Miracle-dz/UniFAR-FTUs huggingface dataset:
ATMConvGRU for Weather Forecasting

Weather forecasting, which is challenging due to the complex atmospheric correlation, focuses on providing explicit meteorological estimations as accurate as possible. Recently, techniques based upon convolutional-recurrent networks have shown dramatic performance in domains including radar echo prediction and precipitation forecasting, indicating that deep learning models have great potential in this area. However, existing methods concentrate on adding extra paralleled memory cells to the inner recurrent unit, where the information is mutually independent. To extract spatial–temporal features with stronger correlation, this letter introduced an axial attention memory module with quasi state-in-state cascaded manner. Benefitting from this unit, the spatial–temporal features can be aggregated and embedded into standard ConvGRU formulating Axial aTtention Memory Cascaded ConvGRU (ATMConvGRU) for sequential weather prediction. Experimental results compared with many state-of-the-art methods on four types of weather forecasting related datasets, including temperature, relative humidity, wind, and radar echo, demonstrate the effectiveness and superiority of the proposed ATMConvGRU.
Modelamiento Hidrológico De La Quebrada San Idelfonso Mediante SIG En Trujillo, La Libertad 2020

– The research focuses on designing a Hydrological Modeling of the San Idelfonso Stream through a Geographic Information System in Trujillo. Where rainfall information was collected on the last fifty years of the occurrence of the phenomenon of the child and its incidence in the districts of Laredo, El Porvenir, Florencia de Mora, Trujillo and Víctor Larco Herrera. Also, the DEM was used with the Arc GIS software, Hec-RAS, Hec-HMS and Civil 3D software were used. The exact location of the San Idelfonso stream was obtained, the collection of thematic maps of different national entities. Also, figures and thematic maps that show rainfall during the last 50 years, being the years 1983, 1998, 2017, where a greater precipitation was observed. After analyzing the rainfall information, vulnerable areas were determined, obtaining an unmanned flight modeling, which shows the distribution of the San Idelfonso creek. Finally, a prevention alternative was proposed for a possible future coming and sliding; thus allowing to handle the situation with the least number of affected in the population. In this way, it was possible to design a hydrological model for the San Idelfonso stream taking GIS into account. Abstract – The research focuses on designing a Hydrological Modeling of the San Idelfonso Stream through a Geographic Information System in Trujillo. Where rainfall information was collected on the last fifty years of the occurrence of the phenomenon of the child and its incidence in the districts of Laredo, El Porvenir, Florencia de Mora, Trujillo and Víctor Larco Herrera. Also, the DEM was used with the Arc GIS software, Hec-RAS, Hec-HMS and Civil 3D software were used. The exact location of the San Idelfonso stream was obtained, the collection of thematic maps of different national entities. Also, figures and thematic maps that show rainfall during the last 50 years, being the years 1983, 1998, 2017, where a greater precipitation was observed. After analyzing the rainfall information, vulnerable areas were determined, obtaining an unmanned flight modeling, which shows the distribution of the San Idelfonso creek. Finally, a prevention alternative was proposed for a possible future coming and sliding; thus allowing to handle the situation with the least number of affected in the population. In this way, it was possible to design a hydrological model for the San Idelfonso stream taking GIS into account.
A Risk Prediction Model of Readmission after coronary artery bypass grafting (CABG) in China

Background At present, there is no risk prediction model suitable for the Chinese population after coronary artery bypass grafting (CABG), this study aims to analyze the risk factors related to readmission after CABG and to construct a risk prediction model of readmission for patients with CABG in China. Methods A total of 1983 patients who had undergone CABG at Wuhan Asian Heart Hospital from 2017 to 2019 were selected to collect general patient information. Univariate analysis was performed on the data of 825 patients in the modeling group to determine potential risk factors, and then independent risk factors of readmission after CABG were determined by multivariate logistic regression. Hosmer-Lemeshow （H-L） test, calibration curve and the area under the receiver operating characteristic （ROC） curve are used to test the calibration and discrimination of the model. Results Six preoperative variables （age≥65, female, Private insurance, diabetes, hypertension level2,3, congenital heart disease）were independent risk factors of readmission after CABG. Our risk prediction model has high application value （the area under the ROC curve of the modeling group is 0.876, and of the validation group is 0.865, H-L test: P=0.561〉0.05）. Conclusion The risk prediction model in our study can be used to predict the risk of readmission in CABG patients in clinical work, providing a basis for more effective perioperative treatment and care to prevent patients from being readmitted to hospital.
Geographic Information System-based Spatial Modelling of Soil-Transmitted Helminth Infections Among Preschool-aged Children in Masbate, Philippines

Objectives. Since the effectiveness of the Zero Open Defecation (ZOD) program as a scaling-up approach in lowering the rates of soil-transmitted helminth (STH) infections has not yet been locally explored, this study aimed to (1) describe the association between environmental determinants and STH cumulative prevalence, and (2) to predict the 2020 STH cumulative prevalence. Methods. A generalized linear regression (GLR) model was used to determine the association of 2014–2015 environmental determinants and observed 2015 STH cumulative prevalence, while a geographically weighted regression (GWR) model was used to produce predicted 2020 STH cumulative prevalence. Results. ArcGIS’ GLR tool with R2 of 63% found that statistically significant environmental determinants include distance near to water bodies, forest land use, access to sanitary toilet, level one water source, and ZOD status, while the ArcGIS’ GWR tool found that barangays, Cabangcalan, Matalangtalang, Talabaan, and Talib in Aroroy hypothetically met the national target below 30% for 2020 STH cumulative prevalence. Conclusion. This study showed that barangays with a moderately low percentage of area with freshwater bodies, a moderately high percentage of households with sanitary toilet and level one water source, and a 100% status of ZOD have lower rates of STH cumulative prevalence in preschool-aged children in the selected municipalities in Masbate.
Density and surface tension of molten cast irons

Computer-aided development of liquid-assisted metallurgical processes requires reliable basic data for the molten materials, including thermophysical properties such as density, surface tension and viscosity. Cast irons belong to the group of Fe-C alloys of practical importance due to their good technological and utility properties, yet experimental thermophysical data of cast irons in the literature are scarce. In this study, the density and surface tension of three compacted graphite cast iron alloys were measured by the sessile drop method in contact heating mode in the temperature range of 1473 - 1723 K with polycrystalline alumina as a substrate. The drop profile images were recorded both during heating and subsequent cooling regimes. At 1473 K, the density values of the studied compacted graphite irons are between 6.66 and 6.69 g? cm-3, whereas surface tension values are between 1130 and 1510 mN? m-1. The density decreases with increasing temperature, while surface tension dependence on temperature is less obvious. The obtained results are compared to the available literature data and analyzed taking into account chemical interaction of liquid cast irons with the substrate material.
A Multi-Feature Learning Model with Enhanced Local Attention for Vehicle Re-Identification

: Vehicle re-identification (ReID) aims to retrieve the target vehicle in an extensive image gallery through its appearances from various views in the cross-camera scenario. It has gradually become a core technology of intelligent transportation system. Most existing vehicle re-identification models adopt the joint learning of global and local features. However, they directly use the extracted global features, resulting in insufficient feature expression. More-over, local features are primarily obtained through advanced annotation and complex attention mechanisms, which require additional costs. To solve this issue, a multi-feature learning model with enhanced local attention for vehicle re-identification (MFELA) is proposed in this paper. The model consists of global and local branches. The global branch utilizes both middle and high-level semantic features of ResNet50 to enhance the global representation capability. In addition, multi-scalepooling operations are used to obtain multi-scale information. While the local branch utilizes the proposed Region Batch Dropblock (RBD), which encourages the model to learn discriminative features for different local regions and simultaneously drops corresponding same areas randomly in a batch during training to enhance the attention to local regions. Then features from both branches are combined to provide a more comprehensive and distinctive feature representation. Extensive experiments on VeRi-776 and VehicleID datasets prove that our method has excellent performance.
Immune Response, Health Status, Blood Components and Growth Performance of Suckling Calves Treated with Thymus vulgaris Extract

| Newly born male Friesian calves (n=15) with average live body weight (LBW) of 35.07±0.63 kg after calving were divided into three groups (5 in each). Calves were fed colostrum from their dams for the first three days of age then whole milk meals were fed and the starter plus good quality berseem hay were given after the second week of age. In the first group, calves had no treatment and considered as control (G1), while those in G2 and G3 were received an oral dose of Thymus vulgaris extract (THY) at levels of 20 and 40 mg per kg BW, respectively. Treatment lasted from 3 up to 105 d of age. Results show that THY at 40 mg/kg LBW increased (P<0.05) serum immunoglobulins (IgG, IgM and IgA), hematological parameters, serum total lipids and cholesterol, improved liver and kidney functions and health status of the calves, while decreased diarrheal incidence. In conclusion, oral administration with thyme extract at a level of 40 mg/kg body weight to Frisian calves, during the suckling period had beneficial effects on their immunity and health status, consequently improving their growth rate and live body weight, which could help farmers to raise the suckling calves for breeding or milk and meat production to relieve milk and beef lack in Egypt.
An Improved Decentralized Control of Cascaded Inverters With Robust Stability Against Grid-Voltage Variation

The existing decentralized control method for grid-connected cascaded inverters has the problem that the system stability is sensitive to grid-voltage variation. As a result, the system would lose stability when the grid-voltage amplitude is abnormal. To address this issue, this letter proposes a novel decentralized ω-sinϕ and V-P power control scheme. The robust stability condition against grid-voltage variation is proved. Moreover, the power-factor-angle consistency of inherent synchronization mechanism is clearly revealed for cascaded inverters, and the flexible grid power factor is enabled. For future practical applications, the proposed primary control of this letter explores a promising control idea for cascaded PV/storage systems. Finally, the performance of the proposed method is compared with the existing method by simulations under small and large grid disturbances.
Evaluating the quality of revitalization of lost spaces with emphasis on abandoned factories (Case Study: Zanjan Match Factory )

Identifying and reviving lost spaces to reduce them is one of the duties of contemporary architects and urban planners; in the meantime, paying attention to the quality of revitalization and users' and beneficiaries' satisfaction is an issue that determines the success rate of this critical issue. The aim of this study was twofold. First, it has assessed the quality of revitalization of lost spaces using the Analytic Hierarchy Process (AHP) method. Second, it has investigated Zanjan Match Factory's revitalization success rate, converted into a museum of industry and mining after renovation and reconstruction. The present article's conceptual model is based on the exploratory analytical research method based on Bradbent's theory and the introduction of his five principles as assessment parameters. Each component in the case study is considered, prioritized, and assessed by a survey of 15 participants in two groups of experts and users. Findings show that the criteria of human protection and economic productivity have a greater score in the proper revitalization of this heritage. In contrast, space proportions with a pattern of behavior have the lowest score (preferences). Furthermore, this space's revitalization shows revitalization's success is the proper coordination between revitalization experts and users of this space regarding fulfilling their desires and needs.
CBC Differential of COPD Exacerbation

Complete blood count parameters provide novel inflammatory markers. We aimed to assess any differences in these novel inflammatory markers between case and control and according to exacerbation severity in patients with acute exacerbation of chronic obstructive pulmonary disease. Method: This a case control study was conducted at Marjan medical city among patients Previously diagnosed as COPD and admitted to the hospital with acute exacerbation were enrolled into the study. Complete blood count parameters were performed for both cases and control and compared among two groups by student T test. The severity of disease was measured by FEV1 and correlated with Complete blood count parameters to find any association by SPSS version 23. Result: Of 50 cases, 58% (29) of cases had Peripheral blood eosinophil ≥2. The mean white blood cell count, total Lymphocyte count, total neutrophil count, Neutrophil/lymphocyte ratio, hematocrit and mean platelet volume were significantly higher in case than control, but only white blood cell correlated with FEV1. Conclusion: In acute exacerbation, some of the complete blood count markers show a significant increase. These findings may be crucial for evaluation of acute exacerbation, determine the severity of exacerbation and treatment response during follow-up of the patient.
Time‐Domain Reflectometry Measurements and Modeling of Firn Meltwater Infiltration at DYE‐2, Greenland

Surface meltwater can be retained in an ice sheet if it infiltrates the firn and refreezes. This is an important mass balance process for the Greenland Ice Sheet, reducing meltwater runoff and associated sea‐level rise. The processes of meltwater infiltration and refreezing are not fully understood, however, and remain difficult to monitor remotely. We deployed vertical arrays of thermistors and time‐domain reflectometry (TDR) probes to 4‐m depth in the firn to continuously monitor meltwater infiltration and refreezing processes at DYE‐2, Greenland. The observations provide a detailed picture of the coupled thermal and hydrological evolution of the firn through the 2016 melt season, including estimates of firn water content. The thaw and wetting fronts reached a maximum depth of 1.8 m, with meltwater infiltration concentrated in four main pulses of melting and subsurface warming that reached progressively deeper into the firn. The observations were used to constrain a coupled model of firn thermodynamics and hydrology, which was then run over the period 1950–2020, driven by meteorological forcing from GC‐Net station data and ERA5 climate reanalyses. Model results suggest that decadal‐scale firn evolution at DYE‐2 is strongly influenced by extreme melt seasons such as those of 1968, 2012, and 2019, when meltwater infiltration reached depths of 6–7 m. Extreme melt years drive increases in firn temperature, ice content, and density, reducing firn meltwater retention capacity. Such processes are likely to govern future meltwater retention as the percolation zone extends to higher elevations in Greenland in the coming decades.
Wital: WiFi-based Real-time Vital Signs Monitoring During Sleep

High-quality sleep is essential to our daily lives, and real-time monitoring of vital signs during sleep is beneficial. Current sleep monitoring solutions are mostly based on wearable sensors or cameras, the former is worse for sleep quality, the latter is worse for privacy, dissimilar to such methods, we implement our sleep monitoring system based on COTS WiFi devices. There are two challenges need to be overcome in the system implementation process: First, the torso deformation caused by breathing/heartbeat is weak, how to effectively capture this deformation? Second, movements such as turning over will affect the accuracy of vital signs monitoring, how to quickly distinguish such movements? For the former, we propose a motion detection capability enhancement method based on Rice-K theory and Fresnel theory. For the latter, we propose a sleep motion positioning algorithm based on regularity detection. The experimental results indicated the performance of our method.
Arrhythmogenic right ventricular cardiomyopathy in a cat

Cardiomyopathies are a heterogeneous group of disorders of the myocardium, characterized by multiple clinical manifestations with different prognoses (1). In cats, heart disease is frequent and is considered one of the most common causes of death (2,3). ARVC is rare in pets and has a lot of similarities to human ARVC (4,5). Signs of the disease include moderate/severe dilation of the right ventricle, regional or diffuse thinning of the wall, and sometimes aneurysm. The histological examination shows the presence of adipose or fibrous tissue that replaces myocardium, focal myocarditis, and cell apoptosis, more frequent in the right ventricular wall (6). Clinical signs are related to right-sided heart failure; dyspnea caused by pleural effusion, ascites, turgor of the jugular veins, episodes of syncope (5,6). The outcome of the disease is not favorable, especially when the symptoms of heart failure become evident (6).
A model for Manufacturing Large Parts with WAAM Technology

Wire Arc Additive Manufacturing (WAAM) is a metallic additive manufacturing process based on the fusion of metallic wire using an electric arc as a heat source. The challenge associated with WAAM is heat management and understanding bead geometry. The printing process involves high temperatures, which results in the build-up of residual stresses can often cause deformations in a component. All of the process variables, such as torch speed (TS), wire feed speed (WFS), idle time, combine to produce the geometry of the deposit bead that results in the desired component shape. So, determining a method for choosing a good combined parameter process is very important to obtain a high-quality part. This article presents a study on how to use the WAAM process to produce a complexity part of aluminium alloys. The step of the determination process parameter is concentrated to develop in this study. An experimental design is determined to study the influence between the process parameters, for example, WFS, TS, high layer, length of bead. Different samples are made using the Yaskawa robot, using the classic CMT (Cold Metal Transfer) as a manufacturing method, using zigzag filling as a manufacturing strategy with the same WFS and same idle times and different TS, different bead lengths. A new manufacturing method using the zigzag filling strategy is proposed by adding an important step in determining the process parameters. The results indicate that the length of the bead has a significant impact on another parameter of the process.
Analysis and Experimental Comparison of Acoustic Noise of Three Switched Reluctance Motors Made of Conventional Steel, High Silicon Steel, and Amorphous Iron

In this article, three test motors are fabricated with different iron materials, conventional steel, high silicon steel, and amorphous iron. Among the three materials, the high silicon steel has the lowest magnetostriction and the amorphous iron has the highest magnetostriction and the lowest saturated flux density. Hammer test is carried out to identify the respective resonant frequency and the optimum Young's modulus and Poisson ratio are identified from the measured resonant frequency for each core. Furthermore, the acoustic noise is measured in load test and it is found that the high silicon steel has the lowest acoustic noise. Then, the electromagnetic finite element analysis (FEA) and acoustic noise analysis are carried out. According to the FEA results, the acoustic noise of the amorphous iron motor is the lowest, while it is the highest in an experiment. This discrepancy is considered to be resulted from the magnetostriction property of the magnetic materials that are ignored in FEA so far. Therefore, the magnetostriction of three iron sheets is measured and the FEAs that take magnetostriction into consideration are carried out. From the results of the improved FEAs, it is found that the magnetostriction plays an important role in acoustic noise analysis.
Modeling and Alleviating Low-Battery Anxiety for Mobile Users in Video Streaming Services

The pervasive low-battery anxiety (LBA) among modern mobile users has a negative impact on users’ emotion and health, and such anxiety may directly lead to the loss of customers in power-hungry applications, e.g., video streaming. Despite its importance, LBA has not been thoroughly investigated due to the difficulty in quantitatively measuring LBA. To fill the gap, we present a quantitative model to measure the LBA of mobile users and design a tailored mechanism for LBA alleviation by saving display energy in video streaming. In specific, we first conduct a large-scale survey of 2000+ mobile users and strategically extract an empirical LBA model that captures the variation of users’ anxiety degree along with the battery power draining. Then, by exploiting the emerging edge computing paradigm, we propose a novel solution for low-power video streaming services (namely, LPVS) at the network edge. It aims to minimize the LBA of mobile users, by integrating the extracted LBA model with the energy-saving image/video content transforming techniques. To accommodate the heterogeneous LBA properties of mobile users under different circumstances, we develop an LBA model updating scheme by further considering the specific and local edge environments. The emulation results using real-world video watching traces demonstrate that LPVS can effectively alleviate mobile users’ LBA and prolong their video watching time (i.e., customer retention) by 39%.