Miracle-dz/UniFAR-FTUs huggingface dataset:
Surface-enhanced near-infrared absorption (SENIRA) of C-H and N-H groups with gold nanoarray

Excitation of localized surface plasmon resonance in noble metal nanoparticles leads to enhancement and localization of electromagnetic fields in the immediate vicinity of nanoparticles. These properties may be employed to amplify the lightmatter interaction in the near-infrared range where the overtone molecular vibrations are situated. Since the overtone vibration bands are much weaker than the fundamental bands, the amplification is essential. Here we explored SENIRA in the framework of molecular overtones sensing, particularly, those overtones that correspond to the C-H (1676 nm) and NH (1494 nm) stretching modes overtones. The gold nanorods (GNRs) are placed on the dielectric substrate and embedded into a thin layer of organic probe molecules (N-Methylaniline). The dispersion characteristics of N-Methylaniline, namely, its wavelength-dependent absorption and refractive indices in the spectral vicinity of the overtone transitions were fully taken into account. To find out the enhancement of overtone transitions provided by the GNR, we numerically calculated the differential transmission (DT) as a function of the gold nanoantenna’s size and grating periods. The computational results evidence that in sparse arrays of GNRs when the near fields of the neighbor GNRs do not overlap with each other, the differential transmission of stretching overtone modes shows the resonance at the right spectral position which is around 8.8 times larger as compared to the absorption of the bare molecular film of the same thickness. Thus, the obtained results substantiate a new sensing spectroscopy concept for identification of versatile “fingerprints” in the near-IR range based on plasmon-overtones interactions.
Adaptation of Unified Dosimetry Index (UDI) and Critical Organ Scoring Index (COSI) for Target and Organ at Risk (OAR) in Prostate IMRT Technique

The aim of the study is to formulate a dosimetry index that can be used for Quality assessment of IMRT treatment plans of prostate site. To compare different radiotherapy plans different indices are utilized. The present study will attempt to combine all the indices into one unified quality index which can define the quality of a treatment plan and serve as a quality indicator of treatment plan developed among similar and different modalities. This quality index will incorporate homogeneity index, conformity index, dose gradient and coverage index resulting in a direct comparison to an ideal plan. We developed another index in this study related to sparing of organs i.e. UDI (OARs) that incorporate the doses of OARs to compare which plan is optimum in terms of target coverage and OARs sparing. In comparison to this UDI (OARs) another work was done to analyze the dosimetry of overall plan including target coverage and organ at risk sparing i.e. critical organ scoring index (COSI). To validate UDI (Target), UDI (OARs) and COSI, 22 patients were studied which were planned on IMRT. We also define the ranking of the plan according to their target coverage and organ sparing quantities as ‘Excellent’, ‘Good’, ‘Average’ or ‘Poor’ plan. UDI index for the target and organ at risk is found to be a useful tool to quantify a treatment plan quality when volumes with different dose prescription are treated. Keywords: Treatment planning system, Conformity index, Homogeneity index, Dose coverage, Dose gradient, Critical organs DOI : 10.7176/CMR/12-1-04 Publication date: January 31 st 2020
DGINN, an automated and highly-flexible pipeline for the detection of genetic innovations on protein-coding genes

Adaptive evolution has shaped major biological processes. Finding the protein-coding genes and the sites that have been subjected to adaptation during evolutionary time is a major endeavor. However, very few methods fully automate the identification of positively selected genes, and widespread sources of genetic innovations as gene duplication and recombination are absent from most pipelines. Here, we developed DGINN, a highly-flexible and public pipeline to Detect Genetic INNovations and adaptive evolution in protein-coding genes. DGINN automates, from a gene’s sequence, all steps of the evolutionary analyses necessary to detect the aforementioned innovations, including the search for homologues in databases, assignation of orthology groups, identification of duplication and recombination events, as well as detection of positive selection using five different methods to increase precision and ranking of genes when a large panel is analyzed. DGINN was validated on nineteen genes with previously-characterized evolutionary histories in primates, including some engaged in host-pathogen arms-races. The results obtained with DGINN confirm and also expand results from the literature, establishing DGINN as an efficient tool to automatically detect genetic innovations and adaptive evolution in diverse datasets, from the user’s gene of interest to a large gene list in any species range.
EFL TEACHERS’ AND LEARNERS’ PERSPECTIVES ON THE PRINCIPLES OF INSTRUCTED LANGUAGE LEARNING: CONFLICT OR CONSENSUS?

The developmental nature of second language acquisition research has resulted in various and at times seemingly contradictory theories, methods and approaches. In 2005, Rod Ellis published his “Principles of Instructed Language Learning,” which he considered to be a set of teaching “generalisations” that could stimulate debate and reflection among teachers in the “post-methods era” (Richards & Rodgers, 2014). The purpose of this study was to investigate Ellis’s principles in terms of their perceived relevance and applicability in an adult EFL learning environment. In order to achieve this aim, a mixed methods research approach was utilised. Separate questionnaires were administered to seventy-one students and eight teachers employed in the English Language Department of a Training Institute in Doha, Qatar. Additionally, thirteen students participated in two – single sex – focus group sessions. The results revealed consensus between students and teachers regarding the importance they placed on some principles, but not others, particularly the contentious issue of meaning vs. form . Furthermore, while both groups emphasised the importance of interaction , many students nonetheless felt uneasy interacting in English with other Arabic speakers. A further key finding was that neither party clearly understood the concept of the learner’s built-in syllabus . The principal conclusion is that the best way to deal with the aforementioned anomalies involves experimentation with task-based approaches as these allow for a focus on meaning, opportunities for interaction, and a retrospective focus on form via corrective feedback, which takes into account the learner’s built-in syllabus. DOI : doi.org/10.24071/llt.2020. 230105
QUALITY OF SPECIALTY NATURAL COFFEE STORED IN DIFFERENT PACKAGES IN BRAZIL AND ABROAD

A challenge in the packaging and export of specialty coffees is to avoid green coffee bean storage and transport conditions that negatively affect the sensory quality of the roasted beans. This study evaluated green beans of specialty coffees in eight types of packaging storaged in in a warehouse in Pocos de Caldas, MG, Brazil, for 18 months (Brazilian phase) and subject to sea transport and subsequent storage at a specialty coffee import company (export phase) in the United States, where it remained stored for 14 months. Physical, chemical, and sensory analyses of the beans were performed in the Brazilian phase and export phase. Green coffee beans stored in high-barrier packages had the best conserved quality. Packages with little or no barrier were not adequate for packaging or exporting of specialty coffees. Beans in high-barrier packaging maintained their quality for long periods, and this type of packaging is recommended for specialty coffee storage and export.
Deepbot: A Deep Neural Network based approach for Detecting Twitter Bots

Social networks have played a very critical role in very aspect of our daily life. However, a wide variety of bots have been found which are designed for some malicious purposes such as spreading spam mes- sages and faking news. Although various techniques have been proposed, this task is still challenging if we want to judge whether the tweets are posted by a bot or not merely based on the textual information. For this challenge, the Deepbot is designed which adopts the Bi-LSTM model to analyze tweets and a Web interface is provided for public access which is developed using Web service. From our empirical studies, this system can achieve better classification accuracy.
The Convergence Study of Nursing Students' Knowledge, Attitudes and Preventive Behaviors against MERS in South Korea

MERS outbreak in Korea was related to healthcare-associated infections. The number of healthcare workers infected with MERS were 39, of which 15 were nurses. We investigated knowledge, attitudes and preventive behaviors against MERS in nursing students who will serve as future nurses. This is a cross-sectional study using a questionnaire survey. Data were collected from 350 nursing students from April to May 2016. As a result, there was a statistically significant positive correlation between attitudes and prevention behaviors against MERS. (r=.387, p <.001). The effect of knowledge and attitudes on preventive behaviors against MERS was analyzed by 15.2% of the explanatory power of regression model and statistically significant by regression equation (F = 31.081, p <.001). This study suggests that nursing students need convergence educational programs to improve their attitudes and preventive behaviors against infectious diseases such as MERS. •
Cultivating Racial Solidarity Among Mathematics Education Scholars of Color to Resist White Supremacy

In this paper, we propose a racial solidarity praxis in mathematics education grounded in Black-, Latinx-, and Indigenous-led scholarship and their respective communities’ joining efforts to combat White supremacy. Increased solidarity across racial groups in mathematics education could illuminate new ways of nourishing and affirming Indigenous, Latinx, and Black students’ racial identities and cultural strengths. We leverage four frameworks: (1) Whiteness as property (a tenet of Critical race theory) and (2) Tribal Critical Race Theory; (3) Latino Critical Theory; and (4) pedagogy of solidarity, to conceptualize the interdependence required for solidarity work and to expose how White supremacy is maintained overtly and covertly in mathematics curriculum, policies and practices. This study outlines the nuances across each community of scholars, drawing on their strengths to combat oppressive educational structures for students. The authors conclude in solidarity, focusing on the ways our communities have sought to challenge White supremacy and deficit framings of our students, families, and communities. Our hope in bringing these bodies of literature together is to invite others within (and outside of) the field of mathematics education to co-imagine how we might engage our work synergistically. It is through a collectivizing of efforts that we imagine a racial solidarity praxis that begins to erode the power of White supremacy in math education because of the unique and unassimilable strengths and priorities of each community engaged.
Quantifying regional effects of plastic mulch on soil nitrogen pools, cycles, and fluxes in rain‐fed agroecosystems of the Loess Plateau

Farmland surface soil mulching with plastic film is extensively used to enhance agricultural productivity in the Loess Plateau (LP). However, the effect of mulching on the key processes that dominate soil nitrogen dynamics is rarely assessed quantitatively. We quantified the responses of agroecosystem nitrogen cycling to plastic mulching using a comprehensive database drawn from mulching experiments in the LP. Our results indicated that through increasing the soil mineral and dissolved organic nitrogen concentrations, plastic mulching significantly enhanced the soil nitrogen availability by 36.6% at the regional scale, compared with traditional nonmulching. Mulching pattern, nitrogen application, and soil type were found to be the most significant drivers in determining nitrogen availability. Furthermore, nitrogen gaseous releases and hydrological leaching were significantly reduced by 7.0% and 9.4%, respectively, under plastic mulching, which led to an insignificant change in the soil total nitrogen pool. Nitrogen input level and soil organic carbon appeared to be the most important factors influencing soil nitrogen losses. Critically, along with increased root residue inputs to soil and improved water thermal conditions under mulching, soil microbial activity was increased significantly. This was indicated by enhanced microbial biomass nitrogen and soil nitrogen‐related extracellular enzyme activity and was driven by nitrogen input, mulching duration, and soil carbon status. We generalize that in the rain‐fed agroecosystems of the LP, plastic mulch will have little impact on nitrogen pool size, largely due to reduced gaseous and hydrological nitrogen losses and increased crop‐sourced nitrogen inputs, but will strongly stimulate microbial growth, metabolism, and activities, which consequently will speed up biogeochemical cycles of soil nutrients.
Statement on the safety of synthetic l‐ergothioneine as a novel food – supplementary dietary exposure and safety assessment for infants and young children, pregnant and breastfeeding women

Abstract Following a request from the European Commission, the EFSA Panel on Dietetic Products, Nutrition and Allergies (NDA) was asked to provide a supplementary dietary exposure and safety assessment of synthetic l‐ergothioneine for those groups of the population which had been excluded by the applicant in the original application, i.e. infants and young children (i.e. toddlers), pregnant and breastfeeding women. Thus, intake estimates were calculated for these population groups and the following maximum anticipated daily intakes of l‐ergothioneine from the NF, in addition to the background diet, were calculated: 2.82 mg/kg body weight (bw) per day for infants, 3.39 mg/kg bw per day for toddlers and 1.31 mg/kg bw per day for adults including pregnant and breastfeeding women. The Panel considers that based on the overall toxicological data the no‐observed‐adverse‐effect level (NOAEL) of 800 mg/kg bw per day as established in the original assessment also pertains to pregnant and breastfeeding women as well as to young children (i.e. toddlers) and infants. The corresponding margins of exposure (i.e. the ratio between the NOAEL and the maximum anticipated daily intakes) are 284 for infants, 236 for young children and 610 for pregnant and breastfeeding women. These margins of exposure are considered sufficient. The Panel concludes that the novel food, synthetic l‐ergothioneine, is safe under the proposed uses and use levels for infants, young children (i.e. toddlers) and pregnant and breastfeeding women.
Dressing and Securement of Peripheral Arterial Catheters: A Pilot Randomised Controlled Trial

The purpose of this research was to assess the feasibility of the trial design and elements for future extensive study to provide evidence of the effectiveness of novel dressing/securement technologies to prevent catheter failure in peripheral arterial catheters in a larger research setting. Peripheral arterial catheters are a type of intravascular catheter that is widely used in the care of critically ill patients. The catheter insertion site is usually covered with a commercially produced transparent dressing to maintain the position of the catheter, as well as endeavouring to prevent microbial entry to the wound. Arterial catheters may accidentally fall out, become blocked, or become infected, causing catheter failure, interrupted therapy, painful reinsertion, and decreased patient satisfaction. The infection risks of arterial catheters have often been underestimated. Inadequate peripheral intravascular catheter securement remains a poorly researched area of patient care, with a paucity of quality studies. Improved securement would likely prevent many cases of catheter failure. The aim was to determine initial effectiveness of one dressing and two securement methods with the potential to minimise failure in peripheral arterial catheters compared with usual care, in a pilot study. Specified feasibility objectives for this pilot trial were to be considered successful if 90 out of 120 patients (75%) fulfilled the feasibility criteria regarding recruitment, delivery and adherence, retention, and patient/staff satisfaction with the study products. This would show that the research methods were suitable for use in a larger trial.
Ethnobotanical uses of ‘cemcem’ (Spondias pinnata (L. F.) kurz; anacardiaceae) leaves in bali (Indonesia) and its antioxidant activity

Spondias pinnata is commonly known in international fruit trade markets as wild mango or hog plum. The use of S. pinnata leaves is considered an integral part of the Balinese ethnobotanical tradition, and is used to make a herbal-medicinal beverage. This present study is not only to improve the historical and ethnobotanical knowledge of this important species, but also to analyse the antioxidant properties and polyphenolic content of the plant in order to confirm, if any, the traditionally well-known beneficial effects. Ethnobotanical data were collected using semi-structured interviews through the snowball method. Informants were asked to determine how familiar they were with S. pinnata and its ethnobotanical values. In order to confirm antioxidant activity, the DPPH and ABTS•+ radical scavenging assays method, together with the Folin-Ciocalteu analysis were carried out. The present study indicated that S. pinnata possesses strong antioxidant activities based on the ABTS•+ and DPPH assays. It was also found that 100% methanolic extracts of S. pinnata leaves contain large amounts of phenolic compounds mainly responsible for free radical scavenging activities. Further study is essential in order to better understand the therapeutic values of S. pinnata leaves and its role in the prevention and treatment of ailments and chronic diseases mentioned in this study, such as diabetes, heartburn, and urolithiasis.
Application of the simulated annealing algorithm to the correlated WMP radiation model for flames

Several alternatives have been proposed to model the radiation profile emitted by flames. Among them there is the weighted-multi-point-source-model (WMP), which is able to provide good predictions for medium and far distances. Despite being a simple model, the determination of its parameters can be difficult, which creates the opportunity to apply optimisation methods in order to find the best answer. Moreover, correlations of these parameters as function of flame variables can be applied aiming to relate the model to the physical phenomenon, making the problem even harder to solve. Previous studies applied the Generalised Extreme Optimisation (GEO) to find the best possible combinations of these parameters, but there is a chance that other methods could improve the results considerably. This study has the objective to further explore the WMP model as formulated previously in the literature and apply the Simulated Annealing optimisation method to assess if the answers could be improved. The same correlation and experimental data were used as well. A total of 77 different cases were explored over 50 runs each, configuring the answers statistically significant. The SA method had better performance, showing similar average results for the objective function, but overall best answers. Abbreviations: GEO: generalised extreme optimisation; PSO: particle swarm optimisation; SA: simulated annealing; SP: single point source model; WMP: weighted multi-point source model
New Distance Measures for Dual Hesitant Fuzzy Sets and Their Application to Multiple Attribute Decision Making

Multiple attribute decision making (MADM) is full of uncertainty and vagueness due to intrinsic complexity, limited experience and individual cognition. Representative decision theories include fuzzy set (FS), intuitionistic fuzzy set (IFS), hesitant fuzzy set (HFS), dual hesitant fuzzy set (DHFS) and so on. Compared with IFS and HFS, DHFS has more advantages in dealing with uncertainties in real MADM problems and possesses good symmetry. The membership degrees and non-membership degrees in DHFS are simultaneously permitted to represent decision makers’ preferences by a given set having diverse possibilities. In this paper, new distance measures for dual hesitant fuzzy sets (DHFSs) are developed in terms of the mean, variance and number of elements in the dual hesitant fuzzy elements (DHFEs), which overcomes some deficiencies of the existing distance measures for DHFSs. The proposed distance measures are effectively applicable to solve MADM problems where the attribute weights are completely unknown. With the help of the new distance measures, the attribute weights are objectively determined, and the closeness coefficients of each alternative can be objectively obtained to generate optimal solution. Finally, an evaluation problem of airline service quality is conducted by using the distance-based MADM method to demonstrate its validity and applicability.
Gastric Cancer Prediction: A Comparative Analysis of Methodologies and Performances in Deep Learning Perspective

Abstract—Cancer is the second leading cause of death globally, and Globally, about 1 in 6 deaths is due to cancer. Among the various types of cancers gastric cancer which starts from epithelial cells on the gastric mucosa is one of the common malignancies cancer disease. In recent years,deep learning is widely used by medical professionals and researchers to discover the hidden patterns in complex images and data and thus serves the healthcare industry better. Deep learning in healthcare provides doctors the analysis of any disease accurately and helps them treat them better, thus resulting in better medical decisions.The goal of deep learning is to understand the structure of data, so that accurate predictions can be made based on the properties of that data. Huge complex datasets which are beyond the scope of human capability, can be processed using deep learning which can then reliably convert analysis of that data into clinical insights that aid physicians in planning and providing care, ultimately leading to better outcomes with lower costs. In this study, an analysis is performed for gastric cancer prediction with deep learning perspective.
Microbubble resonators combined with a digital optical frequency comb for high-precision air-coupled ultrasound detectors

Fast and sensitive air-coupled ultrasound detection is essential for many applications such as radar, ultrasound imaging, and defect detection. Here we present a novel approach based on a digital optical frequency comb (DOFC) technique combined with high-Q optical microbubble resonators (MBRs). DOFC enables precise spectroscopy on resonators that can trace the ultrasound pressure with its resonant frequency shift with femtometer resolution and sub-microsecond response time. The noise equivalent pressure of air-coupled ultrasound as low as 4.4 mPa/√Hz is achieved by combining a high-Q (∼3×107) MBR with the DOFC method. Moreover, it can observe multi-resonance peaks from multiple MBRs to directly monitor the precise spatial location of the ultrasonic source. This approach has a potential to be applied in 3D air-coupled photoacoustic and ultrasonic imaging.