Miracle-dz/UniFAR-FTUs huggingface dataset:
Soluble Solid Content Prediction System of Honey based on Spectral Transmittance Profile of Hyperspectral Imaging

Honey content is constructed by a combination of glucose and fructose which a high sugar content. One of the honey qualities is contributed by the added adulterant in honey producing such as artificial glucose or fructose. Therefore, the soluble solid content of honey is essential to predict according to differentiate the added content of honey. The honey image was acquired using transmittance mode in the Vis-NIR range of 400–1000 nm. The complete system consists of a Hyperspectral camera at 448 bands, slider, a 200 W halogen lamp and light diffuser. The processing method performs image correction, segmentation, feature extraction, feature reduction, and a regression model. The region interest area of the honey sample was selected at the center of honey that prepared in petry-dish. Partial Least Square Regression (PLSR) was used as the feature reduction and regression model to construct the transfer model of soluble solid content based on the transmittance profile of honey. The Digital Refractometer was used to generate the reference standard of the soluble solid content. Three different producers and five types of botanical origin were used as a sample of honey. The artificial glucose or fructose was added to the original honey to produce five variants of soluble solid content. The result of RMSE for training and testing data is 0.07 and 0.45, respectively. Based on the result, the proposed system could be used as an alternative method to predict the soluble solid content in honey with excellent accuracy.
INHIBITORS OF HEATING AND DETERIORATION IN SEEDS. I. ETHYLENE CHLORHYDRIN AND RELATED COMPOUNDS.

A rapid method for the measurement of inhibition of deterioration in seeds was applied in an investigation of organic chemicals in order to discover inhibitors which would be applicable on a commercial scale for the prevention of heating and deterioration during the storage of seeds. Through the courtesy of manufacturers of synthetic organic chemicals, a wide variety of compounds was made available for this investigation, and these were examined without regard to their previously known or alleged biochemical properties. It became evident that members of certain classes of chemicals such as halohydrins, simple esters, organic acids, phenol derivatives, chlorinated xylenes, and sulfon-nitrogen compounds were effective inhibitors. Some of the most active chemicals discovered in this survey have been reported in a preliminary publication (3). It is the purpose of the present report to describe the behavior of chemicals related to ethylene chlorhydrin. Those chemicals which exhibited activity as inhibitors of the same order of magnitude as ethylene chlorhydrin were examined at several concentrations, and their behavior as inhibitors of heating and formation of free fatty acids were compared to that of ethylene chlorhydrin. In comparing inhibitors by an empirical method, such as the one used in this investigation, it was desirable not only to determine the effective concentration at which each completely inhibited deterioration, but also to determine, as far as possible, any differences in the behavior of the inhibitors. It was found that as the concentration of an inhibitor used in treating the seed was reduced, the resulting loss or diminution of ability to inhibit heating and formation of free fatty acids did not necessarily parallel each other. Loss of ability to inhibit heating may have proceeded at a greater or lesser rate than that of inhibition of the formation of free fatty acids. In some instances lowering the concentration of an inhibitor had the effect of stimulating biological activity, and here again this effect was not necessarily similar for heating and formation of free fatty acids. This "pattern" of behavior of seed as a function of the initial concentration of the inhibitor in the seed seems to be characteristic for each inhibitor. Several patterns of inhibitor behavior were found among the inhibitors which are being reported herein. These patterns have been described and compared to those of seed treated with diethyl oxalate and vinyl propionate,
Handwritten Arabic Word Spotting Using Speeded Up Robust Features Algorithm

Optical Character Recognition (OCR) of Arabic text from manuscripts images is virtually impossible, this is due to the semi-cursive nature of Arabic script which is very difficult to explore by algorithms and image processing methods.In this paper, we present a method of exploration and research in content of Arabic manuscript images. It’s about characterizing segmented handwritten words with a set points of interest by providing a means of identification and research in these manuscripts. Each word segmented and described by key features will be compared to query words.The results of this method are encouraging in comparison with other methods, especially when it comes to the same of handwritten style used in the text.
Assessment User Interface: Supporting the Decision-making Process in Participatory Processes

We introduce a novel intelligent user interface for assessing contributions submitted in participatory planning and decision processes. It assists public administrations in decision making by recommending ranked contributions that are similar to a reference contribution based on their textual content. This allows the user to group contributions in order to treat them consistently which is crucial in this domain. Presently, the assessment process is done manually with no sophisticated computer-aided support. The assessment user interface provides a two-column layout with a basic list of contributions in the left column and a list of similar contributions in the right column. We present results of a user study that we conducted with 21 public administration workers to evaluate the proposed interface. We found that the assessment user interface is well suited to the assessment task and the related decision-making process. But there are also unclear elements in the ranking visualization as well as some distrust in the ranked contributions or intelligent methods among the participants.
Pigmentation Prevalence Analysis of Smoker's Tongue Using Hyperspectral Imaging

Visually, it is difficult to differentiate between smoker and non-smoker tongue even for an experienced doctor or dentist. One of the most objective ways to acknowledge the smoker tongue is by using tools such as a camera. The proposed system contains two parts, hardware, and software. The hardware consists of a workbench, slider, a halogen light source and hyperspectral camera with a spectral range between 400–1000 nm connected to a personal computer. The system complemented with image processing software built up especially to analyze the smoker tongue. The reflectance values of the tongue surface were extracted from respondent tongue image that previously corrected using white and dark hyperspectral image references. The principal component analysis (PCA) was used to compute and select the features subset which will be used as an input by the classifier. The support vector machine (SVM) classifier is used as image classification model since it performs excellently to choose the best hyperplane separator between two different classes. The evaluation of system result is checked using confusion matrix by making false positive rate (FPR), false negative rate (FNR), sensitivity and specificity as system reliability parameters. A Smoker detection system to identify smoker's melanosis is successfully classify the tongue of smokers and non-smokers with reasonable accuracy.
Design and evaluation of engineered protein biosensors for live-cell imaging of EGFR phosphorylation

Engineered biosensors accurately report the kinetics of EGFR activation. Building better biosensors The accuracy of a biosensor used to measure signaling events in live cells depends on both the specificity of the biosensor for its intended target and the absence of interference with the signaling pathway. Phosphotyrosine-binding SH2 domains have been used as biosensors for receptor tyrosine kinase activation. Tiruthani et al. showed that a paired SH2 domain biosensor for monitoring phosphorylation of the epidermal growth factor receptor (EGFR) at Tyr992 was not specific for EGFR and was not recruited to the membrane in a manner that accurately reflected the kinetics of EGFR signaling. Hence, the authors used two different mutagenesis and screening approaches to engineer new biosensors, mSH2 and SPY992, that exhibited greater specificity for EGFR Tyr992 and more accurately reported EGFR signaling kinetics. These approaches were extended to develop SPY1148, a biosensor for phosphorylation of EGFR at Tyr1148, and could be extended to generate phospho-specific biosensors for various targets. Live-cell fluorescence microscopy is broadly applied to study the dynamics of receptor-mediated cell signaling, but the availability of intracellular biosensors is limited. A biosensor based on the tandem SH2 domains from phospholipase C–γ1 (PLCγ1), tSH2-WT, has been used to measure phosphorylation of the epidermal growth factor receptor (EGFR). Here, we found that tSH2-WT lacked specificity for phosphorylated EGFR, consistent with the known promiscuity of SH2 domains. Further, EGF-stimulated membrane recruitment of tSH2-WT differed qualitatively from the expected kinetics of EGFR phosphorylation. Analysis of a mathematical model suggested, and experiments confirmed, that the high avidity of tSH2-WT resulted in saturation of its target and interference with EGFR endocytosis. To overcome the apparent target specificity and saturation issues, we implemented two protein engineering strategies. In the first approach, we screened a combinatorial library generated by random mutagenesis of the C-terminal SH2 domain (cSH2) of PLCγ1 and isolated a mutant form (mSH2) with enhanced specificity for phosphorylated Tyr992 (pTyr992) of EGFR. A biosensor based on mSH2 closely reported the kinetics of EGFR phosphorylation but retained cross-reactivity similar to tSH2-WT. In the second approach, we isolated a pTyr992-binding protein (SPY992) from a combinatorial library generated by mutagenesis of the Sso7d protein scaffold. Compared to tSH2-WT and mSH2, SPY992 exhibited superior performance as a specific, moderate-affinity biosensor. We extended this approach to isolate a biosensor for EGFR pTyr1148 (SPY1148). This approach of integrating theoretical considerations with protein engineering strategies can be generalized to design and evaluate suitable biosensors for various phospho-specific targets.
An Eco-physiological and Biotechnological Approach to Conservation of the World-wide Rare and Endangered Aquatic Liverwort Riella helicophylla (Bory et Mont.) Mont.

Abstract The rare aquatic liverwort Riella helicophylla (Bory et Mont.) Mont. , inhabitant of temporary shallow ponds around the Mediterranean basin, is considered threatened throughout its distribution range. In addition, little is known of its biology and ecology or of its role in such an important ecosystem where environmental conditions vary yearly in unpredictable ways. In these variable habitats, due to the seasonal fluctuation of water levels, there is no guarantee of yearly spore input into the spore bank. Spore germination rate and the effects of different culture media in an axenic culture establishment, as well as propagation procedures of R. helicophylla, were tested. New insights into the ecology and biology of R. helicophylla are given. Spore dormancy is documented, and the protocols for the in vitro culture establishment, propagation and acclimatization of this liverwort are developed. Dry storage at 20 ± 2 °C for about three months broke the dormancy of spores, which subsequently germinated in a high percentage (over 90%). A two phase (solid and liquid) culture media system was developed for the purpose of achieving fully developed gametophytes. The liquid phase contained electrolytes simulating brackish water.
Towards Visual Explorations of Forums' Collective Dynamics in Learning Management Systems

Discussion and exchange among peers have being hailed as an essential part of learning since at least, Vygot-sky's socio-constructivist theory. There, learning is presented as a subtle and dynamical collective process. Hence, despite numerous efforts to understand how learners engage and maintain inspiring discussions, researchers continue to question how to effectively reinforce the collective actions. In Learning Management Systems (LMSs) they propose Learning Dashboards (LDBs) to learners, tutors, and managers to help them monitor various learning indicators. But only recently have they employed Natural Language Processings (NLPs) and Social Network Analysis (SNA) techniques to display temporal indicators incorporating the fo-rums' content analysis and the learners' behavioral patterns. In this study, we present our design efforts to model a scalable and portable indicator of collective actions. We aim to support tutors' monitoring of fo-rums' activities through explorable visualizations. We review previous researches about visual explorations of Forums' content and online collaboration's measures. We expose in progress visualizations built from three different datasets and propose directions towards further development of indicators to monitor collective actions.
A Fog-enabled Smart Home Analytics Platform

Although the usage of smart home devices such as smart speakers, light bulbs and thermostats has increased rapidly in the past years, their added value, compared to conventional devices, is mostly limited to simple control and automation logic. In order to provide adaptive smart home environments, it is necessary to gain deeper insights into the data generated by these devices and use it in sophisticated data processing pipelines. Providing such analytics to a multitude of consumers requires specialised architectures, which are able to overcome various challenges identified by scientific literature. Currently available smart home analytics architectures are not designed to tackle all of these issues, specifically fault-tolerance, network-usage, latency and external regulations. In this paper, we propose an architectural solution to address these challenges based on the concept of Fog computing. Furthermore, we provide insight into the motivation for this research as well as an overview of the current state of the art in this field.
On Performance Evaluation of Dynamic Sensitivity Control Techniques in Next-Generation WLANs

Dynamically adapting carrier sensing range, also known as dynamic sensitivity control (DSC), could be an attractive proposition for improving the spatial reuse in dense wireless local area networks. This paper shows the promise and pitfalls of a DSC technique proposed in the IEEE 802.11ax standard and highlights a solution to mitigate these issues. An analytical framework is also presented for the performance evaluation of DSC techniques.
I’m Doing Better on My Own: Social Inhibition in Vocabulary Learning in Adults

Vocabulary learning is better achieved by children facing a teacher than when presented to the same teacher through video (so-called “video deficit” effect), which has significant implications for toddlers’ education. Since millions of adults also learn new vocabulary when acquiring a second language (L2), it is important to explore whether adults suffer from “video deficit” effects, as children do. In the present study, we report two experiments in which Spanish native late learners of English were involved in a vocabulary learning task. In Experiment 1, participants had to learn English (L2) labels associated to real objects. In Experiment 2, participants had to learn English (L2) and Spanish (L1) labels associated to novel objects. In both experiments, vocabulary learning was divided into three conditions: In the NoFace condition, participants were presented with the objects and their auditory labels, through video. In the Video condition, a teacher was showing the objects and uttering their names, through video. The Live condition was equivalent, except that the teacher was facing the participants in the room. Each condition was followed by a recall test. Better learning in Video compared to NoFace condition revealed that adults benefit from the teacher’s display with direct gaze, confirming the fundamental role of face display with direct gaze in social communication in adults. Interestingly, adults learned better through Video than in the Live condition. Those results were obtained in L2 vocabulary learning in both Experiments 1 and 2, and also generalized to native language in Experiment 2. We argue that adults suffer from social inhibition, meaning that they perform worse when in the presence of another person during task performance. In sum, we show that video-mediated teaching might not be detrimental for adults learning new vocabulary lists, as it is the case for young children. These results might have important implications for pedagogical programs targeting adults’ second language vocabulary learning, since proper acquisition of vocabulary list can be achieved through video including a teacher’s display.
Transitional-aged youth perceptions of influential factors for substance-use change and treatment seeking

There is an evident disparity between the number of youth who report experiencing problematic substance use and the number who seek treatment. To address this disparity, it is important to understand the reasons youth do and do not seek substance use treatment. Using qualitative data obtained from semistructured interviews with 31 youth aged 17–25 years presenting for treatment at a mental health hospital, the current study identifies themes in the factors that youth identify as having influenced them to seek or delay treatment. In alignment with self-determination theory, youth identified internal factors, such as wanting to better their academic, social, or financial situation, and external factors, such as familial pressure, as motivating them to seek treatment. Factors beyond those encompassed by self-determination theory were also revealed as having influenced youth decisions to seek treatment for substance abuse. These predominantly included structural factors, including satisfaction with previous treatment, accessibility of services, and availability of clinicians. These findings provide important insight for first-contact professionals and service providers looking to enhance youth motivation to seek and engage in treatment. Limitations and opportunities for future research are discussed.
Diversity, Virulence, and Clinical Significance of Extended-Spectrum β-Lactamase- and pAmpC-Producing Escherichia coli From Companion Animals

Escherichia coli are opportunistic pathogens with the potential to cause a variety of infections in both humans and animals and in many cases have developed antimicrobial resistance. In this study, we characterized extended-spectrum cephalosporin resistant (ESCR) E. coli isolates from diseased companion animals (dogs, cats, and horses) and related the results to clinical findings. ESCR E. coli clinical isolates obtained over a 6-year period were screened for extended-spectrum β-lactamase (ESBL) and/or plasmid mediated AmpC (pAmpC) and virulence markers likely to be associated with extraintestinal pathogenic E. coli (ExPEC). ESBL and/or pAmpC genetic determinants were identified in 79.9% of the ESCR E. coli isolates with blaCTX-M genes being the most common ESBL genotype of which blaCTX-M-15, blaCTX-M-14, and blaCTX-M-55 were the most prevalent. In addition, blaCMY -2 was the most common genotype identified amongst pAmpC producing isolates. Phylogenetic group typing showed that B2 was the most prevalent phylogroup among the ESCR E. coli isolates, followed by the closely related phylogroups D and F which are also associated with extra-intestinal infections. ESCR was also identified in phylogroups commonly regarded as commensals (B1, A, and C). Virulence factor (VF) scores >2 were mostly present amongst isolates in phylogroup B2. Higher virulence scores were found in isolates lacking ESBL/pAmpC resistance genes compared with those carrying both genes (p < 0.05). Five of phylogroup B2 isolates, were typed to the pandemic virulent O25b-ST131 clone and three ST131 isolates carrying blaCTX-M-15 belonged to the subclade C2/H30Rx whilst one isolate carrying blaCTX-M-27 typed to the recently described sub-clade C1-M27. MLST typing also identified other sequence types commonly associated with infections in humans (ST410, ST10, and ST648). Most ESCR E. coli isolates obtained in pure growth were cultured from normally sterile body sites (mostly from urinary tract infections, UTIs) whilst only a small proportion were obtained from body sites populated with commensal flora (p < 0.0001). Our study has shown that ExPEC ESBL/pAmpC producing E. coli isolates are common amongst companion animal isolates and are associated with colonization and infection. In addition, their isolation from a normally sterile site is likely to be clinically significant and warrants antimicrobial treatment.
"It's Modern Day Presidential! An Evaluation of the Effectiveness of Sentiment Analysis Tools on President Donald Trump's Tweets"

This paper reports on an evaluation of five commonly used, lexicon-based sentiment analysis tools (MeaningCloud, ParallelDots, Repustate, RSentiment for R, SentiStrength), tested for accuracy against a collection of Trump’s tweets spanning from election day November 2016 to one year post inauguration (January 2018). Repustate was found to be the most accurate at 67.53%. Our preliminary analysis suggests that this percentage reflects Trump’s frequent inclusion of both positive and negative sentiments in a single tweet. Additionally to providing an evaluative comparison of sentiment analysis tools, a summary of shared features of a number of existing datasets containing Twitter content along with a comprehensive discussion is also provided.
Multi-Parameter Measurement Tool of Heart Rate and Blood Pressure to Detect Indonesian Car Drivers Drowsiness

According to the Indonesian Traffic Police Center, in 2017 Indonesia ranks the top 4th countries in South East Asia which has a high number of road accidents. Many of the accidents, unfortunately, are caused by the drowsiness of car drivers. This indicates that human fatigue significantly affects the safety of traffic. To decrease the number of road accidents in Indonesia, this research proposes an alternative measurement tool and parameter to detect the drowsiness symptoms of car drivers. This research analyzes the usage of a wearable wristband blood pressure and heart rate monitor, attached to a car driver to detect drowsiness. The proposed measurement tool monitors all retrieved data to measure the fatigue condition of the driver. The main purpose of this research is to analyze the effectiveness of proposed wristband to collect the blood pressure and heart rate pattern for indicating drowsiness symptoms. This research concludes that car drivers' drowsiness can be detected by monitoring their heart rate and blood pressure using the proposed wristband. This research can be expanded in the future as a mitigation system to prevent car accidents caused by drivers' drowsiness. It can be expanded as an integrated Internet of Things system in a smart car that can alert a driver to take a rest when the system indicates that the driver is in a fatigue condition. When this integrated system has been developed well, the car accidents caused by driver drowsiness can be effectively prevented so that the number of car accident victims in Indonesia will be minimized.