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This paper focuses on building a non-invasive, low-cost sensor that can be fitted over tree trunks growing in a semiarid land environment. It also proposes a new definition that characterizes tree trunks' water retention capabilities mathematically. The designed sensor measures the variations in capacitance across its probes. It uses amplification and filter stages to smooth the readings, requires little power, and is operational over a 100 kHz frequency. The sensor sends data via a Long Range (LoRa) transceiver through a gateway to a processing unit. Field experiments showed that the system provides accurate readings of the moisture content. As the sensors are non-invasive, they can be fitted to branches and trunks of various sizes without altering the structure of the wood tissue. Results show that the moisture content in tree trunks increases exponentially with respect to the measured capacitance and reflects the distinct differences between different tree types. Data of known healthy trees and unhealthy trees and defective sensor readings have been collected and analysed statistically to show how anomalies in sensor reading baseds on eigenvectors and eigenvalues of the fitted curve coefficient matrix can be detected. [ABSTRACT FROM AUTHOR]

The given document is an editorial from the Annals of Emerging Technologies in Computing (AETiC) journal. It reflects on the Millennium Bug, also known as the Y2K bug, which was a computer flaw that caused concern in the late 1990s. The bug was tied to the transition from December 31, 1999, to January 1, 2000, and arose from the practice of programming dates with only two digits representing the year. The editorial emphasizes the global dependency on digital infrastructure and the extensive efforts made by governments, corporations, and organizations to prevent potential disasters. The author encourages researchers and system builders to learn from the Millennium Bug and strive to get things right the first time. [Extracted from the article]

The Wales Institute of Digital Information has developed a flexible model of education, CPD, research and innovation for the Welsh health and care sectors, in the digital arena. The co-produced model had produced significant benefits for both health employers and the Universities involved in the partnership. The model is continuing to develop collaborative educational provision from level 2 to level 8 and is concentrating on expanding its digital research and innovation offering to the health and care sector in a similar co-developed collaborative way. [ABSTRACT FROM AUTHOR]

Protection of many crops is achieved through the use of genetic resistance. Leptosphaeria maculans, the causal agent of blackleg disease of Brassica napus, has emerged as a model for understanding gene‐for‐gene interactions that occur between plants and pathogens. Whilst many of the characterized avirulence effector genes interact with a single resistance gene in the host, the AvrLm4‐7 avirulence gene is recognized by two resistance genes, Rlm4 and Rlm7. Here, we report the "breakdown" of the Rlm7 resistance gene in Australia, under two different field conditions. The first, and more typical, breakdown probably resulted from widescale use of Rlm7‐containing cultivars whereby selection has led to an increase of individuals in the L. maculans population that have undergone repeat‐induced point (RIP) mutations at the AvrLm4‐7 locus. This has rendered the AvrLm4‐7 gene ineffective and therefore these isolates have become virulent towards both Rlm4 and Rlm7. The second, more atypical, situation was the widescale use of Rlm4 cultivars. Whilst a single‐nucleotide polymorphism is the more common mechanism of virulence towards Rlm4, in this field situation, RIP mutations have been selected leading to the breakdown of resistance for both Rlm4 and Rlm7. This is an example of a resistance gene being rendered ineffective without having grown cultivars with the corresponding resistance gene due to the dual specificity of the avirulence gene. These findings highlight the value of pathogen surveillance in the context of expanded knowledge about potential complexities for Avr–R interactions for the deployment of appropriate resistance gene strategies. [ABSTRACT FROM AUTHOR]

Purpose: People with a borderline personality disorder (BPD) diagnosis can require support from mental health services for managing risk behaviour. Current routine inpatient and community treatment can be unhelpful for this group. Positive risk taking has been developed to help community teams manage risk with people with a BPD. This study aims to explore experiences of risk management in an NHS Trust where positive risk taking is being implemented with people with a BPD. Design/methodology/approach: Interpretative phenomenological analysis is the methodology of transcripts from semi-structured interviews. Nine adults with a diagnosis of BPD and current or previous experiences of risk management approaches were sampled from one NHS Trust. Findings: Limited resources and interpersonal barriers had a negative impact on experiences of Positive risk taking. Participants experienced one-off risk assessments and short-term interventions such as medication which they described as "meaningless". Traumatic experiences could make it difficult to establish therapeutic relationships and elicit unhelpful responses from professionals. Participants could only feel "taken seriously" when in crisis which contributed towards an increase in risky behaviour. Positive risk taking was contingent upon collaborative and consistent professional relationships which created a "safety net", enabling open communication and responsibility taking which challenged recovery-relapse patterns of service use. Research limitations/implications: Positive risk taking approaches to risk management may benefit people with a BPD. Findings complement those from other studies emphasising the importance of compassion and empathy when working with personality disorder. Training and increased resources are required to implement effective risk management with this group. Originality/value: Findings expand upon the sparse existing research in the area of risk management using the Positive risk taking approach with people with a BPD diagnosis, and provide idiographic understanding which is clinically meaningful. Participants' experiences suggest Positive risk taking may provide a framework for improving quality of life and decreasing service use for people diagnosed with BPD engaging in risk management with Community Mental Health Teams, which facilitates recovery and other benefits. [ABSTRACT FROM AUTHOR]

Various images from massive image databases extract inherent, implanted information or different examples explicitly found in the images. These images may help the community in initial self-screening breast cancer, and primary health care can introduce this method to the community. This study aimed to review the different methods of abnormal mass detection in digital mammograms. One of best methods for the detection of breast malignancy and discovery at a nascent stage is digital mammography. Some of the mammograms with excellent images have a high intensity of resolution that enables preparing images with high computations. The fact that medical images are so common on computers is one of the main things that helps radiologists make diagnoses. Image preprocessing highlights the portion after extraction and arrangement in computerized mammograms. Moreover, the future scope of examination for paving could be the way for a top invention in computer-aided diagnosis (CAD) for mammograms in the coming years. This also distinguished CAD that helped identify strategies for mass widely covered in the study work. However, the identification methods for structural deviation in mammograms are complicated in real-life scenarios. These methods will benefit the public health program if they can be introduced to primary health care's public health screening system. The decision should be made as to which type of technology fits the level of the primary health care system. [ABSTRACT FROM AUTHOR]

The article reflects on the dual nature of technological progress, emphasizing both its potential and its risks. Topics discussed include advancements in artificial intelligence (AI) and robotics, ethical concerns surrounding innovation, and the severe consequences of the British Post Office Horizon Information Technology (IT) scandal.

The editorial from the Annals of Emerging Technologies in Computing discusses the dual nature of progress in the field of technology. While advancements in artificial intelligence, robotics, and predictive modeling have the potential to improve our lives, they also bring ethical dilemmas and privacy concerns. The editorial highlights the recent British Post Office scandal, caused by faulty software, which resulted in wrongful convictions, financial losses, and personal tragedies. The author emphasizes the need for careful stewardship of emerging technologies to navigate the complexities of an interconnected world. [Extracted from the article]

Sustaining diverse, yet productive crop sequences that integrate break crops such as canola (Brassica napus L.) remains a critical challenge for farming systems in low-rainfall cropping environments. Recent advances in canola productivity through early sowing, understanding of critical stress periods, hybrid cultivars and improved nitrogen (N) fertilisation offer promise under many conditions but require careful adaptation for risky, low-rainfall environments. A series of eight experiments was implemented over four growing seasons (2015–18) in the low-rainfall environments of southern Australia to test combinations of sowing date, cultivar selection and N-management strategies. Simulation modelling extended the field experiment results, enabling a simple, whole-farm profit–risk analysis across growing season deciles. The aim was to identify combinations of practices where the potential production and risk were understood, thereby assisting management decisions in low-rainfall cropping systems. Earlier sowing (April) was generally beneficial but only where seasonal conditions led to successful establishment, meaning that the best fit for canola in low-rainfall environments is as an opportunity crop. A hybrid cultivar (triazine tolerant) did not provide a yield advantage in an early experiment, but productivity increases were measured with a modern hybrid cultivar (Clearfield) in a later experiment. Profit-risk analysis suggested that a yield advantage of >20% over open-pollinated cultivars needs to be sustained across the full range of season deciles to generate economic advantage. Although there was relative insensitivity to the timing of N application, an adequate dose of N, either through fertiliser or legume crops, was critical to improve canola productivity. We conclude that opportunities exist to make significant gains in yield (by up to 110% compared with current standard practice) and profit–risk outcomes (~30% increased gross margins across all season types) for canola in low-rainfall environments by using a package of agronomic management decisions that includes early sowing on genuine establishment opportunities, hybrids that offer sustained yield benefits, and matching N dose from both fertiliser and legume crops to yield potential of the soil type and seasonal outlook. TOC Summary: The low-rainfall environment presents significant challenges to consistent and profitable canola production. Combinations of time of sowing, cultivar selection and nitrogen treatments were tested to identify management packages that are productive and profitable across a range of season types. The best performing packages identified offer yield gains of up to 110% combined with 30% gross-margin benefits across below-average to above-average growing seasons, indicative of strategies that also manage risk. [ABSTRACT FROM AUTHOR]

The editorial discusses the complexity and rapid evolution of the field of computer science. It acknowledges that the breadth and depth of knowledge required to fully understand computing make it challenging for one person to grasp. The editorial highlights the theoretical and practical aspects of computing, as well as the continuous learning required to keep up with technological advancements. It also emphasizes the collaborative nature of computing projects and the need for specialization and teamwork. The author expresses gratitude to the experts who have contributed to the journal and wishes the readers a successful 2024. [Extracted from the article]

The editorial from the Annals of Emerging Technologies in Computing discusses the challenges and complexities of studying and keeping up with the rapidly evolving field of computing. The author highlights the diverse range of computing technologies, from powerful supercomputers to small IoT sensors, and emphasizes the speed at which advancements occur. They also acknowledge the importance of collaboration and knowledge sharing in driving innovation. The author expresses gratitude for the opportunity to gain insight into the subject area and acknowledges the contributions of those who advance the field. [Extracted from the article]

Blackleg, caused by Leptosphaeria maculans, is the main disease constraint for canola production in Australia. The fungus infects all aboveground and belowground parts of the canola plant. Yield loss in Australia and worldwide is generally associated with cankers at the crown, which arise from leaf infections during the early stages of seedling growth. Infection of flowers, peduncles, siliques, main stems and branches, with resultant lesions and canker formation, are typically uncommon symptoms. We propose the term 'upper canopy infection' to encompass symptoms on all of these plant parts because they generally occur together on the same plant and appear after the plant has undergone elongation. Branch and stem lesions observed in a commercial crop in 2010 were confirmed as L. maculans. Since then, assessment of upper canopy symptoms at 25 sites across the canola-producing regions of Australia between 2011 and 2016 show that symptoms are more prevalent, although they differed between sites and seasons. In 2011, symptoms were present at a single site, and this increased to seven sites in 2013 and 23 sites in 2016. Preliminary data indicate that infection arises from both ascospore and pycnidiospore inoculum, and that earlier onset of flowering is a key risk factor for more severe upper canopy infection. Evidence suggests that host genetic resistance may be an effective control for upper canopy infection. [ABSTRACT FROM AUTHOR]

Evidence for mentalisation-based therapy (MBT) is increasing in relation to the treatment of personality disorder. Individuals with personality disorder are over-represented in inpatient, forensic and forensic inpatient mental health services. This study explores MBT within a forensic setting as an intervention designed to moderate deficits linked to violence and to improve adaptive coping. Interpretative phenomenological analysis was conducted on interviews with four patients who completed MBT at a high-secure hospital. Findings suggest that MBT-enhanced participants’ mentalising which had a positive impact upon their capacity to manage their behaviour and emotions. MBT further enabled participants to process past experiences of violence and develop some degree of empathy for others, which led to a trend in abstinence from risk behaviours. Findings contribute a secure inpatient perspective on the experience of MBT and to MBT clinical outcomes. [ABSTRACT FROM PUBLISHER]

Blackleg disease caused by the pathogen Leptosphaeria maculans is the most devastating disease of canola ( Brassica napus, oilseed rape). This disease occurs in all canola-growing regions of the world except China. It has been suggested that L. maculans contaminated seed and admixture (associated plant debris) could lead to a blackleg epidemic in China and as a consequence, restrictions on importations into China were placed on canola seed from Australia and Canada in 2009. We show that canola pods infected by L. maculans can lead to seed contamination, and resultant seedling infection, which then leads to cankering in adult plants. The fungus can sexually reproduce over summer on stubble derived from these plants. Airborne sexual spores are then released in the following year- thus completing the life cycle of the fungus from a contaminated seed and providing a potential source for an epidemic, particularly in countries such as China where canola cultivars do not have high levels of resistance to L. maculans. Furthermore, sexual fruiting bodies can also be produced on admixture. The presence of blackleg lesions on canola pods correlated with seed contamination by the blackleg fungus. Viability of L. maculans is reduced on contaminated seed over a twelve month period. Surveying blackleg disease in field trials in Australia showed that the presence and degree of stem cankers did not correlate with the level of pod infection. This suggests that pod lesions are likely to arise as a result of new infection events, rather than the pathogen moving from pre-existing infections (stem cankers) onto the pods. Furthermore, pod infections are likely to be a result of seasonal conditions rather than specific to regions where canola is cropped at a high intensity. [ABSTRACT FROM AUTHOR]

Active control of the flow shear, which is related to the radial derivative of the azimuthal flow, is a key factor in reducing the cross-field turbulence-driven particle transport in a magnetically confined plasma column. Once a desired radial azimuthal velocity profile and its associated level of turbulent fluctuations are identified, the challenge of systematically achieving and sustaining it still remains. In this paper, a model-based feedback controller is proposed to overcome this challenge in helicon-cathode (HELCAT). This linear, dual-source, magnetized-plasma, laboratory device employs concentric ring electrodes to mitigate the turbulent plasma transport by generating a sheared radial electric field and modifying the flow profiles by E\timesB actuation. A linear-quadratic-integral optimal feedback controller is designed to minimize a weighted combination of the tracking error and the control effort with an ultimate goal of regulating the radial azimuthal velocity profile around a prescribed desired profile even with external disturbances and perturbed initial conditions. Numerical simulations show the effectiveness of the proposed controller in shaping the azimuthal flow profile in HELCAT. The proposed control solution has the potential of being used as a systematic tool for physics-oriented studies in laboratory plasmas such as those achieved in HELCAT. [ABSTRACT FROM PUBLISHER]

Turbulence and turbulence-driven transport are ubiquitous in magnetically confined plasmas, where there is an intimate relationship between turbulence, transport, destabilizing mechanisms, such as gradients and currents, and stabilizing mechanisms like shear. Active control of fluctuations is investigated in this paper via manipulation of flow profiles in a magnetized laboratory plasma device helicon–cathode (HELCAT). Fluctuations are monitored by electrostatic probes, and E\times B flow profiles are controlled via bias ring electrodes. First, a nonmodel-based extremum-seeking optimal control algorithm is implemented in HELCAT to seek the bias ring voltages that minimize a cost function related to the fluctuation amplitude. The experimental results in HELCAT show that the proposed controller is able to not only suppress the fluctuations but also to regulate their average amplitude around a predefined desired level. It is anticipated that this controller can become a valuable tool for physics-oriented studies designed to elucidate the relationship between the shape of the azimuthal flow profile and the amplitude of the fluctuations once the capability of measuring the flow profile in real time becomes available in HELCAT. Second, with the assistance of a HELCAT-tailored transport code capable of predicting the evolution of the azimuthal flow at several radial points within the plasma, the potential of an extremum-seeking controller for directly regulating the azimuthal flow profile around a prescribed target profile is illustrated numerically. [ABSTRACT FROM PUBLISHER]

Human Activity Recognition (HAR) systems are designed to read sensor data and analyse it to classify any detected movement and respond accordingly. However, there is a need for more responsive and near real-time systems to distinguish between false and true alarms. To accurately determine alarm triggers, the motion pattern of legitimate users need to be stored over a certain period and used to train the system to recognise features associated with their movements. This training process is followed by a testing cycle that uses actual data of different patterns of activity that are either similar or different to the training data set. This paper evaluates the use of a combined Convolutional Neural Network (CNN) and Naive Bayes for accuracy and robustness to correctly identify true alarm triggers in the form of a buzzer sound for example. It shows that pattern recognition can be achieved using either of the two approaches, even when a partial motion pattern is derived as a subset out of a full-motion path. [ABSTRACT FROM AUTHOR]

This article reports on the results from a spatiotemporal analysis of disaggregate fire incident data. The innovative analysis presented here focuses on the exploration of spatial and temporal patterns for four principal fire incident categories: property, vehicle, secondary fires, and malicious false alarms. This research extends previous work on spatial exploration of spatiotemporal patterns by demonstrating the benefits of comaps and kernel density estimation in examining temporal and spatiotemporal dynamics in calls for services. Results indicate that fire incidents are not static in either time or space and that spatiotemporal variation is related to incident type. The application of these techniques has the potential to inform policy decisions both from a reactive, resource-allocation perspective and from a more proactive perspective, such as through spatial targeting of preventive measures. [ABSTRACT FROM AUTHOR]

The article discusses the role of turbulence in the transport of ozone into polar ozone holes. The Navier-Stokes equation is the starting point for modeling turbulence, although final results are highly dependent upon initial conditions. Ozone transport can be significantly affected by the interaction of turbulence and shear.

Background: Cervical cancer is preventable if effective screening measures are in place. Pap-smear is the commonest technique used for early screening and diagnosis of cervical cancer. However, the manual analysis of the pap-smears is error prone due to human mistake, moreover, the process is tedious and time-consuming. Hence, it is beneficial to develop a computer-assisted diagnosis tool to make the pap-smear test more accurate and reliable. This paper describes the development of a tool for automated diagnosis and classification of cervical cancer from pap-smear images.Method: Scene segmentation was achieved through a Trainable Weka Segmentation classifier and a sequential elimination approach was used for debris rejection. Feature selection was achieved using simulated annealing integrated with a wrapper filter, while classification was achieved using a fuzzy C-means algorithm.Results: The evaluation of the classifier was carried out on three different datasets (single cell images, multiple cell images and pap-smear slide images from a pathology lab). Overall classification accuracy, sensitivity and specificity of '98.88%, 99.28% and 97.47%', '97.64%, 98.08% and 97.16%' and '95.00%, 100% and 90.00%' were obtained for each dataset, respectively. The higher accuracy and sensitivity of the classifier was attributed to the robustness of the feature selection method that accurately selected cell features that improved the classification performance and the number of clusters used during defuzzification and classification. Results show that the method outperforms many of the existing algorithms in sensitivity (99.28%), specificity (97.47%), and accuracy (98.88%) when applied to the Herlev benchmark pap-smear dataset. False negative rate, false positive rate and classification error of 0.00%, 10.00% and 5.00%, respectively were obtained when applied to pap-smear slides from a pathology lab.Conclusions: The major contribution of this tool in a cervical cancer screening workflow is that it reduces on the time required by the cytotechnician to screen very many pap-smears by eliminating the obvious normal ones, hence more time can be put on the suspicious slides. The proposed system has the capability of analyzing a full pap-smear slide within 3 min as opposed to the 5-10 min per slide in the manual analysis. The tool presented in this paper is applicable to many pap-smear analysis systems but is particularly pertinent to low-cost systems that should be of significant benefit to developing economies. [ABSTRACT FROM AUTHOR]