How Can Remote Sensing Reduce Required Human Intervention in Robotic Forest Regeneration

In this article, we introduce an alternative solution for forest regeneration based on unmanned ground vehicles (UGV) and describe requirements for external data, which could significantly increase the level of automation. Over the past few decades, the global forested area has decreased, and there is a great need to restore and regenerate forests. Challenges such as the lack of labor and high costs demand innovative approaches for forest regeneration. Mechanization has shown satisfactory results in terms of time-efficient planting, although its usage is limited by high operational costs. Innovative technologies must be cost-efficient and profitable for large scale usage. Automation could make mechanized forest regeneration feasible. Forest regeneration operations can be automated using a purpose built unmanned platform. We developed a concept to automate forest planting operations based on mobility platform. The system requires external data for efficient mobility in clear-cut areas. We developed requirements for external data, analyzed available solutions, and experimented with the most promising option, the SfM (structure from motion) technique. Earth observation data are useful in the planning phase. A DEM (digital terrain model) for UGV planter operations can be constructed using ALS (airborne laser scanning), although it may be restricted by the cost. Low-altitude flights by drones equipped with digital cameras or lightweight laser scanners provided a usable model of the terrain. This model was precise (3–20 cm) enough for manually planning of the trajectory for the planting operation. This technique fulfilled the system requirements, although it requires further development and will have to be automated for operational use.

Sensory Panel Performance Evaluation—Comprehensive Review of Practical Approaches

Sensory assessors determine the result of sensory analysis; therefore, investigation of panel performance is inevitable to obtain well-established results. In the last few decades, numerous publications examine the performance of both panelists and panels. The initial point of any panelist measures are the applied selection methods, which are chosen according to the purpose (general suitability or product-specific skills). A practical overview is given on the available solutions, methods, protocols and software relating to all major panelist and panel measure indices (agreement, discrimination, repeatability, reproducibility and scale usage), with special focus on the utilized statistical methods. The novel approach of the presented methods is multi-faceted, concerning time factor (measuring performance at a given moment or over a period), the level of integration in the sensory testing procedure and the target of the measurements (panelist versus panel). The present paper supports the choice of the performance parameter and its related statistical procedure. Available software platforms, their accessibility (open-source status) and their functions are thoroughly analyzed concerning panelist or whole panel evaluation. The applied sensory test method strongly defines the applicable performance evaluation tools; therefore, these aspects are also discussed. A special field is related to proficiency testing. With the focus on special activities (product competitions, expert panels, food and horticultural goods), practical examples are given. In our research, special attention was given to sensory activity in companies and product experts or product-specific panels. Emerging future trends in this field will involve meta-analyses, application of AI and integration of psychophysics.

Reporting missing children to the police: A qualitative exploration of the factors associated with contacting or not contacting the police

Releasing missing person appeals is common practice when someone goes missing. Despite the wide-scale usage, the understanding on appeal effectiveness remains under-researched. This article aims to identify the factors that influence the likelihood of members of the public to report a child that has gone missing to the police and requires police assistance. Participant responses ( n = 252) were qualitatively analysed identifying four factors that positively influenced the likelihood of contacting the police, and two factors that negatively influenced the likelihood of not contacting the police to report the child. Practical implications are also discussed.

Machine Learning Algorithms in Social Media: the Emergence of a Split Subject?

Machine learning algorithms are the most common way in which most people interact with artificial intelligence. Wide scale usage of Machine learning has grown dramatically during the last decade, particularly within social media platforms. Considering the almost three billion monthly active users at Facebook and that most of their services rely heavily on machine learning, the aim of this essay is to investigate some of the social and moral implications of ML algorithms employed in social media. Guided by the adage ‘we shape our tools and then they shape us’ the common thread among several varied effects of social media was the outsourcing of important social actions from our physical reality to a virtual one. And, with current ML algorithms being successfully utilised to increase user time expenditure, social media platforms are likely to operate as an amplifier of social media effects i.e., greater time expenditure leads to greater amounts of important social actions outsourced to virtual reality. Now, considering that such extraordinary change as could be wrought by a fourth industrial revolution has historically been accompanied by change in the philosophical subject, it is not unreasonable to consider the possibility that change is occurring once more. Yet, I posit the view that we are currently in an intermediary phase between the physical and virtual realities, that we stand today as split subjects. For, while devices like our phones, consoles, watches and computers mean we are always on, many important social actions remain in the physical real. Though, even the effects of a partial transformation of the subject are substantial, as the kind of splitting many of us do today is reminiscent of compartmentalization, a psychologically significant coping mechanism known for its corrosion of moral agency. As such, with a potentially transient contemporary subject and a variety of associated effects the split subject is rich ground for further research.

Engagement in a Multi-Feature Digital Health Lifestyle Change Program as a Predictor of Weight Loss

Background: Modern digital health interventions targeting weight loss employ multiple evidence-based strategies, including nutrition tracking, coaching, and activity monitoring, providing users with choice as they set and achieve their own goals. Still, limited research exists on the partial effects of each component of such interventions, and whether participants choose to use all of the features of a program. The objective of this study was to test the individual components of a fully-featured digital health lifestyle intervention as predictors of weight loss in a single statistical model. Methods: Participants in the study (N=25,273) were enrolled in the Livongo for Weight Loss program as part of their employee wellness benefit across 57 states/territories of the US from April, 2019 to January, 2021. Participants received a cellular-connected scale to use daily in the program; they were asked to track their eating via the app and physical activity via smartphones or wearables. Additionally, participants could engage with coaches voluntarily or by receiving feedback from coaches on their recorded food logs. A mixed-effects generalized linear model was used to test the effects of scale usage, physical activity, human telephonic coaching, and food logs without and without coaching feedback on the percent weight loss the following month. Predictors were disaggregated into between- and within-subject components to understand the impact of each component relative to one’s own mean. The month in the program and whether or not that month occurred during the COVID-19 pandemic were entered as time-varying covariates. Baseline age, gender, and BMI were entered as time-invariant covariates. Results: Participants were 45% male and had average age of 54.3 years old (SD =11.4), with an average BMI of 33.10 kg/m2 (SD: 6.2). On average, participants were enrolled in the program for 10.4 months (SD: 5.1). Each additional use of the scale above one’s own average was associated with an overall 7.4% weight loss (z=21.06,p<0.001). Similarly, each additional minute of moderate-vigorous physical activity (MVPA) above one’s own average was associated with an overall 2.4% weight loss (z=3.14, p<0.01). Lastly, coaching and food logging with coaching feedback at a frequency above one’s own average were associated with approximately a 6% weight loss throughout the program (z=3.08 and 2.35, respectively; p<0.05 for both). Conclusion: We found that frequency of use of a scale in a weight loss intervention was most predictive of weight loss, followed by human coaching interaction and physical activity. However, food logging without feedback did not significantly impact weight loss among participants. Additional work is needed to understand drivers associated with increased utilization of beneficial program features, including optimizing the use of coaching, which offers great benefit, but may be costly to scale.

Characteristics of Ni-Zn Rechargeable Batteries with Zn Anode Prepared by Using Nano-Cellulose as its Binder Agent

While the operating voltages of Ni-Zn batteries are smaller than Li-ion batteries, Ni-Zn batteries offer some advantages, such as high specific energy and low cost. Ni-Zn batteries use green materials as they use aqueous electrolytes and do not need hazardous organic solvents. Both Ni and Zn are abundant and much less expensive in comparison to lithium. Therefore, Ni-Zn batteries are more suitable as secondary batteries for applications that do not need mobility, such as for storing electricity from solar panels at home or office building. At present, large scale usage of Ni-Zn batteries is hindered by their low life cycle due to Zn anode degradation during the operation. The Zn anode deteriorates as dendrite and passivation growth causing self-discharge at the Zn anode. Many efforts have been tried to solve those problems by adding additives in the electrode or electrolyte and a specific binder in the Zn anode. In the present work, in addition to standard CMC and PTFE as the binder in Zn anode, we also added nano-cellulose as its binder agent as the host matrix may be formed with a much smaller void, providing much more dispersion of ZnO nanoparticles and better reduction on Zn dendrite formation. The battery structures in this work were Zn-anode | electrolytes (KOH, aqueous) | Ni-cathode. Ni cathode used in this work is similar to those found in commercial Ni-Zn batteries. The Zn anode was prepared with various compositions of binder and hydroxides, such as Ca(OH)2, and ZnO nanoparticles as the active materials. The characteristics of the batteries are largely affected by the composition of the binder and other substances forming the Zn anode, particularly the proportion of the hydroxide. However, in general, the present result shows the potential of this modified Ni-Zn battery as an alternative to supersede expensive Li-ion batteries for low-cost and stationary applications.

Developing a Framework for the Examination of Anchoring Vignette Assumptions Using Cognitive Interviews: A Demonstration in the ICT Skills Domain

Self-assessment measures are commonly used in questionnaire surveys. However, one of the problems with self-reports is that they may be prone to differences in scale usage among respondents. The anchoring vignette method addresses this issue. It relies on two assumptions: response consistency and vignette equivalence. Here we aim to develop a framework for the examination of these assumptions using cognitive interviews and demonstrate it in the Information and Communications Technology (ICT) skills domain. First, we develop new anchoring vignettes describing various ICT skill domains. Second, we examine both assumptions using cognitive interviews with students who are studying different fields. Our analysis shows that the assumptions are indeed not adhered to, especially the assumption of vignette equivalence. Third, we develop a general framework for the examination of the method’s assumptions.

A Decadal Walkthrough on Energy Modelling for Cloud Datacenters

Cloud computing is the growing field in the industry, and every scale industry needs it now. The high scale usage of cloud has resulted in huge power consumption, and this power consumption has led to increase of carbon footprint affecting our mother nature. Thus, we need to optimize the power usage in the cloud servers. Various models are used to tackle this situation, of which one is a model based on link load. It minimized the bit energy consumption of network usage which includes energy efficiency routing and load balancing. Over this, multi-constraint rerouting is also adapted. Other power models which have been adapted are virtualization framework using multi-tenancy-oriented data center. It works by accommodating heterogeneous networks among virtual machines in virtual private cloud. Another strategy that is adopted is cloud partitioning concept using game theory. Other methods that are adopted are load spreading algorithm by shortest path bridging, load balancing by speed scaling, load balancing using graph constraint, and insert ranking method.

Disulfiram Ethanol Reaction with Alcohol-Based Hand Sanitizer: An Exploratory Study

Aims We conducted a cross-sectional survey to estimate the prevalence and clinical manifestation of disulfiram ethanol reaction (DER) and isopropanol toxicity (IT) in patients with alcohol use disorders, on disulfiram. Alcohol-based hand rub contains either ethanol or isopropanol or both. COVID-19 pandemic has led to wide scale usage of sanitizers. Patients with alcohol use disorders, on disulfiram, might experience disulfiram ethanol like reactions with alcohol-based sanitizers. Methods We telephonically contacted 339 patients, prescribed disulfiram between January 2014 and March 2020. The assessment pertained to the last 3 months (i.e. third week of March to third week of June 2020). Result The sample consisted of middle-aged men with a mean 16 years of alcohol dependence. Among the 82 (24%) patients adherent to disulfiram, 42 (12.3%) were using alcohol-based hand rubs. Out of these, a total of eight patients (19%; 95% CI 9–33) had features suggestive of DER; four of whom also had features indicative of IT. Five patients (62.5%) had mild and self-limiting symptoms. Severe systemic reactions were experienced by three (37.5%). Severe reactions were observed with exposure to sanitizers in greater amounts, on moist skin or through inhalation. Conclusion Patients on disulfiram should be advised to use alternate methods of hand hygiene.