The use of residual analysis to improve the error rate accuracy of machine translation.

The aim of the study is to compare two different approaches to machine translation-statistical and neural-using automatic MT metrics of error rate and residuals. We examined four available online MT systems (statistical Google Translate, neural Google Translate, and two European commission's MT tools-statistical mt@ec and neural eTranslation) through their products (MT outputs). We propose using residual analysis to improve the accuracy of machine translation error rate. Residuals represent a new approach to comparing the quality of statistical and neural MT outputs. The study provides new insights into evaluating machine translation quality from English and German into Slovak through automatic error rate metrics. In the category of prediction and syntactic-semantic correlativeness, statistical MT showed a significantly higher error rate than neural MT. Conversely, in the category of lexical semantics, neural MT showed a significantly higher error rate than statistical MT. The results indicate that relying solely on the reference when determining MT quality is insufficient. However, when combined with residuals, it offers a more objective view of MT quality and facilitates the comparison of statistical MT and neural MT.

In silico hemodynamical simulations show additional benefits of artery wall softening induced by antihypertensive drugs.

BACKGROUND AND OBJECTIVES: Age-related arterial stiffening increases peripheral resistance and decreases arterial distensibility, thus contributing to hypertension, an important risk factor of atherosclerosis. It causes abnormal blood flow, endothelial dysfunction, higher pulse wave velocity, and consequently elevated pressure wave amplitude. METHODS: This paper presents the influence of these changes via multiscale 3D-0D transient computational fluid dynamics simulations of blood flow in five patient-specific geometries of human carotid bifurcation using archetypal flow waveforms for young and old subjects. RESULTS: The proposed model shows a significant decrease in the time-averaged wall shear stress (TAWSS) for the old archetypal flow waveform. This is in good agreement with clinical data on a straight segment of common carotid arteries available for young and old subjects. Moreover, our study showed that the decrease of area-averaged TAWSS related to the old flow waveform is much more pronounced (2.5 ÷ 4.5 times higher) at risk areas (areas showing TAWSS below its threshold value of 0.48 Pa) than in straight segments commonly considered in clinical studies. CONCLUSIONS: Since arterial stiffness can be lowered through long-term usage of any of the five basic groups of antihypertensives, possible benefits of such medical therapy could be not only lowering blood pressure and peripheral resistance but also in increasing the TAWSS and thus attenuating an important mechanism of the atherosclerotic process.

Increased cardiovascular mortality in patients with mechanically expandable transcatheter aortic valve and without permanent pacemaker.

INTRODUCTION: Use of the mechanically expandable transcatheter aortic valve (MEV) has been recently linked to increased risks of valve dysfunction and cardiovascular mortality. The risk of developing conduction disturbance with the MEV valve is well known, and the negative prognostic impact of permanent pacemaker implantation (PPI) after transcatheter aortic valve implantation is another consideration. AIM: This study aimed to compare the mid-term survival of patients with MEV and self-expandable valves (SEV), and to examine survival of both groups according to the presence or absence of PPI. METHODS: This single-centre, retrospective, observational study examined data from MEV and SEV groups comprising 92 and 373 patients, respectively. The mean clinical follow-up was 2.5±1.7 years. Mortality information was obtained from the National Institutes of Health Information and Statistics. RESULTS: Baseline characteristics were comparable between the groups. The log-rank test showed higher cardiovascular mortality in the MEV group (p=0.042; the relative risk (RR) 1.594 (95% CI 1.013 to 2.508)). The Cox proportional hazards model identified MEV implantation as an independent predictor of cardiovascular mortality. The rate of PPI was twice as high in the MEV vs SEV group (33.7% vs 16.1%; p<0.001). We compared the survival of both groups according to the presence or absence of PPI and found higher mortality in the MEV group without PPI versus the SEV group without PPI (p=0.007; RR 2.156 (95% CI 1.213 to 3.831)). Survival did not differ in the groups with PPI. CONCLUSIONS: A higher mid-term cardiovascular mortality rate was observed with MEV versus SEV implants. Comparing both groups according to the presence or absence of PPI, we observed a higher mortality risk in patients with MEV without PPI than in SEV without PPI. In contrast, mortality did not differ between the groups when PPI was implanted.

Woven Carbon-Fiber-Reinforced Polymer Tubular Mesh Reinforcement of Hollow High-Performance Concrete Beams.

This article presents woven carbon-fiber-reinforced polymer (CFRP) tubular mesh used as a reinforcement on the inner surface of hollow beams made of high-performance concrete (HPC). The tubular mesh was designed to serve as both the tensile and shear reinforcement of hollow beams intended for the construction of small self-supporting structures that could be assembled without mechanization. The reinforcement was prepared with a tri-axial weaving machine from carbon filament yarn and was homogenized using epoxy resin. The interaction of the composite reinforcement with the cementitious matrix was investigated, and the surface of the reinforcement was modified using silica sand and polyvinyl alcohol (PVA) fibers to improve cohesion. The sand coating enhanced bond strength, resulting in the significantly higher flexural strength of the hollow beam of 128%. The PVA fibers had a lower positive effect of 64% on the flexural strength but improved the ductility of the beam. Individual beams were connected by gluing steel parts directly inside the hollow core of the HPC beam. This procedure provides good interaction between the CFRP reinforcement and the glued steel insert and allows for the fast and simple assembly of structures. The weaving of additional layers of the CFRP reinforcement around HPC beams was also explored. A small structure made of the hollow HPC beams with inner composite reinforcement was constructed to demonstrate the possibilities of the presented technology.

An interpretable system for predicting the impact of COVID-19 government interventions on stock market sectors.

Evaluating and understanding the financial impacts of COVID-19 has emerged as an urgent research agenda. Nevertheless, the impacts of government interventions on stock markets remain poorly understood. This study explores, for the first time, the impact of COVID-19 related government intervention policies on different stock market sectors using explainable machine learning-based prediction models. The empirical findings suggest that the LightGBM model provides excellent prediction accuracy while preserving computationally efficient and easy explainability of the model. We also find that COVID-19 government interventions are better predictors of stock market volatility than stock market returns. We further show that the observed effects of government intervention on the volatility and returns of ten stock market sectors are heterogeneous and asymmetrical. Our findings have important implications for policymakers and investors in terms of promoting balance and sustaining prosperity across industry sectors through government interventions.

Illumination of Interior Spaces through Structures Made of Unified Slabs of High-Performance Light-Transmitting Concrete with Embedded Optical Fibers.

Light-transmitting concrete as a building material already exists in many forms, but its light properties and the possibilities of using it to improve the lighting of interior spaces have not been investigated in detail yet. This paper focuses on the illumination of interior spaces using constructions made of light-transmitting concrete, which will allow light to pass between individual spaces. The experimental measurements carried out are divided into two typical situations using reduced room models. The first part of the paper focuses on the illumination of the room through the penetration of daylight through the ceiling made of light-transmitting concrete. The second part of the paper investigates the transmission of artificial light from one room to another through a non-load-bearing dividing structure composed of unified slabs of light-transmitting concrete. For the experiments, several models and samples were created for comparison. The first step of the experiment was to create slabs of light-transmitting concrete. While there are many options to produce such a slab, the best option is to use high-performance concrete with glass-fiber reinforcement, which improves the load transfer properties, and plastic optical fibers for light transmission. By adding optical fibers, we can achieve the transmission of light between any two spaces. For both of the experiments, we used reduced-scale models of rooms. Slabs with dimensions of 250 × 250 × 20 mm and 250 × 250 × 30 mm were used in three versions: concrete slabs with optical fibers, concrete slabs with air holes and solid slabs. The experiment measured and compared the level of illumination at several points in the model as it passed through each of the three different slabs. Based on the results of these experiments, it was concluded that the interior level of illumination of any space can be improved by using light-transmitting concrete, especially those without access to natural light. The experiment also assessed the strength properties of the slabs in relation to their intended use and compares them with the properties of stone slabs used as cladding.

Reinforced L-Shaped Frame Made of Textile-Reinforced Concrete.

Textile-reinforced concrete is becoming more and more popular. The material enables the realization of very thin structures and shells, often with organic shapes. However, a problem with this reinforcement occurs when the structure is bent (contains a corner), and the flexural stiffness around this bent area is required. This article presents the design, solution, and load-bearing capacity of an L-shaped rigid frame made of textile-reinforced concrete. Basic material parameters of concrete matrix and carbon textile reinforcement were supplemented by a four-point bending test to calibrate fracture energy Gf, critical compressive displacement Wd, solver type, and other parameters of a numerical model created by Atena Engineering in specialized non-linear structural analysis software for reinforced concrete structures. The calibrated numerical model was used to evaluate different variants of carbon textile reinforcement of the L-shaped frame. The carbon textile reinforcement was homogenized using epoxy resin to ensure the interaction of all fibers, and its surface was modified with fine-grained silica sand to increase the cohesion with the concrete matrix. Specimens were produced based on the most effective variant of the L-shaped frame reinforcement to be experimentally tested. Thanks to the original shaping and anchoring of the reinforcement in the corner area, the frame with composite textile reinforcement is rigid and can transmit the bending stresses in both positive and negative directions. The results of the mechanical loading test on small experimental specimens correspond well to the results of numerical modeling using Atena Engineering software.

Effect of twitter investor engagement on cryptocurrencies during the COVID-19 pandemic.

This study aims to examine whether the prices and returns of two cryptocurrencies, Dogecoin and Ethereum, are affected by Twitter engagement following the COVID-19 pandemic. We use the autoregressive integrated moving average with explanatory variables model to integrate the effects of investor attention and engagement on Dogecoin and Ethereum returns using data from December 31, 2020, to May 12, 2021. The results provide evidence supporting the hypothesis of a strong effect of Twitter investor engagement on Dogecoin returns; however, no potential impact is identified for Ethereum. These findings add to the growing evidence regarding the effect of social media on the cryptocurrency market and have useful implications for investors and corporate investment managers concerning investment decisions and trading strategies.

[Ulnar Carpus Translation - our Experience]. / Ulnare Karpustranslation ­ unsere Erfahrungen.

The ulnar translation (UT) of the wrist is a rare but often missed injury. We report about our experiences in the treatment of 8 patients with an imminent (5), established (1), and chronic UT (2).

Design of Performance-Based Concrete Using Sand Reclaimed from Construction and Demolition Waste-Comparative Study of Czechia and India.

The main goal and novelty of this study is to show the transferability of practices and experiences with the use of reclaimed sand worldwide in the case in two different regions, the Czech Republic and India, which is necessary for both regions due to the sand availability (Czech Republic) and illegal sand mining including criminal offences (India). Due to the deteriorating environmental impacts associated with sand mining, finding substitution possibilities for natural sand is becoming more important worldwide. It is realized that the reuse of construction demolition waste concrete is inevitable in the pursuit of circular concrete and cleaner production, envisioned by the United Nations (UN) as the attainment of ensuring sustainable consumption and production patterns (Sustainable Development Goal 12-SDG 12) with an inclusive approach of partnerships to achieve the goal (Sustainable Development Goal 17-SDG 17) for the validation of results. The basic material properties of reclaimed sand were examined, and its impact on the physical, mechanical, and durability properties of concrete with complete replacement of sand was evaluated. Generally, a slight decline in properties of concrete with fine recycled aggregate was found. No significant decrease was found from usage possibility in the point of view of its utilization in specific structures and conditions. The research shows the slight differences of results between the Czech and Indian investigations, which are not essential for the transferability of the results.

Alkali-silica Reaction Elimination Potential of High-Performance Concrete Containing Glass Powder.

This study is mainly concerned with the assumption that glass powder can eliminate the potential alkali-silica reaction in high performance concrete. Glass is often land filled, produced as a secondary raw material or as a by-product of production. Chemical analyses were carried out, and the ecotoxicity of the material was investigated, serving as a basis for testing a potential alkali-silica reaction. High performance concrete (HPC) containing different types of waste powder (secondary raw material from production (SGP), jewelry production (SGJ), container waste glass (CWG), and glass from used photovoltaic panels (GPP)) are tested according to the international standard ASTM C1260 and the Czech technical condition TP 137. Newly designed mixtures are innocuous from the ASR point of view in the most cases, except SGP HPC.

Fraud Detection in Mobile Payment Systems using an XGBoost-based Framework.

Mobile payment systems are becoming more popular due to the increase in the number of smartphones, which, in turn, attracts the interest of fraudsters. Extant research has therefore developed various fraud detection methods using supervised machine learning. However, sufficient labeled data are rarely available and their detection performance is negatively affected by the extreme class imbalance in financial fraud data. The purpose of this study is to propose an XGBoost-based fraud detection framework while considering the financial consequences of fraud detection systems. The framework was empirically validated on a large dataset of more than 6 million mobile transactions. To demonstrate the effectiveness of the proposed framework, we conducted a comparative evaluation of existing machine learning methods designed for modeling imbalanced data and outlier detection. The results suggest that in terms of standard classification measures, the proposed semi-supervised ensemble model integrating multiple unsupervised outlier detection algorithms and an XGBoost classifier achieves the best results, while the highest cost savings can be achieved by combining random under-sampling and XGBoost methods. This study has therefore financial implications for organizations to make appropriate decisions regarding the implementation of effective fraud detection systems.

Mid-term outcomes of patients with Lotus and Evolut transcatheter valves.

Introduction: Long-term data on the Lotus® (Boston Scientific, USA) valve are lacking. Aim: To evaluate mid-term outcomes of aortic stenosis patients treated with either Lotus or Evolut R® valves (Medtronic, USA). Material and methods: Our study sample comprised 190 patients (71 Lotus and 119 Evolut valves). The mean clinical follow-up was 2.0 ±0.9 years. Information on mortality was obtained from the National Institutes of Health Information and Statistics. Results: No significant differences existed in baseline characteristics between the groups. The rate of procedural complications was low and without significant differences between groups. The log rank test showed higher mortality in the Lotus group for cardiovascular mortality (p = 0.02; RR = 2.4, 95% CI: 1.123-5.075). Multivariable analysis revealed that the Lotus valve was independently associated with cardiovascular mortality (p = 0.03). At the end of echocardiography follow-up (4.1 ±0.9 years), we found a significantly higher mean aortic valve gradient (AVGm) in the Lotus group than in the Evolut group (17.9 ±9.5 vs. 10.2 ±3.5 mm Hg; p = 0.0006), and 3 (10%) patients from the Lotus group suffered from symptomatic re-stenosis requiering re-intervention. Conclusions: The results of our study suggest that higher cardiovascular mortality rates during mid-term follow-up were associated with Lotus compared with Evolut valves. Higher AVGm in the Lotus valves suggests the possibility of accelerated prosthesis degeneration.

Current issues of body donation for teaching and research purposes and their use in the Czech Republic.

Since time immemorial, bodies of deceased have been an integral part of teaching anatomy, and therefore the study of medicine. Without them, the teaching of anatomy, clinical anatomy and many research projects could not be realized. Nowadays, the European countries allow to use exclusively bodies of the deceased donors. Recently, we have registered a growing trend in the needs of the bodies not only for the purposes of medical education, but also for those of clinical anatomy. The question also arose of the suitability of using COVID-19 positive donors or the legislative possibility of obtaining bodies in the absence of donors in the donor program. Our communication addresses current issues of body donation for teaching and research purposes and their use in the Czech Republic.

The impact of education as a marker of socio-economic status on survival of patients after transcatheter aortic valve implantation.

Introduction: An association exists between low socio-economic status (SES) and increased cardiovascular and all-cause mortality worldwide. Aim: To evaluate the impact of educational level as a marker of socio-economic status (SES) on the clinical condition of patients before transcatheter aortic valve implantation (TAVI) and survival after TAVI. Material and methods: We conducted a retrospective observational study involving patients with severe aortic stenosis (AS) who underwent TAVI. We divided patients based on their level of education into lower (LLE) and higher educational level (HLE) groups. We evaluated periprocedural (combined endpoints of device success (DS) and early safety (ES), according to VARC2 criteria) and mid-term outcomes (all-cause and cardiovascular mortality). Results: Of the 379 study patients, 212 were in the LLE group. The mean follow-up was 2.1 ±1.8 years. Patients with a LLE were younger (77.4 ±7.2 vs. 79.4 ±6.5 years, p = 0.006) and more often female (58% vs. 40%, p < 0.001). They had higher body mass index (29.5 ±5.7 vs. 28.3 ±4.8, p = 0.037), more often type 2 diabetes mellitus (43% vs. 31%, p = 0.013) and moderate or severe aortic regurgitation (8% vs. 2%, p = 0.026), and some patients' condition required urgent TAVI (5% vs. 0%, p = 0.003). There were no differences in combined procedural endpoints. The all-cause mortality during mid-term follow-up was 25% in the LLE group and 24% in the HLE group (log-rank, p = 0.941). Cardiovascular mortality was 19% in both groups (log-rank, p = 0.925). Conclusions: Patients with an LLE required TAVI at a younger age, had more comorbidities and had a more risky profile. Level of education did not influence periprocedural and mid-term outcomes.

Experimental Evaluation of Carbon Reinforced TRC with Cement Suspension Matrix at Elevated Temperature.

Textile-reinforced concrete (TRC) is a new composite material comprising high-performance concrete and textile reinforcement from textile yarns with a matrix, usually consisting of epoxy resins (ER). The most significant advantage of ER is the homogenization of all filaments in the yarn and full utilization of its tensile potential. Nevertheless, ER matrix is a critical part of TRC design from the perspective of the fire resistance due to its relatively low resistance at temperatures of approximately 120 ∘C. This work expands the previously performed mechanical tests at normal temperatures with cement suspension (CS) as a non-combustible material for the yarn matrix. Here, the mechanical properties of CS matrix at elevated temperatures were verified. It was found that the addition of polypropylene fibers into HPC negatively affected the mechanical results of CS matrix specimens. Simultaneously, thermal insulation effect of the covering layers with different thicknesses did not significantly influence the residual bending strength of specimens with CS matrix and achieved similar results as reference specimens. Furthermore, all specimens with ER matrix progressively collapsed. Finally, CS as a textile reinforcement of yarn matrix appears to be a suitable solution for increasing the temperature resistance of TRC structures and for substituting synthetic resins.

Deep learning-based exchange rate prediction during the COVID-19 pandemic.

This study proposes an ensemble deep learning approach that integrates Bagging Ridge (BR) regression with Bi-directional Long Short-Term Memory (Bi-LSTM) neural networks used as base regressors to become a Bi-LSTM BR approach. Bi-LSTM BR was used to predict the exchange rates of 21 currencies against the USD during the pre-COVID-19 and COVID-19 periods. To demonstrate the effectiveness of our proposed model, we compared the prediction performance with several more traditional machine learning algorithms, such as the regression tree, support vector regression, and random forest regression, and deep learning-based algorithms such as LSTM and Bi-LSTM. Our proposed ensemble deep learning approach outperformed the compared models in forecasting exchange rates in terms of prediction error. However, the performance of the model significantly varied during non-COVID-19 and COVID-19 periods across currencies, indicating the essential role of prediction models in periods of highly volatile foreign currency markets. By providing an improved prediction performance and identifying the most seriously affected currencies, this study is beneficial for foreign exchange traders and other stakeholders in that it offers opportunities for potential trading profitability and for reducing the impact of increased currency risk during the pandemic.

The role of automated evaluation techniques in online professional translator training.

The rapid technologisation of translation has influenced the translation industry's direction towards machine translation, post-editing, subtitling services and video content translation. Besides, the pandemic situation associated with COVID-19 has rapidly increased the transfer of business and education to the virtual world. This situation has motivated us not only to look for new approaches to online translator training, which requires a different method than learning foreign languages but in particular to look for new approaches to assess translator performance within online educational environments. Translation quality assessment is a key task, as the concept of quality is closely linked to the concept of optimization. Automatic metrics are very good indicators of quality, but they do not provide sufficient and detailed linguistic information about translations or post-edited machine translations. However, using their residuals, we can identify the segments with the largest distances between the post-edited machine translations and machine translations, which allow us to focus on a more detailed textual analysis of suspicious segments. We introduce a unique online teaching and learning system, which is specifically "tailored" for online translators' training and subsequently we focus on a new approach to assess translators' competences using evaluation techniques-the metrics of automatic evaluation and their residuals. We show that the residuals of the metrics of accuracy (BLEU_n) and error rate (PER, WER, TER, CDER, and HTER) for machine translation post-editing are valid for translator assessment. Using the residuals of the metrics of accuracy and error rate, we can identify errors in post-editing (critical, major, and minor) and subsequently utilize them in more detailed linguistic analysis.

Mechanical metric for skeletal biomechanics derived from spectral analysis of stiffness matrix.

A new metric for the quantitative and qualitative evaluation of bone stiffness is introduced. It is based on the spectral decomposition of stiffness matrix computed with finite element method. The here proposed metric is defined as an amplitude rescaled eigenvalues of stiffness matrix. The metric contains unique information on the principal stiffness of bone and reflects both bone shape and material properties. The metric was compared with anthropometrical measures and was tested for sex sensitivity on pelvis bone. Further, the smallest stiffness of pelvis was computed under a certain loading condition and analyzed with respect to sex and direction. The metric complements anthropometrical measures and provides a unique information about the smallest bone stiffness independent from the loading configuration and can be easily computed by state-of-the-art subject specified finite element algorithms.

Long-term survival of carotid stenting patients with regard to single- or double-vessel carotid artery disease: a propensity score matching analysis.

INTRODUCTION: There is lack of long-term data outside of controlled clinical trials in carotid artery stenting (CAS). In this study, we compared the short-term outcome, long-term survival, and rate of re-interventions for restenosis in patients after CAS, related to the extent of carotid atherosclerosis classified as single-vessel (unilateral) or double-vessel (bilateral) carotid artery disease. MATERIAL AND METHODS: We retrospectively evaluated 599 patients with significant carotid artery stenosis, who underwent 763 CAS procedures, and used the propensity score to match 226 pairs (452 patients) in the single- or double-vessel carotid disease. RESULTS: There was no significant difference in the occurrence of in-hospital major adverse events (3.5% vs. 3.1% of patients in the double-vessel carotid group vs. the single-vessel carotid group; p = 1) The mean follow-up was 6.1 ±4.0 years, and a total of 181 (40%) deaths occurred during 2759 patient-years, which translates into 7.8 and 5.3 deaths per 100 patient-years in the double-vessel carotid group and the single-vessel carotid group, respectively (p < 0.01). The survival in the double-vessel carotid group vs. the single-vessel carotid group at 10 years was 46% (95% CI: 38-54%) vs. 55% (95% CI: 47-63%) (p < 0.01). Twenty-four (11%) patients and 6 (3%) patients underwent re-interventions for restenosis in the double-vessel and the single-vessel carotid disease group, respectively (p < 0.01). CONCLUSIONS: Patients with CAS and significant double-vessel carotid artery disease had similar peri-procedural risk, but had a worse long-term survival, and a higher rate of re-interventions for restenosis compared to the single-vessel carotid artery disease patients.