Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated Detection of Diabetic Retinopathy using a Binocular Siamese-Like Convolutional Network

Diabetic retinopathy (DR) is an important causes of blindness worldwide. It is hard to detected in early stages and the diagnostic procedure can be time-consuming. Therefore, we proposed a deep learning method to automatedly diagnose the referable deiabetic retinopathy (RDR) by classifying retinal fundus photographs. In our work, A novel convolutional neural network with Siamese-like architecture is trained with transfer learning technique. Different from previous works, the proposed model accepts binocular fundus images as input and learns their correlation to aid the prediction. A custom loss function combining cross entropy loss and contrastive loss is also adopted to guide the gradient descent. With a training set of only 28104 images and a test set of 3510 images, an area under the receiver operating curve (AUC) of 0.949 is obtained through the proposed method. Furthermore, the sensitivity reaches 80.7% when the specificity is fixed at 95.0%, and the specificity reaches 70.3% when the sensitivity is fixed at 95.0%, which are 3.2% and 4.6% higher than those obtained by the existing Inception V3 model trained with monocular fundus images, respectively.
Partner Empowerment and Relationship Failure in Franchising

Franchisors must empower franchisees to take decisions on a package of peripheral elements in response to pressure for local adaptations and for entrepreneurial autonomy. However, little is known about which specific elements should be decentralized and to what extent adaptation of such elements affects disputes between franchisor and franchisees. This study explores these issues by analyzing which decision rights should be franchisees’ responsibility to reduce early terminations instigated by the franchisor. The results show that delegating decision rights on local advertising and personnel reduces early terminations while delegation of pricing tends to increase them, regardless of the size of the system. Interestingly, successful delegation in other decision‐areas is contingent on the brand‐name value. More specifically, only larger chains seem to benefit from delegating assortment and decoration decisions.
Ontogenetic Cell Death and Phagocytosis in the Visual System of Vertebrates

Programmed cell death (PCD), together with cell proliferation, cell migration, and cell differentiation, is an essential process during development of the vertebrate nervous system. The visual system has been an excellent model on which to investigate the mechanisms involved in ontogenetic cell death. Several phases of PCD have been reported to occur during visual system ontogeny. During these phases, comparative analyses demonstrate that dying cells show similar but not identical spatiotemporally restricted patterns in different vertebrates. Additionally, the chronotopographical coincidence of PCD with the entry of specialized phagocytes in some regions of the developing vertebrate visual system suggests that factors released from degenerating cells are involved in the cell migration of macrophages and microglial cells. Contradicting this hypothesis however, in many cases the cell corpses generated during degeneration are rapidly phagocytosed by neighboring cells, such as neuroepithelial cells or Müller cells. In this review, we describe the occurrence and the sites of PCD during the morphogenesis and differentiation of the retina and optic pathways of different vertebrates, and discuss the possible relationship between PCD and phagocytes during ontogeny. Developmental Dynamics 243:1203–1225, 2014. © 2014 Wiley Periodicals, Inc.
Estimation of a Censored AIDS Model: A Simulated Amemiya-Tobin Approach

Kuhn-Tucker approach and its dual have been proposed to the demand system estimation when there are non-negativity bindings. However, empirical researchers have been struggling two decades in applying this method into practice due to: (1) the difficulty in derivation of a coherent econometric model, and (2) the cumbersome evaluation of high order probability integrals needed in parameter estimation. In this paper, we avoid the above two issues by using the Amemiya-Tobin demand system approach and the simulation procedure to evaluate the probability integrals. An AIDS model is estimated and the elasticities are obtained that are impossible to achieve when using Kuhn-Tucker approach. The model is applied to an analysis of Canadian household food demand.
A CMOS ultra-wideband impulse generator for 22–29 GHz automotive radar application

This paper presents the design and simulation of a CMOS ultra-wideband pulse generator using IBM 90nm CMOS technology. The operating frequency band of the pulse generator is from 22 to 29 GHz for the application of short-range automotive radar. The pulse generator has a simple architecture using digital circuits. The simulation results show that the power spectral density of the pulse generator has a center frequency of 24.4 GHz and has a -10 dB bandwidth from 22 to 29 GHz.
Will Contextual Factors and Providing the Maximum Price Information Affect People's Actual Willingness-to-Pay in BDM Auctions? Evidence from Three Asian Countries

Abstract: The purpose of this study was to measure the effect of maximum price information and contextual factors on people's bidding behaviors in a controlled Becker-DeGroot-Marschak (BDM) experimental auctions. 354 respondents from three Asian countries (China, Cambodia and the Philippines) participated in this study. In each country, both households with piped water connection and households without piped water connection were investigated. The sample in each country was then randomly assigned to two groups: one group was provided with a maximum price of a water filter and the other group was not provided with the maximum price information. The results show that the treatment group with maximum price information had a higher actual willingness-to-pay than the control group without maximum price information, but they were not significantly different. Our results also indicate that contextual and socioeconomic factors did play a role in participants' bid results for the water filter.
Decision regret following treatment for localized breast cancer: Is regret stable over time?

19 Background: While studies suggest most women have little regret with their breast cancer treatment decisions, few (or no) studies have evaluated whether regret changes over time. METHODS Women diagnosed with breast cancer between August 2005 and May 2007 reported to the Detroit, Michigan, or Los Angeles County Surveillance Epidemiology and End Results (SEER) registry completed surveys at 9 months post diagnosis (time 1) and again approximately 4 years later (time 2). A decision regret scale (Brehaut, 2003) consisting of 5 items was completed at both time points. Item responses were summed to create a regret score at both 9 months and 4 years (scales of 5 to 25 points, with 25 being most regret). We used multivariable linear regression to examine change in regret from 9 months to 4 years. Independent variables included surgery type (breast conserving surgery, unilateral mastectomy, bilateral mastectomy), presence of invasive disease (yes/no), and recurrence status (yes/no) at follow-up. We included an interaction between surgery type and recurrence status. The model controlled for demographic and clinical factors. RESULTS The sample included 1,497 women. Mean decision regret at 9 months was 9.5 points and 10.1 points at 4 years (range 5-25) (NS). Two-thirds (64%) of respondents had breast conserving surgery, 26% had unilateral mastectomy, and 9% had bilateral mastectomy. We found no impact of surgery type on change in regret in the overall sample. However, among the, 86 (6%) women who recurred, those who underwent unilateral mastectomy reported significant reduction in decision regret over time relative to recurrent women who had breast conserving surgery (d= -6.76, p=0.024). Average change in regret among non-recurrent women was 0.52 points and was 2.7 points for women who recurred. CONCLUSIONS Decision regret in breast cancer is generally stable over time, yet changes in regret appear to be associated with disease trajectory and treatment received. Our results suggest that more extensive treatment is associated with a reduction in regret only when women experience a recurrence. Understanding patients' assessment of their decisions related to treatment may be useful for informing future decision making processes.
Relation Between Market Model Prediction Errors And Omitted Variables - A Methodological Note

A number of accounting studies have examined market model prediction errors to evaluate the share price effects of various "events," such as voluntary or mandatory accounting changes. A common approach is to examine the prediction errors around the event date of a portfolio of potentially affected firms. This approach has been extended recently through the use of cross-sectional regressions (e.g., Leftwich [1981], Holthausen [1981], Collins, Rozeff, and Dhaliwal [1981], Sepe [1982], and Chow [1983]) in which prediction errors or raw returns are regressed on firm-specific variables such as size. ' The purpose of this paper is to examine the implications of some recent findings in finance for the various finance-based empirical accounting studies. In general, two types of omitted variables from the standard capital assets pricing model have been identified. First, several studies have reported that certain firm-specific variables such as size (Banz [1981] and Reinganum [1981]), earnings yield (Basu [1975; 1983]), and dividend-payout ratio (Litzenberger and Ramaswamy [1979]) may be omitted variables from the standard CAPM. In addition, other studies have found some special time-series characteristics of stock returns, such
Magnetic Field Sensor Based on PT-Symmetry Structure With Magnetic Resonators

We report a novel magnetic field sensor based on a PT-symmetry structure with the modulation of magnetic resonators giving advantages of high sensitivity, large sensing range, and low equipment expenses. The structure has a unique band-edge mode whose wavelength is very sensitive to the external magnetic field. The band-edge mode can be used to detect magnetic fields. The sensitivity range is 240– $2.435 \times 10^{4}$ nm/Oe, which is larger than those obtained using other approaches by an average of two–six orders of magnitude. The sensing range is 1300–4500 (Oe), which is larger than those of other approaches by an average of two orders of magnitude. The proposed magnetic field sensor is very important for applications requiring extremely higher sensitivities over a wide magnetic field range
Influence of dense‐array EEG cap on fMRI signal

Dense‐array (>64 channel) electroencephalography (EEG) systems are increasingly being used in simultaneous EEG–functional magnetic resonance imaging (fMRI) studies. However, with increasing channel count, dense‐array EEG caps can induce more severe signal dropout in the MRI images than conventional systems due to the radiofrequency shielding effect of the denser wire bundle. This study investigates the influence of a 256‐channel EEG cap on MRI image quality and detection sensitivity of blood oxygen level dependent fMRI signal. A theoretical model is first established to describe the impact of the EEG cap on anatomic signal, noise, signal‐to‐noise ratio, and contrast‐to‐noise ratio of blood oxygen level dependent signal. Seven subjects were scanned to measure and compare the T2*‐weighted image quality and fMRI detection sensitivity with and without the EEG cap using an auditory/visual/sensorimotor task. The results show that the dense‐array EEG cap can substantially reduce the anatomic signal in the brain areas (visual cortex) near the conducting wires (average percent decrease ≈ 38%). However, the image signal‐to‐noise ratio with and without the EEG cap was comparable (percent decrease < 8%, not statistically significant), and there was no statistically significant difference in the extent of blood oxygen level dependent activation. This suggests that the ability to detect fMRI signal is nearly unaffected by dense‐array EEG caps in simultaneous EEG–fMRI experiments. Magn Reson Med, 2012. © 2011 Wiley Periodicals, Inc.
Global Political Economy: Understanding the International Economic Order

This book is the eagerly awaited successor to Robert Gilpin's 1987 The Political Economy of International Relations, the classic statement of the field of international political economy that continues to command the attention of students, researchers, and policymakers. The world economy and political system have changed dramatically since the 1987 book was published. The end of the Cold War has unleashed new economic and political forces, and new regionalisms have emerged. Computing power is increasingly an impetus to the world economy, and technological developments have changed and are changing almost every aspect of contemporary economic affairs. Gilpin's Global Political Economy considers each of these developments. Reflecting a lifetime of scholarship, it offers a masterful survey of the approaches that have been used to understand international economic relations and the problems faced in the new economy. Gilpin focuses on the powerful economic, political, and technological forces that have transformed the world. He gives particular attention to economic globalization, its real and alleged implications for economic affairs, and the degree to which its nature, extent, and significance have been exaggerated and misunderstood. Moreover, he demonstrates that national policies and domestic economies remain the most critical determinants of economic affairs. The book also stresses the importance of economic regionalism, multinational corporations, and financial upheavals. Gilpin integrates economic and political analysis in his discussion of "global political economy. " He employs the conventional theory of international trade, insights from the theory of industrial organization, and endogenous growth theory. In addition, ideas from political science, history, and other disciplines are employed to enrich understanding of the new international economic order. This wide-ranging book is destined to become a landmark in the field.
A Java Implementation of the SGA, UMDA, ECGA, and HBOA

The Simple Genetic Algorithm, the Univariate Marginal Distribution Algorithm, the Extended Compact Genetic Algorithm, and the Hierarchical Bayesian Optimization Algorithm are all well known Evolutionary Algorithms. In this report we present a Java implementation of these four algorithms with detailed instructions on how to use each of them to solve a given set of optimization problems. Additionally, it is explained how to implement and integrate new problems within the provided set. The source and binary files of the Java implementations are available for free download at this https URL
German outbreak of Escherichia coli O104:H4 associated with sprouts.

BACKGROUND A large outbreak of the hemolytic-uremic syndrome caused by Shiga-toxin-producing Escherichia coli O104:H4 occurred in Germany in May 2011. The source of infection was undetermined. METHODS We conducted a matched case-control study and a recipe-based restaurant cohort study, along with environmental, trace-back, and trace-forward investigations, to determine the source of infection. RESULTS The case-control study included 26 case subjects with the hemolytic-uremic syndrome and 81 control subjects. The outbreak of illness was associated with sprout consumption in univariable analysis (matched odds ratio, 5.8; 95% confidence interval [CI], 1.2 to 29) and with sprout and cucumber consumption in multivariable analysis. Among case subjects, 25% reported having eaten sprouts, and 88% reported having eaten cucumbers. The recipe-based study among 10 groups of visitors to restaurant K included 152 persons, among whom bloody diarrhea or diarrhea confirmed to be associated with Shiga-toxin-producing E. coli developed in 31 (20%). Visitors who were served sprouts were significantly more likely to become ill (relative risk, 14.2; 95% CI, 2.6 to ∞). Sprout consumption explained 100% of cases. Trace-back investigation of sprouts from the distributor that supplied restaurant K led to producer A. All 41 case clusters with known trading connections could be explained by producer A. The outbreak strain could not be identified on seeds from the implicated lot. CONCLUSIONS Our investigations identified sprouts as the most likely outbreak vehicle, underlining the need to take into account food items that may be overlooked during subjects' recall of consumption.
Actin‐based motility of intracellular bacteria, and polarized surface distribution of the bacterial effector molecules

Several intracellular bacterial pathogens, including species of Listeria, Rickettsia, Shigella, Mycobacteria, and Burkholderia, have evolved mechanisms to exploit the actin polymerization machinery of their hosts to induce actin‐based motility, enabling these pathogens to spread between host cells without exposing themselves to the extracellular milieu. Efficient cell‐to‐cell spread requires directional motility, which the bacteria may achieve by concentrating the effector molecules at one pole of their cell body, thereby restricting polymerization of monomeric actin into actin tails to this pole. The study of the molecular processes involved in the initiation of actin tail formation at the bacterial surface, and subsequent actin‐based motility, has provided much insight into the pathogenesis of infections caused by these bacteria and into the cell biology of actin dynamics. Concomitantly, this field of research has provided an opportunity to understand the mechanisms whereby bacteria can achieve a polarized distribution of surface proteins. This review will describe the process of actin‐based motility of intracellular bacteria, and the mechanisms by which bacteria can obtain a polarized distribution of their surface proteins. J. Cell. Physiol. 209: 288–296, 2006. © 2006 Wiley‐Liss, Inc.
Sphingolipid Storage Induces Accumulation of Intracellular Cholesterol by Stimulating SREBP-1 Cleavage*

We showed previously that the intracellular transport of sphingolipids (SLs) is altered in SL storage disease fibroblasts, due in part to the secondary accumulation of free cholesterol. In the present study we examined the mechanism of cholesterol elevation in normal human skin fibroblasts induced by treatment with SLs. When cells were incubated with various natural SLs for 44 h, cholesterol levels increased 25–35%, and cholesterol esterification was reduced. Catabolism of the exogenous SLs was not required for elevation of cholesterol because (i) a non-hydrolyzable and a degradable SL analog elevated cellular cholesterol to similar extents, and (ii) incubation of cells with various SL catabolites, including ceramide, had no effect on cholesterol levels. Elevated cholesterol was derived primarily from low density lipoproteins (LDL) and resulted from up-regulation of LDL receptors induced by cleavage of the sterol regulatory element-binding protein-1. Upon SL treatment, cholesterol accumulated with exogenous SLs in late endosomes and lysosomes. These results suggest a model in which excess SLs present in endocytic compartments serve as a “molecular trap” for cholesterol, leading to a reduction in cholesterol at the endoplasmic reticulum, induction of sterol regulatory element-binding protein-1 cleavage, and up-regulation of LDL receptors.
Development and Validation of a Prediction Pneumothorax Model in CT-Guided Transthoracic Needle Biopsy for Solitary Pulmonary Nodule

Computed tomography-guided transthoracic needle biopsy (CT-TNB) is widely used in the diagnosis of solitary pulmonary nodule (SPN). However, CT-TNB-induced pneumothorax occurs frequently. This study aimed to establish a predictive model for pneumothorax following CT-TNB for SPN. The prediction model was developed in a cohort that consisted of 311 patients with SPN who underwent CT-TNB. An independent external validation cohort contained 227 consecutive patients. The least absolute shrinkage and selection operator (Lasso) regression analysis was used for data dimension reduction and predictors selection. Multivariable logistic regression was used to develop the predictive model, which was presented with a nomogram. Area under the curve (AUC) was used to determine the discrimination of the proposed model. The calibration was used to test the goodness-of-fit of the model, and decision curve analysis (DCA) was used for evaluating its clinical usefulness. Five variables (age, diagnosis of nodule, puncture times, puncture distance, and puncture position) were filtered by Lasso regression. AUC of the predictive model and the validation were 0.801 (95% CI, 0.738-0.865) and 0.738 (95% CI, 0.656-0.820), respectively. The model was well-calibrated (P > 0.05), and DCA demonstrated its clinical usefulness. Thus, this predictive model might facilitate the individualized preoperative prediction of pneumothorax in CT-TNB for SPN.
MULTIROBOT MOTION PLANNING USING HYBRID MNHS AND GENETIC ALGORITHMS

Planning the motion of multiple robots deals with computing the motion of all robots avoiding any collision. This article focuses on the use of hybrid Multi Neuron Heuristic Search (MNHS) and Genetic Algorithm (GA). The MNHS is an advancement over the conventional A* algorithm and is better suited for maze-like conditions where there is a high degree of uncertainty. The MNHS contributes toward optimality of the solution, and the GA gives it an iterative nature and enables the approach to be used on high-resolution maps. MNHS works over the set of points returned by the GA in its fitness function evaluation. A priority-based approach is used, in which the priorities are decided by the GA. Path feasibility is speeded up by using the concept of coarser-to-finer lookup called momentum. Experimental results show that the combined approach is able to easily solve the problem for a variety of scenarios. [Supplementary materials are available for this article. Go to the publisher's online edition of Applied Artificial Intelligence for the following free supplemental resource(s): Videos 1-4]
Sequential proton MRS study of brain metabolite changes monitored during a complete pathological cycle of demyelination and remyelination in a lysophosphatidyl choline (LPC)‐induced experimental demyelinating lesion model

Metabolite changes in rat brain internal capsule (ic) area were monitored using volume localized in vivo proton MR spectroscopy (MRS) in a lysophosphatidyl choline (LPC)‐induced experimental demyelinating lesion model of multiple sclerosis (MS), during the early phase (pre‐acute) as well as during the complete pathological cycle of de‐ and re‐myelination processes. The N‐acetyl aspartate (NAA) peak showed reduction during the early phase of the lesion progression (demyelination) until day 10 and increased thereafter during remyelination. However, choline (Cho) and lipid resonances showed increased signal intensity during the early phase and decreased during remyelination. A progressive reduction of the NAA/Cr metabolite ratio in lesioned rats was observed during demyelination (up to day 10) compared with before lesion (control), and the value increased thereafter during remyelination (from day 15). During this period, however, the Cho/Cr ratio was a higher until day 10 and subsequently declined and was close to that calculated before lesion creation. The changes in NAA/Cr and Cho/Cr metabolite ratios correspond to changes in the individual metabolite peaks such as NAA and Cho. The increase in the intensity of the choline resonance during the early phase is indicative of the onset of an inflammatory demyelination process, and its rapid decrease thereafter is due to reduction in the inflammatory process associated with remyelination. Similarly, the increase in the intensity of lipids during the pre‐acute stage of the lesion is attributed to active demyelination, which significantly decreased during remyelination. These MR results correlate well with the histology data obtained. Copyright © 2002 John Wiley & Sons, Ltd.