Miracle-dz/UniFAR-FTUs huggingface dataset:
countfitteR: efficient selection of count distributions to assess DNA damage

Background DNA double-strand breaks can be counted as discrete foci by imaging techniques. In personalized medicine and pharmacology, the analysis of counting data is relevant for numerous applications, e.g., for cancer and aging research and the evaluation of drug efficacy. By default, it is assumed to follow the Poisson distribution. This assumption, however, may lead to biased results and faulty conclusions in datasets with excess zero values (zero-inflation), a variance larger than the mean (overdispersion), or both. In such cases, the assumption of a Poisson distribution would skew the estimation of mean and variance, and other models like the negative binomial (NB), zero-inflated Poisson or zero-inflated NB distributions should be employed. The model chosen has an influence on the parameter estimation (mean value and confidence interval). Yet the choice of the suitable distribution model is not trivial. Methods To support, simplify and objectify this process, we have developed the countfitteR software as an R package. We used a Bayesian approach for distribution model selection and the shiny web application framework for interactive data analysis. Results We show the application of our software based on examples of DNA double-strand break count data from phenotypic imaging by multiplex fluorescence microscopy. In analyzing numerous datasets of molecular pharmacological markers (phosphorylated histone H2AX and p53 binding protein), countfitteR demonstrated an equal or superior statistical performance compared to the usually employed two-step procedure, with an overall power of up to 98%. In addition, it still gave information in cases with no result at all from the two-step procedure. In our data sample we found that the NB distribution was the most frequent, with the Poisson distribution taking second place. Conclusions countfitteR can perform an automated distribution model selection and thus support the data analysis and lead to objective statistically verifiable estimated values. Originally designed for the analysis of foci in biomedical image data, countfitteR can be used in a variety of areas where non-Poisson distributed counting data is prevalent.
New Lead Free Halide Double Perovskite Materials: Potential Substitutes Towards Green Technology and Stable Optoelectronic Application

Explorations of new stable lead free perovskites have currently achieved substantial interest in the field of photovoltaics and optoelectronics as it tries to overcome the instability issue and avoid toxicity related with the lead based perovskites. We herein not only comprehensively tried to explain the experimentally synthesized two inorganic halide double perovskite materials but exploring their broader structural stability and also provide us a guideline to better understand their possible potential applications. For this purpose we performed density functional theory to investigate the structural, electronic, optical, elastic and thermoelectric properties of these materials. The stability of these cubic materials is validated by optimizing the structure, from the tolerance factor, mechanical stability test. These materials are found to be small band gap semiconductors with outshining optoelectronic performance. Due to high optical absorption, high conductivity and low reflectivity they have great potential to be used as a light absorbing material for photovoltaic application. Because, of small band gap we also tried to explore the variation of various transport properties with chemical potential. The semiconducting nature of materials results in ZT close to unity predicting its excellent application in thermoelectric technology.
Perceived Drivers of Food Insecurity and Coping Strategies of DACA-Eligible College Students–an Exploratory Study

ABSTRACT Eighteen Deferred Action for Childhood Arrivals (DACA)-eligible students at a Western US university completed a brief food insecurity survey. Eight participated in two focus groups to examine their food insecurity and associated coping strategies. Thirteen participants were food insecure. Drivers of food insecurity included ineligibility to secure federal aid, little time to prepare meals, and inadequate budgeting skills. Students coped with food insecurity at the personal level (e.g. rationing food) or receiving food from others (e.g. Relatives). The unique immigration status of DACA-eligible students contributes to their food insecurity, and policy change is needed to reduce this in higher education.
Long-Term Origin-Destination Demand Prediction With Graph Deep Learning

Accurate long-term origin-destination demand (OD) prediction can help understand traffic flow dynamics, which plays an essential role in urban transportation planning. However, the main challenge originates from the complex and dynamic spatial-temporal correlation of the time-varying traffic information. In response, a graph deep learning model for long-term OD prediction (ST-GDL) is proposed in this article, which is among the pioneering work that obtains both short-term and long-term OD predictions simultaneously. ST-GDL avoids the conventional multi-step forecasting and thus prevents learning from prediction errors, rendering better long-term forecasts. The proposed method captures time attributes from multiple time scales, namely closeness, periodicity, and trend, to study the features with temporal dynamics. In addition, two gate mechanisms are introduced over the vanilla convolution operation to alleviates the error accumulation issue of typical recurrent forecast in long-term OD prediction. A method based on graph convolution is proposed to capture the dynamic spatial relationship, which projects the transportation network into a graphical time-series. Finally, the long-term OD prediction results are obtained by combining the extracted spatio-temporal features with external features from the meteorological information. Case studies on practical datasets show that the proposed model is superior to existing methods in long-term OD prediction problems.
Morphophysiological traits of an amphibian exposed to historical industrial pollution in a Brazilian biodiversity hotspot

Industrial pollution is a significant global threat to biodiversity, but its consequences on rainforest ecosystems remain poorly understood. Amphibians are especially susceptible to pollutants released on natural environments due to their aquatic-terrestrial life cycle. Here, we explored the association of severe historical air, water, and soil pollution with physiological and morphological alterations on Rhinella ornata individuals, an endemic toad species of Atlantic Forest, a world biodiversity hotspot. We hypothesized that individuals sampled in sites closer to the pollution source will present worse indicators of health. As predicted, toads at decreasing distances from the pollution source presented enlargement of organs related to detoxification function (liver and kidneys) and compensatory immunological function (spleen). Contrary to our predictions, however, we do not found significant effects of proximity to the pollution source on individuals’ body condition index, on the indicative of fertility (testicles masses) or on macroparasite infection’s response (eosinophil counts). Surprisingly, proximity to the pollution source was associated with lower chronic stress levels (neutrophil/lymphocyte ratio) on individuals. We discuss which processes could promote the alterations found on the toads. We also discuss the possible acquirement of local resistance to contamination on toads populations closer from pollution source, giving the more than 60 years of exposure to chemical contaminants in the area.
A fuzzy best–worst method (BWM) to assess the potential environmental impacts of the process of ship recycling

ABSTRACT The marine environment has been under threat due to the residues and pollution created during the ship recycling process. Materials contained in ship structure or equipment are the main concern that causes pollution of soil, air, marine, and freshwater resources at the ship recycling process. Accordingly, chemical and biological contaminants that may be released to the environment are the main elements of the ship recycling process. The emphasis of this research is therefore on the assessment of materials found in the ship structure or equipment of hazardous materials. To do so, this paper has applied the best–worth method (BWM) using fuzzy sets. The sets are based on surveys and questionnaires answered by industry experts. The findings of the research show that H4 (heavy metal residues) (H6) (polychlorinated organic compounds (PCBs), tin compound tributyltin (TBT), and asbestos (H3) are the most hazardous materials. Therefore, the study results also have the potential to assist professionals, policymakers, and regulatory authorities in the successful handling of hazardous materials that may release into the environment during the recycling process of ships. Consequently, the research provides a robust analytical model to assess the actual hazardous materials for the prevention and control of environmental pollution.
Devising a method to remotely model and map the distribution of natural landscapes in Europe with the greatest recreational amenity value (cultural services)

With a growing emphasis on the societal benefits gained through recreation outdoors, a method is needed to identify which spaces are most valuable for providing those benefits. Social media platforms offer a wealth of useful information on where people prefer to enjoy the outdoors. We combined geotagged images from Flickr with several environmental metrics in a Maxent model to calculate the probability of a photograph being taken (the potential supply of recreational amenity). We then built a set of population density kernels to express the potential demand of recreational amenity. Linear regression was used to compare supply and demand layers to visitation records from 540 recreation sites across Europe. The result was a map estimating the number of visitors/km2/year. Our analysis showed that natural areas near population centres deliver more recreational benefit than attractive sites in remote locations. The former should therefore be prioritised by planners and policymakers seeking to protect or improve recreational amenity.
Multi-electron corrections in molecular high-order harmonic generation for different formulations of the strong-field

We investigate multi-electron corrections due to electron exchange between the multi-electron residual cation and the continuum electron in high-order harmonic generation of diatomic molecules in a static and analytic framework. These corrections are incorporated perturbatively around the highest occupied molecular orbital of aligned isoelectronic homonuclear and heteronuclear molecules, exemplied by N2 and CO, respectively. This is performed with the velocity and length forms of the dipole operator within the framework of the strong field approximation. We find that inclusion of the multielectron corrections has very little effect on the harmonic spectrum, suggesting that relaxation, excitation and the dynamic motion of the core are important in order to describe multielectron corrections has very little effects in molecular high-order high harmonic generation. © 2012 OSA.
An intervention study to improve primary school students’ self-regulated strategy use in English writing through e-learning in Hong Kong

Abstract The present study reports on the effects of a self-regulated (SRL) writing strategy-based intervention supported with e-learning tools on SRL strategy use in English writing with 468 Hong Kong primary school students. The changes to the students’ motivation in English writing, and their e-learning acceptance were also measured. The study adopted a pretest and posttest design and the data was collected through a questionnaire, which consisted of three measures, i.e. SRL writing strategy use, motivation in English writing, and e-learning acceptance. The SRL writing strategy use measure included four types of strategies, i.e. planning, text-generating, monitoring, and revising. The motivation measure had two scales, i.e. interest and self-efficacy, and the e-learning acceptance measure included four scales, i.e. perceived usefulness, perceived ease of use, attitude and continuance intention. The intervention saw significant improvements on the students’ use of all four types of SRL writing strategies. Positive changes also took place to one scale of motivation, i.e. interest, and three scales of e-learning acceptance, i.e. perceived usefulness, attitude and continuance intention. There was no significant improvement to self-efficacy and perceived ease of use. Additionally, the correlations between all the scales became stronger after the intervention. Important implications for teaching ESL/EFL writing through e-learning are drawn.
Multi-agent cooperative multi-model adaptive guidance law

ABSTRACT A multi-agent engagement scenario is considered in which a high-value aircraft launches two defenders to intercept two homing missiles aimed at the aircraft. Under the assumption that all aircrafts have first-order linear dynamic characteristics, a combined multiple-mode adaptive estimation (MMAE) and a two-way cooperative optimal guidance law are proposed for the target–defenders team. Considering the full cooperation of the target and both the two defenders, the two-way cooperative strategies provide the analytical expressions for their optimal control input, enabling the target–defenders team to intercept the missiles with minimal control effort. To successfully intercept the missiles, MMAE is used to identify the guidance laws adopted by the missiles and estimate their states. The simulation results show that the target cooperating with the defenders to perform lure manoeuvres for the missiles can improve the guidance performance of the defenders as well as reduce the control effort of the defenders for intercepting the missiles.
Simulation of transference regimes in BA-LIFT of water-glycerol and LIFT of high-viscosity silver pastes

Laser-Induced Forward Transfer (LIFT) is a direct-write laser technique for the transference of material in an enormous range of viscosities and rheological behaviors, from solid-state to low-density inks. Furthermore, LIFT enables the transference of small volumes of material (as low as picoliters) with a high lateral spatial resolution (down to a few micrometers) to produce printed patterns with great flexibility. In this work, simulations using a finite-element model involving Phase Field tracking method are presented and compared with experimental results. Specifically, two LIFT processes are studied: a modified model is used to reproduce the secondary effects (such as bulgy shapes and secondary jets) observed after several ms in Blister-Actuated LIFT (BA-LIFT) of glycerol/water mixtures, and a model for LIFT transference of high-viscosity metallic pastes employed to study the different regimes observed in experiments (non-transference, explosive, cluster, dot, and bridge transfer)
Thermophysical Characterization of Cyclic Frost Formation in the Subsurface and Nominal Water Activity on Comets: Case Study of 67P/Churyumov-Gerasimenko

We use a generic thermophysical model to study in detail the formation of water-ice frost in the near-surface layers of comet 67P/Churyumov-Gerasimenko. We show that nightly frost formation is a common phenomenon. In particular, while abrupt landscapes may be conducive to frost formation, they are not a requisite condition. We show that the process of subsurface frost formation is similar to that of the condensed ice layer, or crust, underneath. The sublimation of frost produces regular, enhanced outgassing early in the morning. In the case of 67P, this activity is subordinate to and precedes the daily peak sourced from the ice-rich layers located above the diurnal skin depth. In any case, frost activity should be a nominal component of comet water activity.
ASSESSMENT OF KNOWLEDGE, ATTITUDES AND PRACTICE TOWARD DENGUE FEVER AMONG UNIVERSITY STUDENTS IN MALAYSIA

Introduction: Dengue fever is an acute febrile illness with a significant public health concern in tropical and subtropical countries. Population knowledge and practice play an essential role in the transmission and prevention of the disease. This study aims to evaluate the level of knowledge, attitudes, and practice regarding dengue fever among Malaysian university students. Methods: A cross-sectional descriptive study was conducted in twenty-five randomly selected universities across Malaysia. A total of 1520 respondents were approached by simple random sampling method. A previously validated and published questionnaire was used with little modification. The associations between the level of knowledge, Attitudes, and practice with different risk factors were calculated statistically and the significant association was considered with a p-value <0.05. Results: The data were analysed and showed that most of the students (56.3%, 46.2%, and 43.3%) has a moderate level of knowledge, attitude, and practice respectively toward dengue infection among the respondents. The result shows a significant association between the level of practice and knowledge (p-value <0.001) as well as between the level of practice and attitudes (p-value <0.001). Conclusion: The significant association between the practice and knowledge along with attitudes indicates the more knowledge and attitudes lead to better practice. This study highlighted the important role of university students in dengue prevention-based programs. They should be exposed more to improve and transfer their knowledge and attitude to other community population to reduce the incidence of dengue not only in Malaysia but globally.
Meta-Analysis of The Effectiveness of Problem-Based Learning Towards Critical Thinking Skills in Science Learning

In 21st century learning, students are required to be able to face the world of work that requires the ability, one of them is critical thinking. The objective of this meta-analysis is to estimate the effectiveness of problem-based learning on critical thinking skills. This meta-analysis research method consists of some steps, they are research problem, data collection (study), data coding, data analysis, and interpretation. Based on the journal research, it is found 17 critical thinking skills journals, 17 articles that fulfill the criteria: an empirical study on problem-based learning in college and secondary education conducted in classrooms. This explanation revealed that there is a strong positive effect of Problem-based Learning on critical thinking skills. The findings of the research revealed that the results of the meta-analysis were obtained an effect size of the influence of Problem-based Learning on the dependent variable of critical thinking skills of 3,1 which is classified as high where the influence of Problem-based Learning on the dependent variable of critical thinking skills is 99.9%.
An Overview of Entity Relation Extraction

Plenty of digital text is generated and shared in nowadays life, which constitutes many unstructured text resources. An automatically information extraction method is highly in demand as a large amount of useful information can be stored and output through it. In this paper, several basic concepts about entity relation extraction are introduced, including word embedding, positional embedding and convolutional neutral networks. Several types of relation extraction are also discussed: supervised relation extraction, relation extraction using distant supervision and relation extraction using few-shot approach. In addition, the existing challenges and problems are discussed, like overlapped triples, wrong labeled data and the difficulties that few-shot learning approaches are now facing.
A quantum dash mode-locked laser-based photonic aided broadband multi-Gb/s wireless signal delivery system at 5G NR

To support enhanced mobile broadband (eMBB) communication, 5G is going to use new radios (NRs) at frequencies above 24.25 GHz in the millimeter-wave (mm-wave) bands with abundant available bandwidths. The photonic generation, modulation and distribution of such ultra-high speed broadband RF signals in the optical domain is more promising compared to the bandwidth limiting electrical technology, however, it requires low noise coherent optical sources. In this paper, we present a highly coherent low noise InP-based p-n block buried heterostructure (BH) C-band InAs/InP quantum dash (QD) passively mode-locked laser (MLL) for photonic aided broadband wireless communication systems. The device features repetition rates of 25 GHz resulting in an optical coherent frequency comb (CFC) with a 6-dB optical bandwidth of around 9 nm providing over 46 channels. Each individual channel of the CFC exhibits an average phase noise and integrated relative intensity noise (RIN) of less than 500 kHz and -130 dB/Hz in the frequency range from 10 MHz to 20 GHz, respectively. Its timing jitter and RF beat-note linewidth between any two adjacent channels are as low as 5.53 fs and 3 kHz, respectively. By using this QD MLL, a photonic aided radio-over-fiber (RoF) broadband quadrature amplitude modulated (QAM) signal wireless delivery at around 25 GHz (K-band) is successfully demonstrated over 2-m free space wireless distance through 25.22 km standard single-mode fiber (SSMF) with a total link capacity of 16Gbit/s and error vector magnitude (EVM) below the standard requirements of 12.5%.
Exploring Global Fashion Sustainability Practices through Dictionary-Based Text Mining

Nowadays, more fashion companies have started to adopt various sustainability practices and communicate these practices through their annual public CSR reports. In this study, we aim to provide a holistic perspective of fashion companies’ sustainable development and investigate the sustainability practices of global fashion companies. A total of 181 CSR reports from 29 fashion companies were collected. A Dictionary approach text classification method, combined with Latent Dirichlet Allocation (LDA), a computer-assisted topic modeling algorithm, was implemented to detect and summarize the themes and keywords of detailed practices disclosed in CSR reports. The findings identified 12 main sustainability practices themes based on the triple bottom line theory and the moral responsibility of corporate sustainability theory. In general, waste management and human rights are the most frequently mentioned themes. The findings also suggest that global fashion companies adopted different sustainability strategies based on their product categories and competitive advantages.
Geometry and shape optimization of piezoelectric cantilever energy harvester using COMSOL multiphysics software

In embedded systems that necessarily require a steady source of power and (or) attaches to a sensor(s), there are opportunities to mix small batteries to supply such power. The aim of this research is to optimize the geometry and shape of piezoelectric cantilevers to harvest more power. Several piezoelectric cantilever geometries with various shapes (rectangular, triangular, circular, and trapezoidal cross section) are tested in COMSOL multiphysics simulator to find the best geometry that provides the highest accomplishable power. The most efficient geometry was found to be conferred by the trapezoidal, cross section cantilever. Next, another improvement method was applied to maximize the harvested power of the cantilever by modifying the shape of the trapezoidal cantilever structure through increasing the number of its faces. The results demonstrated that the highest output power (36 mW) was produced by the four faces, trapezoidal cross section design of cantilever.