Miracle-dz/UniFAR-FTUs huggingface dataset:
Atlas of PD-L1 for Pathologists: Indications, Scores, Diagnostic Platforms and Reporting Systems

Background. Innovative drugs targeting the PD1/PD-L1 axis have opened promising scenarios in modern cancer therapy. Plenty of assays and scoring systems have been developed for the evaluation of PD-L1 immunohistochemical expression, so far considered the most reliable therapeutic predictive marker. Methods. By gathering the opinion of acknowledged experts in dedicated fields of pathology, we sought to update the currently available evidence on PD-L1 assessment in various types of tumors. Results. Robust data were progressively collected for several anatomic districts and leading international agencies to approve specific protocols: among these, TPS with 22C3, SP142 and SP263 clones in lung cancer; IC with SP142 antibody in breast, lung and urothelial tumors; and CPS with 22C3/SP263 assays in head and neck and urothelial carcinomas. On the other hand, for other malignancies, such as gastroenteric neoplasms, immunotherapy has been only recently introduced, often for particular histotypes, so specific guidelines are still lacking. Conclusions. PD-L1 immunohistochemical scoring is currently the basis for allowing many cancer patients to receive properly targeted therapies. While protocols supported by proven data are already available for many tumors, dedicated studies and clinical trials focusing on harmonization of the topic in other still only partially explored fields are surely yet advisable.
Using Biosurfactants from Plants to Treat Chicken Feathers into a Green Oil Absorbent Material

While feathers are still commonly regarded in many places as waste, in many developed countries it has been considered a valuable by-product of the poultry industry. The poultry industry of Vietnam has achieved encouraging achievements in the past 10 years. The total flock of poultry from 100 million to now has reached nearly 467 million. Though light as a feather, with the vast quantities of chickens produced annually, the number of feathers produced is considerable. Research has shown that the feathers have hydrophobic properties and can therefore be used to make products that absorb oil. However, the use of large amounts of toxic detergents to clean chicken feathers in reported studies has reduced the environmental significance of agricultural waste reuse. In this study, we evaluated the possibility of replacing toxic cleaning agents with eco-friendly natural cleaners in the handling of chicken feathers. Water-based extracts of soapnuts and bo-ket fruits have been selected for our study due to their high saponin content - an effective cleaning agent, and have been used as a dishwashing liquid or shampoo for a long-time by local housewives. Our study showed that natural detergents derived from soapnuts have been shown the ability to remove lards on the plastic surface, and to clean chicken feathers, thereby increasing their capacity to absorb various oils including cooking oil, used cooking oil, and lubricant oil. We have also created an oil-absorbing pillow containing soapnut extract-treated chicken feathers with a maximum efficiency of 16.8 g/g in absorbing lubricant oil. Our research opens new avenues for the use and treatment of poultry feathers, contributing to the reduction of solid waste from the poultry industry by methods which is friendlier to the environment. The greenness of the created absorber is guaranteed.
Concrete panel thickness demand for the design of composite steel plate shear wall

Composite steel plate shear walls (C‐SPWs) are composed of an infill steel plate and reinforced concrete encasements. With an adequate thickness, the concrete encasement can effectively prevent the premature buckling of the infill steel plate. Researchers have provided nonconservative concrete thickness demands through analyses of approximate elastic buckling, for which the analytical model is too simplistic to simulate C‐SPW buckling. In this paper, the buckling of C‐SPW is addressed using a nonlinear finite element method. To assist this method, a formula for the buckling strength of C‐SPW is theoretically developed. Utilizing the results of nonlinear finite element analysis on C‐SPW, the effects of concrete panel thickness, concrete elastic modulus, infill steel plate thickness, panel aspect ratio, and stud spacing on the infill steel plate buckling are analyzed, and the critical drift ratio corresponding to the buckling of the infill steel plate is obtained. According to the criterion that the C‐SPW will not buckle until its drift ratio achieves the drift limit (0.4%), the minimum concrete panel thicknesses demands are captured from finite element analysis. Fitting these predicted minimum concrete thicknesses, an available formula is proposed for the concrete thickness demand in the design of C‐SPW.
Pengaruh Model Pembelajaran Guided Discovery Learning terhadap Hasil Belajar Siswa pada Mata Pelajaran Dasar Listrik dan Elektronika

Penelitian ini bertujuan untuk mengetahui apakah terdapat perbedaan hasil belajar siswa yang diberi model Guided Discovery Learning dengan siswa yang belajar secara konvensional pada mata pelajaran Dasar Listrik dan Elektronika (DLE). Jenis penelitian ini adalah penelitian eksperimen. Subjek penelitian ini siswa kelas X Teknik Ketenagalistrikan Sekolah Menengah Kejuruan (SMK) Negeri 1 Pariaman yang terdaftar pada semester 2 tahun ajaran 2018/2019. Sampel penelitian yaitu kelas TOI sebagai kelas eksperimen dan TITL1 sebagai kelas kontrol. Data yang dikumpulkan berupa data hasil belajar siswa menggunakan soal objektif. Pengujian hipotesis diuji dengan menggunakan uji-t. Berdasarkan analisis data diperoleh rata-rata nilai kelas eksperimen adalah 79,2 dan kelas kontrol 73 dengan simpangan baku 7,62 dan 8,7. Hasil uji hipotesis menunjukkan perbedaan yang signifikan antara hasil belajar kelas guided Abstract This study aims to determine whether there are differences in student learning outcomes given the Guided Discovery Learning model with students who study conventionally in the Basic Electricity and Electronics (DLE) subjects. This type of research is experimental research. The subject of this study was the tenth-grade students of Electricity Engineering at State Vocational High School 1 Pariaman who were enrolled in semester 2 of the 2018/2019 school year. The research sample is the TOI class as an experimental class and TITL1 as a control class. Data collected in the form of student learning outcomes data using objective questions. Hypothesis testing is tested using t-tests. Based on data analysis, the average value of the experimental class was 79.2 and the control class was 73 with a standard deviation of 7.62 and 8.7. Hypothesis test results showed a significant difference between the learning outcomes of the experimental class and the control class. It can be concluded that student learning outcomes given guided discovery learning models are higher than student learning outcomes that are not given treatment.
Evaluating Poland’s Family 500+ Child Support Programme

I investigate the immediate effects of the introduction of a large-scale child benefit programme on the labour supply of household members in Poland. Due to non-ran-dom eligibility and the universal character of the programme, standard evaluation estimators may be inconsistent. In order to address this issue, I propose an approach that combines difference-in-difference (DID) propensity score based methods with the covariate balancing propensity score (CBPS) approach developed by Imai and Ratkovic [ 2014 ]. The DID estimators exploit the time dimension to uncover the causal effect of interest. The CBPS method is expected to significantly reduce the bias resulting from systematic differences between treated and untreated subpopulations. I also account for potential heterogeneity among households by focus-ing on comparisons between locally defined subpopulations
Effectiveness of Early Favipiravir Therapy in Hospitalised COVID-19 Patients

COVID-19 is a disease caused by a novel coronavirus with no specific, standard treatment. We investigated the clinical data of COVID-19 patients admitted to King Fahad Specialist Hospital (KFSH) in Buraydah by comparing the patients who were treated early with favipiravir (within 3 days of admission) to patients who were treated after three days of admission or not treated. 165 patients were confirmed with PCR tests and admitted to KFSH for treatment. Comorbidities contributed significantly to increasing the length of stay in hospital at 11.4 ± 0.8 days compared to patients with no comorbidities at 8.6 ± 0.9 days (p=0.041). A total of 103 patients were treated with favipiravir, and we found that early treatment with favipiravir (within 3 days) reduced the length of stay in hospital significantly (8.8 ± 1.4 days) compared to patients who were treated after 3 days (13.3 ± 4.6 days) (p=0.0015). Moreover, patients with comorbidities in both early and late treatment groups had significantly higher average lengths of stay in hospital (11.2 ± 0.9 days) compared to patients with no comorbidities (7.9 ± 0.7 days) (p=0.017). Interestingly, patients treated early with favipiravir (with comorbidities and without) stayed fewer days in hospital compared to those with late treatment (p=0.021; a difference of 4.5 ± 1.9 days; and p=0.018; a difference of 4.2 ± 1.7 days, respectively). In conclusion, our analysis indicates that early treatment with favipiravir can reduce the length of stay in hospital and improve clinical manifestations of COVID-19 patients.
Modélisation directe et inverse en prospection électrique sur les structures 3D complexes par la méthode des éléments finis

Ce travail a pour objectif la mise au point d'un ensemble d'outils de modelisation directe et inverse en utilisant le code d'elements finis CESAR-LCPC. Ces outils sont adaptes aux donnees electriques collectees sur des structures 3D a geometrie complexe. Pour le probleme direct, un programme utilitaire servant d'interface avec le solveur CESAR a ete cree afin de modeliser des sequences de mesures electriques (tomographies). Afin de pouvoir inverser un nombre important de donnees sur des modeles de grandes dimensions, une fonction objectif est minimisee en utilisant la technique de l'etat adjoint. Cette approche est originale car elle vise le calcul direct de la variation a apporter aux parametres du modele, sans evaluation explicite de la matrice de sensibilite. Des donnees synthetiques ont ete utilisees pour valider cet algorithme d'inversion. La fiabilite des modeles inverses est testee en utilisant une methode de calcul de l'indice ROI (Region of Investigation).
How building design and technologies influence heat-related habits

ABSTRACT The discrepancy between calculated heat demand and measured heat consumption – the performance gap – suggests that the energy efficiency of houses affects the energy-consuming habits of its occupants. This coincides with the theories of practice describing how materiality affects practices through reconfiguring practical understandings, e.g. comfort expectations. Heat-related habits are investigated in the paper across material contexts, e.g. building characteristics and technologies. Evidence based on a combined questionnaire survey and administrative data on occupants (n = 1216) living in single-family detached houses in Denmark shows that the practices of adjusting thermostats and the amount of clothing worn indoors as well as perceived indoor temperature correlate with building characteristics, e.g. energy efficiency of the building envelope and technical installations. These correlations are moderated by the socio-demographic characteristics of occupants. However, building characteristics are found to be less influential on the frequency of opening windows. The results indicate that occupants dress warmer and keep lower temperatures in energy-inefficient houses. This suggests that material arrangements have a significant influence on occupant expectations and practices, which lead to increased indoor temperatures and energy demand. A challenge for building regulations will be to account for how energy efficient house characteristics and technologies adversely affect occupants’ energy-consuming behaviour.
IWV Measurement and Modelling with GNSS and NWP (WRF) over Northwest Bulgaria

In recent decades, the increase in the number and intensity of high-impact weather events, like intense precipitation, hail and thunderstorms has been an indisputable trend worldwide. In Bulgaria they are common in the summer months and cause large economic losses. As a part of the project “Balkan-Mediterranean real-time severe weather service”, since February 2020, the Sofia University Global Navigation Satellite System (GNSS) Analysis Center processes in operational near-real time mode (NRT) stations in Bulgaria. In this study the Integrated Water Vapour (IWV) for four stations in Northwest Bulgaria was calculated using the Weather Research and Forecasting (WRF) model and the results are compared with IWV derived from the GNSS-meteorology concept. The results obtained lead to the conclusion that the model IWV is higher than the one derived from GNSS.
AN ALGORITHM OF TOTAL VARIATION FOR IMAGE INPAINTING

Abstract— Inpainting, the technique of modifying an image in an undetectable form, is as ancient as art itself. Inpainting is an image interpolation problem with broad applications in image and vision analysis. Digital inpainting is related to automatic filling-in of user-selected regions in digital images. It consider the problem of filling in missing or damaged wavelet coefficients due to lossy image transmission or communication. The task is closely related to classical inpainting problems, but also remarkably differs in that the inpainting regions are in the wavelet domain. New challenges include that the resulting inpainting regions in the pixel domain are usually not well defined, as well as that degradation is often spatially inhomogeneous. An extensive survey of previous work related to the digital inpainting is presented to fill in the gap and a new algorithm using a variational approach to formulate the reconstruction problem which is motivated by the quality of results, easier implementation, efficiency, and effectiveness is presented. The associated Euler Lagrange equations lead to nonlinear partial differential equations (PDE's) in the wavelet domain. Implemented method can be viewed as a method for solving Total-Variation(TV) minimization problems using fast optimization technique which is very efficient calculate an optimal solution for image inpainting in wavelet domain. The restored images obtained with this algorithm look plausible in general and surprisingly good in some cases. In addition, it is also having edge over other algorithms in terms of computation time and image quality while filling-in large region
Moisture Stability of Hard Sandstone Asphalt Mixture Based on APT with MMLS3

To evaluate the moisture stability of a hard sandstone asphalt mixture, a testing section of a hard sandstone asphalt mixture was prepared in the laboratory. The accelerated pavement testing (APT) with the one-third-scale model mobile load simulator (MMLS3) was conducted in this testing section under temperature and water-coupled conditions. As the APT number increased, the elastic modulus of the hard sandstone asphalt mixture pavement gradually decreased. The average elastic modulus was 22.99 GPa after 160000 APT cycles. The bulk specific density of the sample rolled by the MMLS3 increased, and the residual indirect tensile strength ratio was 88.7%. Therefore, the hard sandstone asphalt mixture had good resistance to moisture damage, and hard sandstone aggregates can be used in a hot mix of asphalt.
Secrecy Rate Region Enhancement in Multiple Access Wiretap Channel

|It is commonly known that physical layer security is achieved with a trade-o(cid:11) in terms of the achievable rate. Hence, security constraints generate rate losses in wiretap channels. To mitigate such rate losses in multi-user channels, we propose a coding/decoding scheme for multi-user multiple access wiretap channel (MAC-WT), where previously transmitted messages are used as a secret key to enhance the secrecy rates of the transmitting users, until the usual Shannon capacity region of a multiple access channel (MAC) is achieved without the secrecy constraint. With this coding scheme, all messages transmitted in the recent past are secure with respect to all the information of the eavesdropper till now. To achieve this goal, we introduce secret key bu(cid:11)ers at both the users and the legitimate receiver. Finally, we consider a fading MAC-WT and show that with this coding/decoding scheme, we can achieve the capacity region of a fading MAC channel (in the ergodic sense).
The Absence of STING Ameliorates Non-Alcoholic Fatty Liver Disease and Reforms Gut Bacterial Community

Non-alcoholic fatty liver disease (NAFLD) is one of the primary causes of cirrhosis and a major risk factor for hepatocellular carcinoma and liver-related death. It has been correlated with changes in the gut microbiota, which promote its development by regulating insulin resistance, bile acid and choline metabolism, and inflammation. Recent studies suggested a controversial role of the stimulator of interferon genes (STING) in the development of NAFLD. Here, we showed that as an immune regulator, STING aggravates the progression of NAFLD in diet-induced mice and correlated it with the changes in hepatic lipid metabolism and gut microbiota diversity. After feeding wild-type (WT) and STING deletion mice with a normal control diet (NCD) or a high-fat diet (HFD), the STING deletion mice showed decreased lipid accumulation and liver inflammation compared with WT mice fed the same diet. In addition, STING specifically produced this hepatoprotective effect by inhibiting the activation of CD8+ T cells. The gut microbiota analysis revealed significant differences in intestinal bacteria between STING deletion mice and WT mice under the same diet and environmental conditions; moreover, differential bacterial genera were associated with altered metabolic phenotypes and involved in related metabolic pathways. Overall, our findings reveal the important regulatory role that STING plays in the progression of NAFLD. In addition, the change in intestinal microbiota diversity may be the contributing factor.
Human-Aware Autonomous Navigation of a Care Robot in Domestic Environments

A major societal challenge in occidental countries nowadays is the continuously increasing ageing population. Due to this ageing society, solutions are needed to alleviate the limited care personnel and the ever increasing healthcare costs. To this end, service robots are proposed to meet this demand by assisting the elderly with their daily activities and providing them with a more independent life. When people are present, new behavioral concepts are necessary to assure acceptance of robots as daily assistants. Robot motion must take safety, as well as human comfort into account. This is the goal of Human-Aware Navigation (HAN). Most current HAN approaches focus on maintaining appropriate interaction spatial distances between the robot and the human, aiming at respecting their proximity space. However, these approaches are effective only when the human lies in the close vicinity of the robot. Predictive methods, on the other hand, aim at foreseeing how humans will move in the environment and plan a navigational behavior based on this anticipated motion. Though, these methods usually fail to produce socially acceptable robot motion as they do not account for proximity constraints. This thesis is concerned with the implementation of a Human-Aware navigation framework that incorporates the proximity space around a human as well as human intention, as layers of a layered 2D costmap architecture, used for navigation. The proximity space is modeled as a Gaussian cost function around the person. Human intention is defined by the probability that a person will move to a specific destination within the environment and is used as a means of human motion prediction model. In order to infer the path that the human will follow to reach the destination, a simplistic path planner is implemented. Then the intention cost model is assigned along this expected path. The proposed framework is benchmarked against two current state-of-the-art navigation methods. The contestants are: the navigation method used in the ubiquitous Robot Operating System (ROS) and a social navigation method that accounts only for the proximity space around humans. The goal of the thesis is to show that the incorporation of human intention in the robot path planning process is able to produce friendlier motion and increase human comfort. Simulated experiments have been conducted and metrics have been defined to evaluate the methods in terms of human comfort and navigation performance. Results demonstrate that the proposed navigation framework outperformed the other two methods, proving to be able to produce friendlier robot motion while exhibiting similar navigation performance.
Densely Residual Network with Dual Attention for Hyperspectral Reconstruction from RGB Images

In the last several years, deep learning has been introduced to recover a hyperspectral image (HSI) from a single RGB image and demonstrated good performance. In particular, attention mechanisms have further strengthened discriminative features, but most of them are learned by convolutions with limited receptive fields or require much computational cost, which hinders the function of attention modules. Furthermore, the performance of these deep learning methods is hampered by tackling multi-level features equally. To this end, in this paper, based on multiple lightweight densely residual modules, we propose a densely residual network with dual attention (DRN-DA), which utilizes advanced attention and adaptive fusion strategy for more efficient feature correlation learning and more powerful feature extraction. Specifically, an SE layer is applied to learn channel-wise dependencies, and dual downsampling spatial attention (DDSA) is developed to capture long-range spatial contextual information. All the intermediate-layer feature maps are adaptively fused. Experimental results on four data sets from the NTIRE 2018 and NTIRE 2020 Spectral Reconstruction Challenges demonstrate the superiority of the proposed DRN-DA over state-of-the-art methods (at least −6.19% and −1.43% on NTIRE 2018 “Clean” and “Real World” track, −6.85% and −5.30% on NTIRE 2020 “Clean” and “Real World” track) in terms of mean relative absolute error.