Miracle-dz/UniFAR-FTUs huggingface dataset:
Survival rate of patients with gastric cancer in Hormozgan Province, Iran

Background: Gastric cancer is the fourth most common form of cancer and the second most common cause of death in the world. It is also one of the most common cancers leading to mortality in Iran. Therefore, this study aimed to determine the survival rate of patients with gastric cancer and its affecting factors in the south of Iran (Hormozgan province). Methods: In this study, all patients with gastric cancer (119 patients) that were diagnosed and registered during 2008 to 2013 in Hormozgan province, were studied. All patients were followed to the end of 2015. Kaplan-Meier method and Cox proportional hazards model were used to draw survival curves and to determine the effective factors on the survival rate of surveyed patients. Moreover, Log-rank test was used to evaluate whether or not survival curves for different groups are statistically equivalent (p<0.05). Results: The mean age of the study population was 58.9±14.91, and most of them were men (72.3% (86 persons)). After diagnosis, the survival rates for 1, 2, 3, 4, and 5 years were 62.2%, 49.4%, 43.7%, 39.7%, and 38% respectively. Survival in men were lower than women, but according to log-rank test this difference was not statistically significant (p=0.325). Also patients with advanced stage cancer had significantly lower survival in comparison to individuals with early stage disease (p<0.001). Based on multiple Cox proportional hazards model, job status of the patients and stage of cancer were effective factors on patients’ survival. Conclusion: Based on the findings of the present study, the survival rate was decreased over time after diagnosis. Stage of a cancer at the time of diagnosis is the most important factor affecting the survival of surveyed patients. This shows that there is a crucial need to diagnos the gastric cancer in early stages.
Enhancing Infrastructural Growth in Nigeria: The Sovereign Wealth Fund Strategy

The establishment of the Nigerian Sovereign Wealth Fund (NSWF) with seed capital of $1 billion is by far one of the most significant economic policy decisions taken in recent times. Contrary to expectations, the significant of this decision is not in terms of the monetary implications of the decision. But rather, in terms of what it says about the level of economic and fiscal discipline that the Government at all levels in Nigeria wish to bring to bear on the process of sovereign resource management. Nevertheless, this review believes that the three core mandate given to the fund to pursue concurrently is a bit ambitious and duplicatory of roles performed by the foreign reserve and excess crude account among others. It recommends the pursuance of infrastructural development only for a period of at least ten years, due to its accelerative effect on economic growth and development, through increased productivity and economic competitiveness in the global market.
Infectious Keratitis: The Great Enemy

Infectious keratitis tops the list of diseases leading to visual impairment and corneal blindness. Corneal opacities, predominantly caused by infectious keratitis, are the fourth leading cause of blindness globally. In the developed countries, infectious keratitis is usually associated with contact lens wear, but in developing countries, it is commonly caused by trauma during agricultural work. The common causative organisms are bacteria, fungus, Acanthamoeba, and virus. Severe cases can progress rapidly and cause visual impairment or blindness that requires corneal transplantation, evisceration, or enucleation. The precise clinical diagnosis, accurate diagnostic tools, and timely appropriate management are important to reduce the morbidity associated with infectious keratitis. Despite the advancement of diagnostic tools and antimicrobial drugs, outcomes remain poor secondary to corneal melting, scarring, or perforation. Eye care strategies should focus on corneal ulcer prevention. This review addresses the epidemiology, diagnostic approach, clinical manifestations, risk factors, investigations, treatments, and the update of major clinical trials about common pathogens of infectious keratitis.
ON THE FULL NUMBER OF COLLISIONS IN CERTAIN ONE-DIMENSIONAL BILLIARD PROBLEMS

In the present work we consider motion of a light particle between a wall and a massive particle. Collisions in the system are elastic. In [1] the full number of collisions in this system was calculated. It turned out to be approximately equal to the product of number π and the square root of ratio of the particles’ masses. This formula was derived using reduction of the system to a billiard. In the present work this result is derived by means of the adiabatic perturbation theory for systems with impacts [2].
Frequency of Mycoplasma haemocanis infection in dogs of Cuiaba, Mato Grosso, Brazil

Haemotropic mycoplasmas are pleomorphic, epicellular, gram-negative bacteria, which infect red blood cells. In dogs, the acute phase of this infection may lead to haemolytic anaemia potentially precipitated by splenectomy, or by immunosuppressive drugs or diseases; however, in cases of chronic infection, the signs are inapparent. Molecular techniques and microscopic observation are the most commonly used methods to diagnose mycoplasma infection, though studies about haemotropic mycoplasma infections in dogs from Cuiabá, capital of Mato Grosso, Brazil are scarce. The objective of this study was to evaluate the frequency of mycoplasma infection, the Mycoplasma species present, and factors associated with infection in 334 dogs diagnosed using polymerase chain reaction (PCR). The frequency of infection was 5.4%, and M. haemocanis was the only species identified. No epidemiological factor investigated showed a statistically significant association with infection, including tick infestation.
An Empirical Reassessment of the Commodity Storage Model

We perform an empirical assessment of the rational expectations commodity storage model, with the specific aim of resolving the model’s apparent inability to explain the high autocorrelation historically exhibited by primary commodity prices. In contrast to recent empirical tests of the model, we employ a classical supply of storage formulation to explain speculative and precautionary storage. To estimate the model, we develop a nested maximum likelihood estimation procedure that relies on numerical nonlinear functional equation methods to solve for the implied rational expectations equilibrium. Our results indicate that the rational expectations storage model can explain the autocorrelation exhibited by commodity prices extremely well, challenging recent findings to the contrary. ∗The authors are Associate Professor and Postdoctoral Fellow, respectively, The Ohio State University, 2120 Fyffe Road, Columbus, OH, 53711, USA. Senior authorship is shared equally.
Iterative PSO Algorithms for GRAP Problems

This paper studies the grap problems of two-state, in which the subsystem allows components to be mixed (i.e. the subsystem selects components from several types of heterogeneous components, and the number of selected components types >=1). Each component has a fixed reliability, weight and price, and determines the number of selected components, so that the system has the greatest reliability under the given cost and weight constraints. The coding method of the solution is that the number of elements of each type of subsystem is a variable, and the whole system is arranged in the order of subsystems to form row vectors. An iterative particle swarm optimization algorithm with fixed compression coefficient and dynamic inertia weight is constructed to solve the problem. Typical improved fyffe problems are tested, and the optimal solutions are obtained, which are consistent with the results given by the substitution constraint method. The pso algorithm presented in this paper can effectively solve the grap problem which is allowed to mix components in subsystems.
The Role of Productive Water Use in Women’s Livelihoods: Evidence from Rural Senegal

Enhancing livelihoods and promoting gender equity are primary goals of rural development programmes in Africa. This article explores the role of productive water use in relation to these goals based on 1860 household surveys and 15 women’s focus groups conducted in four regions of Senegal with small-scale piped water systems. The piped systems can be considered 'domestic plus' systems because they were designed primarily for domestic use, and also to accommodate small-scale productive uses including livestock-raising and community-gardening. This research focuses on the significance of productive water use in the livelihood diversification strategies of rural women. In Senegal, we find that access to water for productive purposes is a critical asset for expanding and diversifying rural livelihoods. The time savings associated with small piped systems and the increased water available allowed women to enhance existing activities and initiate new enterprises. Women’s livelihoods were found to depend on productive use activities, namely livestock-raising and gardening, and it is estimated that one half of women’s incomes is linked to productive water use. While these findings are largely positive, we find that water service and affordability constraints limit the potential benefits of productive water use for women and the poorest groups. Implications for targeting women and the poorest groups within the domestic plus approach are discussed.
COMPETITION AND RISK TAKING BEHAVIOR OF BANKS: NEW EVIDENCE FROM MARKET POWER AND CAPITAL REQUIREMENTS

The relationship between competition and banking stability has resulted in two opposing paradigms; competition-fragility view suggests that increased competition erodes market power and encourages banks to take excessive risks. In contrast, the competition-stability view suggests that, low competition results in more market power which may encourage the banks to charge higher loan rates adversely affecting borrowers by risk shifting mechanisms. Given these opposing predictions in the literature, this study aims to test the two views, considering the effects of market power and capital requirements on the riskiness of Pakistani banks. Utilizing annual data for 30 banks over the period of 2004 to 2017, in a dynamic two step system GMM. We construct Lerner index as a direct measure of market power for the banking industry. Our findings support the competition stability paradigm in the case of Pakistan. We also find that the theoretical link between capitalization ratio and market power is sufficiently strong and should be encouraged as greater capital buffers reduce risk exposure.
STORE LOYALTY ON ONLINE STORE CUSTOMERS IN INDONESIA

Nowadays, online retailing in Indonesia had flourished and estimated to be one of the most prominent foundation to boost Indonesia’s economic growth. Aiming to anticipate the trend, this research is written in order to gain a deeper understanding about the loyalty behavior among online store customers in Indonesia by investigating the influence of store image and perceived value towards online store loyalty. Data in this research were collected from online questioner sent troughout online forum and social media. Structural Equation Modelling method is used here along with software Lisrel 8.80. Past studies found that online store image, perceived utilitarian value and perceived hedonic value positively influences one of several dimensions of loyalty, repurchase intention. This research proves that online store image directly influences perceived utilitarian value, perceived hedonic value and online store loyalty while neither perceived utilitarian value nor perceived hedonic value directly influences online store loyalty. This research also found that ease of use and trustworthiness as the most reliable and influential dimensions in online store image.
Manner and Result in English Verb Roots

manner/result complementarity hypothesis (MRC) proposed by Rappaport Hovav and Levin (1998, 2010) holds that a verb root cannot lexicalize manner and result meaning components simultaneously at a time. It has generated much interest and controversy among researchers. In spite of much evidence for it, researchers have also put forward a variety of arguments against it. This paper reviews arguments against the MRC hypothesis, reexamines the data these counterarguments are based on and reveals that these arguments do not pose real challenge for the MRC hypothesis. Counterexample verbs which are proposed to entail both manner and result actually lexicalize only one, either manner or result, and manner and result are indeed meaning component lexicalized in verb roots rather than aspectual focus.
PGPM_A_198224 145..154

Hamdy Awad Ahmed Ahmed Richard D Urman Nicoleta Stoicea Sergio D Bergese 1Department of Anesthesiology, The Ohio State University Wexner Medical Center, Columbus, OH, USA; 2Department of Anesthesiology, The University of Texas, Houston, TX, USA; 3Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA; 4Department of Biological Chemistry and Pharmacology, The Ohio State University Wexner Medical Center, Columbus, OH, USA; 5Department of Neurological Surgery, The Ohio State University Wexner Medical Center, Columbus, OH, USA Abstract: In 2001, a group of European academic surgeons created the Enhanced Recovery After Surgery (ERAS) study group and established the first official ERAS protocol. One of the most significant challenges during ERAS implementation is variability of drugs used throughout the perioperative period. Pharmacogenomic testing (blood or saliva) results (obtained within approximately 48 hrs) provide guidelines on how to prescribe the optimal drug with the optimal dosage to each patient based on an individual’s unique genetic profile. Pharmacogenomic testing of various methods of multimodal analgesia is an essential element of ERAS protocols spanning the entire perioperative period to ultimately optimize postoperative pain control. The key goal for anesthetic management in ERAS protocols is to facilitate rapid emergence by using the shortest acting agents available, thus accelerating recovery and reducing length of stay, hospital expenses, and postoperative complications. Postoperative nausea and vomiting (PONV) is an additional challenge that should be overcome to ensure an enhanced recovery and shorter length of stay with the use of antiemetics. Postoperative ileus (POI) can result in longer hospital stay with increasing susceptibility to associated morbidities along with an increase in associated hospitalization costs. Geneticsguided pharmacotherapy and its impact on clinical outcomes should be thoroughly studied for better understanding and managing drug administration in the settings of ERAS.
Service Quality Towards Bank Customer Loyalty (Empirical Study at BNI USU Medan)

This study aims to analyze the influence of service quality on customer loyalty at PT. BNI (Persero), Tbk USU Medan. This study used a quantitative approach with an explanatory type of research. The sample were 120 respondents and processed statistically using simple linear regression method. The results show that service quality positively has a significant effect on customer loyalty. These findings indicate that good service quality will encourage the interest of customers to conduct transactions continuously and repeatedly in the present and future in a bank.
Quantum Field Theory in CurvedSpacetime and Anomalies

Hawking radiation and Unruh effect are two well-known examples of the effect of quantum fields in curved spacetime. Anomalies play an important role in quantum field theory. It has been shown that anomalies can be used to find Hawking temperature. In this Master's thesis, we review Quantum Field Theory in Curved Spacetime (including Unruh and Hawking effects) and then study the application of gravitational anomalies for deriving Hawking radiation in Schwarzschild spacetime.
Deep Learning for Over-the-Air Non-Orthogonal Signal Classification

Non-cooperative communications, where a receiver can automatically distinguish and classify transmitted signal formats prior to detection, are desirable for low-cost and low-latency systems. This work focuses on the deep learning enabled blind classification of multi-carrier signals covering their orthogonal and non-orthogonal varieties. We define Type-I signals with large feature diversity and Type-II signals with strong feature similarity. We evaluate time-domain and frequency-domain convolutional neural network (CNN) models with wireless channel/hardware impairments. Experimental systems are designed and tested, using software defined radio (SDR) devices, operated for different signal formats in line-of-sight and non-line-of-sight communication link scenarios. Testing, using four different time-domain CNN models, showed the pre-trained CNN models to have limited efficiency and utility due to the mismatch between the analytical/simulation and practical/real-world environments. Transfer learning, which is an approach to fine-tune learnt signal features, is applied based on measured over-the-air time-domain signal samples. Experimental results indicate that transfer learning based CNN can efficiently distinguish different signal formats for Type-I in both line-of-sight and non-line-of-sight scenarios relative to the non-transfer-learning approaches. Type-II signals are not identified correctly in the experiment even with the transfer learning assistance leading to potential applications in secure communications.
A Machine‐Learning Approach for Earthquake Magnitude Estimation

In this study, we present a fast and reliable method for end‐to‐end estimation of earthquake magnitude from raw waveforms recorded at single stations. We design a regressor (MagNet) composed of convolutional and recurrent neural networks that is not sensitive to the data normalization, hence waveform amplitude information can be utilized during the training. The network can learn distance‐dependent and site‐dependent functions directly from the training data. Our model can predict local magnitudes with an average error close to zero and standard deviation of ~0.2 based on single‐station waveforms without instrument response correction. We test the network for both local and duration magnitude scales and show a station‐based learning can be an effective approach for improving the performance. The proposed approach has a variety of potential applications from routine earthquake monitoring to early warning systems.
A systematic literature review of the Prisoner's Dilemma; collaboration and influence

The Prisoner's Dilemma is a well known game used since the 1950's as a framework for studying the emergence of cooperation; a topic of continuing interest for mathematical, social, biological and ecological sciences. The iterated version of the game, the Iterated Prisoner's Dilemma, attracted attention in the 1980's after the publication of the "The Evolution of Cooperation" and has been a topic of pioneering research ever since. The aim of this paper is to provide a systematic literature review on Prisoner's Dilemma related research. This is achieved in two ways. Firstly, we review selected pieces of work and partition the literature into five different sections with each reviewing a different aspect of research. Secondly, we analyse a comprehensive data set of 3077 articles on the Prisoner's Dilemma collected from five different prominent journals. The questions answered in this manuscript are (1) what are the research trends in the field, (2) what are the already existing results within the field, (3) how collaborative is the field and (4) do authors influence the field more compared to other fields.
Syntax-Infused Transformer and BERT models for Machine Translation and Natural Language Understanding

Attention-based models have shown significant improvement over traditional algorithms in several NLP tasks. The Transformer, for instance, is an illustrative example that generates abstract representations of tokens inputted to an encoder based on their relationships to all tokens in a sequence. Recent studies have shown that although such models are capable of learning syntactic features purely by seeing examples, explicitly feeding this information to deep learning models can significantly enhance their performance. Leveraging syntactic information like part of speech (POS) may be particularly beneficial in limited training data settings for complex models such as the Transformer. We show that the syntax-infused Transformer with multiple features achieves an improvement of 0.7 BLEU when trained on the full WMT 14 English to German translation dataset and a maximum improvement of 1.99 BLEU points when trained on a fraction of the dataset. In addition, we find that the incorporation of syntax into BERT fine-tuning outperforms baseline on a number of downstream tasks from the GLUE benchmark.
Hierarchy of Relaxation Timescales in Local Random Liouvillians.

To characterize the generic behavior of open quantum systems, we consider random, purely dissipative Liouvillians with a notion of locality. We find that the positivity of the map implies a sharp separation of the relaxation timescales according to the locality of observables. Specifically, we analyze a spin-1/2 system of size ℓ with up to n-body Lindblad operators, which are n local in the complexity-theory sense. Without locality (n=ℓ), the complex Liouvillian spectrum densely covers a "lemon"-shaped support, in agreement with recent findings [S. Denisov et al., Phys. Rev. Lett. 123, 140403 (2019)PRLTAO0031-900710.1103/PhysRevLett.123. 140403]. However, for local Liouvillians (n<ℓ), we find that the spectrum is composed of several dense clusters with random matrix spacing statistics, each featuring a lemon-shaped support wherein all eigenvectors correspond to n-body decay modes. This implies a hierarchy of relaxation timescales of n-body observables, which we verify to be robust in the thermodynamic limit. Our findings for n locality generalize immediately to the case of spatial locality, introducing further splitting of timescales due to the additional structure.
A closer look at the spur, blob, wiggle, and gaps in GD-1

The GD-1 stream is one of the longest and coldest stellar streams discovered to date, and one of the best objects for constraining the dark matter properties of the Milky Way. Using data from Gaia DR2, we study the proper motions (PMs), distance, morphology, and density of the stream to uncover small-scale perturbations. The PM cleaned data show a clear distance gradient across the stream, ranging from 7 to 12 kpc. However, unlike earlier studies that found a continuous gradient, we uncover a distance minimum at φ1 ≈ −40 deg, after which the distance increases again. We can reliably trace the stream between −85 < φ1 <15 deg, showing an even further extent to GD-1 beyond the earlier extension of Price-Whelan and Bonaca. We constrain the stream track and density using a Boolean matched filter approach and find three large under densities and significant residuals in the stream track lining up with these gaps. The gaps are located at φ1 = −36, −20, and −3 deg, with the gap at −3 deg being surrounded by a clear sinusoidal wiggle. We argue that this wiggle is due to a perturbation since it has the wrong orientation to come from a progenitor. We compute a total initial stellar mass of the stream segment of 1.58 ± 0.07 × 104 M⊙. With the extended view of the spur in this work, we argue that the spur may be unrelated to the adjacent gap in the stream. Finally, we show that an interaction with the Sagittarius dwarf can create features similar to the spur.