Miracle-dz/UniFAR-FTUs huggingface dataset:
Generative Adversarial Networks : A Survey

Generative Modelling has been a very extensive area of research since it finds immense use cases across multiple domains. Various models have been proposed in the recent past including Fully Visible Belief Nets, NADE, MADE, Pixel RNN Variational Auto Encoders, Markov Chain, and Generative Adversarial Networks. Amongst all the models, Generative Adversarial Networks have been consistently showing huge potential and developments in the area of Art, Music, SemiSupervised learning, Handling Missing data, Drug Discovery, and unsupervised learning. This emerging technology has reshaped the research landscape in the field of generative modeling. The research in the area of Generative Adversarial Networks (GANs) was introduced by Ian J. Goodfellow et al in 2014 [1]. However, since its inception, various models have been proposed over the years and are considered state-of-the-art models in generative modeling. In this survey, we provide a comprehensive review of the original GAN model and its modified versions, covering broad topics on model architecture, Objective and Loss Functions, and applications. First, we summarize different architectures proposed along with Objective Functions and loss functions used. Second, we cover the evolution of GAN followed by summarizing comparative analysis for various GANs. Then, we review various applications proposed by various authors which are built over these architectures in different domains. Finally, the technical challenges and several promising directions are highlighted.
Temperature and Prey Species Richness Drive the Broad-Scale Distribution of a Generalist Predator

The ongoing climate change and the unprecedented rate of biodiversity loss render the need to accurately project future species distributional patterns more critical than ever. Mounting evidence suggests that not only abiotic factors, but also biotic interactions drive broad-scale distributional patterns. Here, we explored the effect of predator-prey interaction on the predator distribution, using as target species the widespread and generalist grass snake (Natrix natrix). We used ensemble Species Distribution Modeling (SDM) to build a model only with abiotic variables (abiotic model) and a biotic one including prey species richness. Then we projected the future grass snake distribution using a modest emission scenario assuming an unhindered and no dispersal scenario. The two models performed equally well, with temperature and prey species richness emerging as the top drivers of species distribution in the abiotic and biotic models, respectively. In the future, a severe range contraction is anticipated in the case of no dispersal, a likely possibility as reptiles are poor dispersers. If the species can disperse freely, an improbable scenario due to habitat loss and fragmentation, it will lose part of its contemporary distribution, but it will expand northwards.
Assessment of Treated Wastewater Reuse in Drip Irrigation under Different Pressure Conditions

This study aims to investigate the influence of treated wastewater (TWW) on the hydraulic performance of drip irrigation emitters. A field experiment was conducted in order to test two types of online emitters, a low pressure (LP) and a standard pressure (SP), at different working pressures (0.25 bar, 0.50 bar, and 1.00 bar) using TWW. The emitters were initially evaluated in the laboratory and the field for the discharge exponent (X), discharge coefficient (Kd), average emitter discharge (Qavg), coefficient of variation (CV), distribution uniformity (DU), the mean discharge ratio (Dra), and the main degree of clogging (DC). The main effect of the emitters on the hydraulic parameters of irrigation performance was not significant, while the operational pressure and operational time of irrigation had a significant effect. For the LP emitter, the average emitter discharge was 7.6, 7.7, and 7.8 Lh−1 at 0.25, 0.50, and 1.00 bar, respectively. For the SP emitter, the average emitter discharge was 7.6, 7.8, and 7.8 Lh−1 at 0.25, 0.50, and 1.00 bar, respectively. The EU values for the LP and SP emitters varied from low to moderate at 0.25 bar, as the EU values at 0.50 and 1.00 bar were considered high for both emitter types.
Opinion Mining: An Approach to Feature Engineering

Sentiment Analysis or opinion mining refers to a process of identifying and categorizing the subjective information in source materials using natural language processing (NLP), text analytics and statistical linguistics. The main purpose of opinion mining is to determine the writer’s attitude towards a particular topic under discussion. This is done by identifying a polarity of a particular text paragraph using different feature sets. Feature engineering in pre-processing phase plays a vital role in improving the performance of a classifier. In this paper we empirically evaluated various features weighting mechanisms against the well-established classification techniques for opinion mining, i.e. Naive Bayes-Multinomial for binary polarity cases and SVM-LIN for multiclass cases. In order to evaluates these classification techniques we use Rotten Tomatoes publically available movie reviews dataset for training the classifiers as this is widely used dataset by research community for the same purpose. The empirical experiment concludes that the feature set containing noun, verb, adverb and adjective lemmas with feature-frequency (FF) function perform better among all other feature settings with 84% and 85% correctly classified test instances for Naive Bayes and SVM, respectively.
Research on High Precision Attitude Measurement of Flexible Link Based on Low Cost Sensors

Flexible links are widely used in industrial robots and special robots due to their light weight, high load ratio and good maneuverability. Due to the flexibility of the connecting rod, the vibration and deformation of the manipulator will occur during the movement, which will affect the stability of the flexible arm. According to the theory of elastic deformation, the attitude of the whole flexible arm can be estimated by indirectly measuring the deformation of the flexible arm. In this paper, low-cost sensors such as encoder, strain sensor and angle sensor are used to measure the deformation of the flexible arm. Through theoretical analysis, the posture and end position of the flexible arm after deformation are obtained. The experimental system is built to verify the proposed method. The results show that the method is correct and effective. The measurement error is 6.5% in the experiment, which meets the measurement accuracy requirements of flexible arm control.
Revealing Internal Heavy Chalcogen Atom Effect on the Photophysics of Dibenzo[a,j]phenazine-Cored Donor–Acceptor–Donor Triad

A new twisted donor–acceptor–donor (D–A–D) multi-photofunctional organic molecule comprising of phenoselenazine as the electron-donors (Ds) and dibenzo[a,j]phenazine (DBPHZ) as the electron-acceptor (A) has been developed. The developed selenium-incorporated D–A–D compound is featured with multi-color polymorphism, distinct mechanochromic luminescence, chemically-stimulated luminochromism, thermally-activated delayed fluorescence, and room- temperature phosphorescence. The internal heavy atom effect on the photophysical properties of the D–A–D system has been investigated through the comparison with the physicochemical properties of a previously developed sulfur analogue and a tellurium analogue.
Emerging 3D‐Printed Electrochemical Energy Storage Devices: A Critical Review

Three‐dimensional (3D) printing, a layer‐by‐layer deposition technology, has a revolutionary role in a broad range of applications. As an emerging advanced fabrication technology, it has drawn growing interest in the field of electrochemical energy storage because of its inherent advantages including the freeform construction and controllable 3D structural prototyping. This article focuses on the topic of 3D‐printed electrochemical energy storage devices (EESDs), which bridge advanced electrochemical energy storage and future additive manufacturing. Basic 3D printing systems and material considerations are described to provide a fundamental understanding of printing technologies for the fabrication of EESDs. The performance metrics of 3D‐printed EESDs are then given and the related performance optimization strategies are discussed. Next, the recent advances of 3D‐printed EESDs, including sandwich‐type and in‐plane architectures, are summarized. Conclusions and future perspectives with some unique challenges and important directions are then discussed. It can be expected that, with the help of 3D printing technology, the development of advanced electrochemical energy storage systems will be greatly promoted.
Residential intensification through a new statutory plan in Auckland: outcome evaluation and stakeholders’ experience

ABSTRACT Conformance between plans and expected plan outcomes is at the heart of urban planning processes. Integrating an empirical evaluation and stakeholders’ experience of the realisation of intended intensification goals, this article presents the contradictions between the plan instruments and the anticipated plan outcomes to enable higher intensification than the superseded plans. The findings suggest that statutory land use planning should be accompanied by a thorough outcome-based evaluation and a review of conflicting planning tasks and purposes. The article concludes with recommendations for planning monitoring and strengthening the statutory plan to achieve its expectations.
Phytogeographic regions and geographic distance do not predict genetic structure in the orchid bee Euglossa cordata

Herein, we investigated the genetic diversity and population structure of Euglossa cordata L. , an orchid bee species widely distributed at the heterogeneous set of vegetal physiognomies encompassed in a transition zone (TZ) of different Brazilian biomes. We then tested whether phytogeographic regions would play some rule for the genetic diversity. Results revealed that only 12 and 28 out 78 pairs of samples showed some degree of genetic structure for microsatellites (F ST≤ 0.029; Dest ≤0.091; p < 0.05) and mtDNA(0.138 ≤mt-ϕST≤ 0.495; p < 0.05) markers, respectively. We found evidence of two and three genetic clusters in nuclear and mtDNA markers, but no significant structure based on phytogeographic regions or geographic distances. These findings point out that local idiosyncrasies and historic factors, but not different types of vegetation or geographic distances drive the patterns of the observed genetic structure. Drops in the diversity index and other estimators highlight that E. cordata may have experienced some local bottlenecks despite its resilience to anthropic interferences. These are the first records of relatively high genetic structure in E. cordata populations and have important implications for orchid bees’ conservation.
Who belongs in preschool? Perspectives of children and educators

ABSTRACT The study examines the views of children and educators with regards to belonging in one diverse preschool setting in Iceland. It builds on the ideology of the politics of belonging, referring to children’s relationships in the community of preschool, children’s participation, and the process of inclusion and exclusion among the children. This study is grounded in the fields of Childhood Studies and the Children’s Rights Movement, along with endeavours to conceptualize the space where children’s views are taken seriously and acted upon. Data construction was twofold. First, interviews were conducted with the children using computer tablets (reported elsewhere). The findings from the study with the children were then introduced to educators, who reflected on the children’s experiences. The findings inform three overarching themes: relationships; independence; and cultural constraints.
Mapping the Nanoscale Heterogeneity of Surface Hydrophobicity on the Sphalerite Mineral

Hydrophobic effect plays an important role in a wide range of natural phenomena and engineering applications, such as mineral froth flotation. In this work, atomic force microscope (AFM) force mapping was employed, for the first time, to probe the nanoscale heterogeneity of surface hydrophobicity and surface interactions on the sphalerite mineral surface before/after conditioning treatment (activated by copper sulfate and then treated by amyl xantahte). The AFM force mapping demonstrates that adhesion on sphalerite falls in a narrow range with a peak centered at 16.4 mN/m and adhesion on conditioned sphalerite falls in a wide range with a small peak centered at 15.5 mN/m and a large peak centered at 58.1 mN/m. It is evident that the sphalerite surface is hydrophilic with homogeneous surface hydrophobicity whereas conditioned sphalerite exhibits a heterogeneous distribution of surface hydrophobicity due to the nonuniform adsorption of xanthate. The significantly enhanced adhesion after conditioning treatme.
Research Photocatalytic Water-splitting based on big data mining technology

Visible photocatalytic water splitting is an effective way to solve the global energy and environmental crisis, and its green and environmentally friendly properties are worth researching. In this paper, we extracted 8395 articles from the core collection of Web of Science from 1991 to 2020. Visual analysis of the data by various software, such as Excel, Origin, Citespace V, reflected the following results. First, the number of related papers has increased exponentially, reaching a peak in 2018, with a total of 1508; next, among all countries, China has published the most papers and cooperated most closely with other countries; additionally, in terms of journals, Applied Catalysis B: Environment has the largest number of publications in the field of visible light catalytic cracking of water, and Journal of the American Chemical Society has the highest number of co-citations in this field, researchers can focus on these journals; finally, MAEDA K, ZHANG J, and WANG Y are ideal collaborators in this field. “Application and modification of graphite phase carbon nitride,” “application and modification of Z-scheme photocatalyst,” and “band structure engineering” are the hottest research frontiers in this field and represent the future development direction of this field.
Investment Diversificationand Islamic Risk Management in the Malaysian Stock Market

Risk investment was a matter that should be well managedby each investor since each unit of stock has their own risk. This study will explained in detail related risks of investing in portfolio either Shariah stock or conventional stock. Besidesthat, further discussion on the risk of investment from the perspective of Islamic economics will be include together since any shariah stock have to obey with Islamic principle before it can be considered as a Shariahcompliant stock. Capital Asset Pricing Model (CAPM) will be used to measure the level of risk starting from the year 2007 when subprimecrisisjust done until year of 2010. Results of the study show that the volatility of stock market in Malaysia can be considered as a high volatility and its means as a high risk. The findings of study also found that Islamic economic has recognizes the existence of investmentrisk. One of methods that are used in the management of risk was diversification. This methodwillreduces risk by allocating investments among various financial instruments, industries, and other categories. In conclusion, the process of diversificationthatwas done by most of the investors are keeping to the concept of risk management in the Islam.
Does Listening to English Songs Motivate Students to Expand Their Extramural English ? A Case Study of Swedish Upper-Secondary School Students ’ Perceptions of Possible Impact of Listening to Vocal Music on Their Extramural English

The purpose of this study is to investigate whether listening to music as an out-of-school activity, and English songs in particular, motivated a group of Swedish upper-secondary students to learn extramural English. One aspect that comes into focus is whether the students perceived that there were particular aspects of second language acquisition (SLA) that improved as a result of listening to music. The study focuses on the correlation between the needs of the listeners and the nature of their motivation for learning. This is a qualitative study based on the analysis of semi-structured interviews. The results show that all of the students perceived listening to music as an aid in their extramural English acquisition. A majority of the students had the intrinsic motivation for learning as they exhibited curiosity, emotions and internal needs as the primary factors that empowered them to expand their extramural English. The minority of the interviewees showed signs of extrinsic motivation to learn the vocabulary of the lyrics of the songs they listened to. The learning they experienced was linked to the expectancy in improving their academic performances. They may, however, have had a combination of the extrinsic and intrinsic forms of motivation where the former had a dominant position. In both cases the respondents showed awareness of the correlation between their extramural English acquisition and listening to vocal music. It is suggested that vocabulary acquisition was the primary aspect of language learning that benefited from listening to songs, followed by listening skills. The possibility to make their own choice to listen to music is linked to deep language learning, vocabulary learning in context and mastering listening skills.
Autonomous Navigation in Search and Rescue Simulated Environment using Deep Reinforcement Learning

— Human assisted search and rescue (SAR) robots are increasingly being used in zones of natural disasters, industrial accidents, and civil wars. Due to complex terrains, obstacles, and uncertainties in time availability, there is a need for these robots to have a certain level of autonomy to act independently for approaching certain SAR tasks. One of these tasks is autonomous navigation. Previous approaches to develop autonomous or semi-autonomous SAR navigating robots use heuristics-based methods. These algorithms, however, require environment-related prior knowledge and enough sensing capabilities, which are hard to maintain due to restrictions of size and weight in highly unstructured environments such as collapsed buildings. This study approaches the problem of autonomous navigation using a modified version of the Deep Q-Network algorithm. Unlike the classical usage of the entire game screen images to train the agent, our approach uses only the images captured by the agent's low-resolution camera to train the agent for navigating through an arena avoiding obstacles and to reach a victim. This approach is a much more relevant way of decision making in complex, uncertain contexts; since in real-world SAR scenarios, it is almost impossible to have the area's full information to be used by SAR teams. We simulated a SAR scenario, which consists of an arena full of randomly generated obstacles, a victim, and an autonomous SAR robot. The simulation results show that the agent was able to reach the victim in 56% of the evaluation episodes after 400 episodes of training.
Controls on range shifts of coastal Californian bivalves during the peak of the last interglacial and baseline predictions for today

Abstract. As the most recent time in Earth history when global temperatures were warmer than at present, the peak of the last interglacial (Marine Isotope Substage [MIS] 5e; ∼120,000 years ago) can serve as a pre-anthropogenic baseline for a warmer near-future world. Here we use a new compilation of 22 fossil localities in California that have been reliably dated to MIS 5e to establish baseline expectations for contemporary bivalve species movements by identifying and analyzing bivalve species with “extralimital” ranges, that is, species that occupied the California region during MIS 5e but are now restricted to adjacent regions. We find that 15% of species (n = 142) found in MIS 5e localities have extralimital ranges and currently occupy warmer waters to the south of the California region. The majority of extralimital occurrences occur in paleo-embayments, suggesting that these sheltered habitats were more suitable habitats for warm-water species than exposed coasts during the MIS 5e. We further find that extralimital species now tend to occur in cooler, more seasonally productive coastal waters and to occupy more offshore islands when compared with the broader species pool immediately south of California. These findings suggest that high dispersal potential and preexisting tolerances to environmental conditions similar to California's comparatively cool and seasonally productive environments may have enabled extralimital bivalves to colonize the California region during MIS 5e.
Effect of Low Temperature on Germination, Growth, and Seed Yield of Four Soybean (Glycine max L.) Cultivars

During germination at low temperatures, seeds rich in proteins may experience damage to their cytoplasmic membranes. The study aimed to investigate the influence of the germination temperature on growth, development, and yield of four cultivars of soybean, a typical thermophilic species. The seeds were germinated at 10, 15, and 25 °C in the dark. After 48 h, one part of the seeds was analyzed for their amylase and dehydrogenase activity, cell membrane permeability, and germination vigor. The other part was transferred into soil and cultivated up to yielding. Chlorophyll fluorescence, fresh (FW) and dry weight (DW) of shoots, pod and seed number, and seed DW were analyzed. The plants of cvs. ‘Abelina’, ‘Malaga’, and ‘Merlin’, germinating at low temperature, produced the highest number of seeds. Seed number negatively correlated with their DW and positively with the number of active reaction centers (RC/CSm) in all cultivars. In cvs. ‘Abelina’ and ‘Malaga’, the number of seeds also positively correlated with the index performance of photosystem II (PSII), which was the highest in all plants germinating at low temperature. We suggest cultivating cv. ‘Abelina’ in cooler regions, while cvs. ‘Petrina’ and ‘Malaga’ in warmer areas.
Interactive Kahoot! - An Application to Enhance the Learning of Accounting Subject in School

This study was conducted to examine the effect of using Kahoot! on students’ achievement of their accounting subject. The accounting subject is viewed as a difficult subject and was often dislike by many students. Therefore, this study hopes to provide evidence on a tool that may attract students to learn accounting subject known as Kahoot! The study used a pre-experimental case study research design with explanatory sequential mixed method. A sample of 22 Malaysian students aged 16 years was selected from a school in northern Peninsular Malaysia. The instrument used was a pre-test and post-test which contained 30 multiple choice items. The Kuder-Richardson reliability value (KR20) is . 85. The t-test result shows that there is a significant difference between the pre- and post-test accounting subject achievement scores of the students. Interviews indicates that the students enjoyed learning using Kahoot! and it helps them to be more engaged with the subject.