Single Process Research Articles

Accelerating Loop-Oriented RTL Simulation With Code Instrumentation

The hardware description of circuits usually contains many loops. Register Transfer Level (RTL) simulation is a critical step to verify the correctness of circuits and is time-consuming. Thus, it is necessary to speed up its process. However, the speedup of existing RTL simulation acceleration techniques is usually small. Although the speedup of hardware acceleration is large, the hardware cost is high. Some methods utilize performance models without performing RTL simulation to obtain rough simulation performance and have large speedup. However, they do not support functional verification. In order to address the problems, we propose a loop-oriented RTL simulation acceleration approach based on code instrumentation for designs synthesized by High-Level Synthesis. Our approach reduces the RTL simulation time by skipping a large number of repeated loop iterations, and maintains high accuracy for the prediction of the number of cycles by reserving some loop iterations. We establish a performance prediction model and an interval value formula for skipping loop iterations. We conduct experiments on the MachSuite benchmark. The results show that for the RTL simulation of single data processing and batch data processing, the average speedup of our approach can reach 7.49× and 43.3×, respectively, and the average prediction errors of the number of cycles are 1.71% and 1.06%, respectively. It also reveals that the interval value obtained by our approach for skipping loop iterations can quickly and effectively balance between the accuracy of prediction of the number of cycles and speedup. Compared to the state-of-the-art approach ESSENT, the speedup of our approach is better and the accuracy of prediction of the number of cycles remains at the same level as that of performance models.

HTA191 Discussion of Health Inequalities in the NICE Single Technology Appraisal Process: A Review of Recent Submissions in NHS England Core20PLUS5 Focus Clinical Areas

HTA191 Discussion of Health Inequalities in the NICE Single Technology Appraisal Process: A Review of Recent Submissions in NHS England Core20PLUS5 Focus Clinical Areas

Application of novel constrained friction processing method to produce fine grained biomedical Mg-Zn-Ca alloy

In order to obtain Mg alloys with fine microstructures and high mechanical performances, a novel friction-based processing method, name as “constrained friction processing (CFP)”, was investigated. Via CFP, defect-free Mg-Zn-Ca rods with greatly refined grains and high mechanical properties were produced. Compared to the previous as-cast microstructure, the grain size was reduced from more than 1 mm to around 4 µm within 3 s by a single process cycle. The compressive yield strength was increased by 350% while the ultimate compressive strength by 53%. According to the established material flow behaviors by “tracer material”, the plastic material was transported by shear deformation. From the base material to the rod, the material experienced three stages, i.e. deformation by the tool, upward flow with additional tilt, followed by upward transportation. The microstructural evolution was revealed by “stop-action” technique. The microstructural development at regions adjacent to the rod is mainly controlled by twinning, dynamic recrystallization (DRX) as well as particle stimulated nucleation, while that within the rod is related to DRX combined with grain growth.

Annealing‐Free Ohmic Contacts to n‐Type GaN via Hydrogen Plasma‐Assisted Atomic Layer Deposition of Sub‐Nanometer AlOx

AbstractA plasma‐assisted atomic layer deposition (PE‐ALD) process is reported for creating ohmic contacts to n‐type GaN that combines native oxide reduction, near‐surface doping, and encapsulation of GaN in a single processing step, thereby eliminating the need for both wet chemical etching of the native oxide before metallization and thermal annealing after contact formation. Repeated ALD cycling of trimethyl aluminum (TMA) and high‐intensity hydrogen (H2) plasma results in the deposition of a sub‐nanometer‐thin (≈8 Å) AlOx layer via the partial transformation of the GaN surface oxide into AlOx. Hydrogen plasma‐induced nitrogen vacancies in the near‐surface region of GaN serve as shallow donors, promoting efficient out‐of‐plane electrical transport. Subsequent metallization with a Ti/Al/Ti/Au stack results in low contact resistance, ohmic behavior, and smooth morphology without requiring annealing. This electrical contracting approach thus meets the thermal budget requirements for Si‐based complementary metal–oxide–semiconductor structures and can facilitate the design and fabrication of advanced GaN‐on‐Si heterodevices.

DeepScraper: A complete and efficient tweet scraping method using authenticated multiprocessing

In this paper, we propose a scraping method for collecting tweets, which we call DeepScraper. DeepScraper provides the complete scraping for the entire tweets written by a certain group of users or them containing search keywords with a fast speed. To improve the crawling speed of DeepScraper, we devise a multiprocessing architecture while providing authentication to the multiple processes based on the simulation of the user access behavior to Twitter. This allows us to maximize the parallelism of crawling even in a single machine. Through extensive experiments, we show that DeepScraper can crawl the entire tweets of 99 users, which amounts to 5,798,052 tweets while Twitter standard API can crawl only 243,650 tweets of them due to the constraints of the number of tweets to scrape. In other words, DeepScraper could collect 23.7 times more tweets for the 99 users than the standard API. We also show the efficiency of DeepScraper. First, we show the effect of the authenticated multiprocessing by showing that it increases the crawling speed from 2.03∼10.57 times as the number of running processes increases from 2 to 32 compared to DeepScraper with a single process. Then, we compare the crawling speed of DeepScraper with the existing studies. The result shows that DeepScraper is compared to even Twitter standard APIs and Twitter4J while DeepScraper can scrape much more tweets than them. Furthermore, DeepScraper is much faster than Twitter Scrapy roughly 3.69 times while both can scrape the entire tweets for the target users or keywords.

Configuration-sensitive face-body interactions in primate visual cortex

Traditionally, the neural processing of faces and bodies is studied separately, although they are encountered together, as parts of an agent. Despite its social importance, it is poorly understood how faces and bodies interact, particularly at the single-neuron level. Here, we examined the interaction between faces and bodies in the macaque inferior temporal (IT) cortex, targeting an fMRI-defined patch. We recorded responses of neurons to monkey images in which the face was in its natural location (natural face-body configuration), or in which the face was mislocated with respect to the upper body (unnatural face-body configuration). On average, the neurons did not respond stronger to the natural face-body configurations compared to the summed responses to their faces and bodies, presented in isolation. However, the neurons responded stronger to the natural compared to the unnatural face-body configurations. This configuration effect was present for face- and monkey-centered images, did not depend on local feature differences between configurations, and was present when the face was replaced by a small object. The face-body interaction rules differed between natural and unnatural configurations. In sum, we show for the first time that single IT neurons process faces and bodies in a configuration-specific manner, preferring natural face-body configurations.

Multiple staging of pressure retarded osmosis: Impact on the energy generation

As pressure retarded osmosis (PRO) is getting more attention for sustainable energy generation, further investigation to enhance its efficiency is required. Applying a multiple-stage PRO scenario is one suggestion to boost the generated energy in the PRO process. This research evaluates the benefit of multiple stages of pressure retarded osmosis on specific energy generation. Single, dual, ternary, and quaternary pressure retarded osmosis stages were investigated for power generation using four membrane modules in the PRO process. Eight designs were proposed to cover the arrangement of the membrane modules in a single, dual, ternary and quaternary PRO process and estimate the net-specific energy generation of pressure retarded osmosis. For each design, the variation in the total energy input and the total energy output of single and multistage pressure retarded osmosis processes were calculated. The water flux and the power density enhanced with the number of stages for the investigated multistage PRO scenarios. The maximum water flux and power density resulted in four PRO stages of values equal to 6 L/m2.h and 15 W/m2, respectively. For the Dead Sea-reverse osmosis brine salinity gradient, a 33.96 % rise in the net specific energy generation is observed in the quaternary-stages pressure retarded osmosis scenario. The Dead Sea and wastewater salinity gradients produced the highest net specific energy generation of 0.82 kW.h/m3 over the other investigated types of salinity gradients.

Tandem Synthesis of Valuable Chemicals via Electrocatalysis

AbstractTandem synthesis, the integration of multiple chemical transformations into a single process, has emerged as a promising strategy to streamline the synthesis of valuable chemicals. Meanwhile, electrocatalysis has garnered significant attention as a versatile tool for driving various chemical reactions through the application of electrical energy. This concept highlights the synergistic potential of tandem synthesis and electrocatalysis, focusing on their combined applications in the efficient production of valuable chemicals. The inherent selectivity of electrocatalytic processes, coupled with the ability to manipulate reaction pathways using precise control of electrode potentials, offers a platform for designing intricate tandem reactions. Through a comprehensive survey of the literature, key examples are showcased where tandem electrocatalytic processes have enabled the conversion of simple starting materials into valuable target molecules, minimizing waste and energy consumption. Mechanistic insights are discussed that underpin these reactions and perspectives on the future directions and challenges in this rapidly evolving field are provided.

A loading contribution degree analysis-based strategy for time-variant reliability analysis of structures under multiple loading stochastic processes

This paper proposes a new single-loop method based on the loading contribution degree analysis (LCDA) and decoupling strategy for analyzing the time-variant reliability of structures considering multiple loading stochastic processes and degradation processes. In this method, the loading stochastic processes are first discretized using the expansion optimal linear estimation method. Then, the LCDA is carried out to obtain a total weighted loading stochastic process used to accurately reflects the structural response, thus constructing a single loading stochastic process analysis problem. Subsequently, a decoupling strategy is applied to decouple the degradation processes and the total weighted loading stochastic process to obtain the equivalent extreme-value limit state function (EEV-LSF) of the structure. Finally, an efficient probability distribution reconstruction tool is applied to derive the probability density function of EEV-LSF. Notably, the proposed LCDA can avoid the calculation of the response time series of a structure under the input loading stochastic processes, providing a novel perspective to simplify the calculation of structural extreme-value response. Additionally, the proposed method requires only one round of deterministic analysis to obtain the structural time-variant failure probability at the specified time, constructing an efficient single-loop analysis method. Three numerical examples are used to validate the proposed method.

Identification of Aggregation Processes in Hexamethylenetetramine Aqueous Solutions: A Comprehensive Raman and Acoustic Spectroscopic Study Combined with Density Functional Theory Calculations

Raman scattering has been employed to study in detail the concentration dependence of the vibrational modes for hexamethylenetetramine (HMTA) aqueous solutions. The formation of protonated and/or aggregated species has been clarified by comparing the experimental with the theoretically predicted vibrational spectra by means of quantum mechanical calculations. The analysis has shown that the vibrational modes of the solutions arise from a contribution of the vibrational modes of the HMTA self-aggregates and hetero-aggregates of HMTA with water molecules that are formed in the low- and intermediate-concentration regions, respectively. The protonation of HMTA is ruled out due to the large differences between the experimental and the theoretically calculated spectra of the protonated molecules of HTMA in the fingerprint region. In the low-concentration solutions, the hetero-aggregation reaction of HMTA with water is the dominant mechanism, while at higher concentrations, a self-aggregation mechanism occurs. Ultrasonic absorption and velocity measurements were carried out for hexamethylenetetramine aqueous solutions. The acoustic spectra reveal the presence of only one single Debye-type relaxation process that is assigned to the aggregation mechanism of HMTA. The sound absorption data follow two different dependencies on the HMTA mole fraction. The crossover 0.018 mole fraction signifies two separate regions with distinct structural characteristics. The relaxation mechanism observed in dilute solutions was attributed to hetero-association of HMTA with water molecules, while at higher concentrations, the observed relaxation process was assigned to the self-association reaction of HMTA molecules. This structural transformation is also reflected in several physicochemical properties of the system, including the kinematic viscosity, the mass density, the sound speed and the adiabatic compressibility of the HMTA aqueous solutions. The combination of vibrational and acoustic spectroscopies with molecular orbital calculations allowed us to disentangle the underlying processes and to elucidate the observed relaxation mechanism in the HMTA aqueous solutions.

D2W Hybrid Bonding Using High Accuracy Carrier Solutions for 3D System Integration

Die segmentation and chiplet integration is gaining considerable industry momentum and seen as one important integration process for 3D systems on chips. As interconnect pitches in 3D packaging become tighter with each new product generation, wafer and die bond alignment and overlay processes must also scale accordingly. 10µm pitch is setting a junction in interconnect technology. On the one hand, it is seen as the inflection point of hybrid bonding. At the same time, these extremely tight pitches enable functional partitioning of device functions onto different dies (chiplets) using die-to-wafer (D2W) hybrid bonding or wafer-to-wafer (W2W) hybrid bonding. D2W hybrid bonding is evaluated in different integration processes. While direct placement of fusion bondable dies from a film frame is researched intensely, another option is to reconstitute dies on a carrier wafer and collectively transfer the dies using W2W bonding equipment. In the presentation we will elaborate on all aspects of the die to wafer bonding for a successful single chip type process towards a full system transfer approach. We will show alignment data of the dies on the transfer carrier targeting a pick and place accuracy of <500nm and report on the alignment evolution during the process until final annealing. Further elaboration will be done on different die sizes and die thicknesses. The die flatness and high variation over the whole wafer will be evaluated according to the die dimensions. Most importantly the die high variation and planarity will be shown for different carrier systems such as thermoset and thermoplastic materials, evaluating the bonding performance in terms of alignment propagation bond line integrity.

Pragmatic Ambiguity, Implicatures, and Translation1

AbstractThe goal of this work is to put forward a pragmatic and translational framework for analysing target texts (TT) and source texts (ST) containing conversational implicatures that lead to pragmatic ambiguity. Ambiguity, sensu lato, is deemed to be related to indeterminacy and vagueness. Nevertheless, in the strict sense, ambiguity is understood as ‘more than a single processing instruction for a given utterance’. More specifically, pragmatic ambiguity arises whenever differences in cultural conventions between SL speakers and TL speakers lead to differences in the existence, meaning and salience of implicatures among ST and TT. Using real translation cases selected from a purpose‐built corpus containing fiction written and oral texts, we show which pragmatic ambiguities translators come across, and how translation techniques are used, either to maintain ambiguity or to select one intended processing instruction.

Application of Decision Tree Classification Algorithm in Quality Assessment of Distance Learning in Colleges

INTRODUCTION: The quality assessment technology of distance education in colleges and universities, as the critical technology for identifying the quality of distance education in colleges and universities, is conducive to the improvement of the quality of distance teaching and the progress of the existing means and methods of distance education, which makes the means of distance teaching in colleges and universities rich in science.
 OBJECTIVES: Aiming at the evaluation methods of higher education institutions, there are problems such as insufficient objectivity and comprehensiveness of the evaluation system, single process, and inadequate quantitative analysis.
 METHODS:Proposes a decision tree and intelligent optimization algorithm for the college distance teaching quality assessment method. Firstly, the kernel principal component analysis method is used to carry out dimensionality reduction analysis on the index system of college distance teaching quality assessment; then, the decision tree parameters are optimized through the marine predator algorithm to construct a college distance teaching quality assessment model; finally, the robustness and efficiency of the proposed method are verified through simulation experimental analysis.
 RESULTS: The results show that the proposed method improves the accuracy of the assessment model.
 CONCLUSION: The problem of insufficient objective and scientific evaluation and low precision of distance teaching quality assessment methods in colleges and universities is solved.

Photo-electrodes decorated with carbon quantum dots: Efficient dye-sensitized solar cells

In this study, the blue and green carbon quantum dots (CQDs) are synthesized and applied to the photo-electrodes of dye-sensitized solar cells (DSSCs). The DSSCs exhibited high power conversion efficiency because of the conversion of ultraviolet to the visible region in photo-anode, and good catalytic activity in the photo-cathode. The blue color CQDs (BCQDs) and green color CQDs (GCQDs) are synthesized from the citric acid in a single pot process. We examine the influence of both CQDs decorated on photo-anode and photo-cathode and both photo-electrodes on the photovoltaic performance of the DSSCs. Furthermore, the DSSCs are studied by electrochemical impedance spectroscopy, cyclic voltammetry, and Tafel polarization data to study the charge transfer kinetics. The better performance observed from the DSSCs due to enhanced charge carrier collection through the CQDs. The photovoltaic results of DSSCs shown that the best efficiency shown by DSSC, which fabricated by both photo-electrodes decorated by CQDs.

Uncertainty-driven trustworthy defect detection for high-resolution powder bed images in selective laser melting

Selective laser melting (SLM) is known as one of the most promising metal additive manufacturing technologies, and how to ensure its consistent quality is still a main challenge, which urgently needs to be addressed. The metal powder spreading quality, as the first stage of SLM, has a direct impact on the subsequent forming and it is necessary to be monitored. However, existing deep learning-based methods for monitoring powder spreading quality often suffer from the problem of unreliability. The high-resolution property of powder bed images is often ignored, and the predicted results are not well evaluated. To address the above issues and achieve trustworthy defect detection, this paper proposes an uncertainty-driven trustworthy defect detection method for high-resolution powder bed images in SLM. A super resolution module based on ISDNet is first proposed to refine the upsampling process. Checkpoint ensemble is adopted for better achieving model uncertainty estimation only requiring a single training process, feature reuse helps reduce the computational load, and temperature scaling is used to further calibrate each ensemble member to get a more precise uncertainty. Besides, we design an uncertainty-driven model improvement method to further improve defect detection performance for regions with high uncertainty. Experiments demonstrate the effectiveness of our proposed method, and our work achieves a trustworthy defect detection for high-resolution powder bed images in SLM.

Improved mechanical properties of multiwalled carbon nanotube reinforced acrylonitrile butadiene styrene nanocomposites prepared by twin screw extruder

Dispersion of carbon nanotubes in a thermoplastic polymer matrix is a big challenge in the research community. In the present study, multiwalled carbon nanotubes (MWCNTs) were dispersed in acrylonitrile butadiene styrene (ABS) polymer by a twin screw extruder to improve mechanical and thermal properties. The desired ratio of MWCNT in ABS (1, 2, and 3 wt.%) were dispersed through single and double extrusion processes by a twin screw extruder. The test specimens of produced composites and pure ABS materials were prepared by micro-injection molding. The nanocomposites’ mechanical and thermal properties were investigated and compared with pure ABS. It has been found that the tensile strength has increased significantly for single-extruded and double-extruded composites. A comparative study of MWCNTs reinforced ABS nanocomposites and pure ABS was carried out using thermogravimetric analysis, Fourier's transform infrared, X-ray diffraction, and Scanning electron microscopy. It was found that the microhardness has also increased for single- and double-extruded nanocomposites in comparison to pure ABS.

Stability of cylindrical anisotropic composite shells under torsion in a three-dimensional formulation

The article presents a calculation of the stability of non-thin cylindrical anisotropic layered shells under the action of end torsional moments in a spatial formulation. The anisotropy of the used material is characterized by one plane of elastic symmetry of characteristics. This is caused by the mismatch between the main elastic directions of the composite fibrous orthotropic material and the axes of the curvilinear cylindrical coordinate system.
 A three-dimensional inhomogeneous system of partial differential equations describing the subcritical stress-strain state within the linear theory of elasticity is derived using the Hu-Washizu variational principle. Reducing the dimension of the problem under consideration from three-dimensional to one-dimensional is carried out by taking into account the axial symmetry of the deformation of the cylindrical shell and using the method of straight lines along the generatrix.
 Based on the modified Hu-Washizu variational principle, a three-dimensional system of homogeneous partial differential stability equations is derived within the framework of the spatial theory of elasticity. The reduction of a three-dimensional system to a one-dimensional one is carried out along the generatrix and in the circular direction - by expanding the components of stresses and displacements into double trigonometric series when applying the procedure of the Bubnov-Galorkin method, as well as taking into account the periodicity of the resolving functions.
 An algorithm has been developed, implemented in the form of application software packages for PCs. In it, in a single computational process using the numerical method of discrete orthogonalization in the direction normal to the middle surface of the shell, the establishment of the parameters of the subcritical stress-strain state and the solution on this basis of stability problems for non-thin anisotropic cylindrical shells under the influence of torsion are combined.
 The problem of the influence on the stability of an anisotropic cylindrical non-thin shell of an increase in the number of cross-reinforced layers depending on the angle of rotation of the main directions of elasticity of the material and the direction of application of torque is considered. The obtained results of stability calculations according to the proposed approach were compared with critical torsion loads calculated using an orthotropic model for calculating anisotropic shells. It is shown that for single-layer cylindrical shells the difference between the compared results reaches 69%. An increase in the number of cross-reinforced layers leads to a decrease in this discrepancy, and with seven to eight layers, the difference between the critical loads obtained using the described approach and the orthotropic model is within 5%. This result is consistent with those obtained using classical or refined theories of calculations of both thin and non-thin anisotropic cylindrical shells.

Critical evaluation of key parameters in single particle ICP-MS data processing for the correct determination of platinum nanoparticles in complex environmental and biological matrices.

There is an urgent need for the harmonization of critical parameters in single particle inductively coupled plasma mass spectrometry (SP-ICP-MS) and they have been deeply studied and optimized in the present work using platinum nanoparticles (PtNPs) as a representative case of study. Special attention has been paid to data processing in order to achieve an adequate discrimination between signals. Thus, a comparison between four different algorithms has been performed and the method for transport efficiency calculation has also been thorougly evaluated (finding the use of a well-characterized solution of the same targeted analyte (30nm PtNPs) as adequate). The best results have been obtained after the application of a deconvolution approach for the data processing and using 5ms as dwell time and 40,000 data points for data acquisition. Under the optimized conditions, a correct discrimination between NP events and background signal up to 100 or 750ng L-1 of added ionic Pt was reached for 30 and 50nm PtNPs, respectively. The suitability of the developed method for the characterization of PtNPs in relevant environmental (water samples) and biological (cell culture media) matrices has also been demonstrated.

The Use of High‐Temperature Semi‐Batch Radical Polymerization to Synthesize Acrylate Based Macromonomers and Structured Copolymers

AbstractA high‐temperature starved‐feed semi‐batch operating policy is developed to produce p(acrylates) with high macromonomer content, taking advantage of side reactions inherent to acrylate radical polymerization. This operating strategy results in significantly higher macromonomer content for the polymerization of isobornyl acrylate (iBoA) versus n‐butyl acrylate (BA) under identical operating conditions. This is because steric hindrance favors fragmentation (i.e., terminal double bond (TDB) formation) over addition (i.e., short‐chain or long‐chain branch (LCB) formation), thus increasing the p(iBoA) TDB content and decreasing polymer dispersity. The p(iBoA) macromonomer solution serves as an excellent addition‐fragmentation agent to polymerize a second monomer in a single pot process controlled by sequential feeding, as demonstrates by the production of iBoA‐BA block and comb copolymer structures at different temperatures and macromonomer concentrations. The incorporation of the p(iBoA) macromonomer into a copolymer product is verified by various techniques, including polymer fractionation followed by TDB, composition, and molar mass analyses. Reaction temperature plays a key role in determining whether a blocky versus comb copolymer structure is produced. The ability to synthesize block and comb copolymers by radical polymerization without a mediating agent offers the potential to efficiently produce structured copolymers for industrial applications.

Distyrylbenzene-based semi-conducting molecular material for OLED applications: Synthesis, characterization and TD-DFT calculations

New semi-conducting molecular materiel (M-DSB) based on the distyrylbenzene π-conjugated system was synthesized via the Wittig reaction. The structural properties of M-DSB, displaying three different stereoisomers E-E, Z-Z and Z-E, were investigated through density functional theory (DFT) optimization. The detailed TD-DFT analysis provided insights into the structure-property relationships and revealed good agreement with experimental data. This photoactive material exhibits nearly the same UV–visible spectra in dilute solution and as solid thin film, with a maximum absorption at 363 nm and an optical gap of 2.99 eV. A broad and red-shifted photoluminescence spectrum was obtained in the solid state with blue emission compared to the solution which shows purplish blue emission with relatively narrow emission. The HOMO/LUMO energy levels were calculated by cyclic voltammetry measurements and indicate a p-type semiconductor material. The temperature and frequency dependence of the conductivity shows an activation energy value of about 0.89 eV for the M-DSB thin layer. Impedance spectroscopy of the ITO/M-DSB/Al device indicates a typical behavior of a single relaxation process and confirms that the electrical response becomes faster and the mobility of the charge carriers is enhanced by increasing the temperature.