Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermal-Drones as a Safe and Reliable Method for Detecting Subterranean Peat Fires

Underground peat fires are a major hazard to health and livelihoods in Indonesia, and are a major contributor to carbon emissions globally. Being subterranean, these fires can be difficult to detect and track, especially during periods of thick haze and in areas with limited accessibility. Thermal infrared detectors mounted on drones present a potential solution to detecting and managing underground fires, as they allow large areas to be surveyed quickly from above and can detect the heat transferred to the surface above a fire. We present a pilot study in which we show that underground peat fires can indeed be detected in this way. We also show that a simple temperature thresholding algorithm can be used to automatically detect them. We investigate how different thermal cameras and drone flying strategies may be used to reliably detect underground fires and survey fire-prone areas. We conclude that thermal equipped drones are potentially a very powerful tool for surveying for fires and firefighting. However, more investigation is still needed into their use in real-life fire detection and firefighting scenarios.
Israeli Primary School Teachers' Attitudes towards Using Digital Educational Games in Classroom: Empirical Study

This study investigated the Israeli primary school teachers' attitudes towards using digital educational games in classroom. Through adopting a descriptive analytical approach, the required made sure that the goals of this research. The researcher employed the purposive sampling method for selecting a sample. The selected sample consists from 300female and male primaryIsraeli primary school teachers. Those teachers were selected from 25 primary schools. Those schools are located in the Northern District in Israel. Questionnaire forms were distributed via email to the selected teachers. 288 forms were retrieved. The response rate is 96%. Through the use of the SPSS software, the data collected from the sampled teaches were analysed. The researcher concluded that Israeli primary school teachers show positive attitudes towards using digital educational games in classroom. Such use improves students’ leadership, problem solving and critical thinking skills and raise their self-confidence and academic achievement levels. However, it doesn’t allow instructors to identify the extent of progress achieved by learner. The researcher recommends providing teachers in Israel with professional development courses about modern teaching methods and the significance of employing digital educational games.
Lead Induced, VDR Taq and MAO-A Associated Energy Metabolism Reduction, and CD4+CD3+ Lymphocytes-Dependent Inflammation as Main Pathogenetic Events in Autism Spectrum Disorders

Background Autism Spectrum Disorder (ASD) is characterized by persistent deficits in social communication and interaction and restricted-repetitive patterns of behavior, interests, or activities. ASD is generally associated with chronic inflammatory states, which are linked to immune system dysfunction and/or hyperactivation. The latter might be considered as one of the factors damaging neuronal cells. Several cell types trigger and sustain such neuroinflammation. Methods In this study, we traced different markers of immune system activation on both cellular (immune cell phenotypes) and mediatory levels (production of cytokines) alongside adverse hematology and biochemistry screening in a group of autistic children. In addition, we analyzed the main metabolic pathways potentially involved in ASD development – energy (Krebs cycle components), porphyrin and neurotransmitter metabolism. Several ASD etiological factors like heavy metal intoxication and risk factors – genetic polymorphisms of the relevant neurotransmitters and vitamin D receptors were also analyzed. Finally, broad linear regression analysis allowed us to elucidate the possible scenario that led to the development of chronic inflammation in ASD patients. Results Our data strongly support the lead induced, VDR Taq and MAO-A associated mitochondrial dysfunction, and CD4 + CD3 + T-cell dependent immune system activation and chronic inflammation as the key pathogenetic events in autism spectrum disorders. Moreover, our data supports the CD4 + CD3 + T-cell dependence of mitochondrial dysfunction development in ASD patient reported in our previous study. Limitations Difficulties to obtain target biological material (in this case cerebrospinal fluid, CSF) from autistic children under the age of 6 years and the small population of such patients limited our data from the qualitative and quantitative points of view. Nevertheless, the huge range of complex and target measurements has done partially overlap this flaw. Conclusions We come to the conclusion that redox-immune cross-talk is considered a main functional cell damaging factor in ASD patients.
Synthetic Q-space learning with mixture distribution noise for robust DKI parameter inference

Diffusional kurtosis imaging (DKI) parameters were conventionally inferred by using signal model fitting. Recent researches by using machine learning showed improvement in parameter inference robustness. Especially the approach of training only with synthetic data, called synthetic Q-space learning (synQSL), has been proved to be have several advantages. In our previous study on synQSL, single level of Rician noise was used for simulating realistic signals in training data, but noise level of clinical data is supposed to be in mixture distribution. In this study, we investigated basic characteristics and usefulness of the mixture distribution noise in training data through experiments with synthetic and real data. Five-layered multi-layer perceptron (MLP) was used for synQSL. The MLP inputs were three values of logarithm of normalized signal decays, that is, we assume The output is single for diffusion coefficient 𝐷 or diffusional kurtosis 𝐾. Two different levels of Rician noise were simulated and were mixed to training dataset. Various levels and mixture ratios of synthetic data for training were examined by using synthetic test data and clinical data to obtain the basic characteristics. Synthetic data experiments showed that noise level matching yields robust inference for 𝐷 and 𝐾 also in mixed distribution of noise level, similar to single noise level training. Clinical data experiments showed that training with mixed noise level yielded less outliers (out-of-range values: 𝐾 < 0 or 𝐾 > 2) than single noise level training. Thus, the synQSL with mixture distribution noise has potential to improve robustness for DKI parameter inference in clinical data.
Inovação em Tecnologias de Checkout Aplicada como Vantagem Competitiva e Redução das Filas em Supermercados

This article sought to verify whether there is a relationship between innovation at checkout, competitive advantage, and the reduction of queues in the Supermarkets segment in the city of São Paulo. The work begins with a theoretical foundation on the importance of constant innovation in services and the concept of competitive advantage. Finally, it presents the research methodology and analysis techniques used. We chose to use a Qualitative research methodology. Data were collected through non-participant observation (indirect contact of the researcher) with a non-probabilistic sample for convenience with 40 supermarkets in the city of São Paulo, in the north, south, east and west regions. Data analysis was performed using the descriptive analysis technique. Altogether, three factors were identified: efficiency, waiting time, and withdrawal.
Mechanism of miR-590-3p carried by tumor-derived extracellular vesicles in promoting invasion and metastasis of ovarian cancer

Background Ovarian cancer (OC) remains a common gynecologic malignancy. Tumor-derived extracellular vesicles (EVs) contribute to pro-metastasis microenvironment by carrying microRNAs (miRs). This study investigated the mechanism of miR-590-3p carried by OC cell-derived EVs in OC metastasis. Methods miR-590-3p expression in OC tissues and cells was measured. EVs were extracted from healthy serum and the serum of patients with OC or metastatic OC. EVs were extracted from OC cells and normal OC epithelial cells in vitro. miR-590-3p expression in EVs was tested. The effect of EVs-miR-590-3p on the proliferation, migration and invasion of OC cells was measured. The target of miR-590-3p was predicted and verified. The effect of miR-590-3p targeting CPEB3 on OC cells was confirmed by functional rescue assays. Xenograft tumor experiment was performed to verify the mechanism of EVs-miR-590-3p in the tumorigenesis and metastasis of OC. Results miR-590-3p expression was enhanced in OC, and correlated with OC metastasis. miR-590-3p was elevated in OC cell-derived EVs and could be transferred to other OC cells by EVs. OC cell-derived EVs facilitated proliferation, invasion and migration of OC cells by transferring miR-590-3p. miR-590-3p targeted CPEB3. Overexpressing CPEB3 repressed the promoting effect of EVs-miR-590-3p on OC cells. In vivo experiment confirmed that EVs-miR-590-3p facilitated tumorigenesis and metastasis of OC cells by targeting CPEB3. Conclusion OC cell-derived EVs facilitated progression and metastasis of OC via the miR-590-3p/CPEB3 axis.
Exploiting the Two-Dimensional Nature of Agnostic Music Notation for Neural Optical Music Recognition

State-of-the-art Optical Music Recognition (OMR) techniques follow an end-to-end or holistic approach, i.e., a sole stage for completely processing a single-staff section image and for retrieving the symbols that appear therein. Such recognition systems are characterized by not requiring an exact alignment between each staff and their corresponding labels, hence facilitating the creation and retrieval of labeled corpora. Most commonly, these approaches consider an agnostic music representation, which characterizes music symbols by their shape and height (vertical position in the staff). However, this double nature is ignored since, in the learning process, these two features are treated as a single symbol. This work aims to exploit this trademark that differentiates music notation from other similar domains, such as text, by introducing a novel end-to-end approach to solve the OMR task at a staff-line level. We consider two Convolutional Recurrent Neural Network (CRNN) schemes trained to simultaneously extract the shape and height information and to propose different policies for eventually merging them at the actual neural level. The results obtained for two corpora of monophonic early music manuscripts prove that our proposal significantly decreases the recognition error in figures ranging between 14.4% and 25.6% in the best-case scenarios when compared to the baseline considered.
The Tinder Games: Collective mobile dating app use and gender conforming behavior

Mobile dating apps like Tinder became very popular among young adults, and, in contrast to mobile dating websites, they were designed to create a more game-like experience. While it is well documented that seeking entertainment is one core motivation for mobile dating app use, the social nature of entertainment has garnered less attention. Therefore, in this paper we draw on research on entertainment in dating apps and the socio-physical contexts of use to identify patterned behaviors of heterosexual users. To do this, we employed a qualitative multi-phase research approach. First, we conducted 20 interviews with mobile dating app users. Based on the findings from that study, we conducted gender-specific focus groups and a discourse analysis to explore the social phenomena identified in phase one. Our findings suggest the fun of mobile dating is not just interacting with potential matches through the apps, but the use of the apps among one’s friends. These “dating games” are entertaining, but importantly mitigate potential social or physical risks of mobile dating. Unsurprisingly, notions of “play” across the interview, focus group, and discourse analyses reflect highly gendered practices surrounding mobile dating apps and different risks associated with such games.
A comparison of fragrance ingredients in green and nongreen detergents

ABSTRACT Six green (certified with EU Ecolabel), six nongreen household detergents, and two products for professional cleaning were examined for fragrance compounds by gas chromatography coupled to mass spectrometry (GC-MS). The examined detergents are products from multinational companies and best sellers in the Greek market. Only one fragrance ingredient was found in the products for professional applications compared with the 35 in the nongreen products and the 23 ingredients found in green products. Seven ingredients were the same between green and nongreen products. Fragrances are important for marketing purposes but may threaten human health and the environment.
Assessing the Impact of Automated and Connected Automated Vehicles on Virginia Freeways

This study assesses the impact of the introduction of connected and automated vehicles on Virginia freeway corridors. Three vehicle types: legacy vehicles (LV), automated vehicles (AV), and connected automated vehicles (CAV), were considered in mixed traffic scenarios. Previous relevant studies were reviewed and the proper operating parameters for LV, AV, and CAV identified. AV and CAV driving behavior models were developed in the VISSIM environment. According to the basic freeway test network results, AV and CAV increase road capacity by 29% and 91%. In the merging freeway test network, AV and CAV increase road capacity by 48% and 60% compared with LV, respectively. A model with diverse LV, AV, and CAV market penetration and diverse traffic demand was tested on I-95 in Virginia, where the research team tested the speed and throughput. Under the current traffic demand, the average speed was higher when there were more AV and no CAV in the traffic flow. However, the average speed of CAV in a congested segment is higher than LV. In the case of throughput, CAV shows poor performance under current traffic demand. With increased traffic demand, high penetrations of AV and CAV present better performance because of their short headway and homogeneity. Therefore, the study predicts that in the future, as the traffic demand grows, AV and CAV can reduce traffic congestion.
A Review on the Use of Landscape Indices to Study
the Effects of Three-Dimensional Urban Landscape
Patterns on Haze Pollution in China

The interactions between landscape patterns and ecological processes have become more complex with rapid urbanization. In China, urban haze pollution has become increasingly apparent. Elucidating the relationship between urban landscape patterns and haze effects is essential for understanding the formation and development of haze and implementing effective mitigation measures. In-depth studies of the effects of three-dimensional urban landscape patterns on haze are hindered by data limitations, unreliable methods, and complex processes. This study reviews the use of landscape indices, with the aim of advancing understanding of the impacts of three-dimensional urban landscape patterns on the distribution and diffusion of haze pollution. The literature is examined to assess the status and progress of research on the use of landscape indices, and a summary of case studies in which landscape indices have been used in haze pollution modeling is presented. Furthermore, a feasible perspective based on a landscape pattern index is presented. In light of this review focusing on the relationship between urban landscape patterns and processes, new approaches for determining the spatial and temporal heterogeneity of haze distribution and diffusion and haze-prone areas, and for optimizing landscape patterns, are identified.
Toward Just-in-Time Data Communications over Shared Networks and Computational Resources on Massive Client Environment

Intelligent driving has been benefiting from advances in automotive big data analysis and on-demand data communications, where efficient vehicle-to-cloud communication is a key technology able to collect a huge amount of data from vehicles. However, as the capacities of the network and computational resources of the cloud are not unlimited, simultaneous data transfer based on a best-effort manner results in a resource starvation problem. Therefore, an application is needed to prioritize data communication to alleviate the problem and complete the data transfer just in time. This paper highlights the problem of resource starvation led by best-effort data transfers. It proposes protocols for data communication and control that could enable just-in-time data communication, notably for data collection. We demonstrate through experiments that the proposed mechanism enables efficient and effective data collection over the shared network resources.
Sign languages and second language acquisition research: An introduction

In recent years there has been a growing interest in sign second language acquisition (SSLA). However, research in this area is sparse. As signed and spoken languages are expressed in different modalities, there is a great potential for broadening our understanding of the mechanisms and the acquisition processes of learning a (second) language through SSLA research. In addition, the application of existing SLA knowledge to sign languages can bring new insights into the generalizability of SLA theories and descriptions, to see whether they hold true for sign languages. In this paper I give a brief overview of sign language and SSLA research, together with insights from the research on iconicity and gestures and its role for SSLA, including examples from my own studies on L2 signers. The paper concludes with a discussion of both the potential and challenges of combining sign language and SLA research, providing some notes towards directions for future research.
A review of the effects of colour and light on non‐image function in humans

This paper reviews current knowledge on non-image-forming aspects of vision. Developments in the last 20 years have included the discovery of a fifth class of human visual pigment (melanopsin), in addition to the three classes of photopsin to be found in the cones and rhodopsin in the rods in the human retina. Melanopsin is found in a small number of retinal ganglion cells which then, in addition to receiving input from rods and cones, are intrinsically photosensitive. These retinal ganglion cells send their input primarily to the hypothalamus, where they help to regulate the circadian system (daily rhythms of sleep patterns, body temperature, heart rate, etc.). The discovery of the anatomical basis of non-image-forming vision has led to a great deal of research into the effects of light on sleep, depression and mood, retinal photodamage and well-being, amongst other factors. Given that recent technological innovations in LED lighting now give us greater control over environmental lighting, it is timely to review the non-visual effects of light in humans in order to inform lighting design in the future.
Niche Selection by Soil Bacterial Community of Disturbed Subalpine Forests in Western Sichuan

Soil bacterial microbial communities are important in the ecosystem function and succession of forests. Using high-throughput 16S rRNA gene sequencing and relative importance for linear regression, we explored how the structures of soil bacterial community were influenced by the environmental factors and restoration succession of secondary forests in the Miyaluo Mountains of western Sichuan, China. Using a space-for-time approach, field measurements and sampling were conducted in four stands at different stages of natural restoration. Results of distance-based multivariate analysis showed that soil pH, organic carbon, available phosphorus, and C/N ratio were the predominant environmental factors that collectively explained a 46.9% variation in the bacterial community structures. The community compositions were jointly controlled by the direct and indirect effects of the rehabilitation stages. The changes in soil environmental factors coincided with restoration succession could lead to the shifts in the relative abundance of different soil bacterial taxa. We screened 13 successional discriminant taxa that could quantitatively indicate the secondary succession subalpine stage. Collectively, our findings show that soil bacteria in different taxa are governed by different local soil variables and rehabilitation ages, which can lead to shifts in the relative abundance of different taxa in successional stages, ultimately changing the entire soil bacterial community with the succession of secondary forest.
Forecasting

Expertknowledgeelicitationliesatthecoreofjudgmentalforecasting—adomainthatrelies fully on the power of such knowledge and its integration into forecasting. Using experts in a demand forecasting framework, this work aims to compare the accuracy improvements and forecasting performances of three judgmental integration methods. To do this, a field study was conducted with 31 experts from four companies. The methods compared were the judgmental adjustment , the 50–50 combination , and the divide-and-conquer . Forecaster expertise, the credibility of system forecasts and the need to rectify system forecasts were also assessed, and mechanisms for performing this assessment were considered. When (a) a forecaster’s relative expertise was high, (b) the relative credibility of the system forecasts waslow,and(c)thesystemforecastshadastrongneedofcorrection, judgmentaladjustment improved the accuracy relative to both the other integration methods and the system forecasts. Experts with higher levels of expertise showed higher adjustment frequencies. Our results suggest that judgmental adjustment promises to be valuable in the long term if adequate conditions of forecaster expertise and the credibility of system forecasts are met.
Surface Anchoring Effects on the Formation of Two-Wavelength Surface Patterns in Chiral Liquid Crystals

We present a theoretical analysis and linear scaling of two-wavelength surface nanostructures formed at the free surface of cholesteric liquid crystals (CLC). An anchoring model based on the capillary shape equation with the high order interaction of anisotropic interfacial tension is derived to elucidate the formation of the surface wrinkling. We showed that the main pattern-formation mechanism is originated due to the interaction between lower and higher order anchoring modes. A general phase diagram of the surface morphologies is presented in a parametric space of anchoring coefficients, and a set of anchoring modes and critical lines are defined to categorize the different types of surface patterns. To analyze the origin of surface reliefs, the correlation between surface energy and surface nano-wrinkles is investigated, and the symmetry and similarity between the energy and surface profile are identified. It is found that the surface wrinkling is driven by the director pressure and is annihilated by two induced capillary pressures. Linear approximation for the cases with sufficient small values of anchoring coefficients is used to realize the intrinsic properties and relations between the surface curvature and the capillary pressures. The contributions of capillary pressures on surface nano-wrinkling and the relations between the capillary vectors are also systematically investigated. These new findings establish a new approach for characterizing two-length scale surface wrinkling in CLCs, and can inspire the design of novel functional surface structures with the potential optical, friction, and thermal applications.