Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Acute Ketamine Treatment on Sympathetic Regulation Indexed by Electrodermal Activity in Adolescent Major Depression

Ketamine is a potential rapid-onset antidepressant characterized by sympathomimetic effects. However, the question of ketamine’s use in treating adolescents’ major depressive disorder (MDD) is still discussed. Thus, we aimed to study the acute effect of ketamine infusion treatment on sympathetic regulation using electrodermal activity (EDA) in addition to an assessment of depressive symptomatology in MDD adolescents. Twenty hospitalized adolescent girls with MDD (average age: 15.0 ± 1.46 yrs.) were examined before and two hours after a single intravenous infusion of ketamine. EDA was continuously recorded for 6 min, and depressive symptoms were assessed before and two hours after ketamine administration. The evaluated parameters included skin conductance level (SCL), nonspecific electrodermal responses (NS-SCRs), MADRS (questions no. 1–10, total score), and CDI (items A–E, total score). EDA parameters showed no significant changes after the ketamine treatment, and depressive symptoms were significantly reduced after the ketamine infusion. The analysis revealed a significant negative correlation between index SCL and CDI-A, CDI-E, and the total CDI score and between index NS-SCRs and MADRS no. 4 before the ketamine treatment. In conclusion, ketamine improved depressive symptomatology without a significant effect on EDA, indicating its potential safety and efficiency as an acute antidepressant intervention in adolescent MDD.
Evidence of impact melt sheet differentiation of the lunar South Pole‐Aitken basin

The South Pole‐Aitken (SPA) basin is the largest basin on the Moon. The basin‐forming impact likely melted the upper part of the mantle and formed an impact melt sheet. Impact melt of large terrestrial craters differentiated following a general magmatic differentiation sequence. However, it is still debated whether or not the SPA melt sheet underwent differentiation. To address this, we investigated the vertical and lateral variations in mineral composition of the SPA impact melt sheet area by analyzing the surface mineralogy including 277 post‐SPA craters using remote sensing reflectance data. We identified a 7 km thick, high‐Ca pyroxene‐rich layer and below that, a >8 km thick, low‐Ca pyroxene‐rich layer. Both filled the entire impact melt sheet area (630 km in diameter). Considering the vast distribution of these two layers, their thicknesses, their FeO abundances (around 13.5 wt %), which are lower than most of the lunar mare basalt but within the estimated range of the differentiated SPA impact melt, and that the observed lithologies are consistent with a differentiation model, we conclude that the SPA impact melt was differentiated. Moreover, based on the lunar magma ocean differentiation model, Al2O3 and CaO abundances of the upper part of the mantle would be much lower after the mantle overturn. If the SPA impact occurred after overturn, these elemental abundances of the initial impact melt would be much lower than that of the before‐overturn impact case and result in different solidified layers. Our observation matches only the after‐overturn case, which may imply that the SPA impact occurred after overturn.
Effects of the "migavica" beach seine on coastal fish communities.

The beach seine "migavica" , whose name originates from a Croatian word meaning "to blink" referring to its meshes during fishing, is the most important and wide distributed bottom beach seine on the eastern Adriatic coast. Although it is mainly allocated for fishing of pickarel ( Spicara smaris L.) during day-time, with the beach seine "migavica" other species of fishes and the other marine organisms can be caught as well, but according to the current Croatian law they must constitute less than 20 % of total weight of caught picarel. The main aim of this study is to establish, on the basis of catch analysis of the beach seine "migavica", the presence of other species of fishes and other organisms in its catch in relation to the presence of pickarel, the presence of young and spawn specimens, especially of the important commercial species, and according to the results obtained, evaluate its effects on coastal fish communities. On the basis of the results of the research it is concluded that the beach seine "migavica" can have harmful influence on those communities.
Wide-Field Choroidal Thickness Analysis after Half-Fluence Photodynamic Therapy Combined with Intravitreal Aflibercept Injection in Pachychoroid Neovasculopathy

Background: Pachychoroid neovasculopathy (PNV) is a pachychoroid-spectrum disease. As blood circulation throughout the choroid may be involved in PNV pathogenesis, analysis using ultra-wide-field (UWF) fundus imaging is crucial. We evaluated choroidal thickness after half-fluence photodynamic therapy (PDT) combined with intravitreal aflibercept injection for PNV using UWF swept-source optical coherence tomography. Methods: Seventeen eyes with PNV that underwent half-fluence PDT with an adjuvant single intravitreal aflibercept injection were analyzed. To compare choroidal thicknesses in the central and peripheral choroids, we set subfields <3, <9, and 9–18 mm from the fovea. The <9 and 9–18 mm subfields were divided into four quadrants. Results: Choroidal thickness in each subfield decreased significantly after half-fluence PDT (p < 0.001); this reduction was more pronounced in the central area. We also investigated the relationship between the dominant side of the deep choroidal veins that harbor choroidal vein efflux from the macula. When choroidal thickness in the supratemporal and infratemporal 9 mm subfields were evaluated, the ratio of choroidal thickness reduction was not significantly different between the dominant and non-dominant sides. The dominant side was not associated with the extent of choroidal thickness reduction in PNV. Conclusions: Half-fluence PDT caused thinning of the entire choroid, especially in the central area, in PNV.
Alteration in gut microbiota is associated with immune imbalance in Graves’ disease

Background Graves’ disease (GD), characterized by immune aberration, is associated with gut dysbiosis. Despite the growing interest, substantial evidence detailing the precise impact of gut microbiota on GD’s autoimmune processes remains exceedingly rare. Objective This study was designed to investigate the influence of gut microbiota on immune dysregulation in GD. Methods It encompassed 52 GD patients and 45 healthy controls (HCs), employing flow cytometry and enzyme-linked immunosorbent assay to examine lymphocyte and cytokine profiles, alongside lipopolysaccharide (LPS) levels. Gut microbiota profiles and metabolic features were assessed using 16S rRNA gene sequencing and targeted metabolomics. Results Our observations revealed a disturbed B-cell distribution and elevated LPS and pro-inflammatory cytokines in GD patients compared to HCs. Significant differences in gut microbiota composition and a marked deficit in short-chain fatty acid (SCFA)-producing bacteria, including ASV263(Bacteroides), ASV1451(Dialister), and ASV503(Coprococcus), were observed in GD patients. These specific bacteria and SCFAs showed correlations with thyroid autoantibodies, B-cell subsets, and cytokine levels. In vitro studies further showed that LPS notably caused B-cell subsets imbalance, reducing conventional memory B cells while increasing naïve B cells. Additionally, acetate combined with propionate and butyrate showcased immunoregulatory functions, diminishing cytokine production in LPS-stimulated cells. Conclusion Overall, our results highlight the role of gut dysbiosis in contributing to immune dysregulation in GD by affecting lymphocyte status and cytokine production.
Artificial Intelligence in the Eyes of Society: Assessing Social Risk and Social Value Perception in a Novel Classification

Artificial intelligence (AI) is a rapidly developing technology that has the potential to create previously unimaginable chances for our societies. Still, the public’s opinion of AI remains mixed. Since AI has been integrated into many facets of daily life, it is critical to understand how people perceive these systems. The present work investigated the perceived social risk and social value of AI. In a preliminary study, AI’s social risk and social value were first operationalized and explored by adopting a correlational approach. Results highlighted that perceived social value and social risk represent two significant and antagonistic dimensions driving the perception of AI: the higher the perceived risk, the lower the social value attributed to AI. The main study considered pretested AI applications in different domains to develop a classification of AI applications based on perceived social risk and social value. A cluster analysis revealed that in the two-dimensional social risk × social value space, the considered AI technologies grouped into six clusters, with the AI applications related to medical care (e.g., assisted surgery) unexpectedly perceived as the riskiest ones. Understanding people’s perceptions of AI can guide researchers, developers, and policymakers in adopting an anthropocentric approach when designing future AI technologies to prioritize human well-being and ensure AI’s responsible and ethical development in the years to come.
Annual Estimates of Recharge, Quick‐Flow Runoff, and Evapotranspiration for the Contiguous U.S. Using Empirical Regression Equations

This study presents new data‐driven, annual estimates of the division of precipitation into the recharge, quick‐flow runoff, and evapotranspiration (ET) water budget components for 2000‐2013 for the contiguous United States (CONUS). The algorithms used to produce these maps ensure water budget consistency over this broad spatial scale, with contributions from precipitation influx attributed to each component at 800 m resolution. The quick‐flow runoff estimates for the contribution to the rapidly varying portion of the hydrograph are produced using data from 1,434 gaged watersheds, and depend on precipitation, soil saturated hydraulic conductivity, and surficial geology type. Evapotranspiration estimates are produced from a regression using water balance data from 679 gaged watersheds and depend on land cover, temperature, and precipitation. The quick‐flow and ET estimates are combined to calculate recharge as the remainder of precipitation. The ET and recharge estimates are checked against independent field data, and the results show good agreement. Comparisons of recharge estimates with groundwater extraction data show that in 15% of the country, groundwater is being extracted at rates higher than the local recharge. These maps of the internally consistent water budget components of recharge, quick‐flow runoff, and ET, being derived from and tested against data, are expected to provide reliable first‐order estimates of these quantities across the CONUS, even where field measurements are sparse.
Techniques for assessing water infrastructure for nonstationary extreme events: a review

ABSTRACT Statistical and physically-based methods have been used for designing and assessing water infrastructure such as spillways and stormwater drainage systems. Traditional approaches assume that hydrological processes evolve in an environment where the hydrological cycle is stationary over time. However, in recent years, it has become increasingly evident that in many areas of the world the foregoing assumption may no longer apply, due to the effect of anthropogenic and climatic induced stressors that cause nonstationary conditions. This has attracted the attention of national and international agencies, research institutions, academia, and practicing water specialists, which has led to developing new techniques that may be useful in those cases where there is good evidence and attribution of nonstationarity. We review the various techniques proposed in the field and point out some of the challenges ahead in future developments and applications. Our review emphasizes hydrological design to protect against extreme events such as floods and low flows.
Expanded Newborn Screening for Inborn Errors of Metabolism in Hong Kong: Results and Outcome of a 7 Year Journey

Newborn screening (NBS) is an important public health program that aims to identify pre-symptomatic healthy babies that will develop significant disease if left undiagnosed and untreated. The number of conditions being screened globally is expanding rapidly in parallel with advances in technology, diagnosis, and treatment availability for these conditions. In Hong Kong, NBS for inborn errors of metabolism (NBSIEM) began as a pilot program in October 2015 and was implemented to all birthing hospitals within the public healthcare system in phases, with completion in October 2020. The number of conditions screened for increased from 21 to 24 in April 2016 and then to 26 in October 2019. The overall recruitment rate of the NBS program was 99.5%. In the period between October 2015 and December 2022, 125,688 newborns were screened and 295 were referred back for abnormal results. The recall rate was reduced from 0.26% to 0.12% after the implementation of second-tier testing. An inherited metabolic disorder (IMD) was eventually confirmed in 47 infants, making the prevalence of IMD in Hong Kong 1 in 2674. At the time of the NBS result, 78.7% of the newborns with IMD were asymptomatic. There were two deaths reported: one newborn with methylmalonic acidemia cobalamin B type (MMACblB) died after the initial crisis and another case of carnitine palmitoyltransferase II deficiency (CPTII) died at 18 months of age after metabolic decompensation. The most common IMD noted were disorders of fatty acid oxidation metabolism (40%, 19 cases), closely followed by disorders of amino acid metabolism (38%, 18 cases), with carnitine uptake defect (19.1%, 9 cases) and citrullinemia type II (17%, 8 cases) being the two most common IMD picked up by the NBSIEM in Hong Kong. Out of the all the IMDs identified, 19.1% belonged to diverse ethnic groups. False negative cases were reported for citrullinemia type II and congenital adrenal hyperplasia during this period.
Evaluation of controllers for augmentative hip exoskeletons and their effects on metabolic cost of walking: explicit versus implicit synchronization

Background: Efficient gait assistance by augmentative exoskeletons depends on reliable control strategies. While numerous control methods and their effects on the metabolic cost of walking have been explored in the literature, the use of different exoskeletons and dissimilar protocols limit direct comparisons. In this article, we present and compare two controllers for hip exoskeletons with different synchronization paradigms. Methods: The implicit-synchronization-based approach, termed the Simple Reflex Controller (SRC), determines the assistance as a function of the relative loading of the feet, resulting in an emerging torque profile continuously assisting extension during stance and flexion during swing. On the other hand, the Hip-Phase-based Torque profile controller (HPT) uses explicit synchronization and estimates the gait cycle percentage based on the hip angle, applying a predefined torque profile consisting of two shorter bursts of assistance during stance and swing. We tested the controllers with 23 naïve healthy participants walking on a treadmill at 4 km ⋅ h−1, without any substantial familiarization. Results: Both controllers significantly reduced the metabolic rate compared to walking with the exoskeleton in passive mode, by 18.0% (SRC, p < 0.001) and 11.6% (HPT, p < 0.001). However, only the SRC led to a significant reduction compared to walking without the exoskeleton (8.8%, p = 0.004). The SRC also provided more mechanical power and led to bigger changes in the hip joint kinematics and walking cadence. Our analysis of mechanical powers based on a whole-body analysis suggested a reduce in ankle push-off under this controller. There was a strong correlation (Pearson’s r = 0.778, p < 0.001) between the metabolic savings achieved by each participant with the two controllers. Conclusion: The extended assistance duration provided by the implicitly synchronized SRC enabled greater metabolic reductions compared to the more targeted assistance of the explicitly synchronized HPT. Despite the different assistance profiles and metabolic outcomes, the correlation between the metabolic reductions with the two controllers suggests a difference in individual responsiveness to assistance, prompting more investigations to explore the person-specific factors affecting assistance receptivity.
Engagement of people diagnosed with schizophrenia in a five-month exercise program: CORTEX-SP study

Exercise programs represent useful non-pharmacological resources in preventing and treating mental disorders such as schizophrenia (SZ), but there are aforementioned reasons, (i.e., low rates of participation). The study aimed to explore the engagement of people diagnosed with SZ in a five-month exercise program. Therefore, purposive criterion sampling was utilized to recruit 35 participants who were diagnosed with SZ. Qualitative data was collected using semi-structured interviews; these were recorded and transcribed verbatim. The data was subsequently analyzed using thematic analysis. Three themes were identified from the analysis: intrapersonal factors (characteristics and clinical consequences of the SZ and pharmacotherapy), interpersonal factors (relationships with people that participate, health professionals, and family and friends), and environmental factors (exercise program organization and participants’ perception regarding the program). In conclusion, the symptoms and pharmacological treatments for the illness were perceived to be the primary barriers to engaging in exercise for the participants. Participants gave great importance to interpersonal factors, they perceived the group atmosphere and the program environment to be fundamental axes of the program. The presence of healthcare professionals, as well as the support, were also perceived to facilitate engagement in the exercise program. Keywords: schizophrenia, community exercise, qualitative methods, environmental health, mental health.
Temporal and spatial distribution of the grout pressure and its effects on lining segments during synchronous grouting in shield tunnelling

Abstract The advance of tunnel shield creates void between the lining segments and the surrounding rock at the tail part of the tunnel shield. Grout is continuously injected into that void, to control the ground subsidence and maintain the segments stability. The grouting process must be precisely controlled and monitored to prevent any undesired significant subsidence or segment damage. In this work, a novel model to characterise the temporal and spatial distribution of the grout pressure in the rock-segment void is proposed, based on the theory of group diffusion and consolidation. The temporal variation of the grout viscosity is also considered in the proposed model. The proposed model is verified against field monitored data of the grout pressure, and exhibits quite good performance. Then a three-dimensional finite element model of the lining segments is developed to study the effects of the grout pressure on the mechanical response of the lining segments. The mechanical responses of the lining segments, in terms of internal force, moment and stress profile, are thoroughly analysed. These mechanical responses are also verified against the field monitored data, to further validate the proposed model of grout pressure distribution.
A Multi Representation Deep Learning Approach for Epileptic Seizure Detection

Epileptic seizures, unpredictable in nature and potentially dangerous during activities like driving, pose significant risks to individual and public safety. Traditional diagnostic methods, which involve labour-intensive manual feature extraction from Electroencephalography (EEG) data, are being supplanted by automated deep learning frameworks. This paper introduces an automated epileptic seizure detection framework utilizing deep learning to bypass manual feature extraction. Our framework incorporates detailed pre-processing techniques: normalization via L2 normalization, filtering with an 80 Hz and 0,5 Hz Butterworth low-pass and high-pass filter, and a 50 Hz IIR Notch filter, channel selection based on standard deviation calculations and Mutual Information algorithm, and frequency domain transformation using FFT or STFT with Hann windows and 50% hop. We evaluated on two datasets: the first comprising 4 canines and 8 patients with 2.299 ictal, 23.445 interictal, and 32.915 test data, 400-5000Hz sampling rate across 16-72 channels; the second dataset, intended for testing, 733 icatal, 4.314 interictal, and 1908 test data, each 10 minutes long, recorded at 400Hz across 16 channels. Three deep learning architectures were assessed: CNN, LSTM, and a hybrid CNN-LSTM model-stems from their demonstrated efficacy in handling the complex nature of EEG data. Each model offers unique strengths, with the CNN excelling in spatial feature extraction, LSTM in temporal dynamics, and the hybrid model combining these advantages. The CNN model, comprising 31 layers, yielded highest accuracy, achieving 91% on the first dataset (precision 92%, recall 91%, F1-score 91%) and 82% on the second dataset using a 30-second threshold. This threshold was chosen for its clinical relevance. The research advances epileptic seizure detection using deep learning, indicating a promising direction for future medical technology. Future work will focus on expanding dataset diversity and refining methodologies to build upon these foundational results.
Percepción del cambio climático en comunidades campesinas de la Reserva de la Biosfera La Encrucijada, Chiapas, México

Climate change is a multidimensional and uncertain global environmental problem that presents itself as one of the great challenges our present society needs to face. In order to reach effective answers coherent with various sociocultural realities, scientific knowledge must integrate said realities. This project analyzes the sociocultural perceptions of three rural communities within Reserva de la Biosfera La Encrucijada, in Costa de Chiapas, Mexico, on climate change in the past few decades and how such change may have affected their livelihoods. We conducted semi-structured surveys about climate change perception on elderly individuals in these communities. Generally, there is an agreement on climate having changed: higher average temperatures and different rainfall patterns, which have led to delayed seasonal changes that have affected traditional farming practices. In turn, the observed changes were compared to regional historical climate variables. Public policies are disjointed and defined by sectors (conservation, production), which necessitates an integrative approach, together with traditional peasant knowledge for adaptation strategies to climate change.