High repetition granular Co/Pt multilayers with improved perpendicular remanent magnetization for high-density magnetic recording

Thanks to the strong perpendicular magnetic anisotropy(PMA), excellent processing compatibility as well as novel spintronic phenomenon, Co/Pt multilayers have been attracting massive attention and widely used in magnetic storage.However, reversed magnetic domains come into being with the increasing layer repetition ‘N’ to reduce magneto-static energy, resulting in the remarkable diminishment of the remanent magnetization(Mr). As a result, the product of Mrand thickness(i.e., the remanent moment-thickness product, Mrt), a key parameter in magnetic recording for reliable data storing and reading, also decreases dramatically. To overcome this issue, we deposit an ultra-thick granular [Co/Pt]80multilayer with a total thickness of 68 nm on granular SiNxbuffer layer. The Mrt value, Mrto saturation magnetization(Ms) ratio as well as out of plane(OOP) coercivity(Hcoop) are high up to 2.97 memu/cm^(2), 67%, and 1940 Oe(1 Oe = 79.5775 A·m^(-1)),respectively, which is remarkably improved compared with that of continuous [Co/Pt]80multilayers. That is because large amounts of grain boundaries in the granular multilayers can efficiently impede the propagation and expansion of reversed magnetic domains, which is verified by experimental investigations and micromagnetic simulation results. The simulation results also indicate that the value of Mrt, Mr/Msratio, and Hcoopcan be further improved through optimizing the granule size, which can be experimentally realized by manipulating the process parameter of SiNxbuffer layer. This work provides an alternative solution for achieving high Mrt value in ultra-thick Co/Pt multilayers, which is of unneglectable potential in applications of high-density magnetic recording.

Recording the direct surgeon’s view with an operating microscopic view improves microscopic ophthalmic surgery training

AIM:To establish a recording system with a direct view of the surgeon to supplement video recording under an operating microscope,which lacks information on the movement and position of the surgeon’s hands,and to facilitate the reproduction of a skilled surgeon’s technique by a surgeon in training.METHODS:A small camera was attached to the operating microscope with a custom adapter.Microscopic surgeon’s view and direct surgeon’s view through this new camera were recorded in the surgical recording system.Both movies were synchronized and analyzed how do surgeons handle the instruments.RESULTS:A small camera attached to the operating microscope allowed the surgeon’s hands motion to be recorded without interfering with the surgeon’s movements.Different surgeons used different methods to manipulate the ultrasound handpiece and the irrigation/aspiration device.Even in the simple paracentesis procedure,different surgeons used different methods.Surgeons-in-training were able to identify and improve their weaknesses by watching synchronized movies of their hand motions and microscopic view.CONCLUSION:Simultaneous recording the surgical field out of the operating microscopic view by a small camera set on the microscope is comprehensive and improves surgeons-in-training understanding and learning surgeries.

A Study of Parallelism in English Speeches

Every public speaker prepares his or her public speech meticulously.Witty remarks emerge in an endless stream,and demonstrate the rhetoric beauty of English to a great extent.Almost every speaker employs parallelism in his or her public speeches.The present paper is intended to study the concept,the classification and the significance of parallelism in English.

Multi-Objective Equilibrium Optimizer for Feature Selection in High-Dimensional English Speech Emotion Recognition

Speech emotion recognition(SER)uses acoustic analysis to find features for emotion recognition and examines variations in voice that are caused by emotions.The number of features acquired with acoustic analysis is extremely high,so we introduce a hybrid filter-wrapper feature selection algorithm based on an improved equilibrium optimizer for constructing an emotion recognition system.The proposed algorithm implements multi-objective emotion recognition with the minimum number of selected features and maximum accuracy.First,we use the information gain and Fisher Score to sort the features extracted from signals.Then,we employ a multi-objective ranking method to evaluate these features and assign different importance to them.Features with high rankings have a large probability of being selected.Finally,we propose a repair strategy to address the problem of duplicate solutions in multi-objective feature selection,which can improve the diversity of solutions and avoid falling into local traps.Using random forest and K-nearest neighbor classifiers,four English speech emotion datasets are employed to test the proposed algorithm(MBEO)as well as other multi-objective emotion identification techniques.The results illustrate that it performs well in inverted generational distance,hypervolume,Pareto solutions,and execution time,and MBEO is appropriate for high-dimensional English SER.

Exploring Sequential Feature Selection in Deep Bi-LSTM Models for Speech Emotion Recognition

Machine Learning(ML)algorithms play a pivotal role in Speech Emotion Recognition(SER),although they encounter a formidable obstacle in accurately discerning a speaker’s emotional state.The examination of the emotional states of speakers holds significant importance in a range of real-time applications,including but not limited to virtual reality,human-robot interaction,emergency centers,and human behavior assessment.Accurately identifying emotions in the SER process relies on extracting relevant information from audio inputs.Previous studies on SER have predominantly utilized short-time characteristics such as Mel Frequency Cepstral Coefficients(MFCCs)due to their ability to capture the periodic nature of audio signals effectively.Although these traits may improve their ability to perceive and interpret emotional depictions appropriately,MFCCS has some limitations.So this study aims to tackle the aforementioned issue by systematically picking multiple audio cues,enhancing the classifier model’s efficacy in accurately discerning human emotions.The utilized dataset is taken from the EMO-DB database,preprocessing input speech is done using a 2D Convolution Neural Network(CNN)involves applying convolutional operations to spectrograms as they afford a visual representation of the way the audio signal frequency content changes over time.The next step is the spectrogram data normalization which is crucial for Neural Network(NN)training as it aids in faster convergence.Then the five auditory features MFCCs,Chroma,Mel-Spectrogram,Contrast,and Tonnetz are extracted from the spectrogram sequentially.The attitude of feature selection is to retain only dominant features by excluding the irrelevant ones.In this paper,the Sequential Forward Selection(SFS)and Sequential Backward Selection(SBS)techniques were employed for multiple audio cues features selection.Finally,the feature sets composed from the hybrid feature extraction methods are fed into the deep Bidirectional Long Short Term Memory(Bi-LSTM)network to discern emotions.Since the deep Bi-LSTM can hierarchically learn complex features and increases model capacity by achieving more robust temporal modeling,it is more effective than a shallow Bi-LSTM in capturing the intricate tones of emotional content existent in speech signals.The effectiveness and resilience of the proposed SER model were evaluated by experiments,comparing it to state-of-the-art SER techniques.The results indicated that the model achieved accuracy rates of 90.92%,93%,and 92%over the Ryerson Audio-Visual Database of Emotional Speech and Song(RAVDESS),Berlin Database of Emotional Speech(EMO-DB),and The Interactive Emotional Dyadic Motion Capture(IEMOCAP)datasets,respectively.These findings signify a prominent enhancement in the ability to emotional depictions identification in speech,showcasing the potential of the proposed model in advancing the SER field.

New record of the feather star Palaeocomatella hiwia(Echinodermata:Crinoidea:Comatulida)from Zhenbei Seamount in South China Sea:new insights into the taxonomic position of Palaeocomatella

One specimen belonging to the family Comatellinae was collected from the Zhenbei Seamount(332.5–478.2 m)in the South China Sea in July 2022.Based on the morphological characters,the specimen was identified as Palaeocomatella hiwia McKnight,1977.It is first recorded from China Sea and redescribed in detail.This specimen differs from the original description from New Zealand for never showing syzygy at br4+5 or br5+6 on interior and br1+2 on exterior arms.However,it is much conform to the redescription to specimens from Indonesia,with only differences in position of the second syzygy and distalmost pinnule comb.Specimen is deposited in the Institute of Oceanology,Chinese Academy of Sciences.Phylogenetic analyses based on the mitochondrial c oxidase subunit I(COI)and 16S rRNA genes indicated that P.hiwia was nested within the tribe Phanogeniini and clustered with Aphanocomaster pulcher.Furthermore,P.hiwia showed same morphological features in terms of mouth placement,comb location,and number of comb teeth rows as other genera of Phanogeniini.Therefore,we suggest that the genus Palaeocomatella should be put in the tribe Phanogeniini.

Audio-Text Multimodal Speech Recognition via Dual-Tower Architecture for Mandarin Air Traffic Control Communications

In air traffic control communications (ATCC), misunderstandings between pilots and controllers could result in fatal aviation accidents. Fortunately, advanced automatic speech recognition technology has emerged as a promising means of preventing miscommunications and enhancing aviation safety. However, most existing speech recognition methods merely incorporate external language models on the decoder side, leading to insufficient semantic alignment between speech and text modalities during the encoding phase. Furthermore, it is challenging to model acoustic context dependencies over long distances due to the longer speech sequences than text, especially for the extended ATCC data. To address these issues, we propose a speech-text multimodal dual-tower architecture for speech recognition. It employs cross-modal interactions to achieve close semantic alignment during the encoding stage and strengthen its capabilities in modeling auditory long-distance context dependencies. In addition, a two-stage training strategy is elaborately devised to derive semantics-aware acoustic representations effectively. The first stage focuses on pre-training the speech-text multimodal encoding module to enhance inter-modal semantic alignment and aural long-distance context dependencies. The second stage fine-tunes the entire network to bridge the input modality variation gap between the training and inference phases and boost generalization performance. Extensive experiments demonstrate the effectiveness of the proposed speech-text multimodal speech recognition method on the ATCC and AISHELL-1 datasets. It reduces the character error rate to 6.54% and 8.73%, respectively, and exhibits substantial performance gains of 28.76% and 23.82% compared with the best baseline model. The case studies indicate that the obtained semantics-aware acoustic representations aid in accurately recognizing terms with similar pronunciations but distinctive semantics. The research provides a novel modeling paradigm for semantics-aware speech recognition in air traffic control communications, which could contribute to the advancement of intelligent and efficient aviation safety management.

Impact of Laboratory Value Flowsheet in Electronic Health Record (EHR) Documentation Time

Research on the use of EHR is contradictory since it presents contradicting results regarding the time spent documenting. There is research that supports the use of electronic records as a tool to speed documentation;and research that found that it is time consuming. The purpose of this quantitative retrospective before-after project was to measure the impact of using the laboratory value flowsheet within the EHR on documentation time. The research question was: “Does the use of a laboratory value flowsheet in the EHR impact documentation time by primary care providers (PCPs)?” The theoretical framework utilized in this project was the Donabedian Model. The population in this research was the two PCPs in a small primary care clinic in the northwest of Puerto Rico. The sample was composed of all the encounters during the months of October 2019 and December 2019. The data was obtained through data mining and analyzed using SPSS 27. The evaluative outcome of this project is that there is a decrease in documentation time after implementation of the use of the laboratory value flowsheet in the EHR. However, patients per day increase therefore having an impact on the number of patients seen per day/week/month. The implications for clinical practice include the use of templates to improve workflow and documentation as well as decreasing documentation time while also increasing the number of patients seen per day. .

A Novel System for Recognizing Recording Devices from Recorded Speech Signals

The field of digital audio forensics aims to detect threats and fraud in audio signals.Contemporary audio forensic techniques use digital signal processing to detect the authenticity of recorded speech,recognize speakers,and recognize recording devices.User-generated audio recordings from mobile phones are very helpful in a number of forensic applications.This article proposed a novel method for recognizing recording devices based on recorded audio signals.First,a database of the features of various recording devices was constructed using 32 recording devices(20 mobile phones of different brands and 12 kinds of recording pens)in various environments.Second,the audio features of each recording device,such as the Mel-frequency cepstral coefficients(MFCC),were extracted from the audio signals and used as model inputs.Finally,support vector machines(SVM)with fractional Gaussian kernel were used to recognize the recording devices from their audio features.Experiments demonstrated that the proposed method had a 93.4%accuracy in recognizing recording devices.

The Development of the “Monitoring Application for Inappropriate Expressions in Nursing Records”for PsyNACS©

Lengthening periods of hospitalization, increasing numbers of patients with age-related complications, and a shortage of nursing staff have been of great concern in medical psychiatry in Japan. Under these circumstances, countries such as Japan that face a super-aging society and a decline in the working-age population, have been recommended for use of advanced information and communications technology (ICT) to improve the efficiency of medical treatment and care. This study aims to develop the “Monitoring Application for Inappropriate Expressions in Nursing Records” for using PsyNACS©, which will enable psychiatric nursing plans to harness the advantages of ICT. The functions considered necessary are as follows: 1) identification of users who enter information;2) a necessary database for lists of inappropriate expressions;3) development of a matching function to recommend proper writing input and a warning function;and 4) a management function for an inappropriate expression list database. A demonstration experiment for developing the application in this study was conducted at a specialized psychiatric hospital. To introduce them to the application, nurses and nurse managers were informed about the system developed in this study, and a survey regarding their opinions on the functions of the application was conducted with ten nurse managers. The results were evaluated in terms of usefulness for nursing care, documentation, and the education of nurses from an ethical perspective. This study suggests that matching their input with an inappropriate expression database will allow nurses to record more appropriate expressions. From an ethical perspective, the ability to use appropriate expressions makes records more likely to withstand disclosure requests from patients and their families.

Research on the Application of Second Language Acquisition Theory in College English Speech Teaching

The teaching of English speeches in universities aims to enhance oral communication ability,improve English communication skills,and expand English knowledge,occupying a core position in English teaching in universities.This article takes the theory of second language acquisition as the background,analyzes the important role and value of this theory in English speech teaching in universities,and explores how to apply the theory of second language acquisition in English speech teaching in universities.It aims to strengthen the cultivation of English skilled talents and provide a brief reference for improving English speech teaching in universities.

解铃须从系铃处——Records与Archives概念正史(二)

笔者的“四正”,从名分、本义、学理、法律上已弄清Records的含义,但坚持“Records文件观”者依旧质疑:若Records是档案,那Archives是什么?两者并列时又怎么翻译?还有人说Records是记录。既然是英语和法语带来的问题,循着英法档案历史去寻找,才是解铃的关键:以英法八百年档案工作中重要人物和事件为主线,探求其档案的源流、本质、内含及演变,为档案概念正史。

FAULT LOCATION AND RECORDING SYSTEM OF TRANSMISSION LINES BASED ON COMPUTER NETWORK

提出以计算机网络为基础的超高压输电线路的故障定位和录波系统，在结构上具有开放式的特点，可根据要求方便地接入扩建线路，并且高速网络数通讯使系统具有极好的实时性．文中重点论述了故障定位新方法，它不仅在线路故障定碍位的数学模型建立上考虑了超高压长距离线路的分布参数特性，并且在计算方法上计及故障线路两端故障电流的相位，经ＥＭＴＰ仿真及测试可证明所提出的综合方法对超高运长距离输电线路故障定位的精确性．论述了以计算机网络为基础的输电线故障定位和录波系统，给出了系统结构和主要特点，重点阐述了所提出的精确超高压长距离输电线故障定位的新方法。

An Analysis of the Language Features of Barack Obama's Inaugural Speeches

This thesis tries to analyze the language features of Barack Obama's two inaugural speeches in 2008 and 2012 from the linguistic aspects,including sentence types as well as figures of speech which included imperative sentences,parallelism,rhetorical question,alliteration,hyperbole,simile,metaphor and so on.

Probing the Linguistic and Rhetorical Features of English Speeches

English speech is a discourse delivered at an assembly or on formal occasions. As a variety of the English language, English speech has a unique presentation of its own. This paper, as its title indicates, is to analyze and probe the linguistic and rhetorical features of famous English speeches with a view to improving the ability to appreciate English speeches on the part of Chinese learners of English.

Strong motion observations and recordings from the great Wenchuan Earthquake

The National Strong Motion Observation Network System （NSMONS） of China is briefly introduced in this paper. The NSMONS consists of permanent free-field stations, special observation arrays, mobile observatories and a network management system. During the Wenchuan Earthquake, over 1,400 components of acceleration records were obtained from 460 permanent free-field stations and three arrays for topographical effect and structural response observation in the network system from the main shock, and over 20,000 components of acceleration records from strong aftershocks occurred before August 1, 2008 were also obtained by permanent free-field stations of the NSMONS and 59 mobile instruments quickly deployed after the main shock. The strong motion recordings from the main shock and strong aftershocks are summarized in this paper. In the ground motion recordings, there are over 560 components with peak ground acceleration （PGA） over 10 Gal, the largest being 957.7 Gal. The largest PGA recorded during the aftershock exceeds 300 Gal.

Improved HVSR site classification method for free-field strong motion stations validated with Wenchuan aftershock recordings

Local site conditions play an important role in the effective application of strong motion recordings.In the China National Strong Motion Observation Network System（NSMONS）,some of the stations do not provide borehole information,and correspondingly,do not assign the site classes yet.In this paper,site classification methodologies for free-field strong motion stations are reviewed and the limitations and uncertainties of the horizontal-to-vertical spectral ratio（HVSR） methods are discussed.Then,a new method for site classification based on the entropy weight theory is proposed.The proposed method avoids the head or tail joggle phenomenon by providing the objective and subjective weights.The method was applied to aftershock recordings from the 2008 Wenchuan earthquake,and 54 free-field NSMONS stations were selected for site classification and the mean HVSRs were calculated.The results show that the improved HVSR method proposed in this paper has a higher success rate and could be adopted in NSMONS.

Characteristics of response spectra for long-periods of main-shock recordings of the Chi-Chi earthquake

Current practice uses predictive models to extrapolate long-period response spectra based on far-field recordings in moderate and weak earthquakes. However, the spectra are not long enough and the data are often not reliable, which means that the seismic design code cannot accurately define seismic design requirements for long-period structures. The near-field recordings in the main-shock of the Chi-Chi earthquake have a large signal-to-noise ratio （SNR）, which makes them suitable for studying the long-period acceleration response spectrum up to 20 sec. The acceleration response spectra from 246 stations within 120 km of the causative fault are statistically analyzed in this paper. The influence of distance and site conditions on long-period response spectrum is discussed, and the shapes of the amplification spectra are compared with the standard spectra specified in the seismic design code of China. Finally, suggestions for future revisions to the code are proposed.

Multilevel read-only optical recording methods

The advantages of read-only storage is the predominance of optical recording relative to magnetic and other rewritable methods. Multilevel （ML） read-only technology has been a trend to improve the data capacity and transfer rate. Based on the principle and coding method of ML, this paper demonstrates some ML read-only recording methods, of which a new ML read-only recording is developed. This recording method integrates amplitude modulation achieved by the reaction mechanism of physics and chemistry of photoresist with the run-length-limited technology. The discs can be achieved using standard photoresist mastering and replication techniques with great compatibility to conventional binary read-only discs.