Miracle-dz/UniFAR-FTUs huggingface dataset:
Macrophomina Crown and Root Rot of Pistachio in California

In this study, declining pistachio rootstocks were detected in newly planted commercial pistachio orchards in Kern County, California. Symptoms were characterized by wilted foliage combined with crown rot in the rootstock. From diseased trees, 42 isolates were obtained, and all had similar cultural and morphological characteristics of Macrophomina phaseolina. Analyses of nucleotide sequences of three gene fragments, the internal transcribed spacer region (ITS1–5.8S–ITS2), partial sequences of β-tubulin, and translation elongation factor 1-α (TEF1) confirmed this identification, and 20 representative isolates are presented in the phylogenetic study. Testing of Koch’s postulates showed that M. phaseolina, when inoculated to stems and roots of the pistachio rootstocks using mycelial plugs or a microsclerotial suspension, is indeed pathogenic to this host. The widely used clonal University of California Berkeley I (UCBI) rootstock appeared highly susceptible to M. phaseolina, suggesting that this pathogen is an emerging threat to the production of pistachio in California. This study confirmed the association of M. phaseolina with the decline of pistachio trees and represents the first description of this fungus as a crown rot-causing agent of pistachio in California.
Efficient Learning Algorithms for Rankings and Other Combinatorial Concept Classes

Recently, learning to rank techniques has been attracting increasing attention in various areas such as web search, product recommendation, financial risk analysis, scheduling, and so on. Informally, the task is to obtain an appropriate ranking among items from training data. The amount of data is typically very large in these areas and even rapidly increasing. Therefore, it is particularly important to develop learning algorithms that run efficiently, as well as producing rankings with high quality. In this thesis, we explore efficient algorithms in the following two theoretical learning models, the statistical learning model and the online prediction model. In the statistical learning model, we consider the bipartite ranking problem, which is one of the most fundamental problems of learning ranking functions. In the bipartite ranking problem, we are given a randomly generated sample consisting of positive and negative instances and required to learn a real-valued function called a ranking function, so that it maps a positive instance to a higher value than a negative instance. It is well known that the problem is reduced to a binary classification problem and so we can apply any of standard learning algorithms such as the Support Vector Machines (SVMs). However, the sample is blown up quadratically in size through the reduction. This means that if we use the 1-norm or 2-norm regularized SVM to obtain a good ranking function, we need to solve a linear or quadratic programming problem of size O(m), respectively, where m is the size of the original sample. In this thesis, we reformulate the SVMs for ranking functions as significantly simplified optimization problems of size O(m) and give theoretical guarantees on the generalization ability of the ranking functions obtained by solving the optimization problems. In particular, the reformulation of the 1-norm regularized SVM yields the first practical algorithm that is competitive with the original 1-norm regularized SVM in performance. As an application of our algorithm, we consider the problem of constructing an evalu-
A note on quantum fields in conformally flat spacetimes

We develop a technique relating scalar fields with different masses in different conformally flat spacetimes. We apply this technique to the case of FRW spacetimes, with [Formula: see text], and discuss several examples. We also study various energy conditions and discuss how they constrain the spacetimes related by this technique. We calculate the two-point scalar correlator in the radiation-dominated universe with a hyperbolic spatial section from the one in the Milne universe using the above mapping. Finally, we consider trace anomaly and renormalized stress tensor for conformally flat spacetimes, especially Milne and radiation-dominated universe (with [Formula: see text]) using the transformation.
Play Therapy for Children with Anxiety Disorders

This study uses a literature review to study the effects of play therapy used as an intervention in children with anxiety disorders. The literature consists of 15 international journals published from 2015-2018. The review covers the subject, the design, and the setting of the therapy, as well as the type of game applied. Based on the results of the review, it is known that play therapy is effective in reducing anxiety in children with vulnerable ages ranging from 3-16 years old using various materials and different settings. In addition to reducing anxiety, play therapy can also reduce negative emotions, aggression and can improve the social abilities and academic performance of children with anxiety disorders. Play therapy is often applied to children who experience anxiety disorders while undergoing treatment in the hospital. The results of this research review are expected to be a reference for further research, especially research conducted in Indonesia.
Key Roles of Plasmonics in Wireless THz Nanocommunications—A Survey

Wireless data traffic has experienced an unprecedented boost in past years, and according to data traffic forecasts, within a decade, it is expected to compete sufficiently with wired broadband infrastructure. Therefore, the use of even higher carrier frequency bands in the THz range, via adoption of new technologies to equip future THz band wireless communication systems at the nanoscale is required, in order to accommodate a variety of applications, that would satisfy the ever increasing user demands of higher data rates. Certain wireless applications such as 5G and beyond communications, network on chip system architectures, and nanosensor networks, will no longer satisfy speed and latency demands with existing technologies and system architectures. Apart from conventional CMOS technology, and the already tested, still promising though, photonic technology, other technologies and materials such as plasmonics with graphene respectively, may offer a viable infrastructure solution on existing THz technology challenges. This survey paper is a thorough investigation on the current and beyond state of the art plasmonic system implementation for THz communications, by providing in-depth reference material, highlighting the fundamental aspects of plasmonic technology roles in future THz band wireless communication and THz wireless applications, that will define future demands coping with users’ needs.
EFFECT OF SURFACE ROUGHNESS ON MACH REFLECTION

Summary The effects of surface roughness and transport properties have been compared experimentally to investigate non-self-similar Mach reflection phenomena. The surface roughness was given by pasting a piece of sand paper on the model surface. The results were compared with those for smooth surfaces. The effect of surface roughness turned out to be small compared with viscosity effect so that the effect of transport properties is proved to be dominant. INTRODUCTION It was first reported by Walenta [1] some twenty years ago that, under rarefied-gas conditions, the transition from regular to Mach reflection takes place during the incident shock propagation over a wedge. This non-self-similar phenomenon was first considered to be a phenomenon characteristic of extremely low-pressure, low-density atmosphere, because such dynamic transition phenomena have never been observed in ordinary atmospheric conditions. However, the authors observed a same kind of phenomenon even in atmospheric pressure for the first time [2], proving that such non-self-similar phenomenon is not restricted to low-pressure conditions. The disruption of self-similarity suggests that a length scale has been introduced into the system. There are two candidate causes: viscosity and surface roughness. According to Henderson et al.’s numerical experiment [3], the condition on the solid boundary plays a key role in the phenomenon. The authors’ experiment in Karlsruhe found different wave angles from those obtained in Saitama [4]. In the Karlsruhe experiment, the initial pressure
DNA hazard in Furnace Operating Workers from a Power Plant

The aim of this study was to investigate the possible DNA damage in workers occupationally exposed to coal combustion products in furnace section of Afsin-Elbistan A power plant (Turkey). With this purpose, venous blood samples collected from 36 male power plant workers were analysed by comet assay for determining the level of DNA tail intensity. The obtained results were compared with those of control group consisting of 34 healthy male individuals. The data comparison showed that mean frequency of tail intensity was significantly higher in workers as compared to control group (P<0.05), respectively 9.94±2.51 and 8.48±2.31. Present study indicated the DNA damage in the peripheral lymphocytes of furnace operators, possibly due to the several chemical compounds present in the coal ash and gaseous emissions.
The functional weight of a prosodic cue in the native language predicts the learning of speech segmentation in a second language

This study newly investigates whether the functional weight of a prosodic cue in the native language predicts listeners’ learning and use of that cue in second-language speech segmentation. It compares English and Dutch listeners’ use of fundamental-frequency (F0) rise as a cue to word-final boundaries in French. F0 rise signals word-initial boundaries in English and Dutch, but has a weaker functional weight in English than Dutch because it is more strongly correlated with vowel quality in English than Dutch. English- and Dutch-speaking learners of French matched in French proficiency and experience, and native French listeners completed a visual-world eye-tracking experiment in French where they monitored words ending with/out an F0 rise (replication of Tremblay, Broersma, Coughlin & Choi, 2016). Dutch listeners made earlier/greater use of the F0 rise than English listeners, and in one condition they made greater use of F0 rise than French listeners, extending the cue-weighting theory to speech segmentation.
Design and Analysis of a Novel Magnetic Coupler of an In-Wheel Wireless Power Transfer System for Electric Vehicles

Electric vehicle (EVs), which use an electric motor, are expected to replace internal combustion engine vehicles. However, to date EVs are not highly attractive to consumers due to their unsatisfactory battery charging characteristics and high cost. In particular, the existing conductive charging method makes it more difficult to spread EVs due to the inconvenience of charging and the risk of electric shock. The wireless power transfer (WPT) system can eliminate all of the charging troubles of EVs. However, the WPT systems in existing EVs have large air gaps between the transmitter coil and the receiver coil, posing a hurdle that prevents success. The large air gap cause issues such as a loose coupling, low efficiency, and troublesome electromagnetic compatibility (EMC). An in-wheel WPT system can serve as a solution to address the issues arising due to the large air gap. In this paper, we propose a magnetic coupler structure of an in-wheel WPT system for EV applications. A design of two coils is introduced, in which the transmitter coil and receiver coil are designed based on a design method. Moreover, the pad structure according to the ferromagnetic core geometry is designed and discussed. The aim of this research is to find a suitable configuration of the magnetic coupler for an in-wheel WPT system. The values of the coupling coefficients according the magnetic coupler structure are determined. This paper is expected to provide a good reference for further research, including work on the manufacturing of a prototype.
Novel piezoelectric actuation mechanism for a gimbal-less mirror in 2D raster scanning applications

In this paper, we present the design, fabrication and measurement results of a 2D scanning mirror actuated by 1 × 10 piezoelectric Pb(Zr,Ti)O3 (PZT) cantilever actuators integrated on a thin silicon beam. A combination of bulk silicon micromachining based on a silicon-on-insulator (SOI) substrate and thin-film surface micromachining on a 5 µm thick Si device layer is used to fabricate the device. Multi-layers of Pt/Ti/PZT/Pt/Ti are deposited as electrode materials. A large silicon mirror plate (5 mm × 5 mm) and a 1 × 10 PZT cantilever array arranged in parallel are formed after the backside release process. The ten PZT cantilever actuators are electrically isolated from one another. The device can operate in three modes: bending, torsional and mixed (or combinational) modes. In bending mode, the first resonant frequency was measured to be 30 Hz and an optical deflection angle of ±8° was obtained when all ten cantilevers were actuated at 9 Vpp. In torsional mode, the resonant frequency was measured to be 89 Hz and an optical deflection angle of ±4.6° was obtained by applying a gradually declining ac voltage started at 8 Vpp to two sets of actuators, where each set comprises five cantilever actuators of the said 1 × 10 array, i.e. 1–5 and 6–10. A 2D raster scanning pattern was achieved in the mixed mode when the bending mode was carried out by cantilever actuators of 4–7 and the torsional modes were exercised by two different sets of cantilever actuators, i.e. 1–3 and 8–10, under opposite biasing direction. This mixed mode operation mechanism demonstrates the first 2D raster scanning mirror-driven beam actuators.
SONTRAC-a low background, large area solar neutron spectrometer

SONTRAC will measure 20-250 MeV neutrons from solar flares using scintillator fibers viewed by CCD cameras to track neutron-proton scatters. SONTRAC can also be used to track gamma rays above 20 MeV. Veto shields are used to reject all charged particles. Gamma-ray and neutron events have very different track densities, allowing discrimination between the two. Double neutron-proton scatters allow unambiguous determination of the incident neutron energy and direction. Therefore, SONTRAC is capable of rejecting almost all background except neutrons from the solar direction. SONTRAC would have detected the June 15, 1991 flare with 42/spl sigma/ for 20-100 MeV neutrons, having an effective area of 17 cm/sup 2/ in that energy range. The authors present SONTRAC prototype performance results both for neutrons at threshold energy and for cosmic-ray muons.
Primordial non-Gaussianity from the large-scale structure

Primordial non-Gaussianity is a potentially powerful discriminant of the physical mechanisms that generate the cosmological fluctuations observed today. Any detection of non-Gaussianity would have profound implications for our understanding of cosmic structure formation. In this paper, we review past and current efforts in the search for primordial non-Gaussianity in the large-scale structure of the Universe.
Reliable Semi-Supervised Learning when Labels are Missing at Random

Semi-supervised learning methods are motivated by the availability of large datasets with unlabeled features in addition to labeled data. Unlabeled data is, however, not guaranteed to improve classification performance and has in fact been reported to impair the performance in certain cases. A fundamental source of error arises from restrictive assumptions about the unlabeled features, which result in unreliable classifiers that underestimate their prediction error probabilities. In this paper, we develop a semi-supervised learning approach that relaxes such assumptions and is capable of providing classifiers that reliably quantify the label uncertainty. The approach is applicable using any generative model with a supervised learning algorithm. We illustrate the approach using both handwritten digit and cloth classification data where the labels are missing at random.
A Multi-Agent Technology Based Platform for Marketing Communication

One of the most significant current discussions in marketing is related to personalizing and distribution marketing information content in order to promote services and/or products that will be sent to the customers with a specific profile. In this context, is becoming increasingly difficult to ignore the design process of the dedicated platforms built for composing and spreading marketing information. The entire involved communication process is also characterized by a set of specific tasks. However, a major issue with this kind of platforms is related to the identification of the clients groups (clients with similar needs), building clients’ profiles, information personalization and distribution in an efficient way, collecting a relevant feedback from the clients. The purpose of this paper is to review recent research regarding marketing communication platforms (MCP) and to propose a platform architecture for MCP using intelligent technologies in several aspects specific to this kind of platform. For the proposed architecture each module will be described and also its particularities. In the end, there is outline a conclusion set regarding the platform and its functionalities.
Antireflection Coating on PMMA Substrates by Atomic Layer Deposition

Antireflection coatings (ARC) are essential for various optical components including such made of plastics for high volume applications. However, precision coatings on plastics are rather challenging due to typically low adhesion of the coating to the substrate. In this work, optimization of the atomic layer deposition (ALD) processes towards conformal optical thin films of Al2O3, TiO2 and SiO2 on poly(methyl methacrylate) (PMMA) has been carried out and a five-layer ARC is demonstrated. While the uncoated PMMA substrates have a reflectance of nearly 8% in the visible (VIS) spectral range, this is reduced below 1.2% for the spectral range of 420–670 nm by applying a double-side ARC. The total average reflectance is 0.7%. The optimized ALD coatings show a good adhesion to the PMMA substrates even after the climate test. Microscopic analysis on the cross-hatch areas on PMMA after the climate test indicates very good environmental stability of the ALD coatings. These results enable a possible route by ALD to deposit uniform, crack free, adhesive and environmentally durable thin film layers on sensitive thermoplastics like PMMA.
FLAMMATORY ACTIVITIES OF ETHA OLIC EXTRACT OF PSEUDARTHRIA VISCIDA ( L ) ROOTS Pravin

The present study was designed to investigate the analgesic and anti-inflammatory effects of the ethanolic extract of pseudarthria viscida Linn (EEPV). Acetic acid-induced writhing and hotplate tests were used to determine analgesic effect. Anti-inflammatory activity of EEPV was demonstrated with Wistar rats using carrageenan induced edema of the hind paw of rats. It has been shown that the EEPV (200/400 mg/kg, p. o.) significantly reduced acetic acid-induced writhing response, as well as significantly increase the hot-plate pain threshold in mice. In the Carrageenan induced mouse paw edema test, the group treated with indomethacin showed the strongest inhibition of edema formation by 62.50% in the third hour after carrageenan administration, while EEPV (200/400 mg/kg) showed 42.69% and 55.76% respectively. The extract did not produce any mortality up to the dose of 2000 mg / kg. Preliminary Phytochemical screening revealed the presence of flavonoids, proteins, tannins, and phenolic compounds. The result justifies the traditional uses of Pseudarthria viscida for the treatment of fever, inflammatory and painful conditions.
Familial Hodgkin Lymphoma: A Case Report and Sort Review

Introduction: Mixed cellularity Hodgkin’s Lymphoma (HL) is a subtype of classic HL (c-LH), constituting the second most common subtype and 15% to 30% of all cases of HL. It is mostly observed in patients with either Epstein-Barr Virus (EBV) or Human Immunodeficiency Virus (HIV) infection, having less inheritance rate comparing to other subtypes. Familial HL is very rare. Aim: The aim of this paper is to present a case of familial HL and to review the literature about the incidence and the relationship by histology, age at diagnosis, and gender. Materials and Methods: Two siblings, a girl 15-year old and a boy 25-year old, presented with HL, stage IIIs, with the same affected sites of lymph nodes. The open node biopsy revealed the histological type of mixed cellularity c-HL, in both cases. At the biopsy specimen, both cases were negative for EBV. Results: The girl achieved remission with chemotherapy, only. The boy received also initially chemotherapy but due to relapse during chemotherapy, radiotherapy was added. Unfortunately, he succumbed from refractory disease. The girl, up to date remains in first remission, 10 years after the diagnosis. By contrast, her older brother had a poor outcome. Conclusion: It is a report of familial HL in two siblings. The only apparent difference between the two cases was the presenting age and gender. The girl was diagnosed at the age of 15 years old and the boy at the age of 25 years old. Considering that both patients where similar on their disease characteristics and both where negative for EBV infection, it seems that the age of onset and maybe the gender in this subtype of HL, has a crucial role on the outcome in familial cases of the disease.
Neural Networks for Landscape Applications

The endmost intention of the present survey is to revise the use of a relatively new modelling technique inspired by the function of biological nervous systems and to provide insights as to their application to landscape problems. The models that arise from the aforementioned simulation, called Artificial Neural Networks, promise to alleviate problems posed by traditional statistical methods. Specifically, they are designed so as to accommodate fuzziness, as well as parallel processing and allow for a more accurately inferred classification and/or modelling. Included are the models that pose as the mathematical theoretical bases of the neural network types identified as useful to landscape applications. The types to be described range from the Multilayer Perceptron to the Self Organising Maps and from the Adaptive Resonance Theory to the Hopfield networks. Our aim is to describe and clarify their main features, as well as to show their fast utilisation into more environmental fields, considerably aided by the fast growing usage of PC-based tools.
Nonlinear Model for Condition Monitoring and Fault Detection Based on Nonlocal Kernel Orthogonal Preserving Embedding

The dimension reduction methods have been proved powerful and practical to extract latent features in the signal for process monitoring. A linear dimension reduction method called nonlocal orthogonal preserving embedding (NLOPE) and its nonlinear form named nonlocal kernel orthogonal preserving embedding (NLKOPE) are proposed and applied for condition monitoring and fault detection. Different from kernel orthogonal neighborhood preserving embedding (KONPE) and kernel principal component analysis (KPCA), the NLOPE and NLKOPE models aim at preserving global and local data structures simultaneously by constructing a dual-objective optimization function. In order to adjust the trade-off between global and local data structures, a weighted parameter is introduced to balance the objective function. Compared with KONPE and KPCA, NLKOPE combines both the advantages of KONPE and KPCA, and NLKOPE is also more powerful in extracting potential useful features in nonlinear data set than NLOPE. For the purpose of condition monitoring and fault detection, monitoring statistics are constructed in feature space. Finally, three case studies on the gearbox and bearing test rig are carried out to demonstrate the effectiveness of the proposed nonlinear fault detection method.