Archivio istituzionale della ricerca - Alma Mater Studiorum Università di Bologna
Archivio istituzionale della ricerca - Alma Mater Studiorum Università di BolognaNot a member yet
336958 research outputs found
Sort by
L’ampiezza della discrezionalità e incertezze sulla sindacabilità dei golden power
No full textLo studio si propone di analizzare le criticità del sindacato del giudice amministrativo sui golden powers. Il self restraint del giudice amministrativo, pur nel quadro del più generale sindacato debole sugli atti di alta amministrazione, origina da una affermazione a tratti apodittica (l’amplissima discrezionalità di cui si ammanterebbero i golden powers) e da una insoddisfacente ricostruzione della vicenda procedimentale (secondo lo schema della scansione bifasica tra un prima e un dopo). Ponendo al centro della riflessione gli istituti della vincolatezza in concreto e della unitarietà funzionale del procedimento, il presente contributo intende rispondere ad un interrogativo principale: come si misura l’ampiezza della discrezionalità? La convinzione sta in ciò, che l’ampiezza della discrezionalità non può essere misurata tramite il solo metro della astratta fattispecie normativa. L’obiettivo ultimo è quindi quello di riarticolare il sindacato attorno all’irriducibile principio dell’effettività della tutela giurisdizional
Long-Term Motor and Cognitive Outcome of Deep Brain Stimulation in Patients With Parkinson Disease With a GBA1 Pathogenic Variant
Get PDFBackground and objectives: Deep brain stimulation (DBS) is an established treatment for Parkinson disease (PD). In patients carrying GBA1 variants (GBA-PD), concerns persist that DBS may accelerate cognitive decline. This study investigated the potential additive effects of GBA1 genotype and DBS on long-term motor and nonmotor outcomes. Methods: This multicenter retrospective, controlled, Italian study included 3 groups: DBS-treated PD patients either carrying or noncarrying GBA1 variants (DBS-nonGBA-PD and DBS-GBA-PD) and GBA-PD patients who fulfilled DBS criteria but eventually were not operated. As secondary aims, we assessed the clinical outcomes of DBS-GBA-PD stratified by GBA1 variant classes and by different DBS targets. Cognitive, motor, and other nonmotor features were collected at baseline and after 1, 3 and, when available, 5 years. Between-group comparisons used χ2 and Kruskal-Wallis tests with Bonferroni correction. Longitudinal changes were analyzed with linear mixed-effects models. Subgroup analyses were performed by GBA1 variant class and DBS target. Results: A total of 615 participants were included: 430 DBS-nonGBA-PD (age 57.4 ± 7.7 years, 32% female), 109 DBS-GBA-PD (age 53.5 ± 8.4 years, 38% female), and 76 nonDBS-GBA-PD (age 57.7 ± 8.1 years, 37% female). At baseline, groups were largely matched for clinical features. Longitudinally, both DBS groups showed marked motor improvement (dyskinesias, on-off phenomenon, and wearing-off, all p vs T0 < 0.001), a benefit which was absent in nonDBS-GBA-PD. At 5 years, dementia occurred more frequently in DBS-GBA-PD and nonDBS-GBA-PD compared with DBS-nonGBA-PD (25.5% vs 36.8% vs 10.8%, p < 0.001). Hallucinations and urinary problems increased in both GBA-PD groups than nonGBA-PD (p-between <0.001 and 0.02, respectively), regardless of DBS. No relevant differences emerged on stratification for variant classes or DBS targets, up to 3 years postsurgery. Discussion: Despite its retrospective design, this study supports DBS as a valid therapeutic option for GBA-PD, providing prolonged benefits on motor symptoms and quality of life. The accelerated cognitive decline observed in GBA-PD, compared with non-mutated participants, was similarly present in both operated and non-operated groups, suggesting it is driven by the genotype rather than DBS itself. Classification of evidence: This study provides Class III evidence that DBS does not worsen cognitive function in patients with GBA1-associated PD
Analysis of losses and edible and inedible by-products generated during harvesting, slaughtering and processing stages of broiler chickens under industrial conditions
No full textFood losses, as major sustainability obstacles, have raised enormous concerns in recent years due to their contribution not only to significant resource, climate, and environmental impacts but also to huge economic and nutritional impacts. While various studies have indicated that reducing food loss and waste could benefit food security and environmental sustainability, the extent of such benefits depends on the level of reduction and thus requires a good benchmark of the current loss and waste throughout the agri-food supply chain. Food losses occur at various points in the poultry supply chain, from production and harvest to distribution and consumption. A large proportion of unintentional food losses occurs during the ante-mortem phases. At the end of the growing phase, birds are caught, loaded into cages or coops, and transported to a processing plant that may be located either close to or far from the farm. Many problems may occur at these stages that potentially increase the rate of mortality, liveweight losses, and carcass downgrading. Before birds are caught and crated, feed is removed to allow time for the evacuation of intestinal contents. This reduces the incidence of faecal contamination of the carcass, which may occur during slaughtering. However, the length of fasting is important because it affects liveweight losses, which can impair carcass weight and yield. In the first 4–6 hours, weight loss in birds is mainly due to emptying of the gut, so carcass yield is not negatively influenced. After 6 hours, there are also losses in moisture and nutrients from body tissues, which reduce carcass weight and yield. During catching and crating operations, a certain level of trauma, such as haemorrhages, bruises, and broken bones, occurs and originates food losses at the slaughter plant, as these parts must be trimmed and discarded as by-products, and the remaining parts are downgraded and used as raw materials for further processing. In addition, trauma occurring during harvesting at the farm exacerbates pre-slaughter mortality. Indeed, birds that are dead on arrival (DOA) at the plant represent a complete loss of economic value. The birds may be exposed to a variety of potential stressors during transit, including the thermal demands of the transport microenvironment, acceleration, vibration, motion, impacts, fasting, withdrawal of water, social disruption, and noise. These factors cause adverse effects on the birds that may range from mild discomfort to death. Environmental conditions during transport and lairage of poultry have also been shown to affect live shrink and processing yield, especially because birds respond to the increased temperature by increasing panting, which alters water intake and body moisture loss profiles. At the time of slaughter, a certain percentage of broiler carcasses and parts are condemned by veterinary inspectors due to signs of pre-existing disease, severe injury, abnormality, or contamination, making the products unfit for human consumption
Machine learning for biodiversity: UAV-based flower detection as an indirect proxy for bee abundance
Get PDFPollination plays a crucial role in supporting agriculture and ecosystem functioning, making it an essential
ecosystem service provided by bees and other insects. However, bee populations are increasingly threatened by
habitat fragmentation, intensive agriculture, and climate change, among other threats. Improved monitoring of
critical habitat factors, such as flower cover, is crucial to restore pollinator populations. Traditional approaches,
such as field analyses, are often time-consuming and expensive, prompting the adoption of alternative methods
to achieve greater efficiency and cost-effectiveness. Here, we introduce a novel approach that incorporates
machine learning algorithms and optical images obtained from an unoccupied aerial vehicle (UAV). Using
machine learning methods on RGB UAV imagery enabled us to estimate flower cover in UAV-monitored areas
and make numerical inferences of wild bee pollinator abundance from those estimates.
Unlike our previous study, which relied on separate machine learning models for each study area, our
new method develops a single model that can automatically and efficiently recognize flower cover in various
grassland ecosystems to successively estimate bee abundance and diversity. In addiction to this main objective,
we also sought to determine which machine learning model would perform this important task best. The
machine learning models used, particularly the Gradient Boost Machine (GBM), highlighted the capability of
UAV RGB images combined with artificial intelligence to predict flower cover over time, which was highly
correlated with bee abundance and diversity.
This development represents an additional starting point for the use of machine learning and deep learning
techniques in biodiversity studies within AES systems
A Characterization of Basic Feasible Functionals Through Higher-Order Rewriting and Tuple Interpretations
No full textThe class of type-two basic feasible functionals (BFF2) is the analogue of FP (polynomial time functions) for type-2 functionals, that is, functionals that can take (first-order) functions as arguments. BFF2 can be defined through Oracle Turing Machines with running time bounded by second-order polynomials. On the other hand, higher-order term rewriting provides an elegant formalism for expressing higher-order computation. We address the problem of characterizing BFF2 by higher-order term rewriting. Various kinds of interpretations for first-order term rewriting have been introduced in the literature for proving termination and characterizing first-order complexity classes. In this paper, we consider a recently introduced notion of cost–size tuple interpretations for higher-order term rewriting and see second order rewriting as ways of computing type-2 functionals. We then prove that the class of functionals represented by higher-order terms admitting polynomially bounded cost–size interpretations exactly corresponds to BFF2
A Dual-Encoder framework for Enhancing Driving Behavior and Mission Profiling Characterization
No full text177Lu-PSMA vs. cabazitaxel in patients with castration-resistant prostate cancer: Real-world efficacy and safety data from the ARON-3 study
Get PDFBackground: Radioligand therapy with [177Lu]Lutetium-177-PSMA-617 (177Lu-PSMA) was recently introduced in clinical practice in the US, Latin America and in most European countries for progressive, metastatic castration-resistant prostate cancer (mCRPC). However, multicenter real-world data on cancer-control outcomes are scant. Methods: Real-word data from the ARON-3 collaboration in progressive mCRPC patients treated with 177Lu-PSMA vs. cabazitaxel were collected. A retrospective analysis was performed, including overall survival (OS), progression free survival (PFS), time to treatment failure (TTF) and PSA50/90 rates. Results: Data from 285 (50.1 %) patients receiving 177Lu-PSMA vs. 283 (49.9 %) cabazitaxel after one or two lines of ARPI and Docetaxel were analyzed. PSA50 and PSA90 rates were higher, and TTF and OS were significantly longer in 177Lu-PSMA patients, even after multivariable adjustment (p ≤ 0.01). This effect held true for most subgroups such as age < 70 and ≥ 70 years, ECOG 0-1, distant lymph nodes and one vs. two lines of prior ARPI. Incidence of grade 3-4 adverse events were comparable between both treatments (37 % vs. 43 % for 177Lu-PSMA vs. cabazitaxel cohort p = 0.5) but differed according to the type of adverse events. Sensitivity analyses with cross-over adjustment showed similar effects. Conclusions: Analyzing the currently largest real-world cohort comparing 177Lu-PSMA vs. cabazitaxel, we provided robust information of 177Lu-PSMA being at least equally effective or possibly even superior to cabazitaxel regarding cancer-control outcomes with reasonable side effects
Development of qPCR-based diagnostic assays for Xanthomonas arboricola pv. corylina early detection in Corylus avellana L.
No full textXanthomonas arboricola pv. corylina (Xac) is the causal agent of hazelnut bacterial blight, the most severe disease for coriliculture worldwide. Current Xac detection and identification methods rely on time-consuming diagnostic assays (e.g. microbiological, serological, biochemical and pathogenicity). Molecular diagnosis of Xac assay has been limited to a duplex PCR assay originally designed for X. arboricola pv. pruni, requiring modified thermal profiles to enhance sensitivity to the disadvantage of specificity. In 2023, efforts were made to develop a series of new molecular diagnostic methods (e.g. conventional PCR, qPCR and LAMP) based on the “region 2.4” specific to pathovar corylina. Despite that, to detect latent infections in asymptomatic tissues, the PCR assay typically used, although rapid, is not sufficiently specific. Furthermore, for the identification of X. arboricola, highly pathovar-specific and sensitive methods are not yet available except for pathogenicity testing on host plants. The study aimed to development and validated a reliable qPCR-based diagnostic protocol for the early and rapid detection of Xac in asymptomatic halzenut tissues, thereby improving disease prevention and management. Primers were designed based on ftsX and xopH genes, both specific for pv. corylina. Samples from symptomatic and asymptomatic hazelnut plant material were preliminarily tested. The qPCR assays demonstrated high sensitivity and specify, enabling consistent detection allowed to achieve encouraging results for Xac identification in asymptomatic and symptomatic plant material. However, it is necessary to deepen the genetic aspects on Xac virulence and to broaden the choice and type of molecular targets to prevent and control the disease
An augmented outdoor workout system for jogging and calisthenics support
Get PDFIn this paper we introduce M-AGEW (Magic AuGmentEd Workout), an Augmented Reality (AR) application that assists users during outdoor, high-dynamic workouts such as jogging and calisthenics. It is a client-server-based system with a proprietary data structure (WKAN) that dynamically defines sequences of workouts as finite state machines. M-AGEW adapts workout intensity dynamically based on real-time sensor data and overlays contextual AR feedback and guidance, including biometric readings and a virtual coaching avatar. The technology was created through a user-centric design process, supported by an initial user study and industrial partnership. We validate M-AGEW through a technology acceptance evaluation with professional athletes, reporting promising results in usability, enjoyment, and perceived usefulness. Our findings suggest that AR headsets can effectively enhance and supplement outdoor physical activity, offering a motivating alternative to standard fitness monitoring