Miracle-dz/UniFAR-FTUs huggingface dataset:
An Adjustment Approach for Aerosol Optical Depth Inferred from CALIPSO

The verification and correction of CALIPSO aerosol products is key to understanding the atmospheric environment and climate change. However, CALIPSO often cannot detect the full profile of aerosol for the low instrument sensitivity near the surface. Thus, a correction scheme for the aerosol extinction coefficient (AECs) in the planetary boundary layer (PBL) is proposed to improve the quality of the CALIPSO-based aerosol optical depth (AOD) at 532 nm. This scheme assumed that the aerosol is vertically and uniformly distributed below the PBL, and that the AECs in the whole PBL are equal to those at the top of the PBL; then, the CALIPSO AOD was obtained by vertically integrating AECs throughout the whole atmosphere. Additionally, the CALIPSO AOD and corrected CALIPSO AOD were validated against seven ground-based sites across eastern China during 2007–2015. Our results show that the initial CALIPSO AOD obtained by cloud filtering was generally lower than that of the ground-based observations. After accounting for the AECs in the PBL, the adjustment method tended to improve the CALIPSO AOD data quality. The average R (slope) value from all sites was improved by 7% (46%). Further, the relative distance between the ground track of CALIPSO and the ground station exhibited an influence on the validation result of CALIPSO AOD. The retrieval precision of CALIPSO AOD worsened with the increase in water vapor in the atmosphere. Our findings indicate that our scheme significantly improves the accuracy of CALIPSO AOD, which will help to provide alternative AOD products in the presence of severe atmospheric pollution.
Unsupervised Change Detection Using Fuzzy Topology-Based Majority Voting

Remote sensing change detection (CD) plays an important role in Earth observation. In this paper, we propose a novel fusion approach for unsupervised CD of multispectral remote sensing images, by introducing majority voting (MV) into fuzzy topological space (FTMV). The proposed FTMV approach consists of three principal stages: (1) the CD results of different difference images produced by the fuzzy C-means algorithm are combined using a modified MV, and an initial fusion CD map is obtained; (2) by using fuzzy topology theory, the initial fusion CD map is automatically partitioned into two parts: a weakly conflicting part and strongly conflicting part; (3) the weakly conflicting pixels that possess little or no conflict are assigned to the current class, while the pixel patterns with strong conflicts often misclassified are relabeled using the supported connectivity of fuzzy topology. FTMV can integrate the merits of different CD results and largely solve the conflicting problem during fusion. Experimental results on three real remote sensing images confirm the effectiveness and efficiency of the proposed method.
Explainable Artificial Intelligence in the Medical Domain: A Systematic Review

The applications of Artificial Intelligence (AI) and Machine Learning (ML) techniques in different medical fields is rapidly growing. AI holds great promise in terms of beneficial, accurate and effective preventive and curative interventions. At the same time, there is also concerns regarding potential risks, harm and trust issues arising from the opacity of some AI algorithms because of their un-explainability. Overall, how can the decisions from these AI-based systems be trusted if the decision-making logic cannot be properly explained? Explainable Artificial Intelligence (XAI) tries to shed light to these questions. We study the recent development on this topic within the medical domain. The objective of this study is to provide a systematic review of the methods and techniques of explainable AI within the medical domain as observed within the literature while identifying future research opportunities.
Effect of intermittent microwave vacuum concentration on quality parameters of apple juice and sour cherry nectar and mathematical modeling of concentration

Abstract In this study, sour cherry nectar and apple juice were concentrated using thermal concentration (75, 80, and 85 °C), and intermittent microwave concentration (180, 300, and 450 W) under vacuum condition (at 250 mbar). Thirteen different mathematical models were used to describe the concentration kinetics of the samples. The Midilli model exhibited the best fit to all experimental data (R2 ≥ 0.9972; χ2 ≤ 1.6724; RMSE ≤ 1.2932). The concentration time was reduced with increasing microwave power (from 180 W to 450 W) and thermal vacuum concentration temperature (from 75 °C to 85 °C). In addition, the main quality parameters of the concentrates were comparatively investigated after reconstitution. Generally, major differences were not observed in the physicochemical properties of samples concentrated by thermal and microwave methods. Total phenolic content of the apple juice and sour cherry nectar samples were ranged between 209.87-216.67 mg/L and 571.00-588.57 mg/L, respectively. Fructose was the main sugar in both juices, followed by glucose and sucrose. The particle size of the juice samples increased with concentration processing.
NOTE Detection of Gaseous Methane on Pluto

0.5% CO, 1.5% CH4 (by mass), and N2 in an intimate mixture (Owen et al. 1993). Assuming the N2–CO–CH4 frost acts like an ideal mixture, We obtained Pluto’s spectrum using the CSHELL echelle one finds that XCH4 is only 0.0001% to 0.001%. However, Lellouch (1994) spectrograph at NASA’s IRTF on Mauna Kea, on 25–26 May points out that Triton’s XCH4 is several hundred times greater than that 1992, with a spectral resolution of 13,300. The spectral range predicted by the ideal mixture that Cruikshank et al. (1993) used to (5998–6018 cm, or 1661.8–1666.9 nm) includes the R(0) and interpret similar spectra of Triton. This can be explained if the N2–CO– the Q(1)–Q(9) lines of the 2n3 band of methane. The resulting CH4 frost is nonideal. Lellouch therefore suggests that Pluto’s XCH4 is spectrum shows the first detection of gaseous methane on Pluto, inflated by a similar amount, so that XCH4 P 0.1%. Finally, there is recent with a column height of 1.20 20.87 cm-A (3.22 22.34 3 10 molecule spectral evidence of pure CH4 on Pluto’s surface (Schmitt et al., 1994). Pure CH4 frost would supply more gaseous CH4 than N2–CO–CH4 frost, cm).  1997 Academic Press raising XCH4 above the ideal-mixture value. The thermal structure of Pluto’s atmosphere is further evidence that Introduction. This paper presents the first positive detection of gasXCH4 is larger than the ideal mixture predicts. The temperature of the eous CH4 in Pluto’s atmosphere. Solid CH4 has been previously identified N2–CO–CH4 frost is 40 6 2 K, from the shape of the N2 absorption in Pluto’s visible and near-IR spectra at resolutions of a few hundred up feature at 2148 nm (Tryka et al., 1994), and the brightness temperature to 1200 (e.g., Fink et al. 1980; Spencer et al. 1990; Owen et al. 1993). of Pluto (which is a global average, including frost-covered and frostUnfortunately, these observations cannot be used to find the CH4 mixing free regions) ranges from 55 K at 60 em (Sykes et al. 1987; Tedesco et ratio in the atmosphere directly, since the spectra of solid and gaseous al. 1987) to 35 K at 1300 em (Stern et al. 1993; Jewitt 1994). In contrast CH4 are essentially indistinguishable at these resolutions. Furthermore, with the cold surface, the atmosphere is 100 K at ebar levels (Elliot and the absorption features due to gaseous CH4 are hundreds of times weaker Young 1992), implying a source of heating in the atmosphere. CH4 can than those due to solid CH4, and have not been detected in these spectra. provide the required heating, if XCH4 . 0.1% and there is no CO cooling Because Pluto’s atmosphere is expected to be in vapor-pressure equilib(Yelle and Lunine 1989). For models that include CO cooling, large rium with the surface, the surface temperature and composition can be enough amounts of gaseous CH4 can still heat the atmosphere (Lellouch used indirectly to estimate the atmospheric CH4 mixing ratio (XCH4). 1994; Strobel et al. 1996). Near-IR spectra indicate that Pluto’s surface is dominated by frost with
Development of an antibody-based colloidal gold immunochromatographic lateral flow strip test for natamycin in milk and yoghurt samples

ABSTRACT An immunochromatographic lateral flow strip test was developed for the detection of natamycin (Nata) residues in milk and cheese samples. Monoclonal antibody (mAb) against Nata was produced with a half maximal inhibitory concentration of 1.85 μg L−1. MAb conjugated with gold nanoparticles was the detection reagent. Nata conjugated with ovalbumin via the 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide/N-hydroxysuccinimide method immobilized on a nitrocellulose membrane was the capture reagent. This semi-quantitative method required only 15 min to complete. The optimum concentrations of coating antigen and mAb were 0.15 µg mL−1 and 0.2 µg mL−1, respectively. Based on an optical density scanner, the visual limit of detection of Nata was 5 μg L−1 and 10 μg kg−1 in milk and yoghurt samples, respectively.
A Twitter Corpus and Lexicon for Abusive Speech Detection in Serbian

Abusive speech in social media, including profanities, derogatory and hate speech, has reached the level of a pandemic. A system that would be able to detect such texts could help in making the Internet and social media a better and more respectful virtual space. Research and commercial application in this area were so far focused mainly on the English language. This paper presents the work on building AbCoSER, the first corpus of abusive speech in Serbian. The corpus consists of 6,436 manually annotated tweets, out of which 1,416 were labelled as tweets using some kind of abusive speech. Those 1,416 tweets were further sub-classified, for instance to those using vulgar, hate speech, derogatory language, etc. In this paper, we explain the process of data acquisition, annotation, and corpus construction. We also discuss the results of an initial analysis of the annotation quality. Finally, we present an abusive speech lexicon structure and its enrichment with abusive triggers extracted from the AbCoSER dataset
A New Multi-Scale Sliding Window LSTM Framework (MSSW-LSTM): A Case Study for GNSS Time-Series Prediction

GNSS time-series prediction plays an important role in the monitoring of crustal plate movement, and dam or bridge deformation, and the maintenance of global or regional coordinate frames. Deep learning is a state-of-the-art approach for extracting high-level abstract features from big data without any prior knowledge. Moreover, long short-term memory (LSTM) networks are a form of recurrent neural networks that have significant potential for processing time series. In this study, a novel prediction framework was proposed by combining a multi-scale sliding window (MSSW) with LSTM. Specifically, MSSW was applied for data preprocessing to effectively extract the feature relationship at different scales and simultaneously mine the deep characteristics of the dataset. Then, multiple LSTM neural networks were used to predict and obtain the final result by weighting. To verify the performance of MSSW-LSTM, 1000 daily solutions of the XJSS station in the Up component were selected for prediction experiments. Compared with the traditional LSTM method, our results of three groups of controlled experiments showed that the RMSE value was reduced by 2.1%, 23.7%, and 20.1%, and MAE was decreased by 1.6%, 21.1%, and 22.2%, respectively. Our results showed that the MSSW-LSTM algorithm can achieve higher prediction accuracy and smaller error, and can be applied to GNSS time-series prediction.
Dynamic changes in and time sequence of ultraviolet B-induced apoptosis in rat corneal epithelial cells.

PURPOSE To systematically examine the dynamic changes and time sequence in corneal epithelial cell apoptosis after excessive ultraviolet B irradiation. METHODS Ultraviolet B (144 mJ/cm2) was used to irradiate rat corneal epithelial cells for 2 h. Cell morphology was observed on differential interference contrast microscopy, and the numbers of the different kinds of apoptotic cells were counted using the ImageJ software. Cell viability was measured with the 3-(4,5-dimethyl-2-thiazolyl)-2,5- diphenyl-2-H-tetrazolium bromide method. Cell apoptotic rate and loss of mitochondrial membrane potential were detected using flow cytometric analyses. The expression levels of 3 apoptotic genes were measured with real-time quantitative polymerase chain reaction at different time points within 0-24 h after irradiation. RESULTS After 144-mJ/cm2 ultraviolet B irradiation for 2 h, the expression levels of caspase-8 and Bax were highest at 0 h; furthermore, the mitochondrial membrane potential decreased at 0 h and remained constant for 6 h in a subsequent culture. At 6 h, caspase-3 was activated. The decrease in cell viability and increase in apoptotic rate peaked at 6 h. The caspase-3 expression level decreased within 12-24 h, which led to a decline in apoptotic rate and change in apoptotic stage. CONCLUSIONS The corneal epithelial cells exhibited rapid apoptosis after ultraviolet B irradiation, which was associated with both extrinsic and intrinsic pathways.
A Critical Assessment of Online Vs. Traditional Review Characteristics

With the expansion of internet-based platforms, social media and sharing economy, most individuals are tempted to review products or services that they consume. While useful in various ways, such online reviews raise questions about the reviewer’s expertise, authenticity, intent, and the scales employed in such online reviews. There are emerging evidences that issues pertaining to online reviews have led to damaging consequences for businesses. With the intention of creating an awareness of reviewer characteristics and scales employed in online reviews, we present findings of 220 research papers. The review of literature identifies salient review and reviewer characteristics as well as the scale characteristics of traditional reviews and online reviews.
Fine-grained Content Classification of Development emails

Electronic communication means have become crucial with the adoption of software at any level of everyday life; playing a central role in the coordination of collaborative, distributed development. One widely used means is represented by emails from development mailing list, which contain questions and discussions among developers about design choices and various issues concerning the evolution of a system. The contents in these archives could lead to consistent information e.g., describing the system’s history during its evolution, or giving a meaningful insight on the currently active development tasks. The analysis of emails poses, however, some serious challenges: the text is often noisy, and usually contains characters that make it hard to build a robust parser to automatically extract accurate information. Previous research addresses these issues by working at the document level, without precisely discriminating the various sections that compose a development email. In this thesis we present a classification approach, which integrates machine learning, information retrieval and parsing techniques, to enable robust email content analysis at the line level. The developed technique classifies email lines in five categories—i.e., text, junk, code, patch, and stack trace—that allows one to subsequently apply ad hoc analysis techniques to exploit the peculiarities of each category and removing the sections of the content that would entail noise, reducing the effectiveness of the analysis. We evaluated our approach on a statistically significant set of emails gathered from mailing lists of four unrelated open source systems, reaching high values of precision and recall.
Human-Aware Robot Behavior in Healthcare Facilities

—In this paper, we propose a method for building sophisticated costmaps based on spatio-temporal world information. This enables mobile robots to gain adequate movement behaviors in unconstrained environments, such as hospitals and other healthcare facilities. Here robots needs to be extra cautious as they encounter some of the most fragile members of society, who are likely unfamiliar with robots. We show that our method improves standard navigation methods by keeping a larger distance to people, by predicting people’s future trajectories and acting appropriately to these. Also, we use f-formations to group people who are likely interacting socially, thereby enabling the robot to avoid interrupting them.
A Reproduction of Succinct Data Store System

This is a reproduction of Succinct [2], a distributed in memory data store that utilizes compression to fit more data into memory. Succinct’s compression scheme enables fast queries directly on top of the compressed representation. According to the original authors, Succinct exposes "a minimal, but powerful API," while requiring much less memory than traditional databases. Below, we attempt to reproduce some of the original paper’s findings and evaluate certain claims. Specifically, we attempt to reproduce the paper’s comparison of Succinct and MongoDB in terms of memory usage, throughput, and latency. The original paper found that MongoDB’s in memory in-dicies took up 8x more memory than the actual data, whereas Succinct’s total in memory representation was actually smaller than the raw data, leading to dramatically higher memory usage for MongoDB given the same amount of input data. The original paper also found that Succinct displayed measurably better throughput and latency with respect to MongoDB on a workload of 10,000 search requests. Our reproduction contains mixed results. We were able to reproduce similar Succinct throughput and latency metrics, but due to complications with measuring memory usage in Spark and compiler issues with the C++ version of Succinct, we were not able to obtain a post-compression memory usage metric that we feel confident is correct. Of all our the attempts to measure memory usage, our most promising method yielded a metric 28% larger than the original data, which would contradict many of the paper’s results, but as we discuss below, we believe the issue is likely with our measurement. Wealsocould
Effect of hydrostatic pressure and uniaxial strain on the electronic structure of Pb1−xSnxTe

Matthias Geilhufe,1 Sanjeev K. Nayak,2,* Stefan Thomas,1 Markus Däne,3 Gouri S. Tripathi,4 Peter Entel,5 Wolfram Hergert,2 and Arthur Ernst1 1Max Planck Institute of Microstructure Physics, Weinberg 2, 06120 Halle, Germany 2Institute of Physics, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, 06120 Halle, Germany 3Physical and Life Sciences, Lawrence Livermore National Laboratory, PO Box 808, L-372, Livermore, California 94551, USA 4Physics Department, Berhampur University, Berhampur 760007, Odisha, India 5Faculty of Physics and CENIDE, University of Duisburg-Essen, 47048 Duisburg, Germany (Received 18 August 2015; revised manuscript received 6 November 2015; published 9 December 2015)
REVIEW OF NOISES RELATED HEARING LOSS IN ELDERLY

Audibility, is a common problem for hearing-impaired individuals and is especially frequent in older adults. Despite the debilitating nature of the problem the cause is not yet completely clear. This review considers the role of spatial processing ability in understanding speech in noise, highlights the potential impact of disordered spatial processing, and attempts to establish if aging leads to reduced spatial processing ability. Evidence supporting and opposing the hypothesis that spatial processing is disordered among the aging population is presented. With a few notable exceptions, spatial processing ability was shown to be reduced in an older population in comparison to young adults, leading to poorer speech understanding in noise. However, it is argued that to conclude aging negatively effects spatial processing ability may be oversimplified or even premature given potentially confounding factors such as cognitive ability and hearing impairment. Further research is required to determine the effect of aging and hearing impairment on spatial processing and to investigate possible remediation options for spatial processing disorder. Difficulty understanding speech in background noise, even with amplification to restore.
Optimizing cotton irrigation and nitrogen management using a soil water balance model and in-season nitrogen applications

Nitrogen (N) and irrigation can be two of the costliest management inputs in United States (U.S.) cotton (Gossypium hirsutum L.) production systems. Furthermore, input amounts are often dependent on yearly environmental conditions, making it challenging to optimize N and irrigation management. The objectives of this research were to determine optimal N and irrigation management by: (i) evaluating equally split in-season N rates applied at first square and bloom in combination with varying levels of plant available water replacement (PAWR) estimated by an ET-based soil water balance model for cotton; and (ii) evaluate the whole-plant responses to the interaction between N and water management levels. Field experiments were conducted during 2015 and 2016 at two locations in Florida (Jay and Citra), southeastern U.S. with differing soil textures consisting of a deep sand and sandy loam. Irrigation treatments consisted of: (i) 100% of PAWR (100%); (ii) a primed acclimation (PA) treatment consisting of 50% of PAWR until first bloom and then 100% of PAWR (50% PA); (iii) 50% PAWR for the entire season (50%); (iv) a rain-fed control (RF). Nitrogen treatments consisted of even application splits at first square and bloom applied at a rate of 0 (N0), 22 (N22), 34 (N34), and 45 kg N ha (N45). Lint yield assessments were conducted at both locations in both years. To link yield responses to possible physiological responses, in depth crop measurements consisting of SPAD chlorophyll content, leaf area index (LAI), N uptake, and harvest index (HI) were conducted at the Citra site. Contrasting soil textures and weather conditions between research locations and years allowed for a comprehensive assessment of both N and irrigation management across varying environmental conditions. Lint yield was either increased or at least maintained during the two years of this research at the Citra location by making two split N applications at first square and bloom of N22; while the optimal N treatment at the Jay location was N34 at first square and bloom in both years of this research. Additionally, a yield reduction occurred in the dry year of 2016 at the Citra location when N45 was applied at first square and bloom. The most efficient irrigation strategy at the Citra location was the primed acclimation treatment. At the Jay location, the RF control had similar lint yields as the irrigated treatments in both years, indicating that water application was not limiting at this site. These management strategies offer ways to optimize costly inputs when growing cotton in the southeastern U.S.
Interactive comment on “How vadose zone mass and energy transfer physics affects the ecohydrological dynamics of a Tibetan meadow?” by Lianyu Yu et al

original T&C model, lacking soil freezing processes; (2) a modification of T&C in which an ice fraction and freezing/thawing are accounted for; and (3) a coupling of T&C to the soil physics model STEMMUS. The model versions are parameterized and driven with data from a Tibetan meadow site to evaluate their performance. Differences between results with the three versions of the model are small for most variables, generally smaller than the model-to-data difference, and the simulated differences are confined to parts of the year where freezing dynamics are likely to play a role. The analysis would benefit from a focus on specific periods of the year where differences arise.