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Student-centered approach has been the center of attention in teaching and learning as the emphasis to shift away from teacher-centered approach is growing. While the term has been widely used, it remains unclear how it can be effectively operationalized given the continuum nature of teacher-centered and student-centered approaches. This article examines 34 articles and included a thematic analysis of their contents to systematically present the methods to operationalize student-centered approach. A channel to practice student-centered approach is project-based learning where students work on projects, such as community and design projects, and are expected to manage the projects or at least propose actions or solutions. Problem-based learning is a variant of project-based learning and students often work on scenarios, cases, questions, or problems which are less extensive than projects. Problem-solving usually precedes lectures to promote self-directed learning and facilitate scaffolding. An argument-based curriculum incorporates arguments and debates that engage students in the self-discovery of different perspectives on a given topic. Student-centered approach is closely linked to the use of technology for research, interactions, gamification, simulations, and feedback. Student-centered feedback prompts active learning through deliberate feedback while adaptive teaching involves students in content-building. This review contributes to the enhancement of student-centered elements in teaching and learning.

Reticence prevalent among East Asian students has prompted educators to attempt different methods to engage them. Gamification of courses has gained popularity as an avenue to encourage students’ participation, and it is facilitated by the roll-out of diverse online gamification platforms. This study aims to reflect on an educator’s experience of incorporating elements of gamification in an environmental science course delivered in a micro-campus established through a Sino-American educational collaboration. Gibb’s Reflective Cycle was adopted to guide the reflection practice. Gamification was implemented with three online interactive platforms, namely Poll Everywhere, Kahoot, and Quizizz. Poll Everywhere was mainly used for short polls and activities during lessons, while Kahoot and Quizizz were used for quiz-like competitions whose scores did not contribute to students’ grades. Kahoot created a lively atmosphere in class but was constrained by limits on players’ numbers, internet control, and the lag between sending and receiving responses. Quizizz had more game elements, which thrilled individual players but was less able to create the lively classroom the educator desired. It was more stable, perhaps because it was less subjected to internet control. Poll Everywhere had a less attractive scoreboard and was more appropriate for short classroom activities. Students' interest in the platforms tended to wane with each repeated use of the platforms. To improve the gamification experience, a mix of platforms could be used, and locally developed platforms could be sourced for stability and diversification.

While microplastics have been detected in various spheres of the environment, there are few studies examining their abundance in higher education institutions, where their exposure to students and staff could raise concern. This study aims to quantify and characterise the microplastics in the soil of a higher education institution in China. Surface soil samples were collected in triplicate from nine sampling sites distributed evenly across teaching, recreational, and residential areas on campus. The soil samples were sieved with a 5 mm screen, and the fractions passing through the sieve were digested with 30% hydrogen peroxide. Microplastics were density-separated from the digested soil and observed under the microscope. ATR-FTIR was used to determine their compositions. This study reveals a higher abundance of microplastics in teaching and residential areas (150–700 items/kg and 50–650 items/kg, respectively) as compared to recreational areas (0–450 items/kg), with the highest mean abundance (516.7 items/kg) recorded for residential areas. Fibrous and fragment microplastics (31.5% and 33.3%, respectively) were most common in the soil samples, with the former more prevalent in residential areas. There were more black microplastics (36.4%) and white microplastics (29.1%) than those of other colors. Microplastics £ 0.5 mm constituted the largest fraction (64.3%) of total microplastics recovered and polyethylene microplastics were most abundant (35.2%). This study contributes to a better understanding of microplastic pollution in the compounds of higher education institutions, which could be positively linked to the human activities within those institutions.

Purpose In view of a lack of evidence on the effectiveness of climate change education (CCE) in China, this study aims to evaluate if a CCE course newly designed based on research recommendations and implemented with established pedagogy was effective in changing the beliefs and attitudes of first-year science students. Design/methodology/approach This study took a simple longitudinal approach with surveys administered at the beginning and the end of the course and the differences in the responses analyzed with nonparametric statistical analyses. Findings The results showed that the course produced significant changes in the beliefs concerning the anthropogenic causes of climate change and vulnerability to its impacts, which results in inequality of the impacts received. However, the course did not produce significant attitudinal changes among the students. Spearman’s correlation, which affirmed the belief–attitude association, revealed that the students already had desirable attitudes toward climate change and these attitudes had not been reinforced. The students’ perception of the importance of local government in climate action increased by the end of the course. Multimedia-aid learning, debates and discussions were useful in conveying the concepts of responsibility, ethics and vulnerability, but the addition of student-led community projects will increase personal significance of the course. Research limitations/implications This study is instrumental for the development of a regional model of CCE in the mainstreaming of education for sustainable development in China, knowing that the regional approach is crucial to address the nuances in climate change knowledge, hence conceptions and beliefs across regions and, even, between different sectors of a region. This regional experience could also serve as a reference for other similar settings, particularly those of the developing countries. Originality/value This study presents one of the very few studies dedicated to gauging the effects of CCE in China, particularly of a newly developed climate change course, on the beliefs and attitudes of students. This permits pedagogical development and continuous improvement of CCE in China.

The growing plastic pollution has prompted the quest to reduce plastic waste sustainably and control the mismanaged plastic stream. The valorization of plastic waste through reusing and recycling has received much attention as a sustainable solution to the global plastic problem, and the construction sector provides an important avenue for such an endeavor. This review aims to present the latest advances in the valorization of plastic waste as construction and building materials through the review of 60 relevant scholarly papers and a content analysis of the papers. In the construction sector, plastic waste can be valorized as additives or raw materials for brick production. As additives, plastic waste is added at different proportions (1%–70%) with other materials, including non-plastic waste, followed by curing to acquire the desired properties. Plastic waste is used as a raw material to contain strength-imparting materials. The former has been reported to have good strengths (5.15-55.91 MPa), chemical, and thermal resistance, whereas the latter may impart lower strengths (0.67-15.25 MPa). Plastic waste is also used as additives for road pavement, primarily as substitutes for concrete-making materials, and was observed to produce desirable strengths (0.95–35 MPa) at appropriate proportions (0.5–25%), indicating the importance of optimizing the plastic contents in the concrete. Plastic waste has been recycled as plastic lumber, plastic-based door panels and gates, as well as insulation materials. Plastic-based construction materials are generally lightweight, resistant to chemicals and heat, and have good sound insulation, but they may pose a fire safety concern.

COVID-19 has resulted in an abrupt and significant increase in medical waste, albeit with improving air and water quality in certain regions. This paper aims to review the types, abundance, and impacts of COVID-19-related medical waste through examining the contents of 54 peer-reviewed scholarly papers. COVID-19-related medical waste compositions vary over time, with COVID-19 screening, diagnostic, and treatment wastes, as well as used personal protective equipment (PPE), constituting the majority of medical waste at the start, followed by vaccination waste during the peak of vaccination. COVID-19-related medical waste is expected to decrease and steady as more and more countries relax restrictions in an attempt to live with COVID-19. Geographically, the amount of COVID-19-related medical waste depends on population size, with highly-populated countries and cities such as China, Manila, Jakarta, and Bangkok seeing or expected to see a hike in the waste of between 210 tonnes/day and 280 tonnes/day during COVID-19. Packaging of the medical and PPE items forming the medical waste stream also contributes to a substantial amount of waste. As plastics are a major component of medical waste, the increase in COVID-19-related medical waste and its mismanagement have worsened environmental pollution caused by plastics. The surge of medical waste during COVID-19 strained the existing medical waste disposal systems, and incineration of the waste contributed to air pollution, which was often localized. Mismanagement of the waste could also raise public health concerns and cause visual repercussions.

Wastewater treatment plants (WWTPs) play the role of intercepting microplastics in the environment and provide a platform for bioremediation to remove microplastics. Despite, this opportunity has not been adequately studied. This paper shows the potential ways microplastics-targeted bioremediation could be incorporated into wastewater treatment through the review of relevant literature on bioaugmentation of water treatment processes for pollutants removal. Having reviewed more than 90 papers in this area, it highlights that bioremediation in WWTPs can be employed through bioaugmentation of secondary biological treatment systems, particularly the aerobic conventional activated sludge, sequencing batch reactor, membrane bioreactor and rotating biological contactor. The efficiency of microplastics removal, however, is influenced by the types and forms of microorganisms used, the polymer types and the incubation time (100% for polycaprolactone with Streptomyces thermoviolaceus and 0.76% for low-density polyethylene with Acinetobacter iwoffii). Bioaugmentation of anaerobic system, though possible, is constrained by comparatively less anaerobic microplastics-degrading microorganisms identified. In tertiary system, bioremediation through biological activated carbon and biological aerated filter can be accomplished and enzymatic membrane reactor can be added to the system for deployment of biocatalysts. During sludge treatment, bioaugmentation and addition of enzymes to composting and anaerobic digestion are potential ways to enhance microplastics breakdown. Limitations of bioremediation in wastewater treatment include longer degradation time of microplastics, incomplete biodegradation, variable efficiency, specific microbial activities and uncertainty in colonization. This paper provides important insight into the practical applications of bioremediation in wastewater treatment for microplastics removal.

The impetus to raise awareness and impart positive attitude change toward climate action as one of the sustainability goals has catalyzed the introduction of climate change courses in universities, particularly in developing countries. An online climate change course has been developed and delivered as an elective to the first-year students of a university in China. A reflection of the course in terms of its teaching and learning and assessment was conducted based on the Gibbs’ Reflective Cycle with SWOT employed for evaluation and analysis of the experience. The course has the strength of incorporating abundant audio-visual elements, highlighting important points in slides, employing gamification, and simulating community projects in assignments. However, online teaching could be more time-consuming than face-to-face teaching in certain aspects, such as preparation of activities and games, and responding to students after office hours. Despite this, students felt that more interactions could be integrated, and teamwork might lead to advantage-taking and unequal task distribution in certain groups. This reflection calls for further improvement with the greater use of online interactive platforms and databases; interactions with experts and scientists in the field; delivery of community projects or talks to a real audience; and cross-varsity and cross-regional collaborations.

This study aims to understand the soil impacts of illegal dumpsites in Malaysia through quantifying the heavy metals in the soil of two dumpsites, one receiving construction waste and the other receiving municipal solid waste. Five soil samples were collected from each dumpsite, and sampling was repeated in the second week to examine the temporal changes in the levels of heavy metals. All sampling was conducted in triplicates. The soil samples were sieved, dried, and digested with aqua regia at 70 °C, after which the digested mixtures were filtered. The filtrates were diluted and tested with an atomic absorption spectrophotometer for heavy metals. The soil heavy metal concentration ranges were as follows: Al (24.67-142.20 mg/kg), Cd (< 0.01-0.083 mg/kg), Cu (0.10-14.99 mg/kg), Fe (11.20-241.77 mg/kg), Mn (0.09-22.60 mg/kg), Ni (0.02- 0.77 mg/kg), and Zn (0.14-35.03 mg/kg). All the heavy metals have been detected at all the sampling points except that the Cd levels at some sampling points were below the detection limit. The levels of heavy metals varied spatially and temporally, though higher Cd, Cu, Fe, Mn, Ni, and Zn were detected consistently at two sampling points of the dumpsite receiving municipal waste. This could be linked to the electrical and electronic waste at the dumpsite. The levels of heavy metals in the soil did not constitute soil contamination. However, it is important to control illegal dumping activities to reduce the associated health and safety concerns, such as infestation of vermin, fire, physical hazards, and odor.

Biological removal of dyes has been advocated due to its simplicity, cost-effectiveness, and low operational requirements in comparison to physicochemical methods of treating dye effluents. This paper aims to compare the efficiency of biological removal of dyes using bacteria, algae, and fungi, including yeasts, besides presenting the recent advances in the field. This paper reviewed scholarly articles published mainly between 2010 and 2021. It found bacteria could degrade a myriad of dyes. Different bacteria could degrade the same dye with different efficiencies. Similarly, one bacterial species could degrade multiple dyes with varying efficiencies. Though regarded as having a faster rate of dye biodegradation than fungi, this review finds bacteria to have comparable performance to fungi in decolorizing dyes, and it is worth mentioning that a few yeast species were reported to have very high efficiency in decolorizing dyes. Mixed bacteria or bacteria-fungus cultures were generally found to have better dye-decolorizing efficiency than pure cultures. Algae have relatively lower efficiency than bacteria and fungi in decolorizing dyes and might require longer contact time. New advances such as genetic engineering as well as immobilization of microorganisms and enzymes could improve the efficiency of dye biodegradation. Nonetheless, before biological removal of dyes can be feasibly applied, there are limitations that need to be overcome. Major limitations include the inconsistent performance of various organisms in decolorizing dyes; the complexity of optimization; inability to completely decolorize dyes; potential formation of toxic by-products upon decolorization of dyes; safety concerns of immobilization materials; and cost and technical feasibility of biological removal of dyes. This review has the significance of highlighting the important bottlenecks of the current biological dye removal technology, which could pave the way for breakthroughs in this domain of research.

The utilization of less expensive and more effective adsorbents derived from a variety of basic materials has been investigated. The research aimed to investigate the feasibility of employing waste paper as the adsorbent to remove the cresol red (CR) dye from wastewater through adsorption mechanism. Langmuir, Jovanovic, and Freundlich model were observed for isotherms models, while pseudo-first-order and pseudo-second-order were examined for kinetic models. The results indicated that increasing the adsorbent dose and contact time gave no significant effect to adsorption capacity while adsorption capacity increased with the increasing of pH until it reached a maximum at pH 8, and raising the starting dye concentration leads in a significant increase in adsorption capacity (16.7 mg/g). When the experimental adsorption isotherms and kinetic were fitted using the Freundlich models and pseudo-second-order model, it was discovered that those models were more accurately represented by the data, as indicated by a high correlation coefficient (R2) of 0.974 and 0.963.

Musculoskeletal disorders (MSDs) are collectively referring to an array of conditions affecting the human locomotor system, such as muscles, nerves, joints, tendons and spinal discs. MSDs related to work are called occupational MSDs and are typically caused by physical factors consisting of repetitive tasks, forceful exertions, awkward positions, vibration due to use of vibrational tools and prolonged staying in the same positions. These physical factors are often complicated by psychosocial factors comprising job demand, job control, social support, job satisfaction, job security, work arrangement, etc. which can aggravate the biomechanical loading imposed by physical factors, thus resulting in more severe outcomes. Besides, individual factors such as health conditions, age, education level and medical history could lead to highly variable physiological responses and internal tolerances, hence outcomes. As the physical and psychosocial risk factors vary widely in different workplaces, the prevalence of MSDs tends to vary with sectors, occupations and even regions. Generally, healthcare sector has been reported to have relatively high occupational MSDs cases in multiple nations. To prevent occupational MSDs, priority should be given to elimination of the associated risks through job and workplace designs and management. Where elimination is not practical, the risks could be reduced through modification of workplace layout, work environment, work systems and tools as well as the use of mechanical aids. Provision of information, instruction and training, and other administrative controls such as job rotation which do not target at reducing the risks would have lower priority and should be used together with other control measures of higher priority.

Seagrass meadows provide important ecological functions, particularly by serving as carbon sinks and breeding grounds for marine species. Climate change has threatened seagrass communities, causing their replacement, loss and increased vulnerability. This review examined scholarly articles published between 2010-2021 to comprehensively present the impacts of climate change on seagrass meadows. It shows that ocean warming negatively affects seagrass communities by favouring communities of lower structuring capacities, thus reducing the effectiveness of their ecological functions. Ocean warming also promotes the propagation and spread of invasive species, and changes the trophic structures leading to further loss of seagrasses of value. Higher seawater temperature is associated with shoot mortality and retarded growth of certain seagrasses. Sea level rise causes more wave energy to be received by coastal seagrass communities, thus, creating more damage to the communities. Deepening sea limits light penetration and alters distribution of seagrass meadows. Carbon dioxide enrichment of seawater increases photosynthetic rate of seagrasses but ocean warming and acidification counteract this beneficial effect. Carbon dioxide enrichment affects different seagrass species and different parts of a seagrass species differently, and, where beneficial to seagrass communities, could enhance their ecological services. Temperature extremes could kill seagrasses while marine heatwaves and flooding could act synergistically to increase carbon demand of certain seagrasses and unfavourably change their biomass. These impacts are often aggravated by anthropogenic activities. This review calls for more studies and conservation efforts to understand the impacts of climate change on seagrass communities and future-proof them against the changing climate.

Aims: The impetus to combat intensifying climate change has prompted countries to make policies pertinent to climate change. With China, India, the United States and the European Union contributing to more than half of greenhouse gases emitted, their climate change policies are of concern particularly as signatories of the Paris Agreement. Study Design: This article critically reviews the climate change policies of the four largest emitters of greenhouse gases, particularly their similarities and differences. Methodology: This review examined more than 85 literature including scholarly articles, official reports and policy documents published between 2010 and 2020, pertaining to climate change and energy policies, plans and programs of the four regions. Results: This review shows that the policies address similar domains comprising efficiency in energy and resources utilization, development of cleaner and renewable energy, optimization of transport system and promotion of electric mobility. Land use, land-use change and forestry is more commonly addressed in policies of developing countries than the developed ones. Major differences of the policies are the emphasis where the United States and European Union focus more on clean transportation particularly hydrogen fuel, besides carbon market. The extents of making policy targets legally binding also differ. There is a significant deficiency of adaptation policies compared to mitigation policies. Conclusion: This review, thus, contributes to identifying shortcomings of current climate change policies and continuous improvement of the policies.

The multi-agent system has been a hot topic in the past few decades owing to its lower cost, higher robustness, and higher flexibility. As a particular multi-agent system, the multiple rigid body system received a growing interest since its wide applications in transportation, aerospace, and ocean exploration. Due to the non-Euclidean configuration space of attitudes and the inherent nonlinearity of the dynamics of rigid body systems, synchronization of multiple rigid body systems is quite challenging. This paper aims to present an overview of the recent progress in synchronization of multiple rigid body systems from the view of two fundamental problems. The first problem focuses on attitude synchronization, while the second one focuses on cooperative motion control in that rotation and translation dynamics are coupled. Finally, a summary and future directions are given in the conclusion.

Recent progress in end-to-end Imitation Learning approaches has shown promising results and generalization capabilities on mobile manipulation tasks. Such models are seeing increasing deployment in real-world settings, where scaling up requires robots to be able to operate with high autonomy, i.e. requiring as little human supervision as possible. In order to avoid the need for one-on-one human supervision, robots need to be able to detect and prevent policy failures ahead of time, and ask for help, allowing a remote operator to supervise multiple robots and help when needed. However, the black-box nature of end-to-end Imitation Learning models such as Behavioral Cloning, as well as the lack of an explicit state-value representation, make it difficult to predict failures. To this end, we introduce Behavioral Cloning Value Approximation (BCVA), an approach to learning a state value function based on and trained jointly with a Behavioral Cloning policy that can be used to predict failures. We demonstrate the effectiveness of BCVA by applying it to the challenging mobile manipulation task of latched-door opening, showing that we can identify failure scenarios with with 86% precision and 81% recall, evaluated on over 2000 real world runs, improving upon the baseline of simple failure classification by 10 percentage-points., Comment: Accepted to the 2023 IEEE International Conference on Robotics and Automation (ICRA 2023)

We describe a system for deep reinforcement learning of robotic manipulation skills applied to a large-scale real-world task: sorting recyclables and trash in office buildings. Real-world deployment of deep RL policies requires not only effective training algorithms, but the ability to bootstrap real-world training and enable broad generalization. To this end, our system combines scalable deep RL from real-world data with bootstrapping from training in simulation, and incorporates auxiliary inputs from existing computer vision systems as a way to boost generalization to novel objects, while retaining the benefits of end-to-end training. We analyze the tradeoffs of different design decisions in our system, and present a large-scale empirical validation that includes training on real-world data gathered over the course of 24 months of experimentation, across a fleet of 23 robots in three office buildings, with a total training set of 9527 hours of robotic experience. Our final validation also consists of 4800 evaluation trials across 240 waste station configurations, in order to evaluate in detail the impact of the design decisions in our system, the scaling effects of including more real-world data, and the performance of the method on novel objects. The projects website and videos can be found at \href{http://rl-at-scale.github.io}{rl-at-scale.github.io}., Comment: Published at Robotics: Science and Systems 2023

Recent strides in Large Language Models (LLMs) have saturated many NLP benchmarks (even professional domain-specific ones), emphasizing the need for novel, more challenging novel ones to properly assess LLM capabilities. In this paper, we introduce a novel NLP benchmark that poses challenges to current LLMs across four key dimensions: processing long documents (up to 50K tokens), utilizing domain specific knowledge (embodied in legal texts), multilingual understanding (covering five languages), and multitasking (comprising legal document to document Information Retrieval, Court View Generation, Leading Decision Summarization, Citation Extraction, and eight challenging Text Classification tasks). Our benchmark comprises diverse legal NLP datasets from the Swiss legal system, allowing for a comprehensive study of the underlying Non-English, inherently multilingual, federal legal system. Despite recent advances, efficiently processing long documents for intense review/analysis tasks remains an open challenge for language models. Also, comprehensive, domain-specific benchmarks requiring high expertise to develop are rare, as are multilingual benchmarks. This scarcity underscores our contribution's value, considering most public models are trained predominantly on English corpora, while other languages remain understudied, particularly for practical domain-specific NLP tasks. Our benchmark allows for testing and advancing the state-of-the-art LLMs. As part of our study, we evaluate several pre-trained multilingual language models on our benchmark to establish strong baselines as a point of reference. Despite the large size of our datasets (tens to hundreds of thousands of examples), existing publicly available models struggle with most tasks, even after in-domain pretraining. We publish all resources (benchmark suite, pre-trained models, code) under a fully permissive open CC BY-SA license.

The elevation of waste generation subsequent to population growth has become a severe environmental topic in Malaysia. Since most of the waste is being dumped into a landfill, the open dumpsite, or unsanitary landfills which are not constructed with proper engineering plan, severe impacts on the environment result. The energy demand in Malaysia increased with the growing population, but reliance on fossil fuels to generate electricity has created another greenhouse gas contributor. Alternatively, waste-to-energy technology solves the problem of increasing waste by converting the waste to a renewable energy source. Malaysia has moved towards landfill gas recovery system and incineration for waste energy recovery. The recovery system and refuse-derived fuel plant achieved expectation; however, the incineration plants have failed due to the opposition of the public, lack of funding and technician expertise, and other technical issues. The solid waste management practices lacking separation and recycling sources, become an obstacle for development. The government puts effort into solving the current issue by promoting recycling in the public, enforcing the legislation, and approaching new technologies for better solid waste management practice in the future. This paper aims to discuss the application of energy recovery from municipal solid waste in Malaysia.

With COVID-19 vaccination gaining momentum, strict lockdowns have been perceived as no longer necessary due to their far-reaching socioeconomic impacts. This overview aims to provide insight into Malaysia’s strategy in preparing to live with COVID-19 through stage-wise transition. This overview examined scholarly articles, news articles as well as official government announcements and data pertaining to the National Recovery Plan (NRP) which replaces COVID-19 lockdowns officially known as Movement Control Order (MCO) in Malaysia. NRP, which presents a stage-wise relaxation of lockdown leading ultimately to conditional reopening of all sectors and lifting of travel restrictions, adopts three major indicators for transitions of phases. The indicators are daily new COVID-19 cases, occupancy rate of intensive care units and full vaccination rate. Domestic travel initiatives have been initiated during the NRP, allowing domestic visits to certain tourist spots in the nation. Interstate travel in most parts of the nation has also been permitted without needing to show a negative COVID-19 test. On 28 October 2021, six states and three federal territories of Malaysia were already in phase 4 of NRP, which is the ultimate phase of lockdown relaxation, while all other states were in phase 3. This has resulted in a positive outlook on the gross domestic products of Malaysia in quarter 3, 2021. This overview highlights that a different approach to COVID-19 is necessary as total elimination of COVID-19 is not yet in sight. It sheds light into the use of pertinent indicators or indices to capture the status of COVID-19. Keywords: COVID-19; indicators; Malaysia; MCO; National Recovery Plan;Vaccination.

Aims: With lead being one of the most common soil contaminants and phytoextraction has been reported as a prospective method for remediation of lead-contaminated soil, this review aims to examine the feasibility of lead phytoextraction as well as its constraints and concerns. Study Design: This is a literature review. Methodology: Peer-reviewed papers were sourced from scholarly databases. The papers included in the review were mainly those about phytoextraction of lead, particularly with the shoot, soil and root concentrations of lead mentioned as well as the bioconcentration and translocation factors stated. Besides, papers discussing the limits, for instance, the duration of lead phytoextraction, and concerns of the approach were also included. Results: This review found only 11 plants have been reported to accumulate lead in shoots at nominal threshold of near or above 1,000 mg Pb/kg dry weight and in certain cases, soil amendment was required to achieve this. Only two of the plants had bioconcentration factor > 1 and another two had translocation factor > 1. None of the plants fulfilled all three criteria of a successful hyperaccumulator, indicating the constraints and a lack of feasibility of lead phytoextraction. Besides, lead phytoextraction has been predicted to require significant amount of time, hence increasing the risk of exposure to lead. Conclusion: This review highlights that lead phytoextraction may not be feasible for the remediation of lead-contaminated soil. It recommends phytostabilization as a more viable alternative to immobilize lead in rhizosphere and reduce lead exposure.

This paper introduces a new, highly consequential setting for the use of computer vision for environmental sustainability. Concentrated Animal Feeding Operations (CAFOs) (aka intensive livestock farms or "factory farms") produce significant manure and pollution. Dumping manure in the winter months poses significant environmental risks and violates environmental law in many states. Yet the federal Environmental Protection Agency (EPA) and state agencies have relied primarily on self-reporting to monitor such instances of "land application." Our paper makes four contributions. First, we introduce the environmental, policy, and agricultural setting of CAFOs and land application. Second, we provide a new dataset of high-cadence (daily to weekly) 3m/pixel satellite imagery from 2018-20 for 330 CAFOs in Wisconsin with hand labeled instances of land application (n=57,697). Third, we develop an object detection model to predict land application and a system to perform inference in near real-time. We show that this system effectively appears to detect land application (PR AUC = 0.93) and we uncover several outlier facilities which appear to apply regularly and excessively. Last, we estimate the population prevalence of land application events in Winter 2021/22. We show that the prevalence of land application is much higher than what is self-reported by facilities. The system can be used by environmental regulators and interest groups, one of which piloted field visits based on this system this past winter. Overall, our application demonstrates the potential for AI-based computer vision systems to solve major problems in environmental compliance with near-daily imagery., Comment: Accepted to CIKM '22

Aims: With increasing emphasis on learners-centered approach in teaching and learning, engaging students in course development and refinement is crucial. This study aims to foster a participatory approach in course development by engaging students in meaningful discourse at the early stage of an atmospheric science course. Study design: This is a qualitative study which employed the grounded theory for data analysis. Place and Duration of Study: The study was conducted in March 2021 in an international higher learning institution located in the Guangdong Province of China. Methodology: This qualitative study invited a year 3 cohort of environmental science students taking an atmospheric science and pollution course in an international higher learning institution in China to participate in a meaningful discourse about the course in week 2 of the semester. Their responses were transcribed and the transcripts analyzed with NVIVO based on the grounded theory. The transcripts were coded, the themes were drawn and the relationship was probed. Results: This study identified three overarching themes from the codes, namely assessment, course contents and learning activities, whose codes covered 4.5%, 17.8% and 23.1% of the text respectively. Codes for assessment comprise practical assignment and multiple-choice question, while those for course contents include black carbon, modelling, greenhouse gases, zero-carbon, and removal of Freon. Codes for learning activities include case studies, debate, field trips and quizzes. The words most frequently appeared in the transcripts are learning and field. The findings reflect expectations for interactive learning, simulation-based learning, authentic assignments and activities, experiential learning via field trips and problem-based learning. These are in line with the established pedagogies for environmental science. Conclusion: This study shifts the paradigm of students’ engagement in the increasingly learner-centered educational setting where students are proactively involved in course development in the early stage of teaching and learning instead of reactively involved through feedback collection at advanced stages.

Countries entered lockdown or partial lockdown due to mounting fear for the spread of COVID-19 and emerged from the restrictions with presumably new norms, often known as the ‘new normal’. This commentary aims to examine whether the so-called ‘new normal’ qualifies as the new norms based on the definitions of social and cultural norms. The aim was achieved through reviewing pertinent literature comprising news articles, scholarly articles, government reports and websites centering on norms, COVID-19 new norms and their implications. It posits that social isolation does not align with the social nature of human and can be detrimental to the mind and body while social or physical distancing is situational. Unregulated, it does not quite constitute a norm for people to readily maintain social isolation, and social or physical distancing to a lesser degree. While mask-wearing is comparatively easier to adopt, its significance varies in different social and cultural settings. It is more normal to observe people wearing masks post-lockdown, particularly in Asia though experts’ advice does encourage mask-wearing in certain western countries. Mask-wearing aptly qualifies as the new norm though this norm could last longer in certain societies, often strengthened by cultural norms. Similarly, high level of personal hygiene is still practiced often without coercion and is perceived to be normal at least for as long as the risk of COVID-19 is still present. It is thought that norms can be strengthened through interventions to promote behaviours that fit the norms.

Case investigation and contact tracing (CICT) has been a fundamental public health practice during the COVID-19 pandemic, but little causal evidence exists on its effectiveness. In partnership with the Santa Clara County Public Health Department, this study utilizes a stepped-wedge (randomized rollout) trial to overcome the political and ethical constraints of randomizing the allocation of contact tracing resources. In doing so, we aim to evaluate the effectiveness of COVID-19 contact tracing on community transmission, resource linkage, and other meaningful individual and broader public health outcomes.

Climate change has far-reaching impacts not only on the ecosystems but on the astrosphere. Its effects on the astrosphere are multi-tiered from an entire nation down to individuals including the working population. It alters exposure to environmental hazards and the subsequent occupational risks. This review looks into how various aspects of climate change influence occupational safety and health, and provides recommendations for workplace adaptation. This review examines official data and peer-reviewed scholarly articles published in the past 15 to 20 years to draw the impacts and recommendations. It highlights the susceptibility of outdoor workers to heat and humidity caused by global warming and their works often require high physical demand and the wearing of personal protective clothing which exacerbate heat impacts. Excessive heat causes excessive sweating which could lead to dehydration and kidney disease. Mounting heat reduces working capacity and productivity besides increasing respiration rate hence exposure to chemicals through inhalation. Extreme weather events, particularly wildfires resulted from drought and increasing temperature present high occupational risk to firefighters and other outdoor workers in the wildfire zones, exposing them to extreme heat and numerous air pollutants. Global warming has been linked to increased lightning strikes and more severe heatwaves threatening workers. Flooding and more intense storms increase the occupational risks of those working on sea and in coastal areas. Climate change also alters the distribution and prevalence of disease vectors, creating new occupational risk. Adaptations should take into consideration climate change and workers’ protection in building designs, coastline protection and adaptive response. Keywords: Adaptation; Climate change; Extreme weather; Heat; Safety and health; Workplace

Asset integrity is closely intertwined with process safety where the latter is often perceived to be equivalent or a subset of the former. In Malaysia, the requirements for offshore process safety are set by Petronas assuming exclusive rights to petroleum in the nation. It imposes and enforces these requirements on oil and gas companies entering into its production sharing contracts via the common law. Process safety management in Malaysia is strongly influenced by the US OSHA 3132 with elements comprising process safety information, process hazard analysis, operating procedures, employee participation, training, contractors, pre-startup safety review, mechanical integrity, hot work permit, management of change, incident investigation, emergency planning and response as well as compliance audits. These elements are largely included in the Mandatory Control Framework of Petronas and the trio of design, technical and operating integrity adopted in the process safety management of other oil and gas companies. These management practices align with the reiterative plan-do-check-act model. Process safety performance is also gauged with indicators suggested by international institutions such as the American Petroleum Institute. On top of the Control of Industrial Major Accident Hazards Regulations 1996 for onshore processes, this study deems that establishing statutory law for offshore installations will be beneficial to propel offshore safety in Malaysia to a greater height.

Aims: While the biomechanical factors causing musculoskeletal disorder (MSDs) are well defined, the psychosocial dimension of MSDs is complex and affected by personal, organizational and environmental elements. There is an impetus to understand how psychosocial risk factors contribute to the manifestation of MSDs and systematically present the strengths and constraints of various instruments in assessing psychosocial risk factors. Study Design: This article critically reviews various models linking psychosocial constructs to MSDs and various instruments for evaluating psychosocial risk factors. Methodology: This article reviews the most pertinent literature which presents and discusses the connection of psychosocial domains with the development of MSDs as well as the common instruments used for evaluation of psychosocial factors. Results: It shows an intricate connection between psychosocial and biomechanical aspects compounded by organizational, individual and environmental factors. Psychosocial factors particularly psychological demand, decisional latitude, level of social support and work organization result in stress which produces strain and physiological deterioration hence MSDs. Different psychosocial risk factors have also been found to evoke MSDs in different body parts. Overarching cognitive and psychological aspects consisting of work demands, maneuver margins and work recognition have also been proposed in examining the psychosocial dimension of MSDs. Instruments for measuring psychological constructs are often subjective and rely on personal reflections. Some instruments assess multiple psychosocial factors while other assess specific attributes. There instruments share a common shortcoming of treating risk factors across different workplaces as homogenous. Conclusion: Refinement of the instruments and development of sector-specific instruments are beneficial for more reliable evaluation of psychosocial risk factors.

Ergonomic assessment tools are crucial for evaluation of biomechanical risk factors at workplaces to understand the contributing factors and reduce the prevalence of musculoskeletal disorders (MSDs) which have negative implications on employees’ health and productivity. This review examines a range of methods and ergonomic assessment tools. It shows ergonomic assessment tools, particularly postural analysis to comprise self-reports from workers, observation methods, direct measurement method and advanced techniques for assessment of postural change in executing highly dynamic activities. These tools have been designed for different work activities consisting typically of manual handing, repetitive tasks and static loading. Some of the tools target at specific body parts while others at multiple body parts. The tools have the strengths particularly in the assessment of recurring tasks in standing or sitting postures involving specific or multiple body parts. However, the tools also have obvious limitations in terms of not considering vibration, contact stress and trauma to other body parts for tools assessing specific body parts, and undifferentiated weight of different ergonomic risks for whole-body tools. These strengths and shortcomings prompt a user to consider the job nature and tasks to be assessed prior to selecting the tools. This review advocates an integrated approach in ergonomic assessment using a combination of general and specific methods with direct measurements if permissible. It contributes to the accurate selection of the postural analysis tools through systematically presenting their features and limitations besides highlighting improvement of methods and approaches in ergonomic assessment.

PurposeThis review compares the primary occupational safety and health (OSH) laws of the ASEAN members against the major provisions of the primary OSH laws of the United Kingdom (UK) and United States (US) grouped under the themes for OSH law adopted by the International Labour Organization (ILO).Design/methodology/approachThis review employs the 11 themes for OSH law adopted by the ILO as the basis of comparison. As the themes lack specificity in terms of their respective contents, specific facets of the themes are drawn from the review of the primary OSH laws of the UK and the US.FindingsThe review shows that primary OSH laws of the ASEAN members encompass the fundamental aspects of the ILO OSH themes particularly the regulatory framework, scope, roles of authorities, duties of employers and employees as well as safety inspection and enforcement. The review demonstrates a lack of provision of worksite consultation by the authorities, the emphasis on research, experiment and demonstration by the government as well as certain aspects of training.Practical implicationsOSH in many developing members of the ASEAN is still evolving to advocate the basic rights of employees, protect the safety of the public and ensure the welfare, safety and health of employees are upheld at workplaces. There is an obvious disparity in the coverage of the primary OSH laws of the nations, resulting in widely varied OSH implementation. This study contributes to advancement of the primary OSH laws in developing ASEAN members by highlighting areas of their primary OSH laws that can be improved. Improvement of the primary OSH laws is crucial to subsequent improvement and development of subsidiary laws to provide for adequate protection at workplaces.Originality/valueMost studies of OSH laws in the ASEAN are country-specific and often theme-specific. There is currently no study which compares the primary OSH laws of ASEAN nations using themes derived from the ILO as well as primary OSH laws of the UK and the US. This review is one of its kinds to use such an approach in providing a comparative overview of the primary OSH laws of all ASEAN nations.

Participating in campus security preparedness exercise (CSPE) is vitally important in addressing potential security threats and preventing critical incidents. The present study investigates the various determinants to predict intention, and actual participation in CSPE using the theory of planned behavior (TPB). We also examined the effect of perceived risk on attitude as an extension of the TPB. Based on 441 valid responses collected from students studying in different institutions of higher learning in Malaysia, the partial least squares equation modeling (PLS-SEM) was used to analyze actual participation in CSPE behavior. The findings suggest that TPB is, indeed, a predictive model for explaining participation in CSPE. Based on the findings, the correlation between perceived risk and attitude is insignificant which leads to our subsequent argument on attitude as autonomous and not affected by one’s perceived risk. Nevertheless, the proposed direct relationship between perceived behavioral control (PBC) and intention behavior is not supported. These findings provide an important theoretical platform for new interventions to further promoting active participation in CSPE. Policy implications for improving CSPE behaviors are provided accordingly.

PurposeIt is commonly believed that personality traits determine a person's ability to work in a team and academic performance. However, studies have shown inconsistent results with some personality traits better than the other in predicting students' performance in different academic majors. The purpose of this study is to examine the interrelation between personality traits, teamwork competencies and academic performance among first-year first semester engineering students in an Australian university located in the Sarawak state of Malaysia.Design/methodology/approachThe Individual and Team Performance (ITP) metrics were administered among 189 students to gauge their personality traits as well as self-rated and peer-rated teamwork competencies. The correlations between personality traits and teamwork competencies as well as correlations of both the variables to academic performance were subsequently analyzed.FindingsThis study shows no significant difference between the self-rated and peer-rated teamwork competencies. Adventurous trait appears to negatively correlate with teamwork competencies. This study also reveals teamwork competencies as better predictors of academic performance than personality traits. Commitment and focus show relatively larger effect on academic performance. It can be concluded that commitment is the most significant factor to excel in first-year engineering in the university. Therefore, interventions that promote commitment is crucial to academic performance of the first-year first semester engineering students.Practical implicationsThis study promulgates the development of team competencies which are more crucial to academic excellence than personalities. It is useful for the design of team learning activities which lead to the development of teamwork competencies while improving academic performance. It shows that team activities which reinforce commitment especially and focus secondarily, will have significant positive effect on academic performance of the first-year engineering students generally.Originality/valueWhile most studies in this area examine the correlation between personality traits and academic performance, this study is among the very few that looks into the aspect of teamwork competencies. This study also finds its value in its regional significance as such correlational studies are not prevalent in Malaysia.

Microplastics have permeated most, if not all, ecosystems including the terrestrial ones. The presence of microplastics in soil poses concerns on plants and agriculture. Microplastics alter soil biophysical properties including bulk density, water holding capacity and soil microbial interactions with water stable aggregates. The effects of microplastics on soil and plants frequently depend on the types and sizes of microplastics. This mini review presents a concise illustration of the impacts of microplastics on plants and crops. From the review, microplastics alter soil biophysical and chemical characteristics either positively or negatively depending on their types, concentrations, sizes and shapes. It reveals the ability of microplastics to affect enzymatic activities of plants which could lead to genotoxicity and oxidative damage. It unveils endocytosis of microplastics by specific plant cells as well as the uptake of microplastics via root and their accumulation and transport in plants facilitated by transpiration. This review also shows microplastics reduce root growth and seed germination at least transiently while do not seem to alter chlorophyll content. Microplastics were found to not interfere with phytoremediation of metals by the common reeds. This review highlights the need of more studies to confirm the effects of microplastics on crops and plants as the existing studies in this area are limited.

Aims/ Objectives: This study examines the current municipal solid waste (MSW) management in Sarawak and recommends measures for its improvement.Study Design: This study adopts a qualitative approach involving targeted in-depth interviews guided by a questionnaire.Place and Duration of Study: The study was conducted among 18 local authorities (LAs) in the Sarawak state of Malaysia between January 2019 to June 2019.Methodology: This study is a qualitative survey conducted among 18 LAs in Sarawak, namely Kuching, Limbang, Marudi, Bau, Lundu, Betong, Dalat and Mukah, Kapit, Lubok Antu, Matu and Daru, Maradong and Julau, Serian, Sri Aman, Simunjan, Miri, Saratok, Subis and Lawas. Staff members in the public health section of the LAs were interviewed via phone calls and face-to-face mode. This represents a sampling size of approximately 64% which is deemed sufficient to providean adequate picture of the MSW management practice in Sarawak.Results: Smaller and remote LAs have lower MSW collection coverage than larger and more developed LAs. MSW is collected generally from 2 times a week to daily using compactors or trucks equipped with bin-lifters. Bins smaller than 240L are usually emptied manually. Waste collection is zoned in each LA and contracted to qualified contractors. Collected MSW is sent to dumpsites or landfills. Currently there are one level-4, two level-3 and three level-2 landfills in Sarawak. Organic waste particularly food residues form the bulk of MSW received at landfills. Waste segregation and recycling is not as widely practiced in Sarawak as the Peninsular Malaysia.Conclusion: The study shows that MSW management in Sarawak is equipped with the basic infrastructure but faces challenges in coverage due to the large area of the state. To improve MSW management, the recommendations comprise continuous road network development, decentralized administration of MSW management, composting, creation of ’recycling ecosystem’, education as well as research and development, backed by the state and federal governments’commitment and funding.

Supplemental material, sj-docx-2-tct-10.1177_15330338221142729 for scAnalyzeR: A Comprehensive Software Package With Graphical User Interface for Single-Cell RNA Sequencing Analysis and its Application on Liver Cancer by GS Chuwdhury, Irene Oi-Lin Ng and Daniel Wai-Hung Ho in Technology in Cancer Research & Treatment

Supplemental material, sj-docx-1-tct-10.1177_15330338221142729 for scAnalyzeR: A Comprehensive Software Package With Graphical User Interface for Single-Cell RNA Sequencing Analysis and its Application on Liver Cancer by GS Chuwdhury, Irene Oi-Lin Ng and Daniel Wai-Hung Ho in Technology in Cancer Research & Treatment

One concern with the rise of large language models lies with their potential for significant harm, particularly from pretraining on biased, obscene, copyrighted, and private information. Emerging ethical approaches have attempted to filter pretraining material, but such approaches have been ad hoc and failed to take context into account. We offer an approach to filtering grounded in law, which has directly addressed the tradeoffs in filtering material. First, we gather and make available the Pile of Law, a 256GB (and growing) dataset of open-source English-language legal and administrative data, covering court opinions, contracts, administrative rules, and legislative records. Pretraining on the Pile of Law may help with legal tasks that have the promise to improve access to justice. Second, we distill the legal norms that governments have developed to constrain the inclusion of toxic or private content into actionable lessons for researchers and discuss how our dataset reflects these norms. Third, we show how the Pile of Law offers researchers the opportunity to learn such filtering rules directly from the data, providing an exciting new research direction in model-based processing., Comment: Presented at NeurIPS Datasets & Benchmarks (2022)

In this work we investigate and demonstrate benefits of a Bayesian approach to imitation learning from multiple sensor inputs, as applied to the task of opening office doors with a mobile manipulator. Augmenting policies with additional sensor inputs, such as RGB + depth cameras, is a straightforward approach to improving robot perception capabilities, especially for tasks that may favor different sensors in different situations. As we scale multi-sensor robotic learning to unstructured real-world settings (e.g. offices, homes) and more complex robot behaviors, we also increase reliance on simulators for cost, efficiency, and safety. Consequently, the sim-to-real gap across multiple sensor modalities also increases, making simulated validation more difficult. We show that using the Variational Information Bottleneck (Alemi et al., 2016) to regularize convolutional neural networks improves generalization to held-out domains and reduces the sim-to-real gap in a sensor-agnostic manner. As a side effect, the learned embeddings also provide useful estimates of model uncertainty for each sensor. We demonstrate that our method is able to help close the sim-to-real gap and successfully fuse RGB and depth modalities based on understanding of the situational uncertainty of each sensor. In a real-world office environment, we achieve 96% task success, improving upon the baseline by +16%.

Supplemental material, sj-docx-1-tct-10.1177_15330338221142729 for scAnalyzeR: A Comprehensive Software Package With Graphical User Interface for Single-Cell RNA Sequencing Analysis and its Application on Liver Cancer by GS Chuwdhury, Irene Oi-Lin Ng and Daniel Wai-Hung Ho in Technology in Cancer Research & Treatment

Additional file 1: List of primers used in this study and list of 21 genes associated with glycolysis and gluconeogenesis with higher expression in chronic vs. acute infection in mice. Data was obtained from Pittman et al. dataset available on ToxoDB.

Can foundation models be guided to execute tasks involving legal reasoning? We believe that building a benchmark to answer this question will require sustained collaborative efforts between the computer science and legal communities. To that end, this short paper serves three purposes. First, we describe how IRAC-a framework legal scholars use to distinguish different types of legal reasoning-can guide the construction of a Foundation Model oriented benchmark. Second, we present a seed set of 44 tasks built according to this framework. We discuss initial findings, and highlight directions for new tasks. Finally-inspired by the Open Science movement-we make a call for the legal and computer science communities to join our efforts by contributing new tasks. This work is ongoing, and our progress can be tracked here: https://github.com/HazyResearch/legalbench., Comment: 13 pages, 7 tables

The reliability of food safety inspection disclosures has long been questioned. Providing meaningful disclosures to consumers based on public data is a core challenge for environmental health. We present new results, based on retrospective data and a novel randomized peer review trial, to improve the reliability of the restaurant food safety grading system that was implemented in Seattle and King County, Washington, in 2017. To address critiques of inspections as driven by inspector differences and merely “snapshots-in-time,” we used data from multiple inspections and adjusted scores within each inspector area to isolate relative performance. We studied the geographic distribution, predictability, and reliability of this adjusted grading system. Our findings are threefold. First, critical violations are much more reliably cited than non-critical violations, providing much more reliable inputs for grading. Second, and contrary to common belief, little evidence exists that repeat violations or the time trend of scores are associated with increased risk, hence providing no useful information for grading. Third, the adjusted system, based on quantile rankings of average critical points in up to four inspections, is much more robust to widespread inspector differences in stringency. Compared with conventional systems, this system reduces unwarranted geographic and intertemporal differences and improves predictive power. We provide easy-to-use, open-source statistical software for jurisdictions to implement this approach.

Additional file 1: Supplementary Material S1. Cost analysis of NeuroSAFE technique demonstrating additional cost total of the procedure in the United Kingdom NHS setting according to the results of the Feasibility Study. Supplementary Material S2. Model Intraoperative Frozen Section Reporting Proforma. Supplementary Material S3. Informed Consent Form.

Large language models can encode a wealth of semantic knowledge about the world. Such knowledge could be extremely useful to robots aiming to act upon high-level, temporally extended instructions expressed in natural language. However, a significant weakness of language models is that they lack real-world experience, which makes it difficult to leverage them for decision making within a given embodiment. For example, asking a language model to describe how to clean a spill might result in a reasonable narrative, but it may not be applicable to a particular agent, such as a robot, that needs to perform this task in a particular environment. We propose to provide real-world grounding by means of pretrained skills, which are used to constrain the model to propose natural language actions that are both feasible and contextually appropriate. The robot can act as the language model's "hands and eyes," while the language model supplies high-level semantic knowledge about the task. We show how low-level skills can be combined with large language models so that the language model provides high-level knowledge about the procedures for performing complex and temporally-extended instructions, while value functions associated with these skills provide the grounding necessary to connect this knowledge to a particular physical environment. We evaluate our method on a number of real-world robotic tasks, where we show the need for real-world grounding and that this approach is capable of completing long-horizon, abstract, natural language instructions on a mobile manipulator. The project's website and the video can be found at https://say-can.github.io/., Comment: See website at https://say-can.github.io/ V1. Initial Upload. V2. Added PaLM results. Added study about new capabilities (drawer manipulation, chain of thought prompting, multilingual instructions). Added an ablation study of language model size. Added an open-source version of \algname on a simulated tabletop environment. Improved readability

Recent work in visual end-to-end learning for robotics has shown the promise of imitation learning across a variety of tasks. Such approaches are expensive both because they require large amounts of real world training demonstrations and because identifying the best model to deploy in the real world requires time-consuming real-world evaluations. These challenges can be mitigated by simulation: by supplementing real world data with simulated demonstrations and using simulated evaluations to identify high performing policies. However, this introduces the well-known "reality gap" problem, where simulator inaccuracies decorrelate performance in simulation from that of reality. In this paper, we build on top of prior work in GAN-based domain adaptation and introduce the notion of a Task Consistency Loss (TCL), a self-supervised loss that encourages sim and real alignment both at the feature and action-prediction levels. We demonstrate the effectiveness of our approach by teaching a mobile manipulator to autonomously approach a door, turn the handle to open the door, and enter the room. The policy performs control from RGB and depth images and generalizes to doors not encountered in training data. We achieve 72% success across sixteen seen and unseen scenes using only ~16.2 hours of teleoperated demonstrations in sim and real. To the best of our knowledge, this is the first work to tackle latched door opening from a purely end-to-end learning approach, where the task of navigation and manipulation are jointly modeled by a single neural network.