Miracle-dz/UniFAR-FTUs huggingface dataset:
A Rapid Antimicrobial Resistance Diagnostic Platform for Staphylococcus aureus Using Recombinase Polymerase Amplification

Staphylococcus aureus is a species of Staphylococcus and belongs to Gram-positive. Meanwhile, S. aureus remains one of the most common nosocomial and community-acquired infections, causing blood flow, skin, soft tissue, and lower respiratory tract infections. ABSTRACT Antimicrobial resistance (AMR) has posed a global threat to public health. The Staphylococcus aureus strains have especially developed AMR to practically all antimicrobial medications. There is an unmet need for rapid and accurate detection of the S. aureus AMR. In this study, we developed two versions of recombinase polymerase amplification (RPA), the fluorescent signal monitoring and lateral flow dipstick, for detecting the clinically relevant AMR genes retained by S. aureus isolates and simultaneously identifying such isolates at the species level. The sensitivity and specificity were validated with clinical samples. Our results showed that this RPA tool was able to detect antibiotic resistance for all the 54 collected S. aureus isolates with high sensitivity, specificity, and accuracy (all higher than 92%). Moreover, results of the RPA tool are 100% consistent with that of PCR. In sum, we successfully developed a rapid and accurate AMR diagnostic platform for S. aureus. The RPA might be used as an effective diagnostic test in clinical microbiology laboratories to improve the design and application of antibiotic therapy. IMPORTANCE Staphylococcus aureus is a species of Staphylococcus and belongs to Gram-positive. Meanwhile, S. aureus remains one of the most common nosocomial and community-acquired infections, causing blood flow, skin, soft tissue, and lower respiratory tract infections. The identification of the particular nuc gene and the other eight genes of drug-resistant S. aureus can reliably and quickly diagnose the illness, allowing doctors to prescribe treatment regimens sooner. The detection target in this work is a particular gene of S. aureus, and a POCT is built to simultaneously recognize S. aureus and analyze genes representing four common antibiotic families. We developed and assessed a rapid and on-site diagnostic platform for the specific and sensitive detection of S. aureus. This method allows the determination of S. aureus infection and 10 different AMR genes representing four different families of antibiotics within 40 min. It was easily adaptable in low-resource circumstances and professional-lacking circumstances. It should be supported in overcoming the continuous difficulty of drug-resistant S. aureus infections, which is a shortage of diagnostic tools that can swiftly detect infectious bacteria and numerous antibiotic resistance indicators.
Effect of particle size and laser power on the Raman spectra of CuAlO2 delafossite nanoparticles

A transparent conductive oxide CuAlO2 delafossite is studied using x-ray powder diffraction (XRD) and micro-Raman spectroscopy measurements as a function of the particle size and laser power from 2 to 20 mW. The XRD results indicate that the lattice parameters and the cell volume expand as the particle size reduces. Large red shifts (∼60 cm−1) and line broadening (∼50 cm−1) are observed as the particle size becomes of the order of 13 nm. These huge values can only be justified if collective effects on the Raman spectra created by the lattice expansion, confinement of phonons and enhanced phonon–phonon interactions are included in the interpretations of the Raman spectra of the CuAlO2 nanoparticles.
Knowledge and Awareness of Human Papillomavirus Vaccination and Cervical Cancer among Men and Women in Japan: A Questionnaire Survey

Background: In many advanced countries other than Japan, the incidence and mortality rates of cervical cancer, which is mainly caused by the human papillomavirus (HPV) infection, are decreasing probably due to the high rate of HPV vaccination and cervical cancer screening. In Japan, these rates are on the rise owing to the stagnation of vaccination and low screening rate. To improve these situations, active promotion of HPV vaccination and screening is required. As a preliminary stage, we investigated perceptions regarding cervical cancer and HPV vaccines among Japanese men and women and examined the difference in perceptions by sex. Methods: This was a prospective cross-sectional questionnaire survey targeting Sojo University students and working adults. University students were targeted before learning about cervical cancer. Working adults were recruited on the basis of information from the Health Promotion of Health and Welfare Department of Kumamoto Prefectural Government in Japan and from companies via student organizations promoting cancer prevention. We surveyed respondents’ knowledge and awareness about HPV vaccination and cervical cancer and performed logistic regression analysis to compare the results between men and women. Result: A total of 557 completed questionnaires (205 men and 352 women) were analyzed. Women had high levels of knowledge and awareness about HPV vaccination and cervical cancer compared with men. However, 70% of women surveyed had never been screened for cervical cancer. Conclusion: A total of 557 completed questionnaires (205 men and 352 women) were analyzed. Women had high levels of knowledge and awareness about HPV vaccination and cervical cancer compared with men. However, among surveyed women, the degree of knowledge and awareness was lower than that among women in other countries with established HPV vaccination programs. Furthermore, 70% of women surveyed had never been screened for cervical cancer.
Fabrication of Three-Dimensional Hydrogen Silsesquioxane Resist Structure using Electron Beam Lithography

We have investigated a process for fabricating three-dimensional (3D) structures using electron beam lithography (EBL), in which such a structure is fabricated from a negative tone resist of hydrogen silsesquioxane (HSQ). The HSQ film for this purpose is coated on a Si wafer and is about 250 nm thick. In electron beam (EB) exposure, the depth of HSQ resist is controlled by the strength of the EB acceleration voltage. After exposing the resist according to a carefully planned scheme, followed by a developing process, a free standing and 3D HSQ structure is fabricated. This structure is a mesh saved in midair, and a line in the structure is 200 nm wide, 100 nm thick, and 1.8 µm long. These samples consisting of a periodic structure are then used as 3D photonic crystals. Fabrication of 3D photonic crystals is a complicated process, but our current work simplifies the task to a great extent.
A hierarchical model for space–time surveillance data on meningococcal disease incidence

Summary. We describe a model‐based approach to analyse space–time surveillance data on meningococcal disease. Such data typically comprise a number of time series of disease counts, each representing a specific geographical area. We propose a hierarchical formulation, where latent parameters capture temporal, seasonal and spatial trends in disease incidence. We then add—for each area—a hidden Markov model to describe potential additional (autoregressive) effects of the number of cases at the previous time point. Different specifications for the functional form of this autoregressive term are compared which involve the number of cases in the same or in neighbouring areas. The two states of the Markov chain can be interpreted as representing an ‘endemic’ and a ‘hyperendemic’ state. The methodology is applied to a data set of monthly counts of the incidence of meningococcal disease in the 94 départements of France from 1985 to 1997. Inference is carried out by using Markov chain Monte Carlo simulation techniques in a fully Bayesian framework. We emphasize that a central feature of our model is the possibility of calculating—for each region and each time point—the posterior probability of being in a hyperendemic state, adjusted for global spatial and temporal trends, which we believe is of particular public health interest.
Pomalidomide and dexamethasone until progression after first salvage therapy in multiple myeloma

Lenalidomide maintenance in myeloma is well established. Nevertheless, pomalidomide could provide an alternative. Myeloma patients in first relapse, initially treated in the Intergroupe Francophone du Myélome (IFM) 2009 trial, and subsequently in the IFM 2013‐01 phase 2 trial, received four cycles of salvage therapy with pomalidomide plus cyclophosphamide plus dexamethasone (PCD) with transplantation plus 2 PCD consolidation or without transplantation but with 5 PCD and for all patients pomalidomide plus dexamethasone maintenance therapy. This consisted of 28‐day cycles of pomalidomide 4 mg daily on days 1–21 and dexamethasone 20 mg weekly until progression. The primary endpoint was an improved response to treatment. A total of 75/100 patients reached therapy. The median follow‐up time was 73 months. The median duration of treatment was 23.7 months. One third of patients improved their response from the initiation of treatment: 11%, 19% and 4% to a very good partial response, complete response or stringent complete response respectively. The median progression‐free survival time was 33.2 months and the median overall survival time was not reached. Among the 75 patients, the reasons for pomalidomide discontinuation were progressive disease (54%), adverse events (AEs) (30%), investigator discretion (11%) and consent withdrawal (5%). Grade (G) 3/4 haematological AEs included neutropenia (51%) and lymphopenia (35%); G3/4 drug‐related non‐haematological AEs (>5%) comprised 13% infections. Long‐term administration of pomalidomide and dexamethasone is feasible and one third of the patients improved their response.
Butterfly foraging is remarkably synchronous in an experimental tropical macrocosm

Diel patterns in foraging activity are dictated by a combination of abiotic, biotic and endogenous limits. Understanding these limits is important for insects because ectotherm taxa will respond more pronouncedly to ongoing climatic change, potentially affecting crucial ecosystem services. We leverage an experimental macrocosm, the Montreal Insectarium Grand Vivarium, to test the importance of endogenous mechanisms in determining temporal patterns in foraging activity of butterflies. Specifically, we assessed the degree of temporal niche partitioning among 24 butterfly species originating from the Earth's tropics within controlled environmental conditions. We found strong niche overlap, with the frequency of foraging events peaking around solar noon for 96% of the species assessed. Our models suggest that this result was not due to the extent of cloud cover, which affects radiational heating and thus limits body temperature in butterflies. Together, these findings suggest that an endogenous mechanism evolved to regulate the timing of butterfly foraging activity within suitable environmental conditions. Understanding similar mechanisms will be crucial to forecast the effects of climate change on insects, and thus on the many ecosystem services they provide.
Combining Multiple Psychophysiological Measures of Listening Effort: Challenges and Recommendations

Abstract About one-third of all recently published studies on listening effort have used at least one physiological measure, providing evidence of the popularity of such measures in listening effort research. However, the specific measures employed, as well as the rationales used to justify their inclusion, vary greatly between studies, leading to a literature that is fragmented and difficult to integrate. A unified approach that assesses multiple psychophysiological measures justified by a single rationale would be preferable because it would advance our understanding of listening effort. However, such an approach comes with a number of challenges, including the need to develop a clear definition of listening effort that links to specific physiological measures, customized equipment that enables the simultaneous assessment of multiple measures, awareness of problems caused by the different timescales on which the measures operate, and statistical approaches that minimize the risk of type-I error inflation. This article discusses in detail the various obstacles for combining multiple physiological measures in listening effort research and provides recommendations on how to overcome them.
The Relationship between Bone Mineral Densitometry and Visceral Adiposity Index in Postmenopausal Women

Abstract Objective It was aimed to compare visceral adiposity index (VAI) levels in patients with normal bone mineral density (BMD), osteopenia, and osteoporosis. Methods One hundred twenty postmenopausal women (40 with normal BMD, 40 with osteopenia, and 40 with osteoporosis) between the ages of 50 to 70 years were included in the study. For females, the VAI was calculated using the formula (waist circumference [WC]/[36.58 + (1.89 x body mass index (BMI))]) x (1.52/High-density lipoprotein [HDL]-cholesterol [mmol/L]) x (triglyceride [TG]/0.81 [mmol/L]). Results The time of menopause from the beginning was similar in all groups. Waist circumference was found to be higher in those with normal BMD than in the osteopenic and osteoporotic groups ( p = 0.018 and p < 0.001, respectively), and it was also higher in the osteopenic group than in the osteoporotic group ( p = 0.003). Height and body weight, BMI, blood pressure, insulin, glucose, HDL-cholesterol, and homeostasis model assessment-insulin resistance (HOMA-IR) levels were similar in all groups. Triglyceride levels were found to be higher in the normal BMD group, compared with the osteoporotic group ( p = 0.005). The level of VAI was detected as higher in those with normal BMD, compared with the women with osteoporosis ( p = 0.002). Additionally, the correlation analysis showed a positive correlation between dual-energy X-ray absorptiometry (DXA) spine T -scores, WC, VAI, and a negative correlation between DXA spine T -scores and age. Conclusion In our study, we found higher VAI levels in those with normal BMD, compared with women with osteoporosis. We consider that further studies with a larger sample size will be beneficial in elucidating the entity.
X-CHAR: A Concept-based Explainable Complex Human Activity Recognition Model

End-to-end deep learning models are increasingly applied to safety-critical human activity recognition (HAR) applications, e.g., healthcare monitoring and smart home control, to reduce developer burden and increase the performance and robustness of prediction models. However, integrating HAR models in safety-critical applications requires trust, and recent approaches have aimed to balance the performance of deep learning models with explainable decision-making for complex activity recognition. Prior works have exploited the compositionality of complex HAR (i.e., higher-level activities composed of lower-level activities) to form models with symbolic interfaces, such as concept-bottleneck architectures, that facilitate inherently interpretable models. However, feature engineering for symbolic concepts-as well as the relationship between the concepts-requires precise annotation of lower-level activities by domain experts, usually with fixed time windows, all of which induce a heavy and error-prone workload on the domain expert. In this paper, we introduce X-CHAR, an eXplainable Complex Human Activity Recognition model that doesn't require precise annotation of low-level activities, offers explanations in the form of human-understandable, high-level concepts, while maintaining the robust performance of end-to-end deep learning models for time series data. X-CHAR learns to model complex activity recognition in the form of a sequence of concepts. For each classification, X-CHAR outputs a sequence of concepts and a counterfactual example as the explanation. We show that the sequence information of the concepts can be modeled using Connectionist Temporal Classification (CTC) loss without having accurate start and end times of low-level annotations in the training dataset-significantly reducing developer burden. We evaluate our model on several complex activity datasets and demonstrate that our model offers explanations without compromising the prediction accuracy in comparison to baseline models. Finally, we conducted a mechanical Turk study to show that the explanations provided by our model are more understandable than the explanations from existing methods for complex activity recognition.
Voicify Your UI

Nowadays, voice assistants help users complete tasks on the smartphone with voice commands, replacing traditional touchscreen interactions when such interactions are inhibited. However, the usability of those tools remains moderate due to the problems in understanding rich language variations in human commands, along with efficiency and comprehensibility issues. Therefore, we introduce Voicify, an Android virtual assistant that allows users to interact with on-screen elements in mobile apps through voice commands. Using a novel deep learning command parser, Voicify interprets human verbal input and performs matching with UI elements. In addition, the tool can directly open a specific feature from installed applications by fetching application code information to explore the set of in-app components. Our command parser achieved 90% accuracy on the human command dataset. Furthermore, the direct feature invocation module achieves better feature coverage in comparison to Google Assistant. The user study demonstrates the usefulness of Voicify in real-world scenarios.
Fast Geometric Image Representation Using Wedgelets and Multitree Dictionaries

Wavelet transform is successful for image processing including compression, denoising, detection and so on. But it has significant shortcoming for capturing image geometric feature, such as edges or contours, which causes a large number of multiscale wavelet coefficients for describing the joint coherent behavior. Wedgelet is an effective geometric tool for image representation. We use recursive top-down quadtree pruning algorithm based on fast multitree search and decorate leaves by wedgelets compared to traditional bottom-up pruning strategy. Meanwhile, simple coding strategy is presented and analyzed in this paper. Numerical results suggest that new methods with desirable rate-distortion behavior reduce computation complexity for searching different dyadic squares and capture natural geometric structure of image effectively.
Combined SPR and SERS: Otto and Kretschmann configurations

Combined surface enhanced Raman spectroscopy (SERS) and surface plasmon resonance (SPR) setup was proposed recently. The experimental setup requires a gold layer deposited on a glass substrate. However, due to the poor ability of sticking gold material on glass, a nanometric adhesion layer is used. In this paper we compare numerically both the SERS gain, and the SPR signal, for metallic and dielectric adhesion layers, for two substrates. We show that even if the dielectric materials can be considered as equivalent for the SPR signal, this is not the case for the SERS gain. In particular the dielectric adhesion layer reduces the sensitivity of the SERS gain to this parameter and therefore their use could be more suitable for the fabrication of the sensor. Moreover the higher the refractive index of substrate with regards to the adhesion layer is, the higher efficiency of setup is obtained, and therefore the Otto configuration seems to be more efficient than the Kretschmann one. Optimization of the thicknesses of the adhesion layer and of the gold layer can lead to a SERS gain greater than 103 without nanostructuring.
DETERMINING SPECTROMETER INSTRUMENTAL PROFILES USING FTS REFERENCE SPECTRA

We describe a new technique for determining the instrumental profile (IP) of an astronomical spectrometer. A known instrinsic spectrum of a reference source is convoluted with a parameterized IP and then compared to a spectrum obtained with the spectrometer to be characterized. Nonlinear least-squares (NLLS) optimization is used to solve for the analytic IP that best reproduces the observed spectrum. This technique is most effective for characterizing the central portion of the IP, out to 1% of the peak. IP recovery is demonstrated using both the Sun and an I2 absorption cell as reference spectra. We also describe a second technique employing singular value decomposition (SVD) to recover an approximate IP by directly inverting a discretized convolution. This second technique is less contstrained and therefore gives poorer results than NLLS, but it is useful when the form of the IP is unknown. Using the NLLS technique, we demonstrate by example that the IP is a function of position in the format of cross-dispersed echelle spectrometers. We also compare our results with laser and thorium emission line profiles. Finally, we present the IP for a range of positions in the format of the Hamilton echelle spectrograph at Lick Observatory and the HIRES echelle at the Keck 10-m telescope.
Nonparametric Identification under Discrete Variation

This paper provides weak conditions under which there is nonparametric interval identification of local features of a structural function that depends on a discrete endogenous variable and is nonseparable in latent variates. The function delivers values of a discrete or continuous outcome and instruments may be discrete valued. Application of the analog principle leads to quantile regression based interval estimators of values and partial differences of structural functions. The results are used to investigate the nonparametric identifying power of the quarter-of-birth instruments used in Angrist and Krueger's 1991 study of the returns to schooling.
Recent Acceleration of Wetland Accretion and Carbon Accumulation Along the U.S. East Coast

The long‐term stability of coastal wetlands is determined by interactions among sea level, plant primary production, sediment supply, and wetland vertical accretion. Human activities in watersheds have significantly altered sediment delivery from the landscape to the coastal ocean, with declines along much of the U.S. East Coast. Tidal wetlands in coastal systems with low sediment supply may have limited ability to keep pace with accelerating rates of sea‐level rise (SLR). Here, we show that rates of vertical accretion and carbon accumulation in nine tidal wetland systems along the U.S. East Coast from Maine to Georgia can be explained by differences in the rate of relative SLR (RSLR), the concentration of suspended sediments in the rivers draining to the coast, and temperature in the coastal region. Further, we show that rates of vertical accretion have accelerated over the past century by between 0.010 and 0.083 mm yr−2, at roughly the same pace as the acceleration of global SLR. We estimate that rates of carbon sequestration in these wetland soils have accelerated (more than doubling at several sites) along with accelerating accretion. Wetland accretion and carbon accumulation have accelerated more rapidly in coastal systems with greater relative RSLR, higher watershed sediment availability, and lower temperatures. These findings suggest that the biogeomorphic feedback processes that control accretion and carbon accumulation in these tidal wetlands have responded to accelerating RSLR, and that changes to RSLR, watershed sediment supply, and temperature interact to determine wetland vulnerability across broad geographic scales.