In 2015, the Self-Action Leadership Theory—a qualitative, nomological expansion of self-leadership theory rooted in atmospheric and astronomical metaphor aimed at expanding the personal freedom of individuals, organizations, and nations by bolstering the existential growth of individuals through a series of Maslow-esque stages of holistic, personal development. This article introduces an accompanying, practitioner-based Model of Self-Action Leadership (SAL) aimed at the implicit enhancement of a holistic range of administrative processes through explicit training, mentoring, and coaching in the model’s general and universally-applicable principles and practices. The SAL model produces an original construct of personal leadership practice that builds upon the extant self-leadership academic canon, which dates back to 1983 (Manz, 1983). It also provides an analogue to four of the five core processes of Project Management by positioning a self-action leader (an individual) as the ongoing “project” at hand. The SAL Model is rooted in action research and was developed through a variety of self-oriented, action research projects in conjunction with a comprehensive, qualitative, analytical autoethnographic study of a scholar’s life experiences.

In this paper, a new type of self-excited thermomechanical oscillator containing an oscillating shape memory alloy (SMA) filament with two symmetrically arranged spheres is investigated. The self-excitation of the oscillations is due to a heater of constant temperature, which causes periodic contractions of the filament when it approaches it. The contracted filament moves away from the heater a distance sufficient to cool it. Under the action of the weight of the spheres, the cooled filament re-approaches the heater, causing the above processes to repeat periodically. On the basis of experimental studies, approximating functions of the heater's heat field distribution are derived. A dynamic model of the oscillator has been created, in which the minor and major hysteresis in the SMA alloy and the distribution of the heat field around the heater have been taken into account. By numerical solutions of the differential equations, the laws of motion of the spheres are obtained. The displacements of the spheres in two perpendicular directions were measured using an experimental system. The obtained experimental results validate the proposed dynamic model and its assumptions with a high degree of confidence. Conclusions are drawn about the stochastic nature of the oscillations due to the hysteresis properties of the SMA and the temperature variation of the natural frequency of the oscillating system.

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 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.

Citizen science substantially contributes to large-scale biodiversity monitoring and the enhancement of public literacy. While both of the contributions largely depend on the public’s self- regulated learning. In this study, we employed a mix- method approach, incorporating both a questionnaire survey of 133 participants and interviews with 12 volunteers, aiming to explore the feature of self- regulated learning in citizen science, as well as identify the main factors impacting it. The volunteers are all different ages, from different jobs, with varying educational backgrounds. The findings revealed that the educational background of volunteers did not significantly impact their self-regulated learning. However, an increased frequency of participation was linked to higher levels of self-regulated learning. Furthermore, achievement goal orientation mediates the prediction of self-regulation by scientific epistemology. These insights underscore the importance of enhancing citizen science's impact on scientific literacy by fostering self-regulated learning among participants. This can be achieved through explicit instruction in scientific epistemology and by fostering a sense of achievement to boost achievement goal orientations. Additionally, our study advocates for the promotion of social interaction between students and out- of- school citizen scientists in school-based citizen science projects. The main innovation of this study is to consider volunteers as learners, not merely as contributors of data.

Background: Nursing services provided by nurses are based on knowledge and competence in the field of nursing science developed in accordance with Client needs, scientific developments, and the demands of globalization. These health services include nursing services that are carried out responsibly, accountably, with quality, and safely by nurses who have obtained registration and permission to practice. Nursepreneur is innovation and courage to take risks and is ready to work hard to achieve goals with optimism. Which has important components namely: 1) quality, 2) role, 3) option and success. The post-pandemic new world, especially in the health care system, continues to grapple with the demands of costs to provide patient care and safety. By using the application of the nursing theory model. Purpose :. Assessing scientific studies on the application of evidence-based intervention in wound care using nursing theory, identifying the important role of telenursing in improving nursing services in Nerspreneurship, Method: literature study Conclusion: Telenursing in nursing focuses on providing nursing care through information technology, such as telephone, computers, and the Internet that can be used to improve treatment outcomes among older people, especially those with low literacy skills and low financial status (Esmaeilpour-BandBoni et al., 2020). The statement from the results of the study refutes that Telenursing is intended for patients who have higher education and middle and upper economic states.

Using the culture-work-health model, this study investigates the factors influencing the quality of life of maritime workers. This study conducted a survey of 320 maritime workers who have experience living and working on a ship for more than six months. This self-administered questionnaire included questions on organizational culture and support, self-efficacy, perceived fatigue, as well as the quality of work life. Organizational culture and self-efficacy were identified as factors affecting the quality of work life, while organizational support was found to have an indirect effect after passing through self-efficacy and perceived fatigue. The final model accounts for 63.1% of the variance in maritime workers’ quality of life. As such, this study shows that self-efficacy is important for the quality of life of maritime workers, having both direct and indirect effects. Moreover, organizational support may prove the primary intervention point for relieving perceived fatigue and enhancing self-efficacy, thus improving the quality of work life.

Patients with heart failure have difficulty in self-care management, as daily monitoring and recognizing symptoms do not readily trigger an action to avoid hospital admissions. The purpose of this study was to understand the impact of a nurse-led complex intervention on symptom recognition and fluid restriction. A latent growth model was designed to estimate self-care management and quality of life changes on patients with heart failure and assessed by a pilot study, for three months, to sixty-three patients (33 control, 30 intervention). Patients in the control group had a higher risk of hospitalisation (IRR 11.36; p<.001) and emergency admission (IRR 4.24; p<.001) at three-months follow-up. Analysis of the time scores demonstrated that the intervention group had a clear improvement in self-care behaviours (βSlope. Assign-ment_group=-.881; p<.001) and in the quality of life (βSlope. Assignment_group=1.739; p<.001). This study supports that a nurse-led program on symptom recognition and fluid restriction can have a positive impact on self-care behaviours and quality of life in patients with heart failure.

Material selection for product design is a complex task. Thus, one of the objectives of this work is to analyze, understand and promote the importance of selection of materials to conceive quality products with help of designers' that promote green self-identity in the early stage of the conception of new products. A questionnaire was sent to professional designers and engineers. 38 responses were validated, this being the sample of our study. The aspects that influence the complex selection of materials and the final quality of the products through the design and production process is presented. As a result of the answers carried out with product designers who work in the market, with students who are graduating and with some engineers, a new approach for the selection of materials was developed. Based on a collection of main ideas from traditional and non-traditional methods of material selection, seeking to group the maximum requirements of both methods, inspired by the "Canvas" model on the basic modular methodology, a new model for a project of new product is presented. Our study focuses on the selection of materials, since this aspect is one of the most relevant steps in early stage of the prototyping phase of new products, with a view to reducing CO² from the air in the atmosphere that we all breathe. The classification of materials is complex, due to the diversity of available options. The novelty of this model is that all properties of the newly designed product, such as technical, aesthetic, productive, environmental and other properties, are all grouped in a model, which serves as an innovative support. Thus, the designer has at his disposal a tool that can help him in the selection of the best material for the products he designs. This study intends to make a contribution in the field of material selection, quality and design of new products, promoting a green self-identity for designers in the initial phase of product design. Consequently, all consumers in search of a sustainable planet will profit from it.

Self-organized criticality (SOC) is a universal mechanism for self-sustained critical behavior in large-scale systems evolving outside equilibrium. Our report explores a tentative link between SOC and Lagrangian field theory, with the long-term goal of bridging the gap between complex dynamics and the non-perturbative behavior of quantum fields.

In wireless sensor networks (WSNs), each sensor node can estimate the global parameter from the local data in distributed manner. This paper proposed a robust diffusion estimation algorithm based on minimum error entropy criterion with self-adjusting step-size, which are referred to as diffusion MEE-SAS (DMEE-SAS) algorithm. The DMEE-SAS algorithm has fast speed of convergence and is robust against non-Gaussian noise in the measurements. The detailed performance analysis of the DMEE-SAS algorithm is performed. By combining the DMEE-SAS with diffusion minimum error entropy (DMEE) algorithms, an Improving DMEE-SAS algorithm is proposed, in non-stationary environment where tracking is very important. The Improving DMEE-SAS algorithm can avoid insensitivity of the DMEE-SAS algorithm due to the small effective step-size near the optimal estimator, and obtain a fast convergence speed. Numerical simulations are given to verify the effectiveness and advantages of these proposed algorithms.

Background and Objective: Intimate relationships hold significant importance during emerging adulthood. This study aimed to investigate the critical determinants of perceived well-being in friendship relationships during emerging adulthood.Method: Using a quantitative approach, a sample of 726 undergraduate students from the Ferdowsi University of Mashhad were selected through convenience sampling. They completed the Interpersonal Behaviors Questionnaire (IBQ), the Compassionate and self-image goals scale (CSIGS), the Basic Need Satisfaction in Relationships Scale (BNS-RS), the Interpersonal Needs Questionnaire (INQ-10), Friendship Self-Regulation Questionnaire (SRQ-F), Interpersonal Behaviors Questionnaire-Self (IBQ-self), State Level Subjective Vitality Scale (SVS-SL), the Perceived Relationship Quality Component (PRQC), and the Basic Empathy Scale (BES). Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM).Results: The results indicated that the critical determinants in predicting perceived well-being in friendship relationships were, in order, goals in friendship relationships, friendship self-regulation, perceived support of basic psychological needs by friends, satisfied basic psychological needs, frustrated psychological needs, and supporting the basic psychological needs of friends.Conclusion: The findings demonstrate that self-determination theory (SDT) provides a coherent framework for explaining perceived well-being in friendships.

The goal of this work is to show that the underlying symmetries of effective field theory can be traced to the onset of self-similarity. In particular, we argue that the scale-free structure of fractal geometry lies at the heart of invariance principles in classical and Quantum Field Theory.

Self-assembly is a spontaneous process through which macroscopic structures are formed from basic microscopic constituents (e.g. molecules or colloids). By contrast, the formation of large biological molecules inside the cell (such as proteins or nucleic acids) is a process more akin to self-organization than to self-assembly, as it requires a constant supply of external energy. Recent studies have tried to merge self-assembly with self-organization by analyzing the assembly of self-propelled (or active) colloid-like particles whose motion is driven by a permanent source of energy. Here we present evidence that points to the fact that self-propulsion considerably enhances the assembly of polymers: self-propelled molecules are found to assemble into polymer-like structures, the average length of which increases towards a maximum as the self-propulsion force increases. Beyond this maximum, the average polymer length decreases due to the competition between bonding energy and disruptive forces that result from collisions. The assembly of active molecules might have promoted the formation of large pre-biotic polymers that could be the precursors of the informational polymers we observe nowadays.

Cyber Physical Systems (CPS) has been a popular research area in the last decade. The dependability of CPS is still a critical issue, and rare survey has been published in this domain. CPS is a dynamic complex system, which involves various multidisciplinary technologies. To avoid human error and to simplify management, self-management CPS (SCPS) is a wise choice. And to achieve dependable self-management, systematic solution is necessary to verify the design and to guarantee the safety of self-adaptation decision, as well as to maintain the health of SCPS. This survey first recalls the concepts of dependability, and proposes a generic environment-in-loop processing flow of self-management CPS, and then analyzes the error sources and challenges of self-management through the formal feedback flow. Focus on reducing the complexity, we first survey the self-adaptive architecture approaches and applied dependability means; then we introduce a hybrid multi-role self-adaptive architecture, and discuss the supporting technologies for dependable self-management at the architecture level. Focus on dependable environment-centered adaption, we investigate the verification and validation (V&V) methods for making safe self-adaptation decision and the solutions for processing decision dependably. For system-centered adaption, the comprehensive self-healing methods are summarized. Finally, we analyze the missing pieces of the technology puzzle and the future directions. In this survey, the technical trends for dependable CPS design and maintenance are discussed, an all-in-one solution is proposed to integrate these technologies and build a dependable organic SCPS. To the best of our knowledge, this is the first comprehensive survey on dependable SCPS building and evaluation.

The present paper reports an exact approach quantifying the electromagnetic contribution to the anomalous magnetic moment occurring in isolated system comprised of non-composite particle carrying elementary electric charge. Essential averaging procedure and regularization of the electromagnetic field potentials necessary when quantifying the electromagnetic self-interactions and when deriving equations of motion without singularities and obeying the conservation laws are thoroughly discussed. The study shows that the dynamics of the considered system is associated to unique classical transcendental equations of motion satisfied by the particle's velocity and the electromagnetic contribution to the anomalous $g$-factor known from the quantum electrodynamics. The equations of motion lead to an exact analytical expression for the anomalous $g$-factor that provides more accurate result than that calculated with the aid of quantum electrodynamics. It matches the experimentally measured value reported in the literature to a one part per trillion. We obtain a_e=0.00115965218000(65) thus reveling the potential of non-perturbative, non-probability methods in predicting the electron's anomalous g-factor.

Education is one of the most important tools available to policymakers and non-governmental bodies to promote a change in the behavior of society and to address the climate crisis, in line with the 4^th and 13^th Sustainable Development Goals of the United Nations 2030 Agenda. Project-based learning (PBL) addresses real and global challenges and allows the academic and professional formation of students. As part of the reflection stage of the educational action research method using the Business Canvas Model (BMC), pedagogic deficiencies were identified in the PBL and a didactic proposal was elaborated to emulate the interaction of students with the ecosystems of society. A prototype for improving the management of organic manures as soil amendments was initially developed, to provide the students with a quick start on the first steps of the proposed project. In the 10 sessions designed for the PBL (Make it happen!), the students elaborate a more sophisticated artifact in response to the demands of potential clients, as per the outcomes of the primary market research (5^th session). Active teaching methods and tools, such as a modified template of the BMC with the Rumsfeld’s matrix, aid the metacognition of students and their competences development. In a double session of the PBL, the primary market research is organized with key stakeholders of the agroindustry to enquire about the feasibility of the implementation of the technological solution and the logistics at farm level. Finally, the evaluation relies on the suitability of the upgraded prototype to respond customers’ demands.

Growing crystals of nickel niobate (NiNb2O6), we noticed that changing growth conditions allowed our material to enter different areas of the phase diagram. In particular, we found that excess material accumulated within and above the liquid zone. Analysis showed that this was an unincorporated constituent. Changing the ratio of the constituent oxides - an excess of ~4% of either NiO or Nb2O5 gave us the opportunity to investigate changes in zone stability, melting temperature and quality of the resulting crystal. We found that a small excess of nickel oxide decreases the melting temperature significantly, and created the best pseudo-rutile NiNb2O6 crystal studied, while higher amounts of niobium oxide allowed us to stabilize the NiNb2O6 columbite phase. This research reinforces the idea that self-flux as a travelling solvent can significantly impact crystal growth parameters and quality.

Purpose: To identify the impact of dealing with COVID-19 patients in clinical areas on nurses' professional self-concept and self-confidence. Background: Professional self-concept is considered a critical factor in the recruitment/retention process in nursing, nursing shortage, career satisfaction, and academic achievements. Professional self-confidence is also a crucial determinant in staff satisfaction, reducing turnover, and increasing work engagement. Design: Descriptive, comparative study. Methods: The study was conducted between February to May 2021 by utilizing a convenience sampling technique. A total of 170 nurses from two facilities were recruited from two COVID-19 and non-COVID-19 designated facilities. The level of professional self-concept and self-confidence was assessed by utilizing the Nurses' Self-Concept Instrument and Self-Confidence Scale. Results: The professional self-concept level among the exposed group to COVID-19 patients was lower than the comparison group, while the professional self-confidence level among the exposed group to COVID-19 patients was similar to the comparison group. On the other hand, the satisfied staff and those who received professional training in dealing with COVID-19 patients reported a higher level of professional self-concept. Conclusions: Dealing with COVID-19 patients has an impact on professional self-concept; the exposure group was lower than those who did not deal with COVID-19 patients, while the professional self-confidence level among the exposed group was similar to the comparison group. Getting professional training in dealing with COVID-19 patients and being satisfied at work were significant factors in improving the professional self-concept. Policymakers should create strategies that target the improvement of professional training in dealing with COVID-19 patients.

: BACKGROUND: The prevalence of smoking among students is a growing concern, particular-ly among medical students. Being associated with stress, competitiveness, and various social in-fluences, smoking can have detrimental effects on self-esteem and self-efficacy and may create a vicious cycle that may contribute to students’ well-being and academic performance out-comes.METHODS: A cross-sectional study on 456 medical students was conducted via an online survey using structured questionnaires on socio-demographic characteristics, smoking habits, nicotine dependence, self-esteem, and self-efficacy. RESULTS: The prevalence of smoking was 31.1% The scores of self-esteem and self-efficacy were positively correlated with smoking habits (W1=0.957, W2=0.975, P<0.05). Students presented rather low smoking addiction with male stu-dents having slightly higher scores than female students on self-esteem and self-efficacy, mili-tary students had higher self-esteem scores than civilians with physical activity having a posi-tive correlation with non-smoking behavior. CONCLUSION: According to our results, self-esteem and self-efficacy were slightly positively correlated with smoking habits. Furthermore, there was no statistically significant association between other social factors and smoking. Our results may develop a theoretical basis for medical students’ psychological variables studying for further implementation of university educational programs and preventive interventions em-powering students towards an overall better quality of life, addressing, among others, smoking behaviors.

Background: Student-specific stress is pervasive and impairs health and attainment. Experimentally induced self-affirmation can reduce stress, but little is known about the mechanisms underlying this effect, and the role of individual differences. The present study explores the relationship between spontaneous self-affirmation, student-specific stress, and overlapping constructs of positive self-regard during the COVID-19 pandemic. Methods: The study investigated inter-relationships between spontaneous self-affirmation, student-specific perceived stress and potential covariates including self-esteem, self-integrity and habitual positive self-thought. University students (N = 151) aged 18 to 50 responded to an online questionnaire including the Spontaneous Self-Affirmation Measure, College Student Stress Scale, Rosenberg Self-Esteem Scale, Habitual Index of Positive Thinking and Self-Integrity Scale. Results: Unexpectedly, regression analysis revealed that spontaneous self-affirmation was a positive predictor of student-specific stress, seemingly driven by relational affirmations. Self-esteem and habitual self-thought were negative predictors of student-specific stress, whilst self-integrity was not a predictor. Conclusions: Habitual positive self-thought may offer a sustainable solution to student-specific stress, but spontaneous self-affirmation does not. A reduction in defensive responses, elicitation of negative emotions, or use of conditional relationships in relational affirmation

Online education allows learners to develop knowledge and skills flexibly and conveniently—such observation among students whose characteristics involve student engagement, self-regulation, and self-efficacy. However, studies to characterize Filipino online learners seem lacking. Thus, this study aimed to characterize science education tertiary students in the Philippines concerning their online student engagement (OSE), self-regulated learning (SRL), and online learning self-efficacy (OLSE). The unprecedented events brought by COVID-19 pandemic also urged the implementation of online modalities while there is no available information on students’ online learning profiles. Hence, researchers used a survey research employed through ex post facto approach to determine the effects of the demographic profile on OSE, SRL, and OLSE. The survey was participated by N=373 respondents who answered the questionnaire with informed consent administered via Google Forms. Results revealed that OSE indicators moderately characterized students, while SRL and OLSE indicators are true of them, substantiated by the overall mean M=3.85(SD=0.90), M=3.86(SD=0.92), and M=3.14(SD=0.73), respectively. Also, multivariate tests showed no significant effect among the independent groups (p&gt;0.05), except for gender and OLSE interaction (p&lt;0.05) so, only in OLSE was a significant difference found in gender. In conclusion, Filipino online learners are moderate across aspects of student engagement, self-regulation, and self-efficacy.

While the desire to uncover the neural correlates of consciousness has taken numerous directions, self-face recognition has been a constant in attempts to isolate aspects of self-awareness. The neuroimaging revolution of the 1990’s bought about systematic attempts to isolate the underlying neural basis self-face recognition. These studies, including some of the first fMRI (functional Magnetic Resonance Imaging) studies, revealed a right hemisphere bias for self-face recognition in a diverse set of regions including the insula, the Dorsal Frontal Lobe, the Temporal Parietal Junction and Medial Temporal Cortex. Confirmation of these data (which are correlational) was provided by TMS (Transcranial Magnetic Stimulation) and patients in which direct inhibition or ablation of right hemisphere regions leads to a disruption or absence of self-face recognition. These data are consistent with a number of theories including a right hemisphere dominance for self-awareness and/or a right hemisphere specialization for identifying significant social relationships including to oneself.

Vitrimers are covalent network materials, comparable in structure to classical thermosets. Unlike normal thermosets, they possess a chemical bond swap mechanism that makes their structure dynamic and suitable for activated welding and even autonomous self-healing. The central question in designing such materials is the trade-off between autonomy and material stability: The swap mechanism facilitates the healing but it also facilitates creep, which makes the perfectly stable self-healing solid a hard goal to reach. Here, we address this question for the case of self-healing vitrimers made from star polymers. Using coarse-grained molecular dynamics simulations, we study the adhesion of two vitrimer samples and find that they bond together on timescales that are much shorter than the stress relaxation time. We show that the swap mechanism allows the star polymers to diffuse through the material through coordinated swap events, but the healing process is much faster and does not depend on this mobility.

In this paper, I propose a test for machine self-awareness inspired by the Turing test. While my test is plain and simple, it offers a much-needed alternative to ungrounded speculation while still capturing the essence of self-awareness. I discuss how to apply the test to Large Language Models and conduct experiments on GPT-3.5 that suggest it is not self-aware. I discuss the implications of machine self-awareness and relate it to questions about meaning and understanding. Finally, I present some next steps for studying self-awareness in machines.

Secure attachment, developed through consistent relationships with attachment figures in childhood, is a crucial factor in fostering healthy interpersonal relationships and a positive self-perception. This research aimed to assess how perceived security, as an indicator of secure attachment, predicts adult self-concept through the mediating effects of resilience and positive self-esteem. A quantitative, cross-sectional, and non-probabilistic study was conducted with 383 participants, of whom 76.2% were females, aged between 17 and 86 years (M = 28.52, SD = 12.23). Correlational analyses revealed significant positive associations between perceived security, self-concept, resilience, and positive self-esteem. Path analysis demonstrated that resilience and positive self-esteem sequentially mediate the relationship between perceived security during childhood and adult self-concept (Total Effect R2 = .34, F(1,381) = 193, p < .001; Indirect effect of sequential mediation b = .02, CI 95% [.01, .04]). Findings suggest that the ability to cope with ad-versity and personal acceptance underlie the impact of perceived security on self-concept. It is recommended to promote not only secure attachment in family interventions but also resilience and self-esteem in programs targeting adolescents, youth, and adults.

Since the emergence of the quantified self movement, users aim at health behavior change, but only those who are sufficiently motivated and competent with the tools will succeed. Our literature review shows that theoretical models for quantified self exist but they are too abstract to guide the design of effective user support systems. Here, we propose principles linking theory and implementation to arrive at a hierarchical model for an adaptable and personalized self-quantification system for physical activity support. We show that such a modeling approach should include a multi-factors user model (activity, context, personality, motivation), a hierarchy of multiple time scales (week, day, hour), and a multi-criteria decision analysis (user activity preference, user measured activity, external parameters). This theoretical groundwork, which should facilitate the design of more effective solutions, has now to be validated by further empirical research.

This article presents a self balanced multistage DC-DC step-up converter for photovoltaic applications. Proposed converter topology is designed for unidirectional power transfer and provides a doable solution for photovoltaic applications where voltage is required to be stepped up without magnetic components (Transformer-less and Inductor-less). The output voltage obtained from renewable sources will be low and must be stepped up by using a DC-DC converter for photovoltaic applications. K diodes and K capacitors along with two semiconductor control switch are used in the K-stage proposed converter to obtain an output voltage which is (K+1) times the input voltage. The conspicuous features of proposed topology are i) Magnetic components free (Transformer-less and Inductor-less). ii) Continuous input current iii) Low voltage rating semiconductor devices and capacitors iv) Modularity v) Easy to add a higher number of levels to increase voltage gain vi) Only two control switches with alternating operation and simple control. The proposed converter is compared with recent existing transformer-less and Inductor-less power converter in term of voltage gain, number of devices and cost. The application of proposed circuit is discussed in detail. The proposed converter has been designed with rated power of 60W, input voltage is 24V, output voltage is 100V and switching frequency is 100 kHz. The performance of the converter is verified through experimental and simulation results.

Social media and other web 2.0 tools have provided users the platform to interact and also disclose personal information not only with their friends and acquaintances, but also with relative strangers with unprecedented ease. This has enhanced the ability of people to share more about themselves, their families, and their friends through a variety of media including text, photo, and video, thus developing and sustaining social and business relationships. The purpose of the paper is to identify the factors that predict self-disclosure on social networking sites within the Ghanaian context. Data was collected from 452 students in three leading universities in Ghana and analyzed with Partial Least Square-Structural Equation Modeling. Results from the study revealed that all variables in the proposed model with the exception of interaction and perceived control were significant predictors of self-disclosure with privacy risk being the most significant predictor. In all, the model accounted for 54.6 percent of the variance in self disclosure. The implications and limitations of the current study are discussed and directions for future research proposed.

Background and Objectives: Although there has been growing interest in the association of ADHD with anxiety, depression, suicidal ideation, and self-esteem, there is a lack of consistent results and these associations remain unclear. This study investigated the differential patterns of anxiety, depression, suicidal ideation, and self-esteem with regard to the presence of ADHD. Materials and Methods: The subjects were divided into a patient group and a control group. The patient group included 49 patients diagnosed with ADHD at the department of psychiatry of one university hospital. For the control group, 3,727 students were invited to complete a questionnaire. Of the 1,717 students who responded to the questionnaire, 245 were selected for patient-controlled studies. All the subjects were instructed to complete the Beck Suicide Ideation Scale, Children's Depression Inventory, Beck’s Depression Inventory, State-Trait Anxiety Inventory, and Rosenberg Self-Esteem Scale. Results: ADHD subjects experienced more anxiety, depression, and suicidal ideation as well as lower self-esteem compared to the control group comprising participants without ADHD. Conclusions: These findings suggest that ADHD symptoms may contribute to greater suicidal ideation through experienced depression, anxiety, and low self-esteem in school-aged children. Therefore, appropriate ADHD symptom management is necessary to reduce suicidal ideation among school-aged children with ADHD symptoms.

In this paper I tentatively answer 50 questions sampled from a pool of over 10,000 weekly questions formulated by students in a course entitled “The Self”. The questions pertain to various key topics about self-processes, such as self-awareness, self-knowledge, self-regulation, self-talk, self-esteem, and self-regulation. The students’ weekly questions and their answers highlight what is currently know about the self. Answers to the student questions also allow for the identification of some recurrent lessons about the self. Some of these lessons include: all self-processes are interconnected (e.g., prospection depends on autobiography), self-terms must be properly defined (e.g., self-rumination and worry are not the same), inner speech plays an important role in self-processes, controversies are numerous (are animals self-aware?), measurement issues abound (e.g., self-reflection as an operationalization of self-awareness), deficits in some self-processes can have devastating effects (e.g., self-regulatory deficits may lead to financial problems), and there are lots of unknowns about the self (e.g., gender differences in Theory-of-Mind).

In recent years, the individualized demand of customers brings small batches and diversification of orders towards enterprises. The application of enabling technologies in factory, such as the Industrial Internet of Things (IIoT) and Cloud Manufacturing (CMfg), enhances the ability of customer requirement automatic elicitation and the manufacturing process control. The job shop scheduling problem with random job arrival time dramatically increases the difficulty in process management. Thus, how to collaboratively schedule the production and logistics resources in the shop floor is very challenging, and it has a fundamental and practical significance of achieving the competitiveness for an enterprise. To address this issue, the real-time model of production and logistics resources is built firstly. Then, the task entropy model is built based on the task information. Finally, the real-time self-adaption collaboration of production and logistics resources is realized. The proposed algorithm is carried out based on a practical case to evaluate its effectiveness. Experimental results show that our proposed algorithm outperforms three existing algorithms.

The research aims to examine the extent to which the perceived organizational support (POS) predicted career related self and environmental exploration via the mediation effect of career adaptability. Multi-group comparisons based on the gender, majors and places of origin were also performed to evaluate the differences among these variables. An internet survey was conducted to collect empirical data from 611 Chinese undergraduates. Structural equation modeling (SEM) was conducted to demonstrate the proposed relations in the model and multiple group analysis. Clearly supported was the direct relations between POS and career related self and environmental exploration and the mediation effect of career adaptability. The results also showed that gender and major are the moderating variables for the proposed model, and no significance difference among the rural and urban subgroups was found. POS could be effectively delivered to students in general, marginalized social groups, such as females and those majored in the humanities and social sciences in particular. Four dimensions of career adaptability (concern, control, curiosity and confidence) could also be targeted at in order to promote students’ sustainable employment. The findings provide a better understanding of the career construction model by incorporating the contextual factor in a collective cultural environment.

Recent simulation studies have revealed a wealth of distinct crystal polymorphs encountered in the self-organization of polymer systems driven by entropy or free energy. The present analysis, based on the concept of self-avoiding random walks on crystal lattices, is useful to calculate upper bounds for the entropy difference of the crystals that are formed during polymer crystallization and thus provide predictions on polymorph thermodynamic stability. Here, we compare two pairs of crystals sharing the same coordination number, ncoord: hexagonal close packed (HCP) and face centered cubic (FCC), both having ncoord = 12 and the same packing density, and the less dense hexagonal (HEX) and body centered cubic (BCC) lattices, with ncoord = 8. In both cases, once a critical step length is reached, one of the crystals shows a higher number of SAWs compatible with the crystal. We explain the observed trends in terms of the bending and torsion angles corresponding to the different chain geometry as imposed by the geometric constraints of the crystal lattice.

Climate change, one of the severest environmental threats to humankind, disproportionately affects low-income developing countries in the global South. Having no feasible mitigation alternatives, these countries resort to adaptation efforts in addressing the climate perturbations. Climate change adaptation (or resilience) is primarily a localized course of action that depends on individuals, social networks, economies, ecologies, political structures, and the capabilities of all those to work collectively to absorb, learn from and transform in the face of new realities. With a view to controlling the floods that shattered the life and economy of the then East Pakistan, which is Bangladesh now, during the mid-twentieth century, the coastal embankment project (CEP) was instituted as an adaptation strategy to natural disasters in southwestern Bangladesh. Based on the qualitative analysis of primary and secondary data, this paper seeks to critically evaluate the efficacy of the CEP in terms of the space for feasible action and ecological modernization. The findings of this research indicate that the CEP has become an unrealistic venture that hinders the growing economic activity of shrimp aquaculture in the area. This paper is expected to contribute to generate further theoretical and empirical discourse on evaluating similar development projects around the globe.

In this work, we develop a self-consistent physical model of bubbles in a gas solid two-phase flow. Using the Peng-Robonson state equation and a detailed specific heat ratio equation of bubbles, we obtain the kinetic equations of the bubbles on the basis of the Ergun equation, thermodynamic equations, and kinetic equations. It is found that the specific heat ratio of bubbles in such systems strongly depends on bubble pressures and temperatures, which play an important role in the characteristics of the bubbles. The theoretical studies show that with increasing height in the systems, the gas flow rate shows a downward trend. Moreover, the larger particles in the gas solid flows are, the greater the gas velocity is. The bubble sizes increase with the increasing heights of the gas solid systems, and then decrease. The bubble velocity is affected by the gas velocity and the bubble size, which gradually increase and eventually quasi-stabilize. This shows that gas and solid phases in a gas solid two-phase flow interact with each other and a self-consistent system comes into being. The theoretical results have exhibited important value as a guide for understanding the properties and effects of bubbles in gas solid two-phase flows.

The main consequence of radiation damage on a Silicon-Photomultiplier (SiPM) is a significant increase in the dark current. If the SiPM is not adequately cooled, the power dissipation causes it to heat up, which in turn affects its performance based on the temperature. In order to investigate this heating effect, experiments were carried out using a KETEK SiPM glued on an Al2O3 substrate, as well as HPK SiPMs that were either glued onto an Al2O3 substrate or a flexible PCB. The assemblies were connected either directly to a temperature-controlled chuck on a probe station or through layers of materials with well-defined thermal resistance. A DC-mode LED was used to illuminate the SiPM, and the resulting SiPM current was measured to determine the steady-state temperature. This temperature depended on the power dissipated in the multiplication region of the SiPM and the thermal resistance. This information can be utilized to adjust the SiPMs working point, taking into account the effects of self-heating. Similarly, this approach can be applied to packaged SiPMs that have an unknown thermal contact to a heat sink.

This article is a scoping review analyzing advances in experimental studies on bacterial self-healing of concrete. From Scopus, ScienceDirect, Web of Science and Google Scholar search engine databases, 54 studies were selected for analysis, and an increasing trend of publications since 2015 was found, with India as the country with the largest research presence. Different ma-terials are used as replacement or admixture in concrete, such as fibers, particles and recycled material from construction waste. It was found that the most commonly used bacteria are Bacillus subtilis and Bacillus sphaericus, which can improve the strength of concrete by generating calcite and sealing cracks. In addition, it was found that the presence of materials such as fibers, ashes and construction recyclates can protect bacteria in an alkaline environment. The designs usually in-clude more than two experimental groups and a control. In summary, this study highlights the importance of bacterial self-healing in concrete and provides information on advances in this field of research.

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.

Self-organized criticality (SOC) is a celebrated paradigm from the 90’s for understanding dynamical systems naturally driven to its critical point, where the power-law dynamics taking place make predictions practically impossible, such as in stock prices, earthquakes, pandemics and many other problems in science related to phase transitions. Shortly thereafter, it was realized that traffic flow might be in the SOC category, implying that conventional traffic management strategies seeking to maximize the local flows can become detrimental. This paper shows that the Kinematic Wave model with triangular fundamental diagram, and many other related traffic models, indeed exhibit SOC, thanks in part to the fractal nature of traffic exposed here on the one hand, and our need to get to our destinations as soon as possible, on the other hand. Important implications for congestion management of traffic near the critical region are discussed, such as: (i) Jam sizes obey a power-law distribution with exponent 1/2, implying that both its mean and variance become ill-defined and therefore impossible to estimate. (ii) Traffic in the critical region is chaotic in the sense that predictions becomes extremely sensitive to initial conditions. (iii) However, aggregate measures of performance such as delays and average speeds are not heavy tailed, and can be characterized exactly by different scalings of the Airy distribution, (iv) Traffic state time-space “heat maps” are self-affine fractals where the basic unit is a triangle, in the shape of the fundamental diagram, containing 3 traffic states: voids, capacity and jams. This fractal nature of traffic flow calls for analysis methods currently not used in our field.

This paper proposes a multifractal model, with the aim of providing a possible explanation for the locality phenomenon that appears in the estimation of the Hurst exponent in stationary second order temporal series representing self-similar traffic flows in current high-speed computer networks. It is shown analytically that this phenomenon occurs if the network flow consists of several components with different Hurst exponents.

Partial differential representation of self-similarity feature has been derived from notion of the homogenous function in general sense. This representation allows consideration of stochastic self-similar systems. As well as the partial differential representation allows consideration of Stochastic Partial Differential Equation.

Living organisms are active open systems far from thermodynamic equilibrium. The ability to behave actively corresponds to dynamical metastability: minor but supercritical internal or external effects may trigger major substantial actions such as gross mechanical motion, dissipating internally accumulated energy reserves. Gaining selective advantage from beneficial use of activity requires a consistent combination of sensual perception, memorised experience, statistical or causal prediction models, and resulting favourable decisions on actions. This information processing chain originated from mere physical interaction processes prior to life, here denoted as structural information exchange. From there, the self-organised transition to symbolic information processing marks the beginning of life, evolving by novel purposivity of trial-and-error feedback and accumulation of symbolic information. The emergence of symbols and prediction models can be described as a ritualisation transition, a symmetry-breaking kinetic phase transition of the 2^nd kind previously known from behavioural biology. The related new symmetry is the neutrally stable arbitrariness, conventionality or code invariance of symbols with respect to their meaning. The meaning of such symbols is given by the structural effect they ultimately unleash, directly or indirectly, by deciding on which actions to take. The early genetic code represents the first symbols. The genetically inherited symbolic information is the first prediction model for activities sufficient for survival under the condition of environmental continuity, sometimes understood as a “final causality” property of the model.

Background: The adoption of self-care behaviors among patients with arterial hypertension (AH) plays an important role in the management of their health condition. However, a lack of scales assessing self-care is observed. We aimed to develop and validate the Hippocratic hypertension self-care scale. Methods: From a pool of questions derived from a literature review, 18 items were included in the scale and reviewed by a committee of experts. Participants indicate the frequency at which they follow the self-behavior prescribed in each statement on a five-point Likert scale. Data were collected between April 2019 and December 2019. Re-sults: 202 consecutive adult patients with AH were enrolled in the study. The internal consistency of the scale was found to be 0.807, using Cronbach’s alpha coefficient. An exploratory factor analysis identified two do-mains that accounted for 92.94% of the variance of the scale items; however, each sub-scale could not be used as an independent scale. Finally, the test- retest of the scale showed a significant strong correlation (r=0.0095, p<0.001). Conclusion: Our data indicate that the scale is a reliable and valid tool for assessing self-behaviors in patients with AH. Health professionals can use it in their clinical practice to improve the management of patients’ health condition.

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: Indonesia is an archipelago with various cultured, will bee affects all aspects of people's lives, including beliefs related to health behavior and health care. One problem that needs serious attention is the elderly group because the elderly are a vulnerable group who have a high risk of experiencing health problems, such as anemia with hypertension, so they need good care management. The research objective was to determine self-management intervention for hypertensive elderly. Methods: This research is a literature review with five databases (Scopus, CINAHL, ScienceDirect, PubMed, Proquest), the study design used is an experimental, descriptive, cross-sectional, and review systematic, in March 2021. Guidelines for using JBI to measure quality and listing check out Prisma in this review guide. A feasibility study based on title, abstract, full text, and research methodology. The data analysis used narrative analysis based on the research findings. Results: Twelve articles met the predefined review inclusion criteria. The study found eight interventions for self-management in elderly hypertension, namely: 1) Knowledge of hypertension, 2) Regulation of physical activity, 3) Limitation of alcohol and cigarette consumption, 4) Sleep rest and stress management, 5) Diet and body weight management, 6) Blood pressure control, 7) Family and social support, 8) Adherence to therapy regimens. Conclusion: The conclusion of the study results obtained eight elderly self-management interventions, this done properly will affect compliance in optimizing the health of the elderly.

Anomaly detection and segmentation aim at distinguishing abnormal images from normal images and further localizing the anomalous regions. Feature reconstruction based method has become one of the mainstream methods for this task. This kind of method has two assumptions: (1) The features extracted by neural network is a good representation of the image. (2) The autoencoder solely trained on the features of normal images cannot reconstruct the features of anomalous regions well. But these two assumptions are hard to meet. In this paper, we propose a new anomaly segmentation method based on feature reconstruction. Our approach mainly consists of two parts: (1) We use a pretrained vision transformer (ViT) to extract the features of the input image. (2) We design a self-attention autoencoder to reconstruct the features. We regard that the self-attention operation which has a global receptive field is beneficial to the methods based on feature reconstruction both in feature extraction and reconstruction. The experiments show that our method outperforms the state-of-the-art approaches for anomaly segmentation on the MVTec dataset. It is both effective and time-efficient.

The first group to build artificial general intelligence or AGI stands to gain a significant strategic and market advantage over competitors, so companies, universities, militaries, and other actors have strong incentives to race to build AGI first. An AGI race would be dangerous, though, because it would prioritize capabilities over safety and increase the risk of existential catastrophe. A self-regulatory organization (SRO) for AGI may be able to change incentives to favor safety over capabilities and encourage cooperation rather than racing.

The research proposes a self-directed paradigm with self-design using the existing technology with LMS modules, discussions, and self-tests. The research establishes its criteria for assurance of teaching and learning known as 7x2C for the compliance of content, and appearance along with other criteria for the analysis. The above technology of web and LMS is tested for a business course that is technology-oriented in creating an experiential learning system for Covid-19 awareness. Similarly, among other ideas, an environment for educating learners about diabetes and obesity has been designed. The project is known as Sunchoke with its theme of Grow, Eat, and Heal. The educators can use their technology and apply self-directed pedagogy to transform this approach to their customized ways by using their content and rubrics.

Advanced coatings are essential to modern technologies, as they optimise surface characteristics for different application scenarios. Transparent and self-cleaning coatings are increasingly used as protective coatings for various applications, such as foldable touchscreens, windows, and solar panels. Moreover, incorporating other functionalities such as high hardness, wear resistance, and flexibility into transparent and self-cleaning coatings is important for broadening the use cases. Although many kinds of multifunctional coatings have been developed, it is still difficult to embody several properties in one coating adequately, as some properties, such as hardness and flexibility, are inherently contrastive. This review first describes basic principles, including wetting ability, photocatalytic reactions, photo-induced hydrophilic phenomena, and the implication of self-cleaning. The desired properties of multifunctional coatings are then listed, and methods for evaluating different properties are used. Recent progress in various preparation methods for multifunctional coatings, including the sol-gel, dip/spin, and chemical vapour deposition (CVD) methods, are also presented. Magnetron sputtering (MS) technology is widely used in coating preparation. Compared with chemosynthesis and CVD, MS is time-saving, suitable for industrial production, and environmentally friendly. Coatings prepared by MS usually possess excellent mechanical properties. Thus, we highlight the current research status of MS technology in multifunctional coating preparation. Moreover, according to the multilayer design structure of coatings, their optical and mechanical properties and self-cleaning ability can be controlled by combining the characteristics of different materials. Finally, combining photocatalytic materials such as TiO2 with other materials through a multilayer structure to obtain a multifunctional coating with excellent overall properties is discussed.

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.

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.

Health self-tracking is an ongoing trend as software and hardware evolve, making the collection of personal data not only fun for users but also increasingly interesting for public health research. In a quantitative approach we studied German health self-trackers (N=919) for differences in their data disclosure behavior by comparing data showing and sharing behavior among peers and their willingness to donate data to research. In addition, we examined user characteristics that may positively influence willingness to make the self-tracked data available to research and propose a framework for structuring research related to self-measurement. Results show that users' willingness to disclose data as a "donation" more than doubled compared to their "sharing" behavior (willingness to donate= 4.5/10; sharing frequency= 2.09/10). Younger men (up to 34 years), who record their vital signs daily, are less concerned about privacy, regularly donate money, and share their data with third parties because they want to receive feedback, are most likely to donate data to research and are thus a promising target audience for health data donation appeals. The paper adds to qualitative accounts of self-tracking but also engages with discussions around data sharing and privacy.

Background: The adoption of self-care behaviors among patients with congestive heart failure (CHF) is essential for the management of their health condition. However, there is a lack of tools for estimating self-care in CHF patients. We aim to develop and validate the Hippocratic heart failure self-care scale (HHFSCS). Methods: the scale includes 22 items which are reviewed by a committee of experts. Individuals indicate the frequency at which they follow each self-behavior on a five-point Likert scale. Adult patients with CHF (n=250) from a General Hospital, in Athens, were participated in the study from June 2020 to March 2021. Reliability coefficients and Explanatory Factor Analysis (EFA), using a Varimax rotation and the Principal Components Method were used to assess the psychometric measurements. Results: The Cronbach’s alpha coefficient of the HHFSCS was 0.807. The exploratory factor analysis identified two domains that accounted for 88.44% of the variance of the scale items; however, each sub-scale could not be used as an independent scale. Finally, the test-retest showed a significant strong correlation (r=0.973, p&lt;0.001). Conclusions: The HHFSCS is a reliable and valid tool for assessing self-behaviors in CHF patients. Health professionals can use it in their clinical practice to improve the management of patient’s health conditions.

The main objective of this work is the design and implementation of self-adaptive capabilities in wireless sensors by applying control engineering and model-based design methodologies. It has been addressed the problem related to the changes in the flow of data packets through the network connection and the excess energy consumption that this causes in these devices. To design the solution, a systemic characterization of the scheduling and execution process of embedded tasks on the device has been carried out. This means defining cause-effect relationships in the system and its modelling theoretically and/or experimentally. In turn, these models facilitate the design of control strategies to improve the dynamic behavior of the system. As a solution, a self-adaptation strategy based on feedforward control algorithm has been designed and developed, which has been applied to improve the dynamic behavior and resource consumption. The developed solution has been satisfactorily evaluated experimentally.

Building on the Sustainable Happiness Model, this study examined how congruency between ideal self-image and brand image influence a sense of happiness. The findings show that when ideal self-image and ideal social self-image are congruent with brand image a sense of happiness can be enhanced through brand identification and positive emotions. This study contributes to literature as it reveals the mechanism of how congruency between ideal self-image and brand image positively affect happiness.

In swarm-robotics foraging, the purpose of task allocation is to adjust the number of active foraging robots dynamically based on the task demands and changing environment. It is a difficult challenge to generate self-organized foraging behavior in which each robot can adapt to environmental changes. To complete the foraging task efficiently, this paper presents a novel self-organized task allocation strategy known as the dynamic response threshold model (DRTM). To adjust the behavior of the active foraging robots, the proposed DRTM newly introduces the traffic flow density, which can be used to evaluate the robot density. First, the traffic flow density and the amount of obstacle avoidance are used to adjust the threshold which determines the tendency of a robot to respond to a stimulus in the environment. Then, each individual robot uses the threshold and external stimulus to calculate the foraging probability that determines whether or not to go foraging. Simulation and physical experiments are carried out to evaluate the performance of the proposed method. The experimental results show that the DRTM is superior to and more efficient than the adaptive response threshold model (ARTM) in swarm foraging.

This study addresses the critical challenge of Speech Enhancement (SE) in noisy environments, where the deployment of Deep Neural Networksolutions on microcontrollers is hindered by their extensive computational demands. Focusing on this gap, our research introduces a novel SE method optimized for MCUs, employing a 2-layer GRU model that capitalizes on perceptual speech properties and innovative training methodologies. By incorporating self-reference signals and a dual strategy of compression and recovery based on the Mel scale, we develop an efficient model tailored for low-latency applications. Our GRU-2L-128 model demonstrates a significant reduction in size and computational requirements, achieving a 14.2× decrease in model size and a 409.1× reduction in operations compared to traditional DNN methods like DCCRN, without compromising performance. This advancement offers a promising solution for enhancing speech intelligibility in resource-constrained devices, marking a pivotal step in SE research and application.

Dementia is a public health priority, in which memory impairments are prevalent and affects an individual’s daily activities. Research has tried to find ways to support memory problems of individuals with dementia. Self reference effect (SRE) has been shown to benefit memory in healthy, non-dementia group. The study aimed to investigate if SRE will improve memory performance of individuals with dementia. We used ecologically valid Ownership Procedure and the Remember/Know Paradigm to examine the Self-Reference Effect (SRE) on memory. It was hypothesised that participants living with dementia will perform differently in the recall of items that were self-referentially encoded compared to items other-referentially encoded and that the memory will be different in control participants than in those that live with dementia. The research found that self-referential processes did not have effect on memory in individuals with dementia. We suggest that impaired self-awareness may have contributed to the lack of this effect. However, we had a small sample size and these findings should be treated with caution.

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.

The Photovoltaic modules are usually installed on the ground which exposes it to surface deposition of foreign particles. In the Middle East and North Africa region, the primary culprit is dust and sand. They form an insulating and opaque layer on the surface of the glass, which obstructs its heat transfer and optical properties, thereby reducing the overall yield efficiency of the solar panel. Cleaning of this layer is critical to the operation of the solar panel and often requires great effort and energy on a large-scale solar array. In this paper, we propose a novel self-cleaning mechanism for solar panels, with an understanding of the structural integrity of the Photovoltaic laminate and application of external mechanical vibration. By applying an external source of vibration, the solar panels vibrate, excites its fundamental frequencies and cleans by its own. The method is analyzed using finite element analysis method and tested using experiments. Our simulation results based on IEC 61215 show that the maximum principal stress and deformation in the critical layers is within limits. Our experimental results prove the proposed theory is feasible and can be extended to large scale solar arrays. Our proposed method is retrofittable and could save money, energy and effort in cleaning the solar arrays, which can replace current techniques.

This paper proposes a Grouped Contrastive Learning of self-supervised Sentence Representation (GCLSR), which can learn an effective and meaningful representation of sentences. Previous works maximize the similarity between two vectors to be the objective of contrastive learning, suffering from the high-dimensionality of the vectors. In addition, most previous works have adopted discrete data augmentation to obtain positive samples and directly employed contrastive framework of computer vision to perform contrastive training, which could hamper contrastive training because text data is discrete and sparse compared with image data. To address those issues, we propose a grouped contrastive learning framework, i.e., GCLSR, which divides the high-dimensional feature vector into several groups and respectively computes the groups’ contrastive losses to make use of more local information, eventually obtaining a more fine-grained sentence representation. In addition, in GCLSR, we design a new self-attention mechanism and a continuous as well as partial word vector augmentation (PWVA). For the discrete and sparse text data, the usage of self-attention could help model focus the informative words by measuring the importance of every word in a sentence. By using the PWVA, GCLSR can obtain high-quality positive samples used for contrastive learning. Experimental results demonstrate that our proposed GCLSR achieves an encouraging result on the challenging datasets of the standard semantic textual similarity (STS) task and transfer task.

We develop an optimized force-field for poly(3-hexylthiophene) (P3HT) and demonstrate its utility for predicting thermodynamic self-assembly. In particular, we consider short oligomer chains, model electrostatics and solvent implicitly, and coarsely model solvent evaporation. We quantify the performance of our model to determine what the optimal system sizes are for exploring self-assembly at combinations of state variables. We perform molecular dynamics simulations to predict the self-assembly of P3HT at ~350 combinations of temperature and solvent quality. Our structural calculations predict that the highest degrees of order are obtained with good solvents just below the melting temperature. We find our model produces the most accurate structural predictions to date, as measured by agreement with grazing incident X-ray scattering experiments.

Self-enhancement (SE) is often overlooked as a fundamental cognitive ability mediated via the Pre-Frontal Cortex (PFC). Here we present research that establishes the relationship between the PFC, SE, and the potential evolved beneficial mechanisms. Specifically, we believe there is now enough evidence to speculate that SE exists to provide significant benefits and should be considered a normal aspect of the self. Whatever the metabolic or social cost, the upside of SE is great enough that it is a core and fundamental psychological construct. Furthermore, though entirely theoretical, we suggest that a critical reason the PFC has evolved so significantly in Homo sapien is to, in part, sustain SE. We therefore elaborate as to its proximate and ultimate mechanisms.

This review will explore the four major pillars required for design and development of an saRNA vaccine: antigen design, vector design, non-viral delivery systems, and manufacturing (both saRNA and lipid nanoparticles (LNP)). In will report on the major innovations, preclinical and clinical data reported in the last five years and will discuss future prospects.

Chitosan is a cationic polysaccharide usually obtained by alkaline deacetylation of chitin poly(N-acetylglucosamine). It is biocompatible, biodegradable, mucoadhesive and non-toxic. These excellent biological properties make chitosan a good candidate for a platform in developing drug delivery systems having improved biodistribution, increased specificity and sensitivity, and reduced pharmacological toxicity. In particular, chitosan nanoparticles are found to be appropriate for non-invasive routes of drug administration: oral, nasal, pulmonary and ocular routes. These applications are facilitated by the absorption-enhancing effect of chitosan. Many procedures for obtaining chitosan nanoparticles have been proposed. Particularly, the introduction of hydrophobic moieties into chitosan molecules by grafting to generate a hydrophobic-hydrophilic balance promoting self-assembly is a current and appealing approach. The grafting agent can be a hydrophobic moiety forming micelles that can entrap lipophilic drugs or it can be the drug itself. Another suitable way to generate self-assembled chitosan nanoparticles is through the formation of polyelectrolyte complexes with polyanions. This paper reviews the main approaches for preparing chitosan nanoparticles by self-assembly through both procedures and illustrates the state of the art of their application in drug delivery.

Many researches have identified that adverse childhood experiences (ACEs) are associated with non-suicidal self-injury (NSSI) and suicidality. However, most studies have been restricted to a few types of ACEs. This study aims to investigate associations of 13 common types of ACEs with NSSI, suicidal ideation (SI) and suicide attempt (SA), as well as the mediation of depressive and anxiety symptoms therein. A total of 1771 students aged 11-16 years who participated in the baseline survey of the Chinese Adolescent Health Growth Cohort study were included for the analysis. ACEs, SI, SA, depressive and anxiety symptoms were recorded by standard questionnaire. Of included participants, 92.0% reported one or more category of ACEs. Smoking, parent-child separation, emotional abuse, physical abuse and being bullied were positively associated with NSSI, with the adjusted odds ratio (aOR) of 2.41(95%CI, 1.01-5.75), 1.80(1.28-2.54), 1.69(1.21-2.37), 2.08(1.44-3.01) and 1.87(1.35-2.59), respectively; smoking (4.03, 1.66-9.81), parent-child separation (1.42, 1.07-1.90), emotional abuse (1.91, 1.41-2.59), physical abuse (1.80, 1.27-2.57), emotional neglect (1.78, 1.28-2.49) and being bullied (2.08, 1.54-2.81) were positively associated with SI; smoking(4.30, 1.67-11.10), emotional abuse (2.42, 1.58-3.72) and being bullied (1.75, 1.17-2.60) were positively associated with SA. The associations of ACEs with NSSI, SI and SA were each partially or completely mediated through depressive and anxiety symptoms. Children and adolescents who had experiences of smoking, physical abuse and being bullied during childhood are consistently and independently associated with NSSI and suicidality, and these associations may be largely mediated through depressive and anxiety symptoms.

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.

Our brains process information using a layered hierarchical network architecture, with abundant connections within each layer and sparse long-range connections between layers. As these long-range connections are mostly unchanged after development, each layer has to locally self-organize in response to new inputs to enable information routing between the sparse in- and output connections. Here we demonstrate that this can be achieved by a well-established model of cortical self-organization based on a well-orchestrated interplay between several plasticity processes. After this self-organization, stimuli conveyed by sparse inputs can be rapidly read out from a layer using only very few long-range connections. To achieve this information routing, the neurons that are stimulated form feed-forward projections into the unstimulated parts of the same layer and get more neurons to represent the stimulus. Hereby, the plasticity processes ensure that each neuron only receives projections from and responds to only one stimulus such that the network is partitioned into parts with different preferred stimuli. Along this line, we show that the relation between the network activity and connectivity self-organizes to a biologically plausible regime. Finally, we argue how the emerging connectivity may minimize the metabolic cost for maintaining a network structure under the above described constraints.

The restrictions imposed by the Covid-19 pandemic left many older adults isolated and confined. Under active aging theory, self-management is crucial for well-being among older adults coping with aging. The current study examines how (a) initial self-management, and (b) changes in self-management due to independent physical training, affect psychological outcomes in a sample of care home residents following outbreak of the pandemic. 64 older adults (53 females, 11 males), mean age is 82.23, reported on their self-management abilities, then embarked on six months of training in chair exercises (one session per week). The training exercises were halted after 22 sessions due to the pandemic, but some residents continued to practice independently. Eight weeks after the outbreak of the pandemic, residents who had continued to practice at least once per week (n = 35) and those who had not continued to practice (n = 29) were questioned again about their self-management, and about five psychological outcomes: anxiety, traumatic stress, satis-faction, general mood, and post-traumatic growth (PTG). Self-management improved among older adults who independently practiced the exercises, and declined among those who did not. Pre-pandemic self-management significantly predicted post-outbreak traumatic stress symptoms, anxiety, general mood, and satisfaction with life, but not PTG. However, the difference in self-management between the pre-pandemic and post-outbreak measures was associated with PTG, and made a unique contribution to prediction of the other effects. Self-management abilities among older adults can be seen as a protective factor against adverse psychological outcomes at times of trauma. Further, the improvement in self-management among older adults who independently practiced physical excises made a unique contribution beyond initial self-management abilities.

Disassembly is a pivotal technology to enable the circularity of electric vehicle batteries by applying circular economy strategies that extend the life cycle of their components, like remanufacturing and repurposing, or by using efficient recycling to reintegrate the gained materials in producing new battery systems. This paper aims to develop a multi-method self-configuring simulation model for investigating disassembly scenarios while considering the battery design as well as the configuration and layout of the disassembly station. We demonstrate the developed model in a case study using a battery of Mercedes-Benz and the automated disassembly station of the project DeMoBat at Fraunhofer IPA. Furthermore, we introduce two disassembly scenarios, the component-oriented and the accessibility-oriented disassembly, and compare them using the simulation model to determine several indicators, such as the frequency of tool change, the number and distribution of robot routes, the tool utilization, and the disassembly time.

Complex dynamical fluctuations, from molecular noise within cells, collective intelligence, brain dynamics or computer traffic have been shown to display noisy behaviour consistent with a critical state between order and disorder. Living close to the critical point can have a number of adaptive advantages and it has been conjectured that evolution could select (and even tend to) these critical states. One way of approaching such state is by means of so-called self-organized criticality (SOC) where the system poises itself close to the critical point. Is this the case of living cells? It is difficult to test this idea given the enormous dimensionality associated with gene and metabolic webs. In this paper, we present an alternative approach: to engineer synthetic gene networks displaying SOC behaviour. This is achieved by exploiting the presence of a saturation (congestion) phenomenon of the ClpXP protein degradation machinery in E. coli cells. Using a feedback design that detects and then reduces ClpXP congestion, a {\em critical motif} is built from a two-gene network system, where SOC can be successfully implemented. Both deterministic and stochastic models are used, consistently supporting the presence of criticality in intracellular traffic. The potential implications for both cellular dynamics and designed intracellular noise are discussed.

This review article delves into the intricate psychology behind galivanting, absenteeism, and self-denial among college students. By conducting a meticulous analysis of relevant books, journals, and articles, key psychological factors come to light. The review examines the influence of exploration and identity formation, social motivation, coping mechanisms, lack of motivation or engagement, time management, and self-denial on these behaviors. By addressing gaps in the literature, it provides a deeper understanding of the phenomena at hand. The implications of this study extend to the development of interventions and strategies that address self-denial tendencies, promote effective time management, and foster a supportive learning environment. By shedding light on the intricate interplay of these factors, this paper opens doors for future research and targeted interventions, ultimately aiming to enhance academic engagement, reduce absenteeism, and support the overall well-being and success of college students.

In this paper, first the Self-Written Waveguide (SWW) process in wet photopolymer media (liquid solutions), are examined for three examples: single-, counter-, and co-fibers exposure. Then the SWWs formed inside solid material are examined including the effects of manipulating the alignment of the fibers. In all cases high precision measurements are used to position the fiber optic cables (FOCs) before exposure using a microscope. The self-writing process is indirectly monitored by observing (imaging) the light emerging from the side of the material sample during SWW formation. In this way the optical waveguide trajectories formed in an Acrylamide/Polyvinyl Alcohol (AA/PVA) a photopolymer material (sensitized at 532 nm) are examined. First the transmission of light by this material is characterized. Then the bending and merging of the waveguides which occur are investigated. The predictions of our model are shown to qualitatively agree with the observed trajectories. The largest index changes taking place at any time during the exposure, i.e. during SWW formation, are shown to take place at the positions where the largest exposure light intensity is present. Typically, such maxima exist close to the input face and the first maximum is referred to as the location of the Primary Eye. Other local maxima also appear further along the SWW and are referred to as Secondary Eyes, i.e. deeper within the material.

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.

The threat of antimicrobial resistance to society is compounded by a relative lack of new clinically effective licensed therapies reaching patients over the past three decades. This has been particularly problematic within antifungal drug development leading to a rise in fungal infection rates and associated mortality. This paper highlights the potential of an ultrashort peptide, (naphthalene-2-ly)-acetyl-diphenylalanine-dilysine-OH (NapFFKK-OH), encompassing hydrogel-forming and antifungal properties within a single peptide motif, thus overcoming formulation (e.g. solubility, drug loading) issues associated with many current employed highly hydrophobic antifungals. A range of fungal susceptibility (colony counts) and cell cytotoxicity (MTS cell viability, LIVE/DEAD staining® with fluorescent microscopy, haemolysis) assays were employed. Scanning electron microscopy confirmed the nanofibrous architecture of our self-assembling peptide, existing as a hydrogel at concentrations of 1% w/v and above. Broad-spectrum activity was demonstrated against a range of fungi clinically relevant to infection (Aspergillus niger, Candida glabrata, Candida albicans, Candida parapsilosis and Candida dubliniensis) with greater than 4 log10 CFU/mL reduction at concentrations of 0.5% w/v and above. We hypothesise antifungal activity is due to targeting of anionic components present within fungal cell membranes resulting in membrane disruption and cell lysis. NapFFKK-OH demonstrated reduced toxicity against mammalian cells (NCTC 929, ARPE-19) suggesting increased selectivity for fungal cells. However, further studies relating to safety for systemic administration is required, given the challenges toxicity has presented in the wider context of antimicrobial peptide drug development. Overall this study highlights the promise of NapFFKK-OH hydrogels, particularly as a topical formulation for the treatment of fungal infections relating to the skin and eyes, or as a hydrogel coating for the prevention of biomaterial related infection.

This study is framed on the Information Theory as a constructive criterion to generate probabilistic distributions –through the elaboration of Bayesian Networks- and to reduce the uncertainty in the occurrence and relationship between two key psychological variables associated with the sports’ performance: Self-Determined Motivation and Competitive Anxiety. We analyzed 674 universitary students/athletes who competed in the 2017 Universitary Games (Universiade) in México, from 44 universities, with an average age of 21 years old (SD = 2.07), and with a sportive experience of 8.61 years of average (SD = 5.15). Methods: Regarding the data analysis, first of all a CHAID algorithm was carried out for to know the independence links among variables, and then two Bayesian networks (BN) were elaborated. The validation of the BN revealed AUC values ranging from 0.5 to 0.92. Subsequently, various instantations were carried out with hypothetical values applied to the “bottom” variables. Results showed two probability trees that have Extrinisic Motivation and Amotivation at the top, while the anxiety/activation due to the worry for performance was at the bottom of probabilities. The instantiations carried out support the existence of these probabilistic relationships, demonstrating the little influence on the competition anxiety generated by the intrinsic motivation. In conclusion, the reduction of the uncertainty made up by the restricted BN may aloe to re-introduce Information Theory principles in psychosocial studies, allowing authors to obtain useful probabilities values upon target psychological variables related with sportive performance.

Nowadays Air-Source Heat Pumps (ASHP) in combination with a Photovoltaic (PV) installation are a very promising option for a necessary and urgent energy transformation in European Union (EU). It is extremely important to develop solutions that will help maximize the use of energy generated from renewable energy sources (RES). Such issues include the problem of insufficient use of generated electricity in PV on-grid microinstallations in residential buildings. This paper's aim is to analyze the results of one-year-round operation of a PV array grid-connected hybrid installation with ASHP for domestic hot water (DHW) preparation in a residential building in Cracow, Poland in the context of increasing self-consumption (SC) of PV energy. Models of systems are built and simulated in Transient System Simulation Tool 18 (TRNSYS) software. Simulations were carried out for different scenarios involving different building electricity consumption profiles, PV system capacity and specified runtime management of ASHP. The novelty of this study lies in the evaluation of the impact of a certain range of conditions on the energy performance of the system, in particular on SC. The results showed that the use of ASHP, with specified runtime management, results in an increase in monthly SC values from 7 to 18%, and annual SC values up to 13%. Also determining the appropriate size of the used PV system depending on whether it is present ASHP in the installation is crucial to increase the value of the SC parameter. Overall, this study provides valuable insights into the potential benefits of PV panels and ASHP operating together, in particular on SC values.

Background & Aims: Globally, liver diseases account for 2 million deaths per year. For those with advanced liver disease the only curative approach is liver transplantation. However, less than 10% of those in need get a liver transplant due to limited organ availability. To circumvent this challenge, there has been a great focus in generating a bioengineered liver. Despite its essential role in liver functions, a functional biliary system has not yet been developed. In this framework, exploration of epithelial cell self-organogenesis and microengineering-driven geometrical cell confinement allow to envision the bioengineering of a functional biomimetic intrahepatic biliary tract. Approach: Three-dimensional (3D) bile ducts were built in vitro by restricting cell adhesion to two-dimensional (2D) patterns to guide cell self-organization. Tree shapes mimicking the configuration of the human biliary system were micropatterned on glass slides, restricting cell attachment to these areas. Different tree geometries and culture conditions were explored to stimulate self-organogenesis of normal rat cholangiocytes (NRCs) used as a biliary cell model, either alone or in coculture with human umbilical endothelial cells (HUVECs). Results: Pre-seeding the micropatterns with HUVECs promoted luminogenesis with higher efficiency to yield functional branched biliary tubes. Lumen formation, apico-basal polarity, and preservation of the cholangiocyte phenotype were confirmed. Moreover, intact and functional biliary structures were detached from the micropatterns for further manipulation. Conclusion: This study presents physiologically relevant 3D biliary duct networks built in vitro from 2D micropatterns. This opens opportunities for investigating bile duct organogenesis, physiopathology, and drug testing.

The Voronoi entropy is a mathematical tool for quantitative characterization of the orderliness of points distributed on a surface. The tool is useful to study various surface self-assembly processes. We provide the historical background, from Kepler and Descartes to our days, and discuss topological properties of the Voronoi tessellation, upon which the entropy concept is based, and its scaling properties, known as the Lewis and Aboav-Weaire laws. The Voronoi entropy has been successfully applied to recently discovered self-assembled structures, such as patterned micro-porous polymer surfaces obtained by the breath figure method and levitating ordered water micro-droplet clusters.

A phosphate/molybdate and cerium-modified phosphate/molybdate conversion coatings were deposited on a carbon steel surface and their protective and self-healing abilities were evaluated. Surface morphology and inner structure of the coatings were examined using FE-SEM-FIB and TEM techniques, chemical composition and element distribution depth profiles in conversion layers were determined using EDX measurements, whereas XPS was applied for the analysis of Mo and Ce oxidation states. Voltammetric measurements and EIS were performed to assess the corrosion behavior of the samples. The higher protective and stronger self-healing abilities were found for phosphate/molybdate/cerium conversion coating deposited in a sulphate-containing solution. This was attributed to higher values of both: total cerium and Ce(IV) content in the conversion layer as well as to lower number of structural defects in the coating. It was demonstrated that the micro-structural characteristics of protective coatings are also important in determining self-healing abilities.

While some researchers have suggested that the self-employment (SE) sector is a haven during a financial Crisis, others believe that SE is not necessarily the desired outcome, but an indicator that the labor market is tightening for some groups. Few researchers have compared the SE sector before and after the occurrence of a significant financial Crisis, especially in developed countries. This paper analyzes the determinants of entry into self-employment during the 2008 Spanish Crisis. Using data from the Encuesta de Presupuesto Familiar (EPF), results show that although the rate of SE did not experience a significant change during this time the Crisis affected people differently based on gender, with being females more affected than males. Results also suggest differences between Comunidades Autonomas in how the self-employment sector behaved during the Crisis.

Self-consciousness can be considered as the internal disposition to direct attention to oneself. This dispositional tendency can be focused on private aspects of the self, but also on public characteristics of the individual. We examine self-consciousness in online consumer behavior. This concept has been poorly investigated in consumer research. The main objective of this paper is to analyze the influence of the dimensions of self-consciousness in consumer adoption of online shopping. This study is based on a sample of 725 Spanish undergraduates. Results indicated that public self-consciousness is a significant predictor of the adoption of online shopping.

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.

Self-healing is the capability of materials to repair themselves after damage has occurred, usually by interaction between molecules or chains. Physical and chemical processes are applied for the preparation of self-healing systems. There are different approaches for these systems such as heterogeneous systems, shape memory effects, hydrogen bonding or covalent-bond interaction, diffusion and flow dynamics. Self-healing mechanisms can occur in particular by heat and light exposure or by reconnection without direct effect. The applications of these systems display an increasing trend in both R&D and industry sectors. Moreover, self-healing systems and their energy storage applications are currently getting great importance. This review aims to provide general information on recent developments in self-healing materials and their energy applications in view of the critical importance of self-healing systems for lithium-ion batteries (LIBs). In the first part of the review, an introduction about self-healing mechanisms and design strategies of self-healing materials is given. Then, selected important healing materials in the literature for the anodes of LIBs are mentioned in the second part. The results and future perspectives are stated in the conclusion section.

Today, issues related to people’s mental health and well-being have been described as a challenge for society, globally as well as in Sweden. This calls for new approaches to mental health promotion. The aim was to evaluate the adequacy of the content and structure, describing experiences of study circles as a means of supporting participants' self-care and self-compassion. The overall design is a descriptive, QUAL+quan design, where quantitative and qualitative results are integrated. Five participants participated in a focus group interview, of whom four completed questionnaires. One individual interview was conducted with the study circle leader. Study circles can be an arena for mental health promotion as learning and sharing of experience contributes to a sense of coherence, as well as self-compassion and a genuine concern for one’s own and others' wellbeing, but not considered an alternative to psychiatric care, for those in need of professional services. Study circles can be a possible means to support self-care and thereby promote mental health in the general population, and a valuable contribution to public health. However, in addition to modifications of the content, further research is needed on the qualifications for study circle leaders as well as the dissemination of study circles.

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.

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.

In the study, it was aimed to develop a valid and reliable scale in order to determine the self-efficacy perceptions of classroom teachers in the field of mathematics learning difficulties. In the development process of the scale, the basic resources and the scale development studies in the literature were examined. First, a pool of substances was created. Content validity was ensured by taking the opinions of 21 expert participants in the 24 question areas determined in the item pool. Content validity index was used in content validity. In this analysis, two questions were removed from the scale. Preliminary application was made with 44 participating teachers who are experts in their fields and exploratory factor analysis was started. For exploratory factor analysis, 359 people consisting of classroom teachers in Sakarya province were studied. In the explanatory factor analysis, 5 items were removed from the scale by looking at the factor load. The factor loadings for the 17 items in the scale vary between 0.508 and 0.976. Among the comparative fit indices obtained as a result of confirmatory factor analysis, RMSEA=0.067 and Cmin/DF=1.568 were calculated. The Cronbach alpha reliability coefficient of the measurements is 0.970. The data obtained were analyzed with statistical methods using SPSS 25, AMOS 24 and Microsoft Excel programs. The validity and reliability criteria of the scale developed within the scope of the study were met.

The purpose of the current study was the level of the self-confidence among with high musical abilities Student? The randomly selected sample consisted of students (n= 130, M= 65, F= 65) . The analytical descriptive approach was applied in the study and self-confidence Scale developed by the author was administered to participants. Results indicated that: - The self-confidence among the high musical abilities Student students was rated high. There were no statistically significant differences at (α=≤0.05) attributed to effect of sex on the self-confidence overall degree. There were statistically no significant differences at (α≤0.05) attributed to effect of achievement on the self-confidence overall degree,

Video behavior recognition often needs to focus on object motion processes. In this work, a self-organizing computational system oriented to behavioral clustering recognition is proposed, which achieves the extraction of motion change patterns by binary encoding and completes motion pattern summarization using a similarity comparison algorithm. And in the face of unknown behavioral video data, a self-organizing structure with layer-by-layer accuracy progression is used to achieve motion law summarization by using a multi-layer agent design approach. Finally, the real-time feasibility is verified in the prototype system using real scenes to provide a new feasible solution for unsupervised behavior recognition and space-time scenes.

We report the development of an extrinsic self-healing coating system that shows no fluorescence from the intact coating, yellowish fluorescence in cracked regions, and greenish fluorescence in healed regions, thus allowing the separate monitoring of cracking and healing of coatings. This fluorescence monitoring self-healing system consisted of a top coating, an epoxy matrix resin containing mixed dye-loaded in single microcapsule. The dye-loaded microcapsules consisted of a poly(urea-formaldehyde) shell encapsulating a healing agent containing MAT-PDMS and styrene, a photo-initiator and a mixture of two dyes, one that fluoresces only in the solid state (DCM) and a second that fluoresces dramatically increased in the solid than solution state (4-TPAE). A mixture of the healing agent, photo-initiator and the two dyes was yellow due to fluorescence from DCM. On UV curing of this mixture, however, the color changed from yellow to green and the fluorescence intensity increased due to fluorescence from 4-TPAE in the solid state. When a self-healing coating embedded with microcapsules containing the DCM/4-TPAE dye mixture was scratched, the damaged region exhibited a yellowish color that changed to green after healing. Thus, the self-healing system reported here allows the separate monitoring of cracking and healing based on changes in fluorescence color.

Hydrogels incorporated with hydrophobic motifs have received considerable attention to recapitulate the cellular microenvironments, specifically for the bio-mineralization of a 3D matrix. Introduction of hydrophobic motifs into a hydrogel often results in irregular arrangement of the motifs, and further phase separation of hydrophobic domains, but limited efforts have been made to resolve this challenge in the hydrophobically-modified hydrogel. Therefore, this study presents an advanced integrative strategy to incorporate hydrophobic domains regularly in a hydrogel by self-assembling of polymer cross-linkers, building blocks of a hydrogel. Self-assemblies between polymer cross-linkers were examined as micro-domains to incorporate hydrophobic motifs in a hydrogel. The self-assembled structures in a pre-gelled solution were confirmed with the fluorescence analysis and the hydrophobicity of a hydrogel could be tuned by incorporating the motifs in a controlled manner. Overall, the results of this study would greatly serve to tuning performance of a wide array of hydrophobically-modified hydrogels in drug delivery, cell therapies and tissue engineering.

Owing to the nondiffracting, self-accelerating, and self-healing properties, Airy beams of different nature have become a subject of immense interest in the past decade. Their interesting properties have opened doors to many diverse applications. Consequently, the questions of how to properly design spatial manipulation of Airy beams or how to implement them in different setups have become important and timely in the development of various optical devices. Here, based on our previous work, we present a short review on the spatial control of Airy beams, including the interactions of Airy beams in nonlinear media, beam propagation in harmonic potential, and the dynamics of abruptly autofocusing Airy beams in the presence of a dynamic linear potential. We demonstrate that under the guidance of nonlinearity and external potential, the trajectory, acceleration, structure, and even the basic properties of Airy beams can be adjusted to suit specific needs. We describe other fascinating phenomena observed with Airy beams, such as self-Fourier transformation, periodic inversion of Airy beams, and the appearance of spatial solitons in the presence of nonlinearity. These results have promoted the development of Airy beams, and have been utilized in various applications, including particle manipulation, self-trapping, and electronic matter waves.

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.

Abstract: The Micro-Electro-Mechanical System (MEMS) LiDAR point cloud in autonomous vehicles has a large deflection range, which results in slow registration speed and poor applicability. To maximize speed, an improved NDT (Normal Distribution Transform) method that integrates point cloud density features has been proposed. First, the point cloud is reduced using a modified voxel filter and a pass-through filter. Next, the ISS (Intrinsic Shape Signature) algorithm is utilized to analyze the point cloud features and extract keypoints, the 4PCS (4-Point Congruent Sets) algorithm is then employed to calculate the initial pose under the constraints of the keypoint set to complete the coarse registration. Finally, the self-adaptive segmentation model is constructed by using KD-tree to obtain the density features of keypoints, and the NDT algorithm is combined with this model to form an SSM-NDT algorithm, which is used for fine registration. Each algorithm was compared on the autonomous vehicle dataset PandaSet and actual collected data sets, the results show that the novel method increases the speed by at least 60% and takes into account good registration accuracy and strong anti-interference.

Afghanistan is overwhelmed with food insecurity that is a large percentage of the population lacks reliable access to food supplies. Grains play a vital role in the country's food security due to their importance in terms of consumption and production quantity. This paper estimates cereal self-sufficiency and then makes a food balance forecast of the three major food crops cultivated in Afghanistan over six-decades. Descriptive statistics and coarse metric techniques were employed to determine cereal self-sufficiency and food balance forecast. The econometric analysis demonstrated that (1) Afghanistan is not yet self-sufficient in meeting grain consumption, and the production and consumption ratio declined from 0.9 to 0.55 from 1979 to 2030. (2) The gap of theoretical food imbalance will increase, and by the year 2030, cereal production will likely be sufficient for only 49.8 percentage of inhabitants, leaving a high shortage equivalent to the amount required by 24.4 million people. By evaluating the quantitative food balance and the growing population change, this study presents an analysis of the emerging threat to Afghanistan's food security and suggests a solution for food security, should increase the size of public agricultural expenditure, improve the level of agriculture infrastructure, and continue to introduce a policy to achieve higher yield.

Background: The practice of self-medication is common worldwide and is an important component of medical self-care. However, the practice can be dangerous and is linked to various risks for the patients and the entire community. This study aimed to estimate the prevalence and factors associated with self-medication among Bangladeshi adults. Methods: A cross-sectional survey was conducted between April and June 2021 among Bangladeshi adults (aged &gt;19 years) using convenient sampling. A total of 1320 data were collected through face-to-face interviews using a standardized questionnaire. Multivariable logistic regression analysis was used to identify factors associated with self-medication practice (SMP). Results: Overall, 41% of adults in our survey reported SMP. The most common illnesses that prompted SMP were common cold/flu (66.4%), gastric problems (65%), and headache (64.4%). The most frequent reasons for SMP were to get better services (30.59%), perceive SMP without side effects (23.28%), and save time with effectiveness (14.56%). Potential risk factors included 10 years (AOR = 1.91; 95% CI: 1.04 - 3.50) and &gt;12 years of schooling (AOR = 5.03; 95% CI: 2.27 - 11.15), being a businessman (AOR = 4.64; 95% CI: 1.74 - 12.37), having ≤6 family members (AOR = 2.13; 95% CI: 1.40 - 3.24), being a member of a social group (AOR = 1.53; 95% CI: 1.10 - 2.12), a health status check after every six months (AOR = 1.52; 95% CI: 1.08 - 2.13), and current ill-health (AOR = 1.41; 95% CI: 1.06 - 1.87). Protective factors identified included ≤30 years of age (AOR = 0.40; 95% CI: 0.17 - 0.93), and practice of modern (AOR = 0.39; 95% CI: 0.22- 0.69) and herbal (AOR = 0.45; 95% CI: 0.21- 0.97) healing types. Conclusion: More than one-third of the study participants reported practicing self-medication. Increasing the community’s awareness of the extreme consequences of SMP and not just the average experience might sway individuals away from SMP, and implementing strict jurisdiction could be a way to minimize the SMP.

The study aimed to understand the experiences of adolescent smokers who participated in a smoking cessation program based on self-reflection, and to develop the theoretical basis for constructing similar programs. The participants, ten students from middle and high schools located in cities G and S, were interviewed after the program ended. Data were collected from August to November 2019 and analyzed using a phenomenological approach to understand participant experiences in depth. The analysis revealed five major themes: ‘Uniqueness of the Program,’ ‘Perception of Smoking Cessation,’ ‘Positive Reflection on Life,’ ‘Understanding Others,’ and ‘A Search for Hope and Vision in Life.’ The findings revealed that the smoking cessation program facilitated the development of self-identity and vision, which may indirectly strengthen the motivation for adolescent smokers to quit smoking. These findings suggest the need for a life-changing smoking cessation program that enhances self-concept and self-esteem. Moreover, it highlights the importance of follow-up research to ensure effectiveness, and the need to develop programs with creative content.

This work is the first part of a series of papers on a comprehensive analysis of the processes of prebiotic self-organization and protophotosynthesis on the surface of semiconductor minerals and in systems of natural dispersed semiconductors. Comprehensive analysis within the framework of the "semiconductor world" concept allows integrating a variety of models on a single physical basis - from ZnS world and FeS world (based on inorganic semiconductors) to the PAH world and aromatic world (including organic semiconductors). Thus, we do not put forward a new alternative hypothesis of chemical evolution - a new "chemical world", but only integrate the evolutionary and geochemical criteria of different "chemical worlds" into a single "physical world", which gives one the opportunity to reconstruct and predict the directions of chemical evolution according to the uniform principles of physical chemistry. In the first part of this series we consider photoinduced self-organization and "photo-controlled" evolution of the early protobiological systems performing solar energy conversion on the surface of dispersed semiconductor minerals capable of (photo)catalyzing and photosensitizing prebiological processes. The latter include a transition from the elementary cycles of photocatalytic reactions on the surface of semiconductors to protophotometabolic cycles and protophotosynthesis, from photophysical processes on the surface of mineral semiconductors to photoinduced membrane potentials, from photocontrolled sorption on the surface of such minerals to the formation of photosensitive protomembranes and selection of photosynthetic structures. The evolutionary approach to the analysis of protobiological mechanisms and protobioenergetics within the framework of the "semiconductor world" concept provides a new approach to the study of the last common point of divergence of protobiological systems, where the emergence principles of different energy supply schemes (like the energy source-specific photoautotrophy and substrate-specific chemoautotrophy) merge at the physicochemical level. The proposed integrating scheme is consistent with most biological, geological, and physicochemical concepts, which ensures its complete cross-checking and internal consistency.