Elevation recognition in architecture drawings for 3D converting to BIM models

Building Information Modelling (BIM) is recognized as the next generation of techniques that will bring about digitalization revolution to global AEC industry. Developing countries, such as China, still use CAD in building project. It is valuable to transform architecture drawings to BIM models in a cost-efficient way. Current researches on 3D reconstruction of architecture drawings work on floor plan detection. The problem is elevation and height information in floor plan is not always accessible. This research studies how to use layer property in CAD to detect elevation drawing and combine with floor plan recognition to deliver a comprehensive 3D reconstruction. The layer property and conventions are studied, and an automatic layer classification method (ALCM) is proposed to identify the semantic meaning of layer. Based on ALCM, a method to detect elevation drawing is proposed. Bounding box is created from the floor plan detection and visibility analysis. It can achieve elevation member measuring by searching the inside primitives. ALCM is tested with 70 plan drawings. The average accuracy is 95%, which implies reliable performance. Taking advantage of ALCM, the layer of demanding structural members or symbols are known. The results are inputted in the implementation of elevation detection testing. 50 pieces of elevation drawings are used to evaluate the orientation recognition method; two sets of complete architecture drawings, containing 8 elevation drawings and 36 floor plans, are adopted to test the rest of algorithms. It is found that the precision and recall rate of visibility analysis is 70.6% and 98.4%, which suggests an optimistic capability to catch visible objects, but some invisible objects are also mistaken. It leads to creation of invalid bounding box. Through the elevation detection algorithm, 87% of visible members in elevation drawing successfully acquire their height and offset value. The algorithm is applied in a practical use in University of Nottingham, Ningbo, China. A teaching building is automatically modeled in Revit with correct family dimension and position

An ontology-aided, natural language-based approach for multi-constraint BIM model querying

Being able to efficiently retrieve the required building information is critical for construction project stakeholders to carry out their engineering and management activities. Natural language interface (NLI) systems are emerging as a time and cost-effective way to query Building Information Models (BIMs). However, the existing methods cannot logically combine different constraints to perform fine-grained queries, dampening the usability of natural language (NL)-based BIM queries. This paper presents a novel ontology-aided semantic parser to automatically map natural language queries (NLQs) that contain different attribute and relational constraints into computer-readable codes for querying complex BIM models. First, a modular ontology was developed to represent NL expressions of Industry Foundation Classes (IFC) concepts and relationships, and was then populated with entities from target BIM models to assimilate project-specific information. Hereafter, the ontology-aided semantic parser progressively extracts concepts, relationships, and value restrictions from NLQs to fully identify constraint conditions, resulting in standard SPARQL queries with reasoning rules to successfully retrieve IFC-based BIM models. The approach was evaluated based on 225 NLQs collected from BIM users, with a 91% accuracy rate. Finally, a case study about the design-checking of a real-world residential building demonstrates the practical value of the proposed approach in the construction industry

Searching for axion dark matter with MeerKAT Radio Telescope

Axions provide a natural and well-motivated dark matter candidate, with the capability to convert directly to photons in the presence of an electromagnetic field. A particularly compelling observational target is the conversion of dark matter axions into photons in the magnetospheres of highly magnetised neutron stars, which is expected to produce a narrow spectral peak centred at the frequency of the axion mass. We point the MeerKAT radio telescope towards the isolated neutron star J0806.4$-$4123 for $10$-hours of observation and obtain the radio spectra in the frequency range $769$-$1051$ MHz. By modelling the conversion process of infalling axion dark matter (DM), we then compare these spectra to theoretical expectations for a given choice of axion parameters. Whilst finding no signal above $5\sigma$ in the data, we provide a unique constraint on the Primakoff coupling of axion DM, $g_{{\rm a}\gamma\gamma}\lesssim 9.3 \times 10^{-12}\,{\rm GeV}^{-1}$ at the $95\%$ confidence level, in the mass range $3.18$-$4.35\,\mu$eV. This result serves the strongest constraint in the axion mass range $4.20$-$4.35\,\mu$eV.Comment: 6 pages, 3 figures, accepted by Physical Review

Elevation recognition in architecture drawings for 3D converting to BIM models

Building Information Modelling (BIM) is recognized as the next generation of techniques that will bring about digitalization revolution to global AEC industry. Developing countries, such as China, still use CAD in building project. It is valuable to transform architecture drawings to BIM models in a cost-efficient way. Current researches on 3D reconstruction of architecture drawings work on floor plan detection. The problem is elevation and height information in floor plan is not always accessible. This research studies how to use layer property in CAD to detect elevation drawing and combine with floor plan recognition to deliver a comprehensive 3D reconstruction. The layer property and conventions are studied, and an automatic layer classification method (ALCM) is proposed to identify the semantic meaning of layer. Based on ALCM, a method to detect elevation drawing is proposed. Bounding box is created from the floor plan detection and visibility analysis. It can achieve elevation member measuring by searching the inside primitives. ALCM is tested with 70 plan drawings. The average accuracy is 95%, which implies reliable performance. Taking advantage of ALCM, the layer of demanding structural members or symbols are known. The results are inputted in the implementation of elevation detection testing. 50 pieces of elevation drawings are used to evaluate the orientation recognition method; two sets of complete architecture drawings, containing 8 elevation drawings and 36 floor plans, are adopted to test the rest of algorithms. It is found that the precision and recall rate of visibility analysis is 70.6% and 98.4%, which suggests an optimistic capability to catch visible objects, but some invisible objects are also mistaken. It leads to creation of invalid bounding box. Through the elevation detection algorithm, 87% of visible members in elevation drawing successfully acquire their height and offset value. The algorithm is applied in a practical use in University of Nottingham, Ningbo, China. A teaching building is automatically modeled in Revit with correct family dimension and position

Small extracellular vesicles as potential theranostic tools in central nervous system disorders

Small extracellular vesicles(sEVs), a subset of extracellular vesicles with a bilateral membrane structure, contain biological cargoes, such as lipids, nucleic acids, and proteins. sEVs are crucial mediators of intercellular communications in the physiological and pathological processes of the central nervous system. Because of the special structure and complex pathogenesis of the brain, central nervous system disorders are characterized by high mortality and morbidity. Increasing evidence has focused on the potential of sEVs in clinical application for central nervous system disorders. sEVs are emerging as a promising diagnostic and therapeutic tool with high sensitivity, low immunogenicity, superior safety profile, and high transfer efficiency. This review highlighted the development of sEVs in central nervous system disorder clinical application. We also outlined the role of sEVs in central nervous system disorders and discussed the limitations of sEVs in clinical translation

Health and economic costs of an import-initiated measles outbreak in an international border area of Yunnan Province

Background Measles outbreaks often require labor- and resource-intense response. A border-area measles outbreak occurred in Yunnan province that required outbreak response immunization for its containment. We report results of our investigation into the outbreak and the health sector costs of the response activities, with the goal of providing evidence for policy makers when considering the full value of vaccines and of measles elimination. Methods We conducted case investigations to determine sources of infection and routes of transmission. Costs of outbreak response activities incurred by health sector were determined through retrospective interviews and record reviews of staff. Results In total, 67 measles cases were confirmed, including 4 cases imported from Myanmar. Among the 33 cases aged between 8 months and 14 y old, 22 (66∙7%) had received 2 doses of MCV; 2 (6∙0%) had received 1 dose of MCV; 9 (27∙3%) had not received MCV. The first 4 cases had been infected in Myanmar, and we identified 8 transmission clusters with a total of 62 cases. Transmission among Yunnan province residents occurred in schools, family settings, and at gatherings. The overall cost to control the outbreak was $214,774, for a per-case cost of$3,206. The outbreak response vaccination campaign accounted for 64% of the total outbreak costs. Conclusions Despite high population immunity among Yunnan province children and adolescents, an import-related measles outbreak occurred among individuals who were not vaccinated or had vaccine failure in the across-border area. The economic cost of the outbreak was substantial. Investment in a sensitive measles surveillance system to detect outbreaks in a timely manner, maintaining high population immunity to measles, and reinforcing cross-border collaboration with neighboring countries support achieving and sustaining measles elimination in the border areas of China

Intranasal Delivery of Gene-Edited Microglial Exosomes Improves Neurological Outcomes after Intracerebral Hemorrhage by Regulating Neuroinflammation

Neural inflammatory response is a crucial pathological change in intracerebral hemorrhage (ICH) which accelerates the formation of perihematomal edema and aggravates neural cell death. Although surgical and drug treatments for ICH have advanced rapidly in recent years, therapeutic strategies that target and control neuroinflammation are still limited. Exosomes are important carriers for information transfer among cells. They have also been regarded as a promising therapeutic tool in translational medicine, with low immunogenicity, high penetration through the blood-brain barrier, and ease of modification. In our previous research, we have found that exogenous administration of miRNA-124-overexpressed microglial exosomes (Exo-124) are effective in improving post-injury cognitive impairment. From this, we evaluated the potential therapeutic effects of miRNA-124-enriched microglial exosomes on the ICH mice in the present study. We found that the gene-edited exosomes could attenuate neuro-deficits and brain edema, improve blood–brain barrier integrity, and reduce neural cell death. Moreover, the protective effect of Exo-124 was abolished in mice depleted of Gr-1+ myeloid cells. It suggested that the exosomes exerted their functions by limiting the infiltration of leukocyte into the brain, thus controlling neuroinflammation following the onset of ICH. In conclusion, our findings provided a promising therapeutic strategy for improving neuroinflammation in ICH. It also opens a new avenue for intranasal delivery of exosome therapy using miRNA-edited microglial exosomes

Emerging negative impact of warming on summer carbon uptake in northern ecosystems

International audienceMost studies of the northern hemisphere carbon cycle based on atmospheric CO 2 concentration have focused on spring and autumn, but the climate change impact on summer carbon cycle remains unclear. Here we used atmospheric CO 2 record from Point Barrow (Alaska) to show that summer CO 2 drawdown between July and August, a proxy of summer carbon uptake, is significantly negatively correlated with terrestrial temperature north of 50°N interannually during 1979-2012. However, a refined analysis at the decadal scale reveals strong differences between the earlier (1979-1995) and later (1996-2012) periods, with the significant negative correlation only in the later period. This emerging negative temperature response is due to the disappearance of the positive temperature response of summer vegetation activities that prevailed in the earlier period. Our finding, together with the reported weakening temperature control on spring carbon uptake, suggests a diminished positive effect of warming on high-latitude carbon uptake

Data_Sheet_3_Potential blood biomarkers for chronic traumatic encephalopathy: The multi-omics landscape of an observational cohort.XLSX

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with exposure to repetitive head impacts, which is susceptible in elderly people with declined mobility, athletes of full contact sports, military personnel and victims of domestic violence. It has been pathologically diagnosed in brain donors with a history of repetitive mild traumatic brain injury (rmTBI), but cannot be clinically diagnosed for a long time. By the continuous efforts by neuropathologists, neurologists and neuroscientists in recent 10 years, an expert consensus for the diagnostic framework of CTE was proposed in 2021 funded by the National Institute of Neurological Disorders and Stroke. The new consensus contributes to facilitating research in the field. However, it still needs to incorporate in vivo biomarkers to further refine and validate the clinical diagnostic criteria. From this, a single-center, observational cohort study has been being conducted by Tianjin Medical University General Hospital since 2021. As a pilot study of this clinical trial, the present research recruited 12 pairs of gender- and age-matched rmTBI patients with healthy subjects. Their blood samples were collected for exosome isolation, and multi-omics screening to explore potential diagnostic biomarkers in blood and its exosomes. The expression level of CHL1 protein, KIF2A mRNA, LIN7C mRNA, miR-297, and miR-1183 in serum and exosomes were found to be differentially expressed between groups. Besides, serum and exosomal CHL1, KIF2A, and miR-1183, as well as exosomal miR-297 were further verified as potential biomarkers for CTE by low-throughput assays. They are expected to contribute to establishing a novel set of CTE diagnostic signatures with classic neurodegenerative indicators in our future study, thereby updating the consensus diagnostic criteria for CTE by incorporating new evidence of the in vivo biomarkers.</p

Data_Sheet_4_Potential blood biomarkers for chronic traumatic encephalopathy: The multi-omics landscape of an observational cohort.XLSX

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with exposure to repetitive head impacts, which is susceptible in elderly people with declined mobility, athletes of full contact sports, military personnel and victims of domestic violence. It has been pathologically diagnosed in brain donors with a history of repetitive mild traumatic brain injury (rmTBI), but cannot be clinically diagnosed for a long time. By the continuous efforts by neuropathologists, neurologists and neuroscientists in recent 10 years, an expert consensus for the diagnostic framework of CTE was proposed in 2021 funded by the National Institute of Neurological Disorders and Stroke. The new consensus contributes to facilitating research in the field. However, it still needs to incorporate in vivo biomarkers to further refine and validate the clinical diagnostic criteria. From this, a single-center, observational cohort study has been being conducted by Tianjin Medical University General Hospital since 2021. As a pilot study of this clinical trial, the present research recruited 12 pairs of gender- and age-matched rmTBI patients with healthy subjects. Their blood samples were collected for exosome isolation, and multi-omics screening to explore potential diagnostic biomarkers in blood and its exosomes. The expression level of CHL1 protein, KIF2A mRNA, LIN7C mRNA, miR-297, and miR-1183 in serum and exosomes were found to be differentially expressed between groups. Besides, serum and exosomal CHL1, KIF2A, and miR-1183, as well as exosomal miR-297 were further verified as potential biomarkers for CTE by low-throughput assays. They are expected to contribute to establishing a novel set of CTE diagnostic signatures with classic neurodegenerative indicators in our future study, thereby updating the consensus diagnostic criteria for CTE by incorporating new evidence of the in vivo biomarkers.</p