Miracle-dz/UniFAR-FTUs huggingface dataset:
Provident Headlamps Technology for Electric Vehicles

Electric Vehicle (E.V.) relies on its batteries as the power source. One major issue hampering the use of EV is related to its short driving range due to exhaustion of battery. Battery power consumption suffers with many unbounded conditions that result in excess power consumption. Using the battery providently is the basic idea of the work discussed in this paper, and it can definitely contribute in augmenting the driving range of electric vehicle.In this paper, a system is described, by means of which the battery of E.V. can wisely be utilised by the constant loads of headlamps and thus, it becomes Provident Headlamps. By avoiding unnecessary use of battery and using it precisely when and wherever glow is required, battery power can be conserved. A circuitry is designed, which senses the illumination of the surroundings of vehicle and decides the output requirement of headlamps and will regulate the power from battery to the headlamps accordingly, thus conserving battery and slightly increasing the driving range. This technique has been extended to separate controls for left and right lamps, ensuring safety in two way traffic.
Hybrid Energy Storage using Battery and Ultra-capacitor for Electric Vehicle

The electrical energy storage is an factor which plays an important role from the era of electrical energy generation. The only option available for storage for a very long period were different form of electro-chemical energy storage device known as battery. But now an amalgamation of electrostatic device with chemical element is available for storage known as Ultra-capacitor (UC). Both the devices store the electrical energy in DC. The battery have high energy density while the UC have high power density. In case of smart grid the energy generated is varying due to the different environment conditions. This varying of energy supply from the smart grid to the battery and from the battery to the load reduces the reliability of the system. The Hybrid Energy Storage system (HESS) can provide reliability by providing the energy to the load from battery and UC. An electric vehicle (EV) is the emerging trend in automobile sector. HES installed in EV will increase the reliability of the vehicle energy storage system. The simulation results provided validates the above statement by providing the power for a 2 kW load with transients in it.
Softwarization of UAV Networks: A Survey of Applications and Future Trends

Unmanned Aerial Vehicles (UAVs) have become increasingly important in assisting 5G and beyond 5G (B5G) mobile networks. Indeed, UAVs have all the potentials to both satisfy the ever-increasing mobile data demands of such mobile networks and provide ubiquitous connectivity to different kinds of wireless devices. However, the UAV assistance paradigm faces a set of crucial issues and challenges. For example, the network management of current UAV-assisted systems is time consuming, complicated, and carried out manually, thus causing a multitude of interoperability issues. To efficiently address all these issues, Software-Defined Network (SDN) and Network Function Virtualization (NFV) are two promising technologies to efficiently manage and improve the UAV assistance for the next generation of mobile networks. In the literature, no clear guidelines are describing the different use cases of SDN and NFV in the context of UAV assistance to terrestrial networks, including mobile networks. Motivated by this fact, in this survey, we guide the reader through a comprehensive discussion of the main characteristics of SDN and NFV technologies. Moreover, we provide a thorough analysis of the different classifications, use cases, and challenges related to UAV-assisted systems. We then discuss SDN/NFV-enabled UAV-assisted systems, along with several case studies and issues, such as the involvement of UAVs in cellular communications, monitoring, and routing, to name a few. We furthermore present a set of open research challenges, high-level insights, and future research directions related to UAV-assisted systems.
Data Science: Empowering Business Strategy

Data science is a blanket term for Machine learning, Artificial Intelligence and Big Data. Data science is being used by commercial and noncommercial organizations to get the insides of their customers, their behavior about selecting a product, insides of the staff. Many of the organizations use data science to provide better services to their customers. Financial Institutions use data science to analyze and predict stock markets, determine the risk of lending money, and learn how to attract new clients for their service. Government organizations get inside of public services by using data science and also use data structures to provide better services to citizens. Universities use data science to improve research and enhance study experience of students. Data grows exponentially over the period of time. The problem of working on large data sets can be solved by using the adept algorithm for your problem, use different data structures, and by relying on tools and libraries. The three main data structures used in data science are sparse matrix, hash functions and tree structures. Python has many tools that can deal with large data sets. In reality most of the data which is stored in a relational database is structured data. Now days the data retrieve from most of the websites is not structured and cannot be used by the relational databases. This paper describes how different tools in Python can improve user experience and provide better services to customers by using appropriate data structure and algorithm. This user experience and the better services to the customer boost the business and hence it is important for business strategy and ensures quality of experience (QoE) for the delivery services to their users.
COPPER TOXICITY TO SKELETONEMA COSTATUM (BACILLARIOPHYCEAE) 1, 2

Copper toxicity to Skeletonema costatum (Grev.) Cleve has been studied in batch cultures of chemically defined culture media. The alga is relatively insensitive to cupric ion activity, demonstrating no effect on growth up to (Cu2+) = 10−8.5 M. Cultures inoculated from stationary phase stocks exhibit a prolongation of the lag phase with increasing copper concentrations near and above the point of precipitation of the copper. The toxicity of copper is a function of the silicic acid concentration in the medium. This effect is observed in a range of Si(OH)4 concentrations (10−5 M to 10−4 M) above known values for the saturation of silicon uptake kinetics, thus suggesting an influence of copper on silicate metabolism.
Human Papillomavirus 31 Tyrosine 102 Regulates Interaction with E2 Binding Partners and Episomal Maintenance

Posttranslational modifications by phosphorylation can change protein activities, binding partners, or localization. Tyrosine 102 is conserved between delta papillomavirus BPV-1 and alpha papillomavirus HPV-31 E2. We characterized mutations of HPV-31 E2 for interactions with relevant cellular binding partners and replication in the context of the viral genome. ABSTRACT Several serine and threonine residues of the papillomavirus early E2 protein have been found to be phosphorylated. In contrast, only one E2 tyrosine phosphorylation site in BPV-1 (tyrosine 102) and one in HPV-16/31 (tyrosine 138) site have been characterized. Between BPV-1 and HPV-31 E2, 8 of the 11 tyrosines are conserved in the N-terminal domain, suggesting that phosphorylation of tyrosines has an essential role in E2 biology. In this study, we examine the effect of Y102 phosphorylation on HPV-31 E2 biology. Y102 proteins mutated either to the potential phospho-mimetic glutamic acid (Y102E) or to the nonphosphorylated homologue phenylalanine (Y102F) remain nuclear; however, Y102E is more associated with the nuclear matrix fraction. This is consistent with the inability of Y102E to bind TopBP1. Both BPV-1 and HPV-31 Y102E are similar in that neither binds the C terminus of Brd4, but in all other aspects the mutant behaves differently between the two families of papillomaviruses. BPV-1 Y102E was unable to bind E1 and did not replicate in a transient in vitro assay, while HPV-31 Y102E binds E1 and was able to replicate, albeit at lower levels than wild type. To examine the effect of E2 mutations under more native-like infection conditions, a neomycin-selectable marker was inserted into L1/L2 of the HPV-31 genome, creating HPV-31neo. This genome was maintained in every cell line tested for at least 50 days posttransfection/infection. Y102E in both transfection and infection conditions was unable to maintain high episome copy numbers in epithelial cell lines. IMPORTANCE Posttranslational modifications by phosphorylation can change protein activities, binding partners, or localization. Tyrosine 102 is conserved between delta papillomavirus BPV-1 and alpha papillomavirus HPV-31 E2. We characterized mutations of HPV-31 E2 for interactions with relevant cellular binding partners and replication in the context of the viral genome.
The Impact of Residential Batteries on PV Self-Consumption and PV Exports: early results from the Nextgen Trial in the ACT, Australia

Due to a growing number of residential photovoltaic (PV) installations, an increasing amount of energy is being exported to the grid during times of maximum solar irradiance, potentially causing technical issues such as voltage variation and reverse power flow. Energy storage is one solution to reduce PV exports. Here, we assess the degree to which the Next Generation (Nextgen) Energy Storage program, based in the Australian Capital Territory (ACT), Australia, has increased PV self-consumption and thereby reduced PV exports to the grid. The Nextgen program is one of the largest roll-outs of household batteries world-wide. Beginning in 2016, it will eventually involve up to 5000 households and businesses. Energy data collected as part of this trial provide an unprecedented opportunity to understand both the economics of battery storage as well as the technical impact of household batteries on the grid. Here we show that, for customers surveyed to date, residential battery storage increases PV self-consumption from 34% to 58%. Residential battery storage was more effective at reducing import peak power compared to export peak power. Average import peak power decreased by 39% in summer and 30% in winter. In comparison, average export peak power decreased by 16% in summer and 23% in winter. Choice of battery operation algorithm will be important for reducing this export peak power further.
Exploring Software Design Skills of Students in different Stages of their Curriculum

Computer programming is one of the basic abilities developed in computing science students, but it is important to note that programs are the product of generating code from software design. This work presents the results of examining the design products of students in different stages of their degree program. We have replicated some experiments reported in the literature but a difference between these works and ours is that we analyze the design work of students at all levels of their degree programs. We find results that indicate that the design abilities do not necessarily show a continuous improvement during the passage of time in their studies and we explore possible causes of this and outline future research in this line of investigation.
A ROADMAP FOR CONVERTING AN ELECTRIC POWER UTILITY NETWORK TO DEFEND AGAINST CRAFTED INPUT

In this paper, we propose a concrete roadmap to eliminate the possibility of input-handling vulnerabilities in the OT side of an ICS network by using secure parsing. ICS utilities are responsible for maintaining the integrity of the power grid in the US. A complex communications network is the backbone of these systems. Communication on ICS networks is must be processed correctly and can’t crash devices or allow attackers access to devices. Language-Theoretic Security (LangSec) is the practice of secure input handling via hardened parsers. Secure parsers improve ICS network security. Our previous work covers the implementation details of various ICS protocols. Here, we show that the existing collection of LangSec parsers for SCADA protocols oﬀers coverage for the communication needs of an ICS network. We demonstrate a high degree of communications coverage on a network model, discuss the merits of a network guarded by LangSec parsers, and propose a triage procedure to implement such a network. Furthermore, we collect a summary of security beneﬁts and lessons learned.
Fairness in Learning Analytics: Student At-risk Prediction in Virtual Learning Environments

While the current literature on algorithmic fairness has rapidly expanded over the past years, it has yet to fully arrive in educational contexts, namely, learning analytics. In the present paper, we examine possible forms of discrimination, as well as ways to measure and establish fairness in virtual learning environments. The prediction of students’ course outcome is conducted on a VLE dataset and analyzed with respect to fairness. Two measures are recommended for the prior investigation of learning data, to ensure their balance and fitness for further data analysis.
Learning Analytics and Perceived Experience of Gamifying Homework Assignments

The purpose of this research is to assist the primary school students to complete their homework assignments, and understanding students’ interpretation of gameplay experience and defining their satisfaction with gamification elements while playing online homework assignments. The implementation of the gamified homework followed the instructional design processes. The subsequent evaluation from a cohort of students comprised learning analytics besides surveying students’ experience. The results indicated that they were satisfied with completing the homework with the employed game design elements where they were active and focused. In addition, they showed a tendency to challenges that involved in the treatment. One of the more significant findings to emerge from this study is that the micro gamification design approach has promoted the perception of motivation and enjoyment to take into consideration the design principles of the
The interleukin-1 families of cytokines and receptors: therapeutic potential for immunomodulation and the treatment of inflammatory disorders

The interleukin (IL)-1 cytokine family includes 11 distinct members that are related in their genomic and protein structures. The initial members of this family, IL-1α and IL-1β, were discovered over two decades ago and are now considered as prototypic pro-inflammatory cytokines. Their activity is downregulated by a third family member, termed IL-1-receptor antagonist (IL-1ra). Another IL-1 family cytokine that was also identified early on is IL-18, an agonist cytokine possessing potent immunostimulatory activities. Subsequently, sequence homology searches in DNA databases led to the discovery of genes that encode additional family members. IL-1 cytokines exert their function through structurally related cell surface receptors that have a Toll/IL-1 receptor (TIR) module in their intracellular region and one to three copies of immunoglobulin (Ig)-like domains in their extracellular region. At present, 11 members of the IL-1 receptor family are known. A hallmark of IL-1 receptor signalling, which is mediated via the TIR domain, is the activation of the transcription factor NF-κB and the mitogen-activated protein kinases (MAPK). Owing to their possible roles in immune disease mechanisms, IL-1 and its relatives have long been considered as potential targets of therapeutic intervention in inflammatory and autoimmune conditions. Strong evidence for the importance of IL-1 in pathogenic inflammation was recently provided by the clinical use of a recombinant form of human IL-1ra for the treatment of rheumatoid arthritis and certain autoinflammatory syndromes. The discovery and characterisation of the IL-1 families of cytokines and receptors, as well as the exploration of their therapeutic potential, has generated a large body of patent literature over the past few years. Here, this literature is reviewed and discussed in the context of current research findings.
Identification of the licorice root stored in Shosoin based on the sequences of internal transcribed spacer (ITS) on nrDNA and the chemotaxonomic consideration

For the identification of the botanical origin of licorice (ML-44, N-99) stored in Shosoin, the Imperial Storehouse in the city of Nara since 756AD, we made genetic and chemical analyses in comparison with 205 and 117, respectively, authentic samples of licorice roots derived from Glycyrrhiza uralensis, G. glabra and G. inflata. Referring to the experimental results of the genetic analysis study of internal transcribed spacer (ITS) on nuclear ribosomal DNA (nrDNA) of the above three species of licorice, the contents of glycyrrhizin and five main flavonoids, and their scattering pattern of occurrence, Shosoinlicorice was finally identified to be the root of G. uralensis.
Composition, Mineral and Fatty Acid Profiles of Milk from Goats Fed with Different Proportions of Broccoli and Artichoke Plant By-Products

In the Mediterranean region, artichoke and broccoli are major crops with a high amount of by-products that can be used as alternative feedstuffs for ruminants, lowering feed costs and enhancing milk sustainability while reducing the environmental impact of dairy production. However, nutritional quality of milk needs to be assured under these production conditions and an optimal inclusion ratio of silages should be determined. This work aimed to evaluate the effect of three inclusion levels (25%, 40%, and 60%) of these silages (artichoke plant, AP, and broccoli by-product, BB) in goat diets on milk yield, composition, and mineral and fatty profiles. Treatments with 60% inclusion of AP and BB presented the lowest milk yield. No differences were found on the milk mineral profile. Inclusion of AP in the animals’ diet improved the milk lipid profile from the point of view of human health (AI, TI) compared to BB due to a lower saturated fatty acid content (C12:0, C14:0, and C16:0) and a higher concentration of polyunsaturated fatty acids (PUFA), especially vaccenic acid (C18:1 trans11) and rumenic acid (CLA cis9, trans11), without any differences with the control treatment.
Multi-Cleaning Robots Using Cleaning Distribution Method Based on Map Decomposition in Large Environments

Most cleaning robots have a good cleaning performance for small environments such as houses but require a longer cleaning time due to problems such as slow cleaning progress and low battery capacity, making the robots unsuitable for large environments such as libraries and airports. Cleaning large environments with multiple robots is faster than cleaning them with a single robot. Multi-cleaning robots can utilize several robots to simultaneously clean and share the task of cleaning among the robots. However, as the number of robots increases and the effective distribution of cleaning is not efficient during the cleaning process, the cleaning time will consequently be longer due to the frequent collisions between the robots. Therefore, to shorten the cleaning time, multi-cleaning robots require a coverage path planning that uses an effective cleaning distribution method in the cleaning process. In this paper, a coverage path planning using a cleaning distribution method based on map decomposition is proposed to reduce the cleaning time of multi-cleaning robots. The experimental results demonstrated that the proposed multi-cleaning robots’ coverage path planning could be used in large environments in the presence of several types of obstacles. Furthermore, the cleaning time was found to be shorter than that of the previous methods in the case of multi-cleaning robots.
Unsupervised Hyperspectral Band Selection By Sequentially Clustering A Mahalanobis-Based Dissimilarity Of Spectrally Variable Endmembers

This paper introduces an unsupervised hyperspectral band selection approach based on sequential clustering of a dissimilarity measure between spectrally variable endmembers. The proposed method combines two main techniques. It begins by automatically extracting spectrally variable endmembers, from the considered hyperspectral image, by means of a linear spectral unmixing technique that takes into account the spectral variability phenomenon. Then, dissimilarity values vector, based on Mahalanobis distances that are calculated between samples of extracted spectrally variable endmembers, is segmented into a fixed number of clusters by using a sequential clustering technique. For each obtained cluster, a single spectral band is chosen. This band corresponds to the wavelength at which a maximum dissimilarity value is found. The proposed method is applied to a real hyperspectral image, and its effectiveness is evaluated by means of a supervised pixel-based classification in comparison with three literature band selection methods. Experimental results show that the proposed approach outperforms tested literature techniques.
Prevalence of Anaplasma sp. in Thrushes (Family Turdidae) in Jeju Island, Republic of Korea

Anaplasmosis is a rickettsial zoonosis mediated by blood-sucking arthropods, such as ticks, flies, and mosquitos. Migratory birds are common hosts of ticks that are mediators of anaplasmosis, in particular, the tick infection rate in thrushes (family Turdidae) has been known to be high. The main purpose of this study is to survey the occurrence and prevalence of Anaplasma spp. from the migratory thrushes in Jeju island. We collected blood samples from 6 thrushes rescued at the Jeju Wildlife Rescue Center and from 34 wild-caught thrushes on Mara island which is a satellite island of Jeju. As a result, the nested PCR confirmed that seven out of 40 individuals (17.5%) were infected by Anaplasma spp. and all of them were identified as A. phagocytophilum based on sequences obtained from partial 16S rRNA. All the infected birds were on their northward migration in spring, our results suggest that the Turdidae family, which is a common and abundant migrant group passing through Jeju island, may act a role as active reservoir and disperser of A. phagocytophilum causing potential influx of the zoonotic pathogens from its wintering grounds in lower latitude to the mainland Korea as well as Jeju.
Highly Selective Fluorescence Sensor Based on Graphene Quantum Dots for Sulfamethoxazole Determination

In our research, a reliable fluorescence sensor for the detection of sulfamethoxazole (SMZ) was developed. This method relies on graphene quantum dots (GQDs) entrapped in a silica molecularly imprinted polymer (GQDs@SMIP), which was synthesized by the polymerization using GQDs, SMZ, tetraethoxysilane (TEOS) and 3-aminopropyltriethoxysilane (APTES) as fluorescence material, template, cross-linker, and functional monomers, respectively. The GQDs@SMIP was characterized by fluorometry, Fourier-transform infrared spectroscopy, transmission and scanning electron microscopies, X-ray photoelectron spectroscopy, and powder X-ray diffraction. The GQDs@SMIP exhibited a good capacity to absorb SMZ from solution, which resulted in the quenching of the GQD fluorescence intensity. The intensity of GQDs@SMIP decreased linearly with the SMZ concentration in the range of 1 to 100 µM with a correlation coefficient of 0.99537. In addition, the fluorescence responses of GQDs@SMIP to interfering substances were investigated. The results indicated that there was no effect of interfering substances on SMZ detection. Thus, the highly selective GQDs@SMIP fluorescence sensor is an effective and promising device for SMZ detection and analysis.