Miracle-dz/UniFAR-FTUs huggingface dataset:
The Targeted Negative Income Tax (Tnit) in Germany: Evidence from a Quasi Experiment

We report empirical evidence from the first field experiments to be conducted in Germany with program and control groups between 1999 and 2002. The evaluated program called "Targeted Negative Income Tax (TNIT)" is a time-restricted employee subsidy for means-tested welfare recipients. We focus on a unique data set on welfare recipients in Mannheim and estimate the treatment effect of TNIT on participation probability. The average treatment effect is significant and lies between 6.6 and 6.8 percentage points. Since January 1st, 2005, TNIT can be offered to all means-tested long-term unemployed people in Germany by public case managers.
Overall survival benefit and safety profile of radium-223 chloride, a first-in-class alpha-pharmaceutical: Results from a phase III randomized trial (ALSYMPCA) in patients with castration-resistant prostate cancer (CRPC) with bone metastases.

8 Background: Radium-223 chloride (Ra-223) is a first-in-class alpha-pharmaceutical targeting bone metastases (mets) with high-energy alpha-particles of extremely short range (<100 μm). ALSYMPCA, a phase III, double-blind, randomized, multinational study, compared efficacy, in terms of overall survival (OS), and safety of Ra-223 plus best standard of care (BSC) vs placebo plus BSC in patients (pts) with bone mets in CRPC. METHODS Eligible pts had progressive, symptomatic CRPC with ≥ 2 bone mets on scintigraphy and no known visceral mets; were receiving BSC; and either previously received docetaxel, were docetaxel ineligible, or refused docetaxel. Pts were randomized 2:1 to receive 6 injections of Ra-223 (50 kBq/kg IV) q4 wks or matching placebo and stratified by prior docetaxel use, baseline alkaline phosphatase level, and current bisphosphonate use. A planned interim analysis (IA) was conducted to assess the effect of Ra-223 on the primary endpoint (OS) using a predefined threshold. Survival data were compared using a stratified log-rank test. RESULTS 922 pts (Ra-223, n = 615; placebo, n = 307) were randomized from 6/2008-2/2011. 445 (58%) of 809 pts in the IA data set received prior treatment with docetaxel. Ra-223 significantly improved OS in pts with CRPC with bone mets vs placebo (two-sided P = 0.00185; HR = 0.695; 95% CI, 0.552-0.875; median OS 14.0 mo vs 11.2 mo, respectively). Safety and tolerability of Ra-223 were highly favorable and showed low incidence of myelosuppression (eg, grades 3/4 neutropenia in 1.8% and 0.8% and thrombocytopenia in 4% and 2% of the Ra-223 and placebo groups, respectively). CONCLUSIONS Ra-223 is an effective therapy that improved OS with a highly favorable safety profile, and may provide a new standard of care for the treatment of CRPC pts with bone mets. [Table: see text].
Mpi on millions of Cores

Petascale parallel computers with more than a million processing cores are expected to be available in a couple of years. Although MPI is the dominant programming interface today for large-scale systems that at the highest end already have close to 300,000 processors, a challenging question to both researchers and users is whether MPI will scale to processor and core counts in the millions. In this paper, we examine the issue of scalability of MPI to very large systems. We first examine the MPI specification itself and discuss areas with scalability concerns and how they can be overcome. We then investigate issues that an MPI implementation must address in order to be scalable. To illustrate the issues, we ran a number of simple experiments to measure MPI memory consumption at scale up to 131,072 processes, or 80%, of the IBM Blue Gene/P system at Argonne National Laboratory. Based on the results, we identified nonscalable aspects of the MPI implementation and found ways to tune it to reduce its memory footprint. We also briefly discuss issues in application scalability to large process counts and features of MPI that enable the use of other techniques to alleviate scalability limitations in applications.
Application of Improved Convolutional Neural Network in Text Classification

—Text classification is a basic problem in the field of natural language processing. The model based on deep learning is a common model to deal with this problem. However, there are two problems in the text classification application using deep learning models: one is that the important role of the text hierarchical structure is not fully considered in classification judgment; the other is that the traditional word segmentation may produce ambiguity when dealing with text. Aiming at these problems, a text classification algorithm based on deep convolution neural network and attention mechanism is proposed. The neural network language model word2vec is used to train the word vector of short text. The trained word vector is used to represent the text. The convolution neural network is used to extract the abstract features of short text. Through extracting the abstract features, the classifier is used to classify short text. The results show that the algorithm has higher accuracy than the traditional convolutional neural network and bag of word model.
Ab Initio Based Modelling of Diffusion and Phase Stability of Alloys

In this chapter, we present the basic principles and methods for modelling of diffusion and phase stability of alloys using ab-initio methods. We review briefly first-principles methods and their most important approximations. The direct and approximated methods of prediction of migration energies are shown both for pure metals and for alloys. The cluster expansion method is described in more detail. We show that it can be applied to understand interactions in the alloys, to generate the representative structures of alloys and to predict migration barriers in alloys. We describe the methods to compute the effective cluster interactions and to assess the accuracy of the model. Finally, we present the examples of Monte Carlo simulations with parameters obtained from cluster expansion method. We show that the ordering in alloys can be predicted by the calculations of Warren-Cowley parameters. We investigate also the role of entropy in the stability of alloys at elevated temperatures.
The stability improvement of wide emission Zn0.8Cd0.2S quantum dot for white light-emitting diodes

Recently, the investigation of quantum dots (QDs) as color converters for white light-emitting diodes (WLEDs) has attracted a significant amount of attention, because the emission wavelength and broad excitation band of QDs can be controlled by their particle sizes and compositions. However, owing to the thermal effect, the long-term stability of QDWLEDs is one of the important tasks for their application. Moreover, the commercial WLEDs have low color rendering index (CRI) and the reabsorption effect. Therefore, in order to increase the device stability and CRI, in this study, we have used easy one-pot process to synthesize the colloidal ternary Zn0.8Cd0. 2S (ZnCdS) QDs with wide emission, a quantum yield (QY) of 42 % and a particle size of 3.2 ± 0.5 nm. Three methods have been applied to encapsulate the QDs and their average CRIs are 78. We have demonstrated that the QDs-based WLEDs can achieve color converter robust against photooxidation, thermal quenching, and scattering, and can be applied to fabricate reliable P-QD1 device with an air gap between the emission layers. This encapsulation setup can protect the color converter and maintain the best stability over 750 hours operation time, and the Commission International d’Eclairage (CIE) chromaticity coordinates and luminous efficacy can be tuned from (0.36, 0.40) to (0.32, 0.33) and 4.5 to 3.2, respectively.
Habitable exoplanets detection: overview of challenges and current state-of-the-art [Invited]

Detection and characterization of exoplanets pose formidable observational challenges, as planets are orders of magnitudes fainter, less massive and smaller than the stars they orbit. Multiple detection techniques exist, all relying on the high accuracy measurement of stellar light (flux, spectra, position or wavefront). Astrophotonic technologies for light creation, shaping and detection are essential to meet these challenges. While current detection and characterization techniques are suitable for giant (Jupiter-like) planets, potentially habitable Earth-sized rocky planets are considerably more challenging to observe. Recent advances in astrophotonics hold the key to characterization of these smaller planets, and to the remote identification of biomarkers indicative of life.
Analytical Framework for Mmwave-Enabled V2X Caching

An effective method for supporting the large volume of information required for future vehicular networks is leveraging caching techniques as well as relying on millimeter-wave (mmWave) frequencies. However, characterizing such a system under mmWave directional beamforming and vehicular mobility is a complex task. In this article, we propose the first stochastic geometry framework for V2X caching in mmWave networks. In addition to common parameters considered in stochastic geometry models, our derivations account for caching as well as the speed and the trajectory of the vehicles. Furthermore, our evaluations provide interesting design insights: <inline-formula><tex-math notation="LaTeX">$ (i)$</tex-math></inline-formula> higher base station/vehicle densities does not necessarily improve caching performance; <inline-formula><tex-math notation="LaTeX">$ (ii)$</tex-math></inline-formula> although using a narrower beam leads to a higher SINR, it also reduces the connectivity probability; and <inline-formula><tex-math notation="LaTeX">$ (iii)$</tex-math></inline-formula> V2X caching can be an inexpensive way of compensating some of the unwanted mmWave channel characteristics.
Evidence of myocardial hibernation in the septic heart*

LEARNING OBJECTIVESOn completion of this article, the reader should be able to: Define myocardial hibernation. Explain physiologic changes in hibernating hearts. Use this information in a clinical setting. Dr. Ferrari has disclosed that he is/was the recipient of direct grant/research funds from Novartis and GlaxoSmithKline. All of the remaining authors have disclosed that they have no financial relationships or interests in any commercial companies pertaining to this educational activity. Wolters Kluwer Health has identified and resolved all faculty conflicts of interest regarding this educational activity. Visit the Critical Care Medicine Web site (www.ccmjournal.org) for information on obtaining continuing medical education credit. Objective:Myocardial hibernation is an adaptive response to ischemia and hypoxia. Hibernating cardiomyocytes are reversibly hypocontractile and demonstrate characteristic metabolic and ultrastructural changes. These include a switch in primary substrate utilization from fatty acids to glucose, up-regulation of the myocardial specific glucose transporters (GLUT1 and GLUT4), and glycogen deposition within and between cardiomyocytes. We hypothesized that myocardial hibernation may underlie sepsis-associated myocardial depression. Design:Prospective observational study aimed at identifying the characteristic changes of hibernation in the septic heart. Setting:University hospital-based laboratory. Subjects:Forty-three C57Bl6 male mice. Interventions:Mice underwent cecal ligation and double puncture, sham operation, or no operation and were evaluated 48 hrs after the procedure. Measurements and Main Results:Using novel, clinically relevant technology such as magnetic resonance imaging, positron emission tomography, and single photon emission computed tomography imaging, we found septic mice to have diminished cardiac performance, increased myocardial glucose uptake, increased steady-state levels of myocardial GLUT4, and increased deposits of glycogen, recapitulating the changes during hibernation. Importantly, these changes occurred in the setting of preserved arterial oxygen tension and myocardial perfusion. Conclusions:Sepsis-associated cardiac dysfunction may reflect hibernation. Furthermore, such down-regulation of cellular function may underlie sepsis-induced dysfunction in other organ systems.
Three-dimensional object recognition using an extensible local surface descriptor

Abstract. We present an extensible local feature descriptor that can encode both geometric and photometric information. We first construct a unique and stable local reference frame (LRF) using the sphere neighboring points of a feature point. Then, all the neighboring points are transformed with the LRF to keep invariance to transformations. The sphere neighboring region is divided into several sphere shells. In each sphere shell, we calculate the cosine values of the point with the x-axis and z-axis. These two values are then mapped into two one-dimensional (1-D) histograms, respectively. Finally, all of the 1-D histograms are concatenated to form the signature of position angles histogram (SPAH) feature. The SPAH feature can easily be extended to a color SPAH (CSPAH) by adding another 1-D histogram generated by the photometric information of each point in each shell. The SPAH and CSPAH were rigorously tested on several common datasets. The experimental results show that both feature descriptors were highly descriptive and robust under Gaussian noise and varying mesh decimations. Moreover, we tested our SPAH- and CSPAH-based three-dimensional object recognition algorithms on four standard datasets. The experimental results show that our algorithms outperformed the state-of-the-art algorithms on these datasets.
Radioimmunotherapy of Breast Cancer Metastases with Alpha-Particle-emitter 225 Ac: Comparing Efficacy with 213 Bi, 90 Y

Alpha-particles are suitable to treat cancer micrometastases because of their short range and very high linear energy transfer. Alpha-particle-emitter 213 Bi based radioimmunotherapy has shown efficacy in a variety of metastatic animal cancer models, such as breast, ovarian, prostate cancer and leukemia. Its clinical implementation, however, is challenging due to the limited supply of 225 Ac, the high technical requirement to prepare radioimmunoconjugate with very short half-life (T 1/2 =45.6 mins) on site and prohibitive cost. In this study, we investigated the efficacy of the alpha-particle-emitter 225 Ac, parent of 213 Bi, in a mouse model of breast cancer metastases. A single administration of 225 Ac (400 nCi) labeled anti-rat HER-2/ neu monoclonal antibody (7.16.4) completely eradicated breast cancer lung micrometastases in about 67% of HER-2/ neu transgenic mice and led to long-term survival of these mice for up to one year. Treatment with 225 Ac-7.16. 4 is significantly more effective than 213 Bi-7.16. 4 (120 μ Ci) (median survival = 61 days, P =0.001), and 90 Y-7.16. 4 (120 μ Ci) (median survival = 50 days, P <0.001), as well as untreated control (median survival = 41 days, P =0.0001). Dosimetric analysis showed that 225 Ac treated metastases received a total dose of 9.6 Gy, significantly higher than 2.0 Gy from 213 Bi and 2.4 Gy from 90 Y. Biodistribution studies revealed that 225 Ac daughters, 221 Fr and 213 Bi, accumulated in kidneys and probably contributed to the long-term renal toxicity observed in surviving mice. These data suggest 225 Ac labeled anti-HER-2/ neu monoclonal antibody could significantly prolong survival in HER-2/ neu -positive metastatic breast cancer patients. survival with no significant body weight loss (>15%). Healthy neu -N mice were injected (five mice/group) with 100, 200, 400, 500, 600, 700, or 1,000 nCi 225 Ac-7.16. 4. Mice were weighed twice per week for 90 days. To evaluate the efficacy of radiolabeled mAbs to treat early stage micrometastases, three days after neu -N mice were injected with 1×10 5 NT2.5 cells (i.v.), mice were treated intravenously with ( a ) 400 nCi 225 Ac-7.16. 4, n=12; ( b ) 120 μ Ci 213 Bi-7.16. 4, n=10; ( c ) 120 μ Ci 90 Y-7.16. 4, n=5; ( d ) 200 nCi 225 Ac-7.16. 4, n=5; ( e ) 200 nCi + 200 nCi 225 Ac-7.16. 4 (injected one week apart), n=5; ( f ) 100 μ g 7.16. 4, unlabeled control, n=5; ( g ) 400 nCi 225 Ac-Rituximab, nonspecific control, n=5; ( h ) untreated control, n=10. To evaluate the efficacy of treating late stage lung metastases, at eighteen days after tumor cell inoculation, neu -N mice were treated with (a) 400 nCi 225 Ac-7.16. 4, n=5; (b) 120 μ Ci 213 Bi-7.16. 4, n=5; (c) 120 μ Ci 90 Y-7.16. 4, n=5. Mice were monitored and weighed three times a week and were euthanized when significant body weight loss (>15%) or breathing difficulties developed. In survival and long-term toxicity studies, animals were for up to one year.
Journal of Hospitality Financial Management Journal of Hospitality Financial Management

Restaurant managers often do not have a comprehensive understanding of all of the costs involved in operating a successful restaurant, leading to inaccurate, and potentially unproﬁtable, menu item pricing. One trend in cost analysis is to explore techniques used in other industries, including activity-based costing. A body of work exploring the application of activity-based costing in the foodservice industry has gradually evolved. A review of previous research on activity-based costing in various restaurant segments validates it as a consequential approach that is capable of reducing waste, preserving employment, and producing maintainable proﬁtability in the restaurant industry.
A Framework for Resiliency Assessment of Power Communication Networks

Modern societies are strongly dependent on the continuous and efficient operation of electric power systems as one of the critical infrastructures. Besides, information and communication systems play a crucial role in resiliency enhancement of the power system. As power communication systems are vulnerable against physical and cyber challenges, these systems can be an internal source of threats for power grids by themselves. Therefore, there is a need to identify and study the threats and weaknesses of power communication systems using a comprehensive framework. This framework helps power communication network planners evaluate all challenges and their numerous effects on the system, as a very important step in designing such systems. In the present paper, we propose such a framework by introducing the concept of ‘resiliency matrix’. In this regard, the resiliency of two alternative network plans, both of which are the solutions of a multi objective optimal design problem, is evaluated and compared using the proposed framework. The results reveal that the defined framework is capable to enhance network resiliency and thus can be used as a complementary step to design optimal and robust power communication networks.
Does Money Matter in House Elections? Jake Matise

Although campaign spending has always been prevalent in American political society, the aftermath of decisions like Citizens United has led to higher amounts of election spending than ever before. But does spending have an observable effect on the outcome of elections? This paper evaluates the effect of campaign spending on winning an election using data from the 2020 House election cycle. The data I used consists of every House election from 2020, with seats ranked on a competitiveness scale from “safe Republican/Democrat” to “toss-up” (as categorized by 270ToWin), as well as recording incumbent or challenger victories, and the amount of money the winner and runner-up spent during their respective campaigns (taken from OpenSecrets). I also analyze whether campaign spending has a party bias. The preliminary results illustrate high statistical significance between election competitiveness and an increase in campaign spending.
Lecture Time-Bounded Derandomization

Randomization can (provably) provide benefits in many settings; examples include cryptography (where random keys are used to provide protection against an adversary) and distributed computing (where randomness can be used as a means to break symmetry between parties). Randomness also appears to help in algorithm design. But is it possible that, from a complexity-theoretic perspective, randomness does not help? E.g., might it be the case that every problem that can be solved in randomized polynomial time can also be solved in deterministic polynomial time? (That is, is P = BPP? ) Historically, guided by progress in designing efficient randomized algorithms, most researchers believed that randomness does help. Research over the past 25 years on (timebounded) derandomization has now led many to change their views; the consensus nowadays is that randomization does not help.1 One natural approach to derandomize algorithms is to use a pseudorandom generator (PRG) that expands a small, truly random input into a larger, random-looking output. In the next section we define PRGs and then describe their application to derandomization. The remainder of these notes will focus on constructing a PRG based on some complexity-theoretic assumption.
Polarization Observables in Strangeness Photoproduction with CLAS at Jefferson Lab

This work presents measurements of several polarization observables for the reactions gammap → K+Lambda0 and gammap → K+ Sigma0. The data were collected in the summer of 2005 at the Thomas Jefferson National Accelerator Facility, using a linearly polarized photon beam in the energy range 1.66 GeV < √s < 2.24 GeV. In addition to measuring the photon asymmetry, target asymmetry and hyperon recoil polarization, first ever measurements are made for the double polarization observables O[x] and O[z]. The measurements of the photon and target asymmetries vastly increase the precision of the current world dataset, as well as extending the angular coverage.
Sparse and Smooth: improved analysis for Spectral Clustering in the Dynamic Stochastic Block Model

In this paper, we analyse classical variants of the Spectral Clustering (SC) algorithm in the Dynamic Stochastic Block Model (DSBM). Existing results show that, in the relatively sparse case where the expected degree grows logarithmically with the number of nodes, guarantees in the static case can be extended to the dynamic case and yield improved error bounds when the DSBM is sufficiently smooth in time, that is, the communities do not change too much between two time steps. We improve over these results by drawing a new link between the sparsity and the smoothness of the DSBM: the more regular the DSBM is, the more sparse it can be, while still guaranteeing consistent recovery. In particular, a mild condition on the smoothness allows to treat the sparse case with bounded degree. We also extend these guarantees to the normalized Laplacian, and as a by-product of our analysis, we obtain to our knowledge the best spectral concentration bound available for the normalized Laplacian of matrices with independent Bernoulli entries.