Natural calamities are affecting many parts of the world. Natural disasters, terrorist attacks, earthquakes, wildfires, floods and all unpredicted phenomena. Disasters cause emergency conditions, so imperative to coordinate the prompt delivery of essential services to the sufferers. Often, disasters lead many people to perish by becoming trapped inside, but many more also perish as a result of individuals receiving rescue either too late or not at all. The implementation and design of a Receiver module utilizing Davinci code processor DVM6437, Wireless camera receiver, Zigbee Transceiver and Global Positioning System (GPS) is proposed in this manuscript for Wireless Vision-based Semi-Autonomous rescue robots that are employed in rough terrain. The receiver side’s Zigbee transceiver module eliminates the limitations of tele-operating rescue robots by enabling the control station to receive GPS data signals and aids in robot management by sending control signals wirelessly. Half and full-duplex communication are supported by the Davinci processor DVM6437, a digital media fixed-point DSP processor that relies on Very Long Instruction Words. It includes an extensive instruction set that is ideal for real-time salvage operations. DVM processor is coded utilizing MATLAB Simulink. MATLAB codes and Simulink blocks are employed under Embedded IDE link.

We present an initial analysis of Radio Frequency Interference (RFI) flagging statistics from archived Australian SKA Pathfinder (ASKAP) observations for the ‘Survey and Monitoring of ASKAP’s RFI environment and Trends’ (SMART) project. SMART is a two-part observatoryled project combining analysis of archived observations with a dedicated, comprehensive RFI survey. The survey component covers ASKAP’s full 700–1 800 MHz frequency range, including bands not typically used due to severe RFI. Observations are underway to capture a detailed snapshot of the ASKAP RFI environment over representative 24 h periods. In addition to this dedicated survey, we routinely archive and analyse flagging statistics for all scientific observations to monitor the observatory’s RFI environment in near real-time. We use the telescope itself as a very sensitive RFI monitor and directly assess the fraction of scientific observations impacted by RFI. To this end, flag tables are now automatically ingested and aggregated as part of routine ASKAP operations for all science observations, as a function of frequency and time. The data presented in this paper come from processing all archived data for several ASKAP Survey Science Projects (SSPs). We found that the average amount of flagging due to RFI across the routinely used ‘clean’ continuum science bands is 3%. The ‘clean’ mid band from 1 293 to 1 437 MHz (excluding the 144 MHz below 1293 MHz impacted by radionavigation-satellites which is discarded before processing) is the least affected by RFI, followed by the ‘clean’ low band from 742 to 1 085 MHz. ASKAP SSPs lose most of their data to the mobile service in the low band, aeronautical service in the mid band and satellite navigation service in the 1 510–1 797 MHz high band. We also show that for some of these services, the percentage of discarded data has been increasing year-on-year. SMART provides a unique opportunity to study ASKAP’s changing RFI environment, including understanding and updating the default flagging behaviour, inferring the suitability of and calibrating RFI monitoring equipment, monitoring spectrum management compliance in the Australian Radio Quiet Zone – Western Australia (ARQZWA), and informing the implementation of a suite of RFI mitigation techniques.

Anaemia remains among the most prevalent nutritional problems among children in developing countries. In Ethiopia, more than half of children <5 years of age are anaemic. In the early stages of life, it leads to poor cognitive performance, delay psychomotor development and decreases working capacity in later life. The present study aimed to assess the prevalence and associated factors of anaemia among children aged 6–23 months in the Bale zone. A community-based cross-sectional study was conducted from 1 to 30 June 2021. Multistage stratified sampling and simple random sampling techniques were employed to select 770 samples. An interviewer-administered questionnaire was used to collect data on socio-demographic, child health and feeding practices. Haemoglobin levels were estimated using a portable Hemosmart machine. Children with haemoglobin values below 11 g/dl were considered anaemic. Binary logistic regression analysis was performed to identify factors associated with anaemia. Statistical significance was set at P < 0⋅05. The prevalence of anaemia was 47⋅9 % (95 % CI (44⋅4, 51⋅5)). The multivariate analysis showed that child age (6–11 months) (AOR 1⋅47; 95 % CI (1⋅06, 2⋅03)), household food insecurity (AOR 1⋅44; 95 % CI (1⋅01, 2⋅04)), having diarrhoea and cough in the past 2 weeks (AOR 1⋅70; 95 % CI (1⋅18, 2⋅44)) and (AOR 1⋅97; 95 % CI (1⋅28, 3⋅04), respectively), not consuming the recommended dietary diversity (AOR 2⋅72; 95 % CI (1⋅96, 3⋅77)) and stunting (AOR 1⋅88; 95 % CI (1⋅31, 2⋅70)) were significantly associated with anaemia. Anaemia in children aged 6–23 months was a severe public health problem in the study area. Integrated nutritional interventions combined with iron fortification and supplementation is recommended.

Integrated navigation systems made up of a strap-down inertial navigation system (SINS) and global positioning system (GPS) are increasingly being used to improve the position, speed, and attitude information of unmanned surface vessels (USV). However, a GPS outage could occur due to the dependence of GPS performance on the external environment and the number of available satellites. This study uses an innovative combination of Dempster–Shafer (DS) theory and broad learning (BL) method to design a SINS/GPS integrated navigation system. First, the velocity and position information derived from the SINS and their corresponding GPS were fused using DS fusion rules, while the SINS error was modelled using the BL method. A ‘virtual’ GPS was then designed using the proposed DS–BL approach to provide the speed and position information when the GPS signal was interrupted, thereby ensuring the continuous navigation of the USV. The results of both simulation and sea trial demonstrate that the proposed virtual GPS estimation approach is effective, and the navigational accuracy of the proposed method is superior to other methods.

Sierra Leone is one of the least developed low-income countries (LICs), slowly recovering from the effects of a devastating civil war and an Ebola outbreak. The health care system is characterized by chronic shortage of skilled human resources, equipment, and essential medicines. The referral system is weak and vulnerable, with 75% of the country having insufficient access to essential health care. Consequently, Sierra Leone has the highest maternal and child mortality rates in the world. This manuscript describes the implementation of a National Emergency Medical Service (NEMS), a project aiming to create the first prehospital emergency medical system in the country. In 2017, a joint venture of Doctors with Africa (CUAMM), Veneto Region, and Research Center in Emergency and Disaster Medicine (CRIMEDIM) was developed to support the Ministry of Health and Sanitation (MOHS) in designing and managing the NEMS system, one of the very few structured, fully equipped, and free-of-charge prehospital service in the African continent. The NEMS design was the result of an in-depth research phase that included a preliminary assessment, literature review, and consultations with key stakeholders and managers of similar systems in other African countries. From May 27, 2019, after a timeframe of six months in which all the districts have been progressively trained and made operational, the NEMS became operative at national level. By the end of March 2020, the NEMS operation center (OC) and the 81 ambulances dispatched on the ground handled a total number of 36,814 emergency calls, 35,493 missions, and 31,036 referrals.

The concept of a “digital twin” as a model for data-driven management and control of physical systems has emerged over the past decade in the domains of manufacturing, production, and operations. In the context of buildings and civil infrastructure, the notion of a digital twin remains ill-defined, with little or no consensus among researchers and practitioners of the ways in which digital twin processes and data-centric technologies can support design and construction. This paper builds on existing concepts of Building Information Modeling (BIM), lean project production systems, automated data acquisition from construction sites and supply chains, and artificial intelligence to formulate a mode of construction that applies digital twin information systems to achieve closed loop control systems. It contributes a set of four core information and control concepts for digital twin construction (DTC), which define the dimensions of the conceptual space for the information used in DTC workflows. Working from the core concepts, we propose a DTC information system workflow—including information stores, information processing functions, and monitoring technologies—according to three concentric control workflow cycles. DTC should be viewed as a comprehensive mode of construction that prioritizes closing the control loops rather than an extension of BIM tools integrated with sensing and monitoring technologies.

Leafy spurge is a troublesome, exotic weed in the northern Great Plains of the United States. Leafy spurge produces showy yellow bracts during June that give this weed a conspicuous appearance. A study was conducted to determine the feasibility of using remote sensing techniques to detect leafy spurge in this phenological stage. Study sites were located in North Dakota and Montana. Plant canopy reflectance measurements showed that leafy spurge had higher visible (0.63- to 0.69-μm) reflectance than several associated plant species. The conspicuous yellow bracts of leafy spurge gave it distinct yellow-green and pink images on conventional color and color-infrared aerial photographs, respectively. Leafy spurge also could be distinguished on conventional color video imagery where it had a golden yellow image response. Quantitative data obtained from digitized video images showed that leafy spurge had statistically different digital values from those of associated vegetation and soil. Computer analyses of video images showed/that light reflected from leafy spurge populations could be quantified from associated vegetation. This technique permits area estimates of leafy spurge populations. Large format conventional color photographs of Theodore Roosevelt National Park near Medora, ND were digitized and integrated with a geographic information system to produce a map of leafy spurge populations within the park that can be useful to monitor the spread or decline of leafy spurge.

Cultural practices, such as delayed crop seeding, tillage, black fallow, crop rotation, hand weeding, and competitive crops, when used to replace herbicides, provide an opportunity to reduce the selection pressure that causes weeds to become resistant to herbicides. Herbicides on the other hand reduce the selection pressure that causes weeds to resist cultural practices. Rotation of the two systems should then delay resistance to both systems. Growers consider many factors in addition to weed resistance in selecting herbicide or cultural weed control, from associated convenience to economic potential. Rotation of different types of weed control practices would delay resistance, compared to a continuous single practice. The extent of the delay depends upon genetics of resistance, weed reproduction characteristics, weed seed survival, and fitness of resistant weed plants. An understanding of the basic aspects of weeds and herbicides, as well as their interaction with the environment, would help in predicting the delay in resistance to an herbicide from use of cultural practices in the rotation. A grower's final choice of a weed control practice will involve available equipment, time, markets, and soil erosion in addition to potential weed resistance. Weeds that develop resistance to a control practice still allow for reversion to preresistance practices, an important component of a grower's decision. The rate of resistance development is dependent upon the removal of susceptible genes from the population and fitness of the resistant plants. Resistance might be delayed for many years or be manageable when the resistance is genetically recessive or resistant weeds are poorly fit. Growers may not want to accept alternative cultural practices as long as there is the potential for development of another herbicide or reversion to cultural control after resistance occurs.

This paper describes the application of airborne video data with global positioning system and geographic information system technologies for detecting and mapping Chinese tamarisk infestations in the southwestern United States. Study areas were along the Colorado River in southwestern Arizona, the Rio Grande River in extreme west Texas, and the Pecos River in west-central Texas. Chinese tamarisk could be readily distinguished on conventional color video imagery in late November when its foliage turned a yellow-orange to orange-brown color prior to leaf drop. The integration of the global positioning system with the video imagery permitted latitude/longitude coordinates of Chinese tamarisk infestations to be recorded on each image. The global positioning system latitude/longitude coordinates were entered into a geographic information system to map Chinese tamarisk populations along the three river systems.

The high near-infrared reflectance (0.76 to 0.90 μm) of Big Bend loco and Wooton loco contributed significantly to their orange-red and red image tonal responses, respectively, on color-infrared aerial photographs making them distinguishable from associated vegetation and soil. Big Bend loco could also be distinguished on color-infrared and near-infrared black-and-white video imagery where it had distinct red and whitish tonal responses, respectively. Computer analyses of photographic and videographic images showed that Big Bend loco and Wooton loco populations could be quantified from other landscape features. A global positioning system was integrated with the video imagery that permitted latitude-longitude coordinates to appear on each image. The latitude-longitude data were integrated with a geographical information system to map Big Bend loco populations.

In many regions of the world domestic dogs are free roaming and live in close relationship with humans. These free-roaming domestic dogs (FRDD) can cause public health problems such as dog bites and transmission of infectious diseases. To effectively control diseases transmitted by FRDD, knowledge on the dogs’ behaviour is required. To identify predictors of home range (HR) size, we collected global positioning system data from 135 FRDD living in eight Aboriginal and Torres Strait Islander communities in Northern Australia. The core HR size ranged from 0·17 to 2·33 ha and the extended HR size from 0·86 to 40·46 ha. Using a linear mixed effect model with a Restricted Maximum Likelihood approach, the dog's sex and reproductive status were identified as predictors of roaming. Non-castrated males had the largest HRs, followed by neutered females. Also, FRDDs were found to roam further during the pre- than the post-wet season. These findings have implications for infectious disease spread. Identification of risk groups for disease spread within a population allows for more targeted disease response and surveillance. Further investigation of predictors of roaming in other FRDD populations worldwide would increase the external validity of such studies.

Leafy spurge is a deep-rooted perennial weed that displaces native rangeland vegetation and replaces forage for cattle and other forages used by vertebrate herbivores. Strategic planning to control this weed requires monitoring its distribution and spread. Classical monitoring techniques, which often involve extensive ground survey efforts, can be aided by the synoptic nature of remotely sensed imagery. This research addresses the use of Space Imaging's 4-m multispectral Ikonos imagery for the survey and detection of leafy spurge infestations. Survey data were collected at a site in western North Dakota and used to produce supervised classifications of leafy surge infestations with Ikonos imagery. Multiple image dates per year were combined with each other to assess the added accuracy afforded by multitemporal imagery. Finally, individual patches of leafy spurge were analyzed to determine the minimum patch size and percent cover that were detectable with supervised classification of Ikonos imagery. Under some circumstances, the imagery was effective at detecting leafy spurge, but in areas with a higher forb component, the classification was not as effective. Multidate imagery provided increased accuracy, but improvements were not consistently significant. Leafy spurge infestations of <30% cover and 200 m2 were not reliably detected.