Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective Coflow Scheduling in Hybrid Circuit and Packet Switching Networks

Hybrid circuit and packet switching networks combine optical circuit switching with electrical packet switching technologies. It can provide higher bandwidth at a lower cost than pure optical or electrical networks, which can meet different performance goals. Coflow is a superior traffic abstraction that captures applications' networking semantics. To improve the transmission performance at the application level, we focus on reducing coflow completion time (CCT). Unlike the problem of minimizing CCT in traditional networks, hybrid network provides larger coflow scheduling space about through which network the internal flows are transmitted, in addition to priorities and bandwidth allocations of coflows. To solve this problem, this paper proposes an Online Network State based coflow scheduling algorithm (ONS) in hybrid switching networks, which minimizes CCT by combining coflow priorities and internal flow path planning, fully considering different switches' characteristic. Extensive simulations prove that ONS has smaller CCT and higher throughput under different load levels.
Super-Resolution Diffusion Model for Accelerated MRI Reconstruction

MRI reconstruction is a process to generate high-quality images from the raw data obtained during magnetic resonance imaging. Diffusion models, a class of generative models, have become a popular method for MRI Reconstruction due to their ability to generate high quality images. Diffusion models work by adding Gaussian noise to the original image and training a network to remove the noise. Diffusion models can continue to generate high quality images even with a different type of noise added to the original image. In this study we combine a resolution decreasing operator with noise scheduling used by regular diffusion models, ResDiff to perform MRI Reconstruction. One of the biggest drawbacks of Diffusion models is the amount of time taken to generate images. Down-sampling images to a lower resolution requires fewer steps allowing ResDiff to achieve competitive results in far less time.
Digital ophthalmology in Scotland: benefits to patient care and education

: Tackling visual impairment remains an important public health issue. Due to limited resources and the increasing demand on hospital eye services (HES), delivery of quality eye care within the community is essential. Training of clinical ophthalmic specialists and allied health-care professionals in the detection and management of common eye conditions can thus help to reduce the burden of eye disease and improve prognostic outcomes. Digital imaging has become a useful tool in facilitating eye-care delivery in both the community and hospital setting. In the last decade, the advent of electronic image exchange via a centralized referral unit in Scotland has revolutionized screening for ophthalmic disease, referrals, and shared care between community and HES clinicians. A government-led initiative known as the Scottish Eyecare Integration Project introduced electronic transfer of digital images within referrals from community optometrists to HES, which greatly reduced outpatient waiting times and improved patient satisfaction. The catalogue of live clinical information and digital images that resulted from the project led to the creation of a virtual learning platform through the University of Edinburgh. Participating professionals involved in eye care have interactive discussions about common eye conditions by sharing digital images of cases and investigations on a global online platform. This has received worldwide attention and inspired the creation of other university courses, e-learning platforms in eye-health education, and shared-care schemes in the screening of eye disease. We show that digital ophthalmology plays a vital role in the integration of community and HES partnership in delivery of patient care and in facilitating eye-health education to a global audience.
Estimating Winds and Waves from Synthetic Aperture Radar under Typhoon Conditions

Abstract : The long-term goal of this project is to develop a typhoon Synthetic Aperture Radar (SAR) wind algorithm for C-Band that can be modified to be applied to X-Band and L-Band SAR data. We begin with a multi-pronged approach that will include up to three different SAR wind and wave algorithms to be validated with in-situ observations and accurate model predictions during typical hurricane and typhoon conditions. The next step will be to modify these algorithms to allow both SAR data from L-band and X-band systems. The specific scientific objectives of this study are as follows: (1) to determine how accurately C-band wind algorithms can measure the wind vector field in tropical cyclones, such as hurricanes and typhoons; (2) to determine how accurately C-band wave algorithms can measure the properties of directional wave field in tropical cyclones, such as hurricanes and typhoons; (3) to examine how these wind and wave algorithms could be extended to perform for SAR data from L-band and X-band systems; (4) to determine a test data set of ground truth based on in-situ and airborne observations as well as highly accurate model predictions; and (5) to develop performance metrics that provides error statistics. The new typhoon wind model and complementary sea state and waves algorithm will provide unprecedented information about the intensity and structure of typhoons and hurricanes.
Prognostic Significance of Serum Vitamin D Levels in Egyptian Females with Breast Cancer

Objective: To determine the frequency and prognostic significance of vitamin D deficiency in Egyptian women with breast cancer (BC). Methods: This prospective study included 50 women with primary invasive, non-metastatic BC. The serum level of 25-hydroxy vitamin D [25(OH)D was measured by ELISA at diagnosis, before any cancer treatment. Vitamin D deficiency was defined as 25(OH) D<20 ng/mL. Patients were followed up for a median of 30 months (range: 18-48). Results: The median level of 25(OH)D was 29.0 ng/mL (range: 10.0-55.0 ng/mL). Fifteen patients (30%) had vitamin D deficiency, which was positively associated with larger tumor size (p < 0.001), higher grade (p = 0.014), advanced stage (p = 0.001), lymph node positivity (p = 0.012), and HER2/neureceptor expression (p = 0.002). It was also linked with worse overall survival (OS) and disease free survival (DFS) (p = 0.026, and p = 0.004, respectively). On multivariate analysis, DFS was independently affected by vitamin D deficiency with an HR of 2.8 (95%CI: 1.6-7.0, p = 0.022) and advanced stage, i.e. stage II had worse survival compared to stage I with an HR of 4.8 (95%CI:1.1-21.7, p = 0.042). Conclusion: Vitamin D deficiency had a negative effect on overall and disease-free survival in our breast cancer cases, being related to tumor size, stage, grade, nodal status and HER2/neu receptor expression.
Prognostic Value of Serum Biomarkers in Patients with Idiopathic Pulmonary Fibrosis in Relation to Disease Progression

Background: The aim of this present study was to determine serum biomarker levels and their correlation with respiratory function and the clinical course of patients with idiopathic pulmonary fibrosis (IPF). Materials and Methods: This study included 72 IPF patients, according to the ATS/ERS criteria, in whom antifibrotic treatment was initiated. Blood samples were taken, and serum biomarkers, such as KL-6, SP-D, CCL18, CXCL13, VEGF-A, IL-8, IGFBP-1, IGFBP-2, IGFBP-7 and ICAM-1 were measured using ELISA methodology. Pulmonary function tests (FVC, TLC, DLCO-% pred) were determined at baseline and after 12 and 24 months and analyzed in correlation with the biomarkers. Results: The majority of patients (mean age 72 ± 6 years) were men (83%). The FVC and DLCO values at the 12-month follow-up were found to be statistically decreased in deceased patients (p < 0.05). The SP-D (p < 0.001) and the IGFBP-1 (p = 0.021) levels were found to be increased at the 1-year follow-up in deceased patients, and similarly, the SP-D (p = 0.005) and ICAM-1 (p = 0.043) levels at the 2-year follow-up. A chi-square test revealed that 70% of the category IV GAP index was found with cut-off elevated levels of a biomarker combination (KL-6, SP-D, VEGF-A) from the ROC curve analysis (p < 0.05). Conclusion: This study provides evidence, for the first time in a Greek population, of the possibility of using a combination of KL-6, SP-D, and VEGF-A serum levels along with the GAP index.
Optimized modeling of anti-breast cancer drug candidates based on machine learning

The research data were obtained from the information of ER antagonists provided by the D problem of Huawei Cup. We screened the molecular descriptor variables to construct quantitative prediction models for the biological activity of the compounds against ER, and the classification prediction models for Caco-2, CYP3A4, hERG, HOB, and MN of the compounds, respectively. We also determined the optimal range of molecular descriptors that could lead to compounds with better bioactivity for ER inhibition and better ADMET properties. In turn, we provide data analysis and predictive models for breast cancer research. In the first step, we used the feature es election method to remove redundant variables, and applied random forest to rank the variable sinterms of relevance to lterout7 molecular descriptor variables: MDEC-23, max HsOH, minHBa, min HsOH, minHBint4, C1SP2 and nHBAcc. In the second step, the pIC50 values in the training set were used as dependent variables and the seven molecular descriptor variables were used as independent variables, and extremely randomized trees were applied to construct the non-linear regression quantitative prediction model between compounds and ER bioactivity. In the third step, we used different integration methods to construct classification prediction models for Caco-2, CYP3A4, hERG, HOB, and MN, respectively. In the fourth step, after eliminating the 1974 compounds with the sum of ADMET indicators less than 3, we inverse solve the prediction model using the particle swarm optimization algorithm to obtain the maximum value of pIC50 and the optimal solution for each molecular descriptor variable. pIC50 has a maximum value of 8.9055, and the molecular descriptors C1SP, minHBa, min HBint4, minHsOH, maxHsOH, nHBAcc, MDEC, nHBAcc, and MDEC-23 are 0, - 7.75978169, -3.42842314, 9.46164889, 0.51061438, 2.63674280, and 80, respectively.
Heterometallic ZnHoMOF as a Dual-Responsive Luminescence Sensor for Efficient Detection of Hippuric Acid Biomarker and Nitrofuran Antibiotics

Developing efficient and sensitive MOF-based luminescence sensors for bioactive molecule detection is of great significance and remains a challenge. Benefiting from favorable chemical and thermal stability, as well as excellent luminescence performance, a porous Zn(II)Ho(III) heterometallic–organic framework (ZnHoMOF) was selected here as a bifunctional luminescence sensor for the early diagnosis of a toluene exposure biomarker of hippuric acid (HA) through “turn-on” luminescence enhancing response and the daily monitoring of NFT/NFZ antibiotics through “turn-off” quenching effects in aqueous media with high sensitivity, acceptable selectivity, good anti-interference, exceptional recyclability performance, and low detection limits (LODs) of 0.7 ppm for HA, 0.04 ppm for NFT, and 0.05 ppm for NFZ. Moreover, the developed sensor was employed to quantify HA in diluted urine samples and NFT/NFZ in natural river water with satisfactory results. In addition, the sensing mechanisms of ZnHoMOF as a dual-response chemosensor in efficient detection of HA and NFT/NFZ antibiotics were conducted from the view of photo-induced electron transfer (PET), as well as inner filter effects (IFEs), with the help of time-dependent density functional theory (TD-DFT) and spectral overlap experiments.
Characterization of the Sensory Properties and Quality Components of Huangjin Green Tea Based on Molecular Sensory-Omics

Huangjin green tea (HJC) is one of the most famous regional green teas in China, and has gained attention for its unique flavor. Research on HJC has focused mainly on the synthesis of L-theanine, with fewer studies concentrating on sensory characteristics. In this study, molecular sensory science techniques, including color analysis, gas chromatography–ion mobility spectrometry, and E-tongue, were used to characterize the sensory properties of HJC, with Fuding Dabai and Anji Baicha teas used as conventional and high amino acid controls, respectively. The sensory characteristics and main quality components of HJC lie somewhere between these two other teas, and somewhat closer to the conventional control. They were difficult to distinguish by color, but significant differences exist in terms of volatile organic compounds (VOCs), E-tongue values on bitterness and astringency, and their contents of major taste components. VOCs such as (E)-2-octenal, linalool, ethyl acrylate, ethyl acetate, and 2-methyl-3-furanethiol were found to be the main differential components that contributed to aroma, significantly influencing the tender chestnut aroma of HJC. Free amino acids, tea polyphenols, and ester catechins were the main differential components responsible for taste, and its harmonious phenol-to-ammonia ratio was found to affect the fresh, mellow, heavy, and brisk taste of HJC.
Body composition , energy expenditure and physical activity Body composition reference charts for UK infants and children aged 6 weeks to 5 years based on measurement of total body water by isotope dilution

Background Until recently, pediatric body composition reference data were very limited, hindering interpretation of measurements. In the last decade, such data emerged for several techniques for children ≥ 5 years, but equivalent data for younger age groups remain lacking, due to their poor compliance with most techniques. Objectives To provide reference data for use in clinical practice and research from 6 weeks to 5 years, that are based on measurements of total body water (TBW) by isotope dilution. Design The data on anthropometry and TBW were available from studies of 463 infants and children aged 6 weeks to 7 years, conducted between 1988 and 2010. Both breast-fed and formula-fed infants were included. TBW was measured by Hor O-labeled water, and converted to fat-free mass (FFM) using published hydration coefficients. Reference charts and SD scores (SDS) were constructed for FFM, fat mass (FM), FFM index and FM index for each sex, using the lambda-musigma method. Results Both sexes were significantly heavier and longer than UK 1990 reference data (p < 0.01), but did not differ in body mass index SDS. Breast-fed infants were longer than formula-fed infants but did not differ in body composition. Conclusions These reference data will enhance the ability of clinicians to assess and monitor body composition and FFM/ FM accretion in clinical practice in younger age groups. Total body water can be measured in most patients, though abnormalities of hydration must be addressed. However, the centiles do not overlap exactly with those published for older age groups, limiting comparability between younger and older children.
To TTP or not to TTP?: Exploiting TTPs to Improve ML-based Malware Detection

In the last decade, machine learning (ML) methods have increasingly been applied to the task of malware detection. While these approaches have surely demonstrated their effectiveness, they still present limitations, some of which are a consequence of their purely data-driven nature. In this paper, we show how the MITRE ATT&CK framework of tactics, techniques, and procedures (TTPs) can be exploited to overcome such limitations and improve their ability to detect malware on networks. We conduct an extensive experimental analysis, testing 7 ML models on 5 large datasets comprising over 37 million flows. Our results clearly demonstrate that adding TTP-based features for training the models robustly improves their performance. Our models outperform the standard ones 922 times out of a total of 952, (i.e., 96.8% of the time), with the biggest improvements (up to 84.9% in terms of FPR) being observed in situations designed to be challenging for ML models.
Ginseng Saponin Rb1 Attenuates Cigarette Smoke Exposure-Induced Inflammation, Apoptosis and Oxidative Stress via Activating Nrf2 and Inhibiting NF-κB Signaling Pathways

Objective Cigarette smoke exposure is one of the major risk factors for the development of chronic obstructive pulmonary disease (COPD). Ginseng saponin Rb1 (Rb1) is a natural extract from ginseng root with anti-inflammatory and anti-oxidant effects. However, the underlying mechanism of the Rb1 in COPD remains unknown. Therefore, we sought to explore the role of Rb1 in cigarette smoke-induced damage and to reveal the potential mechanism. Methods The cell viability and lactose dehydrogenase (LDH) activity were analyzed using cell counting kit-8 (CCK-8) and LDH release assays. We further investigated the inflammation, apoptosis and oxidative stress markers and analyzed the nuclear factor-kappa B (NF-κB) and nuclear factor erythroid-2-related factor 2 (Nrf2) pathways in BEAS-2B cells and COPD rat model following cigarette smoke extract (CSE) exposure. Results Our results showed that CSE promoted inflammation, apoptosis and oxidative stress in BEAS-2B cells. Rb1 suppressed the inflammatory response by inhibiting expression of pro-inflammatory cytokines such as tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and IL-1β and inhibiting the NF-κB signaling pathway. Rb1 possessed the ability to hinder cell apoptosis induced by CSE. In addition, Rb1 concurrently reduced CSE-induced oxidative reactions and promoted Nrf2 translocation to nucleus. For in vivo study, Rb1 treatment alleviated CSE-induced lung injury, apoptosis, reactive oxygen species (ROS) release and inflammatory reactions. Also, Rb1 treatment activated Nrf2 signaling and inactivated NF-κB signaling in COPD rats. Conclusion Rb1 attenuates CSE-induced inflammation, apoptosis and oxidative stress by suppressing NF-κB and activating Nrf2 signaling pathways, which provides novel insights into the mechanism underlying CSE-induced COPD.
Optimal Walks in Contact Sequence Temporal Graphs with No Zero Duration Cycle

We develop an algorithm to find walks in contact sequence temporal graphs that have no cycle whose duration is zero. These walks minimize any specified linear combination of optimization criteria such as arrival time, travel duration, hops, and cost. The algorithm also accommodates waiting time constraints. When min and max waiting time constraints are specified, the complexity of our algorithm is $O(\vert V\vert +\vert E\vert\delta)$, where $\vert V\vert$ is the number of vertices, $\vert E\vert$ is the number of edges, and $\delta$ is the maximum out-degree of a vertex in the contact sequence temporal graph. When there are no maximum waiting time constraints, the complexity of our algorithm is $O(\vert V\vert +\vert E\vert)$. On the test data used by Bentert et al., our optimal walks algorithm provides a speedup of up to 77 over the algorithm of Bentert et al. [1] and a memory reduction of up to 3.2.
Laboratory Performance Evaluation of a Low-Cost Electrochemical Formaldehyde Sensor

Formaldehyde is a known human carcinogen and an important indoor and outdoor air pollutant. However, current strategies for formaldehyde measurement, such as chromatographic and optical techniques, are expensive and labor intensive. Low-cost gas sensors have been emerging to provide effective measurement of air pollutants. In this study, we evaluated eight low-cost electrochemical formaldehyde sensors (SFA30, Sensirion®, Staefa, Switzerland) in the laboratory with a broadband cavity-enhanced absorption spectroscopy as the reference instrument. As a group, the sensors exhibited good linearity of response (R2 > 0.95), low limit of detection (11.3 ± 2.07 ppb), good accuracy (3.96 ± 0.33 ppb and 6.2 ± 0.3% N), acceptable repeatability (3.46% averaged coefficient of variation), reasonably fast response (131–439 s) and moderate inter-sensor variability (0.551 intraclass correlation coefficient) over the formaldehyde concentration range of 0–76 ppb. We also systematically investigated the effects of temperature and relative humidity on sensor response, and the results showed that formaldehyde concentration was the most important contributor to sensor response, followed by temperature, and relative humidity. The results suggest the feasibility of using this low-cost electrochemical sensor to measure formaldehyde concentrations at relevant concentration ranges in indoor and outdoor environments.
CLASSIFICAÇÕES CLIMÁTICAS: VARIAÇÕES TEMPORO-ESPACIAIS E SUAS APLICAÇÕES NOS LIVROS DIDÁTICOS E COMO SUBSÍDIO AO ZONEAMENTO AGROCLIMÁTICO

This work relates climate and climatology importance on the direct relationships with human activities. It is tried to demonstrate how climate classifications varies in a temporal series, to analyze and to compare the Köppen’s climate classification from this study with climate classification from didactics books, to confront the Köppen’s climate classification against Strahler’s and to generate a first attempt of a agroclimatic zoning. Two climate classifications were chosen: Köppen’s for its wide divulgation and Thornthwaite’s for its rationality and wide use on agronomy. It was used monthly averaged data of temperature and monthly totals of precipitation, in the interval 1950-1999, in a study area including the São Paulo State and southern region of Brazil. The Köppen’s and Thornthwaite’s climate classifications varies from year to year; Thorthwaite’s detects little climate spatial variations more efficiently than Köppen’s; São Paulo state shows more variations in its climate types due to its geographical localization in a climate transition zone; using Thornthwaite’s classification there are more climatic types variability; the average climatic types are not exactly the most frequents; the representation of both classifications using all average intervals shows differences on the presentation of the climatic types; there are discrepancies among the climate classification maps of the didactic books; there are needs of revision and improvement of chapter about climate into the didactic books; the climate classifications of Köppen and Strahler have many divergences but in essence are the same and there is a need to improve the study of the water balance representation in order to a better contribution to the agroclimatic zoning.
A Novel Weighted Combination Strategy for Quasicoherent Fusion Using Multifrequency-Based Passive Bistatic Radar

This letter examines the fusion detection challenge in multifrequency-based passive bistatic radar (MF-PBR) in the presence of the signal-to-noise ratio (SNR) difference. The traditional equal-gain-combination (EGC)-based methods suffer from performance loss when the SNR difference over the multiple frequency channels is enormous. To this end, a novel weighted combination strategy is proposed for quasicoherent MF integration. Specifically, a closed-form expression of the fusion weight is derived via modifying the noncoherent integration (NCI)-based fusion weight with respect to the MF channel parameters (CPs). Moreover, for the implementation of the proposed fusion technique, an iterative algorithm for the estimation of MF CPs is also developed. Field test results verify the superiority of the proposed method in terms of detection capability.