Artificial Intelligence Image Recognition System for Preventing Wrong-Site Upper Limb Surgery.

Our image recognition system employs a deep learning model to differentiate between the left and right upper limbs in images, allowing doctors to determine the correct surgical position. From the experimental results, it was found that the precision rate and the recall rate of the intelligent image recognition system for preventing wrong-site upper limb surgery proposed in this paper could reach 98% and 93%, respectively. The results proved that our Artificial Intelligence Image Recognition System (AIIRS) could indeed assist orthopedic surgeons in preventing the occurrence of wrong-site left and right upper limb surgery. At the same time, in future, we will apply for an IRB based on our prototype experimental results and we will conduct the second phase of human trials. The results of this research paper are of great benefit and research value to upper limb orthopedic surgery.

Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory Stimulation.

The sense of smell is one of the most important organs in humans, and olfactory imaging can detect signals in the anterior orbital frontal lobe. This study assessed olfactory stimuli using support vector machines (SVMs) with signals from functional near-infrared spectroscopy (fNIRS) data obtained from the prefrontal cortex. These data included odor stimuli and air state, which triggered the hemodynamic response function (HRF), determined from variations in oxyhemoglobin (oxyHb) and deoxyhemoglobin (deoxyHb) levels; photoplethysmography (PPG) of two wavelengths (raw optical red and near-infrared data); and the ratios of data from two optical datasets. We adopted three SVM kernel functions (i.e., linear, quadratic, and cubic) to analyze signals and compare their performance with the HRF and PPG signals. The results revealed that oxyHb yielded the most efficient single-signal data with a quadratic kernel function, and a combination of HRF and PPG signals yielded the most efficient multi-signal data with the cubic function. Our results revealed superior SVM analysis of HRFs for classifying odor and air status using fNIRS data during olfaction in humans. Furthermore, the olfactory stimulation can be accurately classified by using quadratic and cubic kernel functions in SVM, even for an individual participant data set.

[Nursing Experience Caring for a COVID-19 Patient With Hearing Loss].

The focus of this article is on a male patient with hearing loss who was diagnosed with COVID-19 after returning to Taiwan from overseas. Due to the severe pneumonia infiltration, the patient received the clinical-trial treatment Remdesivir. In addition to facing the isolation and new-drug-related anxieties of the patient, the medical team faced difficulties in communicating effectively with the patient and in helping him through the isolation period. During the period of hospitalization (March 14th to April 13th, 2020), the author used Roy's adaptation model to perform a nursing assessment, which confirmed that the patient faced the following problems: (1) ineffective breathing pattern related to COVID-19, (2) impaired verbal communication related to hearing impairment, and (3) social isolation related to the isolation experience and the communication barrier with healthcare workers. During the nursing care process, the author helped the patient receive the antiviral treatment and taught him how to do diaphragmatic breathing in a comfortable, recumbent position to improve his breathing pattern. To reduce the difficulty of communication, the author made a pile of cards with common care-related words, provided pen and paper to write, and used a mobile-phone-based social-networking application to communicate with the patient. The author used writing to communicate with the patient and learned some simple signs from him to enable interaction. Moreover, the intervention helped him adapt to the isolation and treatment protocols to reach holistic nursing care. Based on this experience, the author suggests that hospitals cooperate with sign language organizations to teach healthcare workers simple communication skills, including sign language and cards to provide more complete care for patients with hearing loss during hospitalization.

Homotopy-Theoretic Study &Atomic-Scale Observation of Vortex Domains in Hexagonal Manganites.

Essential structural properties of the non-trivial "string-wall-bounded" topological defects in hexagonal manganites are studied through homotopy group theory and spherical aberration-corrected scanning transmission electron microscopy. The appearance of a "string-wall-bounded" configuration in RMnO3 is shown to be strongly linked with the transformation of the degeneracy space. The defect core regions (~50 Å) mainly adopt the continuous U(1) symmetry of the high-temperature phase, which is essential for the formation and proliferation of vortices. Direct visualization of vortex strings at atomic scale provides insight into the mechanisms and macro-behavior of topological defects in crystalline materials.

A noninvasive brain computer interface using visually-induced near-infrared spectroscopy responses.

Visually-induced near-infrared spectroscopy (NIRS) response was utilized to design a brain computer interface (BCI) system. Four circular checkerboards driven by distinct flickering sequences were displayed on a LCD screen as visual stimuli to induce subjects' NIRS responses. Each flickering sequence was a concatenated sequence of alternative flickering segments and resting segments. The flickering segment was designed with fixed duration of 3s whereas the resting segment was chosen randomly within 15-20s to create the mutual independencies among different flickering sequences. Six subjects were recruited in this study and subjects were requested to gaze at the four visual stimuli one-after-one in a random order. Since visual responses in human brain are time-locked to the onsets of visual stimuli and the flicker sequences of distinct visual stimuli were designed mutually independent, the NIRS responses induced by user's gazed targets can be discerned from non-gazed targets by applying a simple averaging process. The accuracies for the six subjects were higher than 90% after 10 or more epochs being averaged.

First-principle calculations analysis of ELNES splitting for Mn3O4 spinels related to atomic local symmetry.

By using a real space multiple scattering method (FEFF code) with a 2 × 2 × 2 cluster model, we investigated the effects of characteristic Jahn-Teller distortion on the electron energy loss near-edge structure (ELNES) of Mn3O4 spinel. In particular, we examined a correlation between the characteristics of the density of state and the ELNES spectral feature as a function of Jahn-Teller distortion. To this end, we introduced a geometrical variation approach to an Mn3O4 cluster model containing both Mn(3+) and Mn(2+) sites. Upon a prominent Jahn-Teller distortion of the Mn(3+)-octahedral site, we resolved the associated spectral features of Mn, comprising three peaks that merged upon increasing the symmetry of octahedral site from tetragonal (D4h) to cubic (Oh). We have also investigated the interplay between the Mn L-edge and corresponding O K-edge spectra.

Educational needs of inpatient oncology nurses in providing psychosocial care.

Patients with cancer have multiple psychosocial needs during inpatient admissions. However, nurses often are not sure how to best approach those psychosocial needs. Therefore, the purpose of this survey was to determine the educational needs of inpatient oncology nurses in terms of providing psychosocial care to patients and to determine the barriers that inpatient nurses experience when providing psychosocial care. Twenty-six inpatient oncology RNs participated in an online survey that assessed barriers to psychosocial care as well as educational needs. Nurses identified that time, lack of patient privacy, nurses' emotional energy, confusion about clinical guidelines, lack of experience with screening tools, not knowing how to approach sensitive topics, and poor communication between team members undermine psychosocial care. Inpatient nurses need additional training to provide excellent psychosocial care.

Chemical mapping and quantification at the atomic scale by scanning transmission electron microscopy.

With innovative modern material-growth methods, a broad spectrum of fascinating materials with reduced dimensions-ranging from single-atom catalysts, nanoplasmonic and nanophotonic materials to two-dimensional heterostructural interfaces-is continually emerging and extending the new frontiers of materials research. A persistent central challenge in this grand scientific context has been the detailed characterization of the individual objects in these materials with the highest spatial resolution, a problem prompting the need for experimental techniques that integrate both microscopic and spectroscopic capabilities. To date, several representative microscopy-spectroscopy combinations have become available, such as scanning tunneling microscopy, tip-enhanced scanning optical microscopy, atom probe tomography, scanning transmission X-ray microscopy, and scanning transmission electron microscopy (STEM). Among these tools, STEM boasts unique chemical and electronic sensitivity at unparalleled resolution. In this Perspective, we elucidate the advances in STEM and chemical mapping applications at the atomic scale by energy-dispersive X-ray spectroscopy and electron energy loss spectroscopy with a focus on the ultimate challenge of chemical quantification with atomic accuracy.

Spectroscopic characterizations of individual single-crystalline GaN nanowires in visible/ultra-violet regime.

Spectroscopic investigations of individual single-crystalline GaN nanowires with a lateral dimensions of approximately 30-90nm were performed using the spatially resolved technique of electron energy-loss spectroscopy in conjunction with scanning transmission electron microscope showing a 2-A electron probe. Positioning the electron probe upon transmission impact and at aloof setup with respect to the nanomaterials, we explored two types of surface modes intrinsic to GaN, surface exciton polaritons at approximately 8.3eV (approximately 150nm) and surface guided modes at 3.88eV (approximately 320nm), which are in visible/ultra-violet spectral regime above GaN bandgap of approximately 3.3eV (approximately 375nm) and difficult to access by conventional optical spectroscopies. The explorations of these electromagnetic resonances might expand the current technical interests in GaN nanomaterials from the visible/UV range below approximately 3.5eV to the spectral regime further beyond.

Probing non-dipole allowed excitations in highly correlated materials with nanoscale resolution.

Here, we demonstrate that non-dipole allowed d-d excitations in NiO can be measured by electron energy loss spectroscopy (EELS) in transmission electron microscopes (TEM). Strong excitations from (3)A(2g) ground states to (3)T(1g) excited states are measured at 1.7 and 3 eV when transferred momentum are beyond 1.5 A(-1). We show that these d-d excitations can be collected with a nanometrical resolution in a dedicated scanning transmission electron microscope (STEM) by setting a good compromise between the convergence angle of the electron probe and the collected transferred momentum. This work opens new possibilities for the study of strongly correlated materials on a nanoscale.

Probing surface plasmons in individual Ag nanoparticles in the ultra-violet spectral regime.

Previous investigations of surface plasmons in Ag largely focused on their excitations in the visible spectral regime. Using scanning transmission electron microscopy with an electron beam of 0.2 nm in conjunction with electron energy-loss spectroscopy, we spectrally and spatially probe the surface plasmons in individual Ag nanoparticles (approximately 30 nm), grown on Si, in the ultra-violet spectral regime. The nanomaterials show respective sharp and broad surface-plasmon resonances at approximately 3.5 eV (approximately 355 nm) and approximately 7.0 eV (approximately 177 nm), and the correlated spectral calculations established their multipolar characteristics. The near-field distributions of the surface plasmons on the nanoparticles were also mapped out, revealing the predominant dipolar nature of the 3.5 eV excitation with obvious near-field enhancements at one end of the nano-object. The unveiled near-field enhancements have potential applications in plasmonics and molecular sensing.

Probing bright and dark surface-plasmon modes in individual and coupled noble metal nanoparticles using an electron beam.

The rich structure of bright and dark surface-plasmon modes localized in individual and coupled gold nanoparticles is unveiled by electron-energy-loss spectroscopy performed in a scanning transmission electron microscope. Spatially resolved maps of surface-plasmon modes in the approximately 1.5-2.5 eV range (wavelengths approximately 500-800 nm), collected for individual nanorods, coupled nanorod dimers, and touching nanosphere dimers, are in excellent agreement with theory. Surface-plasmon maps constructed from the spatially and spectrally resolved energy-loss signals are shown to mimic rather well the near fields calculated for external illumination in the case of bright surface-plasmon modes (i.e., those coupling to external light). Dark surface-plasmon modes that cannot be excited by optical means are also found, and our electron probing technique provides further insight into their corresponding spatial distribution and symmetry, which are not accessible to any other existing techniques. Our results initiate the study of a whole set of new dark surface-plasmon modes that should become a source of new applications in sensing and microscopy but have escaped experimental scrutiny so far.

Flux dependent MeV self-ion-induced effects on Au nanostructures: dramatic mass transport and nanosilicide formation.

We report a direct observation of dramatic mass transport due to 1.5 MeV Au(2+) ion impact on isolated Au nanostructures of average size ≈7.6 nm and height ≈6.9 nm that are deposited on Si(111) substrate under high flux (3.2 × 10(10)-6.3 × 10(12) ions cm(-2) s(-1)) conditions. The mass transport from nanostructures was found to extend up to a distance of about 60 nm into the substrate, much beyond their size. This forward mass transport is compared with the recoil implantation profiles using SRIM simulation. The observed anomalies with theory and simulations are discussed. At a given energy, the incident flux plays a major role in mass transport and its redistribution. The mass transport is explained on the basis of thermal effects and the creation of rapid diffusion paths in the nanoscale regime during the course of ion irradiation. The unusual mass transport is found to be associated with the formation of gold silicide nano-alloys at subsurfaces. The complexity of the ion-nanostructure interaction process is discussed with a direct observation of melting (in the form of spherical fragments on the surface) phenomena. Transmission electron microscopy, scanning transmission electron microscopy, and Rutherford backscattering spectroscopy methods have been used.