Meaningful Explanation Research Articles

Synaptic boutons sizes are tuned to best fit their physiological performances

To truly appreciate the myriad of events which relate synaptic function and vesicle dynamics, simulations should be done in a spatially realistic environment. This holds true in particular in order to explain as well the rather astonishing motor patterns which we observed within in vivo recordings which underlie peristaltic contractionsas well as the shape of the EPSPs at different forms of long-term stimulation, presented both here, at a well characterized synapse, the neuromuscular junction (NMJ) of the Drosophila larva (c.f. Figure ​Figure1).1). To this end, we have employed a reductionist approach and generated three dimensional models of single presynaptic boutons at the Drosophila larval NMJ. Vesicle dynamics are described by diffusion-like partial differential equations which are solved numerically on unstructured grids using the uG platform. In our model we varied parameters such as bouton-size, vesicle output probability (Po), stimulation frequency and number of synapses, to observe how altering these parameters effected bouton function. Hence we demonstrate that the morphologic and physiologic specialization maybe a convergent evolutionary adaptation to regulate the trade off between sustained, low output, and short term, high output, synaptic signals. There seems to be a biologically meaningful explanation for the co-existence of the two different bouton types as previously observed at the NMJ (characterized especially by the relation between size and Po), the assigning of two different tasks with respect to short- and long-time behaviour could allow for an optimized interplay of different synapse types. We can present astonishing similar results of experimental and simulation data which could be gained in particular without any data fitting, however based only on biophysical values which could be taken from different experimental results. As a side product, we demonstrate how advanced methods from numerical mathematics could help in future to resolve also other difficult experimental neurobiological issues. Figure 1 Simulation of a bouton of the Drosophila NMJ

Efficiency determinations of the worldwide railway companies via DEA and contributions of the outputs to the efficiency and TFP by panel regression

This study attempts to obtain efficiency scores of thirty-one railway companies operating worldwide by using data envelopment analysis. To assess the data covering a term from 2000 to 2009, we use CCR and BCC methods. According to the results of the CCR model analysis, 17 firms are found to have technical efficiency in the first year, whereas this figure goes up to 18 companies in the last year. Input oriented and variable return analysis in the concept of the BCC model, the number of the firms found technically efficient at the beginning of the period are 20. At the end of the period, this figure is up to 24. We implement panel regression analysis to estimate the effects of the companies’ output on their efficiency. Results imply that CCR models provide us more meaningful explanations. Malmquist Index analysis also indicates that total factor productivity increases by 0.03 % for the entire period.

Management's Earnings Justification and Earnings Management under Different Institutional Regimes

AbstractManuscript TypeEmpiricalResearch Question/IssueThis study examines whether accruals earnings management is associated with managers' explanations of performance provided in narrative reports accompanying the financial statements in an international setting that covers voluntary and mandatory institutional environments for management commentary (MC) reporting. Differences in institutional environment are theorized as having a profound impact on the relative adequacy of different explanation types in mitigating earnings management concerns.Research Findings/InsightsBased on 162 companies from four countries (the United Kingdom, Australia, the United States, and Canada), the study reports a close alignment of the use of earnings explanations and the strength and direction of accruals management. The results indicate that explanation type significantly affects the association between performance explanations and accruals management and that this effect becomes more pronounced in a mandatory institutional regime where expected regulatory and litigation costs are higher.Theoretical/Academic ImplicationsThe results indicate that the mandatory setting for narrative reporting (United States and Canada) affects the type of explanation perceived by managers to be more effective in mitigating potential concerns about earnings management. In a mandatory setting, the more costly causal explanations are more likely to be used by companies that are engaged in upwards earnings management.Practitioner/Policy ImplicationsRegulators have debated about how to promote useful disclosure in management commentary reports. They have pointed to the need for more meaningful causal explanations. Our findings are relevant to the debate as they show that more scrutiny via a mandatory reporting regime (with associated higher expected litigation and regulatory costs) is a setting that encourages provision of these more costly causality‐based explanations when preparers have incentives to ensure the adequacy of their explanations.

Stochastic comparison of generalized combined risk processes

Usually, two different types of shock models (extreme and cumulative shock models) are employed to model the dynamic risk processes. In extreme shock models, only the impact of the current fatal shock is usually taken into account, whereas, in cumulative shock models, the impact of the preceding shocks is accumulated as well. However, in practice, the effect of the corresponding shock can be realized in those two ways in one model (i.e., it can be fatal or, otherwise it is accumulated). This observation justifies the consideration of a ‘combined shock model’ in the risk modeling and analysis. In this paper, we generalize the study of the dynamic risk processes that were previously considered in the literature. The main theme of this paper is to find the optimal allocation policies for the generalized combined risk processes via the stochastic comparisons of survival functions. It will be seen that the obtained results hold for ‘general counting processes’ of shocks. In addition, we consider the problem of maximizing a gain function under certain risks and obtain reasonable decisions based on a variability measure. Furthermore, the meaningful explanations for the results on the policy ordering will be provided.

The Revised m-of-k Runs Rule Based on Median Run Length

Runs rules are used to increase the sensitivity of the Shewhart control chart in detecting small and moderate process mean shifts. Most of the charts incorporating runs rules are designed based on the average run length (ARL). It is known that the shape of the run length distribution changes according to the magnitude of the shift in the process mean, ranging from highly skewed when the process is in-control to approximately symmetric when the shift is large. Since the shape of the run length distribution changes with the magnitude of the shift in the mean, the median run length (MRL) provides a more meaningful explanation about the in-control and out-of-control performances of a control chart. In this article, we propose the design of the revised m-of-k runs rule based on MRL. In addition, the standard deviation of the run length (SDRL) of the revised m-of-k rule will also be studied. The revised m-of-k runs rule, suggested by Antzoulakos and Rakitzis (2008), was originally designed based on ARL. The Markov chain technique is employed to obtain the MRLs. Compared with the standard chart, the MRL results show that the revised rules give better performances for small and moderate mean shifts, while maintaining the same sensitivity towards large mean shifts. The MRL results are in accordance with the results obtained by Antzoulakos and Rakitzis (2008), where the rules are designed based on ARL.

Age Variance in the Survival of United States Pediatric Leukemia Patients (1973–2006)

Background. Age at diagnosis remains an important prognostic factor in pediatric leukemia. However, it is not fully understood which prognostic factors are related to its effect on survival. This study aimed to assess the effect of age at diagnosis on pediatric leukemia survival in the United States (US). Methods. We utilized the Surveillance Epidemiology and End Results (SEER) data of the diagnosed pediatric leukemia patients (n=15215) from 1973–2006. Life table, Kaplan-Meier, log rank test, and Cox proportional hazard methods were used to examine the data. Results. The overall 5-year survival was 67.9%. Infants and children of 18 and 19 years had the highest risk of dying, with a rapid declining risk of death at age of 1 year that continued until age of 3 years and thereafter a steady trend of increased risk of death. The increased risk of dying was associated with boys, T-cell type and more than one primary tumor, P < 0.0001. There was significant variability in survival by the age group at diagnosis. Compared to age group <1 year, children of ages 1–4 years, 5–9 years, 10–14 years, and 15–19 years were 76% (adjusted hazard ratio (AHR) = 0.24, 99% CI = 0.21–0.28), 69% (AHR = 0.31, 99% CI = 0.26–0.36), 46% (AHR = 0.54, 99% CI = 0.46–0.62), and 18% (AHR = 0.82, 99% CI = 0.70–0.95) less likely to die, respectively. Conclusion. The age at tumor diagnosis was a single most potent prognostic factor of childhood leukemia survival, with infants and children of age group 15–19 years experiencing the poorest survival. This significant variability persisted after adjustment for the effect of other covariates. Therefore, there is a need to identify other prognostic factors that are associated with age in order to provide a meaningful explanation of the impact of age on pediatric leukemia survival in the US.

Species distribution models

The main goal of species distribution modeling is to identify important underlying factors related to broad-scale ecological patterns in order to make meaningful explanations or accurate predictions. When standard statistical methods such as regression are used to formulate these models, assumptions about the spatial structure of the data and the model parameters are often violated. Autocorrelation and non-stationarity are characteristics of spatial data and models, respectively, and if present and unaccounted for in model development, they can result in poorly specified models as well as inappropriate spatial inference and prediction. While these spatial issues are addressed here in an ecological context using species distribution models, they are broadly relevant to any statistical modeling applications using spatial data.

Explaining Reported Puma-Related Behaviors and Behavioral Intentions Among Northern Arizona Residents

Management of pumas in the American West is typified by conflict among stakeholders plausibly rooted in life experiences and worldviews. We used a mail questionnaire to assess demographics, nature-views, puma-related life experiences and behaviors, and support for puma-related policies among residents of northern Arizona. Data from the questionnaire (n = 693 respondents) were used to model behaviors and support for policies. Compared to models based on nature-views and life experiences, those based on demographics had virtually no support from the data. The Utilitarian/Dominionistic nature-view had the strongest effect of any variable in six of seven models, and was associated with firearms and opposition to policies that would limit killing pumas. The Humanistic/Moralistic nature-view was positively associated with non-lethal behaviors and policies in five models. Gender had the strongest effect of any demographic variable. Compared to demographics alone, our results suggest that worldviews provide a more meaningful explanation of reported human behaviors and behavioral intentions regarding pumas.

Did accelerated filing requirements and SOX Section 404 affect the timeliness of 10-K filings?

This paper examines the effect of Sarbanes-Oxley provisions on 10-K filing delays. We find that tightened filing deadlines for accelerated and large accelerated filers are not associated with changes in the incidence of late filing. While Section 404 compliance does not affect filing timeliness for firms with effective internal controls, we find that about half the firms disclosing internal control weaknesses are late filers. As a consequence, many Section 404 material weakness firms experience negative abnormal returns around late filing notifications before filing the 10-K. Lastly, we find that market reactions to late filing notifications are more negative when management provides no meaningful explanation for the delay, consistent with managers’ incentives to withhold bad news.

Analogies as Tools for Meaning Making in Elementary Science Education: How Do They Work in Classroom Settings?

In this paper there is a critical overview of the role of analogies as tools for meaning making in science education, their advantages and disadvantages. Two empirical studies on the use of analogies in primary classrooms are discussed and analysed. In the first study, the ‘string circuit’ analogy was used in the teaching of electric circuits with students aged 8-9. In the second study, the ‘making a cake’ analogy was introduced within the study of photosynthesis with students aged 10-11. Outcomes of both studies are scrutinised to assess the effectiveness of analogies as tools for meaning making. How the analogies are presented, their contexts, and how much students are involved in mapping the analogical relations appear to be determinant. This strongly suggests that research and pedagogical practice should shift from determining the effectiveness of analogy in cognitive transfer, from analogue to target domains, towards the recognition of its role in generating engagement in developing meaningful explanations through discourse. Finally, most salient aspects of the use of analogies are considered for contexts in which they are used to promote understanding of scientific ideas. Analogy can play and important role in that task if it is seen as a resource to promote understanding and meaning making but its strengths and limitations are not ignored.

The law and economics of class actions

More than four decades ago in The Logic of Collective Action, Olson (1965) provided the evidence that in specific circumstances the uncoordinated action of individuals can be less efficient than coordinated action. He was essentially targeting public goods. Nonetheless, this attitude sometimes extends to different goods even though a large number of individuals have a common interest. The Olson contribution was therefore a meaningful explanation for the formation of groups and, as a by-product, for the emergence of specific institutions devoted to making coordination possible. However, co-operation and organization can not only better serve the private interest of individuals but can be ‘‘the most powerful tools human reason can employ’’ for expressing human liberty (Von Hayek 1960, p. 37) in a wide number of settings, from the market to the political and government systems where other means are ineffective. An important question is thus whether the previous reasoning equally applies to the judiciary: certainly this is an important topic for law and economics research. Generally speaking, in a number of cases legal actions can be brought collectively and imply some coordination, such as for criminal lawsuits involving a number of victims or for litigations fostered by a public company, involving, albeit indirectly, all the investors. However, this only concerns limited situations.

Beyond the ceiling effect: Using a mixed methods approach to measure patient satisfaction

This study reports patient satisfaction with the nursing care on a neurosurgical critical care unit. A modified version of the Ludwig-Beymer Patient Satisfaction Questionnaire (PSQ-7) was used, and included structured items and semi-structured interview questions. Data were collected from 149 patients. Participants rated their satisfaction as high (Mean = 25.14; SD = 2.96). The distribution of scores was skewed and every item demonstrated a ceiling effect. Principal component analysis yielded a one-component solution which explained 48% of the variance. NVivo was used to match PSQ-7 scores with qualitative data. Participants' comments were categorised as positive, negative or 'yes, but'. Just over half the patients made positive comments and 29% of patients in the low group made negative comments. Three categories: 'communication', 'nursing care delivery' and 'the hospital environment' emerged from the qualitative data. A mixed method approach enables researchers to move beyond the ceiling effect of quantitative measures of patient satisfaction and to gain a more meaningful explanation of patient satisfaction.

How to Avoid Mistakes in Valuation: Guidelines for Practitioners

The cash flows discounting is a conventional and theoretically sound approach to valuing firms and projects. Although it is intuitively easy and attractive, the practical implementation is not without challenges. At the first sight the discounting procedure is a simple and routine task, which does not involve much effort. But actually even in simple cases accurate valuation requires attention to plenty of details. The slightest negligence or insufficient knowledge of underlying theory can result in substantial inaccuracy.Sometimes practitioners manifest the fatal conceit of professing disdain for theory. They presume that their experience provides a solid ground for developing complex models. As a result they mostly rely on their intuition and past situations and eventually encounter on fundamentally new or counter-intuitive problems where the intuition has no power and leads to mistaken decisions. In contrast theoretical understanding consists in rational thought and meaningful explanations about a given subject matter in its entirety, considering the matter from different sides and with investigation of cause and effect relationships. As well as the experience can be rich or poor, theories can be imperfect or even controversial. And actually not every set of words can be called a theory. Theory is constructed of a set of true interrelated logical statements about the subject under consideration and it reflects the up to date state of knowledge about the matter. With respect to valuation, theory plays a crucial role, as there are no simple empirical methods to find value of a business or project from observable data. The whole profession is erected on theoretical constructions such as concepts of utility, time value of money, risk avoidance, market equilibrium and other related economic, financial and accounting concepts. This implies not only strong attention to specific theoretical issues suggesting a meaningful guidance to practical problems but also a systematic view and deep understanding of interrelationships between various concepts and variables. Such understanding should be extended to building valuation models and calculations. The present paper intends to investigate the most error-prone, obscure and controversial issues concerning valuation. It also covers some important moments that are often overlooked in textbooks and professional literature. Perhaps, a portion of the paper repeats existing research; however, it is inevitable to ensure a consecutive and consistent writing.At the same time the paper has no purpose to revise the up to date theory, but is mostly oriented on systematization and filling the gaps. The paper focuses only on the practical matters and stands aside chiefly fundamental questions such as determining a magnitude of discount rate. A common wisdom says that knowing a few principles is worth the knowledge of a lot of facts. So the paper has a strong incentive to center mostly on revealing general rules instead of describing all possible cases and situations that may encounter in valuation practice and of providing detailed instructions on how to treat each of the special problems.

Rough Sets as a Knowledge Discovery and Classification Tool for the Diagnosis of Students with Learning Disabilities

Due to the implicit characteristics of learning disabilities (LDs), the diagnosis of students with learning disabilities has long been a difficult issue. Artificial intelligence techniques like artificial neural network (ANN) and support vector machine (SVM) have been applied to the LD diagnosis problem with satisfactory outcomes. However, special education teachers or professionals tend to be skeptical to these kinds of black-box predictors. In this study, we adopt the rough set theory (RST), which can not only perform as a classifier, but may also produce meaningful explanations or rules, to the LD diagnosis application. Our experiments indicate that the RST approach is competitive as a tool for feature selection, and it performs better in term of prediction accuracy than other rulebased algorithms such as decision tree and ripper algorithms. We also propose to mix samples collected from sources with different LD diagnosis procedure and criteria. By pre-processing these mixed samples with simple and readily available clustering algorithms, we are able to improve the quality and support of rules generated by the RST. Overall, our study shows that the rough set approach, as a classification and knowledge discovery tool, may have great potential in playing an essential role in LD diagnosis.

A two-stage clustering method to analyze customer characteristics to build discriminative customer management: A case of textile manufacturing business

In order to obtain comprehensive information about customers, this study aims to use a systematized analytic method to examine customers. This study uses LRFM customer relationship model, which consists of four dimensions: relation length (L), recent transaction time (R), buying frequency (F), and monetary (M), to carry out customer clusters. We proceed with this clustering analysis to classify customers in order to set discriminative marketing strategies. In addition, this study further employed a cross analysis over three predetermined dimensions: area, sales, and new/old characteristics to enhance the clustering analysis. The results obtained from the real textile business show that the customer groups formed using the four-factor (LRFM) clustering all has statistical significant differences, and with meaningful explanations in terms of marketing strategy. Thus, this study considers useful for discriminative customer relationship management.

“This is Why you’ve Been Suffering”: Reflections of Providers on Neuroimaging in Mental Health Care

Mental health care providers increasingly confront challenges posed by the introduction of new neurotechnology into the clinic, but little is known about the impact of such capabilities on practice patterns and relationships with patients. To address this important gap, we sought providers' perspectives on the potential clinical translation of functional neuroimaging for prediction and diagnosis of mental illness. We conducted 32 semi-structured telephone interviews with mental health care providers representing psychiatry, psychology, family medicine, and allied mental health. Our results suggest that mental health providers have begun to re-conceptualize mental illness with a neuroscience gaze. They report an epistemic commitment to the value of a brain scan to provide a meaningful explanation of mental illness for their clients. If functional neuroimaging continues along its projected trajectory to translation, providers will ultimately have to negotiate its role in mental health. Their perspectives, therefore, enrich bioethical discourse surrounding neurotechnology and inform the translational pathway.

Material anisotropy and trimming method effects on total elongation in DP500 sheet steel

The objective of this study is to determine the influence of material anisotropy and trimming method on the total elongation of the trimmed edge of DP500 sheet steel. For various orientations, experimental analysis is carried out on rectangular shaped tensile test specimens featuring a polished edge on one side and a trimmed edge on the other side. It is shown that the total elongation in DP500 steel exhibits significant sensitivity to (1) specimen orientation with respect to rolling direction, and (2) trimming method employed. In particular, difference in total elongation between longitudinal and transverse orientations become more pronounced with increasing trim clearance for conventionally trimmed samples. Total elongation anisotropy, however, can be significant even at small trim clearances and when sheared surface of the blank has relatively good quality without the burr which is the case for samples trimmed by the technology with offal support and dulled upper trim edge. The observations provided herein may be instrumental in contributing to meaningful explanations for unexpected edge cracking problems observed in some DP500 stamping cases. Recommendations for manufacturing best practices are offered.

Ripple-to-dome transition: The growth evolution of Ge on vicinal Si(1 1 10) surface

We present a detailed scanning tunneling microscopy study which describes the morphological transition from ripple-to-dome islands during the growth of Ge on the vicinal Si(1 1 10) surface. Our experimental results show that the shape evolution of Ge islands on this surface is markedly different from that on the flat Si(001) substrate and is accomplished by agglomeration and coalescence of several ripples. By using published data of surface energy and finite-element analysis, we provide a meaningful explanation of our experimental observations.

Impact of Age at Diagnosis on Pediatric Leukemia Survival

PURPOSE: Although age at diagnosis is a surrogate prognostic factor, it remains an important predictor of pediatric leukemia survival. However, it is not fully understood which prognostic factors are directly related to its effect on survival. We aimed in this study to assess the effect of age at diagnosis on childhood leukemia survival. METHODS: We utilized data from Surveillance Epidemiology and End Result (SEER) of newly diagnosed leukemia (nZ15,215) from 1973–2006. Data on sex, race, clinical subtypes of leukemia, children aged 0–19 years involving 17 SEER registries were assessed for overall and age at diagnosis related survival. The Kaplan-Meier, log rank test, and Cox proportional hazard methods were used to examine the impact of age on survival. RESULTS:Theoverall 5 year survival ratewas 67.9%.There was a statistically significant difference in survival by age group at diagnosis, sex, race, tumor cell type, p! 0.0001. This variability persisted after adjustment for the relevant covariates. Compared to infants, children 1–4 years were 76% less likely to die from leukemia (Adjusted Hazard Ratio (AHR) Z 0.24, 99% CIZ0.21–0.28, Children 5–9 years (AHRZ0.31, 99% CI Z 0.26–0.36), children 10–14 years (AHRZ 0.54, 99% CIZ0.46–0.62) and children 15–19 years (AHRZ0.82, 99% CIZ0.70–0.95) CONCLUSIONS:Age at diagnosis remains a single potent predictor of survival in pediatric leukemia, and infants as well as children 15–19 years present with the worst survival. Since age at diagnosis per se does not influence survival but is related to biological and/or clinical tumor prognostic factors, this study adjusted for the effect of some of these factors but survival variability by age at diagnosis persisted. Therefore, identification of such factors will ensure a meaningful explanation of the impact of age at tumor diagnosis on survival.

Simulation of MoS 2 crystal structure and the experimental study of thermal decomposition

In this paper, the theoretical calculations of MoS 2 crystal geometries, energy band structure, electron density, electron density difference, density of states and Mulliken overlap population were carried out by density functional theory (DFT). The dynamics simulations of MoS 2 crystal face (0 0 1) were performed. We obtained the meaningful parameters and explanations to guide the thermal decomposition of MoS 2. The experimental results of the thermal decomposition of MoS 2 were in accordance with the theoretical calculation results. The production of molybdenum powder by direct decomposition of molybdenum concentrate, as a novel method with short flow, less pollution and low cost, was of guiding significance for the next step of the experimental study of thermal decomposition of MoS 2.