Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Depth Estimation in a Single Image Using Lightweight Efficient Neural Network

Depth estimation is a crucial and fundamental problem in the computer vision field. Conventional methods re-construct scenes using feature points extracted from multiple images; however, these approaches require multiple images and thus are not easily implemented in various real-time applications. Moreover, the special equipment required by hardware-based approaches using 3D sensors is expensive. Therefore, software-based methods for estimating depth from a single image using machine learning or deep learning are emerging as new alternatives. In this paper, we propose an algorithm that generates a depth map in real time using a single image and an optimized lightweight efficient neural network (L-ENet) algorithm instead of physical equipment, such as an infrared sensor or multi-view camera. Because depth values have a continuous nature and can produce locally ambiguous results, pixel-wise prediction with ordinal depth range classification was applied in this study. In addition, in our method various convolution techniques are applied to extract a dense feature map, and the number of parameters is greatly reduced by reducing the network layer. By using the proposed L-ENet algorithm, an accurate depth map can be generated from a single image quickly and, in a comparison with the ground truth, we can produce depth values closer to those of the ground truth with small errors. Experiments confirmed that the proposed L-ENet can achieve a significantly improved estimation performance over the state-of-the-art algorithms in depth estimation based on a single image.
Analysis of A 6-Mirna Signature in Serum from Colorectal Cancer Screening Participants as Non-Invasive Biomarkers for Advanced Adenoma and Colorectal Cancer Detection

Early detection of colorectal cancer (CRC) and its precancerous lesion, advanced adenomas (AA), is critical to improve CRC incidence and prognosis. Circulating microRNAs (miRNAs or miR) are promising non-invasive biomarkers for cancer detection. Our previous results showed that a plasma 6-miRNA signature (miR-15b-5p, miR-18a-5p, miR-29a-3p, miR-335-5p, miR-19a-3p and miR-19b-3p) could distinguish between CRC or AA and healthy individuals (controls). However, its diagnostic performance in serum is unknown. In this exploratory study we aim to evaluate the diagnostic performance of the 6-miRNA signature in serum samples in a cohort of individuals participating in Barcelona’s CRC Screening Programme. We prospectively collected serums from 264 faecal immunochemical test (FIT)-positive participants and total RNA was extracted. Finally, 213 individuals (CRC, 59, AA, 74, controls, 80) were included. MiRNA expression was quantified by real-time RT-qPCR and data analysis was performed by logistic regression. Faecal hemoglobin concentration (f(Hb)) from FIT of the same individuals was also considered. As previously described in plasma, serum from patients with AA or CRC presented significant differences in the 6-miRNA signature compared to controls. Moreover, when combined with f(Hb), the final signature showed high discriminative capacity to distinguish CRC from controls (area under the curve (AUC) = 0.88), and even AA (AUC = 0.81) that otherwise are poorly detected if we only consider f(Hb) (AUC = 0.64). Addition of the serum 6-miRNA signature to quantitative f(Hb) show high accuracy to detect patients with advanced colorectal neoplasia in average-risk individuals. A combination of these two non-invasive methods could be a good strategy to improve diagnostic performances of current CRC screening programmes.
Pancreatic Cancer: Current Concepts in Invasion and Metastasis

Pancreatic cancer remains to be one of the most lethal solid tumours of the gastrointestinal tract with a 5-year survival rate lower than 5%. It is characterised by late diagnosis, aggressive local invasion, early systemic dissemination and resistance to chemoand radiotherapy. At the time of diagnosis more than 85% of patients have already developed metastasis and are therefore not eligible for local treatments with curative intention such as surgery or radiotherapy. Chemotherapy with Gemcitabine is the mainstay of palliative treatment with modest antitumour effects in these patients.
Formation of TiO2@Carbon Core/Shell Nanocomposites from Single Molecular Layer of Aromatic Compounds for Photocatalytic Hydrogen Peroxide Generation.

In this article, we demonstrate that TiO2@carbon core/shell (TiO2@C) nanocomposite photocatalysts prepared by carbonizing a single molecular layer of aromatic compounds adsorbed on the surface of TiO2 nanoparticles selectively enhance the generation of hydrogen peroxide (H2O2). Atomically thin carbon shells have been formed directly on the surface of TiO2 nanoparticles through pyrolytic decarboxylation of the adsorbed aromatic compounds, benzoic acid (BA) and 1-naphthoic acid (NA), which yields two types of TiO2@C nanocomposites, TiO2@C(BA) and TiO2@C(NA). Raman spectroscopy shows that the as-obtained nanocomposites have similar degrees of graphitization (D/G band ratio) regardless of the type of aromatic precursors, but TiO2@C(NA) contains more oxygenic species than TiO2@C(BA) (D*/G band ratio). Such oxygenic species predominantly exist in the form of epoxide groups, as determined by attenuated total reflection infrared spectroscopy. The sp2-carbon atoms near the epoxide groups in the carbon shell can act as active sites for the two-electron reduction of O2. Therefore, TiO2@C(NA) can generate H2O2 more efficiently than TiO2@C(BA). Furthermore, the carbon shells retard the re-consumption of the generated H2O2 by inhibiting the adsorption of H2O2 on the surface of TiO2 nanoparticles, thereby improving the photocatalytic efficiency of H2O2 generation. Finally, we have shown the durability and reproducibility of our TiO2@C-based photocatalytic systems. We believe that our research may offer a potentially improved strategy for H2O2 generation and other photocatalytic applications.
Utilization of Finite Element Analysis for Articular Cartilage Tissue Engineering

Scaffold design plays an essential role in tissue engineering of articular cartilage by providing the appropriate mechanical and biological environment for chondrocytes to proliferate and function. Optimization of scaffold design to generate tissue-engineered cartilage has traditionally been conducted using in-vitro and in-vivo models. Recent advances in computational analysis allow us to significantly decrease the time and cost of scaffold optimization using finite element analysis (FEA). FEA is an in-silico analysis technique that allows for scaffold design optimization by predicting mechanical responses of cells and scaffolds under applied loads. Finite element analyses can potentially mimic the morphology of cartilage using mesh elements (tetrahedral, hexahedral), material properties (elastic, hyperelastic, poroelastic, composite), physiological loads by applying loading conditions (static, dynamic), and constitutive stress–strain equations (linear, porous–elastic, biphasic). Furthermore, FEA can be applied to the study of the effects of dynamic loading, material properties cell differentiation, cell activity, scaffold structure optimization, and interstitial fluid flow, in isolated or combined multi-scale models. This review covers recent studies and trends in the use of FEA for cartilage tissue engineering and scaffold design.
A novel multiplexed 11 locus HLA full gene amplification assay using next generation sequencing

The rapid progress of HLA typing techniques has contributed to improving the outcome of haematopoietic stem cell transplantation (HSCT). However, unambiguous HLA typing remains challenging. Next generation sequencing (NGS) has been shown to resolve the HLA typing ambiguity and simplify HLA typing workflows. The aim of this study is to develop a multiplexed full‐gene PCR assay for 11 HLA loci that can be used on any NGS platform to provide additional information to the traditionally sequenced regions. The entire gene of HLA‐A, HLA‐B, HLA‐C, DRB1, DRB3/4/5, DQB1, DQA1, DPB1, and DPA1 were amplified in four multiplexed reactions. A DNA reference panel of 47 samples representing the most common allele groups was selected to evaluate this novel assay using the Ion Torrent sequencing platform. The specificity and sensitivity of this assay was confirmed on additional 158 samples from a local Caucasian control cohort. Full gene sequences from start to stop codons including some UTR regions were obtained for all 11 HLA loci with complete gene coverage and sufficient read‐depth for 3619 alleles. The whole amplicon was analysed for HLA class I genes, while only exons were analysed for class II genes. All alleles were amplified as expected with 100% concordance at full gene resolution for HLA class I and exon resolution for HLA class II loci when compared with previously used NGS or Sanger sequencing methods. In summary, the novel multiplexed PCR approach for full‐gene HLA typing enabled for a large amount of genetic information to be generated in a simple and fast workflow.
Exact Passive-Aggressive Algorithms for Ordinal Regression Using Interval Labels

In this article, we propose exact passive-aggressive (PA) online algorithms for ordinal regression. The proposed algorithms can be used even when we have interval labels instead of actual labels for example. The proposed algorithms solve a convex optimization problem at every trial. We find an exact solution to those optimization problems to determine the updated parameters. We propose a support class algorithm (SCA) that finds the active constraints using the Karush–Kuhn–Tucker (KKT) conditions of the optimization problems. These active constraints form a support set, which determines the set of thresholds that need to be updated. We derive update rules for PA, PA-I, and PA-II. We show that the proposed algorithms maintain the ordering of the thresholds after every trial. We provide the mistake bounds of the proposed algorithms in both ideal and general settings. We also show experimentally that the proposed algorithms successfully learn accurate classifiers using interval labels as well as exact labels. The proposed algorithms also do well compared to other approaches.
Optimization of Geometry Parameters of Inkjet-Printed Silver Nanoparticle Traces on PDMS Substrates Using Response Surface Methodology

Inkjet printing is an emerging technology with key advantages that make it suitable for the fabrication of stretchable circuits. Specifically, this process is cost-effective and less complex compared to conventional fabrication technologies. Inkjet printing has several process and geometry parameters that significantly affect the electromechanical properties of the printed circuits. This study aims to optimize the geometry parameters of inkjet-printed silver nanoparticle traces on plasma-treated polydimethylsiloxane (PDMS) substrates. The optimization process was conducted for two printed shapes, namely straight line and horseshoe patterns. The examined input factors for the straight line traces were: the number of inkjet-printed layers and line width. On the other hand, the number of cycles and amplitude were the examined input parameters for the horseshoe shape. First, the optimal number of layers and line width were found from the straight line analysis and subsequently were used in the optimization of the horseshoe pattern parameters. The optimization of the input parameters was carried out using the response surface methodology (RSM), where the objective of the optimization was to maximize the breakdown strain of the traces while maximizing the gauge factor and minimizing the ink cost. The results indicate that a 1.78 mm line width and one layer are the optimal geometry parameters for the straight line traces, while for the horseshoe pattern, the optimal parameters are one layer, a line width of 1.78 mm, amplitude of 4 mm and one cycle. The optimal straight line was designed to sustain up to 10% strain while the horseshoe pattern was designed to sustain up to 15% strain.
Highly Flexible and Stable Solid-State Supercapacitors based on a Homogeneous Thin Ion Gel Polymer Electrolyte Using a PDMS Stamp.

To achieve both high structural integrity and excellent ion transport, designing ion gel polymer electrolytes (IGPEs) composed of an ionic conducting phase and a mechanical supporting polymer matrix is one of the promising material strategies for the development of next-generation all-solid-state energy storage systems. Herein, we prepared an IGPE thin film, in which an ion-diffusing phase containing ionic liquids and lithium salts was bicontinuously intertwined with a cross-linked epoxy phase, using a silicon elastomer-based stamping method, thus producing a homogeneous IGPE-based thin film with a low surface roughness (RRMS = 0.5 nm). Following the optimization of the IGPE thin film in terms of the concentrations of ionic constituents, the film thickness, and various process parameters, the IGPE itself showed a high ion conductivity of 0.23 mS/cm with a low activation energy for lithium ion transport, as well as the high capacitance of approximately 10 μF/cm2 based on the metal-insulator-metal (MIM) configuration. Furthermore, an all-solid-state supercapacitor containing two IGPE-coating activated carbon electrodes produced using our poly(dimethylsiloxane) (PDMS) stamping method exhibited high energy and power densities (44 Wh/kg at 875W/kg and 28 kW/kg at 3 Wh/kg). It was also found that this supercapacitor showed a dramatic reduction (more than 50%) of the current-resistance (IR) drop, which is an indicator of low interface resistance, while maintaining the initial electrochemical performance even after severe mechanical deformation such as bending or rolling. Therefore, all these results support that our developed PDMS stamping method enables the rendering of a high-performance ion gel polymer thin-film-based electrolyte with acceptable stability and mechanical flexibility for all-solid-state wearable energy storage devices.
Overexpression of OsPT8 Increases Auxin Content and Enhances Tolerance to High-Temperature Stress in Nicotiana tabacum

Temperature is a primary factor affecting the rate of plant development; as the climate warms, extreme temperature events are likely to increasingly affect agriculture. Understanding how to improve crop tolerance to heat stress is a key concern. Wild plants have evolved numerous strategies to tolerate environmental conditions, notably the regulation of root architecture by phytohormones, but the molecular mechanisms of stress resistance are unclear. In this study, we showed that high temperatures could significantly reduce tobacco biomass and change its root architecture, probably through changes in auxin content and distribution. Overexpression of the OsPT8 phosphate transporter enhanced tobacco tolerance to high-temperature stress by changing the root architecture and increased the antioxidant ability. Molecular assays suggested that overexpression of OsPT8 in tobacco significantly increased the expression of auxin synthesis genes NtYUCCA 6, 8 and auxin efflux carriers genes NtPIN 1,2 under high-temperature stress. We also found that the expression levels of auxin response factors NtARF1 and NtARF2 were increased in OsPT8 transgenic tobacco under high-temperature stress, suggesting that OsPT8 regulates auxin signaling in response to high-temperature conditions. Our findings provided new insights into the molecular mechanisms of plant stress signaling and showed that OsPT8 plays a key role in regulating plant tolerance to stress conditions.
Multilayer Nanofiber Composite Separator for Lithium-Ion Batteries with High Safety

An original Von Koch curve-shaped tipped electrospinneret was used to prepare a polyimide (PI)-based nanofiber membrane. A multilayer Al2O3@polyimide/polyethylene/Al2O3@polyimide (APEAP) composite membrane was tactfully designed with an Al2O3@ polyimide (AP) membrane as outer shell, imparting high temperature to the thermal run-away separator performance and a core polyethylene (PE) layer imparts the separator with a thermal shut-down property at low temperature (123 °C). An AP electrospun nanofiber was obtained by doping Al2O3 nanoparticles in PI solution. The core polyethylene layer was prepared using polyethylene powder and polyterafluoroethylene (PTFE) miniemulsion through a coating process. The addition of PTFE not only bonds PE power, but also increases the adhesion force between the PE and AP membranes. As a result, the multilayer composite separator has high safety, outstanding electrochemical properties, and better cycling performance as a lithium-ion battery separator.
Preparation and Photocatalytic Properties of CdS and ZnS Nanomaterials Derived from Metal Xanthate

In this paper, we report a new, simple method for the synthesis of CdS and ZnS nanoparticles (NPs) prepared in a basic aqueous medium using metal xanthate as the sulfur source. The structure, morphology, size distribution, optical band gap, and photocatalytic properties of the newly obtained nanomaterials were investigated by UV-Vis spectroscopy, X-ray diffraction, and transmission electron microscopy. The results show that both CdS and ZnS crystallized in cubic phase and formed NPs with average sizes of 7.0 and 4.2 nm for CdS and ZnS, respectively. A blue shift of UV-Vis absorbance band and higher energy band gap values were observed for both materials in comparison with their bulk counterparts, which is in accordance with the quantum confinement effect. The as-prepared nanomaterials were tested in visible-light driven photocatalytic decomposition of methylene blue (MB). After irradiation for 180 min, the degradation rate of MB with a concentration of 8 × 10−6 mol/L mixed with a photocatalyst (CdS or ZnS, both 10 mg in 100 mL solution of MB) was found to be 72% and 61%, respectively. The CdS NPs showed better photocatalytic activity than ZnS, which could be explained by their lower energy band gap and thus the ability to absorb light more efficiently when activated by visible-light irradiation.
Advantages of training with an adaptive driving device on a driving simulator compared to training only on the road

Abstract Purpose To compare the advantages of training on a driving simulator versus on the road, when learning to drive with new assistive technologies (AT) in individuals with motor impairments. Method An experimental group (EXP = 16) that trained on a driving simulator was compared to a comparison group (CMP = 16) that received training only on the road. A post-training road test assessed driving performance. Analysis included proportion of participants who successfully completed the on-road driving test, number of training sessions, level of satisfaction, simulator sickness, advantages and discomforts. Results EXP and CMP were comparable for age (48 ± 17 years), sex (13 M, 3 F), and AT (3 steering wheel knobs with integrated switches, 4 left accelerators, 9 hand controls and steering wheel knobs). No significant difference was observed between groups in the proportion of participants who were found to be fit to drive (EXP: 9/16; CMP: 13/16; p = 0.126) or in the number of sessions completed (EXP: 4.3; CMP: 3.2; p = 0.061). For 6 of the 9 satisfaction variables, participants reported being satisfied/very satisfied with training on a simulator with driving assistive technologies 76% to 100% of the time. EXP was satisfied to have been able to use simulator sessions before going on the road (100%). Participants determined to be fit to drive on an on-road test following simulator training showed no significant difficulty continuing with the training. EXP reported temporary discomfort on the simulator during the initial session (88%). Conclusion Simulators provide some advantages for training drivers with adaptive aids in a safe context. IMPLICATIONS FOR REHABILITATION Among individuals with motor impairments who used to drive: All participants reported a high level of satisfaction training on the simulator with assistive technologies. The simulator proved to be an interesting tool for initiating training with new driving AT in a safe environment at no cost to individuals. The few discomforts reported during the first session resolved over time when participants continued with the driving simulator protocol. Occupational therapists noticed that the difficulties observed on the simulator were the same as those observed during on-road testing. The simulator allowed participants to begin to learn how to operate a vehicle with new assistive technology in a safe context.
Tumor Expression of Cyclin-Dependent Kinase 5 (Cdk5) Is a Prognostic Biomarker and Predicts Outcome of Oxaliplatin-Treated Metastatic Colorectal Cancer Patients

In recent years, an increasing number of studies have shown that elevated expression of cyclin dependent kinase (Cdk5) contributes to the oncogenic initiation and progression of many types of cancers. In this study, we investigated the expression pattern of Cdk5 in colorectal cancer (CRC) cell lines and in a large number of tumor samples in order to evaluate its relevance in this pathogenesis and possible use as a prognostic marker. We found that Cdk5 is highly expressed and activated in CRC cell lines and that silencing of the kinase decreases their migration ability. In tumor tissues, Cdk5 is overexpressed compared to normal tissues due to a copy number gain. In patients with localized disease, we found that high Cdk5 levels correlate with poor prognosis, while in the metastatic setting, this was only the case for patients receiving an oxaliplatin-based treatment. When exploring the Cdk5 levels in the consensus molecular subtypes (CMS), we found the lowest levels in subtype 1, where high Cdk5 again was associated with a poorer prognosis. In conclusion, we confirm that Cdk5 is involved in CRC and disease progression and that it could serve as a prognostic and predictive biomarker in this disease.