Miracle-dz/UniFAR-FTUs huggingface dataset:
Diterpene Resin Acids and Olefins in Calabrian Pine (Pinus nigra subsp. laricio (Poiret) Maire) Oleoresin: GC-MS Profiling of Major Diterpenoids in Different Plant Organs, Molecular Identification and Expression Analysis of Diterpene Synthase Genes

A quali-quantitative analysis of diterpenoid composition in tissues obtained from different organs of Pinus nigra subsp. laricio (Poiret) Maire (Calabrian pine) was carried out. Diterpene resin acids were the most abundant diterpenoids across all the examined tissues. The same nine diterpene resin acids were always found, with the abietane type prevailing on the pimarane type, although their quantitative distribution was found to be remarkably tissue-specific. The scrutiny of the available literature revealed species specificity as well. A phylogeny-based approach allowed us to isolate four cDNAs coding for diterpene synthases in Calabrian pine, each of which belonging to one of the four groups into which the d3 clade of the plants’ terpene synthases family can be divided. The deduced amino acid sequences allowed predicting that both monofunctional and bifunctional diterpene synthases are involved in the biosynthesis of diterpene resin acids in Calabrian pine. Transcript profiling revealed differential expression across the different tissues and was found to be consistent with the corresponding diterpenoid profiles. The isolation of the complete genomic sequences and the determination of their exon/intron structures allowed us to place the diterpene synthase genes from Calabrian pine on the background of current ideas on the functional evolution of diterpene synthases in Gymnosperms.
Comparing Nanohydroxyapatite Graft and Other Bone Grafts in the Repair of Periodontal Infrabony Lesions: A Systematic Review and Meta-Analysis

Objective: To compare the results of periodontal infrabony lesions treated using nanohydroxyapatite (NcHA) graft with other bone grafts (BGs). Methods: Four electronic databases were searched including PubMed (NLM), Embase (Ovid), Medline, and Dentistry and Oral Sciences (EBSCO). The inclusion criteria included randomised controlled clinical trials (RCTs) and controlled clinical trials (CCTs). The clinical results of NcHA were compared with other BGs. For clinical attachment level (CAL) gain, probing pocket depth (PPD) decrease, and gingival recession (REC) change, weighted averages and forest plots were computed. Results: Seven RCTs fulfilled the selection criteria that were included. When NcHA was compared to other BGs, no clinically significant differences were found in terms of each outcome assessed, except the REC change for synthetic BGs as compared to NcHA. Conclusions: The use of an NcHA graft showed equivalent results compared to other types of BGs. To further validate these findings, future studies are required to compare the NcHA and various BGs over longer time periods and in furcation deficiencies.
Optical frequency measurement for multichannel networks using sum-frequency generation in multilayer waveguides

Practical use of sum-frequency generation in multilayer waveguides is investigated for the purpose of frequency stabilisation in multichannel optical networks. Experimental results are presented on both wide and narrow-range wavelength sensing in the 1.3 mu m communication band using simple optoelectronic components. Optical frequency difference measurement resolution is estimated to be better than 2 GHz. >
Efficient analysis of in‐line waveguide filters and frequency‐selective surfaces with stepped holes

This paper presents a novel method for the analysis of large classes of microwave and mm‐wave passive components, including in‐line waveguide filters, single‐ and multi‐layer frequency selective surfaces, and open‐ended waveguide array antennas. This method is based on the segmentation technique, which permits us to reduce complex components to cascaded waveguide step discontinuities, which are separately characterized through their generalized impedance matrices, as calculated by the integral equation (IE) technique and the boundary integral‐resonant mode expansion (BI‐RME) method. Some examples demonstrate the flexibility and efficiency of the IE/BI‐RME method, and its utility in investigating novel structures not requiring costly fabrication techniques. © 2003 Wiley Periodicals, Inc. Int J RF and Microwave CAE 13: 306–315, 2003.
Characteristics of a magneto-rheological fluid isolator obtained by permanent magnet arrangements

This note focuses on the characteristics of a magneto-rheological (MR) fluid isolator obtained by five permanent magnet arrangements. The basic characteristics of the isolator with various magnetic arrangements were measured from quasi-static tests, and their equivalent models were proposed. The appropriate magnet arrangement for implementing a device that can be used to prevent damage and alignment shift of on-board satellite equipment due to the shock and vibration during lift-off and, at the same time, to isolate disturbances generated by on-orbit momentum- or reaction-wheel operation was investigated.
The new ATLAS track reconstruction (NEWT)

The track reconstruction of modern high energy physics experiments is a very complex task that puts stringent requirements onto the software realisation. The ATLAS track reconstruction software has been in the past dominated by a collection of individual packages, each of which incorporating a different intrinsic event data model, different data flow sequences and calibration data. Recently, the ATLAS track reconstruction has undergone a major design revolution to ensure maintainability during the long lifetime of the ATLAS experiment and the flexibility needed for the startup phase. The entire software chain has been re-organised in modular components and a common event data model has been deployed. A complete new track reconstruction that concentrates on common tools aimed to be used by both ATLAS tracking devices, the Inner Detector and the Muon System, has been established. It has been already used during many large scale tests with data from Monte Carlo simulation and from detector commissioning projects such as the combined test beam 2004 and cosmic ray events. This document concentrates on the technical and conceptual details of the newly developed track reconstruction.
Taguchi Optimization of a SiGe/Si Quantum Dot SOI-Based Lateral PIN Photodiode

A high performance lateral silicon photodiode was designed on a Silicon–on-insulator (SOI)-based substrate with SiGe/Si quantum dot technology. The device has the potential of being a serious candidate for applications in sensing applications as well as in optical fiber communications. Five device process parameters and two device noise factors were identified to make the virtual device design insensitive to variation in the selected fabrication parameters. An L9 array from Taguchi method was used to optimize the device design. The simulator of ATHENA and ATLAS were used for photodiode fabrication process and electrical characterization, respectively. The results obtained for responsivity and frequency response after the optimization approach were 0.36 A/W and 21.2 GHz respectively which correspond to the optimization value for the intrinsic region length of 6 μm, photo-absorption layer thickness of 0.505 μm, incident optical power of 0.5 mW/cm2 and bias voltage of 3.5 V. As a conclusion, the optimum solution in achieving the desired high speed photodiode was successfully predicted using Taguchi optimization method.
Biocompatibility Computation of Muscle Cells on Polyhedral Oligomeric Silsesquioxane-Grafted Polyurethane Nanomatrix

This study was performed to appraise the biocompatibility of polyhedral oligomeric silsesquioxane (POSS)-grafted polyurethane (PU) nanocomposites as potential materials for muscle tissue renewal. POSS nanoparticles demonstrate effectual nucleation and cause noteworthy enhancement in mechanical and thermal steadiness as well as biocompatibility of resultant composites. Electrospun, well-aligned, POSS-grafted PU nanofibers were prepared. Physicochemical investigation was conducted using several experimental techniques, including scanning electron microscopy, energy dispersive X-ray spectroscopy, electron probe microanalysis, Fourier transform infrared spectroscopy, and X-ray diffraction pattern. Adding POSS molecules to PU did not influence the processability and morphology of the nanocomposite; however, we observed an obvious mean reduction in fiber diameter, which amplified specific areas of the POSS-grafted PU. Prospective biomedical uses of nanocomposite were also appraised for myoblast cell differentiation in vitro. Little is known about C2C12 cellular responses to PU, and there is no information regarding their interaction with POSS-grafted PU. The antimicrobial potential, anchorage, proliferation, communication, and differentiation of C2C12 on PU and POSS-grafted PU were investigated in this study. In conclusion, preliminary nanocomposites depicted superior cell adhesion due to the elevated free energy of POSS molecules and anti-inflammatory potential. These nanofibers were non-hazardous, and, as such, biomimetic scaffolds show high potential for cellular studies and muscle regeneration.
Classification and regression tree-based adaptive damping control of inter-area oscillations using wide-area signals

An adaptive damping control scheme based on the classification and regression tree (CART) using wide-area signals is proposed. A family of robust multiple-input multiple-output controllers are designed offline and used in real-time after the current operating point is retrieved from phasor measurement unit (PMU) data with CART interpolation. When the power system is operating close to a previously set operating point, only the corresponding controller is active. When the power system is not close to any previously set operating point, a combined controller is formed. A 16-machine 68-bus system is used for simulation test. Thyristor controlled series compensation, static var compensator and energy storage device are used as actuators and the remote PMUs frequencies are employed as added inputs in the example control. Simulation results demonstrate good damping performance of the proposed control method against a wide range of changes in operating state.
A Method of Insect Recognition Based on Spectrogram

A novel approach to insect recognition is presented in this paper. The difference between the proposed method with traditional methods is that it starts from the perspective of image and combines voice processing algorithms with image processing algorithms. The classification is done based on voice activity detection (VAD) and spectrogram. We show, by means of example that this approach can recognize different insects correctly. However, despite the potential of correct recognition, further justification of the reliability of the method need to be provided by a larger scale of experiments. Hence, some improvements will be proposed latterly.
Initial Estimates in the Design of Rack-and-Pinion Steering Linkages

Based on recent results concerning the occurrence of function cognates in Watt II linkages, it is shown that only 3 geometric parameters are sufficient for defining the kinematic function of simplified planar rack-and-pinion steering linkages. The steering performances of the mechanisms are analytically expressed in terms of these parameters and, by employing an optimization-based synthesis method involving increasing the degree of freedom of the mechanism, the optimum domains are determined. The parameter sets corresponding to these minimum steering error domains are displayed in design charts. These charts aid the automotive engineer in the early stages of conceiving a new steering linkage by providing initial estimates of the basic geometry of the mechanism. They also provide information on two other characteristics of concern, i.e. the minimum pressure angle occurring in the joints and the rack stroke required for maximum turn of the wheels.
A 200 mV low leakage current subthreshold SRAM bitcell in a 130 nm CMOS process

A low leakage current subthreshold SRAM in 130 nm CMOS technology is proposed for ultra low voltage (200 mV) applications. Almost all of the previous subthreshold works ignore the leakage current in both active and standby modes. To minimize leakage, a self-adaptive leakage cut off scheme is adopted in the proposed design without any extra dynamic energy dissipation or performance penalty. Combined with buffering circuit and reconfigurable operation, the proposed design ensures both read and standby stability without deteriorating writability in the subthreshold region. Compared to the referenced subthreshold SRAM bitcell, the proposed bitcell shows: (1) a better critical state noise margin, and (2) smaller leakage current in both active and standby modes. Measurement results show that the proposed SRAM functions well at a 200 mV supply voltage with 0.13 μW power consumption at 138 kHz frequency.
Robust phase-retrieval for quick whole-body SAR assessment using dual plane amplitude-only data

A robust phase-retrieval method with stable convergence and back-propagation properties for quick experimental whole body specific absorption rate (SAR) assessments is presented. A combination of a fast and coarse method and a more accurate gradient-based method is used to optimise the overall performance. To prevent the solution being trapped in a local minimum, several initial phase distributions are used. An accurate measurement procedure has been developed which reduces measurement time by roughly a factor of 2.5-4 at common mobile communication frequencies compared with a volume scan based procedure.
A Dynamic Vehicle-Track Interaction Model for Predicting the Track Degradation Process

Due to the repeated passage of trains, differential settlements are observed in the vertical direction of the railway tracks. These settlements depend on the platform quality, on the train speed, on the dynamic load, and on the track structural behavior. In recent years, several authors have defined laws and models for the prediction of settlement. The majority of those settlement models only consider the vertical degradation of the track, disregarding this phenomena in the lateral direction, since the vertical track geometry deteriorates faster than the horizontal one. In these models also the dynamic nature of the vehicle load is not considered accordingly. This paper presents a vehicle-track dynamic-interaction model for predicting the evolution of the vertical track profile and assessing the track response along the degradation process. The model is one-dimensional (1D) and it estimates the track degradation from a settlement law that uses deformation under instantaneous wheel passage as input. Although track degradation is a three-dimensional (3D) process, a 1D model is considered because the vertical component of the track settlement is the largest one. In order to predict the evolution of the track settlement due to the passage of the dynamic loads on the track, an iterative procedure is proposed. One cycle of this methodology is composed by three phases: numerical calculation of the train-track dynamic-interaction loads along the track, calculation of the track settlement, and definition of the track profile after settlement. Then, a new cycle begins. The proposed methodology is applied to a real track profile, measured in a Portuguese railway line, in order to understand the influence of the dynamic nature of the load on the track, the influence of the settlement rate and the influence of the type of vehicle on the evolution of the vertical track profile. The dynamic response of the track over time due to the evolution of the real vertical profile is evaluated through a vehicle-track dynamic-interaction approach. The attained results reveal the importance not only of the track irregularities, but also of the vehicle speed and characteristics on the evolution of the track profile. The numerical simulations presented in this paper evidence the potential of the proposed methodology, which can be used as a tool to forecast track settlement and to estimate the dynamic response of the track along the degradation process.
Soil water sources in permafrost active layer of Three-River Headwater Region, China

Abstract. Water in permafrost soil is an important factor affecting the ecology of cold environments, climate change, hydrological cycle, engineering, and construction. To explore the variations in soil water in the active layer due to permafrost degradation, the soil water sources in the Three-River Headwater Region were quantified based on the stable isotope data (δ2H and δ18O) of 1140 samples. The results showed that the evaporation equation was δ2H = 7.46 δ18O - 0.37 for entire soil water. The stable isotope data exhibited a spatial pattern, which varied over the soil profile under the influence of altitude, soil moisture, soil temperature, vegetation, precipitation infiltration, soil water movement, ground ice, and evaporation. Based on the stable isotope tracer model, precipitation and ground ice accounted for approximately 88 % and 12 % of soil water, respectively. High precipitation contributed to the soil water in the 3900–4100 m, 4300–4500 m, and 4700–4900 m zones, whereas ground ice contributed to the soil water in the 4500–4700 m and 4900–5100 m zones. Precipitation contributed approximately 84 % and 80 % to the soil water in grasslands and meadows, respectively, whereas ground ice contributed approximately 16 % and 20 %, respectively. Precipitation; evapotranspiration; physical and chemical properties of soil; and the distribution of ground ice, vegetation, and permafrost degradation were the major factors affecting the soil water sources in the active layer. Therefore, establishing an observation network and developing technologies for ecosystem restoration and conservation is critical to effectively mitigate ecological problems caused by future permafrost degradation in the study region.
Product-to-Product Virtual Metrology of Color Filter Processes in Panel Industry

The current thin film transistor liquid crystal display (TFT-LCD) panel industry evolves in transition from volume production to customized production service as a major competition strategy. Owing to the highly mixed production type of small batch sizes and high varieties, metrology data are usually collected too infrequently for building accurate virtual metrology (VM) models. In this paper, a new product-to-product (P2P) VM model to predict photoresist spacer heights in the color filter process of the array sector is developed. First, a position-based random forests model is proposed for the base product. Second, an ensemble model combining the base model and a biased estimation random forests model for the new product of small batch size is proposed to perform P2P VM between different products on the same tool. The real datasets of photoresist spacer heights for different products are used to illustrate the accuracy of the new P2P VM framework in the experimental study. Note to Practitioners—As global competition intensifies, production management needs to be adjusted to adapt swiftly to changes in the time-varying and competitive market. For manufacturing firms, how to operate the manufacturing system effectively and efficiently plays a crucial role in quality and yield improvements. The color filter process in the array sector is of critical importance in the TFT-LCD practice since it essentially dictates the quality level of subsequent processing steps in the cell and assembly sectors. Virtual metrology is a state-of-the-art measure that can be used for monitoring and controlling purposes to maintain the yield and productivity of the color filter process in the highly mixed production environment. An immediate challenge to be faced by the data scientists is how to build accurate virtual metrology models for a variety of product lines separately in color filter manufacturing. A new proposal of product-to-product virtual metrology is first addressed between products, enabling to build appropriate virtual metrology models for new products with small-sized production batches.
Photosystem II Repair Cycle in Faba Bean May Play a Role in Its Resistance to Botrytis fabae Infection

Chocolate spot, which is caused by the necrotrophic fungus Botrytis fabae, is a major foliar disease occurring worldwide and dramatically reducing crop yields in faba bean (Vicia faba). Although chemical control of this disease is an option, it has serious economic and environmental drawbacks that make resistant cultivars a more sensible choice. The molecular mechanisms behind the defense against B. fabae are poorly understood. In this work, we studied the leave proteome in two faba bean genotypes that respond differently to B. fabae in order to expand the available knowledge on such mechanisms. For this purpose, we used two-dimensional gel electrophoresis (2DE) in combination with Matrix-Assisted Laser Desorption/Ionization (MALDI-TOF/TOF). Univariate statistical analysis of the gels revealed 194 differential protein spots, 102 of which were identified by mass spectrometry. Most of the spots belonged to proteins in the energy and primary metabolism, degradation, redox or response to stress functional groups. The MS results were validated with assays of protease activity in gels. Overall, they suggest that the two genotypes may respond to B. fabae with a different PSII protein repair cycle mechanism in the chloroplast. The differences in resistance to B. fabae may be the result of a metabolic imbalance in the susceptible genotype and of a more efficient chloroplast detoxification system in the resistant genotype at the early stages of infection.
Android Malware Detection Using Machine Learning with Feature Selection Based on the Genetic Algorithm

Since the discovery that machine learning can be used to effectively detect Android malware, many studies on machine learning-based malware detection techniques have been conducted. Several methods based on feature selection, particularly genetic algorithms, have been proposed to increase the performance and reduce costs. However, because they have yet to be compared with other methods and their many features have not been sufficiently verified, such methods have certain limitations. This study investigates whether genetic algorithm-based feature selection helps Android malware detection. We applied nine machine learning algorithms with genetic algorithm-based feature selection for 1104 static features through 5000 benign applications and 2500 malwares included in the Andro-AutoPsy dataset. Comparative experimental results show that the genetic algorithm performed better than the information gain-based method, which is generally used as a feature selection method. Moreover, machine learning using the proposed genetic algorithm-based feature selection has an absolute advantage in terms of time compared to machine learning without feature selection. The results indicate that incorporating genetic algorithms into Android malware detection is a valuable approach. Furthermore, to improve malware detection performance, it is useful to apply genetic algorithm-based feature selection to machine learning.