Hidden Factors Research Articles

Prophet modeling for oil production forecasting in an enhanced oil recovery field

Accurate daily oil production forecasting is essential for efficient reservoir management and investment strategy. Forecasting oil production in enhanced oil recovery (EOR) and conformance-dominated fields is a complex process due to the nonlinear, voluminous, and often uncertain nature of reservoir parameters and hidden factors. As a result, conventional tools such as decline curve analysis frequently fail to accurately predict daily oil production in conformance-controlled areas. In contrast, machine learning works efficiently for large datasets, even if the parameter values are unknown. The current study employs a Prophet time series forecasting method for five oil production wells in an EOR applied field, but it fails to achieve the desired sweep efficiency. This study compares the results of conventional decline curve analysis (DCA) and popular autoregressive integrated moving average time series forecasting methods with the Prophet model. This is the first attempt to use Prophet for oil well production forecasting, where polymer flooding is used. In all, 60% of the data are used for training, and the remaining 40% are used for testing. The Prophet shows the best performance for all the wells. This study is also the first to handle shut-in data using the Prophet model for oil production. Well-2 achieves the highest accuracy after incorporating shut-in results, with an R2 score of 92%. The result shows that though the DCA performs reasonably well with higher linearity and trend stationary data, Prophet modeling shows superior results than conventional DCA for all EOR applied producing wells.

Incorporating risky driving behaviour in the injury severity analysis of at-fault and not-at-fault novice driver involved crashes: a correlated random parameters logit model with heterogeneity in means

In order to gain a more detailed understanding of novice driver involved crashes, this paper compares the injury severity of at-fault and not-at-fault novice driver involved crashes with the consideration of risky driving behaviours. The crash data of novice drivers in Shenyang, China, from 2012 to 2017 is used. The correlated random parameters logit model with heterogeneity in means is built for the whole dataset, at-fault dataset, and not-at-fault dataset to explore the significant factors determining the injury severity, and obtain insight into hidden and common factors. The hidden factors indicate factors that are only significant in one dataset, while the common factors indicate factors that are significant in two or more datasets. The results show that nine common factors significantly affect injury severity of novice driver involved crashes. Among them, speeding, legal but unsafe driving behaviours, and improper operation are related to risky driving behaviour. Moreover, road type, functional zone, time interval, and conflict and improper passing are hidden factors, among which conflict and improper passing is related to risky driving behaviour. Finally, some valuable insights for regulatory authorities in formulating targeted policies are provided to mitigate the severity of novice drivers involved crashes.

‘I am not omniscient’: an autoethnography inquiry into a novice L2 teacher’s implementation of digital multimodal composing

While much research has been conducted on the benefits of digital multimodal composing (DMC) projects from the perspective of second language (L2) students, little attention has been paid to L2 teachers, whose implementation of DMC projects in L2 writing contexts may be fraught with challenges. To address the niche, autoethnographic research was undertaken to uncover a novice L2 teacher’s experiences and struggles in DMC implementation, drawing on data from my memories and journals of lived experiences, Wechat messages with students, my PowerPoint (PPT) slides in instructing DMC projects, and student DMC samples. The results revealed that I, as a novice L2 teacher, faced challenges in implementing DMC in the Chinese English as a Foreign Language (EFL) writing context, and the challenges included students’ misinterpretation of the DMC task; some students’ dislike and unpreparedness for collaborative learning tasks; the conflicts between DMC projects and the final exam and the standardized test; and my fear of showing incompetence in video making and editing. To address the challenges, I explored research articles, communicated with the researchers and students, and reflected on the hidden factors that contribute to the problem. This study draws attention to the reform of the exam-, print-, and language-oriented education system in the Chinese EFL writing context, and the incorporation of DMC and multiliteracies/multimodality pedagogy into writing teacher training programs.

Single proxy control.

Negative control variables are sometimes used in nonexperimental studies to detect the presence of confounding by hidden factors. A negative control outcome (NCO) is an outcome that is influenced by unobserved confounders of the exposure effects on the outcome in view, but is not causally impacted by the exposure. Tchetgen Tchetgen (2013) introduced the Control Outcome Calibration Approach (COCA) as a formal NCO counterfactual method to detect and correct for residual confounding bias. For identification, COCA treats the NCO as an error-prone proxy of the treatment-free counterfactual outcome of interest, and involves regressing the NCO on the treatment-free counterfactual, together with a rank-preserving structural model, which assumes a constant individual-level causal effect. In this work, we establish nonparametric COCA identification for the average causal effect for the treated, without requiring rank-preservation, therefore accommodating unrestricted effect heterogeneity across units. This nonparametric identification result has important practical implications, as it provides single-proxy confounding control, in contrast to recently proposed proximal causal inference, which relies for identification on a pair of confounding proxies. For COCA estimation we propose 3 separate strategies: (i) an extended propensity score approach, (ii) an outcome bridge function approach, and (iii) a doubly-robust approach. Finally, we illustrate the proposed methods in an application evaluating the causal impact of a Zika virus outbreak on birth rate in Brazil.

Language development in children's natural environments: People, places, and things.

Our goal in this chapter is to describe young children's experiences with language by examining three domains-people, places, and things-that define and influence their language input. We highlight how features of each of these three domains could provide useful learning opportunities, as well as how differences in infants' and toddlers' experiences may affect their long-term language skills. However, we ultimately suggest that a full understanding of early environments must move beyond a focus on individual experiences and include the broader systems that shape young children's lives, including both tangible aspects of the environment, such as physical resources or locations, and more hidden factors, such as cultural considerations, community health, or economic constraints.

Team-bounded DEA efficiency scores: The case of UEFA Champions League Players

Measuring the efficiency of a football player is an interesting task. Every player invests time and energy to produce an outcome during the game that can lead to a better score for the team. However, football is a team sport, thus the synergy of the entire team is an invisible factor that influences the outcomes a player produces. In this paper, we introduce a novel efficiency estimation model based on the data envelopment analysis that incorporates the team effect in the efficiency score. To achieve this effect, we presented data envelopment analysis models using a single mathematical model. This allows us to define lower and upper bounds on the team efficiency score. More specifically, we introduce a novel type of assurance region constraint around the team performance such that the efficiency score cannot exceed ? times the average team efficiency score. The results of the proposed mathematical model on the UEFA Champions League 2021/22 season show that efficiency scores can be heavily affected by inefficient teammates. However, if the entire team performed well, the drop in efficiency scores is insignificant.

The Bullish Game: The Role of Virtual Currency in Incentivizing Homework on the Skyeng Platform

Even though online learning is an affordable way to gain new knowledge and skills, and millions of people use different platforms, there is a serious problem with students dropping out, as well as with their completion of assignments during training. One effective way to increase student engagement is to use gamification in teaching. In this study, we study the relationship between the introduction of such a gamification element as virtual currency with the results of learning English on the Skyeng platform. Using data from 2019 to 2020, we analyzed the relationship between the indicated intervention and the percentage of completion of homework, as well as the average homework score of platform users. 
 The results of the experiment conducted in the A/B format showed that the introduction of virtual currency had a significant effect on the educational results of students. Thus, students from the experimental group showed an increase in involvement in doing homework on the platform compared to the control group. Moreover, various types of rewards work in general to increase student engagement in homework, including those that are not directly related to learning. At the same time, students who did not use the game currency available to them showed similar or even lower results than participants in the experiment from the control group. It can be assumed that in this case there is an effect of student motivation as a hidden factor, which explains the greater interest in the functionality and capabilities of the platform itself, and in the educational process as a whole.

On hidden factors and design-associated errors that may lead to data misinterpretation: An example from preclinical research on the potential seasonality of neonatal seizures.

Unintentional misinterpretation of research in published biomedical reports that is not based on statistical flaws is often underrecognized, despite its possible impact on science, clinical practice, and public health. Important causes of such misinterpretation of scientific data, resulting in either false positive or false negative conclusions, include design-associated errors and hidden (or latent) variables that are not easily recognized during data analysis. Furthermore, cognitive biases, such as the inclination to seek patterns in data whether they exist or not, may lead to misinterpretation of data. Here, we give an example of these problems from hypothesis-driven research on the potential seasonality of neonatal seizures in a rat model of birth asphyxia. This commentary aims to raise awareness among the general scientific audience about the issues related to the presence of unintentional misinterpretation in published reports.

Practical Logic and Development Path of Urban Hawker Governance from the Perspective of Responsible Politics

The governance issue of urban hawkers, as one of the manifestations of the informal economy, has a long history. However, responsibility, as the core value of governance, becomes a hidden factor in the process of hawker governance. This article starts with the concepts of responsible politics and hawker governance and explores the bidirectional logical relationships between hawkers, hawkers and the government, store operators, social organizations and residents in the process of governance practice in China. It proposes starting from the perspective of hawkers themselves, clarifying the responsibilities of each entity, improving legislation and institutional construction, strengthening the ideological and moral development of all entities, rational spatial planning, and management, and adopting a consultative approach to collaboratively addressing the development path of hawker governance challenges.

Mixed Methods Evaluation of Satisfaction with Two Culturally Tailored Substance use Prevention Programs for American Indian/Alaska Native Emerging Adults

American Indian/Alaska Native (AI/AN) communities are disproportionately affected by the opioid epidemic. AI/AN emerging adults (ages 18–25) in urban areas are at particularly high risk, with the overdose death rate among urban-dwelling AI/AN people 1.4 times higher than rural-dwelling AI/AN people. Despite these challenges, there are no evidence-based culturally tailored prevention or intervention programs to address opioid, alcohol and other drug use among urban AI/AN emerging adults. This study focused on understanding AI/AN emerging adults’ experiences with two culturally tailored programs addressing opioid, cannabis, and alcohol use as part of the randomized controlled trial for Traditions and Connections for Urban Native Americans (TACUNA) in order to enhance feasibility of this intervention. Using a convergent mixed methods design at 3-month follow-up, we collected satisfaction and experience ratings and written narratives (total n = 162; intervention n = 77; control n = 85) from a sample of urban-dwelling AI/AN emerging adults who participated in both programs. We analyzed data through simultaneous examination of qualitative and quantitative data. The quantitative ratings show that both programs were rated highly. The qualitative data contextualized these ratings, illustrating pathways through which specific components were perceived to cause desired or observed behavioral change in participants. Among the elements that mattered most to these participants were the convenience of the virtual format, having a comfortable and safe space to share personal stories, and learning new information about their social networks. Negative comments focused on workshop length and inconvenient scheduling. This is one of the first studies to explore participant satisfaction and experience with culturally tailored substance use programming among a historically marginalized and understudied population. It is important to consider the voices of urban-dwelling AI/AN people in program development because hidden factors, such as limited financial resources, limited time, and misalignment with cultural values may prevent existing programs from being feasible.

Analysis of Stock Portfolio with Global Economic Factors using Dynamic Data Modelling

This article analyzes stock portfolios and worldwide economic challenges. This study uses APIs to retrieve data and analyze correlations. To determine and measure how economic indicators affect stock performance. This work introduces an autoencoder-based model to better comprehend the complex relationship between economic conditions and stock portfolio dynamics. The analysis begins with an API retrieval of a wide range of macroeconomic information. These indicators include global economic metrics like GDP, unemployment, CPI, federal funds rates, and treasury bill rates. After collection, data is carefully curated and prepared for analysis. This study uses correlation analysis to understand economic variables and stock portfolio performance. This study explores how economic conditions affect stock prices and portfolio returns. This study seeks to discover trends, dependencies, and future issues that may affect investment decisions. This study also introduces an autoencoder-based neural network model to capture complex nonlinear relationships between economic variables and stock portfolio behavior. Deep learning improves interpretability and prediction, allowing a better understanding of the complex financial ecosystem dynamics. The inquiry provides valuable insights for investors, financial experts, and regulators. This study advances data-driven investment and risk management solutions. The autoencoder-based approach also reveals latent structures and hidden factors that affect stock portfolios. This novel approach opens new study options. In conclusion, this study provides a thorough stock portfolio analysis approach for global economic challenges. API data retrieval, correlation analysis, and a novel autoencoder model are used in this work to better understand the complicated relationships between economic indicators and financial markets. These insights can improve investment and policy decisions in a more integrated and dynamic global economy.

Клиническая эффективность хирургического лечения катаракты у пациентов после ПРК с использованием основных формул расчета оптической силы ИОЛ

Purpose. To analyze possible refractive errors when calculating IOL power in patients after ARK (anterior radial keratotomy). Material and methods. The data of Intraocular lens (IOL) power calculation in 46 patients (46 eyes) with anterior radial keratotomy (ARK) who also underwent cataract surgery were analyzed. The IOL calculation was performed taking into account the data obtained by the Lenstar LS 900 (HAAG-STREIT AG, Switzerland) and keratotopography (Pentacam HR, Oculus, Germany), with a target refraction corresponding to emmetropia up to ±0.50 D. Results. The analysis of the clinical efficacy of phacoemulsification with IOL implantation in patients after ARK with the refractive error (RE) calculation and refractive prediction error (RPE) calculation according to the basic formulas were performed. It was found that emmetropia (up to ±0.5 D) in the postoperative period was achieved in 52% of cases. The value of the postoperative RPE had no reliable dependence on the values of the eyeball length, it was depended on the corneal optical power in the central zone of the cornea only with some formulas for IOL calculation (Barrett, Barrett Universal II, MIKOFRK/ALF). The obtained results of the analysis provide justification for a deeper study of post keratotomy corneal deformation as a pathological condition with the presence of hidden risk factors. Conclusion. Phacoemulsification with IOL implantation in patients with previously performed ARK is accompanied by the achievement of target refraction in 52% of cases. The high proportion of IOL calculation errors in cataract surgery in patients after ARK largely depends on hidden factors, which determines the need for a detailed study of post keratotomy corneal deformation as a pathological condition. Key words: IOL power calculation, anterior radial keratotomy, emmetropia

Impact of International Trade on the Share Prices of the Industrial Bank of Korea Using Stochastic Prediction Modeling

Purpose – The share price of any financial institution fluctuates due to various hidden and visible factors. Predicting share price behavior in the economy and financial marketing theory is crucial but complex. The Industrial Bank of Korea’s (IBK) share prices are also affected by hidden factors, including Korean international trade flow. The study aims to forecast hidden impacts on IBK share prices resulting from the international trade flow in Korea. Design/Methodology/Approach – Two Hidden Markov Model (HMM) approaches are employed, one based on exports, and the other on imports, to identify trends and fluctuations in the hidden states influencing visible states. Findings – The findings reveal a significant positive correlation between IBK share prices and both exports and imports. Notably, increasing exports indicate a 50% probability of IBK share prices rising, while falling imports indicate a 56% chance of IBK share prices increasing. These results demonstrate how changes in exports and imports impact IBK’s share price in the Korean stock market. Research Implications – The research implications are valuable for short- and long-term investors in IBK shares and the Korean stock exchange. This research can help decision-makers identify the relationships between and within the visible/observed states that influence the stock price of IBK.

Slab gliding, a hidden factor that induces irreversibility and redox asymmetry of lithium-rich layered oxide cathodes

Lithium-rich layered oxides, despite their potential as high-energy-density cathode materials, are impeded by electrochemical performance deterioration upon anionic redox. Although this deterioration is believed to primarily result from structural disordering, our understanding of how it is triggered and/or occurs remains incomplete. Herein, we propose a theoretical picture that clarifies the irreversible transformation and redox asymmetry of lithium-rich layered oxides by introducing a series of global and local dynamic structural evolution processes involving slab gliding and transition-metal migration. We show that slab gliding plays a key role in trigger/initiating the structural disordering and consequent degradation of the anionic redox reaction. We further reveal that the ‘concerted disordering mechanism’ of slab gliding and transition-metal migration produces spontaneously irreversible/asymmetric lithiation and de-lithiation pathways, causing irreversible structural deterioration and the asymmetry of the anionic redox reaction. Our findings suggest slab gliding as a crucial, yet underexplored, method for achieving a reversible anionic redox reaction.

“Blurred facilitation stand” – the hidden factor when working with LGBTQ: Diagnosis and addressing an unspoken effect of internalized homophobia

ABSTRACT While there is always a ‘dance’ of hierarchy and leadership between therapist and client, this article posits that treating LGBTQ clients contains a unique factor that shapes the relationship. Singular challenges may surface as a result of internalized homophobia; it can undermine a client’s stance, in a vague and latent way, to take part meaningfully and effectively in a therapeutic alliance. Moreover, a client may project dimensions rooted in homophobia onto the therapist. As such, it could stymie or undermine the therapeutic alliance. We’ve coined this phenomenon in a therapeutic relationship the ‘blurred facilitation stand”©. This term seeks to underscore a unique effect that can surface in an encounter between a heterosexual or non-heterosexual therapist and a non-heterosexual client. It bears mention this effect may undermine the potency of a therapeutic alliance, which theoreticians and researchers affirm has unique dimensions in working with LBGTQ clients. The ‘blurred facilitation stand’ may damage the hope potential that is essential for the placebo effect in a client’s mind and experience in the long-awaited therapeutic process. We discuss factors that lead to the ‘blurred facilitation stand’ and propose steps in the therapeutic process to reduce its effect.

Investigating the validity and reliability of the GLFS-25 questionnaire by factor analysis in the elderly hospitalized at the intensive and cardiac care units

IntroductionGeriatric Locomotive Function Scale-25 (GLFS-25) is a 25-item tool most commonly used to diagnose locomotive syndrome in the elderly. The purpose of the present study was to investigate the validity and reliability of the GLFS-25 questionnaire using factor analysis. Materials and methodsThis descriptive-analytical study was conducted on 186 elderly people. The GLFS-25 questionnaire contains 25 items, and each item is scored on a five-point Likert scale from 0 to 4. Data were analyzed by SPSS V.19 software. Descriptive (frequency, percentage, mean, and standard deviation) and inferential (Cronbach's alpha, correlation coefficient, Bartlett test, KMO index, scree plot, and factor analysis) statistics were used to present the findings. ResultsFactor analysis revealed two hidden factors in the four dimensions of the questionnaire (i.e., pain, daily activities, social relations, and mental health). The first factor, named mobility and its consequential concerns), with a variance percentage of 74.323, had an effect on questions No. 19, 11, 25, 16, 6, 24, 5, 4, and 3. The second factor, named the problems and risks associated with daily and social activities, with a variance percentage of 78.680, had an effect on questions No. 17, 22, 7, 18, 14, 20, 13, 9, 12, 8, 10, 21, 2, 15, 1, and 23. Cronbach's alpha coefficient among the questionnaire's dimensions was 78.4%. ConclusionThe GLFS-25 questionnaire can be used as a valid and reliable tool to diagnose locomotive syndrome in the elderly.

Unspanned macro risks in VIX futures

AbstractThis study investigates hidden factors in the volatility index (VIX) futures market. Risk factors spanned by the futures curve have a limited ability to capture variations in the expected excess returns. The market's hidden factors provide additional predictive power for future returns in addition to that provided by the factors spanned by the futures curve. The use of a dynamic term structure model with these hidden factors indicates that the hidden factors as a proxy for macro risks materially impact the VIX futures returns and their yield term structure and are significantly helpful in depicting the dynamics of the risk premia.

Topotactic hydrogen forms chains in ABO2 nickelate superconductors

Despite enormous experimental and theoretical efforts, obtaining generally accepted conclusions regarding the intrinsic magnetic and electronic properties of superconducting nickelates remains exceptionally challenging. Experiments show a significant degree of uncertainty, indicating hidden factors in the synthesized films, which call for further investigations. One of those "hidden factors" is the possibility of intercalating hydrogen during the chemical reduction process from Nd(La)NiO$_3$ to Nd(La)NiO$_2$ using CaH$_2$. While hydrogen has been detected in experimental samples, not much is known about its distribution through the crystal and its influence on the electronic environment. Here, we show the tendency toward the formation of one-dimensional hydrogen chains in infinite-layers LaNiO$_2$ superconductors using density-functional theory (DFT) supplemented by dynamical mean-field theory (DMFT). The formation of such hydrogen chains induces a coexistence of different oxidation states of Ni and competing magnetic phases, and possibly explains the recently observed charge order states in nickelate superconductors. Furthermore, it contributes to the difficulty of synthesizing homogeneous nickelates and determining their ground states. The smoking gun to detect excess hydrogen in nickelates are flat phonon modes, which are infrared active and quite insensitive to the exact arrangement of the H atoms.

Involvement of Human and Organizational Factors in Railway Accidents: Application of the Human Factors Analysis and Classification System and Bayesian Network

The occurrence of railway accidents is not always the result of error/violation on the operator’s end; rather, there are many organizational factors involved. This research investigated 97 railway accident reports from the West Zone of Bangladesh Railway between 2015 and 2019 to categorize factors within the institution that contribute to accidents. The accidents were divided into four categories (collision, derailment, locomotive failure, and signal passed at danger [SPAD]) and were applied to the Human Factors Analysis and Classification System (HFACS) framework. The HFACS framework systematically identifies direct and hidden factors that lead to an accident. A total of 225 human and organizational factors were found involved in 97 accidents, of which 106 (47.11%) were organizational-level factors and 119 (52.89%) were front-line/operation-level factors. To understand the association between factors, a Bayesian network was created following the naive Bayes algorithm, keeping “accident type” as the class variable. Analysis revealed that “Collisions” occur because of organizational factors such as the structure of command, planned inappropriate operations, and operation-level factors such as perceptual errors, and personal unreadiness. “Derailment” was influenced by organizational reasons, such as equipment issues, company safety culture, and inadequate supervision, whereas operation-level factors were crew and resource management and skill-based error. “Locomotive failure” was found to be associated with only organizational factors, such as equipment issues and inadequate supervision, and SPAD mostly occurred because of exceptional violations at the operational level. The identified issues, if addressed properly, can help ensure a safer railway industry.

The influence of occupational environment on formation of psycho-emotional stress among remote pilots of unmanned aircraft systems

The aim of this study was to identify informative indicators and establish the level of perception of their impact on the formation of excessive psycho-emotional stress among remote pilots of unmanned aircraft systems (UASs) (class 1 “Light”) during their occupational activities. Materials and methods. 41 servicemen aged 20–35 years old, who had experience in the management of UASs (class I “Light”) and were involved in the performance of a wide range of functional duties as operators of the moving objects, were studied based on the specially developed questionnaire (100-point scale) that reflected questions about the perception of the stress factor impact during their occupational activities. Statistical analysis of data was performed by descriptive and nonparametric statistics, as well as cluster, stepwise discriminant and factor analysis using the software package STATISTICA 13.3. Results. Regarding the perceptions of “stress” factor influence, the UASs pilots (operators of moving objects) were divided into two groups: group 1 could be conventionally called “hypersusceptible”, and representatives of group 2 – “hyposusceptible”. At the same time, it was found that the resulting clustering of the data into two groups provided 99.9 % opportunity for further assignment of new operators to the designated groups using the obtained supporting discriminant model (solving rules). The hidden factors have been revealed that formed the functional state of the “hypersusceptible” UASs operators, which collectively explained 54.9 % of the data variance, and “hyposusceptible” ones, which collectively explained 62.1 % of the original data variance. Conclusions. Two groups of operators, “hypersusceptible” and “hyposusceptible” to the influence of stress factors have been distinguished. The hidden factors that formed the functional state of the “hypersusceptible” UAS operators have been highlighted (the first factor “formation of fear of death” (F1↑) had 33.2 % rate and the second hidden factor “susceptibility to sensory stimuli” (F2↑), covered 21.7 % of the analyzed data variance). Two hidden factors that formed the functional state of the “hyposusceptible” UAS operators have been identified (the first factor “concentration of attention to performance of the functional duties” (F1↓) and the second factor “increased responsibility for occupational activity results” (F2↓). It has been established that there were radically different mechanisms of their functional state regulation, and “hyposusceptible” operators were more adapted to the performance of their functional duties due to the mechanisms of harmonizing their functional state and reducing experiences from the influence of harmful stress-forming factors.