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Recent advancements in membrane-assisted seawater electrolysis powered by renewable energy offer a sustainable path to green hydrogen production. However, its large-scale implementation faces challenges due to slow power-to-hydrogen (P2H) conversion rates. Here we report a modular forward osmosis-water splitting (FOWS) system that integrates a thin-film composite FO membrane for water extraction with alkaline water electrolysis (AWE), denoted as FOWSAWE. This system generates high-purity hydrogen directly from wastewater at a rate of 448 Nm3 day−1 m−2 of membrane area, over 14 times faster than the state-of-the-art practice, with specific energy consumption as low as 3.96 kWh Nm−3. The rapid hydrogen production rate results from the utilisation of 1 M potassium hydroxide as a draw solution to extract water from wastewater, and as the electrolyte of AWE to split water and produce hydrogen. The current system enables this through the use of a potassium hydroxide-tolerant and hydrophilic FO membrane. The established water-hydrogen balance model can be applied to design modular FO and AWE units to meet demands at various scales, from households to cities, and from different water sources. The FOWSAWE system is a sustainable and an economical approach for producing hydrogen at a record-high rate directly from wastewater, marking a significant leap in P2H practice.

Deep learning has shown promising results for multiple 3D point cloud registration datasets. However, in the underwater domain, most registration of multibeam echo-sounder (MBES) point cloud data are still performed using classical methods in the iterative closest point (ICP) family. In this work, we curate and release DotsonEast Dataset, a semi-synthetic MBES registration dataset constructed from an autonomous underwater vehicle in West Antarctica. Using this dataset, we systematically benchmark the performance of 2 classical and 4 learning-based methods. The experimental results show that the learning-based methods work well for coarse alignment, and are better at recovering rough transforms consistently at high overlap (20-50%). In comparison, GICP (a variant of ICP) performs well for fine alignment and is better across all metrics at extremely low overlap (10%). To the best of our knowledge, this is the first work to benchmark both learning-based and classical registration methods on an AUV-based MBES dataset. To facilitate future research, both the code and data are made available online., Comment: Accepted at ICRA 2024 (IEEE International Conference on Robotics and Automation 2024)

Animals kept in homes for personal enjoyment rather than for work or sustenance are typically referred to as "pets." A pet's daily schedule can include exercising its muscles and going outside to relieve stress. Pets may occasionally be drink from community water dishes that could be contaminated with other animals' bacteria, viruses, or parasites. The pets may unknowingly get infections due to this opening up their bodies to bacteria or viruses. Pet's behavior and condition need to be periodically checked. An animal's behavior is directly impacted by its health and vice versa. A pet disease diagnosis application is crucial for pet owners to receive consistent and suitable pet health care. It will help pet owners identify potential illnesses before their animals develop chronic ones. Thus, the construction of a mobile application for diagnosing pet diseases is presented in this paper. This application offers pet owners information on their animals' health and safety. Pet owners can contact veterinarians for rare cases or crises in this application's chat room. The rule-based inference is used to determine the possible diseases based on the pet's symptoms. System prototyping methodology is applied to develop this Android mobile application using Visual Studio Code and Firebase database. User acceptance testing is performed on the users to test how much further their satisfaction with the proposed pet disease diagnosis application is before the application is shifted to the production process.

After experiencing traumatic stress, people may develop stress-induced anxiety disorders such as post-traumatic stress disorder (PTSD). One of the major symptoms of PTSD is the overgeneralization of fear. Our unpublished data demonstrated that this behavior can be caused by foodshock stress of adult mice through transmitter switching in the lateral wings of dorsal raphe (lwDR), but the mechanism triggering this neuroplasticity remained unknown. Because the hypothalamic-pituitary-adrenal (HPA) axis regulates stress, we hypothesized that traumatic stress would activate the HPA axis to induce the switch of the co-expressing neurotransmitter from glutamate to gamma-aminobutyric acid (GABA) in serotonergic (5-HT-expressing) neurons located in the lateral wings of the dorsal raphe (lwDR). To test our hypothesis, we first measured following footshock, the c-fos expression by neurons in the paraventricular nucleus of the hypothalamus (PVN) that release corticotropin-releasing hormone (CRH) and assayed the plasma corticosterone level. We then blocked the activity of the CRHPVN neurons or glucocorticoid receptors in the lwDR using viral tools. Further, we performed intraperitoneal (IP) injections of metyrapone, RU486, or corticosterone-HBC to either temporarily weaken corticosterone’s efficacy or introduce exogenous corticosterone. Analysis of transmitter switching and behavior revealed that the activity of the HPA axis was necessary and sufficient (when accompanied by weak shock) to cause the transmitter switch and change in behavior. These results show that the HPA axis plays an essential role in regulating neuroplasticity, which then generates fearful behavior. Thus, the HPA axis could be a target for treating stress-induced anxiety disorders.

Viewpoint.

Coupling TiO2-coated quartz optical fibers (TiO2-QOFs) with LEDs shows potential in degrading organics in water. Conventional TiO2-QOFs with thick and compact coatings are inefficient to degrade organic pollutants due to refraction losses. The research focuses on manipulating coating strategies to increase the generation of evanescent waves, which react more efficiently with the coated TiO2, which shows a crystal structure at anatase/rutile of 85/15. Through the use of dip-coating methods, TiO2 can be effectively deposited on quartz optical fibers, leveraging the principle of electrostatic attraction. By decreasing TiO2 dip-coating concentrations from 200 to 10 mg/L, dip-coating duration from 2 to 0.5 h, and coating cycles from 3 to 1, TiO2 patchiness on quartz fibers was reduced by 50–60%, enhancing the formation of more interspaces between the fiber surfaces and the coatings, which in turn allowed over 90% of evanescent waves in the TiO2-QOFs. The evanescent wave-dominated TiO2-QOFs irradiated by 275 nm UV-LED exhibited methylene blue degradation rate constants at around 0.03 h−1 and quantum yields greater than unity, indicating a highly efficient interaction between the evanescent wave and the surface coatings. These findings offer significant insights into optimizing the utilization of evanescent waves in TiO2-QOFs for pollutant degradation by regulating the coating structures.

This study investigated the chemical composition and biosynthesis pathway of compounds produced by Streptomyces sulphureus DSM 40104. With the guild of molecular networking analysis, we isolated and identified six uncommon structural characteristics of compounds, including four newly discovered pyridinopyrones. Based on genomic analysis, we proposed a possible hybrid NRPS-PKS biosynthesis pathway for pyridinopyrones. Notably, this pathway starts with the use of nicotinic acid as the starting unit, which is a unique feature. Compounds 1–3 exhibited moderate anti-neuroinflammatory activity against LPS-induced BV-2 cell inflammation. Our study demonstrates the diversity of polyene pyrone compounds regarding their chemical structure and bioactivity while providing new insights into their biosynthesis pathway. These findings may lead to the development of new treatments for inflammation-related diseases.

The performance of conventional photocatalytic reactors suffers from low photocatalyst mass-loading densities affixed to surfaces and light scattering losses or light attenuation in slurry reactors. These limitations are overcome by fabrication of high mass-loading g-C3N4 embedded metamaterial porous structures on flexible polymeric optical fibers (g-C3N4-POFs). In this study, the fabricated g-C3N4-POFs contain g-C3N4 with mass-loading 100−1000x higher than previouly reported, enabling efficient light delivery to g-C3N4 and improved pollutant mass transport within metamaterial porous structures. The key fabrication step involved using acetone, based on its high saturated vapor pressure and low dielectric constant, making roll-to-roll mass production of high mass-loading photocatalyst-embedded metamaterial POFs possible at room-temperature within seconds. Using bundles of 150 individual g-C3N4-POFs in the reactors, we achieved 4x higher degradation rates for micropollutants under visible light irradiation at 420 nm compared with equivalent mass-to-volume ratios of photocatalysts in a slurry suspension reactor. The bundled g-C3N4-POF reactor showed no degradation in the structural integrity or loss of pollutant degradation using deionized or model drinking water under accumulated HO• exposures of ∼4.5 × 10−9 M•s after 20 cycles of treatment. It operates continuously at g-C3N4 dosages equivalent to 100−1000 g/L and a water depth over 40 cm, making it a feasible alternative to conventional photocatalytic reactors.

The photolysis of monochloramine (NH2Cl), a widely used disinfectant, under UVC irradiation produces different radicals for the micropollutant degradation. For the first time, this study demonstrates the degradation of bisphenol A (BPA) via the NH2Cl activation by graphitic carbon nitride (g-C3N4) photocatalysis using visible light-LEDs at 420 nm, termed as the Vis420/g-C3N4/NH2Cl process. The process produces •NH2, •NH2OO, •NO and •NO2 via the eCB−- and O2•−-induced activation pathways and •NHCl and NHClOO• via the hVB+-induced activation pathway. The produced reactive nitrogen species (RNS) enhanced 100% of the BPA degradation compared with the Vis420/g-C3N4. Density functional theory calculations confirmed the proposed NH2Cl activation pathways and further demonstrated that eCB−/O2•− and hVB+ induced the cleavage of N–Cl and N–H bonds in NH2Cl, respectively. The process converted 73.5% of the decomposed NH2Cl to nitrogen-containing gas, compared with that of approximately 20% in the UVC/NH2Cl process, leaving much less ammonia, nitrite and nitrate in water. Among different operating conditions and water matrices tested, of particular significance is natural organic matter of 5 mgDOC/L only reduced 13.1% of the BPA degradation compared against that of at least 46% reduction in the UVC/NH2Cl process. Only 0.017–0.161 µg/L of disinfection byproducts were produced, two orders of magnitudes lower than that in the UVC/chlorine and UVC/NH2Cl processes. The combined use of visible light-LEDs, g-C3N4 and NH2Cl significantly improves the micropollutant degradation and reduces the energy consumption and byproduct formation of the NH2Cl-based AOP. © 2023 Elsevier Ltd

Several ppm levels of free chlorine in high chloride-containing water of no less than 0.20 M show remarkably high degradation rate constants toward carbamazepine (kCBZ′). Dichlorine monoxide (Cl2O) was identified to be responsible for the high kCBZ′. Cl2O degrades aromatic pollutants connected to more electron-donating functional groups faster when comparing kCl2O to 1,4-dimethoxybenzene, bisphenol A, benzoic acid, and CBZ. However, its formation at low free chlorine levels in high chloride-containing water cannot be explained by our current knowledge. We proposed an alternative Cl2O formation mechanism, in which chloride transforms hypochlorous acid/hypochlorite (HOCl/ClO-) to dichlorine (Cl2) and polychloride monoanions (Cln-), which then react with HOCl/ClO- to form Cl2O. Decreasing pH from 8.60 to 4.33 increases Cl2 concentrations and thus generates about 600× higher Cl2O concentrations. Weak acid anions, for example, phosphate and bicarbonate, are strong nucleophiles assisting the Cl2O hydrolysis, but their presence at the testing conditions does not much affect kCBZ′. The proposed alternative Cl2O formation mechanism reveals the roles of chloride in shifting the equilibrium toward the Cl2O formation, allowing the simple chlorine addition strategy to degrade recalcitrant organic pollutants in high chloride-containing wastewater. It may also change our understanding of the speciation of different free chlorine species and their impacts on the DBP formation in high chloride-containing wastewater. © 2023 American Chemical Society.

Multi-output deep neural networks(MONs) contain multiple task branches, and these tasks usually share partial network filters that lead to the entanglement of different task inference routes. Due to the inconsistent optimization objectives, the task gradients used for training MONs will interfere with each other on the shared routes, which will decrease the overall model performance. To address this issue, we propose a novel gradient de-conflict algorithm named DR-MGF(Dynamic Routes and Meta-weighted Gradient Fusion) in this work. Different from existing de-conflict methods, DR-MGF achieves gradient de-conflict in MONs by learning task-preferred inference routes. The proposed method is motivated by our experimental findings: the shared filters are not equally important to different tasks. By designing the learnable task-specific importance variables, DR-MGF evaluates the importance of filters for different tasks. Through making the dominances of tasks over filters be proportional to the task-specific importance of filters, DR-MGF can effectively reduce the inter-task interference. The task-specific importance variables ultimately determine task-preferred inference routes at the end of training iterations. Extensive experimental results on CIFAR, ImageNet, and NYUv2 illustrate that DR-MGF outperforms the existing de-conflict methods both in prediction accuracy and convergence speed of MONs. Furthermore, DR-MGF can be extended to general MONs without modifying the overall network structures., Comment: 15 pages

Acoustic sensors play an important role in autonomous underwater vehicles (AUVs). Sidescan sonar (SSS) detects a wide range and provides photo-realistic images in high resolution. However, SSS projects the 3D seafloor to 2D images, which are distorted by the AUV's altitude, target's range and sensor's resolution. As a result, the same physical area can show significant visual differences in SSS images from different survey lines, causing difficulties in tasks such as pixel correspondence and template matching. In this paper, a canonical transformation method consisting of intensity correction and slant range correction is proposed to decrease the above distortion. The intensity correction includes beam pattern correction and incident angle correction using three different Lambertian laws (cos, cos2, cot), whereas the slant range correction removes the nadir zone and projects the position of SSS elements into equally horizontally spaced, view-point independent bins. The proposed method is evaluated on real data collected by a HUGIN AUV, with manually-annotated pixel correspondence as ground truth reference. Experimental results on patch pairs compare similarity measures and keypoint descriptor matching. The results show that the canonical transformation can improve the patch similarity, as well as SIFT descriptor matching accuracy in different images where the same physical area was ensonified., Comment: 7 pages, 8 figures

Side-scan sonar (SSS) is a lightweight acoustic sensor that is frequently deployed on autonomous underwater vehicles (AUVs) to provide high-resolution seafloor images. However, using side-scan images to perform simultaneous localization and mapping (SLAM) remains a challenge when there is a lack of 3D bathymetric information and discriminant features in the side-scan images. To tackle this, we propose a feature-based SLAM framework using side-scan sonar, which is able to automatically detect and robustly match keypoints between paired side-scan images. We then use the detected correspondences as constraints to optimize the AUV pose trajectory. The proposed method is evaluated on real data collected by a Hugin AUV, using as a ground truth reference both manually-annotated keypoints and a 3D bathymetry mesh from multibeam echosounder (MBES). Experimental results demonstrate that our approach is able to reduce drifts from the dead-reckoning system. The framework is made publicly available for the benefit of the community., Comment: 7 pages, 11 figures

Photocatalytic chlorine activation process shows great potential in emerging contaminants abatement in drinking water. However, its implementation in most photocatalytic slurry-based systems is hindered by the need to recover the photocatalysts from water, and the light scattering or occlusion by photocatalysts and other aqueous constituents. In this study, high mass-loading TiO2 embedded metamaterial porous structures on flexible polymeric optical fibers (TiO2-POFs) was fabricated to implement photocatalytic chlorine activation process under near UV light irradiation, termed nUV/TiO2-POFs/chlorine process, for emerging contaminants abatement in drinking water. Using bundles of 150 individual TiO2-POFs, the carbamazepine degradation rate constants (kCBZ) by nUV/TiO2-POFs/chlorine process increased from 0.019 to 0.027 min-1 with increasing chlorine concentration from 1.0 to 5.0 mgCl2/L, which is 5 to 7.1 times higher than that in the absence of chlorine. The presence of NOM, HCO3-, Cl-, SO42-, NO3-, Ca2+, Cu2+ and Fe3+ shows not impact on the CBZ degradation, while the presence of high level of Mn2+ greatly inhibited the CBZ degradation. The CBZ degradation efficiency by the process in simulated drinking water slightly decreased from 92% to 80% and 70% after 20 and 42 cycles, respectively, and further decreased to 52% after 60 cycles. The reduced reactivity of TiO2-POFs is probably due to the accumulation of Cu on the TiO2-POFs surface and could be regenerated through simple acid-washing. Compared with UV/Chlorine process, the nUV/TiO2-POFs/chlorine process exhibited a 23.7% lower yield of regulated DBPs in degrading CBZ and a 58.2% lower yield of regulated DBPs after one-day post-chlorination.

Side-scan sonar (SSS) is a lightweight acoustic sensor that is commonly deployed on autonomous underwater vehicles (AUVs) to provide high-resolution seafloor images. However, leveraging side-scan images for simultaneous localization and mapping (SLAM) presents a notable challenge, primarily due to the difficulty of establishing sufficient amount of accurate correspondences between these images. To address this, we introduce a novel subframe-based dense SLAM framework utilizing side-scan sonar data, enabling effective dense matching in overlapping regions of paired side-scan images. With each image being evenly divided into subframes, we propose a robust estimation pipeline to estimate the relative pose between each paired subframes, by using a good inlier set identified from dense correspondences. These relative poses are then integrated as edge constraints in a factor graph to optimize the AUV pose trajectory. The proposed framework is evaluated on three real datasets collected by a Hugin AUV. Among one of them includes manually-annotated keypoint correspondences as ground truth and is used for evaluation of pose trajectory. We also present a feasible way of evaluating mapping quality against multi-beam echosounder (MBES) data without the influence of pose. Experimental results demonstrate that our approach effectively mitigates drift from the dead-reckoning (DR) system and enables quasi-dense bathymetry reconstruction. An open-source implementation of this work is available., Comment: 11 pages, 12 figures. arXiv admin note: substantial text overlap with arXiv:2304.01854

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing an extensive sample of people with MDD (N=2,772) and HC (N=4,240), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible.

In this study, g-C3N4 with a high portion of tri-s-triazine groups was synthesized to activate peroxymonosulfate (PMS) under visible light irradiation, termed as Vis/g-C3N4/PMS process, to degrade one frequently detected recalcitrant micropollutant carbamazepine (CBZ). The Vis/g-C3N4/PMS process increased pseudo first-order degradation rate constant of CBZ by 2 times compared with that in the absence of PMS. The enhanced CBZ degradation was because of the production of HO[rad] and SO4[rad]– from the PMS activation, but not the enhanced charge separation of g-C3N4 due to the presence of PMS. The Vis/g-C3N4/PMS process is insensitive to dissolved oxygen, chloride and bicarbonate concentrations, effective over a wide pH range from 6.0 to 10.0, and less affected by high concentrations of natural organic matter compared with the UV/chlorine and UV/TiO2 processes. In addition, photocatalytic activity of g-C3N4 remains stable over 5-cycle of reuse. These features make the process practically relevant and implementable in degrading micropollutants in drinking water, treated wastewater, surface water, groundwater, etc., using more efficient visible light LEDs or even sunlight. © 2021

Background: Bacteria and fungi that grow on the walls can cause allergic reactions and infectious diseases in human. We proposed a low-cost and easy-to-operate testing protocol for large scale field studies to evaluate the long-term antimicrobial performance of a novel WOx paint in 2 primary schools. Methods: In Tun Mun and Tin Shui Wai schools, WOx paints were painted on semi-outdoor and indoor walls and daily chlorine disinfection was applied after class in TSW School. A guidance was proposed for the protocol using the ATP biofluorescence method for large-scale field studies. ATP swab samples were taken at locations with and without the WOx paint on a control basis with a sampling frequency once a week for three months. The ATP values were then processed and presented in box plots. Results: In both schools, the median log-scale ATP values of walls with WOx paint were at least 0.5-log lower than those without WOx paint. The WOx paint also performed better than daily chlorine disinfection in reducing microbial activities in long-term. Conclusions: The proposed testing protocol is suitable to evaluate long-term performance of an antimicrobial paint by analyzing its microbial activity in large-scale field tests. The WOx paint shows long-term effectiveness in reducing microbial activities on wall surfaces in both indoor and semi-outdoor environments. © 2021 Association for Professionals in Infection Control and Epidemiology, Inc.

Drinking water utilities are interested in upgrading their treatment facilities to enhance micropollutant removal and byproduct control. Pre-oxidation by chlorine dioxide (ClO2) followed by coagulation-flocculation-sedimentation and advanced oxidation processes (AOPs) is one of the promising solutions. However, the chlorite (ClO2–) formed from the ClO2 pre-oxidation stage cannot be removed by the conventional coagulation process using aluminum sulfate. ClO2– negatively affects the post-UV/chlorine process due to its strong radical scavenging effect, and it also enhances the formation of chlorate (ClO3–). In this study, dosing micromolar-level ferrous iron (Fe(II)) into aluminum-based coagulants was proposed to eliminate the ClO2– generated from ClO2 pre-oxidation and benefit the post-UV/chlorine process in radical production and ClO3– reduction. Results showed that the addition of 52.1-µmol/L FeSO4 effectively eliminated the ClO2– generated from the pre-oxidation using 1.0 mg/L (14.8 µmol/L) of ClO2. Reduction of ClO2– increased the degradation rate constant of a model micropollutant (carbamazepine) by 55.0% in the post-UV/chlorine process. The enhanced degradation was verified to be attributed to the increased steady-state concentrations of HO· and ClO· by Fe(II) addition. Moreover, Fe(II) addition also decreased the ClO3– formation by 53.8% in the UV/chlorine process and its impact on the formation of chloro-organic byproducts was rather minor. The findings demonstrated a promising strategy to improve the drinking water quality and safety by adding low-level Fe(II) in coagulation in an advanced drinking water treatment train. © 2022

In this study, g-C3N4 with a high portion of tri-s-triazine groups was synthesized to activate peroxymonosulfate (PMS) under visible light irradiation, termed as Vis/g-C3N4/PMS process, to degrade one frequently detected recalcitrant micropollutant carbamazepine (CBZ). The Vis/g-C3N4/PMS process increased pseudo first-order degradation rate constant of CBZ by 2 times compared with that in the absence of PMS. The enhanced CBZ degradation was because of the production of HO[rad] and SO4[rad]– from the PMS activation, but not the enhanced charge separation of g-C3N4 due to the presence of PMS. The Vis/g-C3N4/PMS process is insensitive to dissolved oxygen, chloride and bicarbonate concentrations, effective over a wide pH range from 6.0 to 10.0, and less affected by high concentrations of natural organic matter compared with the UV/chlorine and UV/TiO2 processes. In addition, photocatalytic activity of g-C3N4 remains stable over 5-cycle of reuse. These features make the process practically relevant and implementable in degrading micropollutants in drinking water, treated wastewater, surface water, groundwater, etc., using more efficient visible light LEDs or even sunlight. © 2021

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.

This paper outlines challenges and opportunities in operating underwater robots (so-called AUVs) on a seaweed farm. The need is driven by an emerging aquaculture industry on the Swedish west coast where large-scale seaweed farms are being developed. In this paper, the operational challenges are described and key technologies in using autonomous systems as a core part of the operation are developed and demonstrated. The paper presents a system and methods for operating an AUV in the seaweed farm, including initial localization of the farm based on a prior estimate and dead-reckoning navigation, and the subsequent scanning of the entire farm. Critical data from sidescan sonars for algorithm development are collected from real environments at a test site in the ocean, and the results are demonstrated in a simulated seaweed farm setup., QC 20220721

Patients with hormone receptor (HR)-positive tumors breast cancer usually experience a relatively low pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). Here, we derived a 10-microRNA risk score (10-miRNA RS)-based model with better performance in the prediction of pCR and validated its relation with the disease-free survival (DFS) in 755 HR-positive breast cancer patients (273, 265, and 217 in the training, internal, and external validation sets, respectively). This model, presented as a nomogram, included four parameters: the 10-miRNA RS found in our previous study, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) status, and volume transfer constant (K-trans). Favorable calibration and discrimination of 10-miRNA RS-based model with areas under the curve (AUC) of 0.865, 0.811, and 0.804 were shown in the training, internal, and external validation sets, respectively. Patients who have higher nomogram score (>92.2) with NAC treatment would have longer DFS (hazard ratio=0.57; 95%CI: 0.39-0.83; P=0.004). In summary, our data showed the 10-miRNA RS-based model could precisely identify more patients who can attain pCR to NAC, which may help clinicians formulate the personalized initial treatment strategy and consequently achieves better clinical prognosis for patients with HR-positive breast cancer.

This thesis presents supervised machine learning techniques using acceleration responses recorded from a small number of sensors. Ensemble-based traditional machine learning models are developed as a multi output regression model for the damage identification of the civil engineering structures using acceleration responses and impulse response functions extracted from it. Further, to improve the damage identification performance, a LSTM auto-encoder based multi output regression model is proposed. Finally, for a large-scale bridge, a 1D-CNN based damage classifier is developed using less number of sensors than the existing study.

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.

Context-aware decision support in the operating room can foster surgical safety and efficiency by leveraging real-time feedback from surgical workflow analysis. Most existing works recognize surgical activities at a coarse-grained level, such as phases, steps or events, leaving out fine-grained interaction details about the surgical activity; yet those are needed for more helpful AI assistance in the operating room. Recognizing surgical actions as triplets of combination delivers comprehensive details about the activities taking place in surgical videos. This paper presents CholecTriplet2021: an endoscopic vision challenge organized at MICCAI 2021 for the recognition of surgical action triplets in laparoscopic videos. The challenge granted private access to the large-scale CholecT50 dataset, which is annotated with action triplet information. In this paper, we present the challenge setup and assessment of the state-of-the-art deep learning methods proposed by the participants during the challenge. A total of 4 baseline methods from the challenge organizers and 19 new deep learning algorithms by competing teams are presented to recognize surgical action triplets directly from surgical videos, achieving mean average precision (mAP) ranging from 4.2% to 38.1%. This study also analyzes the significance of the results obtained by the presented approaches, performs a thorough methodological comparison between them, in-depth result analysis, and proposes a novel ensemble method for enhanced recognition. Our analysis shows that surgical workflow analysis is not yet solved, and also highlights interesting directions for future research on fine-grained surgical activity recognition which is of utmost importance for the development of AI in surgery., Comment: CholecTriplet2021 challenge report. Paper accepted at Elsevier journal of Medical Image Analysis. 22 pages, 8 figures, 11 tables. Challenge website: https://cholectriplet2021.grand-challenge.org

Drinking water utilities are interested in upgrading their treatment facilities to enhance micropollutant removal and byproduct control. Pre-oxidation by chlorine dioxide (ClO2) followed by coagulation-flocculation-sedimentation and advanced oxidation processes (AOPs) is one of the promising solutions. However, the chlorite (ClO2–) formed from the ClO2 pre-oxidation stage cannot be removed by the conventional coagulation process using aluminum sulfate. ClO2– negatively affects the post-UV/chlorine process due to its strong radical scavenging effect, and it also enhances the formation of chlorate (ClO3–). In this study, dosing micromolar-level ferrous iron (Fe(II)) into aluminum-based coagulants was proposed to eliminate the ClO2– generated from ClO2 pre-oxidation and benefit the post-UV/chlorine process in radical production and ClO3– reduction. Results showed that the addition of 52.1-µmol/L FeSO4 effectively eliminated the ClO2– generated from the pre-oxidation using 1.0 mg/L (14.8 µmol/L) of ClO2. Reduction of ClO2– increased the degradation rate constant of a model micropollutant (carbamazepine) by 55.0% in the post-UV/chlorine process. The enhanced degradation was verified to be attributed to the increased steady-state concentrations of HO· and ClO· by Fe(II) addition. Moreover, Fe(II) addition also decreased the ClO3– formation by 53.8% in the UV/chlorine process and its impact on the formation of chloro-organic byproducts was rather minor. The findings demonstrated a promising strategy to improve the drinking water quality and safety by adding low-level Fe(II) in coagulation in an advanced drinking water treatment train. © 2022

This study presents a layer-by-layer interfacial polymerization approach to enhance the chlorine resistance and water permeability of thin-film composite (TFC) polyamide (PA) forward osmosis membranes. The PA film was prepared by self-polymerization using 3,5-Dihydroxybenzoic acid (DHBA) and trimesoyl chloride (TMC) with addition of 4-amino-benzene sulfonamide (4-ABSA), which is a sulfonamide monomer, on a polysulfone (PSF) support layer. The cross-linking structure and surface characterisation of the DHBA-ABSA membrane was studied systematically. FTIR results showed the successful grafting of the sulfonamide group on the membrane surface. Compared with the MPD-TMC membrane, the water flux of three modified membranes—DHBA, ABSA, and DHBA with ABSA—improved by 27.6%, 44.0%, and 67.6%, respectively, and reverse salt flux decreased by 9.9%, 12.3%, and 16.2%, respectively. Furthermore, the chlorine-stability test using 200 ppm NaClO indicated stable long-term performance under different pH values. The stable sulfonamide structure of ABSA with N-H group effectively prevented chlorine from directly attacking the active layer and improve the chlorine-stability of the membrane. In addition, the abundant hydrophilic groups on ABSA and DHBA monomers formed a hydration layer with water molecules on the membrane surface through hydrogen bonding, which enhanced the permeability of the TFC-PA membranes. The findings of this study demonstrate the DHBA-ABSA membrane's wider application potential in water and wastewater treatment processes. © 2022 Elsevier B.V.

Background: Bacteria and fungi that grow on the walls can cause allergic reactions and infectious diseases in human. We proposed a low-cost and easy-to-operate testing protocol for large scale field studies to evaluate the long-term antimicrobial performance of a novel WOx paint in 2 primary schools. Methods: In Tun Mun and Tin Shui Wai schools, WOx paints were painted on semi-outdoor and indoor walls and daily chlorine disinfection was applied after class in TSW School. A guidance was proposed for the protocol using the ATP biofluorescence method for large-scale field studies. ATP swab samples were taken at locations with and without the WOx paint on a control basis with a sampling frequency once a week for three months. The ATP values were then processed and presented in box plots. Results: In both schools, the median log-scale ATP values of walls with WOx paint were at least 0.5-log lower than those without WOx paint. The WOx paint also performed better than daily chlorine disinfection in reducing microbial activities in long-term. Conclusions: The proposed testing protocol is suitable to evaluate long-term performance of an antimicrobial paint by analyzing its microbial activity in large-scale field tests. The WOx paint shows long-term effectiveness in reducing microbial activities on wall surfaces in both indoor and semi-outdoor environments.

In this study, g-C3N4 with a high portion of tri-s-triazine groups was synthesized to activate peroxymonosulfate (PMS) under visible light irradiation, termed as Vis/g-C3N4/PMS process, to degrade one frequently detected recalcitrant micropollutant carbamazepine (CBZ). The Vis/g-C3N4/PMS process increased pseudo first-order degradation rate constant of CBZ by 2 times compared with that in the absence of PMS. The enhanced CBZ degradation was because of the production of HO[rad] and SO4[rad]– from the PMS activation, but not the enhanced charge separation of g-C3N4 due to the presence of PMS. The Vis/g-C3N4/PMS process is insensitive to dissolved oxygen, chloride and bicarbonate concentrations, effective over a wide pH range from 6.0 to 10.0, and less affected by high concentrations of natural organic matter compared with the UV/chlorine and UV/TiO2 processes. In addition, photocatalytic activity of g-C3N4 remains stable over 5-cycle of reuse. These features make the process practically relevant and implementable in degrading micropollutants in drinking water, treated wastewater, surface water, groundwater, etc., using more efficient visible light LEDs or even sunlight. © 2021

This study systematically quantified the impacts of different operation conditions, e.g., pH, chlorine dosages, contact times, and temperatures towards the disinfection by-product (DBP) formation, integrated toxicity, and structural changes in seawater natural organic matter during seawater chlorination. Higher concentrations of total DBPs were found under longer contact times, higher chlorine dosages, higher temperatures, and lower pH. The concentration of tribromomethane, the most abundant DBP, was found lowest at pH 10. Monobromoacetic acid, dibromoacetonitrile, and dibromoacetaldehyde were the three main contributors to integrated cyto- and geno-toxicity, stressing the need to monitor DBPs based on their contributions to integrated toxicity, regardless they are regulated or nonregulated. The concentrations of total organic chlorine remained stable under different conditions, while those of total organic bromine increased with increasing contact times, chlorine dosages, and temperatures, but with decreasing pH, indicating the changes of toxicity in chlorinated seawater compared to drinking water or groundwater. Changes of ultraviolet absorbance at 254 nm and fluorescence excitation emission matrix values are useful indicators for monitoring the concentrations of high molecular weight adsorbable organic bromine and total organic halogen under all operating conditions. © 2022 Elsevier Ltd

A system to produce reactive oxidative species in a fluid medium containing a source of Cl(I) by irradiating a solid photocatalyst suspended in the fluid medium or residing on a surface that is contactable by the fluid with electromag­netic radiation. The electromagnetic radiation can be in the UV, near-UV, visible, or near-IR consistent with the photo­catalyst employed. The source of Cl(I) in certain embodi­ments is Cl2, HOCl, or H2NCI. The photocatalyst is g-C3沁 Ti02, BBiOBr, or any other solid insoluble photocatalyst.

Ultraviolet (UV)/chlorine processes are emerging advanced oxidation processes (AOPs) for micropollutant abatement. When excessive chlorine (Cl/N mass ratio of >7.6) is applied to ammonia-containing water to yield free chlorine residual for the UV/free chlorine AOP, the AOP becomes UV/breakpoint chlorination. This study investigated micropollutant degradation by and radical yields from UV/breakpoint chlorination under various conditions using benzoic acid (BA) and nitrobenzene (NB) as representative micropollutants and radical probes. Two stages of degradation were observed. During stage I, BA and NB were rapidly degraded; this was attributed to the reactive species generated from breakpoint chlorination (Rbrk) and UV photolysis of chlor(am)ines and breakpoint chlorination intermediates/products (Rpho). During stage II, the degradation followed pseudo-first-order kinetics, and UV photolysis of unknown irreducible residuals produced from breakpoint chlorination greatly contributed to generating reactive species, in addition to UV photolysis of free chlorine. At pH 7 and an ammonia concentration of 1 mg/L as N, an optimum chlorine dosage for micropollutant degradation existed at 9.6 mg/L as Cl2 due to the strong scavenging from excessive free chlorine. The findings demonstrate that UV/breakpoint chlorination is a promising approach for degrading refractory micropollutants in real-world applications.

Coupling photocatalyst-coated optical fibers (P-OFs) with LEDs shows potential in environmental applications. Here we report a strategy to maximize P-OF light usage and quantify interactions between two forms of light energy (refracted light and evanescent waves) and surface-coated photocatalysts. Different TiO2-coated quartz optical fibers (TiO2-QOFs) are synthesized and characterized. An energy balance model is then developed by correlating different nano-size TiO2 coating structures with light propagation modes in TiO2-QOFs. By reducing TiO2 patchiness on optical fibers to 0.034 cm2/cm2 and increasing the average interspace distance between fiber surfaces and TiO2 coating layers to 114.3 nm, refraction is largely reduced when light is launched into TiO2-QOFs, and 91% of light propagated on the fiber surface is evanescent waves. 24% of the generated evanescent waves are not absorbed by nano-TiO2 and returned to optical fibers, thus increasing the quantum yield during degradation of a refractory pollutant (carbamazepine) in water by 32%. Our model also predicts that extending the TiO2-QOF length could fully use the returned light to double the carbamazepine degradation and quantum yield. Therefore, maximizing evanescent waves to activate photocatalysts by controlling photocatalyst coating structures emerges as an effective strategy to improve light usage in photocatalysis. © 2021, The Author(s).

Background: Bacteria and fungi that grow on the walls can cause allergic reactions and infectious diseases in human. We proposed a low-cost and easy-to-operate testing protocol for large scale field studies to evaluate the long-term antimicrobial performance of a novel WOx paint in 2 primary schools. Methods: In Tun Mun and Tin Shui Wai schools, WOx paints were painted on semi-outdoor and indoor walls and daily chlorine disinfection was applied after class in TSW School. A guidance was proposed for the protocol using the ATP biofluorescence method for large-scale field studies. ATP swab samples were taken at locations with and without the WOx paint on a control basis with a sampling frequency once a week for three months. The ATP values were then processed and presented in box plots. Results: In both schools, the median log-scale ATP values of walls with WOx paint were at least 0.5-log lower than those without WOx paint. The WOx paint also performed better than daily chlorine disinfection in reducing microbial activities in long-term. Conclusions: The proposed testing protocol is suitable to evaluate long-term performance of an antimicrobial paint by analyzing its microbial activity in large-scale field tests. The WOx paint shows long-term effectiveness in reducing microbial activities on wall surfaces in both indoor and semi-outdoor environments. © 2021 Association for Professionals in Infection Control and Epidemiology, Inc.

In this study, the near-ultraviolet (near-UV) light-driven TiO2 photocatalytic chlorine activation process, termed as the UV365/TiO2/chlorine process, degrades a representative recalcitrant micropollutant, carbamazepine (CBZ), at an apparent first-order rate constant (kCBZ′) that is 34.2 and 3.9 times higher than those without TiO2 and chlorine, respectively. In this process, chlorine serves a more important role as a catalyst to enhance the yield of hydroxyl radicals (HO·) without being consumed, in addition to its role as a radical precursor to produce HO· and reactive chlorine species. kCBZ′ increased with increasing TiO2 dosages from 1.0 to 20.0 mg/L and light intensities from 0.1 to 0.33 mW/cm2 and with decreasing chlorine dosages from 5.0 to 1.0 mgCl2/L. Increasing pH increased the overall radical concentrations but transformed HO· and Cl· to less reactive ClO·, leading to a decreasing kCBZ′ from pH 6.0 to 9.0. The dual roles of chlorine in the process enabled the rapid CBZ degradation at a chlorine dosage about 1/20 to that of the conventional UVC/chlorine process, at a TiO2 dosage about 1/200 to that of the UVC/TiO2 process and at an electrical energy per order of CBZ degradation at least 2-order of magnitude lower than those of the existing UVC-based processes.

Ultraviolet (UV)/chlorine processes are emerging advanced oxidation processes (AOPs) for micropollutant abatement. When excessive chlorine (Cl/N mass ratio of >7.6) is applied to ammonia-containing water to yield free chlorine residual for the UV/free chlorine AOP, the AOP becomes UV/breakpoint chlorination. This study investigated micropollutant degradation by and radical yields from UV/breakpoint chlorination under various conditions using benzoic acid (BA) and nitrobenzene (NB) as representative micropollutants and radical probes. Two stages of degradation were observed. During stage I, BA and NB were rapidly degraded; this was attributed to the reactive species generated from breakpoint chlorination (Rbrk) and UV photolysis of chlor(am)ines and breakpoint chlorination intermediates/products (Rpho). During stage II, the degradation followed pseudo-first-order kinetics, and UV photolysis of unknown irreducible residuals produced from breakpoint chlorination greatly contributed to generating reactive species, in addition to UV photolysis of free chlorine. At pH 7 and an ammonia concentration of 1 mg/L as N, an optimum chlorine dosage for micropollutant degradation existed at 9.6 mg/L as Cl2 due to the strong scavenging from excessive free chlorine. The findings demonstrate that UV/breakpoint chlorination is a promising approach for degrading refractory micropollutants in real-world applications.

Coupling TiO2-coated quartz optical fibers (TiO2-QOFs) with LEDs show potential in degrading organics in water. Conventional TiO2-QOFs with compact TiO2 coating layers are inefficient to degrade organics due to large amount of light being refracted out and wasted. Evanescent waves which are generated from total internal reflection of light and return to the optical fibers if not used react more efficient with surface-coated TiO2 than refracted light. This work aims to investigate coating strategies to modulate the quantity of refracted light and evanescent waves generated in TiO2-QOFs, and examine the energy efficiency of degrading a common dye (methylene blue (MB)) by the TiO2-QOFs irradiated by 275 nm light. Three strategies, including decreasing concentrations of dipcoating suspension, decreasing dip-coating duration, and decreasing dip-coating cycles, were effective in reducing TiO2 patchiness (i.e., the ratio of optical fiber surfaces in direct contact with TiO2 to the total optical fiber surfaces), which reduced the portion of refracted light and increased that of evanescent waves to activate TiO2. The degradation of MB by the uncoated optical fibers and TiO2-QOFs irradiated by 275 nm UV light was then conducted. The direct MB photolysis by evanescent waves generated in uncoated optical fibers showed a highest quantum yield at 1.8, which is great than unity, and a degradation rate constant (kMB) of 0.004 h-1 . When a low patchiness TiO2 layer was loaded on optical fibers and activated by evanescent waves, kMB increased by 6.5 times without changing quantum yields. A higher TiO2 patchiness reduced the quantum yields by 44% due to the increased refracted light and decreased evanescent waves generated in TiO2- QOFs. These findings suggest the energy efficiency of MB degradation by TiO2-QOFs is significantly enhanced through the efficient light usage by changing the light mode from at the fiber interfaces from refracted light to evanescent waves.

In this study, the near-ultraviolet (near-UV) light-driven TiO2 photocatalytic chlorine activation process, termed as the UV365/TiO2/chlorine process, degrades a representative recalcitrant micropollutant, carbamazepine (CBZ), at an apparent first-order rate constant (kCBZ′) that is 34.2 and 3.9 times higher than those without TiO2 and chlorine, respectively. In this process, chlorine serves a more important role as a catalyst to enhance the yield of hydroxyl radicals (HO·) without being consumed, in addition to its role as a radical precursor to produce HO· and reactive chlorine species. kCBZ′ increased with increasing TiO2 dosages from 1.0 to 20.0 mg/L and light intensities from 0.1 to 0.33 mW/cm2 and with decreasing chlorine dosages from 5.0 to 1.0 mgCl2/L. Increasing pH increased the overall radical concentrations but transformed HO· and Cl· to less reactive ClO·, leading to a decreasing kCBZ′ from pH 6.0 to 9.0. The dual roles of chlorine in the process enabled the rapid CBZ degradation at a chlorine dosage about 1/20 to that of the conventional UVC/chlorine process, at a TiO2 dosage about 1/200 to that of the UVC/TiO2 process and at an electrical energy per order of CBZ degradation at least 2-order of magnitude lower than those of the existing UVC-based processes.

Coupling photocatalyst-coated optical fibers (P-OFs) with LEDs shows potential in environmental applications. Here we report a strategy to maximize P-OF light usage and quantify interactions between two forms of light energy (refracted light and evanescent waves) and surface-coated photocatalysts. Different TiO2-coated quartz optical fibers (TiO2-QOFs) are synthesized and characterized. An energy balance model is then developed by correlating different nano-size TiO2 coating structures with light propagation modes in TiO2-QOFs. By reducing TiO2 patchiness on optical fibers to 0.034 cm2/cm2 and increasing the average interspace distance between fiber surfaces and TiO2 coating layers to 114.3 nm, refraction is largely reduced when light is launched into TiO2-QOFs, and 91% of light propagated on the fiber surface is evanescent waves. 24% of the generated evanescent waves are not absorbed by nano-TiO2 and returned to optical fibers, thus increasing the quantum yield during degradation of a refractory pollutant (carbamazepine) in water by 32%. Our model also predicts that extending the TiO2-QOF length could fully use the returned light to double the carbamazepine degradation and quantum yield. Therefore, maximizing evanescent waves to activate photocatalysts by controlling photocatalyst coating structures emerges as an effective strategy to improve light usage in photocatalysis. © 2021, The Author(s).

Ultraviolet (UV)/chlorine processes are emerging advanced oxidation processes (AOPs) for micropollutant abatement. When excessive chlorine (Cl/N mass ratio of >7.6) is applied to ammonia-containing water to yield free chlorine residual for the UV/free chlorine AOP, the AOP becomes UV/breakpoint chlorination. This study investigated micropollutant degradation by and radical yields from UV/breakpoint chlorination under various conditions using benzoic acid (BA) and nitrobenzene (NB) as representative micropollutants and radical probes. Two stages of degradation were observed. During stage I, BA and NB were rapidly degraded; this was attributed to the reactive species generated from breakpoint chlorination (Rbrk) and UV photolysis of chlor(am)ines and breakpoint chlorination intermediates/products (Rpho). During stage II, the degradation followed pseudo-first-order kinetics, and UV photolysis of unknown irreducible residuals produced from breakpoint chlorination greatly contributed to generating reactive species, in addition to UV photolysis of free chlorine. At pH 7 and an ammonia concentration of 1 mg/L as N, an optimum chlorine dosage for micropollutant degradation existed at 9.6 mg/L as Cl2 due to the strong scavenging from excessive free chlorine. The findings demonstrate that UV/breakpoint chlorination is a promising approach for degrading refractory micropollutants in real-world applications.

In underwater environments, the perception and navigation systems are heavily dependent on the acoustic wave based sonar technology. Side-scan sonar (SSS) provides high-resolution, photo-realistic images of the seafloor at a relatively cheap price. These images could be considered potential candidates for place recognition and navigation of autonomous underwater vehicles (AUVs). Local feature correspondence matching, or the detection, description and matching of keypoints in overlapping images is a necessary building block for AUV navigation. Recent deep learning based research has resulted in state-of-the-art local correspondence models for camera images. For SSS images, however, deep learning based studies are limited and handcrafted methods such as SIFT and RootSIFT still dominate the field. In this study, SSS images taken from a seafloor area with bottom trawling marks were used for correspondence matching. D2-Net, a detect-and-describe VGG16 based network architecture designed for and tested on camera image correspondence was fine-tuned for SSS image correspondence. Using triplet margin ranking loss, the network was trained to simultaneously detect salient keypoints and produce similar descriptors for corresponding pixels and dissimilar descriptors for non-corresponding pixels. When evaluated on the nontrivial SSS images pairs in the test dataset, the best performing D2-Net based network was found to outperform the RootSIFT baseline in terms of number of detected keypoints, keypoint repeatability and mean matching accuracy at above 10 pixel threshold., I undervattensmiljöer så är perception och navigationssystem ofta beroende av ekolodsteknik. Side scan sonar (SSS) ger högupplösta, fotorealistiska bilder av havsbottnen till en relativt låg kostnad. Dessa bilder kan användas för områdesigenkänning och navigation av autonoma undervattensfordon (AUV). Lokal kännerteckensmatchning består av detektion, beskrivning och matchning av nyckelpunkter på överlappande bilder. Detta är en viktig byggsten för AUV navigation. Nya metoder baserade på djupinlärning har varit i framkant för kännerteckensmatching av kamerabilder. Däremot är kännerteckensmatchning av SSS bilder fortfarande dominerat av traditionella metoder så som SIFT och RootSIFT. Denna rapport använder SSS bilder av havsbottnen där bottentrålning har förekommit för kännerteckensmatching. D2-Net är en detect-and-describe VGG16 baserad nätverksarkitektur designad och testad på kännerteckensmatching av kamerabilder. I denna rapport anpassas denna metod till SSS bilder. Kostnadsfunktionen använder sig av trippelmarginalsrankning så att nätverket ska kunna detektera distinkta nyckelpunkter samt producera liknande deskriptorer för matchande pixlar. Metoden utvärderades på icke-triviala SSS bildpar och uppnådde bättre resultat än RootSIFT.

We make a detailed study on the typical production channel of double charmoniums, $e^+e^-\to J/\psi+\eta_c$, at the center-of-mass collision energy $\sqrt{s}=10.58$ GeV. The key component of the process is the form factor $F_{\rm VP}(q^2)$, which has been calculated within the QCD light-cone sum rules (LCSR). To improve the accuracy of the derived LCSR, we keep the $J/\psi$ light-cone distribution amplitude up to twist-4 accuracy. Total cross sections for $e^+e^-\to J/\psi+\eta_c$ at three typical factorization scales are $\sigma|_{\mu_s} = 22.53^{+3.46}_{-3.49}~{\rm fb}$, $\sigma|_{\mu_k} = 21.98^{+3.35}_{-3.38}~{\rm fb}$ and $\sigma|_{\mu_0} = 21.74^{+3.29}_{-3.33}~{\rm fb}$, respectively. The factorization scale dependence is small, and those predictions are consistent with the BABAR and Belle measurements within errors., Comment: 8 pages, 3 figures, version to be published in Physical Review D

The total charge-changing cross-sections and the partial cross-sections for projectile fragments (PFs) production for the fragmentation of 12C on C, Al, Cu, Pb and CH2 targets at the highest energy of 290AMeV were studied. It was found that the total charge-changing reaction cross-sections and the partial reaction cross-sections of PFs production were independent of the beam energy, and increased with increase of mass of target for the same beam energy. The total charge-changing reaction cross-section was the same as the prediction of Bradt–Peters semi-empirical formula, PHITS and NUCFRG2 simulation models. The partial cross-section of PFs production increased with the increase of the mass of target, and it was the same as the prediction of NUCFRG2 models. The mean scattering angle of projectile particle was smaller than the average emission angle of PF, and the width of scattering angle distribution of projectile particle was smaller than that of emission angle distribution of PFs. The mean emission angle of PFs does not obviously depend on the target mass and beam energy in our studied beam energy regions.

The nuclear charge pickup cross-sections of 12C on CH2, C, Al, Cu and Pb targets at the highest energy of 288MeV/n were investigated using CR-39 nuclear track detector. The cross-section for H was calculated from those measured on C and CH2 targets. The dependence of charge pickup cross-section on target mass was investigated. It was found that the nuclear charge pickup cross-section of 12C at our studied beam energies seems to exponentially depend on the target mass with the fitting exponent b∼0.9, which can be well explained by the peripheral and the surface collisions of the nuclear charge pickup reactions.

One-part alkali-activated slag (AAS) binders are more promising in large-scale constructions because one-part mixing procedure is safer and easier to handle compared to normal two-part method. Thus, this study aims at investigating different properties of one-part AAS binders and control samples prepared using the two-part method. Experimental results of the former suggested the hardening time was greatly extended, but the workability showed little difference. Besides, compared to the control, one-part AAS binders had similar early compressive strength (within 7 days) and flexural strength in all tested curing stages but lower later compressive strength (from 28 days). The characterisation of the porous structures suggests that there were fewer C-A-S-H gels for one-part binders evidenced by less volume of mesopores but with larger amount of bigger pores. In addition, mineralogical and microstructural analyses imply that there was no hydrotalcite formed in the one-part AAS binders. Moreover, one-part AAS binders are more susceptible to efflorescence, presumably further affecting their surface and long-term durability., Accepted author manuscript, Materials and Environment