Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploration de la fonction visuelle sensorielle chez l'animal. Première partie: Rappels anatomo-physiologiques

Light is made of electromagnetic radiation “caught” by a sensor, namely the eye. The eye works simultaneously as an optical instrument, an image receptor and, with the help of the retina, as a light transformer. The retina includes neural tissue and a pigmented epithelium (RPE) connected to two vascular systems (retinal and choroidal). It is divided into three functionally different layers: the prereceptoral layer (RPE), intimately connected with the chorio-capillaris, the receptoral layer which includes two distinct photoreceptors (cones and rods), and the post-receptoral layer (bipolar cells, horizontal cells, amacrine cells and ganglionic cells). The RPE has numerous functions: phagocytic (macrophages) through its involvement in photoreceptor catabolism, ion transport between the blood and the subretinal space (epithelial cells), and subretinal K+ concentration (glial cells) . Furthermore, the RPE is extremely sensitive to variations in pH, PO2, PCO2 and light intensity. Its function can be assessed by electrooculography. The receptoral layer includes two categories of phoreceptor cells, cones and rods, which differ by their number, density and localisation as well as their spectral and energetic properties. The receptoral layer is the site of phototransduction, a sum of electro-ionic events transforming light energy into an electrophysiological signal. Bipolar cells, horizontal cells, amacrine cells and ganglion cells form the post-receptoral layer, which ultimately encodes the visual message into neuronal potentials. These potentials are then transmitted throughout visual pathways to reach the visual cortex where the visual scene is reconstructed. Electroretinograms (ERG) are used to assess the function of the retinal layers, while visual evoked potentials (VEPs) test the function of the visual cortex. Awareness of the visual scene is achieved by further neuronal processing, in what is called the cognitive stage.
Potential of food intake biomarkers in nutrition research

The influence of dietary habits on health/disease is well-established. Accurate dietary assessment is essential to understand metabolic pathways/processes involved in this relationship. In recent years, biomarker discovery has become a major area of interest for improving dietary assessment. Well-established nutrient intake biomarkers exist; however, there is growing interest in identifying and using biomarkers for more accurate and objective measurements of food intake. Metabolomics has emerged as a key tool used for biomarker discovery, employing techniques such as NMR spectroscopy, or MS. To date, a number of putatively identified biomarkers were discovered for foods including meat, cruciferous vegetables and legumes. However, many of the results are associations only and lack the desired validation including dose–response studies. Food intake biomarkers can be employed to classify individuals into consumers/non-consumers of specific foods, or into dietary patterns. Food intake biomarkers can also play a role in correcting self-reported measurement error, thus improving dietary intake estimates. Quantification of food intake was previously performed for citrus (proline betaine), chicken (guanidoacetate) and grape (tartaric acid) intake. However, this area still requires more investigation and expansion to a range of foods. The present review will assess the current literature of identified specific food intake biomarkers, their validation and the variety of biomarker uses. Addressing the utility of biomarkers and highlighting gaps in this area is important to advance the field in the context of nutrition research.
Descemet Membrane Endothelial Keratoplasty in Asian Eyes: Intraoperative and Postoperative Complications.

PURPOSE To describe intraoperative and postoperative complications of Descemet membrane endothelial keratoplasty (DMEK) in Asian eyes. METHODS A: prospective comparative study of consecutive cases of DMEK cases between January 2016 and January 2018. A subgroup of consecutive patients were optimized with preoperative topical eye drops and modification of donor insertion. Main outcome measures were intraoperative complications and total surgical time. Secondary outcome measures were postoperative complications and endothelial cell loss (ECL) at the 6-month follow-up. RESULTS We included 50 consecutive patients in this study; mean age of 66 ± 9 years old with 70% women. The indications for DMEK were Fuchs endothelial dystrophy (82%) and bullous keratopathy (18%). When compared with the standard group (n = 24 eyes), the optimized DMEK group (n = 26 eyes) was associated with a significantly reduced surgical time (33.9 ± 12.7 vs. 26.9 ± 7.6 minutes; P = 0.041), lower ECL at 6 months (27.2 ± 17.1% vs. 13.7 ± 9.7%; P = 0.012) and lower risk of high vitreous pressure causing iris prolapse (16.7% vs. 0%; P = 0.046). Multivariate analysis revealed a shorter surgical time (Odds Ratio [OR]: 0.924; 95% confidence interval: 0.858-0.995; P = 0.036) and reduced ECL (OR: 0.907; 95% confidence interval: 0.843-0.977; P = 0.01) in the optimized group. CONCLUSIONS We observed intraoperative challenges such as difficulty with donor insertion with increased vitreous pressure in Asian eyes by performing DMEK surgery, which may be reduced with anticipated preoperative and postoperative measures.
Presentation, Diagnostic Imaging, and Clinical Outcome of Conventional Ameloblastoma in Dogs

A noninductive tumor of odontogenic epithelium occurs within the tooth bearing regions of the jaw in dogs and fits the conventional definition of ameloblastoma, which is distinct from, and less common than, canine acanthomatous ameloblastoma. In order to clarify the clinical and radiological features of this uncommon odontogenic tumor in dogs, we performed a retrospective study of 20 dogs that were diagnosed between 2007 and 2015. Follow-up information was obtained for 17 of 20 dogs. The study group of dogs showed no apparent age, breed, or gender predilection. Conventional ameloblastoma is typically slow growing, well demarcated, and locally destructive. Tumors most commonly occurred as a mass or focal bony swelling within the maxilla (13/20) or mandible (7/20). Based on cases with available diagnostic imaging, as either dental radiographs or computed tomographic images, the tumors were usually intraosseous and caused mixed lytic/proliferative bone changes. Nevertheless, conventional ameloblastomas did not aggressively infiltrate adjacent tissues and recurrence was not observed within the study group, even in patients with narrow surgical margins or treatment by cyst enucleation.
Automated Measurement of Pancreatic Fat and Iron Concentration Using Multi-Echo and T1-Weighted MRI Data

We present an automated method for estimation of proton density fat fraction and iron concentration in the pancreas using both structural and quantitative imaging data present in the UK Biobank abdominal MRI acquisition protocol. Our method relies on automatic segmentation of 3D T1-weighted MRI data using a convolutional neural network and extracting the location of the multi -echo slice through the segmented volume. We finally estimate the fat and iron content in the pancreas using the extracted segmentation as a mask on the multi-echo data. Our segmentation model achieves a mean dice similarity coefficient of 0.842±0.071 on unseen data, which is comparable to the current state of the art for 3D segmentation of the pancreas. The proposed method is efficient and robust and enables an enhanced analysis of spatial distribution of proton density fat fraction and iron concentration over the current practice of manually placing regions of interest on often ambiguous multi-echo data.
Energy-efficient Design of an STT-RAM-based Hybrid Cache Architecture

The capacity and the energy consumption of the last-level cache (LLC) must be improved toward future microprocessors. This paper proposes an STT-RAM-based hybrid cache architecture (HCA) and its replacement policy, named the Fast Region First Used (FRFU) policy. The proposed HCA is composed of two types of STT-RAM devices with different characteristics to mitigate the disadvantages of non-volatile STT-RAM devices. The FRFU policy provides the better handling of the data blocks for the proposed HCA than the LRU policy. The evaluation results show that the proposed HCA and its policy can successfully reduce the energy consumption by 55% and improve the performance by 1% on average compared with a conventional SRAM LLC.
Modeling and Stability Analysis of a Smart Transformer-Fed Grid

The interaction of the smart transformer (ST) with the grid-converter-based distributed energy resources (DERs) could trigger instability. Recent research efforts have been made to study the stability issues caused by the resonances (e.g. LC or LCL filter resonances of DERs) in ST LV side grid. This paper studies the impact of the grid synchronization of the grid-converter-based DER on the stability of the ST as well as the grid. The equivalent admittance of the grid converter considering the effect of synchronous reference frame phase-locked loop (SRF-PLL) is developed and merged with the ST voltage control. Based on the generalized Nyquist criterion, the stability analysis of a ST-fed grid is carried out, showing that the PLL bandwidth is a key factor that determines the system stability. To address the stability issue, a stabilization method based on virtual impedance is proposed and can be seamlessly integrated with the ST voltage control. Simulation and experimental results are provided to validate the effectiveness of the analysis and the proposed control strategy.
Training of a discrete motor skill in humans is accompanied by increased excitability of the fastest corticospinal connections at movement onset

The primary motor cortex (M1) is fundamentally important for the acquisition of skilled motor behaviours. We tested the excitability changes of distinct M1 circuits at movement onset with TMS H‐reflex conditioning. Human subjects trained a discrete spatiotemporal motor skill. Practice was associated with reduced kinematic variability and improved motor performance. Performance improvements were paralleled by task‐specific excitability increases of the fastest corticospinal connections at infragranular layer 5b of M1. No task‐related changes in excitability were observed at supragranular layers. Excitability changes in the fastest corticospinal connections were not directly related to changes in motor performance.
A Novel Simulated-Annealing Based Electric Bus System Design, Simulation, and Analysis for Dehradun Smart City

Smart transportation network development with environmental issues into consideration has brought Industry 4.0 based solutions on priority. In this direction, battery-powered electric bus systems have been considered widely for ensuring flexibility, operation cost, and lesser pollutants emission. Industry 4.0 provides automation through a cyber-physical system (CPS), the interconnection of bus system entities with industrial internet-of-things (IIoT), remote information availability through cloud computing and scientific disciplines (human-computer interaction, artificial intelligence, machine learning etc.) integration. In this work, a discrete event-based simulation-optimization approach is integrated that take care of bus energy consumption according to real-time city’s passenger needs and on-road friction levels. The proposed simulation optimization methodology utilizes multi-objective with dependent and independent variables for optimizing the overall system performance. In simulation optimization, objective functions are designed to tackle battery consumption, Internet-of-Thing (IoT) network performance, cloud operations efficiency and smart scientific discipline integration. Simulation parameters are based on a real-time bus system which is further analyzed, filtered and adapted as per the needs of the system. In another analysis, supercharger’s capacities are varied to evaluate the performance of the proposed system and identify the low cost and efficient smart transportation system. Simulation results show different scenarios for variations in the number of buses, charging stations, bus-depots, mobile charging facilities, and bus-schedules. Simulation results show that the average passenger’s waiting time in the waiting is (after ticket booking) varies between 0.2 minutes to 0.7 minutes in real-time traffic conditions. In similar traffic conditions, total passenger’s time in system (ticket booking to travel) varies between 41.6 minutes (for 24 hours) to 45.5 minutes (for 1 year). In the simulation, priorities are given to those dependent and independent variables which save the battery consumption and elongate the utilization of buses. Lastly, it is also observed that the proposed system is suitable for resource-constraint devices because Gate Equivalent (GE) calculation shows that the proposed system can be implemented between 1986 GEs (communicational cost without confidentiality and authentication) and 7939 GEs (computational cost with HMAC for authentication in data storage). This ensures varies security primitivs such as confidentiality, availability and authentication.
Effects of Mucosal Ions on Calcium Absorption in the Jejuno-ileum of the Goat in vitro

We, in the first experiment, observed changes in concentrations of minerals, short-chain fatty acids and osmolality along 6 parts of the caprine gastrointestinal tract. The concentrations of Na and HCO3 and pH were lowest in the abomasum, changing reciprocally with those of Ca and Cl-. The concentration of Mg gradually (P<0.05) increased along the intestine. In the second experiment, we examined effects of changing medium ionic compositions on Ca absorption (a ratio of serosal to mucosal Ca concentration) in everted sacs of the jejuno-ileum. Ca absorption in a solution containing 41.2mmol/l MgCl2 was greater than that in a solution containing 1.2mmol/l MgCl2 (P<0.05). The effect of Mg on Ca absorption was dependent on the mucosal Mg concentrations (P<0.01). From these results, we conclude that in goats, a luminal Mg concentration, which increases along the intestine, accelerates Ca absorption in the jejuno-ileum.
The Effect of Landscape Heterogeneity on the Probability of Patch Colonization

The effect of landscape heterogeneity on the dispersal of organisms between habitat islands is poorly understood. Preferred pathways for dispersal (i.e., corridors), as well as dispersal barriers, are difficult to identify when the landscape matrix is composed of a complex mixture of land cover types. We developed an individual-based dispersal model to measure immigration and emigration rates between habitat islands within hetero- geneous landscapes. Dispersing individuals of a model organism were simulated as self- avoiding random walkers (SAW) traversing a digital land cover map, with each habitat type assigned a priori a probability that the SAW would enter that habitat type. Each individual began the dispersal process on a random site at the edge of a deciduous forest patch and was allowed to move until it reached a different deciduous forest patch. Visu- alization of the movement patterns across the landscape was achieved by tabulating the frequency of visitation Qf successful dispersers to each grid cell on the map. The model was used to estimate the probabilities of disperser transfer between patches by varying the a priori probabilities of movement into each habitat type in order to: (1) estimate the effect of changing landscape heterogeneity on the transfer probabilities, and (2) visualize dispersal corridors and barriers as perceived by model organisms operating by specific movement rules and at specific scales. The results show that 89% of the variability in dispersal success can be accounted for by differences in the size and isolation of forest patches, with closer and larger patches having significantly greater exchange of dispersing organisms. However, changes in the heterogeneity of the landscape matrix could significantly enhance or decrease emigration success from an individual patch, depending on the landscape. Changes in emigration success from an individual patch resulting from changes in matrix heterogeneity were not predictable, and transfer rates between patches were not symmetrical due to differences in the proximity of neighboring patches, and differences in the funneling at- tributes of certain landscape patterns. Visualizations showed that corridors are often diffuse and difficult to identify from structural features of the landscape. A wide range of organisms with differing movement capabilities can be simulated using the approach presented to increase our understanding of how landscape structure affects organism dispersal.
P‐glycoprotein and multidrug resistance‐associated protein‐1 expression in acute myeloid leukemia: Biological and prognosis implications

Despite the advances in the cure rate for acute myeloid leukemia (AML), a considerable number of patients die from the disease due to the occurrence of multidrug resistance (MDR). Overexpression of the transporter proteins, such as P‐glycoprotein (Pgp) and multidrug resistance‐associated protein (MRP), confers resistance to the treatment of these leukemias.
Extracellular vesicle‐mediated crosstalk between melanoma and the immune system: Impact on tumor progression and therapy response

Melanoma is a very lethal tumor type that easily spreads and colonizes regional and distant tissues. Crucial phenotypic changes that favor melanoma metastasis are interposed by the tumor microenvironment (TME), representing a complex network in which malignant cells communicate not only with each other but also with stromal and immune cells. This cell‐cell communication can be mediated by extracellular vesicles (EVs), which are lipid bilayer‐delimited particles capable of carrying a wide variety of bioactive compounds. Both melanoma‐derived or TME‐derived EVs deliver important pro‐ and antitumor signals implicated in various stages of tumor progression, such as proliferation, metastasis, and treatment response. In this review, we highlight the recent advances in EV‐mediated crosstalk between melanoma and immune cells and other important cells of the TME, and address different aspects of this bidirectional interaction as well as how this may hinder or trigger the development and progression of melanoma. We also discuss the potential of using EVs as biomarkers and therapeutic strategies for melanoma.
Reagents for detection of Rift Valley fever virus infection in sheep

Rift Valley fever virus (RVFV) causes Rift Valley fever (RVF), resulting in morbidity and mortality in humans and ruminants. Evidence of transboundary outbreaks means that RVFV remains a threat to human health and livestock industries in countries that are free from the disease. To enhance surveillance capability, methods for detection of RVFV are required. The generation of reagents suitable for the detection of RVFV antigen in formalin-fixed, paraffin-embedded tissues from infected animals have been developed and are described herein. Recombinant nucleoprotein (rNP) was expressed in Escherichia coli and purified using immobilized metal ion affinity chromatography. Purified rNP was used as an immunogen to produce anti-NP polyclonal antisera in rabbits for use in detection of RVFV NP in experimentally infected animals by immunohistochemistry. Antisera raised in rabbits against rNP were able to recognize viral NP antigen in fixed infected Vero cell pellets and sheep liver. Therefore, the methods and reagents described herein are useful in assays for detection of RVFV infections in animals, for research and surveillance purposes.
On-Wafer FinFET-Based EUV/eBeam Detector Arrays for Advanced Lithography Processes

A novel microdetector array (MDA) for monitoring electron beam (eBeam) and extreme ultraviolet (EUV) lithography processes in 5 nm and beyond FinFET technology is first-time presented. This on-wafer detector array consists of high-density sensing cells which are fully compatible with standard FinFET CMOS processes. Fin coupling structures and energy-sensing pads are first applied in an ultrasmall detector for realizing efficient eBeam and EUV photon detection. In advanced lithography process, eBeam or EUV level projected on the wafer can be precisely recorded on the on-wafer MDA without power or batteries. The distributions and variations on the beam intensities collected by MDA can be electrically measured in real time or inline through wafer level test after eBeam or EUV exposures. The proposed MDA is expected to provide real-time feedback for the optimization and stable maintenance of advanced photolithography processed critical to the development nanometer CMOS technologies.
Automatic Brain Organ Segmentation with 3D Fully Convolutional Neural Network for Radiation Therapy Treatment Planning

3D organ contouring is an essential step in radiation therapy treatment planning for organ dose estimation as well as for optimizing plans to reduce organs-at-risk doses. Manual contouring is time-consuming and its inter-clinician variability adversely affects the outcomes study. Such organs also vary dramatically on sizes - up to two orders of magnitude difference in volumes. In this paper, we present BrainSegNet, a novel 3D fully convolutional neural network (FCNN) based approach for automatic segmentation of brain organs. Brain-SegN et takes a multiple resolution paths approach and uses a weighted loss function to solve the major challenge of the large variability in organ sizes. We evaluated our approach with a dataset of 46 Brain CT image volumes with corresponding expert organ contours as reference. Compared with those of LiviaNet and V-Net, BrainSegNet has a superior performance in segmenting tiny or thin organs, such as chiasm, optic nerves, and cochlea, and outperforms these methods in segmenting large organs as well. BrainSegNet can reduce the manual contouring time of a volume from an hour to less than two minutes, and holds high potential to improve the efficiency of radiation therapy workflow.
YAP1 Withdrawal in Hepatoblastoma Drives Therapeutic Differentiation of Tumor Cells to Functional Hepatocyte‐Like Cells

Despite surgical and chemotherapeutic advances, the 5‐year survival rate for stage IV hepatoblastoma (HB), the predominant pediatric liver tumor, remains at 27%. Yes‐associated protein 1 (YAP1) and β‐catenin co‐activation occurs in 80% of children’s HB; however, a lack of conditional genetic models precludes tumor maintenance exploration. Thus, the need for a targeted therapy remains unmet. Given the predominance of YAP1 and β‐catenin activation in HB, we sought to evaluate YAP1 as a therapeutic target in HB.
Exploring Deep Learning Approaches to Recognize Handwritten Arabic Texts

Recognition of cursive handwritten Arabic text is a difficult problem because of context-sensitive character shapes, the non-uniform spacing between words and within a word, diverse placements of dots, and diacritics, and very low inter-class variation among individual classes. In this paper, we review and investigate different deep learning architectures and modeling choices for Arabic handwriting recognition. Further, we address the problem that imbalanced data sets present to deep learning systems. In order to address this issue, we are presenting a novel adaptive data-augmentation algorithm to promote class diversity. This algorithm assigns a weight to each word in the database lexicon. This weight is calculated based on the average probability of each class in a word. Experimental results on the IFN/ENIT and AHDB databases have shown that our presented approach yields state-of-the-art results.