent decades, considerable attention has been focused on the design and development of surfaces with defined or tunable properties for a wide range of applications and fields. To this end, self-assembled monolayers (SAMs) of organic compounds offer a unique and straightforward route of modifying and engineering the surface properties of any substrate. Thus, alkane-based self-assembled monolayers constitute one of the most extensively studied organic thin-film nanomaterials, which have found wide application in antifouling surfaces, control of wettability or cell adhesion, sensors, optical devices, corrosion protection, organic electronics, among many other applications. Some of which have led technological transfer to industry. Nevertheless, recently, aromatic-based SAMs have gained in importance as functional components, particularly in molecular electronics, bioelectronics, sensors, etc., due to their intrinsic electrical conductivity and optical properties, opening up new perspectives in these fields. However, some key issues affecting device performances still need to be lifted off to ensure their full use and access to novel functionalities such as memories, sensors, or active layers in optoelectronic devices. In this context, we will present herein recent advances of p-conjugated systems-based self-assembled monolayers (e.g., push-pull chromophores) as active layer and their applications.

Walnut (Juglans regia L.) is a monoecious species and although it exhibits self-compatibility, presents incomplete overlap of pollen shed and female receptivity. Thus, cross-pollination is prerequisite for optimal fruit production. Cross-pollination can occur naturally by the wind, the insects, artificially, or by hand. Pollen has been recognized as one possible pathway for Xanthomonas arboricola pv. juglandis infection, a pathogenic bacterium responsible for walnut blight disease. Other than the well-known cultural and chemical control practices, artificial pollination technologies with the use of drones could be a successful tool for walnut blight disease management of orchards. Drones may carry pollen and release it over crops or mimic the action of bees or other pollinators. Although this new pollination technology could be regarded as a promising tool, pollen germination and knowledge of pollen as a possible pathway for the dissemination of bacterial diseases remain crucial information for design and manufacture of aerial pollinator robot for walnut trees. Thus, our purpose was to describe a pollination model with fundamental components, the identification of the “core” pollen microbiota, specify an appropriate flower pollination algorithm, design an autonomous precision pollination robot, and minimize the average errors of flower pollination algorithm parameters through machine learning and meta-heuristic algorithms.

This paper offers a novel geometric and visual approach to the renowned Four Color Map Theorem and K5 non-planarity problem while unveiling their profound connection to the "kissing number" problem in 2D. We represent planar graphs through circles and tangents, simplifying complex structures and shedding light on these classic problems. Our proofs by contradiction, rooted in the kissing number concept, reveal that both the Four Color Map Theorem and K5 non-planarity are fundamentally linked, as they pivot around the concept of coloring. This study bridges the realms of geometry and graph theory, providing fresh insights and emphasizing the significance of the kissing number problem in various fields.

The aim of the study was to examine the influence of different irrigation protocols on the shear bond strength (SBS) of self-adhesive resin composite cement (SARC) to primed radicular dentin. Radicular dentin slabs (N=58) were sectioned from extracted intact third molars, embedded in acrylate, polished, and randomly assigned to five experimental groups (N=8-12) and one control group, CG (N=8). Irrigation solutions used were sodium hypochlorite (H), ethylene-diamine-tetra acetic acid (EDTA), etidronic acid with hypochlorite (HEDP), saline solution (SS), and chlorhexi-dine (CHX). Each experimental group underwent different irrigation protocol for two minutes: 1) H/EDTA/H, 2) HEDP, 3) H/EDTA/CHX, 4)H/EDTA/SS, and 5) HEDP/SS. The CG samples were not treated with any irrigation solution. After drying, adhesive enhancing primer (AEP) and du-al-curing SARC were applied to the radicular dentin using molds corresponding to the Ultra Tester. Specimens were stored at 37°C in distilled water and fractured in shear mode after 10 days. The results were analyzed using the ANOVA statistical test and Post-hoc Games-Howell test, α=0.05. CG exhibited the highest SBS. Except for HEDP and HEDP/SS, all experimental groups showed significantly lower SBS compared to the control group (p< 0.05). HEDP seems to be ad-equate solution for root canal cleaning before dentin priming and fiber post cementation with self-adhesive resin cement. Cleaning protocols with H, EDTA and CHX cause a significant de-crease in bond strength.

This study investigated whether reciprocal collaborative pedagogy significantly impacts Indonesian electrical engineering polytechnic students in reducing reading anxiety and improving self-efficacy in ESP reading comprehension skills. Fifty Polytechnic students were equally assigned to two groups. Control groups learned in the traditional reciprocal teaching method individually. Experimental group engaged in reciprocal collaborative pedagogy. Each group received a 6-week reading strategy training. E-learning platforms were used in this study as a complementary tool to distribute ESP reading materials, announcements, and the experiment details being taught. The quantitative and qualitative results demonstrated that the tasks in reciprocal collaborative pedagogy positively affects Indonesian electrical engineering polytechnic students' learning experience and outcomes. This pedagogy promotes a productive learning environment through peer interaction, active engagement, and peer group discussions of the whole learning activities, reducing feelings of anxiety and building confidence in ESP-specialized text.

This paper delves into the critical issue of concrete cracks, a common consequence of environmental factors and external forces, and their potential impact on the structural integrity of buildings. Recognizing the urgency of addressing this issue, the concept of self-healing concrete has emerged, aiming to revolutionize the construction industry by autonomously repairing cracks and minimizing the need for labor-intensive and time-consuming manual interventions. The paper employs a bibliographic analysis methodology to comprehensively explore the most significant technologies associated with self-healing concrete, identifying key research countries/regions and prominent research institutions in this field. Through an examination of scholarly articles, the analysis seeks to uncover key themes, technologies, and contributors within the self-healing concrete domain. Insights into the geographical distribution of research efforts and the roles of influential research institutions are provided, shedding light on collaborative networks and knowledge-sharing dynamics that drive innovation in this evolving field.

Cassava mosaic disease (CMD) and cassava brown streak disease (CBSD) are endemic threats to cassava production. To fill the existing gaps in the understanding of the epidemiology of these diseases in Côte d’Ivoire, nationwide field surveys were conducted in 2016, 2017 and 2020. The leaf samples collected were analysed by PCR. CBSD was not detected in all fields visited. However, an increase of CMD incidence was observed from 45.95% in 2016 to 51.37% in 2020 while CMD severity remained moderate over the years with a mean value of 2.29. Low whiteflies number was observed in field and decreasing over the years. Molecular analysis allowed detection of East African cassava mosaic Cameroon virus (EACMCMV) in single as well as in mixed infection with African cassava mosaic virus (ACMV). Single EACMCMV infection, which was detected only in three agroecological zones of the eastern Côte d’Ivoire in 2016, spread throughout the country in 2017 and became more widespread in 2020 with a preponderance in the central and southern zones, whereas the ACMV+EACMCMV coinfection has spread to the entire zones studied. Knowing the dynamics of the evolution of these viruses across the country, better disease management strategies could be adopted to control the disease.

It has been more than a century since Erlang published his paper in 1909. The classical queueing system for the M/D/c queue has been investigated by many authors. The key is to find the roots of an equation using explicit or numerical methods. We present an alternate form of explicit solution(s) of this/these root(s) using the Lambert-W function in this paper. In addition, the unsaturated probabilities of the number of customers in the system is derived explicitly in terms of this/these root(s). Finally, the mean number of customers in the system and the mean queueing delay are obtained from these probabilities. The exact queueing delay formula for the M/D/c queue is expressed in closed-form in terms of the root(s). Numerical results show that they are in excellent agreement with the numerical results published by Seelen, Tijms and Van Hoorn.

The feeling of emotional self-efficacy helps people understand how to handle positive and negative emotions. Emotion regulation indicates the process that helps modulate emotions, to adapt suitably to the demands of the environment. This study has a two-fold aim. Firstly, it analyses the relationships among emotion regulation; the personality traits of extraversion and emotional stability; and the feeling of efficacy of positive and negative emotions in an adolescent population. Secondly, it analyses the mediating role of personality traits (extraversion and emotional stability) in the relationship between emotion regulation and self-efficacy for positive and negative emotions. There were 703 adolescents who took part (49.9% male and 50.1% female) aged between 15 and 18 years (M=15.86, TD=0.30). The results observe the significant relationships among emotion regulation; the personality traits of extraversion and emotional stability; and self-efficacy for positive and negative emotions. The structural equation model confirms that the link between emotion regulation and self-efficacy is direct and is also mediated by the personality traits of extraversion and emotional stability. The study confirms that emotional self-efficacy beliefs are connected to the emotional regulation strategies used. Effective emotional regulation favours self-perception and emotional coping. There is a discussion about the results, which are connected to previous research.

"Enhancing the Efficiency of Natural Gas Liquid (NGL) Extraction and Fractionation Trains: An Integrated Approach of Simulation Analysis, Advanced Modifications, and Technological Advancements. Through comprehensive research, innovative solutions such as the heat pump aided distillation (HPAD) system and self-heat recuperation technology (SHRT) have been developed to significantly reduce the energy consumption associated with conventional distillation systems. To identify a practical system for NGL fractionation trains, this study extensively examined and compared various HPAD and SHRT options to retrofit a single column. The objective was to find the most suitable and efficient solution for the fractionation process of natural gas liquids (NGLs). The retrofit options analyzed in this study encompassed a range of techniques, including vapor compression (VC), mechanical vapor re-compression (MVR), thermal vapor re-compression (TVR), bottom flashing (BF), side heat exchanger (SHE), intermediate heating and cooling (IHC), self-heat recuperative (SHR), and modified self-heat recuperative (MSHR) distillation. These methods were carefully examined to determine their suitability and effectiveness in improving the performance of NGL fractionation trains In this study, a depropanizer column, typically employed in conventional NGL plants, was selected as a case study. The simulation software Aspen HYSYS V7.3 was employed to model and analyze eight retrofit designs based on predefined criteria. The simulation data was carefully evaluated to identify the most efficient design for minimizing energy consumption. Among the retrofit options, the mechanical vapor re-compression (MVR) technique demonstrated the most significant energy cost reduction, with a remarkable 68.11 percent improvement compared to the base case conventional column. These findings highlight the potential of MVR as an effective solution for lowering energy costs in NGL fractionation trainsFollowing the MVR retrofit option, the study found that vapor compression (VC) achieved a considerable energy cost reduction of 66.65 percent, closely followed by modified self-heat recuperative (MSHR) at 64.02 percent, bottom flashing (BF) at 62.88 percent, self-heat recuperative (SHR) at 55.85 percent, side heat exchanger (SHE) at 54.23 percent, intermediate heating and cooling (IHC) at 39.54 percent, and thermal vapor re-compression (TVR) also at 39.54 percent. These findings highlight the significant potential for energy savings offered by these retrofit options, with VC being the most popular choice, closely followed by MSHR, BF, SHR, SHE, IHC, and TVR.

Abstract: This review addresses the complexities of type 1 diabetes (T1D)and its associated complications, with a par-ticular focus on diabetic retinopathy (DR). This review outlines the progression from non-proliferative to proliferative diabetic retinopathy and diabetic macular edema, highlighting the role of dysglycemia in the pathogenesis of these conditions. A significant portion of the review is devoted to technological advances in diabetes management, particu-larly the use of Hybrid Closed Loop systems (HCLS) and to the potential of open-source HCLS systems, which could be easily adapted to different patiens’needs using big data analytics and machine learning. Personalized HCLS algorithms that integrate factors such as patient lifestyle, dietary habits, and hormonal variations are highlighted as critical to reducing the incidence of diabetes-related complications and improving patient outcomes.

This article introduces existential wellbeing (EWB) as one of the most ignored but also the most important kind of wellbeing, especially for people who experience life-limiting diseases and need palliative care (Wong & Yu, 2021). This article will not only review the literature regarding the nature and practice of existential wellbeing in palliative care, but also propose a preliminary Existential Wellbeing Scale. EWB is defined as the quality-of-life characterized by living well and dying well in spite of pain, obstacles, and the shadow of death; wellbeing within the context of human suffering can only be fully understood from the perspective of existential positive psychology (EPP), dedicated to the study of sustainable wellbeing based on the foundation of transcending suffering. The basic tenets of EPP are (1) redefining positivity or wellbeing in terms of seeing and being the light in the darkness; (2) focusing on the dialectical process of navigating an adaptive balance; and (3) re-orienting one’s life attitude from egotism to self-transcendence (Wong, 2023a). More specifically, EWB depends on some combination of the following experiences: (1) Prior experience of overcoming adversity; (2) Existential intelligence (Gardner, 2020) in addressing existential concerns; (3) Existential wisdom of the soul (Wong 2022a; Wong, Ho, et al, 2023a) to achieve existential wellbeing and sustainable flourishing; (4) Spiritual wellbeing based on spiritual values such as faith, hope, and love (Wong, 2023); (5) Knowledge of meaning-focused coping (Eisenbeck et al., 2021); and (6) The new paradigm of self-transcendence (Reed & Haugan, 2021; Wong, Arslan et al., 2021; Wong, Ho et al., 2023b) to transcend and transform suffering into wellbeing and triumph.

Background: This study aimed to examine the obesity¬ stress, weight control behavior, and self-control in overweight and obese female university students, and identify the mediating effect of self-control in the relationship between obesity stress and weight control behavior. Methods: This study employed a descriptive correlational design. A total of 109 female university students who were overweight and obese participated in the study. Data were analyzed using descriptive statistics, Pearson's correlation coefficient analysis, and Bootstrapping using Hayes' PROCESS macro for mediation. Results: Significant relationships between obesity stress and weight control behavior (r=0.25, p<0.001), obesity stress and self-control (r=-0.36, p<0.001), and weight control behavior and self-control (r=.26, p<.001) were observed. Self-control showed indirect mediating effect on the relationship between obesity stress and weight control behavior. Conclusion: Therefore, development of programs and strategies for improving self-control is necessary in order to decrease obesity among female university students.

The study focuses on a novel porous TiNi-based material for ophthalmic orbital implants which was produced by self-propagating high-temperature synthesis (SHS) and, after proper surface modification, possesses a specific microstructure of its surface pores, which makes it attractive for biomedical use in implants. After preparation via SHS, the obtained porous TiNi material was etched in acidic environment, to get rid of its surface Ti2Ni secondary-phase particles. This was found to improve the material’s surface morphology, adding micro-roughness to its macro-rough pores. As a result, cell growth tests conducted on the material demonstrated improved cell adhesion and growth kinetics on such a porous material with improved roughness. Finally, the material was tested in vivo as an ophthalmic orbital implant, demonstrating good biocompatibility, good degree of biointegration with surrounding eyeball tissues, and no signs of rejection after as long as 180 days. Thus, the novel porous TiNi-based material shows promise for its use in ophthalmic implantology, for instanse for manufacturing musculoskeletal stumps of the eyeball after evisceration, as it is biocompatible, has a high tissue-implant integration potential and demonstrates reduced risks of exposure and rejection of the implant.

Microvascular self-healing composite materials have significant potential for application and their mechanical properties need in-depth investigation. In this paper, tensile and compressive properties of woven fabric carbon fiber reinforced polymers (CFRP) laminates containing three-dimensional microvascular channels were investigated experimentally. Several detailed finite element (FE) models were established to simulate the mechanical behavior of the laminate and the effectiveness of different models were examined. The damage propagation process of the microvascular laminates and the influence of microvascular parameters were studied by the validated models. The results show that microvascular channels arranged along the thickness direction (z-direction) of the laminates are critical locations under the loads. The channels have minimal effect on the stiffness of the laminates but causing a certain reduction in strength, which varies approximately linearly with the z-direction channel diameter within its common design range of 0.1~1mm. It is necessary to consider the resin-rich region formed around microvascular channels in the warp and weft fiber yarns of the woven fabric composite when establishing the FE model. And the layers in model should be assigned with equivalent unidirectional ply material in order to calculate the mechanical properties of laminates correctly.

Let R be a commutative ring with identity and m, n be positive integers. In this paper, we introduce the class of (m,n)-prime ideals which lies properly between the classes of prime and (m,n)-closed ideals. A proper ideal I of R is called (m,n)-prime if for a,b∈R, a^{m}b∈I implies either aⁿ∈I or b∈I. Several characterizations of this new class with many examples are given. Analougus to primary decomposition, we define the (m,n)-decomposition of ideals and show that every ideal in an n-Noetherian ring has an (m,n)-decomposition. Furthermore, the (m,n)-prime avoidance theorem is proved.

Agriculture is the main driver of depletion resources worldwide, and its duty is to ensure food security within a rapidly increasing demographic and urbanization, so it is important to transition to sustainable production systems. Vertical crops (VCs) can reduce the pressure on conventional agriculture because they save water and nutrients and increase crop yield. Therefore, this study aimed to validate a proposed predictive model (PM) to simulate water and nutrient uptake in vertical crops under greenhouse conditions. Based on the Penman-Monteith equation, PM estimates transpiration, while nutrient uptake was estimated using the Carmassi-Sonneveld submodel. PM was experimentally evaluated for vertically grown lettuce under Mediterranean greenhouse conditions, during spring 2023. The irrigation technique was a closed-loop fertigation circuit. The experimental consisted of testing two densities (50 and 80 plants·m-2), where each unit of the experiment unit was divided into three heights (low, medium, and upper). It performed ANOVA with a value of p &lt; 0.05 and R2 to assess PM performance. The results suggest a high degree of PM, since R2 ranged from 0.7 to 0.9 for the uptake of water and nutrients. Both densities had a yield between 17-20 times higher than conventional lettuce production and significant savings in water, between 85-88%. In this sense, PM has great potential to intelligently manage VC fertigation, saving water and nutrients, which represents an advance towards reaching SDG 6 and SDG 12, within the 2030 Agenda.

Diabetes self-management education helps to improve health outcomes, quality of life and to reduce expenses for diabetic patients. This systematic review aimed to examine the effectiveness of diabetes self-management education used for newly diagnosed patients with type 2 diabetes (T2DM). A review of studies that have researched the use and the impact of health education in newly diabetic patients with T2DM was implemented. A literature search was conducted using the electronic database of Pub MED, Walters Kluwer, Cochrane Library, Elsevier, JSTORE between January 2017 – November 2022. The data on participants and intervention characteristics were extracted by two reviewers independently. We found 789 studies and after selection of PRISMA flow chart we selected 19 studies, including 2512 newly diagnosed adult T2DM. Biomedical results presented the pooled effect of HbA1c -0.64%, FBG -0.32. The evaluation of emotional and social results and behavioral effects has been evaluated respectively in 10 and 9 studies. The education and support of recently diabetic patients help to improve biomedical, psychosocial, and behavioral results. This intervention must be ongoing to maintain healthy behaviors

Tungsten and its alloys are considered as a key component in high temperature environment. Self-passivating W-Si-xY alloys with different Y contents made from the powders milled for different times were prepared by mechanical alloying (MA) and spark plasma sintering (SPS). Their microstructures and oxidation resistance were investigated. It is found that the oxidation resistance of the alloys with low Y contents (0Y and 2Y) made from 20 h-milled powders is worse than that of the alloys made from 4 h-milled powders. It is because the protective WO3/SiO2 composite layer is discontinuous. While the alloys with high Y contents (4Y and 6Y) made from 4 h and 20 h-milled powders show good oxidation resistance. Even, the thickness of the oxide layer of the alloys with 4Y and 6Y made from 20 h-milled powders after oxidation at 1000 ℃ for 2 h is 84.0 μm and 70.7 μm, less than that made from 4 h-milled powders. This is due to the size and distribution of W5Si3, Y2Si2O7 aggregates and W-Y-O melt. The synergistic effects of Y contents and milling time on the microstructures and oxidation resistance of the alloys are revealed.

The perovskite solar cells (PSCs) have been significantly improved by utilizing inorganic hole transporting layer (HTL), such as nickel oxide. Despite the promising properties, there are still limitations due to defects. Recently, research on self-assembled monolayers (SAM) is being actively conducted, which show promise in reducing defects and enhancing device performance. In this study, we successfully engineered a p-i-n perovskite solar cell structure utilizing HC-A1 and HC-A4 molecules. These SAM molecules were found to enhance the grain morphology and uniformity of the perovskite film, which are critical factors in determining optical properties and device performance. Notably, HC-A4 demonstrated superior performance due to its distinct hydrophilic properties with a contact angle of 50.3°, attributable to its unique functional groups. Overall, the HC-A4 applied film exhibited efficient carrier extraction properties, attaining a carrier lifetime of 117.33 ns. Furthermore, HC-A4 contributed the superior device performance with its favorable band alignment, achieving the highest device efficiency of 20%.

Printed circuit boards (PCBs) make up 3 to 5% of all electronic waste. The metal content of spent PCBs can reach 40%. They usually contain valuable metals - Ag, Au, Pd, as well as other metals such as Cu, Sn, Pb, Cd, Cr, Zn, Ni and Mn. However metallic part of whole PCB is 40-60% including Cu layers between the fiberglass-polymer layers. The paper describes economics of the the valuable metals (Ag, Au, Pd) containing concentrate preparation from raw PCB. Considered the influence of pre-treatment method of PCB before the extraction of valuable metals on the extraction self-cost change. The disintegration method is based on the high-energy impact of the particles of the material to be ground, thus causing the separation of the metallic components of the PCB. In the course of the work, single and double direct grinding by the method of disintegration was studied. For the calculation the test batch 10’000 kg of two types of PCB were taken for estimation of the self costs and potential profit in case of complete valuable metals (Ag, Au, Pd) plus Cu extraction. Is shown that from 10’000 kg of studied PCB is possible to obtain 1144 and 1644 kg of metal-rich concentrate, which further should be subjected to electro-hydrochlorination for metals leaching. The main findings shows, that despite of high content of Cu in studied PCB, the commercial value is insignificant in total income from the Ag, Au and Pd sale. Was established correlation of the self-cost decrease after separative disintegration of PCB by metal content increase (by specific metals such as Au, Ag, Pd and also Cu) with the metal potential yield after extraction.

Objective The aim of this study was to examine the impact of a modern lifestyle on college female students' health, specifically focusing on their hip and knee joint mobility. The objective of this study was to assess the influence of hydraulic resistance training with the self-myofascial release technique on improving joint mobility in female college students. The training also aimed to compare the effectiveness of hydraulic resistance exercise with and without the self-myofascial release technique on hip and knee joint mobility.Methods The study used a randomized controlled trial design to recruit 30 female college students aged 18-25 through campus advertisements and announcements. Medical conditions or injuries that might have affected participation was screened. Participants were indiscriminately allocated to Group A (Hydraulic Resistance Training with Self-Myofascial Technique) or Group B (Hydraulic Resistance Training without Self-Myofascial Technique). The baseline assessments included joint range of motion (ROM) measurements using a goniometer. Certified trainers supervised the training sessions, and the data were analyzed using SD and mean using SPSS. ResultsThis study aimed to evaluate the impact of hydraulic resistance training with self-myofascial release on hip and knee joint mobility in female college students. The results showed that both groups showed improved hip and knee flexion with and without the self-myofascial release technique. However, the Group A using the self-myofascial release technique (Group A) showed a more significant enhancement, as indicated by the smaller p value compared to Group B. It has been suggested that the self-myofascial release technique may improve hip and knee joint mobility. ConclusionThis study concluded that Hydraulic Resistance Training with Self-Myofascial Release (HSMR) could improve hip and knee joint mobility among female college students. These findings suggest that integrating the self-myofascial release technique into training regimens can improve joint mobility. However, further research with larger sample sizes and extended intervention periods was needed to understand the long-term effects and sustainability of these improvements.

Introduction: In an era of increasing public awareness regarding the pivotal role of nutrition in the onset and progression of chronic degenerative diseases, there is a growing demand for information and assistance pertaining to the intricate relationship between diet and disease. Nutritional practices, therefore, emerge as a fundamental element in the prevention and management of these maladies, necessitating a proactive response from healthcare professionals (HCP). This study sought to evaluate the impact of participation in a Culinary Medicine (CM) program on Mediterranean diet adherence, food management skills, culinary proficiency, and counseling confidence among HCP. Methods: A mixed-methods pilot implementation program (PIP) was meticulously designed and executed, engaging a cohort of 20 HCP recruited from Hospital Clinic Barcelona. The program unfolded at the Alícia Foundation kitchen-lab and encompassed a series of interactive, hands-on sessions that delved into the realms of gastronomy, food management, culinary skills, and culinary diet therapy, with a specific focus on prevalent diseases and their prevention, treatment, and care. Tailored questionnaires were administered to all participants both before and after the PIP. Results: Of the 20 participants, 14 successfully completed the study, comprising 86% women, 86% aged above 40, 71% nurses, and 7% medical doctors. Interestingly, 86% of the participants had previously received nutrition training, whereas only 14% had received culinary training. Following the completion of the program, there was a remarkable improvement in adherence to the Mediterranean diet (p < 0.01). However, no statistically significant improvements were observed in food management and culinary skills or counseling confidence (p > 0.5). Despite the absence of statistical significance, there was a noteworthy trend towards greater advocacy for dietary changes before resorting to medication, along with enhanced confidence in providing nutritional and culinary guidance to patients. Conclusion: The findings from this study underscore the potential of hands-on CM training as a vital component of nutrition education for HCP. While statistically significant improvements in certain domains were not observed, the program did demonstrate its ability to influence attitudes, knowledge, and behaviors related to healthy cooking and eating for both HCP themselves and their patients. Given these promising trends, future studies with a larger sample size must be performed to further elucidate the impact of CM training on HCP and its potential benefits for public health.

With the development of electricity spot markets, accurate electricity load forecasting enables power generation companies to supply the right amount of electricity, Significantly avoid power waste. As a result, time series forecasting in the field of power can bring significant benefits. Previously, the Informer model successfully introduced the Transformer into long time series forecasting(LTSF) by proposing the ProbSparse self-attention mechanism, which solved the inherent problem of high memory complexity in self-attention. Recent research has further demonstrated the potential of the self-attention for mining complex dependencies. However, the limited amount of historical data has become one of the main challenges in applying deep learning techniques to power LSTF tasks. Previous reserches often add a large number of time covariates to provide more information. In this paper, to address this issue, (i) we design a simple but effective Season-aware Block to enhance the model’s ability to mine artificial prior information in temporal covariates; (ii) we conduct experiments using the provincial power data of Zhejiang Province, China, from 2019 to 2022, and our model outperforms other models, achieving a 19 percent MSE relative improvement; (iii) we conduct ablation experiments to assess the efficacy of the Season-aware Block in extracting temporal periodic features. Furthermore, we elucidate the underlying reasons for the effectiveness of both the self-attention mechanism and the Season-aware Block through visualization experiments.

Currently, the use of medications during pregnancy in Latin America is common; studies with Latin American samples find that nearly 90% of pregnant women use some medication at least once during pregnancy. Furthermore, approximately 21% of the respondents self-medicated. Worldwide, the prevalence of this disease is 32%. The most common medications are nonsteroidal anti-inflammatory drugs and analgesics. Many of these drugs are available over the counter without a prescription. For this reason, a systematic review of the literature on the adverse effects on the woman and the fetus was performed. Objective: To determine the adverse effects associated with the use of nonsteroidal anti-inflammatory drugs (NSAIDs) on pregnant women and fetuses during pregnancy. Methods: Systematic literature review. The following search strategy was used for the databases: Science Direct, PubMed, Scopus and Web of Science, through September 3, 2022. The population of pregnant women without previous comorbidities was defined. The intervention of interest was the use of NSAIDs during pregnancy. The outcomes of interest were adverse effects for the mother or fetus (weight of the newborn, congenital malformations present in the fetus, systemic effects in the pregnant woman during her gestation period). The types of studies included clinical trials, cohort studies and case‒control studies. Results: 1 study included 2,985 pregnant women without previous comorbidities. The use of aspirin more frequently during pregnancy stands out. The adverse effects on the fetus were preterm birth <37 weeks, low birth weight < 2500 g and increased admission to the neonatal intensive care unit. No adverse effects were found for the mother. Conclusions: There are not enough data indicating that the use of NSAIDs during pregnancy is safe. Some studies show that the use of NSAIDs during pregnancy could be related to problems in the development and growth of the fetus and health effects for the mother during pregnancy, so it is advisable to use these drugs under medical prescription and for the shortest possible time. in the gestation stage.

The study examines the behavior of the Mechanically Stabilized Earth (MSE) wall using available reinforcement materials in Danang, Vietnam. The MSE was reinforced by the self-fabricated galvanized steel grids using CB300V steel with 3 cm ribs. The backfill soil is a sandy clay soil from the local area with a low cohesion. A full-scale model with full instrumentation was installed to investigate the distribution of tensile forces along the reinforcement layers. The highest load that caused the wall to collapse due to internal instability (reinforcement rupture) was 302 kN/m2, which is 15 times the design load of 20 kN/m2. The failure surface within the reinforced soil had a parabolic sliding shape which is similar to the theoretical studies. At the failure load level, the maximum lateral displacement at the top of the wall facing was small (3.9 mm) which is significantly lower than the allowable displacements for the retaining wall. Furthermore, a numerical model using FLAC software was applied to simulate the performance of the MSE wall. The modeling results are in good agreement with the physical model. Thus, the self-fabricated galvanized steel grids could be confidentially used in combination with the local backfill soil for the MSE walls.

This paper deals with a method of calculating the self and mutual inductances of various air coils located arbitrarily in space. Known elementary solutions (the Biot-Savart formulas) were used to determine the magnetic field of infinitely thin current loops and infinitely thin wires of finite length linking magnetically other coils. Unlike commonly used algorithms, these elementary solutions were not extensively transformed analytically but were used to perform calculations by direct numerical integration. This enabled very quick and accurate obtaining of the self-inductance values as well as determining the dependence of mutual inductances on the position of both coils. This method allows analysis of different coil configurations (misaligned coils, inclined to each other, etc.) that other methods do not cover. It also enables the determination of the forces acting on the coils, as well as the calculation of the magnetic field distribution from any coil configuration. The obtained results were compared with those presented by other authors.

The dermatological manifestations of Long Covid (LC) have languished in the shadows of chronic fatigue and brain fog. Yet they are all linked by gut dysbiosis and the cytokine triad of TNF-α, IL-1β, and IL-6. The gut microbiome common not only to LC, psoriasis, AA, and vitiligo but also to neurodegenerative disease has been recently described. This gut microbiome induces an altered tryptophan metabolism linked to autoimmune disease. SARS CoV2 invades enterochromaffin cells rich in ACE2 receptors and curtails absorption of the essential amino acid tryptophan and subsequent synthesis of serotonin and melatonin. This review suggests that an etiologic prebiotic (d-mannose)/probiotic (lactobacilli, bifidobacteria)/postbiotic (butyrate) approach to autoimmune skin disease that improves intestinal barrier integrity and that suppresses the triad of TNF-α, IL-6, and IL-1β may enhance or even eliminate the traditional immunotherapy of targeted monoclonal antibodies, Janus kinase inhibitors, and steroids. Health benefits of this approach extend well beyond suppression of autoimmune skin disease.

In this paper, an ultracompact combined sensor for displacement and angle synchronous measurement is proposed based on self-imaging effect of optical microgratings. Using a two-grating structure, linear and angular displacement can be measured by detecting the change of phase and amplitude of the optical transmission respectively within one single structure in meantime. The optical transmitted properties of the two-grating structure are investigated in both theory and simulation. Simulated results indicate that, the optical transmission changes in a sinusoidal relationship to the input linear displacement. Meanwhile, the amplitude of the curve decreases with an input pitch angle, indicating the ability for synchronous measurement within one single compact structure. The synchronous measurement of the linear displacement and the angle is also demonstrated experimentally. The results show a resolution down to 4nm for linear displacement measurement, and a sensitivity of 0.26mV/arcsec within a range of ±1° for angle measurement. Benefitting from a simple common-path structure without using optical components including reflectors and polarizers, the sensor shows an ultrahigh compactness for multiple-degrees-of-freedom measuring, indicating the great potential for this sensor in the fields such as integrated mechanical positioning and semiconductor fabrication.

This work deals with a novel porous TiNi-based material for ophthalmic orbital implants that was produced by high-temperature synthesis (SHS) and possesses a specific microstructure of its surface pores, which makes it attractive for biomedical use in implants. After preparation via SHS, the obtained porous TiNi material was etched in acidic environment, to get rid of its surface Ti2Ni secondary-phase particles. This was found to improve the material’s surface morphology, adding micro-roughness to its macro-rough pores. As a result, cell growth tests conducted on the material demonstrated improved cell adhesion and growth kinetics on such a porous material with improved roughness. Finally, the material was tested in vivo as an ophthalmic orbital implant, demonstrating good biocompatibility, good degree of biointegration with surrounding eyeball tissues, and no signs of rejection after as long as 180 days. Thus, the novel porous TiNi-based material shows promise for its use in ophthalmic implantology, for instanse for manufacturing musculoskeletal stumps of the eyeball after evisceration, as it is biocompatible, has a high tissue-implant integration potential and demonstrates reduced risks of exposure and rejection of the implant.

Active vitamin D derivatives (VDDs) – 1α,25-dihydroxyvitamin D3/D2 and their synthetic analogs – are well-known inducers of cell maturation with the potential for differentiation therapy of acute myeloid leukemia (AML). However, their dose-limiting calcemic activity is a significant obstacle to using VDDs as an anticancer treatment. We have shown that different activators of the NF-E2-related factor-2/Antioxidant Response Element (Nrf2/ARE) signaling pathway, such as the phenolic antioxidant carnosic acid (CA) or the multiple sclerosis drug monomethyl fumarate (MMF), synergistically enhance the antileukemic effects of various VDDs applied at low concentrations in vitro and in vivo. This study aimed to investigate whether glutathione, the major cellular antioxidant and the product of the Nrf2/ARE pathway, can mediate the Nrf2-dependent differentiation-enhancing activity of CA and MMF in HL60 human AML cells. We report that glutathione depletion using L-buthionine sulfoximine attenuated the enhancing effects of both Nrf2 activators concomitant with downregulating vitamin D receptor (VDR) target genes and the activator protein-1 (AP-1) family protein c-Jun levels and phosphorylation. On the other hand, adding reduced glutathione ethyl ester to dominant negative Nrf2-expressing cells re-stored both the suppressed differentiation responses and the downregulated expression of VDR protein, VDR target genes, as well as c-Jun and P-c-Jun levels. Finally, using the transcription factor decoy strategy, we demonstrated that AP-1 is necessary for the enhancement by CA and MMF of 1α,25-dihydroxyvitamin D3-induced VDR and RXRα protein expression, transactivation of the vitamin D response element, and cell differentiation. Collectively, our findings suggest that glutathione mediates, at least in part, the potentiating effect of Nrf2 activators on VDDs-induced differentiation of AML cells, likely through the positive regulation of AP-1.

Postpartum depression is a significant health issue during the postpartum period and not only affects the woman but also has important repercussions for the newborn. Group support interventions during the postpartum period have proven effective in helping women cope with depression and improving breastfeeding rates. The aim of this study was to assess the effectiveness of a midwife-led breastfeeding support group intervention on breastfeeding rates, postpartum depression and general self-efficacy. This was a multicentric cluster randomized controlled trial with control and intervention groups and was not blinded. It was conducted in Andalusia (southern Spain) from October 2021 to May 2023. A total of 382 women participated in the study. Results showed a significant difference in exclusive breastfeeding rates at 4 months postpartum between the groups (p &lt; 0.001). Additionally, there was a lower mean score on the Edinburgh Postnatal Depression Scale in the intervention group (12.49 ± 3.6 vs 13.39 ± 4.0; p = 0.044). Similarly, higher scores of general self-efficacy were observed among breastfeeding women at 2 and 4 months postpartum (p = 0.002 and p &lt; 0.001, respectively). In conclusion, midwife-led breastfeeding support groups enhanced self-efficacy, prolonged breastfeeding and reduced postpartum depression 4 months after giving birth.

Environmental responsibility and economic benefits have promoted the development of closed-loop supply chain (CLSC), and shortages and channels are considered to be two important issues in CLSC. This paper explores ordering and channel decisions in CLSC with new and differentiated remanufactured products, and considers the price and sales effort-dependent demands, as well as the proportion of emergency orders determined by emergency order costs and backorder losses, and establishes an integrated and decentralized CLSC game models. We introduce a stochastic sales effort, which affects two types of products. Numerical results show that sales effort and the order quantity of new and remanufactured products exhibit concave and convex functions, respectively. Wherein, the upper limit of sales effort has a greater impact on supply chain decisions. High sales efforts can serve as a means of coordinating dispersed supply chains. Moreover, in different cases, decisions of integrated channel are better than those of decentralized channel. Finally, whether the supply chain adopts an emergency order strategy depends on the relative cost of emergency orders and out of stock costs. According to the research in this article, some management insights are also provided.

The Reactive Spark Plasma Sintering (R-SPS) method is compared in this work with the two-steps SHS-SPS route, based on combination of the Self-propagating High-temperature Synthesis (SHS) with the SPS process, for the fabrication of dense (Hf0.2Mo0.2Ti0.2Ta0.2Nb0.2)B2-SiC and (Hf0.2Mo0.2Ti0.2Ta0.2Zr0.2)B2-SiC ceramics. A multiphasic and inhomogeneous product, containing various borides, is obtained at 2000°C/20min by R-SPS, from transition metals, B4C and Si. In contrast, if the same precursors are first reacted by SHS, and then processed by SPS under the optimized condition of 1800°C/20min, the desired ceramics are successfully attained. Both High-Entropy-Boride/SiC products display densities > 97%, uniform microstructures and contained only small amounts of residual oxides (<2.4 wt.%). The presence of SiC makes the sintering temperature milder, i.e. 150°C below to that needed by the corresponding additive-free system. Fracture toughness is also markedly improved, particularly when considering the Nb-containing system processed at 1800°C/20min, whereas KIC progressively decreases (from 7.35 to 5.36 MPa m1/2) as the SPS conditions become more severe. SiC addition is found to inhibit the volatilization of metal oxides like MoO3 formed during oxidation experiments, thus avoiding mass loss in the ceramics. The benefits above also likely take advantage of the fact that the two composite constituents are synthesized in parallel, according to the SHS-SPS approach, rather than being produced separately and combined subsequently, so that strong interfaces between them are formed.

The study aimed to investigate how distributed leadership influences adolescents' social and emotional competence, considering the roles of student-centered instructional practices and teacher self-efficacy. Utilizing survey data from 7,246 Suzhou adolescents enrolled in the SESS program, the study employed multilevel structural equation modeling for analysis. The findings indicated a positive correlation between distributed leadership and adolescents' social and emotional competence, as evaluated by teachers. Moreover, distributed leadership was observed to exert an indirect impact on adolescents' self-assessment and teacher-rated social and emotional competence. This influence operated through several mediators: student-centered instructional practices, teacher self-efficacy, and the sequential mediating pathway of student-centered instructional practices → teacher self-efficacy. This study underscores the significance of supportive elements in fostering students' social and emotional competence. It offers valuable insights into the everyday practices of teachers, principals, and administrators. Additionally, it sheds light on how distributed leadership contributes to enhancing adolescents' overall social and emotional development.

This study presents an in-depth analysis and evaluation of self-healing networks as an innovative solution to combat the escalating threat of ransomware attacks. Recognizing the limitations of traditional network security methods in the face of advanced cyber threats, the research focuses on the development and implementation of self-healing networks, characterized by their dynamic, intelligent response systems. Utilizing a combination of artificial intelligence and machine learning algorithms, these networks demonstrate remarkable adaptability and resilience. Through rigorous simulations, the study examines the efficacy of self-healing networks in detecting, isolating, and recovering from ransomware attacks, with an emphasis on their ability to learn and evolve from each incident. The research highlights the strengths and limitations of these networks and discusses their potential applications in various sectors. The findings suggest that self-healing networks, with their proactive and adaptive defense mechanisms, represent a significant advancement in cybersecurity strategies, offering a robust solution against a range of cyber threats. Future work is recommended to further enhance the capabilities of self-healing networks, particularly in the areas of speed, detection accuracy, and quantum-resistant security measures.

In an outstanding article published in 2008, Suzuki obtained a nice generalization of the Banach contraction principle from which derived a characterization of metric completeness. Although Suzuki’s theorem has been successfully generalized and extended in several directions and contexts, we here show by means of a simple example that the problem of achieving, in an obvious way, its full extension to the framework of w-distances does not have an emphatic response. Motivated by this fact we introduce the concept of presymmetric w-distance on metric spaces, we give some properties and examples of this new structure and show that it provides a reasonable setting to obtain a real and hardly forced w-distance generalization of Suzuki’s theorem. This is realized in our main result, which is a fixed point theorem that involves presymmetric w-distances and certain contractions of Suzuki-type. We also discuss the relationship between our main result and the well-known w-distance full generalization of the Banach contraction principle, due to Suzuki and Takahashi. Connected to this approach we prove another fixed point result that compare with our main result through some examples. Finally, we state a characterization of metric completeness by using our fixed point results.

In today’s competitive landscape, achieving customer-centricity is paramount for the sustainable growth and success of organisations. This research is dedicated to understanding customer preferences in the context of the Internet of Things (IoT) and employs a two-part modeling ap-proach tailored in this digital era. In the first phase, we leverage the power of the Self-Organizing Map (SOM) algorithm to segment IoT customers based on their connected device usage patterns. This segmentation approach reveals three distinct customer clusters, with the second cluster demonstrating the highest propensity for IoT device adoption and usage. In the second phase, we introduce a robust Decision Tree methodology designed to prioritize various factors influencing customer satisfaction in the IoT ecosystem. We employ the Classification and Regression Tree (CART) technique to analyze 17 key questions that assess the significance of factors impacting IoT device purchase decisions. By aligning these factors with the identified IoT customer clusters, we gain profound insights into customer behaviour and preferences in the rapidly evolving world of connected devices. This comprehensive analysis delves into the factors contributing to customer retention in the IoT space, with a strong emphasis on crafting logical marketing strategies, en-hancing customer satisfaction, and fostering customer loyalty in the digital realm. Our research methodology involves surveys and questionnaires distributed to 207 IoT users, categorizing them into three distinct IoT customer groups. Leveraging analytical statistical methods, regression analysis, and IoT-specific tools and software, this study rigorously evaluate the factors influencing IoT device purchases. Importantly, this approach not only effectively clusters the IoT Customer Relationship Management (IoT-CRM) dataset but also provides valuable visualizations that are essential for understanding the complex dynamics of the IoT customer landscape. Our findings underscore the critical role of logical marketing strategies, customer satisfaction, and customer loyalty in enhancing customer retention in the IoT era. This research makes a significant contri-bution to businesses seeking to optimize their IoT -CRM strategies and capitalize on the oppor-tunities presented by the IoT ecosystem.

Gastric outlet obstruction (GOO) poses a common and challenging clinical scenario, characterized by mechanical blockage in the pylorus, distal stomach, or duodenum, resulting in symptoms such as nausea, vomiting, abdominal pain, and early satiety. Its diverse etiology encompasses both benign and malignant disorders. The spectrum of current treatment modalities extends from conservative approaches to more invasive interventions, incorporating procedures like surgical gastroenterostomy (SGE), self-expandable metallic stents (SEMS) placement, and the advanced technique of endoscopic ultrasound-guided gastroenterostomy (EUS-GE). While surgery is favored for longer life expectancy, stents are preferred in malignant gastric outlet stenosis. The novel EUS-GE technique, employing a lumen-apposing self-expandable metal stent (LAMS), combines the immediate efficacy of stents with the enduring benefits of gastroenterostomy. Despite its promising outcomes, EUS-GE is a technically demanding procedure requiring specialized expertise and facilities.

Neurodegeneration is becoming one of the leading causes of death worldwide as the population expands and grows older. There is a growing desire to understand the mechanisms behind prion proteins as well as the prion-like proteins that make up neurodegenerative diseases (NDs) including Alzheimer’s Disease (AD). Both amyloid β (Aβ) and hyperphosphorylated tau (p-tau) proteins behave in ways similar to that of the infectious form of the prion protein, PrPSc, such as aggregating, seeding, and replicating under not yet fully understood mechanisms, thus the designation of prion-like. This review aims to highlight the shared mechanisms between prion-like proteins and prion proteins in the structural variations associated with aggregation and disease development. These mechanisms are largely focusing on the dysregulation of protein homeostasis, self-replication, and protein aggregation, and how this knowledge could contribute to diagnoses and treatments for the given NDs.

This study explores the interplay between web-based professional development, teachers' self-efficacy, resilience, and work values in the context of the Davao Region. The investigation reveals significant findings in three key areas: web-based professional development, teachers' resilience, and teachers' work values. The survey indicates that web-based professional development significantly impacts teachers' self-efficacy, with interaction self-efficacy registering the highest mean score. Moreover, teachers' resilience is manifested across emotional, motivational, and social dimensions, with emotional resilience scoring the highest mean. Teachers' work values, encompassing physical facilities, social environment, job security, new challenges, professional growth, personal growth, and interpersonal relationships, all demonstrate high descriptive equivalents. The study establishes a significant positive correlation between web-based professional development and teachers' self-efficacy, as well as a significant relationship between teachers' resilience and their work values. Furthermore, both web-based professional development and teachers' resilience exert a significant influence on teachers' work values.The conclusions drawn from the study highlight the prominence of web-based professional development, teachers' resilience, and work values in the educational landscape of the Davao Region. The findings underscore the interconnectedness of these factors and their crucial role in shaping the teaching profession. In light of these results, recommendations are made to inform policy decisions and enhance professional development programs for teachers in the region. The study encourages a holistic understanding of the relationships between web-based professional development, self-efficacy, resilience, and work values, aiming to contribute to the continuous improvement of education quality in the Davao Region. Additionally, future research is suggested to delve deeper into specific aspects of teachers' general self-efficacy, social resilience, and interpersonal relationships for a more comprehensive understanding.

This study aimed to expand and inform the growing body of research on Postpartum Depression, from a netnographic standpoint, for the social media platform of Pinterest. More specifically, it aimed to assess the type of content present on Pinterest regarding Postpartum Depression shared by women in 2018 and 2021, as well as examine the subjective experience of women who have experienced this mood disorder. Data were collected following a search using the keywords “Postpartum Depression” on Pinterest on two separate timestamps (2018 and 2021); pins were limited to those in English or French. Master themes were identified among all pins and those identified as “self-disclosure” were subsequently further analyzed. Self-disclosure data were separately analysed using thematic analysis, specifically adopting a deductive thematic approach for the 2021 data set stemming from the coding scheme created from analysis of the 2018 data. Major themes were identified, and an analysis of frequency was performed for each sub-theme, along with qualitative examples associated with each theme. A total of 483 Pinterest pins from two different time points of 2018 (169 pins) and 2021 (314 sample pins) were analyzed. Five primary categories were identified in both 2018 and 2021, with five additional categories being identified in the 2021 dataset. Comparative results from 2018 and 2021 self-disclosure pins show individuals’ varying yet similar subjective manifestations of PPD, the potential need to adopt a multidisciplinary treatment approach, and the societal fears, such as mental health stigma, that are playing a part in help-seeking behavior hesitancies. Our findings provide imperative insight into individuals’ subjective experiences with PPD; experiences that involve a sensitive and vulnerable topic. Netnographic research, along with Pinterest, must be taken into consideration for future work delving into women’s health issues, including those surrounding perinatal mental health.

This research emphasizes a meta-heuristic Modified Ant Lion Optimizer (MALO) optimization approach for simultaneous utilization of DSTATCOM devices and distributed Photovoltaic (PV) sources with network reconfiguration in a radial power distribution scheme. In a radial power distribution network with network reconfiguration majority of the research is based on Constant Power model analysis. However, it is noticed that load models have a substantial impact on the distributed PV sources and the D-STATCOM device's optimal size and position. The effect of the Constant Power (CP) and Polynomial (ZIP) with load growth load models for the simultaneous insertion of distributed PV sources and DSTATCOM devices with network reconfiguration examined in this research work for power system planning. The penetration levels of distributed PV sources considered for the investigation are 25%, 50%, 75%, and 100%. The principal objective of this research is to reduce network total power losses, enhance the voltage magnitude profile at all buses, and reduce the overall operating cost while adhering to equality and inequality constraints. The proposed algorithm verified on 118-node test systems. The investigation is carried out for planning network upgradation to a High Voltage Distribution System(HVDS) on 317 nodes in the rural Bangalore Electricity Supply Company Limited(BESCOM) radial distribution scheme. Simulated results obtained by this method are validated with the BAT algorithm and available techniques in the literature.

In this work, we introduce the concepts of r-fuzzy soft δ-open (resp. semi-open and α-open) sets on fuzzy soft topological space, the relations of these sets with each other are established. Next, we introduce the concepts of fuzzy soft δ-continuous (resp. β-continuous, semi-continuous, pre-continuous and α-continuous) functions, and some properties of these functions along with their mutual relationships are investigated. Also, a decomposition of fuzzy soft semi-continuity and a decomposition of fuzzy soft α-continuity are given. Finally, as a weaker form of fuzzy soft continuity by Aygunoglu et al. (2014), the concepts of fuzzy soft almost (resp. weakly) continuous functions are introduced, and some properties are specified. Moreover, we explore the notion of continuity in a very general setting namely fuzzy soft (L, M, N, O)-continuous functions, and a historical justification are obtained.

his quantitative study investigates teachers' perceptions of self-efficacy during the COVID-19 pandemic and explores the correlation between these perceptions and the preservice training they received. The research addresses the cognitive connection between teachers' current self-efficacy, particularly their satisfaction with and appreciation of preservice lecturers. Utilizing a retrospective lens, the study reveals a significant correlation between teachers' evaluation of their preservice training, especially their appreciation of lecturers, and their present self-efficacy. The findings highlight that teachers, amidst the challenges of the pandemic, evaluated their self-efficacy at a remarkably high level. This underscores their resilience during a period of unprecedented uncertainty, demanding substantial personal and professional adaptability. The nuanced interplay observed suggests that teachers' sense of self-efficacy serves as a predictive variable of their mental and professional resilience when confronting uncertainty and navigating rapid and profound changes, as exemplified by the exigencies of the COVID-19 pandemic.

Nucleobase-containing molecules are compounds essential in biology due to the fundamental role of nucleic acids, and in particular G-quadruplex DNA and RNA in life. Moreover, some molecules different from nucleic acids isolated from different vegetal sources or microorganisms show nucleobase moieties in their structure. Nucleoamino acids and peptidyl nucleosides belong to this molecular class. Closely related to the above, nucleopeptides also known as nucleobase-bearing peptides are chimeric derivatives of synthetic origin and more rarely isolated from plants. Herein the self-assembly properties of a vast number of structures, belonging to the nucleic acid and nucleo amino acid/nucleopeptide family, is explored in the light of the recent scientific literature. Moreover, several technologically relevant properties such as the hydrogelation ability of some of the nucleobase-containing derivatives are reviewed in order to open the door to future experimental investigations of newly-inspired nucleobase-driven hydrogels. Nucleobase-containing molecules, such as mononucleosides, DNA, RNA, quadruplex (G4)-forming oligonucleotides and nucleopeptides, are paramount in gel and hydrogel formation owing to their distinctive molecular attributes and ability to self-assemble in biomolecular nanosystems with the most diverse applications in different fields of biomedicine and nanotechnology. In fact, these molecules and their gels present numerous advantages, underscoring their significance and applicability in both material science and biomedicine. Their versatility, capability for molecular recognition, responsiveness to stimuli, biocompatibility, and biodegradability collectively contribute to their prominence in modern nanotechnology and biomedicine. In this review, we emphasize the critical role of nucleobase-containing molecules of different nature in pioneering novel materials with multifaceted applications highlighting their potential in therapy, diagnostics, and new nanomaterials fabrication as required in order to address the numerous current biomedical and nanotechnological challenges.

In our latest studies with the help of the self-similar Ansatz we derived new type of 1 solutions for the regular diffusion equation which are much more complex than the well-known 2 Gaussian and error functions. These solutions contain additional Kummer’s M and Kummer’s U 3 functions with quadratic argument. In the present treaties we perform an analogous analysis for the 4 regular diffusion equation which has a complex diffusion coefficient. Formally, it is equivalent to 5 the free Schrödinger equation however it is far from being trivial how the solutions can be given 6 quantum mechanical interpretation. We investigate both the one dimensional Cartesian and the 7 spherical symmetric equations. We find solutions which fulfill the L2 integrability criteria therefore 8 might have quantum mechanical relevance in the future.

This review examines the challenges faced by the pig industry, with a specific emphasis on improving the health and growth of weaned pigs. It emphasises the immediate necessity of investigating alternative approaches to managing pig nutrition and health due to restrictions on the use of antibiotics and the prohibition of zinc oxide in weaned pig diets. The weaning phase is identified as a critical stage in piglet development, characterized by stressors that affect their gastrointestinal health, immune responses, and overall physiology. The primary challenge during weaning arises from transitioning piglets from a digestible milk-based diet to a less digestible cereal-based feed, causing nutritional stress. This manifests as reduced feed intake, leading to gastrointestinal disturbances, intestinal inflammation, and adverse effects on intestinal structure and microbiota. To address these challenges and optimise piglet development, various nutritional strategies have been explored. Notably, glucans, particularly β-glucans from fungi, cereals, algae, and yeast, show promise in alleviating weaning-related issues. Furthermore, it's important to highlight the critical roles played by vitamin D and selenium in piglet nutrition. These essential nutrients can be sourced naturally from enriched mushrooms that are specifically enriched with vitamin D and selenium, providing a valuable dietary option. In conclusion, effective nutritional strategies, including glucans, vitamin D, selenium, and enriched mushrooms, are beneficial for addressing weaning-related challenges.

Self-consolidating concrete (SCC) is highly workable concrete that flows under minimal vibrations into congested reinforcement and sophisticated formworks. The properties of SCC are achieved by incorporating chemical admixtures. In this study, we analyzed if SCC could be designed with a cheap, easily accessible plant extract as a bio-admixture known as aloe vera mucilage (AVM). The main aim is to determine the effect of AVM on SCC prepared from ordinary Portland cement (OPC) and blended cement LC3, consisting of clinker (50%), calcined waste clay (30%), limestone (15%), and gypsum (5%). The AVM is applied in different dosages of up to 10%. The findings showed that the LC3 had a lower rate of consistency, lower slump values, and higher initial and final setting times compared to OPC. The V-funnel and L-box values were reduced with increased plasticizer dosing. Additionally, the OPC samples with both plasticizers achieved higher compressive strength than LC3 in the 7, 14, and 28 curing ages. However, the 2.5 % dosage of AVM showed some increase in compressive strength in both OPC and LC3 samples. Overall, AVM is comparable to the commercial plasticizer used as both influence the reduction of yield stress with an increase in slump flow.

Cardiovascular diseases (CVDs) and chronic kidney disease (CKD) are frequently interconnected and their association leads to an exponential increase in the risk of both fatal and non-fatal events. In addition, the burden of arrhythmias in CKD patients is increased. On the other hand, the presence of CKD is an important factor that influences the decision to pursue cardiac device therapy. Data on CKD patients with device therapy is scarce and mostly derives from observational studies and case reports. Cardiac resynchronization therapy (CRT) is associated with decreased mortality, reduced heart failure symptoms and improved renal function in early stages of CKD. Implantable cardioverter defibrillators (ICDs) are associated with a significant reduction in the mortality of CKD patients only for the secondary prevention of sudden cardiac death. Cardiac resynchronization therapy defibrillator (CRT-D) is preferred in patients that meet the established criteria. The need for cardiac pacing is 3-fold higher in dialysis patients. CKD is an independent risk factor for infections associated with cardiac devices.

Lipophilic oligonucleotide derivatives are a potent approach to the intracellular delivery of nucleic acids. The binding of these derivatives to serum albumin is a major determinant of their fate in the body, as its structure contains several sites of high affinity for hydrophobic compounds. This study focuses on the features of self-association and non-covalent interactions with human serum albumin of novel self-penetrating oligonucleotide derivatives. The study revealed that the introduction of a triazinyl phosphoramidate modification bearing two dodecyl groups at the 3' end region of the oligonucleotide sequence has a negligible effect on its affinity for the complementary sequence. Dynamic light scattering verified that the amphiphilic oligonucleotides under study can self-assemble into micelle-like particles ranging from 8 to 15 nm in size. The oligonucleotides with dodecyl groups form stable complexes with human serum albumin with a dissociation constant of approximately 10-6 M. The oligonucleotide micelles are simultaneously destroyed upon binding to albumin. Using an electrophoretic mobility shift assay and affinity modification, we examined the ability of DNA duplexes containing triazinyl phosphoramidate oligonucleotides to interact with Ku antigen and PARP1, as well as the mutual influence of PARP1 and albumin or Ku antigen and albumin upon interaction with DNA duplexes. These findings, together with the capability of dodecyl-containing derivatives to effectively penetrate different cells, such as HEK293 and T98G, indicate that the oligonucleotides under study can be considered as a platform for the development of therapeutic preparations with a target effect.

This research provides a computationally efficient numerical tool for predicting 3-D turbulent flows over hydrofoils. It addresses a gap in existing numerical methods by extending the capabilities of the laminar VIScous Vorticity Equation (VISVE) solver to handle 3-D turbulent flow scenarios. The implementation integrates the k − ω SST model into the 3-D VISVE solver using the Finite Volume Method (FVM), extending its capability to handle turbulent flows. The turbulence model is also parallelized to improve computational efficiency. The application of the newly developed model to 3-D hydrofoil cases expands its scope and serves as preparatory work for future rotational propeller applications. Rigorous testing includes a convergence analysis concerning grid numbers and time step sizes, and validation against a Reynolds-Averaged Navier-Stokes (RANS) solver ensures the reliability and accuracy of the enhanced VISVE solver for turbulent flow simulations. The turbulent VISVE solver offers advantages such as reduced computational domain and costs through a vorticity-based approach. Turbulence concentration within boundary layers and free shear flows does not compromise the advantages of the small computational domain. The simplified meshing process, automatically generated by denoting the number of panels on the hydrofoil, makes the solver accessible for researchers and engineers.

This article introduces a new physically based Lyapunov function difinition, which can be used as acoustic energy for finite amplitude pressure oscillations in reacting systems especially in combustion chambers. Reacting flow is seen as an open, non-equilibrium (parameters are distributed unevenly locally) thermodynamic system. This Lyapunov function is defined as the maximum mechanical work, which could be extracted by a heat engine from studied system, if this system would be disconnected from inlet and outlet and from any other surrounding environment, and the engine could transfer to the surrounding environment only mechanical work.

This paper presents the design and measurement of an IEEE 802.11ad standard compatible RF transceiver for 60GHz wireless communication system. In addition to the traditional half-duplex (HD) mode, this work supports full-duplex (FD) operation to deliver better channel utilization and faster response time for the system. The isolation between the transmitter and receiver from the architecture design to system integration for FD operation has been fully considered. A digital self-interference cancellation (DSIC) is implemented in MATLAB to verify the FD performance. The super-heterodyne architecture with an intermediate frequency (IF) of 12GHz is designed to suppress the image frequencies without using extra filters. A flexible phase-locked loop (PLL) synthesizer provides a local oscillator (LO) frequency with a 2kHz resolution. Other than the time division duplex (TDD) mode used in the conventional 60GHz system, a wide bandwidth baseband digital variable gain amplifier (DVGA) with a 3dB bandwidth of more than 4GHz also supports frequency division duplex (FDD) operation. The transceiver chip is fabricated in Tower Jazz 0.18µm SiGe BiCMOS process. With on-board antenna, the transceiver covers all four channels in 802.11ad standard with MCS-12 (7.04Gbps under 1.76GSym/s and 16-QAM) under 1.5m. In the proposed system design, the RF frontend based self-interference (SI) suppression from the local transmitter to receiver LNA is around 54dB. To achieve a practical FD application, the SI is further suppressed with the help of digital SI compensation. The measured power consumption for transmitter and receiver configuration is 194mW and 231mW, respectively, in HD mode and 398mW for FDD or FD operation mode.

Premature failure and degradation of layers are the main problems for transportation infrastruc-ture. Addressing these issues necessitates implementing structural health monitoring (SHM) for transportation layers. This strategic approach is instrumental in mitigating maintenance expenses, prolonging the operational lifespan, and preventing accidents resulting from abrupt layer col-lapse. To this end, this research investigated the stress/strain and damage detection capabilities of a self-sensing cementitious composite developed for potential utilization in the construction of an intelligent subgrade layer. The prepared self-sensing cementitious composite consisted of 10% cement and hybrid conductive fillers, including multiwalled carbon nanotubes (MWCNTs) and graphene nanoplatelets (GNPs) in sand. Initial findings reveal that the electrical resistivity of the composite is significantly affected by the concentration of MWCNTs/GNPs, with a minimum concentration of more than 0.5% needed to achieve a responsive cementitious composite. More-over, the piezoresistive analysis indicates that an increase in the concentration of MWCNTs/GNPs and stress levels leads to an improvement in the stress/strain sensing perfor-mance. When the self-sensing cementitious composite is subjected to equivalent stress levels, variations in the FCR exhibit an increasing trend with decreasing resilient modulus, stemming from a decrease in stiffness due to the increased concentration of MWCNTs/GNPs. Additionally, the EIS analysis demonstrates a contraction for the Nyquist curves under compressive ramp loading prior to failure, followed by the expansion of these curves postfailure. Scanning electron microscopy (SEM) images visually showcase the bridging effects of MWCNTs and the filling ef-fects of GNPs within the composite structure.

The evolution of sentence representation learning, especially with parse tree encoders, has shown remarkable progress. Traditional approaches predominantly rely on recursive encoding of tree structures, which impedes parallel processing capabilities. Additionally, these methods often overlook the significance of dependency tree arc labels. To overcome these limitations, we introduce the Syntax-Enhanced Transformer (SET), incorporating a novel dual-attention mechanism that integrates relation-focused attention alongside traditional self-attention. This design effectively encodes both dependency and spatial positional relationships within sentence dependency trees. Our approach innovatively incorporates syntactic information into the Transformer framework without compromising its inherent parallelizability. The SET demonstrates superior or comparable performance to contemporary methods across various sentence representation tasks, significantly enhancing computational efficiency.

A Berry geometrical phase is identified in a strongly metastable system containing dynamically responsive clathrate hydrate structures within a crystal-fluid material. High energy degeneracy in the associated chemistry produces local stability and false vacuum conditions that lead to non-extensive and non-additive contributions in the fundamental thermodynamic relation. The reciprocating action of a piston expander confirms a net energy gain despite the crystal-fluid material maintaining almost constant density. Application of Ginzburg-Landau theory and the scaling laws reveals a coherence length and a penetration depth for a macro-scale dual superconductor. The coherence length determines non-extensive volume changes whilst its inverse gives the Higgs mass. The penetration depth determines the extent of QCD vacuum suppression whilst its inverse gives the vector boson mass together with indirect manifestation as non-additive hyperbolic curvature. External pressure perturbations of the low-energy system initiate ‘rolling’ critical responses that see energy and momentum conserved across a synchronized U(2) symmetry group whilst a complex gauge field is also exposed. Simultaneous emergence of the Ginzburg-Landau superconducting phase transition is consistent with gauge-invariant coupling of this scalar field to the Yang-Mills action in QCD. The discovery of an energy gap in the gradient energy term of the system Lagrangian is associated with a critical correlation length revealed in the transition from a gapped to a gapless superconducting state. Together with the emergence and absorption of the Higgs-like scalar field, a mechanism for describing the QCD mass gap arises.

In this paper, an intelligent blind guide system based on 2D LiDAR and RGB-D camera sensing is proposed, and the system is mounted on the smart cane. The intelligent guide system relies on 2D LiDAR, RGB-D camera, IMU, GPS, Jetson nano B01, STM32 and other hardware. The main advantage of the intelligent guide system proposed by us is that the distance between the smart cane and obstacles can be measured by 2D LiDAR based on Cartographer algorithm, thus achieving Simultaneous localization and mapping (SLAM). At the same time, through the improved yolov5 algorithm, pedestrians, vehicles, pedestrian crosswalks, traffic lights, warning posts, stone piers, tactile paving and other objects in front of the visually impaired can be quickly and effectively identified. Laser SLAM and improved yolov5 obstacle identification tests were carried out inside a teaching building on the campus of Hainan Normal University and on a pedestrian crossing on Longkun South Road in Haikou City, Hainan Province. The results show that the intelligent guide system developed by us can drive the wheels and omnidirectional wheels at the bottom of the smart cane, and give the smart cane a self-leading blind guide function like a "guide dog", which can effectively guide the visually impaired to avoid obstacles and reach the predetermined destination, and can quickly and effectively identify the obstacles on the way out. The laser SLAM speed of this system is 25~31FPS, which can realize the short-distance obstacle avoidance and navigation function both in indoor and outdoor envionments. The improved yolov5 helps to identify 86 types of objects, the recognition rate for pedestrian crosswalks and for vehicles are 84.6% and 71.8%, respectively; the overall recognition rate for 86 types of objects is 61.2%, and the obstacle recognition rate of the intelligent guide system is 25-26FPS.

The purpose of this study is to analyze the self-regulated learning and the ability to write scientific papers of students after learning with the Project-Based Digital Science Module (DSM). This research is a mixed methods by analyzing quantitatively and qualitatively. The research instrument used to obtain data is using a product assessment sheet and a self-regulated learning questionnaire. Data analysis uses N-Gain to determine the increase in self-regulated learning scores and student scientific writing skills scores, and uses linear regression analysis to determine the effect of self-regulated learning on student scientific writing skills. The results obtained showed N-Gain score of learning independent is 0,65 and scientific writing ability is 0,94, then significant’s score from linear regression by using SPSS is 0,22 < 0,05. This result showed an increase in self-regulated learning and the ability to write scientific papers of students on each indicator after learning using the Project-Based Digital Science Module (DSM). In addition, based on the results of data analysis, it can be seen that there is an influence of self-regulated learning on the ability to write scientific papers of students after learning using the Project-Based Digital Science Module.

The Konya Closed Basin (Quaternary, Central Turkey) is a graben basin which expands toward the east-west and it is controlled by faults on three sides: The Konya fault zone in the west, the Divanlar fault zone in the east and the Karaömerler fault zone in the north. Calcretes developed in relation to fault systems in the Konya region are concentrated in areas where faults cut Quaternary aged terrestrial deposits. In this study, it is aimed to elucidate the deposition conditions, geochemistry and age (with ESR method) of the calcareous deposits associated with faults in the Konya Closed Basin. Calcretes in the region existing as coatings, dust, nodules and layers are in the form of dolocrete and clayey calcrete. Dolocretes were deposited in the Quaternary terrestrial sediments on the ophiolitic rocks and geochemical data point to an ultramafic source. Bacterial community, clay, quartz minerals and calcite cement are observed in the calcretes formed in areas with limestone basement. According to the results of ICP-MS analysis of samples taken from Konya calcretes, the %MgO contents are between 0.99 and 7.7; CaO%: between 34.71 and 50.71; %SiO2 between 3.22 and 20.59. %MgO in dolocretes are between 11.65 and 21.01; %CaO between 8.44 and 29.57; %SiO2 values between 4.48 and 9.17 The δ13C and δ18O isotope values of calcretes range from -3.87 to -7.62 and from -3.62 to -7.45 respectfully. Average δ13C values indicate that calcrete formation took place under pedogenic condition or in shallow groundwater. The calcretes deposited in 3 locations around the city of Konya (on the Konya fault zone) were dated by using the Electron Spin Resonance (ESR) method and ages between 217.47 and 389.85 ky were obtained. The calcrete samples taken from the fault planes (dip-slip normal fault bordering the Upper Cretaceous Ophiolitic Mélange and the Quaternary Karahüyük Formation) gave a relative age for faulting as being 292.86 ky. This first dating study conducted in the Konya Fault Zone has provided important clues to elucidate the formation history of Konya Closed Basin (KCB) and the paleo-seismological past of Konya.

The COVID-19 pandemic has disrupted healthcare worldwide, potentially impacting disease management. This cross-sectional study assessed the influence of COVID-19 on diabetes self-management in 341 Saudis with type 2 diabetes using the Diabetes Self-Management Questionnaire (DSMQ). The DSMQ contains 16 items across 4 domains assessing glucose management, dietary control, physical activity, and healthcare use. Three additional items measured the perceived overall impact of COVID-19. Total DSMQ scores were significantly higher in patients aged &gt;60 years versus younger groups. Scores were significantly lower in patients diagnosed for 1-5 years versus longer durations. Patients on insulin had higher glucose management subscores than oral medication users. Overall, DSMQ scores were higher than the pre-pandemic Saudi population and Turkish post-pandemic findings. DSMQ results suggest that while COVID-19 negatively impacted some self-management domains, Saudi patients upheld relatively good diabetes control during the pandemic. Further research is warranted on specific barriers to optimize diabetes care during public health crises.

The aim of article is to design a calm water resistance predictor based on Machine Learning Tools and development of a systematic series for battery-driven catamaran hull forms. Regression Trees (RT), Support Vector Machines (SVM), and Artificial Neural Network (ANN) regression models are applied for dataset training on developed systematic series of catamarans. A hullform optimization was implemented for various catamarans including dimensional and hull coefficient parameters based on resistance and structural weight reduction and battery performance improvement. This paper provides a diverse database of catamaran hullform. Hence, an automated Matlab program was coded for geometry generation and cost function evaluation. Design distribution based on Lackenby transformation fulfills all design space and sequentially a novel self-blending method reconstructs new hullforms based on two parents blending. Finally, a machine learning approach was conducted on generated data of case study. This study shows that ANN algorithm correlates well with the measured resistance. Accordingly, a general and unique tool is proposed for optimized and desired design in first design stage.

Hox gene clusters are crucial in Embryogenesis. It was observed that some Hox genes are located in order along the telomeric to centromeric direction of the DNA sequence: Hox1, Hox2, Hox3…. These genes are expressed in the same order in the ontogenetic units of the Drosophila embryo along the Anterior-Posterior axis. The two entities (genome and embryo) differ significantly in linear size and in-between distance. This strange phenomenon was named Spatial Collinearity (SP). Later, it was observed that, particularly in the Vertebrates, a Temporal Collinearity (TC) coexists: first is Hox1 expressed, later Hox2 and even later Hox3,…,. According to a Biophysical Model (BM), pulling forces act at the anterior end of the cluster while a cluster fastening applies at the posterior end. Hox clusters are irreversibly elongated along the force direction. During Evolution, the elongated Hox clusters are broken at variable lengths thus split clusters may be created. An Empirical Rule was formulated distinguishing development due to a complete Hox cluster from development due to split Hox clusters. BM can ‘explain’ this Empirical Rule. In a spontaneous mutation where the cluster fastening is dismantled, a minimal pulling force can automatically shift the cluster inside the Hox activation domain. This cluster translocation can probably explain the absence of Temporal Collinearity in Drosophila.