The prediction of ovulation time is one of the most important and yet difficult processes in pig production, and it has a considerable impact on the fertility of the herd and litter size. The ...objective of this study was to assess the vulvar skin temperature of sows during proestrus and estrus using infrared thermography and to establish a possible relationship between the variations in vulvar temperature and ovulation. The experimental group comprised 36 crossbred Large White × Landrace females, of which 6 were gilts and 30 were multiparous sows. Estrus was detected twice daily and the temperature was obtained every 6 hours from the vulvar area and from two control points in the gluteal area (Gluteal skin temperature GST). A third variable, vulvar–gluteal temperature (VGT) was obtained from the difference between the vulvar skin temperature and the GST values. The animals were divided into two subgroups: group A consisting of 11 animals with estrus detected at 6:00 AM, Day 4 postweaning, and group B comprising seven animals with estrus detected at 6:00 AM, Day 5 post-weaning. Both groups showed a similar trend in the VGT. The VGT increased during the proestrus, reaching a peak 24 hours before estrus in group A and 48 hours before estrus in group B. The VGT then decreased markedly reaching the lowest value in groups A and B, respectively, 12 and 6 hours after estrus. Although the time of ovulation was only estimated on the basis of a literature review, the matching between the temporal variations of the VGT values and the predicted time of the peak of estradiol secretion that ultimately leads to the ovulation processes suggests that the VGT values represent a potential predictive marker of the ovulatory events.
Hiking and cycling have become popular activities for promoting well-being and physical activity. Portugal has been investing in hiking and cycling trail infrastructures to boost sustainable tourism. ...However, the lack of reliable data on the use of these trails means that the times of greatest affluence or the type of user who makes the most use of them are not recorded. These data are of the utmost importance to the managing bodies, with which they can adjust their actions to improve the management, maintenance, promotion, and use of the infrastructures for which they are responsible. The aim of this work is to present a review study on projects, techniques, and methods that can be used to identify and count the different types of users on these trails. The most promising computer vision techniques are identified and described: YOLOv3-Tiny, MobileNet-SSD V2, and FasterRCNN with ResNet-50. Their performance is evaluated and compared. The results observed can be very useful for proposing future prototypes. The challenges, future directions, and research opportunities are also discussed.
Live video streaming has become one of the main multimedia trends in networks in recent years. Providing Quality of Service (QoS) during live transmissions is challenging due to the stringent ...requirements for low latency and minimal interruptions. This scenario has led to a high dependence on cloud services, implying a widespread usage of Internet connections, which constrains contexts in which an Internet connection is not available. Thus, alternatives such as Mobile Ad Hoc Networks (MANETs) emerge as potential communication techniques. These networks operate autonomously with mobile devices serving as nodes, without the need for coordinating centralized components. However, these characteristics lead to challenges to live video streaming, such as dynamic node topologies or periods of disconnection. Considering these constraints, this paper investigates the application of Artificial Intelligence (AI)-based classification techniques to provide adaptive streaming in MANETs. For this, a software-driven architecture is proposed to route stream in offline MANETs, predicting the stability of individual links and compressing video frames accordingly. The proposal is implemented and assessed in a laboratory context, in which the model performance and QoS metrics are analyzed. As a result, the model is implemented in a decision forest algorithm, which provides 95.9% accuracy. Also, the obtained latency values become assumable for video streaming, manifesting a reliable response for routing and node movements.
Background and purpose
The therapeutic scenario of X‐linked adrenoleukodystrophy (X‐ALD) is rapidly changing. Whereas the disease is well characterized in men, the condition remains to be fully ...clarified in women carrying ATP binding cassette subfamily D member 1 (ABCD1) variants. Specifically, data on clinical progression are needed, in order to recommend any appropriate management. The objective of this study was to outline the natural history of a cohort of untreated ABCD1 heterozygous female carriers.
Methods
Longitudinal data from a single‐center population of 60 carriers were retrospectively reviewed. Demographics, anthropometrics, serum very long chain fatty acid (VLCFA) levels, clinical parameters and the Adult ALD Clinical Score (AACS) were collected from every recorded visit in a 7‐year period and analyzed to define the phenotype modifications, to determine factors associated with clinical features, and to estimate the annual progression rate and the subsequent sample size for interventional trials.
Results
Thirty‐two patients were eligible for the study, and 59.4% were symptomatic at baseline. Clinical severity worsens with age which increases risk of symptom onset, the cut‐off of 41 years being crucial for phenoconversion. VLCFA levels were not predictive and did not change over time. Symptomatic carriers were followed up for 3.45 ± 2.1 years. The AACS increased at an annual rate of 0.24 points. The estimated sample size for 30% reduction in annual progression at 80% power was 272.
Conclusions
This study provides data on the natural disease progression of untreated ABCD1 heterozygous female carriers, demonstrating the relevance of aging. The estimated annual increase of the AACS will be useful for future interventional studies.
In recent years, radio-frequency identification (RFID) has aroused significant interest from industry and academia. This demand comes from the technology’s evolution, marked by a reduction in size, ...cost, and enhanced efficiency, making it increasingly accessible for diverse applications. This manuscript presents a case study of the implementation of an RFID traceability system in the packaging section of an industrial company that produces test equipment for the automotive wiring industries. The study presents the proposal and execution of a prototype asset-tracking system utilising RFID technology, designed to be adaptable and beneficial for various industrial settings. The experiments were carried out within the company’s shop-floor environment, alongside the existing barcode system, with the primary objective of evaluating and comparing the proposed solution. The test results demonstrate a significant enhancement in production efficiency, with substantial optimization achieved. The time required for asset identification and tracking was significantly reduced, resulting in an average time of approximately 43.62 s and an approximate 3.627% improvement in the time required to read the test sample of assets when compared to the barcode system. This successful implementation highlights the potential of RFID technology in improving operations, reducing working time, and enhancing traceability within industrial production processes.
The agro-industrial sector consumes a significant amount of natural resources for farming and meat production. By 2050, population growth is expected, generating more demand and, consequently, more ...consumption of scarce resources. This challenging scenario is a concern of the European Commission, revealed in the Green Deal commitment and by the United Nations’ 12th goal of sustainable development. Thus, organizations must increase productivity and be more sustainable as soon as possible. Internet of Things (IoT) is introduced as a solution to facilitate agro-food companies to be more eco-efficient, mainly facing difficulties on farms, such as food loss and waste, best efficiency in management of resources, and production. The deployment of this technology depends on the stage of maturity and potential of implementation. To assess and characterize companies, with respect of IoT implementation, a survey was applied in 21 micro, small and medium agro-food companies, belonging to milk, honey, olive oil, jams, fruticulture, bakery and pastry, meat, coffee, and wine sectors, in the central region of Portugal. As results, this paper reveals the stage of maturity, level of sophistication, potential, opportunities, solutions, and barriers for implementation of IoT. Additionally, suggestions and recommendations to improve practices are discussed.
Pedestrian crossings are an essential part of the urban landscape, providing safe passage for pedestrians to cross busy streets. While some are regulated by timed signals and are marked with signs ...and lights, others are simply marked on the road and do not have additional infrastructure. Nevertheless, the markings undergo wear and tear due to traffic, weather, and road maintenance activities. If pedestrian crossing markings are excessively worn, drivers may not be able to see them, which creates road safety issues. This paper presents a study of computer vision techniques that can be used to identify and classify pedestrian crossings. It first introduces the related concepts. Then, it surveys related work and categorizes existing solutions, highlighting their key features, strengths, and limitations. The most promising techniques are identified and described: Convolutional Neural Networks, Histogram of Oriented Gradients, Maximally Stable Extremal Regions, Canny Edge, and thresholding methods. Their performance is evaluated and compared on a custom dataset developed for this work. Insights on open issues and research opportunities in the field are also provided. It is shown that managers responsible for road safety, in the context of a smart city, can benefit from computer vision approaches to automate the process of determining the wear and tear of pedestrian crossings.
•The spatio-temporal parameters measured by Kinect can provide fundamental information in clinical practice.•The Speed and the Stride Length correlate with the clinical scale SARA.•A machine learning ...approach combined with the Kinect shows a great potential to automatically assess the gait gravity.•Kinect is a tool useful to assess disease severity biomarkers in the framework of the “at-home monitoring systems”.
Ataxic syndromes include several rare, inherited and acquired conditions. One of the main issues is the absence of specific, and sensitive automatic evaluation tools and digital outcome measures to obtain a continuous monitoring of subjects' motor ability.
This study aims to test the usability of the Kinect system for assessing ataxia severity, exploring the potentiality of clustering algorithms and validating this system with a standard motion capture system.
Gait evaluation was performed by standardized gait analysis and by Kinect v2 during the same day in a cohort of young patient (mean age of 13.8±7.2). We analyzed the gait spatio-temporal parameters and we looked at the differences between the two systems through correlation and agreement tests. As well, we tested for possible correlations with the SARA scale as well. Finally, standard classification algorithm and principal components analysis were used to discern disease severity and groups.
We found biases and linear relationships between all the parameters. Significant correlations emerged between the SARA and the Speed, the Stride Length and the Step Length. PCA results, highlighting that a machine learning approach combined with Kinect-based evaluation shows great potential to automatically assess disease severity and diagnosis.
The spatio-temporal parameters measured by Kinect cannot be used interchangeably with those parameters acquired with standard motion capture system in clinical practice but can still provide fundamental information. Specifically, these results might bring to the development of a novel system to perform easy and quick evaluation of gait in young patients with ataxia, useful for patients stratification in terms of clinical severity and diagnosis.
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