Miracle-dz/UniFAR-FTUs huggingface dataset:
Learn2Sign : sign language recognition and translation using human keypoint estimation and transformer model

Sign language recognition and translation has been an active research field in the recent years with most approaches using deep neural networks to extract information from sign language data. This work investigates the mostly disregarded approach of using human keypoint estimation from image and video data with OpenPose in combination with transformer network architecture. Firstly, it was shown that it is possible to recognize individual signs (4.5% word error rate (WER)). Continuous sign language recognition though was more error prone (77.3% WER) and sign language translation was not possible using the proposed methods, which might be due to low accuracy scores of human keypoint estimation by OpenPose and accompanying loss of information or insufficient capacities of the used transformer model. Results may improve with the use of datasets containing higher repetition rates of individual signs or focusing more precisely on keypoint extraction of hands.
Efficacy and safety of chloroquine and hydroxychloroquine for COVID-19: A comprehensive evidence synthesis of clinical, animal, and in vitro studies

Background: The world is facing a pandemic of COVID-19, a respiratory disease caused by a novel coronavirus which is now called SARS-CoV-2. Current treatment recommendations for the infection are mainly repurposed drugs based on experience with other clinically similar conditions and are not backed by direct evidence. Chloroquine (CQ) and its derivative Hydroxychloroquine (HCQ) are among the candidates. We aimed to synthesize current evidence systematically for in vitro, animal, and human studies on the efficacy and safety of chloroquine in patients with COVID-19. Methods: The Cochrane Library, Google Scholar, PubMed (via Medline), Embase, Scopus, and Web of Science, MedRxiv, clinical trial registries including clinicaltrials.gov, ChiCTR (Chinese Clinical Trial Registry), IRCT (Iranian Registry of Clinical Trials), and the EU Clinical Trials Register. We used the Cochrane tool for risk of bias assessment in randomized studies, the ROBINS tool for non-randomized studies, and the GRADE methodology to summarize the evidence and certainty in effect estimates. Results: The initial database searching retrieved 24,752 studies. Of these, 15,435 abstracts were screened and 115 were selected for full-text review. Finally, 20 human studies, 3 animal studies, and 4 in vitro studies were included in this systematic review. The risk of bias within studies was unclear to high and the overall certainty in evidence-based on GRADES- was very low. HCQ may be effective in clinical improvement in a subset of patients with COVID-19. However, the frequency of adverse events was higher in patients taking HCQ compared to standard of care alone. In contrast, animal studies, did not report any adverse effects. Furthermore, clear benefit of the drug in the survival of the animals has been reported. Most in vitro studies indicated a high selectivity index for the drug and one study that used a human coronavirus reported blockage of virus replication. Conclusion: Current evidence background is limited to six poorly conducted clinical studies with inconsistent findings which fail to show significant efficacy for HCQ. Safety data is also limited but the drug may increase adverse outcomes. Routine use of the drug is not recommended based on limited efficacy and concerns about the drug safety especially in high-risk populations.
Development and Validation of a 5-Gene Autophagy-Based Prognostic Index in Endometrial Carcinoma

Background Endometrial carcinoma (EC) is the most common gynecological malignancy worldwide, and 15–20% of patients with EC have a rapid relapse within 3 years. This study aims to develop an autophagy-related genes (ARGs) signature to predict the prognosis of EC. Material/Methods In our study, differentially expressed ARGs were identified by “edgeR” package in R and pathway enrichment analysis was performed to explore biological functions. Univariate and multivariate Cox regression analyses were employed to build autophagy signature. Gene set enrichment analysis (GSEA), Kaplan-Meier curve analysis, and ROC curve analysis were conducted to compare the differences between the high- and low-risk groups. Results A total of 60 differentially expressed ARGs (DEARGs) including 34 upregulated and 26 downregulated DEARGs were identified from the TCGAUCEC dataset, with the adjusted P<0.05 and |Fold Change| >1.5. By using univariate and multivariate Cox regression analyses, ERBB2, PRKAB2, GRID2, NRG3, CDKN2A were identified to construct a prognostic signature with AUC 0.673, 0.719, and 0.791, at 1-, 3- and 5-years, respectively. Patients with EC were divided into low- or high-risk group by median risk score, and GSEA showed that low-risk group was enriched in adjacent cells communication pathways while high-risk group was involved in metabolism and immune pathways. The nomograms could also help to guide personal prognostic prediction and therapeutic strategies in EC. Conclusions Our study not only determine 5 ARGs signature that could predict the prognosis of EC but also provide novel insights into the underlying mechanisms of autophagy.
Crystal Structure of Nonstoichiometric Copper-Substituted La(Ni1−zCuz)x Compounds Studied by Neutron and Synchrotron Anomalous Powder Diffraction

The structural properties of the potential battery electrode materials LaNi[sub 4]Cu, LaNi[sub 4.4]Cu, LaNi[sub 5]Cu, and LaNi[sub 4.5]Cu[sub 1.5] have been investigated by neutron and anomalous synchrotron powder diffraction. The nonstoichiometry of such AB[sub x] (5 [le] x [le] 6) compounds has been described in a structure derived from the hexagonal CaCu[sub 5]-type structure by replacement of the A atoms by dumbbells of B atoms. In these copper-substituted compounds, Cu can occupy any of the four available nickel sites. From a joint refinement procedure using both neutron and synchrotron data, the copper-to-nickel ratio at each B site has been determined. This shows that substitution is not random and that copper occupies some crystallographic sites preferentially. The results are discussed and compared to other substituted AB[sub 5] systems.
Exploring the molecular mechanisms of pneumonia induced by Streptococcus pneumoniae infected lung epithelial cells through comprehensive network analysis

Background: Pneumonia is one of the common hazards in the respiratory intensive care unit, which often leads to systemic inflammatory response syndrome (SIRS). At present, alveolar epithelial cells are seen as the target cells of pulmonary inflammation, which can regulate the development and prognosis of inflammation. The aim of this study was to elucidate the epithelial specific response during pulmonary infection. Methods: We collected DNA data of three independent mice from the GEO database. They are the epithelial cells of mice lived with Streptococcus pneumoniae, the epithelial cells of mice not infected with Streptococcus pneumoniae and the non-epithelial cells of mice infected with Streptococcus pneumoniae. Through co-expression module analysis, enrichment analysis, and the hypergeometric test, we can predict the ncRNA and transcription factors that regulate the module. Eight functional modules were obtained for co-expression analysis of potential pathogenic genes. Results: Aqp5, Mak6 and other genes were significantly differentially expressed and had an active regulatory role in the dysfunction module, so they were identified as the key genes for the occurrence and development of pneumonia. Next, we found that ncRNA pivot and transcription factors (TFs) pivot (including microRNA-181a-5p, Stat3, Sp3, etc.) significantly regulate dysfunction modules. Therefore, we identified these potential regulators as dysfunctional molecules in the development of pneumonia. In this study, the GEO data of three groups of mice were tested to help reveal the core dysfunction module and potential regulatory factors of pneumonia. Conclusion: The results of the analysis elucidated the potential role of Streptococcus pneumonia infecting epithelial cells in causing pneumonia, improved our understanding of its pathogenesis, and provided a new reference for the further treatment of pneumonia.
Risk-Taking, Capital Allocation and Optimal Monetary Policy

We study the role of firm heterogeneity in affecting business cycle dynamics and optimal stabilization policy. Firms differ in their degree of cyclicality, and hence, exposure to aggregate risk, leading to firm-specific risk premia that influence resource allocations. The heterogeneous firm economy can be recast in a representative firm formulation, but where total factor productivity (TFP) is endogenous and depends on the resource allocation. The model uncovers a novel tradeoff between the long-run level and volatility of TFP. Inefficiencies distort this tradeoff and result in either excessive volatility or depressed output, implying a role for corrective policy. Embedding this mechanism into a workhorse New Keynesian model, we show that allocational considerations can strengthen the incentives for leaning against the wind, i.e., optimal policy is more strongly countercyclical than in an observationally equivalent economy that abstracts from heterogeneity. A quantitative exercise suggests that the losses from ignoring heterogeneity can be substantial, which stem largely from a less productive allocation of resources and so depressed TFP and output.
Growth of tomato seedlings under different HCO‐ 3 concentration in the medium

Abstract An increase in the concentration of HCO‐ 3 ions in liquid media surrounding the root system significantly affected the biomass production of tomato seedlings in early stages of growth. This effect depended upon HCO‐ 3 concentration. The cultivation of seedlings during a period of 24 days (from 21–45 days after sowing) on a medium enriched to 5.68 mM HCO3 (0.025% CO2 after the computed dissociation) increased the production of dry matter (DW) plant"1 to about 179% as compared with the respective control. Various tomato organs showed different values of DW increase, the greatest one being noted in leaf blades. This result was correlated with an increase in leaf blade area to about 176% in relation to the control. With an increase in the concentration to 22.72 mM HCO‐ 3 (0.1% CO2 after the computed dissociation) a general tendency of changes was maintained, however, the absolute values of growth were diminished. In media of an enriched HCO3 content the length of shoots, and roots, was not significan.
Cephalexin-mediated synthesis of quasi-spherical and anisotropic gold nanoparticles and their in situ capping by the antibiotic

Here we report, for the first time, synthesis of gold nanostructures in aqueous medium by reducing gold ions using cephalexin, a potent broad-spectrum antibiotic, where the morphology of the gold nanoparticles is found to be dependent on the concentration of chloroauric acid. The characterization techniques indicate that particle surfaces are coated with the robust layer of the antibiotic making them stable for a long time. Thus, cephalexin acts as both the reducing and the capping agent. NMR and XPS analysis indicate that the sulfur moiety is responsible for the reduction and binding process.
Interpolation Cryptanalysis of Unbalanced Feistel Networks with Low Degree Round Functions

Arithmetisierungs-Orientierte Symmetrische Primitive (AOSPs) sprechen das bestehende Optimierungspotential bei der Auswertung von Blockchiffren und Hashfunktionen als Bestandteil von sicherer Mehrparteienberechnung, voll-homomorpher Verschlusselung und Zero-Knowledge-Beweisen an. Die Konstruktionsweise von AOSPs unterscheidet sich von traditionellen Primitiven durch die Verwendung von algebraisch simplen Elementen. Zusatzlich sind viele Entwurfe uber Primkorpern statt uber Bits definiert. Aufgrund der Neuheit der Vorschlage sind eingehendes Verstandnis und ausgiebige Analyse erforderlich um ihre Sicherheit zu etablieren. Algebraische Analysetechniken wie zum Beispiel Interpolationsangriffe sind die erfolgreichsten Angriffsvektoren gegen AOSPs. In dieser Arbeit generalisieren wir eine existierende Analyse, die einen Interpolationsangriff mit geringer Speicherkomplexitat verwendet, um das Entwurfsmuster der neuen Chiffre GMiMC und ihrer zugehorigen Hashfunktion GMiMCHash zu untersuchen. Wir stellen eine neue Methode zur Berechnung des Schlussels basierend auf Nullstellen eines Polynoms vor, demonstrieren Verbesserungen fur die Komplexitat des Angriffs durch Kombinierung mehrere Ausgaben, und wenden manche der entwickelten Techniken in einem algebraischen Korrigierender-Letzter-Block Angriff der Schwamm-Konstruktion an. Wir beantworten die offene Frage einer fruheren Arbeit, ob die verwendete Art von Interpolationsangriffen generalisierbar ist, positiv. Wir nennen konkrete empfohlene untere Schranken fur Parameter in den betrachteten Szenarien. Auserdem kommen wir zu dem Schluss dass GMiMC und GMiMCHash gegen die in dieser Arbeit betrachteten Interpolationsangriffe sicher sind. Weitere kryptanalytische Anstrengungen sind erforderlich um die Sicherheitsgarantien von AOSPs zu festigen.
Organic TFT array on a paper substrate

We demonstrate a high-performance organic thin-film transistor array fabricated on a flexible paper substrate. As a water and chemical barrier layer, 6-/spl mu/m-thick parylene has been coated on the paper substrate by using the vacuum deposition. The parylene layer protects the paper substrate from becoming damp during the wet chemical process. Using poly (3-hexylthiophene) as an active layer, a high-performance organic transistor with field effect mobility up to 0.086 cm/sup 2//V/spl middot/s and an on/off ratio of 10/sup 4/ can be achieved. Organic transistors built on a cheap paper substrate open a channel for future applications in flexible and disposable electronics with extremely low-cost.
Experimental And Theoretical Thermodynamic Studies Of Charging And Adsorption At The Solid-Aqueous Interface Of Aluminum-Bearing Ferrihydrites And Rutile

In this thesis, three techniques are integrated to investigate how best to capture and parameterize complexity in interfacial reactions at mineral-aqueous interfaces. The first chapter employs a novel approach that leans on spectroscopic and computational data to build a Surface Complexation Model for aluminum-doped ferrihydrites. The model places Al on the surface in Fe1 sites and was found to fit empirical zeta potential measurements reasonably well. In chapter two, Flow Adsorption Microcalorimetry and Density Functional Theory calculations were each used to derive the enthalpies of phosphate, oxalate, and chromate sorption on the (110) face of rutile. The difficulty in determining the masses adsorbed in the experiment, and the complexity of electron interactions in our computational calculations, did not allow for a reconciliation of adsorption enthalpies. Although we successfully captured the complexity associated with substitution, we were unable to rationalize differences in deriving thermodynamics parameters. INDEX WORDS: Flow calorimetry, MUSIC model, Computational modeling, enthalpies, SCM EXPERIMENTAL AND THEORETICAL THERMODYNAMIC STUDIES OF CHARGING AND ADSORPTION AT THE SOLID-AQUEOUS INTERFACE OF ALUMINUM-BEARING FERRIHYDRITES AND RUTILE
Fog and Cloud Computing Optimization in Mobile IoT Environments

—With the surge of ubiquitous demand on high-complexity and quality of mobile IoT services, new computing paradigms have emerged. Motivated by the long and unpredictable end-to-end communication latency experienced in cloud computing as well as the rapid growth of mobile trafﬁc, fog computing emerges as the most comprehensive and natural paradigm to support real-time applications and to get more efﬁcient with the data sent to the cloud. From the performed analysis, the lack of research in dynamic environments regarding both the client and fog nodes is noticeable. Moreover, most of the existing proposed schemes only consider few speciﬁc objectives for the system optimization as well as static computing resources. In the present work, a novel fog computing architecture has been designed and evaluated with the purpose of ﬁnding a solution to the aforementioned issues. A novel optimization problem formulation is also proposed in order to match the characteristics of the proposed architecture. A set of optimization algorithms were developed to solve the formulated problem. Moreover, the proposed architecture has been successfully implemented in a suitable developed simulation toolkit. The performance of the optimization algorithms was assessed in different static and mobile scenarios using the QoS offered to the clients and the system provider objectives as the main metrics. It is observed that the proposed architecture effectively helps to improve the offered QoS to its users in mobile and static environments while meeting the system provider objectives.
AUTO3D: Novel view synthesis through unsupervisely

Let Cs,k,c denote a convolutional layer with a stride s, kernel size k, and an output channel c. Then, the discriminator architecture can be expressed as C2,4,32 → C2,4,64 → C2,4,128 → C2,4,256 → C1,1,3. Note that we use a local discriminator similar to that of [1]. We use a Leaky ReLU activation function with slope of 0.2 on every layer, except for the last layer. Normalization layer is not applied. This architecture is shared across all experiments.
Determination of third-order nonlinear optical properties of ABI derivatives

In this paper we studied linear and nonlinear optical properties of novel organic materials MeSBI and MeOBI in form of solution with chloroform as solvent. For experimental measurements we implemented Z-scan method as it is one of the most widely used methods for nonlinear optical studies and can simultaneously measure two-photon absorption and Kerr effects. 1064 nm Nd:YAG laser with 30 ps pulse duration and 10 Hz repetition rate was used to avoid any thermal contribution to changes of optical properties and correctly evaluate magnitude of thirdorder nonlinear optical effects. Using acquired values we also calculated third-order susceptibility and second-order hyperpolarizability, as these coefficients are more appropriate for properties comparison on molecular level. Both materials possess insignificant absorption over 500 nm which makes them applicable for all-optical devices in infrared spectrum. Acquired data for MeSBI and MeOBI were compared with data for previously studied ABI derivative DMABI to better understand how different structural configuration influence third-order nonlinear optical properties.
Effect of MnO2 Dopant on Properties of Na+-β/β"-Al2O3 Solid Electrolyte Prepared by a Synthesizing-cum-sintering Process

In order to simplify the complexity of the conventional solid-state reaction process, Na+-β/β″-Al2O3 as a fast Na+-ionic conductive solid electrolyte was fabricated using a synthesizing-cum-sintering process combined with the double-zeta method, which is able to distribute a small amount of Li2O more homogeneously in the Na2O-Al2O3-Li2O system. Additionally, in order to enhance the ionic conductivity, MnO2 was used as a dopant to increase the Na+-ion concentration on the conduction plane in the Na+-β/β″-Al2O3 crystal structure. The relative sintered density increased with the synthesis temperature, ultimately reaching 99.7 % after synthesis at 1400 °C. The phase formation showed an overall β″-phase fraction over 90 %. The addition of MnO2 had a positive effect on the phase formation, but a negative influence on the relative density resulting from the grain growth promotion effect. The highest ionic conductivity was observed at 1.74 × 10-1 S/cm (350 °C) for the sample sintered at 1600 °C with 0.5 wt. % MnO2.
MVP: M ULTIVARIATE POLYNOMIALS FOR CONDITIONAL DATA GENERATION

Conditional Generative Adversarial Nets (cGANs) have been widely adopted for image generation. cGANs take i) a noise vector and ii) a conditional variable as input. The conditional variable can be discrete (e.g., a class label) or continuous (e.g., an input image) resulting into class-conditional (image) generation and imageto-image translation models, respectively. However, depending on whether the conditional variable is discrete or continuous, various cGANs employ substantially different deep architectures and loss functions for their training. In this paper, we propose a novel framework, called MVP, for conditional data generation. MVP resorts to multivariate polynomials of higher-order and treats in a unified way both discrete and continuous conditional variables. MVP is highly expressive, capturing higher-order autoand cross-correlations of input variables (noise vector and conditional variable). Tailored sharing schemes are designed between the polynomial’s parameter tensors, which result in simple recursive formulas. MVP can synthesize realistic images in both class-conditional and image-to-image translation tasks even in the absence of activation functions between the layers.
REVEALING STRATEGIC PROCESS OF COMPLEMENTARY VALUE CREATION FOR SCOPE INCREASE IN PLATFORM ENTREPREUERSHIP

Digital Platform has taken the central stage in platform entrepreneurship. While much has been discussed on the formal definition and pricing mechanism of platform, researchers call for more studies that address mechanisms for platform growth and evolution. In particular, how the platform can increase its scope (boundary) has been under-explored. Attending to this quest, this research explores the evolution history of one platform – Kakao Talk in South Korea. Kakao Talk began as a simple messenger, and over the 10 years of period, the messenger has incorporated more than 20 categorically distinct features as complementary services, and become a major technology platform in South Korea. On this extreme sample, analysis is conducted with the grounded theory buildings with particular emphasis on scope increase. The grounded model explains that 1) cognitive interpretations of platform boundaries fundamentally allow or limit experimentations for scope increase and that 2) design practices become an effective mean to create complementarities between the focal service and other explored features.