Discussion of Issues Related to Spoken and Signed Language Test Design for L1 Children

This chapter is a joint discussion of key items related to the development of spoken language tests (Chapter 1.1) and signed language tests (Chapter 1.2) for L1 children and the ways in which they have been addressed. We highlight the common issues and challenges in spoken and signed language assessment as well as the differences, e.g., availability of tests. In so doing, we consider how experience with spoken language assessment—for example, the development of methods for assessing language abilities that are independent of language experience—may inform test development in signed language. We also consider how awareness of issues in signed language assessment may increase awareness of similar issues that are easily overlooked in spoken language assessment—for example, the range of communication contexts and partners that children regularly encounter—and stimulate critical reflection on the use of language tests in general. One specific recommendation the chapter has for developers of signed language tests in the future is to consider areas that are unique to signed communication and critical to signing children’s language development.

Antibody Responses to COVID-19 Vaccination in Cancer: A Systematic Review

IntroductionAfter the results of phase III vaccine studies became available, the leading oncology societies recommended two doses of COVID-19 vaccination to all patients with cancer with no specific recommendation for tumor type and active treatments. However, the data on the COVID-19 vaccine efficacy in cancer patients is limited due to exclusion of cancer patients from most vaccine clinical trials. Therefore, we systemically reviewed the available evidence evaluating the antibody responses in cancer patients.MethodsWe conducted a systematic search from the Pubmed database and calculated risk differences (RD) and 95% confidence intervals (CI) to compare seroconversion rates between cancer patients and controls using the Review Manager software, version 5.3.ResultsOur systematic search retrieved a total 27 studies and we included 17 studies with control arms in the analyses. Cancer patients had significantly lower seroconversion rates (37.3%) than controls (74.1%) (RD: -0.44, 95% CI: -0.52, -0.35, p<0.001) with first vaccine dose. After two doses, the seroconversion rates were 99.6% in control arm and 78.3% in cancer patients (RD: -0.19, 95% CI: -0.28, -0.10, p<0.001). The difference in seroconversion rates was more pronounced patients with hematologic malignancies (72.6%) (RD: -0.25, 95% CI: -0.27, -0.22, p<0.001) than patients with solid tumors (91.6%) (RD: -0.09, 95% CI: -0.13, -0.04, p<0.003) and patients in remission (RD: -0.10, 95% CI: -0.14, -0.06, p<0.001).ConclusionIn conclusion, COVID-19 vaccine seroconversion rates were significantly lower in patients with hematological malignancies and patients under active treatment. Further research focusing on the approaches to improve vaccine efficacy and exploration of novel treatment options is urgently needed for these patients.

Assessing and preventing deforestation in Kayan Mentarang National Park, North Kalimantan Province, Indonesia

National parks in Indonesia are valuable assets for the next generations. The urgency to maintain and protect their existence from land degradation and deforestation is an obligation. Moreover, deforestation is the most severe threat to biodiversity. In Kalimantan, deforestation is happening and usually leads to economic loss and poverty. Despite this habitat loss, our ability to quantify deforestation in certain areas to improve mitigation measures, meet the needs of agricultural land, and increases local communities’ resilience and ensure that their customary rights. This study aims to provide models to assess the deforestation rate in Kayan Mentarang National Park and give recommendation action based on existing Land Use Zonation. To achieve this aim, firstly Landsat images was obtained and analysed to produce land use and land cover classification. However, cloud coverage in this area is more than 30% which is too difficult to classify the land cover area. This research use alternative resources from JAXA to generate deforestation map at study area. Then compile this map into map of Land Use Zonation of KMNP to provide specific location of deforestation occurrence. The result showed that deforestation rate at KMNP is low, around 3% and the Traditional Zone has the biggest amount of deforestation occurrence; 18.727 hectare. This finding would give information to the government of KMNP to accelerate empowerment program among indigenous people in term of utilizing their customary land in this zone. Moreover, this research suggest the best practical way to evaluate deforestation occurrence in KMNP area followed by specific recommendation of each land use zonation of KMNP.

Entity Recommendation for Everyday Digital Tasks

Recommender systems can support everyday digital tasks by retrieving and recommending useful information contextually. This is becoming increasingly relevant in services and operating systems. Previous research often focuses on specific recommendation tasks with data captured from interactions with an individual application. The quality of recommendations is also often evaluated addressing only computational measures of accuracy, without investigating the usefulness of recommendations in realistic tasks. The aim of this work is to synthesize the research in this area through a novel approach by (1) demonstrating comprehensive digital activity monitoring, (2) introducing entity-based computing and interaction, and (3) investigating the previously overlooked usefulness of entity recommendations and their actual impact on user behavior in real tasks. The methodology exploits context from screen frames recorded every 2 seconds to recommend information entities related to the current task. We embodied this methodology in an interactive system and investigated the relevance and influence of the recommended entities in a study with participants resuming their real-world tasks after a 14-day monitoring phase. Results show that the recommendations allowed participants to find more relevant entities than in a control without the system. In addition, the recommended entities were also used in the actual tasks. In the discussion, we reflect on a research agenda for entity recommendation in context, revisiting comprehensive monitoring to include the physical world, considering entities as actionable recommendations, capturing drifting intent and routines, and considering explainability and transparency of recommendations, ethics, and ownership of data.

Dietary Soluble Fiber Improved Fecal Consistency in Burned Patients with Diarrhea

Backgrounds: Diarrhea frequently occurs in severely burned patients attributable to impaired intestinal integrity and dysbiosis. Soluble fiber may improve intestinal barrier function, avoid bacterial translocation, then subsequently prevent and treat diarrhea. Soluble fiber is rapidly fermented by commensal bacteria and produces short-chain fatty acids (SCFA). Case Reports: A 51-year-old male with severe burn injury involving 53,5% total body surface area (TBSA) and diarrhea were given soluble fiber as part of his diet. Results: Administration of 6–10 g/d soluble fiber clinically improves stool consistency, assessed by Bristol Stool Scale, in the severely burned patient. The patient was discharged after 19 days of hospitalization with improvement in clinical condition. Summary: SCFA maintains intestinal integrity, supports the growth of commensal bacteria, and inhibits pathogens. There is no specific recommendation regarding fiber intake in burned patients

Chlorhexidine Oral Care in Critically Ill Adults

Three systematic reviews and 2 randomized clinical trials were identified regarding the clinical effectiveness of chlorhexidine oral care in adult patients who were in critical care and being mechanically ventilated. The evidence was of limited quality, with methodological limitations. Compared to ozonated water and to Nanosil, chlorhexidine oral care was associated with a significantly higher risk of ventilator-associated pneumonia. Compared to bicarbonate, chlorhexidine oral care was associated with a significantly lower risk of ventilator-associated pneumonia. There was no significant difference in the risk of ventilator-associated pneumonia between chlorhexidine and other agents, such as potassium permanganate, hydrogen peroxide, or miswak. There was no significant difference in the risk of mortality between oral care with chlorhexidine and that with other oral care drugs. An evidence-based guideline targeting individuals who require assistance on oral care recommended a multi-component oral care protocol. No specific recommendation regarding the use of oral care agents for the prevention of ventilator-associated pneumonia was made because of lack of evidence. There is a lack of evidence on the safety or cost-effectiveness of chlorhexidine oral care in adults who are in critical care and being mechanically ventilated.

JUMRv1: A Sentiment Analysis Dataset for Movie Recommendation

Nowadays, we can observe the applications of machine learning in every field, ranging from the quality testing of materials to the building of powerful computer vision tools. One such recent application is the recommendation system, which is a method that suggests products to users based on their preferences. In this paper, our focus is on a specific recommendation system called movie recommendation. Here, we make use of user reviews of movies in order to establish a general outlook about the movie and then use that outlook to recommend that movie to other users. However, a huge number of available reviews has baffled sophisticated review systems. Consequently, there is a need to find a method of extracting meaningful information from the available reviews and use that in classifying a movie review and predicting the sentiment in each one. In a typical scenario, a review can either be positive, negative, or indifferent about a movie. However, the available research articles in the field mainly consider this as a two-class classification problem—positive and negative. The most popular work in this field was performed on Stanford and Rotten Tomatoes datasets, which are somewhat outdated. Our work is based on self-scraped reviews from the IMDB website, and we have annotated the reviews into one of the three classes—positive, negative, and neutral. Our dataset is called JUMRv1—Jadavpur University Movie Recommendation dataset version 1. For the evaluation of JUMRv1, we took an exhaustive approach by testing various combinations of word embeddings, feature selection methods, and classifiers. We also analysed the performance trends, if there were any, and attempted to explain them. Our work sets a benchmark for movie recommendation systems that is based on the newly developed dataset using a three-class sentiment classification.

Advanced project management approaches for implementation into the public administration system of Kazakhstan

The article discusses the main approaches to program and project management that are used in the UK, Russia and Malaysia. This review was conducted to identify best practices for Kazakhstan. The purpose of this article was a brief overview of the approaches to managing programs and projects in a number of developed countries of the world to determine the most optimal of them in the system of public administration in Kazakhstan. The review was conducted from the point of view of organizational interaction between structural units in the implementation of programs and projects, ensuring transparency of ongoing processes, and ways of involving stakeholders in the project. Also, a brief review of the project management standards in the countries under consideration was carried out. When writing the article, a general scientific research method was used, namely, the comparative-comparative method of the considered approaches to project management in a number of developed economies of the world. The legislative base in terms of the new concept of public administration development is analyzed. As a result of the research, the author identified the experience of Malaysia. The effective approach to the management of national reforms and projects, developed by the PEMANDU Institute, most fully reflects the principles laid down in the new vision of the state development of the Republic of Kazakhstan. The author has given a specific recommendation regarding amendments to legal acts.

Product line of selected agricultural entity in Slovakia and suggestion for its expansion based on analysis of consumers' interest in dairy and meat products

Studies on primary agricultural production in Slovakia aimed mainly at biological, economic, or market point of view and there is a lack of managerial approach providing a specific recommendation for farmers according to their production lines or planning process. As a reaction, we are providing a practically oriented study based on the selected livestock producer, which is aimed at statistical significances as an establishment for further recommendations for management and marketing of this entity. The paper aims to analyze the views and preferences of customers of the monitored company, which sells its meat and dairy products in its stores and verify the expected success of the planned expansion of the product lines. Regarding this, the online questionnaire study was conducted on a sample of 202 respondents. Realized statistical analysis based on the Kruskal-Wallis nonparametric test and subsequent Bonferroni post hoc correction signify that meat products, fresh meat, and slaughter specialties are the most favorite products among customers of the monitored company. Fresh milk, on the other hand, is not as attractive as a meal for them. However, selling it from vending machines placed out of the store would increase the sales. Dairy products of own production should be even more successful, as we assume they would be as interesting for customers as the currently expanding portfolio of meat products. The benefit of this study lies in the consideration of the practical use of the obtained results in the business practice of the monitored company. Regarding this, we are providing a set of recommendations, according to the planning of their product lines and connected marketing tools for their successful placement on the market.

A Comprehensive Survey of Knowledge Graph-Based Recommender Systems: Technologies, Development, and Contributions

In recent years, the use of recommender systems has become popular on the web. To improve recommendation performance, usage, and scalability, the research has evolved by producing several generations of recommender systems. There is much literature about it, although most proposals focus on traditional methods’ theories and applications. Recently, knowledge graph-based recommendations have attracted attention in academia and the industry because they can alleviate information sparsity and performance problems. We found only two studies that analyze the recommendation system’s role over graphs, but they focus on specific recommendation methods. This survey attempts to cover a broader analysis from a set of selected papers. In summary, the contributions of this paper are as follows: (1) we explore traditional and more recent developments of filtering methods for a recommender system, (2) we identify and analyze proposals related to knowledge graph-based recommender systems, (3) we present the most relevant contributions using an application domain, and (4) we outline future directions of research in the domain of recommender systems. As the main survey result, we found that the use of knowledge graphs for recommendations is an efficient way to leverage and connect a user’s and an item’s knowledge, thus providing more precise results for users.