Miracle-dz/UniFAR-FTUs huggingface dataset:
Solid Ammonium Nitrate Aerosols as Efficient Ice Nucleating Particles at Cirrus Temperatures

Recent satellite observations and high‐altitude aircraft measurements have demonstrated the presence of solid ammonium nitrate particles in the Asian monsoon upper troposphere. Most likely, these particles are formed by a heterogeneous crystallization mechanism, given that efflorescence is strongly inhibited for pure ammonium nitrate solution droplets. Crystallization can be induced by the presence of ammonium sulfate, which more easily crystallizes and serves as a heterogeneous nucleus for the crystallization of ammonium nitrate. In the present study, we have investigated this crystallization pathway for different amounts of ammonium sulfate admixed to ammonium nitrate solution droplets and measured the heterogeneous ice nucleation ability of the crystallized particles at cirrus temperatures in a cloud chamber and with a continuous flow diffusion chamber. We found that an admixture of only 0.6 mol% of ammonium sulfate was sufficient to induce the crystallization of ammonium nitrate at 223 K and 22% RHw. These almost pure, crystalline ammonium nitrate particles showed the same temperature‐dependent ice nucleation behavior as observed for other inorganic salts like ammonium sulfate and sodium chloride. At temperatures above 230 K, the crystalline ammonium nitrate particles first deliquesced and nucleated ice homogeneously at ice saturation ratios between about 1.45 and 1.50. Below 230 K, heterogeneous ice nucleation was observed to start at an ice saturation ratio as low as 1.13. The deduced ice nucleation active surface site densities were in the range from 1010–1011 m−2 at ice saturation ratios between 1.2 and 1.4, thus similar in magnitude to those of desert dust particles.
Coverage-Oriented Task Assignment for Mobile Crowdsensing

Crowdsensing tasks are usually described by certain features or attributes, and the task assignment essentially performs a matching with respect to the worker or user’s preference on these features. However, the existing matching strategy could lead to a misaligned task coverage problem, i.e., some popular tasks tend to enter workers’ candidate task lists, while some less popular tasks could be always unsuccessfully assigned. To ensure task coverage after the assignment, the system may have to increase their biding costs to reassign such tasks, which causes a high operational cost of the crowdsensing system. To address this problem, we propose to migrate certain qualified workers to the less popular tasks for increasing the task coverage and meanwhile, optimize other performance factors. By doing this, other performance factors, such as task acceptance and quality, can be comparably achieved as recent designs, while the system cost can be largely reduced. Following this idea, this article presents cTaskMat, which learns and exploits workers’ task preferences to achieve coverage-ensured task assignments. We implement the cTaskMat design and evaluate its performance using both real-world experiments and data set-driven evaluations, also with the comparison with the state-of-the-art designs.
Characterization of circular RNAs and their role in wilt stress tolerance in soybean

Soybean (Glycine max) is an important oil seed crop and widely grown legume in India as well as in the world. The yield of soybean is severely affected by Wilt disease caused by a fungus Fusarium oxysporum. Several coding and non-coding RNAs in plant cells may directly or indirectly play a role in exhibiting stress tolerance to wilt. Here, an attempt has been made to identify the role of circular RNAs (circRNAs), a type of non-coding RNAs, in wilt stress tolerance mechanism. The study also aims at identification of circRNAs that act as endogenous target mimics (eTMs) or as sponges to miRNAs that may regulate the genes involved in wilt stress tolerance. The study reveals the presence of 24 differentially expressed circRNAs (DEcircRNAs) between the transcriptomes of wilt affected and control samples out of which 18 were acted as eTMs for 10 microRNAs (miRNAs). These miRNAs in turn found to regulate 275 genes that fall under 14 Gene Ontology (GO) based functional categories. The GO analysis further shown the annotation term ‘stimulus response’ for most of the DEcircRNAs, which were found in various vital activities like polygalacturonase activity, carbohydrate metabolic process. Hence, it is predicted that the identified miRNAs got absorbed by the circRNAs that acted as sponges or eTMs and the miRNA regulated genes are likely to be freed up in cell to exhibit wilt stress tolerance mechanism in
Water Recharge of Jinan Karst Springs, Shandong, China

As the main scavenge port of groundwater in the karst water system, most of the karst springs affected by human activities experienced discharge attenuation phenomenon in the north of China. Whilst artificial replenishment measures have been taken to keep water spewing, the results are not ideal in many karst springs. This is mainly because of poor understanding about the recharging water sources. This paper used the Jinan Spring region as an example to discuss about different spring water supply sources. Based on a wide range of methods (e.g., dynamic observation of spring water level, real-time monitoring of water temperature and electrical conductivity (EC), tracer test, and frequency analysis), this study obtained several findings. First, the maximum karst-fractured water proportion that Cambrian Zhangxia Formation contribute to the Zhenzhu Spring is 57–59%, and the Heihu Spring only recharges 25–31%. Second, the proportion of fracture-karst water to the Heihu Spring from the Fengshan Formation to the Sanshanzi Formation of the Ordovician is 69–75%, while the proportion of the Tanxi spring is 15–17%. Third, the Baotu Spring and Heihu Spring mainly receive karst-fractured water from the Cambrian Zhangxia Formation and fracture-karst water from the Cambrian Fengshan Formation to the Ordovician Sanshanzi Formation. The supply sources of the Zhenzhu Spring and Tanxi Spring are more diverse, including karst-fractured water of the Cambrian Zhangxia Formation and fracture-karst water of the Cambrian Fengshan Formation to the Ordovician Sanshanzi Formation, as well as a small amount of pore water and fissure water, artificial recharge water supply. Fourth, the frequency analysis of spring water temperature indicated that the Zhenzhu Spring and Tanxi Spring are mainly in deep circulation, while the Baotu Spring and Heihu Spring are predominantly in shallow circulation. The differences in the sources of the four largest spring groups suggest that the karst water movement in Jinan has heterogeneous characteristics. The determination of the mixing ratio of the sources of spring water supplies provides a scientific basis for the protection of spring water, and the implementation of artificial recharge projects.
Vegetation cover dynamics mapping of the curonian spit national park using ALOS and SENTINEL-2 satellite imagery

This article presents the results of assessing the quantitative changes in vegetation cover areas of the Curonian Spit national park (NP) using materials from high spatial resolution multi-temporal multispectral imaging from ALOS and Sentinel-2 satellites. Automated classification algorithms Random Forest and Maximum Likelihood Estimation were tested. Based on the obtained data of automated interpretation of satellite images, ecosystem monitoring indicators of the national park (forest cover percent, share of coniferous trees in stands, share of waving (open) sands and sands covered with vegetation (fixed sands) were calculated, and dynamic maps of these indicators as well as a map of multi-temporal state of vegetation were compiled. Cartographic assessment reflects the main trends in the dynamics of the Curonian Spit NP vegetation structure over the ten-year period from 2007 to 2017: an increased percent of forest cover, increased share of vegetation-fixed sands on the side the Curonian Lagoon as a result of forest protection measures; decreased forest cover percent and increased share of waving sands on the side of the sea coast as a result of foredune destruction under the influence of wind, wave and recreational loads.
Estimation of error correction model with measurement errors

Effects of measurement errors on the analysis of error correction models (ECMs) of vector processes observed with measurement errors were studied in Hong et al. (2016. Analysis of cointegrated models with measurement errors. Journal of Statistical Computation and Simulation. 2016;86:623–639). It was found that statistically undesirable effects on the analysis attributable to endogeneity in the ECM induced by measurement errors, even in their simplest form. Therefore, we first propose a method using instrumental variables (IV) and derive the asymptotic distributions of the reduced rank estimator that eliminate the undesirable effect of endogeneity. Then, we propose a reduced rank maximum likelihood (ML) estimation using a moving-average term to deal with endogeneity. These methods yield estimators that are consistent and asymptotically unbiased. The first method with IV is simple to use computationally and yields good initial estimate for the second ML method. We investigate the effects of the measurement errors on the proposed methods through a Monte Carlo simulation study.
Prediction of
 mixed‐gas
 adsorption equilibria from pure component adsorption isotherms

Using only a single binary interaction parameter per adsorbate-adsorbate pair, the adsorption nonrandom two-liquid theory successfully correlates binary gas adsorption experimental data and predicts multicomponent gas adsorption equilibria. This work estimates the binary adsorbate-adsorbate interaction parameters from pure component isotherms and shows very promising agreement with the binary interaction parameters identified from regression of binary gas adsorption data. The results support the feasibility to predict binary and multicomponent gas adsorption equilibria from pure component isotherms for various adsorbents including silica gel, activated carbon, zeolites, and metal-organic frameworks.
Molecular Genetic Diversity in Lake Van Basin Melons (Cucumis melo L.) Based on RAPD and ISSR Markers

Turkiye Van Golu Havzasi kavunun ikincil gen merkezinde yer almaktadir. Van Golu Havzasi’ndan toplanan otuz yedi kavun genotipi arasindaki molekuler genetik cesitlilik, RAPD ve ISSR belirtecleri yardimiyla belirlenmistir. Sekiz adet RAPD ve 10 adet ISSR primerinden elde edilen toplam 121 polimorfik molekuler belirtec, kavun genotipleri arasindaki genetik iliskilerin karakterizasyonunda kullanilmistir. Grup ici genetik benzerlik katsayisinin 0.55 ve 1.00 arasinda degistigi; benzer bolgelerden toplanan genotiplerin veya akraba genotiplerin benzer kumelerde yer aldigi gozlenmistir. Van Golu Havzasi kavun genotipler arasinda genetik cesitlilik parametreleri olarak H = 0.175, I = 0.231 ve % 96.19 polimorfizm belirlenmistir.
Position Control of Maximum Wetting Plane for Building Walls with Foam Polystyrene Heat Insulator

Current theory of moisture transfer, consisting in combined transfer of vapor in sorption wetting zone and liquid in oversorption zone, is reviewed. Moisture potential F, which is the basis for overwetting protection calculation of the enclosing structure, is described. A steady-stale problem on moisture distribution along enclosing structure thickness is presented. Expression for maximum wetting plane position assessment in the enclosing structure thickness is described. It is proposed to tie origin of coordinates and exterior insulation surface. “Relative shift of the maximum wetting plane” criterion is developed for the new coordinate system. Maximum wetting plane position for the enclosing structure made of aerated concrete masonry base and expanded polystyrene insulation is calculated. One parameter varied and others were taken as constant to find out dependences between maximum wetting plane shift criterion, layers thickness, and interior micro climate parameters. It is found out that increase in base thickness, temperature or relative humidity of inside air results in maximum wetting plane shift inside the enclosure, and increase in insulation thickness results in maximum wetting plane shift outside the enclosure.
Synergistic effects of interferon γ and tumour necrosis factor α on T84 cell function

BACKGROUND Inflammatory bowel disease (IBD) is characterised by chronic intestinal inflammation and increased epithelial permeability. Both tumour necrosis factor α (TNF-α) and interferon γ (IFN-γ) have been implicated in IBD. AIMS To understand better the effects of these cytokines on epithelial cell function. METHODS T84 cells were cultured with IFN-γ and TNF-α and changes in transepithelial resistance (TER), fluorescein isothiocyanate (FITC) dextran flux, short circuit current (I sc), cystic fibrosis transmembrane conductance regulator (CFTR) protein levels, cell morphology, TNF receptor gene expression, and apoptosis were assayed. RESULTS Relative to controls, significant changes (p<0.05) occurred in cells incubated with IFN-γ for two days: TER was decreased to 20 (6.2)%, FITC–dextran flux was increased by 109 (19)-fold, cAMP and Ca dependentI sc were decreased to 51 (6.4)% and 24 (2.2)%, respectively, and CFTR levels were decreased to 47 (11)%. Cell morphology was altered but cell death was not induced. TNF receptor mRNA levels were increased. When added with IFN-γ, TNF-α accelerated IFN-γ dependent changes. Relative to controls, significant changes occurred after one day of culture with IFN-γ plus TNF-α: TER was decreased to 27 (3.5)%, FITC–dextran flux was increased by 185 (45)-fold, and cAMP and Ca dependentI sc were decreased to 66 (12)% and 35 (6.8)%, respectively. TNF-α also enhanced IFN-γ dependent changes in cell morphology but did not induce cell death. CONCLUSION IFN-γ alters T84 cell epithelial properties and TNF-α can enhance these effects, perhaps due to IFN-γ dependent increases in TNF receptor gene expression. Overall, these studies suggest that in IBD, TNF-α may have synergistic effects on IFN-γ mediated alterations of epithelial cell function.
Approaches for full coverage physical design space exploration and analysis by synthetic layout generation

At the core of Design-technology co-optimization (DTCO) processes, is the Design Space Exploration (DSE), where different design schemes and patterns are systematically analyzed and design rules and processes are co-optimized for optimal yield and performance before real products are designed. Synthetic layout generation offers a solution. With rules-based synthetic layout generation, engineers design rules to generate realistic layout they will later see in real product designs. This paper shows two approaches to generating full coverage of the design space and providing contextual layout. One approach relies on Monte Carlo methods and the other depends on combining systematic and random methods to core patterns and their contextual layout. Also, in this paper we present a hierarchical classification system that catalogs layouts based on pattern commonality. The hierarchical classification is based on a novel algorithm of creating a genealogical tree of all the patterns in the design space.
An Aggregation Method for Large-Scale Dynamic Games

It is a well known fact that many dynamic games are subject to the curse of dimensionality, limiting the ability to use them in the study of real-world problems. I propose a new method to solve complex large-scale dynamic games using aggregation as an approximate solution. I obtain two fundamental characterization results. First, approximations with small within-state variation in the primitives have a smaller maximum error bound. I provide numerical results which compare the exact errors and the bound. Second, I find that for monotone games, order preserving aggregation is a necessary condition of any optimal aggregation. I suggest using quantiles as a straightforward implementation of an order preserving aggregation architecture for industry distributions. I conclude with an illustration, by solving and estimating a stylized dynamic reputation game for the hotel industry. Simulation results show maximal errors between the exact and approximated solutions below 6%, with average errors below 1%.
GLRT Approach for Multi-Antenna-Based Spectrum Sensing Under Interference

In this letter, we consider the issue of detecting signal of interest under interference. Two multi-antenna based spectrum sensing algorithms are presented given the knowledge of interference’s statistical characteristics. The first method is designed to neutralize the impacts of interference so that the generalized likelihood ratio test (GLRT) based method for interference-free environment can be used. In the second method, an optimization problem is formulated based on the GLRT concept and an approximate solution is derived in closed-form under low signal-to-interference ratio (SIR) condition. Numerical results are provided, which demonstrate the superiority of the proposed schemes compared with existing methods.
Public knowledge, perception and communication behavior surrounding COVID-19 in Malaysia

The COVID-19 pandemic is the first to occur in an age of hyperconnectivity. This paper presents results from an online anonymous survey conducted in Malay, English, and Chinese, during the first week of the Movement Control Order in Malaysia (n=1075), which aimed to examine public knowledge, perception and communication behavior in the Malaysian society in the face of a sudden outbreak and social distancing measures. Although the level of public knowledge, risk perception and positive communication behavior surrounding COVID-19 was high, a majority of respondents reported receiving a lot of questionable information. Multinomial logistic regression further identified that responses to different items varied significantly across respondent survey language, gender, age, education level and employment status.
Collagen Microfibers Induce Blood Capillary Orientation and Open Vascular Lumen

Achieving vascularization of engineered tissues or structures is a major challenge in the field of tissue engineering. Hitherto, studies on vascularization have demonstrated limited control of vascular network geometry, such as vasculature direction and network density. An open vascular lumen is crucial to ensure that cells survive and that metabolic activity is fully functional in large‐sized tissues. Herein, a method based on high water‐dispersible collagen microfibers (CMF) to fabricate capillary orientation‐controllable 3D tissue with an open vascular lumen using a dispensing machine is reported. A twenty micrometers‐long CMF (CMF‐20) with high dispersion property are shown to be more effective for dispensing a homogenous tissue and inducing formation of an interconnected capillary network than two hundred micrometers‐long CMF (CMF‐200). One of the advantages is the prevention of shrinkage on the z‐axis of hydrogel‐based tissue which acts as a microscaffold. The gaps between the fibers can support endothelial cell migration and maturation, thus forming a larger vascular lumen compared to CMF‐free controls. Besides, shear forces produced by the dispensing process cause the collagen microfibers to align, and these microfibers guide cell alignment by integrin‐induced adhesion. The findings based on CMF to allow blood capillary alignment and vascular lumen stabilization will be an important technology in tissue engineering.
Optimal Resource Allocation of Cloud-Based Spark Applications

Nowadays, the big data paradigm is consolidating its central position in the industry, as well as in society at large. Lots of applications, across disparate domains, operate on huge amounts of data and offer great advantages both for business and research. According to analysts, cloud computing adoption is steadily increasing to support big data analyses and Spark is expected to take a prominent market position for the next decade. As big data applications gain more and more importance over time and given the dynamic nature of cloud resources, it is fundamental to develop an intelligent resource management system to provide Quality of Service guarantees to end-users. This article presents a set of run-time optimization-based resource management policies for advanced big data analytics. Users submit Spark applications characterized by a priority and by a hard or soft deadline. Optimization policies address two scenarios: i) identification of the minimum capacity to run a Spark application within the deadline; ii) re-balance of the cloud resources in case of heavy load, minimising the weighted soft deadline application tardiness. The solution relies on an initial non-linear programming model formulation and a search space exploration based on simulation-optimization procedures. Spark application execution times are estimated by relying on a gamut of techniques, including machine learning, approximated analyses, and simulation. The benefits of the approach are evaluated on Microsoft Azure HDInsight and on a private cloud cluster based on POWER8 by considering the TPC-DS industry benchmark and SparkBench. The results obtained in the first scenario demonstrate that the percentage error of the prediction of the optimal resource usage with respect to system measurement and exhaustive search is in the range 4–29 percent while literature-based techniques present an average error in the range 6–63 percent. Moreover, in the second scenario, the proposed algorithms can address complex problems like computing the optimal redistribution of resources among tens of applications in less than a minute with an error of 8 percent on average. On the same considered tests, literature-based approaches obtain an average error of about 57 percent.
Multivariate Statistical Methods Used in Population Genetics

Several multivariate statistical methods are used in population genetics but there are very few studies that have revealed the strengths and weaknesses of different methods. Thus, this study aims to reveal the strengths and weaknesses of the different multivariate statistical methods used in population genetics through the world. This synthesis is carried out according to the methodology "Preferred Reporting Items for Systematic Reviews and Meta-Analyzes" (PRISMA). This study shown that various statistical methods or combination of multivariate statistical methods are used in population genetics. It emerges that there is no a priori a better method, so it is necessary to determine the method adapted to both the data collected and the research objective. This study identified the most commonly used multivariate statistical methods in genetics such as: Ordination methods (52.50%) are methods that summarize the information contained in the data matrix by minimizing wastage. This are: principal components analysis (by 32.0% of the articles), principal coordinates analysis (by 7.50% of the articles), discriminant analysis of principal component, factorial correspondence analysis, factorial discriminant analysis, factorial analysis on distance table. Clustering methods (35%) that aim to form groups of individuals that are as similar as possible, including the hierarchical ascending clustering (17.50% of articles), neighbor-joining, and Bayesian clustering model (by 15% of the articles). The analysis of the molecular variance (7.50%) which consists of studying the intra and inter-population variation and the Mantel test (5%) which aims to test the correlation between the matrix of genetic distances and other distance matrices (environmental causes of genetic variability).