Miracle-dz/UniFAR-FTUs huggingface dataset:
Recent advances in nanotechnology for eradicating bacterial biofilm

Microorganisms grouped together into spatially-organized communities called biofilms, are the cause of dramatic chronic infections in plants, animals and humans. In this review, the characteristics of biofilms and their interactions with antimicrobials are first described. Limitations of antibiotic treatments are discussed, and state-of-the-art alternative approaches based on the use of polymer, lipid, organic, inorganic and hybrid nanoparticles are presented, highlighting recent achievements in the application of nanomaterials to the field of theranostics for the eradication of biofilm. The aim of this review is to present a complete vision of nanobiotechnology-based approaches for eradicating bacterial biofilms and fighting antimicrobial tolerance.
LARGE-SCALE ANALYSIS OF LYRICS AND MELODIES IN CANTONESE POP SONGS

In pop songs of tonal languages, researchers have found that the tones of lyrics characters and the melodies contours have similar patterns of motion. However, no large-scale quantitative analysis has been done to generalize the phenomenon. The current study explores the extent of relationship between lyrics and melodies quantitatively in a large dataset of pop songs written in Cantonese, a language with one of the richest tonal systems. To align the lyrics with corresponding melody, the singing voices are extracted from the polyphonic music tracks and automatic speech recognition (ASR) systems are applied to the singing voices to detect the lyrics content as well as character-wise timestamps. The transcribed lyrics are matched with true lyrics using Levenshtein distance and then further corrected to ensure the lyrics are precisely sung in each melody segment. Finally, the notes of the melody are extracted and compared with frequencies of generated speech to obtain quantitative relationship.
Health and food security nexus: Evidence from vulnerable rural households in Bangladesh

Health and wellbeing is a crucial enabler for efficient farm and non-farm activities and determines individuals’ and households’ ability to achieve their livelihood objectives. Health status of household heads (earning member) critically affects household food security, which has important policy implications. This study examines the determinants of household food security. It also focuses on the impact of household head (earning member) physical health status on attaining food security by using the survey data of 380 most vulnerable riparian households in Bangladesh. The results reveal that riverine households’ lack of access to many basic necessities and services such as food, safe drinking water, education and health results in increased vulnerability to food insecurity which could lead to an unfortunate vicious cycle of poverty. Model results indicate that household heads’ education, household size, adoption of livestock and access to non-farm earnings also affect food security. Importantly, evidence suggests that access to improved health care also needs policy support in parallel with improved access to food to achieve and sustain long-term food security in Bangladesh.
MILLION SONG SEARCH: WEB INTERFACE FOR SEMANTIC MUSIC SEARCH USING MUSICAL WORD EMBEDDING

We present a web interface for large-scale semantic search using a musically customized word embedding in the back-end. The musical word embedding represents artist entities, track entities, tags, and ordinary words in a single vector space. It is learned based on the afﬁnity between the words and the entities using a wide spectrum of text data including Wikipedia, music review, and music tags. The system can allows users to type a query within 9.8M vocabulary words in the musical word embedding. It also supports a multi-query blending function using a semantic averaging of the queries to provide more reﬁned search.
Influential Factors on Language Creativity of College Students in ESL Writing

Writing ability is a very important language output ability. Current studies on second language writing mainly focus on writing text, writing process, writing teaching methods, writing assessment and other aspects. Relatively few studies on writing language creativity focus on the measurement of language creativity in writing. Based on interpretation of China’s Standards of English Language Ability (CSE) for writing, this study developed a new scale to explore the factors affecting language creativity in English writing. This scale was used to measure 329 sophomores majoring in English. The data were analyzed by factor analysis and regression analysis. It was concluded that four influencing factors including Thinking Ability, Expressing Ability, Information and Technology Literacy and Knowledge and Cultural Literacy had a positive correlation on writing language creativity in ESL writing, and there was also a correlation between the four factors.
OUTLIER DETECTION USING IOT AND MACHINE LEARNING

: Outliers once upon a time regarded as noisy data in statistics, has turned out to be an important problem which is being researched in diverse fields of research and application domains. Many outlier detection techniques have been developed specific to certain application domains, while some techniques are more generic. Some application domains are being researched in strict confidentiality such as research on crime and terrorist activities. The techniques and results of such techniques are not readily forthcoming. A number of surveys, research and review articles and books cover outlier detection techniques in machine learning and statistical domains individually in great details. In this paper we make an attempt to bring together various outlier detection techniques, in a structured and generic description. With this exercise, we hope to attain a better understanding of the different directions of research on outlier analysis for ourselves as well as for beginners in this research field who could then pick up the links to different areas of applications in details.
Ultra-broadband, high-contrast, high-resolution speckle imaging

When observing targets in the near-Earth space environment using ground-based telescopes, the Earth’s turbulent atmosphere and the telescope’s aperture combine to act as a low-resolution spectrometer. The light at disparate wavelengths from a given point in the object lands at different spatial locations in the focal plane. Here we investigate the feasibility of capitalizing on this effect to provide snapshot hyper-spectral imaging of targets in the near-Earth space environment through ultra-broadband speckle imaging. In particular, we focus on the potential for using ultrabroadband speckle images for high-resolution, high-contrast imaging of closely spaced objects with a large contrast in brightness.
AN AI INTEGRATED METHOD FOR PERMEABILITY PREDICTION IN PETROLEUM RESERVOIR

This paper introduces and demonstrates an AI integrated method (“AIM”) for predicting reservoir permeability of sedimentary rocks in drilled wells in the petroleum exploration and development industry. The method employs Takagi-Sugeno’s fuzzy reasoning, and its fuzzy rules and membership functions are automatically derived by neural networks and floating-point encoding genetic algorithms. The method is trained with known data and tested with unseen data. The results show that AIM has a good generalisation capability and is an effective approach for large scale industrial application.
Ion Current Screening Modeling of the Ion–Weibel Instability

Ion–Weibel instability (IWI) is an important mechanism of generating a magnetic field in supernova remnants; it plays a key role in the generation of high-energy cosmic rays. Computational efficiency has been a bottleneck in numerical exploration of the large-scale evolution of IWI. Here I report a new hybrid particle-in-cell (PIC) method that can quickly simulate IWI. The method is based on a new model that describes the relation of the ion current and its magnetic field under the electron screening. The new method’s computational efficiency is nearly two orders of magnitude higher than that of the PIC method. This method is suitable for the full-scale simulation of the IWI in laser-plasma experiments and supernova remnants.
A Robust Estimation of Lorentz Invariance Violation and Intrinsic Spectral Lag of Short Gamma-Ray Bursts

Gamma-ray bursts (GRBs) have been identified as one of the most promising sources for Lorentz invariance violation (LIV) studies due to their cosmological distance and energetic emission in wide energy bands. However, the arrival-time difference of GRB photons among different energy bands is affected not only by the LIV effect but also by the poorly known intrinsic spectral lags. In previous studies, assumptions of spectral lag have to be made which could introduce systematic errors. In this paper, we used a sample of 46 short GRBs (SGRBs), whose intrinsic spectra lags are much smaller than long GRBs, to better constrain the LIV. The observed spectral lags are derived between two fixed energy bands in the source rest frame rather than the observer frame. Moreover, the lags are calculated with the novel Li–CCF method, which is more robust than traditional methods. Our results show that, if we consider LIV as a linear energy dependence of the photon propagation speed in the data fit, then we obtain a robust limit of E QG > 1015 GeV (95% CL). If we assume no LIV effect in the keV–MeV energy range, the goodness of data fit is equivalently as well as the case with LIV and we can constrain the common intrinsic spectral lags of SGRBs to be 1.4 ± 0.5 ms (1σ), which is the most accurate measurement thus far.
iSHELL: a 1–5 micron R = 80,000 Immersion Grating Spectrograph for the NASA Infrared Telescope Facility

iSHELL is a 1.06–5.3 μm high spectral resolution spectrograph built for the 3.2 m NASA Infrared Telescope Facility (IRTF) on Maunakea, Hawaii. Dispersion is accomplished with a silicon immersion grating in order to keep the instrument small enough to be mounted at the Cassegrain focus of the telescope. The white pupil spectrograph produces resolving powers of up to about R ≡ λ/δλ = 80,000 (0.″375 slit). Cross-dispersing gratings mounted in a tiltable mechanism allow observers to select different wavelength ranges and, in combination with a slit wheel and Dekker mechanism, slit widths ranging from 0. ″375 to 4. ″0 and slit lengths ranging from 5″ to 25″. One Teledyne 2048 × 2048 HAWAII-2RG array is used in the spectrograph, and one Raytheon 512 × 512 Aladdin 2 array is used in a 1–5 μm slit viewer for object acquisition, guiding, and scientific imaging. iSHELL has been in productive regular use on IRTF since first light in 2016 September. In this paper we discuss details of the science case, design, construction and astronomical use of iSHELL.
Tissue fibroblasts are a critical source of prostacyclin and anti-thrombotic protection

Prostacyclin is one of the bodies fundamental signalling pathways. It has long been considered principally anti-thrombotic hormone derived from the vascular endothelium. The role of non-vascular sources in prostacyclin synthesis has not been systematically evaluated, however, due to a lack of tools resulting in an underappreciation of its role in other contexts. Here we used cellspecific knockout mice and human tissues to show that lung, and other tissues, are powerful producers of prostacyclin independent of their vascular components. Instead, in mice and humans, lung prostacyclin synthesis is associated with fibroblasts. The fibroblast-derived prostaglandins enter the circulation and provide systemic anti-thrombotic protection. These observations define a new paradigm in prostacyclin biology in which fibroblast/non-vascular-derived prostacyclin works in parallel with endothelium-derived prostaglandins to control cardiovascular health and potentially a broad range of other biology. These results may explain how local diseases of the lung and elsewhere result in cardiovascular risk.
Research on risk management application of construction site

Theory of risk management has been applied to engineering,procurement and construction phase of a project prevailingly,most of foreign enterprises have successfully been controlling risk and preventing accidents using the theory.In generally,construction work is composed of civil work,installation and test activities,and each activity can be divided into work steps among which the work flow is dominated by the work procedure or instruction.As per each work step,if the hazard can be identified,the risk can be assessed and the risk control can be implemented before the commencement of any work activity,the risk should be eliminated or mitigated "at source". Taken the diversity of work activities and the shift of workforce,the risk management theory was introduced into the risk control of work activity in order to provide a practicable means for all level of site management.
Beamforming seizures from the temporal lobe

Background Surgical treatment of drug-resistant temporal lobe epilepsy (TLE) depends on proper identification of the seizure onset zone (SOZ), and differentiation of mesial, temporolimbic seizure onsets from temporal neocortical seizure onsets. Non-invasive source imaging using electroencephalography (EEG) and magnetoencephalography (MEG) can provide accurate information on interictal spike localization; however, EEG and MEG have low sensitivity for epileptiform activity restricted to deep temporolimbic structures. Moreover, in mesial temporal lobe epilepsy (MTLE), interictal spikes frequently arise in neocortical foci distant from the SOZ, rendering interictal spike localization potentially misleading for presurgical planning. Methods In this study, we used two different beamformer techniques applied to the MEG signal of ictal events acquired during EEG-MEG recordings in six patients with TLE (three neocortical, three MTLE). The ictal source localization results were compared to the patients’ ground truth SOZ localizations determined from intracranial EEG and/or clinical, neuroimaging and postsurgical outcome evidence. Results Beamformer analysis proved to be highly accurate in all cases and able to reliably identify focal seizure onsets localized to mesial, temporolimbic structures. In three patients, interictal spikes were either absent, too complex for inverse dipole modeling, or localized to anterolateral temporal neocortex distant to a mesial temporal SOZ. Conclusions This report demonstrates the suitability of MEG beamformer analysis of ictal events in TLE, which can supersede or complement the traditional analysis of interictal spikes. The method outlined is applicable to any type of epileptiform event, greatly expanding the information value of MEG and broadening its utility for presurgical recording in epilepsy.
NOVEL FREQUENCY DOMAIN FEATURES FOR THE PATTERN CLASSIFICATION OF PARTIAL DISCHARGE SIGNALS

The detection of partial discharge (PD) signals and identifying its patterns has been an area of interest in the analysis of insulation defects in high voltage cables. The features for classifying PD patterns are generally acquired from time-frequency domain analysis. This paper investigates the use of sub-bands to extract novel frequency domain features for PD pattern classification. The discrete Fourier Transform maps the sampled PD signal into equivalent discrete frequency bins. The frequency bins are grouped such that they form N sub-bands. The log energy that corresponds to each sub-band is obtained and these energies are smoothed using the discrete cosine transform, thus providing N coefficients as features in the classification of PD signals via the sparse representation classifier. Three types of artificial PDs, namely surface, corona and internal discharges, are measured in a high voltage laboratory environment at different applied voltages. The data obtained is then divided into training and testing sets for classification purposes. Results show that the features obtained using sub-bands are robust under noisy conditions, and in combination with the sparse representation classifier, it provides a better classification rate of PD signals compared to features obtained using wavelet analysis.
Company Profit Prediction Based On Forecasting Of Port Throughput Using Time Series-Adaptive Neuro Fuzzy Inference System

As a maritime country, ports play an important role in economic development in Indonesia. Throughput is an important factor affecting Port Profits. This prediction is needed in an effort to find out the company's prospects, help estimate the long-term profitability of representatives, predict earnings, and estimate risk in investment. In this research, forecasting data throughput will be carried out, such as container traffic, number of ships, export traffics, goods traffic, animal flow and passenger traffic for the next year using Time Series-Adaptive Neuro Fuzzy Inference System (TS-ANFIS) as an input parameter in the decision support system. Before predicting the benefits of the port using the ANFIS method, principal component analysis (PCA) was applied to reduce parameters that did not sufficiently affect the profits of the port. The data used are time series data from 2009 to 2018. From the system built it is expected to be able to provide good results in predicting the value of port throughput using TS-ANFIS and to predict profit values using the ANFIS method. The best results from profit prediction using ANFIS obtained R2 of 0.947, RMSE of 28524582.39, MAPE of 14.74% and MAAPE of 0.145. From the prediction results, it can be used as a reference for company projections in investing, managing cash flow, managing assets and global bonds. KeywordsANFIS, PCA, Time Series, Throughput, Port, Profit.
Characteristic Features of the Transcriptome in a Rat Strain with Audiogenic Epilepsy

Audiogenic epilepsy (AE), developing in rodent strains in response to sound, is widely used as the model of generalized convulsive epilepsy, while the molecular mechanisms determining AE are currently poorly understood. The brain region that is crucial for AE development isthe inferior and superior colliculi (IC, SC). We compared IC-SC gene expression profiles in rats with different AE susceptibility using transcriptome analysis.The transcriptomes were obtained from the IC-SC of Wistar rats (with no AE), Krushinsky-Molodkina (KM) strain rats (100% AE susceptible), and ”0” strain rats (with no AE) selected from F2 KM x Wistar hybrids for AE absence. KM gene expression displayed characteristic differences inboth of the strains that were not susceptible to AE. There was increased expression of a number of genes responsible for positive regulation of the MAPK signaling cascade, as well as of genes responsible for the production of interferon and several other cytokines. An increase in the expression levels of theTTR gene was found in KM rats, as well as significantly lower expression of the Msh3 gene (involved in post-replicative DNA repair systems). AE was also describedin the 101/HY mouse strain with a mutation in the locus controlling DNA repair. The DNA repair system defects could be the primary factor leading to the accumulation of mutations, which, in turn, promote AE. Keywords: udiogenic seizure, KM strain, transcriptome, TTR gene, Msh3 gene, DNA repair
Vibration Signal Analysis and Application of Drill Stem Based on STFT

Mutual action of aiguille and rock face would result in strong vibration of drill string during rotary drilling and vibration signals of drill string varied with different hardness medium.Applying short-term Fourier transformation(STFT) time-frequency method to analyzing vibration signals of drill string in 3 medium models.Time-frequency characteristic difference of different medium was collected.Statistical analysis combined with energy accumulation value of high frequency band was used to predict drilling state and obtain strata information.Test result showed that STFT could effectively distinguish different medium and was practicable.
Femtosecond pump-probe spectroscopy for remote sensing of liquid-liquid interface

We report results establishing that detection of the liquid-liquid interface is possible through femtosecond pumpprobe spectroscopy. In particular, we use femtosecond laser pulses to pump and probe the dynamics of infra-red dye molecules in a liquid pair that can form an interface. We demonstrate that an interface formation can be detected from such femtosecond dynamical study of the dye molecule. The importance of obtaining the molecular description on the relation between the dynamics of solute molecules and solute-solvent interactions arises from the fact that the dynamic and static properties of dye molecules are strongly affected by the surrounding solvent molecules. © Anita Publications. All rights reserved.
Financial Development and Economic Growth in Bangladesh and India: Evidence from Cointegration and Causality Tests

The relationship between financial development and economic growth has been the subject of increasing attention over the 21th century. This study is basically an econometric analysis of financial development and economic growth in Bangladesh and India involving time series data of GDP, domestic credit provided by financial sector, domestic credit to private sector,and broad money from 1974 to 2015.This study employs Johansen’s multivariate cointegration procedure to test the long run relationship. In addition, vector error correction model is used to test the causal relationship between financial development and economic growth. To test thestatioanrity properties of the variables we use ADF and PP unit root tests and find that the variables are stationary in their difference form. Johansen’s cointegration test reveals the presence of long term relationship between financial development and economic growth in Bangladesh and India. Results of ECM provide the evidence of bidirectional causal relationship between financial development and economic growth in both countries.Thus, right and effective monetary policy is very important to accelerate economic growth as both supply-leading and demand-following hypothesesare effective in Bangladesh and India.
Japanese Journal of Applied Psychology

The present study aimed to explore the important factors related to perceived benefit in daily risk-taking behaviors. A web-based questionnaire survey was conducted for five hundred respondents with a wide range of ages. The list of risk-taking behaviors in daily life was developed by consulting previous studies. The perceived benefit of such behaviors was evaluated using several indicators (e.g. whether the benefit can be obtained with certainty). Results of factor analysis indicated that perceived benefit in risk-taking behavior was mainly evaluated by the intuitive thinking process. Multiple regression analysis also revealed the important effect of such intuitive thinking process on intention of risk-taking. Our research suggested the important components of perceived benefit in risk-taking behaviors. The findings should have also been discussed from the viewpoints of several theories such as the dual process theory used in industrial and social psychology.