The importance of resource interaction in strategies for managing supply chain disruptions

The turbulent business environment highlights the need for strategies for mitigating, responding to, and recovering from (that is, managing) supply chain disruptions. Resources are central in these strategies but remain unspecified in the literature. This paper shows how the resource interaction approach (RIA) can help under-standing resources in this setting by acknowledging their interactive and networked nature. Based on a con-ceptual discussion that compares key assumptions within the supply chain risk management (SCRM) and supply chain risk resilience (SCRes) literatures with the RIA, we propose an alternative approach to strategies for managing supply chain disruptions. We challenge the SCRM and SCRes literatures by emphasizing interdepen-dence (as opposed to independence) and pointing to relationships as key resources in strategies for managing supply chain disruptions. Collaboration relying on an interplay between temporary and permanent organizing is suggested as a starting point instead of being just one of several alternative strategies

What is the recommended size of a Volume of Interest for cancellous bone ? A skeleton-based study

The study of the bone fracture is an important issue for oste- oporosis and car safety. The behavior of cancellous bone is strongly linked to the micro-architecture, the strain rate (Prot et al. 2015), and the specimen size Harrison & McHugh 2010). Numerical models are used in order to simulate the viscoelas- tic behavior up to the point of fracture propagation in cancellous bone. Finite element method (FEM) models based on micro-CT scans are currently the most popular approach. However, the results are dependent on the specimen size and the mesh den- sity, in addition to which the fracture analysis is time-consum- ing (Hambli 2013). Moreover, the variable architecture within a typical specimen limits the minimum sample size that will still provide reasonable architectural parameter values in comparison with the full specimen size. Indeed, a BV/TV variation up to 20% was found in the same specimen (ϕ = 7.85 mm) (Stauber et al. 2014). Skeleton-based models have already shown a great poten- tial for the efficient simulation of bone behavior and fracture. Cancellous bone geometry is based on nodes, beams, and plates (Stauber & Müller 2006), which is straightforward to implement from a skeleton. In this study, the effect of the Volume of Interest (VOI) size, within a sample, on the evaluation of cancellous bone architec- tural parameters from the skeletonized model will be presented. The aim was to furnish recommendations for the sample size for further numerical simulations

Fracture characterization in cancellous bone specimens via surface difference evaluation of 3D registered pre- and post-compression micro-CT scans

In recent years, increasingly stringent passenger vehicle safety requirements have led to a renewed interest in the fracture properties of bone. It has been shown that can- cellous bone architecture is strongly linked to its overall behavior (Follet et al. 2011; Prot et al. 2015). Micro- fracture mechanisms have been resolved by time- consuming direct microscopy (Prot et al. 2012) or by the use of calcein (Lambers et al. 2014; Hernandez et al. 2014). Furthermore, the application of CT scanners, along with the development of registration algorithms, has allowed separated portions of fractured specimen to be registered to the pre-compression scan so as to quantify the differ- ence between 3D shapes as a mean to characterize the fracture behavior (Tassani & Matsopoulos 2014). How- ever, this method is operator-dependent in the case of multiple fracture zone identification and requires suffi- cient deformation of the specimen to obtain distinct reg- istration sets. In addition, built-in micro-compression testers, developed by CT scanner manufacturers, are limited to loading at low levels of strain rate, which does not allow measurement over a range that is representative of daily life. The goal of this study was to identify distinct fracture patterns based on micro-CT scans of cancellous bone specimens, loaded over a large range of strain rates, without the need for specimens that have broken into separate pieces

On the absorption spectrum and stability of Ag32+ in aqueous solution

Pulse radiolysis results suggest that the very first steps of silver aggregation in water involve the formation of Ag32+. The authors present a mixed classical quantum simulation of the absorption spectrum of this aggregate which is in agreement with the exptl. spectrum. The formation and structure of this aggregate are discussed with the help of addnl. Monte Carlo and ab initio calcns. The results tend to confirm the formation of Ag32+

A vision transformer-based framework for knowledge transfer from multi-modal to mono-modal lymphoma subtyping models

Determining lymphoma subtypes is a crucial step for better patients treatment targeting to potentially increase their survival chances. In this context, the existing gold standard diagnosis method, which is based on gene expression technology, is highly expensive and time-consuming making difficult its accessibility. Although alternative diagnosis methods based on IHC (immunohistochemistry) technologies exist (recommended by the WHO), they still suffer from similar limitations and are less accurate. WSI (Whole Slide Image) analysis by deep learning models showed promising new directions for cancer diagnosis that would be cheaper and faster than existing alternative methods. In this work, we propose a vision transformer-based framework for distinguishing DLBCL (Diffuse Large B-Cell Lymphoma) cancer subtypes from high-resolution WSIs. To this end, we propose a multi-modal architecture to train a classifier model from various WSI modalities. We then exploit this model through a knowledge distillation mechanism for efficiently driving the learning of a mono-modal classifier. Our experimental study conducted on a dataset of 157 patients shows the promising performance of our mono-modal classification model, outperforming six recent methods from the state-of-the-art dedicated for cancer classification. Moreover, the power-law curve, estimated on our experimental data, shows that our classification model requires a reasonable number of additional patients for its training to potentially reach identical diagnosis accuracy as IHC technologies

An impact model to understand and improve work-life balance in early-career researchers in radiation oncology.

Purpose The COVID-19 pandemic had a substantial effect on mental health and work productivity of early-career researchers working in Radiation Oncology (RO). However, the underlying mechanisms of these effects are unclear. The aim of the current qualitative study was therefore to achieve a better understanding of how these effects arose and could be managed in the future. Methods This study was conducted jointly by RO and qualitative health researchers. Data was collected in four online Focus Groups with 6-11 RO researchers (total N = 31) working in Europe. The transcripts were analysed through a qualitative cross-impact analysis. Results Causal relations were identified between seventeen variables that depict the impact of disrupted working conditions. Mental health and work productivity were indeed the most important affected variables, but relations between variables towards these impacts were complex. Relations could either be positive or negative and direct or indirect, leading to a cascade of interrelated events which are highly personal and could change over time. We developed the model 'impact of disrupted working conditions' depicting the identified variables and their relations, to allow more individual assessment and personalised solutions. Conclusion The impacts of disrupted working conditions on RO researchers varied due to the complexity of interrelated variables. Consequently, collective actions are not sufficient, and a more personal approach is needed. Our impact model is recommended to help guide conversations and reflections with the aim of improving work/life balance. The participants showed high levels of personal responsibility towards their own mental health and work productivity. Although being an individual issue, a collective responsibility in developing such approaches is key due to the dependency on organizational variables

An impact model to understand and improve work-life balance in early-career researchers in radiation oncology

Purpose: The COVID-19 pandemic had a substantial effect on mental health and work productivity of early-career researchers working in Radiation Oncology (RO). However, the underlying mechanisms of these effects are unclear. The aim of the current qualitative study was therefore to achieve a better understanding of how these effects arose and could be managed in the future.Methods: This study was conducted jointly by RO and qualitative health researchers. Data was collected in four online Focus Groups with 6-11 RO researchers (total N = 31) working in Europe. The transcripts were analysed through a qualitative cross-impact analysis.Results: Causal relations were identified between seventeen variables that depict the impact of disrupted working conditions. Mental health and work productivity were indeed the most important affected variables, but relations between variables towards these impacts were complex. Relations could either be positive or negative and direct or indirect, leading to a cascade of interrelated events which are highly personal and could change over time. We developed the model 'impact of disrupted working conditions' depicting the identified variables and their re-lations, to allow more individual assessment and personalised solutions.Conclusion: The impacts of disrupted working conditions on RO researchers varied due to the complexity of interrelated variables. Consequently, collective actions are not sufficient, and a more personal approach is needed. Our impact model is recommended to help guide conversations and reflections with the aim of improving work/life balance. The participants showed high levels of personal responsibility towards their own mental health and work productivity. Although being an individual issue, a collective responsibility in devel-oping such approaches is key due to the dependency on organizational variables

Torula yeast in the diet of Atlantic salmon Salmo salar and the impact on growth performance and gut microbiome

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Ma Orthologous Genes in Prunus spp. Shed Light on a Noteworthy NBS-LRR Cluster Conferring Differential Resistance to Root-Knot Nematodes

Root-knot nematodes (RKNs) are considerable polyphagous pests that severely challenge plants worldwide and especially perennials. The specific genetic resistance of plants mainly relies on the NBS-LRR genes that are pivotal factors for pathogens control. In Prunus spp., the Ma plum and RMja almond genes possess different spectra for resistance to RKNs. While previous works based on the Ma gene allowed to clone it and to decipher its peculiar TIR-NBS-LRR (TNL) structure, we only knew that the RMja gene mapped on the same chromosome as Ma. We carried out a high-resolution mapping using an almond segregating F2 progeny of 1448 seedlings from resistant (R) and susceptible (S) parental accessions, to locate precisely RMja on the peach genome, the reference sequence for Prunus species. We showed that the RMja gene maps in the Ma resistance cluster and that the Ma ortholog is the best candidate for RMja. This co-localization is a crucial step that opens the way to unravel the molecular determinants involved in the resistance to RKNs. Then we sequenced both almond parental NGS genomes and aligned them onto the RKN susceptible reference peach genome. We produced a BAC library of the R parental accession and, from two overlapping BAC clones, we obtained a 336-kb sequence encompassing the RMja candidate region. Thus, we could benefit from three Ma orthologous regions to investigate their sequence polymorphism, respectively, within plum (complete R spectrum), almond (incomplete R spectrum) and peach (null R spectrum). We showed that the Ma TNL cluster has evolved orthologs with a unique conserved structure comprised of five repeated post-LRR (PL) domains, which contain most polymorphism. In addition to support the Ma and RMja orthologous relationship, our results suggest that the polymorphism contained in the PL sequences might underlie differential resistance interactions with RKNs and an original immune mechanism in woody perennials. Besides, our study illustrates how PL exon duplications and losses shape TNL structure and give rise to atypical PL domain repeats of yet unknown role

Leadership for change

This edited volume reveals how the journey of transformation at the University of the Free State (UFS) became interwoven with student leadership development and global learning. The UFS initiated two intersecting co-curricular programmes, namely, the First-Year Leadership for Change (F1L4C) programme in 2010; and the triennial Global Leadership Summit (GLS) in 2012. Although these programmes changed over time, their core focus remained to be the development of transformational student leaders through the creation of global learning spaces. From its inception in 2010 to the last GLS in 2018, the UFS global learning project involved 780 students and 259 staff members from 109 institutions, across four continents. The goal of this edited volume is to create a deeper understanding of how the UFS F1L4C and GLS programmes enhanced student leadership development through global learning, especially in the context of higher education transformation