University of Modena and Reggio Emilia
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Position analysis of the tripod joint: An alternative approach
No full textThe position analysis, which is the most challenging phase of the kinematic analysis of a mechanism, was solved for the tripod joint, in exhaustive form, a few decades ago. The method proposed at the time was supposed to be able to find all possible assembly configurations of the joint. Regrettably, it becomes useless when the angle that parametrizes the position of one of the connected shafts reaches some specific values, which happens several times for each turn of the shaft; moreover, an error in the expression of a coefficient of a pivotal equation hampers adoption of the method. This paper presents a new procedure whose steepest step is finding the roots of a fourth order algebraic equation. It is shown that eight assembly configurations do exist for the adopted kinematic model of tripod joint, in the complex domain. The proposed procedure has a more direct approach than the previous one and is not affected by its singularities. Moreover, because no arbitrarily-selected movable reference frame is introduced, it leads to equations whose coefficients reveal the periodicity of the dependence of some parameters of the joint configuration on the angular position of one of the connected shafts. This means that some aspects of the tripod joint behavior can be hinted even without solving the equations. A numerical example shows application of the new procedure to a case study
Electrochemical and spectroscopic characterization of Co-neuroglobin: a bioelectrocatalyst for H2 production
Get PDFThe electronic absorption, MCD and RR spectra of the Co(III) and Co(II) derivatives of wild type human neuroglobin (Co-WT) and its C46A/C55A mutant (Co-C46AC55A) were thoroughly investigated and compared with those of the corresponding Fe species and of the few Co-substituted heme proteins characterized so far. In both oxidation states, Co-WT and Co-C46AC55A contain a low-spin six-coordinated Co ion, whose axial coordination positions appear to be occupied by the distal and proximal histidines and whose electronic properties are scarcely affected by the deletion of the C46-C55 disulfide bond. Both Co-WT and Co-C46AC55A feature negative E°’Co(III)/Co(II) values. Fe(III) to Co(III) swapping does not significantly alter the pH-dependence of their spectroscopic properties and E°’ values, indicating that no major changes occur in their regulating molecular factors. Most importantly, Co-WT and Co-C46AC55A can catalyze the reduction of H3O+ to H2, with onset potentials and overpotentials comparable to those of Co-porphyrin/polypeptide catalysts. The electrocatalytic efficiency of Co-WT and Co-C46AC55A for the development of H2 is slightly lower compared to six-coordinated aquo-His Co-Mb, although they are less affected by the presence of dioxygen
Citizenship, Math and Gender: Exploring Immigrant Students' Choice of Majors
Get PDFThis study examines the impact of host-country citizenship on immigrant students' choice of academic majors, using data from
an Italian university and incorporating characteristics of students' countries of origin. The analysis focuses on enrolment in
fields of study categorized by mathematical content. The findings reveal three main points: First, obtaining citizenship reduces
the likelihood of choosing math-related disciplines; second, this effect is more pronounced among women, further widening
the gender gap in math-intensive fields; and third, these gaps are larger among students from more gender-equal countries but
are less affected by the acquisition of citizenship. These results are supported by matching techniques, two-stage least squares,
and robustness and sensitivity analyses. Given that math-intensive fields are linked to higher earning potential, the findings
suggest that investment in mathematical skills may serve as a safeguard against labour market risks—a necessity that lessens
upon acquiring citizenship, especially for women. Although this shift could adversely affect future earnings, it also contributes
to a more even distribution of students across disciplines, potentially enhancing diversity in occupations where immigrants are
traditionally under-represented.This study examines the impact of host-country citizenship on immigrant students' choice of academic majors, using data from an Italian university and incorporating characteristics of students' countries of origin. The analysis focuses on enrolment in fields of study categorized by mathematical content. The findings reveal three main points: First, obtaining citizenship reduces the likelihood of choosing math-related disciplines; second, this effect is more pronounced among women, further widening the gender gap in math-intensive fields; and third, these gaps are larger among students from more gender-equal countries but are less affected by the acquisition of citizenship. These results are supported by matching techniques, two-stage least squares, and robustness and sensitivity analyses. Given that math-intensive fields are linked to higher earning potential, the findings suggest that investment in mathematical skills may serve as a safeguard against labour market risks-a necessity that lessens upon acquiring citizenship, especially for women. Although this shift could adversely affect future earnings, it also contributes to a more even distribution of students across disciplines, potentially enhancing diversity in occupations where immigrants are traditionally under-represented
State-of-the-art Review and Benchmarking of Barcode Localization Methods
Get PDFBarcodes, despite their long history, remain an essential technology in supply chain management. In addition, barcodes have found extensive use in industrial engineering, particularly in warehouse automation, component tracking, and robot guidance. To detect a barcode in an image, multiple algorithms have been proposed in the literature, with a significant increase of interest in the topic since the rise of deep learning. However, research in the field suffers from many limitations, including the scarcity of public datasets and code implementations which hinders the reproducibility and reliability of published results. For this reason, we developed ``BarBeR'' (Barcode Benchmark Repository), a benchmark designed for testing and comparing barcode detection algorithms. This benchmark includes the code implementation of various detection algorithms for barcodes, along with a suite of useful metrics. Among the supported localization methods, there are multiple deep-learning detection models, that will be used to assess the recent contributions of Artificial Intelligence to this field. In addition, we provide a large, annotated dataset of 8748 barcode images, combining multiple public barcode datasets with standardized annotation formats for both detection and segmentation tasks. Finally, we provide a thorough summary of the history and literature on barcode localization and share the results obtained from running the benchmark on our dataset, offering valuable insights into the performance of different algorithms when applied to real-world problems
Advantages and challenges of polymer-lipid hybrid nanoparticles for the delivery of biotech drugs
Get PDFPredicting employee attrition and explaining its determinants
Get PDFAn increased focus on utilizing data analytics to tackle human resource (HR) issues and make more informed and data-driven decisions is spreading in firms and public institutions. One of the major challenges faced by organizations is employee turnover, which can have negative impacts on productivity, performance, and overall corporate reputation. In light of these considerations, this study endeavors to predict employee attrition by deploying Machine Learning (ML) models on real-world data obtained from a prominent Italian financial corporation. Although the use of ML to predict attrition and investigate the main employers-employees features is documented in literature, what characterizes our study is the investigation of the crucial dimension of feature direction. Nonetheless, recognizing this directional aspect is pivotal for HR managers entrusted with making informed decisions. In our research, we employ the SHAP (SHapley Additive exPlanation) algorithm to not only identify feature contributions but also to assess their direction. Beyond mere algorithm implementation, our study interprets the outcomes within the specific context of HR decision-making. This comprehensive approach effectively highlights the inherent limitations of standalone algorithms, which may produce only partial results, capturing the importance of a feature, but missing its direction. Indeed, sometimes, while the feature is well known, its direction is somehow counterintuitive, thus requiring a deeper investigation and understanding. In a period like the present one, where the new production paradigms and the Covid-19 pandemic altered the consolidated labor market, new phenomena are emerging and only a profound understanding of the contextual novel dynamics can foster well-informed decision-making processes
Development and Implementation of an Ultrasound Wireless Technology Educational Program for Nursing Students: A Quality Improvement Project
Get PDFBackground: Training on the use of ultrasounds (US) is offered to nurses after their degree in specialization courses or in a work setting. When considering the positive impact of US on patient quality of care, this training should be offered to undergraduate nursing students. The aim of this quality improvement project was to assess the quality of nursing curricula by evaluating the effects of an ultrasound technology educational program (USTep) on nursing students’ knowledge, self-confidence, satisfaction and perceived usefulness of the training for the acquisition of US skills. Methods: 118 nursing students completed a 3-hour USTep, that combined a theoretical introduction with simulation training. Data were collected before and after the USTep, using a survey with closed and open-ended questions. Results: After the educational program, a net increase was seen in knowledge about US (pre-test 48.1% vs. post-test 93.4%, p < 0.00001) and in student self-confidence (pre-test m = 1.7 ± 0.9 vs. post-test m = 3.9 ± 0.8, p < 0.001). According to the participants, this training benefited the students (during their training and for future employment opportunities), the patients, and the profession. Lastly, 97% of the sample expressed satisfaction with the training experience. Conclusions: This quality improvement project shows that a 3-hour USTep improved undergraduate nursing students’ knowledge, self-confidence, and satisfaction