Miracle-dz/UniFAR-FTUs huggingface dataset:
On the prosody of presupposition projection: A production experiment*

The content of the complement of a factive predicate like discover is standardly analyzed as a presupposition (e.g., Heim 1983, van der Sandt 1992, Abrusán 2011). Such analyses capture that the content of the complement (CC, henceforth) can project over entailmentcanceling operators, like the epistemic modal adverb perhaps in (1): when the CC, that Mary is a widow, projects, the speaker is taken to be committed to the truth of the CC.
An Exploration of Entrepreneurial Intentions among University Students in Kenya

Entrepreneurial intention has received much attention from both Scholars and Policy makers in the recent past due to the realization that the entrepreneurial intention may lead to entrepreneurial activities which offers great potential for employment creation among the University Students and economic growth of the country. Although there has been much interest in entrepreneurship, attributes that might impact on the propensity to venture into entrepreneurship among Students in Kenya is rarely examined. The purpose of this study was to explore the triggers and hindrances to entrepreneurial intentions among University Students. The sample includes the final year students of Chuka University from across the various programs. Using a correlation research design; the current study empirically examines the impact of personal attributes, entrepreneurial experience, entrepreneurial education and government support system on entrepreneurship intention. The theory of planned behaviour (TPB) model guided the current research. Primary data was obtained through a questionnaire survey method administered to a sample of 120 final year students from the Chuka University. Statistical techniques employed included confirmatory factor analysis, correlation analysis, and partial least square (PLS) regression analysis. The results were presented in tables and structural equation modeling. The findings revealed that students’ attitude and selfefficacy plays a very significant role in entrepreneurial intentions among the students. Concerning demographic variables, the entrepreneurial experience had a significant impact on entrepreneurial intention. The study recommends that the students should be encouraged to form or join student clubs where they meet and discuss possible joint business ventures. Secondly, the students should seek information on means of accessing capital for their business ideas. Besides, the government’s social and economic structures should be efficient to ensure that youth have access to cheap and readily available
NUTRACEUTICALS: THEIR ROLE IN IMPROVING SPORTS PERFORMANCE

Athletes experience regular cycles of physiological stress accompanied by transient inflammation, oxidative stress and immune perturbations. In fact, during exercise, oxygen consumption in muscle can increase 15fold, leading to free radicals production that impairs the antioxidant system. High concentrations of free radicals can be harmful to many cellular tissues, although some reactive molecules, such as hydrogen peroxide and nitric oxide may serve functions in cellular signaling and as secondary messengers in moderate concentrations. Nutritional support has the potential to partially mitigate exercise-induced changes without interfering with the signaling activities necessary for training adaptations. Athletes should avoid foods that may increase oxidative stress and increase foods that are higher in antioxidants. An example would be a diet rich in fruits and vegetables, which raises plasma levels of antioxidants and protects against many chronic diseases. Optimizing nutrition in combination with exercise is considered an established, effective ergogenic practice for athletic performance. In recent years, the nutraceutical industry has gone from a simple conceptual area in biomedical research to a value-added industry with a promising future. Nutraceutical substances are normally obtained from foods, plants or even microorganisms. They have the potential to treat or prevent diseases, especially chronic ones, to improve physical and mental health, to increase life expectancy and to combat the typical disorders of aging. In this paper, we expose existing evidence surrounding the efficacy of most common nutraceuticals compounds in combination or not with exercise in relation to skeletal muscle mass, metabolism, and exercise performance.
Factors Influencing Municipal Solid Waste Generation and Composition in Kathmandu Metropolitan City, Nepal

Increasing metropolitan solid waste and absence of concrete information sources is a developing worry in urban areas of developing countries like in Kathmandu Metropolitan City (KMC) in Nepal. Two goals of this study were: (1) to estimate household solid waste generation and its composition; and (2) to assess the socioeconomic factors impacting on household waste generation. Using stratified sampling, 288 families were chosen from the 32 wards of KMC for household survey. The quantification of total waste and its composition was undertaken for each household using digital weighing scales. Socioeconomic variables affecting household waste generation were analysis by using regression model. The rate of household waste generation in KMC was found 0.3 kg/capita/day and total household waste generation was found 413 tonnes/day. Household waste comprised of 51% organic and 49% recyclable comprising 5% paper and paper products, 3% glass, 1% metal, 19% plastic, 13% textiles, 4% rubber and leather and 4% other waste. As organic waste constitutes more than half proportion of total solid waste, it should deal appropriately, if not it will create serious health and environmental hazards. Household size and income had a positive impact on waste generation; both were statistically significant and thus are important indicators in forecasting solid waste generation trends. Finding from this study will help concerning authority to formulate sustainable solid waste management plan in KMC and beyond.
Association between COVID-19, mobility and environment in Sao Paulo, Brazil

Background Brazil, the country most impacted by the coronavirus disease 2019 (COVID-19) on the southern hemisphere, uses mobility indices to monitor quarantines. In this study, we quantified the associations between residential mobility index (RMI), air pollution, meteorology, and daily cases and deaths of COVID-19 in Sao Paulo, Brazil Objectives To acquire time-series data to estimate the associations between daily residential mobility index (RMI), air pollution, and meteorology, and daily cases and deaths for COVID-19 in Sao Paulo, Brazil. Methods We applied a semiparametric generalized additive model (GAM) to estimate: 1) the association between residential mobility index and cases and deaths due to COVID-19, accounting for ambient particulate matter (PM2.5), ozone (O3), relative humidity, temperature and delayed exposure between 3-21 days and 2) the association between exposure to for ambient particulate matter (PM2.5), ozone (O3), accounting for relative humidity, temperature and mobility. Results We found an RMI of 45.28% results in 1,212 cases (95% CI: 1,189 to 1,235) and 44 deaths (95% CI: 40 to 47). Reducing mobility 5% would avoid 438 cases and 21 deaths. Also, we found that an increment of 10 g m-3 of PM2.5 risk of 1.140 (95% CI: 1.021 to 1.274) for cases and of 1.086 (95% CI: 1.008 to 1.170 for deaths, while O3 produces a relative risk of 1.075 (95% CI: 1.006 to 1.150) for cases and 1.063 (95% CI: 1.006 to 1.124) for deaths, respectively. Discussion We compared our results with observations and literature review, finding well agreement. These results implicate that authorities and policymakers can use such mobility indices as tools to support social distance activities and assess their effectiveness in the coming weeks and months. Small increments of air pollution pose a risk of COVID-19 cases. Conclusion Spatial distancing is a determinant factor to control cases and deaths for COVID-19. Small increments of air pollution result in a high number of COVID-19 cases and deaths. PM2.5 has higher relative risks for COVID-19 than O3.
Effectiveness of Vivianite to Prevent Lime-Induced Iron Deficiency in Lemon Trees Grown on Highly Calcareous Soil

The short-term effectiveness of three application rates of vivianite [(Fe3(PO4)2·8H2O)] in preventing lime-induced iron (Fe) chlorosis in Eureka lemon (Citrus lemon L.) cuttings grafted on sour orange (Citrus aurantium L.) was investigated and compared with the commonly applied iron ethylenediaminedi(o-hydroxyphenylacetic) acid (FeEDDHA). Treatments were suspension of vivianite injected into the soil at three rates (0.5, 1.0, and 2.0 g kg−1 soil), 417 mg FeEDDHA per plant, and untreated plants. Chlorophyll concentration index (CCI) of the youngest fully expanded leaves was estimated. Growth vigor and leaf Fe concentration were also measured. Vivianite, particularly at the greatest two rates, resulted in significantly greater growth vigor and leaf Fe concentration and exhibited greater CCI values compared to untreated plants similar to FeEDDHA. However, if excessive growth vigor is not favorable, the 0.5 g vivianite kg−1 soil is recommended for farmers. Vivianite is a potential environmentally safe alternative to the expensive FeEDDHA to prevent Fe chlorosis in lemon.
Epidemiology and the Magnitude of Coronary Artery Disease and Acute Coronary Syndrome: A Narrative Review

Background: Coronary Artery Disease (CAD) is the foremost single cause of mortality and loss of Disability Adjusted Life Years (DALYs) globally. A large percentage of this burden is found in low and middle income countries. This accounts for nearly 7 million deaths and 129 million DALYs annually and is a huge global economic burden. Objective: To review epidemiological data of coronary artery disease and acute coronary syndrome in low, middle and high income countries. Methods: Keyword searches of Medline, ISI, IBSS and Google Scholar databases. Manual search of other relevant journals and reference lists of primary articles. Results: Review of the results of studies reveals the absolute global and regional trends of the CAD and the importance and contribution of CAD for global health. Data demonstrates which region or countries have the highest and lowest age-standardized DALY rates and what factors might explain these patterns. Results also show differences among the determinants of CAD, government policies, clinical practice and public health measures across the various regions of world. Conclusion: CAD mortality and prevalence vary among countries. Estimation of the true prevalence of CAD in the population is complex. A significant number of countries have not provided data, the estimation of the exact figures for epidemiological data is a barrier. The incidence of CAD continues to fall in developed countries over the last few decades and this may be due to both effective treatment of the acute phase and improved primary and secondary preventive measures. Developing countries show considerable variability in the incidence of CAD. The globalization of the Western diet and increased sedentary lifestyle will have a dramatic influence on the progressive increase in the incidence of CAD in these countries.
Approximate Query Processing for Label-Constrained Reachability Queries

This work presents a graph summarization technique suitable for label-constrained counting reachability queries on property graphs. We showed that the problem of deciding whether there exists an optimal graph summary, i.e., such the number of label-constrained graph partitions is minimal, is NP-complete. We leverage the obtained graph summary for approximate graph query processing. The experiments show fairly high compression ratios of our GRASP summaries on various datasets, along with the low relative error and time gain of approximate query processing on the summaries. In future work, we are interested to further explore the interplay between visualization techniques and AQP along with studying further graph analytics and aggregation operators on top of our summaries.
Strain-Induced Molecular Ordering in Polylactide upon Uniaxial Stretching

This study deals with the tensile drawing behavior of a polylactide material containing 4% of d-stereoisomer units, in the amorphous state. The draw temperature domain spanned from the glass transition to the onset of thermal crystallization, namely 70−100 °C. The stress−strain curves exhibit a strain-hardening strongly sensitive to the draw temperature regarding both the onset and the slope of the phenomenon. A detailed structural investigation reveals that various strain-induced phase changes take place depending on the draw temperature. For Td = 70 °C, a mesomorphic form develops from the strain-oriented amorphous chains, starting at a strain level e ≈ 130%. In the case Td = 90 °C, a well-defined crystalline phase grows beyond the strain e ≈ 250%. In the midtemperature range, i.e. Td = 80 °C, both the mesomorphic and the crystalline phases are generated in parallel. In all cases, the final weight content of ordered phases at rupture was roughly 30%, irrespective of their form. The observed evolution wi.
Clinical significance and prognostic analysis of the phosphorylation levels of Akt proteins in varying molecular subtypes of breast cancer

Objective: Use immunohistochemical approach to detect the levels of expressions of phospho-Akt (p-Akt) (Thr308) and p-Akt (Ser473) proteins in the varying molecular subtypes of breast cancer tissue, and combine clinicopathological data to analyze the relationship between Akt proteins of different activation levels and prognosis of patients with breast tumor. Methods: A total of 136 cases of tissue specimens were collected from patients with breast cancer that were hospitalized in the Breast Surgery and Head & Neck Surgery of Tumor Hospital Affiliated to Xinjiang Medical University between January 2014 and October 2014. The immunohistochemical approach was used to detect the levels of expressions of p-Akt (Thr308) and p-Akt (Ser473) proteins. The detection results were statistically analyzed with the patients’ clinicopathological data and relapse-free survival (RFS). Results: The positive expression rates of p-Akt (308) and p-Akt (473) in malignant breast tumor and peritumoral tissue were 52.9% and 0% respectively, indicating that the difference was statistically significant (P<0.05); the expression of p-Akt (Thr308) protein was related to the tumor histological grade, expression rate of ki67, vascular tumor thrombus, size of primary tumor, molecular subtype and status of axillary lymph node of patients, indicating that the difference was statistically significant (P<0.05); the expression of p-Akt (Thr473) was related to the age, status of pausimenia, vascular tumor thrombus, size of primary tumor and status of axillary lymph node of patients, with P<0.05, indicating that the difference was statistically significant. The multivariate survival analysis illustrated that the 5-year RFS rate of the cases with positive expressions of both p-Akt (thr308) and p-Akt (ser473) was lower than that of patients with negative expression (P<0.05). Conclusion: The positive expressions of p-Akt (Thr308) and p-Akt (Ser473) are closely related to the unfavorable prognosis of patients diagnosed as breast cancer; the targeted therapy for Akt proteins is expected to be a new treatment option for patients diagnosed as breast tumor.
Effects of everolimus combined with letrozole on MIR-429 and ZEB1 in breast cancer

Objective: To investigate the effect of everolimus combined with letrozole on MIR-429 and Zinc finger E-box binding homeobox 1 (ZEB1) in patients with breast cancer. Methods: A total of 159 patients with breast cancer were enrolled, of which 89 patients received everolimus combined with letrozole and were included as the study group (SG). Another 70 patients who received everolimus monotherapy were assigned to the control group (CG). The clinical efficacy and adverse reactions were compared. MIR-429 and ZEB1 before treatment (T0), one week of treatment (T1), two weeks of treatment (T2), three weeks of treatment (T3), four weeks of treatment (T4), and their relationship with treatment time were analyzed. ROC curve was used to analyze the predictive performance of miR-429 and ZEB1 for efficacy. Results: The SG showed significantly increased response rate compared with the CG (P=0.025). miR-429 and ZEB1 did not differ at T0 and T1 (P>0.05), but were lower at T2, T3 and T4 in the SG than in the CG (P<0.001). The levels of miR-429 and ZEB1 of the two groups were the highest at T0, decreased at T1, and were the lowest at T4 (P<0.001). Spearman analysis showed that miR-429 and ZEB1 in the SG were negatively correlated with treatment time (P<0.001). From the results of ROC curve analysis, we observed that the combined detection of miR-429 and ZEB1 has excellent predictive performance for treatment efficacy (P<0.001). Conclusion: Everolimus combined with letrozole is superior to monotherapy for breast cancer, while miR-429, ZEB1 may be potential indicators for the diagnosis and treatment efficacy of breast cancer.
What affects the dependence of oil and U.S. stock markets? A mixed-data sampling copula approach

The dependence of oil and stock markets is an important issue for portfolio selection and risk management. Investors tend to find out the economic factors affecting oil and stock dependence so as to improve their portfolio performance. This paper proposes a mixed frequency data sampling copula model with explanatory variables (copula-MIDAS-X) by incorporating low frequency explanatory variables into the high frequency dynamic copula model. The new model enables us to investigate the impacts of economic factors on the dependence of oil and stock returns, regardless of their marginal distributions. In the application of Brent oil and U.S. stock markets, it is found that the oil and stock dependence is influenced by aggregate demand and stock specific negative news. The impacts of aggregate demand will last for two years, while the impacts of bad news specific in stock market will last for one quarter. The implications to market regulators and investors are that the changes in aggregate demand have influential and long-lasting effects on oil and stock markets. Also, for investors who rebalance portfolios daily or weekly, it is suggested to utilize the information of both monthly economic indicators and daily returns in portfolio management.
Prognostic Value of the Modi ed Model for End- Stage Liver Disease (MELD) Score Including albumin in acute heart failure

Shengen Liao Jiangsu Province Hospital and Nanjing Medical University First A liated Hospital Xinyi Lu Jiangsu Province Hospital and Nanjing Medical University First A liated Hospital Iokfai Cheang Jiangsu Province Hospital and Nanjing Medical University First A liated Hospital Xu Zhu Jiangsu Province Hospital and Nanjing Medical University First A liated Hospital Ting Yin Jiangsu Province Hospital and Nanjing Medical University First A liated Hospital Wenming Yao Jiangsu Province Hospital and Nanjing Medical University First A liated Hospital Haifeng Zhang Jiangsu Province Hospital and Nanjing Medical University First A liated Hospital Xinli Li (  xinli3267@njmu.edu.cn ) Jiangsu Province Hospital and Nanjing Medical University First A liated Hospital https://orcid.org/0000-0002-7889-6359
Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning

—Federated learning (FL) enables many data owners (e.g., mobile devices) to train a joint ML model (e.g., a next-word prediction classiﬁer) without the need of sharing their private training data. However, FL is known to be susceptible to poisoning attacks by malicious participants (e.g., adversary-owned mobile devices) who aim at hampering the accuracy of the jointly trained model through sending malicious inputs during the federated training process. In this paper, we present a generic framework for model poisoning attacks on FL. We show that our framework leads to poisoning attacks that substantially outperform state-of-the-art model poisoning attacks by large margins. For instance, our attacks result in 1 . 5 × to 60 × higher reductions in the accuracy of FL models compared to previously discovered poisoning attacks. Our work demonstrates that existing Byzantine-robust FL algorithms are signiﬁcantly more susceptible to model poisoning than previously thought. Motivated by this, we design a defense against FL poisoning, called divide-and-conquer (DnC). We demonstrate that DnC outperforms all existing Byzantine-robust FL algorithms in defeating model poisoning attacks, speciﬁcally, it is 2 . 5 × to 12 × more resilient in our experiments with different datasets and models.
icepack: a new glacier flow modeling package in Python, version 1.0

Abstract. We introduce a new software package called icepack for modeling the flow of glaciers and ice sheets. Icepack is built on the finite element modeling library Firedrake, which uses the domain-specific language UFL for describing weak forms of partial differential equations. The diagnostic models in icepack are formulated through action principles that are specified in UFL. The components of each action functional can be substituted for different forms of the user’s choosing, which makes it easy to experiment with the model physics. The action functional itself can be used to define a solver convergence criterion that is independent of the mesh and requires little tuning on the part of the user. Icepack includes the 2D shallow ice and shallow stream models. We have also defined a 3D hybrid model based on spectral semi-discretization of the Blatter-Pattyn equations. Finally, icepack includes a Gauss-Newton solver for inverse problems that runs substantially faster than the BFGS method often used in the glaciological literature. The overall design philosophy of icepack is to be as usable as possible for a wide a swath of the glaciological community, including both experts and novices in computational science.
Training Vision Transformers for Image Retrieval

Transformers have shown outstanding results for natural language understanding and, more recently, for image classification. We here extend this work and propose a transformer-based approach for image retrieval: we adopt vision transformers for generating image descriptors and train the resulting model with a metric learning objective, which combines a contrastive loss with a differential entropy regularizer. Our results show consistent and significant improvements of transformers over convolution-based approaches. In particular, our method outperforms the state of the art on several public benchmarks for category-level retrieval, namely Stanford Online Product, In-Shop and CUB-200. Furthermore, our experiments on ROxford and RParis also show that, in comparable settings, transformers are competitive for particular object retrieval, especially in the regime of short vector representations and low-resolution images.
On Disentanglement in Gaussian Process Variational Autoencoders

Complex multivariate time series arise in many fields, ranging from computer vision to robotics or medicine. Often we are interested in the independent underlying factors that give rise to the high-dimensional data we are observing. While many models have been introduced to learn such disentangled representations, only few attempt to explicitly exploit the structure of sequential data. We investigate the disentanglement properties of Gaussian process variational autoencoders, a class of models recently introduced that have been successful in different tasks on time series data. Our model exploits the temporal structure of the data by modeling each latent channel with a GP prior and employing a structured variational distribution that can capture dependencies in time. We demonstrate the competitiveness of our approach against state-of-the-art unsupervised and weakly-supervised disentanglement methods on a benchmark task. Moreover, we provide evidence that we can learn meaningful disentangled representations on real-world medical time series data.