Miracle-dz/UniFAR-FTUs huggingface dataset:
Stromal Ascorbate Peroxidase (OsAPX7) Modulates Drought Stress Tolerance in Rice (Oryza sativa)

Chloroplast ascorbate peroxidases exert an important role in the maintenance of hydrogen peroxide levels in chloroplasts by using ascorbate as the specific electron donor. In this work, we performed a functional study of the stromal APX in rice (OsAPX7) and demonstrated that silencing of OsAPX7 did not impact plant growth, redox state, or photosynthesis parameters. Nevertheless, when subjected to drought stress, silenced plants (APX7i) show a higher capacity to maintain stomata aperture and photosynthesis performance, resulting in a higher tolerance when compared to non-transformed plants. RNA-seq analyses indicate that the silencing of OsAPX7 did not lead to changes in the global expression of genes related to reactive oxygen species metabolism. In addition, the drought-mediated induction of several genes related to the proteasome pathway and the down-regulation of genes related to nitrogen and carotenoid metabolism was impaired in APX7i plants. During drought stress, APX7i showed an up-regulation of genes encoding flavonoid and tyrosine metabolism enzymes and a down-regulation of genes related to phytohormones signal transduction and nicotinate and nicotinamide metabolism. Our results demonstrate that OsAPX7 might be involved in signaling transduction pathways related to drought stress response, contributing to the understanding of the physiological role of chloroplast APX isoforms in rice.
Intrinsic Capacity to Predict Future Adverse Health Outcomes in Older Adults: A Scoping Review

Objective: Intrinsic capacity is recognized as an important determinant of healthy aging and well-being of older adults; however, relatively little is known about the intrinsic capacity of older adults to predict adverse health outcomes. The study aimed to examine which adverse health outcomes of older adults can be predicted by intrinsic capacity. Methods: The study was conducted using the scoping review methodological framework of Arksey and O’Malley. A systematic literature search of nine electronic databases (i.e., Pubmed, Embase, Cochrane library, Web of science, CINAHL, China National Knowledge Infrastructure, VIP, Wanfang, and the Chinese Biological Medical Literature Database) were performed from the database’s inception to 1 March 2022. Results: Fifteen longitudinal studies were included. A series of adverse health outcomes were assessed, including physical function (n = 12), frailty (n = 3), falls (n = 3), mortality (n = 6), quality of life (n = 2) and other adverse health outcomes (n = 4). Conclusions: Intrinsic capacity could predict some adverse health outcomes of different follow-up times for older adults; however, due to the small number of studies and sample size, more high-quality studies are necessary to explore the longitudinal relationships between intrinsic capacity and adverse health outcomes in the future.
Cross Dataset Analysis for Generalizability of HRV-Based Stress Detection Models

Stress is an increasingly prevalent mental health condition across the world. In Europe, for example, stress is considered one of the most common health problems, and over USD 300 billion are spent on stress treatments annually. Therefore, monitoring, identification and prevention of stress are of the utmost importance. While most stress monitoring is carried out through self-reporting, there are now several studies on stress detection from physiological signals using Artificial Intelligence algorithms. However, the generalizability of these models is only rarely discussed. The main goal of this work is to provide a monitoring proof-of-concept tool exploring the generalization capabilities of Heart Rate Variability-based machine learning models. To this end, two Machine Learning models are used, Logistic Regression and Random Forest to analyze and classify stress in two datasets differing in terms of protocol, stressors and recording devices. First, the models are evaluated using leave-one-subject-out cross-validation with train and test samples from the same dataset. Next, a cross-dataset validation of the models is performed, that is, leave-one-subject-out models trained on a Multi-modal Dataset for Real-time, Continuous Stress Detection from Physiological Signals dataset and validated using the University of Waterloo stress dataset. While both logistic regression and random forest models achieve good classification results in the independent dataset analysis, the random forest model demonstrates better generalization capabilities with a stable F1 score of 61%. This indicates that the random forest can be used to generalize HRV-based stress detection models, which can lead to better analyses in the mental health and medical research field through training and integrating different models.
CNN2Graph: Building Graphs for Image Classification

Neural Network classifiers generally operate via the i.i. d. assumption where examples are passed through independently during training. We propose CNN2GNN and CNN2Transformer which instead leverage inter-example information for classification. We use Graph Neural Networks (GNNs) to build a latent space bipartite graph and compute cross-attention scores between input images and a proxy set. Our approach addresses several challenges of existing methods. Firstly, it is end-to-end differentiable despite the generally discrete nature of graph construction. Secondly, it allows inductive inference at no extra cost. Thirdly, it presents a simple method to construct graphs from arbitrary datasets that captures both example level and class level information. Finally, it addresses the proxy collapse problem by combining contrastive and cross-entropy losses rather than separate clustering algorithms. Our results increase classification performance over baseline experiments and outperform other methods. We also conduct an empirical investigation showing that Transformer style attention scales better than GAT attention with dataset size.
Arbuscular Mycorrhizal Symbiosis Improves Ex Vitro Acclimatization of Sugarcane Plantlets (Saccharum spp.) under Drought Stress Conditions

The symbiotic associations between arbuscular mycorrhizal fungi (AMF) and plants can induce drought stress tolerance. In this study, we evaluated the effect of Glomus intraradices, a mycorrhizal fungus, on the ex vitro development and survival of sugarcane plantlets subjected to drought stress during the acclimatization stage of micropropagation. In vitro obtained sugarcane plantlets (Saccharum spp. cv Mex 69–290) were inoculated with different doses of G. intraradices (0, 100, and 200 spores per plantlet) during greenhouse acclimatization. Sixty days after inoculation, plantlets were temporarily subjected to drought stress. We evaluated the survival rate, total chlorophyll, total protein, carotenoids, proline, betaine glycine, soluble phenolic content, and antioxidant capacity every 3 days for 12 days. Symbiotic interaction was characterized by microscopy. Our results showed that the survival rate of inoculated plants was higher in 45% than the treatment without mycorrhizae. Total chlorophyll, protein, proline, betaine glycine content, and antioxidant capacity were increased in AMF inoculated plants. The soluble phenolic content was higher in non-inoculated plants than the treatment with mycorrhizae during the drought stress period. Microscopy showed the symbiotic relationship between plant and AMF. The early inoculation of 100 spores of G. intraradices per sugarcane plantlet during the acclimatization stage could represent a preconditioning advantage before transplanting into the field and establishing basic seedbeds.
Nonlinearity and forecast performance of realized volatility

Abstract This study examines whether accounting for the nonlinearity of realized volatility leads to better forecast performance. We propose a new realized volatility forecasting model that considers nonlinearities without the assumption of a particular nonlinear model. The proposed model uses the Taylor series approximation method to account for nonlinearities. We applied it to the realized volatility of representative stock indices from the U.S., Japan, the U.K., and China and observed their in-sample nonlinearities. Additionally, we evaluate out-of-sample forecast performance. The empirical results show that realized volatility has nonlinearity, and the proposed models exhibit better forecast performance than standard models.
Development and Optimization of Label-Free Quantitative Proteomics under Different Crossing Periods of Bottle Gourd

Bottle gourd, a common vegetable in the human diet, has been valued for its medicinal and energetic properties. In this experiment, the time-resolved analysis of the changes in the proteins’ electrophoretic patterning of the seed development at different crossing periods was studied in bottle gourd using label-free quantitative proteomics. Hybrid HBGH-35 had the highest observed protein levels at the 4th week of the crossing period (F4) compared to the parental lines, viz. G-2 (M) and Pusa Naveen (F). The crossing period is significantly correlated with grain filling and reserve accumulation. The observed protein expression profile after storage was related to seed maturation and grain filling in bottle gourds. A total of 2517 proteins were identified in differentially treated bottle gourd fruits, and 372 proteins were differentially expressed between different crossing periods. Proteins related to carbohydrate and energy metabolism, anthocyanin biosynthesis, cell stress response, and fruit firmness were characterized and quantified. Some proteins were involved in the development, while others were engaged in desiccation and the early grain-filling stage. F4 was distinguished by an increase in the accumulation of low molecular weight proteins and enzymes such as amylase, a serine protease, and trypsin inhibitors. The seed vigor also followed similar patterns of differential expression of seed storage proteins. Our findings defined a new window during seed production, which showed that at F4, maximum photosynthetic assimilates accumulated, resulting in an enhanced source–sink relationship and improved seed production. Our study attempts to observe the protein expression profiling pattern under different crossing periods using label-free quantitative proteomics in bottle gourd. It will facilitate future detailed investigation of the protein associated with quality traits and the agronomic importance of bottle gourd through selective breeding programs.
Immersive and Non-Immersive Virtual Reality for Pain and Anxiety Management in Pediatric Patients with Hematological or Solid Cancer: A Systematic Review

Simple Summary Pediatric patients with cancer are often subjected to several invasive procedures and treatments, which may determine pain and induce feelings of anxiety and worry. Inadequate management of pain and anxiety can affect the overall quality of life, affecting the physical and psychological well-being of children and their caregivers. The aim of this systematic review is to summarize the findings of published experimental and quasi-experimental studies on the effectiveness of virtual reality for the management of pain and/or anxiety in children and adolescents with cancer. Abstract Invasive and painful procedures, which often induce feelings of anxiety, are necessary components of pediatric cancer treatment, and adequate pain and anxiety management during these treatments is of pivotal importance. In this context, it is widely recognized that a holistic approach, including pharmacological and non-pharmacological modalities, such as distraction techniques, should be the standard of care. Recent evidence suggested the use of virtual reality (VR) as an effective non-pharmacological intervention in pediatrics. Therefore, this systematic review aims to analyze previously published studies on the effectiveness of VR for the management of pain and/or anxiety in children and adolescents with hematological or solid cancer. Medline, SCOPUS, Web of Science, ProQuest, CINAHL, and The Cochrane Central Register of Controlled Trials were used to search for relevant studies in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Randomized controlled trial, crossover trial, cluster randomized trial, and quasi-experimental studies were included. Thirteen studies, published between 1999 and 2022, that fulfilled the inclusion criteria were included. Regarding the primary outcomes measured, pain was considered in five studies, anxiety in three studies, and the remaining five studies analyzed the effectiveness of VR for both pain and anxiety reduction. Our findings suggested a beneficial effect of VR during painful vascular access procedures. Limited data are available on the reduction of anxiety in children with cancer.
Effective assignment of work items for an engineering consulting project based on consulting engineer selection matrix

ABSTRACT To reasonably utilize human resources, engineering consulting firms should establish effective task assignment mechanisms. In this study, the consulting engineer selection matrix (CESM) was proposed to select engineers for a work item of an engineering consulting project on the basis of contract amount reasonableness, work item importance, engineer hourly rate, and engineer experience. The matrix identified the available engineers in an engineering consulting firm who possessed the operating experience to execute a specific work item. The matrix also divided the engineers into four quadrants depending on contract amount reasonableness and work item importance. A project manager then selected the engineers of a work item depending on their hourly rate (high or low) and experience (experienced or inexperienced) and depending on four task assignment strategies, which entailed the lowest cost, maximum engineer experience, optimal cost efficiency, and imparting experience. The results confirmed that the CESM reduced the salary expenditure of projects without reducing the competence requirements of team members or the investment of human resources. It also allowed project managers to select suitable engineers as project team members instead of passively waiting for functional departments to allocate engineers.
Results of monitoring campaign from a cruise ship in the Western Mediterranean

In order to fill in the gap of observation in the Mediterranean basin and to obtain more information about sources of air pollutants and atmospheric dynamical and chemical mechanisms, the Joint Research Centre of the European Commission (JRC, EC) has started a long-term monitoring program over the Mediterranean Sea in collaboration with the cruise line Costa Crociere. In this framework, in a joint experiment with the Department of Physics of the University of Genoa, an intensive PM2.5 sampling campaign was organized in summer 2011, on a cruise ship following a regular route in the Western Mediterranean with continuous measurements of BC, NOx, CO, SO2 and O3 by the monitoring station, placed in a cabin of the top deck of the ship. During this campaign the route of the ship was Civitavecchia-Savona-Barcelona-Palma de MallorcaMalta (Valletta)-Palermo-Civitavecchia (see Figure 1). From July 18 to 25, August 15 to 22, and September 12 to 19, 2011, PM samples were collected on Quartz and Teflon filters (47mm diameter, flow rate 2.3 m 3 /h) using in parallel two Sven Leckel Ingenieurburo sequential samplers, placed on the top of the cabin where the monitoring station itself was located. The samplers were switched on after the departure from each harbor and stopped before the arrival in the next port. Each leg was then divided in periods of about 5 hours with one filter for each sampler collected per period, thus resulting in a variable number of filters per leg and in a total of about 100 filters for all the sampling campaigns during summer 2011. Information about meteorological parameters (wind speed and direction, temperature, humidity) was available with 10 min intervals from the meteorological station of the ship, together with information about the ship position, speed and sailing direction. Samples were analyzed with different techniques: Energy Dispersive X-Ray Fluorescence at the Department of Physics of Genoa (Ariola et al, 2006); Ion Chromatography (Chow and Watson, 1999) at Department of Chemistry of University of Milan; Thermo-optical analysis (Birch and Cary, 1996) at the JRC laboratory. Ion Beam Analysis measurements of the Teflon filters sampled during the week of September 2011, using simultaneously PIXE, EBS and PESA techniques (Chiari, 2005), were performed at the 3 MV Tandetron accelerator of the LABEC laboratory of INFN in Florence. Figure 1. Route of the ship during the sampling campaigns in the summer 2011.
Grid generation for 2D flow problems

A grid generation method is proposed for an arbitrary two-dimensional domain. The method, based on the Delaunay triangulation, is modified so that it can be used as a grid generator for an arbitrary two-dimensional area with complex boundary geometry. Input data for the method are the co-ordinates of all nodes and the ordering of nodes on each boundary. Its efficiency is examined through a number of actual problems, and a numerical experiment clarifies that the grid generation requires a CPU time which is proportional to the number of nodes.
A Belief-Based Task Offloading Algorithm in Vehicular Edge Computing

In vehicular edge computing (VEC), where vehicles offload their tasks to nearby edge clouds, it is not a trivial issue to design an optimal task offloading policy due to the dynamic nature of VEC environment and limited information on computing and communication resources. In this paper, we propose a belief-based task offloading algorithm (BTOA) where a vehicle selects target edge clouds (for computing) and subchannels (for communications) based on its belief, and observe their current resource and channel conditions. Based on the observed information, the vehicle finally determines the most appropriate edge cloud and subchannel. Evaluation results under a realistic traffic scenario demonstrate that BTOA can reduce the total latency of the task offloading over 42% compared to a conventional offloading algorithm where the target edge clouds and subchannels are determined without any real observations.
Development of Adapalene Loaded Liposome Based Gel for Acne

Retinoids are considered the mainstay treatment for moderate to severe acne. Adapalene, a third-generation retinoid, has physiochemical properties which hinder the effective delivery of the drug to the skin. Therefore, the current study aimed to develop and evaluate adapalene liposomal loaded gel (ADA-LP gel) for the effective management of acne to improve tolerability and delivery to targeted sites as compared to the conventional dosage form of the drug. A novel spontaneous phase transition method (SPT) was used to formulate liposomes. Liposomal formulation (ADA-LP) was prepared and optimized based on particle size, zeta potential, and PDI. Optimized formulation was further characterized by different techniques and loaded into Carbopol gel. In vitro drug release, ex vivo permeation, and in vivo studies were performed using the prepared adapalene-loaded liposomal-based gel. The in vivo study was done employing the testosterone-induced acne model in mice. The optimized formulation had a size of 181 nm, PDI 0.145, and a zeta potential of −35 mV, indicating that the formulation was stable. Encapsulation efficiency was 89.69 ± 0.5%. ADA-LPs were loaded into the gel. Prepared ADA-LP showed a 79 ± 0.02% release of drug in a sustained manner, within 24 h. The ex vivo permeability study showed a total of 43 ± 0.06 µg/cm2 of drug able to permeate through the skin within 24 h. Moreover, only 28.27 ± 0.04% was retained on the epidermis. The developed ADA-LP gel showed significant improvement in the acne lesions in mice with no visible scars and inflammation on the skin. Therefore, ADA-LP-based gel could be a promising carrier system for the safe and effective delivery of Adapalene.
Improving Data-Efficiency and Robustness of Medical Imaging Segmentation Using Inpainting-Based Self-Supervised Learning

We systematically evaluate the training methodology and efficacy of two inpainting-based pretext tasks of context prediction and context restoration for medical image segmentation using self-supervised learning (SSL). Multiple versions of self-supervised U-Net models were trained to segment MRI and CT datasets, each using a different combination of design choices and pretext tasks to determine the effect of these design choices on segmentation performance. The optimal design choices were used to train SSL models that were then compared with baseline supervised models for computing clinically-relevant metrics in label-limited scenarios. We observed that SSL pretraining with context restoration using 32 × 32 patches and Poission-disc sampling, transferring only the pretrained encoder weights, and fine-tuning immediately with an initial learning rate of 1 × 10−3 provided the most benefit over supervised learning for MRI and CT tissue segmentation accuracy (p < 0.001). For both datasets and most label-limited scenarios, scaling the size of unlabeled pretraining data resulted in improved segmentation performance. SSL models pretrained with this amount of data outperformed baseline supervised models in the computation of clinically-relevant metrics, especially when the performance of supervised learning was low. Our results demonstrate that SSL pretraining using inpainting-based pretext tasks can help increase the robustness of models in label-limited scenarios and reduce worst-case errors that occur with supervised learning.
Electron-spectroscopy study of inner-shell photoexcitation and ionization of Xe

Electron spectroscopy, combined with synchrotron radiation in the photon-energy range h.nu. approx. =60--190 eV, was used to measure the angular distributions of Xe 5p and 5s photoelectrons and of N/sub 4,5/OO Auger electrons. The branching ratios and partial cross sections for photoionization and Auger processes were also measured in certain cases. The measured asymmetry parameter . beta. for 5p photoelectrons agrees well with many-electron calculations, which predict a pronounced oscillation in . beta. /sub 5p/ above the 4d ionization threshold due to the 4d-5p intershell interaction. The N/sub 4,5/OO Auger electrons are produced with photon-energy-dependent anisotropic angular distributions, resulting from alignment of Xe/sup +/ by photoionization. The theoretical analysis of Auger-electron angular distributions is described, and theoretical calculations are found to predict the measured asymmetries well. In addition, Auger-electron peaks were observed to broaden and shift at photon energies near the 4d ionization threshold because of postcollision interaction. The measured shifts of the N/sub 5/O/sub 1/O/sub 1/ /sup 1/S/sub 0/ line agree with previous measurements and theory. Electron spectra recorded through the energy region of the 4d. -->. np Rydberg states show that they decay primarily by the Auger process, while the 5p and 5s partial cross sections are relatively weakly affected by autoionization. However, distinctmore » resonance structure was observed in the . beta. parameters for 5p/sub 3/2/ and 5p/sub 1/2/ photoelectrons. The measured results are compared with a theoretical calculation of resonant photoionization for the 4d. -->. 6p excitation. « less