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The joint optimization of facility location and service charge arises in many industrial and business contexts. This paper investigates a facility location and mill pricing problem (FLMPr), where a company aims to maximize its profit by locating service facilities and setting appropriate service charges to customers. For each facility, the number of pricing levels are finite, and the company will select exactly one level for each facility if it is open. We visualize the problem from a fully decentralized perspective, i.e., each customer acts as an independent decision-maker. Under mill pricing, customers visiting the same facility encounter the same service charge. The problem is formulated as a bilevel program, in which the company makes location and pricing decisions at the upper level, and customers decide whether to seek the service from a facility at the lower level. To solve FLMPr, we leverage three types of closest assignment constraints to reformulate the problem as mixed-integer linear programs (MILPs), which can be directly solved by modern solvers. However, this approach suffers from a time-consuming solver compiling process and cannot handle large-scale instances effectively. This observation motivates us to design a branch-and-cut algorithm by exploring the bilevel structure and deriving a feasibility cut to efficiently eliminate bilevel infeasible solutions. Our extensive experiments reveal that the proposed algorithm can solve large-scale FLMPr satisfactorily and outperforms the MILP approach by a large margin. Finally, we conduct sensitivity analysis and draw interesting observations.

Herein, five N, S-co-doped carbocatalysts were prepared from different carbonaceous precursors, namely sawdust (SD), biochar (BC), carbon-nanotubes (CNTs), graphite (GP), and graphene oxide (GO) and compared. Generally, as the graphitization degree increased, the extent of N and S doping decreased, graphitic N configuration is preferred, and S configuration is unaltered. As peroxymonosulfate (PMS) activator for ciprofloxacin (CIP) removal, the catalytic performance was in order: NS-CNTs (0.037 min-1) > NS-BC (0.032 min-1) > NS-rGO (0.024 min-1) > NS-SD (0.010 min-1) > NS-GP (0.006 min-1), with the carbonaceous properties, rather than the heteroatoms content and textural properties, being the major factor affecting the catalytic performance. NS-CNTs was found to have the supreme catalytic activity due to its remarkable conductivity (3.38 S m-1) and defective sites (ID/IG = 1.28) with high anti-interference effect against organic and inorganic matter and varying water matrixes. The PMS activation pathway was dominated by singlet oxygen (1O2) generation and electron transfer regime between CIP and PMS activated complexes. The CIP degradation intermediates were identified, and a degradation pathway is proposed. Overall, this study provides a better understanding of the importance of selecting a suitable carbonaceous platform for heteroatoms doping to produce superior PMS activator for antibiotics decontamination. This work was supported by the Universiti Sains Malaysia, Research University Team (RUTeam) Grant Scheme (Grant Number: 1001/PJKIMIA/8580061).

Mobilisation of alternate load path (ALP) mechanisms in 3D beam-slab systems is a key factor in designing structures against progressive collapse. Existing analytical methods on 3D beam-slab systems focusing on limited load-resisting mechanisms often lead to uneconomical and unrealistic design, while finite element models with 3D solid elements are too complicated and time consuming for 3D beam-slab systems. To address these shortcomings, this paper aims to provide structural engineers two simple but effective and reliable approaches to predict structural behaviour of 3D beam-slab systems. They include (i) an analytical method and (ii) a simplified finite element model based on strip method and grillage analysis. Both approaches are validated against published test results for 3D beam-slab systems. Compared to existing approaches on 3D beam-slab systems, these two proposed methods incorporate all the load resisting mechanisms in both the beams and slabs, giving more accurate and realistic predictions of load-displacement curves for the sub-structures considered. In addition, parametric studies on the analytical approach are presented to shed light on the role of boundary conditions and the contribution of slabs to load resistance capacity of 3D beam-slab structures against progressive collapse. The authors gratefully acknowledge the research funding pro-vided by Changi Airport Group, Singapore with award No. NTU Ref: 2018-1451

Experimental and numerical studies have been conducted to investigate the structural behavior of restrained circular hollow section (CHS) T-joints subject to fire. Four CHS T-joints having two different brace-to-chord diameter ratios, 0.47 and 0.69, were tested subject to two kinds of loading: axial brace compression and in-plane bending in fire condition following the iSO-834 fire curve. The two chord ends were connected to reaction A-frames incorporating the thermal restraint effect. The joint behavior was discussed based on maximum deformation, fire resistance and critical temperature. When the joint was under in-plane bending, local plasticization was dominant; the observed failure mode combined global bending and local punching shear when the joint was under brace axial compression. Finite element (FE) models were constructed by incorporating thermal restraints and temperature distributions in the joint regions from the tests. The verified FE models were then adopted to predict the critical temperature of other CHS T-joints where brace-to-chord diameter ratio, load ratio and thermal restraints were taken as variable parameters. Unlike T-joint at ambient temperature, a larger brace-to-chord ratio resulted in a greater critical temperature. Moreover, greater load ratio and thermal restraint caused decrease in fire resistance and critical temperature of CHS T-joint subject to both axial compression and in plane bending. Ministry of Education (MOE) This research was funded by the ARC 2/07 project titled “Failure modes and the ultimate strength of tubular joints under elevated temperatures” from the Ministry of Education, Singapore.

As reinforced concrete (RC) walls with different principal bending axes are connected by the floor diaphragms, unsymmetrical bending is frequently expected for structural members in resisting the lateral loads. In these cases, a portion of lateral reaction forces is anticipated to be perpendicular to the lateral deflection of the members which causes shear deformation and additional curvature perpendicular to the loading plane. This paper investigates these out-of-plane deformations and curvatures and their influences. Magnitude of these shear deformations and curvatures are investigated with experimental data and a theoretical solution. The results confirm that the out-of-plane curvature is related with disproportional shear and flexural stiffness of the wall in different principal bending directions and can account for a significant portion of the in-plane curvature. The curvature could introduce significantly higher strain and render the member more vulnerable to out-of-plane buckling. Methods for modelling the curvature in structural system are proposed based on nonlinear fibre element model. This work was financially supported by Natural Science Foundation of China (52108275), the National Key R&D Program of China (Grant No.2019YFC1509304) and Natural Science Foundation of Jiangsu Province (BK20190365).

Accurate prediction of compressive strength of rocks relies on the rate-dependent behaviors of rocks, and correlation among the geometrical, physical, and mechanical properties of rocks. However, these properties may not be easy to control in laboratory experiments, particularly in dynamic compression experiments. By training three machine learning models based on the support vector machine (SVM), back-propagation neural network (BPNN), and random forest (RF) algorithms, we isolated different input parameters, such as static compressive strength, P-wave velocity, specimen dimension, grain size, bulk density, and strain rate, to identify their importance in the strength prediction. Our results demonstrated that the RF algorithm shows a better performance than the other two algorithms. The strain rate is a key input parameter influencing the performance of these models, while the others (e.g. static compressive strength and P-wave velocity) are less important as their roles can be compensated by alternative parameters. The results also revealed that the effect of specimen dimension on the rock strength can be overshadowed at high strain rates, while the effect on the dynamic increase factor (i.e. the ratio of dynamic to static compressive strength) becomes significant. The dynamic increase factors for different specimen dimensions bifurcate when the strain rate reaches a relatively high value, a clue to improve our understanding of the transitional behaviors of rocks from low to high strain rates. National Research Foundation (NRF) Published version This research is supported by National Research Foundation, Singapore under its Virtual Singapore R&D Programme (Award No. NRF2019VSG-GMS-001).

A variety of control mechanisms have been recommended to concentrate on the issue of bus bunching. However, the majority of existing measures focus on controlling the bus operation directly from the operator's perspective. This study, nevertheless, presents a novel control technique by providing passengers with real-time wait time information and degrees of in-vehicle congestion. Specifically, passengers are expected to use the given information to calculate the overall travel cost and, therefore, make decisions on whether boarding on the arriving bus or waiting for the next buses. In this way, bus service operators would reduce bus bunching by adjusting passengers' boarding choice behavior rather than controlling the bus vehicles directly. We propose a bus traffic propagation model to simulate the bus movements, through which several system performance metrics, such as the shortest vehicle spacing distribution and the average ridership per bus vehicle at each stop, can be evaluated for different bus bunching control measures. The numerical results show that providing in-vehicle congestion information is as effective as the schedule-based and headway-based control methods in achieving mitigation of bus bunching. Passengers on long trips are more inclined to wait for a few more shifts for a bus that is not very crowded. This study proposes a novel control strategy by offering passengers real-time information to serve as a supplement, never a substitute, to the existing control measures in mitigating bus bunching problems. Ministry of Education (MOE) The study was funded by the National Natural Science Foundation of China (No. 72071013, 71890971/71890970) and the Singapore Ministry of Education (MOE) AcRF Tier 1 Grant MOE2021-T1-002-062.

This paper examines the morning commute problem when both household commuters and individual commuters are considered in a Y-shaped network with two upstream links and a single downstream link. The household parents daily pass through an upstream bottleneck with a limited capacity before a school and drop off their children. Then, they traverse the downstream bottleneck common to both household and individual commuters and arrive at the workplace. We explore the effects of staggering policy, that is, staggering work and school start times, on the distribution of traffic congestion and social welfare. We analytically solve all the equilibrium cases and reveal all the traffic congestion patterns. The results reveal that the staggering policy may be harmful in certain cases. When the demand of individuals is relatively low, the staggering policy may not improve social welfare. When the demand of individuals is high, social welfare can be significantly improved if the schedule gap between the work start time and school start time is optimized. The effects of the staggering policy on system performance are examined. We derive a Pareto frontier, which provides a good candidate set for policymakers when the two system performance measures, that is, the total system cost and the total congestion cost, are considered. Our results show that the optimal staggering policy on system performance depends on the demand distribution of the two groups. When the demand of individuals is high, there exists a unique optimal staggering policy that optimizes system performance. However, when the demand of individuals is low, the optimal staggering policy should be selected from the Pareto frontier. Furthermore, we re-examine the capacity expansion paradox under the staggering policy. Our study shows the capacity expansion at the downstream bottleneck can always reduce the total system cost. However, the paradoxical phenomenon may arise when the capacity of the upstream bottleneck is expanded, but it can be eliminated if the schedule gap is properly designed. Ministry of Education (MOE) Nanyang Technological University This research was funded by National University of Singapore, Singapore Ministry of Education Academic Research FundTier 2 [Grant MOE2017-T2-2-128]; Dalian University of Technology, National Natural Science Foun-dation of China [Grant 71533001]; Nanyang Technological University, Singapore Ministry of Educa-tion Academic Research Fund [Grant MOE2017-T2-2-093]; Dalian University of Technology, ChinaScholarship Council.

This study assessed the potential impact of climate change on spatiotemporal distribution of blue and green water resources in the Beijiang River basin, southern China, using the SWAT hydrological model and CORDEX-EAS regional climate models (RCMs). The outputs of three RCMs (namely RMOH, RMPI and RNCC) under two emission scenarios (RCP 2.6 and RCP 8.5) were bias-corrected by using the quantile delta mapping method for the control (1975–2004), near future (2021–2050) and far future (2061–2090) periods. Driven by the corrected climate variables, future blue and green water were assessed by using the SWAT model calibrated with streamflow data. The results indicated that the green water flow in the northwest basin predicted by RMOH under RCP 2.6 would increase up to about 2.7% in 2061–2090; RNCC suggests that most of the basin would experience the most significant reduction in green water storage (over 30%) under RCP 8.5 in the far future. For blue water, the ensemble mean of three RCMs indicates a slight decreasing trend in the northern part of the basin and an increasing one in the southern part under RCP 8.5 in the far future. Our findings could help watershed managers evaluate future hydrological risks and design appropriate adaptation strategies. Ministry of Education (MOE) Published version This work was supported by the National Natural Science Foundation of China (52009022) and AcRF Tier 1 project (2019- T1-001-160) from the Ministry of Education (MOE), Singapore.

Seafarer health is critical for sustainable shipping management. During the COVID-19 pandemic, the unfavourable working environment has posed physical and psychological problems to seafarers. Consequently, seafarer health has been receiving increasing attention from academics, the shipping industry and international organizations. The objective of this review is to identify key characteristics of the articles on seafarer health published in the past two decades, and summarize key investigated health problems, antecedents and health promotion interventions. The review suggests that cardiovascular diseases, transmittable diseases, fatigue and stress have been the most widely studied health issues. Moreover, seafarer health conditions can be influenced by the (1) natural environment; (2) physical working environment; (3) social environment; (4) personal characteristics; (5) management style; (6) industry-specific characteristics; (7) health crisis. Furthermore, medical care provided by telehealth, effective regulatory and education interventions can improve seafarer health. This review contributes to the existing literature by consolidating the scattered research on seafarer health. Combining the literature review results and recommendations from international organizations on public health and maritime transport, this study proposes several future research directions.

This work investigates the applicability of clinoptilolite, a natural zeolite, as a low-cost adsorbent for removing chromium from aqueous solutions using fixed bed studies. To improve its removal performance for the inorganic pollutant, the adsorbent is pretreated with NaCl to prepare it in the homoionic form of Na+ before undertaking ion exchange with Cr3+ in aqueous solution. This work also evaluates if treated effluents could meet the required effluent discharge standard set by legislation for the target pollutant. To sustain its cost-effectiveness for wastewater treatment, the spent adsorbent is regenerated with NaOH. It was found that the clinoptilolite treated with NaCl has a two-times higher Cr adsorption capacity (4.5 mg/g) than the as-received clinoptilolite (2.2 mg/g). Pretreatment of the clinoptilolite with NaCl enabled it to treat more bed volume (BV) (64 BV) at a breakthrough point of 0.5 mg/L of Cr concentration and achieve a longer breakthrough time (1500 min) for the first run, as compared to as-received clinoptilolite (32 BV; 250 min). This suggests that pretreatment of clinoptilolite with NaCl rendered it in the homoionic form of Na+. Although pretreated clinoptilolite could treat the Cr wastewater at an initial concentration of 10 mg/L, its treated effluents were still unable to meet the required Cr limit of less than 0.05 mg/L set by the US Environmental Protection Agency (EPA). Published version This work received Research Grants No. Q.J130000.21A6.00P14 and No. Q.J130000.3809. 22H07 from the Universiti Teknologi Malaysia (UTM).

Control of rock failure under stress wave loading is challenging but important to mitigate the negative impacts of underground excavation on the environment (e.g., rock overbreak and ground vibration). This study reports that dynamically amplified expansion pressure from expansive mortar is an effective and efficient solution to promote the dynamic failure of brittle rock. Our experimental and numerical results reveal that the expansion pressure amplified by stress wave loading facilitates the dynamic failure surrounding the expansive mortar, accompanied by the generation of tangential and radial cracks and the attenuation of stress wave. Our data also show that the dynamically amplified expansion pressure is larger than the radial inertia stress and dominates crack generation in the unconfined rock, but the pressurization capacity of expansive mortar should be improved for the rock fracturing application in confined rock. The application of expansive mortar fundamentally modifies the brittleness of surrounding rock under stress wave loading, resulting in changes in failure mode. However, the application of expansive mortar to control rock dynamic failure should be further investigated in field studies. Nanyang Technological University National Environmental Agency (NEA) National Research Foundation (NRF) W Wu acknowledges the support of Start-up Grant from Nanyang Technological University, Singapore. This research is also supported by the National Research Foundation, Singapore, and National Environment Agency, Singapore under its Closing the Waste Loop Funding Initiative (Award No. USS-IF-2020- 1).

Knowledge of landslide volume is important to understand the extent of damages and evaluating methods of remediation. However, the volume of landslide is difficult to quantify due to its scale and challenges encountered in conventional surveying. Various studies using satellite and aerial images have been conducted to empirically relate volume (i.e., displaced mass) of a landslide to its area through a power-law. However, there are many existing empirical relationships, and the volume estimate may differ substantially. In this study, firstly it is demonstrated that the empirical area-volume power-law relationships could be rationalized by a geometrical and mathematical basis. The empirical relationships in the literature are shown to be bounded by the volumes of “idealized” landslides where the slip surface is either spherical or elliptical. Secondly, a geometry-modelling method is proposed to estimate the volume of a landslide from satellite and aerial images without the need for digital elevation models. Using this method, landslide volume can be expediently estimated, and it yields better accuracy than empirical area-volume power-law relationships.

The revitalisation of the global economy after the Covid-19 era presents environmental geotechnics with the opportunity to reinforce the need for a change in paradigm towards a green, circular economy and to promote aggressively the use and development of sustainable technologies and management practices. This paper aims to assist in this effort by concentrating on several thematic areas where sustainability solutions and future improvements are sought. These include the re-entry of construction and demolition of wastes, excavated materials, industrial wastes and marine sediments into the production cycle and the reuse of existing foundations. Despite the recent trend in advanced countries towards recycling and waste-to-energy thermal treatment, landfills still constitute the most common municipal solid waste management practice, especially in low-and-middle-income countries, and technological solutions to improve their environmental footprint are hereby presented. At the same time, remediation solutions are required to address the multitude of contaminated sites worldwide. Advanced developments that incorporate environmental, economic and social dimensions are expounded by the authors, together with sustainable ground improvement solutions for infrastructure projects conducted in soft and weak soils. The topic of thermo-active geostructures concludes this paper, where, apart from their infrastructure utility, these structures have the potential to contribute to the renewable energy source. Published version The second author would like to acknowledge the support of the Office of the Associate Provost for Research and Academic Development at Abu Dhabi University, UAE through grant19300540.

Among various time series (TS) forecasting methods, ensemble forecast is extensively acknowledged as a promising ensemble approach achieving great success in research and industry. Due to the high diversification of individual model assumptions, heterogeneous information fusion contributes to generating effective and robust forecasts for Economics, Meteorology, and Transportation. This paper proposes a Bayesian optimization-based dynamic ensemble (BODE) that overcomes the single model-based methods limitation and provides a dynamic ensemble forecast combination for TS with time-varying underlying patterns. The proposed BODE method combines ten disparate model candidates, including statistical methods, machine learning (ML)-based models, and the latest deep neural networks (DNN). We take into consideration their prediction performance for the recent past to adjust their weights for combination and apply the model-based Bayesian optimization algorithm (BOA) for the combination hyperparameter (HP) tuning to endow our method with higher adaptability and better generalization performance. Besides, the frequency impact of TS data on the ensemble forecast methods is under-researched in the current literature. Therefore, four groups of distinct seasonal TS datasets are investigated in this paper. The empirical result demonstrates that our method performs robustly better performance with the main reasons analyzed in a detailed ablation study.

In this article, current research findings of local scour at offshore windfarm monopile foundations are presented. The scour mechanisms and scour depth prediction formulas under different hydrodynamic conditions are summarized, including the current-only condition, wave-only condition, combined wave-current condition, and complex dynamic condition. Furthermore, this article analyzes the influencing factors on the basis of classical equations for predicting the equilibrium scour depth under specific conditions. The weakness of existing researches and future prospects are also discussed. It is suggested that future research shall focus on physical experiments under unsteady tidal currents or other complex loadings. The computational fluid dynamics-discrete element method and artificial intelligence technique are suggested being adopted to study the scour at offshore windfarm foundations. Published version This work was supported by the Major International Joint Research Project POW3M of the National Natural Science Foundation of China (Grant No. 51920105013) and the General Project of the National Natural Science Foundation of China (Grant No. 52071127).

A strut-and-tie model (STM) for unsymmetrically-loaded deep beams is proposed in this paper through simplifying the unsymmetrical problem into symmetrical and anti-symmetrical problems. This analytical solution starts with derivations of principal compressive stress fields based on the theory of elasticity. Furthermore, a minimum-strain-energy criterion is adopted to define the optimal STM geometry from the stress field, including the dimensions of struts and nodal zones, and strut angles. The proposed STM is validated against 140 test results, including 14 unsymmetrically-loaded deep beams and 126 symmetric deep and short beams, and finite element models (FEMs) for the 14 unsymmetrical deep beams. The FEM is also used to simulate the load-displacement relationships of unsymmetrical deep beams that could not be modelled by STM. In addition, a worked example is presented to demonstrate in detail the procedure of analysing an unsymmetrically-loaded deep beam using the proposed solution. In summary, the STM predictions are in good agreement with experimental results and FEM predictions. Therefore, the proposed STM is capable of giving accurate and consistent predictions for both symmetrical and unsymmetrical deep and short beams. Ministry of National Development (MND) National Research Foundation (NRF) The authors wish to acknowledge the first authors scholarship from the Singapore Ministry of National Development and National Research Foundation under L2 NIC Award No. L2NICCFP1-2013-4.

Since the phase-out of traditional halogenated flame retardants (HFRs), interests of research are gradually being shifted to organophosphate flame retardants (OPFRs), and this can be reflected by the increasing number of publications on OPFRs year by year. Here, an extensive survey is conducted in an attempt to generate a list of OPFRs that are being produced in factories, and to investigate the annual production volume (APV). This survey suggests that at least n = 56 OPFR monomers and n = 62 OPFR mixtures are being currently produced in 367 factories around the world, and 201 out of them are in Mainland China. APV of OPFRs was estimated as 598,422 metric tons, and this number could be underestimated due to the limitation of available information. We also notice that current researches are confined to a limited number of OPFRs, especially for OP esters (OPEs), and other OPFRs with different structures from OPEs has been rarely studied. Based on all the collected datasets, we provide five recommendations for how to proceed with future research to more comprehensively understand the currently-produced OPFRs in the environment. This research was supported by the National Natural Science Foundation of China (Grant 21976088), and the Fundamental Research Funds for the Central Universities (Grant No. 30919011101).

Working from home becomes the norm; this trend has put added pressure on urban logistics, as large volumes of goods and services are required for domestic use. Meanwhile, public transport operators face a big challenge and trade-off due to higher labour and frequent cleaning costs, with lower passenger revenue over a longer period. Considering the collaborative urban public transport services achieve a seamless movement for both passengers and goods, and could reduce the adverse effects of the existing urban public transport systems. Therefore, a mixed-integer linear programming model introducing the concept of capacity matching is proposed to assist this collaborative urban freight service network in minimising total freight transport time at station hubs and not affecting passenger transportation in this paper. Moreover, an efficient improved optimisation algorithm based on the Artificial Bee Colony Algorithm (ABC) is designed, and the numerical examples and real cases are illustrated to demonstrate the feasibility and effectiveness of the proposed model and algorithm. The performance evaluations suggest that the coordinated operating strategy of the collaborative freight transportation system supports increasing mobility demands for freight, resulting in declining congestion levels and reducing transport emissions, while no influence in passenger transport, notably in urban areas. This work was supported by the Fundamental Research Funds for the Central Universities [grant number 2021JBM014], the National Natural Science Foundation of China [grant numbers 72101013, 71890972/71890970, 71621001], the Beijing Intelligent Logistics System Collaborative Innovation Centre [grant number BILSCIC-2019KF-11], and the 111 Project (No. B20071).

A push-pull demodulation method is used to create an ultrasensitive fiber optic inclinometer based on the dynamic Vernier effect. To demonstrate this new method, two Fabry Perot interferometers (FPIs) in parallel are employed to constitute the optical Vernier effect. Unlike the traditional Vernier effect, in which one interferometer serves as a reference and the other as a sensor, both interferometers in this design participate in sensing measurement simultaneously. The two external FPIs are constructed on opposite sides of a pendulum, the so-called push-pull configuration, ensuring the extension of one FPI and compression of the other simultaneously. Although the carrier signal is maintained constant, the envelope signal manifests a dynamic enhanced Vernier effect for inclination sensing, while reducing the effect from external disturbance. As a result, an ultrahigh inclination sensitivity of 35.96 nm/° is obtained with a resolution of 2.78× 10-5°, i.e., ∼ 0.5μ rad. In addition, the proposed scheme provides a useful alternative for many sensing applications, given its capability of improving measurement sensitivity and reducing external interference. Agency for Science, Technology and Research (A*STAR) This work was supported in part by the Science and Engineering Research Council (SERC), Agency for Science, Technology and Research (A* STAR), Singapore, under Grant 1922200001 and in part by the National Natural Science Foundation of China (NSFC) under Grant 12104350.

The traffic safety of mountain highway has always been one of the taking point. This study aims to collect road design data in large-scale research and analyzes the accident risk of highway geometric alignment. Accordingly, a method based on satellite maps and clustering algorithms is proposed to calculate the geometric alignment of the highway plane and its longitudinal section. The reliability of the method was verified on Nanfu highway in Chongqing, China. The planar and longitudinal sectional geometries of the four highways in Chongqing were obtained by the above method, and the corresponding 36,439 traffic accidents which occurred from 2010 to 2016 were used as the research objects. The accident risk of the highway geometry was analyzed based on the SHAP and MLP theories. The results show that the fitting and prediction abilities of the MLP model are better than those of the negative binomial model, and its correlation coefficient is improved by 33.2%. In addition, compared with the negative binomial model, the MLP model can estimate more accurately and flexibly the complex nonlinear relationship between the independent and the dependent variables. Published version This work was jointly funded by the science and technology innovation program of the department of transportation, Yunnan province, China (No. 2019303 and 2021-90-2), the general program of natural science foundation, Yunnan province, China (No 2019FB072), the general program of key science and technology in transportation, the ministry of transport, China (No. 2018-MS4-102), and the National Engineering Laboratory Open Research Fund Project for Land Traffic Meteorological Disaster Prevention and Control Technology of China (NEL-2020-01).

Conventional organic solvent recovery is energy intensive and challenged by large footprint and complex operation and maintenance. To enable a more circular and sustainable pharmaceutical production, we amalgamate adsorption and membrane processes to address current Achilles heels in organic solvent recovery. In this work, we have successfully designed a polyacrylonitrile (PAN) electrospun membrane as scaffold to incorporate nanomaterial adsorbents in a layer-by-layer hierarchical structure. The porous nanofibrous morphology and layer-by-layer design, which deconstructs the adsorbent layers, help reduce the transport resistance of the isopropyl alcohol (IPA), leading to higher processing capacity at lower applied pressure, while maintaining the removal rates. To bring about versatility for different contaminants, we incorporated two different nanomaterials, namely positively charged metal-organic frameworks (MOFs), particularly MIL-101(Cr), and negatively charged functionalized multi-walled carbon nanotubes (MWCNTs) as powdered adsorbents, for the extraction of anionic and cationic dyes, respectively. Our results show that the MOF-based membrane scaffold can achieve 99% and 95% rose Bengal and methyl orange removal rates in IPA, respectively, while operating at a low operating pressure of 0.04 bar and delivering a processing capacity of 60 L m−2 h−1 of IPA, with good regeneration and recyclability of up to three cycles of removal process. On the other hand, the MWCNT-based membrane scaffold displays up to 90% methylene blue dye in IPA at 0.07 bar pressure and delivering a 40 L m−2 h−1 of IPA processing capacity in a single-cycle removal process. The promising recovery performance and facile tailoring of adsorbents to target contaminants of different charges render our adsorptive membrane scaffold process less energy intensive and highly versatile to meet various needs for solvent recovery in the pharmaceutical industry. National Research Foundation (NRF) Public Utilities Board (PUB) Submitted/Accepted version This research is supported by the National Research Foundation, Singapore, and implemented by the Public Utilities Board (PUB), Singapore’s National Water Agency, under its Competitive Funding for Water Research Funding Initiative (Grant Award CWR-2101-0010).

Liquid crystal monomers (LCMs) are a large family of artificial ingredients that have been widely used in global liquid crystal display (LCD) industries. As a major constituent in LCDs as well as the end products of e-waste dismantling, LCMs are of growing research interest with regard to their environmental occurrences and biochemical consequences. Many studies have analyzed LCMs in multiple environmental matrices, yet limited research has investigated the toxic effects upon exposure to them. In this study, we combined in silico simulation and in vitro assay validation along with omics integration analysis to achieve a comprehensive toxicity elucidation as well as a systematic mechanism interpretation of LCMs for the first time. Briefly, the high-throughput virtual screen and reporter gene assay revealed that peroxisome proliferator-activated receptor gamma (PPARγ) was significantly antagonized by certain LCMs. Besides, LCMs induced global metabolome and transcriptome dysregulation in HK2 cells. Notably, fatty acid β-oxidation was conspicuously dysregulated, which might be mediated through multiple pathways (IL-17, TNF, and NF-kB), whereas the activation of AMPK and ligand-dependent PPARγ antagonism may play particularly important parts. This study illustrated LCMs as a potential PPARγ antagonist and explored their toxicological mode of action on the trans-omics level, which provided an insightful overview in future chemical risk assessment. Ministry of Education (MOE) This work is supported by the Singapore Ministry of Education Academic Research Fund Tier 1 (04MNP000567C120), MOE-T2EP30220-0008, MOE-MOET32020-0004, a Startup Grant of Fudan University (JIH 1829010Y), and the National Natural Science Foundation of China (21976088).

In our previous study, quorum quenching (QQ) bacteria can effectively enhance methane production in an anaerobic membrane bioreactor (AnMBR) while mitigating membrane biofouling. However, the mechanism of such enhancement is unclear. In this study, we analyzed the potential effects from separated hydrolysis, acidogenesis, acetogenesis and methanogenesis steps. The cumulative methane production improved by 26.13%, 22.54%, 48.70% and 44.93% at QQ bacteria dosage of 0.5, 1, 5 and 10 mg strain/g beads, respectively. It was found that the presence of QQ bacteria enhanced acidogenesis step resulting in higher volatile fatty acids (VFA) production, while it had no obvious influence on hydrolysis, acetogenesis and methanogenesis steps. The substrate (glucose) conversion efficiency in acidogenesis step was also accelerated (1.45 folds vs control within first eight hours). The abundance of hydrolytic fermentation gram-positive bacteria and several acidogenic bacteria, such as Hungateiclostridiaceae, was promoted in QQ amended culture, which enhanced VFA production and accumulation. Although the abundance of acetoclastic methanogen Methanosaeta reduced by 54.2% on the 1st day of QQ beads addition, the overall performance of methane production was not affected. This study revealed that QQ had a greater impact on the acidogenesis step in the anaerobic digestion process, though the microbial community in acetogenesis and methanogenesis steps was altered. This work can provide a theoretical basis for using QQ technology to slow down the rate of membrane biofouling in anaerobic membrane bioreactors while increasing methane production and maximizing economic benefits. Nanyang Technological University The authors acknowledge the financial support of Advanced Environmental Biotechnology centre, Nanyang Environment and Water Research Institute (NEWRI), Nanyang Technological University, Singapore.

Using ammonia as an alternative marine fuel has been gaining interest in reducing greenhouse gas emissions in the maritime sector. This paper describes the development of a discrete event simulation model for bunker supply chain, emphasising how ammonia bunkering affects the operational and economic performance of the system. The results show that the model is a useful tool for ammonia bunker supply chain management, including the selection of the number and capacity of ammonia bunker supply vessels, bunkering flow rate and ammonia demand. Flow rate has a significant impact on bunkering service time, with an effect of up to 51.3% when it is changed by ±50%. The greater the demand for ammonia, the more significant the impact of ammonia bunkering flow rate on bunkering service time. Moreover, the number of ammonia bunker supply vessels is the most sensitive parameter for annual operational cost, with an effect of up to 15.2%.

Rainwater infiltration is primarily governed by the soil-water characteristic curve (SWCC) and hydraulic conductivity function (HCF) of soil. Both the SWCC and the HCF are hysteretic during the drying and wetting processes. In a numerical simulation, different seepage results can be obtained by incorporating different hydraulic conductivity functions of soil. In practice, the wetting HCF is commonly estimated from the wetting SWCC using the statistical method, which is named HCFswcc,w in this note. However, there is no study that has verified the results from seepage analyses using HCFswcc,w. Therefore, the objective of this study is to investigate the influence of wetting SWCC and wetting HCF on 1-D water infiltration. The results from the numerical simulations were verified with the instrumentation reading from a soil column. It was observed that the results from the model using wetting HCFPSDF, which defines the wetting HCF estimated using the concept of pore-size distribution function, gave better agreement with the instrumented data. Therefore, both wetting SWCC and wetting HCFPSDF are advised to be used as input information for the numerical simulation of rainwater infiltration. Published version

Estimations of cutting-tool wear and rock-breaking efficiency during underground excavation and geo-energy extraction rely mostly on Cerchar abrasivity index (CAI) tests. However, the measurement of rock abrasivity may not be accurate for highly cracked rock after extreme treatment conditions (e.g., high temperature and rapid cooling). Here we conduct CAI tests on granite specimens after thermal treatment with different combinations of heating temperature and cooling rate. The results show that the CAI value is mainly increased during the first few millimeters scratching distance and strongly influenced by the stylus indentation during the subsequent scratching distance. We examine the stylus and rock interaction based on P-wave velocity and acoustic emission and suggest evaluating the wear flat by reconstructing intact stylus profile. A scratching distance of 10 mm is appliable for highly cracked rock with an acceptable measurement error. We finally discuss the evolution of rock brittleness that fundamentally controls the stylus indentation.

Past studies by the authors have demonstrated the feasibility of utilizing municipal solid waste (MSW) incineration bottom ash (IBA) as an aerating agent to produce autoclaved aerated concrete (AAC). However, the gas generation potential of as-received IBA (General IBA) is significantly poorer than conventional aerating agents such as pure aluminum powder. The classification of IBA showed that coarse non-ferrous IBA fraction with particle size greater than 1.18 mm (CNF-IBA) contains a higher concentration of metallic aluminum. This study proposes specifically utilizing CNF- IBA fraction as an aerating agent to produce AAC. Two other AACs with pure Al powder and General IBA as aerating agents were investigated for systematic comparison. The aeration kinetics, fresh, and hardened properties were experimentally investigated. A novel approach is presented to study the influence of coordination between aeration extent and yield stress development on volume expansion capacity. The developed AAC with CNF-IBA exhibited the highest specific compressive strength. The leaching analysis showed that the usage of IBA as an aerating agent in AAC production is safe during the service life of AAC, and its demolished samples at the end of service time can be landfilled as inert material. National Environmental Agency (NEA) National Research Foundation (NRF) The authors would like to acknowledge financial support from the Environment Technology Research Program (ETRP), National Environment Agency (NEA), Singapore (ETRP 1301 104), and from the SinBerBEST program, National Research Foundation (NRF), Singapore.

Lack of information regarding the shear behavior of high-strength longitudinally reinforced concrete beams without shear reinforcement (HRCBW) impedes the design engineers from using the full yield strength of material. Current shear design provisions for HRCBW were reexamined based on probability density function, confidence interval and confidence level. Based on the principal shear mechanism of beam and arch actions, a probabilistic shear capacity model for HRCBW was proposed based on the Bayesian theory and the Markov Chain Monte Carlo (MCMC) method taking into account both aleatory and epistemic uncertainties. Meanwhile, statistical characteristics (e.g. mean value, standard deviation, distribution type) of shear capacity for HRCBW were determined by Kolmogorov-Smirnov (K-S) test and statistical analysis. Moreover, the accuracy and applicability of three major shear design provisions (i.e. ACI 318-19, EC 2, fib MC2010) for HRCBW were reexamined based on probability density function, confidence interval and confidence level. Fnancial support received from the National Natural Science Foundation of China (grants 52278162 and 62266005), the Guangxi Science Fund for Distinguished Young Scholars (grant 2019GXNSFFA245004) and the Natural Science Foundation of Guangxi Province (grant 2018GXNSFAA281344) is gratefully acknowledged.

In this work, a positively charged hollow fiber nanofiltration (NF) membrane based on twice interfacial polymerization (IP) reactions was developed for water soften and heavy metal ions removal. The first IP reaction was conducted on the polyethersulfone (PES) hollow fiber substrate using a mixture of branched polyethyleneimine (PEI) and piperazine (PIP) as the aqueous phase monomers in the aqueous phase reacting with trimesoyl chloride (TMC) in the cyclohexane solution. Then, a secondary IP reaction was performed between tris(2-aminoethyl) amine (TAEA) solution and the residual acyl chloride groups on the membrane to increase the positive charge density on the membrane surface. Consequently, a NF membrane with intensified positive surface charge density was successfully fabricated. The optimized membranes achieved a high rejection of MgCl2 of 97.6% while maintaining a pure water permeability (PWP) of 16.0 L m−2 h−1 bar−1. Meanwhile, the membranes exhibit high rejection values of 99.8% to Cu2+ and 99.7% to Zn2+, respectively. In conclusion, this work provides a facile way to prepare a positively charged membrane for efficient water softening and metal ions removal. Submitted/Accepted version

Bridge deck pavement damage has a significant effect on the driving safety and long-term durability of bridges. To achieve the damage detection and localization of bridge deck pavement, a three-stage detection method based on the you-only-look-once version 7 (YOLOv7) network and the revised LaneNet was proposed in this study. In stage 1, the Road Damage Dataset 202 (RDD2022) is preprocessed and adopted to train the YOLOv7 model, and five classes of damage were obtained. In stage 2, the LaneNet network was pruned to retain the semantic segmentation part, with the VGG16 network as an encoder to generate lane line binary images. In stage 3, the lane line binary images were post-processed by a proposed image processing algorithm to obtain the lane area. Based on the damage coordinates from stage 1, the final pavement damage classes and lane localization were obtained. The proposed method was compared and analyzed in the RDD2022 dataset, and was applied on the Fourth Nanjing Yangtze River Bridge in China. The results shows that the mean average precision (mAP) of YOLOv7 on the preprocessed RDD2022 dataset reaches 0.663, higher than that of other models in the YOLO series. The accuracy of the lane localization of the revised LaneNet is 0.933, higher than that of instance segmentation, 0.856. Meanwhile, the inference speed of the revised LaneNet is 12.3 frames per second (FPS) on NVIDIA GeForce RTX 3090, higher than that of instance segmentation 6.53 FPS. The proposed method can provide a reference for the maintenance of bridge deck pavement. Published version This research was funded by the National Natural Science Foundation of China (grant number: 51978155), the Postgraduate Research & Practice Innovation Program of Jiangsu Province (grant number: SJCX21_0056), and the Open Foundation of National Engineering Laboratory for High Speed Railway Construction (grant number: HSR202003).

The overlying strata of the lower coal seam is easy to be collapsed causing the roof caving accident at the end face of the mining working face under repeated mining in close-distance coal seams. In order to predict the roof instability of the end face, the mechanical model of the granular arch structure is established in this study to further analyze its main influencing factors. The results show that the mining height of the working face, the advancing speed, the distance of coal seams, the tip-to-face distance, the strength of the surrounding rock and the support setting the load of the support are the main influencing factors on the roof caving of the end face. Subsequently, the prediction model of roof instability in the end face under repeated mining is constructed through the radial basis function neural network (RBFNN) and the above main influencing factors are regarded as input layer indexes. Meanwhile, the roof subsidence, coal wall deformation and support load are determined as the output layer indexes. The predicted results are closer to the results of sample tests. Finally, the early warning system, including monitoring and early warning, data query, emergency management, user management, and system settings, is designed to monitor roof conditions of the end face and timely warn the roof accidents. The field application proves that the system has good practical value, which is of great significance to intelligent prediction of coal mine stope disaster and prevent the end face roof disaster under repeated mining and. This will promote the safe and efficient construction of coal mine production. Published version This study is financially supported by the National Natural Science Foundation of China Regional Fund (No. 52164002), the National Natural Science Foundation of China Regional Fund (No. 52164005), the National Natural Science Foundation of China Regional Fund (No. 52064005), Guizhou Provincial Science and Technology Projects (Qianke Science Support [2021] General 399) and Guizhou University Cultivation Plan ([2020] No.23).

Scanning electron microscopy (SEM) is a widely used method for the analysis of concrete micro structure. To quantitatively analyze the SEM images with high efficiency and accuracy, an automatic segmentation framework is proposed in this paper. The deep segmentation algorithm is purposely optimized from PointRend based on the characteristic of SEM images to improve prediction accuracy, especially the performance around boundaries. Moreover, the SEM images can be segmented without additional treatment. Cement paste samples with 0.2 and 0.4 water-to-cement ratios are prepared and cured for 1, 3, 7, 14, and 28 days. Totally SEM images with 2267 labeled cement particles are included to build the dataset. From the results of intersection over union and pixel accuracy, the proposed algorithm outperforms the trainable waikato environment for knowledge analysis (WEKA) segmentation, Fully Convolutional Networks (FCN), and the original PointRend method. The segmentation results are used to calculate the hydration degree of two cement paste samples. Good agreement is obtained with the hydration degree calculated by using nonevaporable water in the samples for the 5 curing durations. At last, the shape of the cement particles is analyzed. Irregularity and roundness of the cement particles do not change significantly with an increase in curing duration. Ministry of National Development (MND) National Research Foundation (NRF) This work was partially supported by the National Key Research and Development Program of China (Grant No. 2021YFF0500801), the National Research Foundation, Singapore, and Ministry of National Development, Singapore, under its Cities of Tomorrow R&D Programme (CoT Award No. COT-V2-2019-1), Shenzhen Science and Technology Program, China (Grant No. RCYX20200714114525013) and Open Funding of State Key Laboratory of High Performance Civil Engineering Materials (Grant No. 2021CEM006).

Compressibility is one of the important engineering properties of municipal solid waste (MSW) affecting the stability and functionality of a landfill. Although the correlations between MSW properties and compression parameters have been established, they either have low accuracy and small datasets or are only limited to a few specific landfills in a region. In this study, a new method using the initial global void ratio (e0*) of MSW to estimate the compression indices is developed based on a comprehensive MSW dataset. The dataset consists of 124 sets (91 laboratory and 33 field) of MSW compression results obtained from 44 studies in 13 countries with different income levels and climate conditions. We categorized MSW as a ternary mixture with biodegradable (B), reinforcing (R), and inert (I) fractions, and suggested average specific gravity values (Gs,B = 1.20, Gs,R = 1.07, and Gs,I = 2.64), respectively. The e0* values were calculated using the initial dry unit weight (γd,0) and ternary composition of MSW. The correlations between the e0* and the immediate compression index, secondary compression index induced by mechanical creep, and secondary compression index induced by bio-compression of MSW were evidently established. The results are applicable to the MSW with B = 0-79.2 %, R = 0-54.0 %, I = 2.8-100.0 %, and γd,0 = 2.0-14.2 kN/m3. A simple flowchart was established to estimate the compression indices and strains of MSW disposed on in landfills and dumpsites in countries with different income levels.

To review the present scenario of the research on the scheduling and control of the production process in the manufacturing industry, this comprehensive article has extensively examined this field’s hotspots, boundaries, and overall evolutionary trajectory. This paper’s primary goal is to visualize and conduct an organized review of 5052 papers and reviews that were published between 2002 and 2022. To reveal the “social, conceptual, and conceptual framework” of the production area, identify key factors and research areas, highlight major specialties and emerging trends, and conduct research, countries, institutions, literature keywords, etc., are all used. Additionally, research methodologies are always being improved. The aim of this work is to explore more references for research implementation by analyzing and classifying the present research status, research hotspots, and potential future trends in this field of research. Published version This work was funded by the Researchers Supporting Project No. (RSP2023R363), King Saud University, Riyadh, Saudi Arabia.

The soil–water characteristic curve (SWCC) is one of the most crucial and fundamental soil properties in unsaturated soil mechanics. Many theories and equations have been developed to describe and best fit SWCC with unimodal or bimodal characteristics. In this study, a general best-fitting equation for SWCC with multimodal characteristics (bimodal and trimodal SWCC) is proposed. The parameters in the proposed equation are closely related to the properties of soil and variables in the SWCC. To evaluate the performance of the proposed equation in best-fitting multimodal SWCC that has more than two modalities, a trimodal SWCC soil mixture that consists of sand, kaolin and activated carbon has been prepared and tested in the laboratory in this study. The proposed equation has been evaluated with data from published literature and the newly developed soil mixture of trimodal SWCC. The proposed equation has shown high accuracy for best-fitting bimodal SWCC and trimodal SWCC. Nanyang Technological University Submitted/Accepted version This study was supported by a research scholarship from the Nanyang Environment & Water Research Institute (NEWRI) and Nanyang Technological University, Singapore.

Waste-to-Energy (WtE) through municipal solid waste (MSW) incineration is a key waste management strategy to reduce the mass and volume of landfilled wastes, especially for land-constrained areas such as urban centres. However, this process releases large amounts of CO2 into the atmosphere and the ash that remains after burning, which contains a variety of metals and minerals, is often sent to the landfill after some metal recovery. In this study, the CaO containing ash is used to derive sorbents for the calcium looping (CaL) process for post-combustion CO2 capture and storage (CCS), and a techno-economic assessment was performed to preliminarily probe the feasibility of retrofitting a CaL plant using ash-derived sorbents to capture CO2 from a 200MWth WtE plant, as a possible means to decarbonise WtE plants. The analysis was performed through process modelling of the CaL plant using 4 different supplementary fuels in the calciner, namely, biomass charcoal (BC), solid recovered fuel (SRF), coal, and natural gas (NG). At the base purge ratio of 5%, all the cases show increases in the levelised cost of electricity (LCOE) over the base WtE, ranging from 184 (NG) to 246 (BC) USD/MWhe. The sale of additional electricity generated from the heat recovery steam cycle could slightly mitigates the capital intensiveness of the process, resulting in a levelised cost of carbon abatement (LCCA) range of USD 89 (SRF) to 184 (coal)/tCO2, which is competitive with other bioenergy with CO2 capture and storage (BECCS) technologies. The biogenic fuels also result in lower specific primary energy consumption per CO2 avoided (SPECCA) of 5.6 (BC) and 6.8 (SRF) MJLHV/tCO2, which are comparable to values from other CCS technologies and CaL implementation studies. Sensitivity analysis of 14 economic and process parameters reveals that further improvements can be achieved through optimisation of the energy intensive sub-processes, such as cryogenic air separation and CO2 compression and purification. Tighter solid heat integration (SHI) concepts were also modelled and are shown to effectively reduce fuel and O2 requirements by up to 22.2%, thereby lowering annualised costs by up to 11.9%. In addition, this paper highlights the importance of regulatory support through favourable policies such as higher carbon pricing and CO2 credit trading to push the development and adoption of negative emission technologies to meet global decarbonisation targets. Agency for Science, Technology and Research (A*STAR) National Research Foundation (NRF) Public Utilities Board (PUB) Submitted/Accepted version The research team is thankful to the financial support by Singapore Energy Centre (SgEC-Core2019-34) and Agency for Science, Technology and Research (A*STAR) of Singapore under its Low Carbon Energy Research Funding Initiative (LCER-FI, project number: U2102d2007). This research/project is supported by the National Research Foundation, Singapore, and PUB, Singapore’s National Water Agency under its RIE2025 Urban Solutions and Sustainability (USS) (Water) Centre of Excellence (CoE) Programme, awarded to Nanyang Environment & Water Research Institute (NEWRI), Nanyang Technological University, Singapore (NTU).

Global warming-induced sea level rise exacerbates the deterioration of maritime structures and imperils their long-term durability. Cementitious materials such as ordinary Portland cement (OPC), pozzolanic blended cement (PBC) and alkali-activated material (AAM) can chemically interact with seawater, leading to degradation of binding properties. Despite their extensive applications in construction industry, the seawater resistance of these materials remains elusive. The objective of this work is to review and compare the durability of OPC, PBC and AAM in seawater environment from the perspectives of chemical interactions and hardened-state properties. This paper first briefly explains the mechanism of seawater intrusion into hardened cementitious materials. The chemical interactions of chloride, sulphate and carbon dioxide from seawater with hydrate components in OPC, PBC and AAM are discussed. From the durability aspects, this study evaluates and compares the performance of cementitious materials, including compressive strength, mass change, porosity and water absorption, and chloride permeability. Seawater deterioration mechanisms coupled with environmental factors such as wetting–drying cycle, external loading and temperature are also presented. Based on the review, future research is suggested to improve the durability studies related to seawater attack. This review provides better insight into the development of sustainable seawater-resistant construction materials for applications in seawater environment. Ministry of Education (MOE) Submitted/Accepted version This research is supported by the Ministry of Education, Singapore, under its Academic Research Fund Tier 2 (MOE-T2EP50220-0004).

Soil suction plays an important role in governing the stability of slopes. Environmental sustainability could be jeopardized by hazards, such as slope failures (forest destruction, landscape alteration, etc.). However, the quantification of the suction effect on slope stability is a challenging task as the soil suction is usually affected by the precipitation and evapotranspiration. Numerical simulation plays an important role in the estimation of contour in soil suction due to rainfall and evapotranspiration as long-term and widespread monitoring is rarely conducted. The result of numerical simulation is highly dependent on the accuracy of the input parameters. Hence, suction monitoring plays an important role in verifying the result of numerical simulation. However, as a conventional tensiometer is limited to 100 kPa soil suction, it is hard to verify the performance of numerical simulation where suction is higher than 100 kPa. The osmotic tensiometer developed by Nanyang Technological University (NTU) can overcome this problem. It is now possible to monitor changes in soil suction higher than 100 kPa (up to 2500 kPa) for an extended period in the field. In this study, a procedure was proposed to estimate suction changes in residual soil based on rainfall and evapotranspiration data. Numerical simulation was carried out based on the soil properties and geometry of a residual soil slope from Jurong Formation Singapore. Changes in soil suction due to rainfall and evaporation were simulated and compared with the readings from the NTU osmotic tensiometers installed at 0.15 m and 0.50 m from the slope surface in the field. It was observed that numerical simulation was able to capture the variations of suctions accurately at greater depths. However, at shallow depths, erratic suction changes due to difficulties in capturing transpiration. Published version This research was supported by the Nazarbayev University Research Fund under Social Policy Grant and Faculty Development Competitive Research Grants Program (FDCRGP) Grant No. 20122022FD4133.

Polynomial chaos expansion (PCE) is widely adopted in geotechnical engineering as a surrogate model for probabilistic analysis. However, the traditional low-order PCE may be unfeasible for unsaturated transient-state models due to the high nonlinearity. In this study, a temporal-spatial surrogate model of adaptive sparse polynomial chaos expansions (AS-PCE) is established based on hyperbolic truncation with stepwise regression as surrogate models to improve computational efficiency. The uncertainty of pore water pressure of an unsaturated slope under transient-state rainfall infiltration considering hydraulic spatial variability is studied. The saturated coefficient of permeability [Formula: see text] is chosen to be spatial variability to account for the soil hydraulic uncertainty. The effects of location and time and the performances of AS-PCE are investigated. As rainfall goes on, the range of the pore pressure head becomes larger and the spatial variability of [Formula: see text] has little influence in the unsaturated zone with high matric suction. The pore pressure head under the water table suffers more uncertainty than it in the unsaturated zone. The [Formula: see text] in the high matric suction zone has a trend of rising first and then falling. Except for the high matric suction zone, the [Formula: see text] rise over time and they are almost 1 at the end of the time. It can be concluded that the AS-PCE performs better for low matric suction and positive pore pressure head and the fitting effect gradually increases as the rainfall progresses. The quartiles and at least up to second statistical moments can be characterized by the AS-PCE for transient infiltration in unsaturated soil slopes under rainfall.

In the past two decades, the concept of microbial resources evolved from the conserved strains in culture collection centers and microbial genome data in databases to functional microbial consortia, strains with superior phenotypes, novel biochemical and signaling systems, highly efficient enzymes, secondary metabolites, and unique genetic traits. Natural and engineered water environments provide diverse ecological niches for microorganisms to evolve and thrive, serving as treasure troves of microbial resources. Compared with that of chemical and energy resources from water, mining of microbial resources is severely underexplored. In this review, we first summarize various approaches (e.g., cultivation, functional metagenomics, and single-cell genomics) that have been employed to mine microbial resources from water, and then discuss their distinctive advantages and limitations. Lastly, we explore future directions on the mining of microbial resources from water. Nanyang Technological University National Research Foundation (NRF) This research / project is supported by the National Research Foundation, Singapore, under its NERC-NRF Joint Grant Call (Award no. NRF-NERC-SEAP-2020-02). This research is also supported by the Accelerating Creativity and Excellence (ACE) grant (Award no. NTUACE2021-01), Nanyang Technological University, Singapore.

Shared autonomous vehicles (SAVs) are revolutionizing the future of urban mobility. This study aims to investigate the effects of artificial intelligence (i.e., autonomy level and anthropomorphic characteristics), human-related, environmental, and societal factors on public trust and acceptance. Structural equation modelling is used to analyze a valid survey sample of 451 participants. Results show that autonomy level can both directly and indirectly (via trust) increase public acceptance; Whereas, anthropomorphic characteristics cannot directly affect public acceptance, but can indirectly increase their acceptance via trust. The other human-related, environmental, and societal factors also positively contribute to public acceptance. Additionally, moderators, including age, gender, income, housing size, COVID-19 history, shared mobility experience, vehicle ownership, and driving experience are also examined. In theory, this study contextualizes the trust-in-automation three-factor model, UTAUT model, and trust theory and includes two domain-specific constructs (i.e., SAV anthropomorphism and SAV autonomy) to study public trust and acceptance towards SAVs. In practice, this study suggests the incorporation of some anthropomorphic features and relatively high autonomy level in SAVs to build public trust and acceptance.

Cement industry is one of the main sources of greenhouse gases, which accounts for about 7% of global CO2 emissions. Sequestration of CO2 in cement-based materials is regarded as an effective alternative since it can convert CO2 into stable carbonates with relatively low additional energy consumption. This paper presents a comprehensive review on recent research and advances on carbon sequestration in magnesium-based binders with a focus on reactive MgO cement (RMC) and magnesium oxychloride cement (MOC). The carbon sequestration mechanism, the influence of carbonation on mechanical performance, and key parameters that control the carbonation process are summarized. In addition, a quantitative analysis of carbon sequestration in RMC-based materials is presented, demonstrating the effectiveness of offsetting carbon emissions via the use of alternative binder systems. Furthermore, a comparison of the environmental impact of Portland cement, RMC and MOC production is provided, emphasizing the need for enhancing the sustainability of cement production procedures. Overall, this paper presents a roadmap for emerging carbonation techniques that improve the mechanical performance and sustainability of magnesium-based binders. This study is supported under the RIE2020 Industry Alignment Fund – Industry Collaboration Projects (IAF-ICP) Funding Initiative, as well as cash and in-kind contribution from Surbana Jurong Pte Ltd.

Moment redistribution (MR), a nonlinear behavior occurring in continuous reinforced concrete (RC) beams, is related to the redistributed section's ductility and the stiffness distribution along the whole beam. The use of high-strength steel (HSS) reinforcement could affect the redistributed section's ductility and can delay or even prevent the formation of plastic hinge after another. The lack of research regarding the influence of those phenomena on MR is one of the reasons that hinder design engineers from using HSS. This paper conducts a broad-range parametric study through finite element (FE) method to check if the design provisions on MR are still applicable to beams with HSS reinforcement of yield strength of more than 600 MPa. The critical sections' yield state (whether the plastic hinge is formed) at the ultimate limit state (ULS) and its influences on MR are investigated. The study demonstrations that the MR capacity decreases with the increase in yield strength of reinforcement, especially when the midspan section cannot yield at ULS due to the use of HSS reinforcement. Besides, the yield state is influenced by the coupling effect of multi-parameters and significantly affects the influence degree of each parameter on MR. A new method considering the yield state is proposed to estimate the MR capacity of the continuous beams. This method's reasonable accuracy is proved. It is recommended to reduce the specified MR by about 6% for every 100 MPa increase in yield strength of reinforcement. The research described in this paper was financially supported by the Fundamental Research Funds for the Central Universities, CHD (300102282106).

This paper presents an experimental and numerical study of the local–flexural interactive buckling behaviour and resistances of press-braked ferritic stainless steel slender channel section columns. An experimental programme was firstly conducted, including initial geometric imperfection measurements and ten pin-ended column tests. Interaction between local buckling and flexural buckling was observed for all column specimens upon testing and discussed in detail. The test results were used in a parallel numerical modelling programme to validate finite element models, which were then adopted to perform parametric studies to generate additional numerical data over a wide range of cross-section dimensions and member effective lengths. Based on the test and numerical data, the relevant design rules for press-braked ferritic stainless steel slender channel section columns, as given in the American specification and European code, were evaluated. The evaluation results revealed that the American specification resulted in a good level of design accuracy, while the European code led to conservative and scattered interactive buckling resistance predictions. Finally, a revised Eurocode design method was proposed and shown to yield much more accurate and consistent interactive buckling resistance predictions for press-braked ferritic stainless steel slender channel section columns than its original counterpart.

Dams are infrastructural projects with multiple uses that include hydropower, irrigation, water storage, flood management, and recreation. Most research on dams in Southeast Asia focuses on the Mekong River Basin and there is limited research on dams in Indonesia. Here, we developed a comprehensive database of dams in Indonesia derived from global and local datasets. We also used Google Earth Pro to locate additional dams and to validate the presence of all the dams. Our database had a total of 1506 dams (from large to mini dams and run-of river dams) in operation or under construction, and this was three times the number of dams reported in Indonesia’s national database for dams. There were another 250 planned dams, of which, only 30 had known locations. Our database also includes information such as the geographical coordinates of each dam, their physical characteristics, and what each dam is used for. Ultimately, we hope that our work will help researchers, non-government organizations, and government agencies with hydrological and socio-ecological research in Indonesia. Ministry of Education (MOE) National Research Foundation (NRF) Published version This research was supported by the Earth Observatory of Singapore via its funding from the National Research Foundation Singapore and the Singapore Ministry of Education under the Research Centres of Excellence initiative.

Global greenhouse gas (GHG) emissions from food loss and waste (FLW) are not well characterized from cradle to grave. Here GHG emissions due to FLW in supply chain and waste management systems are quantified, followed by an assessment of the GHG emission reductions that could be achieved by policy and technological interventions. Global FLW emitted 9.3 Gt of CO2 equivalent from the supply chain and waste management systems in 2017, which accounted for about half of the global annual GHG emissions from the whole food system. The sources of FLW emissions are widely distributed across nine post-farming stages and vary according to country, region and food category. Income level, technology availability and prevailing dietary pattern also affect the country and regional FLW emissions. Halving FLW generation, halving meat consumption and enhancing FLW management technologies are the strategies we assess for FLW emission reductions. The region-specific and food-category-specific outcomes and the trade-off in emission reductions between supply chain and waste management are elucidated. These insights may help decision makers localize and optimize intervention strategies for sustainable FLW management. We thank the Jiangsu Special Project for Introducing Foreign Talents (grant no. BX2019015, K.Y.) and the Key Achievement Cultivation Plan Project of Nanjing Forestry University (K.Y.) for financial support.

Increasingly waste materials or soft soil dredged from sea or river have to be used as fill materials for land reclamation. Although preloading using prefabricated vertical drains (PVDs) has been commonly used as the treatment method for soft soil, this method is time consuming as it can only be applied after all the fill materials have been placed. In this paper, a conceptual design for land reclamation using a horizontal drainage enhanced geotextile sheet (HDeGs) method combined with vacuum preloading is proposed. Large-scale model tests are carried out to verify the effectiveness of the HDeGs method. The proposed method is also compared with the existing prefabricated horizontal drain (PHD) method and the advantages and disadvantages of the HDeGs with vacuum preloading method are discussed. This study has demonstrated that the proposed HDeGs method is not only effective, but also more efficient compared with the PVD or PHD methods, as it can reduce substantially the construction time required for land reclamation.

Deep excavation supported by vertical retaining walls together with strutting system is commonly used in Singapore for the construction of underground infrastructure. In this paper, a series of numerical scenarios simulated by PLAXIS software are carried out to study the influence of different design parameters such as pre-auger loosening effect, the embedded depth of retaining wall into the stiff soil layer, and the elastic modulus of the ground improvement layer on excavation design especially on strut force, retaining wall deflection, and bending moment. The results show that there is high risk if only a single set of parameters are used as input to predict the performance of the retaining system. Sensitivity analysis shall be carried out to evaluate the effects of these parameter variations within a reasonable range on strut force, retaining wall deflection, and bending moment. Published version

A dual attention deep learning network is developed to classify three types of steel defects, locate their positions, and depict their shapes on the steel surface in an automatic and accurate manner. The novel pixel-level detection algorithm called DAN-DeepLabv3+ integrates a dual attention module into the DeepLabv3+ framework in pursue of more precise segmentation results. For one thing, the dual parallel attention module helps to explicitly model rich contextual dependencies over local feature representations in the spatial and channel dimensions. For another, the popular DeepLabv3+ in an encoder-decoder architecture is useful in capturing multi-scale contextual information and sharp object boundaries. The DAN-DeepLabv3+ is applied to an available dataset containing 6666 images, where three types of steel defects are taken by high-frequency cameras and have been annotated manually. Experimental results show that, compared with other deep learning models, DAN-DeepLabv3+ based on the Xception backbone exhibits the best segmentation performance under the mean intersection over union (IoU) of 89.95% and the frequency-weighted IoU of 97.34%. Besides, the F1-score for the three kinds of defects can reach 86.90%, 99.20%, and 92.81%. From the comparative study, it has been found that the adoption of the dual attention module and DeepLabv3+ contributes to boosting the segmentation performance. The significance of the proposed hybrid model lies in the enhancement in accurately detecting single or multiple steel defects, which has proven to outperform other classical methods. Ministry of Education (MOE) Nanyang Technological University Ministry of Education Tier 1 Grants, Singapore (No. 04MNP000279C120, No. 04MNP002126C120) and the Start-Up Grant at Nanyang Technological University, Singapore (No. 04INS000423C120).