scholarly journals Tracking animal movements using biomarkers in tail hairs: a novel approach for animal geolocating from sulfur isoscapes

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Zabibu Kabalika ◽  
Thomas A. Morrison ◽  
Rona A. R. McGill ◽  
Linus K. Munishi ◽  
Divine Ekwem ◽  
...  
Keyword(s):  
Low Cost ◽  
Additive Model ◽  
Strong Relationship ◽  
Animal Movements ◽  
Invasive Approach ◽  
Serengeti Ecosystem ◽  
Movement Data ◽  
Novel Approach ◽  
Radio Transmitters ◽  
Tail Hair

Abstract Background Current animal tracking studies are most often based on the application of external geolocators such as GPS and radio transmitters. While these technologies provide detailed movement data, they are costly to acquire and maintain, which often restricts sample sizes. Furthermore, deploying external geolocators requires physically capturing and recapturing of animals, which poses an additional welfare concern. Natural biomarkers provide an alternative, non-invasive approach for addressing a range of geolocation questions and can, because of relatively low cost, be collected from many individuals thereby broadening the scope for population-wide inference. Methods We developed a low-cost, minimally invasive method for distinguishing between local versus non-local movements of cattle using sulfur isotope ratios (δ34S) in cattle tail hair collected in the Greater Serengeti Ecosystem, Tanzania. Results We used a Generalized Additive Model to generate a predicted δ34S isoscape across the study area. This isoscape was constructed using spatial smoothers and underpinned by the positive relationship between δ34S values and lithology. We then established a strong relationship between δ34S from recent sections of cattle tail hair and the δ34S from grasses sampled in the immediate vicinity of an individual’s location, suggesting δ34S in the hair reflects the δ34S in the environment. By combining uncertainty in estimation of the isoscape, with predictions of tail hair δ34S given an animal’s position in the isoscape we estimated the anisotropic distribution of travel distances across the Serengeti ecosystem sufficient to detect movement using sulfur stable isotopes. Conclusions While the focus of our study was on cattle, this approach can be modified to understand movements in other mobile organisms where the sulfur isoscape is sufficiently heterogeneous relative to the spatial scale of animal movements and where tracking with traditional methods is difficult.

scholarly journals Predicting Malaria Transmission Dynamics in Dangassa, Mali: A Novel Approach Using Functional Generalized Additive Models

2020 ◽  
Vol 17 (17) ◽  
pp. 6339
Author(s):  
François Freddy Ateba ◽  
Manuel Febrero-Bande ◽  
Issaka Sagara ◽  
Nafomon Sogoba ◽  
Mahamoudou Touré ◽  
...  
Keyword(s):  
Wind Speed ◽  
Malaria Incidence ◽  
Generalized Additive Models ◽  
Community Health Center ◽  
Additive Model ◽  
Additive Models ◽  
Functional Regression ◽  
Novel Approach ◽  
Malaria Incidence Rate ◽  
Mean Wind Speed

Mali aims to reach the pre-elimination stage of malaria by the next decade. This study used functional regression models to predict the incidence of malaria as a function of past meteorological patterns to better prevent and to act proactively against impending malaria outbreaks. All data were collected over a five-year period (2012–2017) from 1400 persons who sought treatment at Dangassa’s community health center. Rainfall, temperature, humidity, and wind speed variables were collected. Functional Generalized Spectral Additive Model (FGSAM), Functional Generalized Linear Model (FGLM), and Functional Generalized Kernel Additive Model (FGKAM) were used to predict malaria incidence as a function of the pattern of meteorological indicators over a continuum of the 18 weeks preceding the week of interest. Their respective outcomes were compared in terms of predictive abilities. The results showed that (1) the highest malaria incidence rate occurred in the village 10 to 12 weeks after we observed a pattern of air humidity levels >65%, combined with two or more consecutive rain episodes and a mean wind speed <1.8 m/s; (2) among the three models, the FGLM obtained the best results in terms of prediction; and (3) FGSAM was shown to be a good compromise between FGLM and FGKAM in terms of flexibility and simplicity. The models showed that some meteorological conditions may provide a basis for detection of future outbreaks of malaria. The models developed in this paper are useful for implementing preventive strategies using past meteorological and past malaria incidence.

A Novel Approach for the Treatment of Sialolithiasis that Preserves Salivary Duct Anatomy

2021 ◽  
pp. 000348942110189
Author(s):  
Gani Atilla Şengör ◽  
Ahmet Mert Bilgili
Keyword(s):  
Salivary Gland ◽  
Success Rate ◽  
Cost Effective ◽  
Complete Removal ◽  
Level Of Evidence ◽  
Invasive Approach ◽  
Pneumatic Lithotripsy ◽  
Novel Approach ◽  
Surgical Methods ◽  
Salivary Gland Stones

Objective: The sialendoscopy era in the treatment of salivary gland stones has reduced the use of classical surgical methods. However, the miniature ducts and tools may cause difficulties in removing large sialoliths. Therefore, invasive combined oral surgeries or gland resection may be considered. We searched for the most suitable method in order to stay in line with the minimally invasive approach that preserves the ductus anatomy, and that can reduce the surgical fears of patients. Materials and Methods: The study included 84 cases (23 parotid and 61 submandibular) in whom stones were fragmented by pneumatic lithotripsy and removed between January 2015 and January 2020. The parotid cases comprised 7 females and 16 males, and the submandibular cases comprised 25 females and 36 males. Intraductal lithotripsy was performed using pneumatic lithotripter. This study has fourth level of evidence. Results: Based on total number of cases (n = 84), success rate was 67/84 (79.7%) immediately after sialendoscopy, and overall success rate was 77/84 (91.6%). Based on number of stones treated (n = 111), our immediate success rate was 94/111 (84.6%), and overall success rate was 104/111 (93.7%). The success criteria were complete removal of the stone and fragments in a single sialendoscopy procedure and resolution of symptoms. Conclusions: We successfully treated salivary gland stones, including L3b stones, in our patient cohort with sialendoscopy combined with pneumatic lithotripsy. The lithotripsy method that we have adapted seems to be more useful and cost-effective compared to its alternatives. We were also able to preserve the ductus anatomy and relieve patients’ concerns. Level of Evidence: Level IV

scholarly journals Improved Mutual Understanding for Human-Robot Collaboration: Combining Human-Aware Motion Planning with Haptic Feedback Devices for Communicating Planned Trajectory

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3673
Author(s):  
Stefan Grushko ◽  
Aleš Vysocký ◽  
Petr Oščádal ◽  
Michal Vocetka ◽  
Petr Novák ◽  
...  
Keyword(s):  
User Study ◽  
Haptic Feedback ◽  
Fundamental Aspect ◽  
Task Completion ◽  
Good Efficiency ◽  
Notification System ◽  
Movement Data ◽  
Novel Approach ◽  
Machine Interface ◽  
High Degree

In a collaborative scenario, the communication between humans and robots is a fundamental aspect to achieve good efficiency and ergonomics in the task execution. A lot of research has been made related to enabling a robot system to understand and predict human behaviour, allowing the robot to adapt its motion to avoid collisions with human workers. Assuming the production task has a high degree of variability, the robot’s movements can be difficult to predict, leading to a feeling of anxiety in the worker when the robot changes its trajectory and approaches since the worker has no information about the planned movement of the robot. Additionally, without information about the robot’s movement, the human worker cannot effectively plan own activity without forcing the robot to constantly replan its movement. We propose a novel approach to communicating the robot’s intentions to a human worker. The improvement to the collaboration is presented by introducing haptic feedback devices, whose task is to notify the human worker about the currently planned robot’s trajectory and changes in its status. In order to verify the effectiveness of the developed human-machine interface in the conditions of a shared collaborative workspace, a user study was designed and conducted among 16 participants, whose objective was to accurately recognise the goal position of the robot during its movement. Data collected during the experiment included both objective and subjective parameters. Statistically significant results of the experiment indicated that all the participants could improve their task completion time by over 45% and generally were more subjectively satisfied when completing the task with equipped haptic feedback devices. The results also suggest the usefulness of the developed notification system since it improved users’ awareness about the motion plan of the robot.

scholarly journals Novel approach to enhance coastal habitat and biotope mapping with drone aerial imagery analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
João Gama Monteiro ◽  
Jesús L. Jiménez ◽  
Francesca Gizzi ◽  
Petr Přikryl ◽  
Jonathan S. Lefcheck ◽  
...  
Keyword(s):  
Anthropogenic Impacts ◽  
Spatial Scales ◽  
Low Cost ◽  
Human Populations ◽  
Coastal Habitat ◽  
Coastal Monitoring ◽  
Monitoring Programs ◽  
Novel Approach ◽  
Aerial Platforms ◽  
Rocky Habitats

AbstractUnderstanding the complex factors and mechanisms driving the functioning of coastal ecosystems is vital towards assessing how organisms, ecosystems, and ultimately human populations will cope with the ecological consequences of natural and anthropogenic impacts. Towards this goal, coastal monitoring programs and studies must deliver information on a range of variables and factors, from taxonomic/functional diversity and spatial distribution of habitats, to anthropogenic stress indicators such as land use, fisheries use, and pollution. Effective monitoring programs must therefore integrate observations from different sources and spatial scales to provide a comprehensive view to managers. Here we explore integrating aerial surveys from a low-cost Remotely Piloted Aircraft System (RPAS) with concurrent underwater surveys to deliver a novel approach to coastal monitoring. We: (i) map depth and substrate of shallow rocky habitats, and; (ii) classify the major biotopes associated with these environmental axes; and (iii) combine data from i and ii to assess the likely distribution of common sessile organismal assemblages over the survey area. Finally, we propose a general workflow that can be adapted to different needs and aerial platforms, which can be used as blueprints for further integration of remote-sensing with in situ surveys to produce spatially-explicit biotope maps.

A Novel Approach With Bayesian Networks to Multi-Robot Task Allocation in Dynamic Environments

2021 ◽  
Author(s):  
Ching-Wei Chuang ◽  
Harry H. Cheng
Keyword(s):  
Bayesian Networks ◽  
Task Allocation ◽  
Low Cost ◽  
Dynamic Environments ◽  
Modern World ◽  
Robot System ◽  
Novel Approach ◽  
Robot Systems ◽  
Robot Task ◽  
Multi Robot

Abstract In the modern world, building an autonomous multi-robot system is essential to coordinate and control robots to help humans because using several low-cost robots becomes more robust and efficient than using one expensive, powerful robot to execute tasks to achieve the overall goal of a mission. One research area, multi-robot task allocation (MRTA), becomes substantial in a multi-robot system. Assigning suitable tasks to suitable robots is crucial in coordination, which may directly influence the result of a mission. In the past few decades, although numerous researchers have addressed various algorithms or approaches to solve MRTA problems in different multi-robot systems, it is still difficult to overcome certain challenges, such as dynamic environments, changeable task information, miscellaneous robot abilities, the dynamic condition of a robot, or uncertainties from sensors or actuators. In this paper, we propose a novel approach to handle MRTA problems with Bayesian Networks (BNs) under these challenging circumstances. Our experiments exhibit that the proposed approach may effectively solve real problems in a search-and-rescue mission in centralized, decentralized, and distributed multi-robot systems with real, low-cost robots in dynamic environments. In the future, we will demonstrate that our approach is trainable and can be utilized in a large-scale, complicated environment. Researchers might be able to apply our approach to other applications to explore its extensibility.

LED Light Sources in Organic Synthesis: An Entry to A Novel Approach

2021 ◽  
Vol 18 ◽  
Author(s):  
Aparna Das
Keyword(s):  
Organic Compounds ◽  
Organic Synthesis ◽  
Photochemical Reaction ◽  
Low Cost ◽  
Environmentally Friendly ◽  
Photochemical Reactions ◽  
Light Sources ◽  
Blue Led ◽  
Oxidation Reduction ◽  
Novel Approach

: In recent years, photocatalytic technology has shown great potential as a low-cost, environmentally friendly, and sustainable technology. Compared to other light sources in photochemical reaction, LEDs have advantages in terms of efficiency, power, compatibility, and environmentally-friendly nature. This review highlights the most recent advances in LED-induced photochemical reactions. The effect of white and blue LEDs in reactions such as oxidation, reduction, cycloaddition, isomerization, and sensitization is discussed in detail. No other reviews have been published on the importance of white and blue LED sources in the photocatalysis of organic compounds. Considering all the facts, this review is highly significant and timely.

Tissue Engineered Successful Reconstruction of a Complex Traumatized Lower Extremity

2021 ◽  
Vol 11 (9) ◽  
Author(s):  
Srinjoy Saha
Keyword(s):  
Minimally Invasive ◽  
Soft Tissues ◽  
Platelet Rich Plasma ◽  
Thigh Muscle ◽  
Muscle Injuries ◽  
Invasive Approach ◽  
Novel Approach ◽  
Duration Of Surgery ◽  
Biomaterial Application ◽  
Split Skin

Introduction: Tissue engineered reconstruction is a minimally invasive approach for healing major complex wounds successfully. It combines accurate, conservative debridement with a specially adapted suction method, platelet-rich plasma (PRP) injections, and biomaterial application to salvage injured tissues and grows new soft tissues over wounds. Case Report: A healthy young man in his early 30s presented to our emergency department with complex knee-thigh injuries following a high-velocity automobile accident. Degloved anterolateral thigh, severe thigh muscle injuries, and ruptured extensor patellar mechanism were observed. Accurate conservative (as opposed to radical) debridement and PRP injections salvaged the injured muscles and tendons. Specially carved reticulated foam wrapped around the injured ischemic muscles, followed by low negative, short intermittent, cyclical suction therapy. Wound exploration 4 days apart revealed progressive improvements with considerable vascularization of the injured soft tissues within 2 weeks. Thereafter, meticulous reconstruction of the salvaged muscles and tendons restored anatomical congruity. An absorbable synthetic biomaterial covered the sizeable open wound with vast areas of exposed tendons. Five weeks later, exuberant granulating tissue ingrowth within the biomaterial filled up the tissue defect. A split-skin graft covered the remaining raw areas, which “took” completely. Early rehabilitation enabled the patient to return to active work, play contact sports, and perform strenuous activities effortlessly. Conclusion: Minimally invasive tissue engineered reconstruction is a novel approach using a series of simple minimally invasive procedures. It lessens the duration of surgery and anesthesia, maximizes soft-tissue salvage, lowers morbidity, minimizes hospitalization, saves costs, and improves the patient’s quality of life significantly. Keywords: Mangled extremity, Limb salvage, Financial, Trauma, Modified negative pres

scholarly journals RFID-Based Human Behavior Modeling and Anomaly Detection for Elderly Care

2010 ◽  
Vol 6 (4) ◽  
pp. 341-354 ◽  
Author(s):  
Hui-Huang Hsu ◽  
Chien-Chen Chen
Keyword(s):  
Anomaly Detection ◽  
Intelligent System ◽  
Elderly Care ◽  
The Elderly ◽  
Behavior Modeling ◽  
Abnormal Behavior ◽  
Daily Movement ◽  
Movement Data ◽  
Novel Approach ◽  
At Home

This research aimed at building an intelligent system that can detect abnormal behavior for the elderly at home. Active RFID tags can be deployed at home to help collect daily movement data of the elderly who carries an RFID reader. When the reader detects the signals from the tags, RSSI values that represent signal strength are obtained. The RSSI values are reversely related to the distance between the tags and the reader and they are recorded following the movement of the user. The movement patterns, not the exact locations, of the user are the major concern. With the movement data (RSSI values), the clustering technique is then used to build a personalized model of normal behavior. After the model is built, any incoming datum outside the model can be viewed as abnormal and an alarm can be raised by the system. In this paper, we present the system architecture for RFID data collection and preprocessing, clustering for anomaly detection, and experimental results. The results show that this novel approach is promising.

scholarly journals DISMIR: a deep learning-based cancer-detection method by integrating DNA sequence and methylation information of individual cell-free DNA reads

2021 ◽  
Author(s):  
Jiaqi Li ◽  
Lei Wei ◽  
Xianglin Zhang ◽  
Wei Zhang ◽  
Haochen Wang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Dna Sequence ◽  
Cancer Detection ◽  
High Throughput Sequencing ◽  
Detection Method ◽  
Low Cost ◽  
Sequencing Data ◽  
Cell Free Dna ◽  
Free Dna ◽  
Novel Approach

ABSTRACTDetecting cancer signals in cell-free DNA (cfDNA) high-throughput sequencing data is emerging as a novel non-invasive cancer detection method. Due to the high cost of sequencing, it is crucial to make robust and precise prediction with low-depth cfDNA sequencing data. Here we propose a novel approach named DISMIR, which can provide ultrasensitive and robust cancer detection by integrating DNA sequence and methylation information in plasma cfDNA whole genome bisulfite sequencing (WGBS) data. DISMIR introduces a new feature termed as “switching region” to define cancer-specific differentially methylated regions, which can enrich the cancer-related signal at read-resolution. DISMIR applies a deep learning model to predict the source of every single read based on its DNA sequence and methylation state, and then predicts the risk that the plasma donor is suffering from cancer. DISMIR exhibited high accuracy and robustness on hepatocellular carcinoma detection by plasma cfDNA WGBS data even at ultra-low sequencing depths. Analysis showed that DISMIR tends to be insensitive to alterations of single CpG sites’ methylation states, which suggests DISMIR could resist to technical noise of WGBS. All these results showed DISMIR with the potential to be a precise and robust method for low-cost early cancer detection.

scholarly journals CLOUDTHINK: A SCALABLE SECURE PLATFORM FOR MIRRORING TRANSPORTATION SYSTEMS IN THE CLOUD

Transport ◽  
2015 ◽  
Vol 30 (3) ◽  
pp. 320-329 ◽  
Author(s):  
Erik Wilhelm ◽  
Joshua Siegel ◽  
Simon Mayer ◽  
Leyna Sadamori ◽  
Sohan Dsouza ◽  
...  
Keyword(s):  
Web Application ◽  
Low Cost ◽  
Application Programming Interface ◽  
Fair Value ◽  
Transportation Systems ◽  
Third Party ◽  
Barriers To Entry ◽  
Moving Vehicle ◽  
Novel Approach ◽  
Vehicle Information

We present a novel approach to developing a vehicle communication platform consisting of a low-cost, open-source hardware for moving vehicle data to a secure server, a Web Application Programming Interface (API) for the provision of third-party services, and an intuitive user dashboard for access control and service distribution. The CloudThink infrastructure promotes the commoditization of vehicle telematics data by facilitating easier, flexible, and more secure access. It enables drivers to confidently share their vehicle information across multiple applications to improve the transportation experience for all stakeholders, as well as to potentially monetize their data. The foundations for an application ecosystem have been developed which, taken together with the fair value for driving data and low barriers to entry, will drive adoption of CloudThink as the standard method for projecting physical vehicles into the cloud. The application space initially consists of a few fundamental and important applications (vehicle tethering and remote diagnostics, road-safety monitoring, and fuel economy analysis) but as CloudThink begins to gain widespread adoption, the multiplexing of applications on the same data structure and set will accelerate its adoption.

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