Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular mechanism of methionine differentiation in high and low methionine maize lines

Since maize is a primary food stuff for humans and livestock, its amino acid balance is important for proper nutrition. Methionine, an essential amino acid and a primary source of sulfur, is lacking in maize endosperm. Several maize populations were developed through breeding with enhanced methionine content in comparison with normal maize populations. BS31HM (high methionine) and BS31LM (low methionine) maize were among such populations created by the selection from the highest or lowest methionine content population from original BS31 maize. Candidate gene approach was adopted to determine the difference between the two populations at transcript level of the selected genes in the endosperm. The genes selected were mostly expressed in the endosperm and could be involved in enhanced methionine biosynthesis. The selected genes, that is, 15-kDa β-zein, 16-kDa γ-zein, 19-kDa α- zeinB1, 27-kDa γ-zein, 22-kDa α-zein and 18-kDa δ-zein were responsible for coding of endosperm storage proteins when analyzed through RT-PCR. Similarly, expression level relative to the high population (2 -ΔΔct ) values were also calculated for BS31HM and BS31LM, respectively. These values were found as 1 and 0.25, 1 and 0.07, 1 and 0.10, 1 and 0.15, 1 and 0.33, 1 and 0.43 for 27-kDa γ-zein, 22- kDa α-zein, 18-kDa δ-zein, 15-kDa β-zein, 16-kDa γ-zein and 19-kDa α-zeinB1, respectively, in both populations. The p-values were determined by student’s t-test at confidence level of 95%. The expression of 18-kDa δ-gene, 15-kDa β-gene and 16-kDa γ-gene were found to be significant (p 0.05) differences in the expression level of 27-kDa γ-gene, 22-kDa α-gene and 19-kDa α- gene were observed in both HM and LM maize populations. From these results it can be concluded that all zein genes did not show expression equally in high and low methionine maize populations. Key words : Maize, methionine, zein, storage protein, amino acid, real time PCR.
Recording and Playback Techniques Employed for the “Urban Sounds” Project

The “Urban Sounds” project, born from a cooperation of the Industrial Engineering Department University of Parma with the municipal institution La Casa della Musica, aims to record characteristic soundscapes in the town of Parma with a dual purpose: delivering to posterity an archive of recorded sound fields to document Parma in 2012, employing advanced 3D surround recording techniques, and creation of a “musical” Ambisonics composition for leading the audience through a virtual tour of the town. The archive includes recordings of various “soundscapes”, such as streets, squares, schools, churches, meeting places, public parks, train station, airport and everything was considered peculiar of the town. This paper details the advanced digital sound processing techniques employed for recording, processing and playback.
Decision tree rule-based feature selection for imbalanced data

DECISION TREE RULE-BASED FEATURE SELECTION FOR IMBALANCED DATA by Haoyue Liu A class imbalance problem appears in many real world applications, e.g., fault diagnosis, text categorization and fraud detection. When dealing with an imbalanced dataset, feature selection becomes an important issue. To address it, this work proposes a feature selection method that is based on a decision tree rule and weighted Gini index. The effectiveness of the proposed methods is verified by classifying a dataset from Santander Bank and two datasets from UCI machine learning repository. The results show that our methods can achieve higher Area Under the Curve (AUC) and F-measure. We also compare them with filter-based feature selection approaches, i.e., Chi-Square and F-statistic. The results show that they outperform them but need slightly more computational efforts. DECISION TREE RULE-BASED FEATURE SELECTION FOR IMBALANCED DATA
Prophenoloxidase and Immune Indices of Indian White Shrimp Fenneropenaeus Indicus

Economical importance of shrimp in aquaculture and to the increase of diseases that are threatening shrimp cultivation, leads to the necessity of studies on immune system of shrimp and are receiving increased attention. The Prophenoloxidase (ProPO) system is the origin of melanin production and considered to be an innate defence mechanism in invertebrates . In crustaceans, prophenoloxidase (ProPO) is present in the haemolymph as an inactive form of phenoloxidase. The present study focuses on the phenoloxidase activity and other innate immune responses such as agglutination activity, phagocytic activity and encapsulation, were studied from the haemocytes of Indian white shrimp Fenneropenaeus indicus. The PO activity of F. indicus showed highest titre value (0.022 ± 0.001) in plasma, with increased concentration of laminarin. F. indicus haemocytes showed the strongest agglutination titre against human erythrocytes A (45 ± 5.5) and yeast Saccharomyces cereviceace. The results of phagocytic activity showed ingestion of yeast S. cereviceace by haemocytes of F. indicus and the encapsulation showed highest response against the sepharose 6CLB beads than other DEAE and CM sepharose beads. The present study supplements the knowledge on crustacean immunity, and understands the host pathogen interactions. An advance made through immunological research is an important criteria to increase the yield, food production and also helps for the development of aqua farming.
Patient's choice of observational strategy for early-stage prostate cancer

Active Surveillance (AS) may represent for selected patients with low risk, potentially indolent prostate cancer (PCa) a viable alternative to radical therapies, thus reducing the risk of over-treatment. Researchers and clinicians emphasized that the choice of AS may be a controversial one as patients have the chance to avoid the side effects of radical therapies but also the burden of living with an untreated PCa. The aim of our study is to focus on the decision-making process leading patients to elect AS amongst different therapeutic options. An observational, qualitative study was conducted. Between 2007 and 2009, 46 patients (mean age 67 years) were administered a semi-structured interview at enrolment in the Prostate Cancer Research International: Active Surveillance protocol. The focus of the interview was on the first question, i.e. “Why did you choose AS? ”. Interviews were audio-recorded and verbatim transcriptions were made. Content analyses were performed by using a text-driven, automatic software (T-lab). Four clusters of themes emerged. In cluster 1, the most meaningful theme was the ambivalence in front of different therapeutic options. In cluster 2, the focus was on patients’ assessment of the aggressiveness of their PCa. In cluster 3, the topic was the collection of information from specialists. In cluster 4, the main theme was the collection of data through informal sources. Patients are motivated to opt for AS based on the subjective evaluation of medical information as well as characteristics of their psycho-social context. Understanding motivation for AS will help clinicians support patients in making the best choice for them. Lara Bellardita et al. Neuropsychological Trends – 12/2012 http://www.ledonline. it/neuropsychologicaltrends/ 108
Use of tunable monochromatic X-ray sources for metrological studies in the low-energy range at the Laboratoire National Henri Becquerel

In the frame of the French Metrology Institute, the Laboratoire National Henri Becquerel (LNHB) performs accurate measurements of photon emission intensities in order to improve the knowledge of radionuclides decay scheme. This is achieved using semiconductor detectors, however, in the low-energy range (E < 20 keV) their efficiency calibration is not straightforward. Moreover, their energy resolution and the detailed shape of their response function are parameters of interest for accurate processing of low-energy X-ray spectra. For these purposes, and in complement to the use of classical calibration method using standard radionuclides, an original method for detectors characterization have been developed using tunable monochromatic radiation. The tunable radiation makes possible examining and identifying the different features of X-ray spectra by fine scanning at the binding energies of the detector materials, thus improving the knowledge of the detector response function and the subsequent processing of complex X-ray spectra. Since 2001, the SOLEX source (Source Of Low Energy X-rays) has been installed at LNHB and provides tunable monochromatic radiation in the 1-20 keV energy range. This facility has been applied to the measurement of photon emission intensities and attenuation coefficients of materials (Al, Cu) in the low-energy range. In the next future, the SOLEIL synchrotron facility will be equipped with a metrology beam line that will be partially managed by LNHB: this will allow subsequent development of such metrological studies with enhanced performances.
Robust Identification of Smart Foam Using Set Membership Estimation in a Model Error Modelling Framework

Robust identification The aim of this paper is robust identification of smart foam, as an electroacoustic transducer, considering un modelled dynamics due to nonlinearities in behaviour at low frequencies and measurement noise at high frequencies as existent uncertainties. Set membership estimation combined with model error modelling technique is used where the approach is based on worst case scenario with unknown but bounded uncertainties. The outcome is a robust identified model which consists of a nominal model with its uncertainty bounds that fits exactly the H∞ robust control scheme which has been utilized in active noise control in recent years. While the nominal model has the desired physical characteristics as cut-off frequency and the anticipated slope and flatness before and after this frequency, respectively, it is maintained in the acceptably tight uncertainty upper and lower limits, thus validating the identification procedure. Looseness and tightness of uncertainty strip has also been discussed regarding nonlinearities and measurement noise in low and high frequency regions. Meanwhile the identified nominal model can also be utilized in non-robust noise control methods due to its lower order, reflecting the advantage of the applied identification approach. ©2015 Iranian Society of Acoustics and Vibration, All rights reserved
Proton Transport Property in Supported Nafion Nanothin Films by Electrochemical Impedance Spectroscopy

TheprotontransportpropertyofNafionnanothinfilms (4‐300nm)hasbeeninvestigatedbyelectrochemical impedancespectroscopy (EIS)usinginterdigitatedarray(IDA)ofgoldelectrodesonSiO2 substrate.Theprotonconductivityhasbeeninvestigatedasafunction of film drying/heating protocol, relative humidity, temperature and film thickness. It is found that the film treatment protocol makes a difference in film transport property. Ultimately, the proton conductivity and capacitance of the Nafion nanothin film is thicknessdependent,wheretheformerdecreased andthelatterincreasedexponentiallywithdecreasingfilmthickness.Moreover,theactivation energy increased exponentially with decreasing film thickness. The proton conductivity of the thin films of Nafion is significantly lower than that of the membrane counterpart regardless of the thickness, which is consistent with the high activation energy found in the thin films. These differences are likely related to the polymer confinement and morphological differences between the thin films and the freestanding membrane. © The Author(s) 2014. Published by ECS. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 License (CC BY, http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse of the work in any
Challenges in breeding high quality apples with durable disease resistance.

The appearance of scab (Venturia inaequalis) strains that are able to overcome the broadly used Vf (Rvi6) scab resistance as well as the spread of new diseases such as Marssonina coronaria, highly relevant for organic apple growing, require adapted strategies for the breeding of new varieties. Approaches for breeding new high quality apple varieties with diverse resistance to several diseases considering phenotypic and molecular selection techniques and results achieved up to now in the Agroscope apple breeding programme will be shown and discussed.
Structural Glass Systems under Fire: Overview of Design Issues, Experimental Research, and Developments

Architectural design concepts incorporating glass beams, panels, or generally load-carrying elements and stiffeners for buildings, claddings, windows, and partitions are largely considered in modern high-rise constructions. A multitude of aspects, including motivations related to transparency, aesthetics, illumination, and energy conservation, progressively increased the use and interest for such a still rather innovative constructional material. However, compared to other traditional materials for buildings, standard glass is typically characterized by brittle behaviour and limited tensile resistance. The intrinsic properties of glass, moreover, together with typically limited thickness-to-size ratios for glazing elements, or the mutual interaction of glass components with adjacent constructional elements as a part of full assemblies they belong (i.e., fixing systems, sealants, etc.), as well as the combination of mechanical and thermal phenomena, make glass structures highly vulnerable. Special safety design rules are hence required, especially under extreme loading conditions. In this review paper, a state of the art on structural glass systems exposed to fire is presented. Careful consideration is paid for actual design methods and general regulations, as well as for existing research outcomes—both at the material and assembly levels—giving evidence of current challenges, issues, and developments.
Improving Disease Outbreak Forecasting Models for Efficient Targeting of Public Health Resources

Dengue is estimated to have approximately 390 million infections annually out of which an estimated 96 million manifest (Bhatt et al., 2013). WHO estimates almost half the global population to be at risk from this neglected tropical infectious disease. The enormous economic burden of the disease is evident when considering that an estimated 264 disability-adjusted life years (DALYs) per million population is lost due to dengue each year (World Health Organization, 2012). In Sri Lanka, it was estimated that within the Colombo district, where the nation’s capital is situated, a financial burden of US$ 971,360 was imposed upon the national health system in 2012 alone just for the execution of preventive measures (Thalagala et al., 2016). Considering all of these factors, optimizing resource allocation and reducing the economic burden of dengue should be a key element of any long term strategy for dealing with the disease. In this context, the ability to predict dengue outbreaks for a particular region 2 weeks in advance would lead to better resource mobilization and would be invaluable asset for the public health sector. Additionally, a disease outbreak forecasting model developed for dengue need not be limited to tackling resource allocation for that disease only, but can also be used to forecast outbreaks of other arboviral diseases such as Ebola, Zika or Chikungunya. In Sri Lanka at least, Chikungunya is already prevalent and it is just a matter of time before Zika comes to Sri Lanka given that cases have been detected in the Asian region including Singapore. In an epidemic or outbreak of an infectious disease, we would need to develop a deep understanding of human mobility patterns within the infected regions to identify the potential hotspots and also to forecast to which regions are most likely to be infected next. For the purpose of understanding human mobility in disease propagation, Mobile Network Big Data (MNBD) has become a low cost data exhaust that provides rich insight into human mobility patterns with better spatial and temporal granularity when compared to statistical methods which rely mostly on macro level population parameters. In this work, we evaluate multiple machine learning techniques such as Neural Networks (NN), Support Vector Machines (SVM), Random Forests and XGBoost to determine which technique performs best. A comparison of the model performance between different techniques is provided. We go on to use a genetic algorithm based optimization to further improve the accuracy of these models. Our work shows that Call Detail Records (CDR) can be used to derive proxy indicators for human movement patterns which are applicable across multiple machine learning models. Our results show that human mobility has an impact on dengue incidence, even in dengue endemic regions. The forecasting models developed in this work can be utilized to effect a significant impact on the issue of allocating resources effectively to combat dengue which in turn would lead to reduced economic burden as well as reduced mortality and morbidity.
Assessment of Plant Growth Promotion by Vermicompost in Different Progenies of Maritime Pine (Pinus pinaster Ait.)

The feasibility of incorporating vermicompost as a plant growth promoter into pine (Pinus pinaster Ait.) nurseries was investigated. Pines were grown in conventional peat-based nursery potting media where the peat was substituted by 0%, 2.5%, 5%, 10% and 25% solid vermicompost. In addition, in order distinguish between possible physical and biochemical mechanisms, the effects of solid vermicompost and vermicompost extracts on pine seedling growth were compared. Five different open-pollinated pine progenies were used in order to evaluate the possible genotype-dependent effects of vermicompost. All pots were provided with adequate mineral fertilization in order to avoid nutrient limitations and arranged in the greenhouse following a bifactorial randomized block design. Twenty weeks after sowing, seedlings were harvested and their aerial and root growth were measured, as well as biomass partitioning and seedling maturity. Amendment with solid vermicompost at 2.5% and 10% significantly stimulated pine seedling height, but not aerial biomass. Vermicompost also produced seedlings with greater shoot:root biomass ratios than the control. Besides, we noticed a significant inhibition of aerial and root biomass with the higher dose of solid vermicompost (25% substrate substitution). No effects, either positive or negative, were detected in plant growth due to the vermicompost extracts. All the reported results were the same for all the different progenies assayed, and therefore no genotype dependent effects were detected.
Integrating the Supervised Information into Unsupervised Learning

This paper presents an assembling unsupervised learning framework that adopts the information coming from the supervised learning process and gives the corresponding implementation algorithm. The algorithm consists of two phases: extracting and clustering data representatives (DRs) firstly to obtain labeled training data and then classifying non-DRs based on labeled DRs. The implementation algorithm is called SDSN since it employs the tuning-scaled Support vector domain description to collect DRs, uses spectrum-based method to cluster DRs, and adopts the nearest neighbor classifier to label non-DRs. The validation of the clustering procedure of the first-phase is analyzed theoretically. A new metric is defined data dependently in the second phase to allow the nearest neighbor classifier to work with the informed information. A fast training approach for DRs’ extraction is provided to bring more efficiency. Experimental results on synthetic and real datasets verify that the proposed idea is of correctness and performance and SDSN exhibits higher popularity in practice over the traditional pure clustering procedure.
Expression QTL mapping using Nelore cattle muscle RNA-seq data

1 São Paulo State University (Unesp), School of Agricultural and Veterinarian Science, Department of Animal Science, Via de Acesso Prof. Paulo Donato Castellane s/n, 144884-900, Jaboticabal, SP, Brazil camila_urbano@yahoo.com. br (Corresponding Author) University of Missouri, Division of Animal Sciences, 920 East Campus Drive, Columbia, MO 65211, USA National Council for Scientific and Technological Development (CNPq), SHIS QI 1 Conjunto B Blocos A, B, C e D, Lago Sul, 71605-001, Brasília, DF, Brazil
Food Safety Concerns and other Factors Affecting Iran's Pistachio Exports to EU, Australia, and Japan

In this paper, the impact of food safety concerns on Iran’s pistachio export demand was investigated. Panel data and panel cointegration analyses were used to estimate the export demand function of Iran’s pistachio nuts to the European Union (EU), Japan, and Australia for the period of 1997 to 2006 so that the relationship between factors affecting Iran’s pistachio exports can be examined. The results show the existence of long-run relationships among the variables that have a significant impact on Iran’s pistachio exports. The empirical results indicate that food safety shocks had a statistically significant negative impact on the import demand of those countries.
Convergence of the frequency-size distribution of global earthquakes

[1] The Gutenberg-Richter (GR) frequency-magnitude relation is a fundamental empirical law of seismology, but its form remains uncertain for rare extreme events. Here, we show that the temporal evolution of model likelihoods and parameters for the frequency-magnitude distribution of the global Harvard Centroid Moment Tensor catalog is inconsistent with an unbounded GR relation, despite if being the preferred model at the current time. During the recent spate of 12 great earthquakes in the last 8 years, record-breaking events result in profound steps in favor of the unbounded GR relation. However, between such events the preferred model gradually converges to the tapered GR relation, and the form of the convergence cannot be explained by random sampling of an unbounded GR distribution. The convergence properties are consistent with a global catalog composed of superposed randomly-sampled regional catalogs, each with different upper bounds, many of which have not yet sampled their largest event.
Motivation and Medium of Information Affecting Behavioural Patterns of Film Viewers in Malaysia

This paper is aimed to identify the key factors on behavioural patterns that affect audiences in making decision to watch films by using the techniques in multiple regressions (MR). The success of a country’s film industry is determined by the collaboration between film producers and audiences. Audiences are a major contributor that will determine the success of a film, while producers is the main supplier to provide films to the audiences. Mathematical modelling concept is used in the methodology where two categorical variables, selected after factor analysis, are transformed into dummies. The search for significant factors would involve data cleaning, factor analysis, dummy transformation and four-phase model building. The model-building phases will incorporate the procedures of selecting the best model involving multicollinearity test using the variance-based approach (VIF) below 5. Results revealed that the best model obtained consists of factors on interest, family, friends, the internet and printed medium of posters and brochures which are influential in attracting audiences. This study has therefore extended our knowledge to build bridges between two different fields, that is scientific and non scientific through the concept and methodology of modelling, and consequently, help in advertising and marketing of the film industry by influencing the perceptions of audiences towards cinemas.