Goal Flexibility as a Predictor of Depression, Rumination and Homesickness in Students

Objective: Theoretical and empirical evidence in the field of self-regulation and goal adjustment posits that being able to disengage from goals that are no longer attainable and reengage with new ones is related to improved wellbeing. Transition to university involves being able to successfully disengage from previous goals that have become unattainable and identify and engage in meaningful new goals, however research in this area is sparse. The current study therefore predicted that greater difficulties with goal disengagement in students would be associated with increased depressive symptoms, rumination and homesickness at the beginning of term. Difficulties with goal adjustment was further predicted to be associated with increased depressive symptoms at the end of term and this would partly be mediated by increased homesickness from the beginning to middle of term. Methods: New undergraduates completed self-report assessments on goal adjustment capacities, depressive symptoms, rumination and homesickness at baseline (N = 221) and a four-month follow up (N = 198). Data was analysed using hierarchical multiple regression and mediation analysis. Results: Goal disengagement was not significant in predicting depressive symptoms, rumination or homesickness at baseline in students. Goal reengagement was also not significant in predicting rumination or homesickness at baseline; however, it was significant in predicting depressive symptoms at baseline. Only goal reengagement was found to significantly predict fewer reported symptoms of depression at time 3. Further analysis revealed that residualised change in homesickness from baseline to time 2 did not mediate goal adjustment and depressive symptoms at the end of term. Conclusion: Despite the lack of support for goal disengagement, findings indicate that identifying and engaging in meaningful and attainable goals may be beneficial for depressive symptoms among university students during the first term

GENETIC ALGORITHM-BASED CLUSTERING OF WIRELESS SENSOR NETWORK WITH NOVEL DATA ENCRYPTION

Wireless sensor networks (WSNs) have been used widely in so many applications. It is the most efficient way to monitor the information. There areso many ways to deploy the sensors. Many problems are not identified and solved. The main challenge of WSN is energy efficiency and information security. WSN power consumption is reduced by genetic algorithm-based clustering algorithm. Information from cluster head to base station may have a lot of chances to get hacked. The most reliable way to manage energy consumption is clustering, and encryption will suit best for information security. In this paper, we explain clustering techniques and a new algorithm to encrypt the data in the network

A ‘quiet revolution’? The impact of Training Schools on initial teacher training partnerships

This paper discusses the impact on initial teacher training of a new policy initiative in England: the introduction of Training Schools. First, the Training School project is set in context by exploring the evolution of a partnership approach to initial teacher training in England. Ways in which Training Schools represent a break with established practice are considered together with their implications for the dominant mode of partnership led by higher education institutions (HEIs). The capacity of Training Schools to achieve their own policy objectives is examined, especially their efficacy as a strategy for managing innovation and the dissemination of innovation. The paper ends by focusing on a particular Training School project which has adopted an unusual approach to its work and enquires whether this alternative approach could offer a more profitable way forward. During the course of the paper, five different models of partnership are considered: collaborative, complementary, HEI-led, school-led and partnership within a partnership

Efficacy and Safety of Varenicline for Smoking Cessation in Schizophrenia: A Meta-Analysis

Objective: Smoking represents a major public health problem among patients with schizophrenia. To this end, some studies have investigated the efficacy of varenicline for facilitating smoking cessation in schizophrenia patients. The present review seeks to synthesize the results of these studies as well as document the reported side effects of using this medication. Methods: An electronic search was performed using five major databases: PubMed, Scopus, EMBASE, Web of Science, and Cochrane Library. Included in the current analysis were randomized clinical trials (RCTs) that have investigated the effect of varenicline in promoting smoking cessation in patients with schizophrenia. Risk of bias among included RCTs was assessed using the Cochrane Collaboration’s quality assessment tool. Results: Among the 828 screened articles, only four RCTs, which involved 239 participants, were eligible for meta-analysis. In patients with schizophrenia, varenicline treatment when compared to placebo significantly reduced the number of cigarettes consumed per day [SMD (95% CI) = 0.89(0.57–1.22)] and expired carbon monoxide levels [SMD (95% CI) = 0.50 (0.06–0.94)] respectively. Conclusion: Despite a limited number of studies included in the meta-analysis, our results suggest that varenicline is an effective and safe drug to assist smoking cessation in patients with schizophrenia. Future large-scale well-designed RCTs are required to validate these findings

Cognitive Behavioral Therapy versus Eye Movement Desensitization and Reprocessing in Patients with Posttraumatic Stress Disorder: Systematic Review and Meta-analysis of Randomized Clinical Trials

Background Post-traumatic stress disorder (PTSD) is prevalent in children, adolescents and adults. It can occur alone or in comorbidity with other disorders. A broad range of psychotherapies such as cognitive behavioral therapy (CBT) and eye movement desensitization and reprocessing (EMDR) have been developed for the treatment of PTSD. Aim Through quantitative meta-analysis, we aimed to compare the efficacy of CBT and EMDR: (i) relieving the post-traumatic symptoms, and (ii) alleviating anxiety and depression, in patients with PTSD. Methods We systematically searched EMBASE, Medline and Cochrane central register of controlled trials (CENTRAL) for articles published between 1999 and December 2017. Randomized clinical trials (RCTs) that compare CBT and EMDR in PTSD patients were included for quantitative meta-analysis using RevMan Version 5. Results Fourteen studies out of 714 were finally eligible. Meta-analysis of 11 studies (n = 547) showed that EMDR is better than CBT in reducing post-traumatic symptoms [SDM (95% CI) = -0.43 (-0.73 – -0.12), p = 0.006]. However, meta-analysis of four studies (n = 186) at three-month follow-up revealed no statistically significant difference [SDM (95% CI) = -0.21 (-0.50 – 0.08), p = 0.15]. The EMDR was also better than CBT in reducing anxiety [SDM (95% CI) = -0.71 (-1.21 – -0.21), p = 0.005]. Unfortunately, there was no difference between CBT and EMDR in reducing depression [SDM (95% CI) = -0.21 (-0.44 – 0.02), p = 0.08]. Conclusion The results of this meta-analysis suggested that EMDR is better than CBT in reducing post-traumatic symptoms and anxiety. However, there was no difference reported in reducing depression. Large population randomized trials with longer follow-up are recommended to build conclusive evidence

Design of Multi-Layer Protocol Architecture using Hybrid Optimal Link State Routing (HOLSR) Protocol for CR Networks

There is a lack of spectrum due to the rising demand for sensing device communication and the inefficient use of the existing available spectrum. Through opportunistic access to licenced bands, which does not obstruct the primary sensory users (PU), it is feasible to enhance the inefficient use of the current sensor device frequency spectrum. Cognitive settings are a demanding environment in which to carry out tasks like sensor network routing and spectrum access since it is difficult to access channels due to the presence of PUs. The basic goal of the routing problem in sensor networks is to establish and maintain wireless sensor multihop paths between cognitive sensor nodes. The frequency to be used as well as the number of hops at each sensor node along the path must be determined for this assignment. In order to improve performance while using less energy, scientists suggested a unique adaptive cross-layer optimisation subcarrier distribution technique with the HOLSR protocol for wireless sensor nodes. Throughput and energy consumption parameters are used to analyse the sensor network architecture protocol that has been developed. The energy usage of the sensor nodes in the network has increased by 50%. The performance of the proposed HOLSR algorithm is assessed using the simulation results, and the results are contrasted with those of a conventional multicarrier (MC) system in terms of bit error rate and throughput

5G Enabled Moving Robot Captured Image Encryption with Principal Component Analysis Method

Estimating the captured image of moving robots is very difficult. These images are vital in analyzing earth's surface objects for many applications like studying environmental conditions, Land use and Land Cover changes, and change detection studies of worldwide change. Multispectral robot-captured images have a massive amount of low-resolution data, which is lost due to a lack of capture efficiency due to artificial and atmospheric reasons. The image transformation is required in a 5G network with effective transmission by reducing noise, inconsistent lighting, and low resolution, degrading image quality. In this paper, the authors proposed the machine learning dimensionality reduction technique i.e. Principle Component Analysis (PCA) and which is used for metastasizing the 5 G-enabled moving robot captured image to enrich the image's visual perception to analyze the exact information of global or local data. The encryption algorithm implanted for data reduction and transmission over the 5G network gives sophisticated results compared with other standard methods. This proposed algorithm gives better performance in developing data reduction, network convergence speed, reduces the training time for object classification, and improves accuracy for multispectral moving robot-captured images by the support of 5G network

Xylazine in the Opioid Epidemic: A Systematic Review of Case Reports and Clinical Implications

Introduction and objectives: The opioid overdose epidemic is exacerbated by the emergence of Xylazine as an illicit drug adulterant. Xylazine, a veterinary sedative, can potentiate opioid effects while also causing toxic and potentially fatal side effects. This systematic review aims to assess the impact of Xylazine use and overdoses within the opioid epidemic context.Method: A systematic search was conducted following PRISMA guidelines to identify relevant case reports, and case series related to Xylazine use. A comprehensive literature search included databases like Web of Science, PubMed, Embase, and Google Scholar, utilizing keywords and Medical Subject Headings (MeSH) terms related to Xylazine. Thirty-four articles met the inclusion criteria for this review. Results: Intravenous (IV) administration was a common route for Xylazine use among various methods, including subcutaneous (SC), intramuscular (IM), and inhalation, with overall doses ranging from 40 mg to 4300 mg. The average dose in fatal cases was 1,200 mg, compared to 525 mg in non-fatal cases. Concurrent administration of other drugs, primarily opioids, occurred in 28 cases (47.5%). Intoxication was identified as a notable concern in 32 out of 34 studies, and treatments varied, with the majority experiencing positive outcomes. Withdrawal symptoms were documented in one case study, but the low number of cases with withdrawal symptoms may be attributed to factors such as a limited number of cases or individual variation. Naloxone was administered in eight cases (13.6%), and all patients recovered, although it should not be misconstrued as an antidote for Xylazine intoxication. Of the 59 cases, 21 (35.6%) resulted in fatal outcomes, with 17 involving Xylazine use in conjunction with other drugs. The IV route was a common factor in six out of the 21 fatal cases (28.6%). Conclusion: This review highlights the clinical challenges associated with Xylazine use and its co-administration with other substances, particularly opioids. Intoxication was identified as a major concern, and treatments varied across the studies, including supportive care, naloxone, and other medications. Further research is needed to explore the epidemiology and clinical implications of Xylazine use. Understanding the motivations and circumstances leading to Xylazine use, as well as its effects on users, is essential for developing effective psychosocial support and treatment interventions to address this public health crisis

The Effectiveness of Selective Serotonin Reuptake Inhibitors for Treatment of Obsessive-Compulsive Disorder in Adolescents and Children: A Systematic Review and Meta-Analysis

Background: Obsessive-compulsive disorder (OCD) is a common behavioral disorder among adolescents and children. The selective serotonin reuptake inhibitors (SSRIs) are the first pharmacological choice for this condition due to mild adverse effect profile. Objective: This systematic review was performed to evaluate the efficacy of SSRI for OCD in adolescents and children. Methods: Search terms were entered into PubMed, PsycINFO, Scopus, CINAHL, and Google Scholar. The included studies were randomized, placebo-controlled trials of SSRIs conducted in populations of children and adolescents younger than 18 years. Change from baseline Children\u27s Yale-Brown Obsessive-Compulsive Scale (CY-BOCS), end-treatment CY-BOCS with respective SD, and response and remission rates were collected for continuous and dichotomous outcome assessment, respectively. Cochrane Rev Man software was used for meta-analyses, providing Forest plots where applicable. Results: SSRIs were superior to placebo with a small effect size. There was no additional benefit of combination treatment over cognitive behavioral therapy (CBT) alone, but CBT added substantial benefit to SSRI monotherapy. Fluoxetine and sertraline appear to be superior to fluvoxamine. Conclusion: The results of current systematic review and meta-analysis support the existing National Institute for Health and Care Excellence (NICE) guidelines for choosing CBT as first line of treatment and substituting it with SSRI, depending on patient preference. Adding CBT to current SSRI treatment is effective for non-responders and partial responders, but adding SSRI to ongoing CBT does not prove beneficial. The SSRIs have different effectiveness, and their relative efficacy remains to be investigated