Adaptive Coping During Protracted Political Conflict, War and Military Blockade in Gaza

Identifying culturally-relevant concepts and coping mechanisms can help protect civilian wellbeing. This study explores how seven professional Palestinian university graduates in the Gaza Strip (occupied Palestinian territories) cope with war, military occupation, military blockade and the challenges of living in a conflict-affected area. Participants were interviewed to determine whether culturally specific modes of coping were used. Thematic analysis was applied. The use of resistance and more specifically, sumud , being steadfast and persevering, were identified alongside the motivation to persevere and other adaptive responses to living conditions. Coping strategies identified in this study include adapting, problem-solving, accepting reality, exercising patience, utilising social support, and faith in God (iman) and religion. The implications of this study and the relevance of the findings to mental health and disaster relief are considered

Incidence on the Self-Regulation as Prevention of the Tobacco in Adolescents

Background the self-regulating in adolescent s smokers as prevention is one of the lines of the work team in the consultation of Ceasing Tobacco Objective to identify the incidence on the self-regulation to prevent the tobacco in adolescents The investigation embraced one period from March 2017 to September 2018 Method A descriptive study of traverse court was used Registered to 31 students for sampling intentional non probabilistic of an universe of 50 adolescent students It was used empiric Methods Clinical histories interviews structured and the questionnaire Conclusion The female sex prevailed where 54 8 between the 12 to 19 years of age Results The incidence the factors of risks that impact on the self-regulation to prevent the tobacco in adolescents are the group contagion with 54 7 family problems for a 29 0 and situational depression with 16 1 where it is necessary the self-regulation that should have the adolescents in the lif

Adaptive Guidance: Training-free Acceleration of Conditional Diffusion Models

This paper presents a comprehensive study on the role of Classifier-Free Guidance (CFG) in text-conditioned diffusion models from the perspective of inference efficiency. In particular, we relax the default choice of applying CFG in all diffusion steps and instead search for efficient guidance policies. We formulate the discovery of such policies in the differentiable Neural Architecture Search framework. Our findings suggest that the denoising steps proposed by CFG become increasingly aligned with simple conditional steps, which renders the extra neural network evaluation of CFG redundant, especially in the second half of the denoising process. Building upon this insight, we propose "Adaptive Guidance" (AG), an efficient variant of CFG, that adaptively omits network evaluations when the denoising process displays convergence. Our experiments demonstrate that AG preserves CFG's image quality while reducing computation by 25%. Thus, AG constitutes a plug-and-play alternative to Guidance Distillation, achieving 50% of the speed-ups of the latter while being training-free and retaining the capacity to handle negative prompts. Finally, we uncover further redundancies of CFG in the first half of the diffusion process, showing that entire neural function evaluations can be replaced by simple affine transformations of past score estimates. This method, termed LinearAG, offers even cheaper inference at the cost of deviating from the baseline model. Our findings provide insights into the efficiency of the conditional denoising process that contribute to more practical and swift deployment of text-conditioned diffusion models

Linear Segmented Arc-Shaped Piezoelectric Branch Beam Energy Harvester for Ultra-Low Frequency Vibrations

Data Availability Statement: Data could be provided upon request to the corresponding author.Piezoelectric energy harvesting systems have been drawing the attention of the research community over recent years due to their potential for recharging/replacing batteries embedded in low-power-consuming smart electronic devices and wireless sensor networks. However, conventional linear piezoelectric energy harvesters (PEH) are often not a viable solution in such advanced practices, as they suffer from a narrow operating bandwidth, having a single resonance peak present in the frequency spectrum and very low voltage generation, which limits their ability to function as a standalone energy harvester. Generally, the most common PEH is the conventional cantilever beam harvester (CBH) attached with a piezoelectric patch and a proof mass. This study investigated a novel multimode harvester design named the arc-shaped branch beam harvester (ASBBH), which combined the concepts of the curved beam and branch beam to improve the energy-harvesting capability of PEH in ultra-low-frequency applications, in particular, human motion. The key objectives of the study were to broaden the operating bandwidth and enhance the harvester’s effectiveness in terms of voltage and power generation. The ASBBH was first studied using the finite element method (FEM) to understand the operating bandwidth of the harvester. Then, the ASBBH was experimentally assessed using a mechanical shaker and real-life human motion as excitation sources. It was found that ASBBH achieved six natural frequencies within the ultra-low frequency range (<10 Hz), in comparison with only one natural frequency achieved by CBH within the same frequency range. The proposed design significantly broadened the operating bandwidth, favouring ultra-low-frequency-based human motion applications. In addition, the proposed harvester achieved an average output power of 427 μW at its first resonance frequency under 0.5 g acceleration. The overall results of the study demonstrated that the ASBBH design can achieve a broader operating bandwidth and significantly higher effectiveness, in comparison with CBH.Southern Cross University, Australia