Search Results (25)

Lean practice is recognised for having a great potential in promoting safety risk management in off-site construction (OSC). This paper presents results of a study conducted to assess the impact of lean practice on safety risk management in OSC in a developing country. A quantitative approach using a survey-based questionnaire was adopted. Lean management practices (LMPs) identified from a literature review were empirically tested using a sample survey of 103 OSC contractors. The survey responses were subjected to descriptive and inferential statistics. The top ranked LMPs for safety risk management in OSC included two mistake-proofing practices, i.e., use of personal protective equipment (PPE) and use of hazard warning equipment; two last planner system (LPS) practices, i.e., involvement of workers in safety planning and providing necessary working equipment; and one first run studies (FRS) practice, i.e., critical analysis of work methods. These LMPs are useful in controlling high-consequence safety risks in OSC. Based on evidence found in this study, the paper argues that lean practice can bring great value to safety risk management in OSC in countries where OSC is transitioning. Full article

Curiosity and question-asking are at the heart of science and engineering education. However, question-asking can be difficult for students due to several factors, including fear, language barriers, and cultural norms. This is especially true among Chinese students, who represent a growing number of upcoming engineers. To address this, in this case study from a university teaching reform project, we investigate the perceptions of curiosity and question-asking among Chinese science, technology, engineering, and mathematics (STEM) undergraduate students following a newly developed semester-long project in a second-year communications course at a recently established Sino-foreign engineering school in China. In this period, students engaged in project-based learning centered around Nobel Prize-winning research, allowing them to explore the driving questions behind groundbreaking discoveries. Through a combination of qualitative analyses from students’ personal reflections as well as from a post-survey, the study examines students’ perceptions of curiosity and question-asking, the influence of gender on these skills, and the role of failure and perseverance in scientific inquiry. Findings indicate that the project increased students’ curiosity and improved their confidence in asking questions while providing insights into gender differences. Moreover, students were inspired by the curiosity of the Nobel Laureates, by the “simplicity” of the questions asked, and by the great importance of tenacity, passion, and learning from mistakes. Full article

For a long time, a company’s Product Development Process (PDP) was seen as supporting the operations department, although PDP decisions and mistakes have a considerable impact on market performance. This is critical even in agriculture where bad habits and practices in the PDP can lead rural producers to great losses. Therefore, this research investigates the effect of the PDP on the market performance of rural products (bananas) in the southern region of Brazil, based on two analyses: (i) how sustainability practices support the PDP phases and (ii) how the phases of the Product Life Cycle Assessment (LCA) mediate sustainability practices and PDP phases. This study presents a quantitative analysis using Confirmatory Factor Analysis (CFA) and hierarchical ordinary least squares (OLS) regression of data obtained from a survey of 110 rural producers who directly participate in the banana production and planning process in southern Brazil. Our results show that sustainability practices support the PDP, and we confirm that the product development and post-development phase has an effect on market performance. In addition, we identify that in the pre-development phase of the PDP, dealing with rural products (bananas), the maturity stage of the LCA mediates sustainability. In the PDP development phase, we conclude that rural families who develop economic and environmental practices with their products, which are in the market growth phase may have reduced results. As for the post-development phase of the PDP, we conclude that when companies invest in environmental and social practices, there is a complete mediation of the effect, where these practices lose strength if the product is in the introductory and maturity phases in the market. In an original matter, our study contributes to demonstrating the value of the product life cycle for the Product Development Process in agriculture using sustainability practices through a systemic approach, filling the gap in the literature due to a lack of integrated research on these areas seen. Full article

Testing of ChatGPT has recently been performed over a diverse range of topics. However, most of these assessments have been based on broad domains of knowledge. Here, we test ChatGPT’s knowledge of tinnitus, an important but specialized aspect of audiology and otolaryngology. Testing involved evaluating ChatGPT’s answers to a defined set of 10 questions on tinnitus. Furthermore, given the technology is advancing quickly, we re-evaluated the responses to the same 10 questions 3 and 6 months later. The accuracy of the responses was rated by 6 experts (the authors) using a Likert scale ranging from 1 to 5. Most of ChatGPT’s responses were rated as satisfactory or better. However, we did detect a few instances where the responses were not accurate and might be considered somewhat misleading. Over the first 3 months, the ratings generally improved, but there was no more significant improvement at 6 months. In our judgment, ChatGPT provided unexpectedly good responses, given that the questions were quite specific. Although no potentially harmful errors were identified, some mistakes could be seen as somewhat misleading. ChatGPT shows great potential if further developed by experts in specific areas, but for now, it is not yet ready for serious application. Full article

Research on sustainability must take into account both the need to create a sustainable world and the urgency of undertaking a radical rethinking of our approach to planning and foresight that encompasses a full understanding of the ineludible unpredictability of the complex systems we are dealing with, which can only come about through long-term inter/multi/transdisciplinary educational processes. Those calling for a “culture of sustainability” need to become aware of the systemic and relational dimensions that characterize all processes and dynamics of reality and of the ecosystems we are endeavoring to inhabit. What this signifies is that a culture of sustainability is a culture of complexity. Complex systems are exclusively living systems, whose intrinsic unpredictability cannot be managed, predicted, or controlled by technology. The misleading idea that technology is our only pathway to sustainability is part of the “great mistake” we are making today: the belief that the solution to every contemporary problem is an accelerated combination of digital and technical skills, obtainable through a predominantly applicational form of education based on simulation, velocity, and connectivity, which teaches competences and know-how rather than stimulating what is so direly needed today: the capacity for reflective knowledge and critical thinking. Full article

A program’s bug, fault, or mistake that results in unintended results is known as a software defect or fault. Software flaws are programming errors due to mistakes in the requirements, architecture, or source code. Finding and fixing bugs as soon as they arise is a crucial goal of software development that can be achieved in various ways. So, selecting a handful of optimal subsets of features from any dataset is a prime approach. Indirectly, the classification performance can be improved through the selection of features. A novel approach to feature selection (FS) has been developed, which incorporates the Golden Jackal Optimization (GJO) algorithm, a meta-heuristic optimization technique that draws on the hunting tactics of golden jackals. Combining this algorithm with four classifiers, namely K-Nearest Neighbor, Decision Tree, Quadrative Discriminant Analysis, and Naive Bayes, will aid in selecting a subset of relevant features from software fault prediction datasets. To evaluate the accuracy of this algorithm, we will compare its performance with other feature selection methods such as FSDE (Differential Evolution), FSPSO (Particle Swarm Optimization), FSGA (Genetic Algorithm), and FSACO (Ant Colony Optimization). The result that we got from FSGJO is great for almost all the cases. For many of the results, FSGJO has given higher classification accuracy. By utilizing the Friedman and Holm tests, to determine statistical significance, the suggested strategy has been verified and found to be superior to prior methods in selecting an optimal set of attributes. Full article

Considering the low coverage of roadside cooperative devices at the current time, automated driving should detect all road markings relevant to driving safety, such as traffic signs that tend to be of great variety but are fewer in number. In this work, we propose an innovative few-shot object detection framework, namely Meta-YOLO, whose challenge is to generalize to the unseen classes by using only a few seen classes. Simply integrating the YOLO mechanism into a meta-learning pipeline will encounter problems in terms of computational efficiency and mistake detection. Therefore, we construct a two-stage meta-learner $ℱ$ model that can learn the learner initialization, the learner update direction and learning rate, all in a single meta-learning process. To facilitate deep networks with learning, the fidelity features of the targets improve the performance of meta-learner $ℱ$, but we also design a feature decorrelation module (FDM), which firstly transforms non-linear features into computable linear features based on RFF, and secondly perceives and removes global correlations by iteratively saving and reloading the features and sample weights of the model. We introduce a three-head module to learn global, local and patch correlations with the category detection result outputted by the aggregation in meta-learner $ℱ$, which endows a multi-scale ability with detector $\varphi$. In our experiments, the proposed algorithm outperforms the three benchmark algorithms and improves the mAP of few-shot detection by 39.8%. Full article

Despite tremendous progress in modern-day stroke therapy, ischemic stroke remains a disease associated with a high socioeconomic burden in industrialized countries. In light of demographic change, these health care costs are expected to increase even further. The current causal therapeutic treatment paradigms focus on successful thrombolysis or thrombectomy, but only a fraction of patients qualify for these recanalization therapies because of therapeutic time window restrictions or contraindications. Hence, adjuvant therapeutic concepts such as neuroprotection are urgently needed. A bench-to-bedside transfer of neuroprotective approaches under stroke conditions, however, has not been established after more than twenty years of research, albeit a great many data have demonstrated several neuroprotective drugs to be effective in preclinical stroke settings. Prominent examples of substances supported by extensive preclinical evidence but which failed clinical trials are tirilazad and disodium 2,4-sulphophenyl-N-tert-butylnitrone (NXY-059). The NXY-059 trial, for instance, was retrospectively shown to have a seriously weak study design, a trial of insufficient quality and a poor statistical analysis, although it initially met the recommendations of the STAIR committee. In light of currently ongoing novel neuroprotective stroke trials, such as ESCAPE-NA, and to avoid the mistakes made in the past, an improvement in study quality in the field of stroke neuroprotection is urgently needed. In the present review, animal models closely reflecting the “typical” stroke patient, occlusion techniques and the appropriate choice of time windows are discussed. In this context, the STAIR recommendations could provide a useful orientation. Taking all of this into account, a new dawn for neuroprotection might be possible. Full article

Laser interaction with nanoparticles in liquid is the fundamental theoretical basis for many applications but it is still challenging to observe this nanoscale phenomenon within a few nanoseconds in liquid by experiment. The successful implementation of the two-temperature method integrated with molecular dynamics (TTM-MD) in laser interaction with bulk material has shown great potential in providing a panoramic view of the laser interaction with the nanoparticles. However, the current TTM-MD model has to divide the system into cubic cells, which leads to mistakes near the nanoparticle’s surface. We introduce the latest model, which performs the TTM-MD on each individual cluster instead of the cubic cells, and its high-performance parallel cluster analysis algorithm to update the cluster size. The cluster-based TTM-MD revealed the nanoparticle formation mechanism of laser fragmentation in liquid (LFL) and facilitated the study of laser fluence’s effect on the size distribution. In addition to LFL, this model is promising to be implemented in the laser thermal therapy of tumors, laser melting in liquid (LML), etc. Although cluster-based TTM-MD has proven to be a powerful tool for studying laser interaction with nanoparticles, a few challenges and future developments for the cluster-based TTM-MD, especially the ionization induced by femtosecond, are also discussed. Full article

The pandemic of COVID-19 has caused millions of infections, which has led to a great loss all over the world, socially and economically. Due to the false-negative rate and the time-consuming characteristic of the Reverse Transcription Polymerase Chain Reaction (RT-PCR) tests, diagnosing based on X-ray images and Computed Tomography (CT) images has been widely adopted to confirm positive COVID-19 RT-PCR tests. Since the very beginning of the pandemic, researchers in the artificial intelligence area have proposed a large number of automatic diagnosing models, hoping to assist radiologists and improve the diagnosing accuracy. However, after two years of development, there are still few models that can actually be applied in real-world scenarios. Numerous problems have emerged in the research of the automated diagnosis of COVID-19. In this paper, we present a systematic review of these diagnosing models. A total of 179 proposed models are involved. First, we compare the medical image modalities (CT or X-ray) for COVID-19 diagnosis from both the clinical perspective and the artificial intelligence perspective. Then, we classify existing methods into two types—image-level diagnosis (i.e., classification-based methods) and pixel-level diagnosis (i.e., segmentation-based models). For both types of methods, we define universal model pipelines and analyze the techniques that have been applied in each step of the pipeline in detail. In addition, we also review some commonly adopted public COVID-19 datasets. More importantly, we present an in-depth discussion of the existing automated diagnosis models and note a total of three significant problems: biased model performance evaluation; inappropriate implementation details; and a low reproducibility, reliability and explainability. For each point, we give corresponding recommendations on how we can avoid making the same mistakes and let AI perform better in the next pandemic. Full article

Central banks have been pursuing an expansionary monetary policy since before the pandemic, although the health and economic crisis of COVID-19 has boosted asset purchase programmes. After the Great Recession, a new phase began, characterised by low interest rates and liquidity injections. These policies spilled over into financial markets and are leading to higher inflation. These policies stabilised the situation in the short term, but if they continue indefinitely there is a risk of debt overhang, investment mistakes and high inflation in the future. The aim of this article is to analyse monetary policy developments from the Great Recession to the COVID-19 crisis. Correlations between different macroeconomic variables will be shown through IBM SPSS Statistics. For this purpose, bi-variate correlations were used. For the predictions and confidence of the model data, Tableau Desktop Edition was used, which in turn was used for the generation of the graphs. There is a strong correlation between the growth of monetary aggregates and public debt and stock market capitalisation for the selected indicators. The main contribution of this research is the analysis of the long-term effects of a monetary policy. Full article

Despite the fact that the Fann Mountains are among the most popular tourist destinations in Tajikistan, they are still in the first stage of tourism development. This represents a great opportunity for the implementation of the principles of sustainable tourism, which will avoid the mistakes associated with the uncontrolled tourism development currently observed in other mountain areas of the world. The aim of this article is to demonstrate, using the example of the Fann Mountains, how hydrogeosites in mountain areas can be valorised for the needs of cognitive tourism. The valorisation methods used in previous research to this point have focused on the evaluation of the objects themselves. This study additionally takes into account features of the surroundings of hydrogeostations, such as the visibility range, the vertical development of the view, and the diversity of the landscape. The conducted value assessments of the sites and their surroundings show that in both internal and external assessments the highest values were achieved by lakes and wetlands. This means that the evaluation of the surroundings has a strong influence on the results obtained and the choice of hydrogeotourism attractions. Full article

The use of game-like elements is become increasingly popular in the context of fitness and health apps. While such “gamified” apps hold great potential in motivating people to improve their health, they also come with a “darker side”. Recent work suggests that these gamified health apps raise a number of ethical challenges that, if left unaddressed, are not only morally problematic but also have adverse effects on user health and engagement with the apps. However, studies highlighting the ethical challenges of gamification have also met with criticism, indicating that they fall short of providing guidance to practitioners. In avoiding this mistake, this paper seeks to advance the goal of facilitating a practice-relevant guide for designers of gamified health apps to address ethical issues raised by use of such apps. More specifically, the paper seeks to achieve two major aims: (a) to propose a revised practice-relevant theoretical framework that outlines the responsibilities of the designers of gamified health apps, and (b) to provide a landscape of the various ethical issues related to gamified health apps based on a systematic literature review of the empirical literature investigating adverse effects of such apps. Full article

Acanthocyclops americanus (Marsh, 1892), first described in Wisconsin (USA), was discovered shortly thereafter in Great Britain and then widely distributed in the Palearctic. Its current range includes Europe, North Africa, western and central Siberia with the largest number of findings along the migration tracks of aquatic birds. Until recently, the northern border was the 60th parallel, but in the last decade it has expanded further into the Arctic. The most rapid expansion of its range in Europe happened in the middle of the last century, which was partially hidden from scientists due to a taxonomic mistake caused by the merging of its name with the native Palearctic form Acanthocyclops robustus (Sars, 1863). This problem was solved only recently with the help of molecular genetic tools, allowing a return to the study of biological, anthropogenic and possible climate-dependent mechanisms of the successful rapid invasion of A. americanus into the Palearctic. This paper, along with a detailed description of the life cycle parameters, adaptive behavior of nauplii and population dynamics in Acanthocyclops americanus compared to those in two other native Acanthocyclops species (Acanthocyclops vernalis and A. robustus), provides a possible history of the biological invasion of A. americanus in the Palearctic. Special attention is paid to the climate-dependent mechanism of the expansion of its range into the north and far east of Asia. The introduction of the A.americanus into small lakes in Great Britain resulted in the dominance of this species in the summer plankton. In many high-trophic reservoirs in Belgium, France and Spain, as well as in newly built reservoirs in Europe, this species has become the only representative of crustacean zooplankton in the warm season. This has led to a significant transformation of the trophic webs of these reservoirs. The rapid dispersal of the invasive species, which was demonstrated by A. americanus in the last century, can make it difficult, and in some cases even impossible to study the historical reasons for the formation of the fauna of other invertebrates associated with such events including the movement of continents and the evolution of the Tethys Sea. Full article

Although suicide has been unfortunately stigmatized unfairly through the ages, we should not make the mistake of going to the opposite extreme and valorizing it. We should not forget that the major role of health care professionals is to prevent suicide when possible and to invigorate the underlying life force in the person. Suicide is often the ultimate outcome of a tragic and pessimistic view of life. It was prevalent in ancient Greek writing. Indeed, over 16 suicides and self-mutilations can be found in the 26 surviving tragedies of Sophocles and Euripides. In contrast, only six suicides can be found in the Hebrew Scriptures, and only one suicide in the Christian Scriptures. In addition, the Hebrew Scriptures present numerous suicide-prevention narratives that effectively provide a psychological instruction for people in despair which seems unavailable to figures in the writings of the great Greek tragedians. Unfortunately, some religious traditions tended to go to the opposite extreme in stigmatizing suicide rather than understanding it and trying to prevent it. This paper examines evidence regarding seven evidence-based risk factors for suicide: (1) Feeling depressed and isolated; (2) Feeling one’s life is without purpose; (3) Being a refugee from one’s homeland; (4) Feeling unable to express oneself with others; (5) Being adopted; (6) Feeling abandoned by one’s child leaving the family nest; and (7) Feeling doomed by a dysfunctional (indeed incestuous) family of origin We contrast biblical and Greek narratives regarding each of these factors, respectively: (1) Elijah against Ajax, (2) Job against Zeno, (3) David against Coriolanus, (4) Jonah against Narcissus, (5) Moses against Oedipus, (6) Rebecca against Phaedra, and finally, (7) Ruth against Antigone. These biblical figures thrive across risk factors while their Greek and Roman counterparts kill or mutilate themselves or provoke others to do the job. All these contrasts should demonstrate to psychotherapists, counselors, and clergy alike as to how Greek narratives lead to self-destructive behaviors while biblical narratives provide a hopeful positive psychology, and a constructive way out these dilemmas. My colleagues (Paul Cantz, Matthew Schwartz, and Moriah Markus-Kaplan) and I call for a biblical psychotherapy for positive psychology, suicide prevention, and indeed life promotion. Where hope is locked up in Pandora’s urn after she has released all the evils unto the world, the biblical God places hope into the sky as a bow after Noah and his family and all the creatures on the ark disembark to land after the receding of the flood. Full article