Search Results (20)

Many sciences exploit algorithms in a large variety of applications. In agronomy, large amounts of agricultural data are handled by adopting procedures for optimization, clustering, or automatic learning. In this particular field, the number of scientific papers has significantly increased in recent years, triggered by scientists using artificial intelligence, comprising deep learning and machine learning methods or bots, to process field, crop, plant, or leaf images. Moreover, many other examples can be found, with different algorithms applied to plant diseases and phenology. This paper reviews the publications which have appeared in the past three years, analyzing the algorithms used and classifying the agronomic aims and the crops to which the methods are applied. Starting from a broad selection of 6060 papers, we subsequently refined the search, reducing the number to 358 research articles and 30 comprehensive reviews. By summarizing the advantages of applying algorithms to agronomic analyses, we propose a guide to farming practitioners, agronomists, researchers, and policymakers regarding best practices, challenges, and visions to counteract the effects of climate change, promoting a transition towards more sustainable, productive, and cost-effective farming and encouraging the introduction of smart technologies. Full article

The paper presents a double-radio wireless multimedia sensor node (WMSN) with a camera on board, designed for plant proximal monitoring. Camera sensor nodes represent an effective solution to monitor the crop at the leaf or fruit scale, with details that cannot be retrieved with the same precision through satellites or unnamed aerial vehicles (UAVs). From the technological point of view, WMSNs are characterized by very different requirements, compared to standard wireless sensor nodes; in particular, the network data rate results in higher energy consumption and incompatibility with the usage of battery-powered devices. Avoiding energy harvesters allows for device miniaturization and, consequently, application flexibility, even for small plants. To do this, the proposed node has been implemented with two radios, with different roles. A GPRS modem has been exclusively implemented for image transmission, while all other tasks, including node monitoring and camera control, are performed by a LoRaWAN class A end-node that connects every 10 min. Via the LoRaWAN downlink, it is possible to efficiently control the camera settings; the shooting times and periodicity, according to weather conditions; the eventual farming operations; the crop growth stages and the season. The node energy consumption has been verified in the laboratory and in the field, showing that it is possible to acquire one picture per day for more than eight months without any energy harvester, opening up further possible implementations for disease detection and production optimization. Full article

Background: Ustekinumab (UST) is an interleukin-12/interleukin-23 receptor antagonist approved for the treatment of Crohn’s disease (CD). Only limited real-life data on the long-term outcomes of CD patients treated with UST are available. This study assessed UST’s long-term effectiveness and safety in a large population-based cohort of moderate to severe CD patients. Methods: This was a multicenter, retrospective, observational cohort study that included both naïve and biologic-experienced patients treated with UST who achieved clinical remission or clinical response after at least one year of treatment. Clinical activity was scored according to the Harvey–Bradshaw Index (HBI). The primary endpoints were the maintenance or achievement of clinical remission after a further 12-month period of treatment, defined as an HBI of ≤5, and safety. Other endpoints included steroid-free remission, mucosal healing (MH), steroid discontinuation, and the need for treatment optimization during the follow-up. Results: Out of 562 CD patients, after an overall 24-month follow-up, clinical remission was present in 450 (80.0%) patients, and at 12 months, clinical remission was observed in 417/437 (95.4%) patients; 33/125 (26.4%) showed clinical response at 12 months (p = 0.000). A total of 38/103 (36.9%) patients achieved MH. Only 2.1% (12/562), 3% (17/562), and 1.1% (6/562) of patients required surgery, optimization, and re-induction, respectively. Adverse events occurred in eight patients (1.42%). According to a multivariate analysis, the only predictor of long-term remission was the presence of remission at the 12-month follow-up (p = 0.000). Conclusions: Long-term treatment with UST presents good efficacy and safety profiles in CD patients, especially for patients who achieve remission after one year. Full article

Background/Objectives: Chronic kidney disease and mineral bone disorders (CKD-MBD) are frequently associated with an increased risk of both vascular calcifications (VCs) and bone fractures (BFs). The complex pathogenesis of VCs and BFs involves various factors such as calcium overload, phosphate imbalance, and secondary hyperparathyroidism. Key players, such as the vitamin K-dependent proteins (VKDPs) matrix Gla protein (MGP) and bone Gla protein (BGP), have pivotal roles both for VCs and BFs. The VIKI study highlighted that hemodialysis patients treated with calcimimetics had higher levels of total BGP and MGP compared to those untreated, suggesting a potential protective effect of these drugs on BFs and VCs beyond the beneficial effect of reducing PTH levels. Methods: ETERNITY-ITA is a multi-center, comparative effectiveness, observational, longitudinal study that will enroll 160 hemodialysis patients (80 patients treated with Etelcalcetide and 80 age- and sex-matched patients treated with calcitriol or vitamin D analogs). Nephrologists will tailor the target dose of Etelcalcetide on an individual level to achieve the KDIGO PTH target. In the Etelcalcetide-treated group, the addition of calcitriol will be allowed when required by clinical practice (for correction of hypocalcemia). Conclusions: This study will evaluate the real-world effect of Etelcalcetide on VKDP levels, such as BGP and MGP, at 3, 9, and 18 months from baseline. The resulting preservation of vascular and bone health will be assessed for the first time by examining aortic and iliac artery calcifications and vertebral fractures, respectively. Full article

Artificial intelligence algorithms have become extensively utilized in survival analysis for high-dimensional, multi-source data. However, due to their complexity, these methods often yield poorly interpretable outcomes, posing challenges in the analysis of several conditions. One of these conditions is obstructive sleep apnea, a sleep disorder characterized by the simultaneous occurrence of comorbidities. Survival analysis provides a potential solution for assessing and categorizing the severity of obstructive sleep apnea, aiding personalized treatment strategies. Given the critical role of time in such scenarios and considering limitations in model interpretability, time-dependent explainable artificial intelligence algorithms have been developed in recent years for direct application to basic Machine Learning models, such as Cox regression and survival random forest. Our work aims to enhance model selection in OSA survival analysis using time-dependent XAI for Machine Learning and Deep Learning models. We developed an end-to-end pipeline, training several survival models and selecting the best performers. Our top models—Cox regression, Cox time, and logistic hazard—achieved good performance, with C-index scores of 0.81, 0.78, and 0.77, and Brier scores of 0.10, 0.12, and 0.11 on the test set. We applied SurvSHAP methods to Cox regression and logistic hazard to investigate their behavior. Although the models showed similar performance, our analysis established that the results of the log hazard model were more reliable and useful in clinical practice compared to those of Cox regression in OSA scenarios. Full article

Irisin is a peptide secreted by skeletal muscle that plays a major role in bone metabolism. Experiments in mouse models have shown that administration of recombinant irisin prevents disuse-induced bone loss. In this study, we aimed to evaluate the effects of irisin treatment for the prevention of bone loss in the ovariectomized (Ovx) mouse, the animal model commonly used to investigate osteoporosis caused by estrogen deficiency. Micro-Ct analysis conducted on Sham mice (Sham-veh) and Ovx mice treated with vehicle (Ovx-veh) or recombinant irisin (Ovx-irisn) showed bone volume fraction (BV/TV) decreases in femurs (Ovx-veh 1.39± 0.71 vs. Sham-veh 2.84 ± 1.23; p = 0.02) and tibia at both proximal condyles (Ovx-veh 1.97 ± 0.68 vs. Sham-veh 3.48 ± 1.26; p = 0.03) and the subchondral plate (Ovx-veh 6.33 ± 0.36 vs. Sham-veh 8.18 ± 0.41; p = 0.01), which were prevented by treatment with a weekly dose of irisin for 4 weeks. Moreover, histological analysis of trabecular bone showed that irisin increased the number of active osteoblasts per bone perimeter (Ovx-irisin 32.3 ± 3.9 vs. Ovx-veh 23.5 ± 3.6; p = 0.01), while decreasing osteoclasts (Ovx-irisin 7.6 ± 2.4 vs. Ovx-veh 12.9 ± 3.04; p = 0.05). The possible mechanism by which irisin enhances osteoblast activity in Ovx mice is upregulation of the transcription factor Atf4, one of the key markers of osteoblast differentiation, and osteoprotegerin, thereby inhibiting osteoclast formation. Full article

Fetal growth restriction is an obstetrical pathological condition that causes high neonatal mortality and morbidity. The mechanisms of its onset are not completely understood. Metabolites were extracted from 493 placentas from non-complicated pregnancies in Hamilton Country, TN (USA), and analyzed by gas chromatography–mass spectrometry (GC–MS). Newborns were classified according to raw fetal weight (low birth weight (LBW; <2500 g) and non-low birth weight (Non-LBW; >2500 g)), and according to the calculated birth weight centile as it relates to gestational age (small for gestational age (SGA), large for gestational age (LGA), and adequate for gestational age (AGA)). Mothers of LBW infants had a lower pre-pregnancy weight (66.2 ± 17.9 kg vs. 73.4 ± 21.3 kg, p < 0.0001), a lower body mass index (BMI) (25.27 ± 6.58 vs. 27.73 ± 7.83, p < 0.001), and a shorter gestation age (246.4 ± 24.0 days vs. 267.2 ± 19.4 days p < 0.001) compared with non-LBW. Marital status, tobacco use, and fetus sex affected birth weight centile classification according to gestational age. Multivariate statistical comparisons of the extracted metabolomes revealed that asparagine, aspartic acid, deoxyribose, erythritol, glycerophosphocholine, tyrosine, isoleucine, serine, and lactic acid were higher in both SGA and LBW placentas, while taurine, ethanolamine, β-hydroxybutyrate, and glycine were lower in both SGA and LBW. Several metabolic pathways are implicated in fetal growth restriction, including those related to the hypoxia response and amino-acid uptake and metabolism. Inflammatory pathways are also involved, suggesting that fetal growth restriction might share some mechanisms with preeclampsia. Full article

The use of robotic technologies for caregiving and assistance has become a very interesting research topic in the field of robotics. Towards this goal, the researchers at Politecnico di Torino are developing robotic solutions for indoor assistance. This paper presents the D.O.T. PAQUITOP project, which aims at developing a mobile robotic assistant for the hospital environment. The mobile robot is composed of a custom omnidirectional platform, named PAQUITOP, a commercial 6 dof robotic arm, sensors for monitoring vital signs in patients, and a tablet to interact with the patient. To prove the effectiveness of this solution, preliminary tests were conducted with success in the laboratories of Politecnico di Torino and, thanks to the collaboration with the Onlus Fondazione D.O.T. and the medical staff of Molinette Hospital in Turin (Italy), at the hematology ward of Molinette Hospital. Full article

In the field of precision agriculture, the automation of sampling and harvesting operations plays a central role to expand the possible application scenarios. Within this context, this work presents the design and prototyping of a novel underactuated tool for the harvesting of autonomous grapevines. The device is conceived to be one of several tools that could be automatically grasped by a robotic manipulator. As a use case, the presented tool is customized for the gripper of the robotic arm mounted on the rover Agri.Q, a service robot conceived for agriculture automation, but it can be easily adapted to other robotic arm grippers. In this work, first, the requirements for such a device are defined, then the functional design is presented, and a dimensionless analysis is performed to guide the dimensioning of the device. Later, the executive design is carried out, while the results of a preliminary experimental validation test are illustrated at the end of the paper. Full article

This review reports the recent state of the art in the field of mobile robots applied to precision agriculture. After a brief introduction to precision agriculture, the review focuses on two main topics. First, it provides a broad overview of the most widely used technologies in agriculture related to crop, field, and soil monitoring. Second, the main robotic solutions, with a focus on land-based robots, and their salient features are described. Finally, a short case study about a robot developed by the authors is introduced. This work aims to collect and highlight the most significant trends in research on robotics applied to agriculture. This review shows that the most studied perception solutions are those based on vision and cloud point detection and, following the same trend, most robotic solutions are small robots dedicated exclusively to monitoring tasks. However, the robotisation of other agricultural tasks is growing. Full article

In Mediterranean streams and rivers in general, aquatic organisms use a specific habitat for rearing, growing, breeding, and wintering. Multiple studies have focused on this subject, but few for the specific purpose of developing suitability models that feed hydrobiological models for the analysis of flow regimes and the design of environmental flows. Therefore, this study analyzes the habitat preferences of five freshwater species of fish and mussels in the NE of the Iberian Peninsula for that purpose. We use simple decision trees and random forest (RF), a machine learning technique based on the aggregation of multiple decision trees, to develop suitability models that relate the habitat preferences of the five species—separately adults and juveniles—to different attributes of a physical habitat at the meso-scale. Selected attributes are the surface percentage of different levels of depth (0–15 cm, 15–30 cm, …, >120 cm), velocity (0–15 cm/s, 15–30 cm/s, …, >120 cm/s) and abiotic/biotic substrate (e.g., gigalithal, megalithal, detritus, phytal), and absence/presence of refuges (boulder, canopy shading, emerging vegetation, undercut banks, woody debris, roots). The models were developed in order to predict three ranks of habitat suitability: absence, presence and abundance, depending on the mentioned attributes of the mesohabitat analysed. Our study provides quantitative results concerning the correspondence between the presence and abundance of different species and habitat characteristics, confirming qualitative observations stated in previous studies. We proved now that the adult mussels of Unio genus require a minimum of 5% of sand or silt, low velocities, and undercut banks and roots; that Barbus meridionalis habitat changes considerably among seasons; that Salaria fluviatilis needs coarse substrates (megalithal, macrolithal and mesolithal) and velocities above 15 cm/s; and that the adult Squalius laietanus prefers glides and pools with depths above 60 cm and velocities below 45 cm/s, depending on the season; and that Anguilla anguilla prefers intermediate size substrates (macrolithal, mesolithal and microlithal). These results are essential for the modeling of environmental flows in rivers where these species are present. Thus, by analyzing how their physical habitat changes according to the flow regime, one can see whether the available habitat of fish and mussels increases or decreases and predict periods of danger for the species. Full article

In recent years, the study of robotic systems for agriculture, a modern research field often shortened as “precision agriculture”, has become highly relevant, especially for those repetitive actions that can be automated thanks to innovative robotic solutions. This paper presents the kinematic model and a motion planning pipeline for a mobile manipulator specifically designed for precision agriculture applications, such as crop sampling and monitoring, formed by a novel articulated mobile base and a commercial collaborative manipulator with seven degrees of freedom. Starting from the models of the two subsystems, characterized by an adjustable position and orientation of the manipulator with respect to the mobile base, the linear mapping that describes the differential kinematics of the whole custom system is expressed as a function of the input commands. To perform pick–and–place tasks, a motion planning algorithm, based on the manipulator manipulability index mapping and a closed form inverse kinematics solution is presented. The motion of the system is based on the decoupling of the base and the arm mobility, and the paper discusses how the base can be properly used for manipulator positioning purposes. The closed form inverse kinematics solution is also provided as an open-source Matlab code. Full article

COVID-19 is a viral infection, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and characterized by a complex inflammatory process and clinical immunophenotypes. Nowadays, several alterations of immune response within the respiratory tracts as well as at the level of the peripheral blood have been well documented. Nonetheless, their effects on COVID-19-related cell heterogeneity and disease progression are less defined. Here, we performed a single-cell RNA sequencing of about 400 transcripts relevant to immune cell function including surface markers, in mononuclear cells (PBMCs) from the peripheral blood of 50 subjects, infected with SARS-CoV-2 at the diagnosis and 27 healthy blood donors as control. We found that patients with COVID-19 exhibited an increase in COVID-specific surface markers in different subsets of immune cell composition. Interestingly, the expression of cell receptors, such as IFNGR1 and CXCR4, was reduced in response to the viral infection and associated with the inhibition of the related signaling pathways and immune functions. These results highlight novel immunoreceptors, selectively expressed in COVID-19 patients, which affect the immune functionality and are correlated with clinical outcomes. Full article

Background: tattooing and piercing are increasingly common, especially among youths. However, several health complications may be associated with these practices if basic hygiene rules are not respected. This multicenter study was aimed at exploring tattoo and piercing experiences reported by a large sample of Italian undergraduate students through a public health perspective. Methods: tattooed and/or pierced students attending 12 Italian universities were asked to complete a web-based questionnaire regarding their body art experience. Results: out of 1472 respondents, 833 (56.6%) were tattooed and 1009 (68.5%) were pierced. The greatest proportion of tattooed students (93.9%) got her/his first tattoo in a tattoo studio, while most of the pierced were serviced in a jewelry store (48.0%). The pierced ones were less informed on health issues related to the procedure (56.0% versus 77.8% of tattooed p < 0.001), and tattooists were reportedly more attentive to hygiene rules (instrument sterilization 91.5% versus 79.1% of piercers, p < 0.001; use of disposable gloves 98.2% versus 71% of piercers, p < 0.001). Conclusions: educational interventions for both professionals and communities are needed to improve the awareness and the control of health risks related to body art throughout the Italian territory. Full article

The escalation of Coronavirus disease 2019 (COVID-19) has required the development of safe and effective vaccines against the severe acute respiratory syndrome coronavirus 2-associated (SARS-CoV-2), which is the causative agent of the disease. Here, we determined the levels of antibodies, antigen-specific B cells, against a recombinant GFP-tagged SARS-CoV-2 spike (S) protein and total T and NK cell subsets in subjects up to 20 days after the injection of the BNT162b2 (Pfizer–BioNTech) vaccine using a combined approach of serological and flow cytometry analyses. In former COVID-19 patients and highly responsive individuals, a significant increase of antibody production was detected, simultaneous with an expansion of antigen-specific B cell response and the total number of NK-T cells. Additionally, through a genetic screening of a specific polymorphic region internal to the 3’ regulatory region 1 (3’RR1) of human immunoglobulin constant-gene (IgH) locus, we identified different single-nucleotide polymorphic (SNP) variants associated with either highly or lowly responsive subjects. Taken together, these results suggest that favorable genetic backgrounds and immune profiles support the progression of an effective response to BNT162b2 vaccination. Full article