Miracle-dz/UniFAR-FTUs huggingface dataset:
Price Discrimination along Multiple Dimensions: Theory and New Evidence∗

This paper examines firms that simultaneously practice quality-based and inter-temporal price discrimination. A model establishes conditions under which these can operate in the same, or opposite, direction, depending on the arrival rate of various consumer types. New data provided by a regional airline reveal that, in some markets, the quality premium increases with inter-temporal price discrimination but the opposite is true in others. New survey data illustrate how the result is driven by differences in the motivation and characteristics of travelers in each market, which fully reconciles both the predictions of the model and the empirical results. ∗I thank Gaurab Aryal, Nate Baum-Snow, Rob Clark, Ricard Gil, Julie Mortimer, Eugene Orlov, Claudio Piga, Steve Puller, Henry Schneider and Alan Sorensen for helpful suggestions. I am especially grateful to Jim Dana for very useful discussions and insights. This research is funded by a SSHRC Insight Grant. †Department of Management, University of Toronto at Scarborough and Rotman School of Management, 105 St. George Street, Toronto, Ontario, M5S 3E6, Canada. Email: ambarishchandra@gmail.com
THE NEGLECTED PIECE OF HEALTH IT ASSIMILATION: UNVEILING THE LEARNING TRAJECTORIES OF ROTATING PHYSICIANS

Job rotation is a necessary and an important part of physician medical training. As the use of HIT becomes a central part of physician work, it is imperative to understand how job rotation can affect the assimilation of HIT for physicians and healthcare organizations. Using situational learning lens to analyze the job rotation experiences of Junior Physicians in a hospital, this study identifies the different forms of situated learning that occurs during system assimilation at the individual and organizational level and the different assimilation outcomes are associated with different forms of situated learning. We conducted an interpretive case study among rotating physicians in a public hospital and identified five types of individual/organizational level learning trajectories. This paper contributes to the existing knowledge of IS assimilation by exploring the relationship between cross-organizational job rotation and the success of HIT assimilation in hospitals.
MCT FIRST DISCLOSURES ANovel Brain-Permeant ChemotherapeuticAgent for the Treatment of Brain Metastasis in Triple-Negative Breast Cancer

Development ofmetastases to central nervous system (CNS) is an increasing clinical issue following the diagnosis of advanced breast cancer. The propensity tometastasize toCNS varies by breast cancer subtype. Of the four breast cancer subtypes, triple-negative breast cancers (TNBC) have the highest rates of both parenchymal brain metastasis and leptomeningeal metastasis (LM). LM is rapidly fatal due to poor detection and limited therapeutic options. Therapy of TNBC brain metastasis and LM is challenged by multifocal brain metastasis and diffuse spread of LM, and must balance brain penetration, tumor cytotoxicity, and the avoidance of neurotoxicity. Thus, there is an urgent need for novel therapeutic options in TNBCs CNS metastasis. QBS10072S is a novel chemotherapeutic that leverages TNBC-specific defects in DNA repair and LAT1 (Lamino acid transporter type 1)-dependent transport into the brain. In our study, activity of QBS10072S was investigated in vitro with various cell lines including the human TNBC cell line MDA-MB231 and its brain-tropic derivativeMDA-MB-231-BR3. QBS10072S was preferentially toxic to TNBC cells. The efficacy of QBS10072S against brain metastasis and LM was tested using a model of brain metastasis based on the internal carotid injection of luciferaseexpressing tumor cells into NuNu mice. The compound was well tolerated, delayed tumor growth and reduced leptomeningeal dissemination, resulting in significant extension of survival. Given that current treatments for LM are palliative with only few studies reporting a survival benefit, QBS10072S is planned to be investigated in clinical trials as a therapeutic for TNBC LM.
Decrease in sleep depth is associated with higher cerebrospinal fluid neurofilament light levels in patients with Alzheimer’s disease

There was a positive correlation between neurofilament light (NF-L) and the time spent in stage 1 of non-rapid eyes movement (NREM) (N1) sleep and a negative correlation between this marker and the time spent in stage 3 of NREM (N3) sleep. Accordingly, we observed that deep sleep was associated with lower levels of NF-L, whereas light sleep increased the probability of having higher levels of this marker. Furthermore, chitinase-3-like-1 (YKL-40) was negatively correlated with sleep efficiency, the time spent in stage 2 of NREM (N2) sleep, and the time spent in N3 sleep. Conversely, there was a positive correlation between N3 sleep and the oxidative protein damage markers N-ε(carboxyethyl)lysine and N-ε-(malondialdehyde)lysine.
Mapping the Central 108 Visual Field to the Optic Nerve Head Using the Structure–Function Relationship

Yuri Fujino, Hiroshi Murata, Masato Matsuura, Mieko Yanagisawa, Nobuyuki Shoji, Kenji Inoue, Junkichi Yamagami, and Ryo Asaoka Department of Ophthalmology, The University of Tokyo, Tokyo, Japan Department of Ophthalmology, Kitasato University, Graduate School of Medical Sciences, Kanagawa, Japan Department of Ophthalmology, Kitasato University, School of Medicine, Kanagawa, Japan Inouye Eye Hospital, Tokyo, Japan JR Tokyo General Hospital, Tokyo, Japan
Not All Operations Contribute Equally: Hierarchical Operation-adaptive Predictor for Neural Architecture Search

Graph-based predictors have recently shown promising results on neural architecture search (NAS). Despite their efficiency, current graph-based predictors treat all operations equally, resulting in biased topological knowledge of cell architectures. Intuitively, not all operations are equally significant during forwarding propagation when aggregating information from these operations to another operation. To address the above issue, we propose a Hierarchical Operation-adaptive Predictor (HOP) for NAS. HOP contains an operation-adaptive attention module (OAM) to capture the diverse knowledge between operations by learning the relative significance of operations in cell architectures during aggregation over iterations. In addition, a cell-hierarchical gated module (CGM) further refines and enriches the obtained topological knowledge of cell architectures, by integrating cell information from each iteration of OAM. The experimental results compared with state-of-the-art predictors demonstrate the capability of our proposed HOP.
Study the Relationship Between Obesity and Fertility in Diabetic Iraqi Men ٌزنسىا ءاذت ُِتاصَىا ُُِقازعىا هاخزىا ذْع باصخلااو حَْسىا ُِت حقلاعىا حسارد

The aim of the present study is to investigate the relationship between obesity and fertility in Iraqi diabetic men whose body mass index (BMI) more than 25Kg/m 2 , and compare the results with control group corresponding age and BMI. Forty samples of men semen's were divided into two groups with and without diabetes and each group subdivided into two subgroups according to BMI. The parameters that measured in this study are( glucose, insulin and lipid profile in fasting state) also (testosterone, prolactin, alkaline phosphatase) were measured for each of four subgroups [controls(I, II) and diabetes(III, IV)]. Semen's analysis included (sperm concentration in ml, total count per ejaculate and viability). In diabetic subgroup (III) the mean levels of fasting blood glucose, insulin, cholesterol and triglycerides were significantly elevated, while significantly decrease in testosterone, prolactin, high density lipoproteinscholesterol, alkaline phosphatase and total sperm count but there were no significant difference in total cholesterol, the sperm concentration and viability as compared with control subgroup(I). In diabetic subgroup (IV) the mean levels of fasting blood (glucose, insulin, cholesterol and triglycerides) were significantly elevated, while significantly decrease in (testosterone, prolactin, high density lipoproteinscholesterol, alkaline phosphatase, sperm concentration, viability and total sperm count) but there were no significant difference in fasting (insulin and high density lipoproteinscholesterol) as compared with control subgroup(II). In diabetic subgroup(III) the mean of BMI and the mean levels of fasting blood (glucose, total cholesterol and triglycerides) significantly elevated, while there were significantly decrease in(testosterone, alkaline phosphatase, sperm concentration, viability and total sperm count but there were no significant difference in fasting (insulin, high density lipoproteinscholesterol) and prolactin, as compared with diabetic subgroup(IV). For all the above biochemical parameters investigated we can conclude that there is inverserelationship between obesity and fertility which increase in the presence of diabetes.
DNA Methylation scores augment 10-year risk prediction of diabetes

Type 2 diabetes mellitus (T2D) is one of the most prevalent diseases in the world and presents a major health and economic burden, a notable proportion of which could be alleviated with improved early prediction and intervention. While standard risk factors including age, obesity, and hypertension have shown good predictive performance, we show that the use of CpG DNA methylation information leads to a significant improvement in the prediction of 10-year T2D incidence risk. Whilst previous studies have been largely constrained by linear assumptions and the use of CpGs one-at-the-time, we have adopted a more flexible approach based on a range of linear and tree-ensemble models for classification and time-to-event prediction. Using the Generation Scotland cohort (n=9,537) our best performing model (Area Under the Curve (AUC)=0.880, Precision Recall AUC (PRAUC)=0.539, McFadden's R2=0.316) used a LASSO Cox proportional-hazards predictor and showed notable improvement in onset prediction, above and beyond standard risk factors (AUC=0.860, PRAUC=0.444 R2=0.261). Replication of the main finding was observed in an external test dataset (the German-based KORA study, p=3.7x10-4). Tree-ensemble methods provided comparable performance and future improvements to these models are discussed. Finally, we introduce MethylPipeR, an R package with accompanying user interface, for systematic and reproducible development of complex trait and incident disease predictors. While MethylPipeR was applied to incident T2D prediction with DNA methylation in our experiments, the package is designed for generalised development of predictive models and is applicable to a wide range of omics data and target traits.
The tapered slot antenna-a new integrated element for millimeter-wave applications

Tapered slot antennas (TSAs) with a number of potential applications as single elements and focal plane arrays are discussed. TSAs are fabricated with photolithographic techniques and integrated in either hybrid or MMIC circuits with receiver or transmitter components. They offer considerably narrower beams than other integrated antenna elements and have high aperture efficiency and packing density as array elements. Both the circuit and radiation properties of TSAs are reviewed. Topics covered include: antenna beamwidth, directivity, and gain of single-element TSAs; their beam shape and the effect of different taper shapes; and the input impedance and the effects of using thick dielectrics. These characteristics are also given for TSA arrays as are the circuit properties of the array elements. Different array structures and their applications are also described. >
Cutoff Frequencies of Eccentric Waveguides

This paper discusses the uniform cylindrical waveguide formed by placing one conductor inside a conducting tube. Because of the complexity of the guide's cross section, the numerical technique of the point-matching method is adopted to solve the boundary-value problem. The formulations are carried out for the case when each of the conductors has an arbitrary cross section and also for the case when one of the conductors has a circular cross section. The coaxial waveguide modes, in which the field components have angular variations, split into odd and even modes when the center conductor begins to shift axis to form the uniform eccentric waveguide. However, only even modes in the eccentric guide correspond to the coaxial modes with no angular variations. The dependence of the cutoff frequency on the eccentricity of the guide is determined numerically for even and odd TE and TM modes. Experimental results verify the theoretical calculations for TE modes.
Constraint-based Diversification of JOP Gadgets

Modern software deployment process produces software that is uniform, and hence vulnerable to large-scale code-reuse attacks, such as Jump-Oriented Programming (JOP) attacks. Compiler-based diversification improves the resilience and security of software systems by automatically generating different assembly code versions of a given program. Existing techniques are efficient but do not have a precise control over the quality, such as the code size or speed, of the generated code variants. This paper introduces Diversity by Construction (DivCon), a constraint-based compiler approach to software diversification. Unlike previous approaches, DivCon allows users to control and adjust the conflicting goals of diversity and code quality. A key enabler is the use of Large Neighborhood Search (LNS) to generate highly diverse assembly code efficiently. For larger problems, we propose a combination of LNS with a structural decomposition of the problem. To further improve the diversification efficiency of DivCon against JOP attacks, we propose an application-specific distance measure tailored to the characteristics of JOP attacks. We evaluate DivCon with 20 functions from a popular benchmark suite for embedded systems. These experiments show that DivCon's combination of LNS and our application-specific distance measure generates binary programs that are highly resilient against JOP attacks (they share between 0.15% to 8% of JOP gadgets) with an optimality gap of 10%. Our results confirm that there is a trade-off between the quality of each assembly code version and the diversity of the entire pool of versions. In particular, the experiments show that DivCon is able to generate binary programs that share a very small number of gadgets, while delivering near-optimal code. For constraint programming researchers and practitioners, this paper demonstrates that LNS is a valuable technique for finding diverse solutions. For security researchers and software engineers, DivCon extends the scope of compiler-based diversification to performance-critical and resource-constrained applications.
The effect of contact opening velocity and the moment of contact opening on the AC erosion of Ag/CdO contacts

This paper presents experimental results on the influence of contact opening velocity and the moment of contact opening with respect to the start of the AC current cycle on arc energy and contact erosion when breaking an AC resistive circuit. The test currents are 5.6 A, 14.7 A and 26.3 A, and the contact material is Ag/CdO (90/10). A computer controlled test system allows the control of the contact velocity profiles with constant velocities up to 0.8 m/s, and also enables the synchronization of the contact opening with a point on the AC current waveform. Contact erosion is evaluated by measuring the mass loss or gain changes of the cathode and anode. The results show that increasing the contact velocity from 0.1 m/s to 0.8 m/s leads to the increase of the arc energy. The material transfer from one electrode to another is shown to depend on the current, the polarity of the moving contact, the moment of the contact opening with respect to the start of the AC current cycle, and the opening velocity of the contacts.
Fooling Adversarial Training with Inducing Noise

Adversarial training is widely believed to be a reliable approach to improve model robustness against adversarial attack. However, in this paper, we show that when trained on one type of poisoned data, adversarial training can also be fooled to have catastrophic behavior, e.g., $<1\%$ robust test accuracy with $>90\%$ robust training accuracy on CIFAR-10 dataset. Previously, there are other types of noise poisoned in the training data that have successfully fooled standard training ($15.8\%$ standard test accuracy with $99.9\%$ standard training accuracy on CIFAR-10 dataset), but their poisonings can be easily removed when adopting adversarial training. Therefore, we aim to design a new type of inducing noise, named ADVIN, which is an irremovable poisoning of training data. ADVIN can not only degrade the robustness of adversarial training by a large margin, for example, from $51.7\%$ to $0.57\%$ on CIFAR-10 dataset, but also be effective for fooling standard training ($13.1\%$ standard test accuracy with $100\%$ standard training accuracy). Additionally, ADVIN can be applied to preventing personal data (like selfies) from being exploited without authorization under whether standard or adversarial training.
FATIGUE RESPONSE OF CONCRETE DECKS REINFORCED WITH FRP REBARS

The fatigue response of concrete decks reinforced with fiber-reinforced plastic (FRP) bars is critical to the long-term endurance of this type of innovative structure. To evaluate the degradation of FRP reinforced bridge decks, fatigue tests were conducted on four concrete deck steel stringers. An initial stress range of 2.27 MPa (0.33 ksi) (tension) in the main FRP reinforcement, 3.1 MPa (0.45 ksi) (compressive) in the concrete deck top, and 24.8 MPa (3.6 ksi) (tension) at the bottom flange of a steel stringer was applied for all specimens. The stringer stiffness, composite versus noncomposite casting, and transverse posttensioning using high-strength Dywidag steel rods were varied during this research. The fatigue test results showed no loss of bond between FRP rebars and concrete in any of the test specimens. The major crack patterns were in the direction parallel to the stringers, i.e., flexural cracks in the concrete deck spanning the steel stringers. Effective central deck deflections could be set as a measure of global deck degradation during fatigue, and this rate of degradation in decks reinforced with FRP rebars was found comparable to decks reinforced with steel rebars.
Pricing S&P 500 Index Options with L\'evy Jumps

We analyze various jumps for Heston model, non-IID model and three L\'evy jump models for S&P 500 index options. The L\'evy jump for the S&P 500 index options is inevitable from empirical studies. We estimate parameters from in-sample pricing through SSE for the BS, SV, SVJ, non-IID and L\'evy (GH, NIG, CGMY) models by the method of Bakshi et al. (1997), and utilize them for out-of-sample pricing and compare these models. The sensitivities of the call option pricing for the L\'evy models with respect to parameters are presented. Empirically, we show that the NIG model, SV and SVJ models with estimated volatilities outperform other models for both in-sample and out-of-sample periods. Using the in-sample optimized parameters, we find that the NIG model has the least SSE and outperforms the rest models on one-day prediction.
Learning Robotic Manipulation Tasks via Task Progress Based Gaussian Reward and Loss Adjusted Exploration

Multi-step manipulation tasks in unstructured environments are extremely challenging for a robot to learn. Such tasks interlace high-level reasoning that consists of the expected states that can be attained to achieve an overall task and low-level reasoning that decides what actions will yield these states. We propose a model-free deep reinforcement learning method to learn multi-step manipulation tasks. We introduce a Robotic Manipulation Network (RoManNet)1, which is a vision-based model architecture, to learn the action-value functions and predict manipulation action candidates. We define a Task Progress based Gaussian (TPG) reward function that computes the reward based on actions that lead to successful motion primitives and progress towards the overall task goal. To balance the ratio of exploration/exploitation, we introduce a Loss Adjusted Exploration (LAE) policy that determines actions from the action candidates according to the Boltzmann distribution of loss estimates. We demonstrate the effectiveness of our approach by training RoManNet to learn several challenging multi-step robotic manipulation tasks in both simulation and real-world. Experimental results show that our method outperforms the existing methods and achieves state-of-the-art performance in terms of success rate and action efficiency. The ablation studies show that TPG and LAE are especially beneficial for tasks like multiple block stacking.
Plot-scale rainfall-runoff characteristics and modeling at six sites in Australia and Southeast Asia

During major runoff events when most soil loss occurs, runoff is likely to dominate the rainfall-driven erosion processes. Thus accurate estimation of the runoff rate is critical to soil loss predictions. At plot scale, the Green-Ampt infiltration model is commonly assumed to be able to describe the temporal variation of the infiltration rate over a storm event. Field measurements of both rainfall intensity and runoff rate at 1-min intervals at six sites in the tropical and subtropical regions of Australia and Southeast Asia, however, strongly suggest that the apparent infiltration rate is closely related to the rainfall intensity and it is essentially independent of the cumulative infiltration amount, features not accord with the Green-Ampt infiltration equation. Furthermore, the storage effect and runoff rate attenuation are not negligible at the plot scale. With an initial infiltration amount to determine when runoff begins, an exponential distribution to describe the spatial variation in the maximum infiltration rate and a linear storage formulation to model the lag between runoff and rainfall, we were able to develop a satisfactory three-parameter model for the runoff rate at 1-min intervals within a storm event.
From word-representable graphs to altered Tverberg-type theorems

Tverberg's theorem says that a set with sufficiently many points in $\mathbb{R}^d$ can always be partitioned into $m$ parts so that the $(m-1)$-simplex is the (nerve) intersection pattern of the convex hulls of the parts. In arXiv:1808.00551v1 [math.MG] the authors investigate how other simplicial complexes arise as nerve complexes once we have a set with sufficiently many points. In this paper we relate the theory of word-representable graphs as a way of codifying $1$-skeletons of simplicial complexes to generate nerves. In particular, we show that every $2$-word-representable triangle-free graph, every circle graph, every outerplanar graph, and every bipartite graph could be induced as a nerve complex once we have a set with sufficiently many points in $\mathbb{R}^d$ for some $d$.
MicroBooNE and the ν_{e} Interpretation of the MiniBooNE Low-Energy Excess.

A new generation of neutrino experiments is testing the 4. 7σ anomalous excess of electronlike events observed in MiniBooNE. This is of huge importance for particle physics, astrophysics, and cosmology, not only because of the potential discovery of physics beyond the standard model, but also because the lessons we will learn about neutrino-nucleus interactions will be crucial for the worldwide neutrino program. MicroBooNE has recently released results that appear to disfavor several explanations of the MiniBooNE anomaly. Here, we show quantitatively that MicroBooNE results, while a promising start, unquestionably do not probe the full parameter space of sterile neutrino models hinted at by MiniBooNE and other data, nor do they probe the ν_{e} interpretation of the MiniBooNE excess in a model-independent way.