Factors Associated With Delays in Presentation and Treatment of Gonorrhea, Massachusetts 2015-2019.

BACKGROUND: Rates of gonorrhea are increasing across the United States. Understanding and addressing contributing factors associated with longer time to diagnosis and treatment may shorten the duration of infectiousness, which in turn may limit transmission. METHODS: We used Massachusetts data from the US Centers for Disease Control and Prevention Sexually Transmitted Disease Surveillance Network collected between July 2015 and September 2019, along with routinely reported surveillance data, to assess time from gonorrhea symptom onset to presentation to care, and time from presentation to care to receipt of treatment. Factors associated with longer time to presentation (TTP) and time to treatment (TTT) were assessed using Cox proportional hazard models with a constant time variable. RESULTS: Among symptomatic patients (n = 672), 31% did not receive medical care within 7 days of symptom onset. Longer TTP was associated with younger age, female gender, reporting cost as a barrier to care, and provider report of proctitis. Among patients with symptoms and/or known contact to gonorrhea (n = 827), 42% did not receive presumptive treatment. Longer TTT was associated with female gender, non-Hispanic other race/ethnicity, and clinics with less gonorrhea treatment experience. Among asymptomatic patients without known exposure to STI (n = 235), 26% did not receive treatment within 7 days. Longer TTT was associated with sexually transmitted disease clinic/family planning/reproductive health clinics and a test turnaround time of ≥3 days. CONCLUSIONS: Delays in presentation to care and receipt of treatment for gonorrhea are common. Factors associated with longer TTP and TTT highlight multiple opportunities for reducing the infectious period of patients with gonorrhea.

Are camera, projector, and camera-projector calibrations different?

Structured light projection systems have become a referent in three-dimensional optical metrology. Calibration of the cameras and projectors of these systems is one of the most critical procedures to achieve high-accuracy measurements. However, the calibration process requires some clarifications for adequate experimental implementation. For instance, it is typically assumed that the calibration of a camera-projector pair differs from calibrating a camera, and the calibration of a projector is possible only with an attached auxiliary camera. This paper presents a unified methodology for camera, projector, and camera-projector calibrations. Experimental results are discussed, providing practical insights into how structured light systems are calibrated. The MATLAB code and data employed in this study are available.

Restoration of Binocular Images Degraded by Optical Scattering through Estimation of Atmospheric Coefficients.

A binocular vision-based approach for the restoration of images captured in a scattering medium is presented. The scene depth is computed by triangulation using stereo matching. Next, the atmospheric parameters of the medium are determined with an introduced estimator based on the Monte Carlo method. Finally, image restoration is performed using an atmospheric optics model. The proposed approach effectively suppresses optical scattering effects without introducing noticeable artifacts in processed images. The accuracy of the proposed approach in the estimation of atmospheric parameters and image restoration is evaluated using synthetic hazy images constructed from a well-known database. The practical viability of our approach is also confirmed through a real experiment for depth estimation, atmospheric parameter estimation, and image restoration in a scattering medium. The results highlight the applicability of our approach in computer vision applications in challenging atmospheric conditions.

Langer's arch in axillary dissections from patients with breast cancer: a retrospective study.

PURPOSE: The study aimed to assess the frequency of Langer's arch in patients undergoing axillary dissection for breast cancer. METHODS: From January-2015 to March-2020, in a general hospital in México City, female patients undergoing axillary dissection for breast cancer were studied. The analysis involved: demographic and anthropometric data, type of surgical treatment, histopathologic diagnosis, number of lymph nodes harvested, and frequency of Langer's arch finding. RESULTS: The sample studied was 123 axillary dissections. The mean age of the patients was 59 ± 10.5-years. Modified radical mastectomy was done in 117 cases (95.1%). Ductal carcinoma occurred in 96 cases (78%). The mean number of lymph nodes harvested was 24 ± 6.5. Langer's arch finding occurred in 33 cases (26.8%). CONCLUSION: Langer's arch is frequent in our patients undergoing axillary dissection for breast cancer.

Stereo-phase rectification for metric profilometry with two calibrated cameras and one uncalibrated projector.

Fringe projection profilometry requires calibrating both cameras and projectors for metric measurements. Cameras are relatively simple to calibrate, but projectors require more sophisticated procedures. In this paper, a fringe projection profilometer with two calibrated cameras and one uncalibrated projector is developed for metric measurements. A phase rectification method, which is crucial for stereo matching, is designed by minimizing the perspective distortion. Also, a simple method for point matching using stereo rectified phase maps is proposed. The principles of metric profilometry using the proposed rectification method are introduced. The developed system is evaluated experimentally by the metric measurement of three-dimensional objects. The obtained results confirm a high accuracy of metric measurement and versatility in the design of fringe projection profilometers with uncalibrated projectors.

Homography estimation from a single-point correspondence using template matching and particle swarm optimization.

Existing feature-based methods for homography estimation require several point correspondences in two images of a planar scene captured from different perspectives. These methods are sensitive to outliers, and their effectiveness depends strongly on the number and accuracy of the specified points. This work presents an iterative method for homography estimation that requires only a single-point correspondence. The homography parameters are estimated by solving a search problem using particle swarm optimization, by maximizing a match score between a projective transformed fragment of the input image using the estimated homography and a matched filter constructed from the reference image, while minimizing the reprojection error. The proposed method can estimate accurately a homography from a single-point correspondence, in contrast to existing methods, which require at least four points. The effectiveness of the proposed method is tested and discussed in terms of objective measures by processing several synthetic and experimental projective transformed images.

Changes in belowground biodiversity during ecosystem development.

Belowground organisms play critical roles in maintaining multiple ecosystem processes, including plant productivity, decomposition, and nutrient cycling. Despite their importance, however, we have a limited understanding of how and why belowground biodiversity (bacteria, fungi, protists, and invertebrates) may change as soils develop over centuries to millennia (pedogenesis). Moreover, it is unclear whether belowground biodiversity changes during pedogenesis are similar to the patterns observed for aboveground plant diversity. Here we evaluated the roles of resource availability, nutrient stoichiometry, and soil abiotic factors in driving belowground biodiversity across 16 soil chronosequences (from centuries to millennia) spanning a wide range of globally distributed ecosystem types. Changes in belowground biodiversity during pedogenesis followed two main patterns. In lower-productivity ecosystems (i.e., drier and colder), increases in belowground biodiversity tracked increases in plant cover. In more productive ecosystems (i.e., wetter and warmer), increased acidification during pedogenesis was associated with declines in belowground biodiversity. Changes in the diversity of bacteria, fungi, protists, and invertebrates with pedogenesis were strongly and positively correlated worldwide, highlighting that belowground biodiversity shares similar ecological drivers as soils and ecosystems develop. In general, temporal changes in aboveground plant diversity and belowground biodiversity were not correlated, challenging the common perception that belowground biodiversity should follow similar patterns to those of plant diversity during ecosystem development. Taken together, our findings provide evidence that ecological patterns in belowground biodiversity are predictable across major globally distributed ecosystem types and suggest that shifts in plant cover and soil acidification during ecosystem development are associated with changes in belowground biodiversity over centuries to millennia.

Stereo Image Matching Using Adaptive Morphological Correlation.

A stereo matching method based on adaptive morphological correlation is presented. The point correspondences of an input pair of stereo images are determined by matching locally adaptive image windows using the suggested morphological correlation that is optimal with respect to an introduced binary dissimilarity-to-matching ratio criterion. The proposed method is capable of determining the point correspondences in homogeneous image regions and at the edges of scene objects of input stereo images with high accuracy. Furthermore, unknown correspondences of occluded and not matched points in the scene can be successfully recovered using a simple proposed post-processing. The performance of the proposed method is exhaustively tested for stereo matching in terms of objective measures using known database images. In addition, the obtained results are discussed and compared with those of two similar state-of-the-art methods.

Evidence of Isomerization in the Michael-Type Thiol-Maleimide Addition: Click Reaction between L-Cysteine and 6-Maleimidehexanoic Acid.

The reaction between L-cysteine (Cys) and 6-maleimidohexanoic acid (Mhx) in an aqueous medium at different levels of pH was analyzed via RP-HPLC, finding the presence of two reaction products throughout the evaluated pH range. By means of solid-phase extraction (SPE), it was possible to separate the products and obtain isolated profiles enriched up to 80%. The products were analyzed individually through mass spectrometry, DAD-HPLC, NMR 1H, 13C, and two-dimensional evidence of isomerization between the hydrogen atoms of the α-amino and the thiol group present in the cysteine. Thus, it was concluded that the products obtained corresponded to a mixture of the isomer Cys-S-Mhx, where the adduct is formed by a thioether bond, and the isomer Cys-NH-Mhx, in which the union is driven by the amino group. We consider that the phenomenon of isomerization is an important finding, since it has not previously been reported for this reaction.

[Prescription of antibiotics in acute respiratory infections non-pneumonia in a private outpatient practice]. / Prescripción de antibióticos en las infecciones respiratorias agudas no neumonías en atención ambulatoria en la práctica privada.

BACKGROUND: The over prescription of antibiotics for acute respiratory infections is a major public health problem worldwide. AIM: To evaluate the frequency of prescription of antibiotics for non-pneumonia acute respiratory infections in private outpatient clinics in individuals without chronic diseases or immunosuppression. MATERIAL AND METHODS: All medical records of adult consultants in a national network of private ambulatory medical centers during May 2018 whose primary diagnosis corresponded to acute respiratory infections not pneumonia (ICD10) were identified and retrospectively analyzed, excluding those with chronic respiratory conditions or states of immunosuppression. RESULTS: Of the 38,072 consultants (aged 36 years, 63% women) who met this criterion, 54% (n = 20,499) received a prescription for at least one antibiotic. The diagnoses that most frequently received this prescription were acute bronchitis (28.7%), acute sinusitis (16.5%) and acute tonsillitis (16.2%). The most frequently prescribed antibiotic globally was azithromycin (37.4%), followed by amoxicillin (20.1%) and amoxicillin plus clavulanic acid (17.7%). Levofloxacin prescription reached 12.5% of total prescriptions. CONCLUSIONS: An antibiotic was prescribed in more than half of the non-pneumonia outpatient acute respiratory infections. Azithromycin was the most prescribed antibiotic, while levofloxacin exceeded 10% of prescriptions. These results reinforce the need to implement an antibiotic prescription surveillance system at the outpatient level.

Genetic imprints of Brosimum alicastrum Sw. in Mexico.

PREMISE: The mechanisms generating the geographical distributions of genetic diversity are a central theme in evolutionary biology. The amount of genetic diversity and its distribution are controlled by several factors, including dispersal abilities, physical barriers, and environmental and climatic changes. We investigated the patterns of genetic diversity and differentiation among populations of the widespread species Brosimum alicastrum in Mexico. METHODS: Using nuclear DNA microsatellite data, we tested whether the genetic structure of B. alicastrum was associated with the roles of the Trans-Mexican Volcanic Belt and the Isthmus of Tehuantepec as geographical barriers to gene flow and to infer the role of past events in the genetic diversity patterns. We further used a maximum-likelihood population-effects mixed model (MLPE) to identify the main factor affecting population differentiation in B. alicastrum. RESULTS: Our results suggested that Mexican B. alicastrum is well differentiated into three main lineages. Patterns of the genetic structure at a finer scale did not fully correspond to the current geographical barriers to gene flow. According to the MLPE mixed model, isolation by distance is the best model for explaining the genetic differentiation of B. alicastrum in Mexico. CONCLUSIONS: We propose that the differentiation patterns might reflect (1) an ancient differentiation that occurred in Central and South America, (2) the effects of past climatic changes, and (3) the functions of some physical barriers to gene flow. This study provides insights into the possible mechanisms underlying the geographic genetic variation of B. alicastrum along a moisture gradient in tropical lowland forests.

Distorted pinhole camera modeling and calibration.

Camera modeling and calibration are essential tasks in modern optics. Conventionally, the pinhole model is adopted with a further extension for lens distortion. However, pinhole and distortion models are mutually dependent; thus, the standard approach induces systematic camera calibration errors. This research presents a unifying distorted pinhole camera model that includes a telecentric, distortion-free pinhole, and radial lens distortion as particular cases. An iterative calibration method based on the derived distorted pinhole model is proposed, and experimental evaluation by calibrating a camera with high radial distortion is performed. The calibration results are compared with the standard and fisheye models using a well-known commercial camera calibrator software. The proposed method outperforms the standard model and achieves accuracy comparable to the fisheye model, and the proposed approach is a versatile and accurate tool for diverse optical metrology applications.

Key concepts for phase-to-coordinate conversion in fringe projection systems.

Fringe projection systems encode the scanned object shape as a phase distribution according to the system parameters. However, to obtain the object shape in physical units of length, the demodulated phase must be converted to the coordinates of the observed points on the object surface. The design of a phase-to-coordinate conversion algorithm is straightforward when the following key concepts are considered: cameras and projectors as direction sensors, gratings as coordinate-encoding devices, absolute phase, and triangulation. In this paper, the theoretical principles of these concepts are formalized. Then, an efficient and generalized phase-to-coordinate conversion method, which supports systems with multiple cameras and projectors arranged arbitrarily, is proposed. The usefulness of this approach is illustrated by a 3D surface imaging experiment.

Adaptive matched filter for implicit-target recognition: application in three-dimensional reconstruction.

The design of matched filters for optical correlators requires explicit knowledge of the shape of the target. This requirement limits its usefulness in applications where the appearance of the target is unspecified or dynamically changing. This research presents the design of an adaptive correlation filter by the optimization of the mean-squared-error criterion when the shape of the target is implicit and embedded on a cluttered background with unknown statistics in the reference image. For this, estimators to obtain the region of support of the target as well as statistical parameters of additive and nonoverlapping noise of the scene are proposed. The performance of the proposed filter is analyzed in terms of detection efficiency and location accuracy of an implicit target in the context of stereo matching and three-dimensional reconstruction.

Vision-Based Novelty Detection Using Deep Features and Evolved Novelty Filters for Specific Robotic Exploration and Inspection Tasks.

One of the essential abilities in animals is to detect novelties within their environment. From the computational point of view, novelty detection consists of finding data that are different in some aspect to the known data. In robotics, researchers have incorporated novelty modules in robots to develop automatic exploration and inspection tasks. The visual sensor is one of the preferred sensors to perform this task. However, there exist problems as illumination changes, occlusion, and scale, among others. Besides, novelty detectors vary their performance depending on the specific application scenario. In this work, we propose a visual novelty detection framework for specific exploration and inspection tasks based on evolved novelty detectors. The system uses deep features to represent the visual information captured by the robots and applies a global optimization technique to design novelty detectors for specific robotics applications. We verified the performance of the proposed system against well-established state-of-the-art methods in a challenging scenario. This scenario was an outdoor environment covering typical problems in computer vision such as illumination changes, occlusion, and geometric transformations. The proposed framework presented high-novelty detection accuracy with competitive or even better results than the baseline methods.

Homography estimation by two PClines Hough transforms and a square-radial checkerboard pattern.

The homography matrix is crucial for many optical metrology applications, such as three-dimensional surface imaging by structured-light projection. In this paper, a straightforward homography estimation method using the image of three particular points on the reference plane is proposed. For this, a new square-radial checkerboard pattern designed to generate three sets of concurrent lines is proposed. The lines and points of interest are detected using two PClines Hough transforms. Relevant concepts such as parallel coordinates and the used Hough transforms are explained. The usefulness of our proposal is verified experimentally.

Sensor Compromise Detection in Multiple-Target Tracking Systems.

Tracking multiple targets using a single estimator is a problem that is commonly approached within a trusted framework. There are many weaknesses that an adversary can exploit if it gains control over the sensors. Because the number of targets that the estimator has to track is not known with anticipation, an adversary could cause a loss of information or a degradation in the tracking precision. Other concerns include the introduction of false targets, which would result in a waste of computational and material resources, depending on the application. In this work, we study the problem of detecting compromised or faulty sensors in a multiple-target tracker, starting with the single-sensor case and then considering the multiple-sensor scenario. We propose an algorithm to detect a variety of attacks in the multiple-sensor case, via the application of finite set statistics (FISST), one-class classifiers and hypothesis testing using nonparametric techniques.

Fatty Acid Diversity is Not Associated with Neutral Genetic Diversity in Native Populations of the Biodiesel Plant Jatropha curcas L.

Jatropha curcas L. (Euphorbiaceae) is a shrub native to Mexico and Central America, which produces seeds with a high oil content that can be converted to biodiesel. The genetic diversity of this plant has been widely studied, but it is not known whether the diversity of the seed oil chemical composition correlates with neutral genetic diversity. The total seed oil content, the diversity of profiles of fatty acids and phorbol esters were quantified, also, the genetic diversity obtained from simple sequence repeats was analyzed in native populations of J. curcas in Mexico. Using the fatty acids profiles, a discriminant analysis recognized three groups of individuals according to geographical origin. Bayesian assignment analysis revealed two genetic groups, while the genetic structure of the populations could not be explained by isolation-by-distance. Genetic and fatty acid profile data were not correlated based on Mantel test. Also, phorbol ester content and genetic diversity were not associated. Multiple linear regression analysis showed that total oil content was associated with altitude and seasonality of temperature. The content of unsaturated fatty acids was associated with altitude. Therefore, the cultivation planning of J. curcas should take into account chemical variation related to environmental factors.

Real-Time Hand Posture Recognition for Human-Robot Interaction Tasks.

In this work, we present a multiclass hand posture classifier useful for human-robot interaction tasks. The proposed system is based exclusively on visual sensors, and it achieves a real-time performance, whilst detecting and recognizing an alphabet of four hand postures. The proposed approach is based on the real-time deformable detector, a boosting trained classifier. We describe a methodology to design the ensemble of real-time deformable detectors (one for each hand posture that can be classified). Given the lack of standard procedures for performance evaluation, we also propose the use of full image evaluation for this purpose. Such an evaluation methodology provides us with a more realistic estimation of the performance of the method. We have measured the performance of the proposed system and compared it to the one obtained by using only the sampled window approach. We present detailed results of such tests using a benchmark dataset. Our results show that the system can operate in real time at about a 10-fps frame rate.

Modeling risk of occupational zoonotic influenza infection in swine workers.

Zoonotic transmission of influenza A virus (IAV) between swine and workers in swine production facilities may play a role in the emergence of novel influenza strains with pandemic potential. Guidelines to prevent transmission of influenza to swine workers have been developed but there is a need for evidence-based decision-making about protective measures such as respiratory protection. A mathematical model was applied to estimate the risk of occupational IAV exposure to swine workers by contact and airborne transmission, and to evaluate the use of respirators to reduce transmission. The Markov model was used to simulate the transport and exposure of workers to IAV in a swine facility. A dose-response function was used to estimate the risk of infection. This approach is similar to methods previously used to estimate the risk of infection in human health care settings. This study uses concentration of virus in air from field measurements collected during outbreaks of influenza in commercial swine facilities, and analyzed by polymerase chain reaction. It was found that spending 25 min working in a barn during an influenza outbreak in a swine herd could be sufficient to cause zoonotic infection in a worker. However, this risk estimate was sensitive to estimates of viral infectivity to humans. Wearing an excellent fitting N95 respirator reduced this risk, but with high aerosol levels the predicted risk of infection remained high under certain assumptions. The results of this analysis indicate that under the conditions studied, swine workers are at risk of zoonotic influenza infection. The use of an N95 respirator could reduce such risk. These findings have implications for risk assessment and preventive programs targeting swine workers. The exact level of risk remains uncertain, since our model may have overestimated the viability or infectivity of IAV. Additionally, the potential for partial immunity in swine workers associated with repeated low-dose exposures or from previous infection with other influenza strains was not considered. Further studies should explore these uncertainties.