Miracle-dz/UniFAR-FTUs huggingface dataset:
Genotype resistance of hybrid corn varieties candidate against major corn diseases

The resistance level of several national superior corn varieties to the primary disease of corn is still varied and unstable. Therefore, evaluating the resistance of hybrid corn varieties candidate to the primary disease of corn is deemed necessary as an initial step in managing the disease. This study aimed to evaluate the resistance reaction of the hybrid corn varieties candidate against the primary disease of corn. This study was conducted at two different locations. The first location was at the Agricultural Technology Research and Assessment Installation (ATRAI) of the Indonesian Cereals Research Institute in Bajeng District, Gowa Regency, South Sulawesi first, where the test for P. phillipinensis downy mildew, leaf blight, and leaf rust was conducted. The next location was at the ATRAI of Muneng of the Research Institute for Various Nuts and Tubers in Probolinggo, East Java, where the test for the P. maydis downy mildew was conducted. The tests were carried out using plants as the source of the test pathogen inoculum planted around the experimental block. The four corn genotypes tested were CHC1, CHC02, CHC3, CHC5, and CHC5. Meanwhile, the comparison varieties used were P36, Pertiwi-6, PAC339, BISI18, Anoman, and Pulut. The test results showed the two hybrid corn varieties candidate that were moderately resistant to P. philipinensis, namely CHC1 and CHC2, with attack intensities of 30.94% and 32.07%, respectively; one variety candidate resistant to P. maydis, namely CHC1 with an attack intensity of 15.92%. Meanwhile, the five hybrid corn varieties candidate, namely CHC1, CHC02, CHC3, CHC5, and CHC5, showed a moderately resistant reaction to maydis leaf blight and leaf rust with an attack intensity of 35%.
A formal pattern of information system design

A new design pattern intended for distributed cloud-based information systems is proposed. Pattern is based on the traditional client-server architecture. The server side is divided into three principal components: data storage, application server and cache server. Each component can be used to deploy parts of several independent information systems, thus realizing shared-resource approach. A strategy of separation of competencies between the client and the server is proposed. The strategy assumes that the client side is responsible for application logic and the server side is responsible for data storage consistency and data access control. Data protection is ensured by means of two particular approaches: at the entity level and at the transaction level. The application programming interface to access data is presented at the level of identified transaction descriptors.
Modified TiO2 for photocatalytic removal of organic pollutants in water

In this work, TiO2/Ti2O3 composite catalysts were prepared by simple one-step thermal treatment method at various temperatures. The morphology and structure of as-prepared samples have been examined by XRD, TGA and SEM. The XRD characterization results revealed three-phase mixture in sample treated at 550°C, while at 650°C phase transformation from TiO2 anatase to TiO2 rutile and particle size growth was observed. Moreover, the effect of treatment temperature on the photocatalytic degradation of caffeine was evaluated under UV light irradiation. Results indicated that TiO2/Ti2O3-550 exhibited higher catalytic activity than others achieving complete caffeine removal in 60 min.
Modeling of Power MOSFET with Parasitic Parameters for the Analysis of Cdv/dt Induced Effects in Power Converters

Abstract Power MOSFETs are important devices in many types of power converters. Considering their main parasitic parameters, the Cdv/dt induced effects that will deteriorate the performance of converters are analyzed. The switching operation process is discussed firstly. Then, an analytical model of power MOSFET is deduced and validated, based on which the Cdv/dt induced effects are simulated with different values of parasitic parameters. Finally, according to the simulation results, the design optimizations are presented, and an experimental prototype is used to validate the proposed approach.
Investigation of localization accuracy in UWB relative ranging system

The hybrid combination of a traditional positioning system with fixed reference points and a relative positioning system based on the relative position of network subscribers on the basis of measuring the distances between them increases the availability of the positioning system for moving objects in harsh environment and the accuracy of their positioning. Depending on the operating conditions, the cascade measurement of the distances between the nodes expands the working area with an acceptable positioning accuracy with the same number of fixed anchors.
Climate Change and Food Security in India: Some Issues and Challenges

Climate change has added to the enormity of India's food-security challenges. While the relationship between climate change and food security is complex, most studies focus on one dimension of food security, i.e., food availability. This paper provides an overview of the impact of climate change on India's food securitySome Issues and Challenges, keeping in mind three dimensions, availability, access, and absorption. It finds that ensuring food security in the face of climate change will be a formidable challenge and recommends, among others, the adoption of sustainable agricultural practices, greater emphasis on urban food security and public health, provision of livelihood security, and long-term relief measures in the event of natural disasters. Climate change and its impact is a matter of great concern among all countries of the world because it has the potential to make vulnerable life on the earth. Therefore an attempt has been made here to examine the impact of climate change on the food security of India with special reference to the agro-climatic regions. The study revealed that climate change can adversely affect the all four dimensions of food security i.e. food availability, accessibility, utilization and stabilization. There is a great deal of uncertainty regarding climate change, but there are some certainties. The prospects of Indian food security under the upcoming climate change will depend a numbers of immediate measure i.e.to reduce the vulnerability of food system to climate change and other global environmental changes, which has started looming large the very existence of human kind.
Obtaining a diesel fuel component from liquid products of oxidative pyrolysis of wood

Recycling and rational use of wood-processing industry waste is an urgent task for the economy and industry. On the basis of experimental studies on the oxidative pyrolysis of Siberian pine and Downy birch, a basic technological scheme for components of motor fuels obtaining is proposed. It is shown that the main components of liquid products of wood pyrolysis in water vapor are aromatic and saturated hydrocarbons, as well as oxygen-containing compounds that need to be hydrogenated.
Combining ability analysis of maize lines under optimal and low nitrogen stress

Most of the land for maize development in Indonesia has low N limiting factor, thus it is necessary to develop a proper maize breeding programs tolerant to low N conditions. One of the breeding methods suitable for low N evaluation is the diallel method between inbred parents (homozygous lines) that are tolerant of low N stress. The aim of this study was to assess the genotype tolerance to low N with comparable yields. The research consisted of two stages. The first stage is the development of hybrid maize grains (F1) using the half diallel cross method. This activity was carried out in KP. Maros, Research Center for Cereal Crops. A half-diallel cross refers to the Griffing IV method, by involving 11 low N-tolerant genotypes (AVLN 100-1, AVLN 118-2, AVLN 122-2, AVLN 124-4, AVLN 32-3, AVLN 83-1, AVLN 83-4, AVLN 83-6, AVLN 86-2, MAL 04, and AVLN 124-9). The second stage was carried out in KP. Bajeng to evaluate 52 genotypes of hybrid maize from diallel crosses plus four hybrid varieties Advanta 777, Bisi 18, P 27 and JH 37 for control. The experiment was carried out under conditions of low N stress (100 kg N/ha) and normal N (200 kg N/ha). The experiment used a randomized block design with three replications. Hybrids that are tolerant (T) under conditions of low N stress was best indicated by AVLN 83-4/AVLN 124-4 genotype pair, with significant higher grain yield than Bisi-18 and JH 37 varieties. This hybrid produced average grain yield of 7.87 t/ha under both conditions. Inbred maize genotypes classified as medium tolerant (MT) were AVLN 83-4/AVLN 124-9, AVLN 124-4/AVLN 86-2, AVLN 122-2/AVLN 124-4, AVLN 83-1/AVLN 124-9, has similar yield potential as to the control varieties.
Compartmental spiking neuron model for pattern classification

One of the directions of development within the framework of the neuromorphic approach is the development of anatomically similar models of brain networks, taking into account the structurally complex structure of neurons and the adaptation of connections between them, as well as the development of learning algorithms for such models. In this work, we use the previously presented compartmental spike model of a neuron, which describes the structure (dendritic tree, soma, synapses) and behaviour (temporal and spatial signal summation, generation of action potential, stimulation and suppression of electrical activity) of a biological neuron. An algorithm for the structural organization of neuron models into a spike neural network is proposed for recognizing an arbitrary impulse pattern by introducing inhibitory synapses between trained neuron models. The dynamically adapting neuron models used are trained according to a previously proposed algorithm that automatically selects parameters such as soma size, dendrite length, and the number of synapses on each of the dendrites in order to induce a temporal response at the output depending on the input pattern encoded using a time window and temporal delays in the vector of single spikes arriving at a separate dendrite of a neuron. The developed algorithms are evaluated on the Iris dataset classification problem with four training examples from each class. As a result of the classification, separate disjoint clusters are formed, which demonstrates the applicability of the proposed spike neural network with a dynamically changing structure of elements in the problem of pattern recognition and classification.
Comparative Effects Of Spent Engine Oil And Unused Engine Oil On The Growth And Yield Of Vigna Unguiculata(Cowpea)

The disposal of Spent Engine Oil and Unused Engine Oil into gutters, water drains, open vacant plots and farms are common practice in Nigeria especially by motor mechanics. This research takes a look into the possible effects of this chemical oil on plants growth, germination and the effects of soil contaminated with spent engine oil after different degree of contamination. Also, its negative impacts on human’s health on consumption of crops grown on such contaminated soil was established as well as creating opportunity for plant breeders in searching for ways of improving cowpea production in oil-producing areas. A total of twenty-seven plastic containers (5 Litres) were filled with 4 kg of sand-loam soil which were mixed with various concentrations of spent engine oil. There were four different concentrations of oil and unused engine oil graded from 25, 50, 75 and 100mg/l of which each treatment has three replicates. The results show that a negative relationship existed between the oil levels in the soil and the growth parameters (plant height, number of leaves, stem girth, leaf area, yellowness of leaves, shedding of leaves, leaves folding, flowering and pod production) measured. The reductions and morphological effects in the growth characteristics measured in the V. unguiculata with spent and unused engine oil increased as the concentration level of the contaminant increases compared to control experiment. The most affected growth parameters occurred with 100mg/l of engine oil on plant height (19.50cm, on the second week), stem girth (0.84cm, on the second week), leaf area (21.40cm 2 , on the sixth week) while the number of leaves increases with increase in concentration of engine oil on the eight week with a value of 19.00. However, the lowest number of leaves was also recorded for the soil mixed with 100mg/l of engine oil during the second week. This study therefore showed that the presence of the engine oil has great implications on the sustainability of V. unguiculata growth. Meanwhile, the consumption of the contaminated plants by man and animals affects their health, which may eventually lead to their death. This is because of the high level of lead which is above the WHO standard for consumption. Therefore, there is the need for government and appropriate agency to enact a strict law and educate the citizenry on the indiscriminate disposal of these pollutants (spent engine oil and unused engine oil).
Signal processing of nonlinear dynamic systems

The paper considers Hermite polynomials that act as a self-similar basis for the decomposition of functions in phase space. It is shown that the equations of behavior of nonlinear dynamical systems are simplified. It is also noted that the wavelet decomposition over Hermite polynomials reduces the number of approximation coefficients and improves the quality of approximation.
Doğrudan Basım Yöntemi Kullanılarak Randomize Metillenmiş- β-siklodekstrin İnklüzyon Kompleksi İçeren Erlotinib Oral Tablet Formülasyonu Geliştirilmesi

Objectives: Erlotinib (ERL) is a tyrosine kinase inhibitor that has been used in the treatment of metastatic non-small cell lung cancer (NSCLC). However, its low aqueous solubility limits its absorption and oral bioavailability. To overcome these pharmacokinetic drawbacks, complexation of ERL can be applied. The aim of this study was to develop and characterize an oral tablet formulation containing ERL: Randomly methylated-βcyclodextrin (RAMEB-CD) inclusion complex to enhance solubility and oral bioavailability of ERL. Materials and Methods: An inclusion complex was prepared with RAMEB-CD using co-lyophilization technique. Structural characterization was performed using X-ray diffractometry and fourier-transform infrared spectroscopy. Tablet formulation of ERL: RAMEB-CD inclusion complex were prepared using direct compression technique. Tablet characteristics like hardness, diameter, thickness, friability, weight variability, disintegration and dissolution were evaluated. Flow properties of the powder were also determined. Results: Characterization studies suggested that stable complexes between ERL and RAMEB-CD were obtained with co-lyophilization method. Tablet formulation using inclusion complex of ERL and RAMEB-CD with drug dose equivalent to 25 mg was successfully prepared using direct compression technique. Physical properties of the powder mixture were studied angle of repose (°): 34.27±1.78; flow time: 2.2±0.4; HR: 1.05±0.02; compressibility index: 14.27±1.55. Moisture content (%) was found to be 0.27±0.05. The thickness, diameter and hardness values were 3.92±0.05 mm, 11.3±0.06 mm and 81.38±2.27 N, respectively. In uniformity of weight test, the average weight was 404.57±1.6 mg, with less than 5% deviation in 20 randomly selected tablets. Friability value was 0.27% and the disintegration time was found to be less than 15 min. Importantly, dissolution study showed that solubility of ERL was increased by complexation with RAMEB-CD. After 60 minutes, 99% of drug was released from the tablet formulation. Conclusion: These results demonstrate that a new tablet formulation of ERL: RAMEB-CD inclusion complex could be an alternative approach to achieve increased dissolution and oral bioavailability of ERL for NSCLC treatment.
A research on Security enhancement in Automobile Industry using the blockchain concept and Artificial Intelligence

- Nowadays autonomous vehicles and security measure improvements in automobile industry are attracting lot of attention. For addressing the security and safety several articles are reviewed in this study. Before the autonomous vehicles’ wide adoption, blockchain technologies are utilized in various fields. This paper presents the Security enhancement related with autonomous vehicles using the blockchain concept and also discussed about various techniques like Artificial intelligence, Deep learning and machine learning algorithms in automobile industry. This proposed review articles have covered the countermeasures, blockchain enabled automotive/vehicle networks and several attacks. Blockchain based data storage, handling security attacks, security countermeasures and authentication process have been analysed in this study for automobile organization enhancement. The comparative analysis has been made to address the benefits and limitations of the various technologies used. However, the above mentioned challenges have been overcome by the blockchain with distributed framework. This study significantly focused on blockchain approaches for adapting the information accessing for entities limits in ecosystem of connected vehicle. Among the roadside and vehicles, the challenge response based data exchange are utilized. It leads to vehicle internal state monitoring for in-vehicle identification. For valid and authentic communication blockchain is the better approach in vehicular network, according to this study. Compatible storage and appropriate response time ensured by the blockchain technologies. Several significant functions like vehicular forensics and trust management are exhibited for vehicular networks security stated from other articles which have been used machine learning and deep learning approaches.
H∞ Filtering for Network-Based Systems with Consecutive Packet Dropouts and Delayed Measurements

The filtering problem is studied for a class of discrete-time systems under the effect of the networks. The investigated issues involved by the network include the consecutive packet dropouts and the one-step transmission delays which can be described by a sequence of mutually independent Bernoulli distributed stochastic variables. A full-order filter is designed such that the filtering error system is exponentially stable in the mean square and the performance is also achieved. Sufficient conditions are developed for the addressed problem and the desired filter is derived by means of the feasibility of certain linear matrix inequality. Numerical example is given to illustrate the effectiveness of the proposed method.
ENABLING ACCURATE RECOMMENDER SYSTEM USING RATING PREDICTION METHODS FROM USER REVIEWS

— In recent years, shopping online is becoming more popular. When it need to decide whether to purchase a product or not on line, the opinions of others become important. It presents a great opportunity to share our viewpoints for various products purchase. However, people face the information overloading problem. How to mine valuable information from reviews to understand a user’s preferences and make an accurate recommendation is crucial. Traditional recommender systems consider some factors, such as user’s purchase records, product category, and geographic location. In this work, it proposes a sentiment-based rating prediction method to improve prediction accuracy in recommender systems. Firstly, it proposes a social user sentimental measurement approach and calculates each user’s sentiment on items. Secondly, it not only considers a user’s own sentimental attributes but also take interpersonal sentimental influence into consideration. Then, consider item reputation, which can be inferred by the sentimental distributions of a user set that reflect customers’ comprehensive evaluation. At last, by fusing three factors-user sentiment similarity, interpersonal sentimental influence, and item’s reputation similarity into recommender system to make an accurate rating prediction. It conducts a performance evaluation of the three sentimental factors on a real-world dataset. Experimental results show the sentiment can well characterize user preferences, which help to improve the recommendation performance.
Feasibility Study of Solar Energy in Iran and Preparing Radiation Atlas

For attaining to a proper feasibility study about solar energy reception the study of solar energy estimation is a necessary factor. For preparing this paper pyranometric data and sunshine hour s data of 21 solar radiation stations of different years are collected from metrological organization. On the basis of performed study sunshine hours has the most impression on the amount of total received solar radiation. for this reason calculation of solar energy is accomplished on the basis of experimental angstrom model which is base on sunshine hours. Because of dependency of Angstrom model coefficients to the regional climatic conditions. therefore the kopen climatic classification based on the temperature and precipitation is presented and accordingly five climatic region is taken in to consideration and cities at the same potential from a climatic point of view the for 139 Iran synoptic stations the amount of total solar radiation by using the visual studio software for several months of the year in terms of Mj /M 2 . day is estimated. At last kriging interpolation procedures in the GIS media software 12 monthly maps and one annually map is drawn up.
Active microfluidic mixer chip

We report the design and fabrication of a chaotic mixer based on the electrorheological (ER) fluid-controlled valves. The flow in the main channel is perturbed by liquid flow in orthogonal side channels, driven by hydrodynamic pulsating pumps. Each pulsating pump consists of a chamber with diaphragm plus two out-of-phase ER valves operating in a push-pull mode. All the valves, pumps, and mixing channels are integrated in one polydimethylsioxane chip. Mixing characteristics in the main channel are controlled by the strength and frequency of external electric fields applied on the ER fluid.