Adaptive Feedback Loop Research Articles

Optimizing Serverless Function Orchestration for Complex Workflows in Cloud Platforms

Purpose: This paper aims to investigate ways of increasing the efficiency of various workloads of serverless function orchestration in cloud systems while decreasing latency and optimizing resources. Materials and Methods: The report suggests adaptive learning systems and a feedback loop framework for managing the orchestrating serverless environment. Findings: It has also been affirmed that case studies help validate the framework rather than presenting the practical implications of the proposed techniques. Implications to Theory, Practice and Policy: The paper recommends focusing on managing performance, dependencies, and expenses in serverless function orchestration by employing adaptive learning systems and feedback loop frameworks.

Understanding non-participation in local governance institutions in Indonesia

Community-centered approaches are crucial and impactful strategies for the global climate and biodiversity crisis. However, these approaches hinge upon participation for both pragmatic and ethical reasons. While there is a growing body of research in this field, most studies focus on those who opt in to these community-based approaches. Research focuses on how interventions do or do not achieve the intended cross-sectoral outcomes that are flagship among these strategies. Few studies seek to understand the objective and subjective constraints of non-participants. We investigated why community members chose not to participate in a community-centered conservation approach in West Kalimantan, Indonesia. We used snowball saturation sampling and semi-structured interviews across nine villages, surveying both non-participants and key informants. Our results show that non-material factors such as time, lack of understanding, and feeling uninvited drove non-participation. Non-participants did not identify a lack of interest in program activities or services as a primary reason for opting out. Key informants suggested that participation could be improved with better outreach around objectives, potential benefits, and data feedback loops that quickly communicated results to community members. These results have implications for conservation strategies around the globe as findings suggest investing in non-material factors (e.g., improved messaging and considerations of time burdens) are significant constraints to participation. Payment for ecosystem services and carbon finance schemes often invest considerable time and money in incentivizing participation with material benefits, and our results suggest a more significant consideration should be placed on time requirements, messaging/outreach, adaptive feedback loops, and democratizing data ownership.

Design Principles for Data-Driven Decision Evaluation

Human-machine collaboration has potentially led to higher quality and more informed data-driven decisions. However, evaluating these decisions is necessary to measure the benefits, as well as enable experiential learning and posterior rationalization of the results and consequences. Nevertheless, the multiplicity of human-machine collaboration modes, as well as the multi-faceted nature of data-driven decisions complicates evaluation, and evaluation solutions are lacking both in research and in practice. This is further reflected in the complexity of incorporating evaluation in the design of such data-driven decision making systems, since developers are left without theoretically grounded and practically feasible principles to guide implementation. In this paper, we propose a set of five design principles, explicated from theory and practice, for systems implementing data-driven decision evaluation as the output of design science research cycles. The design principles are: 1) multi-faceted evaluation criteria, 2) unified viewpoint, 3) collaborative rationality, 4) processual ex-post evaluation, and 5) adaptive feedback and learning loops. They are further contextualized in the case of AI-enabled menu design at Antell, an innovative pioneer in the restaurant business in Finland, and consequently evaluated by the development managers of the project. Accordingly, the design principles contribute to the knowledge base on metahuman systems and data-driven decision evaluation, by concretizing existing normative concepts into prescriptive knowledge, also guiding future research and generalizing towards a design theory. Furthermore, they provide implementable statements for designing and developing such systems in practice and can be used as a checklist to compare and evaluate existing systems.

Looking forward or backward: A temporal lens to disentangle adaptive and maladaptive reactions to daily goal-performance discrepancy.

The fast-changing work environment has created growing hindrances to employee daily goal pursuits and rendered it not uncommon for employees to leave work with unachieved daily work goals. The significant ramifications of unachieved goals on employee well-being and performance thus call for more research efforts to understand how employees respond to unsatisfactory goal progress (e.g., goal-performance discrepancy [GPD]). Interestingly, two paradoxical theoretical perspectives exist on this matter, with the self-regulation perspective suggesting an adaptive feedback loop (i.e., GPD on a given day eventually reduces next-day GPD), whereas the self-focused cognition perspective suggesting a maladaptive feedback loop (i.e., GPD on a given day eventually exacerbates next-day GPD). Taking a temporal lens to integrate these two perspectives, we conducted a daily diary study to map out the self-regulatory cognition mechanisms (i.e., anticipatory thinking) and self-focused cognition mechanisms (i.e., rumination) underlying the feedback loops, and identify employee temporal focus (future and past focuses) as critical cross-level boundary conditions to explain why some react to daily GPD adaptively, whereas others maladaptively. Based on 485 daily reports from 100 work professionals, we revealed that daily GPD at work resulted in reduced next-day GPD via increased after-work anticipatory thinking. Meanwhile, daily GPD also resulted in aggravated next-day GPD via increased after-work rumination. Moreover, employee future focus mitigated the maladaptive cycle, whereas employee past focus hindered the adaptive cycle. Our study thus provides important theoretical and empirical insights into employee goal-pursuit process. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

New Developments in Treating RAS-Mutated Metastatic Colorectal Cancer.

One of the great challenges in digestive oncology is choosing the optimal therapy for RAS-mutated metastatic colorectal cancer (mCRC). Even though the RAS genes and accompanying pathway were identified decades ago and extensive knowledge exists on their role in carcinogenesis, it has proven challenging to translate these insights into new therapies and clinical benefit for patients. However, recently, new drugs targeting this pathway (for example, KRASG12C inhibitors) have shown promising results in clinical trials, as monotherapy or in combination regimens. Although resistance remains an important issue, more knowledge on adaptive resistance and feedback loops in the RAS-pathway has led to strategical combination regimens to overcome this problem. In the past year, many encouraging results have been published or presented at conferences. Even though some of the data is still preliminary, these studies may bring practice-changing results and can lead to a clinical benefit for patients over the coming years. Because of these recent developments, the treatment of RAS-mutated mCRC has become a topic of great interest. Therefore, in this review, we will summarize the standard of care and discuss the most important emerging therapies for this patient population.

The Convergence of Quality and Digitalisation in a Changing World: Implications for Developing Nations such as the BRICS Group

The emergence of digitalisation and the Fourth Industrial Revolution has resulted in a significant shift in practices, resulting in a disconnection among organisations, employees, and technology, particularly affecting developing nations like the BRICS group which have faced disproportionate challenges due to the COVID-19 pandemic. The aim of this paper is to explore the role of quality in the context of intelligent and automated systems operating in a technologically advanced environment. The study employs a systematic literature review methodology, which encompassed a rigorous process of identifying and selecting 38 articles, followed by a comprehensive thematic analysis. The findings highlight that organisations need to adapt their quality systems to effectively operate in a world dominated by intelligent and automated systems. The implication is that by leveraging digital technologies, organisations can embrace the integration of quality with machine learning, programmable logic controllers, adaptive feedback loops, automated information collection, and blockchain technology to develop a value-based, transparent, and secure quality system. The proposed roadmap and model derived from this study affords organisations the opportunity to establish an intelligent quality ecosystem that aptly aligns with the requisites of the technologically advanced era, thereby ensuring the attainment of excellence in quality during the digital era.

Adaptive and Dynamic Feedback Loops between Production System and Production Network based on the Asset Administration Shell

In production networks, production must run efficiently across company boundaries. Companies must be able to react quickly as a single unit. Two trends are influencing this situation: On the one hand, the progressing servitization leads to the increased offering of digital services in the field of manufacturing. From the literature, it is known that digital services let manufacturers, suppliers, and industrial customers interact more closely and frequently in a production network. On the other hand, the concept of the digital twin is trending. It promises the real-time prognosis and control of production systems. Although the concept of the digital twin itself can be vague there are some technologies trying to implement the digital twin of production. The asset administration shell (AAS) is an example of such a technology that draws growing attention. Picking up the initial situation these two trends could be used to create a feedback loop between the production system and network and thus improve the overall efficiency in production networks. Based on this idea, the paper first presents an approach to model systematically a possibility for a feedback loop orienting to the business model concept. Second, a reference architecture is derived from the RAMI 4.0 standard. The specified reference architecture is the basis for the specific implementation. Third, a procedure is developed to implement a specific architecture. For implementing an architecture, the usage of the asset administration shell is assumed. Finally, the approach is validated in a use case from the high precision weight industry.

A revision of the gobiid fish genus Pseudogobius/ (Teleostei, Gobiidae, Tridentigerinae), with description of seven new species from Australia and South-east Asia.

The tridentigerine genus Pseudogobius is widespread, from temperate to tropical areas of the Indo-west Pacific. A morphological review of the genus was carried out, with the initial focus on South-east Asian and Australian species. There are about 21 nominal species in the genus; however, the type specimens for some nominal species are missing. Our work recognises 15 valid species so far, including seven new species, which are described herein: P. aquilonius n. sp., P. cinctus n. sp., P. eos n. sp., P. hoesei n. sp., P. jeffi n. sp., P. rhizophora n. sp. and P. verticalis n. sp. We also conclude that P. poicilosoma (Bleeker, 1849) is the senior synonym of P. javanicus (Bleeker, 1856). Pseudogobius poicilosoma, P. gastrospilos (Bleeker, 1853) and P. javanicus are accepted here as conspecific, although the types are in poor condition (note that all three names were given to specimens collected within close proximity to each other in coastal Java, Indonesia). A key to valid species is presented. The revision benefited from an adaptive feedback loop with companion genetic analyses, with the most comprehensive data available for the Australian region. Broader preliminary genetic data suggest the potential for recognition of additional cryptic species, with the current study providing a platform for future systematic work. Pseudogobius are a prominent part of estuarine biodiversity in the Indo-west Pacific, and this study helps to highlight the need to better understand the taxonomy and conservation requirements of cryptobenthic fishes.

Avenues of reef-building coral acclimatization in response to rapid environmental change.

The swiftly changing climate presents a challenge to organismal fitness by creating a mismatch between the current environment and phenotypes adapted to historic conditions. Acclimatory mechanisms may be especially crucial for sessile benthic marine taxa, such as reef-building corals, where climate change factors including ocean acidification and increasing temperature elicit strong negative physiological responses such as bleaching, disease and mortality. Here, within the context of multiple stressors threatening marine organisms, I describe the wealth of metaorganism response mechanisms to rapid ocean change and the ontogenetic shifts in organism interactions with the environment that can generate plasticity. I then highlight the need to consider the interactions of rapid and evolutionary responses in an adaptive (epi)genetic continuum. Building on the definitions of these mechanisms and continuum, I also present how the interplay of the microbiome, epigenetics and parental effects creates additional avenues for rapid acclimatization. To consider under what conditions epigenetic inheritance has a more substantial role, I propose investigation into the offset of timing of gametogenesis leading to different environmental integration times between eggs and sperm and the consequences of this for gamete epigenetic compatibility. Collectively, non-genetic, yet heritable phenotypic plasticity will have significant ecological and evolutionary implications for sessile marine organism persistence under rapid climate change. As such, reef-building corals present ideal and time-sensitive models for further development of our understanding of adaptive feedback loops in a multi-player (epi)genetic continuum.

P.654 Stress hormones as predictors of response to cognitive-behavior therapy in panic disorder

Runtime uncertainty such as unpredictable resource unavailability, changing environmental conditions and user needs, as well as system intrusions or faults represents one of the main current challenges of self-adaptive systems. Moreover, today's systems are increasingly more complex, distributed, decentralized, etc. and therefore have to reason about and cope with more and more unpredictable events. Approaches to deal with such changing requirements in complex today's systems are still missing. This work presents SACRE (Smart Adaptation through Contextual REquirements), our approach leveraging an adaptation feedback loop to detect self-adaptive systems’ contextual requirements affected by uncertainty and to integrate machine learning techniques to determine the best operationalization of context based on sensed data at runtime. SACRE is a step forward of our former approach ACon which focus had been on adapting the context in contextual requirements, as well as their basic implementation. SACRE primarily focuses on architectural decisions, addressing self-adaptive systems’ engineering challenges. Furthering the work on ACon, in this paper, we perform an evaluation of the entire approach in different uncertainty scenarios in real-time in the extremely demanding domain of smart vehicles. The real-time evaluation is conducted in a simulated environment in which the smart vehicle is implemented through software components. The evaluation results provide empirical evidence about the applicability of SACRE in real and complex software system domains.

Adaptive Full-Order Observer Analysis and Design for Sensorless Interior Permanent Magnet Synchronous Motors Drives

This article proposes a straightforward design guideline and analysis of adaptive full-order observers for rotor position and speed estimation of interior permanent magnet synchronous motors (IPMSM) sensorless drives. The adaptive observer is built upon the IPMSM extended electromotive force model in the stationary reference frame. The design of the adaptation and feedback gains is performed by a cascade approach, where state observer and adaptive law operate at distinct frequencies. Since speed estimation error impacts the system stability, this issue is the focus of the high-bandwidth state observer design. On the other hand, the adaptive feedback loop, which operates at lower frequencies, ensures good rotor speed estimation performance. The effect of synchronous inductances and stator resistance variation on the estimation of the mechanical variables is investigated and analytically described. Experimental results validate the adaptive observer design method and the parameter variation analysis under sensorless vector control.

An Autonomous Fault-Awareness model adapted for upgrade performance in clusters of homogeneous wireless sensor networks

Wireless sensor networks (WSNs) have conquered comprehensive survey progressions in the regular control and management fields. Although WSN allows the spatial monitoring of real-world events, the mobility action depletes a huge part of a sensor’s energy cost in wireless communication. WSN sensors are often prone to various faults as frequent crashes and temporary or permanent failures. This is because it propagates them in very complex and harsh environments. So, we tend to design a Self-Adaptive based Autonomous Fault-Awareness (SAAFA) model, to limit the impact of such failures and filter them. In this paper, we incorporate the two of adaptive-filters FIR with RLS through three adaptive two-stages performed at the level of cluster head, for independent fault-correction during the propagation platform. The proposed model (SAAFA) included two stages, the first stage comprised self-detection the failure and self-aware for the lost scales, in which relied on responses of delay port and prior-knowledge of absent sensor-signals throughout monitoring, through adjusting the filter weights in the adaptive feedback loop for awarding convergent signals for the lost ones. The second stage is adaptive filtering the registered signals from the above stage for gaining pure measures and free of interferences. Compared to the state-of-the-art methods, the scheduled model attained a speed in diagnosing faults and awareness the missing readings with a rate of accuracy reached 98.8% improving the robustness of performance. Evaluation criteria revealed the progress of SAAFA in reducing the radio communication to ~ 97.47% that kept about 93.7% of battery-energy throughout the picked dataset sample. Hence, it expanded the whole network lifetime.

Adaptive Test Feedback Loop: A Modeling Approach for Checking Side Effects during Test Execution in Advised Explorative Testing

<div class="section abstract"><div class="htmlview paragraph">The main objective of testing is to evaluate the functionality, reliability, and operational safety of products. However, this objective makes testing a complex and expensive stage in the development process. From the perspective of an aircraft OEM, test cases are used to verify integration, system, and application levels. Therefore, test cases certify the products against the requirements using the black box testing approach. In doing so, a test plan defines a sequence of test cases whereby it sets up the environment, stimulates the fault, and then observes the system under test (SUT) for each case. Subsequently, the postprocessing of the test execution classifies the test plan as passed or failed. The ongoing digitization and interconnectedness between aircraft systems increase the complexity in functional testing. This trend leads to a high number of test cases and a multitude of reasons why a specific test-case fails. A corresponding error analysis and adaptation of the test plan is a complex and lengthy process that starts repeatedly after executing a manually updated test plan. The goal of the developed approach is to reduce the amount and the duration of the time-consuming trial and error approach. Therefore, the paper proposes the advised “free testing” as an extension of existing functional test processes. The proposal enables the adaptive test feedback loop. It covers the adaption of a current test execution as soon as faulty behavior is detected recursively. The adaption is based on proposals, which are calculated on basis of a knowledge base and selected by a test engineer. For this purpose, the paper proposes a new tool landscape. It describes the required functionality for a test bed. Finally, the paper evaluates the benefits of an adaptive test feedback loop based on an avionics test scenario.</div></div>

HAFLoop: An architecture for supporting Highly Adaptive Feedback Loops in self-adaptive systems

Most of the current self-adaptive systems (SASs) rely on static feedback loops such as the IBM’s MAPE-K loop for managing their adaptation process. Static loops do not allow SASs to react to runtime events such as changing adaptation requirements or MAPE-K elements’ faults. In order to address this issue, some solutions have emerged for manually or automatically perform changes on SASs’ feedback loops. However, from the software engineering perspective, most of the proposals cannot be reused or extended by other SASs. In this paper, we present HAFLoop (Highly Adaptive Feedback control Loop), a generic architectural proposal that aims at easing and fastening the design and implementation of adaptive feedback loops in modern SASs. Our solution enables both structural and parameter adaptation of the loop elements. Moreover, it provides a highly modular design that allows SASs’ owners to support a variety of feedback loop settings from centralized to fully decentralized. In this work, HAFLoop has been implemented as a framework for Java-based systems and evaluated in two emerging software application domains: self-driving vehicles and IoT networks. Results demonstrate that our proposal easies and accelerates the development of adaptive feedback loops as well as how it could help to address some of the most relevant challenges of self-driving vehicles and IoT applications. Concretely, HAFLoop has demonstrated to improve SASs’ feedback loops’ runtime availability and operation.

A 56-Gb/s Long-Reach Fully Adaptive Wireline PAM-4 Transceiver in 7-nm FinFET

This letter presents a 56-Gb/s PAM-4 transceiver which achieves a bit error rate of $2\times 10^{-9}$ through −33 dB of channel insertion loss while consuming 500-mW receiver and 90-mW transmitter power. Its compact 0.31-mm2 area is achieved by rigorously applying a digital design style to exploit the high logic density offered by the 7-nm technology node. This is realized by an all-digital PLL, source-series-terminated transmitter, and synthesized DSP section for the majority of the receiver signal processing. Receiver analog signal conditioning is limited to 8-dB of peaking provided by a low-distortion analog frontend that feeds a 28-GS/s 8-bit ADC implemented as an 8-way time-interleaved SAR-ADC array. Digital receiver signal equalization, as well as timing recovery, relies on adaptive filtering which eliminates the need for training sequences, a concept extended to ADC calibration. Here, signal distortion caused by sampling clock skew and SAR-ADC array mismatch is removed by fully adaptive feedback loops.

Adaptive Responses as Mechanisms of Resistance to BRAF Inhibitors in Melanoma.

The introduction of v-raf murine sarcoma viral oncogene homolog B (BRAF) inhibitors in melanoma patients with BRAF (V600E) mutations has demonstrated significant clinical benefits. However, rarely do tumours regress completely. Frequently, the reason for this is that therapies targeting specific oncogenic mutations induce a number of intrinsic compensatory mechanisms, also known as adaptive responses or feedback loops, that enhance the pro-survival and pro-proliferative capacity of a proportion of the original tumour population, thereby resulting in tumour progression. In this review we will summarize the known adaptive responses that limit BRAF mutant therapy and discuss potential novel combinatorial therapies to overcome resistance.

A CMOS MedRadio Transceiver With Supply-Modulated Power Saving Technique for an Implantable Brain–Machine Interface System

A MedRadio 413–419-MHz inductorless transceiver (TRX) for an implantable brain–machine interface (BMI) in a 180 nm-CMOS process is presented. Occupying 5.29 mm2 of die area (including pad ring), this on–off keying (OOK) TRX employs a non-coherent direct-detection receiver (RX), which exhibits a measured in-band noise figure (NF) of 4.9 dB and $S_{11}$ of −13.5 dB. An event-driven supply modulation (EDSM) technique is introduced to dramatically lower the RX power consumption. Incorporating an adaptive feedback loop, this RX consumes 42-/92- $\mu \text{W}$ power from 1.8-V supply at 1/10-kbps data rates, achieving −79/−74-dBm sensitivities for 0.1% bit error rate (BER). The TX employs a current starved ring oscillator with an automatic frequency calibration loop, covering 9% supply voltage variation and 15 °C–78 °C temperature range that guarantees operation within the emission mask. The direct-modulation TX achieves 14% efficiency for a random OOK data sequence at −4-dBm output power. Wireless testing over a 350-cm distance accounting for bio-signal data transfer, multi-user coexistence, and in vitro phantom measurement results is demonstrated.

Enzalutamide in Combination with Abiraterone Acetate in Bone Metastatic Castration-resistant Prostate Cancer Patients

BackgroundIt is hypothesised that cotargeting the androgen receptor (AR) and paracrine androgen biosynthesis with enzalutamide and abiraterone acetate in metastatic castration-resistant prostate cancer (mCRPC) will dissipate adaptive feedback loops observed with either agent alone. ObjectiveTo assess the safety, efficacy, androgen signalling/metabolome, and drug-drug interactions (DDIs) of enzalutamide with abiraterone acetate in progressive bone mCRPC (bmCRPC). Design, setting, and participantsThis open-label, single-centre interventional study was conducted in bmCRPC patients. InterventionEnzalutamide 160mg and abiraterone acetate 1000mg once daily; prednisone 5mg twice daily. Outcome measurements and statistical analysisAdverse events (AEs), prostate-specific antigen (PSA) response, progression-free survival (PFS), tumour biomarker/metabolite expression, and Cmin plasma concentrations were evaluated. Results and limitationsSixty patients were enrolled. Common AEs independent of grade/causality included fatigue (72%), hyperglycaemia (67%), alkaline phosphatase (ALP) elevation (53%), and hot flush (43%). Grade 3 AEs included hypertension (17%), alanine aminotransferase elevation (12%), ALP elevation (5%), and arthralgia (5%). No treatment-related grade 4 AEs or deaths were reported. Median treatment-discontinuation time was 312d (95% confidence interval [CI] 196.0–483.0). Maximal PSA decline ≥50% and ≥90% occurred in 46 (77%) and 29 (48%) patients, respectively. Median PFS was 251d (95% CI 147–337). At week 9, median tumour microenvironment androgens, precursors, and nuclear AR expression decreased (p<0.001). The baseline tumour AR C/N terminal ratio of ≥80% was associated with treatment benefit. At enzalutamide steady state, abiraterone acetate Cmin was ∼23% lower (range 14.05–200.5ng/ml) than when given alone. ConclusionsEnzalutamide combined with abiraterone acetate has a manageable safety profile, without a meaningful DDI. Both agents are pharmacodynamically active with no feedback. Efficacy findings do not support significant benefit of combined treatment for unselected bmCRPC. Patient summaryThis is the first study combining enzalutamide plus abiraterone in bone metastatic castration-resistant prostate cancer. Results show that this combination is safe.

SACRE: Supporting contextual requirements’ adaptation in modern self-adaptive systems in the presence of uncertainty at runtime

Runtime uncertainty such as unpredictable resource unavailability, changing environmental conditions and user needs, as well as system intrusions or faults represents one of the main current challenges of self-adaptive systems. Moreover, today's systems are increasingly more complex, distributed, decentralized, etc. and therefore have to reason about and cope with more and more unpredictable events. Approaches to deal with such changing requirements in complex today's systems are still missing. This work presents SACRE (Smart Adaptation through Contextual REquirements), our approach leveraging an adaptation feedback loop to detect self-adaptive systems’ contextual requirements affected by uncertainty and to integrate machine learning techniques to determine the best operationalization of context based on sensed data at runtime. SACRE is a step forward of our former approach ACon which focus had been on adapting the context in contextual requirements, as well as their basic implementation. SACRE primarily focuses on architectural decisions, addressing self-adaptive systems’ engineering challenges. Furthering the work on ACon, in this paper, we perform an evaluation of the entire approach in different uncertainty scenarios in real-time in the extremely demanding domain of smart vehicles. The real-time evaluation is conducted in a simulated environment in which the smart vehicle is implemented through software components. The evaluation results provide empirical evidence about the applicability of SACRE in real and complex software system domains.

Evaluating an On-Ranch Rangeland Monitoring Program in Nebraska

On the Ground Rangeland monitoring is an important component of rangeland management. The Nebraska Grazing Lands Coalition developed a rangeland monitoring program (RMP) in 2009 to assist livestock producers in monitoring rangelands on their ranches. Determining rangeland condition and fulfilling a requirement for conservation incentive programs were the most important reasons livestock producers participated in the RMP. Eighty-seven percent of survey participants indicated they had continued monitoring following the RMP and many indicated they had made management changes to their ranches. Monitoring is an important part of the adaptive management feedback loop. The RMP provided a resource to train producers in monitoring techniques. More tools to interpret monitoring data and increased follow-up by technicians may help producers better utilize their monitoring data.