Review on physical performance, modification mechanisms, carbon emissions and economic costs of recycled aggregates modified with physical enhancement technologies.

With the continuous advancement of urban renewal, the application of recycled aggregates (RA) is a win-win measure to solve the treatment of construction waste and provide the required building materials. However, the existence of a large amount of old adhesive mortar (OAM) makes it difficult for RA to equivalently replace natural aggregates (NA) due to their higher water absorption and crushing index, as well as a lower apparent density. From the published literature on enhancing RA, the most mature and easiest method for construction is physical enhancement technology. Therefore, through a review of recent related researches, this article summarizes and compares the modification effects of mechanical grinding technology, traditional heating and grinding technology, and microwave heating technology on the physical properties of RA, including water absorption, apparent density, and crushing value. The related modification mechanisms were discussed. Additionally, the impacts of different physical enhancement technologies on the environment and economy effects are assessed from the perspectives of carbon emissions and cost required during processing. Based on multi-criteria analysis, microwave heating technology is more efficient and cleaner, which is the most recommended in the future.

Microwave-assisted catalytic pyrolysis of waste cooking oil to monocyclic aromatics under a bifunctional SiC ball catalyst.

Catalytic pyrolysis technology proves to be a highly effective approach for waste cooking oil management. However, high-pressure drops and easy deactivation of powder catalysts hinder the industrialization of this technology. In this study, a bifunctional SiC ball (ZSM-5/SiC ball structured) catalyst was prepared to produce monocyclic aromatics. Bifunctional SiC ball catalyst demonstrates notable microwave-responsive properties and remarkable catalytic efficacy. Results showed that the content of monocyclic aromatics under BFSB catalysis with microwave heating was the highest. Weight hourly space velocity is no longer one of the main factors affecting microwave-assisted catalytic pyrolysis under bifunctional SiC ball catalyst. Monocyclic aromatics content did not decrease significantly and was still higher than 86% when space velocity increased from 30 h-1 to 360 h-1. The highest space velocity could only be 180 h-1 under Powder ZSM-5, and the content of the monocyclic aromatics dropped rapidly to 67.68%. Furthermore, even after five operating cycles, the content of monocyclic aromatics with bifunctional SiC ball catalyst continues to surpass the initial content observed with Powder ZSM-5 at 500 °C and 180 h-1. Related characterizations revealed that coking is the primary cause of catalyst deactivation for both catalyst types; however, the bifunctional SiC ball catalyst exhibits a 29.1% lower occurrence of polyaromatic coke formation compared to Powder ZSM-5.

Prevalence and Procedural Risk of Intracranial Atherosclerotic Stenosis Coexisting With Unruptured Intracranial Aneurysm.

BACKGROUND: Coexistence of intracranial atherosclerotic stenosis (ICAS) and unruptured intracranial aneurysms (UIAs) is increasingly encountered in clinical practice. This study aims to determine the prevalence of ICAS in patients with UIAs and procedural ischemic risk associated with ICAS when treating UIAs. METHODS: Based on the CAIASA study (Coexistence of Atherosclerotic Intracranial Arterial Stenosis With Intracranial Aneurysms), we prospectively included patients undergoing treatment procedures for UIAs from October 2015 to December 2020 at Beijing Tiantan Hospital, China. We used computed tomography angiography or digital subtraction angiography to diagnose ICAS (stenosis≥50%). Multivariable logistic regression and propensity-score matching were performed to evaluate the risk of procedure-related ischemic stroke and unfavorable outcome associated with ICAS. The ICAS score was used to explore the association between different burden of ICAS and procedure-related ischemic risk. RESULTS: Among 3949 patients who underwent endovascular or open surgical procedures for UIAs, 245 (6.2%) had ICAS. After exclusion, 15.7% (32/204) of patients with ICAS experienced procedure-related ischemic stroke compared with 5.0% (141/2825) of patients without ICAS. From the unmatched and matched cohort, ICAS was significantly associated with increased risk of procedure-related ischemic stroke (unmatched: adjusted odds ratio=3.11 [1.89-5.11]; and matched: adjusted odds ratio=2.99 [1.38-6.48]). This association became more evident among patients not receiving antiplatelet therapy (Pinteraction=0.022). For patients undergoing different treatment modalities, similar increased risks were observed (clipping: adjusted odds ratio=3.43 [1.73-6.79]; and coiling: adjusted odds ratio=3.59 [1.94-6.65]). Higher ICAS score was correlated with higher procedural ischemic risk (Ptrend<0.001). CONCLUSIONS: The occurrence of ICAS is not infrequent in patients with UIAs. ICAS confers an ~2-fold increased procedural ischemic risk, irrespective of clipping or coiling. Previous antiplatelet therapy may decrease the risk. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT02795078.

Noise-resilient deep learning for integrated circuit tomography.

X-ray tomography is a non-destructive imaging technique that reveals the interior of an object from its projections at different angles. Under sparse-view and low-photon sampling, regularization priors are required to retrieve a high-fidelity reconstruction. Recently, deep learning has been used in X-ray tomography. The prior learned from training data replaces the general-purpose priors in iterative algorithms, achieving high-quality reconstructions with a neural network. Previous studies typically assume the noise statistics of test data are acquired a priori from training data, leaving the network susceptible to a change in the noise characteristics under practical imaging conditions. In this work, we propose a noise-resilient deep-reconstruction algorithm and apply it to integrated circuit tomography. By training the network with regularized reconstructions from a conventional algorithm, the learned prior shows strong noise resilience without the need for additional training with noisy examples, and allows us to obtain acceptable reconstructions with fewer photons in test data. The advantages of our framework may further enable low-photon tomographic imaging where long acquisition times limit the ability to acquire a large training set.

Comprehensive measurement of the near-infrared refractive index of GaAs at cryogenic temperatures.

The refractive index is a critical parameter in optical and photonic device design. However, due to the lack of available data, precise designs of devices working in low temperatures are still frequently limited. In this work, we have built a homemade spectroscopic ellipsometer (SE) and measured the refractive index of GaAs at a matrix of temperatures (4 K < T < 295 K) and photon wavelengths (700 nm < λ < 1000 nm) with a system error of ∼0.04. We verified the credibility of the SE results by comparing them with afore-reported data at room temperature and with higher precision values measured by vertical GaAs cavity at cryogenic temperatures. This work makes up for the lack of the near-infrared refractive index of GaAs at cryogenic temperatures and provides accurate reference data for semiconductor device design and fabrication.

The construction and operational models of internet hospitals in China: a hospital-based survey study.

BACKGROUND: China has empowered and continues to empower internet hospitals, which saw an increase in their development due to the pandemic, to fight against COVID-19. The construction and operational models of internet hospitals can be categorized as self-constructed and self-managed models, self-constructed and enterprise-run models, hospital and enterprise joint-owned models, and hosted by a third-party platform. Despite the growing importance of internet hospitals, there have been few systematic summaries of their construction and operational models. The primary purpose of the study was to understand the construction and operational models of internet hospitals in China. METHODS: Data was collected from 39 internet hospitals and 356 medical staff between September 2020 and April 2021, via internet hospital and hospital staff surveys. T-tests were used to compare the continuous variables, while Chi-square tests were employed to compare the proportions of categorical variables. The self-perception of the internet hospitals' services was assessed using a 5-point Likert scale on 16 aspects and a root cause analysis was conducted to identify the root causes and influencing factors of current deficiencies experienced by internet hospitals. RESULTS: Among the 39 internet hospitals, 22 (56.4%) were self-constructed and self-managed. Compared to other models of Internet hospitals, self-constructed and self-managed hospitals had lower percentages of professionals providing online services (P = 0.006), numbers of doctors outside of the entity (P = 0.006), numbers of online nurses (P = 0.004), and the ratio of online nurses to offline doctors (P < 0.001). Of the 16 aspects evaluated with regards to the medical staff's self-perception of the internet hospital services, the highest scores were given for fee transparency, fee rationality, travel cost capital, patience and responsibility, and consultation behaviors. The root causes included five aspects: human, channels, prices, services, and time. CONCLUSIONS: While the self-constructed and self-managed model was found to be the most prevalent form of internet hospital in China, the different models of internet hospitals can have an impact on both the quantity and quality of online healthcare services. This study contributes to the existing literature on internet hospitals' construction and operational models, offering additional policy implications for telemedicine management.

Barriers and facilitators to accessing sexual health services for older LGBTQIA+ adults: a global scoping review and qualitative evidence synthesis.

The number of older adults identifying as lesbian, gay, bisexual, transgender and other sexual and gender diverse identities (LGBTQIA+) is growing as populations age and social environments become more accepting. This study uses a global evidence synthesis to understand perceived barriers and facilitators to access to sexual healthcare globally for older LGBTQIA+ adults. We used a scoping review and qualitative evidence synthesis. Embase, PubMed and PsycInfo were searched with terms related to LGBTQIA+ populations, adults aged 45years, and sexual health care. We used the Cochrane Handbook and the review protocol was registered. Primary and secondary textual data were coded and grouped into themes using PRISMA-SCR and the Minority Stress Model. The certainty of review findings was assessed using the GRADE-CERQual approach. We identified 19 studies and 15 were included in the qualitative evidence synthesis. All studies were from high-income countries. Heterocentricity and male-centricity of sexual healthcare services contributed to feelings of exclusion for older LGBTQIA+ adults. Both anticipated and enacted stigma from healthcare providers resulted in older LGBTQIA+ adults, especially those with chronic conditions, avoiding health services (seven studies each, low certainty). Older LGBTQIA+ adults have unique sexual health needs and may feel their age empowers them to access appropriate care (four studies, low certainty). This review highlights the need for additional research and interventions to improve sexual health services for older LGBTQIA+ adults. Practical strategies to make sexual health less heterocentric (e.g. gender neutral signage) may increase uptake of essential sexual health services.

[Corona virus disease 2019 lesion segmentation network based on an adaptive joint loss function].

Corona virus disease 2019 (COVID-19) is an acute respiratory infectious disease with strong contagiousness, strong variability, and long incubation period. The probability of misdiagnosis and missed diagnosis can be significantly decreased with the use of automatic segmentation of COVID-19 lesions based on computed tomography images, which helps doctors in rapid diagnosis and precise treatment. This paper introduced the level set generalized Dice loss function (LGDL) in conjunction with the level set segmentation method based on COVID-19 lesion segmentation network and proposed a dual-path COVID-19 lesion segmentation network (Dual-SAUNet++) to address the pain points such as the complex symptoms of COVID-19 and the blurred boundaries that are challenging to segment. LGDL is an adaptive weight joint loss obtained by combining the generalized Dice loss of the mask path and the mean square error of the level set path. On the test set, the model achieved Dice similarity coefficient of (87.81 ± 10.86)%, intersection over union of (79.20 ± 14.58)%, sensitivity of (94.18 ± 13.56)%, specificity of (99.83 ± 0.43)% and Hausdorff distance of 18.29 ± 31.48 mm. Studies indicated that Dual-SAUNet++ has a great anti-noise capability and it can segment multi-scale lesions while simultaneously focusing on their area and border information. The method proposed in this paper assists doctors in judging the severity of COVID-19 infection by accurately segmenting the lesion, and provides a reliable basis for subsequent clinical treatment.

Recurrent neural network reveals transparent objects through scattering media.

Scattering generally worsens the condition of inverse problems, with the severity depending on the statistics of the refractive index gradient and contrast. Removing scattering artifacts from images has attracted much work in the literature, including recently the use of static neural networks. S. Li et al. [Optica5(7), 803 (2018)10.1364/OPTICA.5.000803] trained a convolutional neural network to reveal amplitude objects hidden by a specific diffuser; whereas Y. Li et al. [Optica5(10), 1181 (2018)10.1364/OPTICA.5.001181] were able to deal with arbitrary diffusers, as long as certain statistical criteria were met. Here, we propose a novel dynamical machine learning approach for the case of imaging phase objects through arbitrary diffusers. The motivation is to strengthen the correlation among the patterns during the training and to reveal phase objects through scattering media. We utilize the on-axis rotation of a diffuser to impart dynamics and utilize multiple speckle measurements from different angles to form a sequence of images for training. Recurrent neural networks (RNN) embedded with the dynamics filter out useful information and discard the redundancies, thus quantitative phase information in presence of strong scattering. In other words, the RNN effectively averages out the effect of the dynamic random scattering media and learns more about the static pattern. The dynamical approach reveals transparent images behind the scattering media out of speckle correlation among adjacent measurements in a sequence. This method is also applicable to other imaging applications that involve any other spatiotemporal dynamics.

Accurate Measurement of the Gap of Graphene/h-BN Moiré Superlattice through Photocurrent Spectroscopy.

Monolayer graphene aligned with hexagonal boron nitride (h-BN) develops a gap at the charge neutrality point (CNP). This gap has previously been extensively studied by electrical transport through thermal activation measurements. Here, we report the determination of the gap size at the CNP of graphene/h-BN superlattice through photocurrent spectroscopy study. We demonstrate two distinct measurement approaches to extract the gap size. A maximum of ∼14 meV gap is observed for devices with a twist angle of less than 1°. This value is significantly smaller than that obtained from thermal activation measurements, yet larger than the theoretically predicted single-particle gap. Our results suggest that lattice relaxation and moderate electron-electron interaction effects may enhance the CNP gap in graphene/h-BN superlattice.

Real-time in situ detection of the local air pollution with laser-induced breakdown spectroscopy: errata.

One misprint in our manuscript is reported and corrected.

Online detection of halogen atoms in atmospheric VOCs by the LIBS-SPAMS technique.

Volatile organic compounds (VOCs) are one of the major pollutants in the atmospheric and indoor environment. The direct detection of halogen atoms in VOCs via laser induced breakdown spectroscopy (LIBS) is highly challenging work because of the high ionization energy of these halogen elements. In this paper, the LIBS system combined with a self-designed single particle aerosol mass spectrometry (SPAMS) system were applied to the direct online detection of VOCs in the atmosphere. The experimental parameters of LIBS experiment were optimized in the measurement of ambient air. Under the best experimental conditions, the characteristic peaks of nitrogen, hydrogen, oxygen, as well as argon, were observed in the LIBS spectra of air. Then, LIBS and SPAMS measurements were performed on Halon 2402, Freon R11 and iodomethane samples under the atmospheric pressure. The characteristic spectral lines of fluorine, chlorine, bromine and iodine were observed and recorded in LIBS spectra. The SPAMS measurements also provide the elemental compositional information of individual VOCs aerosol particles in real time, which is an effective supplement to LIBS analysis. In addition, the different isotopes of bromine and chlorine can be clearly distinguished at the same time. Finally, the home-built portable Raman spectrometer was utilized to analyze the vibrational modes and get the "spectral fingerprint" of VOCs. All the results indicate that the direct online detection performed by the LIBS and SPAMS techniques could provide elemental and isotopic information of halogen atoms in atmospheric VOCs.

CRISPR/Cas technology promotes the various application of Dunaliella salina system.

Dunaliella salina (D. salina) has been widely applied in various fields because of its inherent advantages, such as the study of halotolerant mechanism, wastewater treatment, recombinant proteins expression, biofuel production, preparation of natural materials, and others. However, owing to the existence of low yield or in the laboratory exploration stage, D. salina system has been greatly restricted for practical production of various components. In past decade, significant progresses have been achieved for research of D. salina in these fields. Among them, D. salina as a novel expression system demonstrated a bright prospect, especially for large-scale production of foreign proteins, like the vaccines, antibodies, and other therapeutic proteins. Due to the low efficiency, application of traditional regulation tools is also greatly limited for exploration of D. salina system. The emergence of the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas system offers a precise editing tool to overcome the obstacles of D. salina system. This review not only comprehensively summarizes the recent progresses of D. salina in domain of gene engineering but also gives a deep analysis of problems and deficiencies in different fields of D. salina. Moreover, further prospects of CRISPR/Cas system and its significant challenges have been discussed in various aspects of D. salina. It provides a great referencing value for speeding up the maturity of D. salina system, and also supplies practical guiding significance to expand the new application fields for D. salina. KEY POINTS: • The review provides recent research progresses of various applications of D. salina. • The problems and deficiencies in different fields of D. salina were deeply analyzed. • The further prospects of CRISPR/Cas technology in D. salina system were predicted. • CRISPR/Cas system will promote the new application fields and maturity for D. salina.

Real-time in situ detection of the local air pollution with laser-induced breakdown spectroscopy.

The smoke of burning mosquito-repellent incense was taken as an example for the local air pollution to be detected and analyzed in situ and in real time. And the spectra of the ambient air, human breathing, and smoke were detected in situ with the LIBS technique. There are some additional spectral lines being found in human breathing, such as the C, Hß line, and the CN molecular bands. Some characteristic peaks of the elements Fe, Ca, Ti, Sr, and Cr have been observed in the smoke. Moreover, the vibrational and rotational temperature of the CN molecule were calculated. The mosquito-repellent incense was dipped into the solutions containing Mn and Pb to simulate heavy metal pollution in the atmosphere.

Broadband nonvolatile photonic switching based on optical phase change materials: beyond the classical figure-of-merit.

In this Letter, we propose a broadband, nonvolatile on-chip switch design in the telecommunication C-band with record low loss and crosstalk. The unprecedented device performance builds on: 1) a new optical phase change material (O-PCM) Ge2Sb2Se4Te1 (GSST), which exhibits significantly reduced optical attenuation compared to traditional O-PCMs, and 2) a nonperturbative design that enables low-loss device operation beyond the classical figure-of-merit (FOM) limit. We further demonstrate that the 1-by-2 and 2-by-2 switches can serve as basic building blocks to construct nonblocking and nonvolatile on-chip switching fabric supporting arbitrary numbers of input and output ports.

Luteolin protects mouse hippocampal neuronal cells against isoflurane-induced neurotoxicity through miR-214/PTEN/Akt pathway.

Isoflurane is one of the most commonly used anaesthetic agents in surgery procedures. During the past decades, isoflurane has been found to cause impairment in neurological capabilities in new-borns and elderly patients. Luteolin is a flavonoid that has been documented to possess a neuroprotective effect. Here we investigated the putative neuroprotective effects of luteolin on isoflurane-induced neurotoxicity in mouse hippocampal neuronal HT22 cells and explored the potential mechanisms. We demonstrated that luteolin improved mitochondrial dysfunction and reduced oxidative stress and apoptosis in isoflurane-treated HT22 cells, and thus inhibiting the isoflurane-induced neuronal injury. Further investigations showed that isoflurane exposure caused miR-214 downregulation, which could be mitigated by treatment with luteolin. Knockdown of miR-214 attenuated the neuroprotection of luteolin on isoflurane-induced neuronal injury. More importantly, luteolin inhibited isoflurane-caused regulation of the PTEN/Akt pathway, while miR-214 knockdown altered the regulatory effect of luteolin on the PTEN/Akt pathway. Furthermore, the effects of miR-214 knockdown on the neuroprotection of luteolin could also be prevented by knockdown of PTEN, implying that the neuroprotective effect of luteolin was mediated by miR-214/PTEN/Akt signaling pathway. These findings provided evidence for the potential application of luteolin in preventing isoflurane-induced neurotoxicity.

Context-aware and local-aware fusion with transformer for medical image segmentation.

Objective. Convolutional neural networks (CNNs) have made significant progress in medical image segmentation tasks. However, for complex segmentation tasks, CNNs lack the ability to establish long-distance relationships, resulting in poor segmentation performance. The characteristics of intra-class diversity and inter-class similarity in images increase the difficulty of segmentation. Additionally, some focus areas exhibit a scattered distribution, making segmentation even more challenging.Approach. Therefore, this work proposed a new Transformer model, FTransConv, to address the issues of inter-class similarity, intra-class diversity, and scattered distribution in medical image segmentation tasks. To achieve this, three Transformer-CNN modules were designed to extract global and local information, and a full-scale squeeze-excitation module was proposed in the decoder using the idea of full-scale connections.Main results. Without any pre-training, this work verified the effectiveness of FTransConv on three public COVID-19 CT datasets and MoNuSeg. Experiments have shown that FTransConv, which has only 26.98M parameters, outperformed other state-of-the-art models, such as Swin-Unet, TransAttUnet, UCTransNet, LeViT-UNet, TransUNet, UTNet, and SAUNet++. This model achieved the best segmentation performance with a DSC of 83.22% in COVID-19 datasets and 79.47% in MoNuSeg.Significance. This work demonstrated that our method provides a promising solution for regions with high inter-class similarity, intra-class diversity and scatter distribution in image segmentation.

Histamine and receptors in neuroinflammation: Their roles on neurodegenerative diseases.

Histamine, an auto-reactive substance and mediator of inflammation, is synthesized from histidine through the action of histidine decarboxylase (HDC). It primarily acts on histamine receptors in the central nervous system (CNS). Increasing evidence suggests that histamine and its receptors play a crucial role in neuroinflammation, thereby modulating the pathology of neurodegenerative diseases. Recent studies have demonstrated that histamine regulates the phenotypic switching of microglia and astrocytes, inhibits the production of pro-inflammatory cytokines, and alleviates inflammatory responses. In the CNS, our research group has also found that histamine and its receptors are involved in regulating inflammatory responses and play a central role in ameliorating chronic neuroinflammation in neurodegenerative diseases. In this review, we will discuss the role of histamine and its receptors in neuroinflammation associated with neurodegenerative diseases, potentially providing a novel therapeutic target for the treatment of chronic neuroinflammation-related neurodegenerative diseases in clinical settings.

Release characteristics of volatile organic compounds at residential garbage collection points: a case study of Hangzhou, China.

With the implementation of garbage classification, perishable waste has become increasingly concentrated. This has led to a significant change in the VOC release characteristics at residential garbage collection points, posing a potential risk with unknown characteristics. This study investigated the release characteristics, odor pollution, and health risks of VOCs at garbage collection points under different classification effectiveness, seasons, garbage drop-off periods, and garbage collection point types. The results showed that the average concentration of VOCs released from the garbage sorting collection points (SPs) was 341.43 ± 261.16 µg/m3, and oxygenated compounds (e.g., ethyl acetate and acetone) were the main VOC components. The VOC concentration increased as the community classification effectiveness improved, and it was higher in summer (followed by spring, autumn, and winter). Moreover, the VOC concentrations were higher in the evenings than in the mornings and at centralized garbage collection points (CPs) than at SPs. Further, odor activity value (OAV) assessments indicated that acrolein, styrene, and ethyl acetate were the critical odorous components, with an average OAV of 0.87 ± 0.85, implying marginal odor pollution in some communities. Health risk assessments further revealed that trichloroethylene, benzene, and chlorotoluene were the critical health risk substances, with an average carcinogenic risk (CR) value of 10-6-10-4, and a non-carcinogenic risk (HI) value < 1. These results indicated that HIs were acceptable, but potential CRs existed in the communities. Therefore, VOC pollution prevention and control measures should be urgently strengthened at the garbage collection points in high pollution risk scenarios.

Risk Factors for Specific Postoperative Ischemic Complications in Patients with Moyamoya Disease: A Single-Center Retrospective Study.

AIM: To evaluate and compare postoperative ischemic complications to determine the risk factors for ischemic complications following revascularization surgery for Moyamoya disease (MMD). MATERIAL AND METHODS: This single-center retrospective study included 266 procedures between 2016 and 2021. Three types of revascularization approaches including direct bypass, indirect bypass, and combined bypass were performed. To identify risk factors for postoperative ischemic complications and contralateral cerebral infarction, preoperative clinical characteristics and radiographic features were examined using multivariate and ordinal logistic regression analyses. RESULTS: Postoperative ischemic complications occurred in 103 (6.6%) procedures. Ischemic presentation (p=0.001, odds ratios [OR] 5.59, 95% confidence interval [CI] 2.05-15.23), hypertension (p=0.030, OR 2.75, 95%CI 1.11- 6.83), advanced Suzuki stage (p=0.006, OR 3.19, 95%CI 1.40-7.26), and collateral circulation (p=0.001 OR 0.17, 95%CI 0.06-0.47) were risk factors for postoperative ischemic complications. Ordinal regression analysis revealed that unilateral involvement (p=0.043, OR 2.70, 95%CI 0.09-5.31), hemorrhagic presentation (p=0.013, OR 3.45, 95%CI 0.72-6.18), surgical approach (p=0.032, OR -1.38, 95%CI -2.65, -0.12), and collateral circulation [p=0.043, OR -1 .27, 95%CI -2.51, -0.04)] were associated with the type of ischemic complications. History of hypertension (p=0.031) and contralateral computed tomography (CT) perfusion stage (p=0.045) were associated with contralateral infarction. CONCLUSION: Inability of cerebral vessels to withstand changes in blood pressure induced by revascularization-related hemodynamic instability might be associated with postoperative complications in patients with Moyamoya disease.