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Vocabulary plays an important part in second language learning and there are many existing techniques to facilitate word acquisition. One of these methods is code-switching, or mixing the vocabulary of two languages in one sentence. In this paper the authors propose an experimental system for computer-assisted English vocabulary learning in context using a code-switching based approach for Japanese learners. First they introduce the CO-MIX system, an English vocabulary teaching system that uses code-switching for vocabulary acquisition. Next, they show how they utilize incidental learning techniques with graded readers to increase language proficiency. The authors present the system architecture, underlying technologies, and evaluate the system's performance through user interaction with both a baseline and the proposed system by using a semantic differential scale. They also perform separate factor analysis of participants' attitudes for both systems, an analysis of users' mistakes and compare users' language tests scores. Finally, the authors discuss the evaluation results and further development of this technology.

The archaeological site Tell el-Retaba in north-eastern Egypt, about 35 km to the west of Ismailia city, is located in the middle of Wadi Tumilat, a shallow valley running from the Nile Delta to the Bitter Lakes, along which flows the Suez Canal. In ancient times the valley was a route between Egypt and Syro-Palestine, strongly fortified in the New Kingdom times (16th–11thcentury BC). Mud bricks were analyzed from two parts of the Wall 1 (core of grey-brown bricks and inner extension of green bricks) in a fortress which existed during the Ramesses II times. Grain-size composition of the studied bricks was almost identical in both parts of the wall, suggesting the same source material for a production of brick. However, significant differences were observed in physical and mechanical properties (uni-axial compressive strength) in both types of bricks. Bricks from the core had lower bulk density, higher porosity and soak faster, whereas their resistance parameters were much lower than those of the bricks from the inner extension. The reason for such large differences in brick properties was a technology of their production, particularly proportion of components, water volume added during brick formation or density degree. Brick preparation and in consequence, physical-mechanical properties had direct influence on preservation of defensive structures during environmental changes related to changes of groundwater and surface water levels or of precipitation. Ancient Egyptians responsible for construction works in mud brick structures of the fortress must have had good knowledge and experience. This could be observed particularly for the heaviest and most important construction element that is the defensive wall, founded on well-densified deposits. It was also testified by higher resistance of green bricks from the inner extensions, which probably originated slightly later and were intended to reinforce a weaker core built of grey-brown bricks.

We developed a supporting solution for “cyberbullying” prevention based on recent discoveries in Artificial Intelligence and Natural Language Processing. Cyberbullying, defined as using the Internet to humiliate and slander other people has become a serious problem. In Japan members of the Parent–Teacher Association manually perform Web monitoring to stop cyberbullying activities. Unfortunately, reading through the whole Web manually is an impossible task. Although the complexity of cyberbullying makes it a problem unsolvable solely with the help of technology, we found that technology could make cyberbullying prevention more efficient. We developed a novel method of automatic detection of cyberbullying entries on the Internet. In the method we use seed words from three categories to calculate a semantic orientation score and then maximize the relevance of categories. The proposed method outperformed baseline settings in both laboratory and real world conditions. The developed system was deployed and tested in practice. After a year of testing we noticed a greater than 30 percent-point-drop in its performance. We hypothesize on the reasons for the drop. To regain the lost performance and retain it in the future we propose additional improvements including automatic acquisition and filtering of seed words. Experimentally selected optimal improvements regained much of the lost performance.

The results of anaerobic digestion (AD) of buttermilk (BM) and cheese whey (CW) with a digested sewage sludge as inoculum is described. The substrate/inoculum mixtures were prepared using 10% buttermilk and 15% cheese whey. The essential parameters of the materials were described, including: total solids (TS), volatile solids (VS), pH, conductivity, C/N ratio (the quantitative ratio of organic carbon (C) to nitrogen (N)), alkalinity, chemical oxygen demand (COD). The potential directions of biodegradation of the organic waste types, as used in this study, are also presented. Appropriate chemical reactions illustrate the substrates and products in each phase of anaerobic decomposition of the compounds that are present in buttermilk and cheese whey: lactic acid, lactose, fat, and casein. Moreover, the biogas and biomethane production rates are compared for the substrates used in the experiment. The results have shown that buttermilk in AD generates more biogas (743 m3/Mg VS), including methane (527 m3/Mg VS), when compared with cheese whey (600 m3/Mg VS, 338 m3/Mg VS for biogas and methane, respectively).

Statistics Canada estimated that approximately 1.4 million Canadians suffer from long COVID. Although cardiovascular changes during acute SARS-CoV-2 infection are well documented, long-term cardiovascular sequelae are less understood. In this review, we sought to characterize adult cardiovascular outcomes in the months after acute COVID-19 illness. In our search we identified reports of outcomes including cardiac dysautonomia, myocarditis, ischemic injuries, and ventricular dysfunction. Even in patients without overt cardiac outcomes, subclinical changes have been observed. Cardiovascular sequelae after SARS-CoV-2 infection can stem from exacerbation of preexisting conditions, ongoing inflammation, or as a result of damage that occurred during acute infection. For example, myocardial fibrosis has been reported months after hospital admission for COVID-19 illness, and might be a consequence of myocarditis and myocardial injury during acute disease. In turn, myocardial fibrosis can contribute to further outcomes including dysrhythmias and heart failure. Severity of acute infection might be a risk factor for long-term cardiovascular consequences, however, cardiovascular changes have also been reported in young, healthy individuals who had asymptomatic or mild acute disease. Although evolving evidence suggests that previous SARS-CoV-2 infection might be a risk factor for cardiovascular disease, there is heterogeneity in existing evidence, and some studies are marred by measured and unmeasured confounders. Many investigations have also been limited by relatively short follow-up. Future studies should focus on longer term outcomes (beyond 1 year) and identifying the prevalence of outcomes in different populations on the basis of acute and long COVID disease severity.

The aim of this paper is to get insight into measurement uncertainties for thermomechanical measurements performed using a piezoresistive silicon-based stress sensor in a standard microelectronic package. All used sensors have the same construction, were produced in the same technological processes at the same time, yet the measurement results show significant distribution. The possible causes for this phenomenon are discussed in this paper. Additionally, Finite Element Method (FEM) model is created and validated, what enables a study of sensitive parameters influencing the measurement uncertainties.

Chronic Obstructive Pulmonary Disease (COPD) remains the fourth recognized cause of death worldwide. Smoking is known as the most important risk factor for COPD with nicotine abstinence being the most effective COPD prophylaxis. Smoking cessation programs are less effective and may be considered as disease secondary prevention actions with smoking cessation slowing down lung function decline. Severe exacerbations, if not treated, on time (no comma) are responsible for the highest number of lung related deaths among COPD patients. As the definition of COPD exacerbation may be subjective, attributing symptoms to an exacerbation can be difficult, especially among less educated patients. This problem may be even more important in areas where the doctor/patient ratio is small and where patients need to travel long distances to obtain consultation and medical help. For these reasons COPD telemonitoring programs are being tested and implemented in some countries. This review is an updated overview of the current scientific evidence regarding patient education and telemonitoring implementation in COPD, based on the article on this topic published herein in 2013. The evidence provided, herein, is presented to help identify the effectiveness of education and telemonitoring in COPD in societies with different economies.

The article presents a comparison between classical and jazz trumpet playing. Topics include the ringing and vocal qualities of a classical sound, the importance of technique and articulation when playing jazz, and the link between sound and one's imagination. It also discusses improvisation in jazz music, the need to go to concerts to hear new sounds and musical ideas, and the value of singing for jazz and classical playing.

Obtaining medical information has a beneficial influence on patients' treatment and QOL (quality of life). The authors aim to make a system that helps patients to collect narrative information. Extracting information from data written by patients will allow the acquisition of information which is easy to understand and provides encouragement. Additionally, by using large-scale data, the system can be utilized for discovering unknown effects or patterns. As the first step, the purpose of this paper is to extract descriptions of the effects caused by taking drugs as a triplet of expressions from illness survival blogs' snippets. This paper proposes a method to extract the triplets using specific clue words and parsing the results in order to extract from blogs written in free natural language. Moreover, recall was improved by combining their proposed method and a baseline system, and precision was improved by filtering using dictionaries we created from existing medical documents.

This paper describes using a finite-state automaton (FSA) to retrieve Japanese TV guide text. The proposed FSA application can be considered novel due to lack of research on the subject. The automaton has been implemented for matching and extracting all possible combinations of search query words in all possible word orders that may be present in the TV guide text. This implementation also sorts the extraction results by analyzing word semantic features (such as “being an object” or “being a property of an object”). The present paper also proposes a search system using the above implementation and compares it with a baseline system that matches query words (of multi-word queries) in exactly the same and exactly the opposite word orders only. Both systems use morphological parsing and apply a stop list to the query. A multi-parameter evaluation has shown advantages of the proposed system over the baseline one.

Japanese emoticons are widely used to express users' feelings and intentions in social media, blogs and instant messages. Japanese smartphone keypads have a feature that shows a list of emoticons, enabling users to insert emoticons simply by touching them. However, this list of emoticons contains more than 200, which is difficult to choose from, so a method to reorder the list and recommend appropriate emoticons to users is necessary. This paper proposes an emoticon recommendation method based on the emotive statements of users and their past selections of emoticons. The system is comprised of an affect analysis system and an original emoticon database: a table of 59 emoticons numerically categorized by 10 emotion types. The authors' experiments showed that 73.0% of chosen emoticons were among the top five recommended by the system, which is an improvement of 43.5% over the method used in current smartphones, which is based only on users' past emoticon selections.

AbstractDirect carbon fuel cells (DCFCs) are very promising systems to provide electricity at medium term due to the more efficient utilization of carbon at high temperatures. In this work, the focus is on a DCFC operating with a SOFC system. Button cells with an anode layer for carbon conversion, based on gadolinia-doped ceria (GDC) and CuO, are used in the experimental setup. Different contents of ceria have been incorporated in the electrode composition to test its catalytic activity for the direct carbon conversion. Vulcan®XC72 is used in the fuel cell as carbon fuel, and results in the temperature range of 750–850 °C are presented. Performing measurements of YSZ-based cells with or without anode layers as well as a systematic analysis of the anodic off-gas composition, it can be demonstrated that ceria catalyzes both reactions: the direct carbon conversion and in particular the partial oxidation of carbon. Moreover, it has been found that the DCFC system is dominated by the complete oxidation of carbon.

At medium term, electricity could be partially provided by the utilization of carbon in high temperature fuel cells. The thermodynamic efficiency of a direct carbon fuel cell (DCFC) slightly exceeds 100% in a wide temperature range due to the positive value of the reaction entropy change. Thus, the thermodynamic efficiency is higher than those of conventional fuel cell types for gaseous fuels.

This paper presents research in Contextual Affect Analysis (CAA) for the need of future application in intelligent agents, such as conversational agents or artificial tutors. The authors propose a new term, Computational Fronesis (CF), to embrace the tasks included in CAA applied to development of conversational agents such as artificial tutors. In tutor-student discourse it is crucial that the artificial tutor was able not only to detect user/student emotions, but also to verify toward whom they were directed and whether they were appropriate for the context of the conversation. Therefore, as the first task in CF the authors focus on verification of contextual appropriateness of emotions. They performed some of the first experiments in this task for the Japanese language and discuss future directions in development and implications of Computational Fronesis.

AbstractHeavy metals are particularly present in industrial harbour areas, mainly under particle form. Three possible applications of rye—grass in heavy metals biomonitoring were studied in this work: bioaccumulation, observation of particle deposition on leaves and genotoxicity. Only lead and cadmium were detected on leaves, with higher concentrations in industrial site. This results show the application limits of French norm NF X43-901 when atmospheric concentrations of heavy metals are relatively low during the survey. However, size, composition, and quantity of particles microscopically observed on foliar surfaces (with SEM) change according to the sites. Moreover, comet assay, that was performed for the first time on rye—grass leaves, show genotoxic effects more important in road site.

In this paper we present an innovative work on a multiagent joking conversational system. In our research so far we have shown that implementing humor into a chatterbot can visibly improve its performance. The results presented in this paper are the outcome of the next step of our work. They show that a multiagent system, combining a conversational agent, a pun generator and an emotiveness analysis engine, works reasonably well in interactions with users. In the setup used in this research, the emotiveness analysis agent analyses users' utterances and decides whether it is appropriate to tell a pun. Depending on the results of this analysis, the agent chooses either the pun generator, if the decision is that a joke should be told, or the non-humor-equipped agent when the decision is different. Two evaluation experiments were conducted: user (first person) focused and automatic (emotiveness-analysis-based). In both, we compared the performance of the multiagent joking system and a baseline (non-humorous) conversation agent. The results show that in both cases the humor-equipped engine was evaluated as better than the baseline agent. The results are discussed and some ideas for the future are given.

This paper presents a novel method for estimating speaker's affective states based on two contextual features: valence shifters and appropriateness. Firstly, a system for affect analysis is used to recognise specific types of emotions. We improve the baseline system with the analysis of Contextual Valence Shifters (CVS), which determine the semantic orientation of emotive expressions. Secondly, a web mining technique is used to verify the appropriateness of the recognised emotions for the particular context. Verification of contextual appropriateness of emotions is the next step towards implementation of Emotional Intelligence Framework in machines. The proposed method is evaluated using two conversational agents.

The article offers tips and ideas on how to build a strong trumpet section for an orchestra or concert band. Topics covered include the responsibilities of the first trumpet player or the head of the brass section, the difficult role of second trumpet player to that requires excellent ears, some exercises for breathing and coming in together, and tips on how to balance octaves.

Aims:Isoprostanes may serve as sensitive and specific markers of in vivooxidative stress intensity. We wanted to determine, whether or not isoprostane concentration may be considered as a risk marker of premature rupture of fetal membranes (PROM).Methods:On the basis of the presence of PROM and gestational maturity, a total of 128 patients were divided into: (1) preterm PROM (pPROM) group; (2) PROM at term group; (3) control preterm (C1) group and (4) control at term (C2) group. The concentrations of 8-iPF2α-III were determined using the enzyme-linked immunosorbent assay method.Results:The mean free isoprostane concentrations, examined in amniotic fluid and maternal plasma in the PROM at term patients were significantly higher than in C2 individuals (p < 0.01). The mean concentrations of free 8-iPF2α-III measured in blood plasma from women in the C1 group were significantly lower than in patients from the pPROM, PROM at term and C2 groups (p < 0.001, p < 0.00001 and p < 0.00001, respectively).Conclusion:The measurement of free isoprostane concentration in maternal plasma and amniotic fluid may be considered as a laboratory marker of a PROM-risk pregnancy.

Until now, phosphorus is the best substitutional dopant for n-type diamond. Its incorporation is usually achieved using phosphine gas. However, organic precursors of phosphorus have been recently investigated. Among them, tertiarybutylphosphine (TBP) appears as an alternative to phosphine. In this report, we investigate the n-type doping of diamond with liquid TBP using the metal-organic chemical vapour deposition (MOCVD) technology for dopant incorporation. Our first results with liquid TBP precursor are compared with the results published for gaseous organic precursors of phosphorus. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

This article relates the medical treatment and recovery of Sergeant Walter R. Davis of the 2nd Battalion, 1st Infantry Regiment, 172nd Infantry Brigade, after being shot by a sniper during a military mission near Mosul, Iraq. He was shot while providing security to a psychological-operations team. He was immediately given an emergency initial treatment at the site. He was brought immediately to the 47th Combat Support Hospital where he eventually recovered from his injury.