Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Organic Waste Potential of Mersin Province on Biogas Energy Production

In this study is to determine the current status of organic wastes obtained from plant, animal, kitchen and industrial sewage sludge plants in Mersin province and to generate biogas energy production potential and to create sustainable solutions at the local level. Data on animals and plants were obtained from Mersin Provincial Directorate of Agriculture and Forestry and data on kitchen and industrial wastes were obtained from Mersin Metropolitan Municipality. As a result of this study, the daily organic matter produced in animal, vegetable, kitchen and sewage sludge plant in Mersin province is 16801.48 tons and the amount of biogas produced from these wastes is 557432.47 m3 and the electricity generated from methane is 2619.93 MWh. The amount of electricity produced from organic wastes; 57% can be obtained from animal manure, 33% from treatment sludge, 6% from kitchen waste and 4% from agricultural waste. In Mersin province, it has been determined that animal manure and sewage sludge have significant potential in terms of organic matter. In addition, the biogas facilities to be established will provide commercial value contribution to the enterprises.
Synthesis , characterization , and crystal structure determination O 2 ] . 2 H 2 [ Cu ( pydc ) en ] 2 [ H ( II ) complex : of a new copper

The new complex of [H2en][Cu(pydc)2]. 2H2O (1) (where H2en and pydc are ethylenediammonium and 2,6pyridinedicarboxylate, respectively) was synthesized by the reaction of a mixture of ethylenediamine (en) and 2,6-pyridinedicarboxylic acid (H2pydc) in a mixture of CH3OH/H2O as solvent. This complex was fully characterized by elemental analysis, IR, UV–Vis spectroscopy as well as single-crystal X-ray diffraction method. The crystallographic analysis revealed that the complex of 1 consists of discrete [Cu(pydc)2] anion, one bis(protonated) ethylene diamine cation and two crystal water molecules. In the anionic part of this complex, the copper(II) cation is coordinated by two tridentate pydc anionic ligands through the two oxygen atoms of two carboxylate groups and one nitrogen atom of pyridine ring. Also, in this complex, intermolecular C-H.O, N-H.O and O-H.O hydrogen bonds and the strong π. π interactions between the pyridine rings are effective on the stabilization of the crystal packing.
A Gradual Non-Convexation Method for Minimizing VaR

Given a finite set of m scenarios, computing a portfolio with the minimium Value-at-Risk (VaR) is computationally difficult: the portfolio VaR function is non-convex, non-smooth, and has many local minima. Instead of formulating an n-asset optimal VaR portfolio problem as minimizing a loss quantile function to determine the asset holding vector R, we consider it as a minimization problem in an augmented space R, with a linear objective function under a probability constraint. We then propose a new gradual non-convexation penalty method, aiming to reach a global minimum of nonconvex minimization under the probability constraint. A continuously differentiable piecewise quadratic function is used to approximate step functions, the sum of which defines the probabilistic constraint. In an attempt to reach the global minimizer, we solve a sequence of minimization problems indexed by a parameter ρk > 0 where −ρk is the minimum curvature for the probability constraint approximation. As the indexing parameter increases, the approximation function for the probabilistic inequality constraint becomes more non-convex. Furthermore, the solution of the k-th optimization problem is used as the starting point of the (k+1)-th problem. Our new method has three advantages. Firstly, it is structurally simple. Secondly, it is efficient since each function evaluation requires O(m) work. Thirdly, a gradual non-convexation process is designed to track the global minimum. Both historical and synthetic data are used to illustrate the efficacy of the proposed VaR minimization method. We compare our method with Gaivoronski and Pflug’s quantile-based smoothed VaR method in terms of VaR, CPU time, and efficient frontiers. We show that our gradual non-convexation penalty method yields better minimal VaR portfolio. We show that the proposed gradual nonconvexation penalty method is computationally much more efficient, especially when the number of scenarios is large.
The Efficacy of Ultrasound on The Inactivation of Shiga Toxin-Producing Cells of Escherichia Coli in Raw Beef Trim

Shiga toxin-producing Escherichia coli (STEC) has been recognized as a human pathogen since 1982. However, the nonO157 STEC strains have been implicated in many human illnesses and seem to cause disease as severe as the potent E. coli O157: H7. Hence, the objective of this study was to evaluate the effectiveness of organic acids such as lactic and citric acid combine containing surfactants such as sodium lauryl sulfate in combination with ultrasound treatment for the inactivation of E. coli O26:H11, O45:H2, O103:H2, O111: H-, O121:H19, O145: NM and O104:H4 on beef trim when compared to E. coli O157:H7. The beef trim was inoculated (ca. 8.0 log CFU/g) with a seven-strain cocktail of rifampicin-resistant STEC strains (STEC-7: O111: H, O45: H2, O103: H2, O104: H4, O121: H19, O145: NM and O26: H11) and O157: H7. Inoculated meat was portioned at 25 grams and stored at 4oC for up to 8-18 h. Beef trim samples were subjected to the ultrasound treatment with operating frequency of 20 kHz at room temperature and resident times of 0, 10, and 15 min. Treated and untreated samples were stomached and plated on Sorbitol MacConkey agar with rifampicin (100 μg/ml) followed by incubation at 37oC for 24 h, the treatments were conducted in three replications. The effect of the antimicrobial treatments of beef trim showed neither the O157: H7 and non-O157 STEC cocktail were significantly (p > 0.05) inactivated in the beef trim to an acceptable level. The effect of ultrasonic treatment and the combination of ultrasound and antimicrobial treatments did not show any significant (p > 0.05) reduction of the microbial populations to an appreciable level in beef trim. The impact of the ultrasound and antimicrobial was very low (< 1 log CFU/g) on the inactivation of microbes in beef trim. International Journal of Food and
Standardization of a regeneration protocol in yellow pitahaya (Selenicereus megalanthus

A protocol for in vitro regeneration in yellow pitahaya by using indirect organogenesis pathway from axillary meristem grown on MS medium was standardized. The medium was supplemented with three concentrations of 2,4-D (2.26, 3.26 and 4.26 pM) or 2,4-D + 6BAP to 2.21 mM, or with three concentrations of TDZ (200, 300 and 400 pM) or TDZ + 6BAP, a total of 12 treatments. Growing conditions evaluated included the use of light (photoperiod of 16/8) and darkness (0/24). The 2.4-D induced calli but regeneration efficiency for the species was nil. In turn, the TDZ or TDZ + BAP were more efficient in inducing compact calli, green-purple, with capacity of regeneration following indirect organogenesis. With 300pM of TDZ more efficiency of response was observed, because the number of buds formed by regeneration point was the highest. Histological analysis confirmed the route of regeneration in S. megalanthus, showing primary structures characteristic of the formation of shoots from calli.
Towards a Universal Document Encoder for Authorship Attribution

Distributed embeddings of words and sentences have been successful in representing the semantic and syntactic properties of text. In this paper, we examine the creation of distributed document embeddings based on textual style. We present a supervised training architecture to train an encoder to produce these embeddings. We explore the viability of these embeddings for the authorship attribution task, and assess the effects of encoder architecture, text processing, and classiﬁer architecture on authorship attribution performance. While our model does not meet or exceed state of the art re-sults on the same datasets, we are able to conﬁrm our hypothesis that our supervised encoder training method produces an encoder which embeds texts based on that which unites an authors own work and distinguishes it from others, collectively speaking
T High frequency isolated boost converter for application in PV systems

In this paper a high frequency power electronics conversion system is used to connect a PV panel to the power grid. The proposed system is sized, the controllers are designed and simulated. A DC-DC converter allowing the conversion from the direct current (that is obtained through the photovoltaic panel) to a higher DC voltage is used. Then, DC / AC converters are used in the connection to the high frequency transformer and to the grid, using different modulation approaches. A MPPT algorithm is tested for two different operating scenarios: in the first one, a constant irradiance is introduced in order to verify if the system behaves as expected. In the second test a variation of solar irradiance is imposed. The obtained results show that the proposed system is able to inject sinusoidal currents in the grid, guaranteeing MPPT operation.
Comparisons of Break Points Selection Strategies for Piecewise Linear Approximation

Many optimization approaches adopt piecewise linear functions to solve real applications that are formulated as nonlinear programming problems. The number of the break points and the positions of the break points are two major factors that affect the quality of the linear approximation. Most of existing methods select evenly-spaced break points for constructing a piecewise linear approximation of a nonlinear function. This study investigates the impact of different break points selection strategies on the accuracy of the linear approximation. Two numerical experiments are presented to compare the performance of different break points selection strategies in solving nonlinear programming problems.
A Survey: Challenge & Implementation Issues in Non-Orthogonal Multiple Access Technique

— Non orthogonal multiple access or NOMA as it is known is one of the most promising multiple access techniques which is being developed for 5G networks. It has been shown through various research that NOMA provides better throughput and spectrum utilization than present existing techniques. NOMA can be classified broadly into two types power domain and code domain. This paper focuses on the implementation challenges that NOMA presents.
Semi-Automating Knowledge Base Construction for Cancer Genetics

In this work, we consider the exponentially growing subarea of genetics in cancer. The need to synthesize and centralize this evidence for dissemination has motivated a team of physicians to manually construct and maintain a knowledge base that distills key results reported in the literature. This is a laborious process that entails reading through full-text articles to understand the study design, assess study quality, and extract the reported cancer risk estimates associated with particular hereditary cancer genes (i.e., penetrance). In this work, we propose models to automatically surface key elements from full-text cancer genetics articles, with the ultimate aim of expediting the manual workflow currently in place. We propose two challenging tasks that are critical for characterizing the findings reported cancer genetics studies: (i) Extracting snippets of text that describe \emph{ascertainment mechanisms}, which in turn inform whether the population studied may introduce bias owing to deviations from the target population; (ii) Extracting reported risk estimates (e.g., odds or hazard ratios) associated with specific germline mutations. The latter task may be viewed as a joint entity tagging and relation extraction problem. To train models for these tasks, we induce distant supervision over tokens and snippets in full-text articles using the manually constructed knowledge base. We propose and evaluate several model variants, including a transformer-based joint entity and relation extraction model to extract } pairs. We observe strong empirical performance, highlighting the practical potential for such models to aid KB construction in this space. We ablate components of our model, observing, e.g., that a joint model for fares substantially better than a pipelined approach.
Cancer Therapy Optimization based on Unsupervised Learning and Multiple Model Adaptive Control

During the last years several clinical decision support systems have been developed, some of which clearly improved the results. However, this kind of decision computing process has not been quite explored in cancer treatment. In this work a control system that designs an optimal therapy based on adaptive control methods, allowing the eradication of a metastatic renal cell carcinoma as quickly and efficiently as possible and with lower associated toxicity, is developed. In order to do so, a new mathematical model describing the growth of this kind of tumor is developed, taking into account the effects of two of the most promising therapies: anti-angiogenesis and immunotherapy. Additionally, models describing pharmacodynamical aspects of the organism are also included. The therapy is designed through multiple model adaptive control. Together with a system of selection and aggregation of key classes of models, it allows to deal with the uncertainty associated with the patient, namely his intra and inter variability. The results demonstrate that the built system presents robustness in terms of stability and performance. The reference following errors for the simulations are around 3 %, which allows a tumor eradication in less than a year and a half with mild and moderate toxicity levels. Therefore, the tool developed allows to create new perspectives in the creation of decision support systems for cancer therapy, thus enhancing the medical choices.
Fast Pyrolysis of Laurel (Laurus Nobilis L.) Seed in a Fixed-bed Tubular Reactor

The daphne seed can be utilized as a biomass feedstock for conversion to bio-oil with pyrolysis process. The samples were initially pyrolyzed on a lab-scale resistively heated fixed-bed pyrolysis system at different values in the ranges of 400-700 C and 5-700Cmin to determine the effects of operation temperature and heating rate on the yields on products, respectively. Then, the bio-oil in the highest yield (35.2%) which was obtained at pyrolysis final temperature (600C) temperature, heating rate (350Cmin1), and sweeping flow rate of 100 cmmin was characterized by Fourier Transform infra-red (FT-IR) spectroscopy, gas chromatography/mass spectrometry (GC-MS) and column chromatography. The characterization results revealed that the pyrolytic oils which were complex mixtures of C11– C23 organic compounds. The elemental analysis and calorific value of the bio-oil were determined, the calorific value of 24.4 MJkg and the empirical formula of CH1.69N 0.04O0. 45. Based on the determined properties of the pyrolytic oil, it was decided that the use of pyrolytic oil derived from the daphne seed may possible be for the production of the alternative liquid fuels such as fuel for combustion systems in industry and finely chemicals after the necessary improvements.
elōs technology for Hair Removal – Combination of 810 nm diode laser with conducted Bi-polar RF energy

1. Wavelength: Diode lasers are most popular at a wavelength of 810 nm which is at the center of the hair removal wavelength band of 694-1064 nm. The 810nm wavelength has a deep penetration depth, and therefore can target major parts of the hair follicle down to the papilla. At the same time, melanin absorption is lower than the Ruby laser wavelength (694 nm), and the Alexandrite laser (755 nm), and is more suitable to treat darker skin types.
Conversational AI: Social and Ethical Considerations

Conversational Agents are becoming ubiquitous in our daily lives. They are used in various areas including customer service, education, medicine, and entertainment. As tools that are increasingly perme-ating various social domains, Conversational Agents can have a direct impact on individual’s lives and on social discourse in general. Consequently, critical evaluation of this impact is imperative. In this paper, we highlight some emerging ethical issues and suggest ways for agent designers, developers, and owners to approach them with the goal of responsible development of Conversational Agents.
Enhancement of Plant Growth by Using PGPR for a Sustainable Agriculture: A Review

Our nature is embedded with full of treasures with not only expensive products like gold, diamond, minerals etc. but also with some priceless things which are having literally even more value than all of this. Apart from these things which are so important for the survival on this earth like air, water and soil, nature is aiding things which are equally important for a sustainable future. Yes, it is in fact beyond our imagination that even small organisms surviving in soil can be useful for the plants. There are group of natural entities like beneficial soil microbial flora which are dwelling in the rhizosphere and on the surface of the plant roots which impose overall wellbeing of the plants are categorized as Plant Growth Promoting Rhizobacteria (PGPR). Researchers are studying these microbes for the past 30 years to understand the mechanics and usefulness employed by these PGPR to International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 2 (2020) Journal homepage: http://www.ijcmas. com
Testing for Common Features

Based on Engle and Krozicki's idea, co-integration, a special case of common feature will be presented in this paper. A co-integrated economic system is a system with a common stochastic trend. The paper will describe the procedure of testing for nonstationary time series which aims at the case about unit root, linear and nonlinear co-integration. With individual series in a data set, a series of tests will be presented to find whether there is existing stochastic trend, and linear co-integration test based on spurious regression is also introduced to test the linear combination. Further, we discuss the nonlinear co-integration system with STAR model, and construct the nonlinear co-integration F test. By Monte Carlo simulation, the article simulates the asymptotic distribution of the F test. Finally, the empirical application is grounded on Purchasing Power Parity theory and the testing procedure is applied into real economic data, consumer price index and exchange rate of Sweden and the US. It is concluded that each individual series has a stochastic trend, and there does not exist a linear co-integration relation, but a nonlinear co-integration relation in the system.
Vessel Detection in Oceanographic Airborne Imagery

The work here reported proposes a semi autonomous system able to detect vessels in an oceanographic environment. The Portuguese Air Force and Navy are patrolling the coast line using unmanned aerial vehicles (UAVs), since they are a pratical and inexpensive solution. Our solution encompasses preprocessing stages based on saliency and thresholding techniques before computing rotation-invariant HOG descriptors, in order to reduce the overall computational cost. We evaluated our method on a challenging dataset composed by almost 10000 images, achieving very satisfactory results comparing to state-of-the-art methods.
Alternative splicing analysis for finding novel molecular signatures in renal carcinomas

The analysis of next-generation sequencing data in oncology has been primarily focused on the genome, even though most molecular oncogenic mechanisms ultimately involve transcriptomic variation. The void in current knowledge about cancer transcriptomes and particularly oncogenic alternative splicing (AS) alterations may be overcome by analyzing RNA sequencing (RNA-Seq) data. AS is an essential mechanism of gene expression regulation, allowing a single gene to give origin to various transcripts and, consequently, different proteins. The deregulation of this process is known to cause disease and there is evidence for the role of splicing regulation in cellular programs altered in oncogenesis. This project aimed to define potential molecular signatures of prognostic value and to identify possible therapeutic targets for clear cell renal cell carcinoma (ccRCC). Thus, RNA-Seq data for tumor and matched normal renal tissue from The Cancer Genome Atlas were analyzed. The performed biostatistics analysis suggests that AS quantification could be a good measure to distinguish between tumor and normal samples. Furthermore, there are AS events that seem to be associated with survival in oncologic patients. A classification of events according to their AS quantification data distributions is also proposed, from which a loss of AS regulation in ccRCC may be inferred. Overall, this work shows that AS quantification analysis may have a great impact in clinical practice, ameliorating health care in oncology and driving precision medicine. Besides honing diagnosis and prognosis, it can contribute to the improvement of the efficacy of current genetic therapies or even lead to innovative ones.
A350 Take-off Configuration Optimization using a Surrogate-based Steepest Descent Method

At present, determination of optimal aircraft takeoff configurations is done resorting to very expensive and time-consuming flight testing. This often limits not only the quality of the optima found but also the number of configuration parameters that can be optimized. The present work implements a novel gradient steepest descent optimization algorithm to tackle this problem in an economically viable way. To achieve this, it resorts to surrogate modelling and optimal design of experiment techniques, allowing for flexibility and optimal information gain in process, respectively. Results obtained show satisfactory accuracy as long as great care is taken in the modelling and interpolation of data. An innovative statistical assessment of configuration optimality solidly supports the optima obtained thus far in the industry. This work confirms the applicability of method for real-time flight testing and, more importantly, its scalability and adaptability to different configuration problems or problem dimensionality, opening up the door for potentially large savings in future optimal configuration campaigns.
Analysis of calf sex ratio between semidomestic reindeer cows

The objective of our investigation is to test whether the probability of having a male calf is 0.5 for all individual mothers in semidomestic reindeer (Rangifer tarandus). In other words, we want to examine whether there are variations in calf sex ratio among reindeer cows. We also investigated the influence of mothers' age and calf birth year on calf sex ratio. The analyses were made on data recorded from 1986 to 1997 on 10539 semidomestic reindeer in the herding district of Ruvhten Sijte in Sweden. It was shown that there was no significant relationship between calf sex ratio and mothers' age and calf birth year. But there were indications of very young (one year old) and very old mothers (>13 years) having a lower proportion of male calves. Though there might be downward bias of estimated variance of random effects by using Laplace approximation in R software, the estimated variance (0.004) was small enough to conclude that there were no variations in calf sex ratio among individual reindeer cows.