Miracle-dz/UniFAR-FTUs huggingface dataset:
The Small GTPase FgRab1 Plays Indispensable Roles in the Vegetative Growth, Vesicle Fusion, Autophagy and Pathogenicity of Fusarium graminearum

Rab GTPases are key regulators of membrane and intracellular vesicle transports. However, the biological functions of FgRab1 are still unclear in the devastating wheat pathogen Fusarium graminearum. In this study, we generated constitutively active (CA) and dominant-negative (DN) forms of FgRAB1 from the wild-type PH-1 background for functional analyses. Phenotypic analyses of these mutants showed that FgRab1 is important for vegetative growth, cell wall integrity and hyphal branching. Compared to the PH-1 strain, the number of spores produced by the Fgrab1DN strain was significantly reduced, with obviously abnormal conidial morphology. The number of septa in the conidia of the Fgrab1DN mutant was fewer than that observed in the PH-1 conidia. Fgrab1DN was dramatically reduced in its ability to cause Fusarium head blight symptoms on wheat heads. GFP-FgRab1 was observed to partly localize to the Golgi apparatus, endoplasmic reticulum and Spitzenkörper. Furthermore, we found that FgRab1 inactivation blocks not only the transport of the v-SNARE protein FgSnc1 from the Golgi to the plasma membrane but also the fusion of endocytic vesicles with their target membranes and general autophagy. In summary, our results indicate that FgRab1 plays vital roles in vegetative growth, conidiogenesis, pathogenicity, autophagy, vesicle fusion and trafficking in F. graminearum.
Implantação das Normas Internacionais de Auditoria pelos Tribunais de Contas Brasileiros

O presente estudo objetivou analisar o processo de implantação das normas internacionais de auditoria pelos Tribunais de Contas (TCs) brasileiros, por meio de pesquisa exploratória e de levantamento, utilizando dois questionários com perguntas abertas e fechadas, que foram enviados a todos os TCs e às instituições que apoiam suas atividades. Os resultados da pesquisa demonstraram diferentes movimentos realizados pelos TCs na adesão às normas, em linha com pesquisas prévias sobre as práticas das Cortes de Contas brasileiras e das Entidades Fiscalizadoras Superiores internacionais. Dos 20 TCs respondentes (61% do total), 60% iniciaram o processo de implantação das normas, mas somente 10% concluíram-no. As normas internacionais de auditoria cuja implantação está mais avançada são as NBASP 20 e 30, que emanam os princípios da transparência e accountability com a gestão da ética pelos TCs. Os achados quanto à vasta disponibilidade de capacitação sobre o tema, ao apoio fornecido pelas organizações e à ausência de necessidade de utilização de recursos financeiros para a implantação pelos órgãos que concluíram o processo trazem dúvidas a respeito das motivações dos TCs que não iniciaram o processo. Embora os esforços verificados no sentido de qualificar a atuação dos TCs, parece haver um longo caminho para a conclusão da implantação no país, devido à falta de previsão pela maioria dos respondentes.
KLASIFIKASI CUACA PROVINSI DKI JAKARTA MENGGUNAKAN ALGORITMA RANDOM FOREST DENGAN TEKNIK OVERSAMPLING

Nowadays Indonesia experiences extreme weather changes that cause many disasters such as floods, fires, landslides and storms. The type of weather depends on many factors such as temperature, humidity, wind direction and others. Some human activities depend on changes in weather such as in the agricultural sector, plantations, aviation, highlands and beaches. Weather prediction is important to understand extreme weather changes based on weather factors. This research adopts ensemble learning which is able to perform weather classification. The algorithm used is Random Forest combined with oversampling technique to handle the uneven amount of data from each weather class. Some of the weather categories classified are Sunny, Sunny Cloudy, Cloudy, Heavy Cloudy, Local Rain, Light Rain, Moderate Rain and Thunderstorms. The experimental results show that the Random Forest model achieves accuracy of 70%. The oversampling technique used is the Synthetic Minority Over-sampling Technique (SMOTE) method. With the combination of SMOTE the predictions of each minority class can be increased by average of 50%.
Suppression algorithm of phase noises in OFDM system based on interpolation combined with MMSE equalization

Aiming at the orthogonal frequency division multiplexing(OFDM) system is sensitive to the phase noise,a suppression algorithm of phase noises in OFDM system based on interpolation combined with MMSE equalization is introduced.Before IFFT in the transmitter,interpolating the zero subcarriers into the symbol may reduce the inter carrier interference(ICI) effectively and improve the signal-to-interference(SIR) ratio.By using the MMSE equalization method,the common phase error(CPE) of the OFDM system caused by the phase noise can be eliminated.The simulation results show that the algorithm can eliminate the rotation of the constellation caused by CPE and suppress the cloud of divergence of the constellation caused by ICI.The phase noise of the OFDM system can be suppressed effectively over Gauss channel and multipath channel,so the proposed algorithm has low complexity and is good in practice.
Motivation to Reduce Drinking and Engagement in Alcohol Misuse Treatment in Alcohol-Related Liver Disease: A National Health Survey

INTRODUCTION: The study aim was to identify predictors of motivation to reduce alcohol consumption and whether motivation predicts engagement in alcohol misuse treatment in alcohol-related liver disease (ALD). METHODS: Data from health surveys and health-care registries were combined. RESULTS: Of 674 patients with ALD, 65% consumed alcohol. Recent hospital admission and severe alcohol problems were associated with motivation to reduce alcohol consumption. Two-year probability for engagement in misuse treatment was 29% for patients with motivation to reduce alcohol consumption versus 6.5% for patients without motivation. DISCUSSION: ALD patients with recent hospital admission were more motivated to cut down alcohol consumption, and motivation predicted engagement in alcohol misuse treatment. This insight can help us target brief interventions.
3-Hydroxyphenylacetic Acid: A Blood Pressure-Reducing Flavonoid Metabolite

Regular intake of polyphenol-rich food has been associated with a wide variety of beneficial health effects, including the prevention of cardiovascular diseases. However, the parent flavonoids have mostly low bioavailability and, hence, their metabolites have been hypothesized to be bioactive. One of these metabolites, 3-hydroxyphenylacetic acid (3-HPAA), formed by the gut microbiota, was previously reported to exert vasorelaxant effects ex vivo. The aim of this study was to shed more light on this effect in vivo, and to elucidate the mechanism of action. 3-HPAA gave rise to a dose-dependent decrease in arterial blood pressure when administered i.v. both as a bolus and infusion to spontaneously hypertensive rats. In contrast, no significant changes in heart rate were observed. In ex vivo experiments, where porcine hearts from a slaughterhouse were used to decrease the need for laboratory animals, 3-HPAA relaxed precontracted porcine coronary artery segments via a mechanism partially dependent on endothelium integrity. This relaxation was significantly impaired after endothelial nitric oxide synthase inhibition. In contrast, the blockade of SKCa or IKCa channels, or muscarinic receptors, did not affect 3-HPAA relaxation. Similarly, no effects of 3-HPAA on cyclooxygenase nor L-type calcium channels were observed. Thus, 3-HPAA decreases blood pressure in vivo via vessel relaxation, and this mechanism might be based on the release of nitric oxide by the endothelial layer.
Immunoglobulin G4-related Disease: A New Systemic Disease Emerging in Japan

Immunoglobulin G4-related disease (IgG4-RD) is a fibro-inflammatory disease characterized by organ enlargement and elevated serum IgG4 levels. In 2003, IgG4-RD was proposed as a distinct form of IgG4-related systemic disease based on a histopathological study involving patients with autoimmune pancreatitis. IgG4-RD occurs mainly in older men and can affect almost any organ simultaneously or metachronously. Pathophysiologically, IgG4-RD occurs when an autoantigen triggers an immune response characterized by Th2 predominance with increased production of cytokines, such as interleukin 4 (IL-4), IL-5, IL-10, IL-13, and tumor growth factor-β (TGF-β), in the affected organ. IL-10 and TGF-β produced by the increased number of regulatory T cells induce a switch from B cells to IgG4-producing plasma cells and fibrosis, respectively. The characteristic histological features consist of dense infiltration of lymphocytes and IgG4-positive plasma cells, storiform fibrosis, and obliterative phlebitis. IgG4-RD is diagnosed based on a combination of clinical, serological, radiological, and histopathological findings. Differentiating IgG4-RD from malignant tumors or similar inflammatory diseases in the affected organs is important. The 2019 America College of Rheumatology/European League against Rheumatism classification criteria for IgG4-RD have high diagnostic sensitivity and specificity. IgG4-RD generally responds well to treatment with steroids, and a swift response is reassuring and provides further diagnostic confirmation. However, relapses are common during tapering or after cessation of steroids. In Japan, low-dose steroid maintenance therapy is usually given to prevent a relapse. B-cell depletion with rituximab is effective in patients resistant to or dependent on steroids. Most patients with IgG4-RD who receive steroid therapy show good short-term clinical, morphological, and functional outcomes. However, long-term outcomes, such as relapse, fibrosis development, and associated malignancies, have not been clearly defined. Therefore, novel treatment strategies, including rituximab, need to be tested in international randomized controlled clinical trials.
Freeze-Dried Curdlan/Whey Protein Isolate-Based Biomaterial as Promising Scaffold for Matrix-Associated Autologous Chondrocyte Transplantation—A Pilot In-Vitro Study

The purpose of this pilot study was to establish whether a novel freeze-dried curdlan/whey protein isolate-based biomaterial may be taken into consideration as a potential scaffold for matrix-associated autologous chondrocyte transplantation. For this reason, this biomaterial was initially characterized by the visualization of its micro- and macrostructures as well as evaluation of its mechanical stability, and its ability to undergo enzymatic degradation in vitro. Subsequently, the cytocompatibility of the biomaterial towards human chondrocytes (isolated from an orthopaedic patient) was assessed. It was demonstrated that the novel freeze-dried curdlan/whey protein isolate-based biomaterial possessed a porous structure and a Young’s modulus close to those of the superficial and middle zones of cartilage. It also exhibited controllable degradability in collagenase II solution over nine weeks. Most importantly, this biomaterial supported the viability and proliferation of human chondrocytes, which maintained their characteristic phenotype. Moreover, quantitative reverse transcription PCR analysis and confocal microscope observations revealed that the biomaterial may protect chondrocytes from dedifferentiation towards fibroblast-like cells during 12-day culture. Thus, in conclusion, this pilot study demonstrated that novel freeze-dried curdlan/whey protein isolate-based biomaterial may be considered as a potential scaffold for matrix-associated autologous chondrocyte transplantation.
CONGRUENCE BETWEEN NON TECHNICAL MARKET REQUIRED COMPETENCES AND COMPETENCES MET BY NEW ENGINEERING PROGRAMMES. THE CASE OF SPAIN

The extent of competency gaps in engineering graduates that has been perceived by business and industry has been analyse d by various authors in North America and Europe. Several non technical competences have been pointed out such as: listening skills, sharing information and cooperating with co-workers, adapting to changing work environments, customer orientation and focus, ethical decision ma king and behaviour, etc. Other authors have addressed the need of emphasizing the preparation o engineering graduates for globalization in a context of an open economy or the communication needs of engineering graduates. On the graduates side, it has been pointed out how income results show that jobs with higher participative and methodological competency requirements are better paid and that higher requirements in terms of competencies increase grad uates' job satisfaction In this context, this paper analyses the gap between addressed competences by the new European Space engineering curricula set out in Spain and the perception of in dustry leaders of the real situation based on a survey carried out in the region of Valencia on 150 industry representatives during 2010.
VisuoTactile 6D Pose Estimation of an In-Hand Object using Vision and Tactile Sensor Data

Knowledge of the 6D pose of an object can benefit in-hand object manipulation. Existing 6D pose estimation methods use vision data. In-hand 6D object pose estimation is challenging because of heavy occlusion produced by the robots grippers, which can have an adverse effect on methods that rely on vision data only. Many robots are equipped with tactile sensors at their fingertips that could be used to complement vision data. In this paper, we present a method that uses both tactile and vision data to estimate the pose of an object grasped in a robots hand. The main challenges of this research include 1) lack of standard representation for tactile sensor data, 2) fusion of sensor data from heterogeneous sourcesvision and tactile, and 3) a need for large training datasets. To address these challenges, first, we propose use of point clouds to represent object surfaces that are in contact with the tactile sensor. Second, we present a network architecture based on pixel-wise dense fusion to fuse vision and tactile data to estimate the 6D pose of an object. Third, we extend NVIDIAs Deep Learning Dataset Synthesizer to produce synthetic photo-realistic vision data and the corresponding tactile point clouds for 11 objects from the YCB Object and Model Set in Unreal Engine 4. We present results of simulated experiments suggesting that using tactile data in addition to vision data improves the 6D pose estimate of an in-hand object. We also present qualitative results of experiments in which we deploy our network on real physical robots showing successful transfer of a network trained on synthetic data to a real system.
Lithocholic Acid Amides as Potent Vitamin D Receptor Agonists

1α,25-Dihydroxyvitamin D3 [1α,25(OH)2D3, 1] is an active form of vitamin D3 and regulates various biological phenomena, including calcium and phosphate homeostasis, bone metabolism, and immune response via binding to and activation of vitamin D receptor (VDR). Lithocholic acid (LCA, 2) was identified as a second endogenous agonist of VDR, though its potency is very low. However, the lithocholic acid derivative 3 (Dcha-20) is a more potent agonist than 1α,25(OH)2D3, (1), and its carboxyl group has similar interactions to the 1,3-dihydroxyl groups of 1 with amino acid residues in the VDR ligand-binding pocket. Here, we designed and synthesized amide derivatives of 3 in order to clarify the role of the carboxyl group. The synthesized amide derivatives showed HL-60 cell differentiation-inducing activity with potency that depended upon the substituent on the amide nitrogen atom. Among them, the N-cyanoamide 6 is more active than either 1 or 3.
Technological Challenges for Large-Size AMOLED Display

In this work,we review the current technological challenges for large-size AMOLED displays with an emphasis on the backplane technology. Then,it will be discussed how the new technology of oxide TFTs combines the advantages of LTPS and a-Si TFTs to make an optimal solution for large-size backplanes. In particular,we reveal the technological challenges in oxide TFTs by comparing the device characteristics of conventional excimer laser annealing(ELA) LTPS and amorphous indium-gallium-zinc-oxide(a-IGZO) TFTs. Finally,we demonstrate a 12.1" WXGA AMOLED prototype display fabricated by an a-IGZO TFT backplane.
Airport Runway Foreign Object Debris Detection System Based on Arc-Scanning SAR Technology

Due to the small size of foreign object debris (FOD) and varied complex weather conditions, the detection of FOD on airport runways is a great challenge. Radar is an important method for detecting FOD targets. However, almost all the existing systems are based on real apertures, which have disadvantages such as low azimuth resolution and susceptibility to rain interference. Here, an innovative FOD detection radar system based on arc-scanning synthetic aperture radar (AS-SAR) technology, the AS-SAR based FOD detection system (AS-FODR), achieves omnidirectional coverage with a very high azimuth resolution and the suppression of flicker clutter, such as rain drops in severe weather. According to the radar imaging simulation of a scene under rainy conditions and the information processing analysis of field experiments, a prototype system was built, and an efficient data process flow was proposed. In short, a one centimeter FOD target was detected on the runway more than 250 m away, proving that the use of AS-FODR is feasible and effective.
Decentralized Coordination and Stabilization of Hybrid Energy Storage Systems in DC Microgrids

Hybrid energy storage system (HESS) is an attractive solution to compensate power balance issues caused by intermittent renewable generations and pulsed power load in DC microgrids. The purpose of HESS is to ensure optimal usage of heterogeneous storage systems with different characteristics. In this context, power allocation for different energy storage units is a major concern. At the same time, the wide integration of power electronic converters in DC microgrids would possibly cause the constant power load instability issue. This paper proposes a composite model predictive control based decentralized dynamic power sharing strategy for HESS. First, a composite model predictive controller (MPC) is proposed for a system with a single ESS and constant power loads (CPLs). It consists of a baseline MPC for optimized transient performance and a sliding mode observer to estimate system disturbances. Then, a coordinated scheme is developed for HESS by using the proposed composite MPC with a virtual resistance droop controller for the battery system and with a virtual capacitance droop controller for the supercapacitor (SC) system. With the proposed scheme, the battery only supplies smooth power at steady state, while the SC compensates all the fast fluctuations. The proposed scheme achieves a decentralized dynamic power sharing and optimized transient performance under large variation of sources and loads. The proposed approach is verified by simulations and experiments.
Deep Learning and Earth Observation to Support the Sustainable Development Goals: Current approaches, open challenges, and future opportunities

The synergistic combination of deep learning (DL) models and Earth observation (EO) promises significant advances to support the Sustainable Development Goals (SDGs). New developments and a plethora of applications are already changing the way humanity will face the challenges of our planet. This article reviews current DL approaches for EO data, along with their applications toward monitoring and achieving the SDGs most impacted by the rapid development of DL in EO. We systematically review case studies to achieve zero hunger, create sustainable cities, deliver tenure security, mitigate and adapt to climate change, and preserve biodiversity. Important societal, economic, and environmental implications are covered. Exciting times are coming when algorithms and Earth data can help in our endeavor to address the climate crisis and support more sustainable development.
Determinants of Demand Response Program Participation: Contingent Valuation Evidence from a Smart Thermostat Program

As renewable electricity generation continues to increase in the United States (US), considerable effort goes into matching heterogeneous supply to demand at a subhour time-step. As a result, some electric providers offer incentive-based programs for residential consumers that aim to reduce electric demand during high-demand periods. There is little research into determinants of consumer response to incentive-based programs beyond typical sociodemographic characteristics. To add to this body of literature, this paper presents the findings of a dichotomous choice contingent valuation (CV) survey targeting US ratepayers’ participation in a direct-load-control scheme utilizing a smart thermostat designed to reallocate consumer electricity demand on summer days when grid stress is high. Our results show approximately 50% of respondents are willing to participate at a median willingness-to-accept (WTA) figure of USD 9.50 (95% CI: 3.74, 15.25) per month that lasts for one summer (June through August)—or slightly less than USD 30 per annum. Participation is significantly affected by a respondent’s attitudes and preferences surrounding various environmental and institutional perspectives, but not by sociodemographic characteristics. These findings suggest utilities designing direct-load-control programs may improve participation by designing incentives specific to customers’ attitudes and preferences.
Taxonomy and Benchmarking of Precision-Scalable MAC Arrays Under Enhanced DNN Dataflow Representation

Reduced-precision and variable-precision multiply-accumulate (MAC) operations provide opportunities to significantly improve energy efficiency and throughput of DNN accelerators with no/limited algorithmic performance loss, paving a way towards deploying AI applications on resource-constraint edge devices. Accordingly, various precision-scalable MAC array (PSMA) architectures were proposed recently. However, it is difficult to make a fair comparison between those alternatives, as each proposed PSMA is demonstrated in different systems and technologies. This work aims to provide a clear view of the design space of PSMA and offer insights for selecting the optimal architectures based on designers’ needs. First, we introduce a precision-enhanced for-loop representation for DNN dataflows. Next, we use this new representation towards a comprehensive PSMA taxonomy, capable of systematically covering most prominent state-of-the-art PSMAs, as well as uncovering new PSMA architectures. Following that, we build a highly parameterized PSMA template that can be design-time configured into a huge subset of the design space spanned by the taxonomy. This allows to fairly and thoroughly benchmark 72 different PSMA architectures. We perform such studies in 28nm technology targeting run-time precision scalability from 8 to 2 bits, operating at 200 MHz and 1 GHz. Analyzing resulting energy and area breakdowns reveals key design guidelines for PSMA architectures.