Miracle-dz/UniFAR-FTUs huggingface dataset:
Lithosphere-mantle interactions

We study the interaction between lithospheric dynamics and mantle convection to establish a comprehensive model of large-scale deformation that can be tested using a variety of surface observables. In chapter 1 we explore subduction and upper-mantle convection using fluid-dynamic models. Comparing results from analog and numerical experiments, we show that key observations in subduction zones can be explained using fluid flow. We analyze contrasting styles of back-arc deformation based on the balance between viscous dissipation and gravitational energy release in the subducting plate. By combining a wide range of geological and geophysical data in chapter 2 we are able to reconstruct the subduction history of the Central Mediterranean. Subduction initiated slowly and lead to episodic back-arc spreading, as predicted from our models for predominantly slabpull driven subduction. Based on these regional studies, we estimate global deformation in the lithosphere from spherical-circulation calculations. Chapter 3 describes a comprehensive and quantitative comparison between mantle models from tomography and geodynamics. Establishing such a benchmark for three-dimensional structure is important if we want to move from the mapping phase of tomography to hypothesis testing. To examine the dynamic self-consistency of our flow models, we study the torques on the plates in chapter 4 and reevaluate arguments of the plate-driving force discussion. We substantiate the finding that slab pull contributes most to the driving forces but find that a range of models can explain plate motions. Velocity inversions are shown to have limited sensitivity to parameterized plate-boundary forces, here included in a velocity model for the first time. Chapter 5 deals with a first application of our deformation model: the prediction of finite-strain development in the uppermost mantle and its comparison with seismic anisotropy. We can fit a range of anisotropy data for oceanic and young continental plate-regions and compare our global models with surface-wave derived azimuthal anisotropy. Alignment of fast propagation axes with finite strain leads to low misfits and better results than the absolute plate motion hypothesis. Three-dimensional flow modeling with realistic plate geometries may provide the needed tool to interpret seismic anisotropy quantitatively as an indicator of mantle flow.
Upaya Perlindungan Hukum Bagi Para Konsumen Pemegang Aset Kripto di Indonesia

This research focuses on analyzing the regulations governing the legal aspects related to crypto assets and their protection. Within this analysis, attention is directed toward the three fundamental pillars of Indonesian law, namely justice, certainty, and expediency. Additionally, this study identifies two pertinent issues. The first pertains to legal regulations concerning the legitimacy of crypto assets. The second involves the form of legal protection provided to holders of crypto assets in general, as well as to those who possess NFT and SFT-based crypto assets specifically. The findings of this study outline several strategies aimed at enhancing regulations governing the trade, use, and circulation of crypto assets in Indonesia. These strategies encompass protective measures that guarantee the quality of block chain technology system performance, ensure value preservation in crypto asset trading, facilitate dispute resolution in crypto asset trading, and endeavor to safeguard Intellectual Property Rights (IPR) in crypto asset trading.
How do thinking styles and STEM attitudes have effects on computational thinking? A structural equation modeling analysis

Computational thinking (CT) is vital for success in numerous domains. However, the nature, definition, and scope of CT are ill‐defined, and research on how best to develop CT is very limited. This study focused on how thinking styles and STEM attitudes have effects on computational thinking. Using a proportionate stratified random sampling procedure, 1195 students from two universities were surveyed. A structural equation modeling analysis showed that students' thinking styles and STEM attitudes directly predicted their computational thinking skills and that thinking styles mediated the relationship between STEM attitudes and computational thinking skills. Thinking styles and STEM attitudes are strong predictors of CT skills. Based on the results, we recommended that the conceptualization of CT be broadened to reflect its trans‐disciplinary nature within the context of STEM education. This study adds to the limited theoretical understanding of CT and CT‐predictors in higher education, which has been studied much less than in K‐12 education.
Two common, often coexisting grassland plant species differ in their evolutionary potential in response to experimental drought

Abstract For terrestrial plant communities, the increase in frequency and intensity of drought events is considered as one of the most severe consequences of climate change. While single‐species studies demonstrate that drought can lead to relatively rapid adaptive genetic changes, the evolutionary potential and constraints to selection need to be assessed in comparative approaches to draw more general conclusions. In a greenhouse experiment, we compare the phenotypic response and evolutionary potential of two co‐occurring grassland plant species, Bromus erectus and Trifolium pratense, in two environments differing in water availability. We quantified variation in functional traits and reproductive fitness in response to drought and compared multivariate genetic variance–covariance matrices and predicted evolutionary responses between species. Species showed different drought adaptation strategies, reflected in both their species‐specific phenotypic plasticity and predicted responses to selection indicating contrasting evolutionary potential under drought. In T. pratense we found evidence for stronger genetic constraints under drought compared to more favourable conditions, and for some traits plastic and predicted evolutionary responses to drought had opposing directions, likely limiting the potential for adaptive change. Our study contributes to a more detailed understanding of the evolutionary potential of species with different adaptive strategies in response to climate change and may help to inform future scenarios for semi‐natural grassland ecosystems.
A scientific foundation for informed management decisions: Quantifying the abundance, important habitat and cumulative exposure of the Hawaii Island spinner dolphin (Stenella longirostris) stock to human activities

Coastal dolphin populations are exposed to non-consumptive human activities that can pose conservation challenges. Consequently, effective management strategies, using rigorous scientific assessments of exposed populations, are needed to mitigate any potential negative impacts of these activities. To inform management decisions for the conservation of the Hawaii Island spinner dolphin (Stenella longirostris) stock, I: (i) estimated abundance and survival rates; (ii) measured the effectiveness of various sampling scenarios to detect changes in abundance; (iii) identified important spinner dolphin resting habitats; and (iv) measured cumulative exposure to human activities. Between September 2010 and March 2013, boat-based and land-based sampling was undertaken to collect dolphin photo-identification, group behaviour and acoustic data from both inside and outside four important spinner dolphin resting bays on the Kona Coast of Hawaii Island. Between years, independent survival rate estimates were similar (0.97 ± 0.05 SE), and abundance estimates of 631 (95% CI 524-761) and 668 (95% CI 556-801; CV =0.09) were very consistent. At this precision, and with 95% power and a monitoring interval of three years, a 5% change in abundance would not be detected for 12 years. I documented that should resting spinner dolphins be displaced from resting bays, they are unlikely to engage in rest behaviour elsewhere. When resting inside bays, dolphins were most likely to rest between 10:00-14:00, and over sandy substrates. Individual spinner dolphins spent between 49.5% and 69.4% of daytime resting (mean = 61.7%). Dolphins were chronically and repeatedly exposed to human activities during daytime hours (> 82% of time), with a median duration of only ten min between interactions. The short interval between interactions may prevent recovery from disturbance and deprive individuals of rest and change their sleep state from “deep” to “light”. Rest deprivation and the disruption of sleep can lead to impaired cognitive abilities and ultimately effect population viability. These data provide a firm baseline for urgent consideration by managers to evaluate the risks to the spinner dolphins of Hawaii Island, potential pathways for mitigating human interactions and ways to measure the success of management interventions.
Small Area Estimation with a Multivariate Spatial-Temporal Model

A multivariate generalization of a spatial-temporal model is postulated and used in model-based small area estimation where small area information is borrowed from other units through spatial and temporal correlations. An estimation procedure that combined the backfi tting algorithm, AR-sieve bootstrap and Lorenz curve parameterization is proposed. The procedure is illustrated using data on mean per capita income quintiles of households in the Philippines with provincial unit of analysis. The generation of unitrecord synthetic household income is feasible even if modeling is done at the provincial level. Estimates of poverty indices based on the synthetic unit-record data generated from the multivariate spatial-temporal model are more reliable than the direct survey estimates. There are only small deviations between the modelbased and direct survey estimates of poverty indices at the domain level that validates the accuracy of the model-based small area estimates generated from the multivariate spatial-temporal model.
The efficacy and practicality of the Neurotrack Cognitive Battery assessment for utilization in clinical settings for the identification of cognitive decline in an older Japanese population

Introduction Japan has the largest aging population with 33% of the population over the age of 60 years. The number of Japanese adults with dementia is estimated to be approximately 4.6 million, comprising nearly 15% of the older adult population. It is critical to administer cognitive assessments early in the disease state that have high reliability and low user burden to detect negative cognitive changes as early as possible; however, current preclinical AD detection methods are invasive, time-consuming, and expensive. A number of traditional and digital cognitive assessments are also available, but many of these tests are time-consuming, taxing to the user, and not widely scalable. The purpose of this study was to incorporate a digital cognitive assessment battery into a standard clinical assessment performed within a Japanese-based neuropsychology clinic to assess the diagnostic accuracy and the relationship between the digital Neurotrack Cognitive Assessment Battery (N-CAB) to traditional cognitive assessments. Methods Healthy individuals and probable Alzheimer's patients completed the N-CAB, as well as two traditional cognitive assessments, the Mini Mental Status Exam (MMSE) and the Revised Hasegawa's Dementia Scale (HDS-R). Results Our results demonstrate the Image Pairs hand-response phase of the N-CAB had the highest diagnostic accuracy with 95% sensitivity and 89% specificity to probable Alzheimer's disease. This was closely followed by the Symbol Match assessment, with a 96% sensitivity and 74% specificity to probable Alzheimer's disease. Additionally, Symbol Match and Path Points used in combination resulted in a sensitivity of 94%, specificity of 90%; a model with all N-CAB assessments resulted in a sensitivity and specificity of 100%. All N-CAB assessments had moderate to strong and significant correlations with the MMSE and HDS-R. Discussion Together, this suggests that the N-CAB assessment battery may be an appropriate alternative for the clinical screening of cognition for earlier detection of Alzheimer's disease.
Antibiotic Use in Patients Undergoing Complex Clean-Contaminated Head and Neck Surgery: A Prospective Study

Aims and Objectives: Oncological surgery of the upper aerodigestive tract is a complex procedure and often includes neck dissection and flap reconstruction. It can be complicated by severe surgical site infection (SSI) leading to flap necrosis, delayed wound healing, and increasing mortality and morbidity. The purpose of this study is to perform a systematic descriptive analysis and to evaluate the effect of our adapted antibiotic regimen strategy on postoperative outcomes. Materials and Methods: A prospective cohort analysis of 47 patients undergoing major clean-contaminated head and neck surgery was conducted at the Cervicomaxillofacial Surgery Department (Saint-Pierre Hospital), between 2019 and 2022. The patients were divided into two groups: group I, which received a short-term postoperative antibiotic regimen for 24 h, and group II, which received a more extended postoperative antibiotic course for more than 24 h. Antibioprophylaxy amoxicillin and clavulanate were administered intravenously 30–60 min before making the incision. The antibiotic regimen was continued after surgery. The prognostic significance of the antibiotic regimen on postoperative outcomes, including clinical signs of infection and biological markers such as white blood cells count, and C-reactive protein levels was evaluated using univariate analysis. Results: Eighteen patients developed SSIs. All of these infections were grade 2 and were treated with antibiotics. After univariate analysis, only a history of hypothyroidism seems to be a predictor of SSI (P = 0.038). No significant difference was found in terms of onset and hospital stay when we compared the patients who received antibiotics for 24 h or more. Moreover, the rate of multidrug-resistant bacteria was not different in both groups. Conclusions: Our results suggest that postoperative antibiotics for more than 24 h do not confer benefit in terms of SSI. Oncological patients undergoing complex clean-contaminated head and neck surgery are often suffering from infectious complications and, despite the absence of guidelines, practicians should consider these findings in their decision-making.
Cross Modal Compression With Variable Rate Prompt

Traditional image/video compression compresses the highly redundant visual data while preserving signal fidelity. Recently, cross modal compression (CMC) is proposed to compress the data into a compact, human-comprehensible domain (such as text) with an ultra-high compression ratio while preserving semantic fidelity for machine analysis and semantic monitoring. CMC is with a constant rate because the CMC encoder can only represent the data with a fixed grain. But in practice, variable rate is necessary due to the complicated and dynamic transmission conditions, the different storage mediums, and the diverse levels of application requirements. To deal with this problem, in this paper, we propose variable rate cross modal compression (VR-CMC), where we introduce variable rate prompt to represent the data with different grains. Variable rate prompt is composed of three strategies. Specifically, 1) target length prompt (TLP) introduces the target length into the language prompt to guide the generation of the text representation; 2) decaying EOS probability (DEP) exponentially decays the probability of the EOS token with regard to the decoding step and target length, where the EOS (end-of-sequence) token is a special token indicating the end of the text; 3) text augmentation (TA) enriches the training data and makes the text representation length more balanced when training. Experimental results show that our proposed VR-CMC can effectively control the rate in the CMC framework and achieve state-of-the-art performance on MSCOCO and IM2P datasets.
Microspherophakic Angle Closure Glaucoma in a Patient with Coffin-Siris Syndrome: Case Report

Background Bilateral secondary angle closure glaucoma is a presenting symptom of microspherophakia and ectopia lentis. Characterizing the associated syndrome and confirmation by genetic testing can identify associated systemic abnormalities and provide appropriate genetic counseling. Case Presentation A 42-year-old woman with severe intellectual disability presented with light perception visual acuity and glaucoma, with intraocular pressure (IOP) in her right and left eyes of 69 and 70 mmHg, respectively. She underwent two sessions of 270-degree laser diode transscleral cytophotocoagulation treatment at a 6-month interval and was prescribed topical anti-glaucoma medication. Her family noticed a progressive decrease in her vision while on treatment for 2 years. She was diagnosed with apparent Weill-Marchesani syndrome, accompanied by angle closure glaucoma and microspherophakia. Cataract surgery and intraocular lens implantation were successful in both eyes and post-operative IOP was controlled with anti-glaucoma medication but her vision did not improve from severe glaucomatous optic neuropathy. Her underlying syndrome was investigated genetically by whole exome sequencing. Results Sequencing showed a pathogenic variant in ARID1B, c.3955dupC (p.Gln1319Profs*14), diagnostic of Coffin-Siris syndrome. This is the first report of Coffin-Siris syndrome associated with microspherophakia and angle closure glaucoma. Conclusion Bilateral angle closure glaucoma from ectopia lentis in patients with genetic syndromes could be an indicator of microspherophakia in adulthood. Ophthalmological surveillance is important in patients with Coffin-Siris syndrome.
Comparative study of environmental regulations in Latin America.

Air quality regulations describe the quality level enforced by the regulating authority. These regulations have been established as an attempt to reduce and control the negative impact of air pollution upon the environment and human health. They are based upon the concentration levels of pollutants that are considered non-hazardous for each individual, including the more vulnerable population like children and the elderly. This study presents an analysis of current environmental regulations for permitted PTS, PM10, PM2.5, CO, NO2, SO2, and O3 concentration levels in thirteen Latin-American countries (LACs), and their comparison with similar regulations established by the United States Environmental Protection Agency (US EPA) and the World Health Organization (WHO). Most LACs reproduce US EPA standards, regardless of their specific regional circumstances; however, they do not update these standards at the frequency the US EPA does. Few regulations follow WHO recommendations. Concerns are raised regarding LACs capabilities to effectively monitor air quality and enforce compliance.
Two-Stage Focus Measurement Network with Joint Boundary Refinement for Multifocus Image Fusion

Focus measurement, one of the key tasks in multifocus image fusion (MFIF) frameworks, identifies the clearer parts of multifocus images pairs. Most of the existing methods aim to achieve disposable pixel-level focus measurement. However, the lack of sufficient accuracy often gives rise to misjudgments in the results. To this end, a novel two-stage focus measurement with joint boundary refinement network is proposed for MFIF. In this work, we adopt a coarse-to-fine strategy to gradually achieve block-level and pixel-level focus measurement for producing more fine-grained focus probability maps, instead of directly predicting at the pixel level. In addition, the joint boundary refinement optimizes the performance on the focused/defocused boundary component (FDB) during the focus measurement. To improve feature extraction capability, both CNN and transformer are employed to, respectively, encode local patterns and capture long-range dependencies. Then, the features from two input branches are legitimately aggregated by modeling the spatial complementary relationship in each pair of multifocus images. Extensive experiments demonstrate that the proposed model achieves state-of-the-art performance in both subjective perception and objective assessment.
Impact of sleep quality on glycaemic control in type 2 diabetes: a cross-sectional study

Background: Inadequate sleep is associated with type 2 diabetes (T2DM) and has a negative impact on glycaemic management. The purpose of this research was to examine the relationship between sleep quality and glucose control in individuals with T2DM. Methods: A cross-sectional study was conducted at the Family Medicine Clinic of University of Ilorin Teaching Hospital (UITH), a tertiary hospital in North-Central Nigeria. Three hundred and seventy-eight participants took part in the research (103 men and 275 women). Questionnaires were used to compile the data, and the Pittsburgh Sleep Quality Index was included. Diabetic indicators were gathered using a combination of a thorough medical history assessment and a battery of diagnostic testing. Statistical analysis was conducted using the SPSS software version 20.0. Results: The median age of the respondents was 61.01 (S.D. ± 9.8) years. Seventy-four percent (74%) of people reported having poor sleep quality, 45.5% had poorly controlled diabetes, and 29.9% were obese. Inadequate sleep or poor sleep quality was shown to be statistically linked with poor glycaemic management (p= 0.0001). There were significant associations between glycaemic management and subjective sleep quality (OR 1.495, 95% C.I 1.039-2.152), sleep disturbances (OR 0.279, 95% C.I 0.122-0.636), and daytime dysfunction (OR 3.571, 95% C.I 2.253-5.662). Conclusion: This research shows that poor glycaemic management is linked to poor sleep quality in people with T2DM.
A Review of Hybrid VLC/RF Networks: Features, Applications, and Future Directions

The expectation for communication systems beyond 5G/6G is to provide high reliability, high throughput, low latency, and high energy efficiency services. The integration between systems based on radio frequency (RF) and visible light communication (VLC) promises the design of hybrid systems capable of addressing and largely satisfying these requirements. Hybrid network design enables complementary cooperation without interference between the two technologies, thereby increasing the overall system data rate, improving load balancing, and reducing non-coverage areas. VLC/RF hybrid networks can offer reliable and efficient communication solutions for Internet of Things (IoT) applications such as smart lighting, location-based services, home automation, smart healthcare, and industrial IoT. Therefore, hybrid VLC/RF networks are key technologies for next-generation communication systems. In this paper, a comprehensive state-of-the-art study of hybrid VLC/RF networks is carried out, divided into four areas. First, indoor scenarios are studied considering lighting requirements, hybrid channel models, load balancing, resource allocation, and hybrid network topologies. Second, the characteristics and implementation of these hybrid networks in outdoor scenarios with adverse conditions are analyzed. Third, we address the main applications of hybrid VLC/RF networks in technological, economic, and socio-environmental domains. Finally, we outline the main challenges and future research lines of hybrid VLC/RF networks.