Miracle-dz/UniFAR-FTUs huggingface dataset:
Solubilization of Polycyclic Aromatic Hydrocarbons in Bentonite/Aqueous Systems by Nonionic Surfactants

Enhanced solubilization of phenanthrene and pyrene from bentonite in micellar solutions of Brij 30 and Triton X-100 has been studied. Experiments in batch bentonite/aqueous systems were conducted to investigate the effectiveness of solubilization of phenanthrene and pyrene. The results obtained in the present study are as follows:The solubilization of pyrene from bentonite in surfactant solutions was very low because of low water solubility and strong sorption onto bentonite of pyrene. Meanwhile, the solubilization of phenanthrene increased at bulk surfactant concentrations greater than the surfactant critical micelle concentration and was in the order of Triton X-100 > Brij 30. The solubilization of phenanthrene was also analyzed based on the partitioning of phenanthrene between bentonite, nonionic surfactant micelles and aqueous solution surrounding the micelles.
Study of Multi-Model Ensemble High-Resolution Projections of Major Climatic Variables Over the Indus River Basin and Pakistan

Water resources managers and policy-makers need reliable projections of hydro-climatic conditions to develop sound water management policies. Global Climate Models (GCMs) are the primary basis for projecting howthe climate may change over the coming decades. However, GCMs have low spatial resolution and inherentbiases that limit their direct utility for understanding localized climate change impacts. These limitations are particularly pronounced in mountainous areas, where the terrain exhibits variations at scales much finer than the GCM grid spacing. The main goal of this study is to downscale precipitation and mean temperature simulations from an ensemble of 10 GCMs that participated in the Coupled Model Inter-comparison ProjectPhase-5 (CMIP5) under two Representative Concentration Pathways – RCP4.5 and RCP8.5. The simulations were bias corrected using quantile mapping and downscaled to a 30 arc second spatial resolution (approximately 1 km) through using the delta method over the Indus River Basin and Pakistan for 2040-2070. The GCM processing was carried out using the Global Climate Data (GCD) package. The results show that for all seasons and most of the Indus River Basin (IRB) and Pakistan, future precipitation will be highly uncertain except UIB wherein mean annual precipitation is projected to increase by 8% under RCP 4.5 and 14% under RCP 8.5. However, the models are highly confident about increase in the temperature for this region. Relative to the baseline period (1960-1990), the annual mean temperature in the IRB is projected to increase by 2°C under RCP 4.5 and 2.6°C under RCP 8.5 for 2040-2070.
Investigation on morphology of polymer structure in polymer-stabilized blue phase

ABSTRACT Polymer stabilization effect to increase the thermal stability of blue phases (BPs) for potential application in flat-panel display has been studied in detail though directly observing the morphology of the polymer network on the substrate formed under different experimental conditions during the polymerization process. The tiny and dense polymer network, in which the diameter of the polymer chain is not greater than 250 nm, is useful for stabilizing the BPI structure. Moreover, these experimental results can be explained by the free-energy density of BPI, where its temperature range depends inversely on the square of the polymer-chain diameter. In terms of the experimental results shown in this study, we can conclude an optimal photo-polymerization process for a wide-temperature-range polymer-stabilized BP. Graphical Abstract
Barcode Detection and Classification using SSD (Single Shot Multibox Detector) Deep Learning Algorithm

Barcodes have become ubiquitous in this era, as they are widely used in many applications. With the rapid usage of barcodes, thus fast and accurate detecting is essential. We introduce deep learning detector based on SSD (Single Shot Multibox Detector) which is expected to be fast and accurate. This system is expected to be capable of detecting both the barcodes i.e. 1D and 2D barcodes. The detector can also find the rotation of both the barcodes using angle prediction network. The proposed approach is one of the deep learning algorithm which will use a single convolutional neural network and expected to perform well as compared to other detectors such as YOLO (You Only Look Once) in both speed and accuracy.
Characterization of 1q Duplication by Array Comparative Genomic Hybridization in Acute Myeloid Leukemia Patients with t(8;16)(p11.2;p13.3)

Background: Acute myeloid leukemia (AML) is a complex hematological disease characterized by genetic and clinical heterogeneity. The identification and understanding of chromosomal abnormalities are important for the diagnosis and management of AML patients. Compared to recurrent chromosomal translocations in AML, t(8;16)(p11.2;p13.3) can be found in any age group, but is very rare and typically associated with poor prognosis. Methods: Cytogenetic studies were performed among 1,824 AML patients from our oncology database in the last 20 years by karyotype analysis. Fluorescence in situ hybridization (FISH) was used to further confirm the chromosomal translocation fusion. Array comparative genome hybridization (aCGH) was carried out to characterize the additional chromosomal segments in patients with t(8;16)(p11.2;p13.3). Results: Three patients with t(8;16)(p11.2;p13.3) were identified. One patient was pure t(8;16)(p11.2;p13.3), and the other two had an additional chromosomal anomaly of 1q duplication. Interestingly, the molecular size and position of this 1q duplication were similar in both patients, showing as 46.7 Mb and 49.9 Mb, respectively. Conclusion: 1q duplication is a recurrent event in AML patients with t(8;16)(p11.2;p13.3), indicating it could also play a role of an unfavorable prognostic factor.
Thermodynamic Control on Biogeography and Functioning of Rare-Biosphere Propionate Syntrophs in Paddy Field Soils

Background Global biogeochemical processes are not only gauged by dominant taxa of soil microbiome but also depend on the critical functions of “rare biosphere” members. Here we evaluated the biogeographical pattern of “rare biosphere” propionate-oxidizing syntrophs in 113 paddy soil samples collected across eastern China. Results The relative abundance, functioning capacity and growth potential of propionate-oxidizing syntrophs were analyzed to provide a panoramic view of syntroph biogeographical distribution at the continental scale. The relative abundances of four syntroph genera, Syntrophobacter, Pelotomaculum, Smithella and Syntrophomonas were significantly greater at the warm low latitudes than at the cool high latitudes. Correspondingly, the functioning potential of propionate degradation was greater in the low latitude soils compared with the high latitude soils. The slow rate of propionate degradation in high latitude soils resulted in a greater fold change in increase of the relative abundance, probably due to the growth rate-yield tradeoff relationship. The mean annual temperature (MAT) is the most important factor shaping the biogeographical pattern of propionate-oxidizing syntrophs, with the next factor to be the total S content (TS) in soil. Conclusions We suggest that the effect of MAT is related to the Gibbs free energy change, in which the endergonic tension of propionate oxidation is leveraged with the increase of MAT. The TS effect is likely due to that some propionate syntrophs can facultatively perform sulfate respiration.
Average Transmit Power Analysis and User Clustering Design of Downlink Multi-Antenna NOMA with Matched Filter Beamforming

Non-orthogonal multiple access (NOMA) in power domain is considered as a candidate technique in the next generation mobile networks as it can improve the spectral efficiency, the number of connected devices and user fairness compared to traditional orthogonal multiple access (OMA) techniques. In this thesis we analyze the average transmit power in downlink multiantenna NOMA systems with two-user clusters where the signal-to-interferenceplus-noise-ratios (SINRs) for all users are guaranteed. For systems with a single cluster, a modified NOMA scheme based on the threshold on the alignment of channel directions is proposed to save the transmit power and theoretical analysis in terms of the average transmit power is conducted to demonstrate the superiority of our proposed scheme compared to the original NOMA scheme. To further improve the alignment-based NOMA scheme, a hybrid of NOMA and multi-user beamforming is also proposed. In addition, for systems with more than two users, user clustering algorithms are developed to group the users into multiple two-user clusters with respect to the minimization of the total transmit power. Simulation results validate the correctness of our theoretical results and demonstrate the performance improvement brought by the clustering algorithms.
A Novel Risk Scoring Tool to Predict Saphenous Vein Graft Occlusion in patients with type 2 diabetes mellitus after Cardiac Artery Bypass Graft Surgery

Background: Coronary artery bypass grafting (CABG) success is reduced by graft occlusion. Patients with type 2 diabetes mellitus(T2DM) are more likely to develop graft occlusion. Understanding factors associated with graft occlusion may improve T2DM patient outcomes. The aim of this study was to develop a predictive risk score for saphenous vein graft (SVG) occlusion in T2DM patients after CABG.Methods: This retrospective cohort study enrolled 3716 CABG patients with T2DM from January 2012 to March 2013. The development cohort included 2477 patients and the validation cohort included 1239 patients. The baseline clinical data at index CABG was analyzed for their independent impact on graft occlusion in our study using Cox proportional hazards regression. The predictive risk scoring tool was weighted by beta coefficients from the final model. Concordance (c)-statistics and comparison of the predicted and observed probabilities of predicted risk were used for discrimination and calibration.Results: A total of 959 (25.8%) out of 3716 patients developed at least one SVG occlusion. Significant risk factors for occlusion were male sex, estimated glomerular filtration rate<90, smoking (currently), hyperuricemia, dyslipidemia, prior percutaneous coronary intervention (PCI), a rising number of lesion vessels, and SVG. On-pump surgery, and the use of angiotensin-converting enzyme inhibitors (ACEI)/angiotensin receptor blockers (ARB) and calcium channel blockers (CCB) were protective factors. The risk scoring tool with 11 variables was developed from the derivation cohort, which delineated each patient into risk quartiles. The c-statistic for this model was 0.71 in the validation cohort.Conclusions: An easy-to-use risk scoring tool that used common clinical variables was developed and validated. The scoring tool accurately estimated the risk of late SVG occlusion in T2DM patients after CABG.
BIOMECHANICAL ASSESSMENT OF PERI-IMPLANT BONE TISSUE: EFFECT OF MATERIAL MODEL HOMOGENEITY ON STRAIN DISTRIBUTION IN MANDIBLE

: The aim of this study was to compare mechanical performances of bone-implant interaction when different material models were used in the computational modeling process. Specifically, homogeneous and non-homogeneous material models of mandibular bone tissue were scrutinized. Peri-implant region of the mandible was analyzed using three variants of cancellous bone material model. The first two variants were based on the assumption of perfect material homogeneity (with various elastic constants), the third one was assumed to be nonhomogeneous and based on CT image data. The results indicated that the strain intensities in cancellous bone tissue were concentrated in the region of implant apex regardless of the variant. The character of strains in the peri-implant region (up to 0.1 mm from the implant) is influenced dominantly by the geometry of the selected dental implant than by the used material model variant. To perform more credible analysis of local strains in the peri-implant region, it is preferable to adopt material model based on CT images.
The Rumen Microbiome in Dry Dairy Cows Reveals the Specific Bacteriome Contributing to Various Physiological Roles and Phenotypes

Background Most microbiome studies of dairy cows have investigated the compositions and functions of rumen microbial communities in lactating dairy cows. The importance of the relationships among hosts, microbiota, diet composition, and milk production remains unknown in dry dairy cows. Thus, in the present study, the composition of the rumen microbiome in cows from three dairy farms was investigated to identify core bacteria contributing to various physiological roles during rumen fermentation in dry dairy cows. Results The results indicated that ruminal fluid in dry dairy cows from different regional farms had core rumen microbiota that could be clearly distinguished from that of cows of the other farms. Further identification of key microorganisms associated with each farm revealed that Prevotella, Methanobrevibacter, Pseudobutyrivibrio, Ruminococcus, Bacteroides, and Streptococcus were major contributors. Spearmen’s correlation indicated that the abundance of genera such as Prevotella and Ruminococcus in dry dairy cows could indicate milk yield in the previous lactating period. Functional pathway analysis of the rumen bacterial communities demonstrated that amino acid metabolism and carbohydrate metabolism were the major pathways. Conclusions Our findings provide knowledge of the composition and predicted functions of rumen microbiota in dry dairy cows from regional farms, which underscores the importance of the relationships among hosts, microbiota, diet composition, and milk production.
Cricket Team Prediction Using Machine Learning Techniques

Player selection is an essential task for any sport and similarly for the game of cricket as well. The players’ performance varies on various factors. The team management and the captain selects eleven players for each match from the entire squad. Review of different attributes and players’ results is considered to pick the best eleven players. By scoring runs each batsman contributes and each bowler contributes by taking wickets and awarding minimum runs. This project aims to predict team success based on the player's past records. Acquisition of the players 'results individually and their contribution to the team i.e. Best batting performance among the batsmen available, best bowling performance among the available bowlers and best all-rounder performance will be a great help in selecting the eleven players. We used the Random Forest Algorithm and Decision Tree classifiers to produce the problem's prediction models. It was found that the Random Forest classifier is the most reliable for the problems proposed.
Misspecification Analysis of a Gamma- with an Inverse Gaussian-based Degradation Model in the presence of Measurement Error

Gamma-and inverse Gaussian-based degradation models are natural choices for modelling monotonic degradation phenomena. Although not equivalent, in many applications these models are treated to each other. This situation makes the model misspecification problem interesting and important, especially when data are affected by measurement error, because from this kind of data it is not possible to check whether the selected model is able to fit the hidden degradation process or not. Motivated by the above considerations, in the paper we have carried out a small (i.e., very preliminary) Monte Carlo study to evaluate the effect produced by a misspecification of a gamma-with an inverse Gaussian-based perturbed degradation process. The study is performed considering as reference model a perturbed Gamma process recently proposed in the literature. The competing model is new and has been constructed with the aim of facilitating the misspecification study. In fact, it is an inverse Gaussian-based perturbed degradation model that share the same parameters and the same error term of the reference model. By virtue of the adopted setup, the mean and variance functions of the considered hidden Inverse Gaussian and Gamma processes have identical functional forms. The measurement error is modelled by a 3-parameter inverse gamma random variable, which depends in stochastic sense on the hidden degradation level. Model parameters are estimated by adopting the maximum likelihood method, via a sequential Monte Carlo approach. The fitting ability of the considered competing models is evaluated by using the Akaike information criterion. The effect of the misspecification is highlighted on the maximum likelihood estimate of mean remaining useful life. The impact of the presence of measurement error on the severity of the misspecification problem is also evaluated by comparing the obtained results with those attained by performing the same misspecification analysis in the absence of measurement error.
Microdochium albescens may affect the physiological quality of irrigated rice cultivar seeds

ABSTRACT: Knowledge of the effect of the seedborne inoculum is important for knowing the level of tolerance of the pathogen by the seed. This research evaluated the effect of the incidence of the fungus Microdochium albescens on the physiological quality of the seeds of different cultivars of irrigated rice. The study was carried out in the seed testing laboratory (STL), phytopathology laboratory and in greenhouse, located at the Center of Agroveterinary Sciences of the Santa Catarina State University, Lages, SC, Brazil. Seeds from six irrigated rice cultivars produced in the Alto Vale do Itajaí Region in the 2016/17 harvest, were used. The lots were submitted to the seed health test, identifying four lots per cultivar with a natural incidence of M. albescens, with two lots of each cultivar with an incidence greater than 40% and two lots equal or less than 40%, totaling 24 seed lots. The following evaluations were carried out on the lots: germination, accelerated aging test, emergence in a greenhouse at 14 days, emergence speed index (ESI), emergence speed (ES), shoot length, root length and fresh and dry mass. There was a significant interaction between cultivar and level of incidence only in the variables germination, vigor and root length. Fresh mass, shoot length and ESI were not affected, regardless of cultivar and incidence of fungus in the seed. The irrigated rice cultivars SCS118 Marquês and SCSBRS Tio Taka are susceptible to a high incidence (> 40%) of the fungus M. allbescens.
A GPU-Based Radio Wave Propagation Prediction With Progressive Processing on Point Cloud

Point cloud data (PCD) can record a high-resolution model of the environment much more efficiently than the conventional geometrical mesh. This feature makes PCD suitable for the radio channel prediction of a new environment, especially for the millimeter-wave (mmWave). Since the multiple propagations and visibility computation using PCD are time consuming, progressive processing on PCD is introduced to make the prediction compatible with GPU-based frameworks such as OptiX and CUDA. Compared with the surface reconstruction from PCD, progressive data from the processing reserves more domain features such as diffraction wedge and the label of planar or nonplanar points. The numerical result of an outdoor environment shows that the proposed method has a close agreement with measurement, as well as two impressive speedups, 49.8 for the ray tracing and field calculation and 18.8 for the total prediction, compared with the original method using PCD.
Genome-wide association analysis uncovers candidate genes for forage quality traits in Brassica napus stems

Background Brassica napus (rapeseed) is an important oilseed crop and its leaves and stems can also be used as animal feed. Lignocellulose content is closely related to the nutritional quality and palatability of animal feed. However, quantitative trait loci (QTLs) associated with acid detergent fiber (ADF) and neutral detergent fiber (NDF) contents in rapeseed stems have not yet been mapped. Results In this study, we used 494 B. napus accessions to perform genome-wide association studies (GWAS) of ADF and NDF contents. Ninety-two single-nucleotide polymorphisms (SNP) and 35 simple-sequence repeat (SSR) loci were significantly correlated with ADF and NDF contents, respectively, and six genetic loci associated with ADF and NDF contents were detected using both types of markers. We identified three candidate genes on chromosome A05 related to ADF content, including genes encoding chitinase-like protein 2 (CTL2) and two trichome birefringence-like 41 s (TBL41s). Seven genes on chromosomes A03 and A04 were related to NDF content, including genes encoding glycosyl hydrolase (GH), reversibly glycosylated polypeptide 1 (RGP), irregular xylem 12 (IRX12), trichome birefringence-like 34 (TBL34), galacturonosyltransferase 7 (GAUT7), cytokinesis defective 1 (CYT1), and LOB domain-containing protein 15 (LBD15). These candidate genes encode factors that likely participate in secondary cell wall formation and lignocellulose biosynthesis. Conclusions These findings lay the foundation for identifying genes related to forage quality traits and improving the efficiency of forage utilization in rapeseed, which will be beneficial for breeding new varieties for high-quality forage with low lignocellulose content.
A photo- and thermo-responsive star-shaped diblock copolymer with a porphyrin core prepared via consecutive ATRPs

A star-shaped and diblock copolymer poly(6-[4-(4-methoxyphenylazo)phenoxy]hexylmethacrylate)s-b-poly(N-isopropylacrylamide)s with a zinc-porphyrin core (PAzo-b-PNIPAM) is synthesized via consecutive atom transfer radical polymerizations (ATRPs). The synthesis involves the preparation of the intermediate poly(6-[4-(4-methoxyphenylazo)phenoxy]hexyl methacrylate) with a zinc-porphyrin core (por-PAzo) via ATRP, and then por-PAzo is used as a macroinitiator to polymerize N-isopropylacrylamide (NIPAM) via ATRP to gain PAzo-b-PNIPAM. The structures of the target products are characterized by FT-IR, 1H NMR and UV-vis spectra, and the polydispersity index (PDI) indicates that the molecular weight distribution is narrow and the polymerization is well controlled. Furthermore, the photo- and thermo-responsive properties are also investigated in detail, which demonstrate that the star-shaped diblock copolymer PAzo-b-PNIPAM has a potential application in targeted photodynamic therapy and photo-electro informational storage.
Interlayer Structure and Dynamics of HDTMA(+)-Intercalated Rectorite with and without Water: A Molecular Dynamics Study

Rectorite is a special kind of clay mineral, consisting of illite layer and smectite layer in a regular order. In this study, we employ classical molecular dynamics simulations to study the microscopic interlayer properties of HDTMA+ (hexadecyl trimethyl ammonium)-intercalated rectorites with and without water at different HDTMA+ loading levels. The simulation results show that as the loading level increases, monolayer, bilayer, transition, and trilayer configurations of HDTMA+ occur in succession. The different layer charge characteristics between illite sheet and smectite sheet lead to special interlayer distributions of HDTMA+. In the systems without water, the headgroups of HDTMA+ and Na+ are controlled by six-membered rings of clay surface. With water addition, water molecules show the highest mobility among the interlayer species. However, HDTMA headgroups are still controlled by clay surfaces mainly with low mobility. At the same time, most of Na+ cations escape from surfaces because of the attract.