Octopus-Inspired Suction Cups with Embedded Strain Sensors for Object Recognition

The octopus has unique capacities are sources of inspiration in developing soft robotic-enabling technologies. Herein, soft, sensorized, suction cups inspired by the suckers of Octopus vulgaris are presented. The suction cups using direct casting are fabricated, so that materials with different mechanical properties can be combined to optimize sensing and grasping capabilities. The artificial suckers integrate four embedded strain sensors, individually characterized and placed in a 90 degrees configuration along the rim of the suction cup. Based on this arrangement, how well the sensory suction cup can detect 1) the direction and 2) the angle (from 30 degrees to 90 degrees) of a touched inclined surface and 3) the stiffness of a touched flat object (shore hardness between 0010 and D50) both in air and underwater is evaluated. Data processing on neural networks is based using a multilayer perceptron to perform regression on individual properties. The results show a mean absolute error of 0.98 for angles, 0.02 for directions, and 97.9% and 93.5% of accuracy for the material classification in air and underwater, respectively. In view of the results and scalability in manufacturing, the proposed artificial suckers would seem to be highly effective solutions for soft robotics, including blind exploration and object recognition

Using TurbSim stochastic simulator to improve accuracy of computational modelling of wind in the built environment

Small wind turbines are often sited in more complex environments than in open terrain. These sites include locations near buildings, trees and other obstacles, and in such situations, the wind is normally highly three-dimensional, turbulent, unstable and weak. There is a need to understand the turbulent flow conditions for a small wind turbine in the built environment. This knowledge is crucial for input into the design process of a small wind turbine to accurately predict blade fatigue loads and lifetime and to ensure that it operates safely with a performance that is optimized for the environment. Computational fluid dynamics is a useful method to provide predictions of local wind flow patterns and to investigate turbulent flow conditions at small wind turbine sites, in a manner that requires less time and investment than actual measurements. This article presents the results of combining a computational fluid dynamics package (ANSYS CFX software) with a stochastic simulator (TurbSim) as an approach to investigate the turbulent flow conditions on the rooftop of a building where small wind turbines are sited. The findings of this article suggest that the combination of a computational fluid dynamics package with the TurbSim stochastic simulator is a promising tool to assess turbulent flow conditions for small wind turbines on the roof of buildings. In particular, in the prevailing wind direction, the results show a significant gain in accuracy in using TurbSim to generate wind speed and turbulence kinetic energy profiles for the inlet of the computational fluid dynamics domain rather than using a logarithmic wind-speed profile and a pre-set value of turbulence intensity in the computational fluid dynamics code. The results also show that small wind turbine installers should erect turbines in the middle of the roof of the building and avoid the edges of the roof as well as areas on the roof close to the windward and leeward walls of the building in the prevailing wind direction

Do Patients with Penetrating Abdominal Stab Wounds Require Laparotomy?

Background: The optimal management of hemodynamically stable asymptomatic patients with anterior abdominal stab wounds (AASWs) remains controversial. The goal is to identify and treat injuries in a safe cost-effective manner. Common evaluation strategies are local wound exploration (LWE), diagnostic peritoneal lavage (DPL), serial clinical assessment (SCAs) and computed tomography (CT) imaging. Making a decision about the right time to operate on a patient with a penetrating abdominal stab wound, especially those who have visceral evisceration, is a continuing challenge. Objectives: Until the year 2010, our strategy was emergency laparotomy in patients with penetrating anterior fascia and those with visceral evisceration. This survey was conducted towards evaluating the results of emergency laparotomy. So, better management can be done in patients with penetrating abdominal stab wounds. Patients and Methods: This retrospective cross-sectional study was performed on patients with abdominal penetrating trauma who referred to Al- Zahra hospital in Isfahan, Iran from October 2000 to October 2010. It should be noted that patients with abdominal blunt trauma, patients under 14 years old, those with lateral abdomen penetrating trauma and patients who had unstable hemodynamic status were excluded from the study. Medical records of patients were reviewed and demographic and clinical data were collected for all patients including: age, sex, mechanism of trauma and the results of LWE and laparotomy. Data were analyzed with PASW v.20 software. All data were expressed as mean ± SD. The distribution of nominal variables was compared using the Chi-squared test. Also diagnostic index for LWE were calculated. A two-sided P value less than 0.05 was considered to be statistically significant. Results: During the 10 year period of the study, 1100 consecutive patients with stab wounds were admitted to Al-Zahra hospital Isfahan, Iran. In total, about 150 cases had penetrating traumas in the anterior abdomen area. Sixty-three (42%) patients were operated immediately due to shock, visceral evisceration or aspiration of blood via a nasogastric tube on admission. Organ injury was seen in 78% of patients with visceral evisceration. Among these 87 cases, 29 patients’ (33.3%) anterior fascia was not penetrated in LWE. So, they were observed for several hours and discharged from the hospital without surgery. While for the remaining 58 patients (66.6%), whose LWE detected penetration of anterior abdominal fascia, laparotomy was performed which showed visceral injuries in 11 (18%) cases. Conclusions: All in all, 82 percent of laparotomies in patients with penetrated anterior abdominal fascia without visceral evisceration, who had no signs of peritoneal irritation, were negative. So, we recommended further evaluation in these patients. However, visceral evisceration is an indication for exploratory laparotomy, since in our study; the majority of patients had organ damages

Formation of chlorobenzenes by oxidative thermal decomposition of 1,3-dichloropropene

We combine combustion experiments and density functional theory (DFT) calculations to investigate the formation of chlorobenzenes from oxidative thermal decomposition of 1,3-dichloropropene. Mono- to hexa-chlorobenzenes are observed between 800 and 1150. K, and the extent of chlorination was proportional to the combustion temperature. Higher chlorinated congeners of chlorobenzene (tetra-, penta-, hexa-chlorobenzene) are only observed in trace amounts between 950 and 1050. K. DFT calculations indicate that cyclisation of chlorinated hexatrienes proceeds via open-shell radical pathways. These species represent key components in the formation mechanism of chlorinated polyaromatic hydrocarbons. Results presented herein should provide better understanding of the evolution of soot from combustion/pyrolysis of short chlorinated alkenes

Novel Hybrid Integration Approach of Bagging-Based Fisher’s Linear Discriminant Function for Groundwater Potential Analysis

© 2019, International Association for Mathematical Geosciences. Groundwater is a vital water source in the rural and urban areas of developing and developed nations. In this study, a novel hybrid integration approach of Fisher’s linear discriminant function (FLDA) with rotation forest (RFLDA) and bagging (BFLDA) ensembles was used for groundwater potential assessment at the Ningtiaota area in Shaanxi, China. A spatial database with 66 groundwater spring locations and 14 groundwater spring contributing factors was prepared; these factors were elevation, aspect, slope, plan and profile curvatures, sediment transport index, stream power index, topographic wetness index, distance to roads and streams, land use, lithology, soil and normalized difference vegetation index. The classifier attribute evaluation method based on the FLDA model was implemented to test the predictive competence of the mentioned contributing factors. The area under curve, confidence interval at 95%, standard error, Friedman test and Wilcoxon signed-rank test were used to compare and validate the success and prediction competence of the three applied models. According to the achieved results, the BFLDA model showed the most prediction competence, followed by the RFLDA and FLDA models, respectively. The resulting groundwater spring potential maps can be used for groundwater development plans and land use planning

Multi-criteria decision making (MCDM) model for seismic vulnerability assessment (SVA) of urban residential buildings

© 2018 by the authors. Earthquakes are among the most catastrophic natural geo-hazards worldwide and endanger numerous lives annually. Therefore, it is vital to evaluate seismic vulnerability beforehand to decrease future fatalities. The aim of this research is to assess the seismic vulnerability of residential houses in an urban region on the basis of the Multi-Criteria Decision Making (MCDM) model, including the analytic hierarchy process (AHP) and geographical information system (GIS). Tabriz city located adjacent to the North Tabriz Fault (NTF) in North-West Iran was selected as a case study. The NTF is one of the major seismogenic faults in the north-western part of Iran. First, several parameters such as distance to fault, percent of slope, and geology layers were used to develop a geotechnical map. In addition, the structural construction materials, building materials, size of building blocks, quality of buildings and buildings-floors were used as key factors impacting on the building’s structural vulnerability in residential areas. Subsequently, the AHP technique was adopted to measure the priority ranking, criteria weight (layers), and alternatives (classes) of every criterion through pair-wise comparison at all levels. Lastly, the layers of geotechnical and spatial structures were superimposed to design the seismic vulnerability map of buildings in the residential area of Tabriz city. The results showed that South and Southeast areas of Tabriz city exhibit low to moderate vulnerability, while some regions of the north-eastern area are under severe vulnerability conditions. In conclusion, the suggested approach offers a practical and effective evaluation of Seismic Vulnerability Assessment (SVA) and provides valuable information that could assist urban planners during mitigation and preparatory phases of less examined areas in many other regions around the world

Land subsidence susceptibility mapping in South Korea using machine learning algorithms

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. In this study, land subsidence susceptibility was assessed for a study area in South Korea by using four machine learning models including Bayesian Logistic Regression (BLR), Support Vector Machine (SVM), Logistic Model Tree (LMT) and Alternate Decision Tree (ADTree). Eight conditioning factors were distinguished as the most important affecting factors on land subsidence of Jeong-am area, including slope angle, distance to drift, drift density, geology, distance to lineament, lineament density, land use and rock-mass rating (RMR) were applied to modelling. About 24 previously occurred land subsidence were surveyed and used as training dataset (70% of data) and validation dataset (30% of data) in the modelling process. Each studied model generated a land subsidence susceptibility map (LSSM). The maps were verified using several appropriate tools including statistical indices, the area under the receiver operating characteristic (AUROC) and success rate (SR) and prediction rate (PR) curves. The results of this study indicated that the BLR model produced LSSM with higher acceptable accuracy and reliability compared to the other applied models, even though the other models also had reasonable results

SWPT: An automated GIS-based tool for prioritization of sub-watersheds based on morphometric and topo-hydrological factors

© 2019 China University of Geosciences (Beijing) and Peking University The sub-watershed prioritization is the ranking of different areas of a river basin according to their need to proper planning and management of soil and water resources. Decision makers should optimally allocate the investments to critical sub-watersheds in an economically effective and technically efficient manner. Hence, this study aimed at developing a user-friendly geographic information system (GIS) tool, Sub-Watershed Prioritization Tool (SWPT), using the Python programming language to decrease any possible uncertainty. It used geospatial–statistical techniques for analyzing morphometric and topo-hydrological factors and automatically identifying critical and priority sub-watersheds. In order to assess the capability and reliability of the SWPT tool, it was successfully applied in a watershed in the Golestan Province, Northern Iran. Historical records of flood and landslide events indicated that the SWPT correctly recognized critical sub-watersheds. It provided a cost-effective approach for prioritization of sub-watersheds. Therefore, the SWPT is practically applicable and replicable to other regions where gauge data is not available for each sub-watershed