Shaping Guidance Research Articles

Нравственный идеал современного ребенка: педагогическое сопровождение выбора

The study aims to determine the factors influencing the definition of moral ideals among adolescents and the peculiarities of pedagogical support of their moral choice. The main approaches are represented by the authors’ research tools. In total, 3,443 teenagers aged 11–14 years participated in the study that had been conducted since 2017 till 2023. The study revealed that when predicting their ideals, children focus on individuals who are successful, smart, goal-oriented, kind, talented, and ready to overcome obstacles in achieving the goal. TikTokers, bloggers, streamers, YouTubers, programmers, gamers, and e-sportsmen serve as role models for teenagers. The virtual space has a major impact on the moral choices of the new generation. The authors found out the key factors (intellectual, motivational, emotional, volitional, objective and practical, existential, and self-control) that influence an individual’s perception of moral ideals. The risk of forming values unworthy of imitation through social media and the risk of creating an unrealistic idealised ‘self’ projected by the virtual space were identified. The paper concludes that teacher’s guidance in shaping the children’s moral choices is needed.

Social and Personal Determinants of Herbal Supplement Use in Metro Cebu, the Philippines

The present study identified herbal supplement usage patterns in Metro Cebu and comprehensively examined consumer education and behavior regarding these supplements. A cross-sectional online survey was conducted from March–July 2023 involving 316 respondents, selected through purposive sampling. The study collected data on demographic characteristics, usage patterns, sources of information, and potential hesitations related to herbal supplement use. Results indicate that the typical Metro Cebu herbal supplement user is more likely to be female, possess higher education, earn above the minimum wage, and primarily reside in Cebu City (n = 202, 63.9%). Usage of herbal supplements is driven by proactive health behaviors often influenced by social networks. Respondents generally hold a positive view of herbal supplement use, particularly those who consume them daily, attributing their preference to natural products, and their perceived cost-effectiveness and potential health benefits compared to conventional medicines. The following subgroups also tend to have more positive views about herbal supplements: [a] older age, [b] employed, [c] at a lower level of education, [d] have known illnesses, and [e] have used the product for 1-5 yr. While respondents actively verify information (n = 243, 76.9%) and inform healthcare providers (n = 180, 57%) about their supplement use, the extent to which they rely on healthcare professionals and scientific sources for guidance in shaping their behavior and product choices is limited. The study underscores the need for enhanced guidance and surveillance from healthcare providers. Furthermore, it highlights a regulatory gap in the governing framework for herbal supplement use and marketing, emphasizing the importance of revisiting or introducing regulations and guidelines to ensure safe and informed consumption practices.

Challenges and aspirations of neurosurgery residents in Germany: Insights from a questionnaire-based survey

ObjectiveNeurosurgery residents in Germany face numerous challenges including receiving comprehensive surgical training with adequate learning opportunities, achieving balanced work life equilibrium, maintaining a positive work environment and navigating career prospects. The objectives of this study are to assess overall satisfaction with the training program, identify factors contributing to dissatisfaction, explore various dimensions of the training program, evaluate the psychological well-being of residents, and ascertain their preferences for future subspecialties. MethodsA questionnaire-based survey was conducted anonymously among neurosurgery residents from various training hospitals, nationwide. The survey utilized a quantitative questionnaire as data collection tool. The data collection took place from June 2021 to January 2023. ResultsThe survey encompassed 120 neurosurgery residents, with a gender distribution of 55 % male and 45 % female. The respondents were primarily from university hospitals (53 %), followed by community hospitals (38 %) and private hospitals (9 %). In terms of training program satisfaction, 37 % reported moderate satisfaction, 39 % indicated below-moderate satisfaction, and 28 % experienced above-moderate satisfaction. The predominant causes of dissatisfaction identified were insufficient surgical exposure (reported by 39 % of respondents), suboptimal educational content (38 %), and inadequate research opportunities (32 %). Additionally, 24 % of respondents highlighted psychological stress, and 36 % reported frequent experiences of burnout. A majority (63 %) indicated a workload of 60–80 h weekly. About half of the residents indicated a future specialization interest in neurosurgical oncology. ConclusionThe results of the survey findings provide valuable insights into the challenges and aspirations of neurosurgery trainees in Germany. These results serve as a basis for improving the training system, enhancing the working environment, and guiding future planning in this field. To optimize the training of residents, it is important to address issues such as limited surgical and research opportunities and psychological well-being. The expressed interest in subspecializing offers guidance for shaping the training program’s future direction.

Urgensi Bimbingan Penyuluhan Islam (BPI) Dalam Membentuk Karakter Remaja di Lingkungan Tembelok Kelurahan Mandalika Kecamatan Sandubaya Kota Mataram

This research aims to determine the urgency of Islamic counseling guidance in shaping the character of teenagers and to find out the supporting and inhibiting factors for implementing the urgency of Islamic counseling guidance in shaping the character of teenagers in the Tembelok Neighborhood, Mandalika Village, Sandubaya District, Mataram City. This research uses a qualitative approach. This approach is used so that the author can gain a broad and in-depth understanding of the urgency of BPI in shaping the character of teenagers in the Tembelok Neighborhood, Mandalika Village, Sandubaya District, Mataram City. The research results show that Islamic Counseling Guidance (BPI) is very important. First, BPI helps direct teenagers to the path of goodness with strong supervision from parents and religious figures. Second, BPI instills religious values ​​from an early age to direct youth's piety and faith. Third, BPI helps develop an attitude of awareness in teenagers with love, patience and coaching. Meanwhile, supporting and inhibiting factors in shaping adolescent character include the existence of Islamic Counselors and the active role of religious and community leaders as supporting factors, while environmental complexity, difficulty in controlling adolescent self-control, character formation from an early age or during puberty, negative environmental impacts, and lack of affection. from parents as an inhibiting factor.

Design and optimization of a thermoelectric generator with dimple fins to achieve higher net power

To enhance the performance of the automobile thermoelectric generator (ATEG), this study proposes a heat exchanger with dimple fins, where the number of dimples systematically increases along the direction of exhaust flow. The innovative combination of dimples with fins effectively addresses the impact of temperature reduction in the exhaust. The distribution of dimples on the fins is optimized based on a fluid-thermal-electric multiphysics model and a net power model. According to simulation results, it can be found that as the number of columns and radius of the dimples increase, the ability of the heat exchanger to transfer heat is improved while the back pressure loss of the exhaust flow is also increased. Through optimizations, the optimal dimple distribution of n = 8 and r = 1.45 mm is obtained, achieving a maximum net power output of 62.46 W. The performance of the optimized ATEG with dimple fins is greatly improved in comparison with the conventional plate-fin structure, and its conversion efficiency, output power, output voltage, and net power output are increased by 16.07 %, 28.95 %, 13.56 %, and 10.09 %, respectively. The results of this study offer valuable guidance for shaping the heat exchanger’s design.

Semi-Supervised Medical Image Segmentation Using Cross-Style Consistency With Shape-Aware and Local Context Constraints.

Despite the remarkable progress in semi-supervised medical image segmentation methods based on deep learning, their application to real-life clinical scenarios still faces considerable challenges. For example, insufficient labeled data often makes it difficult for networks to capture the complexity and variability of the anatomical regions to be segmented. To address these problems, we design a new semi-supervised segmentation framework that aspires to produce anatomically plausible predictions. Our framework comprises two parallel networks: shape-agnostic and shape-aware networks. These networks learn from each other, enabling effective utilization of unlabeled data. Our shape-aware network implicitly introduces shape guidance to capture shape fine-grained information. Meanwhile, shape-agnostic networks employ uncertainty estimation to further obtain reliable pseudo-labels for the counterpart. We also employ a cross-style consistency strategy to enhance the network's utilization of unlabeled data. It enriches the dataset to prevent overfitting and further eases the coupling of the two networks that learn from each other. Our proposed architecture also incorporates a novel loss term that facilitates the learning of the local context of segmentation by the network, thereby enhancing the overall accuracy of prediction. Experiments on three different datasets of medical images show that our method outperforms many excellent semi-supervised segmentation methods and outperforms them in perceiving shape. The code can be seen at https://github.com/igip-liu/SLC-Net.

Test-Time Adaptation via Style and Structure Guidance for Histological Image Registration

Image registration plays a crucial role in histological image analysis, encompassing tasks like multi-modality fusion and disease grading. Traditional registration methods optimize objective functions for each image pair, yielding reliable accuracy but demanding heavy inference burdens. Recently, learning-based registration methods utilize networks to learn the optimization process during training and apply a one-step forward process during testing. While these methods offer promising registration performance with reduced inference time, they remain sensitive to appearance variances and local structure changes commonly encountered in histological image registration scenarios. In this paper, for the first time, we propose a novel test-time adaptation method for histological image registration, aiming to improve the generalization ability of learning-based methods. Specifically, we design two operations, style guidance and shape guidance, for the test-time adaptation process. The former leverages style representations encoded by feature statistics to address the issue of appearance variances, while the latter incorporates shape representations encoded by HOG features to improve registration accuracy in regions with structural changes. Furthermore, we consider the continuity of the model during the test-time adaptation process. Different from the previous methods initialized by a given trained model, we introduce a smoothing strategy to leverage historical models for better generalization. We conduct experiments with several representative learning-based backbones on the public histological dataset, demonstrating the superior registration performance of our test-time adaptation method.

Metal-Organic Frameworks for the Enhancement of Lithium-Based Batteries: A Mini Review on Emerging Functional Designs.

Metal-organic frameworks (MOFs) have played a crucial role in recent advancements in developing lithium-based battery electrolytes, electrodes, and separators. Although many MOF-based battery components rely on their well-defined porosity and controllable functionality, they also boast a myriad of other significant properties relevant to battery applications. In this mini-review, the distinct advantages of MOFs in battery applications are discussed, including using MOFs to 1) scavenge impurities to increase cycling stability, 2) widen the operation temperature range of conventional electrolytes, 3) widen the operation voltage range of common electrolytes, and 4) employ as artificial solid-electrolyte interphases to prevent lithium dendrite growth. Furthermore, subsisting challenges of developing these emerging MOF-based battery technologies are discussed and guidance for shaping the future of this field is given.

Seaweed and climate change: A mapping review

Seaweed has garnered increasing interest due to its capacity to mitigate climate change by curbing carbon emissions from agriculture, as well as its potential to serve as a supplement or alternative for dietary, livestock feed, or fuel source production. Moreover, seaweed is regarded as one of the earliest plant forms to have evolved on Earth. Owing to the extensive body of literature available and the uncertainty surrounding the future trajectory of seaweed research under evolving climate conditions, this review scrutinizes the structure, dynamics, and progression of the literature pertaining to seaweed and climate change. This analysis is grounded in the Web of Science Core Collection database, augmented by CiteSpace software. Furthermore, we discuss the productivity and influence of individual researchers, research organizations, countries, and scientific journals. To date, there have been 8047 articles published globally (after a series of filters and exclusions), with a notable upswing in publication frequency since 2018. The USA, China, and Australia are among the leading countries contributing to this research area. Our findings reveal that current research on seaweed and climate change encompasses 13 distinct research clusters, including “marine heatwave”, “temperate estuary”, “ocean acidification”, and “macroalgal bloom”. The most frequently cited keywords are “climate change”, “biomass”, “community”, and “photosynthesis”. The seaweed species most commonly referenced in relation to climate change include Gracilaria sp., Sargassum sp., Ecklonia maxima, and Macrocystis pyrifera. These results provide valuable guidance for shaping the direction of specialized topics concerning marine biodiversity under shifting climate conditions. We propose that seaweed production may be compromised during prolonged episodes of reduced water availability, emphasizing the need to formulate strategies to guarantee its continued viability. This article offers fresh perspectives on the analysis of seaweed research in the context of impending climate change.

Exploration of visual variable guidance in outdoor augmented reality geovisualization

ABSTRACTThe visual perception of augmented reality (AR) geovisualization is significantly different from traditional controllable 2D and 3D visualization. In this study, we extended the rendering styles of color variables to include natural material color (NMC) and illuminating material color (IMC) and extended the size to include linear size (LS) and angular size (AS). Outdoor AR geovisualization user experiments were conducted, examining the guidance characteristics of five static variables (NMC, IMC, shape, AS, LS) and two dynamic variables (vibration, flicker). The results showed that the two dynamic variables provided the highest guidance, and among all the static variables, the order of guidance was shape, IMC, AS, NMC, and finally LS. This is a new finding that is different from the color, size, and shape guidance order in 2D visualization and the color, shape, and size order in 3D visualization. The results could be utilized to guide the selection of visual variables for symbol design in AR geovisualization.

Seminar Parenting: Membentuk Karakter 4.0 Anak Melalu Peran Bimbingan Orang Tua

The purpose of the seminar is to provide participants with knowledge about the role of parental guidance in shaping the character of 4.0 in children. The implementation method is face-to-face with a duration of 3.5 hours. The equipment used is an LCD projector, laptop, manual, sound system, table, and chairs. Service flow: forming a committee; designing guidebooks, banners, and flyers; making invitations; implementation of seminars and evaluation of seminars. The results of the dedication: the seminar was successful with the following agenda: first the opening by the head of the study program; second, giving material I about character education, character 4.0 in children and the role of parents; third, the provision of material on approaches and guidance techniques; fourth discussion and fifth group photo. Conclusion: the seminar went according to the agenda. Suggestion: the seminar committee provides mini-assignments for seminar participants.

Improving breast tumor segmentation via shape-wise prior-guided information on cone-beam breast CT images

Objective. Due to the blurry edges and uneven shape of breast tumors, breast tumor segmentation can be a challenging task. Recently, deep convolution networks based approaches achieve satisfying segmentation results. However, the learned shape information of breast tumors might be lost owing to the successive convolution and down-sampling operations, resulting in limited performance. Approach. To this end, we propose a novel shape-guided segmentation (SGS) framework that guides the segmentation networks to be shape-sensitive to breast tumors by prior shape information. Different from usual segmentation networks, we guide the networks to model shape-shared representation with the assumption that shape information of breast tumors can be shared among samples. Specifically, on the one hand, we propose a shape guiding block (SGB) to provide shape guidance through a superpixel pooling-unpooling operation and attention mechanism. On the other hand, we further introduce a shared classification layer (SCL) to avoid feature inconsistency and additional computational costs. As a result, the proposed SGB and SCL can be effortlessly incorporated into mainstream segmentation networks (e.g. UNet) to compose the SGS, facilitating compact shape-friendly representation learning. Main results. Experiments conducted on a private dataset and a public dataset demonstrate the effectiveness of the SGS compared to other advanced methods. Significance. We propose a united framework to encourage existing segmentation networks to improve breast tumor segmentation by prior shape information. The source code will be made available at https://github.com/TxLin7/Shape-Seg.

DPText-DETR: Towards Better Scene Text Detection with Dynamic Points in Transformer

Recently, Transformer-based methods, which predict polygon points or Bezier curve control points for localizing texts, are popular in scene text detection. However, these methods built upon detection transformer framework might achieve sub-optimal training efficiency and performance due to coarse positional query modeling. In addition, the point label form exploited in previous works implies the reading order of humans, which impedes the detection robustness from our observation. To address these challenges, this paper proposes a concise Dynamic Point Text DEtection TRansformer network, termed DPText-DETR. In detail, DPText-DETR directly leverages explicit point coordinates to generate position queries and dynamically updates them in a progressive way. Moreover, to improve the spatial inductive bias of non-local self-attention in Transformer, we present an Enhanced Factorized Self-Attention module which provides point queries within each instance with circular shape guidance. Furthermore, we design a simple yet effective positional label form to tackle the side effect of the previous form. To further evaluate the impact of different label forms on the detection robustness in real-world scenario, we establish an Inverse-Text test set containing 500 manually labeled images. Extensive experiments prove the high training efficiency, robustness, and state-of-the-art performance of our method on popular benchmarks. The code and the Inverse-Text test set are available at https://github.com/ymy-k/DPText-DETR.

Platooning in UAM airspace structures: applying trajectory shaping guidance law and exploiting cooperative localization

A novel control technique for the platooning of aerial vehicles is here introduced, and its stability is analyzed. The controller applies a missile guidance law that was initially adapted for path-following and subsequently extended to platooning. The positions of all agents within a platoon employing this controller are estimated by exploiting cooperative localization, and these estimated positions are fed back into the controller. Using simulation, the agents within a platoon are demonstrated to follow their desired path and avoid collision, even in environments with intermittent Global Positioning System signals and limited sensing ranges.

Cooperative trajectory shaping guidance law for multiple anti-ship missiles

Abstract To enhance the performance of anti-ship missiles cooperative attack, this paper proposes a finite-time trajectory shaping-based cooperative guidance law (TSCGL). Firstly, the cooperative guidance model is established on segmented linearisation of the missile’s heading angle. Then, a trajectory shaping guidance law for a single missile is derived by a weighted optimal energy cost function and Schwarz inequality. On this basis, a finite-time TSCGL is proposed combined with trajectory shaping technology and finite-time theory. The desirable finite-time convergence performance can ensure a simultaneous attack. Through an improved method of time-to-go estimation, it is independent of small-angle assumption and relaxes the launching conditions of the missiles. Additionally, the proposed finite-time TSCGL can achieve better damage performance through energy management. Finally, simulation results demonstrate the effectiveness and superiority of the proposed finite-time TSCGL.

RFS-Net: Railway Track Fastener Segmentation Network With Shape Guidance

The fastener is one of the main components of a rail track system. In recent years, deep learning methods such as image segmentation have greatly boosted the fastener state detection process. However, there is still a need to improve the segmentation accuracy and speed, especially for the fasteners in complex environments. To handle this problem, a fast and accurate fastener semantic segmentation network named RFS-Net is proposed based on shape guidance, which can offer a better speed/accuracy trade-off performance via a very shallow architecture. Specifically, in the encoder, a two-stream structure (i.e., regular stream and shape stream) that processes the fastener and shape image in parallel is introduced. The shape image is created based on the geometric structure of the fastener, and it is served as input to the shape stream to guide the segmentation of the fastener. The decoder integrates deep features from the two-stream encoder and then recovers the shape information by the shape attention blocks with skipping connections. We provide two versions of RFS-Net: RFS-Net_S (1.0M, 1014FPS) and RFS-Net_L (12.01M, 453FPS) on the NVIDIA RTX 3060. Experimental results demonstrate the effectiveness of our method by achieving a promising trade-off between accuracy and inference speed. In particular, our method is faster and more accurate on a challenging dataset, from fast modes: 1014 FPS for RFS-Net_S versus 724 FPS for Segmenter, to high-quality segmentation: better performance than STDC with nearly one percent (92.36% versus 91.48% Mean IoU score).

ПОЛІТИКА НАЦІОНАЛЬНОГО БАНКУ УКРАЇНИ ПІД ЧАС ВІЙНИ ТА ПЕРСПЕКТИВИ ЇЇ ПОДАЛЬШОГО РОЗВИТКУ

The article scrutinises and assesses the efficacy of the National Bank of Ukraine's (NBU) policy amidst the period of military conflict. It is discerned that the timely interventions of the NBU facilitated control over devaluation tendencies and inflationary pressures while bolstering the liquidity of the banking sector through refinancing mechanisms. This ensured the uninterrupted functionality of electronic payment systems, thereby upholding a commendable degree of financial stability amid the adversities of conflict. The appraisal of the NBU's policy effectiveness throughout 2022-23 underscores its commendable outcomes. The article emphasises the significance of Ukraine's financial bolstering from allied nations and its collaboration with international financial bodies, notably the International Monetary Fund, playing a pivotal compensatory role in sustaining the operational framework of Ukraine's economy. The research has unearthed nuanced outcomes stemming from the implemented array of measures, particularly concerning capital outflows and escalated benchmark interest rates. These measures, while instrumental, have led to an upsurge in the cost of credit for economic agents. This underscores the imperative for enhanced synchronisation between the NBU and the Government, particularly concerning interest rate policy and deposit certificates rates, and accentuates the necessity for broader credit extension within the tangible sectors of the economy. The article navigates the nuances in NBU decisions within conflict conditions, reflecting both positive and adverse outcomes and implications. Emphasis is placed on the need to mitigate prospective risks during the execution of monetary and currency policies, predicated upon an in-depth analysis of pros and cons, coupled with a more precise delineation of priorities. Given considerable domestic and international uncertainties, the article stresses the pivotal role of augmenting scholarly and analytical guidance in shaping the managerial decisions of the national regulator, aimed at fortifying financial resilience and preserving the controllability of the financial sector.

Numerical Shape Planning Algorithm for Hyper-Redundant Robots Based on Discrete Bézier Curve Fitting

The paper proposes a novel numerical method S-GUIDE that provides real-time planning of the shape of hyper-redundant robots with serial architecture by means of a guidance curve, represented in parametrized analytical form and in numerical form by a set of key points associated with the robot structure. To model the shape of the robot, the method uses an equivalent model, and a shape guidance curve obtained through a controlled adjustment of a Bézier curve. This is achieved in three computing steps were the robot equivalent structure, it’s associated kinematic parameters and the robot actuation parameters in joint space are calculated. The proposed method offers several advantages in relation with the precision, computing time and the feasibility for real-time applications. In the paper, the method accuracy, execution time, and the absolute error for different work scenarios are determined, compared and validated.

Unified Control Parameterization Approach for Finite-Horizon Feedback Control With Trajectory Shaping

This article presents control parameterization as a unifying framework for designing a linear feedback control law that achieves the finite-time transfer of output as well as trajectory shaping. Representing control input as a linear combination of independent basis functions allows wide variability in the resultant feedback control laws through the selection of the number and types of basis functions. Given an array of basis functions that meets the trajectory shaping necessities, the unified design approach proceeds with the determination of the coefficients so that the predicted trajectory attains the desired output at the final time. The input evaluated with the coefficients found at each instance essentially turns out to be a linear state feedback policy with an additional feedforward term and time-dependent gains, which is appropriate for practical use. The unified control parameterization approach lends itself well to missile guidance applications with the expandability and direct trajectory shaping capability that it provides. To emphasize the expandability of the framework, this study revisits the trajectory shaping guidance laws from the control parameterization viewpoint and shows how the notion of specifying input basis functions not only generalizes various existing methods but also enables further extensions. Furthermore, an application to integrated guidance and control illustrates the strength of the design process in handling the shaping requirements more directly through the construction of appropriate basis.

Optimal Look-Angle Guidance with Field-of-View and Impact Angle Constraints for Strapdown Munition

A strapdown seeker with limited field-of-view (FOV) can simplify and decrease cost of the guidance system for a munition. However, the inherent defect of the strapdown seeker is that it could not provide the necessary line-of-sight (LOS) angular information for typical guidance application. This paper proposed an optimal look-angle guidance law (OLAGL) which directly utilized seeker angle information and satisfies the constraints of FOV and terminal impact angle. The coefficient determination, effects of switching threshold, and gains for the guidance law are analyzed and detailed. The simulation results compared with typical trajectory shaping guidance for a ground target show that the presented guidance law can satisfy the impact angle constraint under the limitation of FOV and provide a well engineering reference.