Miracle-dz/UniFAR-FTUs huggingface dataset:
Public health nurses’ experiences following up children with overweight and obesity according to national guidelines. A qualitative study

ABSTRACT Purpose This study aimed to develop knowledge of how the follow-up regarding overweight and obesity among children in primary school is experienced by the PHN and how the guidelines may be used to improve health services in this follow-up. Methods We analysed semi-structured interviews of 9 PHNs using qualitative content analysis. Results Two themes emerged: Following up with children with overweight and obesity is an important but challenging duty; The PHNs call for clearer guidelines. Following five sub-themes: PHNs strive to adhere to the guidelines, show compassion in the follow-up, have difficulty handling parents’ feelings and reactions, feel alone with the responsibility, and have suggestions for clearer guidelines. Conclusions PHNs call for enough resources to communicate the results of the child’s weight in a sufficient form. PHNs and families should establish common goals. The PHN should avoid one-way communication but meet the parents’ concerns and needs. This requires the PHN to focus on building a secure relation to the child and the families, as described by Peplau. Guidelines must include instructions and tools on how to communicate and meet the family’s concerns. Political action and increased funding could strengthen the follow-up and thereby prevent more obesity among children, which can be a predictor of poorer health outcomes later in life.
Impact of vitamin D supplementation as COVID-19 vaccine adjuvant on sperm parameters and sex hormones in men with idiopathic infertility: Two separate pre-post studies.

Objective Vitamin D deficiency is a major problem for human health worldwide. The mechanisms of vitamin D in the male reproductive system are unknown. After coronavirus disease 2019 (COVID-19) vaccines were developed, doubts were raised about their possible effects on male fertility. Based on vitamin D's function in the immune system, its potential role as an adjuvant for COVID-19 vaccines is intriguing. The aims of this study were to assess the effects of vitamin D first on sperm parameters and sex hormones, and then as an immune adjuvant on sperm parameters and sex hormones after study participants had received their second doses of COVID-19 vaccines. Methods Phase 1 (before the COVID-19 pandemic) included 72 men with idiopathic infertility, and phase 2 had 64 participants who received two doses of COVID-19 vaccines. Both groups were instructed to take 50,000 IU of vitamin D twice monthly for 3 months. Sperm parameters and sex hormones were assessed pre- and post-supplementation. Results Regular vitamin D intake for 3 months significantly increased the participants' vitamin D levels (p=0.0001). Both phases showed a positive correlation between vitamin D intake and sperm parameters. Vaccination had no negative effects on sperm parameters and sex hormones. Vitamin D was associated with follicle-stimulating hormone (p=0.02) and testosterone (p=0.0001) in phase 2 after treatment. Conclusion Our results support vitamin D supplementation as an immune adjunct to COVID-19 vaccination for improving sperm parameters and hormone levels. COVID-19 vaccination is not harmful for male fertility potential, and vitamin D is an effective factor for male fertility.
Evaluation of six empirical reference crop evapotranspiration equation. Case study: Campos dos Goytacazes

A evapotranspiracao e um dos componentes do balanco hidrico que representa grande desafio em sua quantificacao. Os processos fisicos complexos envolvidos em sua determinacao eficaz em larga escala tem estimulatedo cientistas a fazer o uso, muitas vezes, das equacoes empiricas, que limitam a aplicabilidade destas equacoes e da descricao do comportamento do evapotranspiracao em diferentes regioes do mundo. O estudo foi procedido para a regiao de Campos dos Goytacazes, no estado do Rio de Janeiro. O mesmo propoe-se investigar e avaliar o desempenho de seis equacoes comparadas a equacao de FAO56-Penman-Monteith. Os resultados indicaram que os erros observados entre as equacoes empiricas aplicadas neste estudo e os valores calculados pela equacao de FAO56-Penman-Monteith foram maiores que 10%.
Lower limbs strength variations between injured and non-injured professional soccer players

Due to its physical demands, professional soccer is becoming a real challenge regarding players’ exposure to high injury risk. Given its tight correlation with high-intensity actions, muscular strength is a crucial physical characteristic for soccer players. Therefore, the aims of this study are (a) to compare the vertical jumping performance during the season according to the injury profile, and (b) to investigate differences in isokinetic strength performance at the beginning and the end of the season. Twenty-one male professional soccer players (age: 26.0 ± 4.1 years, height: 181.0 ± 6.9 cm, body mass: 73.7 ± 6.9 kg) were assessed in isokinetic strength (Biodex System 4 Pro Dynamometer), and Optojump Next (Microgate, Bolzano, Italy). Isokinetic strength analyses considered the peak torque scores of knee flexors and knee extensors, according to the player's preferred and non-preferred limb. The countermovement and squat jump maximum height were assessed as lower body explosive strength indicators. No significant differences were found when comparing injured and non-injured players in vertical jump and isokinetic strength assessments. However, significant results were found when comparing both groups’ initial and final evaluation in isokinetic strength assessment, with both groups significantly improving their performance. Our findings indicate that the overall lower body strength performance was not a discriminant factor between injured and non-injury players. Thus, muscular strength assessment performance increased throughout the season independently of the injury profile. Future research needs to integrate other variables related to sports injuries since they seem to result from multifactorial causes.
Adaptation of energy systems to climate change and water resource constraints

This dissertation assesses the long-term technological and policy implications of adapting to water constraints and climate change impacts in the energy sector. Energy systems are increasingly vulnerable to climate change and water resource variability. Yet, the majority of long-term energy infrastructure plans ignore adaptation strategy. New analytical approaches are needed to address the spatial and temporal scales relevant to both climate change and water resources. The research in this dissertation overcomes these challenges with improved engineering-economic modeling. Specifically, the conventional systemsengineering energy technology planning framework is extended to incorporate: (1) robust capacity decisions in the electricity sector in light of impacts from hydro-climatic change and uncertain environmental performance of technology options; (2) an endogenous, spatially-distributed representation of water systems and feedbacks with energy demand; and (3) multi-objective decision-making. The computational modeling framework is applied to four regional case study analyses to quantify previously unaccounted for policy-relevant interactions between water, energy and climate systems. Application of the robust adaptation planning framework to the power system in British Columbia, Canada,
Exploring the feasibility of empirical, dynamical and combined probabilistic rainy season onset forecasts for São Paulo, Brazil

This study investigates the feasibility and presents an assessment of probabilistic rainy season onset forecasts for São Paulo, Brazil, located in a region with a well‐defined wet season from mid‐austral spring (October) to austral autumn (March/April). The probabilistic forecasts were produced with (1) a simple empirical Cox‐regression model using July Niño‐3 index as predictor, (2) the dynamical coupled atmosphere‐land‐surface‐ocean‐sea‐ice model used in the UK Met Office Global Seasonal Forecast System (GloSea5) and (3) a procedure that combines the empirical and dynamical model onset probabilistic forecasts. The probabilistic forecast assessment was performed over the 1996–2009 retrospective forecast period for the event rainy season onset earlier (or later) than the historical (mean) onset date. The three investigated approaches resulted in similar discrimination ability of around 80%, which represents the probability of the probabilistic forecasts correctly distinguishing earlier from a later than mean onsets, suggesting good potential for rainy season onset forecasts for São Paulo. The robustness of this assessment for an extended period (longer than 1996–2009) and for a region (20°S, 25°S, 45°W, 55°W) that includes the city of São Paulo was checked, reinforcing the validity of the obtained results at both local and regional scales.
An International, Cross-Sectional Survey of Psychiatry Researchers and Clinicians: Perceptions of Complementary, Alternative, and Integrative Medicine

Background: Psychiatry is a branch of medicine that focuses on mental, behavioural and emotional well-being. Complementary, alternative, and integrative medicine has been an increasingly popular choice for patients with psychiatric disorders, therefore our study aimed to explore the perceptions of psychiatry researchers and clinicians on the use of CAIM. Methods: We conducted an online, anonymous, cross-sectional survey for researchers and clinicians who have published their work in psychiatry medical journals that are indexed in MEDLINE. 42,667 researchers and clinicians were sent the link to the survey after extraction of their email addresses from their respective publications. Respondents were asked numerous multiple-choice questions regarding their perceptions on various CAIM therapies, followed by an open-ended question where they could include any additional thoughts. Results: The survey was completed by 987 respondents, with a majority identifying as a researcher (n=447, 46.51%), or as both a researcher and a clinician (n=368, 38.29%) within the field of psychiatry. Most respondents (n=629, 78.04%) perceived mind-body therapies such as meditation, biofeedback, hypnosis, and yoga to be the most promising CAIM therapy for the prevention, treatment, and management of psychiatric diseases. Many participants said that they agree (n=285, 38.14%) that most CAIM therapies in general are safe, however, many disagree that CAIM therapies are effective (n=245, 32.93%). Respondents indicated that there is value to conducting research on CAIM therapies (n=356, 47.91%), and that there should be more funding allocated to researching these therapies (n=265, 35.71%). Respondents are also in agreement that clinicians should receive training on CAIM therapies through formal education (n=295, 39.76%) or supplementary education (n=380, 51.28%). Conclusions: The findings from this study showed that there is great interest and potential in researching CAIM within the field of psychiatry. This information can be used as a basis for further research and to develop tailored educational resources for researchers and clinicians in psychiatry.
Periodic Fractional Discrete Nonlinear Schrödinger Equation and Modulational Instability

The fractional discrete nonlinear Schr\"odinger equation (fDNLS) is studied on a periodic lattice from the analytic and dynamic perspective by varying the mesh size $h>0$ and the nonlocal L\'evy index $\alpha \in (0,2]$. We show that the discrete system converges to the fractional NLS as $h \rightarrow 0$ below the energy space by directly estimating the difference between the discrete and continuum solutions in $L^2(\mathbb{T})$ using the periodic Strichartz estimates. The sharp convergence rate via the finite-difference method is shown to be $O(h^{\frac{\alpha}{2+\alpha}})$ in the energy space. On the other hand for a fixed $h>0$, the linear stability analysis on a family of continuous wave (CW) solutions reveals a rich dynamical structure of CW waves due to the interplay between nonlinearity, nonlocal dispersion, and discreteness. The gain spectrum is derived to understand the role of $h$ and $\alpha$ in triggering higher mode excitations. The transition from the quadratic dependence of maximum gain on the amplitude of CW solutions to the linear dependence, due to the lattice structure, is shown analytically and numerically.
3. PHOSPHOLIPID FATTY ACID-DERIVED MICROBIAL BIOMASS AND COMMUNITY DYNAMICS IN HOT, HYDROTHERMALLY INFLUENCED SEDIMENTS FROM MIDDLE VALLEY, JUAN DE FUCA RIDGE

Phospholipid fatty acids were measured in samples of 60°–130°C sediment taken from three holes at Site 1036 (Ocean Drilling Program Leg 169) to determine microbial community structure and possible community replacement at high temperatures. Five of six samples had similar concentrations of phospholipid fatty acids (2–6 pmol/g dry weight of sediment), and biomass estimates from these measurements compare favorably with direct microscopic counts, lending support to previous microscopic measures of deep sedimentary biomass. Very long-chain phospholipid fatty acids (21 to 30 carbons) were detected in the sediment and were up to half the total phospholipid fatty acid measured; they appear to increase in abundance with temperature, but their significance is not known. Community composition from lipid analysis showed that samples contained standard eubacterial membrane lipids but no detectable archaeal lipids, though archaea would be expected to dominate the samples at high temperatures. Cluster analysis of Middle Valley phospholipid fatty acid compositions shows that lipids in Middle Valley sediment samples are similar to each other at all temperatures, with the exception of very long-chain fatty acids. The data neither support nor deny a shift to a high-temperature microbial com1Summit, M. , Peacock, A. , Ringelberg, D. , White, D.C., and Baross, J.A. , 2000. Phospholipid fatty acid-derived microbial biomass and community dynamics in hot, hydrothermally influenced sediments from Middle Valley, Juan De Fuca Ridge. In Zierenberg, R.A. , Fouquet, Y. , Miller, D.J., Normark, W.R. (Eds.), Proc. ODP, Sci. Results, 169 1–19 [Online]. Available from World Wide Web: . [Cited YYYY-MM-DD] 2Oceanography Box 357940, University of Washington, Seattle WA
PlaceFormer: Transformer-based Visual Place Recognition using Multi-Scale Patch Selection and Fusion

Visual place recognition is a challenging task in the field of computer vision, and autonomous robotics and vehicles, which aims to identify a location or a place from visual inputs. Contemporary methods in visual place recognition employ convolutional neural networks and utilize every region within the image for the place recognition task. However, the presence of dynamic and distracting elements in the image may impact the effectiveness of the place recognition process. Therefore, it is meaningful to focus on task-relevant regions of the image for improved recognition. In this paper, we present PlaceFormer, a novel transformer-based approach for visual place recognition. PlaceFormer employs patch tokens from the transformer to create global image descriptors, which are then used for image retrieval. To re-rank the retrieved images, PlaceFormer merges the patch tokens from the transformer to form multi-scale patches. Utilizing the transformer's self-attention mechanism, it selects patches that correspond to task-relevant areas in an image. These selected patches undergo geometric verification, generating similarity scores across different patch sizes. Subsequently, spatial scores from each patch size are fused to produce a final similarity score. This score is then used to re-rank the images initially retrieved using global image descriptors. Extensive experiments on benchmark datasets demonstrate that PlaceFormer outperforms several state-of-the-art methods in terms of accuracy and computational efficiency, requiring less time and memory.
Stochastic Algorithms for Large-Scale Composite Optimization: the Case of Single-Shot X-FEL Imaging

We apply a recently developed framework for analyzing the convergence of stochastic algorithms to the general problem of large-scale nonconvex composite optimization more generally, and nonconvex likelihood maximization in particular. Our theory is demonstrated on a stochastic gradient descent algorithm for determining the electron density of a molecule from random samples of its scattering amplitude. Numerical results on an idealized synthetic example provide a proof of concept. This opens the door to a broad range of algorithmic possibilities and provides a basis for evaluating and comparing different strategies. While this case study is very specific, it shares a structure that transfers easily to many problems of current interest, particularly in machine learning.
Clue-Guided Path Exploration: An Efficient Knowledge Base Question-Answering Framework with Low Computational Resource Consumption

In recent times, large language models (LLMs) have showcased remarkable capabilities. However, updating their knowledge poses challenges, potentially leading to inaccuracies when confronted with unfamiliar queries. While integrating knowledge graphs with LLMs has been explored, existing approaches treat LLMs as primary decision-makers, imposing high demands on their capabilities. This is particularly unsuitable for LLMs with lower computational costs and relatively poorer performance. In this paper, we introduce a Clue-Guided Path Exploration framework (CGPE) that efficiently merges a knowledge base with an LLM, placing less stringent requirements on the model's capabilities. Inspired by the method humans use to manually retrieve knowledge, CGPE employs information from the question as clues to systematically explore the required knowledge path within the knowledge base. Experiments on open-source datasets reveal that CGPE outperforms previous methods and is highly applicable to LLMs with fewer parameters. In some instances, even ChatGLM3, with its 6 billion parameters, can rival the performance of GPT-4. Furthermore, the results indicate a minimal invocation frequency of CGPE on LLMs, suggesting reduced computational overhead. For organizations and individuals facing constraints in computational resources, our research offers significant practical value.
Emergence of anti-coordinated patterns in snowdrift game by reinforcement learning

Patterns by self-organization in nature have garnered significant interest in a range of disciplines due to their intriguing structures. In the context of the snowdrift game (SDG), which is considered as an anti-coordination game, but the anti-coordination patterns are counterintuitively rare. In the work, we introduce a model called the Two-Agents, Two-Action Reinforcement Learning Evolutionary Game ($2\times 2$ RLEG), and apply it to the SDG on regular lattices. We uncover intriguing phenomena in the form of Anti-Coordinated domains (AC-domains), where different frustration regions are observed and continuous phase transitions at the boundaries are identified. To understand the underlying mechanism, we develop a perturbation theory to analyze the stability of different AC-domains. Our theory accurately partitions the parameter space into non-anti-coordinated, anti-coordinated, and mixed areas, and captures their dependence on the learning parameters. Lastly, abnormal scenarios with a large learning rate and a large discount factor that deviate from the theory are investigated by examining the growth and nucleation of AC-domains. Our work provides insights into the emergence of spatial patterns in nature, and contributes to the development of theory for analysing their structural complexities.
Sharp second-order regularity for widely degenerate elliptic equations

We consider local weak solutions of widely degenerate or singular elliptic PDEs of the type \begin{equation*} -\,\mathrm{div}\left((\vert Du\vert-\lambda)_{+}^{p-1}\frac{Du}{\vert Du\vert}\right)=f \,\,\,\,\,\,\, \text{in}\,\,\Omega, \end{equation*} where $\Omega$ is an open subset of $\mathbb{R}^{n}$ for $n\geq2$, $\lambda$ is a positive constant and $(\,\cdot\,)_{+}$ stands for the positive part. We establish some higher differentiability results, under essentially sharp conditions on the datum $f$. Our results improve the one contained in [8] for $\lambda=0$ and $p>2$, and give back a result similar to that in [12] for $1
Delocate: Detection and Localization for Deepfake Videos with Randomly-Located Tampered Traces

Deepfake videos are becoming increasingly realistic, showing subtle tampering traces on facial areasthat vary between frames. Consequently, many existing Deepfake detection methods struggle to detect unknown domain Deepfake videos while accurately locating the tampered region. To address thislimitation, we propose Delocate, a novel Deepfake detection model that can both recognize andlocalize unknown domain Deepfake videos. Ourmethod consists of two stages named recoveringand localization. In the recovering stage, the modelrandomly masks regions of interest (ROIs) and reconstructs real faces without tampering traces, resulting in a relatively good recovery effect for realfaces and a poor recovery effect for fake faces. Inthe localization stage, the output of the recoveryphase and the forgery ground truth mask serve assupervision to guide the forgery localization process. This process strategically emphasizes the recovery phase of fake faces with poor recovery, facilitating the localization of tampered regions. Ourextensive experiments on four widely used benchmark datasets demonstrate that Delocate not onlyexcels in localizing tampered areas but also enhances cross-domain detection performance.
Interaction of intense ultrashort laser pulses with solid targets: A systematic analysis using first-principles calculations

Intense ultrashort laser pulse irradiation of solid targets was systematically investigated at the first-principles level, both theoretically and computationally. In the method, the propagation of a pulsed light through a thin film is described by a one-dimensional Maxwell's equation, and the microscopic electronic motion at different positions in the film is described by employing first-principles time-dependent density functional theory (TDDFT). The method uses a coarse-graining approximation to couple light propagation and electronic motion, and is termed the multiscale Maxwell-TDDFT method. The reflectance, transmittance, and absorbance of pulsed light incident normally on thin films of 50-200 nm thickness were calculated for materials with different optical properties, such as aluminum (simple metal), graphite (semi-metal), silicon (small-gap dielectric), and quartz (wide-gap dielectric). Optical response transitions were explored as the light intensity shifted from the linear regime, represented by the dielectric function for weak light, to the extremely nonlinear regime, represented by plasma reflection under intense light conditions. Numerous mechanisms that depend on the laser pulse intensity and material type were found to contribute to these changes. These include multiphoton absorption, saturable absorption, sign change of the effective dielectric constant, and transition from quantum occupation to classical Boltzmann distribution. Thus, the calculations provide a unified understanding of the interaction of intense pulsed light with solids, occurring on an extremely short time scale.