Miracle-dz/UniFAR-FTUs huggingface dataset:
“Seeing a Brighter Future” – Experiences of Adolescents with Common Mental Disorders Receiving the Problem-Solving Therapy “Youth Friendship Bench” in Zimbabwe

Abstract In Zimbabwe common mental disorders are prevalent among adolescents and the treatment gap is large. The recently introduced Youth Friendship Bench intervention (YouFB) addresses this gap by task-shifting youth lay health workers to offer a culturally contextualised, manual-based, six-session problem-solving therapy to adolescents, 16-19 years of age. The aim of this study was to explore participants´ experiences of YouFB to attain a first insight into this novel intervention. Interviews with nine adolescents were analysed using qualitative content analysis on a latent level. The experience of YouFB was positive, perceived to offer hope and relief from feelings of isolation and uncertainty, increase manageability of problems, and contribute to feelings of autonomy, resulting in a feeling of optimism about the future. The notion among participants that this brief intervention had such a positive influence on their lives, sparks interest because of its applicability in low-resource settings.
Influence of Enological Practices on Ochratoxin A Concentration in Wine

The effects of several enological practices on ochratoxin A (OTA) concentration in wines were evaluated. Analysis of OTA was performed by reverse-phase high-performance liquid chromatography (HPLC) after immunoaffinity cleanup. Higher toxin levels were found in red wines (0.017 to 0.050 μg/L) than white wines (0.006 to 0.022 μg/L). Intensive pressing of pomace, prolonged drying of grapes, and storage in partially empty tanks increased OTA contamination of wines. Poor winery sanitation practice was the primary source of OTA contamination, as wines from contaminated wineries had the highest OTA values (0.130 to 1.300 μg/L). Filtration through a 10-μm membrane and heating on hot plates at 55°C did not cause a significant decrease in the toxin level. An 80% decrease of OTA was observed after wine filtration through a 0.45-μm membrane ( p F = 3.172 (mg/g)/(mg/L) 0.8474 ), but it did not affect polyphenol content and color of red wine. Nevertheless, a decrease of key sensory odorants of wine, such as 3-methylbutyl acetate, ethyl hexanoate, ethyl octanoate, and geraniol, was observed.
Redefining monetary policy rules: A threshold approach

In this paper, we try to analyse the extent to which a redefinition of the monetary policy rule would help to avoid the zero-lower bound, as well as to explore the conditions needed to avoid that constraint. To that aim, we estimate the threshold values of the key variables of the policy rule: the inflation gap and the output gap. The threshold model allows us to know which are the turning points from which the relationship between the key variables and the interest rate revert. In the Eurozone countries, we have found that the inflation gap always contributes to increasing the nominal interest rate. On the contrary, the output gap works differently when it reaches values above or below the threshold value, which would favour the reduction of the interest rates towards the zero level.
Age Prediction by DNA Methylation in Neural Networks

<bold>A</bold>ging is traditionally thought to be caused by complex and interacting factors such as DNA methylation. The traditional formula of DNA methylation aging is based on linear models and little work has explored the effectiveness of neural networks, which can learn non-linear relationships. DNA methylation data typically consists of hundreds of thousands of feature space and a much less number of biological samples. This leads to overfitting and a poor generalization of neural networks. We propose Correlation Pre-Filtered Neural Network (CPFNN) that uses Spearman Correlation to pre-filter the input features before feeding them into neural networks. We compare CPFNN with the statistical regressions (i.e., Horvath's and Hannum's formulas), the neural networks with LASSO regularization and elastic net regularization, and the Dropout Neural Networks. CPFNN outperforms these models by at least 1 year in term of Mean Absolute Error (MAE), with a MAE of 2.7 years. We also test for association between the epigenetic age with Schizophrenia and Down Syndrome (<inline-formula><tex-math notation="LaTeX">$p=0.024$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn>0</mml:mn><mml:mo>.</mml:mo><mml:mn>024</mml:mn></mml:mrow></mml:math><inline-graphic xlink:href="zhang-ieq1-3084596.gif"/></alternatives></inline-formula> and <inline-formula><tex-math notation="LaTeX">$p<0.001$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>p</mml:mi><mml:mo><</mml:mo><mml:mn>0</mml:mn><mml:mo>.</mml:mo><mml:mn>001</mml:mn></mml:mrow></mml:math><inline-graphic xlink:href="zhang-ieq2-3084596.gif"/></alternatives></inline-formula>, respectively). We discover that for a large number of candidate features, such as genome-wide DNA methylation data, a key factor in improving prediction accuracy is to appropriately weight features that are highly correlated with the outcome of interest.
Transient IL-33 upregulation in neonatal mouse lung promotes acute but not chronic type 2 immune responses induced by allergen later in life

Early life respiratory insults, such as viral infections or hyperoxia, often increase asthma susceptibility later in life. The mechanisms underlying this increased susceptibility are not fully understood. IL-33 has been shown to be critically involved in allergic airway diseases. IL-33 expression in the neonatal lung can be increased by various respiratory insults associated with asthma development. Therefore, we investigated whether and how early life increases in IL-33 impact allergic airway responses later in life. Using a novel IL-33 transgenic mouse model, in which full-length IL-33 was inducible overexpressed in lung epithelial cells, we transiently upregulated lung IL-33 expression in neonatal mice for one week. After resting for 4–6 weeks, mice were intranasally exposed to a single-dose of recombinant IL-33 or the airborne allergen Alternaria. Alternatively, mice were exposed to Alternaria and ovalbumin multiple times for one month. We found that a transient increase in IL-33 expression during the neonatal period promoted IL-5 and IL-13 production when mice were later exposed to a single-dose of IL-33 or Alternaria in adulthood. However, increased IL-33 expression during the neonatal period did not affect airway inflammation, type 2 cytokine production, lung mucus production, or antigen-specific antibody responses when adult mice were exposed to Alternaria and ovalbumin multiple times. These results suggest that transient increased IL-33 expression early in life may have differential effects on allergic airway responses in later life, preferentially affecting allergen-induced acute type 2 cytokine production.
An incoherent feedforward loop formed by SirA/BarA, HilE and HilD is involved in controlling the growth cost of virulence factor expression by Salmonella Typhimurium

An intricate regulatory network controls the expression of Salmonella virulence genes. The transcriptional regulator HilD plays a central role in this network by controlling the expression of tens of genes mainly required for intestinal colonization. Accordingly, the expression/activity of HilD is highly regulated by multiple factors, such as the SirA/BarA two-component system and the Hcp-like protein HilE. SirA/BarA positively regulates translation of hilD mRNA through a regulatory cascade involving the small RNAs CsrB and CsrC, and the RNA-binding protein CsrA, whereas HilE inhibits HilD activity by protein-protein interaction. In this study, we show that SirA/BarA also positively regulates translation of hilE mRNA through the same mentioned regulatory cascade. Thus, our results reveal a paradoxical regulation exerted by SirA/BarA-Csr on HilD, which involves simultaneous opposite effects, direct positive control and indirect negative control through HilE. This kind of regulation is called an incoherent type-1 feedforward loop (I1-FFL), which is a motif present in certain regulatory networks and represents a complex biological problem to decipher. Interestingly, our results, together with those from a previous study, indicate that HilE, the repressor component of the I1-FFL reported here (I1-FFLSirA/BarA-HilE-HilD), is required to reduce the growth cost imposed by the expression of the genes regulated by HilD. Moreover, we and others found that HilE is necessary for successful intestinal colonization by Salmonella. Thus, these findings support that I1-FFLSirA/BarA-HilE-HilD cooperates to control the precise amount and activity of HilD, for an appropriate balance between the growth cost and the virulence benefit generated by the expression of the genes induced by this regulator. I1-FFLSirA/BarA-HilE-HilD represents a complex regulatory I1-FFL that involves multiple regulators acting at distinct levels of gene expression, as well as showing different connections to the rest of the regulatory network governing Salmonella virulence.
Comparative Skip-Oviposition Behavior Among Container Breeding Aedes spp. Mosquitoes (Diptera: Culicidae)

Abstract Container Aedes mosquitoes are the most important vectors of human arboviruses (i.e., dengue, chikungunya, Zika, or yellow fever). Invasive and native container Aedes spp. potentially utilize natural and artificial containers in specific environments for oviposition. Several container Aedes spp. display ‘skip-oviposition’ behavior, which describes the distribution of eggs among multiple containers during a single gonotrophic cycle. In this study, we compared individual skip-oviposition behavior using identical eight-cup testing arenas with three container Aedes species: Aedes aegypti (Linnaeus), Aedes albopictus (Skuse), and Aedes triseriatus (Say). We applied the index of dispersion, an aggregation statistic, to individual mosquitoes’ oviposition patterns to assess skip-oviposition behavior. Aedes aegypti and Ae. albopictus utilized more cups and distributed eggs more evenly among cups than Ae. triseriatus under nutritionally enriched oviposition media (oak leaf infusion) conditions. When presented with a nutritionally unenriched (tap water) oviposition media, both Ae. aegypti and Ae. albopictus increased egg spreading behavior. Aedes albopictus did not modify skip-oviposition behavior when reared and assessed under fall-like environmental conditions, which induce diapause egg production. This study indicates specific oviposition site conditions influence skip-oviposition behavior with ‘preferred’ sites receiving higher amounts of eggs from any given individual and ‘non-preferred’ sites receive a limited contribution of eggs. A further understanding of skip-oviposition behavior is needed to make the best use of autodissemination trap technology in which skip-ovipositing females spread a potent larvicide among oviposition sites within the environment.
FiberApp: An Open-Source Software for Tracking and Analyzing Polymers, Filaments, Biomacromolecules, and Fibrous Objects

Biological semiflexible polymers and filaments such as collagen, fibronectin, actin, microtubules, coiled-coil proteins, DNA, siRNA, amyloid fibrils, etc., are ubiquitous in nature. In biology, these systems have a direct relation to critical processes ranging from the movement of actin or assembly of viruses at cellular interfaces to the growth of amyloid plaques in neurodegenerative diseases. In technology and applied sciences, synthetic macromolecules or fibrous objects such as carbon nanotubes are involved in countless applications. Accessing their intrinsic properties at the single molecule level, such as their molecular conformations or intrinsic stiffness, is central to the understanding of these systems, their properties, and the design of related applications. In this Perspective we introduce FiberApp—a new tracking and analysis software based on a cascade of algorithms describing structural and topological features of objects characterized by a very high length-to-width aspect ratio, generally d.
Exploring the Role of Community Health Workers in Improving the Collection of Family Health History: A Pilot Study

Community health workers (CHWs) have been successful partners in addressing public health and health care challenges but have yet to be engaged in efforts to promote family health history (FHH) collection. FHH information is a key factor in determining disease risk and supporting screening and prevention across multiple diseases. The collection of FHH information could be facilitated by the existing cadre of CHWs already working alongside clients and families. In this qualitative study, we interviewed 30 CHWs from Georgia to better understand the current level of knowledge about FHH, perceptions of how FHH collection aligns with their role, and barriers and facilitators in order to support more active involvement of CHWs in FHH collection. Interviews were completed, transcribed, and double coded by three study team members. More than half of CHWs reported knowing their own FHH information. CHWs showed a strong interest and support for collecting FHH in their job, despite limited current engagement in this role. CHWs acknowledged the collection of FHH as being an opportunity to empower clients to have conversations with their providers. To better support this work, CHWs requested training in using and integrating FHH tools into their workflow and support in communicating about FHH with their clients. Our findings suggest that with support and training, CHWs are uniquely positioned to improve FHH collection among their client base. Ultimately, improving FHH collection skills among the population could allow for better integration of risk-stratified approaches that are informed by FHH information for the prevention, management, and treatment of disease.
Modeling Spatial Trajectories with Attribute Representation Learning (Extended Abstract)

The widespread use of positioning devices has given rise to many trajectories, with each having three explicit attributes: user ID, location ID, and time-stamp and an implicit attribute: activity type (akin to "topic" in text mining). To model these trajectories, existing works learn different attribute representations by either introducing latent activity types based on topic models or transforming the location and time context into a low-dimensional space via embedding techniques. In this paper, we propose a holistic approach named Human Mobility Representation Model (HMRM) to simultaneously produce the vector representations of all four (explicit and implicit) attributes. We evaluate HMRM on two real check-in datasets collected from Foursquare. Experimental results show that HMRM could not only improve the performance of capturing latent activity types, but also learn better trajectory embeddings.
EMG Activity of Transversus Abdominis, Multifidus and Co-Contraction Index in Different Phases Amongst Varied Level Archers: A Cross-Sectional Study

Abstract Introduction. Core muscle activity is a necessary requirement in most sports. However, its role in archers has not been studied. Therefore, this study sought to determine muscle activity of Transversus abdominis (TA) and Multifidus (MF) and co-contraction index (CCI) using surface electromyography (s EMG) during different phases of shots in archers with different levels of training. Material and Methods. It was an observational study with a cross-sectional design. Twenty-eight healthy male archers were recruited and grouped according to their level of training: Group A (Beginners (n = 9)), Group B (Trained (n = 10)), Group C (Elite (n = 9)). The muscle activation (%MVIC) for MF and TA for 10 successive archery shots (distance: 10 meters in 200 seconds) was recorded using s EMG for all the phases of the shots along with CCI. Results. Three-way ANOVA revealed a significant difference for TA activity within groups (p ≤ 0.001) and phases (p = 0.002), A significant difference for MF activity was found within groups (p ≤ 0.001). A significant difference for CCI was found between groups (p ≤ 0.001) and in the interaction between phase × shot (p = 0.001). Conclusions. The findings of the study showed that elite archers had more activity of the core muscles (TA and MF) and their CCI was found to be much higher with respect to the trained and beginner archers. Therefore, it is essential to incorporate dynamic stabilization exercises into archery training.
Pattern Analysis of Aerosol Optical Depth and Its Relationship with Meteorological Parameters over Bangladesh During the Covid-19 Pandemic Lockdown

This study looks at the relationship between aerosol optical depth (AOD) and meteorological parameters during the COVID-19 lockdown in Bangladesh. Aerosols in the atmosphere are liquid or solid particles suspended in the air. AOD is an essential parameter of atmospheric aerosol and has become a significant uncertainty in global climate simulation. The patterns of AOD, meteorological parameters and relationships among them were analyzed across Bangladesh during the covid-19 lockdown period using MODerate Resolution Imaging Spectroradiometer (MODIS) and Global Land Data Assimilation System (GLDAS) remote sensing data. Higher AOD values were reported in western part of Bangladesh and lower AOD values were observed over the hilly area of the eastern part of the country. Highest precipitations were found in the Sylhet division on the other hand lowest precipitations were recorded in the southwestern regions of the Khulna division. An intensive peak land surface temperature was observed in Gazipur of Dhaka division. Wind speed was gradually decreasing from the southern to the northern direction. Lowest AOD and highest precipitation rate were observed in July 2020. Peak values of AOD, land surface temperature, and wind speed occurred in January, May, and June of 2021 respectively. Precipitation and wind speed were both minimum in December 2020, whereas land surface temperature was minimum in January 2021.
An Optimization Strategy for PBFT Consensus Mechanism Based On Consortium Blockchain

At present, the transaction delay of the consortium block chain applying the Practical Byzantine Fault Tolerance (PBFT) consensus protocol can only reach 2 to 5 seconds, and the throughput cannot reach tens of thousands. In addition as the number of nodes increases, the performance of the consortium block chain declines very quickly. The main challenge of previous research are to realize communication network topology of PBFT algorithm and high information exchange in the case of Byzantine failure, thus, this paper proposes an optimized Byzantine fault-tolerant algorithm to solve the performance bottleneck of the consortium chain. First of all, for the communication network structure of the whole network broadcast, we have reached an agreement on the transaction according to the pre-prepare and prepare phases of PBFT, and generally enter the commit phase, there is a high probability that the leader is honest, so we will communicate with the commit phase The network is optimized as a star communication structure. Second, combined with Tendermint, merge the view-change process of Byzantine failures of the normal consensus process, and switch the leader according to the longest chain principle. The algorithm is based on a partially synchronized network model to ensure the security and liveness of the protocol, and improve the performance and effective robustness.
A Novel Infrared Small Target Detection Algorithm Based on Deep Learning

Infrared imaging has been an efficient anti-drone approach due to its low-cost, anti-interference and all-weather working characteristics. However, the detection of Unmanned Aerial Vehicle (UAV) through infrared camera is still a challenging issue because infrared targets in the field-of-view are usually small and lack of shape and texture features. In this paper, we propose a novel deep learning-based infrared small target detection algorithm called Single Shot Detector for Small Target (SSD-ST) by redesigning the network architecture of Single Shot Detector (SSD). We drop the low-resolution layers and enhance the high-resolution layer in SSD to make it more suitable for the detection task of infrared small targets. We have evaluated our algorithm over a dataset with 16177 infrared images and 30 trajectories. The results show that the proposed algorithm can effectively reduce the false detection rate and achieve higher than 90% precision and recall rate on the infrared small target dataset.
Psychophysiological Modeling of Trust In Technology

Trust as a precursor for users' acceptance of artificial intelligence (AI) technologies that operate as a conceptual extension of humans (e.g., autonomous vehicles (AVs)) is highly influenced by users' risk perception amongst other factors. Prior studies that investigated the interplay between risk and trust perception recommended the development of real-time tools for monitoring cognitive states (e.g., trust). The primary objective of this study was to investigate a feature selection method that yields feature sets that can help develop a highly optimized and stable ensemble trust classifier model. The secondary objective of this study was to investigate how varying levels of risk perception influence users' trust and overall reliance on technology. A within-subject four-condition experiment was implemented with an AV driving game. This experiment involved 25 participants, and their electroencephalogram, electrodermal activity, and facial electromyogram psychophysiological signals were acquired. We applied wrapper, filter, and hybrid feature selection methods on the 82 features extracted from the psychophysiological signals. We trained and tested five voting-based ensemble trust classifier models using training and testing datasets containing only the features identified by the feature selection methods. The results indicate the superiority of the hybrid feature selection method over other methods in terms of model performance. In addition, the self-reported trust measurement and overall reliance of participants on the technology (AV) measured with joystick movements throughout the game reveals that a reduction in risk results in an increase in trust and overall reliance on technology.
Production of human translation-competent lysates using dual centrifugation

Protein synthesis is a central process in gene expression and the development of efficient in vitro translation systems has been the focus of scientific efforts for decades. The production of translation-competent lysates originating from human cells or tissues remains challenging, mainly due to the variability of cell lysis conditions. Here we present a robust and fast method based on dual centrifugation that allows for detergent-free cell lysis under controlled mechanical forces. We optimized the lysate preparation to yield cytoplasm-enriched extracts from human cells that efficiently translate mRNAs in a cap-dependent as well as in an IRES-mediated way. Reduction of the phosphorylation state of eIF2α using recombinant GADD34 and 2-aminopurine considerably boosts the protein output, reinforcing the potential of this method to produce recombinant proteins from human lysates.