Automating Drug Discovery using Machine Learning.

Drug discovery and development have been sped up because of the advances in computational science. In both industry and academics, artificial intelligence (AI) has been widely used. Machine learning (ML), an important component of AI, has been used in a variety of domains, including data production and analytics.

An intent classification method for questions in "Treatise on Febrile diseases" based on TinyBERT-CNN fusion model.

"Treatise on Febrile Diseases" is an important classic book in the academic history of Chinese material medica. Based on the knowledge map of traditional Chinese medicine established by the study of "Treatise on Febrile Diseases", a question-answering system of traditional Chinese medicine was established to help people better understand and use traditional Chinese medicine. Intention classification is the basis of the question-answering system of traditional Chinese medicine, but as far as we know, there is no research on question intention classification based on "Treatise on Febrile Diseases".

Cardiac phase detection in echocardiography using convolutional neural networks.

Echocardiography is a commonly used and cost-effective test to assess heart conditions. During the test, cardiologists and technicians observe two cardiac phases-end-systolic (ES) and end-diastolic (ED)-which are critical for calculating heart chamber size and ejection fraction. However, non-essential frames called Non-ESED frames may appear between these phases.

Development of Novel Balloon-Integrated Optical Catheter for Endoscopic and Circumferential Laser Application.

The current study aims to demonstrate the feasibility of a novel balloon-integrated optical catheter (BIOC) to achieve endoscopic laser application for circumferential coagulation of a tubular tissue structure. Both optical and thermal numerical simulations were developed to predict the propagation of laser light and a spatio-temporal distribution of temperature in tissue. Ex vivo esophagus tissue was tested with 980 nm laser light at 30 W for 90 s for quantitative evaluations.

Nonmetallic SERS-based biosensor for ultrasensitive and reproducible immunoassay of ferritin mediated by magnetic molybdenum disulfide nanoflowers and black phosphorus nanosheets.

To improve the curability of cancer patients, it is essential to propose an early diagnosis technology with ultra-high sensitivity and reliable biocompatibility. Herein, a sophisticated nonmetallic SERS-based immunosensor, comprised by a MoS @FeO nanoflower-based immunoprobe with magnetism and a black phosphorus (BP) nanosheet-based immunosubstrate, was proposed for the specific in-situ monitoring of ferritin (FER). The sandwich immunosensor was endowed with an excellent SERS performance mainly ascribed to a synergistic chemical enhancement as well as an additional electrostatic adsorption effect, achieving a limit of detection down to 7.

Multi-planar 2.5D U-Net for image quality enhancement of dental cone-beam CT.

Cone-beam computed tomography (CBCT) can provide 3D images of a targeted area with the advantage of lower dosage than multidetector computed tomography (MDCT; also simply referred to as CT). However, in CBCT, due to the cone-shaped geometry of the X-ray source and the absence of post-patient collimation, the presence of more scattering rays deteriorates the image quality compared with MDCT. CBCT is commonly used in dental clinics, and image artifacts negatively affect the radiology workflow and diagnosis.

Temperature compensation and entrainment in cyanobacteria circadian rhythm.

Circadian rhythm is an endogenous rhythmic behavior of organisms used to adapt to the external environment. Although most biochemical reactions accelerate with increasing temperature, the period of circadian rhythms remains relatively stable across a range of temperature, a phenomenon known as temperature compensation. Meanwhile, circadian rhythms can be reset by environmental signals, such as daily periodic light or temperature, a phenomenon known as entrainment.

A novel method for Pu-erh tea face traceability identification based on improved MobileNetV3 and triplet loss.

Ensuring the traceability of Pu-erh tea products is crucial in the production and sale of tea, as it is a key means to ensure their quality and safety. The common approach used in traceability systems is the utilization of bound Quick Response (QR) codes or Near Field Communication (NFC) chips to track every link in the supply chain. However, counterfeiting risks still persist, as QR codes or NFC chips can be copied and inexpensive products can be fitted into the original packaging.

Analyzing Factors Influencing Situation Awareness in Autonomous Vehicles-A Survey.

Autonomous driving of higher automation levels asks for optimal execution of critical maneuvers in all environments. A crucial prerequisite for such optimal decision-making instances is accurate situation awareness of automated and connected vehicles. For this, vehicles rely on the sensory data captured from onboard sensors and information collected through V2X communication.

Paraoxonases at the Heart of Neurological Disorders.

Paraoxonase enzymes serve as an important physiological redox system that participates in the protection against cellular injury caused by oxidative stress. The PON enzymes family consists of three members (PON-1, PON-2, and PON-3) that share a similar structure and location as a cluster on human chromosome 7. These enzymes exhibit anti-inflammatory and antioxidant properties with well-described roles in preventing cardiovascular disease.

Towards a Deep Learning Pain-Level Detection Deployment at UAE for Patient-Centric-Pain Management and Diagnosis Support: Framework and Performance Evaluation.

The outbreak of the COVID-19 pandemic revealed the criticality of timely intervention in a situation exacerbated by a shortage in medical staff and equipment. Pain-level screening is the initial step toward identifying the severity of patient conditions. Automatic recognition of state and feelings help in identifying patient symptoms to take immediate adequate action and providing a patient-centric medical plan tailored to a patient's state.

A comparative analysis of sleep spindle characteristics of sleep-disordered patients and normal subjects.

Spindles differ in density, amplitude, and frequency, and these variations reflect different physiological processes. Sleep disorders are characterized by difficulty in falling asleep and maintaining sleep. In this study, we proposed a new spindle wave detection algorithm, which was more effective compared with traditional detection algorithms such as wavelet algorithm.

Diphenyl imidazole-based fluorescent chemosensor for Al and its Al complex toward water detection in food products.

A sophisticated fluorescent chemosensor, 2-(4-nitrophenyl)-4,5-diphenyl-1H-imidazole (NPDI), was designed and synthesized through a one-step condensation reaction. NPDI exhibited a fluorescence enhancement response toward Al, accompanied by significant emission color change without interference from other tested metal ions. The binding stoichiometry and mechanism was corroborated using various techniques.

On closed-loop brain stimulation systems for improving the quality of life of patients with neurological disorders.

Emerging brain technologies have significantly transformed human life in recent decades. For instance, the closed-loop brain-computer interface (BCI) is an advanced software-hardware system that interprets electrical signals from neurons, allowing communication with and control of the environment. The system then transmits these signals as controlled commands and provides feedback to the brain to execute specific tasks.

Long-term stability of PVDF-SiO-HDTMS composite hollow fiber membrane for carbon dioxide absorption in gas-liquid contacting process.

Hybrid polyvinylidene fluoride-silica-hexadecyltrimethoxysilane (PVDF-SiO-HDTMS) membranes were fabricated via a non-solvent-induced phase-inversion method to create stable hollow-fiber membranes for use in the membrane contact absorption of carbon dioxide (CO). The surface properties, performance characteristics, and long-term performance stability of the prepared membranes were compared and analyzed. The outer surfaces of the prepared membranes were superhydrophobic because of the formation of rough nanoscale microstructures on the surfaces and their low surface free energy.

An optimization-based algorithm for obtaining an optimal synchronizable network after link addition or reduction.

Achieving a network structure with optimal synchronization is essential in many applications. This paper proposes an optimization algorithm for constructing a network with optimal synchronization. The introduced algorithm is based on the eigenvalues of the connectivity matrix.

Tuning the Red-to-Green-Upconversion Luminescence Intensity Ratio of NaScF: 20% Yb, 2% Er Particles by Changes in Size.

NaScF: 20% Yb, 2% Er samples were synthesized with different reaction times and reaction temperatures using the solvothermal method. We carried out a series of tests on Na3ScF6 crystals. The XRD patterns showed that the monoclinic phases of the NaScF samples could be synthesized under different reaction conditions, and doping with Yb ions and Er ions did not change the crystal structures.

Hierarchical fusion detection algorithm for sleep spindle detection.

Background: Sleep spindles are a vital sign implying that human beings have entered the second stage of sleep. In addition, they can effectively reflect a person's learning and memory ability, and clinical research has shown that their quantity and density are crucial markers of brain function. The "gold standard" of spindle detection is based on expert experience; however, the detection cost is high, and the detection time is long.

A gene pathway enrichment method based on improved TF-IDF algorithm.

Gene pathway enrichment analysis is a widely used method to analyze whether a gene set is statistically enriched on certain biological pathway network. Current gene pathway enrichment methods commonly consider local importance of genes in pathways without considering the interactions between genes. In this paper, we propose a gene pathway enrichment method (GIGSEA) based on improved TF-IDF algorithm.

Patterns of structure-function association in normal aging and in Alzheimer's disease: Screening for mild cognitive impairment and dementia with ML regression and classification models.

Background: The combined analysis of imaging and functional modalities is supposed to improve diagnostics of neurodegenerative diseases with advanced data science techniques.

Objective: To get an insight into normal and accelerated brain aging by developing the machine learning models that predict individual performance in neuropsychological and cognitive tests from brain MRI. With these models we endeavor to look for patterns of brain structure-function association (SFA) indicative of mild cognitive impairment (MCI) and Alzheimer's dementia.

Nano-Enriched Self-Powered Wireless Body Area Network for Sustainable Health Monitoring Services.

Advances in nanotechnology have enabled the creation of novel materials with specific electrical and physical characteristics. This leads to a significant development in the industry of electronics that can be applied in various fields. In this paper, we propose a fabrication of nanotechnology-based materials that can be used to design stretchy piezoelectric nanofibers for energy harvesting to power connected bio-nanosensors in a Wireless Body Area Network (WBAN).

DeepmRNALoc: A Novel Predictor of Eukaryotic mRNA Subcellular Localization Based on Deep Learning.

The subcellular localization of messenger RNA (mRNA) precisely controls where protein products are synthesized and where they function. However, obtaining an mRNA's subcellular localization through wet-lab experiments is time-consuming and expensive, and many existing mRNA subcellular localization prediction algorithms need to be improved. In this study, a deep neural network-based eukaryotic mRNA subcellular location prediction method, DeepmRNALoc, was proposed, utilizing a two-stage feature extraction strategy that featured bimodal information splitting and fusing for the first stage and a VGGNet-like CNN module for the second stage.

Dynamics of a two-layer neuronal network with asymmetry in coupling.

Investigating the effect of changes in neuronal connectivity on the brain's behavior is of interest in neuroscience studies. Complex network theory is one of the most capable tools to study the effects of these changes on collective brain behavior. By using complex networks, the neural structure, function, and dynamics can be analyzed.

Dynamic analysis of the discrete fractional-order Rulkov neuron map.

Human evolution is carried out by two genetic systems based on DNA and another based on the transmission of information through the functions of the nervous system. In computational neuroscience, mathematical neural models are used to describe the biological function of the brain. Discrete-time neural models have received particular attention due to their simple analysis and low computational costs.

Inhibitory effect of 405 nm laser light on bacterial biofilm in urethral stent.

The clinical use of urethral stents is usually complicated by various adverse effects, including dysuria, fever, and urinary tract infection (UTI). Biofilms (formed by bacteria, such as Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus) adhering to the stent cause UTIs in stented patients (approximately 11%). The undesirable consequences of antibiotics use include bacterial resistance, weight gain, and type 1 diabetes, which occur when antibiotics are used for a long time.