The evolution of man–machine interaction: the role of human in Industry 4.0 paradigm

ndustry 4.0 is a new paradigm in the manufacturing world and it has deeply changed the Human–machine interaction. This paper focus is on the nature of this interaction, which is made possible thanks to the Internet of Things (IoT), and Cyber-Physical System (CPS). These Industry 4.0 key technologies are studied related to the standard Deming cycle, in order to underline the importance of Human–machine interaction. The Fourth Industrial Revolution involves several changes in the workforce’s key features. In this paper, a new perspective based on the centrality of humans is given in the new Industry era. The importance of the human factor will be deeply studied through the implementation of the ‘Sand Cone Model’. A new framework is proposed in order to explain the quality measures addiction on the workforce quality skills, and how it engraves on improving efficiency and effectiveness of an industrial process

The evolution of man–machine interaction: the role of human in Industry 4.0 paradigm

Industry 4.0 is a new paradigm in the manufacturing world and it has deeply changed the Human–machine interaction. This paper focus is on the nature of this interaction, which is made possible thanks to the Internet of Things (IoT), and Cyber-Physical System (CPS). These Industry 4.0 key technologies are studied related to the standard Deming cycle, in order to underline the importance of Human–machine interaction. The Fourth Industrial Revolution involves several changes in the workforce's key features. In this paper, a new perspective based on the centrality of humans is given in the new Industry era. The importance of the human factor will be deeply studied through the implementation of the 'Sand Cone Model'. A new framework is proposed in order to explain the quality measures addiction on the workforce quality skills, and how it engraves on improving efficiency and effectiveness of an industrial process

Surgical site infection after caesarean section. Space for post-discharge surveillance improvements and reliable comparisons

Surgical site infections (SSI) after caesarean section (CS) represent a substantial health system concern. Surveying SSI has been associated with a reduction in SSI incidence. We report the findings of three (2008, 2011 and 2013) regional active SSI surveillances after CS in community hospital of the Latium region determining the incidence of SSI. Each CS was surveyed for SSI occurrence by trained staff up to 30 post-operative days, and association of SSI with relevant characteristics was assessed using binomial logistic regression. A total of 3,685 CS were included in the study. A complete 30 day post-operation follow-up was achieved in over 94% of procedures. Overall 145 SSI were observed (3.9% cumulative incidence) of which 131 (90.3%) were superficial and 14 (9.7%) complex (deep or organ/space) SSI; overall 129 SSI (of which 89.9% superficial) were diagnosed post-discharge. Only higher NNIS score was significantly associated with SSI occurrence in the regression analysis. Our work provides the first regional data on CS-associated SSI incidence, highlighting the need for a post-discharge surveillance which should assure 30 days post-operation to not miss data on complex SSI, as well as being less labour intensive

Azimuthal correlation between beauty particles produced in 350 GeV/c π−\pi^{-}-Cu interactions

Using a sample of $10^8$ triggered events, produced in $350\, \hbox{GeV}/c$ $\pi^-$ interactions in a copper target, we have identified $26$ b\=b events. These include $13$ events where the decays of both $B$ and $\overline{B}$ are well reconstructed. We measure the azimuthal \hbox{correlation} between beauty particles, and compare our result with predictions based on perturbative QCD

Mapping targets for small nucleolar RNAs in yeast

Background: Recent analyses implicate changes in the expression of the box C/D class of small nucleolar RNAs (snoRNAs) in several human diseases. Methods: Here we report the identification of potential novel RNA targets for box C/D snoRNAs in budding yeast, using the approach of UV crosslinking and sequencing of hybrids (CLASH) with the snoRNP proteins Nop1, Nop56 and Nop58. We also developed a bioinformatics approach to filter snoRNA-target interactions for bona fide methylation guide interactions. Results: We recovered 241,420 hybrids, out of which 190,597 were classed as reproducible, high energy hybrids. As expected, the majority of snoRNA interactions were with the ribosomal RNAs (rRNAs). Following filtering, 117,047 reproducible hybrids included 51 of the 55 reported rRNA methylation sites. The majority of interactions at methylation sites were predicted to guide methylation. However, competing, potentially regulatory, binding was also identified. In marked contrast, following CLASH performed with the RNA helicase Mtr4 only 7% of snoRNA-rRNA interactions recovered were predicted to guide methylation. We propose that Mtr4 functions in dissociating inappropriate snoRNA-target interactions. Numerous snoRNA-snoRNA interactions were recovered, indicating potential cross regulation. The snoRNAs snR4 and snR45 were recently implicated in site-directed rRNA acetylation, and hybrids were identified adjacent to the acetylation sites. We also identified 1,368 reproducible snoRNA-mRNA interactions, representing 448 sites of interaction involving 39 snoRNAs and 382 mRNAs. Depletion of the snoRNAs U3, U14 or snR4 each altered the levels of numerous mRNAs. Targets identified by CLASH were over-represented among these species, but causality has yet to be established. Conclusions: Systematic mapping of snoRNA-target binding provides a catalogue of high-confidence binding sites and indicates numerous potential regulatory interactions

Measurements of charmed-meson production in interactions between 350 GeV/c π−\pi^- particles and nuclei

Charmed-meson production by $350$~GeV/$c$ {$\pi^-$} particles incident on copper and tungsten targets has been studied in the WA$92$ experiment, performed at the CERN $\Omega^\prime$ spectrometer. Results obtained are reported and discussed. Reconstruction of decays from the set ${\rm D}^0 \rightarrow {\rm K}^- \pi^+$, ${\rm D}^0 \rightarrow {\rm K}^- \pi^- \pi^+ \pi^+$, ${\rm D}^+ \rightarrow {\rm K}^- \pi^+ \pi^+$, ${{\rm D}_{\rm s}}^+ \rightarrow \phi \pi^+$ and charge conjugates has yielded a sample of $7280 \pm 108$ charmed mesons, produced with \xf > 0, \langle \xf \rangle = 0.18 and \langle {\pt}^2 \rangle = 1.86~{\rm (GeV/}c{\rm )}^2. Assuming a relationship $\sigma = \sigma_0 A^\alpha$ between the cross-section, $\sigma$, per nucleus of mass $A$ and the nucleonic cross-section, $\sigma_0$, the $\alpha$ value found for the detected charmed particles is $0.95 \pm 0.06 \pm 0.03$. Taking $\alpha = 1$, the measured cross-sections per nucleon for \xf > 0 production are $7.78 \pm 0.14 \pm 0.52$~$\mu$barn for ${\rm D}^0$/$\bar{\rm D}^0$, $3.28 \pm 0.08 \pm 0.29$~$\mu$barn for ${\rm D}^+$/${\rm D}^-$ and $1.29 \pm 0.16 \pm 0.33$~$\mu$barn for ${{\rm D}_{\rm s}}^+$/${{\rm D}_{\rm s}}^-$. Differential cross-sections with respect to \xf and {\pt}^2 have been determined for the various types of charmed meson, and particle-antiparticle asymmetries have been analysed

How to do an evaluation: pitfalls and traps

The recent literature is replete with papers evaluating computational tools (often those operating on 3D structures) for their performance in a certain set of tasks. Most commonly these papers compare a number of docking tools for their performance in cognate re-docking (pose prediction) and/or virtual screening. Related papers have been published on ligand-based tools: pose prediction by conformer generators and virtual screening using a variety of ligand-based approaches. The reliability of these comparisons is critically affected by a number of factors usually ignored by the authors, including bias in the datasets used in virtual screening, the metrics used to assess performance in virtual screening and pose prediction and errors in crystal structures used

How to do an evaluation: pitfalls and traps

The recent literature is replete with papers evaluating computational tools (often those operating on 3D structures) for their performance in a certain set of tasks. Most commonly these papers compare a number of docking tools for their performance in cognate re-docking (pose prediction) and/or virtual screening. Related papers have been published on ligand-based tools: pose prediction by conformer generators and virtual screening using a variety of ligand-based approaches. The reliability of these comparisons is critically affected by a number of factors usually ignored by the authors, including bias in the datasets used in virtual screening, the metrics used to assess performance in virtual screening and pose prediction and errors in crystal structures used