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Gravity-driven powder flow and the influence of external vibration on flow characteristics

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Particuology 2024年第5期88卷 201-209页

作者： Muhammad Shahid Ansari Ratna Kumar Annabattula Sathyan Subbiah department of Mechanical Engineering Indian Institute of Technology MadrasChennai 600036India

The controlled and homogeneous flow of dry granular powders through hoppers is essential for applications,namely,packaging of food grains,fertilizers and additive manufacturing processes such as directed energy deposition for better product *** of the major issues encountered in the granular flows through hoppers is flow stagnation due to the well-known arching ***-assisted granular flow through hoppers is one of the mechanisms used for better mass flow *** this work,the influence of external mechanical vibration on the powder flow is investigated experimentally and using discrete element ***,the mass flow rate through the hopper increases with an increase in vibration amplitude and then decreases,signifying the existence of an optimal amplitude of *** DEM simulations explained the underlying mechanisms for the existence of an optimal amplitude of vibration corresponding to the maximum mass flow rate.A range of vibration amplitudes from 0 mm to 3.5 mm is used to study the flow behaviour;the maximum flow of around 33 g/s to 35 g/s is observed for 0.75 mm to 1.25 mm vibration amplitude for the hopper-particle combination studied in this *** work also reports the influence of vibration frequency,hopper,and particle dimension on the flow *** research facilitates the effective use of mechanical vibration to enhance powder flow that can further be extended to non-spherical and multi-material particles.

关键词： Discrete element method Flow rate Granular flow Path tracking Vibration intensity

Magnetic field regression using artificial neural networks for cold atom experiments

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Chinese Physics B 2024年第2期33卷 46-51页

作者：陈子霆黃建陶 Bojeong Seo 黄明琛 Mithilesh K.Parit 何逸飞甄浩廷 Jensen Li Gyu-Boong Jo department of Physics The Hong Kong University of Science and TechnologyKowloon 999077China

Accurately measuring magnetic fields is essential for magnetic-field sensitive experiments in areas like atomic,molecular,and optical physics,condensed matter experiments,and other ***,since many experiments are often conducted in an isolated environment that is inaccessible to experimentalists,it can be challenging to accurately determine the magnetic field at the target ***,we propose an efficient method for detecting magnetic fields with the assistance of an artificial neural network(NN).Instead of measuring the magnetic field directly at the desired location,we detect fields at several surrounding positions,and a trained NN can accurately predict the magnetic field at the target *** training,we achieve a below 0.3%relative prediction error of magnetic field magnitude at the center of the vacuum chamber,and successfully apply this method to our erbium quantum gas apparatus for accurate calibration of magnetic field and long-term monitoring of environmental stray magnetic *** demonstrated approach significantly simplifies the process of determining magnetic fields in isolated environments and can be applied to various research fields across a wide range of magnetic field magnitudes.

关键词： ultracold gases trapped gases measurement methods and instrumentation

DIR:Dynamic Request Interleaving for Improving the Read Performance of Aged Solid-State Drives

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Journal of Computer Science & technology 2024年第1期39卷 82-98页

作者：聂世强张驰伍卫国 department of Computer Science and technology Xi'an Jiaotong UniversityShaanci 710049China

Triple-level cell(TLC)NAND flash is increasingly adopted to build solid-state drives(SSDs)for modern computer *** TLC NAND flash effectively improves storage density,it faces severe reliability issues;in partic-ular,the pages exhibit different raw bit error rates(RBERs).Integrating strong low-density parity-check(LDPC)code helps to improve reliability but suffers from prolonged and proportional read latency due to multiple read retries for worse *** straightforward idea is that dispersing page-size data across several pages in different types can achieve a low-er average RBER and reduce the read ***,directly implementing this simple idea into flash translation lay-er(FTL)induces the read amplification issue as one logic page residing in more than one physical page brings several read *** this paper,we propose the Dynamic Request Interleaving(DIR)technology for improving the performance of TLC NAND flash-based SSDs,in particular,the aged ones with large *** exploits the observation that the la-tency of an I/O request is determined,without considering the queuing time,by the access of the slowest device page,i.e.,the page that has the highest *** grouping consecutive logical pages that have high locality and interleaving their encoded data in different types of device pages that have different RBERs,DIR effectively reduces the number of read re-tries for LDPC with limited read *** meet the requirement of allocating hybrid page types for interleaved data,we also design a page-interleaving friendly page allocation scheme,which splits all the planes into multi-plane re-gions for storing the interleaved data and single-plane regions for storing the normal *** pages in the multi-plane re-gion can be read/written in parallel by the proposed multi-plane command and avoid the read amplification *** on the DIR scheme and the proposed page allocation scheme,we build DIR-enable FTL,which integrates the pro

关键词： triple-layer cell solid-state drive(TLC SSD) performance interleaving data unbalanced bit error rate

Enhanced in-vitro degradation resistance and cytocompatibility of a thermomechanically processed novel Mg alloy:Insights into the role of microstructural attributes

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Journal of Magnesium and Alloys 2024年第2期12卷 700-725页

作者： Darothi Bairagi Santanu Mandal Mangal Roy Manas Paliwal Sumantra Mandal department of Metallurgical and Materials Engineering Indian Institute of TechnologyKharagpur 721302India

The role of microstructural features on in-vitro degradation and surface film development of a thermomechanically processed Mg-4Zn-0.5Ca-0.8Mn alloy has been investigated employing electrochemical studies,scanning electron microscopy and X-ray photoelectron *** specimen forged at 523 K temperature developed a coarse unimodal microstructure consisting of basal oriented grains,whereas the specimens forged at 623 K and 723 K temperatures exhibited bimodal microstructures containing randomly oriented fine grains and basal oriented coarse *** bimodal microstructures exerted higher resistance to corrosion compared to the unimodal microstructure in presence of a protective surface *** optimum size distribution of fine and coarse grains as well as the prevalence of basal oriented grains led to the lowest anodic current density in the specimen forged at 623 *** morphology of Ca_(2)Mg_(6)Zn_(3)precipitates governed the cathodic kinetics by controlling the anode to cathode surface area *** the specimen forged at 723 K comprised comparatively lower fraction of precipitates than at 623 K,the mesh-like precipitate morphology increased the effective cathodic surface area,leading to enhanced localised corrosion in the former *** microstructural features developed at 623 K forging temperature formed a well-protective surface film with lower Mg(OH)_(2)to MgO ratio,exhibiting distinctly high polarization resistance and superior cytocompatibility in terms of cell-proliferation and cell-differentiation.

关键词： Magnesium alloy Microstructure Corrosion Electrochemical impedance spectroscopy X-ray photoelectron spectroscopy Cytotoxicity

Memory-enhanced text style transfer with dynamic style learning and calibration

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Science China(Information Sciences) 2024年第4期67卷 181-196页

作者： Fuqiang LIN Yiping SONG Zhiliang TIAN Wangqun CHEN Diwen DONG Bo LIU College of Computer Science and technology National University of Defense Technology department of Computer Science and Engineering The Hong Kong University of Science and Technology Strategic Assessments and Consultation Institute Academy of Military Sciences

Text style transfer aims to rephrase a sentence to match the desired style while retaining the original content. As a controllable text generation task, mainstream approaches use content-independent style embedding as control variables to guide stylistic generation. Nonetheless, stylistic properties are contextsensitive even under the same style. For example, “delicious” and “helpful” convey positive sentiments,although they are more likely to describe food and people, respectively. Therefore, desired style signals must vary with the content. To this end, we propose a memory-enhanced transfer method, which learns fine-grained style representation concerning content to assist transfer. Rather than employing static style embedding or latent variables, our method abstracts linguistic characteristics from training corpora and memorizes subdivided content with the corresponding style representations. The style signal is dynamically retrieved from memory using the content as a query, providing a more expressive and flexible latent style space. To address the imbalance between quantity and quality in different content, we further introduce a calibration method to augment memory construction by modeling the relationship between candidate *** results obtained using three benchmark datasets confirm the superior performance of our model compared to competitive approaches. The evaluation metrics and case study also indicate that our model can generate diverse stylistic phrases matching context.

关键词： style transfer memory-enhanced method text generation deep learning text representation

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Machine learning-assisted efficient design of Cu-based shape memory alloy with specific phase transition temperature

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International Journal of Minerals,Metallurgy and Materials 2024年第4期31卷 773-785页

作者： Mengwei Wu Wei Yong Cunqin Fu Chunmei Ma Ruiping Liu department of Materials Science and Engineering China University of Mining&Technology(Beijing)Beijing 100083China Institute for Advanced Materials and technology University of Science and Technology BeijingBeijing 100083China

The martensitic transformation temperature is the basis for the application of shape memory alloys(SMAs),and the ability to quickly and accurately predict the transformation temperature of SMAs has very important practical *** this work,machine learning(ML)methods were utilized to accelerate the search for shape memory alloys with targeted properties(phase transition temperature).A group of component data was selected to design shape memory alloys using reverse design method from numerous unexplored *** modeling and feature modeling were used to predict the phase transition temperature of the shape memory *** experimental results of the shape memory alloys were obtained to verify the effectiveness of the support vector regression(SVR)*** results show that the machine learning model can obtain target materials more efficiently and pertinently,and realize the accurate and rapid design of shape memory alloys with specific target phase transition *** this basis,the relationship between phase transition temperature and material descriptors is analyzed,and it is proved that the key factors affecting the phase transition temperature of shape memory alloys are based on the strength of the bond energy between *** work provides new ideas for the controllable design and performance optimization of Cu-based shape memory alloys.

关键词： machine learning support vector regression shape memory alloys martensitic transformation temperature

Modified DS np Chart Using Generalized Multiple Dependent State Sampling under Time Truncated Life Test

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2471-2495页

作者： Wimonmas Bamrungsetthapong Pramote Charongrattanasakul Division of Applied Statistics Department of Mathematics and Computer ScienceFaculty of Science and TechnologyRajamangala University of Technology ThanyaburiPathum Thani12110Thailand Division of Mathematics Department of Mathematics and Computer ScienceFaculty of Science and TechnologyRajamangala University of Technology KrungthepBangkok10120Thailand

This study presents the design of a modified attributed control chart based on a double sampling(DS)np chart applied in combination with generalized multiple dependent state(GMDS)sampling to monitor the mean life of the product based on the time truncated life test employing theWeibull *** control chart developed supports the examination of the mean lifespan variation for a particular product in the process of *** control limit levels are used:the warning control limit,inner control limit,and outer control ***,they enhance the capability for variation detection.A genetic algorithm can be used for optimization during the in-control process,whereby the optimal parameters can be established for the proposed control *** control chart performance is assessed using the average run length,while the influence of the model parameters upon the control chart solution is assessed via sensitivity analysis based on an orthogonal experimental design withmultiple linear regression.A comparative study was conducted based on the out-of-control average run length,in which the developed control chart offered greater sensitivity in the detection of process shifts while making use of smaller samples on average than is the case for existing control ***,to exhibit the utility of the developed control chart,this paper presents its application using simulated data with parameters drawn from the real set of data.

关键词： Modified DS np chart generalizedmultiple dependent state sampling time truncated life test Weibull distribution average run length average sample size

Organochlorides Mediate Oxidation Reactions Induced by Low Dose Ionizing Radiation

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CCS Chemistry 2024年第7期6卷 1712-1720页

作者： Juncheng Liu Tobias G.Brevé bing Xu Peter-Leon Hagedoorn Antonia G.Denkova Rienk Eelkema department of Radiation Science and technology Delft University of Technology2629 JB Delft department of Chemical Engineering Delft University of Technology2629 HZ Delft department of Biotechnology Delft University of Technology2629 HZ Delft

The controlled release of drugs using local ionizing radiation presents a promising approach for targeted cancer treatment,particularly when applied in concurrent *** these approaches,radiation-generated reactive species often play an important ***,the reactive species that can be used to trigger release have low yield and lack ***,we demonstrate the generation of highly oxidative species when aqueous solutions containing low concentrations of organochlorides(such as chloroform)are irradiated with ionizing radiation at therapeutically relevant *** reactive species were identified as peroxyl radicals,which formed in a reaction cascade between organochlorides and aqueous *** employed stilbene-based probes to investigate the oxidation process,showing double bond oxidation and *** translate this reactivity into a radiation-sensitive material,we synthesized a micelle-forming amphiphilic block copolymer that has stilbene as the linker between two *** exposure to ionizing radiation,the oxidation of stilbene led to the cleavage of the polymer,which induces the dissociation of the block-copolymer micelles and the release of loaded drugs.

关键词： drug delivery micelles radiation chemistry reactive oxygen species ionizing radiation reaction mechanisms

An Enhanced Hybrid Model Based on CNN and BiLSTM for Identifying Individuals via Handwriting Analysis

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1689-1710页

作者： Md.Abdur Rahim Fahmid Al Farid Abu Saleh Musa Miah Arpa Kar Puza Md.Nur Alam Md.Najmul Hossain Sarina Mansor Hezerul Abdul Karim department of Computer Science and Engineering Pabna University of Science and TechnologyPabna6600Bangladesh Faculty of Engineering Multimedia UniversityCyberjaya63100Malaysia department of Computer Science and Engineering Bangladesh Army University of Science and TechnologySaidpur5311Bangladesh department of Mathematics Pabna University of Science and TechnologyPabna6600Bangladesh department of Electrical Electronic and Communication EngineeringPabnaUniversity of Science and TechnologyPabna6600Bangladesh department of Electrical and Communication Engineering Pabna University of Science and TechnologyPabna6600Bangladesh

Handwriting is a unique and significant human feature that distinguishes them from one *** are many researchers have endeavored to develop writing recognition systems utilizing specific signatures or symbols for person identification through ***,such systems are susceptible to forgery,posing security *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** innovative method is intricately designed,encompassing five distinct phases:data collection,preprocessing,feature extraction,significant feature selection,and *** key advancement lies in the creation of a novel dataset specifically tailored for Bengali handwriting(BHW),setting the foundation for our comprehensive ***-preprocessing,we embarked on an exhaustive feature extraction process,encompassing integration with kinematic,statistical,spatial,and composite *** meticulous amalgamation resulted in a robust set of 91 *** enhance the efficiency of our system,we employed an analysis of variance(ANOVA)F test and mutual information scores approach,meticulously selecting the most pertinent *** the identification phase,we harnessed the power of cutting-edge deep learning models,notably the Convolutional Neural Network(CNN)and Bidirectional Long Short-Term Memory(BiLSTM).These models underwent rigorous training and testing to accurately discern individuals based on their handwriting ***,our methodology introduces a groundbreaking hybrid model that synergizes CNN and BiLSTM,capitalizing on fine motor features for enhanced individual ***,our experimental results unde

关键词： Bengali handwriting(BHW) person identification convolutional neural network(CNN) BiLSTM