Premature Decisions Research Articles

Imposing order on a creative chaos

Abstract It is uncontested that terminologists leading multi-professional terminology projects need a thorough knowledge of the principles and standards of terminology work. However, the softer skills involved in the work have gained less attention. In this paper, we apply interaction analysis to a multi-professional expert meeting led by a terminologist and highlight the communicative and interpersonal work he carries out. Our results show how the terminologist allows for a certain “creative chaos” and makes the team “feel good”, while still keeping epistemic quality under permanent scrutiny and never losing focus on the task at hand. He does this through flexible agenda management — sticking to his meeting agenda, but not rigidly, and allowing for and taking note of useful contributions, even if they come in the wrong phase. He also upholds a sufficient degree of conceptual rigour, by holding back premature decisions but not unnecessarily correcting the other’s erroneous use of meta-terminology.

Graph Out Loud: Pre-Service Teachers' Data Decisions and Interpretations of CBM Progress Graphs.

Data-based instruction (DBI) is a process in which teachers use progress data to make ongoing instructional decisions for students with learning disabilities. Curriculum-based measurement (CBM) is a common form of progress monitoring, and CBM data are placed on a graph to guide decision-making. Despite the central role that graph interpretation plays in the successful implementation of DBI, relatively little attention has been devoted to investigating this skill among special education teachers. In the present study, we examined the data decisions of 32 pre-service special education teachers (29 females and 3 males). Participants viewed data presented sequentially on CBM progress graphs and used a think-aloud procedure to explain their reasoning each time they indicated they would make instructional changes. We also asked participants to make the same type of decisions in response to static CBM progress graphs depicting 10 weeks of data. Overall, there was inconsistency in pre-service teachers' responses related to when or why they would make an instructional change. Decisions were often influenced by graph-related features, such as variability in the data. Furthermore, responses suggested misunderstandings that led to premature instructional change decisions and reliance on individual data points.

Pre-crastination: Extra Physical Effort for Mind-Clearing in Reaching, Walking, and Other Activities

Background: In this opinion we consider the roles of physical and cognitive effort in choosing between actions that make different physical and cognitive demands.
 View of the past: In choosing between a less or more demanding physical task, the cognitive effort of each was not expected to have a large effect.
 Current state: However, people are willing to expend extra physical effort to clear their minds (to avoid cognitive effort), a phenomenon called pre-crastination.
 Future perspective: Because pre-crastination can lead to premature decisions, a new priority is to understand the tradeoffs between physical and mental effort.

Technical debt in the engineering of complex systems

AbstractThe metaphor of technical debt (TD) is widely adopted in the software engineering field, referring to short‐term compromises in software artifacts in exchange for speed or to meet release schedules or other constraints. The implication is that TDs accumulate over time, and may eventually make rework or maintenance very expensive or even impossible. The analogy is generally applicable in the systems engineering field, particularly concerning numerous program cancellation and obsolescence challenges due to premature decisions made in early acquisition phases. This paper adapts this metaphor of TD to the systems engineering field, and proposes a TD taxonomy to support the early identification and assessment of TD items in engineering complex systems, especially in the early life cycle phases of engineering complex, distributed systems. The taxonomy identifies seven TD types: functionality, performance, interoperability, version conflicts, documentation and support, system evolution, and organic, based on systematic indicators and signs discoverable during early acquisition activities. We expect that the notion and the taxonomy of TD will offer an additional perspective for design decisions that will help mitigate challenging integration and obsolescence issues in the engineering of complex systems.

Optimal admission and queuing control with reneging behavior under premature discharge decisions

AbstractQueues or waiting lines are a common phenomenon in healthcare facilities. The increasing number of admissions to hospital emergency departments (EDs) has resulted in overcrowded EDs and decreased quality of care. Patients may renege with dissatisfaction while waiting, prolonged hospital stays, or the cancelation of surgeries, especially for those with acute diseases. This paper studies patient admission and queuing control policies, considering premature discharge decisions and reneging behavior. First, we formulate this problem as an infinite‐horizon total discounted cost Markov decision process to balance bed utility and experiences of patients waiting for admission to minimize the total expected cost for the hospital. Then, we characterize an optimal admission threshold policy by analyzing the structural properties of the optimal value function. Numerical experiments are employed to discuss how the optimal dynamic policy depends on some key parameters of the system. Finally, the performance of the optimal policy is discussed through comparison with the benchmark: A myopic rule (first come, first served) mimicking the decision‐making in practice under different scenarios. The numerical results show that the reneging behavior can affect the superiority of the optimal policy compared to the benchmark, and the optimal policy can significantly reduce the number of waiting patients without increasing the total expected cost when the system is overloaded.

Analysis of some common reading strategies used by teachers in teaching reading comprehension skills to students with reading disabilities in secondary schools in Nigeria

Introduction: The study analyzed some common reading strategies used by teachers in teaching reading comprehension skills to students with reading disabilities in secondary schools in Nigeria Purpose: To identify and explain some common reading strategies used in teaching reading comprehension skills to students with reading disabilities. Methodology: Interpretive research paradigm was employed for the study. All the four special education teachers in GSS Township made up the population and sample of the study. Purposive sampling technique was employed for the study. Observation and oral interviews were used as instruments for data collection. Richness, depth, honesty, credibility, transferability, and dependability of information given were used to validate the instruments. Premature decisions, personal interest and opinions that could cause biases in the results were avoided. Reliability was established using teachers' responses and students' actual performances. Data was analyzed qualitatively. Results: Teachers understood the reading problems faced by the students. They identified and explained some common reading strategies used in teaching reading comprehension skills to students with reading disabilities. The students were able to use their prior knowledge to read and answer questions from the text correctly. Conclusion: Knowledge of students' problems is a mean to solving the problem. Teachers identified and explained some common reading strategies used in teaching students with reading disabilities. Recommendations: To qualify for teaching, all teachers, apart from their area of specialization must have at least a certificate or Diploma in Learning Disabilities, specifically in reading disabilities where various activities, methods and strategies for teaching reading to students are taught.

Reasoning about Confidence in Goal Satisfaction

Goal models are commonly used requirements engineering artefacts that capture stakeholder requirements and their inter-relationships in a way that supports reasoning about their satisfaction, trade-off analysis, and decision making. However, when there is uncertainty in the data used as evidence to evaluate goal models, it is crucial to understand the confidence or trust level in such evaluations, as uncertainty may increase the risk of making premature or incorrect decisions. Different approaches have been proposed to tackle goal model uncertainty issues and risks. However, none of them considers simple quality measures of collected data as a starting point. In this paper, we propose a Data Quality Tagging and Propagation Mechanism to compute the confidence level of a goal’s satisfaction level based on the quality of input data sources. The paper uses the Goal-oriented Requirement Language (GRL), part of the User Requirements Notation (URN) standard, in examples, with an implementation of the proposed mechanism and a case study conducted in order to demonstrate and assess the approach. The availability of computed confidence levels as an additional piece of information enables decision makers to (i) modulate the satisfaction information returned by goal models and (ii) make better-informed decisions, including looking for higher-quality data when needed.

A Corticothalamic Circuit Trades off Speed for Safety during Decision-Making under Motivational Conflict

Decisions to act while pursuing goals in the presence of danger must be made quickly but safely. Premature decisions risk injury or death, whereas postponing decisions risk goal loss. Here we show how mice resolve these competing demands. Using microstructural behavioral analyses, we identified the spatiotemporal dynamics of approach–avoidance decisions under motivational conflict in male mice. Then we used cognitive modeling to show that these dynamics reflect the speeded decision-making mechanisms used by humans and nonhuman primates, with mice trading off decision speed for safety of choice when danger loomed. Using calcium imaging in paraventricular thalamus and optogenetic inhibition of the prelimbic cortex to paraventricular thalamus pathway, we show that this speed-safety trade off occurs because increases in paraventricular thalamus activity increase decision caution, thereby increasing approach–avoid decision times in the presence of danger. Our findings demonstrate that a discrete brain circuit involving the paraventricular thalamus and its prefrontal input adjusts decision caution during motivational conflict, trading off decision speed for decision safety when danger is close. We identify the corticothalamic pathway as central to cognitive control during decision-making under conflict.SIGNIFICANCE STATEMENT Foraging animals balance the need to seek food and energy against the conflicting needs to avoid injury and predation. This competition is fundamental to survival but rarely has a stable, correct solution. Here we show that approach–avoid decisions under motivational conflict involve strategic adjustments in decision caution controlled via a top-down corticothalamic pathway from the prelimbic cortex to the paraventricular thalamus. We identify a novel corticothalamic mechanism for cognitive control that is applicable across a range of motivated behaviors and mark paraventricular thalamus and its prefrontal cortical input as targets to remediate the deficits in decision caution characteristic of unsafe and impulsive choices.

Optimal admission control under premature discharge decisions for operational effectiveness

AbstractThe shortage of inpatient beds causes surgery cancellations, treatment delays, and inappropriate ward arrangements. That is why studying how to make admission decisions on the wards of crowded units under premature discharge decisions is essential. In this study, we set up an infinite‐horizon total discounted cost Markov decision process model to minimize the total expected cost to the hospital. By analyzing the structural properties of the optimal value function, we find that there is an optimal admission control policy of the threshold type for low‐acuity emergency patients (type‐2). Numerical experiments are done to examine how optimal dynamic policy depends on key system parameters. Furthermore, we evaluate the performance of the optimal dynamic policy with a benchmark policy without premature discharge decisions. The results indicate that the optimal admission control policy helps hospitals in maintaining low costs and enables patients with high‐acuity diseases to enter primary wards more quickly.

A value of information methodology for multiobjective decisions in quantitative set‐based design

AbstractEngineering complex systems is an exercise in sequential multiobjective decision making under uncertainty. One method for handling this complexity and uncertainty is set‐based design (SBD). SBD is a concurrent engineering and management methodology that develops, analyzes, and matures numerous design options, reducing risk and delivering higher value to the stakeholders and end users. SBD accomplishes this through controlled design space convergence which reduces uncertainty and prevents premature design decisions. While SBD has been the subject of numerous scholarly articles, there is limited research providing quantitative methodologies that inform decisions enabling design maturation and convergence. We present a value of information (VOI) based methodology for multiobjective decision problems, and demonstrate its applicability for SBD decisions. We apply Bayesian decision models and information value to inform multiobjective modeling and design maturation decisions. Research contributions include: 1) a framework integrating VOI into the SBD process, 2) a multiobjective VOI method assessing a higher‐resolution model's ability to reduce uncertainty, and 3) a means of informing modeling decisions by comparing multiple high resolutions models, given their usage cost and their potential to deliver information value. Finally, we demonstrate the inherent issues associated with premature decisions and traditional point‐based design approaches which run the risk of selecting an alternative that later proves infeasible.

How Costly is Follow-on Financing After Premature Going-public Decisions?

Entrepreneurs often regard Initial Public Offerings (IPOs) as the crowning pinnacle at the end of a highly successful entrepreneurial journey, and studies in entrepreneurial finance therefore rarely extend beyond the going-public decision. This research gap is important because many post-IPO entrepreneurs need to revert to their pre-IPO entrepreneurial investors for follow-on financing in private transactions as they fail to raise additional equity in public markets. While the investment relationship is usually mutually beneficial pre-IPO, the rent sharing in post-IPO transactions is less obvious. Evidence from Private Investments in Public Equity (PIPEs) over the 2001-2018 period in recent-IPO firms suggests highly asymmetric rent sharing. Entrepreneurs earn a negative return of up to -15% in the first post-PIPE year, while investors benefit due to the ability to dictate transaction terms. We find some evidence that corporate governance and asymmetric information considerations matter in the cross section of the returns. The results have real implications for entrepreneurs who often remain CEO of the public company and have a large portion of their personal wealth tied to their company stock.

A Collaborative Decision Support System Framework for Vertical Farming Business Developments

The emerging industry of vertical farming (VF) faces three key challenges: standardisation, environmental sustainability, and profitability. High failure rates are costly and can stem from premature business decisions about location choice, pricing strategy, system design, and other critical issues. Improving knowledge transfer and developing adaptable economic analysis for VF is necessary for profitable business models to satisfy investors and policy makers. A review of current horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. Data from the literature alongside lessons learned from industry practitioners are centralised in the proposed DSS, using imprecise data techniques to accommodate for partial information. The DSS evaluates business sustainability using financial risk assessment. This is necessary for complex/new sectors such as VF with scarce data.

‘It became an anchor for stuff I really want to keep’: the stabilising weight of self-storage when moving home and away

ABSTRACT The process and stresses of moving home are a common experience in our lives, and few find sorting and packing household possessions easy. When moves are temporary, uncertain or contingent on other factors it can be particularly difficult to know what to take with us, so renting a self-storage unit allows for movement and mobility without the need to reduce the material convoy or make premature decisions on what to keep or dispose of. Contrary to previous research, which has focused on the purchase or divestment of objects during life course transitions, house moves and experiences of mobility, this paper argues that the practice of storing objects is equally as important. The data for this paper is drawn from object-elicited interviews undertaken in the UK with three women who were motivated to rent self-storage to store their household possessions when moving to a new home temporarily or more permanently, across the country and abroad, in the pursuit of different opportunities (education, work, lifestyle change). Self-storage is seen to both accommodate materiality caught up in feelings of uncertainty and indecision, and anchor possessions which collectively stand-in for a sense of home when itself is not yet remade.

Stochastic optimization of economic, financial, information, and logistics inter-cluster cooperation

Subject. This article deals with the simulation technologies based on the principles of stochastic optimization. They can bring a significant financial effect in the planning of investment development of both individual innovation and industrial clusters and federal districts of the country. Objectives. The article aims to investigate the mechanisms of inter-cluster cooperation within a single district. Methods. For the analysis, we used a stochastic optimization model in view of economic, financial, information, and logistics inter-cluster cooperation within a single federal district. Results. The considered stochastic optimization model of economic, financial, information, and logistics inter-cluster cooperation shows that the increase in fixed investment does not always cause population growth in the federal district regions. Conclusions. The use of a digital twin mechanism of inter-cluster cooperation can help avoid premature unreasonable public policy management decisions regarding the further development of innovation and industrial clusters.

Epidemic trends, public health response and health system capacity: the Chilean experience in four months of the COVID-19 pandemic.

ABSTRACTObjectives.To report the surveillance of COVID-19 pandemic in Chile and analyse the response to public health interventions implemented from 3 March to 30 June 2020 and to assess the risks of collapse of the health care system.Methods.We analysed the effective reproductive number, underreporting of cases, burden of critical beds, case fatality ratio and number of diagnostic RT-PCR for SARS-CoV-2.Results.After an accelerated onset, the COVID-19 pandemic seemed to be relatively controlled in Chile (late April 2020), with reproductive numbers close to 1.00. However, at this time, the load of infected patients was high, with an important number of underreported cases; the diagnostic effort was still limited and heterogeneous across regions. After 1 May up to 30 June a marked exponential increase in the number of cases was observed with a peak on June 14. In this last period the occupation of intensive care unit beds increased to saturation level (89% nationally; 95% in the Metropolitan Region).Conclusions.Our findings suggest that the implemented public health interventions have been initially effective in decreasing the spread of the pandemic. Premature decisions to relax these interventions may have resulted in a rebound in cases with a rapid saturation of the health care system.

Developing the digital twin of the economic, financial, information and logistics inter-cluster cooperation mechanism

Subject. This article deals with the issues related to the use of digital twins in order to manage innovation and industrial clusters and the liaison between them. Objectives. The article aims to develop a digital twin model of inter-cluster cooperation within a Federal district of Russia. The Volga (Privolzhsky) Federal District is considered a case study. Methods. For the study, we used a multiple non-linear regression method and a fast simulated annealing (FSA). Results. The article offers and describes a designed digital twin model of inter-cluster cooperation mechanism. Conclusions and Relevance. When reallocating investment and human resources within one federal district, the interests of the population of innovation and industrial clusters should be taken into account, as only just an increase in fixed investment does not always lead to the growth of the region's population. The use of the digital twin model of inter-cluster cooperation mechanism will help avoid premature unreasonable management decisions of the public-policy level regarding the further development of innovation-industrial clusters.

A Novel Link between the Oxytocin Receptor Gene and Impulsivity

Impulsivity includes hasty actions, social intrusiveness or premature decision-making. Neuropeptides like oxytocin alleviate haste and anxiety, and affect fear conditioning. However, no investigations have been done via gene-network based approach with cognitive and interventional genetic association studies to scrutinize the link between impulsive behavior and oxytocin. Here, interactive gene network and pathways associated with impulsivity were reconstructed, and serotonin transporter gene (SLC6A4) and serotoninergic synaptic transmission were identified as the most central gene and pathway related to impulsivity. Young healthy males received intranasal oxytocin or placebo, and impulsivity was evaluated via go/no-go test. Test performance scores then were analyzed based on commission and omission errors, response inhibition and reaction time. Blood DNA was extracted and a 761 bp intronic region in oxytocin receptor (OXTR) gene was amplified and sequenced using PCR-pyrosequencing. Employing Haploview, haplotypes and linkage disequilibrium (LD) pattern among all SNPs in the target sequence were determined based on D′ and LOD values, and rs2254298 with the highest LD was indicated as the tag SNP. Oxytocin group and participants with GG genotype showed a significantly decreased commission error and increased inhibition. This means that oxytocin alleviated impulsive behavior, and subjects with GG genotype had lower rate of impulsivity than those with GA and AA genotypes. rs2254298 may modulate the function or expression of the OXTR gene, implying that G allele may increase the expression of OXTR gene compared to A allele. We suggest that intranasal oxytocin may notably moderate impulsive behavior and tendency to make hasty or premature decisions.

Evaluation of Self-Healing Systems: An Analysis of the State-of-the-Art and Required Improvements

Evaluating the performance of self-adaptive systems is challenging due to their interactions with often highly dynamic environments. In the specific case of self-healing systems, the performance evaluations of self-healing approaches and their parameter tuning rely on the considered characteristics of failure occurrences and the resulting interactions with the self-healing actions. In this paper, we first study the state-of-the-art for evaluating the performances of self-healing systems by means of a systematic literature review. We provide a classification of different input types for such systems and analyse the limitations of each input type. A main finding is that the employed inputs are often not sophisticated regarding the considered characteristics for failure occurrences. To further study the impact of the identified limitations, we present experiments demonstrating that wrong assumptions regarding the characteristics of the failure occurrences can result in large performance prediction errors, disadvantageous design-time decisions concerning the selection of alternative self-healing approaches, and disadvantageous deployment-time decisions concerning parameter tuning. Furthermore, the experiments indicate that employing multiple alternative input characteristics can help with reducing the risk of premature disadvantageous design-time decisions.

ДИНАМІКА ЕМОЦІЙНОГО ЗАБАРВЛЕННЯ ТЕКСТІВ ПУБЛІКАЦІЙ ВЕНЧУРНИХ ІНВЕСТОРІВ У СОЦІАЛЬНІЙ МЕРЕЖІ TWITTER

Venture industry itself is risky, full of surprises and requires attention. Information is a new air, but it can be used in different ways, and sometimes might be harmful for the market. COVID-19 is a perfect example that happened only half a year ago: internet and media were overdosed with materials predicting the future of all VC industry and startups market. Eventually, all this data could influence a company with premature decisions and intensify the crisis. That’s why it is crucially important to define and understand the media landscape. For this purpose, one of the methods of automatized linguistics is being used – sentiment-analysis. During the study, we confirmed the hypothesis of changes in the dynamics of emotional coloring of investors’ publications under the influence of difficult-to-predict events in the long run. The main trends in terms of geography, investment industries, investment stage and average investment were described. In addition, a parallel with 2008 was found, which is another signal of the approaching new economic crisis. The results of the study are of high public importance, as they revealed the problem of the lack of resilience of the industry to emotional shocks and viral spread among participants in the ecosystem. Depending on the studied data sections, investors and founders of startups are able to properly adjust their long-term development strategies.

TrollBOT: A Spontaneous Networking Tool Facilitating Rapid Prototyping of Wirelessly Communicating Products

In early stages of product development, prototyping is an invaluable tool which allows designers to generate learnings and uncover unknown challenges which can be used to further construct design requirements. While generous use of prototyping early in the design process might reduce the risk of premature design decisions, it also demands significant investments in terms of resources such as time, material, and skills. Tools that allow designers to rapidly implement and test new functionalities are therefore desired. With wirelessly communicating products having become ubiquitous in modern society, designers should be comfortable designing products utilizing these technologies. In this paper we present an Arduino library, named TrollBOT, that facilitates rapid implementation of wireless communication between two or more Arduinos. The Arduinos form nodes in a tree topology using inexpensive nRF24-based radio transceivers. The library is constructed in such a way that a minimal amount of new language syntax must be learned. All nodes can be programmed from a single master node in an intuitive manner, significantly reducing the amount of code that needs to be written as compared to similar existing solutions.