Miracle-dz/UniFAR-FTUs huggingface dataset:
Internet-based behavioural activation therapy versus online psychoeducation for self-reported suicidal ideation in individuals with depression in Indonesia: a secondary analysis of an RCT

Background Southeast Asia has the highest suicide mortality worldwide. To improve our knowledge on the effectiveness of interventions for suicidal ideation (SI) in individuals with depression in Indonesia, we conducted a secondary analysis of a randomised controlled trial. Objective We explored whether an internet-based behavioural activation (BA) intervention (‘Guided Act and Feel Indonesia’ (GAF-ID)) was superior in targeting SI compared with online-delivered psychoeducation (PE). Methods In total, 313 participants were randomised between treatment allocation. The SI item of the Patient Health Questionnaire-9 was the primary outcome measure. Mediation analyses were conducted to identify if BA at week 10 mediated the relationship between intervention and SI at week 24. Findings The GAF-ID intervention was not superior in reducing SI compared with online minimal PE at week 10 (OR 0.61, 95% CI (0.37 to 1.01)), nor at week 24 (OR 0.84, 95% CI (0.47 to 1.52)). SI at week 24 was not mediated by BA at week 10 (b=−0.03, 95% CI (−0.05 to 0.00), p=0.07). Conclusions In individuals with depression in Indonesia, the GAF-ID intervention was not superior in reducing self-reported SI compared with PE. Also, the association between treatment condition and SI at week 24 was not mediated via BA at week 10. Clinical implications This study supports the need for further research on the efficacy of psychological treatments targeting SI in the Southeast Asia context.
Mediating Effect of Tobacco Dependence on the Association Between Maternal Smoking During Pregnancy and Chronic Obstructive Pulmonary Disease: Case-Control Study

Background Maternal smoking during pregnancy (MSDP) is a known risk factor for offspring developing chronic obstructive pulmonary disease (COPD), but the underlying mechanism remains unclear. Objective This study aimed to explore whether the increased COPD risk associated with MSDP could be attributed to tobacco dependence (TD). Methods This case-control study used data from the nationwide cross-sectional China Pulmonary Health study, with controls matched for age, sex, and smoking status. TD was defined as smoking within 30 minutes of waking, and the severity of TD was assessed using the Fagerstrom Test for Nicotine Dependence. COPD was diagnosed when the ratio of forced expiratory volume in 1 second to forced vital capacity was <0.7 in a postbronchodilator pulmonary function test according to the 2017 Global Initiative for Chronic Obstructive Lung Disease criteria. Logistic regression was used to examine the correlation between MSDP and COPD, adjusting for age, sex, BMI, educational attainment, place of residence, ethnic background, occupation, childhood passive smoking, residential fine particulate matter, history of childhood pneumonia or bronchitis, average annual household income, and medical history (coronary heart disease, hypertension, and diabetes). Mediation analysis examined TD as a potential mediator in the link between MSDP and COPD risk. The significance of the indirect effect was assessed through 1000 iterations of the “bootstrap” method. Results The study included 5943 participants (2991 with COPD and 2952 controls). Mothers of the COPD group had higher pregnancy smoking rates (COPD: n=305, 10.20%; controls: n=211, 7.10%; P<.001). TD was more prevalent in the COPD group (COPD: n=582, 40.40%; controls: n=478, 33.90%; P<.001). After adjusting for covariates, MSDP had a significant effect on COPD (β=.097; P<.001). There was an association between MSDP and TD (β=.074; P<.001) as well as between TD and COPD (β=.048; P=.007). Mediation analysis of TD in the MSDP-COPD association showed significant direct and indirect effects (direct: β=.094; P<.001 and indirect: β=.004; P=.03). The indirect effect remains present in the smoking population (direct: β=.120; P<.001 and indirect: β=.002; P=.03). Conclusions This study highlighted the potential association between MSDP and the risk of COPD in offspring, revealing the mediating role of TD in this association. These findings contribute to a deeper understanding of the impact of prenatal tobacco exposure on lung health, laying the groundwork for the development of relevant prevention and treatment strategies.
Effect of Antibiotic Spacer Dosing on Treatment Success in Two-Stage Exchange for Periprosthetic Joint Infection

Introduction: In two-stage exchange for periprosthetic joint infection (PJI), adding antibiotics to cement spacers is the standard of care; however, little is known about optimal dosage. There is emphasis on using >3.6 g of total antibiotic, including ≥2.0 g of vancomycin, per 40 g of cement, but these recommendations lack clinical evidence. We examined whether recommended antibiotic spacer doses affect treatment success. Methods: This was a retrospective review of 202 patients who underwent two-stage exchange for PJI from 2004 to 2020 with at least 1-year follow-up. Patients were separated into high (>3.6 g of total antibiotic per 40 g of cement) and low-dose spacer groups. Primary outcomes were overall and infectious failure. Results: High-dose spacers were used in 80% (162/202) of patients. High-dose spacers had a reduced risk of overall (OR, 0.37; P = 0.024) and infectious (OR, 0.35; P = 0.020) failure for infected primary arthroplasties, but not revisions. In multivariate analysis, vancomycin dose ≥2.0 g decreased the risk of infectious failure (OR, 0.31; P = 0.016), although not overall failure (OR, 0.51; P = 0.147). Conclusion: During two-stage exchange for PJI, spacers with greater than 3.6 g of total antibiotic may reduce overall and infectious failure for infected primary arthroplasties. Furthermore, using at least 2.0 g of vancomycin could independently decrease the risk of infectious failure.
BIO-EKOLOGI TUMBUHAN OBAT KEDAWUNG (Parkia timoriana (DC) Merr.) DI HUTAN ALAM TAMAN NASIONAL MERU BETIRI (Bioecological of kedawung (Parkia timoriana (DC) Merr.) medicinal plant in natural forest Meru Betiri National Park)

The article was describe some aspect of bioecological Parkia timoriana DC Merr in Meru Betiri National Park i.e. ecological characteristis, population dan regenration status, seed production, seed dispersal dan seed distributor, spatial distribution of parkia, and relation of parkia abundance and community interaction and distance of village to the forest (parkia habitat). In Meru Betiri National Park, tke parkia was found at 0 -500 m upper sea, topographyi 0-125 % (general 40 %), land pH 5 – 7. Total population of parkia in natural forest only 200 individu and naturally regeration process was very low. As a intolerant species, parkia was needed most sun radiation to sprout the seed and growth of parkia. The pattern of spatial distribution and abundance of parkia were relating to the interaction intensity of people to parkia and the distance of communities village to the parkia habitat in natural forest. In this case, the parkia abundance were found in natural forest where people who has highest interaction with parkia and nearest distance of communities village to the natural forest as parkia habitat. Peoples as parkia harvester was actor in parkia distribution and parkia seed dispersal in Meru Betiri National Park.
Managing the impacts of dingoes and other wild dogs

Australia's wild dogs include dingoes, introduced around 4000 years ago, feral domestic dogs and hybrids between the two. They are widely distributed throughout Australia. Predation and harassment of stock by wild dogs causes millions of dollars worth of losses to Australian sheep, cattle and goat producers each year. There are also opportunity costs in areas where sheep are not grazed because of the high risk of wild dog predation. For this reason, wild dog control is a significant expense for many pastoralists and government agencies. Yet conservation of pure dingoes is also important and is threatened by their hybridisation with feral domestic dogs on the mainland.
Nuclear pore dysfunction and disease: a complex opportunity

ABSTRACT The separation of genetic material from bulk cytoplasm has enabled the evolution of increasingly complex organisms, allowing for the development of sophisticated forms of life. However, this complexity has created new categories of dysfunction, including those related to the movement of material between cellular compartments. In eukaryotic cells, nucleocytoplasmic trafficking is a fundamental biological process, and cumulative disruptions to nuclear integrity and nucleocytoplasmic transport are detrimental to cell survival. This is particularly true in post-mitotic neurons, where nuclear pore injury and errors to nucleocytoplasmic trafficking are strongly associated with neurodegenerative disease. In this review, we summarize the current understanding of nuclear pore biology in physiological and pathological contexts and discuss potential therapeutic approaches for addressing nuclear pore injury and dysfunctional nucleocytoplasmic transport.
RelayAttention for Efficient Large Language Model Serving with Long System Prompts

Practical large language model (LLM) services may involve a long system prompt, which specifies the instructions, examples, and knowledge documents of the task and is reused across numerous requests. However, the long system prompt causes throughput/latency bottlenecks as the cost of generating the next token grows w.r. t. the sequence length. This paper aims to improve the efficiency of LLM services that involve long system prompts. Our key observation is that handling these system prompts requires heavily redundant memory accesses in existing causal attention computation algorithms. Specifically, for batched requests, the cached hidden states (i.e., key-value pairs) of system prompts are transferred from off-chip DRAM to on-chip SRAM multiple times, each corresponding to an individual request. To eliminate such a redundancy, we propose RelayAttention, an attention algorithm that allows reading these hidden states from DRAM exactly once for a batch of input tokens. RelayAttention is a free lunch: it maintains the generation quality while requiring no model retraining, as it is based on a mathematical reformulation of causal attention. Code is available at \url{https://github.com/rayleizhu/vllm-ra}.
Baryogenesis and leptogenesis with relativistic bubble walls

In this talk, we study the impact of first order phase transitions with fast bubble walls on mechanisms of leptogenesis and baryogenesis. We begin our exploration with the usual leptogenesis where the breaking of $B-L$ occurs via a PT with fast walls. Then we move to a more exotic case where the $B-L$ breaking phase transition creates heavy particles in the plasma and catalizes the leptogenesis. Finally, we apply the same production mechanism to the EWPT at low energy and build a new model of EWBG. Those models are all original and contain crucial new phenomenological aspects like the emission of large amount of Gravitational waves.
MENTOR: Guiding Hierarchical Reinforcement Learning with Human Feedback and Dynamic Distance Constraint

Hierarchical reinforcement learning (HRL) provides a promising solution for complex tasks with sparse rewards of intelligent agents, which uses a hierarchical framework that divides tasks into subgoals and completes them sequentially. However, current methods struggle to find suitable subgoals for ensuring a stable learning process. Without additional guidance, it is impractical to rely solely on exploration or heuristics methods to determine subgoals in a large goal space. To address the issue, We propose a general hierarchical reinforcement learning framework incorporating human feedback and dynamic distance constraints (MENTOR). MENTOR acts as a"mentor", incorporating human feedback into high-level policy learning, to find better subgoals. As for low-level policy, MENTOR designs a dual policy for exploration-exploitation decoupling respectively to stabilize the training. Furthermore, although humans can simply break down tasks into subgoals to guide the right learning direction, subgoals that are too difficult or too easy can still hinder downstream learning efficiency. We propose the Dynamic Distance Constraint (DDC) mechanism dynamically adjusting the space of optional subgoals. Thus MENTOR can generate subgoals matching the low-level policy learning process from easy to hard. Extensive experiments demonstrate that MENTOR uses a small amount of human feedback to achieve significant improvement in complex tasks with sparse rewards.
Discrete slip plane analysis of ferrite microtensile tests: On the influence of dislocation source distribution and non-Schmid effects on slip system activity

The slip system activity in microtensile tests of ferrite single crystals is compared with predictions made by the discrete slip plane model proposed by Wijnen et al. (International Journal of Solids and Structures 228, 111094, 2021). This is an extension of conventional crystal plasticity in which the stochastics and physics of dislocation sources are taken into account in a discrete slip band. This results in discrete slip traces and non-deterministic mechanical behavior, similar to what is observed in experiments. A detailed analysis of which slip systems are presumed to be active in experiments is performed. In small-scale mechanical tests on BCC metals and alloys, non-Schmid effects are often needed to explain the observed response. Therefore, these effects are incorporated into the model by extending a non-Schmid framework commonly used to model {110} slip to {112} planes. The slip activity in the simulations is compared to the slip activity in single crystal ferrite microtensile tests. This is done for the discrete slip plane model with and without non-Schmid effects, as well as for a conventional crystal plasticity model. The conventional crystal plasticity model fails to predict the diversity in active slip systems that is observed experimentally. The slip activity obtained with the discrete slip plane model is in convincingly better agreement with the experiments. Including non-Schmid effects only entails minor differences. This suggests that stochastic effects dominate the behavior of ferrite crystals with dimensions in the order of a few micrometers and that non-Schmid effects may not play a large role.
ACE : Off-Policy Actor-Critic with Causality-Aware Entropy Regularization

The varying significance of distinct primitive behaviors during the policy learning process has been overlooked by prior model-free RL algorithms. Leveraging this insight, we explore the causal relationship between different action dimensions and rewards to evaluate the significance of various primitive behaviors during training. We introduce a causality-aware entropy term that effectively identifies and prioritizes actions with high potential impacts for efficient exploration. Furthermore, to prevent excessive focus on specific primitive behaviors, we analyze the gradient dormancy phenomenon and introduce a dormancy-guided reset mechanism to further enhance the efficacy of our method. Our proposed algorithm, ACE: Off-policy Actor-critic with Causality-aware Entropy regularization, demonstrates a substantial performance advantage across 29 diverse continuous control tasks spanning 7 domains compared to model-free RL baselines, which underscores the effectiveness, versatility, and efficient sample efficiency of our approach. Benchmark results and videos are available at https://ace-rl.github. io/.
Efecto inhibidor del aceite esencial de Thymus Vulgaris L. (Tomillo) Y Rosmarinus Officinalis (Romero) en diferentes concentraciones frente A cepas de Porphyromona Gingivalis

xv INTRODUCCIÓN . 1 CAPÍTULO I . 2 1. EL PROBLEMA . 2 1.1. Planteamiento del problema . 2 1.2. Objetivos . 3 1.2.1. Objetivo general . 3 1.2.2. Objetivos específicos . 3 1.3. Justificación . 4 1.4. Hipótesis . 5 1.4.1. Hipótesis de investigación. 5 1.4.2. Hipótesis nula . 5 CAPÍTULO II . 6 2. MARCO TEÓRICO . 6 2.1. Aceite esencial . 7 viii 2.2. Thymus vulgaris L. (Tomillo) . 7 2.2.1. Clasificación taxonómica del tomillo . 9 2.2.2. Propiedades medicinales . 9 2.3. Rosmarinus officinalis (Romero) . 10 2.3.1. Composición química . 11 2.3.2. Principios activos . 11 2.3.3. Aceites esenciales. 12 2.3.4. Propiedades medicinales . 13 2.3.5. Actividad antimicrobiana en odontología . 15 2.4. Porphyromona gingivalis . 15 2.4.1. Definición . 15 2.4.2. Taxonomía. 16 2.4. 3. Factores de virulencia . 16 2.4. 4. Fisiopatología . 18 2.5. Enfermedad periodontal . 18 2.5.1. Definición . 18 2.5.2. Síntomas . 19 2.5. 3. Clasificación de las enfermedades periodontales . 20 CAPÍTULO III . 25 3. DISEÑO METODOLÓGICO . 25 3.1. Diseño de la investigación . 25 3.2. Población de estudio y muestra . 25 3.3. Criterios de inclusión y exclusión . 27 3.3.1. Criterios de inclusión . 27 3.3.2. Criterios de exclusión . 27 3.4. Conceptualización de variables . 27 3.4.1. Variables independientes . 27 3.4.2. Variable dependiente . 28 ix 3.4. 3. Variables intervinientes . 28 3.5. Definición operacional de variables . 29 3.6. Estandarización . 30 3.7. Manejo y métodos de recolección de datos . 30 3.8. Aspectos bioéticos . 40 3.9. Aspectos metodológicos . 40 CAPÍTULO IV . 42 4. ANÁLISIS DE RESULTADOS . 42 4.1. Estudio estadístico . 42 4.2. Discusión . 54 CAPÍTULO V . 57 5. CONCLUSIONES Y RECOMENDACIONES . 57 5.1. Conclusiones . 57 5.2. Recomendaciones . 58 BIBLIOGRAFÍA . 59 ANEXOS . 64
First-principle tight-binding approach to angle-resolved photoemission spectroscopy simulations: importance of light-matter gauge and ubiquitous interference effects

Angle-resolved photoemission spectroscopy (ARPES) is one of the most powerful techniques to study the electronic structure of materials. To go beyond the paradigm of band mapping and extract aspects of the Bloch wave-functions, the intricate interplay of experimental geometry, crystal structure, and photon polarization needs to be understood. In this work we discuss several model approaches to computing ARPES signals in a unified fashion. While we represent the Bloch wave-functions by first-principle Wannier functions, we introduce different approximations to the final states and discuss the implications for the predictive power. We also introduce various light-matter gauges and explain the role of the inevitable breaking of gauge invariance.Finally, we benchmark the different models for the two-dimensional semiconductor WSe$_2$, known for its strong Berry curvature, orbital angular momentum (OAM), and nontrivial orbital texture. The models are compared based on their ability to simulate photoemission intensity and interpret circular dichroism in ARPES (CD-ARPES). We show that interference effects are crucial to understanding the circular dichroism, and explain their photon-energy dependence. Our in-depth analysis provides insights into the advantages and limitations of various model approaches in clarifying the complex interplay between experimental observables and underlying orbital texture in materials.
Local Manipulation of Skyrmion Lattice in Fe3GaTe2 at Room Temperature

Motivated by advances in spintronic devices, an extensive exploration is underway to uncover materials that host topologically protected spin textures, exemplified by skyrmions. One critical challenge involved in the potential application of skyrmions in van der Waals (vdW) materials is the attainment and manipulation of skyrmions at room temperature. In this study, we report the creation of intrinsic skyrmion state in van der Waals ferromagnet Fe3GaTe2. By employing variable temperature magnetic force microscopy, the skyrmion lattice can be locally manipulated on Fe3GaTe2 flake. The ordering of skyrmion state is further analyzed. Our result suggest Fe3GaTe2 emerges as a highly promising contender for the realization of skyrmion-based layered spintronic memory devices.
Localised Natural Causal Learning Algorithms for Weak Consistency Conditions

By relaxing conditions for natural structure learning algorithms, a family of constraint-based algorithms containing all exact structure learning algorithms under the faithfulness assumption, we define localised natural structure learning algorithms (LoNS). We also provide a set of necessary and sufficient assumptions for consistency of LoNS, which can be thought of as a strict relaxation of the restricted faithfulness assumption. We provide a practical LoNS algorithm that runs in exponential time, which is then compared with related existing structure learning algorithms, namely PC/SGS and the relatively recent Sparsest Permutation algorithm. Simulation studies are also provided.
Magnitude homology is a derived functor

We prove that the magnitude (co)homology of an enriched category can, under some technical assumptions, be described in terms of derived functors between certain abelian categories. We show how this statement is specified for the cases of quasimetric spaces, finite quasimetric spaces, and finite digraphs. For quasimetric spaces, we define the notion of a magnitude module over a quasimetric space, define the functor of (co)invariants of a magnitude module and show that the magnitude (co)homology can be presented via its derived functors. As a corollary we obtain that the magnitude cohomology of a quasimetric space can be presented in terms of Ext functors in the category of magnitude modules. For finite quasimetric spaces, we show that magnitude (co)homology can be presented in terms of Tor and Ext functors over a certain graded algebra. For finite digraphs, this graded algebra is a bound quiver algebra. In addition, we show that the magnitude cohomology algebra of a finite quasimetric space can be described as a Yoneda algebra.
Quadruplet Loss For Improving the Robustness to Face Morphing Attacks

Recent advancements in deep learning have revolutionized technology and security measures, necessitating robust identification methods. Biometric approaches, leveraging personalized characteristics, offer a promising solution. However, Face Recognition Systems are vulnerable to sophisticated attacks, notably face morphing techniques, enabling the creation of fraudulent documents. In this study, we introduce a novel quadruplet loss function for increasing the robustness of face recognition systems against morphing attacks. Our approach involves specific sampling of face image quadruplets, combined with face morphs, for network training. Experimental results demonstrate the efficiency of our strategy in improving the robustness of face recognition networks against morphing attacks.
Parking of Connected Automated Vehicles: Vehicle Control, Parking Assignment, and Multi-agent Simulation

This paper introduces a novel approach to optimize the parking efficiency for fleets of Connected and Automated Vehicles (CAVs). We present a novel multi-vehicle parking simulator, equipped with hierarchical path planning and collision avoidance capabilities for individual CAVs. The simulator is designed to capture the key decision-making processes in parking, from low-level vehicle control to high-level parking assignment, and it enables the effective assessment of parking strategies for large fleets of ground vehicles. We formulate and compare different strategic parking spot assignments to minimize a collective cost. While the proposed framework is designed to optimize various objective functions, we choose the total parking time for the experiment, as it is closely related to the reduction of vehicles' energy consumption and greenhouse gas emissions. We validate the effectiveness of the proposed strategies through empirical evaluation against a dataset of real-world parking lot dynamics, realizing a substantial reduction in parking time by up to 43.8%. This improvement is attributed to the synergistic benefits of driving automation, the utilization of shared infrastructure state data, the exclusion of pedestrian traffic, and the real-time computation of optimal parking spot allocation.