Miracle-dz/UniFAR-FTUs huggingface dataset:
Screening of Potato Lines Including Department Genetic & National Plant Gene Bank of Iran for Resistance to Early Blight (Alternaria. solani) Using Culture Filtrate Produced by the Fungus

Potato is a plant that can be influenced by early blight disease. Early blight is one of the most destructive plant diseases, especially in the members of solanaceae family. This disease can reduce yield. Experiment design was a factorial randomized complete design to evaluate the isolate pathogenic Alternaria solani in National Plant Gene Bank of Iran, during 2008-2009. This experiment was conducted with three replications, and the factors include test methods and three lines 9506, 10908-05 and 10908-18 with genotypes of Agria, Casmos and Desiree (susceptible) and Delta (resistant control). Analysis of variance table was based on the area under the disease progress curve, indicating the effects of the experimental methods; genotype and their interactions are significant at the 1% level. In greenhouse evaluation, the symptoms appeared on, the first day. In this method the area under the curve progression was noted in 10 times, but in vitro method, the symptoms of this evaluation appeared on the first or second day. The Evaluation was carried out after inoculation, and was noted 6 times. The results indicate that genotypes and lines are located in four different groups. In this case, line 9506 and Cosmos were quite sensitive to the surface, and Desiree, is located in a sensitive area. Line 10908-18 and Agria, located approximately at the level of resistance, and line 10908-05 and Delta, have been resistant surface.
Integration of LoRa Wide Area Network with the 5G Test Network

The global communication network is going through major transformation from conventional to more versatile and diversified network approaches. With the advent of virtualization and cloud technology, information technology (IT) is merging with telecommunications to alter the conventional approaches of traditional proprietary networking techniques. From radio to network and applications, the existing infrastructure lacks several features that we wished to be part of 5 Generation Mobile Networks (5G). Having a support for large number of applications, Internet of Things (IoT) will bring a major evolution by creating a comfortable, flexible and an automated environment for end users. A network having the capability to support radio protocols on top of basic networking protocols, when blended with a platform which can generate IoT use cases, can make the expectations of 5G a reality. Low Power Wide Area Network (LPWAN) technologies can be utilized with other emerging and suitable technologies for IoT applications. To implement a network where all the technologies can be deployed virtually to serve their applications within a single cloud, Network Functions Virtualization (NFV) and Software Defined Network (SDN) is introduced to implement such a networking possibility for upcoming technologies. The 5G Test Network (5GTN), a testbed for implementing and testing 5G features in real time, is deployed in virtual platform which allows to add other technologies for IoT applications. To implement a network with an IoT enabler technology, LoRa Wide Area Network (LoRaWAN) technology can be integrated to test the feasibility and capability of IoT implications. LoRaWAN being an IoT enabler technology is chosen out of several possibilities to be integrated with the 5GTN. Using MultiConnect Conduit as a gateway, the integration is realized by establishing point to point protocol (PPP) connection with eNodeB. Once the connection is established, LoRa packets are forwarded to the ThingWorx IoT cloud and responses can be received by the end-devices from that IoT cloud by using Message Queuing Telemetry Transport (MQTT) protocol. Wireshark, an open source packet analyser, is then used to ensure successful transmission of packets to the ThingWorx using the 5GTN default packet routes.
Beyond Additionality: Are Innovation Subsidies Counterproductive?

Building on a standard policy evaluation literature mainly aimed at estimating the additional effect of subsidies on either firms' innovative expenditures or innovative outputs only, this paper tries to move one step further, combining the two (input and output) dimensions of innovation into a unique efficiency perspective. To this aim, the impact of public funding on the ratio between innovative sales and innovative expenditures (innovative productivity) is estimated using a sample of firm-level data drawn from the third Italian Community Innovation Survey (CIS). A bivariate endogenous switching model has been developed in order to free the analysis of any ex ante sources of sample selection and firm heterogeneity, at the same time getting rid of the two sources of endogeneity potentially affecting the results, i.e. the possible simultaneity between subsidy allocation and the qualitative composition of the innovative output, as well as the endogeneity of public support with respect to innovative performance. Results show that innovative productivity is negatively affected by the innovation subsidy; far from 'doing better' as a result of government intervention, supported firms appear to exhaust their advantage through merely increasing their innovative expenditures.
Efficient prediction of total column ozone based on support vector regression algorithms, numerical models and Suomi-satellite data

This paper proposes a novel prediction method for Total Column Ozone (TCO), based on the combination of Support Vector Regression (SVR) algorithms and different predictive variables coming from satellite data (Suomi National Polar-orbiting Partnership satellite), numerical models (Global Forecasting System model, GFS) and direct measurements. Data from satellite consists of temperature and humidity profiles at different heights, and TCO measurements the days before the prediction. GFS model provides predictions of temperature and humidity for the day of prediction. Alternative data measured in situ, such as aerosol optical depth at different wavelengths, are also considered in the system. The SVR methodology is able to obtain an accurate TCO prediction from these predictive variables, outperforming other regression methodologies such as neural networks. Analysis on the best subset of features in TCO prediction is also carried out in this paper. The experimental part of the paper consists in the application of the SVR to real data collected at the radiometric observatory of Madrid, Spain, where ozone measurements obtained with a Brewer spectrophotometer are available, and allow the system’s training and the evaluation of its performance.
ANTI-DRUG PREVENTIVE ACTIVITIES IN A SITUATION OF A HIV OUTBURST WITHIN A PRISON INSTITUTION ( Experience and Conclusions from the HIV Outburst in Alytus Top Security Prison )

Innovationsaimed to reduce any production, delivery, and consumption of drugs are the most prospective measures to work out more efficientprevention of drug related offences. This is especially true for prison institutions, where drug consumption tends to be several times greater that in the general population. Therefore, prison institution has especially great need in new efficient anti-drug activities. However, just here especially great problems are met designing and implementing such activities, overcoming resistance against these innovations. A great part of these problems origins in attitudes of the prison administration towards these activities. In case of an HIV epidemic in prison its administration takes a great part designing and selecting preventive activities, accepting or rejecting recommendations of criminologists and AIDS experts, implementing or sabotaging them. We investigated 112 prison officers in the greatest Lithuanian prison enveloped into a large HIV epidemic, their evaluations of efficiency of 73 activities included in anti-HIV epidemic programs in this prison, as well as their comments on them. Analysis of evaluations and their comments revealed that opinions of our respondents are based on rather primitive (oneand twofactors) causal reasoning schemes. Factor analysis revealed strong connections of evaluations with personal factors (like enthusiasm-skepticism, inclination to individual or large-scale measures, readiness to break prison order), which had nothing to do with real efficiency of an preventive activity. Therefore, “professional experience” based opinions of prison staff cannot be a substitute for scientific evaluations of preventive activities. All these can be seen as a consequence of the lack of criminological training of people implementing crime prevention activities.The lack of professional criminological knowledge urges them to substitute their lacking knowledge with the so-called “common wisdom”naïve criminological ideas on crime and crime prevention. This, in turn, causes distortion indesigning and implementation ofprevention activities andbrings the global reduction of their efficiency.
Cultivable Bacterial Community Analysis of Saeu-jeotgal, a Korean High-Salt-fermented Seafood, during Ripening

Jeotgal is the generic term given to traditional Korean high-salt seafoods. These products are used as an additive for improving the taste of other foods, or eaten alone as a side dish, providing saltiness and nutrition to steamed rice. Jeotgal is made by adding up to 30% (w/w) sea salt to various types of seafood, and becomes palatable through subsequent ripening. During the >1-year ripening period, jeotgal attains rich flavors and unique physical and chemical structures through autolytic and microbial proteolytic processes. In the typical production of jeotgal as fish sauce in Southeast Asian countries, which may take up to 12−18 months, no control measures are implemented, which sometimes results in inconsistent product quality. Therefore, acceleration of the ripening process is a major research focus, not only to improve quality but also reduce costs. Many attempts have been made to accelerate the fish sauce ripening process by reducing salt content, lowering pH, and elevating the temperature [12, 26]. The addition of proteases from plants and fish intestines has been relatively successful in accelerating the ripening process [5, 11, 23]. However, the proteases from plants did not produce the traditional aromatic flavors, and the activity of proteases from fish intestines declined gradually during ripening because of the high salt content and acidic pH [36]. To determine the dominant bacterial species during the Saeu-jeotgal ripening process, the cultivable bacterial population was examined over a 135-day period using six different growth media. The greatest numbers of bacteria were identified when marine agar was used for culture, with maximum cell density identified at day 65 (2.51 × 10 colony forming units/g). Over the course of 135 days, the bacterial diversity was analyzed eight times. A total of 467 isolates, comprising 87 species from 42 genera, as well as 16 isolates belonging to previously unknown species, were identified. The number of species detected decreased from 39 at day 1 to 13 at day 135. The order of dominance at the genus level was as follows: Staphylococcus, Salimicrobium, Kocuria, and Psychrobacter. Staphylococcus and Salimicrobium accounted for 2% of the diversity at day 1, and then increased to 39% and 36%, respectively, at day 135. The dominant species Staphylococcus equorum, Salimicrobium salexigens, and Kocuria palustris accounted for 23.6%, 16.1%, and 10.9% of all isolates, respectively. Importantly, both St. equorum and Sm. salexigens remained viable at a NaCl concentration of 21% (w/v), which indicates their strong involvement in the ripening of Saeu-jeotgal.
LOW COST HEXACOPTER AUTONOMOUS PLATFORM FOR TESTING AND DEVELOPING PHOTOGRAMMETRY TECHNOLOGIES AND INTELLIGENT NAVIGATION SYSTEMS

Low-cost solutions for autonomous aerial platforms are being intensively developed and used within geodetic community. Unmanned aerial vehicles are becoming very popular and widely used for photogrammetry and remote sensing applications. Todays market offers an affordable price components for unmanned solution with significant quality and accuracy growth. Every year market offers a new solutions for autonomous platforms with better technical specifications. Commercial drones for amateurs are offered widely and presents a quality and accuracy not available in past few years. In this paper an autonomous open source low cost haxacopter system for photogrammetry and intelligent navigation technologies evaluation is being presented. The system was designed and assembled for technologies testing and for educational purposes. The drone is based only on open source hardware and software. All components are based on commercial of the shelf products. That approach to the drones construction provides a many capabilities to test, implement and execute new algorithms, solutions and tasks. Providing basic configuration tools system enables students to safely perform elementary setup and testing. An advanced configurations system tool and open source structure enables to execute advanced scientific test and research. Paper presents a results of designed process, system configuration and specification, technical issues that was being solved during test flights and practical research results. DOI: https://doi.org/10.3846/enviro.2017. 172
Traffic Calming Schemes : Monte Carlo Simulation to Evaluate Efficient Designs of Choice ( 1 )

Riassunto: L’obiettivo del presente lavoròe la valutazione dell’effetto dei disegni di scelta sulla stima delle misure di benessere. In particolare, si valuta l’impatto dei disegni D-efficienti negli studi di choice experiments per la valutazione monetaria del danno ambientale. Si prendono in considerazione gli effetti negativi derivanti dal traffico urbano, cos̀ ı come percepiti dal cittadino, e si dimostra, attraverso un esperimento Monte Carlo, come i diversi disegni sperimentali influenzano la stima della disponibilit à a pagare. Nel lavoro si descrivono alcuni disegni sperimentali per modelli non lineari (Multinomial Logit) e si dimostra la perdita di efficienza in presenza di scarsa informazione a priori. In relazione al modello si considera la presenza o meno della alternativa specifica costante; mentre per il disegno di scelta si valuta la presenza o meno dello status quo.
Researches on the Wideband Spectrum Sensing Prototype System Based on MWC

Recently, researches based on the Compressed Sensing (CS) become an important direction in the field of signal processing. The newly proposed system called Modulated Wideband Converter (MWC), which breaks through the limit of traditional Nyquist sampling, has presented huge advantages in sub-Nyquist sampling technique. It is composed of several analog channels that alias the signal intentionally before sampling it at a low rate. Then the signal can be reconstructed from the samples by using some commonly used algorithms in compressed sensing theory. It is one of the most successful compressive sampling hardware architectures, but in real hardware implementation, the digital board is fairly difficult to realize. In this paper, we made exploration of the MWC sampling theory and designed a three channels prototype system. To realize the 1  logic waveform, we present using Rocket I/O on Xilinx FPGA. In this way, the hardware system can be simplified so as to implement quickly. Through hardware experiments and algorithm reconstruction, we verify the feasibility of MWC system in sub-Nyquist sampling theory. 
Wavelet operational matrix method for solving fractionalintegral and differential equations of Bratu-type

In this paper, a wavelet operational matrix method based on the second kind Chebyshev wavelet is proposed to solve the fractional integral and differential equations of Bratu-type. The second kind Chebyshev wavelet operational matrix of fractional order integration is derived. A truncated second kind Chebyshev wavelet series together with the wavelet operational matrix is utilized to reduce the fractional integral and differential equations of Bratu-type to a system of nonlinear algebraic equations. The convergence and the error analysis of the method are also given. Two examples are included to verify the validity and applicability of the proposed approach.
ESTIMATION OF REGIONAL FOREST ABOVEGROUND BIOMASS COMBINING ICESAT-GLAS WAVEFORMS AND HJ-1A/HSI HYPERSPECTRAL IMAGERIES

Estimation of forest aboveground biomass (AGB) is a critical challenge for understanding the global carbon cycle because it dominates the dynamics of the terrestrial carbon cycle. Light Detection and Ranging (LiDAR) system has a unique capability for estimating accurately forest canopy height, which has a direct relationship and can provide better understanding to the forest AGB. The Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and land Elevation Satellite (ICESat) is the first polarorbiting LiDAR instrument for global observations of Earth, and it has been widely used for extracting forest AGB with footprints of nominally 70 m in diameter on the earth's surface. However, the GLAS footprints are discrete geographically, and thus it has been restricted to produce the regional full coverage of forest AGB. To overcome the limit of discontinuity, the Hyper Spectral Imager (HSI) of HJ-1A with 115 bands was combined with GLAS waveforms to predict the regional forest AGB in the study. Corresponding with the field investigation in Wangqing of Changbai Mountain, China, the GLAS waveform metrics were derived and employed to establish the AGB model, which was used further for estimating the AGB within GLAS footprints. For HSI imagery, the Minimum Noise Fraction (MNF) method was used to decrease noise and reduce the dimensionality of spectral bands, and consequently the first three of MNF were able to offer almost 98% spectral information and qualified to regress with the GLAS estimated AGB. Afterwards, the support vector regression (SVR) method was employed in the study to establish the relationship between GLAS estimated AGB and three of HSI MNF (i.e. MNF1 , MNF2 and MNF3 ), and accordingly the full covered regional forest AGB map was produced. The results showed that the adj.R 2 and RMSE of SVR-AGB models were 0.75 and 4.68 t hm −2 for broadleaf forests, 0.73 and 5.39 t hm −2 for coniferous forests and 0.71 and 6.15 t hm −2 for mixed forests respectively. The full covered regional forest AGB map of the study area had 0.62 of accuracy and 11.11 t hm −2 of RMSE. The study demonstrated that it holds great potential to achieve the full covered regional forest AGB distribution with higher accuracy by combing LiDAR data and hyperspectral imageries.
Perturbations in the self-similar Bondi flow

Instituto de Matema´ticas y F´isica Fundamental, CSIC, Serrano 113bis, 28006 Madrid, SpainReceived: 24 August 2005 / Accepted: 12 November 2005Abstract. The question of stability of steady spherical accretion has been studied for many years and, recently, the conceptof spatial instability has been introduced. Here we study perturbations of steady spherical accretion ﬂows (Bondi solutions),restricting ourselves to the case of self-similarﬂow, as a case amenable to analytic treatment and with physic al interest. We fur-ther restrict ourselves to its acoustic perturbations. The radial perturbation equation can be solved in terms of Bessel functions.We study the formulation of adequate boundary conditions and decide for no matter-ﬂux-perturbation conditions (at theBondiradius and at r = 0). We also consider the problem of initial conditions and time evolution, in particular, of radial perturbations.No spatial instability at r = 0 is found. The time evolution is such that perturbations eventually become ergodic-likeand showno trace of instability or of acquiring any remarkable pattern.Key words. accretion, accretion discs – hydrodynamics
Integrating population dynamics into mapping human exposure to seismic hazard

Abstract. Disaster risk is not fully characterized without taking into account vulnerability and population exposure. Assessment of earthquake risk in urban areas would benefit from considering the variation of population distribution at more detailed spatial and temporal scales, and from a more explicit integration of this improved demographic data with existing seismic hazard maps. In the present work, "intelligent" dasymetric mapping is used to model population dynamics at high spatial resolution in order to benefit the analysis of spatio-temporal exposure to earthquake hazard in a metropolitan area. These night- and daytime-specific population densities are then classified and combined with seismic intensity levels to derive new spatially-explicit four-class-composite maps of human exposure. The presented approach enables a more thorough assessment of population exposure to earthquake hazard. Results show that there are significantly more people potentially at risk in the daytime period, demonstrating the shifting nature of population exposure in the daily cycle and the need to move beyond conventional residence-based demographic data sources to improve risk analyses. The proposed fine-scale maps of human exposure to seismic intensity are mainly aimed at benefiting visualization and communication of earthquake risk, but can be valuable in all phases of the disaster management process where knowledge of population densities is relevant for decision-making.
Strengthening Women’s Strategic Role Through Locally Specific Households Industry in Bali, Indonesia

This study aims to identify the typology of rural households industries in the district of Abang, Karangasem regency, to analyze the strategic role of women in households industry, and to propose strengthening women’s strategic role models through the development of households industries locally specific. The database obtained from studies conducted in rural sub-district of Abang, Karangasem regency, Bali province of Indonesia in 2014. The field observations and information obtained from a critical review on the relevant reports were published and further referenced in the expert meeting to determine the elements of the system are believed to be appropriate for strengthening women’s strategic role. Analytic Network Process (ANP) was selected as decision analysis tools and software Super Decisions as supporters. The results showed that the involvement of women in households industry are very high, although not yet a profitable business for himself and his households because it is only able to account for 30% of total households income. Women dominate decision-making, particularly in the selection of the type of business, labor utilization and marketing, but they still need their husband's opinion, especially in terms of the fulfillment of working capital, education of children, and investment in production equipment. The development of households’ industries locally specific benefits in terms of availability of raw materials, the absorption of labor force, market demand, access to capital and business places, but in the context of fulfilling the needs of households, the development of households industry is still considered to have limitations. There are five alternative formulation of the strategy for developing the strategic role of women through locally specific households industry, i.e. partnerships synergy, strengthening of the human resource competencies, institutional strengthening, strengthening of marketing functions, and stimulus for the application of machine technology and equipment. Results of Analytic Network Process (ANP) showed that the strengthening the competence of human resources is the best alternative to the relative priority of 39%. It is therefore, in applying the strategy of strengthening the competency of human resources, women need to incorporate important strategic orientation and product innovation capabilities in order to expand the business and in turn is able to increase the scale of their business from households scale only becomes SMEs. Keywords : Women’s strategic role, ANP model, local specific households industries in Bali.