Miracle-dz/UniFAR-FTUs huggingface dataset:
Real Effects of Competition Laws: International Evidence Abstract We employ the statutory laws that regulate competitions among firms to examine the effect of competition on firms’ financing and investment decisions around the world. Using a large sample

We employ the statutory laws that regulate competitions among firms to examine the effect of competition on firms’ financing and investment decisions around the world. Using a large sample of 206,713 firm-year observations from 59 countries, we find evidence that the stringency of competition laws spurs improvement in governance that positively influences firms’ access to external financing and investment. This finding is robust to several sensitivity tests, including alternative fixed effects, alternative sample compositions and a first-difference change analysis. A breakdown of the competition law index into its two subcategories, namely, authority and substance, reveals that the effect is mainly driven by the authority subcomponent of the competition law index. In cross-sectional analysis, we find that the positive association between the stringency of competition laws and external financing and investment is stronger for firms from countries with weaker institutional environments. Using a sample that covers diverse industries and many countries, our study improves the understanding of the effects of market competition, particularly, how variation in institutional settings matters for the success of competition laws and should be of value to policymakers.
Contention Grading and Adaptive Model Selection for Machine Vision in Embedded Systems

Real-time machine vision applications running on resource-constrained embedded systems face challenges for maintaining performance. An especially challenging scenario arises when multiple applications execute at the same time, creating contention for the computational resources of the system. This contention results in increase in inference delay of the machine vision applications, which can be unacceptable for time-critical tasks. To address this challenge, we propose an adaptive model selection framework that mitigates the impact of system contention and prevents unexpected increases in inference delay by trading off the application accuracy minimally. The framework has two parts, which are performed pre-deployment and at runtime. The pre-deployment part profiles the system for contention in a black-box manner and produces a model set that is specifically optimized for the contention levels observed in the system. The runtime part predicts the inference delays of each model considering the system contention and selects the best model according to the predictions for each frame. Compared to a fixed individual model with similar accuracy, our framework improves the performance by significantly reducing the inference delay violations against a specified threshold. We implement our framework on the Nvidia Jetson TX2 platform and show that our approach achieves greater than 20% reductions in delay violations over the individual baseline models.
Assessing Production E ciency by Farm Size in Rwanda: A Zero-ine ciency Stochastic Frontier Approach

6 This study investigates the relationship between farm size and technical efficiency for maize 7 production in Rwanda. Since levels of technical efficiency tend to vary considerably across farms 8 in sub-Saharan Africa, with a mixture of both inefficient and fully efficient farms, the use of the 9 conventional stochastic frontier method is not appropriate. In this paper, we apply a zero10 inefficiency stochastic frontier method that manages both efficiency and inefficiency in the 11 studied sample. The average technical efficiency of maize farms for the full sample is estimated 12 at 0.64, demonstrating that maize output can be improved by approximately 36% without 13 increasing the proportion of farm inputs used. Regarding the relationship between farm size and 14 technical efficiency, the study results show a positive relationship between farm size and 15 technical efficiency for maize production in Rwanda. Thus, the enforcement of land reforms such 16 as land consolidation and enhanced aggregate productivity growth are needed. The results also 17 indicate that education, cooperative membership, extension services, access to credit, off-farm 18 income, land tenure, and livestock ownership have significant and positive effects on technical 19 efficiency. 20
Managing Public Portfolios

We develop a unified framework for optimally managing public portfolios for a class of macro-finance models that include widely-used specifications for households’ risk and liquidity preferences, market structures for financial assets, and trading frictions. An optimal portfolio hedges fluctuations in interest rates, primary surpluses, liquidities and inequalities. It recognizes liquidity benefits that government debts provide and internalizes equilibrium effects of public policies on financial asset prices. We express an optimal portfolio in terms of statistics that are functions only of macro and financial market data. An application to the U.S. shows that hedging interest rate risk plays a dominant role in shaping an optimal maturity structure of government debt. *We thank Marios Angeletos, Hanno Lustig, and Deborah Lucas, and Benjamin Moll for discussions earlier drafts along with audiences at Chicago, Penn State, TSU, UPenn, UCLA, Bank of Portugal, NBER Asset Pricing Meeting, Bank of Finland, Penn State, Arizona State University, MIT, Wisconsin, College de France, St. Louis Fed, and the Minneapolis Fed. We thank Jiawei Fan for excellent research assistance. Bhandari, Evans, and Golosov thank the NSF for support (grant #36354.00.00.00).
The Implementation of Curriculum: A Case Study

The aim of this research is to examine the implementation of eight national education standards at SMA Negeri 2 Surakarta. This research is a qualitative method by using primer and secondary data. The analyzing of data is using triangulation technique. Based on the assessment of indicators, the implementation of eight national education standards resulted the percentage of the success in implementation which is 82.26% including standard content is 91.67%, standard process is 85%, standard of graduate competence is 87.5%, standard of educators and educational personnel is 79.17%, standard of facilities and infrastructure is 91.67%, management standard is 78.47%, financing standard is 79.86%, the standard of assessment in education is 77.08%. The summary of the research is implementation standard as the best standard which has many contents as follows: graduate competence, process and facilities, and infrastructure. Meanwhile, the implementation of the lowest standards is financing, educators and educational personnel, Management and assessment of education.
Segmentation-Consistent Probabilistic Lesion Counting

Lesion counts are important indicators of disease severity, patient prognosis, and treatment efficacy, yet counting as a task in medical imaging is often overlooked in favor of segmentation. This work introduces a novel continuously differentiable function that maps lesion segmentation predictions to lesion count probability distributions in a consistent manner. The proposed end-to-end approach--which consists of voxel clustering, lesion-level voxel probability aggregation, and Poisson-binomial counting--is non-parametric and thus offers a robust and consistent way to augment lesion segmentation models with post hoc counting capabilities. Experiments on Gadolinium-enhancing lesion counting demonstrate that our method outputs accurate and well-calibrated count distributions that capture meaningful uncertainty information. They also reveal that our model is suitable for multi-task learning of lesion segmentation, is efficient in low data regimes, and is robust to adversarial attacks.
Mechanizing Refinement Types

Practical checkers based on refinement types use the combination of implicit semantic subtyping and parametric polymorphism to simplify the specification and automate the verification of sophisticated properties of programs. However, a formal metatheoretic accounting of the soundness of refinement type systems using this combination has proved elusive. We present λRF, a core refinement calculus that combines semantic subtyping and parametric polymorphism. We develop a metatheory for this calculus and prove soundness of the type system. Finally, we give two mechanizations of our metatheory. First, we introduce data propositions, a novel feature that enables encoding derivation trees for inductively defined judgments as refined data types, and use them to show that LiquidHaskell’s refinement types can be used for mechanization. Second, we mechanize our results in Coq, which comes with stronger soundness guarantees than LiquidHaskell, thereby laying the foundations for mechanizing the metatheory of LiquidHaskell.
Kant and the Duty to Act from Duty

Several interpreters argue that Kant believes we have a duty to act “from duty. ” If there is such a duty, however, then Kant's moral theory faces a serious problem, namely that of an allegedly vicious infinite regress of duties. No serious attempt has been made to determine how Kant might respond to this problem and insufficient work has been done to determine whether he even believes we have a duty to act from duty. In this paper I argue that not only does Kant not hold that there is a duty to act from duty, but he also explicitly rejects the idea.
Real-time anomaly detection in logs using rule mining and complex event processing at scale

Author: Alexandros Stavroulakis Student ID: 4747933 Email: stavroulakisalexandros@gmail.com Log data, produced from every computer system and program, are widely used as source of valuable information to monitor and understand their behavior and their health. However, as large-scale systems generate a massive amount of log data every minute, it is impossible to detect the cause of system failure by examining manually this huge size of data. Thus, there is a need for an automated tool for finding system’s failure with little or none human effort. Nowadays lots of methods exist that try to detect anomalies on system’s logs by analyzing and applying various algorithms such as machine learning algorithms. However, experts argue that a system error can not be found by looking into a single event, but in multiple log event data are necessary to understand the root cause of a problem. In this thesis work, we aim to detect patterns in sequential distributed system’s logs that can capture effectively the abnormal behavior. Specifically as a first step, we will apply rule mining techniques to extract rules that represent an anomalous behavior, which potentially in the future may lead to a failure of a system. Except for that step, we implemented a real-time anomaly detection framework to detect problems before they actually occur. Processing log data as streams is the only way to achieve a real-time detection concept. In that direction we will process streaming log data using a complex event processing technique. Specifically, we would like to combine rule mining algorithms with complex event processing engine to raise alerts on abnormal log data based on automatically generated patterns. The evaluation of the work is conducted on Hadoop’s logs, a widely used system in the industry. The outcome of this thesis project gives really promising results, reaching a Recall of 98% in detecting anomalies. Finally, a scalable anomaly detection framework was build by integrating different systems into the cloud. The motivation behind this is the direct application of our framework to a real-life use case.
Factors Influencing Customer Purchase Intention: Reference to Social Media Advertising

Social media plays a vital role in the lives of customers. Customer buying decision is influenced by social media advertising (SMA). It is a great challenge of marketers, to identify how customers’ make purchasing decisions and what factors influence their purchase decision. Current study is conducted to identify factors of SMA influence customer purchase intention. Theoretical framework developed based on the UTAUT2 model (performance expectancy, hedonic motivation, & habit) including interactivity and informativeness. Data collected from 400 respondents through google forms with 81% of response rate. Data analyzed through correlation and multiple regression techniques. Results revealed performance expectancy, hedonic motivation, interactivity & informativeness impacted on purchase intention whereas habit was not a significant influencing factor. Facebook dominates in Sri Lanka and informativenss is the strongest influencer of purchase intention. Furthermore, SMA is more effective in advertising products to male, young, & educated customers. Keywords-: Customer Purchase Intention, Social Media Advertising, Informativeness, Interactivity, UTAUT2
The effect of transdermal gender-affirming hormone therapy on markers of inflammation and hemostasis

Background Cardiovascular risk is increased in transgender persons using gender-affirming hormone therapy. To gain insight into the mechanism by which sex hormones affect cardiovascular risk in transgender persons, we investigated the effect of hormone therapy on markers of inflammation and hemostasis. Methods In this exploratory study, 48 trans women using estradiol patches plus cyproterone acetate (CPA) and 47 trans men using testosterone gel were included. They were between 18 and 50 years old and did not have a history of cardiovascular events. Measurements were performed before and after 3 and 12 months of hormone therapy. Results After 12 months, in trans women, systemic and endothelial inflammatory markers decreased (hs-CRP -66%, (95% CI -76; -53), VCAM-1–12%, (95% CI -16; -8)), while platelet activation markers increased (PF-4 +17%, (95% CI 4; 32), β-thromboglobulin +13%, (95% CI 2; 24)). The coagulation marker fibrinogen increased transiently, after 3 months (+15%, (95% CI 1; 32)). In trans men, hs-CRP increased (+71%, (95% CI 19; 145)); platelet activation and coagulation markers were not altered. In both trans women and trans men, leptin and adiponectin changed towards reference values of the experienced gender. Conclusions Platelet activation and coagulation marker concentrations increased in trans women using transdermal estradiol plus CPA, but not in trans men using testosterone. Also, concentrations of inflammatory markers decreased in trans women, while hs-CRP increased in trans men. Our results indicate that hormone therapy may affect hemostasis in transgender persons, which could be an underlying mechanism explaining the increased cardiovascular risk in this population.
Immunotherapy Outcomes in Individuals With Non–Small Cell Lung Cancer and Poor Performance Status

Abstract Background Patients with non–small cell lung cancer (NSCLC) treated in real-world practice typically have worse performance status (PS) compared with clinical trial patients, and the effectiveness of immunotherapy in this population in unknown. In this study, we assessed the effectiveness of standard of care immunotherapy for the first-line treatment of stage IV patients with NSCLC with Eastern Cooperative Oncology Group (ECOG) PS greater than or equal to 2. Methods We selected ECOG PS greater than or equal to 2 patients from real-world oncology data from a deidentified database and included them if they were diagnosed with stage IV NSCLC and had documented Programmed death-ligand 1 [PD-(L)1] expression greater than 0. Patients with tumor PD-(L)1 expression of at least 50% treated with pembrolizumab monotherapy were compared with those who did not have any documented treatment. Patients with tumor PD-(L)1 expression less than 50% treated with pembrolizumab and chemotherapy were compared with those treated with pembrolizumab monotherapy and those without documented treatment. Results In our propensity score–adjusted analysis, patients with ECOG PS of at least 2 and tumor PD-(L)1 expression of at least 50% treated with pembrolizumab monotherapy had statistically significantly better real-world overall survival compared with those without documented treatment (adjusted hazard ratio [HR] = 0.39, 95% confidence internal [CI] = 0.32 to 0.47). For patients with tumor PD-(L)1 expression less than 50%, there was also a statistically significant real-world overall survival benefit for those who received treatment either with combination pembrolizumab plus chemotherapy (adjusted HR = 0.39, 95% CI = 0.32 to 0.46) or pembrolizumab monotherapy (adjusted HR = 0.55, 95% CI = 0.41 to 0.70) compared with patients receiving no documented treatment. Conclusions Among a highly representative sample of patients with advanced NSCLC and poor PS, our findings suggest that immunotherapy may provide an important survival benefit in individuals with high PD-(L)1–expressing tumors and in conjunction with chemotherapy in tumors with low PD-(L)1 expression.
Association between low levels of HIV-1 DNA and HLA class I molecules in chronic HIV-1 infection

Background HLA-B27 and -B57 were found in people with low levels of HIV-1 DNA, suggesting that HLA class I molecules may influence the size of HIV-1 reservoir. Aim of the study was to explore the association between HLA class I molecules and HIV-1 DNA in people with chronic HIV-1 infection. Methods Post-hoc analysis of the APACHE trial, on adults with chronic HIV-1 infection, prolonged suppressive antiretroviral therapy and good immunological profile. HIV-1 DNA was quantified in peripheral blood mononuclear cells (PBMCs); HLA-A, -B and -C were tested on genomic DNA. Crude odds ratios (OR) with their respective 95% Wald confidence intervals (95% CIs) were estimated by univariable logistic regression for HLAs with a p-value <0.10. Results We found 78 and 18 patients with HIV-1 DNA ≥100 copies/106PBMCs and with HIV-1 DNA <100 copies/106PBMCs, respectively. HLA-A24 was present in 21 (29.6%) participants among subjects with HIV-1 DNA ≥100 copies/106PBMCs and 1 (5.9%) among those with HIV-1 DNA <100 copies/106PBMCs (OR = 5.67, 95%CI = 0.79–46.03; p = 0.105); HLA-B39 was present in 1 (1.4%) with HIV-1 DNA ≥100 copies/106PBMCs and in 3 (17.6%) with HIV-1 DNA <100 copies/106PBMCs (OR = 13.71, 95%CI = 1.33–141.77; p = 0.028) and HLA-B55 in 3 (4.2%) and 3 (17.6%), respectively (OR = 4.43, 95%CI = 0.81–24.29; p = 0.087). All the three patients with HLA-B39 and HIV-1 DNA <100 copies/106PBMCs did not have HLA-A24. Conclusions In patients with HIV-1 infection who maintained a good virological and immunological profile, HLA-B39 and -B55 may be associated with lower levels of HIV-1 DNA.
Risk of heart disease following treatment for breast cancer – results from a population-based cohort study

Background: There is a rising concern about treatment-associated cardiotoxicities in breast cancer patients. This study aimed to determine the time- and treatment-specific incidence of arrhythmia, heart failure, and ischemic heart disease in women diagnosed with breast cancer. Methods: A register-based matched cohort study was conducted including 8015 breast cancer patients diagnosed from 2001 to 2008 in the Stockholm-Gotland region and followed up until 2017. Time-dependent risks of arrhythmia, heart failure, and ischemic heart disease in breast cancer patients were assessed using flexible parametric models as compared to matched controls from general population. Treatment-specific effects were estimated in breast cancer patients using Cox model. Results: Time-dependent analyses revealed long-term increased risks of arrhythmia and heart failure following breast cancer diagnosis. Hazard ratios (HRs) within the first year of diagnosis were 2.14 (95% CI = 1.63–2.81) for arrhythmia and 2.71 (95% CI = 1.70–4.33) for heart failure. HR more than 10 years following diagnosis was 1.42 (95% CI = 1.21–1.67) for arrhythmia and 1.28 (95% CI = 1.03–1.59) for heart failure. The risk for ischemic heart disease was significantly increased only during the first year after diagnosis (HR = 1.45, 95% CI = 1.03–2.04). Trastuzumab and anthracyclines were associated with increased risk of heart failure. Aromatase inhibitors, but not tamoxifen, were associated with risk of ischemic heart disease. No increased risk of heart disease was identified following locoregional radiotherapy. Conclusions: Administration of systemic adjuvant therapies appears to be associated with increased risks of heart disease. The risk estimates observed in this study may aid adjuvant therapy decision-making and patient counseling in oncology practices. Funding: This work was supported by the Swedish Research Council (grant no: 2018-02547); Swedish Cancer Society (grant no: CAN-19-0266); and FORTE (grant no: 2016-00081).
Olaparib With or Without Cediranib Versus Platinum-Based Chemotherapy in Recurrent Platinum-Sensitive Ovarian Cancer (NRG-GY004): A Randomized, Open-Label, Phase III Trial

PURPOSE Platinum-based chemotherapy is the standard of care for platinum-sensitive ovarian cancer, but complications from repeated platinum therapy occur. We assessed the activity of two all-oral nonplatinum alternatives, olaparib or olaparib/cediranib, versus platinum-based chemotherapy. PATIENTS AND METHODS NRG-GY004 is an open-label, randomized, phase III trial conducted in the United States and Canada. Eligible patients had high-grade serous or endometrioid platinum-sensitive ovarian cancer. Patients were randomly assigned 1:1:1 to platinum-based chemotherapy, olaparib, or olaparib/cediranib. The primary end point was progression-free survival (PFS) in the intention-to-treat population. Secondary end points included activity within germline BRCA-mutated or wild-type subgroups and patient-reported outcomes (PROs). RESULTS Between February 04, 2016, and November 13, 2017, 565 eligible patients were randomly assigned. Median PFS was 10.3 (95% CI, 8.7 to 11.2), 8.2 (95% CI, 6.6 to 8.7), and 10.4 (95% CI, 8.5 to 12.5) months with chemotherapy, olaparib, and olaparib/cediranib, respectively. Olaparib/cediranib did not improve PFS versus chemotherapy (hazard ratio [HR] 0.86; 95% CI, 0.66 to 1.10; P = .077). In women with germline BRCA mutation, the PFS HR versus chemotherapy was 0.55 (95% CI, 0.32 to 0.94) for olaparib/cediranib and 0.63 (95% CI, 0.37 to 1.07) for olaparib. In women without a germline BRCA mutation, the PFS HR versus chemotherapy was 0.97 (95% CI, 0.73 to 1.30) for olaparib/cediranib and 1.41 (95% CI, 1.07 to 1.86) for olaparib. Hematologic adverse events occurred more commonly with chemotherapy; however, nonhematologic adverse events were higher with olaparib/cediranib. In 489 patients evaluable for PROs, patients receiving olaparib/cediranib scored on average 1.1 points worse on the NFOSI-DRS-P subscale (97.5% CI, –2.0 to –0.2, P = .0063) versus chemotherapy; no difference between olaparib and chemotherapy was observed. CONCLUSION Combination olaparib/cediranib did not improve PFS compared with chemotherapy and resulted in reduced PROs. Notably, in patients with a germline BRCA mutation, both olaparib and olaparib/cediranib had significant clinical activity. Cediranib/olaparib is active but did not improve PFS vs platinum chemo in plat-sens ovarian cancer.