In the majority of Abhidharmic Buddhist schools, smṛti serves the crucial function of ensuring the recollection of past events and is thus conceptualized as memory in scholarly discourse nowadays. Nevertheless, upon closer examination of various doctrinal perspectives, the interpretation of smṛti diverges significantly among different schools. Notably, it is deemed to be omnipresent in every moment of perception within the Sarvāstivādin tradition, while in Yogācāra, it is regarded as a specific response to an experienced object. This paper seeks to delve into the concept of smṛti within the latter tradition, with a specific focus on the Cheng Weishi Lun (成唯識論, henceforth: CWSL). Drawing upon the foundational principles of Yogācāra doctrine, which posit the ālayavijñāna as an underlying substratum responsible for retaining past information, I contend that smṛti embodies a cognitive faculty that intensifies the apprehension of learned objects when they are present. Furthermore, I argue that smṛti serves as the inception point for a series of cognitive processes acquiring knowledge that helps decision-making. Additionally, I will demonstrate that the function of smṛti in the CWSL diverges from both traditional Buddhist conceptions of memory and contemporary understandings thereof. Full article

High-rise timber residential towers (≥eight-stories) represent a burgeoning and auspicious sector, predominantly due to their capability to provide significant ecological and financial advantages throughout their lifecycle. Like numerous other building types, spatial optimization in high-rise timber residential structures stands as a pivotal design factor essential for project viability. Presently, there exists no comprehensive investigation on space efficiency in such towers. This study analyzed data from 51 case studies to enhance understanding of the design considerations influencing space efficiency in high-rise timber residential towers. Key findings included (1) the average space efficiency within the examined cases was recorded at 83%, exhibiting variances ranging from 70% to 93% across different cases, (2) the average percentage of core area to gross floor area (GFA) was calculated at 10%, demonstrating fluctuations within the range of 4% to 21% across diverse scenarios, and (3) no notable distinction was observed in the effect of various core planning strategies on spatial efficiency when properly designed, and similar conclusions were drawn regarding building forms and structural materials. This research will aid in formulating design guidelines tailored for various stakeholders such as architectural designers involved in high-rise residential timber building developments. Full article

In the context of climate change mitigation and adaptation, climate risks stemming from climate transition innovations have garnered significant attention due to concerns about the inadequate climate finance. To shed light on the climate transition risk posed by innovations, this study constructed low-carbon innovation indicators of listed firms in China spanning 2015 to 2021. This study investigated the impact of climate transition innovations on the default risk, considering the mediation effect of investor attention, total factor productivity, and technology spillovers. The findings suggest that low-carbon innovations can mitigate the default risk of listed firms, as evidenced by three low-carbon innovation indicators. Additionally, the research reveals that the climate innovation effect on default risks was moderated when considering climate policy through heterogenous analysis. Furthermore, instrumental variable regressions using the time costs of innovation support the findings. Lastly, default risk was mitigated through lower levels of investor attention, greater total factor productivity, and technology spillovers. Full article

The late Roman discourse on divinatory dreams and their interpretation reflects a context of cultural fragmentation. The political turbulence of the 350s to 360s was due partly to the ongoing external war with the (Persian) Sasanians, but also to the internal struggle between the heirs of Constantine for rule over the Roman empire, still undergoing a process of Christianization when Julian was acclaimed Augustus in 360. A third arena of fragmentation was religious beliefs and practices during the 350s and 360s. The contested transformation of Rome in the religious sphere was the context of Julian’s dynastic vision of the two trees, received in late 358 or 359. Full article

Under the new wave of scientific and technological revolution, the construction industry finds itself with a critical need to alter the traditional and outdated production mode through technological innovation in order to realize industry transformation and move towards a new era characterized by digitalization, informatization, and intelligence. As intelligent construction is the indispensable pathway for the transformation and upgrading of the construction industry, it is of great significance to conduct in-depth research on its evaluation indicators and causality. This paper adopts the system dynamics method, based on the overall structure of intelligent construction, extracts the causality chain and causal feedback loop of intelligent construction, and presents a causality diagram and system dynamics diagram to build a robust system dynamics model for intelligent construction. On this basis, an evaluation index system for intelligent construction is constructed from the five dimensions—investment, design, construction, operation, and environment—for a holistic assessment of the current state of intelligent construction. The research aims to provide a valuable reference for professionals focusing on intelligent construction and the broader development of the industry. Full article

For decades, linguists have been working to formulate an objective means of distinguishing dialects from languages, but dialect recognition has largely remained a subjective enterprise. Only recently have some studies proposed a processing-based psycholinguistic approach toward dialect recognition. These studies argued that dialect words are stored as a co-dependent representation, not as an independent representation of the words of bilingual speakers. Based on these studies, we investigated the lexical selection and processing mechanisms of bilingual and bidialectal speakers of two understudied languages, Oromo and Amharic, using the picture–word interference paradigm. We found independent lexical representations for both the bilingual and the bidialectal groups, which implies the involvement of the same cognitive mechanisms in both language and dialect processing. Thus, we argue that bidialectal speakers have flexible lexical representation and selection mechanisms that are dependent on the speakers’ previous language experience. Here, we propose a dynamic lexical selection model that accommodates diverse dialect ecologies. Full article

The testis-specific double sex and mab-3-related transcription factor 1 (DMRT1) has long been recognized as a crucial player in sex determination across vertebrates, and its essential role in gonadal development and the regulation of spermatogenesis is well established. Here, we report the cloning of the key spermatogenesis-related DMRT1 cDNA, named Tc-DMRT1, from the gonads of Tridacna crocea (T. crocea), with a molecular weight of 41.93 kDa and an isoelectric point of 7.83 (pI). Our hypothesis is that DMRT1 machinery governs spermatogenesis and regulates gonadogenesis. RNAi-mediated Tc-DMRT1 knockdown revealed its critical role in hindering spermatogenesis and reducing expression levels in boring giant clams. A histological analysis showed structural changes, with normal sperm cell counts in the control group (ds-EGFP) but significantly lower concentrations of sperm cells in the experimental group (ds-DMRT1). DMRT1 transcripts during embryogenesis exhibited a significantly high expression pattern (p < 0.05) during the early zygote stage, and whole-embryo in-situ hybridization confirmed its expression pattern throughout embryogenesis. A qRT-PCR analysis of various reproductive stages revealed an abundant expression of Tc-DMRT1 in the gonads during the male reproductive stage. In-situ hybridization showed tissue-specific expression of DMRT1, with a positive signal detected in male-stage gonadal tissues comprising sperm cells, while no signal was detected in other stages. Our study findings provide an initial understanding of the DMRT1 molecular machinery controlling spermatogenesis and its specificity in male-stage gonads of the key bivalve species, Tridacna crocea, and suggest that DMRT1 predominantly functions as a key regulator of spermatogenesis in giant clams. Full article

In 2019, the International Consortium for Personalised Medicine (ICPerMed) developed a vision on how the use of personalized medicine (PM) approaches will promote “next-generation” medicine in 2030 more firmly centered on the individual’s personal characteristics, leading to improved health outcomes within sustainable healthcare systems through research, development, innovation, and implementation for the benefit of patients, citizens, and society. Nevertheless, there are significant hurdles that healthcare professionals, researchers, policy makers, and patients must overcome to implement PM. The ICPerMed aims to provide recommendations to increase stakeholders’ awareness on actionable measures to be implemented for the realization of PM. Starting with best practice examples of PM together with consultation of experts and stakeholders, a careful analysis that underlined hurdles, opportunities, recommendations, and information, aiming at developing knowledge on the requirements for PM implementation in healthcare practices, has been provided. A pragmatic roadmap has been defined for PM integration into healthcare systems, suggesting actions to overcome existing barriers and harness the potential of PM for improved health outcomes. In fact, to facilitate the adoption of PM by diverse stakeholders, it is mandatory to have a comprehensive set of resources tailored to stakeholder needs in critical areas of PM. These include engagement strategies, collaboration frameworks, infrastructure development, education and training programs, ethical considerations, resource allocation guidelines, regulatory compliance, and data management and privacy. Full article

Chemical reactions, mineral diffusion, and deposition are pivotal in understanding the mechanisms of mineral deposition and the formation of seafloor sulfides in the hydrothermal circulation process. To understand the formation process of anhydrite in submarine hydrothermal systems, a computational model that combined component transport and chemical reactions was established and simulated using the mass transport model. The deposition rate of calcium sulfate was defined, and the effects of factors such as porosity, ion concentration, and inflow velocity on the temperature field in the reaction zone were thoroughly investigated. The distribution of temperature, porosity, and velocity during the reaction process was obtained, allowing for the identification of the chemical reaction patterns of certain ions in the early stages of hydrothermal activity. The simulation revealed the occurrence of biochemical reactions between two types of ions, leading to their deposition on the solid framework of a porous medium. With the increase in inflow velocity and solute concentration, the average porosities of the porous medium decreased by 0.495% and 0.468%, respectively, which consequently altered the structure of the rock. Such findings contribute to the inference of formation and extinction mechanisms of seafloor crusts and hydrothermal chimneys. Full article

Interest in psychosocial predictors of doping has been increasing as a way of finding new approaches to reduce the use of performance-enhancing drugs. This investigation aimed to test the psychometric properties of an instrument to assess doping attitudes in Brazilian athletes. The PEAS was validated in Brazilian sports through a process of translation, back-translation and content validity assessment, presenting satisfactory evidence based on its content (CVC > 0.80). Then, 994 athletes from different sexes, types of sports and competitive levels answered the Brazilian version of the PEAS. The results showed satisfactory evidence of validity based on its response process, internal structure (X²/df = 2.04; RMSEA = 0.032 (0.026–0.038); CFI = 0.96; TLI = 0.95) and reliability (Cronbach’s α, McDonald’s ω and CR > 0.70). Network analysis was also used to further explore the PEAS’s internal structure. Overall, the results provide support for the adoption of the PEAS for Brazilian athletes and possibly other Portuguese-speaking countries. Full article

Cholangiocarcinoma (CCA) poses a substantial threat as it ranks as the second most prevalent primary liver tumor. The documented annual rise in intrahepatic CCA (iCCA) incidence in the United States is concerning, indicating its growing impact. Moreover, the five-year survival rate after tumor resection is only 25%, given that tumor recurrence is the leading cause of death in 53–79% of patients. Pre-operative assessments for iCCA focus on pinpointing tumor location, biliary tract involvement, vascular encasements, and metastasis detection. Numerous studies have revealed that portal vein embolization (PVE) is linked to enhanced survival rates, improved liver synthetic functions, and decreased overall mortality. The challenge in achieving clear resection margins contributes to the notable recurrence rate of iCCA, affecting approximately two-thirds of cases within one year, and results in a median survival of less than 12 months for recurrent cases. Nearly 50% of patients initially considered eligible for surgical resection in iCCA cases are ultimately deemed ineligible during surgical exploration. Therefore, staging laparoscopy has been proposed to reduce unnecessary laparotomy. Eligibility for orthotopic liver transplantation (OLT) requires certain criteria to be granted. OLT offers survival advantages for early-detected unresectable iCCA; it can be combined with other treatments, such as radiofrequency ablation and transarterial chemoembolization, in specific cases. We aim to comprehensively describe the surgical strategies available for treating CCA, including the preoperative measures and interventions, alongside the current options regarding liver resection and OLT. Full article

Islam is widely spread throughout every corner of China, with the Hui people, the largest Muslim ethnic group in China, numbering over 10 million people, serving as its main carrier. Their culture types and local features exhibit great diversity across different provinces. The ceremony of Prophet’s Day or Mawlid al-Nabi in China, as one of the three fundamental festivals of the Hui people alongside Eid al-Fitur and Eid al-Qurban, appears to be more comprehensive, open, and localized. Drawing from fieldwork in three Hui communities—Xi’an in Shaanxi province, Najiaying in Yunnan province, and Hezhou in Gansu province—this paper approaches the topic from the perspective of inculturation and cultural innovation. It aims to describe the ritual processes observed in these three different Hui communities and discuss how the Hui people integrate Islam with traditional Chinese culture in their local contexts, with the intention of forming and preserving their own cultural characteristics. Full article

Dysferlin is a large transmembrane protein involved in critical cellular processes including membrane repair and vesicle fusion. Mutations in the dysferlin gene (DYSF) can result in rare forms of muscular dystrophy; Miyoshi myopathy; limb girdle muscular dystrophy type 2B (LGMD2B); and distal myopathy. These conditions are collectively known as dysferlinopathies and are caused by more than 600 mutations that have been identified across the DYSF gene to date. In this review, we discuss the key molecular and clinical features of LGMD2B, the causative gene DYSF, and the associated dysferlin protein structure. We also provide an update on current approaches to LGMD2B diagnosis and advances in drug development, including splice switching antisense oligonucleotides. We give a brief update on clinical trials involving adeno-associated viral gene therapy and the current progress on CRISPR/Cas9 mediated therapy for LGMD2B, and then conclude by discussing the prospects of antisense oligomer-based intervention to treat selected mutations causing dysferlinopathies. Full article

Skin aging is an unavoidable natural phenomenon caused by intrinsic and extrinsic factors. In modern society, the pursuit of a wrinkle-free and aesthetically appealing face has gained considerable prominence. Numerous studies have aimed at mitigating the appearance of facial wrinkles. Antiaging research focused on regulating the function of mitochondria, the main reactive oxygen species-generating organelles, has been extensively conducted. In this study, we investigated the correlation between facial wrinkles and the expression of PPARGC1B, considering the association of this gene with mitochondrial function, to identify its potential as a target for exploring antiaging cosmetic materials. We elucidated the role of PPARGC1B in the skin and identified five bioactive materials that modulated its expression. The effectiveness of these materials was verified through in vitro experiments on human dermal fibroblasts. We prepared cosmetic formulations incorporating the five materials and confirmed their ability to enhance dermal collagen in three-dimensional skin models and reduce facial wrinkles under the eyes and nasolabial fold areas in human subjects. The study findings have significant implications for developing novel antiaging cosmetic formulations by reinforcing mitochondrial functions. Full article

The parameters of the roll characteristics of a large-scale round bale machine were collected in real time to investigate the bale rolling mechanism. This investigation develops a set of adaptable and highly integrated data acquisition systems for the bale rolling performance parameters of large-type round bale machines. A rolling experiment is conducted using sunflower straw as the material, and the power consumption and radial tension of the roller-round bale machine during the bale rolling process are studied. In the grass core formation stage, the round bale machine’s torque need was minimal, the radial tension of the bale remained nearly constant, and the bale chamber was primarily filled with loose sunflower straw. The motor torque and the straw bale’s radial tension both showed a tendency of gradual increase when the round bale machine was in the grass-filling stage. The motor torque and bale radial tension displayed a roughly linear trend of rapid rise as the sunflower straw continued to enter the rolling bale chamber; this was when the round bale machine was in the compressed bale rolling stage. When the power consumption of the round bale machine was measured using the data acquisition system during the test bench empty run and core-creation stage, the energy consumption comparison analysis produced a relative error of 5.8%. During the stage of bale rolling and compression, the data acquisition system monitored the power consumption of the round bale machine. The relative error was 9.5%. The data acquisition system of the round bale machine test bed has an accuracy of 90.5%–94.2% when measuring the machine’s power consumption, indicating that it is a stable and efficient system. This study provides a foundation for further research on intelligent the roller-round bale machine. Full article

The accurate classification of brain tumors is an important step for early intervention. Artificial intelligence (AI)-based diagnostic systems have been utilized in recent years to help automate the process and provide more objective and faster diagnosis. This work introduces an enhanced AI-based architecture for improved brain tumor classification. We introduce a hybrid architecture that integrates vision transformer (ViT) and deep neural networks to create an ensemble classifier, resulting in a more robust brain tumor classification framework. The analysis pipeline begins with preprocessing and data normalization, followed by extracting three types of MRI-derived information-rich features. The latter included higher-order texture and structural feature sets to harness the spatial interactions between image intensities, which were derived using Haralick features and local binary patterns. Additionally, local deeper features of the brain images are extracted using an optimized convolutional neural networks (CNN) architecture. Finally, ViT-derived features are also integrated due to their ability to handle dependencies across larger distances while being less sensitive to data augmentation. The extracted features are then weighted, fused, and fed to a machine learning classifier for the final classification of brain MRIs. The proposed weighted ensemble architecture has been evaluated on publicly available and locally collected brain MRIs of four classes using various metrics. The results showed that leveraging the benefits of individual components of the proposed architecture leads to improved performance using ablation studies. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as nonalcoholic fatty liver disease, is a steatotic liver disease associated with metabolic syndrome (MetS), especially obesity, hypertension, diabetes, hyperlipidemia, and hypertriglyceridemia. MASLD in 43–44% of patients can progress to metabolic dysfunction-associated steatohepatitis (MASH), and 7–30% of these cases will progress to liver scarring (cirrhosis). To date, the mechanism of MASLD and its progression is not completely understood and there were no therapeutic strategies specifically tailored for MASLD/MASH until March 2024. The conventional antiobesity and antidiabetic pharmacological approaches used to reduce the progression of MASLD demonstrated favorable peripheral outcomes but insignificant effects on liver histology. Alternatively, phyto-synthesized metal-based nanoparticles (MNPs) are now being explored in the treatment of various liver diseases due to their unique bioactivities and reduced bystander effects. Although phytonanotherapy has not been explored in the clinical treatment of MASLD/MASH, MNPs such as gold NPs (AuNPs) and silver NPs (AgNPs) have been reported to improve metabolic processes by reducing blood glucose levels, body fat, and inflammation. Therefore, these actions suggest that MNPs can potentially be used in the treatment of MASLD/MASH and related metabolic diseases. Further studies are warranted to investigate the feasibility and efficacy of phytonanomedicine before clinical application. Full article

Gastrointestinal tract perforation is uncommon in children, accounting for <10% of cases of blunt abdominal trauma. Diagnosis of bowel perforation in children can be challenging due to poor diagnostic imaging accuracy. Intra-abdominal free air is found only in half of the children with bowel perforation. Ultrasound findings are nonspecific and suspicious for perforation in only two-thirds of cases. A computer tomography (CT) scan has a sensitivity and specificity of 50% and 95%, respectively. Surgical decisions should be made based on clinical examination despite normal CT results. Management of bowel perforation in children includes primary repair in 50–70% and resection with anastomosis in 20–40% of cases. Full article

With the widespread adoption of smart farms and continuous advancements in IoT (Internet of Things) technology, acquiring diverse additional data has become increasingly convenient. Consequently, studies relevant to deep learning models that leverage multimodal data for crop disease diagnosis and associated data augmentation methods are significantly growing. We propose a comprehensive deep learning model that predicts crop type, detects disease presence, and assesses disease severity at the same time. We utilize multimodal data comprising crop images and environmental variables such as temperature, humidity, and dew points. We confirmed that the results of diagnosing crop diseases using multimodal data improved 2.58%p performance compared to using crop images only. We also propose a multimodal-based mixup augmentation method capable of utilizing both image and environmental data. In this study, multimodal data refer to data from multiple sources, and multimodal mixup is a data augmentation technique that combines multimodal data for training. This expands the conventional mixup technique that was originally applied solely to image data. Our multimodal mixup augmentation method showcases a performance improvement of 1.33%p compared to the original mixup method. Full article

Green finance has been widely acknowledged as a pivotal instrument for mitigating carbon emissions. However, few studies have focused on the role of maturity mismatches in promoting carbon emission reduction through green finance. This study aims to develop a composite criterion for green finance and examine the mechanism of how green finance affects carbon emissions via the new perspective of maturity mismatch. It is accomplished by applying a two-way fixed effects model which incorporates provincial data spanning from 2010 to 2020. The empirical evidence suggests green finance plays a significant role in carbon emission reduction, a result that remains robust even after undergoing other tests such as using instrumental variables and alternating econometric models. Furthermore, this effect is particularly pronounced in regions with high degrees of green finance and low energy consumption. Mechanism analysis documents that green finance reduces carbon emissions by addressing maturity mismatch issues faced by green enterprises. Further research finds that green finance can promote the synergy of pollution and carbon reduction; in particular, the effect of maturity mismatch on SO₂ reduction is more obvious. Consequently, this study offers practical recommendations for governments, financial institutions, and other relevant policymakers to further propel the advancement of green finance. Full article

In response to the need for a space security situation assessment during orbit, the multi-satellite space environmental risk prediction and early warning system is based on the detection results of the space weather payload of the Fengyun 4A and 4B satellites, as well as the prediction results of the National Space Weather Center, for the first time. By comprehensively utilizing some open-source data, it is the first time that we have achieved a 24 h advanced prediction of the space environment high-energy proton, low-energy particle, and high-energy electron risks for the safety of the Fengyun-series high-orbit satellites, and a real-time warning of satellite single-event upset, surface charging, and deep charging risks. The automation system has preliminarily achieved an intelligent space risk assessment for the safety of multiple stationary meteorological satellites, effectively improving the application efficiency of the space environmental data and the products of Fengyun-series satellites. The business status is stable in operation, and the resulting error between the predicted results of various risk indices and the measured data was less than one level. The warning accuracy was better than 90%. This article uses the system for the first time, to use Fengyun satellite data to, accurately and in a timely manner, predict and warn us about the low-energy particles and surface charging high-risk levels of the Fengyun 4A and 4B satellites during the typical space weather event on 21 April 2023, in response to the impact of complex spatial environmental factors on the safety of Fengyun-series high-orbit satellites. The construction and operation of a multi-satellite space environmental risk prediction and early warning system can provide a reference for the safety work of subsequent satellite ground system operations. Full article

The development height of the water-conducting fracture zone (WCFZ) is crucial for the safe production of coal mines. The back-propagation neural network (BP-NN) can be utilized to forecast the WCFZ height, aiding coal mines in water hazard prevention and control efforts. However, the stochastic generation of initial weights and thresholds in BP-NN usually leads to local optima, which might reduce the prediction accuracy. This study thus invokes the excellent global optimization capability of the Improved Radial Movement Optimization (IRMO) algorithm to optimize BP-NN. The influences of mining thickness, coal seam depth, working width, and hard rock lithology proportion coefficient on the height of WCFZ are investigated through 75 groups of in situ data of WCFZ heights measured in the Jurassic coalfield of the Ordos Basin. Consequently, an IRMO-BP-NN model for predicting WCFZ height in the Jurassic coalfield of the Ordos Basin was constructed. The proposed IRMO-BP-NN model was validated through monitoring data from the 4⁻²216 working faces of Jianbei Coal Mine, followed by a comparative analysis with empirical formulas and conventional BP-NN models. The relative error of the IRMO-BP-NN prediction model is 4.93%, outperforming both the BP-NN prediction model, the SVR prediction model, and empirical formulas. The results demonstrate that the IRMO-BP-NN model enhances the accuracy of predicting WCFZ height, providing an application foundation for predicting such heights in the Jurassic coalfield of the Ordos Basin and protecting the ecological environment of Ordos Basin mining areas. Full article