Search

Telementoring is a low-cost, flexible way for school mental health professionals to access professional learning. Using a mixed-methods intervention design, we examined the impact of prolonged telementoring on school mental health professionals' (school counselors, psychologists, social workers, and others) understanding and application of evidence-based school counseling, including associations between their use of evidence-based, culturally responsive, and collaborative practices to support student mental health. Our findings demonstrate support for the use of telementoring to improve school mental health professionals' understanding and application of the evidence-based school counseling model. We provide specific considerations for school counseling professionals.

Background: Spinal stenosis treatment includes laminectomies with or without fusion or with interspinous distraction with or without fixation. Lack of published data on interspinous fixation devices (IFD) at L5-S1 is less considered as an option due to the smaller anatomical S1 spinous process and the higher stresses from the immobile sacrum. Our objective was to evaluate the outcomes of an IFD used as a stand-alone treatment for spinal stenosis at L5-S1 and L4-5 compared to historical data on open laminectomies., Methods: Prospective comparative cohort study (Level 2) looking at collected preoperatively and postoperatively Visual Analog Scores (VAS) and Oswestry Disability Index (ODI) data, complications, and revision rates on 100 consecutive patients with spinal stenosis treated with midline decompression and InSpan (InSpan LLC, Malden, MA, USA) IFD, at L5-S1 and L4-5, up to five-year follow-up. All patients were treated by a single surgeon in an academic private practice. Historical published outcome data for open laminectomies were compared., Results: Among the 100 patients, 45 underwent surgery at L5-S1 with a mean VAS pain score that decreased by 75% and ODI improved by 63% (P<0.001). Fifty-five patients had surgery at L4-5 with mean VAS and ODI scores improved by 80% and 66% (P<0.001) respectively. Preoperative and postoperative ODI and preoperative VAS scores were similar at L5-S1 and L4-5, however, postoperative VAS scores were significantly less for L4-5 versus L5-S1 (P<0.01). All surgeries were completed in less than one hour. There was a total of one L4-5 revision (1.8%) and two L5-S1 revisions (4.4%). Comparable laminectomy data showed decrease in VAS and ODI scores by 51% and 62% (P<0.05). The reoperation rate for laminectomies at five to ten years varied up to 24%., Conclusions: Spinal stenosis patients treated with midline decompression and InSpan IFD, used as a stand-alone treatment for interspinous-interlaminar fixation, at L4-5 and L5-S1, showed improved outcome scores and low complication and revision rates at five years and were comparable to historical open laminectomy data. InSpan is a successful substitute for laminectomies in selected patients and was performed in less than 60 minutes. We recommend choosing the appropriately sized implant to achieve adequate distraction decompression to avoid recurrent symptoms., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jss.amegroups.com/article/view/10.21037/jss-23-49/coif). K.R.C. reports that he is the cofounder and CEO of KIC (Kingsley Investment Company) Ventures and has ownership shares in the company. W.M.C. and E.S. have shares in KIC (Kingsley Investment Company) Ventures. J.A.S. and K.R.C. are members of Less Exposure Surgery Specialists (LESS) Institute, a for-profit single surgeon private clinical practice. V.L. is an employee of LESSpine, a for-profit medical device company. The other authors have no conflicts of interest to declare., (2023 Journal of Spine Surgery. All rights reserved.)

In recent years DevOps and agile approaches like microservice architectures and Continuous Integration have become extremely popular given the increasing need for flexible and scalable solutions. However, several factors such as their distribution in the network, the use of different technologies, their short life, etc. make microservices prone to the occurrence of anomalous system behaviours. In addition, due to the high degree of complexity of small services, it is difficult to adequately monitor the security and behavior of microservice environments. In this work, we propose an NLP (natural language processing) based approach to detect performance anomalies in spans during a given trace, besides locating release-over-release regressions. Notably, the whole system needs no prior knowledge, which facilitates the collection of training data. Our proposed approach benefits from distributed tracing data to collect sequences of events that happened during spans. Extensive experiments on real datasets demonstrate that the proposed method achieved an F&#95;score of 0.9759. The results also reveal that in addition to the ability to detect anomalies and release-over-release regressions, our proposed approach speeds up root cause analysis by means of implemented visualization tools in Trace Compass., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s) 2022.)

Advances in technology and computing power have led to the emergence of complex and large-scale software architectures in recent years. However, they are prone to performance anomalies due to various reasons, including software bugs, hardware failures, and resource contentions. Performance metrics represent the average load on the system and do not help discover the cause of the problem if abnormal behavior occurs during software execution. Consequently, system experts have to examine a massive amount of low-level tracing data to determine the cause of a performance issue. In this work, we propose an anomaly detection framework that reduces troubleshooting time, besides guiding developers to discover performance problems by highlighting anomalous parts in trace data. Our framework works by collecting streams of system calls during the execution of a process using the Linux Trace Toolkit Next Generation(LTTng), sending them to a machine learning module that reveals anomalous subsequences of system calls based on their execution times and frequency. Extensive experiments on real datasets from two different applications (e.g., MySQL and Chrome), for varying scenarios in terms of available labeled data, demonstrate the effectiveness of our approach to distinguish normal sequences from abnormal ones.

The aim of this study was to analyze the effects of a multicomponent exercise program on the physical and hemodynamic functions of community-dwelling older adults with low schooling levels in relation to simple multicomponent group exercises. Twenty-one older people were randomly assigned to two groups: G1 ( n  = 11) and G2 ( n  = 10); sixteen of whom completed the sixteen sessions over a six-week period, three times a week. During eight sessions, G1 performed adapted dual-task multicomponent exercises (strengthening, balance, and cognition) and G2 simple multicomponent exercises (strengthening and balance), and both groups engaged in eight additional sessions of simple multicomponent exercises. The dual-task multicomponent exercises exhibited similar effects to those of their simple multicomponent counterparts. The older adults from both groups improved mobility, frailty, static postural control, balance, and hemodynamic stability. The adapted program was beneficial to the community-dwelling older people with low schooling in the group intervention., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2021 Neildja Maria da Silva et al.)

Finding modules, or clusters, in networks currently attracts much attention in several domains. The most studied criterion for doing so, due to Newman and Girvan [Phys. Rev. E 69, 026113 (2004)], is modularity maximization. Many heuristics have been proposed for maximizing modularity and yield rapidly near optimal solution or sometimes optimal ones but without a guarantee of optimality. There are few exact algorithms, prominent among which is a paper by Xu [Eur. Phys. J. B 60, 231 (2007)]. Modularity maximization can also be expressed as a clique partitioning problem and the row generation algorithm of Grötschel and Wakabayashi [Math. Program. 45, 59 (1989)] applied. We propose to extend both of these algorithms using the powerful column generation methods for linear and non linear integer programming. Performance of the four resulting algorithms is compared on problems from the literature. Instances with up to 512 entities are solved exactly. Moreover, the computing time of previously solved problems are reduced substantially.