Miracle-dz/UniFAR-FTUs huggingface dataset:
High-resolution typhoon precipitation integrations using satellite infrared observations and multi-source data

Abstract. Typhoon-related precipitation over land can result in severe disasters such as floods and landslides, and satellites are a valuable tool to estimate surface precipitation with high spatial-temporal resolutions. This study develops a high-resolution surface precipitation integration framework to combine observations from geostationary Fengyun-4A/ Himawari-8 (F4/H8) satellite radiometers, high-density rain-gauge observations (or Integrated Multisatellite Retrievals for GPM (IMERG) data) and atmospheric reanalysis (ERA5) based on a random forest (RF) algorithm. The RF methods fuse cloud and atmospheric features from radiometric observations and reanalysis information, and the intensity and spatial distribution of rainfall can be revealed by high-density rain-gauge or IMERGE observations. We take three typhoons made landfall in South China in 2018 as examples. Both F4- and H8-based results using rain-gauge data as the predictand show excellent results with correlation coefficients (R) with the references ~0.75 and probabilities of detection (POD) as large as 0.98, higher than current satellite-only results. However, if the IMERG data are used as the predictand, the corresponding R and POD drop to ~0.5 and 0.93, respectively, due to the uncertainties related to IMERG retrievals. By carefully choosing the predictors, the RF algorithm can clearly summarize the information from satellite observations, surface observations and atmospheric reanalysis, resulting in precipitation results that are highly consistent with the actual ground observations. Our proposed integration framework can not only reconstruct hourly surface precipitation estimation datasets at high-spatial resolution for historical typhoon studies but also potentially monitor the fine- resolution surface precipitation of frequent typhoons in near-real time.
APPLICATION OF HIERARCHIC ANALYSIS TO QUANTITATIVE EVALUATION OF CARBONATE RESERVOIR

Quantitative evaluation for carbonate reservoir can improve the accuracy and correction of reservoir evaluation.The factors that are used in quantitatively evaluating carbonate reservoir are too more,so it is quite important to know how to use these factors and their relationships.Research finds the factors have some typical hierarchic properties,and therefore hierarchic analysis method can be used as important quantitative indexes.Combined with fuzzy comprehensive evaluation,it can be used to evaluate reservoir quantitatively.A quantitative evaluation example for every members of the Jia-2 member in the Jialing River formation in Moxi area which is situated in central Sichuan suggests that the calculating result is accordance with the actual result,in another word,hierarchic analysis method is effective.
The Transcriptional Cell Atlas of Testis Development in Sheep at Pre-Sexual Maturity

Sheep testes undergo a dramatic rate of development with structural changes during pre-sexual maturity, including the proliferation and maturation of somatic niche cells and the initiation of spermatogenesis. To explore this complex process, 12,843 testicular cells from three males at pre-sexual maturity (three-month-old) were sequenced using the 10× Genomics ChromiumTM single-cell RNA-seq (scRNA-seq) technology. Nine testicular somatic cell types (Sertoli cells, myoid cells, monocytes, macrophages, Leydig cells, dendritic cells, endothelial cells, smooth muscle cells, and leukocytes) and an unknown cell cluster were observed. In particular, five male germ cell types (including two types of undifferentiated spermatogonia (Apale and Adark), primary spermatocytes, secondary spermatocytes, and sperm cells) were identified. Interestingly, Apale and Adark were found to be two distinct states of undifferentiated spermatogonia. Further analysis identified specific marker genes, including UCHL1, DDX4, SOHLH1, KITLG, and PCNA, in the germ cells at different states of differentiation. The study revealed significant changes in germline stem cells at pre-sexual maturation, paving the way to explore the candidate factors and pathways for the regulation of germ and somatic cells, and to provide us with opportunities for the establishment of livestock stem cell breeding programs.
Do clergy recognize and respond appropriately to the many themes in obsessive-compulsive disorder?: Data from a Pacific Island community

ABSTRACT Obsessive-compulsive disorder (OCD) is a debilitating psychiatric condition with high rates of misdiagnoses and extended treatment gaps. These may derive in part from poor mental health literacy (MHL) among clergy, who are frequently consulted by those with mental health problems. Therefore, the current study examined the MHL of OCD among clergy on Guam. Clergy (N = 110) provided diagnostic impressions, treatment recommendations, and referral recommendations in response to one of six randomized vignettes describing a common manifestation of OCD: contamination, symmetry, religion, homosexuality, pedophilia, or aggression. Clergy typically misidentified OCD (64.5%), especially in vignettes describing taboo thoughts. They more often recommended that the cases described in the vignettes receive pastoral/biblical counseling and a referral to a clergyperson for professional help rather than professional medical or mental health services. Overall, results reveal needs among clergy for increased MHL, especially concerning OCD's heterogeneous symptomology and evidence-based treatments.
Peroxisomal Stress Response and Inter-Organelle Communication in Cellular Homeostasis and Aging

Peroxisomes are key regulators of cellular and metabolic homeostasis. These organelles play important roles in redox metabolism, the oxidation of very-long-chain fatty acids (VLCFAs), and the biosynthesis of ether phospholipids. Given the essential role of peroxisomes in cellular homeostasis, peroxisomal dysfunction has been linked to various pathological conditions, tissue functional decline, and aging. In the past few decades, a variety of cellular signaling and metabolic changes have been reported to be associated with defective peroxisomes, suggesting that many cellular processes and functions depend on peroxisomes. Peroxisomes communicate with other subcellular organelles, such as the nucleus, mitochondria, endoplasmic reticulum (ER), and lysosomes. These inter-organelle communications are highly linked to the key mechanisms by which cells surveil defective peroxisomes and mount adaptive responses to protect them from damages. In this review, we highlight the major cellular changes that accompany peroxisomal dysfunction and peroxisomal inter-organelle communication through membrane contact sites, metabolic signaling, and retrograde signaling. We also discuss the age-related decline of peroxisomal protein import and its role in animal aging and age-related diseases. Unlike other organelle stress response pathways, such as the unfolded protein response (UPR) in the ER and mitochondria, the cellular signaling pathways that mediate stress responses to malfunctioning peroxisomes have not been systematically studied and investigated. Here, we coin these signaling pathways as “peroxisomal stress response pathways”. Understanding peroxisomal stress response pathways and how peroxisomes communicate with other organelles are important and emerging areas of peroxisome research.
ANALYSIS OF PEDESTRIAN BEHAVIOR IN THE CITY OF PILA

Resume Every year, many people lose their health and/or lives on Polish roads. One of the reasons for this is behavior of pedestrians at pedestrian crossings, which affects the road safety. The aim of the article was to conduct experimental research, the idea of which was to study the behavior of pedestrians at pedestrian crossings in the city of Pila, the results of which can be applied to Poland. During the research, the behavior of pedestrians and the impact on the probability of a road accident were analyzed. Undoubtedly, the prevailing epidemic, during which people are in many respects limited, had an impact on the results obtained, therefore the number of people at the analyzed crossings may have decreased. The conducted research confirmed the Police statistical data that the most dangerous crossings for pedestrians are those without traffic lights. Article info Received 12 August 2021 Accepted 3 November 2021 Online 19 January 2022
A Robust Model for MODIS and Landsat Image Fusion Considering Input Noise

Significant progress has been made in spatiotemporal fusion for remote sensing images; however, most models require inputs to be free of clouds and without missing data, considerably confining their applications in practice. Due to recent advances in deep learning technologies, powerful modeling capabilities could be leveraged to bring potential solutions to this problem. This article proposes a novel architecture named the robust spatiotemporal fusion network (RSFN) based on the generative adversarial network and attention mechanism with dual temporal references to automatically handle input noise. The RSFN only needs one coarse-resolution image on the prediction date and two referential fine-resolution images before and after the prediction date as model inputs. Most notably, there is no special restriction attached on the data quality of referential images. The comparison with other models demonstrates the effectiveness of the RSFN model quantitatively and visually in four study areas using MODIS and Landsat images. Two main conclusions can draw from the experiments. First, the input data noise hardly affects the prediction results of the RSFN, and the RSFN can gain a comparable or even higher accuracy; conversely, the other methods only show limited resistance to input noise. Second, the RSFN with cloud-contaminated references outperforms the other models with cloud-free references after data filtering in the same study area during the same period. The satellite data quality usually varies significantly; the model robustness and fault tolerance are considered critical for actual applications. The RSFN is a simple end-to-end deep model with high accuracy and fault tolerance designed for spatiotemporal fusion with imperfect data inputs, showing promising prospects in practical applications.
Health Monitoring of Bridges and Optimal Placement of Sensor

In order to avoid or reduce certain damages and failures to bridge during the service period, it is necessary to take effective monitoring method for the bridges. The necessity of health monitoring of bridges are introduced in this paper. Then the development and investigation of health monitoring of bridges in recent years are presented. The researches on the optimal placement of sensor are emphasized, and some examples are listed. Finally the problems which need to further study are pointed out in the paper.
Characterization of Social Risk Factors Among Newborns Seen at an Urban Pediatric Primary Care Predictive of Appointment Nonattendance During the First 6 Months of Life

Purpose: Appointment attendance is critical in monitoring health and well-being of children. Low income Medicaid-insured families with newborns often experience social risks that may affect attendance. This project sought to characterize social risk factors present at first newborn visits predictive of future appointment nonattendance. Methods: Retrospective cohort study of minority and Medicaid-insured population at St. Christopher's Hospital for Children using a standardized social risk screener administered at first newborn visits as part of routine clinical care. In total, 720 survey responses between December 2016 and June 2017 were correlated with electronic health record-derived sociodemographic and appointment attendance data in the first 6 months of life. Nonattendance included missed and canceled appointments. Caregiver-reported social risk factors were included as covariates in linear regressions predicting proportion nonattendance outcomes. Results: Newborn caregivers identified many social risk factors including mental health diagnoses (14%), lack of child care support (45%), and food insecurity (9%). Approximately 74% had nonattendance with 41% missing or canceling a quarter or more appointments. Number of siblings (p<0.01) and maternal age (p<0.01) were most predictive for nonattendance, respectively. Other social risks were not significant except for maternal mental health (p=0.01) among those identifying number of risk factors above cohort average (16%). Conclusion: Screening of newborns at first medical visits can be used to characterize social risks. Most social risk factors at first visits were not strongly predictive of nonattendance, although our results suggested associations between non-attendance and maternal demographics, mental health and household makeup.
Ophthalmic imaging for the diagnosis and monitoring of glaucoma: A review

The last three decades have been a turning point for early glaucoma diagnosis and monitoring by newly developed imaging techniques. Improvements in imaging of the anterior segment (AS), retinal nerve fibre layer (RNFL), optic nerve head (ONH), and macular ganglion cell complex (GCC) came into existence and broke new ground for early diagnosis and progression survey. This review will summarise the different ophthalmic imaging techniques, their principles, pros and cons, ongoing development processes, and the future of imaging methods. The aim is to provide the clinician with an understanding of the role of imaging methods and provide insight for appropriate use and evaluation of their outputs in glaucoma diagnosis and treatment.
Test and Analysis of High Voltage Helium Tight EAST Tokamak insulator

In order to ensure reliable operation of the overall security of devices,the reliable detection of insulators and analysis is needed.A special testing method for EAST Tokamak insulator is introduced.High voltage insulation property of EAST Tokamak insulator is analyzed with finite element analysis method to achieve electric field intensity along different contours and thermal stress distribution.Calculation results show that the insulator structure is reliable.This study may provide a theoretical basis for further improvement of the EAST insulator.
Anticipated Mode Generating for On-line Verification of Relay Protection Setting Based on Maintenance Tickets Information

In order to make the verification of relay protection setting more scientific and effective,a method of realizing the anticipated mode for on-line verification of relay protection setting based on maintenance tickets information is studied.First,a general description about the realization of on-line verification based on SG-OSS platform is given,especially the way to obtain data source of maintenance tickets is explained.By using the balanced binary tree method and based on maintenance tickets,an optimization algorithm to obtain the possible mode section is then proposed.Based on this,the generating way of anticipated mode at the calculation moment is elaborated.Finally,apractical method of appropriate power flow section selection for different load cases is proposed.
The assessment of the attractiveness of memorials in historic urban landscape

ABSTRACT The memorial attractiveness assessment presented in this paper is based on the multi-perspective approach. The Warsaw city centre Poland is a good field for such research as it is the area with the highest memorial saturation. There are 40 memorials on the Royal Route, the most representative part of the city centre. The study presents a number of guidelines and recommendations in a coherent and complex way regarding prospective location changes and suggestions for enhancing the attractiveness of newly established memorials.
Research on One Kind of Worming Robot for Sewage Pipe Working

It summarizes of structure scheme of robot for working of drainpipe deposit cleaning inland and oversea,analyzes their characteristics and limitations. So one new type worming robot for sewage pipe working was put forward based on combination mechanism. The main structure and walking principle of the robot were given,the model of walking kinematical and driving torque were set up,so main influence parameters and numerical value analysis were given. Further more the virtual prototype was made and kinematical simulation analysis had been accomplished. Finally,results which wrer based on theoretical numerical analysis and virtual prototype simulation analysis validated the robot scheme was feasibility,design theory and analysis conclusions of the robot were correct. The robot can have bigger tensile draw and long working distance.
Fabrication and characterisation of carbon nanotube reinforced copper matrix nanocomposites

ABSTRACT Carbon nanotube reinforced metal matrix nanocomposite can be fabricated by using several processes: namely powder metallurgy, molecular-level-mixing, electrodeposition, melt stirring, etc. In this work, carbon nanotube reinforced copper matrix nanocomposites were fabricated by employing the simple powder metallurgy method. Prepared nanocomposites have been characterized by using various characterisation techniques: namely compression test, hardness and density measurement. Morphology and microstructure of composite samples were characterised by using SEM. Properties of the metal matrix nanocomposites were correlated with the microstructure. Experimental results revealed that the density and the specific wear rate of the nanocomposites samples are slightly decreased with the increment of carbon nanotube reinforcement in the metal matrix. Compressive strength of the nanocomposite samples are dramatically increased (155% improvement) with carbon nanotube reinforcement in the copper matrix, while Rockwell hardness number of the samples are slightly increased (22.5% improvement) with an increment of carbon nanotube reinforcement in the matrix material.
A Novel Single-stage Buck-boost Inverter Based on Improved Spwm Control Method

A novel single-stage series-resonant Buck-Boost inverter is proposed in this paper,which can generate a sine ac output voltage larger or lower than the input one in a single stage. The operation principle is analyzed in detail and the mathematics model is founded by the state-space average method. Based on discontinuous conduction mode (DCM),the new inverter circuit topology provides all the switches for turn-on and the auxiliary switches for turn-off at zero current switching (ZCS) by a series-resonant tank,so that the switching loss is reduced and system effeciency is improved. An improved SPWM control method employing a sine modulation wave with dc bias value is presented to optimize the inverter performance. The proposed control method eliminates the output voltage zero-crossing distortion as caused by linear approximation in traditional SPWM method. Laboratory experimental results from a 1kW prototype are given to verify the validity and effectiveness of the proposed inverter.
SU(2)-in-SU(1,1) Nested Interferometer for High Sensitivity, Loss-Tolerant Quantum Metrology.

We present experimental and theoretical results on a new interferometer topology that nests a SU(2) interferometer, e.g., a Mach-Zehnder or Michelson interferometer, inside a SU(1,1) interferometer, i.e., a Mach-Zehnder interferometer with parametric amplifiers in place of beam splitters. This SU(2)-in-SU(1,1) nested interferometer (SISNI) simultaneously achieves a high signal-to-noise ratio (SNR), sensitivity beyond the standard quantum limit (SQL) and tolerance to photon losses external to the interferometer, e.g., in detectors. We implement a SISNI using parametric amplification by four-wave mixing (FWM) in Rb vapor and a laser-fed Mach-Zehnder SU(2) interferometer. We observe path-length sensitivity with SNR 2.2 dB beyond the SQL at power levels (and thus SNR) 2 orders of magnitude beyond those of previous loss-tolerant interferometers. We find experimentally the optimal FWM gains and find agreement with a minimal quantum noise model for the FWM process. The results suggest ways to boost the in-practice sensitivity of high-power interferometers, e.g., gravitational wave interferometers, and may enable high-sensitivity, quantum-enhanced interferometry at wavelengths for which efficient detectors are not available.
Serverless Empowered Video Analytics for Ubiquitous Networked Cameras

Ubiquitous deployment of networked cameras has boosted the prevalence of video analytics. Leveraging machines to automatically analyze captured videos has become the driving force behind a variety of contemporary applications. However, it is known to be resource-hungry with highly dynamic demands, which mismatches the existing monolithic cloud service deployment with coarse-grained resource allocation. Recent advances in serverless computing, which offers ultra-fast and fine-grained autoscaling, would become a game-changer. This article closely examines the potential and challenges of serverless computing in building modern video analytics applications. We accordingly present an integrated framework with geo-distributed resources, and identify the critical design issues toward its implementation. We further discuss a series of promising research directions in this field.
Method of data fusion for multi-sensor and its applications

The method of multi sensor information fusion is the key technology in this times,it is begotten and developed in military domains.It is remarkable significance to improve manufacture level with this high technology.For this reason,a method of multi sensor information fusion is brought forward.The experiment result shows that this method is better than tradition in statistics,and it is successful to improve the accuracy of intelligent instruments.
Energy-Efficient Computation Offloading in Mobile Edge Computing Systems with Uncertainties

Computation offloading is indispensable for mobile edge computing (MEC). It uses edge resources to enable intensive computations and save energy for resource-constrained devices. Existing works generally impose strong assumptions on radio channels and network queue sizes. However, practical MEC systems are subject to various uncertainties rendering these assumptions impractical. In this paper, we investigate the energy-efficient computation offloading problem by relaxing those common assumptions and considering intrinsic uncertainties in the network. Specifically, we minimize the worst-case expected energy consumption of a local device when executing a time-critical application modeled as a directed acyclic graph. We employ the extreme value theory to bound the occurrence probability of uncertain events. To solve the formulated problem, we develop an ϵ-bounded approximation algorithm based on column generation. The proposed algorithm can efficiently identify a feasible solution that is less than (1+ϵ) of the optimal one. We implement the proposed scheme on an Android smartphone and conduct extensive experiments using a real-world application. Experiment results corroborate that it will lead to lower energy consumption for the client device by considering the intrinsic uncertainties during computation offloading. The proposed computation offloading scheme also significantly outperforms other schemes in terms of energy saving.
Military Application of Animals Flight Control Technology

Semi-mechanical animal air vehicles represent the developing trend of micro air vehicle(MAV),which developed rapidly in recent years.In present paper,the animal flight control technology(AFCT) was introduced briefly;the values and prospects of military applications of semi-mechanical animal air vehicles were discussed;the trends of AFCT were reviewed.As one of our research findings recently,the Beetle robots were introduced,and finally,the bottleneck and the trends of studying AFCT were prospected.