Miracle-dz/UniFAR-FTUs huggingface dataset:
Micropolar theory for two–dimensional stresses in elastic honeycomb

A micropolar theory has been used to calculate the stress field generated by a fundamental boundary–value problem in planar elasticity; namely, a normal line force acting on the surface of a honeycomb half–space. In this two-dimensional analysis the microstructure of the honeycomb results in couple stresses and microrotations in addition to the usual components of stress and strain. Constitutive relations for a unit cell of the honeycomb are obtained that are sensitive to the symmetry of the microstructure. Because of the six–fold symmetry of the regular hexagonal microstructure these constitutive relations contain only four independent material constants. The discontinuous traction on the boundary of the honeycomb generates stresses σij that have a 1/r dependence on radial distance from the discontinuity while the microcouples mi3 have a 1/r2 dependence on radial distance.
Evaluation of prognostic factors in stage IIA breast tumors and their correlation with mortality risk

ABSTRACT: Breast tumors exhibit extensive molecular and clinical heterogeneity. One of the most utilized breast carcinoma classifications is based on its molecular aspects and subdivides breast cancer into five major groups based on the expression of certain genes. In this study, we evaluated which factors are important in determining a prognosis after 5 years of follow-up for patients with clinical stage IIA breast tumors. We took into consideration the different phenotypes (luminal A luminal B HER-2 overexpression, basal and triple-negative), various epithelial-mesenchymal (EMT) molecular markers and adhesion molecules (E-cadherin, P-cadherin, N-cadherin, vimentin, twist snail and slug) and NOS-2, in addition to clinical and demographic data, tumor characteristics and treatment types. METHODS: The study population consisted of 82 patients with breast cancer. We analyzed eight molecular markers by immunohistochemistry on tissue microarrays containing breast tumor specimens from patients with ten years of follow-up, and we classified each tumor according to its estrogen receptor, progesterone receptor and HER-2 expression. We then placed the tumor into one of the above categories. RESULTS: The presence of several clinical and demographic factors, various histopathologies, treatment forms and several immunohistochemical markers were not associated with a worse prognosis for group IIA patients. The factors that were associated with a mortality risk were the triple-negative (odds ratio (OR) = 11.8, 95% confident interval (CI) = 2.0-70.3, P = 0.007) and basal (OR = 18.4, 95% CI = 1.8-184.7, P = 0.013) phenotypic patterns. CONCLUSIONS: The EMT markers and NOS-2 were not mortality risk factors. Basal and triple-negative phenotypic patterns were related to a higher mortality risk in patients with stage IIA tumors.
An Empirical Comparison of Field Defect Modeling Methods

In this study, we report empirical results from forecasting field defect rates and predicting the number of field defects for a large commercial software system. We find that we are not able to accurately forecast field defect rates using a combined time-based and metrics-based approach, as judged by the Theil forecasting statistic. We suggest possible conditions that may have contributed to the poor results. Next, we use metrics-based approaches to predict the number of field defects within the six months after deployment. We find that the simple ratios method produce more accurate predictions than more complex metrics-based methods. Our results are steps toward quantitatively managing the risks associated with software field defects.
Bayesian Inference in Semiparametric Mixed Models for Longitudinal Data

Summary We consider Bayesian inference in semiparametric mixed models (SPMMs) for longitudinal data. SPMMs are a class of models that use a nonparametric function to model a time effect, a parametric function to model other covariate effects, and parametric or nonparametric random effects to account for the within‐subject correlation. We model the nonparametric function using a Bayesian formulation of a cubic smoothing spline, and the random effect distribution using a normal distribution and alternatively a nonparametric Dirichlet process (DP) prior. When the random effect distribution is assumed to be normal, we propose a uniform shrinkage prior (USP) for the variance components and the smoothing parameter. When the random effect distribution is modeled nonparametrically, we use a DP prior with a normal base measure and propose a USP for the hyperparameters of the DP base measure. We argue that the commonly assumed DP prior implies a nonzero mean of the random effect distribution, even when a base measure with mean zero is specified. This implies weak identifiability for the fixed effects, and can therefore lead to biased estimators and poor inference for the regression coefficients and the spline estimator of the nonparametric function. We propose an adjustment using a postprocessing technique. We show that under mild conditions the posterior is proper under the proposed USP, a flat prior for the fixed effect parameters, and an improper prior for the residual variance. We illustrate the proposed approach using a longitudinal hormone dataset, and carry out extensive simulation studies to compare its finite sample performance with existing methods.
Exposure, probable PTSD and lower respiratory illness among World Trade Center rescue, recovery and clean-up workers

Background Thousands of rescue and recovery workers descended on the World Trade Center (WTC) in the wake of the terrorist attack of September 11, 2001 (9/11). Recent studies show that respiratory illness and post-traumatic stress disorder (PTSD) are the hallmark health problems, but relationships between them are poorly understood. The current study examined this link and evaluated contributions of WTC exposures. Method Participants were 8508 police and 12 333 non-traditional responders examined at the WTC Medical Monitoring and Treatment Program (WTC-MMTP), a clinic network in the New York area established by the National Institute for Occupational Safety and Health (NIOSH). We used structural equation modeling (SEM) to explore patterns of association among exposures, other risk factors, probable WTC-related PTSD [based on the PTSD Checklist (PCL)], physician-assessed respiratory symptoms arising after 9/11 and present at examination, and abnormal pulmonary functioning defined by low forced vital capacity (FVC). Results Fewer police than non-traditional responders had probable PTSD (5.9% v. 23.0%) and respiratory symptoms (22.5% v. 28.4%), whereas pulmonary function was similar. PTSD and respiratory symptoms were moderately correlated (r=0.28 for police and 0.27 for non-traditional responders). Exposure was more strongly associated with respiratory symptoms than with PTSD or lung function. The SEM model that best fit the data in both groups suggested that PTSD statistically mediated the association of exposure with respiratory symptoms. Conclusions Although longitudinal data are needed to confirm the mediation hypothesis, the link between PTSD and respiratory symptoms is noteworthy and calls for further investigation. The findings also support the value of integrated medical and psychiatric treatment for disaster responders.
A mouse model of prenatal ethanol exposure using a voluntary drinking paradigm.

BACKGROUND The incidence of fetal alcohol spectrum disorders is estimated to be as high as 1 in 100 births. Efforts to better understand the basis of prenatal ethanol-induced impairments in brain functioning, and the mechanisms by which ethanol produces these defects, will rely on the use of animal models of fetal alcohol exposure (FAE). METHODS Using a saccharin-sweetened alcohol solution, we developed a free-choice, moderate alcohol access model of prenatal alcohol exposure. Stable drinking of a saccharin solution (0.066%) was established in female mice. Ethanol then was added to the saccharin in increasing concentrations (2%, 5%, 10% w/v) every 2 days. Water was always available, and mice consumed standard pellet chow. Control mice drank saccharin solution without ethanol. After a stable baseline of ethanol consumption (14 g/kg/day) was obtained, females were impregnated. Ethanol consumption continued throughout pregnancy and then was decreased to 0% in a step-wise fashion over a period of 6 days after pups were delivered. Characterization of the model included measurements of maternal drinking patterns, blood alcohol levels, food consumption, litter size, pup weight, pup retrieval times for the dams, and effects of FAE on performance in fear-conditioned learning and novelty exploration. RESULTS Maternal food consumption, maternal care, and litter size and number were all found to be similar for the alcohol-exposed and saccharin control animals. FAE did not alter locomotor activity in an open field but did increase the time spent inspecting a novel object introduced into the open field. FAE mice displayed reduced contextual fear when trained using a delay fear conditioning procedure. CONCLUSIONS The mouse model should be a useful tool in testing hypotheses about the neural mechanisms underlying the learning deficits present in fetal alcohol spectrum disorders. Moreover, a mouse prenatal ethanol model should increase the opportunity to use the power of genetically defined and genetically altered mouse populations.
catena-[[(nitrato-κO)silver(I)]-μ-1,10-phenanthroline-5,6-dione-κ4 O,O′:N,N′]

In the title one-dimensional coordination polymer, [Ag(NO3)(C12H6N2O2)]n, the AgI atom is pentacoordinated by two N atoms from a 1,10-phenanthroline-5,6-dione (phen-dione) ligand, one O atom from the nitrate anion and two O atoms from another phen-dione ligand. The coordination environment around silver is slightly distorted square-pyramidal. Interestingly, the Ag—O distances to the phen-dione ligand are different [Ag—O = 2.612 (6) and 2.470 (5) Å]. The one-dimensional chains run parallel to [101] and are further interconnected by weak hydrogen bonds (C—H⋯O) and π–π stacking interactions [centroid–centroid distances 3.950 (4) and 3.792 (4) Å], forming a three-dimensional supramolecular network.
Use of Liver Stiffness Measurement for Liver Resection Surgery: Correlation with Indocyanine Green Clearance Testing and Post-Operative Outcome

Background Liver stiffness measurement (LSM) using transient elastography has recently become available for the assessment of liver fibrosis. Whether LSM can predict the functional liver reserve in patients undergoing liver resection is not certain. Aim To correlate liver stiffness measurement (LSM) with indocyanine green (ICG) clearance test and liver biochemistry, and to determine its usefulness in predicting postoperative outcomes in patients undergoing liver resection. Patients and Methods Transient elastography and ICG clearance test were performed pre-operatively in 44 patients with hepatocellular carcinoma. The LSM and ICG retention rate at 15 minutes (R15) were correlated with pre-operative factors and post-operative outcomes. Results There was significant correlation between ICG R15 and LSM. In patients with LSM ≥11 kPa vs <11 kPa, there was significantly higher ICG R15 (17.1% vs 10.0% respectively, p = 0.025). For patients with ICG R15≥10% compared to those <10%, there was significantly higher LSM (12.0 vs 7.6 kPa respectively, p = 0.015). Twenty-eight patients proceeded to resection. There was a significant correlation between LSM and the peak INR after liver resection (r = 0.426, p = 0.024). There was a significant correlation between ICG R15 and the post-operative peak AST level (r = −0.414, p = 0.029) and peak ALT level (r = −0.568, p = 0.002). The operative time was a significant independent factor associated with post-operative complications and peak INR. Conclusion LSM correlated well with ICG R15 in patients undergoing liver resection, and predicted early post-operative complications. Addition of LSM to ICG R15 testing may provide better prognostic information for patients undergoing resection.
Sorption of remazol brilliant blue R onto polyurethane‐type foam prepared from peanut shell

The powders of peanut shell is first liquefied with the mixture of polyethylene glycol-400 and monoethylene glycol (MEG) using sulfuric acid at 160°C for 2 h. Polyurethane (PU)-type rigid foam is prepared from the reaction between peanut shell liquefied with the MEG and diphenylmethane diisocyanate. Then the PU foam is used as a sorbent for the removal of the remazol brilliant blue R from aqueous solution. The sorption of the dye increases with increasing initial concentration, temperature, and ionic strength, while decreasing with increasing pH. From the isotherm and kinetic studies, it is seen that the sorption process is in the best agreement with the Langmuir isotherm and the pseudo second-order kinetic model. Desorption and FTIR studies show that a chemisorption process occurs between dye and foam, probably indicating electrostatic interactions. The thermodynamic parameters (i.e., standard free energy, standard enthalpy, and standard entropy) are determined, and the results obtained are discussed in detail. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci, 2013
Inhibition of Herpes Simplex Virus Type 1 Replication by Adeno-Associated Virus Rep Proteins Depends on Their Combined DNA-Binding and ATPase/Helicase Activities

ABSTRACT Adeno-associated virus (AAV) has previously been shown to inhibit the replication of its helper virus herpes simplex virus type 1 (HSV-1), and the inhibitory activity has been attributed to the expression of the AAV Rep proteins. In the present study, we assessed the Rep activities required for inhibition of HSV-1 replication using a panel of wild-type and mutant Rep proteins lacking defined domains and activities. We found that the inhibition of HSV-1 replication required Rep DNA-binding and ATPase/helicase activities but not endonuclease activity. The Rep activities required for inhibition of HSV-1 replication precisely coincided with the activities that were responsible for induction of cellular DNA damage and apoptosis, suggesting that these three processes are closely linked. Notably, the presence of Rep induced the hyperphosphorylation of a DNA damage marker, replication protein A (RPA), which has been reported not to be normally hyperphosphorylated during HSV-1 infection and to be sequestered away from HSV-1 replication compartments during infection. Finally, we demonstrate that the execution of apoptosis is not required for inhibition of HSV-1 replication and that the hyperphosphorylation of RPA per se is not inhibitory for HSV-1 replication, suggesting that these two processes are not directly responsible for the inhibition of HSV-1 replication by Rep.
A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories

Representation and learning of commonsense knowledge is one of the foundational problems in the quest to enable deep language understanding. This issue is particularly challenging for understanding casual and correlational relationships between events. While this topic has received a lot of interest in the NLP community, research has been hindered by the lack of a proper evaluation framework. This paper attempts to address this problem with a new framework for evaluating story understanding and script learning: the 'Story Cloze Test'. This test requires a system to choose the correct ending to a four-sentence story. We created a new corpus of ~50k five-sentence commonsense stories, ROCStories, to enable this evaluation. This corpus is unique in two ways: (1) it captures a rich set of causal and temporal commonsense relations between daily events, and (2) it is a high quality collection of everyday life stories that can also be used for story generation. Experimental evaluation shows that a host of baselines and state-of-the-art models based on shallow language understanding struggle to achieve a high score on the Story Cloze Test. We discuss these implications for script and story learning, and offer suggestions for deeper language understanding.
The Relationship Between RN Job Satisfaction and Accountability

The purpose of this descriptive correlational secondary data analysis is to describe the relationship between job satisfaction and accountability among registered nurses with clinical responsibilities employed by a rural health care network in the Midwest. The response rate from the primary study is 39%, with 337 RN respondents. The sample for this secondary analysis is 299. The instruments used to measure accountability and job satisfaction are the Specht and Ramler Accountability Index—Individual Referent and the McCloskey—Mueller Satisfaction Scale (MMSS). The results indicate that accountability is perceived to be relatively high and job satisfaction is moderate. Accountability and job satisfaction are significantly correlated at a moderate level. The correlations between the subscales of the MMSS and accountability are all statistically significant but low. The subscales with the highest correlations (e.g., control and responsibility, praise and recognition, professional opportunities, scheduling) provide direction for nurse administrators about important target areas for improvement.
Effects of hearing an incorrect stress on word naming in Dutch by Francophones

In this paper, we investigate the effect of Dutch stress misplacements on the perception and subsequent production by Francophone learners of Dutch in a word naming task. The results suggest that Francophones experience a strong bias towards the final syllable when perceiving Dutch words and producing Dutch stress. Moreover, the results suggest that Francophones are less sensitive to misstressing than natives.
Coordination Breakdowns and Their Impact on Development Productivity and Software Failures

The success of software development projects depends on carefully coordinating the effort of many individuals across the multiple stages of the development process. In software engineering, modularization is the traditional technique intended to reduce the interdependencies among modules that constitute a system. Reducing technical dependencies, the theory argues, results in a reduction of work dependencies between teams developing interdependent modules. Although that research stream has been quite influential, it considers a static view of the problem of coordination in engineering activities. Building on a dynamic view of coordination, we studied the relationship between socio-technical congruence and software quality and development productivity. In order to investigate the generality of our findings, our analyses were performed on two large-scale projects from two companies with distinct characteristics in terms of product and process maturity. Our results revealed that the gaps between coordination requirements and the actual coordination activities carried out by the developers significantly increased software failures. Our analyses also showed that higher levels of congruence are associated with improved development productivity. Finally, our results showed the congruence between dependencies and coordinative actions is critical both in mature development settings as well as in novel and dynamic development contexts.
Inflation Dynamics During the Financial Crisis

Using confidential product-level price data underlying the U.S. Producer Price Index (PPI), this paper analyzes the effect of changes in firms’ financial conditions on their price-setting behavior during the ”Great Recession” that surrounds the financial crisis. The evidence indicates that during the height of the crisis in late 2008, firms with “weak” balance sheets increased prices significantly relative to industry averages, whereas firms with “strong” balance sheets lowered prices, a response consistent with an adverse demand shock. These stark differences in price-setting behavior are consistent with the notion that financial frictions may significantly influence the response of aggregate inflation to macroeconomic shocks. We explore the implications of these empirical findings within a general equilibrium framework that allows for customer markets and departures from the frictionless financial markets. In the model, firms have an incentive to set a low price to invest in market share, though when financial distortions are severe, firms forgo these investment opportunities and maintain high prices in an effort to preserve their balance-sheet capacity. Consistent with our empirical findings, the model with financial distortions—relative to the baseline model without such distortions—implies a substantial attenuation of price dynamics in response to contractionary demand shocks.
Rfid-Enabled Capabilities and their Impact on Healthcare Process Performance

In recent years, hospitals have begun to invest in RFID systems to control costs, reduce errors, and improve quality of care. Despite the transformative impact that RFID may have in healthcare settings, few studies have examined how and why this change may occur. The purpose of this study is to systematically understand how RFID can transform work practices and address cost, safety, and quality of care issues, most notably in inventory management. We leverage a sociomateriality framework to explore the causal linkages that connect the material properties of RFID with the behavioral changes that are observed through its use. By linking the material properties of RFID with innovations in existing practices, we provide a data-driven account of how and why RFID is useful in this setting. In doing so, we also contribute to recent work by IS scholars who argue for a reconfiguration of conventional assumptions regarding the role of technology in contemporary organizations. By adopting this perspective, we recast the issue of whether or not IT matters, and instead offer interesting and useful insight into how and why it does.
N-best error simulation for training spoken dialogue systems

A recent trend in spoken dialogue research is the use of reinforcement learning to train dialogue systems in a simulated environment. Past researchers have shown that the types of errors that are simulated can have a significant effect on simulated dialogue performance. Since modern systems typically receive an N-best list of possible user utterances, it is important to be able to simulate a full N-best list of hypotheses. This paper presents a new method for simulating such errors based on logistic regression, as well as a new method for simulating the structure of N-best lists of semantics and their probabilities, based on the Dirichlet distribution. Off-line evaluations show that the new Dirichlet model results in a much closer match to the receiver operating characteristics (ROC) of the live data. Experiments also show that the logistic model gives confusions that are closer to the type of confusions observed in live situations. The hope is that these new error models will be able to improve the resulting performance of trained dialogue systems.