Strokes2Surface: Recovering Curve Networks From 4D Architectural Design Sketches

We present Strokes2Surface, an offline geometry reconstruction pipeline that recovers well-connected curve networks from imprecise 4D sketches to bridge concept design and digital modeling stages in architectural design. The input to our pipeline consists of 3D strokes' polyline vertices and their timestamps as the 4th dimension, along with additional metadata recorded throughout sketching. Inspired by architectural sketching practices, our pipeline combines a classifier and two clustering models to achieve its goal. First, with a set of extracted hand-engineered features from the sketch, the classifier recognizes the type of individual strokes between those depicting boundaries (Shape strokes) and those depicting enclosed areas (Scribble strokes). Next, the two clustering models parse strokes of each type into distinct groups, each representing an individual edge or face of the intended architectural object. Curve networks are then formed through topology recovery of consolidated Shape clusters and surfaced using Scribble clusters guiding the cycle discovery. Our evaluation is threefold: We confirm the usability of the Strokes2Surface pipeline in architectural design use cases via a user study, we validate our choice of features via statistical analysis and ablation studies on our collected dataset, and we compare our outputs against a range of reconstructions computed using alternative methods.Comment: 15 pages, 14 figure

Estimating the furrow infiltration characteristic from a single advance point

Management and control of surface irrigation, in particular furrow irrigation, is limited by spatio-temporal soil infiltration variability as well as the high cost and time associated with collecting intensive field data for estimation of the infiltration characteristics. Recent work has proposed scaling the commonly used infiltration function by using a model infiltration curve and a single advance point for every other furrow in an irrigation event. Scaling factors were calculated for a series of furrows at two sites and at four points down the length of the field (0.25 L, 0.5 L, 0.75 L and L). Differences in the value of the scaling factor with distance were found to be a function of the shape of the advance curves. It is concluded that use of points early in the advance results in a substantial loss of accuracy and should be avoided. The scaling factor was also strongly correlated with the furrow-wetted perimeter suggesting that the scaling is an appropriate way of both predicting and accommodating the effect of the hydraulic variability

Placental kisspeptins differentially modulate vital parameters of estrogen receptor-positive and-negative breast cancer cells

Kisspeptins (KPs) are major regulators of trophoblast and cancer invasion. Thus far, limited and conflicting data are available on KP-mediated modulation of breast cancer (BC) metastasis; mostly based on synthetic KP-10, the most active fragment of KP. Here, we report for the first time comprehensive functional effects of term placental KPs on proliferation, adhesion, Matrigel invasion, motility, MMP activity and pro-inflammatory cytokine production in MDA-MB-231 (estrogen receptor-negative) and MCF-7 (estrogen receptor-positive). KPs were expressed at high level by term placental syncytiotrophoblasts and released in soluble form. Placental explant conditioned medium containing KPs (CM) significantly reduced proliferation of both cell types compared to CM without (w/o) KP (CM-w/o KP) in a dose-and time-dependent manner. In MDA-MB-231 cells, placental KPs significantly reduced adhesive properties, while increased MMP9 and MMP2 activity and stimulated invasion. Increased invasiveness of MDA-MB-231 cells after CM treatment was inhibited by KP receptor antagonist, P-234. CM significantly reduced motility of MCF-7 cells at all time points (2-30 hr), while it stimulated motility of MDA-MB-231 cells. These effects were reversed by P-234. Co-treatment with selective ER modulators, Tamoxifen and Raloxifene, inhibited the effect of CM on motility of MCF-7 cells. The level of IL-6 in supernatant of MCF-7 cells treated with CM was higher compared to those treated with CM-w/o KP. Both cell types produced more IL-8 after treatment with CM compared to those treated with CM-w/o KP. Taken together, our observations suggest that placental KPs differentially modulate vital parameters of estrogen receptor-positive and-negative BC cells possibly through modulation of pro-inflammatory cytokine production. © 2016 Rasoulzadeh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Implementation outcome instruments for use in physical healthcare settings: a systematic review

BACKGROUND: Implementation research aims to facilitate the timely and routine implementation and sustainment of evidence-based interventions and services. A glaring gap in this endeavour is the capability of researchers, healthcare practitioners and managers to quantitatively evaluate implementation efforts using psychometrically sound instruments. To encourage and support the use of precise and accurate implementation outcome measures, this systematic review aimed to identify and appraise studies that assess the measurement properties of quantitative implementation outcome instruments used in physical healthcare settings. METHOD: The following data sources were searched from inception to March 2019, with no language restrictions: MEDLINE, EMBASE, PsycINFO, HMIC, CINAHL and the Cochrane library. Studies that evaluated the measurement properties of implementation outcome instruments in physical healthcare settings were eligible for inclusion. Proctor et al.'s taxonomy of implementation outcomes was used to guide the inclusion of implementation outcomes: acceptability, appropriateness, feasibility, adoption, penetration, implementation cost and sustainability. Methodological quality of the included studies was assessed using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist. Psychometric quality of the included instruments was assessed using the Contemporary Psychometrics checklist (ConPsy). Usability was determined by number of items per instrument. RESULTS: Fifty-eight publications reporting on the measurement properties of 55 implementation outcome instruments (65 scales) were identified. The majority of instruments assessed acceptability (n = 33), followed by appropriateness (n = 7), adoption (n = 4), feasibility (n = 4), penetration (n = 4) and sustainability (n = 3) of evidence-based practice. The methodological quality of individual scales was low, with few studies rated as 'excellent' for reliability (6/62) and validity (7/63), and both studies that assessed responsiveness rated as 'poor' (2/2). The psychometric quality of the scales was also low, with 12/65 scales scoring 7 or more out of 22, indicating greater psychometric strength. Six scales (6/65) rated as 'excellent' for usability. CONCLUSION: Investigators assessing implementation outcomes quantitatively should select instruments based on their methodological and psychometric quality to promote consistent and comparable implementation evaluations. Rather than developing ad hoc instruments, we encourage further psychometric testing of instruments with promising methodological and psychometric evidence. SYSTEMATIC REVIEW REGISTRATION: PROSPERO 2017 CRD42017065348

The Effectiveness of Education on Prevention of Osteoporosis among High School Female Students

Background & Aim: Osteoporosis is a silent and preventable disease that mostly affects women. Osteoporosis prevention requires enhancing knowledge and awareness of students. The purpose of this study was to assess the effectiveness of education on prevention of osteoporosis among high school female students in the sixth distinct of Tehran. Methods & Materials: In this randomized controlled trial, 600 students were selected using cluster sampling method. Data were gathered using a three-part questionnaire including demographic, knowledge, and practice items. After the baseline measurement, the students were randomly allocated into intervention and control groups. Two educational sessions were held for the intervention group. At the end of the sessions, educational booklets were distributed among the students. The educational strategies included giving lectures, and practicing physical exercises. After two weeks, the participants completed the questionnaires again. The educational classes were held for the control group after the last measurements. Results: Data analysis showed that the mean of knowledge score and the participants' practice were significantly different between two groups after the intervention (P<0.001). Conclusion: Regarding the effect of education on enhancing students' awareness and practice about osteoporosis prevention, designing educational programs could be beneficial.   Key words: education, osteoporosis, preventio

A comparative stationarity analysis of EEG signals

While developing models of brain functioning by using time series data, the stationary interval of the time series should be used to model the corresponding state of the brain. Here it is assumed that at the borders of stationarity, brain changes its state where a state is considered as a group of brain regions working together. If the whole nonstationary time series is used, many different brain states could be included in one model. However, it is very hard to decide the stationary intervals for such a complicated system as brain. There are some methods, which have proved their performances based on manually constructed synthetic data, in the literature. Only very few results with EEG data have been presented. But, there is usually no ground truth accompanying the data to make an evaluation. In this study, suitable approaches for stationary analysis were applied on visual evoked potentials (VEP) where we can approximately know the possible stationary intervals due to the properties of the experiment during which the data was recorded. Experts designed the experiment and marked the possible borders of the intervals carefully. Parameters of the methods were set automatically. We compared the manually marked intervals with the intervals detected automatically by the applied methods and evaluated the methods in terms of their performances of estimating the stationary intervals of EEG signals