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Effective treatments for Substance Use Disorders (SUDs) are of critical importance, particularly among veterans. We present a successful application of Transcending Self Therapy: Four-Session Individual Integrative Cognitive Behavioral Treatment (Individual TST-I-CBT), that helped a male combat veteran with Alcohol Use Disorder, Severe, and PTSD enter recovery and reduce depressive symptoms. Session 1 focused on problem solving and behaviors; Session 2 centered on checking and changing thoughts; Session 3 emphasized behaviors, thoughts, and coping; and Session 4 consisted of review and finalizing the recovery plan. After the second Individual TST-I-CBT session, he was abstinent from alcohol use and remained abstinent throughout the remainder of treatment. At the end of treatment, his depressive symptoms declined substantially from pretreatment (from severe to low), his desire to stop using alcohol was 10/10, and his confidence in his ability to stop using alcohol was 10/10. He demonstrated personal growth and accomplishments throughout the course of treatment, such as improving his self-concept and relationships; living in accordance with his values; developing the passionate pursuit of being a productive member of society by holding a job; looking for a job; and taking steps to continue his education. Accordingly, he accomplished all of his identified treatment goals. This case suggests Individual TST-I-CBT is a potentially effective adjunctive treatment for SUD. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Verstek's decision is a decision handed down by the judge without the presence of the defendant or respondent at the trial, the principle that the judge is authorized to make a decision or not without the presence of the defendant at the trial so that the judge has facultative rights, in this case referring to article 126 HIR (about verstek) as a reference: 1. The absence of the defendant at the first hearing that authorized the judgeimmediately to decide on the verstek 2. Delay the session and call the defendant once again. In such legal cases / events, the position of the defendant / defendant in the divorce case is always in a weak position, especially if the respondent is a woman, with all her limitations she will always be passive and difficult to provide resistance is most likely caused by the following factors: a. Unclear address; b. The call (relas) for the trial does not arrive; c. Lack of understanding procedures in court proceedings and reluctance to consult; d. More resigned and accept fate.

Raising incidents of security threats among active sessions is an increasing concern in IoT environment. Continuous authentication was introducing to be superior to traditional authentication schemes by constantly verify users’ identities on an ongoing basis and spot the moment at which an illicit attacker seizes control of the session. However, several challenges remain unsolved. This research aims to investigate the power of Blockchain technology to provide real-time and non-intrusive continuous authentication for the IoT environment. Accordingly, a distributed and scalable continuous authentication solution based on Blockchain technology called CAB-IoT was proposed. It enabled fog nodes layer that tackles the limitations of IoT resources by providing localized processing of heavy continuous authentication-related tasks for a group of IoT devices. Besides, CAB-IoT introduced a trust module that depends on the face recognition machine learning model to detect outliers and abnormal access. Moreover, mutual authentication between end-users and fog nodes is also designed, as well as secure communication between the authenticated nodes. The results demonstrate a lightweight continuous authentication solution that achieved the desired balance between security and performance requirements where it was observed in a real-world environment for truly performance results. Security analysis and attack analysis are also considered during the evaluation.

BACKGROUND: Due to the SARS-COV2 pandemic-related restrictions the 2020 Belgian Surgical Week (BSW) was organized as a virtual congress, being the first surgical, virtual congress in Belgium. Since this was a new experience and probably not the last, we aim to share our experience to assist other professionals in organizing their virtual events. METHODS: The 'BSW-light' was organized by the RBSS in collaboration with a Professional Congress Organizer (PCO), which is described in detail. Analytical data of the event were provided by the PCO and a UEMS 'live educational events participant evaluation form' based survey was sent out to all registered participants, using google forms, to evaluate the event. RESULTS: During 2 days, 78 prerecorded presentations were broadcasted in 2 virtual conference rooms, each followed by a live Q & A session. The plenary session on the third day contained 8 live presentations, both from Belgium and from abroad. A total of 503 people registered for the congress, of whom 224 trainees. Each session attracted 158 visitors on average, each spending an average of 73 min. Attendees were satisfied with the technical aspect of the virtual congress, but they preferred an event that is at least partially live. CONCLUSION: Although the 'BSW-light' proved to be successful, a preference to meet in real life remained. However, given its potential, we should keep an open mind towards integrating the advantages of a virtual meeting into a live event. ispartof: ACTA CHIRURGICA BELGICA vol:123 issue:2 pages:105-109 ispartof: location:England status: published

While 5G can facilitate high-speed Internet access and make over-the-horizon control a reality for unmanned aerial vehicles (UAVs; also known as drones), there are also potential security and privacy considerations, for example, authentication among drones. Centralized authentication approaches not only suffer from a single point of failure, but they are also incapable of cross-domain authentication, which complicates the cooperation of drones from different domains. To address these limitations, a blockchain-based cross-domain authentication scheme for intelligent 5G-enabled Internet of drones is proposed in this paper. Our approach employs multiple signatures based on threshold sharing to build an identity federation for collaborative domains. This allows us to support domain joining and exiting. Reliable communication between cross-domain devices is achieved by utilizing smart contract for authentication. The session keys are negotiated to secure subsequent communication between two parties. Our security and performance evaluations show that the proposed scheme is resistant to common attacks targeting Internet of Things (IoT) devices (including drones), as well as demonstrating its effectiveness and efficiency.

Mobile app users are often exposed to a sequence of short-lived marketing interventions (e.g., ads) within each usage session. This study examines how an increase in the variety of ads shown in a session affects a user's response to the next ad. The authors leverage the quasi-experimental variation in ad assignment in their data and propose an empirical framework that accounts for different types of confounding to isolate the effects of a unit increase in variety. Across a series of models, the authors consistently show that an increase in ad variety in a session results in a higher response rate to the next ad: holding all else fixed, a unit increase in variety of the prior sequence of ads can increase the click-through rate on the next ad by approximately 13%. The authors then explore the underlying mechanism and document empirical evidence for an attention-based account. The article offers important managerial implications by identifying a source of interdependence across ad exposures that is often ignored in the design of advertising auctions. Furthermore, the attention-based mechanism suggests that platforms can incorporate real-time attention measures to help advertisers with targeting dynamics.

In recent years, traditional logistics systems are developing towards intelligence based on the Internet of Things (IoT). Sensing devices throughout the logistics network provide strong support for smart logistics. However, due to the insufficient local computing and storage resources of IoT (Internet of things) devices, logistics records with sensitive information are generally stored in a centralized cloud center, which could easily cause privacy leakage. In this study, we propose a blockchain-assisted secure storage scheme for logistics data. To be specific, this scheme can be briefly divided into two parts. The first part involves data generation and aggregation, session establishing, records encryption and storage, wherein a blockchain network is used to assist the cloud server with data storage, and smart contracts are deployed to provide reliable storage interfaces. In the second part, an efficient consensus mechanism is introduced to improve the efficiency of the consensus process. Also, the stored records can be securely audited by leveraging the deployed blockchain network. Finally, we analyze the security and privacy properties of this scheme and evaluate its performance in terms of computation and communication overhead by developing an experimental platform. The experimental results indicate that the performance of our scheme is acceptable.

We developed a mixed-integer linear programming model to plan exam sessions for external candidates in the Vestfold region, Norway. With our model, the administration planned the last session of 2018, the two sessions of 2019, and the first session of 2020. The plans produced are of high quality and saved three weeks of person effort per session.

Considering sessions as directed subgraphs, Graph Neural Networks (GNNs) are supposed to be capable of capturing the complex dependencies among items and suitable for session-based recommendation. However, deep GNNs suffer from the over-smoothing problem of making all nodes converge to the same value. In session-based recommendation, the subgraphs transformed by short sessions are usually simple, which cause worse over-smoothing problem. To apply GNNs to session-based recommendation sufficiently, we propose a Hybrid-order Gated Graph Neural Network (HGNN) on account of the over-smoothing problem. The proposed HGNN model is based on the hybrid-order propagation, which avoids insignificant patterns and captures complex dependencies in propagation. What's more, the attention mechanism is utilized to learn different weights of orders in propagation. Then HGNN is applied to session-based recommendation, which results in a new method called SR-HGNN. Experimental results show that SR-HGNN outperforms the state-of-the-art session-based recommendation methods and eases the over-smoothing problem.

As the usability of IoT devices increases, the security threats and vulnerabilities associated with these resource-constrained IoT devices also rise. One of the major threats to IoT devices is Distributed Denial of Service (DDoS). To make the security of IoT devices effective and resilient, continuous monitoring and early detection, along with adaptive decision making, are required. These challenges can be addressed with Software-defined Networking (SDN), which provides an opportunity for effectively managing the DDoS threats faced by IoT devices. This research proposes a novel SDN-based secure IoT framework that can detect the vulnerabilities in IoT devices or malicious traffic generated by IoT devices using session IP counter and IP Payload analysis. The framework’s DDoS attack detection module consisting of proposed algorithms can easily detect the DDoS attack in the SD-IoT network by analyzing different parameters even with a large traffic volume. These techniques are implemented on an SDN controller and tested by generating a large volume of traffic from a compromised node which is then detected and notified. According to results and comparative analysis, the proposed framework detects DDoS attacks in the early stage with high accuracy and detection rate from 98% to 100%, having a low false-positive rate.

Background: Besides maintaining health precautions, vaccination has been the only prevention from SARS-CoV-2, though no clinically proved 100% effective vaccine has been developed till date. At this stage, to withhold the debris of this pandemic-experts need to know the impact of the vaccine efficacy rates, the threshold level of vaccine effectiveness and how long this pandemic may extent with vaccines that have different efficacy rates. In this article, a mathematical model study has been done on the importance of vaccination and vaccine efficiency rate during an ongoing pandemic. Methods: We simulated a five compartment mathematical model to analyze the pandemic scenario in both California, and whole U.S. We considered four vaccines, Pfizer (95%), Moderna (94%), AstraZeneca (79%), and Johnson & Johnson (72%), which are being used rigorously to control the SARS-CoV-2 pandemic, in addition with two special cases: a vaccine with 100% efficacy rate and no vaccine under use. SARS-CoV-2 related data of California, and U.S. were used in this study. Findings: Both the infection and death rates are very high in California. Our model suggests that the pandemic situation in California will be under control in the last quartile of the year 2023 if vaccination program is continued with the Pfizer vaccine. During this time, six waves may happen from the beginning of the immunization where the case fatality and recovery rates will be 1.697% and 98.30%, respectively. However, according to the considered model, this period might be extended to the mid of 2024 when vaccines with lower efficacy rates are used. On the other hand, the daily cases and deaths in the U.S. will be under control at the end of 2026 with multiple waves. Although the number of susceptible people will fall down to none in the beginning of 2027, there is less chance to stop the vaccination program if vaccinated with a vaccine other than a 100% effective vaccine or Pfizer, and at that case vaccination program must run till the mid of 2028. According to this study, the unconfirmed-infectious and infected cases will be under control at the end of 2027 and at the mid of 2028, respectively. Interpretation: The more effective a vaccine is, the less people suffer from this malign infection. Vaccines which are less than 90% effective do not have notable contribution to control the pandemic besides hard immunity. Furthermore, specific groups of people are getting prioritized initially, mass vaccination and quick responses are required to control the spread of this disease.

Internet of Things (IoT) produces massive heterogeneous data from various applications, including digital health, smart hospitals, automated pathology labs, and so forth. IoT sensor nodes are integrated with the medical equipment to enable the health workers to monitor the patients’ health condition and appliances in real-time. However, due to security vulnerabilities, an unauthorized user can access health-related information or control the IoT nodes attached to the patient’s body resulting in unprecedented outcomes. Due to wireless channels as a medium of communication, IoT poses several threats such as a denial of service attack, man-in-the-middle attack, and modification attack to the IoT networks’ security and privacy. The proposed research presents a lightweight and anonymity-preserving user authentication protocol to counter these security threats. The given scheme establishes a secure session for the legitimate user and prohibits unauthorized users from gaining access to the IoT sensor nodes. The proposed protocol uses only lightweight cryptography primitives (hash) to alleviate the node’s tiny processor burden. The proposed protocol is efficient and superior because it has low computational and communication costs than conventional protocols. The proposed scheme uses password protection to let only the legitimate user access the IoT sensor nodes to obtain the patient’s real-time health report.

Session-based recommendation is an overwhelming task owing to the inherent ambiguity in anonymous behaviors. Graph convolutional neural networks are receiving wide attention for session-based recommendation research for the sake of their ability to capture the complex transitions of interactions between sessions. Recent research on session-based recommendations mainly focuses on sequential patterns by utilizing graph neural networks. However, it is undeniable that proposed methods are still difficult to capture higher-order interactions between contextual interactions in the same session and has room for improvement. To solve it, we propose a new method based on graph attention mechanism and target oriented items to effectively propagate information, HOGAN for brevity. Higher-order graph attention networks are used to select the importance of different neighborhoods in the graph that consists of a sequence of user actions for recommendation applications. The complementarity between high-order networks is adopted to aggregate and propagate useful signals from the long distant neighbors to solve the long-range dependency capturing problem. Experimental results consistently display that HOGAN has a significantly improvement to 71.53% on precision for the Yoochoose1_64 dataset and enhances the property of the session-based recommendation task.

Session-based recommendation leverages anonymous sessions to predict which item a user is most likely to click on next. While previous approaches capture items-transition patterns within current session and neighbor sessions, they do not accurately filter out noise within session or widen the range of feasible data in a more reasonable way. In a current session, the user may accidentally click on an unrelated item, resulting in the fact that, the users’ primary intents from neighbor sessions, may mismatch the current session. Thereby, we propose a new framework, dubbed Graph Neural Networks with Global Noise Filtering for Session-based Recommendation (GNN-GNF), aiming to filter noisy data and exploit items-transition patterns in a more comprehensive and reasonable manner. In simple terms, GNN-GNF contains two parts: data preprocessing and model learning. In data preprocesing, an item-level filter module is used to obtain the main intent of user and a session-level filter module is designed to filter the sessions unrelated to the target session intent by means of edge matching. In model learning, we consider both local-level interest obtained by an aggregation of the items representing the main intent of user within a session, and global-level interest deduced from a global graph. We take two kinds of neighbor aggregations, summation and interactive aggregation, respectively, to iteratively derive the representation of the central node in the global graph. Finally, GNN-GNF concatenates the local and global preference to characterize the current session, towards better recommendation prediction. Experiments on two datasets demonstrate that GNN-GNF can achieve competitive results. The source code is available at: https://github.com/Fenglixia/GNF.

68Ga-DOTATATE PET-CT is routinely used for imaging neuroendocrine tumor (NET) somatostatin receptor subtype 2 (SSTR2) density in patients, and is complementary to FDG PET-CT for improving the accuracy of NET detection, characterization, grading, staging, and predicting/monitoring NET responses to treatment. Performing sequential 18F-FDG and 68Ga-DOTATATE PET scans would require 2 or more days and can delay patient care. To align temporal and spatial measurements of 18F-FDG and 68Ga-DOTATATE PET, and to reduce scan time and CT radiation exposure to patients, we propose a single-imaging session dual-tracer dynamic PET acquisition protocol in the study. A recurrent extreme gradient boosting (rXGBoost) machine learning algorithm was proposed to separate the mixed 18F-FDG and 68Ga-DOTATATE time activity curves (TACs) for the region of interest (ROI) based quantification with tracer kinetic modeling. A conventional parallel multi-tracer compartment modeling method was also implemented for reference. Single-scan dual-tracer dynamic PET was simulated from 12 NET patient studies with 18F-FDG and 68Ga-DOTATATE 45-min dynamic PET scans separately obtained within 2 days. Our experimental results suggested an 18F-FDG injection first followed by 68Ga-DOTATATE with a minimum 5 min delayed injection protocol for the separation of mixed 18F-FDG and 68Ga-DOTATATE TACs using rXGBoost algorithm followed by tracer kinetic modeling is highly feasible.

This article provides a review of literature on the psychology of rest in athletes with the aim of advancing research and practice in this area. While the concept of rest represents an important component of several key topics in sport psychology, researchers and practitioners have paid relatively little attention to this concept and to psychological aspects of rest in particular. We review literature in three sport psychology topic areas within which the concept of rest in athletes has received theoretical or empirical attention, which are recovery, skill learning, and expertise development. For each area, we describe how rest has received little direct research attention within this literature, identify how this shortcoming limits current theory, research, and practice, and propose directions for future research and practice. We then describe a recent study that has attempted to address the paucity of research on this topic by prioritizing an understanding of the psychology of rest in athletes. We also explore reasons why rest has received little attention in sport psychology with the rationale that an increased awareness of these reasons will help advance research and practice in our field. We conclude by considering implications of our review for best practice. Lay summary: Rest is critical to athlete performance and well-being, yet researchers and practitioners have paid little attention to psychological aspects of rest. We review the sport psychology literature to identify directions for research aimed at advancing our understanding of rest and practical guidelines to help athletes obtain the rest they require. Implications for Practice Practitioners should consider that recovery following training and competitions does not just involve recovering physically; it involves recovering psychologically Recovering psychologically depends in part on engagement in high-quality sleep and wakeful resting High-quality wakeful resting involves obtaining specific resting experiences such as not thinking about or “psychologically detaching from” one’s sport.

The present study compared intensity of training between technology-supported and conventional exercises during a regular therapy session in three brain injured patients with arm/hand limitations. Results showed that intensity was higher during technology-supported exercises. Further research with a larger sample is needed to confirm these outcomes and assess its potential relation to treatment effect.

The need to provide simulation as a replacement for clinical education due to a pandemic forced nursing faculty to be creative. Social distancing, hybrid methods of delivery and potential need for quarantining made it necessary to develop a cost-effective way to combine in-person and remote students into a single simulation session. The current simulation management system was not being supported by the vendor, nor did it have the capability to allow interactive streaming of the simulation session. Nurse educators were tasked to find an affordable, innovative replacement that would meet program needs. This article details the use of a combined 360-degree camera, mic and speaker product, a web document camera, and a video communication product. Existing equipment and technology purchased and readily available was used in a creative and innovative way to deliver simulation without addition cost.

To alleviate the impact of outages caused by dynamic blockage of propagation paths in millimeter wave (mmWave) systems, 3GPP has proposed multi-connectivity operation, where user equipment (UE) maintains simultaneous links to both sub-6 GHz and mmWave BSs. We address one of the most challenging prospective deployments – multi-lane street deployment with intra-and inter-RAT multi-connectivity. By utilizing the mixture of analytical and simulation tools, we first characterize the outage characteristics at mmWave layer. These characteristics further serve as an input to the queuing model characterizing service performance of sub-6 GHz BS serving sub-6 GHz and temporarily offloaded mmWave sessions and implementing traffic protection strategies. Our numerical results show that the use of inter-RAT multi-connectivity to offload mmWave sessions decreases sub-6 GHz session rate multiple times while utilizing multi-connectivity at the mmWave layer allows to partially compensate it. Traffic “jam” road conditions affect the sub-6 GHz session rate reducing it by approximately 20% compared to “normal” road traffic conditions. Furthermore, reserving shares of resources to sub-6 GHz and mmWave traffic favors “heavy-weight” mmWave sessions. On the other hand, individual session resource allocation leads to fair performance. However, this option induces the trade-off between the attained rate and the session drop probability. acceptedVersion

In the absence of user profile information, recommender systems have to only rely on current session information for recommendation. E-commerce sites may use transitions between interactions in each session to improve recommendation. This situation is known as the session-based recommendation. It can be challenging due to the limited information and the uncertain user behavior. Recurrent Neural Networks (RNN) have become the state-of-the-art models for session-based recommendation due to their ability to model long sequences. Although powerful, RNN-based models suffer from learning complex transition between the interactions. To mitigate it, Graph Neural Networks (GNN) have been proposed for session-based recommendation. However, different sequences of interactions may lead to the same outcome especially on E-commerce sites, hence non-sequential interactions between items of the current session may improve the performance of a recommender system. To learn both the sequential and non-sequential transition interactions between the items in the current session, we proposed a GNN based model named GRASER. Specifically, the proposed model first learns the non-sequential and then the sequential transition interactions between the items of the current session using GNN in an end-to-end manner. Extensive experiments were carried out on two datasets: Yoochoose from the RecSys Challenge 2015 and Diginetica from CIKM Cup 2016. The results showed that the proposed model outperforms the other state-of-the-art models by 11% and 10% on MRR@20 on Yoochoose and Diginetica datasets respectively.

This chapter talks about the tenth and final session of the Acceptance and Commitment Therapy (ACT) Enhanced Behavior Therapy for Trichotillomania (AEBT-T) treatment package. The therapist should urge the client to continue using the skills learned in therapy. Common pitfalls and methods for addressing them are covered. The first pitfall involves becoming less reliable in using habit reversal training and trigger reduction strategies. The second pitfall involves more time fighting with urges, increased pulling, and less time pursuing the meaningful parts of life. Clients may once again react to pulling-related thoughts, urges, or emotions as if they were real events with physical characteristics. In the final session the therapist should review with the client the progress made in therapy and should congratulate the client on their progress.

This interactive session brings together researchers and educators interested in using external representations to facilitate and assess learning. The session will juxtapose four systems, each of which takes a different design approach. The representations include concept maps, metaphorical textual descriptions or visualizations for helping students learn in complex domains such as science or programming.

We investigated the impact of a 1.5 hr workshop based on mindfulness-based compassion practices (MBCP) for 6 doctoral student therapists, followed by these therapists engaging in pre-session preparation for each of their clients in one of 3 randomly assigned conditions (MBCP, self-supervision, preparation-as-usual) over a 1-month period. State mindfulness and meditation self-efficacy increased following the workshop. Therapist ratings of session effectiveness were higher following pre-session meditation relative to preparation-as-usual, although there were no client-rated differences in session outcome. In a focus group, therapists reported that the workshop was generally helpful, and noted that pre-session MBCP led to a positive state of being and increased selfcare. However, they felt rushed to fit in the exercises and some doubted their meditation self-efficacy. They suggested that longer, at-home practice might be more beneficial than pre-session exercises. We encourage replication in larger samples varying the amount and format of meditation training for improving outcomes.

OBJECTIVE To determine the effectiveness of peer-assisted learning against expert-assisted learning in terms of scores achieved by medical students, and to assess the perceptions of students about peer-assisted learning. Methods The mixed-method study was conducted at Wah Medical College, Wah Cantonment, Pakistan, from October 2017 to December 2018, and comprised fourth year medical students who were randomised into groups A and B. In the first session the topic 'Data' was taught to group A by a peer and to group B by an expert teacher. In the next session the topic 'Sampling' was taught to group A by an expert teacher and to group B by a peer. Each session was followed by an assessment. Students' views about peer-assisted learning were collected using a predesigned questionnaire. An open-ended question about the role of expert in teaching was also asked from the students. Data was analysed using SPSS 22. Qualitative data was analysed to identify emerging themes. RESULTS Of the 80 subjects, 41(51.25%) were group A and 39(48.75%) were in group B. Overall, there were 36(45%) males and 44(55%) females. In the first session, mean group A score was 6.85±1.99 and for group B it was 7.54±1.76 (p>0.05). In the second session, the mean score of group A was 6.12±2.06 and for group B it was 4.82±2.01 (p=0.005). CONCLUSIONS Peer-assisted learning was found to be a valuable tool that can be incorporated in the curriculum delivery for easy topics. However the significance of expert's assistance, guidance and feedback cannot be negated.

This field experiment examined whether the well-documented benefit of spaced over massed training for humans and other animals generalizes to horses. Twenty-nine randomly selected horses (Equus ferus caballus) repeatedly encountered a novel obstacle-crossing task while under saddle. Horses were randomly assigned to the spaced-training condition (2 min work, 2 min rest, 2 min work, 2 min rest) or the massed-training condition (4 min work, 4 min rest). Total training time per session and total rest per session were held constant. Days between sessions (M = 3) were held as consistent as possible given the constraints of conducting research on a working ranch and safety–threatening weather conditions. During each training session, the same hypothesis-naïve rider shaped horses to cross a novel obstacle. Fifteen of 16 horses in the spaced-training condition reached performance criterion (94% success) while only 5 of 13 horses in the massed-training condition reached performance criterion (39% success). Horses in the spaced-training condition also initiated their first obstacle-crossing faster than horses in the massed-training condition and were faster at completing eight crossings than horses in the massed-training condition. Overall, task acquisition was higher for horses undergoing spaced training despite both groups experiencing the same total work and rest time per session. These findings generalize the learning-performance benefit observed in human spaced practice to horses and offer applied benefit to equine training.

The present study focuses on preliminary session, which was altered in its function by the resolutions of the new Law of Criminal Procedure (entering into force in 2018), that is Act XC of 2017 (henceforth LCP) with special regard to the relationship between accusation and evidentiary procedure with the help of a case. I also examine the rules of criminal procedure codified in Hungarian judicature, the function and influence of preliminary session, the main characteristics and the place of preliminary session among procedural forms of court procedures. The study examines whether preliminary session regulated by LCP meets the requirements and checks indictment eliminating unsubstantiated procedures. In case it fails to do so, what further regulations are needed to be added to present ones in order to meet requirements with special regard to codification policy embodied in criminal judicature, especially effectiveness, promptness, simplicity and coherence. I examine in details the possibility whether it could be the right and obligation of the court to examine not only the means of evidence deriving from legal elements and other informative elements contained in the presented indictment but also the legality of preliminary sessions and investigation procedures as a legal condition of initiating a court procedure. The study describes the regulation of LCP concerning evidentiary procedures in the preliminary session emphasizing the modifications by Act XLIII of 2020 concerning the interrogation of the accused. I examine its significance and point out whether anomalies in connection with the limits of evidentiary procedure are successfully eliminated in judicature.

RESUMO Este artigo apresenta duas seções que, apesar de distintas, estão conectadas pelo objeto comum, o romance A Senhora de Pangim, do autor integralista brasileiro Gustavo Barroso, publicado, no Brasil, em 1932, e, em Portugal em 1940. Na primeira sessão são analisados estudos de fundo histórico e literário, publicado entre 1932 e 1965. Na segunda seção são analisadas representações gráficas da personagem histórica de Baltasar do Couto Cardoso/Maria Úrsula de Abreu e Lencastro (1682-1730), com especial interesse para duas revistas em quadrinhos, uma brasileira Edição Maravilhosa, n. 116, publicada em 1956, e uma mexicana Mujeres Célebres, n. 57, publicada em 1965. Estamos interessados não só em pensar as reiterações e rupturas entre o discurso histórico e o discurso literário, mas também a discussão sobre donzelas-guerreiras e a maneira como essas representações consideraram a instabilidade de gênero da personagem. ABSTRACT This article presents two sections that, although distinct, are connected by the common object, the novel A Senhora de Pangim (The lady of Pangim), by Brazilian integralist writer Gustavo Barroso, published in Brazil in 1932 and Portugal in 1940. In the first session, we analyze historical and literary studies, published between 1932 and 1965. In the second section, we exam graphic representations of the historical character of Baltasar do Couto Cardoso / Maria Úrsula de Abreu and Lencastro (1682-1730), with special interest for two comic magazines, Brazilian Edição Maravilhosa (Wonderful Edition), n. 116, published in 1956, and Mexican Mujeres Célebres (Celebrated Women), n 57, published in 1965. We are interested not only in thinking about the reiterations and ruptures between historical and literary discourse but also in the discussion about warrior maidens and the way these representations considered the character's gender instability.

Introduction. Medical trainees fear disclosing psychological distress and rarely seek help. Social sharing of difficult experiences can reduce stress and burnout. Drawing comics is one way that has been used to help trainees express themselves. The authors explore reasons why some medical trainees chose to draw comics depicting stressful situations that they had never shared with anyone before. Methods. Trainees participated in a comic drawing session on stressors in medicine. Participants were asked if they had ever shared the drawn situation with anyone. Participants who had not previously shared were asked what prevented them and why they shared it now. The authors performed content analysis of the responses. Results. Of two hundred forty participants, forty-six (19.2%) indicated sharing an experience for the first time. Analysis of the responses revealed dedicated time and space was essential to sharing, trainee insecurity was a barrier, and comics were perceived as a safe way to communicate. Discussion. Depicting a stressful situation may be beneficial for trainees who drew an experience they had never shared before. Providing trainees with the opportunity to externalize their experience and create a community for sharing tough experiences may be one way to reduce trainee stress and burnout.

Virtual reality-based exercise (exergames) improves cognition of the elderly but the neurophysiological effects are poorly understood. The hypothesis herein established is that an ultrafast neurophysiological adaptation occurs in prefrontal cortex of elderly after completion of a single exergames session. To reinforce the aforementioned hypothesis, individuals living in a Long-Term Care Home (LTCH) participated in the study and were randomly allocated into two groups (Virtual Reality Group, VRG, n = 5; and Active Control Group, ACG n = 5). VRG performed six exercises with exergames and ACG performed exercises with the same VRG movements but with no virtual reality. Assessment of frontal cortical activity at rest and during cognitive testing via electroencephalographic activity (EEG) was performed before and immediately after the intervention. Significant decrease in relative power of EEG (RPEEG) Beta brainwave (−29 ± 18%) in the left prefrontal cortex of VRG compared to ACG (4 ± 9%) (p = 0.007). A slight improvement on semantic fluency in VRG (ES=0.21) was noted. An ultrafast prefrontal cortical adaptation may occur as an effect of a single exergames session, causing a small improvement on cognition of institutionalized elderly.

Session-based recommendation aims to generate recommendations merely based on the ongoing session, which is a challenging task. Previous methods mainly focus on modeling the sequential signals or the transition relations between items in the current session using RNNs or GNNs to identify user’s intent for recommendation. Such models generally ignore the dynamic connections between the local and global item transition patterns, although the global information is taken into consideration by exploiting the global-level pair-wise item transitions. Moreover, existing methods that mainly adopt the cross-entropy loss with softmax generally face a serious over-fitting problem, harming the recommendation accuracy. Thus, in this article, we propose a Graph Co-Attentive Recommendation Machine (GCARM) for session-based recommendation. In detail, we first design a Graph Co-Attention Network (GCAT) to consider the dynamic correlations between the local and global neighbors of each node during the information propagation. Then, the item-level dynamic connections between the output of the local and global graphs are modeled to generate the final item representations. After that, we produce the prediction scores and design a Max Cross-Entropy (MCE) loss to prevent over-fitting. Extensive experiments are conducted on three benchmark datasets, i.e., Diginetica, Gowalla, and Yoochoose. The experimental results show that GCARM can achieve the state-of-the-art performance in terms of Recall and MRR, especially on boosting the ranking of the target item.

Byrne, PJ, Moody, JA, Cooper, SM, and Kinsella, S. Acute effects of "composite" training on neuromuscular and fast stretch-shortening cycle drop jump performance in hurling players. J Strength Cond Res 35(12): 3474-3481, 2021-"Composite" training is a term developed by the authors and defined as the combination of a plyometric exercise with an explosive activity such as a sprint run, performed as a "combined repetition"/session. The purposes of this study were to investigate the acute effect of a "composite" training session on neuromuscular and fast stretch-shortening cycle bounce drop jumps (BDJs) in hurling players' immediately, after session, and after 7 days of recovery. Eight hurling players first completed a drop jump test to identify individual BDJ drop height, followed 72 hours later with a single "composite" training session. Three repetition maximum (3RM) back squat strength, BDJ, countermovement jump (CMJ), and sprint performance testing were performed 10 minutes before and immediately after session and 7 days after session. An analysis of variance reported a significant decrease in CMJ measures (height, velocity, and eccentric rate of force development) and sprint performance from presession to postsession (p ≤ 0.05). Moreover, a significant increase was evident for CMJ performance (height and power), sprint performance (5 and 20 m), 3RM back squat strength, and BDJ performance (reactive strength index and height) from postsession to post-7-day recovery (p ≤ 0.05). Pairwise comparisons indicated that absolute and relative 3RM strength significantly increased from presession to post-7 days (absolute 3RM: p = 0.0001; relative 3RM: p = 0.01). The findings indicate that "composite" training results in an immediate decline in CMJ measures after session possibly due to acute muscle fatigue, and supercompensation augments maximum lower-limb strength after 7 days of recovery.

Tujuan pelatihan ini untuk meningkatkan kemampuan mahasiswa mengelola dirinya (self regulation/SRL) agar dapat mengikuti pembelajaran online dengan lebih produktif. Dua puluh empat mahasiswa fakultas Psikologi Unika Soegijapranata berpartisipasi dalam pelatihan ini. Sebelum pelaksanaan, peserta diminta untuk mengisi skala yang berisi aitem tentang SRL sebagai data pre test. Pelatihan diselenggarakan dalam 4 minggu dengan durasi waktu 120 menit setiap sesi yang akan disampaikan secara daring dengan menggunakan platform google meet. Setiap sesi pelatihan diikuti dengan pemberian tugas rumah yang harus disusun dan dipraktekkan. Di akhir sesi akan diberikan skala SRL yang sama sebagai data post test. Materi pelatihan mencakup : (1)Penyampaian materi tentang SRL, menetapkan goal setting dan latihan untuk menyusun aktivitas harian selama satu hari; (2) Pemberian materi tentang kesiapan diri sebelum-saat dan setelah mengikuti pembelajaran online dan time management; (3) Evaluasi pelaksanaan dari perencanaan yang telah dilakukan selama 3 hari; (4) Evaluasi pelaksanaan aktivitas yang diselenggarakan selama 5 hari.Lembar informed consent diberikan untuk memastikan kesediaan peserta untuk mengikuti keseluruhan pelatihan. E-sertifikat diberikan pada peserta yang mengikuti seluruh rangkaian pelatihan. Data pre test dan post test dianalisis dengan menggunakan statistik parametrik analisis Uji Paired T-Test. Hasilnya menunjukkan nilai t = 1.707 (p>0.05) yang menunjukkan tidak ada perbedaan antara sebelum dan setelah mengikuti pelatihan. Sekalipun demikian, secara lisan peserta menyampaikan setelah mengikuti pelatihan ini lebih mampu mengelola waktunya dengan lebih prduktif, menetapkan goal setting, membuat perencanaan aktivitas yang realistis dengan menimbang aktvitas lain yang harus dilakukan seperti waktu untuk istirahat, family time dan me time.

This paper is about the practical application of Metamorphoses creative-developmental fairy tale therapy, which is presented based on a three-session Metamorphoses creative-developmental fairy tale therapy session. The sessions were conducted between April and May 2021, among students (n=24) of the University of Debrecen, who were previously not familiar with fairy tale therapy, nor with the works of Ildikó Boldizsár. Through the media environment of the session, we also reflected together on the effects of internet consumption and the dangers of the internet. The study highlights the students' attitudes towards this method and their participation and activity in the online space. The experiences gained during the 3 sessions and the feedback of the students appear as a guideline to conclude the study. The practical application of the Metamorphoses creative-developmental fairy tale therapy will show whether this methodology has a role to play in higher education.

PURPOSE: Patients with diabetic neuropathy usually suffer from impaired balance, pain, and decreased sole-foot sensation. The present research was designed to appraise the relic of whole-body vibration (WBV) on balance, pain, and sole-foot sensation in diabetic neuropathy patients. METHODS: Present study was a single-blind randomized controlled clinical trial. Thirty-four patients with type 2 diabetic neuropathy were randomly divided into intervention groups (n=17) and control (n=17). The therapeutic program in the intervention group included standing on the platform of the WBV device, and in the control group included using the device in off mode. Dynamic balance (including overall, anterior-posterior, and medial-lateral stability indices) was measured using Biodex device, functional balance with timed up and go (TUG) test, pain using the visual analog scale (VAS), and sole-foot sensation of both feet with a monofilament. The outcomes were measured in both groups before and after the interventions. RESULTS: Sixteen people in each group were analyzed. Intra-group comparison showed a significant improvement in the mean pain (P = 0.000), functional balance (P = 0.011), right and left sole-foot sensation (P = 0.001), and overall (P = 0.000), anterior-posterior (P = 0.000) and medial-lateral (P = 0.000) stability indices for the intervention group in post-intervention compared to pre-intervention. However, changes in the control group were not statistically significant. Results of inter-group comparison indicated a significant improvement in all parameters in the intervention group, except for functional balance. CONCLUSION: WBV can be effective in reducing pain and improving the sole-foot sensation and dynamic balance.

Annually, the Operations Committee (OpCo) of the Program for Cooperative Cataloging (PCC) presents a two-day meeting in Washington, DC, to advise participants in the PCC programs of what they need to know to work cooperatively with all the other catalogers in the program. This year, as last year, an online meeting replaced the in-person meeting, but the purpose was the same. This Listen and Learn session will update Atla participants in the NACO, CONSER, or SACO funnels with the information that was presented at OpCo, so that their work in the Atla funnels will adhere to the current practices in the PCC programs. The session also presents news of changes coming in programs and tools that funnel participants use.

Devices that populate the Internet of Things (IoT) are typically constrained with respect to energy consumption. When the data that are processed, stored and/or communicated by these devices need to be secured, low-energy security mechanisms have to be designed and implemented. Related work mainly concentrates either on low-energy security algorithms and protocols, or on low-energy wireless communication. However, it is important for system developers to take into account the overall energy consumption of the IoT system when making design choices. Therefore, this work presents an in-depth analysis of the energy consumption of IoT devices that provide end-to-end secure communication and digital signatures. The paper follows a granular approach, profiling and measuring each individual contribution to the overall energy consumption, including the computation of cryptographic operations as well as the wireless transmission of messages in cryptographic protocols. The paper also calculates the minimal time period of a secure communication session in order to minimize the energy impact of the session’s setup phase and thus minimize the overall average power consumption. The goal of this work is to provide assistance in the selection of a suitable wireless communication standard and cryptographic cipher suite for building end-to-end secure IoT applications.

Some of the events of the past year have resulted in theological institutions assessing their own racial ethnic diversity and making plans for increasing that diversity. This year Atla celebrates seventy-five years of existence. This session will reflect back over the past 75 years and note what has been done. The presentation given at the ATLA Annual Conference in 2011, Sixty-Five Years of Racial Ethnic Diversity in ATLA will be the basis for the session. At the conclusion of the 2011 presentation, the vision of the future was of an association which reflected the general population in terms of percentage of racial ethnic persons. The session will chronicle events from the last 10 years, update data, and see how close to that vision the association has come. Areas of possible growth will also be noted.

To investigate (1) whether expert clinicians within psychodynamic therapy (PDT), mentalization-based treatment (MBT), cognitive-behavioral therapy (CBT), and interpersonal psychotherapy (IPT) agree on the essential adolescent psychotherapy processes using the Adolescent Psychotherapy Q-Set (APQ); (2) whether these four session prototypes can be empirically distinguished; and (3) whether mentalization is a shared component in expert clinicians' conceptualizations of these four treatment models. Thirty-nine raters with expertize in PDT, MBT, CBT, and IPT provided ratings of the 100 APQ items to characterize a prototypical session that adheres to the principles of their treatment model. A Q-factor analysis with varimax rotation was conducted. Expert clinicians reached a high level of agreement on their respective session prototypes, which loaded onto five independent factors. The PDT session prototype straddled two different factors, suggesting more variability in PDT expert clinicians' understanding of PDT process for adolescents than in the views of the expert clinicians representing the other treatment models. Mentalization process was shared among all four session prototypes; however, the correlation between the CBT and IPT session prototypes remained significant after controlling for the MBT session prototype. Researchers can now assess adherence to four adolescent treatments and identify change processes beyond these labels.

Interactive video-based instruction (IVBI) session was organized in day-care rehabilitation settings to provide training in acquiring new skills related to social skills development for targeted mo...

Large movements during the night tend to have a lasting influence on the next trading session. By following the resulting trends, investors can benefit from fluctuations in the returns of major equity indices during the trading session. This study extends recent research on late-day trading and shows that trends are best caught early during the day. Intraday patterns are revealed using machine learning techniques, and new evidence on the origin of trends is presented. The defensive nature of intraday trend strategies is illustrated by considering the business cycle, investigating correlation with government bonds and simulating the impact on a multi-asset portfolio.

Operating room (OR) resources are limited, and for this reason there is usually a competition among surgeons to win them. However, the methods developed for allocating OR sessions are mostly based on optimisation methods which compensate the preferences of surgeons or surgical specialities in favour of the productivity of the entire OR department. This leads to conflict and dissatisfaction among surgeons. To overcome this problem, a methodology based on game theoretic solutions is presented in this paper that formulates the allocation problem as a simple game. The surgeons or specialities as players then jointly pursue the goal of achieving overall stability. Stability is defined and measured using a method called Power Index. The proposed method is then combined with the Monte-Carlo technique to deal with uncertainties. To demonstrate the capability of the suggested procedures, they are applied to a case study from the literature and a set of hypothetical scenarios.

Graphical abstract, Highlights • Associations between caregiver-infant behaviours during social interactions and brain development outcomes were investigated. • Caregivers' and infants' behaviours in interactions related to children’s structural, functional and connectivity measures. • Concurrent associations between behavioural and brain measures were apparent as early as three months postnatally. • Long-term associations between behaviours in early interactions and brain development outcomes were observed decades later. • Individual differences in early interactions and associated brain development is an important avenue for further research., From birth, interactions with others are an integral part of a person’s daily life. In infancy, social exchanges are thought to be critical for optimal brain development. This systematic review explores this association by drawing together infant studies that relate adult-infant behaviours – coded from their social interactions - to children’s brain measures collected during a neuroimaging session in infancy, childhood, adolescence or adulthood. In total, we identified 55 studies that explored associations between infants’ social interactions and neural measures. These studies show that several aspects of caregiver-infant behaviours are associated with, or predict, a variety of neural responses in infants, children and adolescents. The presence of both concurrent and long-term associations - some of which are first observed just a few months postnatally and extend into adulthood - open an important research avenue and motivate further longitudinal studies.

This article examines gender differences in participation and communication behaviour at the German Congress of Geography 2019 in Kiel. The programme booklet and over 70 sessions with more than 200 lectures as well as over 800 discussion contributions were analysed for gender-specific differences using a standardised structured observation form. The results show significant gender differences both on the level of participation and on the level of communication behaviour: Lectures delivered by men achieved higher attendance figures than lectures by women due to gender-selective attendance behaviour of men; women were under-represented in the role of session chair; men tended to dominate the discussion rounds after the presentations, they took the floor more often and talked longer; the session chairs’ gender exercised a decisive influence on who participated in the discussions, there was a clear tendency towards gender homophily; in general, discussion activity was higher after presentations by women, because women then participated in the discussions significantly more often and for longer periods of time. In the second part of the paper, we put our findings in historical context. This reveals that gender inequality has decreased e.g. with regard to women’s conference participation, personnel structure and the number of women being appointed as full professors. On a structural level, positive gender dynamics are emerging within German-speaking geography. On the other hand, it becomes evident that especially at the level of communication at conferences, traditional gender-specific behaviours do persist. These behavioural patterns are obviously more enduring than the formal structures and positions.

In this paper, Harris’ Hawks weight optimization-guided artificial neural learning-based quicker session key coordination for Industrial Internet-of-Things (IIoT) to enhance the security of Critical Energy Infrastructure (CEI) is proposed. Transportation, telecommunications, healthcare, finance, and defense are all being revolutionized by the energy industry’s digitization. CEI is widely dispersed, resulting in complex cyber-physical networks that require constant monitoring and quick recovery to avoid cyberattacks. Substantial efforts were made in this regard to tackle the key exchange problem in IIoT devices, the majority of which have depended on traditional approaches. Existing solutions fail to adequately resolve the security and privacy issues that IIoT systems face. This study proposes a Triple Layer Vector-Valued Neural Network (TLVVNN) to cope with the problem. However, research into optimizing the value of neural weights for quicker neural synchronization is rare. In this case, Harris’ Hawks is used to optimizing the neural network’s weight vector for quicker coordination. The coordinated weight becomes the session key once this process is accomplished. This technique has several advantages, including (1) Generation of session key via mutual neural synchronization over the public channel. (2) It enables Harris’ Hawks-based neural weight vector optimization for faster neural synchronization across public channels. (3) Vector inputs and weights are taken into consideration for TLVVNN networks. (4) The internal structure of the TLVVNN is complex by three hidden layers. As a result, the attacker might have a lot of difficulties determining the internal architecture. (5) Several pairs of variable-length session keys are generated by TLVVNN. (6) It prevents impersonation, geometric, brute force, and majority assaults. Tests to validate the performance of the proposed methodology are carried out, and the results show that the proposed methodology outperforms similar approaches already in use.

In recent months, the demand for services provided on the Internet (scientific conferences, training, webinars) has increased. As this activity grew, so did cybercrime. Social networks share invitations to various training and webinars. We also receive similar announcements via e-mail. It is not difficult to accidentally click on the attached link. The submitted URL may contain a script. The script may infect our device or steal our login details. We have developed a new security protocol — Amelia, to protect against responding to a false invitation to a web event. Our protocol makes it possible to check if the link sent is valid. Also, it enables the generation of unique user identifiers. Amelia protocol provides users’ verification and distribution of symmetric session keys. We conducted a study of our protocol. We checked its vulnerability to Intruder attacks. The obtained results are promising. We did not find an attack on this protocol.