Miracle-dz/UniFAR-FTUs huggingface dataset:
Natural dissemination of hypovirulent Cryphonectria parasiticastrain used for biological control of chestnut blight

Chestnut blight, caused by Cryphonectria parasitica Murr. Barr, is the most serious disease of chestnut trees in Turkey on which several studies related to biological control were conducted. The aim of this study was to determine the cause of the occurrence of healing cankers on untreated chestnut trees and the role of carriers in the spread of hypovirulence by laboratory tests, and to discover the effect of some environmental factors (temperature and relative humidity) on the natural spreading of hypovirulence. The study was carried out in a chestnut grove where biological control studies of the disease had been performed in previous years. Bark samples were collected from healed cankers and 388 possibly hypovirulent isolates were obtained. Two of them that were white converted virulent isolates to hypovirulent ones, but others developed yellowish cream-colored mycelia and did not convert virulent isolates. dsRNA analysis was performed on randomly selected possible hypovirulent isolates collected from healed cankers. After the virus concentration had increased, dsRNA-positive reactions were obtained for 56.73% of the isolates. Thirty-one possible hypovirulent isolates from Formicidae and Gastropoda did not convert virulent isolates to hypovirulent ones. dsRNA analysis was performed on these isolates and 61.29% of them containing dsRNA were observed in the invertebrates collected from cankers that had healed from hypovirulence. It was also observed that there was no significant difference among the date of average temperatures and date of relative humidity from 3 different altitudes. It was determined that the reason for the occurrence of the healed cankers on untreated trees was the natural dissemination of hypovirulence, ants and snails might have played a role in the natural dissemination of hypovirulence, and healed cankers mostly occurred on the western sides of shaded slopes.
Optical remote sensing of lakes: an overview on Lake Maggiore

Optical satellite remote sensing represents an opportunity to integrate traditional methods for assessing water quality of lakes: strengths of remote sensing methods are the good spatial and temporal coverage, the possibility to monitor many lakes simultaneously and the reduced costs. In this work we present an overview of optical remote sensing techniques applied to lake water monitoring. Then, examples of applications focused on lake Maggiore, the second largest lake in Italy are discussed by presenting the temporal trend of chlorophyll-a (chl-a), suspended particulate matter (SPM), coloured dissolved organic matter (CDOM) and the z90 signal depth (the latter indicating the water depth from which 90% of the reflected light comes from) as estimated from the images acquired by the Medium Resolution Imaging Spectrometer (MERIS) in the pelagic area of the lake from 2003 to 2011. Concerning the chl-a trend, the results are in agreement with the concentration values measured during field surveys, confirming the good status of lake Maggiore, although occasional events of water deterioration were observed ( e.g ., an average increase of chl-a concentration, with a decrease of transparency, as a consequence of an anomalous phytoplankton occurred in summer 2011). A series of MERIS-derived maps (summer period 2011) of the z90 signal are also analysed in order to show the spatial variability of lake waters, which on average were clearer in the central pelagic zones. We expect that the recently launched ( e.g ., Landsat-8) and the future satellite missions ( e.g ., Sentinel-3) carrying sensors with improved spectral and spatial resolution are going to lead to a larger use of remote sensing for the assessment and monitoring of water quality parameters, by also allowing further applications ( e.g ., classification of phytoplankton functional types) to be developed.
A publication of IIETA

NUCLEAR (Nuclear CLEAn Reactor) Project arises from a scientific collaboration among of the Department of Industrial Engineering and the Department of Physics and Astronomy of the University of Catania, and the TECFIS Division of the Frascati Research Center of ENEA. Aim of the project is to develop a device prototype able to check the production of clean energy trough Lattice Assisted Nuclear Reactions LANR. The first step of the project is to study an engineered version of an experiment realized at ENEA Frascati in 1992 by one of the authors (ADN). It has been shown that whenever a flux of deuterons crosses a strong deuterated palladium membrane, an anomalous excess heat is produced which cannot be accounted for conventional chemical reactions. That experiment was realized in electrolysis of heavy water in order to produce a flux of d+ towards a cathode made out of 500 microns thick palladium membrane. The thermal anomaly has been shown to be related to the flux of atoms crossing the metal. The new design of the experiment avoids the obstacle of electrolysis such as the poisoning of the materials, due to long time running, using Polymer Electrolyte Membranes (PEM) such as those used in fuel cells. Furthermore is possible to drive the current of positive ions applying an electric field across the PEM. Preliminary measures have shown that the flux obtained in such a configuration is even greater than the flux obtained in electrolysis with several hundreds of milliampere and it is linearly related to the voltage across the PEM. The condition of the experiments thus result to be easily and accurately controlled and reproducible.
Immunomodulatory, anti-inflammatory, and antioxidant effects of curcumin

Turmeric is a widely used spice derived from the rhizomes of Curcuma longa. Having been used as a dietary spice, it has drawn scientists’ attention to the possible medicinal benefits of its active compounds called curcuminoids which consist of curcumin, demethoxycurcumin and bisdemethoxycurcmin. Considering wide range of pharmacological properties that curcumin offers, numerous studies have investigated its potency as a therapeutic agent in various diseases such as autoimmune, cardiovascular, neoplastic, pulmonary, neurodegenerative and metabolic diseases. With regard to its wide array of health benefits and published data on the underlying mechanisms of its action, a complex interaction between three main events including inflammation, oxidative stress, and immunity, seems to contribute to different therapeutic roles of this compound. Hence, this review discusses the current knowledge on the anti-inflammatory, antioxidant, and immunomodulatory roles of curcumin with the hope of recruiting curcumin as a therapeutic agent in future therapeutic regimen in order to enhance the efficacy of the treatment, as well as decreasing the adverse effects of synthetic chemical drugs.
DESIGN OF DUAL CIRCULARLY POLARIZED ANTENNA WITH HIGH ISOLATION FOR RFID APPLICATION

In this paper, a dual-fed circularly polarized antenna design with high isolation is presented for radio frequency identiflcation (RFID) reader. The proposed antenna is excited by two fed ports connected with a circular split-ring microstrip line underneath the ground plane. A radial aperture in the ground plane provides coupling between the split-ring microstrip and radiating patch. For multiple RFID band requirements, the dimension of the aperture can be modifled to obtain high isolation on difierent RFID Band. Finally, an antenna prototype for China RFID Band (920{925MHz) is fabricated. The measured results agree well with simulation, and show 10-dB matching bandwidth of 18% (820{1000MHz), 3-dB axial ratio (AR) bandwidth of 11% (854{960MHz), and 25-dB isolation bandwidth of 11MHz (917{928MHz).
Multiresolution quantification of deciduousness in West-Central African forests

The characterization of leaf phenology in tropical forests is of major importance for forest typology as well as to improve our understanding of earth–atmosphere–climate interactions or biogeochemical cycles. The availability of satellite optical data with a high temporal resolution has permitted the identification of unexpected phenological cycles, particularly over the Amazon region. A primary issue in these studies is the relationship between the optical reflectance of pixels of 1 km or more in size and ground information of limited spatial extent. In this paper, we demonstrate that optical data with high to very-high spatial resolution can help bridge this scale gap by providing snapshots of the canopy that allow discernment of the leaf-phenological stage of trees and the proportions of leaved crowns within the canopy. We also propose applications for broad-scale forest characterization and mapping in West-Central Africa over an area of 141 000 km 2 . Eleven years of the Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) data were averaged over the wet and dry seasons to provide a data set of optimal radiometric quality at a spatial resolution of 250 m. Sample areas covered at a very-high (GeoEye) and high (SPOT-5) spatial resolution were used to identify forest types and to quantify the proportion of leaved trees in the canopy. The dry-season EVI was positively correlated with the proportion of leaved trees in the canopy. This relationship allowed the conversion of EVI into canopy deciduousness at the regional level. On this basis, ecologically important forest types could be mapped, including young secondary, open Marantaceae, Gilbertiodendron dewevrei and swamp forests. We show that in West-Central African forests, a large share of the variability in canopy reflectance, as captured by the EVI, is due to variation in the proportion of leaved trees in the upper canopy, thereby opening new perspectives for biodiversity and carbon-cycle applications.
FDI TECHNOLOGY SPILLOVERS IN CHINA: IMPLICATIONS FOR DEVELOPING AREAS

Using firm level data from China, this paper examines channels of FDI technology spillovers in different entry modes of MNCs, and draws policy implications for developing countries. Developing countries should encourage multinational corporations (MNCs) to enter their markets in the form of joint ventures rather than wholly foreign owned enterprises. In establishing joint ventures, moreover, they should encourage MNCs to invest in tangible assets, production of domestically-consumed products, promotion of traditional products, and employment and training of unskilled local workers. Furthermore, they should help domestic firms overcome the adverse effect of market stealing and skill stealing generated by wholly foreign owned enterprises. JEL Classifications: M1, M2, O1 and O2
Robust Constituent-to-Dependency Conversion for English

This paper suggests a robust way of converting constituent-based trees in the Penn Treebank style into dependency trees for several different English corpora. For English, there already exist conversion tools. However, these tools are often customized enough for a specific corpus that they do not necessarily work as well when applied to different corpora involving newly introduced POS-tags or annotation schemes. The desire to improve conversion portability motivated us to build a new conversion tool that would produce more robust results across different corpora. In particular, we have modified the treatment of head-percolation rules, function tags, coordination, gapping, and empty category mappings. We compare our method with the LTH conversion tool used for the CoNLL’07-09 shared tasks. For our experiments, we use 6 different English corpora from OntoNotes release 4.0. To demonstrate the impact our approach has on parsing, we train and test two state-of-the-art dependency parsers, MaltParser and MSTParser, and our own parser, ClearParser, using converted output from both the LTH tool and our method. Our results show that our method removes certain unnecessary nonprojective dependencies and generates fewer unclassified dependencies. All three parsers give higher parsing accuracies on average across these corpora using data generated by our method; especially on semantic dependencies.
Viability Bovine Tooth Hydroxiapatite on Bone Marrow MesenchymalStem Cells

Different types of bone-graft substitutes have been developed. Hydroxyapatite is a scaffold- has the ability to perform osteoinduction and osteoconduction activity. Of these, Bovine tooth hydroxyapatite (BTHA) is a novel material produced by Airlangga University. Bone marrow mesenchymal stem cells (BMSCs) is a potential material in the regenerative medicine. It has tissue source and multipotent somatic stem cells. BMSCs have been combined with biomaterials such as osteoinductive and osteoconductive scaffold in order to improve bone regeneration. This study was performed to determine the viability of BTHA on bone marrow stem cells. This study is an experimental research. BTHA was extracted from bovine's teeth and formed into particles 355-710 μm. The viability effect of BTHA scaffold on BMSCs in a variety concentration 10%,50% and 100% (w/v)were analyzed by using 3-(4,5'dimethylihiazol-2-yl),2.5-di-phenyl-tetrazolium bromide (MTT) assay. Results were analyzed with ANOVA to see the difference between group. The highest viability of the cells (97.1%)were found in concentration 10% by using MTT assay. Viability BTHA 10% and 50 % on BMSCs is not different significantly (p≤ 0.05). BTHA is viable in 10% and 50% on bone marrow mesenchymal stem cell. In addition, economical production of BTHA should be taken into consideration. In future, BTHA may be a viable alternative for bone grafting when clinical trials have been completed.
Modeling the dynamics of molecular concentration during the diffusion procedure

In this paper, a numerical method is proposed to solving a reaction-diffusion system. The systems describe the solid state reaction mechanism of all the reaction components at the preparatory stage of yttrium aluminum garnet (YAG) in one dimension. Kansa's method and forward Euler method are employed to discrete the spatial variable and time respectively.
High Level Synthesis with Stream Query to C Parser : Eliminating Hardware Development Difficulties for Software Developers

Recently, reconfigurable hardware is attracting wide attention as a stream processing platform for its high performance and power efficiency. To allow many software engineers to benefit from reconfigurable hardware, high level synthesis tools have been actively developed. Although these tools have enormously reduced the amount of work and difficulties, the users still need hardware development knowledge. In this paper, we introduce a method that parses SQL queries into high-level-synthesis-intended C codes. Our experiments using a dynamically reconfigurable hardware that features a high level synthesis tool showed that the hardware’s potential was fully extracted and the developer writing the SQL queries does not need hardware development knowledge.
Indirect determination of the energy spectra of particles precipitated in the lower ionosphere associated with solar proton events

Electron density profiles previously measured using the phase and amplitude of VLF radio signals during outstanding solar proton events (SPE), together with the associated energy spectra of protons and electrons simultaneously measured by satellite, allowed the calculation of the electron-ion pair production rate q(h), for the sub-Antarctic and South Atlantic Geomagnetic Anomaly (SAGA) regions. Plots of q(h) together with the predetermined electron density vertical profiles were used to calculate the effective recombination coefficient ψ(h) for the SAGA region. Assuming that the chemical processes in the lower ionosphere due to the impact of neutral atmospheric constituents are basically the same, the spectra of the energetic particles responsible for the d elayed ionization detected in the SAGA were estimated indirectly. The parameters obtained are in good agreement with results for the northern hemisphere and the spectra deduced are within the limits imposed by the cutoff rigidity and the penetration depth of t he incident particles. The experimental data correspond to VLF signals transmitted from Australia (NWC - 22.3 kHz ) and from ΩTrinidad (13.6 kHz) and received respectively in Atibaia and Curitiba, Brasil, during the SPE of August 4-7, 1972.
Development of thermoplastic elastomers based on maleated ethylene propylene rubber (m-EPM) and polypropylene (PP) by dynamic vulcanization

Dicumyl peroxide (DCP)-cured thermoplastic vulcanizates (TPVs) based on blends of maleated ethylene propylene rubber (m-EPM) and polypropylene (PP) using maleated-PP as a compatibilizer have been developed. Physical properties of these TPVs change significantly with concentrations of DCP and rubber/plastic blend ratios. Important correlations were obtained from rheometer delta torque values with various physical properties of the TPVs like tension set and crosslink density etc. Wide angle X-ray diffraction study confirms that concentration of DCP has a strong influence on the crystallinity of PP, which might affect the final physical properties of TPVs. The recyclability and ageing characteristics of these TPVs are also found excellent.
Anatomy of a Socially Responsible Firm

This paper investigates the relation between firm characteristics and corporate social responsibility (CSR) with the purpose to understand the reason for investment activities in CSR. We develop a principal component based approach to categorize the KLD fourteen-dimensions of CSR activities into two groups, namely, reactive CSR, which firms would apply to counter any potential fallout from CSR concerns, and proactive CSR, which stands for not reactive CSR activities. We find evidence supporting that (1) financially strong firms, older firms, and firms with more R&D expenditures are more likely to invest in CSR; (2) firms operating in multiple markets tend to invest more in reactive CSR while do the same as single market firms in proactive CSR; (3) firms tend to increase their investment in both CSR as the level of competition decreases but reduce proactive CSR more in extreme high level of concentration; and (4) better corporate governance leads to lower reactive CSR but higher proactive CSR.
A Novel Assessment of Various Bio-Imaging Methods for Lung Tumor Detection and Treatment by using 4-D and 2-D CT Images

Lung Cancer is known as one of the most difficult cancer to cure, and the number of deaths that it causes generally increasing. A detection of the Lung Cancer in its early stage can be helpful for Medical treatment to limit the danger, but it is a challenging problem due to Cancer cell structure. Interpretation of Medical image is often difficult and time consuming, even for the experienced Physicians. The aid of image analysis Based on machine learning can make this process easier. This paper describes fully Automatic Decision Support system for Lung Cancer diagnostic from CT Lung images. Most traditional medical diagnosis systems are founded on huge quantity of training data and takes long processing time. However, on the occasion that very little volume of data is available, the traditional diagnosis systems derive defects such as larger error, Time complexity. Focused on the solution to this problem, a Medical Diagnosis System based on Hidden Markov Model (HMM) is presented. In this paper we describe a pre-processing stage involving some Noise removal techniques help to solve this problem, we preprocess an images (by Mean Error Square Filtering and Histogram analysis)obtained after scanning the Lung CT images. Secondly separate the lung areas from an image by a segmentation process (by Thresholding and region growing techniques). Finally we developed HMM for the classification of Cancer Nodule. Results are checked for 2D and 4D CT images. This automation process reduces the time complexity and increases the diagnosis confidence.
On-line New Event Detection, Clustering, and Tracking TITLE2:

In this work, we discuss and evaluate solutions to text classification problems associated with the events that are reported in on-line sources of news. We present solutions to three related classification problems: new event detection, event clustering, and event tracking. The primary focus of this thesis is new event detection, where the goal is to identify news stories that have not previously been reported, in a stream of broadcast news comprising radio, television, and newswire. We present an algorithm for new event detection, and analyze the effects of incorporating domain properties into the classification algorithm. We explore a solution that models the temporal relationship between news stories, and investigate the use of proper noun phrase extraction to capture the `who'', `what'', `when'', and `where'' contained in news. Our results for new event detection suggest that previous approaches to document clustering provide a good basis for an approach to new event detection, and that further improvements to classification accuracy are obtained when the domain properties of broadcast news are modeled. New event detection is related to the problem of event clustering, where the goal is to group stories that discuss the same event. We investigate on-line clustering as an approach to new event detection, and re-evaluate existing cluster comparison strategies previously used for document retrieval. Our results suggest that these strategies produce different groupings of events, and that the on-line single-link strategy extended with a model for domain properties is faster and more effective than other approaches. In this dissertation, we explore several text representation issues in the context of event tracking, where a classifier for an event is formulated from one or more sample stories. The classifier is used to monitor the subsequent news stream for documents related to the event. We discuss different approaches to classifier formulation, and compare feature selection and weight-learning steps as extensions to a baseline process used for new event detection. In addition, we evaluate an unsupervised adaptive approach to event tracking that captures the property of event evolution in broadcast news. We introduce a theoretical framework for automatic threshold estimation for our tracking algorithm, viewing the threshold as a statistic of the incoming data stream. Bias defined in terms of threshold estimators can be identified with statistical and learning techniques using our representation for text. Two methods are presented that learn estimator bias and result in improved classification accuracy for tracking. The implementations of our approaches to on-line new event detection, clustering, and tracking have been evaluated in comparison to other systems, and we present cross-system comparisons for all three classification problems. In general, the results using our approaches compared favorably to other approaches for each problem.
Separation of Carotenes and Vitamin E from Palm Oil Mill Effluent Using Silica from Agricultural Waste as an Adsorbent

Palm oil mill effluent (POME) was characterized. The effluent had low nitrogen with high Biochemical Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). 6,500 mg/L of oil (78 % of oil recovery) was recovered from 1 L of POME using n -hexane. 70 and 71 % of BOD and COD in POME were significantly reduced after oil recovery. The carotenes and vitamin E concentration from recovered oil were 580 and 160 ppm, respectively. α-carotene and β-carotene were presented as a major component in oil. Afterward, carotenes and vitamin E in oil were concentrated by adsorption chromatography using either rice hull silica or rice straw silica as adsorbents. After oil recovery, 4.60 g/L oil was obtained with high concentrations of carotenes (5,590 ppm) and vitamin E (630 ppm). Rice hull silica (RSH) had a higher capability to recover carotenes and vitamin E than rice straw silica (RSS) did. The recovery of carotenes and vitamin E using RSH were 70.77 and 11.88 % recovery, respectively. The carotene and vitamin E recovery method using RHS developed in this work has potential applications in the palm oil industry.