Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Elastic Deflection of Single Point Cutting Tool and Optimization of Cutting Speed in Turning Operation by Using MADM Method

In the present paper, an analysis was carried out to optimize the cutting parameter i.e. speed in turning operation. The turning was done on a cylindrical rod with diameter and length of 35 mm and 300 mm respectively. The actual length of cutting was 100 mm. Five different cutting operations were taken place with five different cutting speeds i.e. 45, 105, 160, 270, 630 (in rpm) respectively. The surface roughness of the job and forces involved during cutting were measured through profilo-meter and dynamometer respectively. Also, the tool life was calculated by using Taylor’s tool life equation in each cutting condition. The elastic deflection of the tool in each cutting condition was simulated by using FUSION360 software. The optimum cutting speed was found out by applying multiple objective decision making (MADM) method.
Robust reliable H∞ optimization control for uncertain discrete‐time Takagi–Sugeno fuzzy systems with time‐varying delay

In this article, the problems of robust reliable H∞ optimization control for discrete‐time nonlinear systems with or without time‐delay subject to faults are investigated. A static state feedback controller is explored for Takagi–Sugeno fuzzy systems against nonlinear dynamics, exogenous disturbances, and model uncertainties. In contrast to the design of conventional controllers, the proposed controller is easier and more flexible. The Lyapunov function is utilized to assure the stability of the closed‐loop systems. Besides, linear matrix inequalities are utilized to derive the sufficient conditions by MATLAB toolbox. Finally, two simulation examples are shown to validate the feasibility of the suggested approach.
Identification of Innovativeness Provided by Logistics Service Providers

Purpose: The aim of the study is to identify the types of innovations implemented by logistics service providers (logistics operators 3PL and integrators 4PL), influencing the creation of logistics services in modern supply chains. Design/Methodology/Approach: The article presents the results of empirical research covering the issues of implementing innovative solutions in logistics services provided by service providers. Based on the results of the study, it was found that the dynamically changing conditions of the economic and political environment, progressing globalization and growing customer requirements have determined logistics service providers to go beyond the implementation of traditional, individual logistics services, e.g., such as transport, warehousing, to expand the range of offered and implemented services, thus implementing innovation in logistics services. Findings: It was identified that the role of logistics service providers offering a wide range of services for the proper integration and monitoring of logistics processes as part of outsourcing is played by logistics service provider operators ((3PL), logistics operators and integrators (4PL)). Practical Implications: Findings show a wide variation in the innovation implementation by logistics service providers. The main findings indicate that 3PL and 4PL companies are the leading service providers implementing innovations in the provided logistics services. No less important findings show that by far the largest group of the surveyed companies were suppliers of a few simple logistics services (transport, forwarding, distribution or supply logistics, etc.). Nevertheless, also this group is entering the next stage of improving and developing the offer of services and implementing innovative solutions to compete on the market. Originality/Value: In conclusion, it is worth emphasizing that the results of the study show that in the contemporary dynamically changing global economy, the activity in the field of innovation implemented by logistics service providers is becoming the leading driving force of competing not only individual enterprises but also supply chains and networks.
Setting up Reference Variants to Comply With Current Boundary Settings in Finite Set Model Predictive PMSM Control

Finite control set model predictive control (FCS-MPC), especially the reference-voltage-vector-based model predictive control (MPC) (RVV-MPC), considers a limited set of input vectors. However, the control performance is not satisfactory enough due to a severe lack of voltage input variants. In particular, additional restraints, such as limiting the currents within setting boundaries, could not be supported with RVV-MPC. In this article, to truly comply with the boundary settings, a reference variant FCS-MPC approach is introduced. In the proposed strategy, reference currents are considered under the maximum torque per current (MTPC) control. As boundary settings could not be supported in RVV-MPC, it is better to search for the optimal current reference that is feasible within the imposed boundaries. Therefore, rather than fixing the current reference, a well-considered neighborhood of the MTPC reference is introduced, and these variants are processed, resulting in a set of optimal candidate inputs. As multiple, but still finite, optimal solutions become possible, additional efforts can be made within the objective function to restrain the current and reduce the torque ripple. The size of the current reference space can be automatically adapted to generate current references that correspond to truly bounded current vectors. A trade-off is then made between control performance and meeting the boundary settings.
Authigenic Iron Sulfides Indicate Sea‐Level Change on the Continental Shelf: An Illustration From the East China Sea

Although sea‐level is the primary control over sedimentary architectures on continental shelves, deciphering such changes is still challenging, except for the easily recognized transgression‐regression cycles. This problem becomes more prominent in sedimentary units with relatively homogenous and fine‐grained lithologies that have been deposited over short periods. Here, we focus on a dominantly clayey silt section of a sediment core from the outer shelf of the East China Sea. Detailed rock magnetic and electron microscopy analyses indicate that authigenic greigite (Fe3S4) is the major magnetic component in an almost 4‐m‐thick interval that was deposited during the late Marine Isotope Stage (MIS) 3, while pyrite (FeS2) is enriched in the underlying middle MIS 3 sediments. According to microfossil analyses, the identified greigite formed in a prodelta setting that was affected by cold coastal currents after the middle MIS 3, when the Taiwan Warm Current and its associated upwelling were prevailing within a middle‐outer shelf setting favorable for pyrite formation. Large‐amplitude regression occurred subsequently during the MIS 2, limiting sulfate supply and favoring the greigite preservation. Our results, along with the previous studies, demonstrate that both the material and environmental conditions that are crucial to iron sulfide survival have been largely controlled by sea‐level change. Moreover, we make a preliminary proposition that a water depth range of 30–60 m is more likely to lead to the enrichment of greigite on continental shelves. We, therefore, provide a promising avenue for the assessment of sea‐level change on continental shelves over orbital and even suborbital timescales.
Effect of Structural Transformations on Precipitability and Polarity of Red Wine Phenolic Polymers

Condensed tannins and polymeric pigments are essential red wine components that contribute to color stability, taste, and mouthfeel. Phenolic polymers in red wine consist of flavan-3-ol monomers and anthocyanins and cause the perception of astringency. Due to the chemical heterogeneity of proanthocyanidin polymers, analytical tools to determine the polymers’ structural features are limited. Incorporation of anthocyanins increases the structural complexity even more and makes it almost impossible to assess the influence of structure on the perceived astringency. To better understand the structural diversity of red wine polymers, this study combines forced aging and FLASH-fractionation of polyphenolic wine extracts to reveal the relationship between phenolic polymers and two physicochemical properties: polarity and hydrophilicity. Red wine fractions were characterized using polarity, the octanol-water partitioning coefficient, protein precipitation assay, ultra high-performance liquid chromatography-mass spectrometry, and color. Tannin concentrations in wine decreased during forced aging and were constant in the corresponding extracts, suggesting alteration of the precipitation behavior. A simultaneous increase in precipitable polymeric pigments leads to the assumption that incorporating anthocyanins into tannin molecules alters their interactions with red wine polysaccharides and proteins, lowering tannin readings. Finding tannins and polymeric pigments in different FLASH-fractions indicates that precipitability of polymers is affected by their physicochemical properties, which in turn depend on the degree of polymerization as well as degree of pigmentation. The results of this study show that red wine astringency and its sub-qualities may be related to the increase in precipitable polymeric pigments during forced red wine aging and their putative enhanced interaction with wine polysaccharides, increasing understanding of astringency mechanisms.
A Multi-party Secure E-commerce Voting Scheme Based on SDGHV Algorithm

In the era of continuous development of e-commerce, the selection of e-commerce affects the development of e-commerce business and management efficiency. Based on the multi-party secure computing technology, this paper designs a set of the electronic voting scheme based on SDGHV multi-party secure data platform for the feedback on customers’ opinions after the goods are sold, which provides a useful reference for the selection of e-commerce products.
Subjective QoE assessment method for 360° videos

: This paper proposes a subjective assessment method for video quality and sense of presence for 360 ◦ videos. Since it is necessary to view 360 ◦ videos with a wide ﬁeld of view, we adopted a subjective assessment method that allows repeated viewing of 10 s long videos. First, by analysis of the subject’s observation behavior (i.e., head movement), it was clariﬁed that the appropriate number of observation repetitions was 2. The relationship between the video quality and the sense of presence was then quantiﬁed using the proposed method. Finally, we determined the number of subjects necessary to derive stable evaluation results.
Modelling of Unidirectional Oscillating Buoy Wave Energy Converter Based on Direct Mechanical Drive System Under Irregular Wave

The development of wave energy converters (WEC) is increasing over time with various designs. The need for a WEC design that emphasizes the level of simplicity, portability, and closeness of its implementation to the nearshore is quite interesting to discuss. One of the WECs that can meet these criteria is oscillating buoy based on a direct mechanical drive system. This research proposes the concept of oscillating buoy WEC based on a direct mechanical drive system, which is designed with a unidirectional gear system to be able to generate energy both in the upward and downward wave phases. The WEC is also making to produce high rotation on the output side from the small motion of the buoy, especially in the heave direction. Predicting the power generated by this concept is very interesting because up to now, there has not been sufficient analytical model to estimate the power generated by oscillating buoys WEC based on a direct mechanical drive system, especially under irregular waves. In this work, an analytical method is conducting to describe the interaction between the model and irregular waves from the JONSWAP model. Model interaction is simulating numerically using the MATLAB program. The buoy translational motion of the model in the heave direction, which is converting to electric power by increasing the rotation of the gearbox and the energy stored in the flywheel, can produce significant output power. In the future, the proposed model can be used to develop more feasible and efficient models of wave energy converters.
Buch 1.indb

In this paper, we evaluate growth stocks by modeling a company’s customer equity. We start with the observation that the number of customers in successful start-ups increases very quickly (exponentially) in the first few years. Then the customer base converges towards an industry average. On the other hand, the number of clients in poorly performing start-ups rapidly declines until bankruptcy occurs. These observations imply a “bathtub” shape to the probability distribution for the number of customers in the initial years, i.e., low probabilities for the number of clients close to average but high probabilities for extreme realizations. The valuation procedure we present here is based on a binomial scenario tree technique for the number of clients and the cash flow generated by each client. We show that the model can explain higher company values than can traditional net present value calculations. Furthermore, and in contrast to traditional valuation models, increasing the volatility in the change of the number of customers increases the value of each customer. Jel Classification: G3, M3.
Enhanced Protein Adsorption, Cell Attachment, and Neural Differentiation with the Help of Amine Functionalized Polycaprolactone Scaffolds

ABSTRACT Today, neurodegenerative diseases are very common among people. As a result, researchers are investigating methods for treatment of these diseases. One therapeutic approach is differentiating stem cells into neural cells to replace damaged areas of the brain. Cell attachment is the first, necessary step for the process of differentiation. Hence, we tried to enhance cell adhesion and proliferation of bone marrow stem cells on poly(ϵ-caprolactone) (PCL) scaffolds through modifying this substrate with amine functional groups. The presence of amine groups was confirmed by Fourier transform infrared spectrometry (FTIR). Protein adsorption was measured at 280 nm via UV-spectrometry. The proliferation of differentiated neurons was assessed by 3-(4,5-Dimethylthiazol-2-Yl)-2,5-Diphenyltetrazolium Bromide (a dye) and cresyl violet staining. Finally, the morphology of differentiated neurons was shown by scanning electron microscopy (SEM). Results showed that amine modification of PCL scaffolds enhanced protein absorption and, consequently, cell adhesion and proliferation.
Control of NOx by Positive and Negative Pulsed Corona Discharges

Pulse-induced plasma chemical process (PPCP) is a novel means of processing with a very large potential in various applications, including removal of NO, SO2, HCl, Hg vapor, and other gaseous pollutants from combustion gases, composition of new gaseous and solid substances, production of ultra-fine particulate materials, treatment of surfaces, etc. This is because PPCP can raise Linder normal pressure the electron temperature for production of active chemical species, such as OH radical, O, O3, O2, O2, N, N2, etc., without, raising ion temperature, which had been possible only by high frequency glow discharge under a low pressure condition. The authors developed a reliable nanosecond pulse high voltage generator allowing a continuous operation necessary to realize the PPCP as industrial devices. As one of its R&D program series the author investigated DeNOx and DeSOx of combustion gas by PPCP, and confirmed that DeNOx is possible by both positive and negative pulsings, and DeSOx only by positive pulsing. NO is oxidized by PPCP to NO, which is removed again by PPCP. The reaction speed by PPCP with positive pulsing is more than one order of magnitude higher than that by negative pulsing applicable to electrostatic precipitators. The reaction speed is greatly enhanced by raising the peak field intensity, which requires the use of very sharp pulse. The speed is also enhanced by raising pulse frequency, lowering gas temperature, and using sharp corona wires. The oxidation of NO and removal of NO2 can proceed without O2 and moisture, but it is greatly enhanced by them. The addition of NH3 enhances also NO2-removal, possibly by its NO2-scavenging effect from gas phase, while it does not enhance NO-oxidation. The combination of PPCP with the Electron Beam DeNOx and DeSOx does not produce non-linear enhancing effect other than the independent any effect by PPCP alone.
Formation of the first galaxies in the aftermath of the first supernovae

We perform high-resolution cosmological hydrodynamic simulations to study the formation of the first galaxies that reach the masses of 108 − 9 h−1 M⊙ at z = 9. The resolution of the simulations is high enough to resolve minihaloes and allow us to successfully pursue the formation of multiple Population (Pop) III stars, their supernova (SN) explosions, resultant metal-enrichment of the inter-galactic medium (IGM) in the course of the build-up of the system. Metals are ejected into the IGM by multiple Pop III SNe, but some of the metal-enriched gas falls back on to the halo after $\gtrsim 100~\rm Myr$. The star formation history of the first galaxy depends sensitively on the initial mass function (IMF) of Pop III stars. The dominant stellar population transits from Pop III to Pop II at z ∼ 12 − 15 in the case of power-law Pop III IMF, dn/dM∝M−2.35 with the mass range 10 − 500 M⊙. At z ≲ 12, stars are stably formed in the first galaxies with a star formation rate of ∼10−3-10−1 M⊙/yr. In contrast, for the case with a flat IMF, gas-deprived first galaxies form due to frequent Pop III pair-instability SNe, resulting in the suppression of subsequent Pop II star formation. In addition, we calculate UV continuum, Lyα- and Hα-line fluxes from the first galaxies. We show that the James Webb Space Telescope will be able to detect both UV continuum, Lyα and Hα line emission from first galaxies with halo mass ≳ 109 M⊙ at z ≳ 10.
Broadband Back Action Cancellation in a Dichromatic Variational Measurement

Quantum back action imposes fundamental sensitivity limits to the majority of quantum measurements. The effect results from the unavoidable contamination of the measured parameter with the quantum noise of a meter. Back action evading measurements take advantage of the quantum correlations introduced by the system under study to the meter and allow overcoming the fundamental limitations. The measurements are frequently restricted in their bandwidth due to a finite response time of the system components. Here we show that probing a mechanical oscillator with a dichromatic field with frequencies separated by the oscillator frequency enables independent detection and complete subtraction of the measurement noise associated with the quantum back action.
Prediction of Ultrasonic Guided Wave Propagation in Solid-fluid and their Interface under Uncertainty using Machine Learning

Structural health monitoring (SHM) systems use the non-destructive testing principle for damage identification. As part of SHM, the propagation of ultrasonic guided waves (UGWs) is tracked and analyzed for the changes in the associated wave pattern. These changes help identify the location of a structural damage, if any. We advance existing research by accounting for uncertainty in the material and geometric properties of a structure. The physics model used in this study comprises of a monolithically coupled system of acoustic and elastic wave equations, known as the wave propagation in fluid-solid and their interface (WpFSI) problem. As the UGWs propagate in the solid, fluid, and their interface, the wave signal displacement measurements are contrasted against the benchmark pattern. For the numerical solution, we develop an efficient algorithm that successfully addresses the inherent complexity of solving the multiphysics problem under uncertainty. We present a procedure that uses Gaussian process regression and convolutional neural network for predicting the UGW propagation in a solid-fluid and their interface under uncertainty. First, a set of training images for different realizations of the uncertain parameters of the inclusion inside the structure is generated using a monolithically-coupled system of acoustic and elastic wave equations. Next, Gaussian processes trained with these images are used for predicting the propagated wave with convolutional neural networks for further enhancement to produce high-quality images of the wave patterns for new realizations of the uncertainty. The results indicate that the proposed approach provides an accurate prediction for the WpFSI problem in the presence of uncertainty.
Point Cloud Audio Processing

Most audio processing pipelines involve transformations that act on fixed-dimensional input representations of audio. For example, when using the Short Time Fourier Transform (STFT) the DFT size specifies a fixed dimension for the input representation. As a consequence, most audio machine learning models are designed to process fixed-size vector inputs which often prohibits the repurposing of learned models on audio with different sampling rates or alternative representations. We note, however, that the intrinsic spectral information in the audio signal is invariant to the choice of the input representation or the sampling rate. Motivated by this, we introduce a novel way of processing audio signals by treating them as a collection of points in feature space, and we use point cloud machine learning models that give us invariance to the choice of representation parameters, such as DFT size or the sampling rate. Additionally, we observe that these methods result in smaller models, and allow us to significantly subsample the input representation with minimal effects to a trained model performance.
Assessing Dialogue Systems with Distribution Distances

An important aspect of developing dialogue systems is how to evaluate and compare the performance of different systems. Existing automatic evaluation metrics are based on turn-level quality evaluation and use average scores for system-level comparison. In this paper, we propose to measure the performance of a dialogue system by computing the distribution-wise distance between its generated conversations and real-world conversations. Specifically, two distribution-wise metrics, FBD and PRD, are developed and evaluated. Experiments on several dialogue corpora show that our proposed metrics correlate better with human judgments than existing metrics.
Probing the Spins of Supermassive Black Holes with Gravitational Waves from Surrounding Compact Binaries

Merging compact black hole (BH) binaries are likely to exist in the nuclear star clusters around supermassive BHs (SMBHs), such as Sgr A*. They may also form in the accretion disks of active galactic nuclei. Such compact binaries can emit gravitational waves (GWs) in the low-frequency band (0.001–1 Hz) that are detectable by several planned space-borne GW observatories. We show that the angular momentum vector of the compact binary ( L in) may experience significant variation due to the frame-dragging effect associated with the spin of the SMBH. The dynamical behavior of L in can be understood analytically as a resonance phenomenon. We show that the rate of change of L in encodes the information on the spin of the SMBH. Therefore, detecting GWs from compact binaries around SMBHs, particularly the modulation of the waveform associated with the variation of L in, can provide a new probe of the spins of SMBHs.