Miracle-dz/UniFAR-FTUs huggingface dataset:
Stochastic Computation Offloading for LEO Satellite Edge Computing Networks: A Learning-Based Approach

The deployment of mobile edge computing services in LEO satellite networks achieves seamless coverage of computing services. However, the time-varying wireless channel conditions between satellite–terrestrial channels and the random arrival characteristics of ground users’ (GUs) tasks bring new challenges for managing the LEO satellite’s communication and computing resources. Facing these challenges, a stochastic computation offloading problem of joint optimizing communication and computing resources allocation and computation offloading decisions is formulated for minimizing the long-term average total power cost of the GUs and the LEO satellite, with the constraint of long-term task queue stability. However, the computing resource allocation and the computation offloading decisions are coupled within different slots, thus making it challenging to address this problem. To this end, we first employ the Lyapunov optimization to decouple the long-term stochastic computation offloading problem into the deterministic subproblem in each slot. Then, an online algorithm combining deep reinforcement learning and conventional optimization algorithms is proposed to solve these subproblems. Simulation results show that the proposed algorithm can achieve the superior performance while ensuring the stability of all task queues in LEO satellite networks.
The Effectiveness of The General Election Commission (KPU) Organization of Bengkulu Province In The Gubernatorial Election And Deputy Governor of Bengkulu

Based on the Constitution of the Republic of Indonesia Year 1945 states that the State of Indonesia is a unitary state in the form of a republic. Regional Head Elections or also called Elections for Governors and Vice Governors, Regents and Vice Regents, as well as Mayors and Deputy Mayors hereinafter referred to as Elections are the exercise of people's sovereignty in provincial and regency/city areas to elect Governors and Vice Governors, Regents and Vice Regents, as well as Mayors and Vice Mayors directly and democratically. The type of research used is qualitative descriptive with descriptive elaboration, the effectiveness of the General Election Commission (KPU) Organization of Bengkulu Province in the 2020 Bengkulu Governor and Deputy Governor Elections during the Covid-19 pandemic has been quite effective. KPU Bengkulu Province can carry out tasks that are used as research aspects in this study. To find out the effectiveness can be seen from the following data: Aspects of Tasks or Functions. The KPU of Bengkulu Province can carry out the duties and functions that have been mandated to it effectively even in the conditions of the Covid-19 pandemic. This can be seen from the tasks and functions given can be carried out entirely
Cytogenetically Cryptic Acute Promyelocytic Leukemia: A Diagnostic Challenge

Cytogenetically cryptic acute promyelocytic leukemia (APL) is rare, characterized by typical clinical and morphological features, but lacks t(15;17)(q24;q21)/PML::RARA translocation seen in conventional karyotyping or FISH. The prompt diagnosis and treatment of APL are critical due to life-threatening complications associated with this disease. However, cryptic APL cases remain a diagnostic challenge that could mislead the appropriate treatment. We describe four cryptic APL cases and review reported cases in the literature. Reverse transcriptase polymerase chain reaction (RT-PCR) is the most efficient diagnostic modality to detect these cases, and alternative methods are also discussed. This study highlights the importance of using parallel testing methods to diagnose cryptic APL cases accurately and effectively.
Implementing the WPS Standard; A Case Study for Dissemination of Coastal and Marine Tools

The Open Geospatial Consortium has been developing a wide range of open standards for the field of Geographical Information (GI). One of the standards allows for remote processing; the Web Processing Service (WPS). WPS has not been implemented in many project yet but it is a promising standard which can also be applied outside the field of GI. In this project the WPS standard is applied by means of two case studies, the first is on tidal forecasting and the second is on wrapping an existing remote processing service. The focus of the project is not on making the most optimal and reliable tools but on demonstrating the possibilities WPS offers for a wide range of applications and interoperability between different systems. The goal of the research is to expose complex processes that feed marine and coastal models via a WPS.
Investigating microbial size classes associated with the transmission of stony coral tissue loss disease (SCTLD)

Effective treatment and prevention of any disease necessitates knowledge of the causative agent, yet the causative agents of most coral diseases remain unknown, in part due to the difficulty of distinguishing the pathogenic microbe(s) among the complex microbial backdrop of coral hosts. Stony coral tissue loss disease (SCTLD) is a particularly destructive disease of unknown etiology, capable of transmitting through the water column and killing entire colonies within a matter of weeks. Here we used a previously described method to (i) isolate diseased and apparently healthy coral colonies within individual mesocosms containing filtered seawater with low microbial background levels; (ii) incubate for several days to enrich the water with coral-shed microbes; (iii) use tangential-flow filtration to concentrate the microbial community in the mesocosm water; and then (iv) filter the resulting concentrate through a sequential series of different pore-sized filters. To investigate the size class of microorganism(s) associated with SCTLD transmission, we used 0.8 µm pore size filters to capture microeukaryotes and expelled zooxanthellae, 0.22 µm pore size filters to capture bacteria and large viruses, and 0.025 µm pore size filters to capture smaller viruses. In an attempt to further refine which size fraction(s) contained the transmissible element of SCTLD, we then applied these filters to healthy “receiver” coral fragments and monitored them for the onset of SCTLD signs over three separate experimental runs. However, several factors outside of our control confounded the transmission results, rendering them inconclusive. As the bulk of prior studies of SCTLD in coral tissues have primarily investigated the associated bacterial community, we chose to characterize the prokaryotic community associated with all mesocosm 0.22 µm pore size filters using Illumina sequencing of the V4 region of the 16S rRNA gene. We identified overlaps with prior SCTLD studies, including the presence of numerous previously identified SCTLD bioindicators within our mesocosms. The identification in our mesocosms of specific bacterial amplicon sequence variants that also appear across prior studies spanning different collection years, geographic regions, source material, and coral species, suggests that bacteria may play some role in the disease.
β-Sitosterol Inhibits The Proliferation of Endometrial Cells via Regulating Smad7-Mediated TGF-β/Smads Signaling Pathway

Objective: To investigate the effect of β-sitosterol on endometrial cells to understand the underlying mechanism. Materials and Methods: This is a laboratory-based experimental study conducted on animals and cells. Histological assays were performed to determine the effect of β-sitosterol on endometrial cells. The CCK-8 assay was used to assess the inhibitory effect of β-sitosterol on the proliferation of ectopic endometrial stromal cells (hEM15A). Flow cytometry was performed to evaluate the induction of apoptosis by β-sitosterol in hEM15A cells. The transwell invasion assay was conducted to measure the suppression of hEM15A cell migration by β-sitosterol. Western blot analyses were performed to analyze the effect of β-sitosterol on the expression of Smad family member 7 (Smad7) and the activity of transforming growth factor-β (TGF-β1), as well as the phosphorylation of Smad2 and Smad3. Results: Histological assays showed that β-sitosterol regulates histopathology and induces apoptosis of endometrial cells in vivo. The CCK-8 assay revealed that β-sitosterol could inhibit the proliferation of hEM15A in human endometriosis patients. Flow cytometry showed that apoptosis was triggered by β-sitosterol in hEM15A. The transwell invasion assay indicated that the hEM15A migration under the β-sitosterol treatment group was suppressed. Western blot analyses suggested that β-sitosterol increased the expression of Smad7, decreased the activity of TGF-β1, and reduced the phosphorylation of Smad2 and Smad3. The effect of β-sitosterol was weakened by the silence of Smad7. Conclusion: The results suggest that β-sitosterol can inhibit the proliferation of endometrial cells and relieve endometriosis by inhibiting TGF-β-induced phosphorylation of Smads through regulation of Smad7.
The Laguerre mixture model

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A new species of Euscorpius Thorell, 1876 from the Antalya Province, southern Turkey (Scorpiones: Euscorpiidae).

A new scorpion species, Euscorpius gocmeni sp. n. , is described based on specimens collected from the Antalya Province (Akseki District) in southern Turkey. It is characterized by a high trichobothrial count (Pv = 11–13, et = 7–8, em = 4, and eb = 4), a high pectinal teeth count (Dp = 10–12 in males, 8–9 in females), medium-small size, and light to medium brown-reddish color.
GHOST SEGMENTS IN THE FLEMISH TUSSENTAAL

The Flemish informal standard ( Tussentaal ) exhibits a word-ﬁnal elision process whereby words such as ‘wat’ and ‘met’ are realised without their ﬁnal plosive: [ BA ] and [ mE ]. This elided segment triggers devoicing in following fricatives. This process is not derivable from phonological context alone, and the current literature has not explained its distribution. This study therefore set off to (1) document this elision process, and (2) account for its distribution. Using Python and the corpus engine OpenSonar, audio tokens of the ﬁfty most common Dutch words containing ﬁnal coronal plosives were scraped from the Corpus Gesproken Nederlands. Joint results of an algorithmic and a manual analysis reveal that this elision occurs in the present tense marker /-t/ and most function words. All exceptions found have historically undergone word-ﬁnal schwa deletion, suggesting that ﬁnal coronal plosive elision may be older. Evidence from 13th century texts supports this claim.
Sufficient principal component regression for pattern discovery in transcriptomic data

Abstract Motivation Methods for the global measurement of transcript abundance such as microarrays and RNA-Seq generate datasets in which the number of measured features far exceeds the number of observations. Extracting biologically meaningful and experimentally tractable insights from such data therefore requires high-dimensional prediction. Existing sparse linear approaches to this challenge have been stunningly successful, but some important issues remain. These methods can fail to select the correct features, predict poorly relative to non-sparse alternatives or ignore any unknown grouping structures for the features. Results We propose a method called SuffPCR that yields improved predictions in high-dimensional tasks including regression and classification, especially in the typical context of omics with correlated features. SuffPCR first estimates sparse principal components and then estimates a linear model on the recovered subspace. Because the estimated subspace is sparse in the features, the resulting predictions will depend on only a small subset of genes. SuffPCR works well on a variety of simulated and experimental transcriptomic data, performing nearly optimally when the model assumptions are satisfied. We also demonstrate near-optimal theoretical guarantees. Availability and implementation Code and raw data are freely available at https://github.com/dajmcdon/suffpcr. Package documentation may be viewed at https://dajmcdon.github. io/suffpcr. Contact daniel@stat.ubc. ca Supplementary information Supplementary data are available at Bioinformatics Advances online.
Source apportionment of soot particles and aqueous-phase processing of black carbon coatings in an urban environment

Abstract. The impacts of soot particles on climate and human health depend on the concentration of black carbon (BC) as well as the thickness and composition of the coating material, i.e., organic and inorganic compounds internally mixed with BC. In this study, the size-resolved chemical composition of BC-containing aerosol was measured using a high-resolution soot particle aerosol mass spectrometer (SP-AMS) during wintertime in Fresno, California, a location influenced by abundant combustion emissions and frequent fog events. Concurrently, particle optical properties were measured to investigate the BC absorption enhancement. Positive matrix factorization (PMF) analysis was performed on the SP-AMS mass spectral measurements to explore the sources of soot particles and the atmospheric processes affecting the properties of BC coatings. The analysis revealed that residential woodburning and traffic are the dominant sources of soot particles. Alongside primary soot particles originating from biomass burning (BBOABC) and vehicles (HOABC) two distinct types of processed BC-containing aerosol were identified: fog-related oxidized organic aerosol (FOOABC) and winter-background OOABC (WOOABC). Both types of OOABC showed evidence of having undergone aqueous processing, albeit with differences. The concentration of FOOABC was substantially elevated during fog events, indicating the formation of aqueous secondary organic aerosol (aqSOA) within fog droplets. On the other hand, WOOABC was present at a relatively consistent concentration throughout the winter and was likely related to the formation of secondary organic aerosol (SOA) in both the gas phase and aerosol liquid water. By comparing the chemical properties and temporal variations in FOOABC and WOOABC, we gain insights into the key aging processes of BC aerosol. It was found that aqueous-phase reactions facilitated by fog droplets had a significant impact on the thickness and chemical composition of BC coatings, thereby affecting the light absorption and hygroscopic properties of soot particles. These findings underscore the important role of chemical reactions occurring within clouds and fogs and influencing the climate forcing of BC aerosol in the atmosphere.
association of metabotropic glutamate receptor 3 gene polymorphisms with schizophrenia risk: evidence from a meta-analysis

: To date, the role of metabotropic glutamate receptor 3 (GRM3) rs274622, rs1468412, rs917071, rs6465084, and rs2299225 polymorphisms in schizophrenia remains controversial. To provide a clearer picture for the effect of the five most studied GRM3 polymorphisms on risk of schizophrenia, this meta-analysis with eligible data from published studies was performed. Relevant case–control studies were retrieved by literature search and selected according to established inclusion criteria. Odds ratios with 95% confidence intervals were used to assess the strength of association. A total of 33 individual studies were identified and included in our meta-analysis: nine for rs1468412, with 5,314 cases and 6,147 controls; six for rs917071, with 2,660 cases and 3,517 controls; seven for rs274622, with 3,820 cases and 4,015 controls; five for rs2299225, with 3,492 cases and 3,735 controls; and six for rs6465084, with 4,960 cases and 5,613 controls. However, no significant association was found between these GRM3 polymorphisms and schizophrenia in the overall population. With respect to rs1468412 polymorphism, a finding of very borderline statistical significance emerged in dominant comparison model for non-Asian populations, calling for large-scale verification to assess the marginally elevated risk of schizophrenia. In conclusion, these GRM3 polymorphisms have limited effect on the risks of schizophrenia. Further large and well-designed studies are needed to confirm this conclusion.
Water Vapor Exchange between Atmospheric Boundary Layer and Free Troposphere over Eastern China: Seasonal Characteristics and ENSO Anomaly

This study develops a quantitative climatology of water vapor exchange between the 1 atmospheric boundary layer (ABL) and free troposphere (FT) over Eastern China. The 2 exchange flux is estimated for January, April, July, and October over 7 years (2011 and 2014-3 2019) based on a water vapor budget equation using simulated meteorological data. The spatial 4 pattern of the ABL-FT water vapor exchange flux is closely related to the topographic 5 distribution. The seasonal variation shows that the water vapor exchange in the northern region 6 is downward in January and October with the flux being 37%-72% of the surface evaporation 7 to maintain the ABL moisture, while it is weak upward in April and July; the southern region 8 presents persistently water vapor output from the ABL to the FT, with the ratio of exchange 9 flux to surface evaporation increasing from 10% in January and October to 60%-80% in April 10 and July. Three physical processes determine the total water vapor exchange, among which the 11 ABL diurnal variation drives large magnitude exchange flux within the one-day cycle, but for 12 the net monthly mean flux, the vertical motion at the ABL top is the main contributor. The 13 anomaly of water vapor exchange in ENSO years illustrates triple antiphase distribution: 14 strengthening in the middle area and weakening in the north and south zones of Eastern China 15 in La Niña year, and vice versa in El Niño year. It agrees with the spatial pattern of anomalous
Detection of Agricultural Pests Based on YOLO

Focus on the problem of the species pests are difficult to identify in agricultural production an application based on the YOLO algorithm is presented. The algorithm extracts features fastly and complete detection task simultaneously. Through collecting agricultural pests, the algorithm establishes a data-set build target object detection model and train them, the problem of difficulties in identifying agricultural pest species and locating them has been solved. The result shows that the mAP’value of YOLO algorithm is 92.42%, the prediction precision is 96.8%. The algorithm has a high recognition rate, and identify the species of pests fastly and accurately, it can meet the detection and identification requirements.
Anomaly Pixel Detection via Dual-Branch Uncertainty Metrics

Anomaly detection aims to detect abnormal samples from normal data. Existing methods mainly use synthesis-based approach and uncertainty-based approach. Moreover, the above-mentioned methods need to re-train part/all of the deep network, which limits its application scenarios especially real-time scenarios. We propose a novel retraining-free anomaly detection method, which includes a dual-branch anomaly detection mechanism to detect abnormal pixels from two views. In the pseudo-supervised branch, we use the Copy post method to transform the unsupervised anomaly detection task into a supervised binary detection task. In the prototype detection branch, we use prototypes to improve the accuracy of abnormal pixel detection. The anomaly results of the two branches are fused by means of soft voting to produce anomaly detection results with higher recall. Our experiments show that our method significantly outperforms other methods and achieves excellent results on different datasets, which also shows that our method has good generalization ability. Therefore, our proposed method can effectively improve the effectiveness and safety of anomaly detection in real-time scenarios, such as autonomous driving.
Applications of common energy variability methods for establishing the equilibrium equation in mechanics

The principles of the energy variation method are commonly utilized in mechanics. Energy is a scalar variable, so these are more convenient and simple to establish the equilibrium equations compared to vector-based approaches (i.e. using forces and displacements). The present article applied the theorem of the energy variation method in order to set the equilibrium equations for various complicated problems. Four examples of applying the energy variation method include the differential equation of the Euler – Bernoulli beam based on the energy method, the system of Equilibrium Equations of the Euler–Bernoulli beam with the theorem of Least Work, the principle of maximum work to establish the equation of motions for the Euler–Bernoulli beam and the equation of motion for the Euler–Bernoulli beam by the virtual work theorem, have been implemented. The results obtained from this study open up further research directions on the application of the energy variation method in mechanics as well as in the analysis theory of beam bridges.
Research on an Improved Adaptive Image Enhancement Algorithm

Aiming at the image degradation problems that occur during industrial activities and the shortcomings of traditional fuzzy enhancement algorithms in dealing with image degradation problems with high algorithm complexity and poor enhancement results. Based on the tuned tri-threshold fuzzy intensification algorithm, this paper proposes an adaptive image enhancement algorithm, which combines three kinds of degraded images in reality (i.e., images in dusty, night and foggy environments) for simulation verification, and compares the visual effects of the enhanced images and makes objective quantitative evaluation. The experimental results show that: the proposed algorithm can not only effectively improve the contrast of the image, keep the detailed information of the image, and make the image present a more natural visual effect, but also improve the quality evaluation index of the image, and make the variance value is improved by more than 5% compared with other comparison algorithms.
High Precision License Plate Recognition Algorithm in Open Scene

At present, license plate recognition algorithm under restricted conditions is relatively mature and widely used in various license plate recognition system. Due to the influence of factors such as large differences in shooting angles and vehicle motion blur, Chinese license plate recognition is quite challenging. In response to the above problems, this research abandoned the single end-to-end deep learning license plate recognition method, and proposed a step-by-step license plate recognition algorithm that integrated detection and classification, and utilized a level-by-level object detection strategy combined with character classification to predict the characters of the license plate result. On the basis of the above, a multi-anchor character position regression algorithm was proposed to further accurately regress the local area position information of all license plate characters. At the same time, in order to meet the needs of character detection and character classification, as well as the imbalance of the existing license plate datasets, this study contributed a series of supporting license plate datasets. According to the published publications, this study contributed the first large-scale character-level annotated license plate dataset. Extensive experiments show that the method in this study can reach the current state-of-the-art on different datasets. If accepted, the dataset will be publicly available at https://gitee.com/wust30405/lpdataset.