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ObjectiveTo develop an accurate and efficient binary classification model for predicting the binding capacity of endocrine-disrupting chemicals （EDCs） to the G protein-coupled estrogen receptor （GPER）.MethodsGPER...

BackgroundPredicting enterocutaneous fistula (ECF)–associated sepsis and mortality poses significant challenges in digital health care due to the disease’s complexity and heterogeneous clinical manifestations. Curren...

With the proposal of the national dual-carbon strategic goal, distributed photovoltaic (PV) ushers in new development opportunities, and the management of voltage quality for photovoltaic power stations becomes a key cha...

Organizations frequently fail to sustain transformation despite substantial investment in leadership development, cultural change programs, and structural redesign. Existing frameworks tend to treat organizational stabil...

Abstract Engine tests are both costly and time consuming in developing a new internal combustion engine. Therefore, it is of great importance to predict engine characteristics with high accuracy using artificial intellig...

Craniofacial morphogenesis is a highly coordinated developmental process governed by complex genetic and molecular interactions. Among these, the PAX family of transcription factors plays a pivotal role in the regulation...

In the growing diversity of human induced pluripotent stem cell (iPSC)-derived models of brain development, we present here a novel method that exhibits 3D cortical layer formation in a reproducible topography of minimal...

Abstract Mutations in the CYFIP2 gene, particularly the R87C variant, are associated with severe epileptic encephalopathy, and present challenges for therapeutic development. This study utilized CRISPR/Cas9-edited human ...

The identification of suitable models for predicting daily water flow is important for planning and management of water storage in reservoirs of Argentina. Long-term prediction of water flow is crucial for regulating res...

The prediction and design of photonic features have traditionally been guided by theory-driven computational methods, spanning a wide range of direct solvers and optimization techniques. Motivated by enormous advances in...

Abstract The accurate prediction of the deterioration of Continuously Reinforced Concrete Pavement (CRCP) is essential for the effective management of pavements and the maintenance of infrastructure. In this study, a co...

The need for early and precise identification of abnormalities has made the detection and classification of brain tumours essential components of medical diagnosis. Because brain tumours are naturally complex and can hav...

Abstract Graph neural networks (GNNs) are widely used as surrogates for costly experiments and first-principles simulations to study the behavior of compounds at atomistic scale, and their architectural complexity is con...

Reading fluency depends on rapid integration of print and speech, yet the spatiotemporal mechanisms supporting this integration in school aged children remain poorly understood. This study combined fMRI and EEG to examin...

The rapid growth and increasing complexity of Internet of Things (IoT) networks require efficient real-time monitoring and anomaly detection mechanisms. Traditional machine learning approaches often struggle to handle th...

ABSTRACT With the development of unmanned aerial vehicle and satellite technology, the application of tiny object detection in remote sensing images is becoming increasingly widespread. Although significant progress has ...

The foremost task in agriculture is the decisive identification of citrus plants and the timely identification of diseases in the plants with the aim of improving the quality of crops and the yield. In this work, a machi...

Perinatal asphyxia (PA) is a primary cause of neonatal morbidity, with persistent neurological sequelae, associated with mitochondrial dysfunction and redox imbalance. The lack of experimental approaches for region-speci...

Abstract The rapid development of China’s financial markets, particularly the expansion of the ETF ecosystem, has made dynamic sector rotation strategies increasingly feasible and cost-effective for investors. At the s...

The rapid proliferation of unmanned aerial vehicles (UAVs) has created an urgent need for robust detection & identification systems to ensure airspace security and safety. However, the scarcity of large-scale, div...

Over the past decade, mobile devices have become an integral part of our daily routines, offering a broad spectrum of applications that enhance everyday tasks. As more people adopt smartphones, developers are increasingl...

Abstract Pheochromocytomasand paragangliomas (collectively referred as PPGLs) are highly heritable neoplasms arise from chromaffin cells of neural crest tissues; 40% of patients with PPGLs harbour germline pathogenic var...

Malware represents the most critical threat in cybersecurity, meant to compromise the security for any individual or any organization. These are covert software, designed to perform malicious act like data theft, data al...

Today, Artificial Intelligence (AI) has permeated across diverse disciplines, professional sectors, and recreational activities. Translation and interpreting are two sectors in which AI is becoming increasingly important...