Guidance Approach Research Articles

Healthcare Providers' Perspectives on Autistic Adolescents Transitioning to Independent Driving.

Licensure is an option for some autistic adolescents and families that increases mobility by enabling independent travel to employment, school, and social activities. The objective of this study was to identify current strategies used by healthcare providers (HCPs) in their guidance to autistic adolescents and families on the transition to independent driving. Semi-structured interviews were conducted with 15 HCPs. The team's previous research, literature review and expert feedback informed the development of the interview guide. A content analysis approach was used in the coding of transcripts, nine of which were double coded. Study team members reviewed coded transcripts, provided and discussed narrative summaries, and identified themes. Interviews were conducted with physicians, social workers, psychologists, therapist and a nurse practitioner. HCP identified their perceptions of autistic adolescents' strengths and weaknesses to be addressed in their individualized approaches. They described using clinical interactions as time to address licensure and driving, but also referred to specialists as needed. HCPs described using existing resources, but also provided a wish list of future resources. HCPs use an individualized approach for guidance in the transition to independent driving, considering the unique needs of autistic adolescent patients and families. These HCPs identified a clear need for tailored resources and guidance they can use in support of independent driving when appropriate for their patients and families.

Sustainable development of Chinese Baijiu Tourism resources: an analytical approach for evaluation and guidance

Sustainable development of Chinese Baijiu Tourism resources: an analytical approach for evaluation and guidance

Peran Konselor dalam Membantu Siswa Mengatasi Stres Akademik: Pendekatan Bimbingan Konseling

Academic stress is a significant problem experienced by students at various levels of education. Academic stress can have a negative impact on students' well-being and their academic performance. Individual counseling has been recognized as an effective approach in helping students overcome academic stress. This research aims to determine the role of counselors in helping students overcome academic stress: a counseling guidance approach. This research is qualitative research. The results of the analysis show that there are several individual counseling strategies that are effective in dealing with academic stress in students. These strategies include relaxation techniques, time management, developing study skills, social support, self-regulation, and developing adaptive thinking patterns. Previous research also shows that individual counseling conducted by trained and experienced counselors has a positive impact on reducing academic stress and improving student well-being. This research has important reinforcement for counseling practitioners and researchers in the field of education. By understanding effective individual counseling strategies, counseling practitioners can develop appropriate and scalable interventions to help students cope with academic stress. In addition, this research also identifies research opportunities that could provide opportunities for further research in this area.

Individual Career Guidance Approach for Science Subject Selection among Public Secondary School Students of Karagwe District, Tanzania

The study investigated how individual career guidance enhances the selection of science subjects among public secondary school students of Karagwe District. Anchored in Expectancy-Value Theory (EVT), the study employed a convergent design within the mixed methods approach. The study targeted 31 heads schools (HSs), 1225 students, and 31 teacher counselors (TCs) in 31 public secondary schools, and one District Education Officer (DSEO). The sample included 120 students, 10 TCs, 10 HSs, and 1 DSEO obtained through simple random, total population, and stratified random sampling techniques. Quantitative data were collected through questionnaires, while qualitative data were collected through interview guides and focus group discussion guides whose validity were made certain by research experts in the field of education. The reliability of .894 was established for students questionnaires based on the Likert-type items using Cronbach's Alpha technique while peer debriefing and triangulation methods were used for qualitative data. The quantitative data were descriptively analyzed with the aid of SPSS version 22 while qualitative data were subjected to a thematic analysis that involved familiarization, coding, topic generation, theme review, theme definition and name, and writing up. Ethical guidelines for research were conformed, which included obtaining approval for the study, seeking informed consent, maintaining confidentiality and anonymity, properly attributing sources, and acknowledging papers According to the study, students in Karagwe District have chosen science subjects differently as a result of receiving individualized career counseling. Students appreciate the significance of one-on-one career counseling sessions in helping them define their interests and aspirations in science subjects. The study revealed further that students can better align their goals and receive tailored support by receiving personalized advice and guidance on science subjects. The study came to the conclusion that individual career counseling is a useful tool since teacher counselors are crucial in helping students receive guidance that could boost their interest in and aspirations for science courses. According to the report, teacher counselors should receive more training so they may proactively identify students who are struggling or unsure about their future career prospects and offer them specialized counseling and support.

DMMGNet: A discrimination mapping and memory bank mean guidance-based network for high-performance few-shot industrial anomaly detection

For deep learning-based industrial anomaly detection, it is still challenging to get adequate images for model training and achieve cold start for cross-product migration, restricting their practical application in real industrial production. Herein, an innovative few-shot anomaly detection network DMMGNet based on discrimination mapping and memory bank mean guidance strategies are demonstrated, which is trained by a new two-branch data augmentation technique. By separating the features stored in memory bank from the features used for training, the two-branch data augmentation method can significantly improve the robustness of few-shot model training and reduce the redundance of memory bank. In the elaborately designed discrimination mapping module, new negative samples are generated by adding dynamic Gaussian noise to normal samples along the channel dimension in feature space to solve the problem of sample imbalance. Meanwhile, the discrimination mapping module also helps to map the feature distribution of positive samples to the target domain more efficiently and reduce the deviation of feature domain, conducive to a more precise separation of positive and negative samples. In addition, a novel mean guidance approach with an optimized loss function is developed to guide the positive sample feature mapping by specifying the local feature space center to form a clear feature domain contour and enhance the detection accuracy. The multiple experimental results validate that our DMMGNet outperforms the most advanced anomaly detection counterparts on image-level AUROC, showing an increase by 0.3–3 % on both MVTec AD and MPDD benchmarks under several few-shot scenarios.

Guiding Diffusion Models for Antibody Sequence and Structure Co-design with Developability Properties

Recent advances in deep generative methods have allowed antibody sequence and structure co-design. This study addresses the challenge of tailoring the highly variable complementarity-determining regions (CDRs) in antibodies to fulfill developability requirements. We introduce a guidance approach that integrates property information into the antibody design process using diffusion probabilistic models. This approach allows us to simultaneously design CDRs conditioned on antigen structures while considering critical properties like solubility and folding stability. Our property-guided diffusion model offers versatility by accommodating diverse property constraints, presenting a promising avenue for computational antibody design in therapeutic applications. Published by the American Physical Society 2024

Rethinking Propellant-Optimal Powered Descent Guidance

The propellant-optimal powered descent solution requires a bang-bang thrust magnitude profile that switches instantaneously between the upper and lower bounds of the engine thrust. Implementing a bang-bang thrust pattern for guidance can be challenging for the engine and may cause practical and operational difficulties. Motivated by the observation that excellent propellant performance does not appear to be predicated on necessarily having a bang-bang thrust structure, a new powered descent guidance method is proposed in this work. The foundation lies in a propellant-optimal problem in which the thrust magnitude is parameterized by a user-prescribed continuous function of time. In particular, constant and linear functions are considered. The solution determines the optimal thrust direction, time of flight, and design parameters defining the thrust function. An indirect-method-based guidance algorithm is developed to solve this problem rapidly and reliably. Substantial evidence is provided to demonstrate that the solutions proposed in this paper in general yield a propellant consumption very close to that of the optimal bang-bang solution. Given its comparable propellant performance, implementability, and robustness, this paper makes a strong case that the proposed propellant-optimal powered descent guidance approach is preferred to the long-standing bang-bang guidance approach.

Comparative Analyses of Bioequivalence Assessment Methods for In Vitro Permeation Test Data.

For topical, dermatological drug products, an in vitro option to determine bioequivalence (BE) between test and reference products is recommended. In particular, in vitro permeation test (IVPT) data analysis uses a reference-scaled approach for two primary endpoints, cumulative penetration amount (AMT) and maximum flux (Jmax), which takes the within donor variability into consideration. In 2022, the Food and Drug Administration (FDA) published a draft IVPT guidance that includes statistical analysis methods for both balanced and unbalanced cases of IVPT study data. This work presents a comprehensive evaluation of various methodologies used to estimate critical parameters essential in assessing BE. Specifically, we investigate the performance of the FDA draft IVPT guidance approach alongside alternative empirical and model-based methods utilizing mixed-effects models. Our analyses include both simulated scenarios and real-world studies. In simulated scenarios, empirical formulas consistently demonstrate robustness in approximating the true model, particularly in effectively addressing treatment-donor interactions. Conversely, the effectiveness of model-based approaches heavily relies on precise model selection, which significantly influences their results. The research emphasizes the importance of accurate model selection in model-based BE assessment methodologies. It sheds light on the advantages of empirical formulas, highlighting their reliability compared to model-based approaches and offers valuable implications for BE assessments. Our findings underscore the significance of robust methodologies and provide essential insights to advance their understanding and application in the assessment of BE, employed in IVPT data analysis.

Manajemen Peningkatan Kepercayaan Diri Siswa Melalui Layanan Bimbingan Kelompok di Kelas X SMAN 1 Parigi

This study aims to explore the management of confidence-building in students through group guidance services in the 10th grade at SMAN 1 Parigi. The study employs a descriptive method with a qualitative approach, involving data collection techniques such as observation, in-depth interviews, documentation studies, and data source triangulation. The research process includes planning, organizing, implementing, and controlling group guidance services focused on enhancing students' confidence. The results show that group guidance services are effective in boosting students' confidence through active participation in group discussions, role-playing, and other activities designed to motivate students to express their opinions and feelings. The school counselors play a crucial role in facilitating and directing the group guidance sessions and conducting regular evaluations to ensure the program's goals are met. Challenges include students who tend to be reserved and the lack of collaboration between homeroom teachers and school counselors. However, with a closer approach and higher intensity of guidance, it is expected to build closer relationships and trust between school counselors and students, significantly increasing students' confidence.

Machine learning-based integration develops a mitophagy-related lncRNA signature for predicting the progression of prostate cancer: a bioinformatic analysis

Prostate cancer remains a complex and challenging disease, necessitating innovative approaches for prognosis and therapeutic guidance. This study integrates machine learning techniques to develop a novel mitophagy-related long non-coding RNA (lncRNA) signature for predicting the progression of prostate cancer. Leveraging the TCGA-PRAD dataset, we identify a set of four key lncRNAs and formulate a riskscore, revealing its potential as a prognostic indicator. Subsequent analyses unravel the intricate connections between riskscore, immune cell infiltration, mutational landscapes, and treatment outcomes. Notably, the pan-cancer exploration of YEATS2-AS1 highlights its pervasive impact, demonstrating elevated expression across various malignancies. Furthermore, drug sensitivity predictions based on riskscore guide personalized chemotherapy strategies, with drugs like Carmustine and Entinostat showing distinct suitability for high and low-risk group patients. Regression analysis exposes significant correlations between the mitophagy-related lncRNAs, riskscore, and key mitophagy-related genes. Molecular docking analyses reveal promising interactions between Cyclophosphamide and proteins encoded by these genes, suggesting potential therapeutic avenues. This comprehensive study not only introduces a robust prognostic tool but also provides valuable insights into the molecular intricacies and potential therapeutic interventions in prostate cancer, paving the way for more personalized and effective clinical approaches.

Effects of Drug and Substance Abuse on Academic Performance among Secondary School Students, Kauma Subcounty, Kilifii County, Kenya

Purpose: The study aims at investigating effects of substance abuse in Kauma Sub County of Kilifi County of the Coast Province. The Purpose is of the study is to uncover the effects of substance abuse and its relation to academic performance in Secondary schools in Kauma, with the purpose of recommending how to address the Situation. Methodology: The study involves Random selection of Schools and random filling of questioners by learners and Teachers. It was pegged on Uri Bronfenbrenner’s’ Ecological Contextual Theory (1979). Which denotes that behavior is controlled by ecological environmental systems that affects positively or negatively the personality of man culminating to the totality of one’s character. Findings: The research found that the cultural norms of Disco Matanga has greatly contributed to Palm wine (Mnazi), Muguka/ Ghat and Marijuana abuse. Efforts by the Presidency to address the issue and stop the vice has met stiff resistance from locals and politicians for their own motives which were not captured in this research. The research also found that 70% of Secondary school students scored D plus and below in National Examinations. Unique Contribution to Theory, Policy and Practice: The research recommends collaborative efforts on addressing drug abuse in secondary school students and the use of Faith based organizations , academic institutions, Intercountry – National and NGO approaches in Guidance and Counselling with emphasis to co-curricular and art therapies to first educate and inform the population on the effects of drug Abuse, the economic strain on both county and national government on rehabilitation and apply the multi sectorial approach to scaffold the emotional, mental, physiological effects on health and academics with subsequent methods to address the issue including further research studies..

Professional and Personality Competency in Prophetic Counseling: A Phenomenological Study of School Counselors

Balancing transcendental and worldly values through prophetic counseling is crucial for preventing mental disorders and addressing global socio-cultural challenges. Prophetic counseling focuses on spiritual and afterlife concerns, unlike traditional counseling which centers on worldly matters. The purpose of this study is to explore prophetic values and internalization experienced by counselors at school. This study is a qualitative research that used Descriptive Phenomenological Psychology. Data were obtained by interviewing 3 guidance and counseling teachers from Islamic schools. Data analysis was carried out by arranging the description and categorization based on the founding of the theme that intrigued and internalized the values of prophetic counseling at school. The result showed that prophetic in school counseling by the counselors was drawn into two aspects: professional competency, which is applied in approach, strategy, technique, or method of guidance and counseling, and personality competency, which tends to reflect their personality character. Internalization of prophetic values gradually occurred through the relationship of counselor-counselee in the guidance and counseling that have been turned into a method for adding new knowledge and improving counselor attitude and behavior.

Camouflaged object segmentation with prior via two-stage training

The camouflaged object segmentation (COS) task aims to segment objects visually embedded within the background. Existing models usually rely on prior information as an auxiliary means to identify camouflaged objects. However, low-quality priors and the singular guidance form hinder the effective utilization of prior information. To address these issues, we propose a novel approach for prior generation and guidance, named prior-guided transformer (PGT). For prior generation, we design a prior generation subnetwork consisting of a Transformer backbone and simple convolutions to obtain higher-quality priors at a lower cost. In addition, to fully exploit the backbone’s understanding capabilities of the camouflage characteristics, a novel two-stage training method is proposed to achieve the backbone’s deep supervision. For prior guidance, we design a prior guidance modules (PGM), with distinct space token mixers to respectively capture global dependencies of location priors and local details of boundary priors. Additionally, we introduce a cross-level prior in the form of features to facilitate inter-level communication of backbone features. Extensive experiments have been conducted and experimental results illustrate the effectiveness and superiority of our method. The code is available at https://github.com/Ray3417/PGT.

Agent-based modelling of polarized news and opinion dynamics in social networks: a guidance-oriented approach

Abstract In the contemporary social network landscape, opinion polarization has emerged as a prominent challenge, sparking concerns about the effective guidance of news sentiment and mitigation of opposing opinions. This is particularly pertinent in the intricate web of social networks, where complexity reigns supreme. Addressing this pivotal issue, this article introduces a news opinion guidance approach grounded in motif recognition. To accurately mirror real-world social networks, we have crafted an agent-based model that simulates polarized news propagation. This model encompasses diverse media agents and user agents, meticulously replicating the news dissemination process within the network. In our quest to unveil the underlying structures of social networks, we have enhanced the Augmented Multiresolution Network approach, incorporating multi-dimensional node attributes for more nuanced clustering and network mapping. This refinement enables us to pinpoint potential motif regions with greater precision. Leveraging these insights, we introduce a triangular motif-based opinion guidance strategy aimed at shaping opinion distribution by bolstering the influence of nodes within these motifs. Once the pertinent motifs are identified, we undertake simulation experiments that reveal the remarkable efficacy of our motif recognition-driven guidance strategy. Notably, it reduces opinion polarization by a substantial 74% compared to scenarios without guidance strategies. This research offers a fresh perspective on crafting personalized and targeted news sentiment guidance strategies. It presents a versatile and potent computational framework for understanding and managing polarization phenomena in social networks, carrying profound theoretical and practical ramifications.

Pengembangan Modul Bimbingan Kelompok Teknik Role Playing Untuk Meningkatkan Self Awareness Siswa

The aim of the research is to develop media in the form of modules with a group guidance approach to role playing techniques to increase the self-awareness of class XI students at SMAN 1 Kramatwatu. The research method used is research and development (R&D) with the ADDIE development model. The data collection technique uses a questionnaire and the data analysis technique uses a Likert scale. The results of the feasibility test obtained an overall result of 90% with a very feasible category with the provisions of the material and media feasibility test obtaining a result of 86%, the language feasibility test of 94% and the practitioner feasibility test of 93% and to strengthen the effectiveness of the services provided the N-Gain percent result was 57.61%, namely quite effective with a score of 0.57 in the medium category. From the results of this management, the module was declared suitable for use by guidance and counseling teachers in providing understanding to students regarding self-awareness.

A Multi-layer Guidance Approach for Submerged Sensor Networks Integrating Acoustic and Optical Technologies

A Multi-layer Guidance Approach for Submerged Sensor Networks Integrating Acoustic and Optical Technologies

Perkembangan Individu Dan Kebutuhan Belajar: Perspektif Psikologi Dan Bimbingan Konseling Di SDN Sangkali

This research aims to investigate the counseling and psychological guidance approaches applied by homeroom teachers at SDN Sangkali, Tasikmalaya City, in dealing with problems such as bullying and stress experienced by students. The methods used include observation and interviews to understand how teachers manage the emotions and pressure experienced by students. The research results show the importance of understanding students' individual development and learning needs to create a supportive learning environment in elementary schools. In particular, this research highlights the important role of homeroom teachers in dealing with problems such as bullying and stress resulting from bullying, as well as effective strategies in supporting students' psychological well-being.

Identifying iliotibial band graft length and incision site may minimise the potential risk of harming adjacent structures: A novel approach for surgeon guidance.

The Iliotibial band (ITB) is a fibrous thickening of the fascia lata originating at the iliac crest and inserting at Gerdy's tubercle on the lateral tibia. The ITB significantly contributes to lateral knee stabilisation. Due to its size, tensile strength and easy access, it is widely used in orthopaedic surgery as an autograft during reconstruction procedures. Although ITB harvesting may result in complications, such as reduced knee extension or hip flexion, no safety margins or guidelines have been proposed for the procedure. Our aim was to determine the maximal safe length of an ITB graft, that is, that does not harm the lateral collateral ligament (LCL), tensor fasciae latae (TFL), gluteus maximus (GM) or adjacent structures, and reduce the complication rate. The study included 50 lower limbs of 25 human cadavers, previously fixed in 10% formalin solution. The inclusion criterion was the lack of visible signs of surgical interventions in the study region. Forty lower limbs were included in the study: 16 female (mean age 83.1 ± 3.4 years) and 24 male (mean age 84.2 ± 6.8 years). Dissection was performed with a previously established protocol. Morphometric measurements were then obtained twice by two researchers. The mean femur length was 404.8 mm [female (F) = 397.3 mm, male (M) = 409.9 mm, standard deviation (SD): F = 23.8 mm, M = 24.1 mm]. The mean ITB length was 318.9 mm (F = 309.4 mm, M = 325.2 mm, SD: F = 25.7 mm, M = 33.7 mm). Longer femurs were associated with longer ITB (p < 0.05). The mean distance from the insertion of the GM to the myofascial junction of TFL and ITB was 34.6 mm (F = 34.5 mm, M = 34.6 mm, SD: F = 3.2 mm, M = 3.3 mm). The longer femurs or ITBs demonstrated a greater distance from GM insertion to the myofascial junction of the TFL and ITB (p < 0.05). ITB grafts longer than 21 cm may contribute to the greater risk of TFL rupture. Based on simple measurements of the femur length, the surgeon may assess approximate ITB length, and thus assess the length of the maximal graft length. Moreover, to avoid harming the LCL, the incision should be performed 5 cm proximal to the articular surface of the lateral femoral condyle or 13 mm proximal to the lateral femoral epicondyle. Such preparation and preoperative planning may greatly reduce the risk of complications during ITB harvesting, while performing, for instance, the over-the-top technique for anterior cruciate ligament reconstruction in skeletally immature patients. Basic I.

The role of prediction and visual tracking strategies during manual interception: An exploration of individual differences.

The interception (or avoidance) of moving objects is a common component of various daily living tasks; however, it remains unclear whether precise alignment of foveal vision with a target is important for motor performance. Furthermore, there has also been little examination of individual differences in visual tracking strategy and the use of anticipatory gaze adjustments. We examined the importance of in-flight tracking and predictive visual behaviors using a virtual reality environment that required participants (n = 41) to intercept tennis balls projected from one of two possible locations. Here, we explored whether different tracking strategies spontaneously arose during the task, and which were most effective. Although indices of closer in-flight tracking (pursuit gain, tracking coherence, tracking lag, and saccades) were predictive of better interception performance, these relationships were rather weak. Anticipatory gaze shifts toward the correct release location of the ball provided no benefit for subsequent interception. Nonetheless, two interceptive strategies were evident: 1) early anticipation of the ball's onset location followed by attempts to closely track the ball in flight (i.e., predictive strategy); or 2) positioning gaze between possible onset locations and then using peripheral vision to locate the moving ball (i.e., a visual pivot strategy). Despite showing much poorer in-flight foveal tracking of the ball, participants adopting a visual pivot strategy performed slightly better in the task. Overall, these results indicate that precise alignment of the fovea with the target may not be critical for interception tasks, but that observers can adopt quite varied visual guidance approaches.

The adherence and response of a combined approach of online self-help cognitive behavioral therapy and phone-based psychological guidance among French patients with cancer with insomnia.

12100 Background: Insomnia affects 30–60% of patients with cancer. Cognitive behavioral therapy for insomnia (CBT- I) is the gold-standard treatment for insomnia. However, the uptake of CBT-I in routine care remains low. Technology can be leveraged to facilitate the access and delivery of CBT-I. Nevertheless, adherence rates to online self-help interventions seem low (50-60%), and is associated with reduced intervention efficacy. The Sleep-4-All-2.0 is a prospective multicentric single arm study that evaluated an approach that combined a validated online self-help CBT-I program (Insomnet, 6 modules) to a phone-based guidance with a psychologist (3 orientation meetings). This study assessed: 1) how this combined approach performed in terms of adherence, behavior change and insomnia remission rates compared to prior literature investigating self-help CBT-I, and 2) the patients’ characteristics that are associated with a better or a poorer response. Methods: Data were collected with online questionnaires to compare outcomes: adherence (5 to 6 modules completed), behavior change (ad hoc questionnaire), insomnia remission (Insomnia Severity Index, ISI &lt; 8), sleep perception (ad hoc questionnaire), response to the program (changes in ISI score) at post intervention (week 6, 12 and 24). A descriptive analysis of patient characteristics at each time point was performed. Then, multivariate analyses were conducted: mixed models with a random effect at patient level (repeated measures) and fixed effects for the other variables. The following variables at baseline were used in the adjusted models: socio-demographic and clinical variables, ISI score, symptoms (ESAS), digital skills, barriers to change, motivation, social support and the referring professional. Results: Among the 348 patients included: 79% were women, 59% had breast cancer and 68% were undergoing treatment. A total of 310 patients (89%) initiated Insomnet. The adherence rate was 74% and 79% have changed their behavior. Insomnia remission rates were 34%, 46% and 50% at week 6, 12 and 24, respectively. Insomnia was no longer a problem for 48%, 63% and 66% at week 6, 12 and 24, respectively. Female gender (β=-1.22; p=0.05) and unemployed patients (β=-1.77; p&lt;0.01) were associated with a decrease in ISI scores. Sleep medication (β=1.58; p&lt;0.01), patients with a high sleepiness score (ESAS) (β=0.25; p=0.02) and patients with less digital skills (β=1.85; p&lt;0.01) were associated with an increase in ISI scores. Conclusions: A combination of online self-help CBT-I with phone-based guidance showed satisfactory rates of program adherence, change behavior and insomnia remission. However, some patient profiles such as the ones with lower digital skills and severe insomnia at baseline seemed to benefit less from this approach, and may require further care intensification. Clinical trial information: CONVENTION DE RECHERCHE no. 2020-1-PL SHS-03-IGR-1.