Evaluation of Vestibular Function with Visual Feedback Posturography and Motorized Head Impulse Test.

Objectives: To evaluate the applicability of visual feedback posturography (VFP) for quantification of postural control, and to characterize the horizontal angular vestibulo-ocular reflex (AVOR) by use of a novel motorized head impulse test (MHIT). Methods: In VFP, subjects standing on a platform were instructed to move their center of gravity to symmetrically placed peripheral targets as fast and accurately as possible. The active postural control movements were measured in healthy subjects (n = 23), and in patients with vestibular schwannoma (VS) before surgery (n = 49), one month (n = 17), and three months (n = 36) after surgery. In MHIT we recorded head and eye position during motorized head impulses (mean velocity of 170º/s and acceleration of 1 550º/s²) in healthy subjects (n = 22), in patients with VS before surgery (n = 38) and about four months afterwards (n = 27). The gain, asymmetry and latency in MHIT were calculated. Results: The intraclass correlation coefficient for VFP parameters during repeated tests was significant (r = 0.78-0.96; p < 0.01), although two of four VFP parameters improved slightly during five test sessions in controls. At least one VFP parameter was abnormal pre- and postoperatively in almost half the patients, and these abnormal preoperative VFP results correlated significantly with abnormal postoperative results. The mean accuracy in postural control in patients was reduced pre- and postoperatively. A significant side difference with VFP was evident in 10% of patients. In the MHIT, the normal gain was close to unity, the asymmetry in gain was within 10%, and the latency was a mean ± standard deviation 3.4 ± 6.3 milliseconds. Ipsilateral gain or asymmetry in gain was preoperatively abnormal in 71% of patients, whereas it was abnormal in every patient after surgery. Preoperative gain (mean ± 95% confidence interval) was significantly lowered to 0.83 ± 0.08 on the ipsilateral side compared to 0.98 ± 0.06 on the contralateral side. The ipsilateral postoperative mean gain of 0.53 ± 0.05 was significantly different from preoperative gain. Conclusion: The VFP is a repeatable, quantitative method to assess active postural control within individual subjects. The mean postural control in patients with VS was disturbed before and after surgery, although not severely. Side difference in postural control in the VFP was rare. The horizontal AVOR results in healthy subjects and in patients with VS, measured with MHIT, were in agreement with published data achieved using other techniques with head impulse stimuli. The MHIT is a non-invasive method which allows reliable clinical assessment of the horizontal AVOR.

Naphthalene Carbohydrazone Based Dizinc(II) Chemosensor for a Pyrophosphate Ion and Its DNA Assessment Application in Polymerase Chain Reaction Products

A new naphthalene carbohydrazone based dizinc(II) complex has been synthesized and investigated to act as a highly selective fluorescence and visual sensor for a pyrophosphate ion with a quite low detection limit of 155 ppb; this has also been used to detect the pyrophosphate ion released from polymerase-chain-reaction.

Assessment of driver vision functions in relation to their crash involvement in India

Among the human factors that influence safe driving, visual skills of the driver can be considered fundamental. This study mainly focuses on investigating the effect of visual functions of drivers in India on their road crash involvement. Experiments were conducted to assess vision functions of Indian licensed drivers belonging to various organizations, age groups and driving experience. The test results were further related to the crash involvement histories of drivers through statistical tools. A generalized linear model was developed to ascertain the influence of these traits on propensity of crash involvement. Among the sampled drivers, colour vision, vertical field of vision, depth perception, contrast sensitivity, acuity and phoria were found to influence their crash involvement rates. In India, there are no efficient standards and testing methods to assess the visual capabilities of drivers during their licensing process and this study highlights the need for the same.

Measurement errors in body size of sea scallops (Placopecten magellanicus) and their effect on stock assessment models

Body-size measurement errors are usually ignored in stock assessments, but may be important when body-size data (e.g., from visual sur veys) are imprecise. We used experiments and models to quantify measurement errors and their effects on assessment models for sea scallops (Placopecten magellanicus). Errors in size data obscured modes from strong year classes and increased frequency and size of the largest and smallest sizes, potentially biasing growth, mortality, and biomass estimates. Modeling techniques for errors in age data proved useful for errors in size data. In terms of a goodness of model fit to the assessment data, it was more important to accommodate variance than bias. Models that accommodated size errors fitted size data substantially better. We recommend experimental quantification of errors along with a modeling approach that accommodates measurement errors because a direct algebraic approach was not robust and because error parameters were diff icult to estimate in our assessment model. The importance of measurement errors depends on many factors and should be evaluated on a case by case basis.

Ultrasound elastography as an adjuvant to conventional ultrasound in the preoperative assessment of axillary lymph nodes in suspected breast cancer: a pilot study.

AIMS: To compare the performance of ultrasound elastography with conventional ultrasound in the assessment of axillary lymph nodes in suspected breast cancer and whether ultrasound elastography as an adjunct to conventional ultrasound can increase the sensitivity of conventional ultrasound used alone. MATERIALS AND METHODS: Fifty symptomatic women with a sonographic suspicion for breast cancer underwent ultrasound elastography of the ipsilateral axilla concurrent with conventional ultrasound being performed as part of triple assessment. Elastograms were visually scored, strain measurements calculated and node area and perimeter measurements taken. Theoretical biopsy cut points were selected. The sensitivity, specificity, positive predictive value (PPV), and negative predictive values (NPV) were calculated and receiver operating characteristic (ROC) analysis was performed and compared for elastograms and conventional ultrasound images with surgical histology as the reference standard. RESULTS: The mean age of the women was 57 years. Twenty-nine out of 50 of the nodes were histologically negative on surgical histology and 21 were positive. The sensitivity, specificity, PPV, and NPV for conventional ultrasound were 76, 78, 70, and 81%, respectively; 90, 86, 83, and 93%, respectively, for visual ultrasound elastography; and for strain scoring, 100, 48, 58 and 100%, respectively. There was no significant difference between any of the node measurements CONCLUSIONS: Initial experience with ultrasound elastography of axillary lymph nodes, showed that it is more sensitive than conventional ultrasound in detecting abnormal nodes in the axilla in cases of suspected breast cancer. The specificity remained acceptable and ultrasound elastography used as an adjunct to conventional ultrasound has the potential to improve the performance of conventional ultrasound alone.

Cruise report: regional assessment of ecosystem condition and stressor impacts along the northwestern Gulf of Mexico Shelf. NOAA Ship 'Nancy Foster' NF-11-07-RACOW (August 8-16, 2011)

This cruise report is a summary of a field survey conducted along a portion of the U.S. continental shelf in northwestern Gulf of Mexico (GOM), at navigable depths along the coastline seaward to the shelf break (~100m) from about 89°30' W to 95°28' W longitude, August 8 – 16, 2011 on NOAA Ship Nancy Foster Cruise NF-11-07-RACOW. Synoptic sampling of multiple ecological indicators was conducted at each of 34 stations throughout these waters using a random probabilistic sampling design. The original study design consisted of 50 stations extending from the Mississippi delta all the way to the U.S./Mexican border, but vessel failures precluded sampling at 16 stations within the western-most portion of the study area. At each station samples were collected for the analysis of benthic community structure and composition; concentrations of chemical contaminants in sediments and target demersal biota; sediment toxicity; nutrient and chlorophyll levels in the water column; and other basic habitat characteristics such as salinity, temperature, dissolved oxygen, turbidity, pH, sediment grain size, and organic carbon content. Other indicators, from a human-dimension perspective, were also recorded, including presence of vessels, oil rigs, surface trash, visual oil sheens in sediments or water, marine mammals, or noxious/oily sediment odors. The overall purpose of the survey was to collect data to assess the status of ecosystem condition and potential stressor impacts throughout the region, based on these various indicators and corresponding management thresholds, and to provide this information as a baseline for determining how such conditions may be changing with time. While sample analysis is still ongoing, some preliminary results and observations are reported here. A final report will be completed once all data have been processed.

Cruise report: regional assessment of ecosystem condition and stressor impacts along the northeastern Gulf of Mexico shelf; NOAA Ship Nancy Foster NF-10-09-RACOW (August 13-21, 2010)

This cruise report is a summary of a field survey conducted along the continental shelf of the northeastern Gulf of Mexico (GOM), encompassing 70,062 square kilometers of productive marine habitats located between the Mississippi Delta and Tampa Bay, August 13–21, 2010 on NOAA Ship Nancy Foster Cruise NF-10-09-RACOW. Synoptic sampling of multiple ecological indicators was conducted at each of 50 stations throughout these waters using a random probabilistic sampling design. At each station samples were collected for the analysis of benthic community structure and composition; concentrations of chemical contaminants (metals, pesticides, TPHs, PAHs, PCBs, PBDEs) in sediments and target demersal biota; sediment toxicity; nutrient and chlorophyll levels in the water column; and other basic habitat characteristics such as depth, salinity, temperature, dissolved oxygen, turbidity, pH, CDOM fluorescence, sediment grain size, and organic carbon content. Discrete water samples were collected just below the sea surface, in addition to any deeper subsurface depths where there was an occurrence of suspicious CDOM fluorescence signals, and analyzed for total BTEX/TPH and carcinogenic PAHs using immunoassay test kits. Other indicators of potential value from a human-dimension perspective were also recorded, including presence of any vessels, oil rigs, surface trash, visual oil sheens in sediments or water, marine mammals, or noxious/oily sediment odors. The overall purpose of the survey was to collect data to assess the status of ecosystem condition and potential stressor impacts throughout the region, based on these various indicators and corresponding management thresholds, and to provide this information as a baseline for determining how such conditions may be changing with time. In addition to the original project goals, both the scientific scope and general location of this project are relevant to addressing potential ecological impacts of the Deepwater Horizon oil spill. While sample analysis is still ongoing, a few preliminary results and observations are reported here. A final report will be completed once all data have been processed.

Visual retrieval of concrete crack properties for automated post-earthquake structural safety evaluation

The safety of post-earthquake structures is evaluated manually through inspecting the visible damage inflicted on structural elements. This process is time-consuming and costly. In order to automate this type of assessment, several crack detection methods have been created. However, they focus on locating crack points. The next step, retrieving useful properties (e.g. crack width, length, and orientation) from the crack points, has not yet been adequately investigated. This paper presents a novel method of retrieving crack properties. In the method, crack points are first located through state-of-the-art crack detection techniques. Then, the skeleton configurations of the points are identified using image thinning. The configurations are integrated into the distance field of crack points calculated through a distance transform. This way, crack width, length, and orientation can be automatically retrieved. The method was implemented using Microsoft Visual Studio and its effectiveness was tested on real crack images collected from Haiti.

Machine vision based concrete surface quality assessment

Manually inspecting concrete surface defects (e.g., cracks and air pockets) is not always reliable. Also, it is labor-intensive. In order to overcome these limitations, automated inspection using image processing techniques was proposed. However, the current work can only detect defects in an image without the ability of evaluating them. This paper presents a novel approach for automatically assessing the impact of two common surface defects (i.e., air pockets and discoloration). These two defects are first located using the developed detection methods. Their attributes, such as the number of air pockets and the area of discoloration regions, are then retrieved to calculate defects’ visual impact ratios (VIRs). The appropriate threshold values for these VIRs are selected through a manual rating survey. This way, for a given concrete surface image, its quality in terms of air pockets and discoloration can be automatically measured by judging whether their VIRs are below the threshold values or not. The method presented in this paper was implemented in C++ and a database of concrete surface images was tested to validate its performance. Read More: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29CO.1943-7862.0000126?journalCode=jcemd4

Defects Detection and Assessment in Concrete Surfaces

Aside from cracks, the impact of other surface defects, such as air pockets and discoloration, can be detrimental to the quality of concrete in terms of strength, appearance and durability. For this reason, local and national codes provide standards for quantifying the quality impact of these concrete surface defects and owners plan for regular visual inspections to monitor surface conditions. However, manual visual inspection of concrete surfaces is a qualitative (and subjective) process with often unreliable results due to its reliance on inspectors’ own criteria and experience. Also, it is labor intensive and time-consuming. This paper presents a novel, automated concrete surface defects detection and assessment approach that addresses these issues by automatically quantifying the extent of surface deterioration. According to this approach, images of the surface shot from a certain angle/distance can be used to automatically detect the number and size of surface air pockets, and the degree of surface discoloration. The proposed method uses histogram equalization and filtering to extract such defects and identify their properties (e.g. size, shape, location). These properties are used to quantify the degree of impact on the concrete surface quality and provide a numerical tool to help inspectors accurately evaluate concrete surfaces. The method has been implemented in C++ and results that validate its performance are presented.

Automated Detection of Concrete Columns from Visual Data

After earthquakes, licensed inspectors use the established codes to assess the impact of damage on structural elements. It always takes them days to weeks. However, emergency responders (e.g. firefighters) must act within hours of a disaster event to enter damaged structures to save lives, and therefore cannot wait till an official assessment completes. This is a risk that firefighters have to take. Although Search and Rescue Organizations offer training seminars to familiarize firefighters with structural damage assessment, its effectiveness is hard to guarantee when firefighters perform life rescue and damage assessment operations together. Also, the training is not available to every firefighter. The authors therefore proposed a novel framework that can provide firefighters with a quick but crude assessment of damaged buildings through evaluating the visible damage on their critical structural elements (i.e. concrete columns in the study). This paper presents the first step of the framework. It aims to automate the detection of concrete columns from visual data. To achieve this, the typical shape of columns (long vertical lines) is recognized using edge detection and the Hough transform. The bounding rectangle for each pair of long vertical lines is then formed. When the resulting rectangle resembles a column and the material contained in the region of two long vertical lines is recognized as concrete, the region is marked as a concrete column surface. Real video/image data are used to test the method. The preliminary results indicate that concrete columns can be detected when they are not distant and have at least one surface visible.

Imaging as a technique for assessment and control in the field

C.R. Bull, R. Zwiggelaar and J.V. Stafford, 'Imaging as a technique for assessment and control in the field', Aspects of Applied Biology 43, 197-204 (1995)

Patient-based outcome assessment instruments in acupuncture research.

BACKGROUND: Outcome assessment can support the therapeutic process by providing a way to track symptoms and functionality over time, providing insights to clinicians and patients, as well as offering a common language to discuss patient behavior/functioning. OBJECTIVES: In this article, we examine the patient-based outcome assessment (PBOA) instruments that have been used to determine outcomes in acupuncture clinical research and highlight measures that are feasible, practical, economical, reliable, valid, and responsive to clinical change. The aims of this review were to assess and identify the commonly available PBOA measures, describe a framework for identifying appropriate sets of measures, and address the challenges associated with these measures and acupuncture. Instruments were evaluated in terms of feasibility, practicality, economy, reliability, validity, and responsiveness to clinical change. METHODS: This study was a systematic review. A total of 582 abstracts were reviewed using PubMed (from inception through April 2009). RESULTS: A total of 582 citations were identified. After screening of title/abstract, 212 articles were excluded. From the remaining 370 citations, 258 manuscripts identified explicit PBOA; 112 abstracts did not include any PBOA. The five most common PBOA instruments identified were the Visual Analog Scale, Symptom Diary, Numerical Pain Rating Scales, SF-36, and depression scales such as the Beck Depression Inventory. CONCLUSIONS: The way a questionnaire or scale is administered can have an effect on the outcome. Also, developing and validating outcome measures can be costly and difficult. Therefore, reviewing the literature on existing measures before creating or modifying PBOA instruments can significantly reduce the burden of developing a new measure.

Computer vision tools for the non-invasive assessment of autism-related behavioral markers

The early detection of developmental disorders is key to child outcome, allowing interventions to be initiated that promote development and improve prognosis. Research on autism spectrum disorder (ASD) suggests behavioral markers can be observed late in the first year of life. Many of these studies involved extensive frame-by-frame video observation and analysis of a child's natural behavior. Although non-intrusive, these methods are extremely time-intensive and require a high level of observer training; thus, they are impractical for clinical and large population research purposes. Diagnostic measures for ASD are available for infants but are only accurate when used by specialists experienced in early diagnosis. This work is a first milestone in a long-term multidisciplinary project that aims at helping clinicians and general practitioners accomplish this early detection/measurement task automatically. We focus on providing computer vision tools to measure and identify ASD behavioral markers based on components of the Autism Observation Scale for Infants (AOSI). In particular, we develop algorithms to measure three critical AOSI activities that assess visual attention. We augment these AOSI activities with an additional test that analyzes asymmetrical patterns in unsupported gait. The first set of algorithms involves assessing head motion by tracking facial features, while the gait analysis relies on joint foreground segmentation and 2D body pose estimation in video. We show results that provide insightful knowledge to augment the clinician's behavioral observations obtained from real in-clinic assessments.