Mechanical Proofs about BW Multi-Party Contract Signing Protocol

We report on the verification of a multi-party contract signing protocol described by Baum-Waidner and Waidner （BW）. Based on Paulson＇s inductive approach, we give the protocol model that includes infinitely many signatories and contract texts signing simuhaneously. We consider composite attacks of the dishonest signatory and the external intruder, formalize cryptographic primitives and protocol arithmetic including attack model, show formal description of key distribution, and prove signature key secrecy theorems and fairness property theorems of the BW protocol using the interactive theorem prover Isabelle/HOL.

Unlicensed Personnel’s Experience of Digital Signing for Medication Administration in Municipal Healthcare

Aim: To describe unlicensed personnel’s experience of digital signing lists via a smartphone application for the distribution of medication in municipal healthcare in Western Sweden. Design: A qualitative and quantitative design was used. Methods: The study included 48 unlicensed personnel, 28 of whom answered an open-ended questionnaire, while an additional 20 volunteered for individual interviews. The material was analysed by qualitative content analysis. Results: The results indicate that digital signing lists via a smartphone application are feasible, and efficient and facilitate the work. However, some aspects negatively affected the sense of security, meetings with patients and quality of care, such as an insufficient internet signal in some rural areas, difficulty remembering the password, as well as the change of focus from patient to smartphone. To improve quality of care and the meeting with the patient, it is crucial that the technology works and that unlicensed personnel develop technical skills.

Signing the Contract(Ⅰ)

签署合同(Ⅰ) 参考译文: 在进行价格商谈后,王先生和史密斯小姐准备签合同。王先生:史密斯小姐,现在双方就价格问题已达成协议,我们是否把合同的相关条款再看一遍?

CNPC/EXXON/MITSUBISH Jointly Signing of Natural Gas Pipeline Study agreement

ＣＮＰＣ／ＥＸＸＯＮ／ＭＩＴＳＵＢＩＳＨＪｏｉｎｔｌｙＳｉｇｎｉｎｇｏｆＮａｔｕｒａｌＧａｓＰｉｐｅｌｉｎｅＳｔｕｄｙａｇｒｅｅｍｅｎｔ￥ＺｈａｎｇＸｉｎＣｈｉｎａＮａｔｉｏｎａｌＰｅｔｒｏｌｅｕｍＣｏｒｐｏｒａｔｉｏｎ（ＣＮＰＣ），Ａｍｅｒｉｃａｎ...

Signing Ceremony Between CAS and Schneider Electric Held in Beijing

On April 9, 2008, a strategic cooperation signing ceremony between the China Association for Stan- dardization(CAS)and Schneider Electric took place at the Diao Yutai Guest Hotel in Beijing. Attending the signing ceremony were Mr Sun Xiaokang,Duty Director of SAC, Mr. Ma Lingcong, Secretary General of CAS, Mr. Noel Girard, Schneider Electric Marketing Director, Mr.Guy Dufrdi sse,Chairman of Schneider Electric(China)and more than twenty high-ranking managers from both companies.

Do investors care about auditor assignments?Evidence from last-minute changes to signing auditors

Against the background of China’s strengthening of finance and accounting supervision,this study examines the practice among listed companies of changing signing auditors at the last minute and explores whether Chinese investors can capture this information in a timely manner.We find that China’s capital market responds significantly negatively to these last-minute changes,implying that investors perceive a potential negative impact of this behavior.Crosssectional analyses suggest that the characteristics of the change event,recent corporate events,and accounting firm capability significantly affect the stock price response.Furthermore,in terms of the individual characteristics of signing auditors,external investors appear to comprehensively consider busyness level,industry experience,and the timing of the change to determine the causes and effects of the auditor change and make different market reactions accordingly.In addition,consistent with investor perceptions,we find that last-minute changes significantly impair the quality of financial statements,indicating that external investors’judgments based on information about changes in signing auditors are rational and effective.

Signing Ceremony of English Version of Studies on Chinese Modernization Series(Series 1)Held in Beijing

In March,China Renmin University Press and Gale of Cengage Group held a signing ceremony for the English version of the Studies on Chinese Modernization Series(Series I),in which ten published books were selected.

17例耳硬化症患者的临床与影像学分析

目的分析17例耳硬化症患者的临床特征、影像学表现及手术治疗效果。方法收集2020年5月~2023年5月在湖州市中心医院接受手术治疗的17例(17耳)耳硬化症患者临床、影像学资料,分析其临床表现、颞骨CT影像学表现及手术前后纯音测听结果变化。结果17例(17耳)患者中,11耳(64.71%)为前庭窗型,表现为进行性传导性听力损失,其中9耳有耳鸣,3耳有轻微平衡问题;混合型6耳(35.29%)显示混合性听力损失,5耳有耳鸣,3耳有偶发性平衡障碍。影像学上,前庭窗型显示镫骨底板区域骨质增厚、前庭窗密度增加;混合型则显示镫骨底板增厚及耳蜗周围密度减低,1耳可见“双环征”,两种类型耳硬化症患者骨密度差异无统计学意义(P>0.05)。术后均未见耳鸣加重或其他严重并发症,仅2例(11.76%)出现暂时性头晕,术后随访显示术区恢复良好,无感染或其他迟发性并发症;术后听力测试显示气导阈值、气骨导差较术前显著改善(P均<0.05)。结论前庭窗型和混合型耳硬化症的影像学和临床表现各有特点,镫骨成形术可显著改善听力,降低气导阈值和气骨导差,且手术安全、并发症少。

A provable-secure and practical two-party distributed signing protocol for SM2 signature algorithm

Mobile devices are widely used for data access,communications and storage.However,storing a private key for signature and other cryptographic usage on a single mobile device can be challenging,due to its computational limitations.Thus,a number of(t,n)threshold secret sharing schemes designed to minimize private key from leakage have been proposed in the literature.However,existing schemes generally suffer from key reconstruction attack.In this paper,we propose an efficient and secure two-party distributed signing protocol for the SM2 signature algorithm.The latter has been mandated by the Chinese government for all electronic commerce applications.The proposed protocol separates the private key to storage on two devices and can generate a valid signature without the need to reconstruct the entire private key.We prove that our protocol is secure under nonstandard assumption.Then,we implement our protocol using MIRACL Cryptographic SDK to demonstrate that the protocol can be deployed in practice to prevent key disclosure.

Multi-policy threshold signature with distinguished signing authorities

Threshold signature plays an important role to distribute the power of a single authority in modem electronic society. In order to add functions and improve efficiency of threshold signatures, a multi-policy threshold signature scheme with distinguished signing authorities is proposed. In the scheme two groups can sign and verify each other, so the scheme is two-way signing and verifying. Moreover, the threshold values of the two groups can change with the security classification of the signing document, every discretionary signatory only signs a small part of the document instead of the whole one, so the bandwidth of data transmission for group signature construction can be reduced and the size of group signature is equivalent to that of any individual signature.

Source localization in signed networks with effective distance

While progress has been made in information source localization,it has overlooked the prevalent friend and adversarial relationships in social networks.This paper addresses this gap by focusing on source localization in signed network models.Leveraging the topological characteristics of signed networks and transforming the propagation probability into effective distance,we propose an optimization method for observer selection.Additionally,by using the reverse propagation algorithm we present a method for information source localization in signed networks.Extensive experimental results demonstrate that a higher proportion of positive edges within signed networks contributes to more favorable source localization,and the higher the ratio of propagation rates between positive and negative edges,the more accurate the source localization becomes.Interestingly,this aligns with our observation that,in reality,the number of friends tends to be greater than the number of adversaries,and the likelihood of information propagation among friends is often higher than among adversaries.In addition,the source located at the periphery of the network is not easy to identify.Furthermore,our proposed observer selection method based on effective distance achieves higher operational efficiency and exhibits higher accuracy in information source localization,compared with three strategies for observer selection based on the classical full-order neighbor coverage.

Recent Advances on Deep Learning for Sign Language Recognition

Sign language,a visual-gestural language used by the deaf and hard-of-hearing community,plays a crucial role in facilitating communication and promoting inclusivity.Sign language recognition(SLR),the process of automatically recognizing and interpreting sign language gestures,has gained significant attention in recent years due to its potential to bridge the communication gap between the hearing impaired and the hearing world.The emergence and continuous development of deep learning techniques have provided inspiration and momentum for advancing SLR.This paper presents a comprehensive and up-to-date analysis of the advancements,challenges,and opportunities in deep learning-based sign language recognition,focusing on the past five years of research.We explore various aspects of SLR,including sign data acquisition technologies,sign language datasets,evaluation methods,and different types of neural networks.Convolutional Neural Networks(CNN)and Recurrent Neural Networks(RNN)have shown promising results in fingerspelling and isolated sign recognition.However,the continuous nature of sign language poses challenges,leading to the exploration of advanced neural network models such as the Transformer model for continuous sign language recognition(CSLR).Despite significant advancements,several challenges remain in the field of SLR.These challenges include expanding sign language datasets,achieving user independence in recognition systems,exploring different input modalities,effectively fusing features,modeling co-articulation,and improving semantic and syntactic understanding.Additionally,developing lightweight network architectures for mobile applications is crucial for practical implementation.By addressing these challenges,we can further advance the field of deep learning for sign language recognition and improve communication for the hearing-impaired community.

Deep Learning Approach for Hand Gesture Recognition:Applications in Deaf Communication and Healthcare

Hand gestures have been used as a significant mode of communication since the advent of human civilization.By facilitating human-computer interaction(HCI),hand gesture recognition(HGRoc)technology is crucial for seamless and error-free HCI.HGRoc technology is pivotal in healthcare and communication for the deaf community.Despite significant advancements in computer vision-based gesture recognition for language understanding,two considerable challenges persist in this field:(a)limited and common gestures are considered,(b)processing multiple channels of information across a network takes huge computational time during discriminative feature extraction.Therefore,a novel hand vision-based convolutional neural network(CNN)model named(HVCNNM)offers several benefits,notably enhanced accuracy,robustness to variations,real-time performance,reduced channels,and scalability.Additionally,these models can be optimized for real-time performance,learn from large amounts of data,and are scalable to handle complex recognition tasks for efficient human-computer interaction.The proposed model was evaluated on two challenging datasets,namely the Massey University Dataset(MUD)and the American Sign Language(ASL)Alphabet Dataset(ASLAD).On the MUD and ASLAD datasets,HVCNNM achieved a score of 99.23% and 99.00%,respectively.These results demonstrate the effectiveness of CNN as a promising HGRoc approach.The findings suggest that the proposed model have potential roles in applications such as sign language recognition,human-computer interaction,and robotics.

Japanese Sign Language Recognition by Combining Joint Skeleton-Based Handcrafted and Pixel-Based Deep Learning Features with Machine Learning Classification

Sign language recognition is vital for enhancing communication accessibility among the Deaf and hard-of-hearing communities.In Japan,approximately 360,000 individualswith hearing and speech disabilities rely on Japanese Sign Language(JSL)for communication.However,existing JSL recognition systems have faced significant performance limitations due to inherent complexities.In response to these challenges,we present a novel JSL recognition system that employs a strategic fusion approach,combining joint skeleton-based handcrafted features and pixel-based deep learning features.Our system incorporates two distinct streams:the first stream extracts crucial handcrafted features,emphasizing the capture of hand and body movements within JSL gestures.Simultaneously,a deep learning-based transfer learning stream captures hierarchical representations of JSL gestures in the second stream.Then,we concatenated the critical information of the first stream and the hierarchy of the second stream features to produce the multiple levels of the fusion features,aiming to create a comprehensive representation of the JSL gestures.After reducing the dimensionality of the feature,a feature selection approach and a kernel-based support vector machine(SVM)were used for the classification.To assess the effectiveness of our approach,we conducted extensive experiments on our Lab JSL dataset and a publicly available Arabic sign language(ArSL)dataset.Our results unequivocally demonstrate that our fusion approach significantly enhances JSL recognition accuracy and robustness compared to individual feature sets or traditional recognition methods.

A Survey on Chinese Sign Language Recognition:From Traditional Methods to Artificial Intelligence

Research on Chinese Sign Language(CSL)provides convenience and support for individuals with hearing impairments to communicate and integrate into society.This article reviews the relevant literature on Chinese Sign Language Recognition(CSLR)in the past 20 years.Hidden Markov Models(HMM),Support Vector Machines(SVM),and Dynamic Time Warping(DTW)were found to be the most commonly employed technologies among traditional identificationmethods.Benefiting from the rapid development of computer vision and artificial intelligence technology,Convolutional Neural Networks(CNN),3D-CNN,YOLO,Capsule Network(CapsNet)and various deep neural networks have sprung up.Deep Neural Networks(DNNs)and their derived models are integral tomodern artificial intelligence recognitionmethods.In addition,technologies thatwerewidely used in the early days have also been integrated and applied to specific hybrid models and customized identification methods.Sign language data collection includes acquiring data from data gloves,data sensors(such as Kinect,LeapMotion,etc.),and high-definition photography.Meanwhile,facial expression recognition,complex background processing,and 3D sign language recognition have also attracted research interests among scholars.Due to the uniqueness and complexity of Chinese sign language,accuracy,robustness,real-time performance,and user independence are significant challenges for future sign language recognition research.Additionally,suitable datasets and evaluation criteria are also worth pursuing.

Adaptive Sensor-Fault Tolerant Control of Unmanned Underwater Vehicles With Input Saturation

This paper investigates the tracking control problem for unmanned underwater vehicles(UUVs)systems with sensor faults,input saturation,and external disturbance caused by waves and ocean currents.An active sensor fault-tolerant control scheme is proposed.First,the developed method only requires the inertia matrix of the UUV,without other dynamic information,and can handle both additive and multiplicative sensor faults.Subsequently,an adaptive fault-tolerant controller is designed to achieve asymptotic tracking control of the UUV by employing robust integral of the sign of error feedback method.It is shown that the effect of sensor faults is online estimated and compensated by an adaptive estimator.With the proposed controller,the tracking error and estimation error can asymptotically converge to zero.Finally,simulation results are performed to demonstrate the effectiveness of the proposed method.

Appendiceal intussusception complicated by adenocarcinoma of the cecum:A case report

BACKGROUND Appendiceal intussusception is a pathological condition in which the appendix is inverted into the cecum,which may cause symptoms that resemble those of other gastrointestinal disorders and may induce intestinal obstruction.The rarity of this case presentation is the co-occurrence of appendiceal intussusception and cecal adenocarcinoma,a combination that to our knowledge has not previously been reported in the medical literature.This case provides new insights into the complexities of diagnosing and managing overlapping pathologies.CASE SUMMARY A 25-year-old woman presented with persistent periumbilical pain and bloody stools.An initial biopsy showed cecal cancer;however,subsequent colonoscopy and computed tomography findings raised the suspicion of appendiceal intussus-ception,which was later confirmed postoperatively.This unique case was charac-terized by a combination of intussusception and adenocarcinoma of the cecum.The intervention included a laparoscopic right hemicolectomy,which led to the histopathological diagnosis of mucinous adenocarcinoma with appendiceal intussusception.The patient recovered well postoperatively and was advised to initiate adjuvant chemotherapy.This case highlights not only the importance of considering appendiceal intussusception in the differential diagnosis,but also the possibility of appendicitis and the atypical presentation of neoplastic lesions.CONCLUSIONS Physicians should consider the possibility of appendiceal intussusception in cases of atypical appendicitis,particularly when associated with neoplastic presentation.

Alterations of sleep deprivation on brain function:A coordinatebased resting-state functional magnetic resonance imaging metaanalysis

BACKGROUND Sleep deprivation is a prevalent issue that impacts cognitive function.Although numerous neuroimaging studies have explored the neural correlates of sleep loss,inconsistencies persist in the reported results,necessitating an investigation into the consistent brain functional changes resulting from sleep loss.AIM To establish the consistency of brain functional alterations associated with sleep deprivation through systematic searches of neuroimaging databases.Two metaanalytic methods,signed differential mapping(SDM)and activation likelihood estimation(ALE),were employed to analyze functional magnetic resonance imaging(fMRI)data.METHODS A systematic search performed according to PRISMA guidelines was conducted across multiple databases through July 29,2023.Studies that met specific inclusion criteria,focused on healthy subjects with acute sleep deprivation and reported whole-brain functional data in English were considered.A total of 21 studies were selected for SDM and ALE meta-analyses.RESULTS Twenty-one studies,including 23 experiments and 498 subjects,were included.Compared to pre-sleep deprivation,post-sleep deprivation brain function was associated with increased gray matter in the right corpus callosum and decreased activity in the left medial frontal gyrus and left inferior parietal lobule.SDM revealed increased brain functional activity in the left striatum and right central posterior gyrus and decreased activity in the right cerebellar gyrus,left middle frontal gyrus,corpus callosum,and right cuneus.CONCLUSION This meta-analysis consistently identified brain regions affected by sleep deprivation,notably the left medial frontal gyrus and corpus callosum,shedding light on the neuropathology of sleep deprivation and offering insights into its neurological impact.

Medication for Birth Control in Bitch at Battambang City,Battambang Province,Cambodia

The observation study was conducted in Battambang City,Battambang province,by interviewing the 88 dog owners,who came to the animal pharmacy stores and clinics by using convenience sampling method of nonrandomized sampling.Though the results of the interviews,showed that the dog owners were selected in different range of age and gender,however,most of them were in middle age from 21-40 years old,with medium and rich living wellbeing.The confinement in premise/house was primarily applied by dog owners.The number of bitches per household was from 1 to 3 batches,and there was no association with the wellbeing of the owners,and the age was from 2 to 4 years old,but some bitches had older age.Most of the bitches were dewormed in last 3 months and 6 months,however,there were some bitches last more than 6 months after deworming.The bitch vaccination was applied by owner around for 60.00%.There were two popular types of vaccination,Rabies and DHLPP(Distemper,Hepatitis,Leptospirosis,Parvovirus,and Parainfluenza).For dog population management,about 94.29%of the owners apply nonsurgical method with applying medicine.The reasons for using nonsurgical method were not only the cheapest price and easy way,but also there was no information on the consequence of using medication for birth control.The medication was highly used before heat.But,almost half of them got health problem in less than 3 months after administration,also some got long-term effect.Among clinical signs observed,the enlargement of belly was the most evidence,since 54.76%of affected bitches had shown it,then followed by discharge blood from vulvar,clear discharge and thick white pus from vulvar,accounting for 38.10%,35.71%and 26.71%,respectively.