Computerized cognitive remediation therapy on cognitive impairment and social function in patients with chronic schizophrenia

BACKGROUND Patients with schizophrenia may have various disease manifestations,most of which gradually tend toward incurable chronic decline,leading to mental disability.The basic symptoms of the disease can impair social function,whereas long-term hospitalization produces hospitalization syndrome,causing serious damage to social function.AIM To investigate the effects of Computerized Cognitive Remediation Therapy(CCRT)on cognitive and social functioning in patients with chronic schizophrenia.METHODS A retrospective analysis of 120 patients with chronic schizophrenia in Shanghai Pudong New Area Mental Health Center was performed.They were divided into an intervention group(60 cases treated with CCRT combined with conventional medication)and a control group(60 cases treated with conventional medication).After treatment,effects on cognitive function and social roles were observed in both groups.The Positive and Negative Syndrome Scale(PANSS)was used to assess the patients'psychiatric symptoms.The Wisconsin Card Sorting Test(WCST)was used to assess the patients'cognitive functioning,and the Social Functioning Scale for Psychiatric Inpatients(SSPI)was used to assess the social functioning of the inpatient psychiatric patients.RESULTS No significant differences were observed in the PANSS,WCST,and SSPI intergroup scores before treatment(P>0.05).After 2,4,and 6 wk of therapy,general psychopathological factors,positive symptoms,negative symptoms,and total PANSS scores of PANSS in the intervention group were lower than in the control group(P<0.05).After 2,4,and 6 wk of treatment,the number of false responses,number of persistent bugs,and total responses in the WCST were significantly lower in the intervention group than in the control group(P<0.05),and the amount of completed classification was significantly higher than in the control group(P<0.05).After 2,4,and 6 wk of therapy,the SSPI scores were significantly greater than those of the controls(P<0.05).After 6 wk of treatment,the efficacy rates of the control and intervention groups were 81.67%and 91.67%,respectively.The curative effect in the intervention group was significantly higher than that in the control group(P<0.05).CONCLUSION CCRT can significantly improve cognitive function and social abilities in patients with chronic schizophrenia.

Privacy-Preserving Information Fusion Technique for Device to Server-Enabled Communication in the Internet of Things:A Hybrid Approach

Due to the overwhelming characteristics of the Internet of Things(IoT)and its adoption in approximately every aspect of our lives,the concept of individual devices’privacy has gained prominent attention from both customers,i.e.,people,and industries as wearable devices collect sensitive information about patients(both admitted and outdoor)in smart healthcare infrastructures.In addition to privacy,outliers or noise are among the crucial issues,which are directly correlated with IoT infrastructures,as most member devices are resource-limited and could generate or transmit false data that is required to be refined before processing,i.e.,transmitting.Therefore,the development of privacy-preserving information fusion techniques is highly encouraged,especially those designed for smart IoT-enabled domains.In this paper,we are going to present an effective hybrid approach that can refine raw data values captured by the respectivemember device before transmission while preserving its privacy through the utilization of the differential privacy technique in IoT infrastructures.Sliding window,i.e.,δi based dynamic programming methodology,is implemented at the device level to ensure precise and accurate detection of outliers or noisy data,and refine it prior to activation of the respective transmission activity.Additionally,an appropriate privacy budget has been selected,which is enough to ensure the privacy of every individualmodule,i.e.,a wearable device such as a smartwatch attached to the patient’s body.In contrast,the end module,i.e.,the server in this case,can extract important information with approximately the maximum level of accuracy.Moreover,refined data has been processed by adding an appropriate nose through the Laplace mechanism to make it useless or meaningless for the adversary modules in the IoT.The proposed hybrid approach is trusted from both the device’s privacy and the integrity of the transmitted information perspectives.Simulation and analytical results have proved that the proposed privacy-preserving information fusion technique for wearable devices is an ideal solution for resource-constrained infrastructures such as IoT and the Internet ofMedical Things,where both device privacy and information integrity are important.Finally,the proposed hybrid approach is proven against well-known intruder attacks,especially those related to the privacy of the respective device in IoT infrastructures.

Smart object recommendation based on topic learning and joint features in the social internet of things

With the extensive integration of the Internet,social networks and the internet of things,the social internet of things has increasingly become a significant research issue.In the social internet of things application scenario,one of the greatest challenges is how to accurately recommend or match smart objects for users with massive resources.Although a variety of recommendation algorithms have been employed in this field,they ignore the massive text resources in the social internet of things,which can effectively improve the effect of recommendation.In this paper,a smart object recommendation approach named object recommendation based on topic learning and joint features is proposed.The proposed approach extracts and calculates topics and service relevant features of texts related to smart objects and introduces the“thing-thing”relationship information in the internet of things to improve the effect of recommendation.Experiments show that the proposed approach enables higher accuracy compared to the existing recommendation methods.

Effect of non-pharmacological treatment on the full recovery of social functioning in patients with attention deficit hyperactivity disorder

BACKGROUND Long-term treatment of attention deficit/hyperactivity disorder(ADHD)is associated with adverse events,such as nausea and vomiting,dizziness,and sleep disturbances,and poor maintenance of late ADHD medication compromises treatment outcomes and prolongs the recovery of patients’social functioning.AIM To evaluate the effect of non-pharmacological treatment on the full recovery of social functioning in patients with ADHD.METHODS A total of 90 patients diagnosed with ADHD between May 2019 and August 2020 were included in the study and randomly assigned to either the pharmacological group(methylphenidate hydrochloride and tomoxetine hydrochloride)or the non-pharmacological group(parental training,behavior modification,sensory integration therapy,and sand tray therapy),with 45 cases in each group.Outcome measures included treatment compliance,Swanson,Nolan,and Pelham,Version IV(SNAP-IV)scores,Conners Parent Symptom Questionnaire(PSQ)scores,and Weiss Functional Impairment Rating Scale(WFIRS)scores.RESULTS The non-pharmacological interventions resulted in significantly higher compliance in patients(95.56%)compared with medication(71.11%)(P<0.05).However,no significant differences in SNAP-IV and PSQ scores,in addition to the learning/school,social activities,and adventure activities of the WFIRS scores were observed between the two groups(P>0.05).Patients with non-pharmacological interventions showed higher WFIRS scores for family,daily life skills,and self-concept than those in the pharmacological group(P<0.05).CONCLUSION Non-pharmacological interventions,in contrast to the potential risks of adverse events after longterm medication,improve patient treatment compliance,alleviate patients’behavioral symptoms of attention,impulsivity,and hyperactivity,and improve their cognitive ability,thereby improving family relationships and patient self-evaluation.

Application of Physical Unclonable Function for Lightweight Authentication in Internet of Things

IoT devices rely on authentication mechanisms to render secure message exchange.During data transmission,scalability,data integrity,and processing time have been considered challenging aspects for a system constituted by IoT devices.The application of physical unclonable functions(PUFs)ensures secure data transmission among the internet of things(IoT)devices in a simplified network with an efficient time-stamped agreement.This paper proposes a secure,lightweight,cost-efficient reinforcement machine learning framework(SLCR-MLF)to achieve decentralization and security,thus enabling scalability,data integrity,and optimized processing time in IoT devices.PUF has been integrated into SLCR-MLF to improve the security of the cluster head node in the IoT platform during transmission by providing the authentication service for device-to-device communication.An IoT network gathers information of interest from multiple cluster members selected by the proposed framework.In addition,the software-defined secured(SDS)technique is integrated with SLCR-MLF to improve data integrity and optimize processing time in the IoT platform.Simulation analysis shows that the proposed framework outperforms conventional methods regarding the network’s lifetime,energy,secured data retrieval rate,and performance ratio.By enabling the proposed framework,number of residual nodes is reduced to 16%,energy consumption is reduced by up to 50%,almost 30%improvement in data retrieval rate,and network lifetime is improved by up to 1000 msec.

Dynamics modeling and optimal control for multi-information diffusion in Social Internet of Things

As an ingenious convergence between the Internet of Things and social networks,the Social Internet of Things(SIoT)can provide effective and intelligent information services and has become one of the main platforms for people to spread and share information.Nevertheless,SIoT is characterized by high openness and autonomy,multiple kinds of information can spread rapidly,freely and cooperatively in SIoT,which makes it challenging to accurately reveal the characteristics of the information diffusion process and effectively control its diffusion.To this end,with the aim of exploring multi-information cooperative diffusion processes in SIoT,we first develop a dynamics model for multi-information cooperative diffusion based on the system dynamics theory in this paper.Subsequently,the characteristics and laws of the dynamical evolution process of multi-information cooperative diffusion are theoretically investigated,and the diffusion trend is predicted.On this basis,to further control the multi-information cooperative diffusion process efficiently,we propose two control strategies for information diffusion with control objectives,develop an optimal control system for the multi-information cooperative diffusion process,and propose the corresponding optimal control method.The optimal solution distribution of the control strategy satisfying the control system constraints and the control budget constraints is solved using the optimal control theory.Finally,extensive simulation experiments based on real dataset from Twitter validate the correctness and effectiveness of the proposed model,strategy and method.

Analysing the Social Media Momo Phenomenon:Causes and Effects

The“Momo Army”is an anonymous group on social media platforms like Douban and Xiaohongshu.It uses similar avatars and nicknames to demonstrate collective identity and engage in group interactions.This group rapidly forms a strong network of interaction,establishing stable group relationships,and achieving digital invisibility.However,anonymous groups conceal anonymous violence and cyberbullying,negatively affecting individuals and society.This study will explore the reasons for the emergence of such groups,self-presented characteristics of their group members,and social impacts.It will conduct in-depth research and analysis through participant observation and interviews.

Relationship between primary caregivers’social support function,anxiety,and depression after interventional therapy for acute myocardial infarction patients

BACKGROUND An acute myocardial infarction(AMI)is often treated with direct coronary intervention and requires home-based rehabilitation.Caregivers of patients with AMI need adequate social support to maintain high-quality care;however,their social support function is low,and relevant indicators for intervention must be identified.AIM To analyze the correlation between social support for primary caregivers,their anxiety,and depression,when caring for patients with AMI after interventional therapy.METHODS Using convenience sampling,we selected 300 primary caregivers of patients with AMI who had undergone interventional therapy.The Social Support Rating Scale(SSRS),Self-Rating Anxiety Scale(SAS),and Self-Rating Depression Scale(SDS)were used to assess the primary caregivers.A Pearson’s correlation analysis was used to analyze the correlations between the SSRS,SAS,and SDS,and a multiple logistic regression analysis was used to analyze the factors influencing the low social support function of primary caregivers.The receiver operating characteristic curve and area under the curve(AUC)were used to evaluate the predictive ability of the SAS and SDS for low social support function in primary caregivers.RESULTS Considering the norm among Chinese people,AMI caregivers’objective support,subjective support,support utilization,and SSRS scores were lower,while their SAS and SDS scores were higher.The SSRS scores of female caregivers were higher than those of the male caregivers(t=2.123,P=0.035).The Pearson correlation analysis showed that objective support,subjective support,support utilization,and SSRS total scores were significantly correlated with both SAS(r=-0.414,-0.460,-0.416,-0.535)and SDS scores(r=-0.463,-0.379,-0.349,-0.472).Among the 300 AMI caregivers,56 cases(18.67%)had a low level of support function(SSRS≤22 points).Logistic regression model analysis showed that SAS and SDS were independent risk factors for low social support function of AMI caregivers,regardless of adjustment for other variables(P<0.05).SAS and SDS predicted that the AUC of AMI caregivers with low support function was 0.84,sensitivity was 67.9 and 71.4,and specificity was 84.0 and 70.9,respectively.CONCLUSION The social support function of the primary caregiver of patients with AMI after interventional therapy was lower and negatively correlated with anxiety and depression in the primary caregiver.

Reflections on,and Improvements of,the Mediation Functions of People's Assessors

Legislatively,the people’s assessors are defined as individuals who share judicial power.However,in the context of dispute resolutions,their role is restricted by the courts,which affects the extent of their assessorial activities.It is imperative to reconsider the implications of the people’s assessors’deep involvement in mediation from the standpoint of societal division of labor.To enhance this division of labor,it is advisable that the people’s assessors relinquish their mediation roles.It is necessary to redefine the distinctions between people’s assessors,judges,and people’s mediators,including specially invited mediators.This would not only make up the deficiencies in the role of professional judges but also relieve the tension between judicial professionalism and popular accountability.

The Impact of Internet Usage on Youth Social Interaction in China

The purpose of this paper intends to explore specifically whether heavy usage of the Internet by youths increase or decrease their social interaction opportunities. Issues that will be examined include that of the change of face-to-face communication between the youth and their families, friends and social activities. A quantitative research method with questionnaires is adopted to meet the objective of this study.

Social learning contributions to the etiology and treatment of functional abdominal pain and inflammatory bowel disease in children and adults

This paper reviews empirical work on cognitive and social learning contributions to the etiology and treatment of illness behavior associated with functional abdominal pain and inflammatory bowel disease. A particular emphasis is placed on randomized controlled trials, the majority of which are multi-modal in orientation, incorporating elements of cognitive behavioral therapy, social learning, and relaxation. Based on this review, we offer methodological and clinical suggestions: (1) Research investigations should include adequate sample sizes, long-term follow-up assessments, and a credible, active control group. (2) Standard gastrointestinal practice should include, when appropriate, learning opportunities for patients and family members, for example, instruction regarding the encouragement of wellness behavior.

ED-SWE:Event detection based on scoring and word embedding in online social networks for the internet of people

Online social media networks are gaining attention worldwide,with an increasing number of people relying on them to connect,communicate and share their daily pertinent event-related information.Event detection is now increasingly leveraging online social networks for highlighting events happening around the world via the Internet of People.In this paper,a novel Event Detection model based on Scoring and Word Embedding(ED-SWE)is proposed for discovering key events from a large volume of data streams of tweets and for generating an event summary using keywords and top-k tweets.The proposed ED-SWE model can distill high-quality tweets,reduce the negative impact of the advent of spam,and identify latent events in the data streams automatically.Moreover,a word embedding algorithm is used to learn a real-valued vector representation for a predefined fixed-sized vocabulary from a corpus of Twitter data.In order to further improve the performance of the Expectation-Maximization(EM)iteration algorithm,a novel initialization method based on the authority values of the tweets is also proposed in this paper to detect live events efficiently and precisely.Finally,a novel automatic identification method based on the cosine measure is used to automatically evaluate whether a given topic can form a live event.Experiments conducted on a real-world dataset demonstrate that the ED-SWE model exhibits better efficiency and accuracy than several state-of-art event detection models.

A Brief Study of the Pragmatic Functions of English Euphemism in Social Life

Euphemism,as a unique form in language expression,conveys a lot about the society and culture in which it exits.This paper studies the functions of euphemism and its application of euphemisms in social-cultural activities.

Automated Service Search Model for the Social Internet of Things

The social internet of things(SIoT)is one of the emerging paradigms that was proposed to solve the problems of network service discovery,navigability,and service composition.The SIoT aims to socialize the IoT devices and shape the interconnection between them into social interaction just like human beings.In IoT,an object can offer multiple services and different objects can offer the same services with different parameters and interest factors.The proliferation of offered services led to difficulties during service customization and service filtering.This problem is known as service explosion.The selection of suitable service that fits the requirements of applications and objects is a challenging task.To address these issues,we propose an efficient automated query-based service search model based on the local network navigability concept for the SIoT.In the proposed model,objects can use information from their friends or friends of their friends while searching for the desired services,rather than exploring a global network.We employ a centrality metric that computes the degree of importance for each object in the social IoT that helps in selecting neighboring objects with high centrality scores.The distributed nature of our navigation model results in high scalability and short navigation times.We verified the efficacy of our model on a real-world SIoT-related dataset.The experimental results confirm the validity of our model in terms of scalability,navigability,and the desired objects that provide services are determined quickly via the shortest path,which in return improves the service search process in the SIoT.

Internet Addiction： Just Facebook Me! The Role of Social Networking Sites in Internet Addiction

Internet based social-networking sites like Facebook are highly attractive, user-friendly, and increasingly popular. Current estimates indicate over 750 million users of Facebook alone. However, Internet addiction is an increasing problem amongst today＇s youth and as yet, is understudied in the United States. This study looked at the relationship between this new social-networking tool and the increasing phenomenon of internet addiction symptoms using both a US college sample （age 19years） and a US high-school sample （age 14years）. Findings indicate that SNS （Social Networking Site） activity maybe more predictive of addictive behaviors than general internet use and that higher percents of symptomology occur in those users reporting SNS activity as their primary internet activity.

C-E Translation of Internet Neologisms from the Perspective of Functional Equivalence

With the rapid development of China' s economy and society,neologisms are involved in every field and continue to boom.However,Internet neologisms have an important influence on our mind and language form and update the way of information transmission and communication as well.It rapidly steps into people s life with different style and reflect social phenomenon and special cultural connotation with its unique charm.It is necessary to be aware of Internet neologisms translation when applying them into the language system.To those foreign readers who differ from Chinese mind and culture,inappropriate translation could result in misunderstanding and further cause communication failure.Hence,English translation for Internet neologisms should be placed considerable value.This paper will employ Eugene A.Nida s functional equivalence to probe into translation methods of Internet neologisms in order to find out appropriate translation.

On the English Translation of Chinese Internet Catchwords from the Perspective of Functional Equivalence Theory

Due to the long history of China,the special features of the Chinese Internet catchwords and the few translations of the Chinese Internet catchwords at home and abroad,it is very hard for the foreigners to comprehend the Chinese Internet catchwords.Functional Equivalence Theory is put forward by an American translation theorist,Eugene A.Nida,which casts great influence on the translation circle.This paper applies the literal translation and the free translation to translate the Chinese Internet catchwords in the light of functional equivalence theory.

Set pair three-way overlapping community discovery algorithm for weighted social internet of things

There are many problems in Social Internet of Things(IoTs),such as complex topology information,different degree of association between nodes and overlapping communities.The idea of set pair information grain computing and clustering is introduced to solve the above problems so as to accurately describe the similarity between nodes and fully explore the multi-community structure.A Set Pair Three-Way Overlapping Community Discovery Algorithm for Weighted Social Internet of Things(WSIoT-SPTOCD)is proposed.In the local network structure,which fully considers the topological information between nodes,the set pair connection degree is used to analyze the identity,difference and reverse of neighbor nodes.The similarity degree of different neighbor nodes is defined from network edge weight and node degree,and the similarity measurement method of set pair between nodes based on the local information structure is proposed.According to the number of nodes'neighbors and the connection degree of adjacent edges,the clustering intensity of nodes is defined,and an improved algorithm for initial value selection of k-means is proposed.The nodes are allocated according to the set pair similarity between nodes and different communities.Three-way community structures composed of a positive domain,boundary domain and negative domain are generated iteratively.Next,the overlapping node set is generated according to the calculation results of community node membership.Finally,experiments are carried out on artificial networks and real networks.The results show that WSIoT-SPTOCD performs well in terms of standardized mutual information,overlapping community modularity and F1.

Effect of cognitive behavioral group therapy on rehabilitation of community patients with schizophrenia:A short-term randomized control trial

BACKGROUND The efficacy of cognitive behavioral group therapy(CBGT)for cognitive dysfunction and negative symptoms of schizophrenia is established,but more evidence is required.AIM To assess the effectiveness of CBGT combined with mental health education as a treatment for schizophrenia compared with mental health education alone.METHODS In all,120 schizophrenia out-patients were randomized into CBGT combined with mental health education or single mental health education.The primary outcomes were positive and negative symptoms,cognitive function,excitatory factor,anxiety and depression symptom improvements on the positive and negative syndrome scale score.Secondary outcome measures included social function and drug compliance.RESULTS There were significant differences between CBGT combined with mental health education and single mental health education on measures of positive and negative symptoms,cognitive functions,excitatory factor,anxiety and depression symptoms,and social functions.No other significant difference in outcomes was observed.CONCLUSION CBGT combined with mental health education may be relevant beneficial treatment method in reducing symptoms,cognitive and social functions of patients with schizophrenia.