Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of Malaria Complication Using CART (Classification and Regression Tree) and Naïve Bayes

Malaria is a disease caused by the Plasmodium parasite that transmitted by female Anopheles mosquitoes. Malaria can become a dangerous disease if late have the medical treatment. The late medical treatment happened because of misdiagnosis and lack of medical staff, especially in the countryside. This problem can cause severe malaria that has complications. This study creates a system prediction to classify the severe malaria disease using Classification and Regression Tree (CART) method and the probability of malaria complication using Naive Bayes method. The first step of this study is classifying the patients that have symptom are infected severe malaria or not based on the model that has been built. The next step, if the patient classified severe malaria then the data predicted if there any probability of complication by the malaria. There are 8 possibilities of complication malaria which are convulsion, hypoglycemia, hyperpyrexia, and the combinations of these four. The first step will evaluate by using F-score, precision and recall while the second step will evaluate by using accuracy. The highest result F-score, precision and recall are 0.551, 0.471 and 0.717. The highest accuracy 81.2% which predicted the complication is Hypoglycemia.
Buckling and postbuckling behavior of shell type structures under thermo-mechanical loads

The thermomechanical buckling and postbuckling behavior of layered composite shell type structure are considered with the finite element method (FEM) under the combination of temperature load and applied mechanical loads. To account for through-thickness shear deformation effects, the thermal elastic, Higher-Order Shear deformation Theory (HOST) is used in this study. The refined higher order theories, that takes into account the effect of transverse normal deformation, is used to develop discrete finite element models for the thermal buckling analysis of composite laminates. Attention in this study is focused on analyzing the temperature effects on buckling and postbuckling behavior of thin shell structural components. Special attention in this paper is focused on studying of values of the hole in curved panel on thermal buckling behavior and consequently to expend and upgrade previously conducted investigation. Using FEM, a broader observation of the critical temperature of loss of stability depending on the size of the hole was conducted. The presented numerical results based on HOST can be used as versatile and accurate method for buckling and postbuckling analyzes of thin-walled laminated plates under thermo-mechanical loads.
Extract of bacterial strain isolated from cave in the eastern Amazon induces selective cytotoxicity on tumor line of murine melanoma

Cancer is one of the most deadly diseases in the world, being related to the disordered growth of defective cells which produces harmful substances to the body. In this context, one of the great challenges of science is finding an effective bioactive compound for treating of this disease and microorganisms from restrictive environments, such as caves, are indicated as a promising source of these compounds. The objective of this work was to evaluate the extracts cytotoxic effects obtained from cultures of two bacterial strains isolated from Pedra da Cachoeira cave, Altamira-PA, located in a preserved forest fragment in the Eastern Amazon. Bacteria were identified by DNA sequencing analysis encoding ribosomal RNA. The choice of the ideal period of microbial development, aiming at the biocompounds production, was based in a kinetic study realized from a growth curve. Organic extracts were produced after 30 hours (stationary phase) and 40 hours (decline phase) of cultivation, obtaining four extracts by liquid - liquid partition of culture medium and four extracts from the bacterial cells. In vitro cytotoxicity tests were performed with B16F10 tumor cells using the MTT method. From the phylogenetic analyzes of the DNA sequences of both strains, a cluster with the species Bacillus subtilis was verified. The extracts obtained were subjected to cytotoxic assays and their cell viability was evaluated based on the minimum inhibitory concentration (IC50) and selectivity index (IS), with the CV26AI30H extract having an IC50 value of 83.99 and IS greater than 4.70.
Precision agriculture and the digital contributions for site-specific management of
 the fields

Site-specific management practices have been possible due to the wide range of solutions for data acquisition and interventions at the field level. Different approaches have to be considered for data collection, like dedicated soil and plant sensors, or even associated with the capacity of the agricultural machinery to generate valuable data that allows the farmer or the manager to infer the spatial variability of the fields. However, high computational resources are needed to convert extensive databases into useful information for site-specific management. Thus, technologies from industry, such as the Internet of Things and Artificial Intelligence, applied to agricultural production, have supported the decision-making process of precision agriculture practices. The interpretation and the integration of information from different sources of data allow enhancement of agricultural management due to its capacity to predict attributes of the crop and soil using advanced data-driven tools. Some examples are crop monitoring, local applications of inputs, and disease detection using cloud-based systems in digital platforms, previously elaborated for decision-support systems. In this review, we discuss the different approaches and technological resources, popularly named as Agriculture 4.0 or digital farming, inserted in the context of the management of spatial variability of the fields considering different sources of crop and soil data.
Running BGP in Data Centers at Scale

Border Gateway Protocol (BGP) forms the foundation for routing in the Internet. More recently, BGP has made serious inroads into data centers on account of its scalability, extensive policy control, and proven track record of running the Internet for a few decades. Data center operators are known to use BGP for routing, often in different ways. Yet, because data center requirements are very different from the Internet, it is not straightforward to use BGP to achieve effective data center routing. In this paper, we present Facebook’s BGP-based data center routing design and how it marries data center’s stringent requirements with BGP’s functionality. We present the design’s significant artifacts, including the BGP Autonomous System Number (ASN) allocation, route summarization, and our sophisticated BGP policy set. We demonstrate how this design provides us with flexible control over routing and keeps the network reliable. We also describe our in-house BGP software implementation, and its testing and deployment pipelines. These allow us to treat BGP like any other software component, enabling fast incremental updates. Finally, we share our operational experience in running BGP and specifically shed light on critical incidents over two years across our data center fleet. We describe how those influenced our current and ongoing routing design and operation.
Nutrient intake, digestibility and nitrogen balance of two temperate and two tropical forage legume hays fed to New Zealand white rabbits

Nutrient intake, digestibility and nitrogen balance of two temperate and two tropical forage legume hays fed to New Zealand white rabbits 1 * 2 2 3 4 1 Akpensuen, T. T . , Amodu, J. T. , Tanko, R. J., Abdu, S. B. , Namo, O. A. T. , Luka, J. 3 2 S. , Hassan, M. R. and Gadzama, I. U. 1 Department of Animal Production, Faculty of Agriculture, University of Jos 2 National Animal Production Research Institute, Shika, Ahmadu Bello University, Zaria 3 Department of Animal Science, Faculty of Agriculture, Ahmadu Bello University, Zaria Department of Plant Science and Biotechnology, Faculty of Natural Sciences, University of Jos *Corresponding author: atersur@gmail.com; +2348058828892 Abstract
Adaptive Sampling Line Search for Stochastic Optimization with Integer Variables

We consider optimization problems with an objective function that is estimable using a Monte Carlo oracle, constraint functions that are known deterministically through a constraint-satisfaction oracle, and integer decision variables. Seeking an appropriately deﬁned local minimum, we propose an iterative adaptive sampling algorithm that, during each iteration, performs a local optimality test using an adaptive statistical procedure, followed by a line search executed along a stochastic descent direction. The proposed algorithm is adaptive in a precise sense: the sample size used for function estimation is a stopping time with respect to the sigma algebra of already generated observations. We prove a number of results. First, the true function values at the iterates generated by the algorithm form an almost-supermartingale process, and the iterates are absorbed with probability one into the set of local minima in ﬁnite time. Second, such absorption happens exponentially fast in iteration number and in oracle calls. This result is analogous to non-standard rate guarantees in stochastic continuous optimization contexts involving sharp minima. Third, the oracle complexity of the proposed algorithm increases linearly in the dimensionality of the local neighborhood. Importantly, as a solver, the proposed algorithm is eﬀective on a variety of problems; we illustrate this performance on two ﬂexible problem classes, on problems with dimensions ranging from 25 to 200.
A Green Hazardous Waste Location-routing Problem Considering the Risks Associated with Transportation and Population

The researches on environmental and sustainability are an active topic, especially in the waste management. As such, the hazardous waste optimization is an active research topic in developing countries which may be integrated with carbon emissions and green subjects. This grand challenge motivates the current research to contribute a new multi-objective optimization model to address the green hazardous waste location-routing problem. The proposed multi-objective optimization model establishes four objectives simultaneously for the first time. In addition to the total cost and the greenhouse gas emissions of the transportation systems as the two main objectives, another objective function aims to minimize the risk of transportation of the hazardous waste alongside the waste residue associated with the people’s exposure around transportation paths. Furthermore, the total risk linked with the population in a certain radius around the treatment and disposal centers is minimized. As the proposed model is complex with conflicting objectives, several multi-objective decision making (MODM) tools are employed and compared with each other based on different test problems associated with an industrial example. Based on the solution quality and the computational time, the technique for the order of preference by similarity to the ideal solution (TOPSIS) is selected as the strongest technique to assess the performances of all five MODM methodologies. doi: 10.5829/ije.2020. 33.11b. 18
Water durable glasses with ultra low melting temperatures

On montre que les verres de fluorophosphate de plomb et d'etain possedent une association extraordinaire de temperature de transition vitreuse tres basse et de tres bonne resistance a l'attaque de l'eau. Une partie de ce comportement peut etre expliquee par la separation de phases et on propose un modele de structure
Anticancer activity of milk fat rich in conjugated linoleic acid against Ehrlich ascites carcinoma cells in female Swiss albino mice

Background and Aim: The major conjugated linoleic acid (CLA) isomers have anticancer effect, especially breast cancer cells, inhibits cell growth and induces cell death. Also, CLA has several health benefits in vivo, including antiatherogenesis, antiobesity, and modulation of immune function. The present study aimed to assess the safety and anticancer effects of milk fat CLA against in vivo Ehrlich ascites carcinoma (EAC) in female Swiss albino mice. This was based on acute toxicity study, detection of the tumor growth, life span of EAC bearing hosts, and simultaneous alterations in the hematological, biochemical, and histopathological profiles. Materials and Methods: One hundred and fifty adult female mice were equally divided into five groups. Groups (1-2) were normal controls, and Groups (3-5) were tumor transplanted mice (TTM) inoculated intraperitoneally with EAC cells (2×106/0.2 mL). Group (3) was (TTM positive control). Group (4) TTM fed orally on balanced diet supplemented with milk fat CLA (40 mg CLA/kg body weight). Group (5) TTM fed orally on balanced diet supplemented with the same level of CLA 28 days before tumor cells inoculation. Blood samples and specimens from liver and kidney were collected from each group. The effect of milk fat CLA on the growth of tumor, life span of TTM, and simultaneous alterations in the hematological, biochemical, and histopathological profiles were examined. Results: For CLA treated TTM, significant decrease in tumor weight, ascetic volume, viable Ehrlich cells accompanied with increase in life span were observed. Hematological and biochemical profiles reverted to more or less normal levels and histopathology showed minimal effects. Conclusion: The present study proved the safety and anticancer efficiency of milk fat CLA and provides a scientific basis for its medicinal use as anticancer attributable to the additive or synergistic effects of its isomers.
Undercover: Cooperation-based Routing Protocol for Cognitive Radio Networks

Primary user activity is a major bottleneck for existing routing protocols in cognitive radio networks. In the scope of cognitive radio networks, typical routing protocols avoid areas that are highly congested with primary users, leaving only a small fragment of available links for secondary route construction. In addition, wireless links are prone to channel impairments such as multipath fading; which renders the quality of the available links highly fluctuating. In this work, we investigate using cooperative communication mechanisms to reveal new routing opportunities, enhance route qualities, and enable true coexistence of primary and secondary networks. As a result, we propose Undercover : a cooperative routing protocol that utilizes the available location information to assist in the routing process. Specifically, our protocol revisits a fundamental assumption taken by the state of the art routing protocols designed for cognitive radio networks. In Undercover , we integrate cooperative communication techniques into the route discovery process where secondary users can transmit in the regions of primary users activity through nulling out transmission at primary receivers via beamforming. In addition, the secondary links qualities are enhanced using cooperative diversity. To account for the excessive levels of interference typically incurred due to cooperative transmissions, we allow our protocol to be interference-aware. Thus, cooperative transmissions are penalized in accordance to the amount of negatively affected secondary flows. We evaluate the performance of our proposed protocol via NS2 simulations which show that the main protocol idea can enhance the network goodput by a ratio reaches up to 250% compared to other popular cognitive routing protocols with minimal added overhead. Then, we propose CSCR, a channel selection scheme for cooperation-based routing protocols in cognitive radio networks. The proposed scheme increases the spectrum utilization through integrating the channels selection in the route discovery phase of Undercover . The best channels, that are less congested with primary users and that lead to minimum switching overhead, are chosen while constructing the cooperative group. Evaluating CSCR via NS2 simulations shows the advantage of choosing wisely the working channel. Undercover , with CSCR added over it, outperforms its counterparts in terms of goodput, end-to-end delay, and packet delivery ratio. The proposed scheme can enhance the network goodput, in some cases, by more than 150%, as compared to other related protocols.
Complexity Neural Networks for Estimating Flood Process in Internet-of-Things Empowered Smart City

With the advancement of the Internet of Things (IoT)-based water conservation computerization, hydrological data is increasingly enriched. Considering the ability of deep learning on complex features extraction, we proposed a flood process forecasting model based on Convolution Neural Network(CNN) with two-dimension(2D) convolutional operation. At first, we imported the spatial-temporal rainfall features of the Xixian basin. Subsequently, extensive experiments were carried out to determine the optimal hyper parameters of the proposed CNN flood forecasting model.
The Influence of Social TV Multitasking Behavior on the Effectiveness of Cross-Media Advertising

Social TV, a second screen activity comprising a community of users engaged in a primary screen activity, differs from watching TV alone (i.e., individual TV). A 2 (TV viewing condition: individual vs. social TV) ́ 2 (advertisement on the second screen: video vs. picture) factors between-subjects experiment design was conducted to investigate whether interactions occurring in the two TV viewing conditions affect advertising effectiveness. The results confirmed two-way interactions: (1) In the social TV viewing condition, video advertisements on the second screen led to better advertising effectiveness; (2) in the individual TV viewing condition, picture advertisements on the second screen led to better advertising effectiveness; and (3) gratifications from media use partially mediated viewing conditions and advertising effectiveness.
Consistency between high throughput sequencing and microscopy-based morphological characterization of phytoplankton communities

Thus far, the phytoplankton community composition analyses, used e.g. monitoring and assessment of the ecological status of water bodies, are based on time-consuming and expertise-demanding light microscopy analyses. Currently, DNA-based molecular tools are being developed to replace microscopy-based analyses. Although most of the DNA is expected to be found in living cells, long-lasting DNA in damaged cells or soluble extracellular or relic DNA can make up a large proportion of the total DNA in water samples. DNA-based phytoplankton analysis has been shown to be affected by the huge variation in the copy number of the rRNA gene between phytoplankton species (Mäki et al. 2017). On the contrary, RNA is present only in living organisms and reflects active protein synthesis. Therefore, RNA-based methods can provide a more reliable estimate of community composition. The large copy number variation of ribosomal genes and the absence of universal primers for simultaneous amplification of cyanobacterial and eukaryotic phytoplankton genes hinder the application of DNA-based molecular methods. We applied a directional randomprimed high throughput sequencing (HTS) approach (Mäki and Tiirola 2018) to analyse 16S and 18S rRNA community structures of 83 boreal lakes in Finland, Northern Europe. ‡ § § | § ‡ © Vuorio K et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. With the method it was possible to simultaneously amplify all groups of aquatic microorganisms in addition to cyanobacteria and eukaryotic phytoplankton. A comparison between microscopy and HTS showed that the relative phylum (Fig. 0) and class level abundances of eukaryotic phytoplankton and order level abundances of cyanobacteria were consistent between the methods, despite that the HTS method overestimated the relative abundance of cyanobacteria. However, correspondence was low at genus and species level, mainly due to the lack of reference library sequences. HTS revealed more genera and was able to differentiate cryptic genera lacking morphological characteristics, but microscopy revealed a longer list of species (Vuorio et al. 2020). The RNA-based method applied showed potential, but it is not yet able to replace microscopy, mainly due to the lack of full length 16S and 18S sequences in the reference libraries. The main advantage of the method is that it is not limited to phytoplankton, but can be applied to simultaneous investigation of the total composition of microbes, including all bacteria, protists, ciliates, rotifers and zooplankton.
Comprehensive end-to-end test for intensity-modulated radiation therapy for nasopharyngeal carcinoma using an anthropomorphic phantom and EBT3 film

Background: In head and neck radiotherapy, immobilization devices can affect dose delivery. In this study, a comprehensive end-to-end test was developed to evaluate the accuracy of radiotherapy treatment. Materials and Methods: An Alderson Radiation Therapy (ART) anthropomorphic phantom with EBT3 film was used to mimic the actual patient treatment process. Ten patients treated for nasopharyngeal carcinomas with IMRT were retrospectively selected. For each patient, the treatment plan, as well as the targets and OARs was transplanted onto the phantom, and the IMRT plan was subsequently recalculated to the phantom with EBT3 film. Two quality assurance (QA) plans were generated, namely “Plan-with” wherein the immobilization device was contoured and “Plan-without” wherein it was omitted. EBT3 measurements were compared with the results of the TPS calculation. Results: With different gamma calculation criteria applied, the results obtained for Plan-with were closer to the dose measured with the EBT3 film. Moreover, 1.8% deviation was observed in the posterior neck skin dose for Plan-with when compared to the film measurements while the value was 33.1% lower for Plan-without. When compared to Plan-without, each target volume in Plan-with exhibited a 1–4% reduction in the maximum dose (D2%), minimum dose (D98%) and mean dose (Dmean). Conclusion: Immobilization devices decrease the radiation dose to target volumes while increasing the skin dose and should be included within the body contour to ensure an accurate planning dose. The end-to-end IMRT test using an ART anthropomorphic phantom is a valuable tool to identify discrepancies between calculated and delivered radiation doses.
The Effect of Board of Directors and CEO on Audit Quality: Evidence from Listed Manufacturing Firms in Jordan

This study aims to examine (1) the association between the chief executive officer tenure and audit quality, (2) the relationship between chief executive officer duality and audit quality, (3) the association between board independence and audit quality, (4) the relationship between board size and audit quality, and (5) the role of controlling variables (client size, leverage debt, and business complexity) in controlling these relationships. The research sample includes 325 financial reports from manufacturing firms listed in Amman Stock exchange over the 20142018 period. The study relationships are tested by using logistic regression. The results revealed a negative relationship, but not significant between CEO tenure and independent directors with audit quality. In addition, the results showed there is a negative effect of CEO duality on audit quality; also the results revealed that there is a statistically significant effect on the board of directors (board size) on the AQ. In general, the coefficient estimates of controlling variables show that client size and leverage debt positively affect audit quality, and on the contrary, business complexity has an insignificant positive relationship with audit quality. The summary of the study findings play an active role to external auditor opinion on business practice in towered the corporate governance system.