Neural 360∘^\circ Structured Light with Learned Metasurfaces

Structured light has proven instrumental in 3D imaging, LiDAR, and holographic light projection. Metasurfaces, comprised of sub-wavelength-sized nanostructures, facilitate 180$^\circ$ field-of-view (FoV) structured light, circumventing the restricted FoV inherent in traditional optics like diffractive optical elements. However, extant metasurface-facilitated structured light exhibits sub-optimal performance in downstream tasks, due to heuristic pattern designs such as periodic dots that do not consider the objectives of the end application. In this paper, we present neural 360$^\circ$ structured light, driven by learned metasurfaces. We propose a differentiable framework, that encompasses a computationally-efficient 180$^\circ$ wave propagation model and a task-specific reconstructor, and exploits both transmission and reflection channels of the metasurface. Leveraging a first-order optimizer within our differentiable framework, we optimize the metasurface design, thereby realizing neural 360$^\circ$ structured light. We have utilized neural 360$^\circ$ structured light for holographic light projection and 3D imaging. Specifically, we demonstrate the first 360$^\circ$ light projection of complex patterns, enabled by our propagation model that can be computationally evaluated 50,000$\times$ faster than the Rayleigh-Sommerfeld propagation. For 3D imaging, we improve depth-estimation accuracy by 5.09$\times$ in RMSE compared to the heuristically-designed structured light. Neural 360$^\circ$ structured light promises robust 360$^\circ$ imaging and display for robotics, extended-reality systems, and human-computer interactions

Spectral and Polarization Vision: Spectro-polarimetric Real-world Dataset

Image datasets are essential not only in validating existing methods in computer vision but also in developing new methods. Most existing image datasets focus on trichromatic intensity images to mimic human vision. However, polarization and spectrum, the wave properties of light that animals in harsh environments and with limited brain capacity often rely on, remain underrepresented in existing datasets. Although spectro-polarimetric datasets exist, these datasets have insufficient object diversity, limited illumination conditions, linear-only polarization data, and inadequate image count. Here, we introduce two spectro-polarimetric datasets: trichromatic Stokes images and hyperspectral Stokes images. These novel datasets encompass both linear and circular polarization; they introduce multiple spectral channels; and they feature a broad selection of real-world scenes. With our dataset in hand, we analyze the spectro-polarimetric image statistics, develop efficient representations of such high-dimensional data, and evaluate spectral dependency of shape-from-polarization methods. As such, the proposed dataset promises a foundation for data-driven spectro-polarimetric imaging and vision research. Dataset and code will be publicly available

Antibiotic resistance mechanisms inform discovery: identification and characterization of a novel amycolatopsis strain producing ristocetin.

Discovering new antibiotics is a major scientific challenge, made increasingly urgent by the continued development of resistance in bacterial pathogens. A fundamental understanding of the mechanisms of bacterial antibiotic resistance will be vital for the future discovery or design of new, more effective antibiotics. We have exploited our intimate knowledge of the molecular mechanism of glycopeptide antibiotic resistance in the harmless bacterium Streptomyces coelicolor to develop a new two-step cell wall bioactivity screen, which efficiently identified a new actinomycete strain containing a previously uncharacterized glycopeptide biosynthetic gene cluster. The screen first identifies natural product extracts capable of triggering a generalized cell wall stress response and then specifically selects for glycopeptide antibacterials by assaying for the induction of glycopeptide resistance genes. In this study, we established a diverse natural product extract library from actinomycete strains isolated from locations with widely varying climates and ecologies, and we screened them using the novel two-step bioassay system. The bioassay ultimately identified a single strain harboring the previously unidentified biosynthetic gene cluster for the glycopeptide ristocetin, providing a proof of principle for the effectiveness of the screen. This is the first report of the ristocetin biosynthetic gene cluster, which is predicted to include some interesting and previously uncharacterized enzymes. By focusing on screening libraries of microbial extracts, this strategy provides the certainty that identified producer strains are competent for growth and biosynthesis of the detected glycopeptide under laboratory conditions.This work was supported by funding from the Royal Society, UK (516002.K5877/ROG), the Medical Research council, UK (G0700141) and St. John’s College, University of CambridgeThis the the author accepted manuscript. The final version is available from ASM at http://aac.asm.org/content/early/2014/07/09/AAC.03349-14.abstract

A simple iterative independent component analysis algorithm for vibration source signal identification of complex structures

ABSTRACT:Independent Component Analysis (ICA), one of the blind source separation methods, can be applied for extracting unknown source signals only from received signals. This is accomplished by finding statistical independence of signal mixtures and has been successfully applied to myriad fields such as medical science, image processing, and numerous others. Nevertheless, there are inherent problems that have been reported when using this technique: insta- bility and invalid ordering of separated signals, particularly when using a conventional ICA technique in vibratory source signal identification of complex structures. In this study, a simple iterative algorithm of the conventional ICA has been proposed to mitigate these problems. The proposed method to extract more stable source signals having valid order includes an iterative and reordering process of extracted mixing matrix to reconstruct finally converged source signals, referring to the magnitudes of correlation coefficients between the intermediately separated signals and the signals measured on or nearby sources. In order to review the problems of the conventional ICA technique and to vali- date the proposed method, numerical analyses have been carried out for a virtual response model and a 30m class submarine model. Moreover, in order to investigate applicability of the proposed method to real problem of complex structure, an experiment has been carried out for a scaled submarine mockup. The results show that the proposed method could resolve the inherent problems of a conventional ICA technique

Thermal performance evaluation of horizontal spiral coil-type ground heat exchangers

Geothermal energy has been widely used over the world instead of fossil fuel for environmental merits. A ground-source heat pump (GSHP) system utilizes a constant ground temperature to absorb heat during winter and to emit heat in summer. The GSHP system can be devieded into a closed type system and an open type system. The closed type system using a horizontal ground heat exchanger (HGHE) is relatively inexpensive and easy to install compared to the other types of systems. Among the types of HGHEs, since a horizontal spiral-coil type GHE has the advantageous arrangement for heat exchange between the heat exchanger and surrounding ground, it is the most effective type of the HGHE in terms of thermal performance. However, the thermal performance of a horizontal spiral-coil type GHE critically depends on its dimension which consists of the radius and pitch of a spiral, and thus it is important to accurately analyze how the radius and pitch affect the thermal performance of the horizontal spiral-coil type GHE. Therefore, this paper investigated the thermal performance of a horizontal spiral-coil type GHE according to its diverse shapes to suggest a beneficial design specification of the horizontal spiral-coil type GHE. In order to evaluate the thermal performance of the heat exchanger, a spiral-coil type HGHE was installed in a steel box of which the size was 5 m x 1 m x 1 m filled with dry Joomunjin standard sand, and a thermal response test (TRT) was conducted for 30 hours continuously. Besides, a numerical analysis was performed for its verification and a parametric study of the horizontal spiral-coil GHE using a numerical program which is based on a finite element method (FEM). As a result, in case that the pitch of the horizontal spiral-coil type GHE was more than 0.6 m, there was no more significant benefit in the thermal performance

Association between Obesity and Physical Fitness, and Hemoglobin A1c Level and Metabolic Syndrome in Korean Adults

BACKGROUND: The purpose of the current study was to investigate the association of obesity level, physical fitness level, hemoglobin A1c (HbA1c) level and metabolic syndrome (MetS) risk factors among Korean adults. METHODS: A total of 557 adults (272 males and 285 females) who underwent medical check-up at local hospital were recruited. In addition to regular health check-up, cardiopulmonary fitness, muscular endurance were measured and their association were analyzed. RESULTS: The prevalence of MetS was 31.7% for males and 23.7% for females. Females with the higher muscular endurance had lower waist circumference, triglyceride level, and HbA1c level than those with the lower muscular endurance. Males with the higher level of cardiopulmonary fitness had lower diastolic blood pressure, lower high-sensitivity C-reactive protein level and higher high density lipoprotein cholesterol level than males with the lower level of cardiopulmonary fitness. Females with the higher level of cardiopulmonary fitness had lower body weight, body mass index, systolic blood pressure, and fasting blood glucose level than females with the lower level of cardiopulmonary fitness. Participants with the higher level of adiposity and the lower level of physical fitness were 5.26 times (95% confidence interval [CI], 2.19 to 12.62), 5.71 times (95% CI, 2.23 to 14.60) more likely to have MetS, respectively, in male and female compared to participants who were neither obese nor have the lower level of fitness. CONCLUSION: This study suggests that maintaining a healthy body weight as well as a certain level of fitness is important for the prevention of MetS.ope

A case of assisted reproductive therapy-induced erythema nodosum

Erythema nodosum is a common variant of panniculitis. It is characterized by tender erythematous nodule and plaque on the anterior aspect of the leg. The etiology is not fully understood. It may be associated with a variety of disorders, including infection, medication, autoimmune disorders, pregnancy, and malignancy. A 33-year-old Korean woman presented with 1 week history of painful erythematous plaques on both knees. She was 7 weeks pregnant with assisted reproductive therapy, and had been maintained on daily intramuscular progesterone injection for 4 weeks. Histological examination of the lesions revealed septal panniculitis without vasculitis. Two days after discontinuing progesterone injection, the symptoms and lesions started to resolve. Herein we present a case of erythema nodosum caused by progesterone injection for endometrial preparation.OAIID:oai:osos.snu.ac.kr:snu2011-01/102/2008000790/5SEQ:5PERF_CD:SNU2011-01EVAL_ITEM_CD:102USER_ID:2008000790ADJUST_YN:NEMP_ID:A079501DEPT_CD:801CITE_RATE:.531FILENAME:reproductive therapy e nodosum.pdfDEPT_NM:의학과SCOPUS_YN:NCONFIRM:

Prognostic value of low muscle mass at the 12th thoracic vertebral level in multiple myeloma treated with transplantation: CAREMM-2101 study

PURPOSEAutologous hematopoietic stem cell transplantation (ASCT) has been introduced as a standard treatment for newly diagnosed multiple myeloma (NDMM) following novel agent-based induction chemotherapy. This study investigated whether pre-ASCT low muscle mass evaluated using the paraspinal muscle index (PMI) at the 12th thoracic vertebra (T12) level is a reliable prognostic marker in NDMM after chemotherapy.METHODSA multi-center registry database was retrospectively analyzed. Between 2009 and 2020, 190 patients with chest computed tomography images underwent frontline ASCT following induction therapy. The PMI was defined as the value of the paraspinal muscle area at the T12 level divided by the square of the patient’s height. The cut-off value indicating a low muscle mass was sex-specific, using the lowest quintiles.RESULTSOf the 190 patients, 38 (20%) were in the low muscle mass group. The low muscle mass group had a lower 4-year overall survival (OS) rate than the non-low muscle mass group (68.5% vs. 81.2%; P = 0.074). The median progression-free survival (PFS) in the low muscle mass group was significantly shorter compared with the non-low muscle mass group (23.3 months vs. 29.2 months; P = 0.029). The cumulative incidence of transplant-related mortality (TRM) was significantly higher in the low muscle mass group than in the non-low muscle mass group (4-year probability of TRM incidence, 10.6% vs. 0.7%; P < 0.001). In contrast, no significant difference in the cumulative incidence of disease progression was found between the two groups. Multivariate analysis revealed that low muscle mass was associated with significant negative outcomes for OS [(hazard ratio (HR): 2.14; P = 0.047], PFS (HR: 1.78; P = 0.012), and TRM (HR: 12.05; P = 0.025).CONCLUSIONParaspinal muscle mass may have a prognostic role in NDMM patients who undergo ASCT. Patients with low paraspinal muscle mass have lower survival outcomes compared to non-low muscle mass group

Draft Genome Sequence of Ristocetin-Producing Strain Amycolatopsis sp. Strain MJM2582 Isolated in South Korea.

The draft genome sequence of a ristocetin-producing Amycolatopsis strain (sp. MJM2582) isolated in South Korea is reported here. This strain has a genome of approximately 8.9 Mb containing 7,933 predicted genes, including the ristocetin cluster and 32 additional predicted secondary metabolite biosynthesis clusters.This work was supported by grants from the Royal Society (516002.K5877/ROG) and the Medical Research Council (G0700141).This is the final published version. It first appeared at http://genomea.asm.org/content/2/5/e01091-14.abstract