Complex Questions Research Articles

Barns hållbarhetsfrågor i digitala och fysiska gränssnitt - transduktionskedja som ett didaktiskt verktyg

In this article, we show empirically how preschool childrens’ creative, physical, and digital leaps, provide new perspectives concerning childrens’ engagement in ecology related questions in the domain of Sustainability Education. The metamorphosis of insects is explored by children digitally, embodied and 'hands-on', and the children move through the digital and analogue interfaces. Childrens’ embodied explorations through instant encounters with nature has an obvious place where the digital world and nature become intersected forming a whole. We introduce a transduction chain, a didactic design-theoretic analysis tool, which supports teachers and researchers to get to hold of childrens’ digital and analogue meaning-making sign use. We draw attention to the preschool children's contribution in the area, which is made visible through transduction processes. We do not yet have the answers to the complex questions of sustainability, implying the need of all citizens’ participation and contributions. In anthropocene, it is also important to strengthen agency processes by paying attention to children's own course of actions and proposals. In light of this study, preschool teachers need to provide rich opportunities where children can explore and process what is happening around them.

AUTOMATIC PRONUNCIATION ASSESSMENT IN A FLIPPED CLASSROOM CONTEXT

Automatic pronunciation assessment programs allow learners to practice pronunciation independently and receive immediate feedback based on acoustic analysis of their speech compared to a pronunciation model. The programs display a high level of reliability when assessing speakers’ pronunciation accuracy. The paper aims to present the results of an investigation into a recent experimental application of an automatic pronunciation assessment online program used within the flipped classroom of English phonetics and phonology course taught to foreign language pre-service teachers of English. Flipped learning approach was selected to offload the preliminary activities and tasks that do not require the immediate attention of the teacher to an online learning management system. Thus, course participants’ face-to-face learning could be enhanced and more effective. The participants could practice and receive tailored feedback from an online program before the face-to-face class. After the individual pronunciation practice, they could discuss more complex questions with the lecturer and, in collaboration with fellow students. The paper will present the survey results among the course participants who evaluated their experience with automatic pronunciation evaluation. Special attention is paid to the potential use of such programs for developing linguistic competence.

Exploring the complexities of posthumous reproduction in fertility preservation for oncology patients with poor prognosis.

The field of fertility preservation (FP) for oncology patients has evolved significantly in recent years, offering new possibilities for individuals with life-threatening illnesses. We commend Jones et al. for their comprehensive ethical review of offering FP to patients with poor prognoses, acknowledging the potential benefits that it may bring. "Poor prognosis" in this context implies a high likelihood of death due to cancer progression. We highlight the importance of considering posthumous reproduction, involving the use of cryopreserved gametes or embryos to conceive a child after one or both partners have passed away, a topic briefly mentioned by Jones et al. Posthumous reproduction raises complex ethical, logistical, and legal questions. Distinctions between cryopreserved sperm and oocytes are discussed, with each scenario presenting unique challenges. The article also examines the complexities faced by same-sex couples in posthumous reproduction, addressing issues related to donor selection, legal parentage, and rights. Legal and regulatory aspects play a crucial role, including obtaining clear and legally valid consent, defining parental rights, navigating surrogacy laws, and addressing inheritance and estate planning. Ethical dilemmas require healthcare professionals to ensure informed decision-making, consider psychological impacts, and offer information on alternative family-building options.

Assessment of the School Resources Availability in Public Day Secondary Schools in Kenya: Case of Manga Sub-County

Education is a human activity that fashions and models mankind for society. Thus, all educational stakeholders ought to combine forces towards realising quality education. This study assesses the availability of schools resources. The study was triggered by the ongoing trend of diminishing academic performance among students in day secondary schools in the Manga sub-county, posing complex questions that must be addressed. The study employed a descriptive survey research approach grounded in the Resource-Based Theory. The targeted population was 378 individuals, consisting of 351 teachers and 27 head teachers from 27-day schools in the Manga subcounty. A sample size of 299 was selected using simple random sampling. Questionnaires were used to collect data. Quantitative data was analysed using a descriptive survey approach. It was recommended that for effective learning and improved academic performance, the school administration should ensure that it has provided adequate school resources materials in all schools and that there is effective and efficient management of teaching-learning materials for the improved academic performance of the learner

Multi-hop community question answering based on multi-aspect heterogeneous graph

Community question answering aims to connect queries and answers based on users' community behaviors, find the most relevant solutions for newly raised questions, and improve community activity. Existing research mainly focuses on the single-hop method, which relies on a particular feature for simple question answering. However, multi-hop question answering, which depends on multi-step reasoning to solve complex questions, still faces the destitute adaptability caused by various entity features and complex entity correlations. In this work, we put forward a Multi-Hop Community Question-Answering method called MHCQA, that combines the multi-aspect features of community entities, constrains the answer retrieval process from different perspectives and improves the adaptability of multi-hop answer retrieval. Firstly, we utilize phrases for representing the semantic features of question-answering and fuse them with entity constitution properties through heterogeneous graphs to effectively indicate the diverse relationships among entities in communities. At the same time, we bring a dynamic heterogeneous network construction strategy to improve the efficiency of feature representation. Secondly, we enhance heterogeneous graph attention networks for efficiently computing local entity similarities to find relevant answers to questions based on partial graphs. Finally, we propose a multi-constraint multi-hop community question-answering method, which optimizes answer retrieval from three aspects: the hop count, the number of answers, and the relevance of responses, to improve the scene adaptability of multi-hop answer retrieving. Abundant experiments on realistic corpus (Quora, Math, Super User, and Stack Overflow) illustrate that MHCQA improves the multi-hop question answering error rate by about 2 % and is about 11 % ahead of the baselines in terms of operating efficiency. Given our present literature survey, MHCQA is a promising research idea for automatic answering services in online question-answering communities.

Implementation Matters: Evaluating the Proportional Hazard Test’s Performance

Abstract Political scientists commonly use Grambsch and Therneau’s (1994, Biometrika 81, 515–526) ubiquitous Schoenfeld-based test to diagnose proportional hazard violations in Cox duration models. However, some statistical packages have changed how they implement the test’s calculation. The traditional implementation makes a simplifying assumption about the test’s variance–covariance matrix, while the newer implementation does not. Recent work suggests the test’s performance differs, depending on its implementation. I use Monte Carlo simulations to more thoroughly investigate whether the test’s implementation affects its performance. Surprisingly, I find the newer implementation performs very poorly with correlated covariates, with a false positive rate far above 5%. By contrast, the traditional implementation has no such issues in the same situations. This shocking finding raises new, complex questions for researchers moving forward. It appears to suggest, for now, researchers should favor the traditional implementation in situations where its simplifying assumption is likely met, but researchers must also be mindful that this implementation’s false positive rate can be high in misspecified models.

New horizons in evidence synthesis for older adults.

Evidence synthesis, embedded within a systematic review of the literature, is a well-established approach for collating and combining all the relevant information on a particular research question. A robust synthesis can establish the evidence base, which underpins best practice guidance. Such endeavours are frequently used by policymakers and practitioners to inform their decision making. Traditionally, an evidence synthesis of interventions consisted of a meta-analysis of quantitative data comparing two treatment alternatives addressing a specific and focussed clinical question. However, as the methods in the field have evolved, especially in response to the increasingly complex healthcare questions, more advanced evidence synthesis techniques have been developed. These can deal with extended data structures considering more than two treatment alternatives (network meta-analysis) and complex multicomponent interventions. The array of questions capable of being answered has also increased with specific approaches being developed for different evidence types including diagnostic, prognostic and qualitative data. Furthermore, driven by a desire for increasingly up-to-date evidence summaries, living systematic reviews have emerged. All of these methods can potentially have a role in informing older adult healthcare decisions. The aim of this review is to increase awareness and uptake of the increasingly comprehensive array of newer synthesis methods available and highlight their utility for answering clinically relevant questions in the context of older adult research, giving examples of where such techniques have already been effectively applied within the field. Their strengths and limitations are discussed, and we suggest user-friendly software options to implement the methods described.

Gastroenterology Fellowship and Postdoctoral Training in Omics and Statistics-Part I: Why Is It Needed?

A multitude of federally and industry-funded efforts are underway to generate and collect human, animal, microbial, and other sources of data on an unprecedented scale; the results are commonly referred to as "big data." Often vaguely defined, big data refers to large and complex datasets consisting of myriad datatypes that can be integrated to address complex questions. Big data offers a wealth of information that can be accessed only by those who pose the right questions and have sufficient technical knowhow and analytical skills. The intersection comprised of the gut-brain axis, the intestinal microbiome and multi-ome, and several other interconnected organ systems poses particular challenges and opportunities for those engaged in gastrointestinal and liver research. Unfortunately, there is currently a shortage of clinicians, scientists, and physician-scientists with the training needed to use and analyze big data at the scale necessary for widespread implementation of precision medicine. Here, we review the importance of training in the use of big data, the perils of insufficient training, and potential solutions that exist or can be developed to address the dearth of individuals in GI and hepatology research with the necessary level of big data expertise.

Communal Geographies: Space, Identity and Electoral Constituency in Colonial North India

The Indian Councils Act, 1909, the Government of India Act, 1919, and the Government of India Act, 1935, defined political space—an arena of political negotiations through electoral representation—along religious lines. The most crucial aspect of these legislative-institutional developments was the definition and delimitation of ‘communal-territorial constituencies’, and franchisee qualifications. This specific colonial form of representative politics, which was debated, negotiated and translated by the religio-political elite in the arena of local politics, produced a communal notion of space. Thus, each of the localities, wards, cities and regions at large were officially demarcated into Muhammadan, General/Hindu, Sikh and Indian-Christian electoral constituencies. The paper explores the intricacies of this process and the complex question of ‘representation’ during the period of the national movement. It argues that this official demarcation of social groups and localities into political constituencies produced a complex configuration of identity and space, which had multiple manifestations with extended franchise. It established electoral representation as a mode to make legitimate claims and counterclaims over space.

Complex Knowledge Base Question Answering: A Survey

Knowledge base question answering (KBQA) aims to answer a question over a knowledge base (KB). Early studies mainly focused on answering simple questions over KBs and achieved great success. However, their performances on complex questions are still far from satisfactory. Therefore, in recent years, researchers propose a large number of novel methods, which looked into the challenges of answering complex questions. In this survey, we review recent advances in KBQA with the focus on solving complex questions, which usually contain multiple subjects, express compound relations, or involve numerical operations. In detail, we begin with introducing the complex KBQA task and relevant background. Then, we present two mainstream categories of methods for complex KBQA, namely semantic parsing-based (SP-based) methods and information retrieval-based (IR-based) methods. Specifically, we illustrate their procedures with flow designs and discuss their difference and similarity. Next, we summarize the challenges that these two categories of methods encounter when answering complex questions, and explicate advanced solutions as well as techniques used in existing work. After that, we discuss the potential impact of pre-trained language models (PLMs) on complex KBQA. To help readers catch up with SOTA methods, we also provide a comprehensive evaluation and resource about complex KBQA task. Finally, we conclude and discuss several promising directions related to complex KBQA for future research.

Assessing Antitrust Damages in Follow-On Actions Against Cartels

AbstractAssessing damages in follow-on actions against cartels that have infringed EU or domestic antitrust law is still in its infancy in Europe. This Article highlights the reasons why this issue has only recently started reaching the courts and analyses the pitfalls and problems courts face when calculating or estimating the amount of loss caused by a cartel to individual plaintiffs. As this endeavour raises complex economic questions, the Article outlines the basic economic approaches to measure antitrust harm and derives general principles from EU law on how courts should deal with economic evidence in follow-on actions to ensure an effective enforcement of competition law.

Carrying Trans Forward

What utility does trans hold and carry forward at this politically and ecologically volatile moment, when increasingly prevalent legal restrictions are preventing trans people from accessing gender affirming and reproductive health care and seeking to disallow our presence in public life altogether? Taking an autoethnographic approach to exploring trans life and scholarship across generations, this essay poses trans*plantation as a framework for navigating complex questions about how life comes to be defined and whose lives come to hold value or not over time.

From Guwen to Chinese Literature

This article examines the Sinologists’ conceptually mediated approach in their studies and translations of Chinese literature in the nineteenth century. Gems of Chinese Literature (1884), compiled and translated by Herbert Allen Giles (1845–1935), contains the English translation of 110 Chinese prose extracts and eight poems from fifty-nine Chinese authors. This article historicizes the genesis and construction of this translation anthology and argues that, though most likely derived from a Chinese guwen (classical prose) collection, it was designed to provide a more systematic view of Chinese literature informed by the concept of national literature. By analysing its organizational strategies, discursive paratexts, and how it deviated from its possible Chinese source, the author demonstrates that Gems of Chinese Literature reveals more complex questions concerning the (re-)conceptualization and representation of Chinese literature at the encounter of Chinese and Western literary paradigms.

Multigranularity Pruning Model for Subject Recognition Task under Knowledge Base Question Answering When General Models Fail

In general knowledge base question answering (KBQA) models, subject recognition (SR) is usually a precondition of finding an answer, and it is a common way to employ a general named entity recognition (NER) model such as BERT-CRF to recognize the subject. However, in previous researches, the difference between a NER task and a SR task is usually ignored, and a wrong entity recognized by the NER model will certainly lead to a wrong answer in the KBQA task, which is one bottleneck for KBQA performance. In this paper, a multigranularity pruning model (MGPM) is proposed to answer a question when general models fail to recognize a subject. In MGPM, the set of all possible subjects in the Knowledge Base (KB) is pruned by 4 multigranularity pruning submodels successively based on the constraint of relation (domain and tuple), string similarity, and semantic similarity. Experimental results show that our model is compatible with various KBQA models for both single-relation and complex questions answering. The integrated MGPM model (with the BERT-CRF model) achieves a SR accuracy of 94.4% on the SimpleQuestions dataset, 68.6% on the WebQuestionsSP dataset, and 63.7% on the WebQuestions dataset, which outperforms the original model by a margin of 3.6%, 8.6%, and 5.3%, respectively.

Roofscapes

This article reads several works of African American literature that depict the urban roofscape as a site of contemporary fugitive praxis, made in and against the enclosures of 20th century urban space. The forms of freedom rehearsed on the roof are intersecting, overlapping and, at times, contradictory. Ultimately, I argue that the roofscape offers an analytic object through which to explore the thorny questions of property, gender, enclosure, and mobility—questions that enrich and complicate the study of fugitive geographies and their use as models for escaping and living outside of the violent enclosures of gendered racial capitalism. The multivalence of the rooftop provides an opportunity to dwell with the complex questions of fugitive method: What forms do geographies of fugitivity take? Who do they limit or enable? And under what conditions? How do fugitive geographies both sustain and break from the social, political, and economic relations from which their producers flee?

Framing The Responsibility of Public-Private Partnerships (PPPs) on Space Technology in International Law

Public-Private Partnerships (PPPs) have gained popularity as a way to use resources and expertise from the private sector to support governmental space activities. In the event of a space-related incident, the division of duties and liabilities between public and private partners may be complicated. Clarifying the division of duties and liabilities between public and private actors is necessary given the rising participation of private companies in space activities.. With the growing involvement of private entities in space activities, there is a need to clarify the allocation of responsibilities and liabilities between public and private actors. Who is held responsible when a private company causes a technological disaster strike? On what basis can the responsibility be made, understood from international law? The research is normative legal research, where the data is collected through a statutory and case approach. The study results show that Public-private partnerships (PPPs) in outer space activities raise complex questions regarding responsibility. Responsibility refers to the Liability Convention on the Outer Space Treaty. The treaty emphasizes that states bear international responsibility for their national activities in outer space, including those conducted by private entities under their jurisdiction. However, the treaty does not explicitly address the specific responsibilities of private actors. Private companies only bear indirect international responsibility. PPPs need to consider the notion of shared responsibility, which acknowledges the contributions of both public and private actors and emphasizes cooperation and transparency

The SIB Swiss Institute of Bioinformatics Semantic Web of data.

The SIB Swiss Institute of Bioinformatics (https://www.sib.swiss/) is a federation of bioinformatics research and service groups. The international life science community in academia and industry has been accessing the freely available databases provided by SIB since its inception in 1998. In this paper we present the 11 databases which currently offer semantically enriched data in accordance with the FAIR principles (Findable, Accessible, Interoperable, Reusable), as well as the Swiss Personalized Health Network initiative (SPHN) which also employs this enrichment. The semantic enrichment facilitates the manipulation of large data sets from public databases and private data sets. Examples are provided to illustrate that the data from the SIB databases can not only be queried using precise criteria individually, but also across multiple databases, including a variety of non-SIB databases. Data manipulation, be it exploration, extraction, annotation, combination, and publication, is possible using the SPARQL query language. Providing documentation, tutorials and sample queries makes it easier to navigate this web of semantic data. Through this paper, the reader will discover how the existing SIB knowledge graphs can be leveraged to tackle the complex biological or clinical questions that are being addressed today.

Advancements in Complex Knowledge Graph Question Answering: A Survey

Complex Question Answering over Knowledge Graph (C-KGQA) seeks to solve complex questions using knowledge graphs. Currently, KGQA systems achieve great success in answering simple questions, while complex questions still present challenging issues. As a result, an increasing number of novel methods have been proposed to remedy this challenge. In this survey, we proposed two mainstream categories of methods for C-KGQA, which are divided according to their use for knowledge graph representation and construction, namely, graph metric (GM)-Based Methods and graph neural network (GNN)-based methods. Additionally, we also acknowledge the influence of ChatGPT, which has prompted further research into utilizing knowledge graphs as a knowledge source to assist in answering complex questions. We also introduced methods based on pre-trained models and knowledge graph joint reasoning. Furthermore, we have compiled research achievements from the past three years to make it easier for researchers with similar interests to obtain state-of-the-art research. Finally, we discussed the resources and evaluation methods for tackling C-KGQA tasks and summarized several research prospects in this field.

Human Rights in Sports Arbitration: What Should the Court of Arbitration for Sport do for Protecting Human Rights in Sports?

Sports governing bodies establish their sporting rules and regulations. Nevertheless, they confront a complex question concerning whether a female athlete who inherently possesses an advantageous quantity of testosterone may participate in female athletic competitions. In Caster Semenya and Athletics South Africa (ASA) v. IAAF, the Court of Arbitration for Sport (CAS) held that she could not participate in female sports events because “the elevated testosterone levels that such athletes possess can create an insuperable advantage over other female athletes who do not have a 46 XY DSD condition”. Consequently, the CAS ruled that she would no longer be eligible to compete in professional female competitions. In this scenario, the primary focus of this article is to examine how the CAS should address human rights-related issues, even though it is not a human rights court like the European Court of Human Rights (ECtHR) but rather an arbitral tribunal. To achieve this purpose, this article will address the following questions: (1) How can athletes claim a violation of their human rights before the CAS?; and (2) What steps should the CAS take to safeguard human rights in sports? Through this research, it may serve to identify the CAS’s role in human rights protection in sports.

Counting in Visual Question Answering: Methods, Datasets, and Future Work

Visual Question Answering (VQA) is a language-based method for analyzing images, which is highly helpful in assisting people with visual impairment. The VQA system requires a demonstrated holistic image understanding and conducts basic reasoning tasks concerning the image in contrast to the specific task-oriented models that simply classifies object into categories. Thus, VQA systems contribute to the growth of Artificial Intelligence (AI) technology by answering open-ended, arbitrary questions about a given image. In addition, VQA is also used to assess the system’s ability by conducting Visual Turing Test (VTT). However, because of the inability to generate the essential datasets and being incapable of evaluating the systems due to flawlessness and bias, the VQA system is incapable of assessing the system’s overall efficiency. This is seen as a possible and significant limitation of the VQA system. This, in turn, has a negative impact on the progress of performance observed in VQA algorithms. Currently, the research on the VQA system is dealing with more specific sub-problems, which include counting in VQA systems. The counting sub-problem of VQA is a more sophisticated one, riddling with several challenging questions, especially when it comes to complex counting questions such as those that demand object identifications along with detection of objects attributes and positional reasoning. The pooling operation that is considered to perform an attention mechanism in VQA is found to degrade the counting performance. A number of algorithms have been developed to address this issue. In this paper, we provide a comprehensive survey of counting techniques in the VQA system that is developed especially for answering questions such as “How many?”. However, the performance progress achieved by this system is still not satisfactory due to bias that occurs in the datasets from the way we phrase the questions and because of weak evaluation metrics. In the future, fully-fledged architecture, wide-size datasets with complex counting questions and a detailed breakdown in categories, and strong evaluation metrics for evaluating the ability of the system to answer complex counting questions, such as positional and comparative reasoning will be executed.