Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Haloxyfop and CGA-82725 on Cell Cycle and Cell Division of Oat (Avena sativa) Root Tips

The mode of action of two experimental pyridinyloxyphenoxy propionate herbicides, haloxyfop {2-[4-[[3-chloro-5-(trifluoromethyl)-2-pyridinyl]oxy] phenoxy] propanoic acid} and CGA-82725 {2-propynyl-2-[4-[(3,5-dichloro-2-pyridinyl)oxy] phenoxy] propanoic acid} was studied. Oat (Avena sativa L.) roots showed a rate-dependent sensitivity to both herbicides. Consequently, a series of assays was performed to study cell division, cell cycle dynamics, and nucleic acid and protein synthesis in oat root tips in order to characterize growth inhibition. Both herbicides inhibited cell division, apparently by inhibiting protein synthesis in the G2 stage of interphase. Supporting evidence for this assumption comes from the following observations: a) There was almost complete absence of leucine incorporation within 1 h of exposure to 2.7 × 10−4 M of either herbicide; b) the number of 3H-labeled dividing cells was reduced to about 20% of the control within 4 h, and essentially to zero within 8 h, after exposure to 2.7 × 10−4 M of herbicide; c) the number of unlabeled cells was reduced to less than 10% of the control within 8 h of exposure to 2.7 × 10−4 M of herbicide; d) during this 8-h period, the number of 3H-labeled cells in interphase which had been exposed to herbicide greatly exceeded the control; e) thymidine incorporation into DNA was inhibited but was not proportional to reduction in cell division; f) uridine incorporation was enhanced during the first 8 h of exposure before a reduction was evident at 12 h; and g) an oat coleoptile elongation bioassay showed that cell enlargement was not inhibited at herbicide concentrations less than 2.7 × 10−4 M.
Source Microphone Recognition Aided by a Kernel-Based Projection Method

Microphone recognition aims at recognizing different microphones based on the recorded speeches. In the literature, Gaussian Supervector (GSV) has been used as the feature vector representing a speech recording, which is obtained by adapting a universal background model (UBM). However, it is not clear how the performance of the GSV will be affected by the number of mixture components in the UBM. Besides, the raw GSV obtained from a speech recording contains both the microphone response information and the speech information, meaning that the raw GSV can be quite noisy as the feature vector for microphone recognition. In this paper, we investigate how GSV will be affected by the UBM and other parameters during the calculation of the GSV. In addition, in order to improve the quality of the raw GSV, we propose a kernel-based projection method to be applied to the raw GSV. This projection method maps the raw GSV onto another dimensional space. It is expected that in the projected feature space, the microphone response information and the speech information can be separated into different dimensions, meaning that the projected GSV should be better as the feature vector for microphone recognition compared to the raw GSV. Two classifiers that have been used in the literature, namely linear support vector machine (SVM) and sparse representation-based classifier (SRC), are employed to compare the performance of the raw GSV and the projected GSV. The experimental results demonstrate that the projected GSV can outperform the raw GSV no matter using linear SVM or SRC as the classifier, which shows the effectiveness of the projection method.
A New Form of Velocity Distribution in Rectangular Microchannels with Finite Aspect Ratios

This study presents a new form of velocity distribution in laminar liquid flow in rectangular microchannels using the eigenfunction expansion technique. Darcy friction factor and Poiseuille number are also obtained analytically. Due to the symmetry of the solutions, the effects of changing the aspect ratio from 0 to ∞ are also discussed. Using finite element method (FEM), the obtained analytical results are further compared with the 3D numerical simulations for the rectangular microchannels with different range of aspect ratio and pressure gradient, and excellent agreements were found. These findings provide additional insights in interpreting the results of the pressure-driven flows in finite aspect ratio microchannels, in which very precise comparison with the macroscale theory is crucial.
Personal Music Emotion Analysis Based on BP Neural Model

Music as an art is an indispensable part of human life. From ancient times to the present, music has always been a special channel for humans to express their emotions with rich expression style and delicate emotional classifications. Thus, the emotional analysis of music has become an important issue. With the advent of the information age, the analysis of musical emotions through computers has begun to enter people's horizons. Music emotion analysis model can be generally divided into three parts, music feature model, music emotion model and classification cognitive model. The music feature model consists of features extracted from music. This paper proposes some new features. The emotional model mainly describes the classification of emotions. The BP neural network model is selected for this classification cognitive model.
A virtual assistant in cultural heritage scenarios

New technologies, tools, and methodologies have been used in the Cultural Heritage (CH) scenarios to assist the visitor to enrich and enjoy his experiences during the visit. Intelligent information systems based upon machine learning approaches have been specifically designed for CH to enhance the quality of services in art exhibitions and events. In this work, we show an innovative framework that can be specifically designed to help visitors during his/her visit by answering to their questions. We also describe a system architecture and a case study in a well‐defined CH context.
Application of Sulfated Tin (IV) Oxide Solid Superacid Catalyst to Partial Coupling Reaction of α-Pinene to Produce Less Viscous High-Density Fuel

Brønsted acid-catalyzed reactions of α-pinene have been studied because of their ability to produce various types of fragrance molecules. Beyond this application, dimeric hydrocarbon products produced from coupling reactions of α-pinene have been suggested as renewable high-density fuel molecules. In this context, this paper presents the application of a sulfated tin(IV) oxide catalyst for the partial coupling reaction of α-pinene from turpentine. Brønsted acid sites inherent in this solid superacid catalyst calcined at 550 °C successfully catalyzed the reaction, giving the largest yield of dimeric products (49.6%) at 120 °C over a reaction time of 4 h. Given that the low-temperature viscosity of the mentioned dimeric products is too high for their use as a fuel in transportation engines, lowering the viscosity is an important avenue of study. Therefore, our partial coupling reaction of α-pinene provides a possible solution as a considerable amount of the isomers of α-pinene still remained after the reaction, which reduces the low-temperature viscosity. On the basis of a comparison of the reaction products, a plausible mechanism for the reaction involving coinstantaneous isomerization and coupling reaction of α-pinene was elucidated.
A High-Efficiency Charger With Adaptive Input Ripple MPPT for Low-Power Thermoelectric Energy Harvesting Achieving 21% Efficiency Improvement

A high-efficiency charger for low-power thermoelectric energy harvesting with a method for improving the efficiency, which is called the adaptive input ripple (AIR) maximum power point tracking (MPPT) technique, is introduced in this paper. On the basis of the key finding that the end-to-end efficiency (<italic>η<sub>E-E</sub></italic>) is highly dependent on the amplitude of the input ripple of the charger (Δ<italic>V</italic><sub>IN</sub>) in the low-power region, the proposed AIR MPPT technique adjusts Δ<italic>V</italic><sub>IN</sub> to maximize <italic>η<sub>E-E</sub></italic>. Moreover, the minimum input power that allows the charger to maintain operation is enhanced by the proposed AIR MPPT technique. The proposed charger is implemented with 180-nm complementary metal oxide–semiconductor technology. An improvement of 21% in <italic>η<sub>E-E</sub></italic> is achieved with the proposed technique. Furthermore, the proposed technique enhances the minimum power by 7.5 <italic>μ</italic>W. The startup power and minimum power of the prototype are 37 and 6 <italic>μ</italic>W, respectively. The maximum <italic>η<sub>E-E</sub></italic> is 82%.
Reservoir Structure and Hydraulic Properties of the Campi Flegrei Geothermal System Inferred by Audiomagnetotelluric, Geochemical, and Seismicity Study

The Campi Flegrei caldera is a large volcanic complex lying in the Campanian Plain, Southern Italy. During its history the caldera experienced episodes of bradyseism and intense swarm seismicity. The mechanism leading to unrest episodes is still debated, and great efforts are ongoing to improve the knowledge of this structure and its evolution due to the high volcanic risk in such a densely populated area. Here we present a resistivity model from a two‐dimensional inversion of audiomagnetotelluric data acquired along an approximately 5.6‐km long profile crosscutting the Solfatara‐Pisciarelli district and the Agnano plain. The resistivity model shows (1) very low resistivity values confined in the first 500 m of depth both in correspondence of the Solfatara‐Pisciarelli districts and the Agnano depression; (2) a resistive plume that extends underneath the Solfatara crater down to 2,000‐ to 3,000‐m depth, and (3) an adjoining relative conductive unit eastward. We discuss the resistivity structures in a multidisciplinary framework integrating inedited geochemical and seismological observations with existing surface geology and subsurface information. The Solfatara‐Pisciarelli district and the Agnano plain, both being expression of intense hydrothermal activity, show different characteristics. Below the Solfatara‐Pisciarelli area, the shallow conductive zone is interpreted as a faulted clay cap that overlies a highly active vapor‐dominated reservoir characterized by a convective mechanism. Conversely, below the Agnano plain, a liquid phase seems to prevail in the reservoir. The spatiotemporal variations of seismicity imply a combined action of preexisting tectonic lineaments and fluid interaction between the gas/steam reservoir and the outflow zone.
Investigation and Calculation of Seismic Reliability of Structures

Recently, analysis and designing of the structures based on the Reliability theory have been the center of attention. Reason of this attention is the existence of the natural and random structural parameters such as the material specification, external loads, geometric dimensions etc. By means of the Reliability theory, uncertainties resulted from the statistical nature of the structural parameters can be changed into the mathematical equations and the safety and operational considerations can be considered in the designing process. According to this theory, it is possible to study the destruction probability of not only a specific element but also the entire system. Therefore, after being assured of safety of every element, their reciprocal effects on the safety of the entire system can be investigated. Keywords—Probability, Reliability, Statistics, Uncertainty
Active Cancellation of Vibration in Switched Reluctance Motor Using Mechanical Impulse Response Method

Vibration and acoustic noise are considered as major factors preventing the widespread use of switched reluctance motor (SRM) drives in industrial and commercial applications. In this paper, a new active vibration cancellation strategy for radial vibration is proposed based on the optimal current switching instants. The mechanical impulse response method has been used to estimate the radial vibration of the stator and an optimization routine was developed to define the optimal instants for phase current switching in such a way that the resulting vibration would cancel the vibration caused by prior switching. Experimental verification was conducted on an 8/6 SRM and the results show significant reduction in the stator radial vibration which in turn contributes to reduction of acoustic noise.
Nanoscale Sensor-Based Tunneling Carbon Nanotube Transistor for Toxic Gases Detection: A First-Principle Study

Carbon nanotube transistor is a spotlight components for toxic gas monitoring. In this regard, we present a new toxic gas molecules sensor base on a single-walled carbon nanotube transistor and use the Poisson and Schrodinger equations in a self-consistent manner and is modeled using non-equilibrium Green’s function. The reaction between gaseous molecules and single-walled carbon nanotubes can harness the charge and potential level inside the channel, which changes the electrical characteristics of the device. Investigations carried out over a 20-nm channel and at a temperature range between 200 and 400 K shows that the conductivity and current–voltage characteristic of the proposed Nano-sensor depend on temperature and gas conditions. According to the simulation results, the decrease in the temperature decreases the OFF-state current of the tunneling carbon nanotube field-effect transistor which leads to a decrease in the leakage current and the band-to-band tunneling. In addition, due to the temperature rise, the sensitivity is increased, and by increasing the dielectric constant of the gas, the on-state current of the device will also increase significantly. The maximum sensitivity for Carbonyl Chloride is 630 (nm/RIU).
Conditional risk measures relying on international accounting standards

This paper is devoted to the definition of an Expected -Shortfall -like Risk Measure, relying mainly on IAS39, being applied in EU. The connection between certain reporting variables and corporate capital requirements is a subject that is not entirely studied. Since the reporting variables are statistically dependent, we propose a model of Principal Components Regression for the assets’ forecast under a specific IAS. Consequently, a Coherent Risk Measure is needed for the calculation of the capital requirements which provide a securitization of the corporate assets. Mathematics Subject Classifications: 91G70; 62P05; 91B30
Mindfulness meditation is associated with decreases in partner negative affect in daily life

To date, very little research has examined the extrapersonal effects of mindfulness meditation practice. In this study, we investigated whether individual meditation practice exerted an influence on friends or romantic partners. Thirty-five dyads completed an eight-week single-subject protocol using an A-B-A-B design to compare non-meditation phases with meditation phases. One member of each pair was randomly assigned to meditate daily for 15-minutes during the B-phases of the study; the other dyad member did not meditate in either the A or B phases. Daily diaries for each participant assessed negative affect, positive affect, and facets of mindfulness. For participants in the intermittent meditation condition, meditation was associated with decreased negative affect, increased positive affect, and higher scores on the mindfulness facets of observing, describing, and nonreactivity to inner experience. Results further demonstrated that the negative affect of non-meditating partners decreased during the weeks that their partner meditated and was lower on days that their partner meditated. We did not find similar results for positive affect or mindfulness at the group level. Exploratory analyses suggested that the extrapersonal effects of meditation days on a partner’s negative affect might be stronger in romantic couples. This study indicates that 15-minutes of daily meditation in novice meditators can decrease the negative affect of relationship partners.
Numerical Simulation of Small Defects Flow Resistance Characteristics of Thin-walled Components of Titanium Alloy with Adding Material Manufacturing Based on CT Data

In order to study the influence of different types of small defects on the flow resistance characteristics of thin-walled components, the method of micro-focus industrial CT images and numerical simulation was used. According to CT imaging technology, there were mainly three types of small defects on the inner surface of the runner: surface pores, surface inclusions, and surface cracks. Extracting small defects, refining the local grid, and establishing the finite element analysis model. Through finite element calculation software Fluent, a low Reynolds number k-e model was adopted to carry out numerical simulation and analysis on the flow channels with three small defects on the inner surface. The results showed that under the same Reynolds number condition, the flow resistance coefficient of surface cracks was the largest, which was much larger than that of surface inclusions and surface pores. The resistance of surface pores and surface inclusions to the flow passage was similar and relatively small. The flow resistance coefficient of three kinds of minor defects decreased with the increase of Reynolds number. In the case of low Reynolds number, the separation of flow boundary layer occurred at the surface cracks.
Dynamic Shape Features Based Retinal Lesions Classification Using Random Forest Classifier

We describe a dynamic shape feature method to identify the lesion present in the retina. Diabetic retinopathy [DR] happens when these small blood vessels leak blood and different liquids. [4] This makes the retinal tissue swell, bringing about overcast or obscured vision. A PC supported screening and reviewing framework depends on the programmed discovery of injuries is required for Screening of diabetic retinopathy. DR show dim lesions, for example, Micro aneurysms (MA) and haemorrhages (HE) and bright lesions, such as, exudates and cotton-fleece spots. [6] The existing systems utilized normal strategies, for example, adaptive fuzzy thresholding [10] However, after finding the detected vessels, these lesions are lost and not recovered in resulting handling and gives less characterization precision. Automatic detection of both microaneurysms , haemorrhages and exudates in color fundus image is described and validated based on new set of shape features called dynamic shape features (Elongation, eccentricity, circularity, solidity, rectangularity) that do not require precise segmentation of the regions to be classified. These features represent the evolution of the shape during image flooding and allow discriminating between lesions and vessel segments. Finally machine learning technique random forest classifier is used to classify the diabetic retinopathy type based on dynamic shape features.
STRUCTURALLY SUPPORTED CELL-LADEN SCAFFOLDS FOR BONE TISSUE REGENERATION

Due to challenges associated with current clinical techniques used to treat bone defects, there has been an increased focus on finding a tissue engineered solution. However, while great progress in this field has been achieved, researchers have yet to suitably combine the proper biological and structural environments needed to serve as a complete bone tissue substitute that is comparable to modern clinical solutions. To achieve the goal of creating a model bone tissue substitute which could eventually serve as a viable therapy for bone trauma, be it caused by congenital medical conditions, age related diseases or high impact forces, three areas of the engineered construct architecture and composition were identified and studied in a successive fashion. First, a soft, biocompatible matrix within which cells could be encapsulated was studied, followed by an investigation on how to combine the soft matrix with a 3D printed structural frame. Finally, user-defined perfusable vasculature was added to the soft matrix in order to create a model bone tissue engineering construct capable of possible in vivo implantation. In Chapter 2 of this work, osteoblast-like human osteosarcoma cells (Saos-2) were encapsulated within gelatin methacrylate (GelMA) hydrogels and the effect of the hydrogel density on cellular morphology and mineralization was investigated. It was found that the less dense hydrogels allowed for increased cell viability and spreading, while the denser gels appeared to encourage more mineral deposition on the construct periphery. Building upon Chapter 2, Chapter 3 focused on the 3D printing of polycaprolactone (PCL) and composite PCL cages which could be combined with the soft GelMA matrices used for cellular encapsulation. It was found that while PCL and PCL composite cages could be reproducibly printed via a Makerbot 3D printer, the structural strengths did not surpass those of standard poly lactic acid (PLA) thermoplastic cages. Furthermore, it was demonstrated that the cell-laden GelMA hydrogels containing encapsulated Soas-2 cells could be incorporated with the 3D printed structures for potential bone tissue engineering applications. In Chapter 4, a simpler version of the cages produced in Chapter 3 were combined with sacrificial 3D printed polyvinyl alcohol (PVA) pipes and the dense cell-laden hydrogels investigated in Chapter 2 to create structurally supported, cell-laden hydrogel constructs. It was found that encapsulated cells could be stimulated to deposit mineral in the centers of the constructs via direct perfusion. However, in a larger version of the construct containing multiple pipes, mineralization was impeded due to diffusion issues caused by individual channel mineralization. Finally, in Chapter 5 future strategies to improve upon the structurally supported cell-laden hydrogels are discussed which would solve the issues found in Chapter 4. Additionally, potential in vivo applications for this system are explored. STRUCTURALLY SUPPORTED CELL-LADEN SCAFFOLDS FOR BONE TISSUE REGENERATION
Integrated Approach of Ergonomics and MCDM into Truck Drivers' Seat Comfort: A Case Study in Bangladesh

Seats are one of the most significant components for automotive vehicles. Prolonged driving a truck in Bangladesh is not so comfortable because no one design the seat properly considering anthropometric data. The improper seat design causes various health problems. Therefore, the improvement of seating posture is the urgency for reducing health issues. In this paper, a total of 120 Bangladeshi truck drivers were taken as sample for measuring anthropometric data. A comparison of health status between drivers and normal people showed that drivers suffer much than the control group. The relevant feedbacks required for the analysis were collected from the expert's opinion. The integrated approach (AHP-TOPSIS)found that among four health issues, back pain is more critical health issue associated with the existing seat dimension. Finally, the study suggested seat width as the most decisive design parameter on which designers should give much attention while designing truck drivers' seat.