LLukas22/scidocs huggingface dataset:
Macroeconomic Risk and Debt Overhang ∗

Since debt is typically riskier in recessions, transfers from equity holders to debt holders associated with each investment also tend to concentrate in recessions. Such systematic risk exposure of debt overhang has important implications for the investment and financing decisions of firms and on the ex ante costs of debt overhang. Using a calibrated dynamic capital structure/real option model, we show that the costs of debt overhang become significantly higher in the presence of macroeconomic risk. We also provide several new predictions that relate the cyclicality of a firm’s assets in place and growth options to its investment and capital structure decisions. We are grateful to Santiago Bazdresch, Bob Goldstein, David Mauer (WFA discussant), Erwan Morellec, Stew Myers, Chris Parsons, Michael Roberts, Antoinette Schoar, Neng Wang, Ivo Welch, and seminar participants at MIT, Federal Reserve Bank of Boston, Boston University, Dartmouth, University of Lausanne, University of Minnesota, the Third Risk Management Conference at Mont Tremblant, the Minnesota Corporate Finance Conference, and the WFA for their comments. MIT Sloan School of Management and NBER. Email: huichen@mit.edu. Tel. 617-324-3896. MIT Sloan School of Management. Email: manso@mit.edu. Tel. 617-253-7218.
Dilemma in Differentiating between Acute Osteomyelitis and Bone Infarction in Children with Sickle Cell Disease: The Role of Ultrasound

BACKGROUND
Distinguishing between acute presentations of osteomyelitis (OM) and vaso-occlusive crisis (VOC) bone infarction in children with sickle cell disease (SCD) remains challenging for clinicians, particularly in culture-negative cases. We examined the combined role of ultrasound scan (USS), C - reactive protein and White blood counts (WCC) in aiding early diagnosis in children with SCD presenting acutely with non-specific symptoms such as bone pain, fever or swelling which are common in acute osteomyelitis or VOC.


METHODS
We reviewed the records of all children with SCD who were discharged from our department from October 2003 to December 2010 with a diagnosis of osteomyelitis based on clinical features and the results of radiological and laboratory investigations. A case control group with VOC who were investigated for OM were identified over the same period.


RESULTS
In the osteomyelitis group, USS finding of periosteal elevation and/or fluid collection was reported in 76% cases with the first scan (day 0-6). Overall 84% were diagnosed with USS (initial +repeat). 16% had negative USS. With VOC group, USS showed no evidence of fluid collection in 53/58 admissions (91%), none of the repeated USS showed any fluid collection. Mean C-reactive protein (CRP), and white cell count (WCC) were significantly higher in the OM.


CONCLUSION
The use of Ultrasound in combination with CRP and WCC is a reliable, cost-effective diagnostic tool for differentiating osteomyelitis from VOC bone infarction in SCD. A repeat ultrasound and/or magnetic resonance imaging (MRI) scan may be is necessary to confirm the diagnosis.
1 An Introduction to Conditional Random Fields for Relational Learning

1.1 Introduction Relational data has two characteristics: first, statistical dependencies exist between the entities we wish to model, and second, each entity often has a rich set of features that can aid classification. For example, when classifying Web documents, the page's text provides much information about the class label, but hyperlinks define a relationship between pages that can improve classification [Taskar et al., 2002]. Graphical models are a natural formalism for exploiting the dependence structure among entities. Traditionally, graphical models have been used to represent the joint probability distribution p(y, x), where the variables y represent the attributes of the entities that we wish to predict, and the input variables x represent our observed knowledge about the entities. But modeling the joint distribution can lead to difficulties when using the rich local features that can occur in relational data, because it requires modeling the distribution p(x), which can include complex dependencies. Modeling these dependencies among inputs can lead to intractable models, but ignoring them can lead to reduced performance. A solution to this problem is to directly model the conditional distribution p(y|x), which is sufficient for classification. This is the approach taken by conditional random fields [Lafferty et al., 2001]. A conditional random field is simply a conditional distribution p(y|x) with an associated graphical structure. Because the model is
Lung ultrasound characteristics of community-acquired pneumonia in hospitalized children.

BACKGROUND
The diagnosis of community-acquired pneumonia (CAP) is based mainly on the patient's medical history and physical examination. However, in severe cases a further evaluation including chest X-ray (CXR) may be necessary. At present, lung ultrasound (LUS) is not included in the diagnostic work-up of pneumonia.


AIM
To describe the ultrasonographic appearance of CAP at presentation and during the follow-up.


METHODS
A total of 102 patients with clinical signs and symptoms suggesting pneumonia, who underwent a clinically driven CXR, were evaluated by LUS on the same day. LUS signs of pneumonia included subpleural lung consolidation, B-lines, pleural line abnormalities, and pleural effusion. The diagnostic gold standard was the ex-post diagnosis of pneumonia made by two independent experienced pediatricians on the basis of clinical presentation, CXR and clinical course following British Thoracic Guidelines recommendations.


RESULTS
A final diagnosis of pneumonia was confirmed in 89/102 patients. LUS was positive for the diagnosis of pneumonia in 88/89 patients, whereas CXR was positive in 81/89. Only one patient with normal LUS examination had an abnormal CXR, whereas 8 patients with normal CXR had an abnormal LUS. LUS was able to detect pleural effusion resulting from complicated pneumonia in 16 cases, whereas CXR detected pleural effusion in 3 cases.


CONCLUSIONS
LUS is a simple and reliable imaging tool, not inferior to CXR in identifying pleuro-pulmonary alterations in children with suspected pneumonia. During the course of the disease, LUS allows a radiation-free follow-up of these abnormalities.
The self-tuning PID control in a slider–crank mechanism system by applying particle swarm optimization approach

By using the particle swarm optimization (PSO) algorithm, a novel design method for the self-tuning PID control in a slider–crank mechanism system is presented in this paper. This paper demonstrates, in detail, how to employ the PSO so as to search efficiently for the optimal PID controller parameters within a mechanism system. The proposed approach has superior features, including: easy implementation; stable convergence characteristics; and good computational efficiency. Fast tuning of optimum PID controller parameters yields high-quality solutions. By using the PSO approach, both the initial PID parameters under normal operating conditions and the optimal parameters of PID control under fully-loaded conditions can be determined. The proposed self-tuning PID controller will automatically tune its parameters within these ranges. Moreover, the PC-based controller is implemented to control the position of the motor-mechanism coupling system. In order to prove the performance of the proposed PSO self-tuning PID controller, the responses are compared with those by the real-coded genetic algorithm (RGA) PID controller and the fixed PID controller. The numerical simulations and experimental results will show the potential of the proposed controller. 2006 Elsevier Ltd. All rights reserved.
Flow-diverter silk stent for the treatment of intracranial aneurysms: 1-year follow-up in a multicenter study.

BACKGROUND AND PURPOSE
FD stent placement is a promising therapy for challenging intracranial aneurysms. Long-term evaluations about angiographic and morphologic results are still missing. This is the aim of this multicenter series.


MATERIALS AND METHODS
We report our experience and 1-year FU in a retrospective chart review of 65 consecutive subjects with 77 unruptured or recanalized aneurysms that were treated with Silk FD stents at 6 centers in France. Both angiographic and clinical results were recorded before treatment and at 6 and 12 months after treatment. At the 12-month FU, relationships between angiographic aneurysm occlusion and shrinkage of the thrombosed aneurysm sac were evaluated.


RESULTS
Stent deployment was achieved in 64 cases (98.5%) and failed in 1 case (1.5%). Seven misdeployments of the Silk stent caused the occlusion of 6 parent arteries. Overall acute/subacute procedural morbidity was 7.7%, and mortality was zero. Delayed complications were observed in 10.9% of subjects. At the 6-month FU, permanent morbidity was 7.8% and mortality was 3%. Complete occlusion occurred within 6 months in 68% of aneurysms and within 12 months after treatment in 84.5% of aneurysms. At the 12-month FU, in angiographically complete occluded aneurysms, MR imaging/CT analysis showed the complete disappearance of the thrombosed aneurysm in 30% of cases and partial shrinkage in 52%; furthermore, thrombosed aneurysms were stable in 11% of cases and enlarged in 7%.


CONCLUSIONS
The Silk stent is an effective tool for the treatment of challenging aneurysms because it allows complete occlusion in most cases 1 year after treatment. Permanent morbidity was 7.8%, and mortality was 3%.
Dose-associated changes in safety and efficacy parameters observed in a 24-week maintenance trial of olanzapine long-acting injection in patients with schizophrenia

BACKGROUND
In a recently published 24-week maintenance study of olanzapine long-acting injection (LAI) in schizophrenia (Kane et al., 2010), apparent dose-associated changes were noted in both efficacy and safety parameters. To help clinicians balance safety and efficacy when choosing a dose of olanzapine LAI, we further studied these changes.


METHODS
Outpatients with schizophrenia who had maintained stability on open-label oral olanzapine for 4 to 8 weeks were randomly assigned to "low" (150 mg/2 weeks; N = 140), "medium" (405 mg/4 weeks; N = 318), or "high" (300 mg/2 weeks; N = 141) dosages of olanzapine LAI for 24 weeks. Potential relationships between dose and several safety or efficacy measures were examined via regression analysis, the Jonckheere-Terpstra test (continuous data), or the Cochran-Armitage test (categorical data).


RESULTS
Safety parameters statistically significantly related to dose were mean weight change (low: +0.67 [SD = 4.38], medium: +0.89 [SD = 3.87], high: +1.70 [SD = 4.14] kg, p = .024; effect size [ES] = 0.264 high vs. low dose), mean change in prolactin (low: -5.61 [SD = 12.49], medium: -2.76 [SD = 19.02]), high: +3.58 [SD = 33.78] μg/L, p = .001; ES = 0.410 high vs. low dose), fasting triglycerides change from normal at baseline to high (low: 3.2%, medium: 6.0%, high: 18.9%, p = .001; NNT = 7 high vs. low dose) and fasting high-density lipoprotein cholesterol change from normal at baseline to low (low: 13.8%, medium: 19.6%, high: 30.7%, p = .019; NNT = 6 high vs. low dose). Efficacy measures significantly related to dose included Positive and Negative Syndrome Scale total score mean change (low: +2.66 [SD = 14.95], medium: -0.09 [SD = 13.47], high: -2.19 [SD = 13.11], p <.01; ES = 0.356 high vs. low dose), relapse rate (low: 16%, medium: 10%, high: 5%, p = .003; NNT = 9 high vs. low dose), all-cause discontinuation rate (low: 36%, medium: 30%, high: 24%, p = .037; NNT = 9 high vs. low dose), and rate of discontinuation due to efficacy-related reasons (low: 20%, medium: 14%, high: 6%, p <.001). Time to all-cause discontinuation (p = .035) and time to relapse (p = .005) were also significantly related to dose.


CONCLUSIONS
Analyses of several safety and efficacy parameters revealed significant associations with dose of olanzapine LAI, with the highest dose generally showing greater efficacy as well as greater adverse changes in metabolic safety measures. When considering olanzapine LAI, as with all antipsychotics, it is important to carefully consider the potential benefits and risks for an individual patient.


TRIAL REGISTRATION
ClinicalTrials.gov: NCT00088491.
Williams syndrome: cognition, personality, and adaptive behavior.

Williams syndrome is caused by a microdeletion of at least 16 genes on chromosome 7q11.23. The syndrome results in mild to moderate mental retardation or learning disability. The behavioral phenotype for Williams syndrome is characterized by a distinctive cognitive profile and an unusual personality profile. Relative to overall level of intellectual ability, individuals with Williams syndrome typically show a clear strength in auditory rote memory, a strength in language, and an extreme weakness in visuospatial construction. The personality of individuals with Williams syndrome involves high sociability, overfriendliness, and empathy, with an undercurrent of anxiety related to social situations. The adaptive behavior profile for Williams syndrome involves clear strength in socialization skills (especially interpersonal skills related to initiating social interaction), strength in communication, and clear weakness in daily living skills and motor skills, relative to overall level of adaptive behavior functioning. Literature relevant to each of the components of the Williams syndrome behavioral phenotype is reviewed, including operationalizations of the Williams syndrome cognitive profile and the Williams syndrome personality profile. The sensitivity and specificity of these profiles for Williams syndrome, relative to individuals with other syndromes or mental retardation or borderline normal intelligence of unknown etiology, is considered. The adaptive behavior profile is discussed in relation to the cognitive and personality profiles. The importance of operationalizations of crucial components of the behavioral phenotype for the study of genotype/phenotype correlations in Williams syndrome is stressed. MRDD Research Reviews 2000;6:148-158.
Three-dimensional finite element analysis of cartilaginous tissues in human temporomandibular joint during prolonged clenching.

OBJECTIVE
Bruxism, the parafunctional habit of nocturnal grinding of the teeth and clenching, is associated with the onset of joint degeneration. Especially prolonged clenching is suggested to cause functional overloading in the temporomandibular joint (TMJ). In this study, the distributions of stresses in the cartilaginous TMJ disc and articular cartilage, were analysed during prolonged clenching. The purpose of this study was to examine if joint degradation due to prolonged clenching can be attributed to changes in stress concentration in the cartilaginous tissues.


DESIGN
Finite element model was developed on the basis of magnetic resonance images from a healthy volunteer. Condylar movements recorded during prolonged clenching were used as the loading condition for stress analysis.


RESULTS
At the onset of clenching (time=0s), the highest von Mises stresses were located in the middle and posterior areas (6.18MPa) of the inferior disc surface facing the condylar cartilage. The largest magnitude of the minimum principal stress (-6.72MPa) was found in the condylar cartilage. The stress concentrations were relieved towards the superior disc surface facing the temporal cartilage. On the surfaces of the temporal cartilage, relatively lower stresses were found. After 5-min clenching, both stress values induced in the TMJ components were reduced to 50-80% of the stress values at the onset of clenching, although the concomitant strains increased slightly during this period.


CONCLUSIONS
It is suggested that both the condylar and temporal cartilage layers along with the TMJ disc, play an important role in stress distribution and transmission during prolonged clenching due to tissue expansion. Furthermore, our study suggests that a development of stress concentrations in the TMJ during prolonged clenching and risk factors for the initiation of TMJ degeneration could not be confirmed.
Fitting single-cell models to voltage- and current-clamp data: Bayesian filtering

We have incorporated into the NEURON simulation environment parameter estimation by maximizing the log-likelihood function. For linear models, we use an optimal Bayesian filter, the Kalman filter [1], to compute the log-likelihood. For non-linear models, likelihood cannot be computed exactly and we have explored several approximate Bayesian filters including an extended Kalman filter [1] and a particle filter [1]. Bayesian filtering iteratively implements two steps for each data point: prediction and update. The first step uses the model to predict the state of the cell at the next time data is collected. The second step updates the prediction based on the new data point. Even when the model is deterministic, both the “predicted state” and the “updated state” are actually joint distributions for all components of state, even hidden components that are not measured. To give a deterministic model a probabilistic structure, we add Gaussian white noise to one or more of its states. The update step implements Bayes Rule to force the model to better follow the data. Bayes rule selects the optimal tradeoff between measurement noise and process noise. It is assumed by the method that it is actually the noise that forces the model; the log-likelihoods of the required noise are tallied. A graphical interface allows the user to obtain an intuitive understanding of how the standard deviations of the state estimates propagate and are modified by Bayes rule forcing the model to follow the data. The likelihood can be used to generate 95% confidence regions for the parameters using the chi-squared statistic [2]. We test the validity of this construction using simulated data where 95% of the confidence regions drawn should cover the true values of the parameters. We similarly test the validity of our confidence regions under the often inevitable situation that the model being fitted has been misspecified. Finally we compare the log-likelihood objective function with the square norm objective function in terms of location of minima and the efficiency of search methods such as Praxis in finding the minima when starting from reasonable parameter values that are not close to their true value.
Treatment of angiokeratoma of Fordyce with long-pulse neodymium-doped yttrium aluminium garnet laser.

BACKGROUND
Angiokeratomas are typically asymptomatic, blue-to-red papules with a scaly surface located on the scrotum, shaft of penis, labia majora, inner thigh, or lower abdomen. The treatment of angiokeratomas may be necessary if they bleed and lead to patient anxiety.


OBJECTIVE
To determine the safety and effectiveness of long-pulse 1,064 neodymium-doped yttrium aluminium garnet (Nd:YAG) laser for the treatment of angiokeratomas of Fordyce.


MATERIALS AND METHODS
Ten consecutive patients with angiokeratoma of Fordyce were treated with long-pulse Nd:YAG laser in two to six sessions. The three authors independently assessed improvement of the lesion based on digital photographs taken before the treatment and 2 months after the end of the treatment.


RESULTS
Significant (>75%, <100%) and moderate (>50%, <75%) improvement was seen in six and two patients, respectively. Complete improvement was achieved in one patient. Transient swelling, purpura, bleeding, and some pain in the treated area were noted in all patients as short-term side effects. There were no permanent side effects.


CONCLUSION
The long-pulse Nd:YAG laser is a highly effective and safe treatment for angiokeratoma of Fordyce.
Research Paper: Development and Psychometric Evaluation of the Impact of Health Information Technology (I-HIT) Scale

OBJECTIVE
The use of health information technology (HIT) for the support of communication processes and data and information access in acute care settings is a relatively new phenomenon. A means of evaluating the impact of HIT in hospital settings is needed. The purpose of this research was to design and psychometrically evaluate the Impact of Health Information Technology scale (I-HIT). I-HIT was designed to measure the perception of nurses regarding the ways in which HIT influences interdisciplinary communication and workflow patterns and nurses' satisfaction with HIT applications and tools.


DESIGN
Content for a 43-item tool was derived from the literature, and supported theoretically by the Coiera model and by nurse informaticists. Internal consistency reliability analysis using Cronbach's alpha was conducted on the 43-item scale to initiate the item reduction process. Items with an item total correlation of less than 0.35 were removed, leaving a total of 29 items.


MEASUREMENTS
Item analysis, exploratory principal component analysis and internal consistency reliability using Cronbach's alpha were used to confirm the 29-item scale.


RESULTS
Principal components analysis with Varimax rotation produced a four-factor solution that explained 58.5% of total variance (general advantages, information tools to support information needs, information tools to support communication needs, and workflow implications). Internal consistency of the total scale was 0.95 and ranged from 0.80-0.89 for four subscales.


CONCLUSION
I-HIT demonstrated psychometric adequacy and is recommended to measure the impact of HIT on nursing practice in acute care settings.
Solving parity-N problems with feedforward neural networks

Several neural network architectures for computing parity problems are described. Feedforward networks with one hidden layer require N neurons in the hidden layer. If fully connected feedforward networks are considered, the number of neurons in the hidden layer is reduced to N/2. In the case of fully connected networks with neurons connected in cascade, the minimum number of hidden neurons is between log2(N+1)-1 and log2(N+1). This paper also describes hybrid neuron architectures with linear and threshold-like activation functions. These hybrid architectures require the least number of weights. The described architectures are suitable for hardware implementation since the majority of weights equal +1 and weight multiplication is not required. The simplest network structures are pipeline architectures where all neurons and their weights are identical. All presented architectures and equations were verified with MATLAB code for parity-N problems as large as N=100.