University of Bologna

The possibility of pre-birth microbiota colonisation remains controversial in the scientific community. Due to the placenta’s characteristics in pigs, the umbilical cord is the sole way for mother-foetus microbial transmission to occur. Studies on this topic have demonstrated conflicting results; some of these discrepancies might be due to differences during sampling, DNA extraction, bioinformatics and data analysis. The aim of this study is to assess a workflow for characterising the umbilical cord blood microbial profile by adjusting for the contaminating sources of bacterial DNA during the extraction procedure. The results show that among 735 amplicon sequence variants (ASVs), 568 ASVs were contaminants, while 165 ASVs were true samples. Using this workflow, we could distinguish the contaminant ASVs introduced during bacterial DNA extraction and amplification. With the results of the present study, however, we cannot confirm the pre-birth bacterial transfer by the umbilical cord blood due to the lack of samples representative of the contaminants in the surrounding sampling environment. Nevertheless, the present study can be used as a reference to address low microbial biomass, particularly with umbilical cord blood.

Deformable Linear Objects (DLOs) such as cables, wires, ropes, and elastic tubes are numerously present both in domestic and industrial environments. Unfortunately, robotic systems handling DLOs are rare and have limited capabilities due to the challenging nature of perceiving them. Hence, we propose a novel approach named RT-DLO for real-time instance segmentation of DLOs. First, the DLOs are semantically segmented from the background. Afterward, a novel method to separate the DLO instances is applied. It employs the generation of a graph representation of the scene given the semantic mask where the graph nodes are sampled from the DLOs center-lines whereas the graph edges are selected based on topological reasoning. RT-DLO is experimentally evaluated against both DLO-specific and general-purpose instance segmentation deep learning approaches, achieving overall better performances in terms of accuracy and inference time.

In integer programming and combinatorial optimisation, people use the term "matheuristics" to refer to methods that are heuristic in nature, but draw on concepts from the literature on exact methods. We survey the literature on this topic, with a particular emphasis on matheuristics that yield both primal and dual bounds (i.e., upper and lower bounds in the case of a minimisation problem). We also make some comments about possible future developments.

GaN power transistors are being increasingly used in high-power and high-frequency electronic systems due to their high breakdown field, high carrier density, and good thermal conductivity. Despite these advantages, system durability of GaN-based power systems is hindered by the necessity to work at variable operating conditions. The necessary real-time monitoring of the load current is normally implemented by using external shunt resistors, yet the implementation of GaN-based isolated current sensor would be beneficial to the final power system in terms of space occupation as well as cost. This work describes the implementation of two Hall-effect devices in p-GaN technology, which can potentially be used as integrated current sensors in GaN monolithic implementation. These devices are experimentally characterized and compared in terms of sensitivity, offset, and input resistance. Some non-ideality effects are also outlined, identifying future research directions.

Binary Neural Networks (BNNs) use 1-bit weights and activations to efficiently execute deep convolutional neural networks on edge devices. Nevertheless, the binarization of the first layer is conventionally excluded, as it leads to a large accuracy loss. The few works addressing the first layer binarization, typically increase the number of input channels to enhance data representation; such data expansion raises the amount of operations needed and it is feasible only on systems with enough computational resources. In this work, we present a new method to binarize the first layer using directly the 8-bit representation of input data; we exploit the standard bit-planes encoding to extract features bit-wise (using depth-wise convolutions); after a re-weighting stage, features are fused again. The resulting model is fully binarized and our first layer binarization approach is model independent. The concept is evaluated on three classification datasets (CIFAR10, SVHN and CIFAR100) for different model architectures (VGG and ResNet) and, the proposed technique outperforms state of the art methods both in accuracy and BMACs reduction.

Herein, a simple, solvent‐free method to fabricate polymer‐encapsulated halide perovskite photoconductors is described. Dry mechanochemical synthesis is used to prepare CsPbBr3 in the presence of poly(butyl methacrylate) (PBMA). The resulting composite powder is then heated and pressed into a free‐standing disk with a thickness controlled by a metallic spacer ring. The disk can be laminated on a glass substrate patterned with interdigitated electrodes, resulting in a planar photoconductor device. The best photoconductive performance is obtained for disks that consist of 75 wt.% CsPbBr3 in PBMA, reaching a detectivity of ≈2 × 10¹¹ Jones. Moreover, by adjusting the thickness of the disk, narrowband detectors can be obtained due to charge collection narrowing. Depending on the thickness of the pressed disk, the position and width of the detectivity peak can be tuned. At last, the disks are tested as possible absorber materials for X‐ray detectors, where ow detection limit, and fast and linear response are measured for perovskite‐polymer disks with 50 wt.% perovskite content. This work shows a simple and versatile approach toward the fabrication of halide perovskite photodetectors, which can be carried out in air and without the use of solvents.

Importance Integrating video clips in the discharge process may enhance patient’s understanding and awareness of their condition and improve recall of discharge instructions. Objective To determine the effect of video clip-integrated discharge discussion on patient comprehension of atrial fibrillation (AF) and deep vein thrombosis (DVT), and their main complications (stroke and pulmonary embolism). Design Multicentre, pragmatic, parallel groups, randomised clinical trial, 1:1 randomisation. Setting Two Emergency Units of tertiary hospitals in Italy. Participants 144 adult patients (or their caregivers) discharged home with either AF or DVT. Interventions Participants in the study group were shown a clip related to their condition. The controlgroup received standard verbal instructions. All participants received standard written instructions. Main Outcomes and Measures Main outcome: knowledge of the diagnosis and its potential complication. Secondary outcomes: knowledge of the prescribed therapy, patient satisfaction, adherence rate to newly prescribed anticoagulants, incidence of stroke or pulmonary embolism at follow up. Results Mean score for primary outcome (range 0-18, higher score indicating greater knowledge) was 5.87 (95% CI, 5.02-6.72] in the control group and 8.28 (95% CI, 7.27-9.31) in the intervention group, a difference that was statistically significant (mean difference, -2.41; 95% CI, -3.73 to -1.09; p<0.001). Mean score for knowledge of the prescribed therapy (range 0-6, higher score indicating greater knowledge) was 2.98 (95% CI, 2.57-3.39) in the control group and 3.20 (95% CI, 2.73-3.67) in the study group (mean difference, -0.22; 95% CI, -0.84 to 0.39). Mean score for satisfaction (range 0-12, higher score indicating greater satisfaction) was 7.34 (95% CI, 6.45-8.23) in the control arm, whereas patients in the intervention arm had a mean score of 7.97 (95% CI, 7.15-8.78)(mean difference, -0.625; 95% CI -1.82 to 0.57). Adherence rate to newly prescribed anticoagulants was 80% (36/45) in the control group and 90.2% (46/51) in the intervention group. Among 109 patients reached at a median follow up of 21 (IQR 16-28) months, 5.55% (3/54) in the control arm and 1.82% (1/55) in the intervention arm had developed stroke or pulmonary embolism. Conclusions and Relevance In this trial, two clips shown at discharge, improved participants comprehension of AF and DVT. Physicians should consider integrating these inexpensive tools during the discharge process. Trial Registration ClinicalTrials.gov Identifier: NCT03734406

Availability of information about a good with uncertain quality can influence the way consumers perceive its quality, hence, their willingness to pay (WTP) for it. We present a study to investigate whether and to what extent WTP is impacted by the degree of information available to consumers who are exposed first to extrinsic and then intrinsic information regarding a variety of Italian wines. We implement linear mixed models in a Bayesian framework, which provides a flexible tool to account for different sources of heterogeneity, e.g. correlation within groups of observations and spatial correlation between participants sitting nearby. Based on data collected in Italy, results show that the availability of extrinsic and intrinsic information yields relevant changes in WTP, but this effect also depends on age, gender, drinking habits, wine quality, and connoisseurship of the agents. According to the findings, the analyzed wines cannot be considered search goods, although this might not hold for more experienced consumers.

Feature-based 3D reconstruction methods only work reliably for images with enough features (i.e., texture) that can be identified and matched to infer a depth map. Contradicting the core assumption of such methods, the 3D reconstruction of textureless objects remains challenging. This paper explores a simple solution to this problem, i.e., adding artificial texture to such objects. In particular, we equipped a multi-view stereo based inline computational imaging system with a pattern illumination module to compensate for the absence of texture. Comparisons of 3D reconstructions from acquisitions with and without projected patterns show an increase in accuracy when using the pattern illumination.

Background Leber’s hereditary optic neuropathy (LHON) is a mitochondrial disorder characterised by complex I defect leading to sudden degeneration of retinal ganglion cells. Although typically associated with pathogenic variants in mitochondrial DNA, LHON was recently described in patients carrying biallelic variants in nuclear genes DNAJC30 , NDUFS2 and MCAT . MCAT is part of mitochondrial fatty acid synthesis (mtFAS), as also MECR, the mitochondrial trans-2-enoyl-CoA reductase. MECR mutations lead to a recessive childhood-onset syndromic disorder with dystonia, optic atrophy and basal ganglia abnormalities. Methods We studied through whole exome sequencing two sisters affected by sudden and painless visual loss at young age, with partial recovery and persistent central scotoma. We modelled the candidate variant in yeast and studied mitochondrial dysfunction in yeast and fibroblasts. We tested protein lipoylation and cell response to oxidative stress in yeast. Results Both sisters carried a homozygous pathogenic variant in MECR (p.Arg258Trp). In yeast, the MECR-R258W mutant showed an impaired oxidative growth, 30% reduction in oxygen consumption rate and 80% decrease in protein levels, pointing to structure destabilisation. Fibroblasts confirmed the reduced amount of MECR protein, but failed to reproduce the OXPHOS defect. Respiratory complexes assembly was normal. Finally, the yeast mutant lacked lipoylation of key metabolic enzymes and was more sensitive to H 2 O 2 treatment. Lipoic Acid supplementation partially rescued the growth defect. Conclusion We report the first family with homozygous MECR variant causing an LHON-like optic neuropathy, which pairs the recent MCAT findings, reinforcing the impairment of mtFAS as novel pathogenic mechanism in LHON.

Background Differential diagnosis between uterine leiomyomas and sarcomas is challenging. Magnetic resonance imaging (MRI) represents the second‐line diagnostic method after ultrasound for the assessment of uterine masses. Objectives To assess the accuracy of MRI in the differential diagnosis between uterine leiomyomas and sarcomas. Search Strategy A systematic review and meta‐analysis was performed searching five electronic databases from their inception to June 2023. Selection Criteria All peer‐reviewed observational or randomized clinical trials that reported an unbiased postoperative histologic diagnosis of uterine leiomyoma or uterine sarcoma, which also comprehended a preoperative MRI evaluation of the uterine mass. Data Collection and Analysis Sensitivity, specificity, positive and negative likelihood ratios, diagnostic odds ratio, and area under the curve on summary receiver operating characteristic of MRI in differentiating uterine leiomyomas and sarcomas were calculated as individual and pooled estimates, with 95% confidence intervals (CI). Results Eight studies with 2495 women (2253 with uterine leiomyomas and 179 with uterine sarcomas), were included. MRI showed pooled sensitivity of 0.90 (95% CI 0.84–0.94), specificity of 0.96 (95% CI 0.96–0.97), positive likelihood ratio of 13.55 (95% CI 6.20–29.61), negative likelihood ratio of 0.08 (95% CI 0.02–0.32), diagnostic odds ratio of 175.13 (95% CI 46.53–659.09), and area under the curve of 0.9759. Conclusions MRI has a high diagnostic accuracy in the differential diagnosis between uterine leiomyomas and sarcomas.

Lightweight design is often assumed to be the leading strategy to improve the sustainability of parts produced by additive manufacturing. The present study confutes such an assumption by a cradle-to-gate life cycle assessment of different lightweight strategies applied to a specific case study in the medical field. In particular, a patient-specific finger splint made of polyamide is redesigned by means of generative design, topology optimization and lattice structures. The analysis investigates two markedly different deposition processes, namely Arburg plastic freeforming and fused filament fabrication. The former is carried out on an industrial-grade machine, while a desktop printer is used for the latter. This allows for observing the impact of the redesign in two quite distinct scenarios. Findings demonstrate that, since environmental impacts are mainly driven by building time, the adoption of automated design algorithms can be detrimental to the sustainability of the process. On the other hand, relevant benefits on environmental impacts were achieved by reducing the infill percentage of parts. The results of this work highlight the most relevant aspects which must be considered to limit environmental impacts when designing parts for deposition-based additive manufacturing. This information can be used by designers to drive weight reduction towards sustainability.

Various disconnected chord datasets are currently available for music analysis and information retrieval, but they are often limited by either their size, non-openness, lack of timed information, and interoperability. Together with the lack of overlapping repertoire coverage, this limits cross-corpus studies on harmony over time and across genres, and hampers research in computational music analysis (chord recognition, pattern mining, computational creativity), which needs access to large datasets. We contribute to address this gap, by releasing the Chord Corpus (ChoCo), a large-scale dataset that semantically integrates harmonic data from 18 different sources using heterogeneous representations and formats (Harte, Leadsheet, Roman numerals, ABC, etc.). We rely on JAMS (JSON Annotated Music Specification), a popular data structure for annotations in Music Information Retrieval, to represent and enrich chord-related information (chord, key, mode, etc.) in a uniform way. To achieve semantic integration, we design a novel ontology for modelling music annotations and the entities they involve (artists, scores, etc.), and we build a 30M-triple knowledge graph, including 4 K+ links to other datasets (MIDI-LD, LED).

With a proliferation of scholarly work focusing on populist, far-left, and far-right parties, questions have arisen about the correct ways to ideologically classify such parties. To ensure transparency and uniformity in research, the discipline could benefit from a systematic procedure. In this letter, we discuss how we have employed the method of ‘Expert-informed Qualitative Comparative Classification’ (EiQCC) to construct the newest version of The PopuList (3.0) – a database of populist, far-left, and far-right parties in Europe since 1989. This method takes into account the in-depth knowledge of national party experts while allowing for systematic comparative analysis across cases and over time. We also examine how scholars have made use of the previous versions of the dataset, explain how the new version of The PopuList differs from previous ones, and compare it to other data. We conclude with a discussion of the strengths and limitations of The PopuList dataset.

Accurate streamflow simulations rely on good estimates of the catchment-scale soil moisture distribution. Here, we evaluated the potential of Sentinel-1 backscatter data assimilation (DA) to improve soil moisture and streamflow estimates. Our DA system consisted of the Noah-MP land surface model coupled to the HyMAP river routing model and the water cloud model as backscatter observation operator. The DA system was set up at 0.01° resolution for two contrasting catchments in Belgium: i) the Demer catchment dominated by agriculture, and ii) the Ourthe catchment dominated by mixed forests. We present results of two experiments with an ensemble Kalman filter updating either soil moisture only or soil moisture and Leaf Area Index (LAI). The DA experiments covered the period January 2015 through August 2021 and were evaluated with independent rainfall error estimates based on station data, LAI from optical remote sensing, soil moisture retrievals from passive microwave observations, and streamflow measurements. Our results indicate that the assimilation of Sentinel-1 backscatter observations can partly correct errors in surface soil moisture due to rainfall errors and overall improve surface soil moisture estimates. However, updating soil moisture and LAI simultaneously did not bring any benefit over updating soil moisture only. Our results further indicate that streamflow estimates can be improved through Sentinel-1 DA in a catchment with strong soil moisture-runoff coupling, as observed for the Ourthe catchment, suggesting that there is potential for Sentinel-1 DA even for forested catchments.