A fixed-target platform for serial femtosecond crystallography in a hydrated environment.

For serial femtosecond crystallography at X-ray free-electron lasers, which entails collection of single-pulse diffraction patterns from a constantly refreshed supply of microcrystalline sample, delivery of the sample into the X-ray beam path while maintaining low background remains a technical challenge for some experiments, especially where this methodology is applied to relatively low-ordered samples or those difficult to purify and crystallize in large quantities. This work demonstrates a scheme to encapsulate biological samples using polymer thin films and graphene to maintain sample hydration in vacuum conditions. The encapsulated sample is delivered into the X-ray beam on fixed targets for rapid scanning using the Roadrunner fixed-target system towards a long-term goal of low-background measurements on weakly diffracting samples. As a proof of principle, we used microcrystals of the 24 kDa rapid encystment protein (REP24) to provide a benchmark for polymer/graphene sandwich performance. The REP24 microcrystal unit cell obtained from our sandwiched in-vacuum sample was consistent with previously established unit-cell parameters and with those measured by us without encapsulation in humidified helium, indicating that the platform is robust against evaporative losses. While significant scattering from water was observed because of the sample-deposition method, the polymer/graphene sandwich itself was shown to contribute minimally to background scattering

Order and nFl Behavior in UCu4Pd

We have studied the role of disorder in the non-Fermi liquid system UCu4Pd using annealing as a control parameter. Measurement of the lattice parameter indicates that this procedure increases the crystallographic order by rearranging the Pd atoms from the 16e to the 4c sites. We find that the low temperature properties depend strongly on annealing. Whereas the non-Fermi liquid behavior in the specific heat can be observed over a larger temperature range after annealing, the clear non-Fermi liquid behavior of the resistivity of the unannealed sample below 10 K disappears. We come to the conclusion that this argues against the Kondo disorder model as an explanation for the non-Fermi liquid properties of both as-prepared and annealed UCu4Pd

Magnetic-Field Induced Quantum Critical Point in YbRh2_2Si2_2

We report low-temperature calorimetric, magnetic and resistivity measurements on the antiferromagnetic (AF) heavy-fermion metal YbRh$_2$Si$_2$ (${T_N =}$ 70 mK) as a function of magnetic field $B$. While for fields exceeding the critical value ${B_{c0}}$ at which ${T_N\to0}$ the low temperature resistivity shows an ${AT^2}$ dependence, a ${1/(B-B_{c0})}$ divergence of ${A(B)}$ upon reducing $B$ to ${B_{c0}}$ suggests singular scattering at the whole Fermi surface and a divergence of the heavy quasiparticle mass. The observations are interpreted in terms of a new type of quantum critical point separating a weakly AF ordered from a weakly polarized heavy Landau-Fermi liquid state.Comment: accepted for publication in Phys. Rev. Let

The impact of diabetes on multiple avoidable admissions: a cross-sectional study

Background Multiple admissions for ambulatory care sensitive conditions (ACSC) are responsible for an important proportion of health care expenditures. Diabetes is one of the conditions consensually classified as an ACSC being considered a major public health concern. The aim of this study was to analyse the impact of diabetes on the occurrence of multiple admissions for ACSC. Methods We analysed inpatient data of all public Portuguese NHS hospitals from 2013 to 2015 on multiple admissions for ACSC among adults aged 18 or older. Multiple ACSC users were identified if they had two or more admissions for any ACSC during the period of analysis. Two logistic regression models were computed. A baseline model where a logistic regression was performed to assess the association between multiple admissions and the presence of diabetes, adjusting for age and sex. A full model to test if diabetes had no constant association with multiple admissions by any ACSC across age groups. Results Among 301,334 ACSC admissions, 144,209 (47.9%) were classified as multiple admissions and from those, 59,436 had diabetes diagnosis, which corresponded to 23,692 patients. Patients with diabetes were 1.49 times (p < 0,001) more likely to be admitted multiple times for any ACSC than patients without diabetes. Younger adults with diabetes (18–39 years old) were more likely to become multiple users. Conclusion Diabetes increases the risk of multiple admissions for ACSC, especially in younger adults. Diabetes presence is associated with a higher resource utilization, which highlights the need for the implementation of adequate management of chronic diseases policies.NOVASaudeinfo:eu-repo/semantics/publishedVersio

From global to local: reshoring for sustainability

The UK clothing industry has seen the extensive offshoring of manufacturing, which has created fragmented global supply chains; these present a range of supply issues and challenges, including many related to sustainability. Reshoring is a reversion of a previous offshoring decision, thereby ‘bringing manufacturing back home’ (Gray et al. J Supply Chain Management 49(2):27–33, 2013), and can be motivated by increased costs and supply management problems. While not a new phenomenon, the reshoring of activities is growing in practice and there is an imperative for academic research (Fratocchi et al. J Purch Supply Manag 20:54–59, 2014). Through an in-depth longitudinal case study, this paper explores how sustainability can be addressed through reshoring; the studied UK-based clothing SME has strong principles and is explicitly committed to bringing its supply chain ‘home’. There is a recognised need for more OM research using a social lens (Burgess and Singh Oper Manag Res 5:57–68, 2012), so Social Network Theory (SNT) is employed to examine the reshoring decision-making process. SNT applies a relational, qualitative approach to understand the interactions between network actors, and focuses on the types and strengths of relationships and how they provide context for decisions (Galaskiewicz J Supply Chain Manag 47(1):4–8, 2011). The findings demonstrate the importance of socially complex, long-term relationships in managing a sustainable supply network. These relationships contribute to the resources that a firm can harness in its supply practices, and SNT extends this with its emphasis on the strength of ties with suppliers, and the trust, reciprocity and shared meanings it engenders. For the studied firm these advantages are derived through its localised supply chain, and collaborative supplier relationships, and its progressive reshoring of activities is integral to achieving its sustainability principles

Use of twitter data for waste minimisation in beef supply chain

Approximately one third of the food produced is discarded or lost, which accounts for 1.3 billion tons per annum. The waste is being generated throughout the supply chain viz. farmers, wholesalers/processors, logistics, retailers and consumers. The majority of waste occurs at the interface of retailers and consumers. Many global retailers are making efforts to extract intelligence from customer’s complaints left at retail store to backtrack their supply chain to mitigate the waste. However, majority of the customers don’t leave the complaints in the store because of various reasons like inconvenience, lack of time, distance, ignorance etc. In current digital world, consumers are active on social media and express their sentiments, thoughts, and opinions about a particular product freely. For example, on an average, 45,000 tweets are tweeted daily related to beef products to express their likes and dislikes. These tweets are large in volume, scattered and unstructured in nature. In this study, twitter data is utilised to develop waste minimization strategies by backtracking the supply chain. The execution process of proposed framework is demonstrated for beef supply chain. The proposed model is generic enough and can be applied to other domains as well

Artificial Intelligence in Supply Chain Operations Planning: Collaboration and Digital Perspectives

[EN] Digital transformation provide supply chains (SCs) with extensive accurate data that should be combined with analytical techniques to improve their management. Among these techniques Artificial Intelligence (AI) has proved their suitability, memory and ability to manage uncertain and constantly changing information. Despite the fact that a number of AI literature reviews exist, no comprehensive review of reviews for the SC operations planning has yet been conducted. This paper aims to provide a comprehensive review of AI literature reviews in a structured manner to gain insights into their evolution in incorporating new ICTs and collaboration. Results show that hybrization man-machine and collaboration and ethical aspects are understudied.This research has been funded by the project entitled NIOTOME (Ref. RTI2018-102020-B-I00) (MCI/AEI/FEDER, UE). 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