Miracle-dz/UniFAR-FTUs huggingface dataset:
ASSESSMENT OF THE PERFORMANCE OF SEVERAL ROADWAY MIXES UNDER RAIN, SNOW, AND WINTER MAINTENANCE ACTIVITIES

The purpose of this study was to assess the relative functional performance, including skid resistance and splash and spray, of five hot-mix-asphalt (HMA) surfaces and a tinned portland cement concrete highway surface during controlled wet and wintry weather events. The study compared the way that these surfaces respond to various deicing and anti-icing snow removal and ice control techniques under artificial wintry conditions. In addition, the splash and spray characteristics of the surfaces during and immediately after rain were also evaluated. The study focused on the surfaces placed within the all-weather testing area at the Virginia Smart Road. The winter maintenance techniques tested include the application of sodium chloride (salt) in granular, pre-wetted, and liquid forms. The snow removal and ice control measures that were used followed the recommendation ofthe FHWA Project T&E 28 and variations thereof. The experiments to compare the splash and spray characteristics of the mixes were conducted using artificial rain. The study defined and tested a methodology for testing winter maintenance operations under controlled, artificial wintry events. The winter maintenance test results were inconclusive, as the various maintenance treatments were unable to significantly improve the functional condition ofthe road. Under the temperature and precipitation conditions encountered, there were no significant differences in the performance of the different surface mixes tested. However, conditions encountered did not correspond to conditions normally encountered with natural snow. The researcher concluded that at temperatures at and just below freezing, artificial snow might not be appropriate for evaluating the effectiveness of winter maintenance chemicals. Studies that depend upon imitating the on-road attributes of natural snow, such as testing effectiveness of winter maintenance chemicals, should adhere to the ideal temperature-humidity guidelines for the snowmaking equipment. The open-graded friction course appears to have enhanced spray and splash performance when compared with the dense HMA surface mixes; however, a more objective measure of splash and spray characteristics of the surfaces is needed to quantify the beneficial effect of this type of mixes. No visual difference in performance was observed among the other mixes.
Low-Cost 2-bit Phase and 1-bit Amplitude Reconfigurable Antenna for Beam Steering and Shaping

A low-cost 2-bit phase and 1-bit amplitude reconfigurable array with beam-steering and beam-shaping functions is presented in this article. To manipulate the radiation beam, a novel 2-bit phase radiator is proposed based on the mode control and the phase-shifting surface. This radiator element can directly realize four switchable radiation phase states without extra phase-shifting circuits. By introducing the higher order mode characteristics, these array elements are fed by a single-port cavity rather than the conventional multiport feeding networks. Thus, this design is very different from traditional phased arrays and bit arrays. More importantly, the 1-bit amplitude switching function is cleverly introduced by controlling the field distribution of this radiator, which can further manipulate the beam shape. To validate the proposed working principles, a phase and amplitude digitally reconfigurable substrate integrated waveguide (SIW) antenna is fabricated and measured. By controlling the digital phase and amplitude states of each element, this antenna can realize multifunctional beam steering and shaping. The achieved impedance bandwidth is 9.52–10.27 GHz (7.6%), and the realized peak gain is 11.0 dBi. To our knowledge, the presented design is a new type of phase and amplitude digitally reconfigurable antenna/array without the multiport feeding network or T/R components. It has good potential in intelligent and low-cost beam-steering wireless communication systems.
3D pipeline reconstruction and diameter measurement method based on target segmentation

3D reconstruction technology utilizes 3D data to create models of physical objects. Cameras, laser scanners, and other sensors can be used to gather 3D data of objects, which can be processed using computer graphics technology for creating 3D models through 3D reconstruction technology. In engineering, high-precision 3D reconstruction models can substitute physical pipes for automatic measuring of pipe diameters. This paper proposes a target segmentation-based optimization method for single-frame reconstruction, which enables precise diameter measurement of pipes. Experimental results show that single-frame reconstruction, based on target segmentation technology, produces excellent results in the current application scenario. The proposed method is better adapted to complex construction conditions than the complex reconstruction methods. Complex backgrounds include excessive and uneven distributed light and interfering objects. Using target segmentation technology based on image processing, the MIVOS user-interactive video can produce and distribute the target object mask based on the user's interaction with the video frame. Complex background removal can improve the quality of reconstructed sample images. MIVOS is used to segment the pipe area in the image and remove most of the background noise. Consequently, the process lessens the interference of background noise in the reconstruction results. The proposed method exhibits significant progress in measuring both the inner and outer diameters of pipes when compared to both multi-frame and single-frame reconstruction methods. Their measurements have an average error of no more than 1 mm. The proposed method provides technical guidance for measuring the inner and outer diameters of pipes under complex conditions.
Coal gangue sorting based on deep learning

Coal gangue sorting is an important link in the process of coal mining and processing, which can effectively reduce the difficulty and cost of coal post-processing. Aiming at the problems of complicated sorting process and low sorting efficiency of coal gangue, a coal gangue sorting method based on deep learning was proposed. The method is based on the YOLO v7 deep learning algorithm, and it achieves real-time detection of coal gangue by creating a coal gangue dataset and training the detection model. By constructing a coal gangue sorting platform, the capture of target gangue has been achieved. The experimental results show that the mAP of YOLO v7 model is 96.70%, and the detection speed is 69fps, which has significant advantages compared to YOLO v5, SSD and Faster RCNN algorithms.
Current status and development of coal geophysical technology in China

6 prominent progresses and developments had been made in coal and mine geophysical technique in recent years,namely popularization for 3D seismic application;seismic data fine processing and interpretation dynamically;new spanning has been taken from structural to lithological explanation for seismic;ground TEM technology has been widely used;attention was regained for underground geophysics and innovations have been achieved for embedded labeled service mode has been used in coal mine safety production guarantee.By making the comparison between China and oversea technological levels in coal geophysics,the shortcomings had been pointed out and suggestions on how to improve geophysical technology in China had been put forward.In the end,outlooks for future geophysical technique and equipment were predicted in the paper.
Optimalisasi Pembelajaran Berbasis Proyek: Penggunaan Aplikasi Sipebi dalam Mata Kuliah Bahasa Indonesia

The limited time in learning activities and the lack of student understanding in writing make this output-based learning often experience obstacles. One of the most common obstacles is the non-achievement of learner output targets. The purpose of writing this article is to present how the Sipebi application can support outcome-based learning activities in Indonesian language courses. The research method used by researchers is mixed method, which is a combination of qualitative and quantitative. The research stages carried out began with the introduction of the Indonesian language course, providing RPS, teaching, practice, evaluation
Solution Growth and Characterization of 4-Carboxyanilinium Tartrate Single Crystal

Background and Objective: The organic compound of 4-carboxyaniline has UV absorption and antifibrotic properties. It was naturally found in Streptomyces griseus, Synechococcus elongatus and other organisms. In this study, an effort was made to the growth of the 4-carboxyaniline derivative crystal with tartaric acid using the solution growth technique. Materials and Methods: The 4-carboxyanilinium tartrate crystal was grown from a slow evaporation technique in an aqueous ethanol solution at room temperature. The grown crystal was characterized by single crystal XRD, powder XRD, FT-IR, FT-Raman, UV-visible spectroscopy, SEM with EDX and antibacterial activity studies. Result: The monoclinic crystal system and P2 1 space group was confirmed from the single crystal XRD study. The diffraction peaks were indexed using INDX software. The average crystalline size was determined as 55 nm. All the wavenumber assignments were exactly matched with recently reported corresponding compounds. From the optical absorbance data, the band gap was determined as 3.75 eV using Tauc’s plot. The well-defined shape of the crystal was confirmed by the SEM micrographs. Bacillus subtilis and Acinetobacter baumannii exhibited the highest zone of inhibition towards the grown crystal than Escherichia coli . Conclusion: The finding result of this study supports the previous knowledge of the structural and biological assortment of 4-carboxyanilium tartrate complex crystals.
Screening eighty traditional and improved rice genotypes in Sri Lanka for salinity tolerance at the seedling stage in Yoshida solution 

A total of eighty different rice genotypes consisting of fifty-three traditional rice accessions and twenty-seven improved rice varieties were evaluated for salinity tolerance. To identify the tolerant genotypes and the relationship between tolerance level with plant height and dry matter accumulation, the seedlings were subjected to electrical conductivity (EC) ~12 dSm-1 for ten and sixteen days separately at the seedling stage. The salinity tolerance of the seedlings was evaluated by standard evaluation scores (SES). Plant height, and total, shoot, and root-dry matter were evaluated in stressed and controlled plants. Rathuheenati4992 was highly tolerant at salinity stresses, and Heenati4618, Kaluwee3728, Mawee (5531, 3618), and Pokkali3573 were highly tolerant at the 10-day and tolerant at the 16-day salinity stress. Pokkali3881 was moderately tolerant at both stress conditions. Improved rice varieties At354 and Bg250 were highly tolerant at 10-day salinity stress and tolerant at 16-day salinity stress. Cultivation of highly susceptible improved rice varieties, Bg360, At306, At362, Ld368 At405, At402, Ld371, Bw272-6b, Ld365, and Bg352 must be avoided in salinized soils. There was no correlation between plant height and salinity tolerance (r = -0.381, α = 0.000), salinity tolerance and total dry matter (r = 0.325 α = 0.002), salinity tolerance and root dry matter (r = 0.294, α = 0.008), or salinity tolerance and shoot dry matter (r = 0.061, α = 0.594). Plant height or dry matter accumulation can be considered unreliable parameters for salinity tolerance screening since they differ with the genotype. The highly tolerant and tolerant genotypes must be further studied at different growth stages.
Observed Changes of Köppen Climate Zones in Spain since 1951

Despite of having been originally formulated more than one hundred years ago, the Köppen classification is still nowadays the climate classification most widely used in climatological studies. Based on the empirical relationship between climate and vegetation, this climate classification provides an efficient and easy way to describe climate conditions and their seasonality by using a simple but ecologically meaningful classification scheme. This study examines the temporal evolution of the Köppen climate classification in Spain for the period 1951-2020, using high-resolution gridded datasets of monthly mean temperature and precipitation with 1 x 1 km spatial resolution. Climate classification maps for consecutive 30-year reference periods are compared, and the temporal evolution of each climate type in Spain is analysed, showing a progressive expansion of the arid climate zones and a contraction of the cold climate zones along the study period.
Plant diversity based on pollen and spores morphology from sediment lake of Kedung Ombo Purwodadi

Kedung Ombo Lake was an artificial lake that has formed since 26 years ago. Environmental has changed from the terrestrial environment into the aquatic environment, because of that the diversity of flora around the Lake Kedung Ombo was changed. The diversity of flora can be learned through the morphology of pollen and spores. Aimed of this study was to determine the diversity of plants based on the morphology pollen and spores that found in the Lake Kedung Ombo sediment. Sampling took by coring clay soil sediment in depth of 1 m, located near the outlet of Lake Kedung Ombo. Data were analyzed by making the morphology of pollen and spores description. The result showed that morphology of pollen and spores are found in the Lake Kedung Ombo sediment has a variety of shapes and sizes. The plant's diversity obtained are 25 taxa plants that were categorized into 3 taxa of arboreal pollen (AP), 9 taxa of non-arboreal pollen (NAP) and 13 taxa of spores. The dominance of taxa NAP is Celtis sp. (45,12%), this suggested that shrubs or not plant trees were more developed in Lake Kedung Ombo environment. The study concluded that the value of diversity index categorized as low and the value of similarity index categorized as high, it means that plant diversity was quite similar and there is no significant changes of diversity with their presence were quite stable.
Determining the quality factor of sandstone using acoustic laboratory measurements

The paper presents the velocity-pressure and quality factor-pressure dependences of a sandstone sample, using the Fourier spectra of the complete waveforms of the P waves measured in laboratory. Measurements were performed on sandstone and (a reference) aluminum sample at 40 different pressures. The professional literature uses approximate methods to determine the value of the quality factor. The spectral ratio method was used to evaluate our measurements. The measured velocity and quality factor data were processed using inversion methods. The results showed that both the velocity-pressure and the quality factor pressure dependence can be well-described utilizing the double relaxation model in forward modeling.
Generation of Temperature Sensitive Mutations with Error-Prone PCR in a Gene Encoding a Component of the Spindle Pole Body in Fission Yeast

Temperature-sensitive (ts) mutants provide powerful tools, thereby investigating cellular functions of essential genes. We report here a simple procedure to generate ts mutations using error-prone PCR in pcp1 that encodes a spindle pole body (SPB) component in Schizosaccharomyces pombe. This manipulation is not restricted to analysis of Pcp1, and can be suited to any essential genes involved in other processes.
SYNTHESIS THEORY IN ACTION: DEDUCTIVE DERIVATION OF ALGORITHMS FOR APPLICATION SOFTWARE

The significance of the study is contingent upon two criteria. All objects in the actual world that can capture a researcher’s attention are inherently complicated. Furthermore, every commodity that an individual manufactures and every work of art that an individual develops are intricate in nature. The entirety of the processes that an individual perceives and instigates are intricate. Although many professions have established techniques for constructing intricate entities, there currently exists no universally applicable concepts or methodologies for comprehensively studying, designing, producing, or generating complicated items.The objective of this work is two-fold: firstly, to develop a comprehensive methodology for analysing complex synthetic processes, and secondly, to propose universal models or synthesis mechanisms that can be used to systematically derive specific process synthesis algorithms for various practical applications. The ability to utilize generalized models and synthesis techniques is highly advantageous when designing realistic computer programming.The authors introduced a comprehensive process model and enumerated its characteristics. Using this concept, techniques for creating and suggesting processes have been formulated and put forward. The concept of a decomposition diagram enables the systematic design of intricate multi-level hierarchical processes. The multitude of processes and the intricacy of their combination give rise to the notion of formulating a synthesis theory. The acquired results can be regarded as the initial stage in the construction of such a theory. The authors’ proposed methods of process synthesis enable the deductive derivation of useful algorithms for application software. Although the concept of the breakdown scheme and synthesis procedures is relatively straightforward, this advancement has been suggested for the first time.In order to further this project, it is necessary to augment the generalized process model with supplementary traits and properties, as well as to further refine the synthesis procedures. A proposal is being made to initiate the development of a theory for synthesizing a comprehensive plan using the decomposition scheme and methods of synthesis and decomposition.
Face Reflection Removal Network Using Multispectral Fusion of RGB and NIR Images

Images captured through glass are usually contaminated by reflections, and the removal of them from images is a challenging task. Since the primary concern on photos is face, the face images with reflections annoy viewers severely. In this article, we propose a face reflection removal network using multispectral fusion of color (RGB) and near infrared (NIR) images, called FRRN. Due to the different spectral wavelengths of visible light [380 nm, 780 nm] and near infrared [780 nm, 2526 nm], NIR cameras are not sensitive to the visible light and thus NIR images are less corrupted by reflections. NIR images preserve structure information well and can guide the restoration process from reflections on the RGB images. Thus, we adopt multispectual fusion of RGB and NIR images for reflection removal from a face image. FRRN consists of one encoder model (contextual encoder model (CEM)) and two decoder models (NIR inference decoder model (NIDM) and image inference decoder model (IIDM)). CEM captures features from shallow to deep layers on the scene information while suppressing the sparse reflection component. NIDM infers NIR image to facilitate multi-scale guidance for reflection removal, while IIDM estimates the transmission layer with the guidance of NIDM. Besides, we present the reflection confidence generation module (RCGM) based on Laplacian convolution and channel attention-based residual block (CARB) to represent the reflection confidence in a region for reflection removal. To train FRRN, we construct a large-scale training dataset with face image and reflection layer (RGB and NIR images) and its corresponding test dataset using JAI AD-130 GE camera. Various experiments demonstrate that FRRN outperforms state-of-the-art methods for reflection removal in terms of visual quality and quantitative measurements.
Comparison of methods: Attributing the 2014 record European temperatures to human influences

The year 2014 broke the record for the warmest yearly average temperature in Europe. Attributing how much this was due to anthropogenic climate change and how much it was due to natural variability is a challenging question but one that is important to address. In this study, we compare four event attribution methods. We look at the risk ratio (RR) associated with anthropogenic climate change for this event, over the whole European region, as well as its spatial distribution. Each method shows a very strong anthropogenic influence on the event over Europe. However, the magnitude of the RR strongly depends on the definition of the event and the method used. Across Europe, attribution over larger regions tended to give greater RR values. This highlights a major source of sensitivity in attribution statements and the need to define the event to analyze on a case‐by‐case basis.
FACTORS INFLUENCING GENERATION Z’S PURCHASE INTENTION IN OMNICHANNEL RETAIL SETTINGS

The retail industry has undergone a significant transformation due to information technology (IT) progress, shifting the retail paradigm from traditional brick-and-mortar stores to the contemporary omnichannel platform. This evolution is characterised by a customer-centric approach known as omnichannel, which aims to provide a seamless shopping experience across various channels, including physical stores, telephone, social media, and websites. Despite the growing importance of omnichannel strategies, academic research in this domain still needs to be explored. This research proposes theoretical contributions to the Unified Theory of Acceptance and Use of Technology (UTAUT2), thus expanding its applicability in omnichannel retailing. Additionally, this study holds practical significance for the retail sector by examining how omnichannel strategies can enhance customer experiences, contributing to retailers' ability to gain a competitive edge in the market. The sample data will be coded, and the hypothesis will be statistically analysed using the Statistical Programme for Social Sciences (SPSS). As the retail landscape continues to evolve, understanding the preferences and behaviours of the digitally savvy Generation Z demographic becomes increasingly crucial. This research contributes to bridging the gap in academic literature and provides valuable insights for retailers aiming to optimise their omnichannel strategies, ultimately fostering more robust customer engagement and loyalty.
Judging the relative trustworthiness of research results: How to do it and why it matters

This paper describes, and lays out an argument for, the use of a procedure to help groups of reviewers to judge the quality of prior research reports. It argues why such a procedure is needed, and how other existing approaches are only relevant to some kinds of research, meaning that a review or synthesis cannot successfully combine quality judgements of different types of research. The proposed procedure is based on four main factors: the fit between the research question(s) for any study and its design(s); the size of the smallest group of cases used in the headline analyses; the amount and skewness of missing data; and the quality of the data collected. This simple procedure is now relatively widely used, and has been found to lead to widespread agreement between reviewers. It can fundamentally change the findings of a review of evidence, compared to the conclusions that would emerge from a more traditional review that did not include genuine quality rating of prior evidence. And powerfully, because it is not technical, it permits users to help judge research findings. This is important as there is a growing demand for evidence‐led approaches in areas of social science such as education, wherein summaries of evidence must be as trustworthy as possible.