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Accurate water content detection is crucial for optimizing chemical reactions, ensuring product quality in pharmaceutical manufacturing, and maintaining food safety. In this study, nitrogen and sulfur co-doped graphene quantum dots (R-GQDs) were synthesized via a one-step hydrothermal method using o-phenylenediamine as the carbon source. The synthesis conditions, including reaction time, temperature, o-phenylenediamine concentration, and H2SO4/water ratio, were optimized using the Box-Behnken response surface methodology. The R-GQDs exhibited excellent fluorescence stability and distinct solvent-dependent characteristics, alongside a broad linear detection range and high sensitivity, making them highly suitable for dual-mode water content detection (colorimetric and fluorescent). To enhance the accuracy of visual detection, R-GQDs were incorporated into portable test strips with smartphone-assisted analysis, compensating for the human eye’s limitations in distinguishing subtle color changes. The sensor’s practical utility was validated through spiked recovery experiments in food samples, and the R-GQDs demonstrated good biocompatibility for in vivo imaging in shrimp. These findings highlight a novel strategy for developing portable, real-time water content sensors with potential applications in both portable detection systems and biological imaging.

Abstract Purpose To investigate the feasibility and performance of deep learning (DL) models combined with plan complexity (PC) and dosiomics features in the patient-specific quality assurance (PSQA) for patients underwent volumetric modulated arc therapy (VMAT). Methods Total of 201 VMAT plans with measured PSQA results were retrospectively enrolled and divided into training and testing sets randomly at 7:3. PC metrics were calculated using house-built algorithm based on Matlab. Dosiomics features were extracted and selected using Random Forest (RF) from planning target volume (PTV) and overlap regions with 3D dose distributions. The top 50 dosiomics and 5 PC features were selected based on feature importance screening. A DL DenseNet was adapted and trained for the PSQA prediction. Results The measured average gamma passing rate (GPR) of these VMAT plans was 97.94% ± 1.87%, 94.33% ± 3.22%, and 87.27% ± 4.81% at the criteria of 3%/3 mm, 3%/2 mm, and 2%/2 mm, respectively. Models with PC features alone demonstrated the lowest area under curve (AUC). The AUC and sensitivity of PC and dosiomics (D) combined model at 2%/2 mm were 0.915 and 0.833, respectively. The AUCs of DL models were improved from 0.943, 0.849, 0.841 to 0.948, 0.890, 0.942 in the combined models (PC + D + DL) at 3%/3 mm, 3%/2 mm and 2%/2 mm, respectively. A best AUC of 0.942 with a sensitivity, specificity and accuracy of 100%, 81.8%, and 83.6% was achieved with combined model (PC + D + DL) at 2%/2 mm. Conclusions Integrating DL with dosiomics and PC metrics is promising in the prediction of GPRs in PSQA for patients underwent VMAT.

Scanning electrochemical microscopy (SECM) is a scanning probe technology based on Faraday current changes when an ultramicroelectrode is moved across a sample surface, which can directly reflect the surface topography and electrochemical information on the sample through imaging. This Review briefly introduces the basic SECM, including its developmental history and working mode. The application of SECM imaging in energy catalysis is mainly introduced, and the development trend of SECM is described briefly.

A 3-year-old girl with a chief complaint of lower urinary tract symptoms (LUTS) for 3 years was admitted in our center. Urinary ultrasonography showed left hydronephrosis with ureteral dilatation and left solitary kidney. Voiding cystourethrography indicated left vesicoureteral reflux and trabeculated bladder wall. Urodynamics study revealed the low flow rate and high detrusor pressure. Cystoscopy showed trabeculated bladder wall with elevation of the bladder neck. Then we performed transurethral bladder neck incision tentatively. The patient recovered from LUTS and the upper urinary tract dilation disappeared postoperatively.

The discovery of single-atom catalysts (SACs) represents a groundbreaking advancement in the field of catalysis over the past decades. With the in-depth exploration of relevant structure-activity relationships, the metal-support interaction (MSI) is widely adopted to elucidate variations in electronic structure and coordination configuration of atomic active sites on various kinds of supports. Herein, we briefly summarize the metal oxide supports for SACs fabrication, including the distinctive characteristics of metal oxide supports, enlightening advancements in metal oxide support-based SACs (MO-SACs), feasible preparation methods for MO-SACs and effective regulation strategies of MSI effect in MO-SACs. In addition, we present our viewpoints and outlook in this field to stimulate rational design and construction of novel MO-SACs applied in diverse renewable energy devices, while some universal suggestions are sincerely given to provoke thoughtful considerations during the research process. [ABSTRACT FROM AUTHOR]

ObjectiveThe objective of this study is to introduce a novel technique of robotic-assisted laparoscopic pyeloplasty (RALP) for ureteropelvic junction obstruction (UPJO) with long proximal ureteral stricture in children.Materials and methodsClinical information on patients who underwent a modified RALP between July 2018 and May 2019 in our center was collected retrospectively. Our surgical modifications mainly include “double-flap” tailoring of the renal pelvis and anastomosis of spatulate ureter with the double-flap. Demographic, perioperative, postoperative, and follow-up information was recorded in detail.ResultsA total of 13 patients were included in the study. All the patients underwent a modified RALP without conversion to open surgery. They were followed up with a median time of 36 months. The anteroposterior diameter of the renal pelvis was 1.19 ± 0.21 at 6 months after the surgery, which was significantly lower than that on admission (3.93 ± 0.79). The split renal function of the children was also significantly improved from 0.37 ± 0.05) to 0.46 ± 0.02 at 6 months after surgery (p < 0.05). The diuretic renography revealed that all the patients have a T1/2 time less than 20 min postoperatively. The children were in good condition during the follow-up period.ConclusionsModified RALP is an effective surgical treatment for children with UPJO with long proximal ureteral stricture. The success rate of this modification has been preliminarily confirmed.

Abstract Objective To research and assess automatic volumetric modulated arc therapy (VMAT) planning methods for patients with intraocular cancer. Methods The mdaccAutoPlan system was added to the Pinnacle3 treatment planning system as a plug‐in. Automatic VMAT plans were generated for 10 patients diagnosed with intraocular cancer, and evaluated according to standard dose‐volume histogram parameters. Results The planning target volume of enrolled patients ranges from 14.24 to 50.69 cm3. Both planning methods lead to acceptable planning target volume target coverage with a V95 of 97.9 ± 1.4% and 96.4 ± 1.5% for manual and automatic plans (P = 0.03), respectively. Automatic planning lowered the dose delivered to the ipsilateral lens and optical nerves, but increased the dose to the brainstem compared with manual planning. Automatic planning significantly prolonged VMAT planning time (3.25 ± 0.53 h vs. 1.02 ± 0.69 h, P

While water-splitting affords a renewable means to store energy, expensive catalysts are often required to achieve high performances. Here, authors modulate nickel-vanadium double hydroxide properties by noble-metal doping to accelerate electrocatalytic water splitting kinetics.

The development of low-cost, high-efficiency, and stable bifunctional electrocatalysts toward the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is of paramount importance for large-scale water splitting. Here, we develop a new strategy for the first design and synthesis of a NiO@Ni decorated WS2 nanosheet array on carbon cloth (NiO@Ni/WS2/CC) composite. This composite serves as a unique three-dimensional (3D) synergistic electrocatalyst that not only combines the intrinsic properties of individual NiO@Ni and WS2, but also exhibits significantly improved HER and OER activities when compared to that of pure NiO@Ni and WS2. This electrocatalyst possesses Pt-like activity for HER and exhibits better OER performance than that for commercial RuO2, as well as demonstrating superior long-term durability in alkaline media. Furthermore, it enables an alkaline electrolyzer with a current density of 10 mA cm–2 at a cell voltage as 1.42 V, which is the lowest one among all reported values to date. The excellent performance is mainly attributed to the unique 3D configuration and multicomponent synergies among NiO, Ni, and WS2. Our findings provide a new idea to design advanced bifunctional catalysts for water splitting.

Abstract Objective The purpose of this study is to investigate the dosimetric advantages of volumetric modulated arc therapy (VMAT) in the treatment of intraocular cancer by comparing it directly with three-dimensional conformal radiotherapy (CRT) and intensity-modulated radiotherapy (IMRT). Methods CRT plan, 7f-IMRT plan, and one-arc VMAT plan were generated for 14 intraocular cancer patients. Dosimetric and biological quality indices for target volume and organs at risks (OARs) were evaluated and compared. Results The target coverage presented by V95 for CRT, IMRT and VMAT were 95.02% ± 0.67%, 95.51% ± 2.25%, and 95.92% ± 3.05%, respectively. The homogeneity index (HI) for CRT, IMRT and VMAT were 0.15 ± 0.05, 0.23 ± 0.05, and 0.23 ± 0.06, respectively. IMRT and VMAT greatly decreased the dose to ipsilateral lens compared with CRT with a D1 of 2972.66 ± 1407.12 cGy, 3317.82 ± 915.28 cGy and 4809.54 ± 524.60 cGy for IMRT, VMAT and CRT, respectively. Similar results were observed for ipsilateral eyeballs. IMRT and VMAT also spared better on brainstem, optical nerves and optical chiasm compared CRT. However, CRT achieved lower dose to the eyeballs compared with IMRT and VMAT. VMAT and IMRT showed mixed results on target coverage and OAR sparing. The average MUs and delivery time of IMRT and VMAT were 531.25 ± 81.21 vs. 400.99 ± 61.49 and 5.05 ± 0.53 vs.1.71 ± 0.69 min, respectively. Conclusions Although no clear distinction on PTV coverage among CRT, IMRT and VMAT plans was observed in the treatment of intraocular cancer, VMAT and IMRT achieved better homogeneity and conformity for target volume, and delivered fewer doses to ipsilateral lens and eyeballs compared with CRT. However, VMAT and IMRT increased the low dose volume to the contralateral OARs. Although VMAT and IMRT showed mixed results on target coverage and OAR sparing, VMAT decreased MU and delivery time significantly compared with IMRT. VMAT is a promising and feasible external beam radiotherapy technique in the treatment of intraocular cancer patients.

Seismic events prediction is a crucial task for preventing coal mine rock burst hazards. Currently, this task attracts increasing research enthusiasms from many mining experts. Considering the temporal characteristics of monitoring data, seismic events prediction can be abstracted as a time series prediction task. This paper contributes to address the problem of long-term historical dependence on seismic time series prediction with deep temporal convolution neural networks (CNN). We propose a dilated causal temporal convolution network (DCTCNN) and a CNN long short-term memory hybrid model (CNN-LSTM) to forecast seismic events. In particular, DCTCNN is designed with dilated CNN kernels, causal strategy, and residual connections; CNN-LSTM is established in a hybrid modeling way by utilizing advantage of CNN and LSTM. Based on these manners, both of DCTCNN and CNN-LSTM can extract long-term historical features from the monitoring seismic data. The proposed models are experimentally tested on two real-life coal mine seismic datasets. Furthermore, they are also compared with one traditional time series prediction method, two classic machine learning algorithms, and two standard deep learning networks. Results show that DCTCNN and CNN-LSTM are superior than the other five algorithms, and they successfully complete the seismic prediction task.

Tool wear monitoring is necessary for cost reduction and productivity improvement in the machining industry. Machine learning has been proven to be an effective means of tool wear monitoring. Feature engineering is the core of the machining learning model. In complex parts milling, cutting conditions are time-varying due to the variable engagement between cutting tool and the complex geometric features of the workpiece. In such cases, the features for accurate tool wear monitoring are tricky to select. Besides, usually few sensors are available in an actual machining situation. This causes a high correlation between the hand-designed features, leading to the low accuracy and weak generalization ability of the machine learning model. This paper presents a tool wear monitoring method for complex part milling based on deep learning. The features are pre-selected based on cutting force model and wavelet packet decomposition. The pre-selected cutting forces, cutting vibration and cutting condition features are input to a deep autoencoder for dimension reduction. Then, a deep multi-layer perceptron is developed to estimate the tool wear. The dataset is obtained with a carefully designed varying cutting depth milling experiment. The proposed method works well, with an error of 8.2% on testing samples, which shows an obvious advantage over the classic machine learning method.

Due to the enclosed chip evacuation space in deep hole drilling process, chips are accumulated in drill flutes as drilling depth increases, resulting in the increase of drilling torque and lead to drill breakage. Peck drilling is a widely used method to periodically alleviate the drilling torque caused by chip evacuation; the drilling depth in each step directly determines both drill life and machining efficiency. The existing drilling depth optimization methods face problems including low accuracy of the prediction model, the hysteresis of signal diagnosis, and onerous experiments. To overcome these problems, a novel drilling depth optimization method for peck drilling based on the iterative learning optimization is proposed. First, the chip evacuation torque coefficients (CETCs) are introduced into the chip evacuation torque model to simplify the model for learning. Then, the effect of chip removal process in peck drilling on drilling depth is analyzed. The extended depth coefficient by chip removal (EDCbCR) is introduced to develop the relationship between the extended depth in each drilling step and drilling depth. On the foundation of the modeling above, an iterative learning method for drilling depth optimization in peck drilling is developed, in which a modified Newton's method is proposed to maximize machining efficiency and avoid drill breakage. In experiments with different cutting parameters, the effectiveness of the proposed method is validated by comparing the optimized and measured results. The results show that the presented learning method is able to obtain the maximum drilling depth accurately with the error less than 10%. [ABSTRACT FROM AUTHOR]

A cobalt-based MOF (Co-MOF) and macroporous carbon (MPC) composite has been synthesised for the first time using a one-step hydrothermal treatment of the Co-MOF precursor mixture and MPC. The carbon skeleton exhibited a restrictive effect on the growth of Co-MOF crystallites; thus, the sizes of the crystallites matched well with those of the macropores of the MPC matrix. The formation of the composite material was verified by detailed characterisation (i.e., X-ray diffraction, Fourier transform infrared, X-ray photoelectron spectroscopy, energy dispersive X-ray, and thermogravimetric analyses). The obtained nanosized and nanocrystalline Co-MOF composite with incorporated MPC exhibited greatly improved electrochemical activity. More importantly, this composite, which displays excellent electrocatalytic ability for the oxidation of hydrazine and the reduction of nitrobenzene, can be used as a good electrochemical sensing platform. [ABSTRACT FROM AUTHOR]

Purpose To investigate the feasibility of constant dose rate volumetric modulated arc therapy (CDRVMAT) in the treatment of nasopharyngeal cancer (NPC) patients and to introduce rotational arc radiotherapy for linacs incapable of dose rate variation. Materials and methods Twelve NPC patients with various stages treated previously using variable dose rate (VDR) VMAT were enrolled in this study. CDR-VMAT, VDR-VMAT and mutlicriteria optimization (MCO) VMAT plans were generated for each patient on RayStation treatment planning system with identical objective functions and the dosimetric differences among these three planning schemes were evaluated and compared. Non dosimetric parameters of optimization time, delivery time and delivery accuracy were also evaluated. Results The planning target volume of clinical target volume (PTV-CTV) coverage of CDR-VMAT was a bit inferior to those of VDR- and MCO-VMAT. The V93 (p = 0.01) and V95 (percent volume covered by isodose line) (p = 0.04) for CDR-VMAT, VDR-VMAT and MCO-VMAT were 98.74% ± 0.31%, 99.76% ± 0.16%, 99.38% ± 0.43%, and 98.40% ± 0.48%, 99.53% ± 0.28%, 99.07% ± 0.52%, respectively.. However, the CDR-VMAT showed a better dose homogeneity index (HI) (p = 0.01) in PTV-CTV. No significant difference in other target coverage parameters was observed. There was no significant difference in OAR sparing among these three planning schemes except for a higher maximum dose (Dmax) on the brainstem for CDR-VMAT. The brainstem Dmax of CDR-VMAT, VDR-VMAT and MCOVMAT were 54.26 ± 3.21 Gy, 52.19 ± 1.65 Gy, and 52.79 ± 4.77 Gy, respectively. The average delivery time (p < 0.01) and the average percent γ passing rates (p = 0.02) of CDRVMAT, VDR-VMAT and MCO-VMAT were 7.01 ± 0.43 min, 4.75 ± 0.07 min, 4.01 ± 0.28 min, and 95.75% ± 2.57%, 97.65% ± 1.45%, 97.36% ± 2.45%, respectively. Conclusion CDR-VMAT offers an additional option of rotational arc radiotherapy for linacs incapable of dose rate variation with a lower initial cost. Its plan quality was acceptable but should be thoroughly checked compared with VDR-VMAT and MCO-VMAT in the treatment of NPC. [ABSTRACT FROM AUTHOR]

Background: To investigate the feasibility and benefits of a modified adaptive radiotherapy (ART) by replanning in the initial CT (iCT) with new contours from a repeat CT (rCT) based on CT-CT image fusion for nasopharyngeal cancer (NPC) patients underwent volumetric modulated arc radiotherapy (VMAT).Materials and Methods: Nine NPC patients underwent VMAT treatment with a rCT at 23rd fraction were enrolled in this study. Dosimetric differences for replanning VMAT plans in the iCT and in the rCT were compared. Volumetric and dosimetric changes of gross tumor volume (GTV) and organs at risk (OARs) of this modified ART were also investigated.Results: No dosimetric differences between replanning in the iCT and in the rCT were observed. The average volume of GTV decreased from 78.83 ± 38.42 cm3 in the iCT to 71.44 ± 37.46 cm3 in the rCT, but with no significant difference (p = 0.42).The average volume of the left and right parotid decreased from 19.91 ± 4.89 cm3 and 21.58 ± 6.16 cm3 in the iCT to 11.80 ± 2.79 cm3 and 13.29 ± 4.17 cm3 in the rCT (both p < 0.01), respectively. The volume of other OARs did not shrink very much. No significant differences on PTVGTV and PTVCTV coverage were observed for replanning with this modified ART. Compared to the initial plans, the average mean dose of the left and right parotid after re-optimization were decreased by 62.5 cGy (p = 0.05) and 67.3 cGy (p = 0.02), respectively, and the V5 (the volume receiving 5 Gy) of the left and right parotids were decreased by 7.8% (p = 0.01) and 11.2% (p = 0.001), respectively. There was no significant difference on the dose delivered to other OARs.Conclusion: Patients with NPC undergoing VMAT have significant anatomic and dosimetric changes to parotids. Repeat CT as an anatomic changes reference and re-optimization in the iCT based on CT-CT image fusion was accurate enough to identify the volume changes and to ensure safe dose to parotids. [ABSTRACT FROM AUTHOR]

Objective To investigate the anatomic and dosimetric variations of volumetric modulated arc therapy (VMAT) in the treatment of nasopharyngeal cancer (NPC) patients based on weekly cone beam CT (CBCT). Materials and methods Ten NPC patients treated by VMAT with weekly CBCT for setup corrections were reviewed retrospectively. Deformed volumes of targets and organs at risk (OARs) in the CBCT were compared with those in the planning CT. Delivered doses were recalculated based on weekly CBCT and compared with the planned doses. Results No significant volumetric changes on targets, brainstem, and spinal cord were observed. The average volumes of right and left parotid measured from the fifth CBCT were about 4.4 and 4.5 cm³ less than those from the first CBCT, respectively. There were no significant dose differences between average planned and delivered doses for targets, brainstem and spinal cord. For right parotid, the delivered mean dose was 10.5 cGy higher (p = 0.004) than the planned value per fraction, and the V26 and V32 increased by 7.5% (p = 0.002) and 7.4% (p = 0.01), respectively. For the left parotid, the D50 (dose to the 50% volume) was 8.8 cGy higher (p = 0.03) than the planned values per fraction, and the V26 increased by 8.8% (p = 0.002). Conclusion Weekly CBCTs were applied directly to study the continuous volume changes and resulting dosimetric variations of targets and OARs for NPC patients undergoing VMAT. Significant volumetric and dosimetric variations were observed for parotids. Replanning after 30 Gy will benefit the protection on parotids. [ABSTRACT FROM AUTHOR]

Radiation-associated toxicities due to sophisticated ocular anatomy and shape variability of organs at risk (OARs) are major concerns during external beam radiation therapy (EBRT) of patients with intraocular cancer. A novel two-step image registration strategy between optical coherence tomography (OCT) and computed tomography (CT) images was proposed and validated to precisely localize the target in the EBRT of patients with intraocular cancer. Specifically, multiple features from OCT and CT images were extracted automatically, then spatial transformation based on thin-plate spline function was performed iteratively to achieve feature alignment between the CT and OCT images. Finally, an exclusive OR (XOR) algorithm was applied for precise 3D registration using a 3D-mesh model generated from OCT and CT volumes. The accuracy of the proposed novel registration strategy was validated and tested in a schematic-eye phantom with an artificially introduced tumor and in ten patients with confirmed primary and/or secondary intraocular cancer. There was an average registration error and computational time of 0.21  ±  0.05° and 259  ±  5 s, together with an average Dice similarity coefficient and Hausdorff distance of 88.4  ±  0.65 and 0.89  ±  0.09, respectively. The preliminary experimental results demonstrated that the proposed novel strategy to overcome current limitations on eye modeling and to localize precisely the tumor target during EBRT of intraocular cancer is promising. [ABSTRACT FROM AUTHOR]

Dynamic myocardial perfusion CT (DMP-CT) imaging provides quantitative functional information for diagnosis and risk stratification of coronary artery disease by calculating myocardial perfusion hemodynamic parameter (MPHP) maps. However, the level of radiation delivered by dynamic sequential scan protocol can be potentially high. The purpose of this work is to develop a pre-contrast normal-dose scan induced structure tensor total variation regularization based on the penalized weighted least-squares (PWLS) criteria to improve the image quality of DMP-CT with a low-mAs CT acquisition. For simplicity, the present approach was termed as ‘PWLS-ndiSTV’. Specifically, the ndiSTV regularization takes into account the spatial-temporal structure information of DMP-CT data and further exploits the higher order derivatives of the objective images to enhance denoising performance. Subsequently, an effective optimization algorithm based on the split-Bregman approach was adopted to minimize the associative objective function. Evaluations with modified dynamic XCAT phantom and preclinical porcine datasets have demonstrated that the proposed PWLS-ndiSTV approach can achieve promising gains over other existing approaches in terms of noise-induced artifacts mitigation, edge details preservation, and accurate MPHP maps calculation. [ABSTRACT FROM AUTHOR]

The thermal, water and electrochemical stability of Cu-based metal organic frameworks (Cu-MOFs) confined in macroporous carbon (MPC) hybrids has been investigated. Thermogravimetric analyses, X-Ray diffraction, scanning electron microscopy, and cyclic voltammetry were employed to confirm the stability of pure Cu-MOFs, MPC, and Cu-MOFs-MPC. As compared to pure Cu-MOFs, the porous composite materials of MPC and Cu-MOFs interact and seem to form new materials having homogenous structure and chemistry, which show structural stability in aqueous media and electrochemical stability in phosphate buffer solution (PBS pH 7.4). The detection of ascorbic acid and hemoglobin is performed as an electrochemical probe, indicating Cu-MOFs-MPC holds great promise for the design of electrochemical sensors. [ABSTRACT FROM AUTHOR]