Technological progress and coupling renewables enable substantial environmental and economic benefits from coal-to-olefins.

China's growing demand for bulk chemicals and concerns regarding energy security are scaling up coal-to-olefins (CTO) production. Three generations of independent dimethyl ether/methanol-to-olefins technologies have been successively launched with greatly improved production efficiencies. However, to date, widespread concerns regarding the intensive environmental impacts and potential economic risks have not been addressed in the context of this industrialization. Here we show that, through the technological progress from the first to the third generation, life cycle energy consumption, water consumption, and carbon emissions can be reduced to 119.5 GJ/t, 27.6 t/t, and 9.1 t CO2-eq/t, respectively, and human health damage, ecosystem quality damage, and resource scarcity impacts can be decreased by 40.5 %, 50.1 %, and 16.4 %, respectively. This is accompanied by an excellent performance in terms of production cost, net present value, and internal return rate at 792.5 USD/t, 173.4 USD/t, and 19.4 %, respectively. Substantial environmental and economic benefits can be gained by coupling renewables in the form of using green hydrogen from solar and wind power to synthesize methanol. Particularly, life cycle carbon emissions and resource scarcity impacts are reduced by 23.4 % and 22.4 %, respectively, exceeding the reduction in technological progress. However, coupling renewables increases the life cycle energy consumption to 154.5 GJ/t, counteracting the benefits of technological progress. Our results highlight the importance of technological progress and coupled renewables for enhancing the sustainability of the CTO industry.

Comparison of treatment planning approaches for spatially fractionated irradiation of deep tumors.

PURPOSE: The purpose of this work was to compare the dosimetry and delivery times of 3D-conformal (3DCRT)-, volumetric modulated arc therapy (VMAT)-, and tomotherapy-based approaches for spatially fractionated radiation therapy for deep tumor targets. METHODS: Two virtual GRID phantoms were created consisting of 7 "target" cylinders (1-cm diameter) aligned longitudinally along the tumor in a honey-comb pattern, mimicking a conventional GRID block, with 2-cm center-to-center spacing (GRID2 cm ) and 3-cm center-to-center spacing (GRID3 cm ), all contained within a larger cylinder (8 and 10 cm in diameter for the GRID2 cm and GRID3 cm , respectively). In a single patient, a GRID3 cm structure was created within the gross tumor volume (GTV). Tomotherapy, VMAT (6 MV + 6 MV-flattening-filter-free) and multi-leaf collimator segment 3DCRT (6 MV) plans were created using commercially available software. Two tomotherapy plans were created with field widths (TOMO2.5 cm ) 2.5 cm and (TOMO5 cm ) 5 cm. Prescriptions for all plans were set to deliver a mean dose of 15 Gy to the GRID targets in one fraction. The mean dose to the GRID target and the heterogeneity of the dose distribution (peak-to-valley and peak-to-edge dose ratios) inside the GRID target were obtained. The volume of normal tissue receiving 7.5 Gy was determined. RESULTS: The peak-to-valley ratios for GRID2 cm /GRID3 cm /Patient were 2.1/2.3/2.8, 1.7/1.5/2.8, 1.7/1.9/2.4, and 1.8/2.0/2.8 for the 3DCRT, VMAT, TOMO5 cm , and TOMO2.5 cm plans, respectively. The peak-to-edge ratios for GRID2 cm /GRID3 cm /Patient were 2.8/3.2/5.4, 2.1/1.8/5.4, 2.0/2.2/3.9, 2.1/2.7/5.2 and for the 3DCRT, VMAT, TOMO5 cm , and TOMO2.5 cm plans, respectively. The volume of normal tissue receiving 7.5 Gy was lowest in the TOMO2.5 cm plan (GRID2 cm /GRID3 cm /Patient = 54 cm3 /19 cm3 /10 cm3 ). The VMAT plans had the lowest delivery times (GRID2 cm /GRID3 cm /Patient = 17 min/8 min/9 min). CONCLUSION: Our results present, for the first time, preliminary evidence comparing IMRT-GRID approaches which result in high-dose "islands" within a target, mimicking what is achieved with a conventional GRID block but without high-dose "tail" regions outside of the target. These approaches differ modestly in their ability to achieve high peak-to-edge ratios and also differ in delivery times.

Online dosimetric evaluation of larynx SBRT: A pilot study to assess the necessity of adaptive replanning.

PURPOSE: We have initiated a multi-institutional phase I trial of 5-fraction stereotactic body radiotherapy (SBRT) for Stage III-IVa laryngeal cancer. We conducted this pilot dosimetric study to confirm potential utility of online adaptive replanning to preserve treatment quality. METHODS: We evaluated ten cases: five patients enrolled onto the current trial and five patients enrolled onto a separate phase I SBRT trial for early-stage glottic larynx cancer. Baseline SBRT treatment plans were generated per protocol. Daily cone-beam CT (CBCT) or diagnostic CT images were acquired prior to each treatment fraction. Simulation CT images and target volumes were deformably registered to daily volumetric images, the original SBRT plan was copied to the deformed images and contours, delivered dose distributions were re-calculated on the deformed CT images. All of these were performed on a commercial treatment planning system. In-house software was developed to propagate the delivered dose distribution back to reference CT images using the deformation information exported from the treatment planning system. Dosimetric differences were evaluated via dose-volume histograms. RESULTS: We could evaluate dose within 10 minutes in all cases. Prescribed coverage to gross tumor volume (GTV) and clinical target volume (CTV) was uniformly preserved; however, intended prescription dose coverage of planning treatment volume (PTV) was lost in 53% of daily treatments (mean: 93.9%, range: 83.9-97.9%). Maximum bystander point dose limits to arytenoids, parotids, and spinal cord remained respected in all cases, although variances in carotid artery doses were observed in a minority of cases. CONCLUSIONS: Although GTV and CTV SBRT dose coverage is preserved with in-room three-dimensional image guidance, PTV coverage can vary significantly from intended plans and dose to critical structures may exceed tolerances. Online adaptive treatment re-planning is potentially necessary and clinically applicable to fully preserve treatment quality. Confirmatory trial accrual and analysis remains ongoing.

Single fraction radiosurgery/stereotactic body radiation therapy (SBRT) for spine metastasis: A dosimetric comparison of multiple delivery platforms.

There are numerous commercial radiotherapy systems capable of delivering single fraction spine radiosurgery/SBRT. We aim to compare the capabilities of several of these systems to deliver this treatment when following standardized criteria from a national protocol. Four distinct target lesions representing various case presentations of spine metastases were contoured in both the thoracic and lumbar spine of an anthropomorphic SBRT phantom. Single fraction radiosurgery/SBRT plans were designed for each target with each of our treatment platforms. Plans were prescribed to 16 Gy in one fraction to cover 90% of the target volume using normal tissue and target constraints from RTOG 0631. We analyzed these plans with priority on the dose to 10% of the partial spinal cord and dose to 0.03 cc of the spinal cord. Each system was able to maintain 90% target coverage while meeting all the constraints of RTOG 0631. On average, CyberKnife was able to achieve the lowest spinal cord doses overall and also generated the sharpest dose falloff as indicated by the Paddick gradient index. Treatment times varied widely depending on the modality utilized. On average, treatment can be delivered faster with Flattening Filter Free RapidArc and Tomotherapy, compared to Vero and Cyberknife. While all systems analyzed were able to meet the dose constraints of RTOG 0631, unique characteristics of individual treatment modalities may guide modality selection. Specifically, certain modalities performed better than the others for specific target shapes and locations, and delivery time varied significantly among the different modalities. These findings could provide guidance in determining which of the available modalities would be preferable for the treatment of spine metastases based on individualized treatment goals.

Spatially fractionated radiotherapy (GRID) using helical tomotherapy.

Spatially fractionated radiotherapy (GRID) was designed to treat large tumors while sparing skin, and it is usually delivered with a linear accelerator using a commercially available block or multileaf collimator (LINAC-GRID). For deep-seated (skin to tumor distance (> 8 cm)) tumors, it is always a challenge to achieve adequate tumor dose coverage. A novel method to perform GRID treatment using helical tomotherapy (HT-GRID) was developed at our institution. Our approach allows treating patients by generating a patient-specific virtual GRID block (software-generated) and using IMRT technique to optimize the treatment plan. Here, we report our initial clinical experience using HT-GRID, and dosimetric comparison results between HT-GRID and LINAC-GRID. This study evaluates 10 previously treated patients who had deep-seated bulky tumors with complex geometries. Five of these patients were treated with HT-GRID and replanned with LINAC-GRID for comparison. Similarly, five other patients were treated with LINAC-GRID and replanned with HT-GRID for comparison. The prescription was set such that the maximum dose to the GTV is 20 Gy in a single fraction. Dosimetric parameters compared included: mean GTV dose (DGTV mean), GTV dose inhomogeneity (valley-to-peak dose ratio (VPR)), normal tissue doses (DNmean), and other organs-at-risk (OARs) doses. In addition, equivalent uniform doses (EUD) for both GTV and normal tissue were evaluated. In summary, HT-GRID technique is patient-specific, and allows adjustment of the GRID pattern to match different tumor sizes and shapes when they are deep-seated and cannot be adequately treated with LINAC-GRID. HT-GRID delivers a higher DGTV mean, EUD, and VPR compared to LINAC-GRID. HT-GRID delivers a higher DNmean and lower EUD for normal tissue compared to LINAC-GRID. HT-GRID plans also have more options for tumors with complex anatomical relationships between the GTV and the avoidance OARs (abutment or close proximity).

Long-term evaluation and cross-checking of two geometric calibrations of kV and MV imaging systems for Linacs.

Geometric or mechanical accuracy of kV and MV imaging systems of two Varian TrueBeam linacs have been monitored by two geomertirc calibration systems, Varian IsoCal geometric calibration system and home-developed gQA system. Results of both systems are cross-checked and the long-term geometric stabilities of linacs are evaluated. Two geometric calibration methodologies have been used to assess kV and MV imaging systems and their coincidence periodically on two TrueBeam linacs for about one year. Both systems analyze kV or MV projection images of special designed phantoms to retrieve geometric parameters of the imaging systems. The isocenters ­ laser isocenter and centers of rotations of kV imager and EPID ­ are then calculated, based on results of multiple projections from different angles. Long-term calibration results from both systems are compared for cross-checking. There are 24 sessions of side-by-side calibrations performed by both systems on two TrueBeam linacs. All the disagreements of isocenters between two calibrations systems are less than 1 mm with ± 0.1 mm SD. Most of the large disagreements occurred in vertical direction (AP direction), with an averaged disagreement of 0.45 mm. The average disagreements of isocenters are 0.09 mm in other directions. Additional to long-term calibration monitoring, for the accuracy test, special tests were performed by misaligning QA phantoms on purpose (5 mm away from setup isocenter in AP, SI, and lateral directions) to test the liability performance of both systems with the known deviations. The errors are within 0.5 mm. Both geometric calibration systems, IsoCal and gQA, are capable of detecting geometric deviations of kV and MV imaging systems of linacs. The long-term evaluation also shows that the deviations of geometric parameters and the geometric accuracies of both linacs are small and very consistent during the one-year study period.

An accurate algorithm to match imperfectly matched images for lung tumor detection without markers.

In order to locate lung tumors on kV projection images without internal markers, digitally reconstructed radiographs (DRRs) are created and compared with projection images. However, lung tumors always move due to respiration and their locations change on projection images while they are static on DRRs. In addition, global image intensity discrepancies exist between DRRs and projections due to their different image orientations, scattering, and noises. This adversely affects comparison accuracy. A simple but efficient comparison algorithm is reported to match imperfectly matched projection images and DRRs. The kV projection images were matched with different DRRs in two steps. Preprocessing was performed in advance to generate two sets of DRRs. The tumors were removed from the planning 3D CT for a single phase of planning 4D CT images using planning contours of tumors. DRRs of background and DRRs of tumors were generated separately for every projection angle. The first step was to match projection images with DRRs of background signals. This method divided global images into a matrix of small tiles and similarities were evaluated by calculating normalized cross-correlation (NCC) between corresponding tiles on projections and DRRs. The tile configuration (tile locations) was automatically optimized to keep the tumor within a single projection tile that had a bad matching with the corresponding DRR tile. A pixel-based linear transformation was determined by linear interpolations of tile transformation results obtained during tile matching. The background DRRs were transformed to the projection image level and subtracted from it. The resulting subtracted image now contained only the tumor. The second step was to register DRRs of tumors to the subtracted image to locate the tumor. This method was successfully applied to kV fluoro images (about 1000 images) acquired on a Vero (BrainLAB) for dynamic tumor tracking on phantom studies. Radiation opaque markers were implanted and used as ground truth for tumor positions. Although other organs and bony structures introduced strong signals superimposed on tumors at some angles, this method accurately located tumors on every projection over 12 gantry angles. The maximum error was less than 2.2 mm, while the total average error was less than 0.9mm. This algorithm was capable of detecting tumors without markers, despite strong background signals.

Coke workers' exposure to volatile organic compounds in northern China: a case study in Shanxi Province.

China is the largest coke producer and exporter in the world, and it has been a major concern that large populations of coke workers are exposed to the associated air pollutants such as volatile organic compounds (VOCs). This study aimed to preliminarily quantify the potential exposure to VOCs emitted from two representative coking plants and assess the potential health risks. Air samples from various stages of coking were collected from the topside of coke ovens and various plant areas and then analyzed for benzene, toluene, ethylbenzene, and xylene (BTEX). The time-weighted average (TWA) concentrations were used to quantify the coke oven emission (COE). The TWA concentrations for benzene were 705.6 and 290.4 µg m(-3) in plant A and plant B, respectively, which showed a higher exposure level than those reported in other countries. COE varied on the topside of coke ovens during charging and pushing processes, from 268.3 to 1197.7 µg m(-3) in plant A and 85.4-489.7 µg m(-3) in plant B. Our results indicate that benzene exposure from the diffusion of tar distillation also exerts significant health risks and thus should also be concerned. Charging and pushing activities accounted for nearly 70 % of benzene dose at the topside, and the benzene exposure risks to the coke oven workers in China were higher than those reported by US EPA. Compared to the reported emission sources, the weight-based ratios of average benzene to toluene, ethylbenzene, and xylene in different COE air samples showed unique characteristic profiles. Based on the B/T ratios from this work and from literatures on several major cities in northern China, it was evident that COE contributes significantly to the severe pollution of VOCs in the air of northern China. Future more rigorous studies are warranted to characterize VOC emission profiles in the stack gas of the coking processes in China.

Analyzing ozone formation sensitivity in a typical industrial city in China: Implications for effective source control in the chemical transition regime.

Volatile organic compounds (VOCs) play a major role in O3 formation in urban environments. However, the complexity in the emissions of VOCs and nitrogen oxides (NOx) in industrial cities has made it challenging to identify the key factors influencing O3 formation. This study used observation-based-model (OBM) to analyze O3 sensitivities to VOCs and NOx during summer in a typical industrial city in China. The OBM model results were coupled with a receptor model to analyze the sources of O3. Higher concentrations of O3 precursors were observed during polluted periods indicating that precursor accumulation contributed to the higher maxima of the net ozone formation rate and HOx concentrations. Analyses of ROx· budgets and relative incremental reactivity (RIR) indicated that O3 production is in a chemical transition regime and was sensitive to both VOCs and NOx. Results from Positive Matrix Factorization (PMF) analysis indicated that gasoline vehicle emissions, industrial processes, and coal combustion were major sources of O3 precursors. The sensitivities of O3 production to these sources depend on if both VOC and NOx sensitivities are considered. If only VOCs sensitivity is considered, in contrast, the contribution of anthropogenic sources to O3 production was significantly underestimated. This study highlights the importance of accounting for both VOCs and NOx sensitivities when O3 chemistry is in a transition regime in O3 production attribution studies.

ART2Dose: A comprehensive dose verification platform for online adaptive radiotherapy.

BACKGROUND: Online adaptive radiotherapy (ART) involves the development of adaptable treatment plans that consider patient anatomical data obtained right prior to treatment administration, facilitated by cone-beam computed tomography guided adaptive radiotherapy (CTgART) and magnetic resonance image-guided adaptive radiotherapy (MRgART). To ensure accuracy of these adaptive plans, it is crucial to conduct calculation-based checks and independent verification of volumetric dose distribution, as measurement-based checks are not practical within online workflows. However, the absence of comprehensive, efficient, and highly integrated commercial software for secondary dose verification can impede the time-sensitive nature of online ART procedures. PURPOSE: The main aim of this study is to introduce an efficient online quality assurance (QA) platform for online ART, and subsequently evaluate it on Ethos and Unity treatment delivery systems in our clinic. METHODS: To enhance efficiency and ensure compliance with safety standards in online ART, ART2Dose, a secondary dose verification software, has been developed and integrated into our online QA workflow. This implementation spans all online ART treatments at our institution. The ART2Dose infrastructure comprises four key components: an SQLite database, a dose calculation server, a report generator, and a web portal. Through this infrastructure, file transfer, dose calculation, report generation, and report approval/archival are seamlessly managed, minimizing the need for user input when exporting RT DICOM files and approving the generated QA report. ART2Dose was compared with Mobius3D in pre-clinical evaluations on secondary dose verification for 40 adaptive plans. Additionally, a retrospective investigation was conducted utilizing 1302 CTgART fractions from ten treatment sites and 1278 MRgART fractions from seven treatment sites to evaluate the practical accuracy and efficiency of ART2Dose in routine clinical use. RESULTS: With dedicated infrastructure and an integrated workflow, ART2Dose achieved gamma passing rates that were comparable to or higher than those of Mobius3D. Additionally, it significantly reduced the time required to complete pre-treatment checks by 3-4 min for each plan. In the retrospective analysis of clinical CTgART and MRgART fractions, ART2Dose demonstrated average gamma passing rates of 99.61 ± 0.83% and 97.75 ± 2.54%, respectively, using the 3%/2 mm criteria for region greater than 10% of prescription dose. The average calculation times for CTgART and MRgART were approximately 1 and 2 min, respectively. CONCLUSION: Overall, the streamlined implementation of ART2Dose notably enhances the online ART workflow, offering reliable and efficient online QA while reducing time pressure in the clinic and minimizing labor-intensive work.

Impact of primary emission variations on secondary inorganic aerosol formation: Prospective from COVID-19 lockdown in a typical northern China city.

Hourly observations in northern China city of Taiyuan were performed to compare secondary inorganic aerosol (SIA) reaction mechanisms, and emission effects on SIA during the pre-lock and COVID-19 lock days. Emission control implemented and meteorological conditions during lock days both caused beneficial impact on air quality. NO2 showed the highest decrease ratio of -49.5%, while the relative fraction of NO3- in PM2.5 increased the most (2.7%). Source apportionment revealed the top three contributors to PM2.5 were secondary formation (SF), coal combustion (CC), and vehicle exhaust (VE) during both pre-lock and lock days. EC lock/pre were all lower than 1, suggesting the overall reduction of primary emissions during lock days, while the higher ratio of (SIA/EC) lock/pre (1.01-1.36) indicated the enhanced secondary formation in lock days. The ratio of SIA of pollution to clean days during lock periods considerably higher by 23.7% compared with that in pre-lock periods, which was indicated SIA secondary formation was more pronounced and contributed great to pollution days in lock periods though secondary formation existed in pre-lock and lock periods. Enhanced secondary formation of NO3- and SO42- during lock days might be mainly due to the increased in aqueous and gas-phase reactions, respectively. Except for SF, high contribution of VE and CC were also important for high SIA concentration in pre-lock and lock days, respectively. The decreased contribution of VE weakens its contribution to SIA formation, indicating the effectiveness of VE emission control, as confirmed during the COVID-19 pandemic. This study highlights the aqueous and gas-phase reactions for nitrate and sulfate, respectively, which contributed to heavy pollution, as well as indicated the important role of VE on SIA formation, suggesting the urgent need to further strengthen controls on vehicle emissions.

Comparison of the Mechanical Properties and Crack Expansion Mechanism of Different Content and Shapes of Brass-Coated Steel Fiber-Reinforced Ultra-High-Performance Concrete.

Steel fiber-reinforced ultra-high-performance concrete (UHPC) is becoming an important type of concrete reinforcement. After mixing with the reinforced steel fibers, the UHPC has perfect flex resistance, shear strength, crack resistance, shock resistance, and anti-seepage. In this study, the influence of straight, corrugated, and hooked brass-coated steel fibers (BCSFs) on the microstructure, mechanical properties, and crack expansion mechanism of ultra-high-performance concrete (UHPC) with varying content of 1-6 wt.% under different curing times were investigated. Field emission scanning electron microscopy and energy dispersive X-ray spectrometry were employed to characterize the microstructure of the BCSF-reinforced UHPC mix specimens. X-ray computed tomography was employed to determine the porosity of the BCSF-reinforced UHPC mix specimens. The obtained results indicate the flexural strength and compressive strength of BCSF-reinforced UHPC mix specimens are enhanced, along with increasing the content of BCSFs reinforcement with different shapes (straight, corrugated, and hooked). The embedded BCSFs play a major role in the adhesive property and stress transfer of the BCSFs-UHPC matrix interface. Different from many studies, the flexural strength of mix UHPC with straight BCSFs is higher than those with corrugated and hooked BCSFs. However, the compressive strength of UHPC with corrugated BCSFs is higher than those with straight and hooked BCSFs. The flexural strength of mix UHPC with 6 wt.% straight BCSFs at 28 days reaches the maximum value of 26.2 MPa, and the compressive strength of UHPC with 6 wt.% corrugated BCSFs at 28 days reaches the maximum value of 142.3 MPa. With the increase in straight BCSF content from 1 wt.% to 6 wt.%, the porosity in mix UHPC reduces gradually from 18.4% to 8.3%. The length of average crack spacing is dependent on the straight BCSF content. With the increase in straight BCSF content from 1 wt.% to 6 wt.%, the average crack length reduces gradually from 34.2 mm to 12.1 mm, and the average crack width reduces gradually from 0.78 mm to less than 0.1 mm. During crack extension, part of the energy in the UHPC mixture specimen with the 6 wt.% BCSF content flows into the crack tip region converted into the work dissipated during the bridging process. The crack propagation resistance of the UHPC mixture with straight BCSFs was improved compared with those with corrugated and hooked BCSFs. The bond strength between the BCSFs and UHPC matrix was enhanced by using vibrational mixing, and the brass film coated on the BCSFs contributes to increase the flexural and compressive strength of the UHPC mixture.

Decomposition and humification process of domestic biodegradable waste by black soldier fly (Hermetia illucens L.) larvae from the perspective of dissolved organic matter.

Black soldier fly larvae (Hermitia illucens L.) (BSFL) bioconversion is a promising technology for domestic biodegradable waste (DBW) management and resource recovery. However, little is known about the DBW biodegradation during the BSFL bioconversion from the perspective of dissolved organic matter (DOM). In the current study, field tests were conducted on a full-scale BSFL bioconversion facility with treatment capacity of 15 tons DBW/day. Composition of DOM in DBW were investigated by spectral analysis (UV-vis, fluorescence, and Fourier Transform Infrared spectroscopy (FT-IR)), coupled with enzyme activity analysis. After BSFL bioconversion, DOM concentrations, total carbon and total nitrogen in residues decreased by 51.5%, 18.3% and 19.9%, respectively. Meanwhile, enzymes like catalase, lipase, protease, sucrase, urease and cellulase significantly increased (9.28%-56.3%). The specific UV absorbance at 254 nm and 280 nm (SUVA254, SUVA280), the area at 226-400 nm (A226-400) and slope in the 280-400 nm region (S280-400) of DOM increased by 230%, 186%, 143% and 398%, respectively. Moreover, the characteristic peaks at 1636, 1077 and 1045 cm-1 in FT-IR increased continuously, with a significant decrease in peak at 1124 and 1572 cm-1. DOM spectral data show that BSFL decomposed the carboxylic, cellulose and aliphatic components, resulting in the increase of oxygen-containing functional groups (e.g., hydroxyl, carboxyl, carbonyl) and aromatic compounds. Furthermore, fluorescence profiles show that Region Ⅰ, Ⅱ (aromatic proteins) and Ⅳ (soluble microbial byproducts) decreased while Region Ⅴ (humic-like substances) increased significantly. Humification index increased by 122% while biological index decreased by 18.0%, indicating a significant increase in degree of humification and stabilization of the residues. The current evidence provides a theoretical basis for technical re-innovation and improving economic potential of BSFL technology.

Effect of Hollow 304 Stainless Steel Fiber on Corrosion Resistance and Mechanical Properties of Ultra-High Performance Concrete (UHPC).

This study investigated the effect of hollow 304 stainless-steel fiber on the corrosion resistance and mechanical properties of ultra-high-performance concrete (UHPC), and prepared copper-coated-fiber-reinforced UHPC as the control group. The electrochemical performance of the prepared UHPC was compared with the results of X-ray computed tomography (X-CT). The results reveal that cavitation can improve the distribution of steel fibers in the UHPC. Compared with solid steel fibers, the compressive strength of UHPC with hollow stainless-steel fibers did not exhibit significant change, but the maximum flexural strength increased by 45.2% (2 vol% content, length-diameter ratio of 60). Hollow stainless-steel fiber could better improve the durability of UHPC compared with copper-plated steel fiber, and the gap between the two continued to increase as the durability test progressed. After the dry-wet cycle test, the flexural strength of the copper-coated-fiber-reinforced UHPC was 26 MPa, marking a decrease of 21.9%, while the flexural strength of the UHPC mixed with hollow stainless-steel fibers was 40.1 MPa, marking a decrease of only 5.6%. When the salt spray test had run for seven days, the difference in the flexural strength between the two was 18.4%, but when the test ended (180 days), the difference increased to 34%. The electrochemical performance of the hollow stainless-steel fiber improved, owing to the small carrying capacity of the hollow structure, and more uniform distribution in the UHPC and lower interconnection probability were achieved. According to the AC impedance test results, the charge transfer impedance of the UHPC doped with solid steel fiber is 5.8 KΩ, while that of the UHPC doped with hollow stainless-steel fiber is 8.8 KΩ.

Modeling gamma knife radiosurgical toxicity for multiple brain metastases.

BACKGROUND AND PURPOSE: Radiation oncology protocols for single fraction radiosurgery recommend setting dosing criteria based on assumed risk of radionecrosis, which can be predicted by the 12 Gy normal brain volume (V12). In this study, we show that tumor surface area (SA) and a simple power-law model using only preplan variables can estimate and minimize radiosurgical toxicity. MATERIALS AND METHODS: A 245-patient cohort with 1217 brain metastases treated with single or distributed Gamma Knife sessions was reviewed retrospectively. Univariate and multivariable linear regression models and power-law models determined which modeling parameters best predicted V12. The V12 power-law model, represented by a product of normalized Rx dose Rxn, and tumor longest axial dimension LAD (V12 âˆ¼ Rxn1.5*LAD2), was independently validated using a secondary 63-patient cohort with 302 brain metastases. RESULTS: Surface area was the best univariate linear predictor of V12 (adjR2 = 0.770), followed by longest axial dimension (adjR2 = 0.755) and volume (adjR2 = 0.745). The power-law model accounted for 90% variance in V12 for 1217 metastatic lesions (adjR2 = 0.906) and 245 patients (adjR2 = 0.896). The average difference ΔV12 between predicted and measured V12s was (0.28 ± 0.55) cm3 per lesion and (1.0 ± 1.2) cm3 per patient. The power-law predictive capability was validated using a secondary 63-patient dataset (adjR2 = 0.867) with 302 brain metastases (adjR2 = 0.825). CONCLUSION: Surface area was the most accurate univariate predictor of V12 for metastatic lesions. We developed a preplan model for brain metastases that can help better estimate radionecrosis risk, determine prescription doses given a target V12, and provide safe dose escalation strategies without the use of any planning software.

[Revealing Driving Factors of Urban O3 Based on Explainable Machine Learning].

Driven by precursor emissions, meteorological conditions, and other factors, atmospheric ozone (O3) has become the main pollutant affecting urban air quality in summer. The current deductive models driven by physical and chemical mechanisms require a large number of parameters for the analysis of O3 pollution, and the calculation timeliness is poor. The data-driven inductive models are efficient but have problems such as poor explanation. In this study, an explainable model of data-driven Correlation-ML-SHAP was established to reveal the strongly correlated influencing factors of O3 concentration. Additionally, the machine learning ML module coupled with the explainable SHAP module was used to calculate the contributions of driving factors to O3 concentration, so as to realize the quantitative analysis of driving factors. The O3 pollution process in the summer of 2021 in Jincheng City was used as an example to carry out the application research. The results showed that the Correlation-ML-SHAP model could reveal and use strong driving factors to simulate O3 concentration and quantify influence contribution, and the ML module used the XGBoost model to achieve the best simulation accuracy. Air temperature, solar radiation, relative humidity, and precursor emission level were the strong driving factors of O3 pollution in Jincheng City in summer 2021, and the contribution weights were 32.1%, 21.3%, 16.5%, and 15.6%. The contribution weights of air temperature, solar radiation, and precursor emission level increased by 3.4%, 1.2%, and 1.2% on polluted days, respectively, and the contribution weights of precursor emission level rose to third place on polluted days. Each driving factor had a nonlinear interaction effect on O3 concentration. When the air temperature exceeded 24℃, or the relative humidity was lower than 70%, there was a 94.9% and 94.1% probability of positive contribution to O3 pollution, respectively. Under such meteorological conditions, ρ(NO2) exceeded 9 µg·m-3, or ρ(CO) exceeded 0.7 mg·m-3, and there was a 94.9% and 99.3% probability of positive contribution to O3 pollution, respectively. The southeast wind speed was lower than 5.8 m·s-1, or the south wind speed was lower than 5.3 m·s-1, both of which contributed positively to O3 pollution. The model quantitatively analyzed the influence contribution of various driving factors on urban O3 concentration, which could provide a basis for the prevention and control of urban atmospheric O3 pollution in summer.

Ensemble learning and personalized training for the improvement of unsupervised deep learning-based synthetic CT reconstruction.

BACKGROUND: The growing adoption of magnetic resonance imaging (MRI)-guided radiation therapy (RT) platforms and a focus on MRI-only RT workflows have brought the technical challenge of synthetic computed tomography (sCT) reconstruction to the forefront. Unpaired-data deep learning-based approaches to the problem offer the attractive characteristic of not requiring paired training data, but the gap between paired- and unpaired-data results can be limiting. PURPOSE: We present two distinct approaches aimed at improving unpaired-data sCT reconstruction results: a cascade ensemble that combines multiple models and a personalized training strategy originally designed for the paired-data setting. METHODS: Comparisons are made between the following models: (1) the paired-data fully convolutional DenseNet (FCDN), (2) the FCDN with the Intentional Deep Overfit Learning (IDOL) personalized training strategy, (3) the unpaired-data CycleGAN, (4) the CycleGAN with the IDOL training strategy, and (5) the CycleGAN as an intermediate model in a cascade ensemble approach. Evaluation of the various models over 25 total patients is carried out using a five-fold cross-validation scheme, with the patient-specific IDOL models being trained for the five patients of fold 3, chosen at random. RESULTS: In both the paired- and unpaired-data settings, adopting the IDOL training strategy led to improvements in the mean absolute error (MAE) between true CT images and sCT outputs within the body contour (mean improvement, paired- and unpaired-data approaches, respectively: 38%, 9%) and in regions of bone (52%, 5%), the peak signal-to-noise ratio (PSNR; 15%, 7%), and the structural similarity index (SSIM; 6%, <1%). The ensemble approach offered additional benefits over the IDOL approach in all three metrics (mean improvement over unpaired-data approach in fold 3; MAE: 20%; bone MAE: 16%; PSNR: 10%; SSIM: 2%), and differences in body MAE between the ensemble approach and the paired-data approach are statistically insignificant. CONCLUSIONS: We have demonstrated that both a cascade ensemble approach and a personalized training strategy designed initially for the paired-data setting offer significant improvements in image quality metrics for the unpaired-data sCT reconstruction task. Closing the gap between paired- and unpaired-data approaches is a step toward fully enabling these powerful and attractive unpaired-data frameworks.

Preliminary Evaluation of PTV Margins for Online Adaptive Radiation Therapy of the Prostatic Fossa.

PURPOSE: In modern trials, traditional planning target volume (PTV) margins for postoperative prostate radiation therapy have been large (7-10 mm) to account for both daily changes in patient positioning and target deformation. With daily adaptive radiation therapy, these interfractional changes could be minimized, potentially reducing the margins required for treatment and improving adjacent normal-tissue dosimetry. METHODS AND MATERIALS: A single-center retrospective study was conducted from March 2021 to November 2021. Patients receiving conventionally fractionated postoperative radiation therapy (PORT) for prostate cancer with pretreatment and posttreatment cone beam computed tomography (CBCT) imaging (pre-CBCT and post-CBCT, respectively) were included (248 paired images). Pretreatment and posttreatment clinical target volumes (pre-CTVs and post-CTVs) were contoured by a single observer on all CBCTs and verified by a second observer. Motion was calculated from pre-CTV to that of the post-CTV, and predicted margins were calculated with van Herk's formula. Adequate coverage of the proposed planning target volume (PTV) margin expansions (pre-PTV) were verified by determining overlap with post-CTV. In a smaller cohort (25 paired images), dosimetric changes with the proposed online adaptive margins were compared with conventional plans in the Ethos emulator environment. RESULTS: The estimated margins predicted to achieve ≥95% CTV coverage for 90% of the population were 1.6 mm, 2.0 mm, and 2.2 mm (x-, y-, and z -xes, respectively), with 95% of the absolute region of interest displacement being within 1.9 mm, 2.8 mm, and 2.1 mm. After symmetrically expanding all pre-CTVs by 3 mm, the percentage of paired images achieving ≥95% CTV coverage was 97.1%. When comparing adaptive plans (3-mm margins) with scheduled plans (7-mm margins), rectum dosimetry significantly improved, with an average relative reduction in V40Gy[cc] of 59.2% and V65Gy[cc] of 79.5% (where V40Gy and V65Gy are defined as the volumes receiving 40 Gy and 65 Gy or higher dose, respectively). CONCLUSIONS: Online daily adaptive radiation therapy could significantly decrease PTV margins for prostatic PORT and improve rectal dosimetry, with a symmetrical expansion of 3 mm achieving excellent coverage in this cohort. These results need to be validated in a larger prospective cohort.

Bony structure enhanced synthetic CT generation using Dixon sequences for pelvis MR-only radiotherapy.

BACKGROUND: MRI-only radiotherapy planning (MROP) is beneficial to patients by avoiding MRI/CT registration errors, simplifying the radiation treatment simulation workflow and reducing exposure to ionizing radiation. MRI is the primary imaging modality for soft tissue delineation. Treatment planning CTs (i.e., CT simulation scan) are redundant if a synthetic CT (sCT) can be generated from the MRI to provide the patient positioning and electron density information. Unsupervised deep learning (DL) models like CycleGAN are widely used in MR-to-sCT conversion, when paired patient CT and MR image datasets are not available for model training. However, compared to supervised DL models, they cannot guarantee anatomic consistency, especially around bone. PURPOSE: The purpose of this work was to improve the sCT accuracy generated from MRI around bone for MROP. METHODS: To generate more reliable bony structures on sCT images, we proposed to add bony structure constraints in the unsupervised CycleGAN model's loss function and leverage Dixon constructed fat and in-phase (IP) MR images. Dixon images provide better bone contrast than T2-weighted images as inputs to a modified multi-channel CycleGAN. A private dataset with a total of 31 prostate cancer patients were used for training (20) and testing (11). RESULTS: We compared model performance with and without bony structure constraints using single- and multi-channel inputs. Among all the models, multi-channel CycleGAN with bony structure constraints had the lowest mean absolute error, both inside the bone and whole body (50.7 and 145.2 HU). This approach also resulted in the highest Dice similarity coefficient (0.88) of all bony structures compared with the planning CT. CONCLUSION: Modified multi-channel CycleGAN with bony structure constraints, taking Dixon-constructed fat and IP images as inputs, can generate clinically suitable sCT images in both bone and soft tissue. The generated sCT images have the potential to be used for accurate dose calculation and patient positioning in MROP radiation therapy.

Effects of regional transport from different potential pollution areas on volatile organic compounds (VOCs) in Northern Beijing during non-heating and heating periods.

Despite the adoption of air quality control measures, the influence of regional transport on volatile organic compounds (VOCs) pollution has gradually increased in Beijing. In this study, the whole observation period (September 24 to December 12, 2020) was divided into heating period and non-heating period to explore the impact of changing VOCs sources in different observation periods, and also classified into "Type-N" and "Type-S" periods both in non-heating period and heating period to explore the impact of regional transport from the northern and southern regions of sampling site, respectively. The average VOCs concentrations in northern Beijing during observation period were 22.6 ± 12.6 ppbv, which showed a decrease trend in recent years compared with other studies. And higher VOCs concentrations were observed in Type-S than in Type-N period. The positive matrix factorization results showed that vehicular exhaust dominated VOCs (26.1%-33.7%), but coal combustion could not be ignored in heating period, when it was twice that in non-heating period. In particular, coal combustion dominated VOCs in southern trajectories (30.9%) in heating period. The analysis of concentration weighted trajectory showed that coal combustion was affected by regional transport from the southeast regions of Beijing, while vehicular exhaust was affected by urban and the southeast regions of Beijing. Regarding human health risks, the carcinogenic risks of benzene and ethylbenzene exceeded the acceptable cancer risk value (1 × 10-6), and were higher in Type-S than in Type-N period. The results indicated that regional transport from urban areas and the areas south of Beijing had a significant impact on VOCs in northern Beijing. Thus, targeted control measures for different potential pollution regions are important for controlling VOCs pollution in Beijing.