Adaptive Decision Research Articles

Methodology for adapting a co-created early childhood development intervention and implementation strategies for use by frontline workers in India and Guatemala: a systematic application of the FRAME-IS framework

ABSTRACT There is little evidence on optimizing the effectiveness and implementation of evidence-based early childhood development (ECD) interventions when task-shifted to frontline workers. In this Methods Forum paper, we describe our adaptation of the International Guide for Monitoring Child Development (GMCD) for task-shifting to frontline workers in Guatemala and India. In 2021–2022, implementers, trainers, frontline workers, caregivers, and international GMCD experts collaborated to adapt the GMCD for a task shifted implementation by frontline workers. We used an eight-step co-creating process: assembling a multidisciplinary team, training on the existing package, working groups to begin modifications, revision of draft modifications, tailoring of visual materials and language, train-the-trainers activities, pilot frontline worker trainings, final review and feedback. Preliminary effectiveness of adaptations was evaluated through narrative notes and group-based qualitative feedback following pilot trainings with 16 frontline workers in India and 6 in Guatemala. Final adaptations included: refining training techniques to match skill levels and learning styles of frontline workers; tailoring all visual materials to local languages and contexts; design of job aids for providing developmental support messages; modification of referral and triage processes for children in need of enhanced support and speciality referral; and creation of post-training support procedures. Feedback from pilot trainings included: (1) group consensus that training improved ECD skills and knowledge across multiple domains; and (2) feedback on ongoing needed adjustments to pacing, use of video-based vs. role-playing materials, and time allocated to small group work. We use the Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies (FRAME-IS) framework to document our adaptations. The co-creating approach we use, as well as systematic documentation of adaptation decisions will be of use to other community-based early childhood interventions and implementation strategies.

Psychological Trust Dynamics in Climate Change Adaptation Decision-Making Processes: A Literature Review

There has been a growth in interest among academics and professionals in psychological trust dynamics during climate change adaptation. This literature review aimed to examine the research concerning trust dynamics in climate change adaptation from different levels of analysis, encompassing the different phases of adaptation and considering the importance of trust in climate change decision-making. The method consisted of systematically reviewing researches on this topic published in scientific articles, by using appropriate and relevant search keywords (e.g., trust, community, natural hazard, climate change adaptation, decision-making) in academic databases. A total of 25 studies met inclusion criteria. All the articles focused on the latter phases of the climate change adaptation cycle, specifically implementation and monitoring/evaluation, with limited attention devoted to decision-making related to earlier phases of preparation, assessment of risks, and identification and selection of adaptation options. The reviews also indicates that psychological trust is related to different adaptive actions (e.g., adoption of renewable energy technologies), and low- and high-impact mitigation behaviors (e.g., acceptance of paying taxes for actions that mitigate climate change). Therefore, this review underscores the significant role of psychological trust dynamics in shaping individuals’ decision-making processes concerning climate change adaptation, thereby yielding immediate and direct implications for climate systems. Therefore, it is essential to actively promote the culture of trust within the context of climate change adaptation.

The Role of Social Capital in Climate Change Adaptation: Small Farmers’ Perspective

Climate change represents a major challenge for businesses and society. Small farmers in emerging economies are most vulnerable to extreme weather events and must adapt their strategies and operations. Adaptive decision-making depends on the risk perception and the availability of resources, which can be a major limitation for the context of small farmers. Our study investigates how farmers perceive climate change risks and decide on climate adaptation. We explore the small farmers` vulnerability, risk perception, and decision-making process with in-depth interviews with small farmers in different network contexts. Our data reveal that small farmers, isolated in terms of communication and support regarding climate adaptation, used social exchanges to learn and adapt. However, as the social network was the primary source of information, knowledge, and experience sharing, the quality of network relationships made a difference. Thus, the importance of social capital to enable climate adaptation.

A 16-Gb/s 3-tap adaptive DFE in 12-nm FinFET CMOS technology

This paper introduces a 3-tap half-rate adaptive decision feedback equalizer (DFE) and a 2-D eye-opening monitor (EOM). A newly developed regenerating sampler (RG-sampler) with smaller setup time and ck2q time is integrated into the proposed DFE, enhancing its performance. To ensure greater robustness, the sign-sign least-mean-squares (SSLMS) algorithm with a pattern filter is employed to adapt DFE tap coefficients. The proposed 2-D EOM accurately captures the shape of the eye diagram using adjustment steps of 1.95ps and 7 mV in the horizontal and vertical directions, respectively. Additionally, by reusing analog components within the adaptive DFE and 2-D EOM modules, significant reductions in silicon area and power consumption are achieved. Implemented in 12-nm FinFET CMOS technology, the transceiver integrated with adaptive DFE and 2-D EOM operates at a data rate of 16 Gb/s over a channel with 30 dB loss at 8 GHz frequency. The proposed adaptive DFE and 2-D EOM occupy a total area of 0.00808 mm2. Measurement results demonstrate that following DFE adaptation, the eye height is 77 mV, and the eye width is 29.25ps at 16 Gb/s.

Are cities genuinely healthy? Diagnosis of urban development from the perspective of adaptive capacity

As urban diseases continue to emerge with the acceleration of urbanization, the transformation of urban governance concepts and systems must be urgently promoted. In dealing with the complex systemic problem of city governance, the concept of adaptation in complex adaptative system (CAS) theory has shown obvious advantages. This approach provides a new perspective for solving this problem in the face of the unprecedented complexity of current disasters. However, research on urban adaptation is currently hindered by imprecise terminology, significant bias, and insufficient empirical evidence. This study reinterprets the concept of urban adaptation in conjunction with CAS theory. The formula for the functional expression of urban adaptation is derived using dissipative structure theory. Indicators are then selected to describe the system of urban adaptive capacity. An adaptive decision support framework is established that covers 29 quantitative and 8 qualitative indicators. The adaptive performance of 12 sample cities is analyzed. Finally, this study provides corresponding planning paths for optimizing urban adaptation based on the evaluation results. The research findings can assist city managers in comprehending the actual situation of cities and provide a basis for formulating targeted governance programs.

Weather variability risks slow climate adaptation: An empirical analysis of forestry

The timing of climate adaptation decisions can have substantial consequences for the assessment of climate damages. Since weather variability can create risks for natural resource management that differ across adaptation choices, such variability has the potential to alter the speed of climate adaptation. This paper estimates the effect of weather variability on the timing of adaptation decisions of forest landowners in the Eastern United States. A discrete-choice econometric model of forest management is estimated and used in a bio-economic simulation that shows how variability in cold temperatures can significantly slow the rate of adapting from cold-tolerant natural hardwood forests to cold-sensitive, but highly valuable pine plantations. The range of weather variability in climate projections and across the landscape generates large differences in adaptation timing. Ignoring projected future decreases in weather variability results in a large downward bias in estimating future paths of climate adaptation. Since pine plantations produce fewer non-market ecosystem services than natural hardwood forests, an important source of future conservation uncertainty is the economic response of private forest landowners to changing weather variability.

A Low-Complexity Adaptive Confidence Decision Equalizer for ZP-OTFS Systems

A Low-Complexity Adaptive Confidence Decision Equalizer for ZP-OTFS Systems

Understanding the neural principles of interacting multiple internal states

In dynamic ethological environments, animals are constantly confronted with conflicting choices driven by interacting internal motivations. This intricate dance between internal states prompts the question: How do these states interact to determine the optimal innate behavior at any given moment? Specifically, when hungry animals encounter food and potential intruders, how do they navigate between feeding, attack, and mating behaviors? Despite extensive neuroscience research on instinctive behaviors, our understanding of the mechanisms governing adaptive behavioral decisions in the face of competing internal signals remains limited. This research aims to shed light on the complex interplay of internal physiological homeostasis in modulating defensive, aggressive, and sexual behaviors. Our focus lies on exploring the intricate network between the body and the brain to unravel the most adaptive responses within a concise time window. Currently, our investigations center around the hypothalamus, a crucial region known for representing emotional states upon encountering conspecifics or predators. Intriguingly, this same hypothalamic nucleus plays a pivotal role in regulating homeostatic metabolic states, including glucose homeostasis. Here, I will share the observation from innate behaviors of animals and the associated neural activity patterns in the hypothalamus. We will explore the current understanding of how these behaviors are modulated by internal physiological states and discuss the future directions of our research. Additionally, we aim to highlight the significance of combining the measurement of physiological signals to comprehensively address how multiple internal states interact with each other. By unraveling the complexities of these interactions, our research contributes to a deeper comprehension of the adaptive decision-making processes that animals employ in the face of conflicting choices. Helen Hay Whitney Foundation, HHMI. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Modeling and Simulation of Phase Change Memory Using Digital Logic Implementation Approach

Phase Change Memory (PCM) adapts to space utilization and bit storage for displaying amorphous or crystalline states. This change of state relies on the nature of the information and its non-volatility period. As is well known Digital Logic operations are influential over memory modeling, this article introduces a Propagative Adaptability Decision Module (PADM) using DL. This module is utilized based on the information non-volatility across overflow and underflow memory conditions. This utilization-based classification induces the digital logic influence by swapping the states that are robust for further propagative adaptability. This means the possible logical combinations of 0’s and 1’s are used for deciding the states of PCM. The logical operations using OR and NOT are used for reducing overflows whereas the AND and NOT combinations are used for preventing underflows. This reduces the volatility show-up in two distinct phases of memory utilization. Therefore, the 0 and 1 combinations are validated for all the logical operations to ensure propagative memory swapping for balancing the overflow and underflow conditions. This process does not mark up the highest 1 or 0 combination individually due to state changes. The proposed module is validated using swapping rate, time, complexity, and overflow conditions.

Enhancing Techniques for Adaptable Decision Feedback Balancer for 5G Communication

Abstract: This complete review examines two basic parts of cutting edge correspondence frameworks. First and foremost, it investigates novel plan procedures and models for Adaptable Decision Feedback Balancer (ADFB) in rapid correspondence frameworks. Strategies like look-into tables, disseminated math, and prescient equal branch slicers are utilized to upgrade union rates, throughput, and mistake execution while limiting equipment intricacy. The proposed plans exhibit significant advancement in region, power proficiency, and rationale usage across different regulation plans, channel models, and portability situations. Furthermore, the examination digs into Super Dependable Low Idleness Correspondence (SDLIC) headways inside the 5G New Radio (NR) downlink, tending to actual layer difficulties determined in 3GPP Delivery 15. The review presents a clever correspondence framework utilizing super codes to moderate between image impedance in remote conditions. Also, inventive equal plans for high velocity Choice Input Adjusters (CIAs) and equipment proficient models for versatile balancers utilizing disseminated number-crunching are introduced. The joined discoveries contribute significant bits of knowledge into streamlining versatile balancers for group of people yet to come correspondence frameworks and progressing SDLIC in 5G NR.

A Study of Adaptive Threshold Based on the Reconstruction Model for Marine Systems and Their Equipment Failure Warning

To achieve the failure warning of marine systems and their equipment (MSAE), the threshold is one of the most prominent issues that should be solved first. In this study, a fusion model based on sparse Bayes and probabilistic statistical methods is applied to determine a new and more accurate adaptive alarm threshold. A multistep relevance vector machine (RVM) model is established to realize the parameter reconstruction in which the internal uncertainties caused by the degradation process and the external uncertainty caused by the loading, environment, and disturbances were considered. Then, a varying moving window (VMW) method is employed to determine the window size and achieve continuous data reconstruction. Further, the model based on Johnson distribution systems is utilized to complete the transformation of the residual parameters and calculate the adaptive threshold. Finally, the proposed adaptive decision threshold is successfully involved in the actual examples of the peak pressure and exhaust temperature of marine diesel engines. The results show that the proposed method can realize the continuous health condition monitoring of MSAE, successfully detect abnormal conditions in advance, achieve an early warning of failure, and reserve sufficient time for decision-making to prevent the occurrence of catastrophic disasters.

An adaptive seamless 2-in-1 design with biomarker-driven subgroup enrichment

ABSTRACT Adaptive seamless phase 2/3 subgroup enrichment design plays a pivotal role in streamlining efficient drug development within a competitive landscape, while also enhancing patient access to promising treatments. This design approach identifies biomarker subgroups with the highest potential to benefit from investigational regimens. The seamless integration of Phase 2 and Phase 3 ensures a timely confirmation of clinical benefits. One significant challenge in adaptive enrichment decisions is determining the optimal timing and maturity of the primary endpoint. In this paper, we propose an adaptive seamless 2-in-1 biomarker-driven subgroup enrichment design that addresses this challenge by allowing subgroup selection using an early intermediate endpoint that predicts clinical benefits (i.e. a surrogate endpoint). The proposed design initiates with a Phase 2 stage involving all participants and can potentially expand into a Phase 3 study focused on the subgroup demonstrating the most favorable clinical outcomes. We will show that, under certain correlation assumptions, the overall type I error may not be inflated at the end of the study. In scenarios where the assumptions may not hold, we present a general framework to control the multiplicity. The flexibility and efficacy of the proposed design are highlighted through an extensive simulation study and illustrated in a case study in multiple myeloma.

Adaptive decision threshold algorithm based on a sliding window to reduce BER of free-space optical communication systems

Free-space optical communication (FSOC) systems face susceptibility to several factors, such as transmission distance, atmospheric turbulence, and alignment errors. These elements contribute to fluctuations in the signal strength reaching the receiver. The resultant signal fluctuations can result in misjudgments and an elevated bit error rate (BER). This paper proposes an adaptive decision threshold algorithm based on a sliding window (ADTSW). By estimating received signal parameters and delimiting the amplitude interval, the algorithm ensures that the decision threshold tracks signal fluctuations, thereby reducing signal misjudgment. The effectiveness of the algorithm is validated through simulations and experimentation. When the signal peak-to-peak value fluctuates, simulation results demonstrate that the proposed algorithm achieves a 1-order-of-magnitude reduction in BER compared to the traditional fixed decision threshold (FDT) method. Under the influence of weak atmospheric turbulence with different scintillation variance, both simulation and experimentation indicate a 1-order-of-magnitude reduction in BER compared to the FDT method. The ADTSW algorithm proves its capability in minimizing misjudgments, thereby effectively reducing BER and improving communication quality.

Constructivist Feedback-Based Assessment Method as Key for Effective Teaching and Learning: The Development and Impact on Mechanical Engineering Students’ Adaptive Capacity, Decision Making, Problem Solving and Creativity Skills

Educators must conduct assessments in their learning; it determines students’ weaknesses in the teaching material they follow during learning. Unfortunately, the implementation of assessment by educators was not optimal, and the weakness was that the existing assessment method was only fixated on assessing students without providing feedback on the assessment. At the same time, this feedback was essential for students in learning, which can help learners assess performances that cannot be seen and felt by themselves, as well as a tool to motivate students, notification or information, and reinforcement. Therefore, this research aimed to develop a Constructivist Feedback-Based Assessment Method for learning assessment. The method used in this research was Research and Development (R&D). After development, the Constructivist Feedback-Based Assessment Method for learning assessment will be implemented to see its effect on students’ adaptive capacity, decision-making, problem-solving, and creativity skills. Independent sample t-test and linear regression analysis were used as data analysis techniques describing the impact of the assessment on those skills. The results showed that the Constructivist Feedback-Based Assessment Method has five stages: preparing the assessment material, diagnostic assessment, assessment for learning, assessment of learning, and reflection. It effectively affects students’ skills, such as adaptive capacity, decision-making, problem-solving, and creativity. It can be concluded that the Constructivist Feedback-Based Assessment Method can improve students’ adaptive capacity, decision-making, problem-solving, and creativity. Novelty in this research was the existence of constructivism integrated into feedback-based assessment, which the existing assessment has not highlighted the constructivist side of assessment.

Management of innovative activities of technological and industrial territorial systems

Management of innovative activity in technological and industrial territorial systems (TITS) becomes particularly relevant in the context of globalization and increasing competitiveness. This study focuses on exploring methods of innovation management within TITS, including strategic planning, implementation of innovative processes, and cooperation among government structures, the private sector, and scientific institutions. The research aims to develop recommendations for managing innovative activities in technological and industrial territorial systems. The article delves into the essence of managing innovative processes at the territorial and industrial territorial systems level, exemplified by techno and industrial parks. It establishes fundamental principles of management, including the principle of foresight, the principle of integration of innovative processes, the principle of division of labor, specialization, and cooperation, the principle of delineation of competencies, the principle of informatization, and the principle of efficiency in managing innovative activities in a science and technology park. Management of innovative activity in technological and industrial territorial systems is carried out through stages such as forming a complete spectrum of tasks related to organizing innovative activity, providing detailed descriptions according to the chosen methodology, assessing interrelationships between tasks, and systematizing tasks by considering established criteria. The essence of managing innovative processes at territorial-technological structures is thoroughly investigated. Particular emphasis is placed on critical principles of managing innovative activity, which include the ability to forecast the development of innovative processes and adapt management decisions according to future trends; ensuring coordinated work of various innovative initiatives and projects to achieve a synergistic effect; optimizing the distribution of functions and tasks among participants of the innovation process to enhance overall efficiency; clear definition and distribution of authority and responsibility among different management levels and organizations; implementation of modern information technologies to support decision-making and enhance the transparency of innovative processes; focus on achieving maximum results with minimal resource expenditure. The essence of managing innovative activity in technological and industrial territorial systems is substantiated; principles of managing innovative activity are defined: the principle of foresight; the principle of integration of innovative processes; the principle of division of labor, specialization, and cooperation; the principle of delineation of competencies; the principle of informatization; the principle of management efficiency in regional innovation activity. The following stages for managing innovative activity in technological and industrial territorial systems are implemented: construction of a complete set of tasks for organizing innovative activity and their description according to the chosen scheme; assessment of the connection between tasks; grouping of tasks by given criteria. Keywords: innovation, innovative activity, management, technological and industrial territorial systems, social effect, cluster

Ocean ecosystem services: modeling a factor development process to create sustainable value for decisions

PurposeThe purpose of this paper is to model a process for moving toward sustainable ecosystem service decisions in a Coastal Biodiversity and discuss the directions of the process for decision-makers to apply in ocean ecosystem services.Design/methodology/approachAfter the development of theoretical approaches to understand their prospects for the future development of ecosystem services, the authors worked on a process for developing factors for sustainable decision-making. It uses the Delphi method to develop all the factors supported by six dimensions in two specific moments: deductive-inductive and inductive-deductive.FindingsThis process of modeling the factors expands the possibility of adaptive governance to make prior and subsequent decisions using factors related to dimensions, stakeholders and benefits, risks, opportunities and costs.Research limitations/implicationsConsidering the limitations, future studies could use another database to widen the view in terms of the studies, factors, dimensions and other additional information to maintain the evolution of this process in ocean ecosystem services decision-making. Another limitation arose in the number of projects and experts defining the factors. This may prevent the opportunity to have more impact in terms of future decisions if more sources are used in the market. In addition, time and the access to experts during this modeling process demonstrate a limitation, as does the time for feedback.Practical implicationsThis set of factors developed for adaptive governance decision-making can be applied to develop a prior alignment of stakeholder interests with sustainable practices.Social implicationsThis set of factors developed with the intervention of experts reinforces the importance of sustainable collective decisions on ocean ecosystem services. This is a joint approach with participants in the NextOcean project, sponsored by the European Commissions (EC)’s Horizon 2020 program. An Earth Observation-based Consortia aims to create sustainable value for Space, Land and Oceans.Originality/valueThis modeling process generated dimensions and factors to support adaptive governance stakeholders in making sustainable decisions in a coastal biodiversity zone.

Unveiling the TRAPP: The role of plant TRAPPII in adaptive growth decisions.

The regulation of intracellular membrane traffic is coupled with the cell's need to respond to environmental stimuli, which ultimately is critical for different processes such as cell growth and development. In this issue, Wiese et al. (https://www.doi.org/10.1083/jcb.202311125) explore the role of the trans-Golgi network (TGN) in stress response, exposing its role in mediating adaptive growth decisions.

Preliminary Efficacy of a Web-Based Alcohol and Emotion Regulation Intervention on Sexual Risk Behaviors Among College Women.

Using substances before sex may affect sexual decision-making among young women and increase their risk for a variety of negative consequences, including sexual victimization, sexually transmitted infections, and unintended pregnancies. A brief, web-based intervention combining alcohol reduction strategies with emotion regulation skills demonstrated initial efficacy at reducing heavy drinking and improving emotion regulation abilities among college women with sexual victimization histories. The present study represents a secondary analysis of this intervention to evaluate its preliminary efficacy in reducing sexual risk behaviors, specifically alcohol and other drug use before sex. The sample comprised 200 heavy-drinking college women with histories of sexual victimization randomized to an assessment-only control or the intervention consisting of 14 brief online alcohol reduction and emotion regulation skill-building modules administered daily over a 2-week period. The analytic sample included 173 women who reported their substance use before sex at baseline and at least one of two (1-month and/or 6-month) follow-up surveys. Repeated-measures mixed models revealed significant time-by-intervention interaction effects on alcohol use. Women who received the intervention had a significant decrease in alcohol use before sex from baseline to 1-month follow-up. Although levels of alcohol use before sex continued to be lower at the 6-month follow-up relative to baseline, differences did not reach statistical significance. Time-by-intervention interaction effects on drug use before sex were not statistically significant. Skills to reduce alcohol use and improve emotion regulation skills may be beneficial in helping women make adaptive decisions surrounding their sexual well-being.

Real-time Gait Event Tracker (RGET): An Innovative Approach to Digital Human Modeling through Integration of Inertial Measurement Unit and Dynamic Feature Extraction

The advancement of digital human modeling technology underscores the importance of accurately representing human characteristics and behaviors using motion capture technologies. This paper introduces the Real-time Gait Event Tracker (RGET), an advanced method aimed at precisely detecting gait events via an Inertial Measurement Unit (IMU), thereby supporting high-precision digital human modeling. RGET integrates planning techniques into continuous states and action spaces, utilizing first-order difference functions and sliding window techniques to effectively identify four key gait events: Heel Strike (HS), Toe Off (TO), Walking Start (WS), and Walking Pause (WP). The system efficiently manages IMU gait signal data through real-time queuing techniques and extracts dynamic features within time frames using positive/negative windowed first-order difference integrations. By adopting weighted sleep time methods and adaptive threshold decision rules, RGET accurately extracts gait event features from sequences. Not only does RGET support precise gait segmentation with an F1 score of 95.9%, but it also provides an innovative method for digital human modeling and its applications.

Adapting to climate change: what really drives the choices of the producers of Geographical Indications?

In an era of rapid climate change, there is an increasing call for the efforts directed at detecting best practices of climate change adaptation in agriculture and understanding the factors behind producers’ willingness to implement adaptation strategies. Many studies consider solely traditional agriculture and specific sectors (e.g., wine), while little attention has been paid to certified and high-quality products, as a whole. To fill this knowledge gap, in 2022 a questionnaire-based online survey was administered to 137 producers of agri-food Geographical Indications in the Veneto Region (north-eastern Italy). Using a multinomial logit model, this study highlights the factors explaining adaptation strategies distinguishing three cases: (i) farmers who have implemented adaptation strategies; (ii) farmers intending to implement them in the future; (iii) farmers neither having implemented nor willing to do so. Results suggest that socio-demographic characteristics, particularly education, matter, with producers holding a high school degree in agriculture showing a greater willingness to adapt. Also, being full-time farmer couples with higher probability of having already implemented adaptation strategies. Lastly, also a direct observation of climate change in the production area affects farmers’ adaptation decisions.