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• A novel model is proposed for real-time risk evaluation of vehicle–pedestrian interactions at intersections. • A perspective on the relative movement between vehicles and pedestrians is taken. • Driving spaces are defined for identifying safety–critical events. • Dynamic relationship between driving spaces and relative velocity is revealed. • The proposed model outperforms the commonly used surrogate safety models. Safety decisions for vehicles at an intersection rely on real-time, objective and continuous assessment of risks in vehicle–pedestrian interactions. Existing surrogate safety models, constrained by ideal assumptions of constant current speed and reliant on interaction points, often misjudge risks, and show inefficiency, inaccuracy and discontinuity. This work proposes a novel model for evaluation of those risks in vehicle–pedestrian interactions at intersections, which abstracts the pedestrian distribution density around a vehicle into a generalized model of driver-pedestrian interaction preferences. The introduction of two conceptions: 'driving risk index' and 'driving risk gradient,' facilitates the delineation of driving spaces for identifying safety–critical events. By means of the trajectory data from three intersections, model parameters are calibrated and a multidimensional vehicle–pedestrian interaction risk (VPIR) model is proposed to adapt the complex and dynamic characteristics of vehicle–pedestrian interactions at intersections. Commonly used surrogate safety models, such as Time to Collision (TTC), are selected as benchmark models. Results show that the proposed model overcomes the limitations of the existing interaction-point-based models, and offers a ideal assessment of driving risks at intersections. Finally, the model is illustrated with a case study that assesses the risks in vehicle–pedestrian interactions in varied scenarios and the case study indicates that the VPIR model works well in evaluating vehicle–pedestrian interaction risks. This work can facilitate humanoid learning in the autonomous driving domain, and achieve an ideal evaluation of vehicle–pedestrian interaction risks for safe and efficient vehicle navigation through an intersection. [ABSTRACT FROM AUTHOR]

BiVO 4 /Cu 2 O/g-C 3 N 4 ternary heterojunction as a double Z-scheme sonocatalyst was effectively synthesized by the solvothermal and thermal decomposition method. The sonocatalysts' structure, morphology, chemical makeup, and physicochemical characteristics were assessed by using XRD, SEM, TEM, XPS, DRS, and BET. Tetracycline (TET) was utilized for the modeled chemical contaminant to investigate the sonocatalytic capabilities of the sonocatalysts. The findings showed that BiVO 4 /Cu 2 O/g-C 3 N 4 had remarkable sonocatalytic activity, and the degradation rate reached 93.80±0.33 % within 30 min. By further studying the electron separation and migration behavior, a feasible sonocatalytic mechanism of BiVO 4 /Cu 2 O/g-C 3 N 4 is proposed. This research will pave the practicable way for the new double Z-scheme sonocatalytic system. [Display omitted] • BiVO 4 /Cu 2 O/g-C 3 N 4 was a good sonocatalyst with 93.80±0.33 % of tetracycline removal rate in 30 min. • The construction mechanism of double Z-scheme heterojunction in BiVO 4 /Cu 2 O/g-C 3 N 4 was proposed. • The mechanism and pathway of sonocatalytic degradation of TC by BiVO 4 /Cu 2 O/g-C 3 N 4 was proposed. • BiVO 4 /Cu 2 O/g-C 3 N 4 composite showed good stability and reusability in four reuses. [ABSTRACT FROM AUTHOR]

Directly deriving electrical energy from waste activated sludge (WAS) by using microbial fuel cell (MFC) is one of the most promising alternatives to resource utilization of WAS. However, obtaining high MFC performance is still a great challenge for the full-scale implementation of MFC. Therefore, this study aimed to quantify and model the effect of different operating parameters on the performance of MFC fed with dried WAS as anode substrate. The results indicated that MFC exhibited a fast start-up time of 3 days at the inoculated anaerobic sludge: dry WAS mass ratio of 1:5. Moreover, the output voltage and power density of MFC were highly dependent of anolyte pH and temperature, WAS concentration, which was well simulated and predicted by the BPANN model. It was revealed that MFC fed with dry WAS exhibited good performance at 55ºC, pH 9.0 and WAS concentration of 16 g/L, while the stable output voltage and power density were 0.705 V and 5.248 W/m3, respectively. The anolyte temperature significantly affected microbial communities of the anode biofilm. At the phylum level, Synergistota and Proteobacteria dominated the anode biofilm at 35ºC, while Firmicutes was absolutely enriched in the anode biofilm at 55ºC. At the genus level, the predominant Advenella is detected in the anode biofilm at 35ºC, whereas the preponderant MBA03 is identified in the anode biofilm at 35ºC. The findings herein may provide a route for efficiently driving power energy from WAS, which can facilitate the fulfillment of full-scale MFC for the resource utilization of WAS. [Display omitted] • Electricity production performance from dried waste activated sludge in dual chamber microbial fuel cells was investigated. • The rapid start-up time of 3 – 4 days was achieved in microbial fuel cells. • The output power performance was controlled by anolyte pH and temperature, sludge concentration. • Artificial neural network predicts the MFC output performance of microbial fuel cell. • The anolyte temperature affects microbial community structure of the anode biofilm. [ABSTRACT FROM AUTHOR]

Dry bulk shipping market, as an indispensable part of maritime supply chains, can be affected by the transport demand from commodity market, the costs from bunker market, the macroeconomic environment, and threats from the competitor market. To analyze such interactions between these markets, this paper proposes the use of a vector-autoregression (VAR) model to explore volatility spillover effects in dry bulk shipping markets in terms of the secondhand ship prices of Capesize, Panamax and Handymax during 2009–2019. The characteristics of sub-segments of dry bulk shipping market are deeply analyzed, which are necessary for asset allocation in shipping industry. A series of numerical experiments are carried out, by means of variance decomposition approach and historical decomposition approach. Results reveal the existence of different responses to shocks in sub-segments of dry bulk shipping market. It is also shown that smaller vessels are more likely to be affected by related markets except the outlier of the relationship between China interest rate and Panamax market. In addition, responses to both negative and positive contributions are discussed. For example, commodity market has a profound effect on dry bulk shipping market when the market is stable, whereas influences of the bunker market represents the volatility of a market. Finally, this paper finds insignificant effects of the US-CNY exchange rate market and the container shipping market on the dry bulk shipping market. • Build a comprehensive mechanism to measure spillover effects on different segments of dry bulk shipping markets • A 10.5-year dataset from January 2009 to July 2019 is adopted to cover several important global economic events. • A robust approach is proposed to specifying the contribution of each index to the dry bulk shipping market. • Forecast and explore the spillover effects in next 12 months and analyze the historical shocks. • An advisable investment strategy for market participants is explored by analyzing characteristics of varied markets. [ABSTRACT FROM AUTHOR]

The nature and growth of city size distribution in China are examined by using urban data. Convergence, Gibrat' s law, Zipf' s law, etc. are discussed.

Recent advancements in energy harvesting have led to innovative methods for converting droplet motion into electricity, such as droplet triboelectric nanogenerators (D-TENGs). However, enhancing their power generation capacity and efficiency remains a challenge. We present a novel surface engineering approach that significantly boosts the electrical outputs of the D-TENGs. By grafting perfluorodecyltrimethoxysilane (PFDTMS) onto polydimethylsiloxane (PDMS) surfaces pre-treated with sandpaper, we achieve a dual effect: fluoridation and increased contact area between droplets and PDMS. This modification, when applied to a droplet-based TENG, yields a remarkable 10–20 fold increase in power metrics such as current, charge, and voltage as compared to untreated counterparts, resulting in an energy conversion efficiency of 17.1% under a 30 MΩ load. Our enhanced D-TENG efficiently harvested energy from falling tap water droplets, producing a current of ∼2 mA. Remarkably, a single droplet impact could illuminate 400 LED lights. Furthermore, when coupled with capacitors, the device powered a hygrometer and 3 W light bulbs, demonstrating substantial potential for real-world applications. This breakthrough in surface engineering for energy harvesters represents a significant step forward in the efficient and powerful generation of electricity from droplet motions. [Display omitted] • High performance device harvests energy from droplets. • Improved device performance achieved through surface engineering. • The impact of a single tap water droplet can generate a current exceeding 2 mA. • An energy conversion efficiency of 17.1% is achieved under a 30 MΩ load. • A single droplet impact can illuminate up to 400 LED lights. [ABSTRACT FROM AUTHOR]

The fast advancement of flexible electronic technology hastens an ever-growing demand for power sources that are adaptable and flexible, and the arrival of innovative energy harvesting technologies such as triboelectric nanogenerator (TENG) further endow the potable electronics with versatility and sustainability. Herein, polyvinyl alcohol/ polyacrylamide/ zinc sulfate (PPZ) hydrogel was synthesized via an one-step UV-initiated polymerization. The hydrogel demonstrates exceptional tensile properties (with a large strain of 915 % and a corresponding tensile strength of 231 KPa), excellent electrical conductivity and light transmittance. A highly flexible and easily adaptable single-electrode TENG was thus fabricated on the base of the as-synthetized PPZ (PPZ-TENG), where the PPZ hydrogel functions as both the charging layer and current collector. While promoting a high electrical output performance of the PPZ-TENG (an open circuit voltage of 176 V and a power density of 328 mW/m2), the PPZ hydrogel also serves as an efficient ion-conductive electrolyte to construct highly flexible self-charging zinc ion batteries (ZIBs). Besides, highly sensitive strain response toward environmental stimuli was also demonstrated, which makes the integration strategy a promising solution for future development self-powered flexible wearable electronics toward the sustainable monitoring of human vital signs such as pulse and limb movement. [Display omitted] • The PPZ hydrogel was simply synthesized via an one-step UV-initiated polymerization. • PPZ hydrogel-based TENG was designed and assembled which could generate a power density of 328 mW/m2. • The flexible and adaptable TENG was used to human motion sensing and drive zinc-ion batteries. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: To develop and validate 2 iodine maps based radiomics nomograms for preoperatively predicting cervical lymph node metastasis (LNM) and central lymph node metastasis (CLNM) in papillary thyroid cancer (PTC).Materials and Methods: A total of 346 patients with PTC were enrolled and allocated to training (242) and validation (104) sets. Radiomics features were extracted from arterial and venous phase iodine maps, respectively. Aggregated machine-learning strategy was applied for features selection and construction of 2 radiomics scores (LN rad-score; CLN rad-score). Logistic regression model was employed to establish two radiomics nomograms (nomogram 1: predicting LNM; nomogram 2: predicting CLNM) after incorporating LN or CLN rad-score with clinical predictors. Nomograms performance was determined by discrimination, calibration and clinical usefulness.Results: Nomogram 1 incorporated LN rad-score, age (categorized by 55) and CT reported LN status; Nomogram 2 incorporated CLN rad-score, capsule contact >25% and CT reported CLN status. 2 nomograms both showed good discrimination and calibration in the training (AUC = 0.847; AUC = 0.837) and validation cohorts (AUC = 0.807; AUC = 0.795). Significant improved AUC, net reclassification index (NRI) and integrated discriminatory improvement (IDI) confirmed additional great predictive value of 2 rad-scores, compared with clinical models without radiomics. Decision curve analysis indicated clinical utility of nomograms. 2 nomograms both demonstrated favorable predictive efficacy in CT reported LN or CLN negative subgroup (AUC = 0.766; AUC = 0.744).Conclusion: The presented 2 radiomics nomograms are useful tools for preoperative prediction of LNM and CLNM in PTC. [ABSTRACT FROM AUTHOR]