Miracle-dz/UniFAR-FTUs huggingface dataset:
Manufacture of Bio-ethanol from Waste Material (Cassava Peels) Utilizing Some Microbes

Introduction: There has been various report of the potential of manufacturing of bioethanol from the use of different microbial inoculants for the fermentation of different feedstocks has been previously described and carried out by various researchers. And bioethanol is considered as cheap and efficient biofuel, and environmentally friendly Aims: The aim of this study is to manufacture bio-ethanol from waste material; such as cassava peel, which would serve as an alternate source of fuel. Methodology: Cassava peels obtained from garri processing plant in Ado-Ekiti, Ekiti State, were washed, sun-dried, grounded into powdery form and then sieved with 1.5 μ nylon sieve. The powdery cassava peels obtained was cultured using the following inoculant combinations: A = 20 g + Bacillus; B = 20 g + Pseudomonas; C = 20 g + Bacillus + Pseudomonas; D = 40 g + Bacillus; E = 40 g + Pseudomonas; F = 40 g + Bacillus + Pseudomonas; G = 20 g + Aspergillus niger; H = 20 g + Fusarium; I = 40 g + Aspergillus niger; J = 40 g + Fusarium. The control was free of inoculated organism. The cultures were subjected to distillation process for on the 21st day; and the quantity of bio-ethanol manufactured in each group was recorded. Results: The waste material (cassava peels) produced the highest bio-ethanol yield of 147 mL with A. niger, followed by the combination of Bacillus + Pseudomonas which yielded 108 mL of bio-ethanol. Low ethanol yields of 45, 83 and 94 ml/L were obtained from the cassava peels of in combination with Fusarium, Pseudomonas and Bacillus alone. Conclusion: Microbes of choice in this study displayed great potential for manufacturing of bio-ethanol from cassava peels.
Shot-noise cojumps: Exact simulation and option pricing

Abstract We consider a parsimonious framework of jump-diffusion models for price dynamics with stochastic price volatilities and stochastic jump intensities in continuous time. They account for conditional heteroscedasticity and also incorporate key features appearing in financial time series of price volatilities and jump intensities, such as persistence of contemporaneous jumps (cojumps), mean reversion and feedback effects. More precisely, the stochastic variance and stochastic intensity are jointly modelled by a generalised bivariate shot-noise process sharing common jump arrivals with any non-negative jump-size distributions. This framework covers many classical and important models in the literature. The main contribution of this paper is that, we develop a very efficient scheme for its exact simulation based on perfect decomposition where neither numerical inversion nor acceptance/rejection scheme is required, which means that it is not only accurate but also the efficiency would not be sensitive to the parameter choice. Extensive numerical implementations and tests are reported to demonstrate the accuracy and effectiveness of this scheme. Our algorithm substantially outperforms the classical discretisation scheme. Moreover, we unbiasedly estimate the prices of discrete-barrier European options to show the applicability and flexibility of our algorithms.
Sepsis and Thrombocytopenia: A Nowadays Problem

Sepsis is a life-threatening organ failure produced by a dysregulated host response to infection that involves 15.6% of hospital mortality. The most common signs and symptoms of sepsis are hypotension, tachypnea, fever, and leukocytosis, whether suspected or confirmed. Including a major one, thrombocytopenia is a sign that is an independent predictor of poor outcomes in patients with sepsis, increasing their mortality rate and their length of stay in the intensive care unit (ICU). So far, the ongoing treatment for this problem is securing the airway, treating hypoxemia, and providing vascular access for hydration, antibiotic delivery, and vasopressors, if needed. This article has reviewed the different possible mechanisms found for sepsis-associated thrombocytopenia, going from the most acknowledged one as decreased platelet production to the potential aftermath of sepsis itself as disseminated intravascular coagulation (DIC). This article has also discussed the future treatment for patients suffering from thrombocytopenia and sepsis, going from phase I and II trials as GI antagonists to the well-known drug aspirin as a possible treatment for this problem.
A Web-Based Knowledge Engineering and Management System

This paper presents a web-based system for knowledge engineering and management. The system consists of three components: data preprocessing, machine learning, and rule-based classifier generator. The only requirement from end users is data sets stored in CSV (Comma Separated Value) format. The system integrates data base systems, rule-based systems, and machine learning systems with a web-based interface to provide an easily accessible and managable knowledge engineering tool that can release end users from any programming burdens.
Genetic Diversity and Its Impact in Enhancement of Crop Plants

Plant breeding is a science that focuses on the development of new plant varieties in a systematic and ongoing method. It takes advantage of genetic variation among individuals within a plant species and combines desired traits to produce new and improved varieties. Plant breeding depends on genetic variety, and new variation is critical for introducing interesting characteristics into breeding programs. Genetic erosion is a term used to describe the loss of variation in crops as a result of agricultural modernization. Plant breeding has had a significant impact on food production and will continue to play an important role in ensuring global food security. Plant breeding can be broadly described as changes in plants caused by human use, ranging from unintended modifications generated by the introduction of agriculture through the use of molecular tools for precision breeding. Plant breeding based on observed variation by selection of plants based on natural variants appearing in nature or within traditional varieties; plant breeding based on controlled mating by selection of plants presenting recombination of desirable genes from different parents; and plant breeding based on monitored recombination by selection of specific genes or marker profiles. Continuous use of traditional breeding methods in a given species may reduce the gene pool from which cultivars are derived, making crops more susceptible to biotic and abiotic challenges and impeding future advancement. Plant breeding's primary objectives are 'high yield, high quality, and quantity, extension of climate and soil adaptability ability, and tolerance or resistance to pests and diseases. ' Plant breeders achieve these goals by exploiting genetic differences between plants. The range of the genetic base, as measured by genetic diversity, is a limiting factor in successful adaptation to environmental conditions and plant breeding. Many challenges in plant breeding require genetic variation, which can be found in the biodiversity of plant genetic resources such as breeding lines, landraces, primitive forms, wilds and wild relatives, and weed races.
Method of Critical Set construction for Successive Cancellation List Decoder of Polar Codes Based on Deep Learning of Neural Networks

The Successive Cancellation List (SCL) algorithm is a widely used decoding technique in communication systems. However, constructing the critical set for SCL decoding is a challenging task, as it requires a large number of computations and can lead to significant decoding delays. In this paper, a new approach to critical set construction for SCL decoding is proposed, which is based on deep learning of neural networks with special structure and activation functions.The proposed method is shown to significantly reduce the cardinality of the critical set required for achieving the target frame error rate, when used with an SCL decoder with a list size of 8. Simulation results demonstrate that the proposed method outperforms existing methods in terms of reducing decoding delay, while maintaining high decoding accuracy.The key innovation of the proposed approach lies in the use of deep learning techniques to learn the structure of the critical set, which enables the construction of a more efficient and compact set. This approach has the potential to significantly improve the performance of SCL decoding in practical communication systems, where decoding delay is a critical factor.
Quality Indicators in Laboratory Medicine

We are still under discussion about Quality issues in nowadays laboratories despite their super technical and robotically packed equipment. It seems that all fully automated systems generate the same issues as many years ago when laboratories mainly been equipped with semiautomated machines or totally manually procedures took place on a bench. Bearing in mind that human errors will be still possible while even single person operate any process or any step within laboratory, the Quality Indicators (QI) calculation and monitoring will be under control of the members of staff. Routine testing requires maximum strength everyday while Quality Management requires not only enough time to perform procedures at excellent manner but also relevant knowledge and skills. This short Opinion article should be helpful to create own laboratory Quality Indicators design and subsequent monitoring.
Extended Reality in Marketing - A Multiple Case Study on Internet of Things Platforms

This research highlights how cloud platform as a service technologies host extended reality technologies and convergent technologies in integrated solutions. It was only around 2019 that scholarly literature conceptualized the role of extended reality, that is, augmented reality, virtual reality, and mixed reality, in the marketing function. This article is a multiple case study on the leading eleven platform as a service vendors. They provide the programming technology required to host software as a service in the cloud, making the software available from everywhere. Of the eleven cases, 10% integrate technologies in solutions. Research results show that extended reality technologies reinvent digital marketing; as part of this, they shape the customer delivery model in terms of customer value proposition; favor the choice of customer channel (the omnichannel); possibly lead to new customer relationships, such as cocreation; and reach global mass customers. Extended reality in the delivery model is complemented by other technologies in the operating model. These combinations provide the foundations of the business models, which are either network or platform business models. This study identifies a number of solutions enabled by extended reality, which have an integrated goal in the form of customer value contribution and are to be studied in further articles.
Increasing the Autonomy of the Pipe Inspection Robot PIRATE

The Pipe Inspection Robot for AuTonomous Exploration, or for short PIRATE, is an inspection robot for gas pipes. It aims to determine the location of a leak more accurately. Ideally and in order to be usable in a commercial (industrial) environment a certain level of autonomy is required. The present thesis aims at increasing the current level of autonomy for the PIRATE by designing and implementing autonomous behaviors. At first an analysis of the possible layered control software structure is done. To demonstrate the potential of the design a simple mission that combines various Partially Autonomous Behaviors has been developed. For the implementation of the software framework the Robot Operating System environment is chosen. During the development, the transition conditions (guards) were experimentally defined. The results show that, in each of these situations, the proposed sequence and transition conditions effectively clamp the robot in the desired orientation. Apart from these experiments, the simple mission was tested and it successfully shows that different PAB classes could be combined to create more complex sequences or plans. Overall the present study successfully presents a suitable software framework for further development of other PABs in the Sequential layer, as well as potential for creating more complex missions by integrating them.
System Evaluation and Management of College Students’ Physical Exercise Behavior Stages Integrating Bayesian Association Rules Data Mining Algorithm

The form of association rules is simple, and it is efficient and convenient to apply. However, because association rules cannot express the connection between different rules, in some more complex application fields, when it is necessary to comprehensively consider the impact of multiple factors on the results, the application of rules is more difficult. In the process of reasoning about the node state, the influence of various factors (parent nodes) can be comprehensively considered. This paper proposes a Bayesian network-based association rule representation method. After mining the association rules from the data, through structural learning and conditional probability table learning, the original rules are finally used as Bayesian nets. This effectively expands the application of association rules. The experimental results show that after using MapReduce parallelization, the improved algorithm can not only process larger-scale data sets, but also save a lot of running time. The correlation between physical exercise behavior evaluation management, dimensional exercise motivation, exercise method, and college students’ school adaptability reached a significance of 0.001, and the correlation between dimension exercise time and college students’ school adaptability reached a significance of 0.05. The correlation between physical exercise behavior evaluation management and school adaptability in terms of interpersonal relationship adaptation, learning adaptation, campus adaptation, career adaptation, emotional adaptation, self-adjustment, and satisfaction reached significant levels.
Integrating Maintenance Planning and Production Scheduling: Making Operational Decisions with a Strategic Perspective

Integrating Maintenance Planning and Production Scheduling: Making Operational Decisions with a Strategic Perspective Maliheh Aramon Bajestani Doctor of Philosophy Graduate Department of Mechanical & Industrial Engineering University of Toronto 2014 In today’s competitive environment, the importance of continuous production, quality improvement, and fast delivery has forced production and delivery processes to become highly reliable. Keeping equipment in good condition through maintenance activities can ensure a more reliable system. However, maintenance leads to temporary reduction in capacity that could otherwise be utilized for production. Therefore, the coordination of maintenance and production is important to guarantee good system performance. The central thesis of this dissertation is that integrating maintenance and production decisions increases efficiency by ensuring high quality production, effective resource utilization, and on-time deliveries. Firstly, we study the problem of integrated maintenance and production planning where machines are preventively maintained in the context of a periodic review production system with uncertain yield. Our goal is to provide insight into the optimal maintenance policy, increasing the number of finished products. Specifically, we prove the conditions that guarantee the optimal maintenance policy has a threshold type. Secondly, we address the problem of integrated maintenance planning and production scheduling where machines are correctively maintained in the context of a dynamic aircraft repair shop. To solve the problem, we view the dynamic repair shop as successive static repair scheduling sub-problems over shorter periods. Our results show that the approach that uses logic-based Benders decomposition to solve the static sub-problems, schedules over longer horizon, and quickly adjusts the schedule increases the utilization of aircraft in the long term. Finally, we tackle the problem of integrated maintenance planning and production scheduling where machines are preventively maintained in the context of a multi-machine production system. Depending on the deterioration process of machines, we design decomposed techniques that deal with the stochastic
Rendering land touristifiable: (eco)tourism and land use change

Abstract Critical research concerning ecotourism has revealed the activity’s socio-economic impacts, including low-wage employment-based dependencies for many rural communities. While these dynamics are important, a crucial aspect of the ecotourism industry that falls outside this conventional sort of dependency is land use dynamics, specifically land use change, sales and entrepreneurship. We examine these dynamics in Corbett Tiger Reserve, India, where promotion of (eco)tourism since the 1990s has influenced significant changes in local land use. These changes were initially facilitated by outsiders buying land and setting up hotels and resorts in villages adjoining the Reserve. Empirical research reveals that while this initial boom of outsiders buying land has waned, land owning villagers are now setting up tourism enterprises on their own land, thereby diversifying land use from agriculture to tourism. Critical agrarian research has shown that material and symbolic factors influence farmers’ decision-making regarding land use change. An agrarian studies perspective thus facilitates a nuanced understanding of tourism-related land use diversification and change. By bringing agrarian and ecotourism studies approaches together here, we contribute to both by emphasising the importance of (eco)tourism in agrarian change and of attention to land use change in ecotourism studies to understand how rural people negotiate and navigate (eco)tourism in relation to land use. We also contribute to tourism geographies more broadly by highlighting how land use decision-making shapes local spaces in the course of ecotourism development. We draw attention to the broader processes of and impacts of ecotourism that shift generational rural land use influenced by changing values of land outside a protected area. Rendering land touristifiable deepens villagers’ dependence on the market and alienates them from their land. Ecotourism commodifies nature, and we show that this commodification extends to rural land outside of ecotourism zones per se.
A CRYPTOGRAPHIC PRIMITIVE TO PREVENT AN INVADER FROM CREATING DODGING ATTACKS

Keyed invasion recognition method is a charge card applicatoin-layer network system of anomaly recognition that extracts several features from all the payload. The essential idea of Keyed invasion recognition system to obstruct evasion attacks is always to are the thought of key, this like a secret element which determines extraction of classification features within the payload. Our focus remains on recovering key completely through efficient procedures, demonstrating that classification procedure leaks data regarding this which may be leveraged by means of an opponent. Inside our work we evaluate strength of Keyed Invasion Recognition System against key-recovery attacks. We describe that recovering of the end result is particularly simple when as long as the attacker can talk to Keyed invasion recognition system and get feedback regarding probing demands.
ANALISIS PENDAPATAN PETERNAK AYAM RAS PEDAGING POLA KEMITRAAN INTI –PLASMA (Studi Kasus Peternak Plasma PT.Genesis di Kecamatan Grabag Kabupaten Magelang Jawa Tengah)

A broiler chicken meat producer that has some advantages including, rapid capital turnover rate and a short maintenance period ie within five weeks of broiler already be harvested and weighs 1.9 kg / head. This has encouraged many farmers who seek broiler farms. PT. Genesis is one of the broiler farms, which work closely with the farmers in the district through a partnership Grabag core-plasama. The partnership goal is to increase revenue, and increase both the scale of the company's businesses and farmers. The purpose of this study was to analyze the mechanism of partnerships undertaken in partnership plasma core, know the maintenance management (cultivation) of cattle in partnership nucleus-plasma, and calculates the income and value of the R / C ratio obtained in the plasma farmer-core partnership plasma. The research was conducted in partnership with farmers who farm company PT. Genesis. Nucleus location is in Taman Anggrek Unggaran Housing. Plasma breeders located in District Grabag, Magelang regency. The research was carried out for 1 month, ie in February and March 2013 which was designed as a case study, a total of 11 respondents breeders who partnered with PT. Genesis is currently in production. Data were collected by census method. The data used are primary data and secondary data. Maintenance of production data using the data on the plasma farmers February to March 2013 period (1 period). Analysis of the data used is descriptive analysis, revenue analysis, and analysis of R / C ratio. Results of the analysis showed that the income on the income earned period February to March 2013 were farmers Rp 3,332,844.97 per period. Analysis results Net B / C ratio showed 1.02 and BEP are at the point 66,524,262.00 Key words: partnership mechanism, plasma farmers, income, Net B / C ratio
Liver Transplant Oncology: Towards Dynamic Tumor-Biology-Oriented Patient Selection

While liver transplantation was initially considered as a curative treatment modality only for hepatocellular carcinoma, the indication has been increasingly extended to other tumor entities over recent years, most recently to the treatment of non-resectable colorectal liver metastases. Although oncologic outcomes after liver transplantation (LT) are consistently good, organ shortage forces stringent selection of suitable candidates. Dynamic criteria based on tumor biology fulfill the prerequisite of an individual oncological prediction better than traditional morphometric criteria based on tumor burden. The availability of specific (neo-)adjuvant therapies and customized modern immunosuppression may further contribute to favorable post-transplantation outcomes on the one hand and simultaneously open the path to LT as a curative option for advanced stages of tumor patients. Herein, we provide an overview of the oncological LT indications, the selection process, and expected oncological outcome after LT.
A Metal Tag Antenna for Passive UHF RFID Applications

In this paper, a passive tag antenna operating in RFID UHF band is presented, which may be mounted on a metallic object. This metal tag antenna design is composed of a slot radiator, a capacitive coupling structure and a coplanar waveguide (CPW) feed to provide a good power transfer to the tag IC. No additional matching network is required to achieve a conjugated matching between the tag IC and the proposed tag antenna. A commercial simulator, HFSS is used to analyze the proposed antenna performance. This tag antenna for the 900MHz RFID band has dimensions of only 93(L) £ 20(W) £ 3:4(H)mm 3 , and therefore can be easily attached on metal surfaces, such as license plates for vehicle managements. Also, the antenna with low cost, easy fabrication and high e-ciency are achieved by using a 0.4mm FR4 PCB attached on a 3mm PP substrate. For the metal tag mounted on the license plate, the maximum readable range measured in an anechoic chamber is more than 7m for a reader with an EIRP equal to 4W.
High Step-Up Interleaved Forward-Flyback Boost Converter for RES

- A novel high step-up interleaved converter for high-voltage applications is proposed in this paper. High step-up conversion with high efficiency is obtained through three-winding coupled inductors. The proposed converter decreases the conduction losses and reduces the current stress on swtches. In addition, due to the lossless passive clamp performance, leakage energy is recycled to the output terminal. Hence, large voltage spikes across the main switches are suppressed and the efficiency is improved. Finally MATLAB/ Simulink implementation of the proposed converter is developed for an output voltage of 380V with minimum ripple <2%.