Miracle-dz/UniFAR-FTUs huggingface dataset:
ROAD TRANSPORT INFORMATION SYSTEM: A PANACEA FOR ROAD TRANSPORT FACILITY MANAGEMENT IN KATSINA LOCAL GOVERNMENT, KATSINA STATE, NIGERIA

This study aimed at examining the spatial pattern of RTF within Katsina Local Government with a view to developing a comprehensive Road Transport Facility Information System (RTFIS) to enable efficient management and planning for sustainable development. Analogue record (maps and attributes) of the existing RTF were obtained from the relevant departments, and were updated with the data obtained through field and GPS surveys, and Google Earth image (2019). QGIS 3.8 software was used for Nearest Neighbor Analysis, developing comprehensive database and series of spatial and attributes queries in order to demonstrate the capability of Geospatial technology in efficient management of RTF information. The result revealed a dispersed distribution pattern of Roundabouts within the study area with nearest neighbor ratio of 1.3 and z-score value of 2.9. It is therefore recommended that the departments involved in RTF management should embrace Geospatial technology as one of the contemporary methods for efficient managing, manipulating, retrieving and updating RTF records for sustainable urban development.
Sparse-Coding Variational Auto-Encoders

The sparse coding model posits that the visual system has evolved to efficiently code natural stimuli using a sparse set of features from an overcomplete dictionary. The original sparse coding model suffered from two key limitations, however: (1) computing the neural response to an image patch required minimizing a nonlinear objective function via recurrent dynamics; (2) fitting relied on approximate inference methods that ignored uncertainty. Although subsequent work has developed several methods to overcome these obstacles, we propose a novel solution inspired by the variational auto-encoder (VAE) framework. We introduce the sparse-coding variational auto-encoder (SVAE), which augments the sparse coding model with a probabilistic recognition model parametrized by a deep neural network. This recognition model provides a neurally plausible feedforward implementation for the mapping from image patches to neural activities, and enables a principled method for fitting the sparse coding model to data via maximization of the evidence lower bound (ELBO). The SVAE differs from standard VAEs in three key respects: the latent representation is overcomplete (there are more latent dimensions than image pixels), the prior is sparse or heavy-tailed instead of Gaussian, and the decoder network is a linear projection instead of a deep network. We fit the SVAE to natural image data under different assumed prior distributions, and show that it obtains higher test performance than previous fitting methods. Finally, we examine the response properties of the recognition network and show that it captures important nonlinear properties of neurons in the early visual pathway.
The Cameriere method using cone-beam computed tomography (CBCT) scans for dental age estimation in children

ABSTRACT This study evaluated the accuracy of Cameriere’s method based on normalized measurement of open apices of developing permanent teeth (xi ) and a number of teeth with closed apices (N0 ) in a sample of 121 cone-beam computed tomography (CBCT) scans of children (60 males and 61 females), aged between 5 and 13 years from Krakow, Poland. Intra-class correlation coefficient on randomly selected 30 CBCT scans showed good to exceptional intra-observer, and inter-observer agreement of normalized open apices, while Kappa score showed an absolute agreement of the number of teeth with complete maturation. Dental age overestimated by 0.17 years (p = 0.120) and 0.18 years (p = 0.149) in males and females, respectively. The mean absolute errors between dental and chronological age of MAE between dental and chronological age of the complete sample were 0.73 years and 0.77 years in males and females, respectively. In conclusion, the present results support usage of Cameriere’s method for age estimation in Polish children in cases where CBCT scans are available and previously taken for a specific clinical indication and taking into account the more demanding procedure of measuring variables in a non-orthogonal projection of teeth compared to a panoramic image.
Pollution and Treatment of Dye Waste-Water

With the rapid development of industry, the production of dye waste-water has increased year by year. Dye composition complex, high concentration, and high color, difficult to biodegradable substances, difficult to biodegrade. According to the chemical structure, dyes are mainly divided into eight categories, such as azo dyes; according to the application can be divided into 14 categories, such as reactive dyes, acid dyes and so on. Dyes show chroma contamination due to the presence of chromophore and chromophore in the molecular structure. Dye waste-water comes from dyestuff industry, printing and dyeing factory, wool spinning factory and other industrial enterprises. The treatment methods of dye waste-water include physical method, chemical method and biological method, among which biological method is economical and practical.
In vitro bioassessment of novel δ- carboline derivatives as an antiproliferative agent

Several carboline derivatives are anticancer agents and studied for antiproliferative action against various cancer cells. Based on the preliminary analysis using insilico strategies, we have selected eight compounds for the study. All compounds have been synthesised and characterised for their purity and chemical composition. Antiproliferative activity was assessed by insilico Carcinogenicity assay, Cytotoxicity analysis by sulphorhodamine B, Antiproliferation assay and DNA damage analysis. The cytotoxic effects of the CH5, CH17, CH29, CH34, CH37, CH39, CH42 and CH47 on Vero, HeLa, A549, BRL3A, HCT116, and MCF7 were determined using the SRB assay. CH5, CH34, CH37 and CH42 was the most potent cytotoxic towards HCT116 cells with CTC50 value of 62.1±0.19, 47.1±0.41, 78.5±1.26 and 32.1±1. 11μg/ml respectively. The assay revealed a noticeable reduction in cell number for CH5 and CH37 tested except CH34 and CH42. CH5 and CH37 observed cytotoxic effects were found to destroy the cells according to time, and cell viability decreased with that time length. To learn their role in cell death, CH5 and CH37 were therefore taken up for a further screening. This study suggested that CH5 and CH37 had a separatemechanismof action to kill and that in the cell line. Such results will provide enrichment of scienti ic knowledge on the molecular mechanism and target therapies of CH5 and CH37, thereby potentially helpful for patients with Colon cancer.
Robust finite-time and fixed-time bipartite consensus problems for multi-agent systems via discontinuous protocol

This paper addresses the robust finite-time and fixed-time bipartite consensus problems for multi-agent systems under the signed graphs. A unified discontinuous control protocol is constructed to achieve both finite-time bipartite consensus (FINBC) and fixed-time bipartite consensus (FIXBC) only by adjusting the parameters, regardless of whether the signed graph is structurally balanced or unbalanced. By using discontinuous techniques, some simple sufficient conditions for FINBC/FIXBC are provided; moreover, the upper bounds of the settling times are explicitly estimated. Simulations show that the proposed control protocols are effective.
Intelligent optimization methodology of battery pack for electric vehicles: A multidisciplinary perspective

Past studies focused on proposing new materials for batteries components, state of health (SOH) prediction, thermal design, equivalent circuit modeling, and so on. Those studies have been implemented on individual basis on a single battery or battery pack. However, there is hardly any research found that encompasses all the multidisciplinary aspects (such as materials, SOH, intelligent configuration [assembly], thermal design, mechanical safety, and recycling of materials and pack) simultaneously for the battery pack design of electric vehicles. This research article proposes a synthetic methodology for an advanced design of battery pack and its components by incorporating optimal scenario of materials selection for battery electrodes, SOH estimation, configurations (assembly) of cells, thermal (air and liquid cooling) design, battery pack casing mechanical safety, and recycling aspects of battery and battery pack. The problem is divided into the several parts and methodology for each is proposed. Cumulative advantages of the methodology with six future critical directions are discussed in the end.
Cloud-Based Charging Management of Heterogeneous Electric Vehicles in a Network of Charging Stations: Price Incentive Versus Capacity Expansion

This article presents a novel cloud-based charging management system for electric vehicles (EVs). Two levels of cloud computing, i.e., local and remote clouds, are employed to meet the different latency requirements of the heterogeneous EVs while exploiting the lower-cost computing in remote clouds. Specifically, we consider time-sensitive EVs at highway exit charging stations and EVs with relaxed timing constraints at parking lot charging stations. We propose algorithms for the interplay among EVs, charging stations, system operator, and clouds. Considering the contention-based random access for EVs to a 4G Long-Term Evolution network, and the quality of service metrics (average waiting time and blocking probability), the model is composed of: queuing-based cloud server planning, capacity planning in charging stations, delay analysis, and profit maximization. We propose and analyze a price-incentive method that shifts heavy load from peak to off-peak hours, a capacity expansion method that accommodates the peak demand by purchasing additional electricity, and a hybrid method of price incentives and capacity expansion that balances the immediate charging needs of customers with the alleviation of the peak power grid load through price-incentive based demand control. Numerical results demonstrate the effectiveness of the proposed methods and elucidate the tradeoffs between the methods.
Warming accelerates mangrove expansion and surface elevation gain in a subtropical wetland

Climatic warming can change how coastal wetland plants grow, thus altering their capacity to build land and keep pace with rising seas. As freeze events decline with climate change, mangroves expand their range to higher latitudes and displace salt marsh vegetation. Warmer air temperatures will likely alter above‐ and below‐ground plant dynamics as this dramatic coastal wetland biome shift proceeds, which in turn may result in changes in ecosystem function such as sediment building. We used a large scale in situ warming experiment in a subtropical wetland to increase both marsh and mangrove ecosystem air temperatures. We assessed how 2 years of continuous warming influenced above‐ and below‐ground plant growth and surface elevation relative to sea level. We found that chronic warming doubled plant height and accelerated the expansion of mangrove into salt marsh vegetation, as indicated by a sixfold greater increase in mangrove cover in warmed plots compared to ambient temperature plots and a corresponding loss in salt marsh cover. Surface elevation gain, a measure of soil‐building capacity, increased due to warming over a 2‐year period and these changes in surface elevation were driven by increased mangrove root production in warmed plots. Synthesis. Our findings suggest that, in some coastal wetlands, warming can facilitate plant community changes from marsh to mangrove, with corresponding increases in growth that help coastal wetlands to keep pace with sea‐level rise.
Inoculum dynamics of Ralstonia spp.: potential sources, persistence in a local population and selection of phages to reduce bacteria survival

Dispersal of Ralstonia spp. by rivers and contaminated plant material and the importance of weeds as inoculum sources have been poorly investigated in Brazil. Water of rivers, soil of the biomes Amazônia, Cerrado and Mata Atlântica, from fields of diverse crops and areas of natural vegetation, besides soil of the rhizosphere of weeds present in tomato fields with records of bacterial wilt were sampled and analyzed to detect Ralstonia spp. Seeds of tomato plants artificially and naturally infected with Ralstonia spp. were also processed. All samples were enriched a priori in selective medium South Africa (SMSA) and colonies were isolated in plates containing solid SMSA. Detection of Ralstonia spp. was confirmed by polymerase chain reaction (PCR) with specific primers. The Co – operational PCR (CO-PCR) was also used to detect Ralstonia spp. Colonies of Ralstonia spp. were obtained from soil samples and from a commercial substrate sample. Five soil samples from eggplant fields, one from coffee field, one substrate from potato seed tuber production, two soil samples from the rhizosphere of Amaranthus spp. , one from Bidens pilosa and one from Solanum americanum tested positive for Ralstonia spp. Besides these soil samples, five water samples of rivers were positive for CO-PCR detection: two samples from Amazônia, one from Cerrado and two samples from irrigation water collected from tomato fields located in the Mata Atlântica biome. Ralstonia spp. were not detected in tomato seeds. These results revealed potential inoculum sources, especially weeds, in areas with historical records of bacterial wilt. Additionally, rivers may be reservoirs and dispersal agents of Ralstonia spp.
Incremental Dilations Using CNN for Brain Tumor Classification

Brain tumor classification is a challenging task in the field of medical image processing. Technology has now enabled medical doctors to have additional aid for diagnosis. We aim to classify brain tumors using MRI images, which were collected from anonymous patients and artificial brain simulators. In this article, we carry out a comparative study between Simple Artificial Neural Networks with dropout, Basic Convolutional Neural Networks (CNN), and Dilated Convolutional Neural Networks. The experimental results shed light on the high classification performance (accuracy 97%) of Dilated CNN. On the other hand, Dilated CNN suffers from the gridding phenomenon. An incremental, even number dilation rate takes advantage of the reduced computational overhead and also overcomes the adverse effects of gridding. Comparative analysis between different combinations of dilation rates for the different convolution layers, help validate the results. The computational overhead in terms of efficiency for training the model to reach an acceptable threshold accuracy of 90% is another parameter to compare the model performance.
Enzymatic Activity of Rhizobacillus Isolated from Tomato Rhizosphere

Aim: The aim of this study was to isolate Rhizobacillus from tomato rhizosphere and its screening for the production of hydrolytic enzymes to be used as a biocontrol agent. Place of Study: The study was carried out in the Department of Microbiology, Faculty of Science, Ekiti State University, Ado Ekiti, Nigeria in August 2018. Methodology: Isolation was of Rhizobacillus carried out from rhizospheric soil of tomato plant at agro-zone along Afao road Ado Ekiti using pour plate method. Enzyme assay was carried out on the bacterial isolates, to examine their ability to produce hydrolytic enzyme required for biocontrol of phytopathogenic fungi. Isolates were tentatively identified with the help of Bergy’s Manual of Systemic Bacteriology. Results: Ten strains were tentatively identified as B. brevis, B. circulans BC1, B. macquariensis BM1, B. macquariensis BM2, B. macerans, B. macquarensis BM3, B. alcalophilus B. macerans BC11, B. circulans BC3 and B. macerans BC9. All the Isolates demonstrated the ability to produce hydrolytic enzymes with the highest activity recorded in Bacillus macquariensis BM2 (60.28 μmol) Original Research Article Ayantola and Fagbohun; AJBGMB, 4(3): 11-19, 2020; Article no.AJBGMB. 55144 12 for chitinase, Bacillus macerans BC9 (11.14 μmol) for Protease, Bacillus macquariensis BM2 (150.00 μmol) for Glucanase, and Bacillus circulans BC1 (46.45 μmol) for cellulase respectively. In conclusion the Bacillus strains isolated from rhizosphere are promising and could be used in bioprocessing technology to produce hydrolytic enzymes for the purpose of biocontrol in management of phytopathogenic fungi.
Identifying and Classifying Shared Selective Sweeps from Multilocus Data

Positive selection causes beneficial alleles to rise to high frequency, resulting in a selective sweep of the diversity surrounding the selected sites. Accordingly, the signature of a selective sweep in an ancestral population may still remain in its descendants. Identifying signatures of selection in the ancestor that are shared among its descendants is important to contextualize the timing of a sweep, but few methods exist for this purpose. We introduce the statistic SS-H12, which can identify genomic regions under shared positive selection across populations and is based on the theory of the expected haplotype homozygosity statistic H12, which detects recent hard and soft sweeps from the presence of high-frequency haplotypes. SS-H12 is distinct from comparable statistics because it requires a minimum of only two populations, and properly identifies and differentiates between independent convergent sweeps and true ancestral sweeps, with high power and robustness to a variety of demographic models. Furthermore, we can apply SS-H12 in conjunction with the ratio of statistics we term H2Tot and H1Tot to further classify identified shared sweeps as hard or soft. Finally, we identified both previously reported and novel shared sweep candidates from human whole-genome sequences. Previously reported candidates include the well-characterized ancestral sweeps at LCT and SLC24A5 in Indo-Europeans, as well as GPHN worldwide. Novel candidates include an ancestral sweep at RGS18 in sub-Saharan Africans involved in regulating the platelet response and implicated in sudden cardiac death, and a convergent sweep at C2CD5 between European and East Asian populations that may explain their different insulin responses.
Tissue damage to wheat seedlings (Triticum aestivum) under salt exposure

High content of mineral salts reduces crop yields. Agricultural areas are being reduced due to the secondary salinization of land. Wheat is one of the main crops, however, wheat is a type of plant that is sensitive to the toxic effects of mineral salts. Therefore, the identification of cytological and biochemical markers for determining resistant and sensitive wheat varieties to abiotic stress caused by the toxic effects of mineral salts is one of the important tasks of agriculture. Methods of fluorescence, cytophotometry, electrophoresis, and light-optical microscopy produced suitable cytological markers for creating a test system for the early diagnosis of wheat sensitivity to the tested salts. Different wheat genotypes of Triticum aestivum Host. (varieties Agata, Uchitel’, and Zhemchuzhina Povolzh’ya) underwent treatment to investigate their reaction to the toxic effects of sodium chloride and sodium sulfate. The varieties responded differently to the presence of the salts; these were reflected in changes in biometric data, the passage of the cell cycle, features of ROS accumulation, and a quantitative assessment of the viability of seedling cells. In the genotypes sensitive to sodium chloride and sodium sulfate (varieties Zhemchuzhina Povolzh’ya and Uchitel’), tissue damage was observed in root cells under toxic effects, while in the resistant genotype (variety Agata) cell damage was minimal. The developed complex of intravital markers of various wheat genotypes in the early development stages can be effectively used to characterize wheat with different tolerance to chloride and sulfate salinization.
WNT1 Inducible Signaling Pathway Protein 1 (WISP1) stimulates melanoma cell invasion and metastasis by promoting epithelial – mesenchymal transition

Besides intrinsic changes, malignant cells release soluble signals to reshape their microenvironment. Among the signaling factors is WNT1 inducible signaling pathway protein 1 (WISP1), a secreted matricellular protein that is elevated in a variety of cancers including melanoma and is associated with reduced overall survival of patients diagnosed with primary melanoma. In this work, we found that WISP1 knockout both increased cell proliferation and repressed wound healing, migration and invasion of mouse and human melanoma cells in an ensemble of in vitro assays. In vivo metastasis assays showed that WISP1 knockout repressed tumor metastasis in both C57BL/6Ncrl and NOD-scid IL2Rgammanull (NSG) mice with B16F10 and YUMM1.7 melanoma cells. Mechanistically, B16F10 cells that invaded in a transwell assay possessed a gene expression signature similar to Epithelial - Mesenchymal Transition (EMT), including coincident repression of E-cadherin and induction of fibronectin and N-cadherin. Upon WISP1 knockout, these EMT signature genes went in opposite directions in both mouse and human cell lines and were rescued by media containing WISP1 or recombinant WISP1 protein. In vivo, metastasis repression by WISP1 knockout was reversed by the reintroduction of either WISP1 or SNAI1. A set of EMT gene activation and inhibition experiments using recombinant WISP1 or kinase inhibitors in B16F10 and YUMM1.7 cells suggested that WISP1 activates Akt and MAP kinase signaling pathways to shift melanoma cells from a proliferative to invasive phenotype. Collectively, the results supported a model that WISP1 within the tumor microenvironment stimulates melanoma invasion and metastasis by promoting an EMT-like process.
Cascaded single-phase, PWM multilevel inverter with boosted output voltage

Splitting of a dc voltage source with two capacitors has been the approach in generating 5-level output voltage with single- and three-phase full-bridge circuits and added bidirectional switch. Associated with this configuration is the problem of voltage imbalance between the splitting capacitors. In addition, the inverter output voltage magnitude is obviously limited to the value of the split input voltage source. Presented in this paper is a unit topology for single-phase 5-level multilevel inverter, MLI. It simply consists of a full-bridge circuit, a capacitor, charge-discharge unit and a dc source. The charge-discharge unit with the capacitor is the interface between the full-bridge and the dc source. The proposed unit cell can generate a 5-level output voltage waveform whose peak value is twice the input voltage value. For higher output voltage level, a cascaded structure of the developed unit cell is presented. Comparing the proposed inverter with CHB inverter and some recent developed MLI topologies, it is found that the proposed inverter configuration generates higher output voltage value, at reduced component-count, than other topologies, for a specified number of dc input voltages. For two cascaded modules, simulation and experimental verifications are carried out on the proposed inverter topology for an R-L load. Keywords: Cascaded multilevel, Inverter, total harmonic distortion, topologies, waveform