Unexpected Factors Research Articles

Psychometric Properties of the Chinese Version of the Gilliam Autism Rating Scale-Third Edition (CV-GARS-3).

Gilliam Autism Rating Scale-Third Edition (GARS-3) serves as an effective screening tool for autism spectrum disorder (ASD) that is based on the latest and authoritative diagnostic criteria, however, there is a deficiency in adaptive research in China. We aimed to revise the Chinese version of GARS-3 (CV-GARS-3) and evaluate its psychometric characteristics, providing a theoretical basis for the improvement of ASD screening tools in China. This study developed CV-GARS-3 through translation and cultural adaptation of GARS-3. 362 ASD individuals, 126 typical development individuals, and 103 individuals with other disorders were recruited to analyze the psychometric characteristics of CV-GARS-3. The results showed that exploratory structural equation model demonstrated satisfactory goodness-of-fit. Within the non-verbal ASD samples, all items loaded on anticipated factors. Regarding verbal ASD samples, 3 items exhibited considerable cross-loadings and were categorized under unexpected factors. Meanwhile, acceptable criterion validity was reflected in the four subscales (r = 0.71) and the six subscales (r = 0.74). Satisfactory reliability was observed in the four subscales (Cronbach's α = 0.96, inter-rater consistency = 0.86, test-retest consistency = 0.87) and the six subscales (Cronbach's α = 0.94, inter-rater consistency = 0.81, test-retest consistency = 0.81). In addition, receiver operating characteristic analysis demonstrated that both the four subscales (sensitivity = 89%, specificity = 85%, accuracy = 88%) and the six subscales (sensitivity = 86%, specificity = 88%, accuracy = 86%) had outstanding screening effects. Therefore, the results suggested that the CV-GARS-3 is considered as a useful tool for the screening and auxiliary diagnosis of ASD. Notably, the expression of scale should be further improved to adapt the context of Chinese culture and achieve more precise diagnostic results.

Abbreviated in-situ inter-professional debriefing simulation training in peri-operative care environments: Minimizing the impact on clinical care using standardized videos

IntroductionOur facility leadership posed questions to the perioperative leadership team regarding the presence of collaborative communication during the reconciliation of events occurring in several perioperative care areas (operating rooms {OR}, clinic procedure areas, Intensive Care Unit {ICU}). Our team* collaborated to pilot a rapid cycle performance improvement project focused on improving the effectiveness of debriefings and handoffs that could conceivably lead to more effective after-action reviews following events which were complicated by multiple simultaneous unexpected factors. We proposed we could implement standardized abbreviated low-fidelity point of care (in-situ) inter-professional simulation training across the healthcare system with minimal impact on clinical schedules. We believed this would improve the perception of teamwork and collaboration among surgical team members. MethodsInter-professional in-situ simulation training exercises were designed and performed in perioperative care areas systemwide at our three major facilities (Main hospital and two Healthcare Community Centers [HCC]). Multiple iterations of styles of training were conceived and trialed. In the end, preconstructed videos were used to standardize the processes that framed the simulation role-playing of a debriefing after a complex situation. These videos contain the pre-simulation pre-briefings, the clinical situation that preceded the clinical debriefing and the simulation debriefing. Successful reconciliation of the multiple events required team members to exercise closed-loop communication, mutual trust, reengagement, and de-escalation of disengaged team members. Anonymous institutional review board reviewed, and Association of Federal Government Employees (AFGE) approved retrospective pre/post implementation surveys were made available to participants immediately after and sixty to ninety days following simulation exercises. ResultsBetween July 2023 and March 2024, one hundred and six staff in the perioperative care areas participated in twenty-two inter-professional simulation trainings (eleven OR, eight clinic, and three ICU simulations). Fourteen simulation scenarios in seven surgical disciplines were created. Eleven videos were produced covering cases in the O.R., clinic and ICU. Ultimately, the simulations were completed within twenty minutes in the three perioperative care clinical areas. Seventy-nine staff responded to the initial surveys after the simulation training. Eighty percent of the respondents gave favorable assessments regarding the effectiveness of the training in improving components of teamwork and agreed this program should continue. ConclusionsThe pilot program affirmed that we could implement simulations across the healthcare system in a format that minimally impacted the staffs’ clinical schedule. The process was standardized through the creation of multiple specialty specific videos. We proposed that perioperative team leadership could utilize these videos in the future to conduct spontaneously arranged simulations when they identified the presence of members naïve to this training and opportunities in the clinical schedule.*Refer to the acknowledgments for construct of our perioperative leadership simulation advisory team

Navigating the uncertainty: the impact of a student-centered final year project allocation mechanism on student performance

The Final Year Project (FYP) is one of the most important courses for every undergraduate student, and the effective operation of the FYPs in higher education still faces challenges, such as uneven resource distribution and limited efficiency. This study reports a mixed-methods approach to study the impact of a student-centered FYP allocation mechanism on student performance. This research aims to investigate how aligning students’ FYP choices with their interests can inspire motivation and enhance academic performance. More importantly, this mechanism improves students’ academic resilience, enabling them to navigate unexpected contextual factors. The study’s findings take into account various aspects, including student satisfaction with the allocation process, future improvement methods, and the relationship between interest and context. The outcomes observed in this study support our hypotheses, indicating the improvements in students’ academic performance as well as the pass and completion rates. Moreover, this research contributes to ‘resilience theory’ by exploring students’ adaptability to contextual changes and their enhancement of academic resilience. This study proposes recommendations for cultivating a dynamic student-centered classroom environment. Future work could pay attention to addressing the limitations of this study, exploring other factors influencing FYP allocation, and integrating more quantitative measures for a comprehensive assessment of its impact.

Real‐Time Noise Source Estimation of a Camera System from an Image and Metadata

Autonomous machines must self‐maintain proper functionality to ensure the safety of humans and themselves. This pertains particularly to its cameras as predominant sensors to perceive the environment and support actions. A fundamental camera problem addressed in this study is noise. Solutions often focus on denoising images a posteriori, that is, fighting symptoms rather than root causes. However, tackling root causes requires identifying the noise sources, considering the limitations of mobile platforms. In this work, a real‐time, memory‐efficient, and reliable noise source estimator that combines data‐based and physically based models is investigated. To this end, a deep neural network that examines an image with camera metadata for major camera noise sources is built and trained. In addition, it quantifies unexpected factors that impact image noise or metadata. This study investigates seven different estimators on six datasets that include synthetic noise, real‐world noise from two camera systems, and real‐field campaigns. For these, only the model with most metadata is capable to accurately and robustly quantify all individual noise contributions. This method outperforms total image noise estimators and can be plug‐and‐play deployed. It also serves as a basis to include more advanced noise sources, or as part of an automatic countermeasure feedback loop to approach fully reliable machines.

Feasibility of a Capacity Building Organizational Intervention for Worker Safety and Well-being in the Transportation Industry: Pivoting to Address the COVID-19 Pandemic and Social and Political Unrest in Chile.

This study developed, implemented, and evaluated the feasibility of executing an organizational capacity building intervention to improve bus driver safety and well-being in a Chilean transportation company. Method: Through an implementation science lens and using a pre-experimental mixed methods study design, we assessed the feasibility of implementing a participatory organizational intervention designed to build organizational capacity. Result: We identified contextual factors that influenced the intervention mechanisms and intervention implementation and describe how the company adapted the approach for unexpected external factors during the COVID-19 pandemic and social and political unrest experienced in Chile. Conclusions: The intervention enabled the organization to create an agile organizational infrastructure that provided the organization's leadership with new ways to be nimbler and more responsive to workers' safety and well-being needs and was robust in responding to strong external forces that were undermining worker safety and well-being.

Telework as a dynamic capability of firms: A qualitative research and narratives

Unexpected and negative factors such as pandemics, crises, etc. have a profound effect on business environment and entail a paradigm shift in the classical concept of work schedule. The paper aims to explore the phenomenon of telework as a dynamic capability of firms to ensure business continuity in the face of all kinds of unpredictable events and delves into the factors behind telework applications that contribute to increasing the resilience of SMEs to chaotic business shifts. Dynamic capabilities theory constitutes the methodological basis of the study. For the purpose of the research, the qualitative method was used, which has a detailed and exploratory approach with inductive questions and enables a holistic picture of the phenomenon under investigation to be revealed. The multi-site case study design was preferred, and the data collected were analysed using content analysis. In July–August 2022, 13 semi-structured interviews were conducted with the owners, top and mid-level managers of SMEs operating in the service sector in Turkey. MAXQDA 2020 programme was used to analyse the data obtained. As a result of the research, the structure of the telework theme consisting of three dimensions (technological infrastructure, culture, and work attributes) and ten sub-dimensions (working order, trust, implementation history, business strategy, etc.) was discovered. For telework to be carried out healthily, firms should establish working order, work to be done, time spent by employees in front of the computer, etc., be more flexible and receptive to changes in work practices, create an appropriate culture and establish manager-employee trust.

COVID Impacts Cause Critical Gaps in the Indian Ocean Observing System

Abstract Observing and understanding the state of the Indian Ocean and its influence on climate and maritime resources is of critical importance to the populous nations that rim its border. Acute gaps have occurred in the Indian Ocean Observing System, which underpins monitoring and forecasting of regional climate, since the start of the COVID pandemic. The pandemic disrupted the deployment and maintenance cruises for the observational array and also resulted in supply chain issues for procurement and refurbishment of equipment. In particular, the observational platforms that provide key measurements of upper ocean heat variability have experienced serious multiyear declines. There is now record-low data reporting and the platforms that are successfully reporting are old and quickly surpassing their expected period of reliable operation. The overall impact on the observing system will take a few years to fully comprehend. In the meantime, there is a critical need to document the gaps that have appeared over the past few years and how this will impact our ability to improve understanding and model representations of the real world that support regional weather and climate forecasts. The article outlines the expected slow road to recovery for the Indian Ocean Observing System, documents case studies of successful international collaborative efforts that will revive the observing system and provides guidelines for resilience from unexpected external factors in the future.

Covid 19’s Social Quarantine-Moderated Self-Reported Mental Health and Substance Use Among US Adults

In 2019 the novel coronavirus spread quickly throughout the world. It was easily transmitted, resulting in a sudden increase in infection and death rates that overwhelmed hospitals. This sudden pandemic resulted in government and health officials mandating physical and social quarantines to decrease the spread of COVID-19. All these unexpected factors induced traumatic stress across the world. The impact of this trauma is seen to date, as many studies reported adverse mental health effects in an array of populations and researchers speculate these effects will continue long after COVID-19. The role of social quarantine as a moderating factor to these adverse mental health symptoms was assessed in a Qualtrics sample of 596 US adults. Participants completed a demographic survey, Adverse Childhood Experiences (ACEs) Questionnaire, COVID-19 Pandemic Mental Health Questionnaire, Patient Health Questionnaire-9, Generalized Anxiety Disorder Scale-7, International Trauma Questionnaire, Brief Resiliency Scale, and the Tobacco, Alcohol, Prescription Medication and Other Substances Tool. Hierarchical regressions with demographic and risk factors as predictors assessed the role of social quarantine as a moderator in predicting mental health symptoms. ACEs and risk factors were stronger predictors of mental health symptoms, but social quarantine added significant incremental variance in self-reported anxiety, depression, PTSD, complex PTSD, and substance use; β<em> </em>ranged for 0.24 to 0.30. Quarantine had a significant adverse impact on mental health symptoms among these adults. Fostering resilience and distress tolerance is a proposed clinical intervention.

Religion's influence on consumption: A life course paradigm perspective

AbstractThis article applies the life course paradigm to research on religion's influence on consumer behavior to provide an alternative perspective to theories explaining how religion influences consumption and marketing practice. While the life course paradigm has been shown to be highly influential in general consumer behavior research, this concept has been seemingly forgotten in the context of religion and consumer behavior, which is concerning given the role that religion can play in consumers' lives through various life transitions. Specifically, six major transitioning times in consumers' lives (leaving home, marriage, kids, retirement, spouse/parent death, and unexpected factors) are discussed with application to religion and consumer behavior research as well as future research directions. Discussion concludes with a call to action for more research on religion's influence on consumer behavior that is theoretically grounded utilizing the life course paradigm in an effort to more accurately understand the influence of religion on consumer behavior.

Analisis Pengendalian Kualitas pada Proses Produksi dengan Metode Six Sigma (Studi Kasus PT. Busana Indah Global)

To maintain consistent quality of production results and as an effort to identify unexpected factors that cause the production process to not function smoothly, quality control is very important. The research questions answered are how much production output and level of defects in products at PT. Busana Indah Global for the 2022 period?; what is the Six Sigma level in the products produced at PT. Busana Indah Global?; What factors cause defects in products?; What are the suggestions for improving the causes of product defects to improve product quality? The data analysis method used in this research is the Six Sigma method. This method is used to anticipate the occurrence of errors or defects by using measurable and structured steps. From the results of quality control research using the Six Sigma method, it is hoped that companies will carry out quality control continuously and consistently to reduce the level of defect values in production and to increase the Six Sigma value.

Unexpected Factors That Influence Viral Detection and Viral Load Using Real-Time PCR

This communication takes note of unexpected factors that can influence the results of RT-PCR in quantitation of copy numbers such as in determination of viral loads and in viral identification. We show that the presence of serum separator gel in authorized collection tubes for hepatitis C (HCV) viral load determinations causes underestimation of viral loads by blocking viral diffusion into plasma and that the presence of more than one targeted virus in a multiplex RT-PCR viral assay, while not affecting analytical specificity, results in raising of the minimal detectable viral titer and therefore a decreased analytical sensitivity. Our results suggest the possibility that HCV samples should be placed in cell lysis buffer for full viral load determination and that multiplex assays should be carefully validated and modified if necessary to minimize loss of sensitivity.

Analysis Of Factors Inhibiting Employees From Reading Kwh Post-Paid Meters In The Field (PT. IDO SINERGI)

PT. PLN (PERSERO) as a State-Owned Enterprise to provide the best service for all electricity users in Indonesia, PLN which takes care of all aspects of electricity for the public interest throughout Indonesia. At first PLN used postpaid electricity kwh recording calculating tool, where the kWh meter recording used analog system. Several problems and complaints from the public regarding the use postpaid electricity in the form of late payments, meter recording errors and erratic bills, PLN specifically for the Sorong branch in collaboration with PT. Ido Sinergi as a service provider, especially in the work of recording kwh meters, must be able to provide satisfaction to PLN as its partner. When recording kwh meters, factors that often hinder activities in the field such as fence locks, closed houses, empty houses, tall meters, opaque meters, fierce animals, unloading meters, lost meters other unexpected factors. The purpose this study to find out the various factors inhibiting kWh meter readings in the field, the data obtained was then processed using data analysis tool used to answer the research problem using the Pareto Diagram. The conclusion from this study is that the inhibiting factors for reading kwh meters in the field are fence locks, closed houses, empty houses, tall meters, opaque meters, fierce animals, unloading meters, missing meters with a total of 598 constraints from 20,580 customers, along with the percentage pk 31%, rt 13%, rk 15%, mt 7%, mbrm 15%, hg 3%, mb 10%, mh 7%.

Clinical profiles in multiple myeloma patients with extreme survivals: a study from a National Medical Center in China

ABSTRACT Objectives The clinical outcomes of multiple myeloma (MM) patients are highly variable in the real-world setting. Some MM patients may have clinical endings that do not abide by the book. We aim to describe features of MM patients with extreme survivals in real-world practice. Methods This retrospective study enrolled 941 patients consecutively visited a national medical center, China, between July 1995 and December 2021. Among patients, we identified two groups of MM patients with extreme survivals, 56 were in the long-term remission (LR) group with progression-free survival (PFS) ≥ 60 months, and 82 were in the rapid progression (RP) group with PFS ≤ 6 months. Results CRAB features, of which hypercalcemia, renal insufficiency, and anemia were more common in the RP group, except for bone disease, with a comparable incidence at diagnosis in both groups (88.8 vs 85.7%, P = 0.52). High-risk cytogenetics was detected in 45.7% of patients in the RP group. Of note, 14.3% of MM patients in the LR group harbored del (17p). According to the Revised International Staging System (R-ISS), 9% of patients belonged to stage I in the RP group, and 19% of patients in the LR group were found in stage III. There were 8 (15.7%) patients in the LR group only achieved partial response (PR) as the best response. Median time to best response (TBR) for LR and RP group patients was 4.6 and 1.4 months, respectively. Conclusions The disparities in the survivals of MM patients indicated that some unexpected factors have influenced the outcomes in the real-world setting.

Assessing Workplace Factors That Influence Burnout and Identifying Recommendations to Support Well-being in Pharmacy Faculty

ObjectiveCreating environments that promote well-being is critical as studies have shown that burnout, and thus poor well-being, results in poor health outcomes and declining workplace retention. While studies have measured the prevalence of burnout in pharmacy faculty, a gap exists regarding workplace factors that impact faculty well-being. The purpose of this study was to assess factors influencing pharmacy faculty burnout and identify recommendations to improve faculty well-being. MethodsFull-time pharmacy faculty were invited to participate in this exploratory study. Focus groups were divided by faculty rank (ie, assistant, associate, full professor). A semistructured interview format was used to identify factors contributing to faculty burnout and fulfillment as well as solicit suggestions for strategies to improve well-being. Inductive coding was used to identify themes. ResultsEleven faculty participated in 4 focus groups: 6 assistant professors in 2 focus groups (n = 3 faculty/focus group), 3 associate professors in 1 focus group, and 2 full professors in 1 focus group. Common factors influencing faculty burnout included overwhelming workload, workplace inefficiencies, and unexpected factors. Factors contributing to faculty fulfillment included impact, having a passion for work, and connecting with others. Recommendations for improving well-being included school-level well-being initiatives from leadership, encouraging work-life balance, and implementing intentional well-being initiatives and resources. ConclusionParticipants identified several workplace factors that contribute to burnout and faculty fulfillment. This study fills a critical gap in the literature regarding factors that influence pharmacy faculty well-being and burnout and can inform strategies for fostering faculty well-being in pharmacy education.

빅데이터 분석을 활용한 중소기업, 소상공인 ESG 경영 이슈 분석

In the context of experiencing unexpected external factors like COVID-19, businesses are facing a significant demand for change. The management focus on ESG has emerged as a practical issue concerning the survival and sustainability of companies.
 Existing research has primarily concentrated on empirical analysis based on ESG evaluation systems, with relatively little attention given to analyzing key ESG-related keywords. This study aims to fill the gap in such research.
 To achieve this, the study utilized big data from news channels operating on major portal sites such as Naver, Daum, and Google. Through the application of big data analysis tools, the study performed the extraction and analysis of ESG-related keywords targeting small and medium-sized enterprises (SMEs) and small businesses.
 The ESG keywords extracted through the use of big data analysis tools contribute to the ongoing discussions about integrated approaches to ESG evaluation criteria. Additionally, they provide foundational data necessary for developing differentiated ESG strategies based on the size of the companies. As a result, this study holds significance in deriving both academic and practical insights.

Explainable Prognostics Method through Differential Evolved RVR Ensemble of Relevance Vector Machines

Operating experience from various mechanical components indicates that their operating performance depends on non-well known physical mechanisms, while it is likely that various unexpected factors will act as catalysts for reaching the failure point. Therefore, one way to overcome the partially knowledge of physical mechanisms is the use of data-driven methods that estimate the degradation patterns and predict the failure point. Thus, there is a growing need to design and develop new and more sophisticated prognostic technologies that can estimate the remaining useful life of a mechanical component. In this work, a new method for prognostics is proposed that not only provides a prediction over the failure point but also provides an explanation over the rationale behind that prediction. The proposed method utilized tools from artificial intelligence and more specifically relevance vector machines (RVM) and differential evolution (DE). The cornerstone of the method is the assembly of an ensemble comprised of multiple RVM equipped with different kernels, and the subsequent evolution of the ensemble using the differential evolution. DE will provide a set of values for the coefficients of the ensemble. Then based on the coefficients together with their associated RVMs are used to provide an explanation over the prediction. The explanation stems from the kernels themselves as each kernel models different set of properties. The presented method is tested on a set of real-world degradation data taken from a Gas Turbine (GT) propulsion plant.

CCR4-NOT differentially controls host versus virus poly(a)-tail length and regulates HCMV infection.

Unlike most RNA and DNA viruses that broadly stimulate mRNA decay and interfere with host gene expression, human cytomegalovirus (HCMV) extensively remodels the host translatome without producing an mRNA decay enzyme. By performing a targeted loss-of-function screen in primary human fibroblasts, we here identify the host CCR4-NOT deadenylase complex members CNOT1 and CNOT3 as unexpected pro-viral host factors that selectively regulate HCMV reproduction. We find that the scaffold subunit CNOT1 is specifically required for late viral gene expression and genome-wide host responses in CCR4-NOT-disrupted cells. By profiling poly(A)-tail lengths of individual HCMV and host mRNAs using nanopore direct RNA sequencing, we reveal poly(A)-tails of viral messages to be markedly longer than those of cellular mRNAs and significantly less sensitive to CCR4-NOT disruption. Our data establish that mRNA deadenylation by host CCR4-NOT is critical for productive HCMV replication and define a new mechanism whereby herpesvirus infection subverts cellular mRNA metabolism to remodel the gene expression landscape of the infected cell. Moreover, we expose an unanticipated host factor with potential to become a therapeutic anti-HCMV target.

The Association Between Performance Information and the Satisfaction of Different Social Groups: Citizen Evaluation by Racial Groups

ABSTRACT Citizen satisfaction is an important instrument to assess the quality of public services and hold governments accountable to their citizens. Despite significant amount of research, few studies have examined whether citizen satisfaction is generalizable across social groups or whether different social groups interpret it differently. Based upon the ingroup preference theory, this study uses data from Chicago Public Schools to argue that citizen satisfaction varies across different social groups, such that different performance information influences each groups’ level of satisfaction differently. The findings suggest that different types of performance information (overall v. group performance) have different effects on citizens of different racial groups when they evaluate public services. Further, it is important to measure performance for each social group, and as each group’s performance increases, divergence in citizen satisfaction among racial groups may decrease, helping public managers reduce unexpected factors that harm citizens’ perception of their agencies.

Aeromonas SPP In Sardinian Snail Farms

Snails, also known as Gastropod molluscs of the order Stilommatophoridae, belonging to the family Helicidae, are farmed in Sardinian agriculture. Nonetheless, this practice is currently causing numerous problems and critical issues. Setting up snail farming facilities demands high organisational standards to optimise production, as well as continuous in-depth technical training for dedicated personnel. The aim of this paper was to acquire knowledge on the epidemiology and ecology of Aeromonas spp. in snail farms and to assess the pathogenicity of the different strains, isolated through molecular characterisation of virulence genes. In order to do this, snails belonging to the genus and species Helix aspersa (N.22) and irrigation water (N.22) from various farms in Sardinia were sampled and microbiological culture investigations for Aeromonas spp. were carried out. The microorganisms isolated were subjected to culture and molecular investigations for the characterisation of virulence genes. From this study, it was possible to highlight the presence of 15 positive samples for Aeromonas spp. In addition, it was discovered that the origin of the contamination was often associated with unexpected factors, which were not under the control of those responsible for the plant. As a result, this study revealed the need for further preventive actions in two key aspects; improve the production in the surveillance of the farms; increase the assessment of associated risks caused by virulent strains that may compromise product quality and consumer safety.

Modeling of Digital Twin Workshop in Planning via a Graph Neural Network: The Case of an Ocean Engineering Manufacturing Intelligent Workshop

In the era of Industry 4.0 to 5.0, the manufacturing industry is dedicated to improving its production efficiency, control capability and competitiveness with intelligent enhancement. As a typical discrete manufacturing industry, it is difficult for ocean engineering (OE) manufacturers to accurately control the entire production process, and the establishment of an integrated system supported by digital twin (DT) technology is a better solution. This paper proposes a comprehensive set of system architectures for the DT workshop. It focuses on planning, which is the main line of control, to establish a model based on graph neural networks (GNNs) and suggests five decision-support approaches associated with the model from a practical application perspective. The utilization of complete twin data for prediction and visual simulation effectively eliminates the problem of unexpected factors interfering with scheduling in enterprise production planning and achieves the goals of rapid processing and just-in-time completion. The planning model is based on the attention mechanism, which characterizes the disjunctive graph, extracts the input GNN, and outputs the scheduling decision by constructing the multi-attention network of operations and machines to deal with the complicated “operation–machine” combination relationship. The proposed method has been verified in the case of structural assembly and welding workshops, has validity and reliability, and is superior to the traditional priority scheduling rules and heuristics in terms of precision rate and rapidity. Furthermore, the DT system completes the production line application, and its proven reliability supports its full-scale application in future smart factories.