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Objectives: To explore whether dual-energy computed tomography (DECT) angiography can provide reliable quantitative information on net water uptake (NWU) of ischemic brain to identify stroke patients within 4.5 h. Methods: We retrospectively reviewed 142 patients with stroke occurrence and who underwent DECT angiography between August 2016 and May 2022. DECT angiography manual drawn the ischemic area by referring to the normal area of the contralateral hemisphere and follow-up images. The NWU in the ischemic area was determined using virtual non-contrast and monoenergetic (VNC &VM) images acquired from DECT angiography. The NWU values in the ischemic area were compared between stroke patients within and beyond 4.5 h. The diagnostic performance of the NWU values derived from the VNC and VM images was assessed through receiver operating characteristic curve analysis. Additionally, Furthermore, we examined the correlation between the NWU values and the stroke onset time. Results: Seventy-eight (54.93 %) stroke patients underwent DECT angiography and within 4.5 h. These patients with lower median National Institute of Health stroke scale (NIHSS) scores on admission than those beyond 4.5 h (p

This case study conducted a cradle-to-gate life cycle assessment (LCA) on the production of hardwood lumber in New Brunswick, Canada, evaluating the environmental impacts from raw material extraction to the point where lumber exited the mill as rough green lumber, the primary input for manufacturing pallets and railway ties. Data on annual production, material flow, and energy use for harvesting and sawmilling were gathered through survey questionnaires and on-site visits. The life cycle inventory (LCI) was developed in SimaPro software, the life cycle impact assessment (LCIA) was conducted using the North American TRACI method to quantify impact categories, and the cumulative energy demand (CED) method was employed to analyze the total energy consumption. It was found that rough green hardwood lumber production emitted approximately 41 kg CO2−eq/m3 (excluding biogenic carbon storage), with manufacturing accounting for 42% of total emissions and consuming 736 MJ/m3 of total energy, 98% of which came from non-renewable sources. The carbon stored in lumber was 975 CO2 eq/m3, 24 times greater than its cradle-to-gate emissions, highlighting its significant environmental benefit. Future research will aim to conduct a cradle-to-grave LCA on hardwood production by including drying and planing and increase the number of sawmill samples. [ABSTRACT FROM AUTHOR]

The processes of hemp bast fiber retting, forming, and drying offer the opportunity for value-added products such as natural fiber-reinforced composites. A new process for the retting of raw bast fibers through enzyme-triggered self-cultured bacterial retting was developed in the lab-scale setup. This study focused on comparing the energy consumption and environmental impacts of this bacterial retting process with the thermochemical retting process currently widely used to obtain lignocellulosic fibers for composites. The gate-to-gate life cycle assessment (LCA) models of the two retting processes were constructed to run a comparison analysis using the TRACI (the tool for the reduction and assessment of chemical and other environmental impacts) method for environmental impacts and the cumulative energy demand (CED) method for energy consumptions. This work has demonstrated the advantages of the bacterial retting method from an environmental standpoint. The result of our research shows about a 24% gate-to-gate reduction in CED for bacterial retting and 20–25% lower environmental impacts relating to global warming, smog formation, acidification, carcinogenics, non-carcinogenics, respiratory effects, ecotoxicity, and fossil fuel depletion when compared to that of thermochemical retting. [ABSTRACT FROM AUTHOR]

Buildings play a significant role in the rise of energy consumption and carbon emissions. Building operations are responsible for 28% of the world's carbon emissions. It is crucial, therefore, to evaluate the environmental impact of various buildings' operational phase in order to implement sustainable strategies for the mitigation of their energy usage and associated carbon footprint. While numerous studies have been conducted to determine the carbon footprint of conventional building operation phases, there are still a lack of actual data on the operational carbon (OC) emissions of mass timber buildings. There is also a lack of research pertaining to the operational carbon of buildings within larger campuses and their inherent energy usage. This study, therefore, aims to quantify empirical data on the carbon footprint of a mass timber building, using, as a case study, the recent Adohi Hall building, situated at the University of Arkansas, Fayetteville. The study also aims to examine and identify the best energy use scenarios for the campus building under consideration. The research team obtained data on Adohi Hall's energy consumption, fuel input usage, and other utilities (such as water, electricity, chilled water, and natural gas) accounting for the operation of the building from 2021 to 2023, a span of three years. The University of Arkansas Facilities Management (FAMA) provided the data. The study relies on the life cycle assessment (LCA) as its primary approach, with SimaPro 9, Ecoinvent v3.7 database, DataSmart, version 2023.1 and the U.S. Life Cycle Inventory (USLCI) database utilized to model the energy and water consumption of Adohi Hall during the operational phase (B6 & B7). The results indicate 4496 kg CO2 eq emissions associated with the operation per square meter of Adohi Hall over its 50-year lifespan. The study also examines various scenarios of fuel sources leading to carbon emissions and provides insights into reduction strategies during the operational phase of buildings. Among them, the electricity based on a cleaner fuel source diversification, according to realistic expectations and technological advancements projections, results in a 17% reduction in Adohi Hall's OC. Due to the usage of the combined heat and power (CHP) plant on the campus of the University of Arkansas as a complementary source of electricity and heating for Adohi Hall, the resulting carbon emission is approximately 21% (20.73%) less when compared to similar buildings in the same city but outside the campus. The study, therefore, reveals that CHP plant development is a highly effective strategy for building OC reduction. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to quantify and compare the embodied carbon (EC) from the materials used or designed to build the Adohi Hall, a residence building located on the University of Arkansas campus in Fayetteville, AR. It has been constructed as a mass timber structure. It is compared to the same building design with a steel frame for this study. Based on the defined goal and scope of the project, all materials used in the building structure are compared for their global warming potential (GWP) impact by applying a life cycle assessment (LCA) using a cradle-to-construction site system boundary. This comparative building LCA comprises the product stage (including raw material extraction, processing, transporting, and manufacturing) plus transportation to the construction site (nodule A1–A4, according to standard EN 15804 definitions). In this study, GWP is primarily assessed with the exclusion of other environmental factors. Tally®, as one of the most popular LCA tools for buildings, is used in this comparative LCA analysis. In this study, the substitution of mass timber for a steel structure with a corrugated steel deck and concrete topping offers a promising opportunity to understand the GWP impact of each structure. Mass timber structures exhibit superior environmental attributes considering the carbon dioxide equivalent (CO2 eq). Emissions per square meter of gross floor area for mass timber stand at 198 kg, in stark contrast to the 243 kg CO2 eq recorded for steel structures. This means the mass timber building achieved a 19% reduction in carbon emissions compared to the functional equivalent steel structure within the building modules A1 to A4 studied. When considering carbon storage, about 2757 tonnes of CO2 eq are stored in the mass timber building, presenting further benefits of carbon emission delays for the life span of the structure. The substitution benefit from this construction case was studied through the displacement factor (DF) quantification following the standard process. A 0.28 DF was obtained when using mass timber over steel in the structure. This study provides insights into making more environmentally efficient decisions in buildings and helps in the move forward to reduce greenhouse gas (GHG) emissions and address GWP mitigation. [ABSTRACT FROM AUTHOR]

Today, the application of green materials in the building industry is the norm rather than the exception and reflects an attempt to mitigate the sector's environmental impacts. Mass timber is growing rapidly in the construction field because of its long span, speed of installation, lightness and toughness, carbon sequestration capabilities, renewability, fire rating, acoustic isolation, and thermal resistance. Mass timber is close to overtaking steel and concrete as the preferred material. The endeavor of this research is to quantitatively assess the ability of this green material to leverage the abatement of carbon emissions. Life cycle assessment (LCA) is a leading method for assessing the environmental impacts of the building sector. The recently completed Adohi Hall mass timber building on the University of Arkansas campus was used as a case study in an investigation to quantify greenhouse gas (GHG) emissions throughout the construction phase only. The energy used in building operations is the most dominant source of emissions in the building industry and has galvanized research on increasing the efficiency of building operations, but reduced emissions have made the impacts of embodied carbon (EC) components more noticeable in the building life cycle. While most studies have focused on the manufacturing stage, only a few to date have focused on the construction process. Consequently, few data are available on the environmental impacts associated with the installation of mass timber as a new green material. The present study began with the quantification of the materials and an inventory of the equipment used for construction. Then, this study determined the EC associated with running the equipment for building construction. The GHG emissions resulting from the transportation of materials to the site were also quantified. Based on data collected from the construction site, the results of this study indicate that earthwork ranks first in carbon emissions, followed by mass timber installation and construction. In third place is ready-mix poured concrete and rebar installation, followed by Geopiers. A comparison of these results with those in the existing literature shows that the EC generally associated with the building construction phase has been underestimated to date. Furthermore, only emissions associated with the fuel usage of the main equipment were considered. [ABSTRACT FROM AUTHOR]

Liquiritin (LQ) is an important monomer active component in flavonoids of licorice. The objective of this study was to evaluate the hepatoprotective effects of LQ in cholestatic mice. LQ (40 or 80 mg/kg) was intragastrically administered to mice once daily for 6 days, and mice were treated intragastrically with a single dosage of ANIT (75 mg/kg) on the 5th day. On the 7th day, mice were sacrificed to collect blood and livers. The mRNA and protein levels were determined by qRT‐PCR and western blot assay. We also conducted systematical assessments of miRNAs expression profiles in the liver. LQ ameliorated ANIT‐induced cholestatic liver injury, as evidenced by reduced serum biochemical markers and attenuated pathological changes in liver. Pretreatment of LQ reduced the increase of malondialdehyde, TNF‐α, and IL‐1β induced by ANIT. Moreover, ANIT suppressed the expression of Sirt1 and FXR in liver tissue, which was weakened in the LQ pre‐treatment group. LQ enhanced the nuclear expression of Nrf2, which was increased in the ANIT group. LQ also increased the mRNA expressions of bile acid transporters Bsep, Ntcp, Mrp3, and Mrp4. Furthermore, a miRNA deep sequencing analysis revealed that LQ had a global regulatory effect on the hepatic miRNA expression. Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis showed that the differentially expressed miRNAs were mainly related to metabolic pathways, endocytosis, and MAPK signaling pathway. Collectively, LQ attenuated hepatotoxicity and cholestasis by regulating the expression of Sirt1/FXR/Nrf2 and the bile acid transporters, indicating that LQ might be an effective approach for cholestatic liver diseases. This study demonstrated that pre‐treatment of LQ can ameliorate serum biochemical markers, pathological changes in liver, and the increase of MDA, TNF‐α, and IL‐1β induced by ANIT, which suggested that LQ has a protective effect on cholestatic liver injury. Furthermore, the possible mechanism is to induce the expression of Sirt1/FXR/Nrf2 and modulate bile acid transporters BSEP, NTCP, MRP3, and MRP4. To sum up, LQ might be a potential approach for preventing and treating cholestatic liver diseases. [ABSTRACT FROM AUTHOR]

The identification of speech emotions is amongst the most strenuous and fascinating fields of machine learning science. In this article, Chinese emotions are classified as a disruptive atmosphere that classifies several feelings into four major emotional organizations: pleasure, sorrow, resentment, and neutrality. A machine learning in human emotion detection (ML-HED) framework is proposed. The technology suggested removing prosodic and spectrum elements of an audio wave, such as a pulse, power, amplitude, Cepstrum melt frequency correlations, linearly fixed Cepstral, and identification with a template. In all, 87,75% of performers' statements and 93% of women's actors were given reliability. The research findings show that the revolutionary technology achieves greater precision by accurately interpreting the feelings, which contrasts with current speech emotion recognition approaches. Besides, the derived characteristics were contrasting with various classification techniques in this study for the comprehensive idea. [ABSTRACT FROM AUTHOR]

• Radiomics features from combined intrathrombus and perithrombus regions enhance the predictive accuracy of intracranial hemorrhage risk following endovascular thrombectomy. • Our radiomic models provide valuable insights for optimizing clinical decision-making post-endovascular thrombectomy. • The robustness of radiomic approach is confirmed through successful multicenter validation. This study aimed to assess the predictive performance of radiomics derived from computed tomography (CT) images of thrombus regions in predicting the risk of intracranial hemorrhage (ICH) following endovascular thrombectomy (EVT). This retrospective multicenter study included 336 patients who underwent admission CT and EVT for acute anterior-circulation large vessel occlusion between December 2018 and December 2023. Follow-up imaging was performed 24 h post-procedure to evaluate the occurrence of ICH. 230 patients from centers A and B were randomly allocated into training and test groups in a 7:3 ratio, while the remaining 106 patients from center C comprised the validation cohort. Radiologists manually segmenting the thrombus on CT images, and the perithrombus region was defined by expanding the initial region of interest (ROI). A total of 428 radiomics features were extracted from both intrathrombus and perithrombus regions on CT images. The Mann–Whitney U test was used for feature selection, and least absolute shrinkage and selection operator (LASSO) regression was employed for model development, followed by validation using a 5-fold cross-validation approach. Model performance was assessed using the area under the curve (AUC) of the receiver operating characteristic (ROC). Among the eligible patients, 128 (38.1 %) experienced ICH after EVT. The combined model exhibited superior performance in the training cohort (AUC: 0.913, 95 % CI: 0.861–0.965), test cohort (AUC: 0.868, 95 % CI: 0.775–0.962), and validation cohort (AUC: 0.850, 95 % CI: 0.768–0.912). Notably, in the validation group, both the perithrombus and combined models demonstrated higher predictive accuracy compared to the intrathrombus model (0.837 vs. 0.684, p = 0.02; AUC: 0.850 vs. 0.684, p = 0.01). Radiomics features derived from the perithrombus region significantly enhance the prediction of ICH after EVT, providing valuable insights for optimizing post-procedural clinical decisions. This study highlights the importance of radiomics extracted from intrathrombus and perithrombus region in predicting intracranial hemorrhage following endovascular thrombectomy, which can aid in improving patient outcomes. [ABSTRACT FROM AUTHOR]