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User-centered logistics that aim at customer satisfaction are gaining importance because of growing e-commerce and home deliveries. Customer satisfaction can be strongly increased by offering narrow delivery time windows. However, there is a tradeoff for the logistics provider because user-friendly delivery time windows might decrease operational flexibility. Against this background, we study the vehicle routing problem with multiple time windows (VRPMTW) that determines a set of optimal routes such that each customer is visited once within one out of several time windows. We present a large neighborhood search–based metaheuristic for the VRPMTW that contains a dynamic programming component to optimally select a time window for each customer on a route, and we present computationally efficient move descriptors for all search operators. We evaluate the performance of our algorithm on the Belhaiza instance set for the objectives of minimizing traveled distance and duration. For the former objective, we provide new best-known solutions for 9 of 48 instances, and for the latter, we provide new best-known solutions for 13 of 48 instances. Overall, our algorithm provides the best average solution quality over the full benchmark set among all available algorithms. Furthermore, we design new benchmark instances that reflect planning tasks in user-centered last-mile logistics. Based on these, we present managerial studies that show the benefit of our algorithm for practitioners and allow to derive insights on how to offer time windows to customers. We show that offering multiple time windows can be economically beneficial for the logistics service providers and increases customer flexibility simultaneously.

In this paper, we propose a general algorithmic framework for rotating workforce scheduling. We develop a graph representation that allows to model a schedule as a Eulerian cycle of stints, which we then use to derive a problem formulation that is compact toward the number of employees. We develop a general branch-and-cut framework that solves rotating workforce scheduling in its basic variant, as well as several additional problem variants that are relevant in practice. These variants comprise, among others, objectives for the maximization of free weekends and the minimization of employees. Our computational studies show that the developed framework constitutes a new state of the art for rotating workforce scheduling. For the first time, we solve all 6,000 instances of the status quo benchmark for rotating workforce scheduling to optimality with an average computational time of 0.07 seconds and a maximum computational time of 2.53 seconds. These results reduce average computational times by more than 99% compared with existing methods. Our algorithmic framework shows consistent computational performance, which is robust across all studied problem variants. Summary of Contribution: This paper proposes a novel exact algorithmic framework for the well-known rotating workforce scheduling problem (RWSP). Although the RWSP has been extensively studied in different problem variants and for different exact and heuristic solution approaches, the presented algorithmic framework constitutes a new state-of-the-art for the RWSP that solves all known benchmark sets to optimality and improves on the current state-of-the-art by orders of magnitude with respect to computational times, especially for large-scale instances. The paper is both of methodological value for researchers and of high interest for practitioners. For researchers, the presented framework is amenable for various problem variants and provides a common ground for further studies and research. For practitioners and software developers, low computational times of a few seconds allows the framework to be to embedded into personnel scheduling software.

Journal of sustainable metallurgy (2022). doi:10.1007/s40831-022-00642-5, Published by Springer, Berlin

Aspergillus fumigatus is an environmental saprobe and opportunistic human fungal pathogen. Despite an estimated annual occurrence of more than 300,000 cases of invasive disease worldwide, a comprehensive survey of the genomic diversity present in A. fumigatus-including the relationship between clinical and environmental isolates and how this genetic diversity contributes to virulence and antifungal drug resistance-has been lacking. In this study we define the pan-genome of A. fumigatus using a collection of 300 globally sampled genomes (83 clinical and 217 environmental isolates). We found that 7,563 of the 10,907 unique orthogroups (69%) are core and present in all isolates and the remaining 3,344 show presence/absence of variation, representing 16-22% of the genome of each isolate. Using this large genomic dataset of environmental and clinical samples, we found an enrichment for clinical isolates in a genetic cluster whose genomes also contain more accessory genes, including genes coding for transmembrane transporters and proteins with iron-binding activity, and genes involved in both carbohydrate and amino-acid metabolism. Finally, we leverage the power of genome-wide association studies to identify genomic variation associated with clinical isolates and triazole resistance as well as characterize genetic variation in known virulence factors. This characterization of the genomic diversity of A. fumigatus allows us to move away from a single reference genome that does not necessarily represent the species as a whole and better understand its pathogenic versatility, ultimately leading to better management of these infections.

Background: Mucorales are opportunistic pathogens that can cause life-threatening diseases predominantly in immunocompromised patients. Objectives: This study aimed to investigate the frequency, seasonal variation and antifungal susceptibility of pathogenic Mucorales in the soil collected from seven hospitals in Urmia, Iran, between November 2017 and July 2018 in four different seasons. Methods: Mucorales isolates obtained from soil were characterised based on conventional and molecular assays. In addition, in vitro antifungal susceptibility was performed using the CLSI M38Ed3 procedure. Results: Out of 196 tested soil samples, 80 (40.8) samples were positive for mucoralean fungi. Rhizopus arrhizus var. arrhizus (n = 47) was the most frequent species followed by Mucor circinelloides (n = 21) and Cunninghamella echinulata (n = 6). A seasonal variation in the frequency of Mucorales in soil was detected with a maximum of culture-positive soil samples detected in wet autumn (43.2) followed by winter (23.4), summer (19.7) and spring (13.6). In vitro antifungal susceptibility testing for 80 environmental isolates exhibited MIC of â�¤2 I¼g/ml for amphotericin B indicating the smallest range of MIC variation among the tested Mucorales (range: 0.125â��2 I¼g/ml). Among the azoles, posaconazole was the most effective antifungals (GM MIC, 0.724 I¼g/ml). Conclusions: We considered associations of species and seasonal frequencies between soil mucoralean fungi and mucormycosis. The effect of opportunistic Mucorales dominating in the soil and prevalent causative agents of mucormycosis in Iran reported in the literatures but more comprehensive studies are needed to confirm this conclusion. © 2021 Wiley-VCH GmbH

We present a case of Kluyveromyces marxianus keratitis nine months after Descement's membrane endothelial keratoplasty (DMEK) in a patient with Fuchs endothelial disease. Endothelial scraping revealed this rare yeast infection at the interface between graft and host cornea. Immediate antifungal treatment with intracameral and corneal intrastromal injections of voriconazole and amphotericin B remained unsuccessful, requiring penetrating keratoplasty. This case highlights the challenging management of keratomycosis in patients with endothelial grafts.

International audience; Scientific communication is facilitated by a data-driven, scientifically sound taxonomy that considers the end-user's needs and established successful practice. Previously (Geiser et al. 2013; Phytopathology 103:400-408. 2013), the Fusarium community voiced near unanimous support for a concept of Fusarium that represented a clade comprising all agriculturally and clinically important Fusarium species, including the F. solani Species Complex (FSSC). Subsequently, this concept was challenged by one research group (Lombard et al. 2015 Studies in Mycology 80: 189-245) who proposed dividing Fusarium into seven genera, including the FSSC as the genus Neocosmospora, with subsequent justification based on claims that the Geiser et al. (2013) concept of Fusarium is polyphyletic (Sandoval-Denis et al. 2018; Persoonia 41:109-129). Here we test this claim, and provide a phylogeny based on exonic nucleotide sequences of 19 orthologous protein-coding genes that strongly support the monophyly of Fusarium including the FSSC. We reassert the practical and scientific argument in support of a Fusarium that includes the FSSC and several other basal lineages, consistent with the longstanding use of this name among plant pathologists, medical mycologists, quarantine officials, regulatory agencies, students and researchers with a stake in its taxonomy. In recognition of this monophyly, 40 species recently described as Neocosmospora were recombined in Fusarium, and nine others were renamed Fusarium. Here the global Fusarium community voices strong support for the inclusion of the FSSC in Fusarium, as it remains the best scientific, nomenclatural and practical taxonomic option available.

Free-floating car sharing (FFCS) systems are a promising concept to reduce the traffic volume in cities. However, spatial and temporal mismatches of supply and demand require a relocation of rental cars in order to avoid low degrees of utilization. Here, especially user-based relocation strategies seem to be promising to increase utilization in a cost-efficient manner. However, a thorough optimization-based assessment of user-based relocation strategies for FFCS systems is still missing. In this paper, we introduce an integer program that optimizes the assignment of user-based relocation strategies in FFCS fleets. We develop a graph representation that allows to reformulate the problem as a k-disjoint shortest paths problem and propose an exact algorithm to solve large-size instances. We show that this algorithm can solve real-world instances within a few milliseconds as well as instances with up to 100,000 customers and 10,000 vehicles in a few minutes. Furthermore, we present a case study based on real-world data and derive managerial insights on user-based relocation strategies. Our results reveal an upper bound on the benefit of user-based relocation strategies and demonstrate that the employment of such strategies can increase the number of fulfilled rental requests by 21%, while increasing the operator’s revenue by 10%.

The European Union is aiming at a circular economy and increased resource efficiency, which requires a waste management at the end-of-life of products. This is especially challenging for new and innovative products for which no recycling infrastructure exists so far. Wind power plants are such a product, for which large amounts of waste are expected within the next years as more and more plants reach their end-of-life. Especially the end-of-life rotor blades of wind power plants pose challenges with regard to waste management, since treatment options for the installed glass and carbon fiber reinforced plastics are still in a development stage. Moreover, material specific characteristics and technical aspects require separate treatment of these materials. To plan efficient treatment infrastructure, detailed knowledge on future waste streams is required. Against this background, this paper aims at estimating the mass of glass and carbon fiber reinforced plastic waste from rotor blades. To do so, we derive material specific weight functions and material specific shares to calculate the amount of installed glass and carbon fiber reinforced plastics in rotor blades. We apply normally distributed life times to project the calculated installed masses into the future and account for uncertainties within a simulation study. The estimation model is applied to a dataset of wind power plants within the European Union. Based on the considered dataset, we estimate that 570 [Mt] of fiber reinforced plastic waste will occur between 2020 and 2030 in the European Union of which 18 [Mt] are carbon fiber reinforced plastic waste.

Production planners in the non-ferrous metal industry face an inherent combinatorial complexity of the metal production process within a fast-changing market environment. Herein, we study the benef...

International audience; Magnusiomyces clavatus and Magnusiomyces capitatus are emerging yeasts with intrinsic resistance to many commonly used antifungal agents. Identification is difficult, and determination of susceptibility patterns with commercial and reference methods is equally challenging. For this reason, few data on invasive infections by Magnusiomyces spp. are available. Our objectives were to determine the epidemiology and susceptibility of Magnusiomyces isolates from bloodstream infections (BSI) isolated in Germany and Austria from 2001 to 2020. In seven institutions, a total of 34 Magnusiomyces BSI were identified. Identification was done by internal transcribed spacer (ITS) sequencing and matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS). Antifungal susceptibility was determined by EUCAST broth microdilution and gradient tests. Of the 34 isolates, M. clavatus was more common (n = 24) than M. capitatus (n = 10). BSI by Magnusiomyces spp. were more common in men (62%) and mostly occurred in patients with hemato-oncological malignancies (79%). The highest in vitro antifungal activity against M. clavatus/M. capitatus was observed for voriconazole (MIC50, 0.03/0.125 mg/L), followed by posaconazole (MIC50, 0.125/0.25 mg/L). M. clavatus isolates showed overall lower MICs than M. capitatus. With the exception of amphotericin B, low essential agreement between gradient test and microdilution was recorded for all antifungals (0 to 70%). Both species showed distinct morphologic traits on ChromAgar Orientation medium and Columbia blood agar, which can be used for differentiation if no MALDI-TOF MS or molecular identification is available. In conclusion, most BSI were caused by M. clavatus. The lowest MICs were recorded for voriconazole. Gradient tests demonstrated unacceptably low agreement and should preferably not be used for susceptibility testing of Magnusiomyces spp.

Construction and demolition waste (CDW) constitutes the biggest share of all waste generated. In addition to the environmental advantages, CDW recycling provides also high resource conservation benefits if used as recycled aggregates. Integrated forecasting of demolition and construction activities is crucial for quantifying and reconciling future supply and demand. While spatial characteristics are significant to minimize transportation costs, temporal aspects and material characteristic are important to regard for the development of the urban stock over time. This paper presents a Dynamic-Locational MFA as a model that integrates spatial, temporal and CDW material characteristics into material flow analysis at the demand and supply side. The relevant drivers of construction and demolition activities are defined in order to derive the required equations. Also, the empirical analysis is used to conclude the parameters and demonstrate the model on a real case study. Hence, the synergies between the recycling and construction activities are identified and the supply and demand of materials can be reconciled. The outcomes are not only important in terms of resource efficiency, but also help in anticipating and planning the restructuring of the value chain of the construction sector, such as the locations and capacities of concrete and recycling plants.

Green chemistry (2022). doi:10.1039/D2GC02244C, Published by Royal Society of Chemistry, Cambridge

Magnusiomyces clavatus and Magnusiomyces capitatus are emerging yeasts with intrinsic resistance to many commonly used antifungal agents. Identification is difficult, and determination of susceptibility patterns with commercial and reference methods is equally challenging. For this reason, few data on invasive infections by

Rare invasive fungal infections are increasingly emerging in hosts with predisposing factors such as immunodeficiency. Their timely diagnosis remains difficult, as their clinical picture may initially mimic infections with more common fungal species and species identification may be difficult with routine methods or may require time-consuming subcultures. This often results in ineffective drug administration and fatal outcomes. We report on a patient in their early twenties with mixed cellularity classical Hodgkin lymphoma with a disseminated Trichosporon asahii (T. asahii) infection. Even though pathogen detection and identification was possible via the standard procedure consisting of culture followed by matrix-assisted laser desorption ionisation–time of flight (MALDI-TOF) mass spectrometry, the patient passed away in the course of multi organ failure. Herein, we report on a retrospectively applied experimental diagnostic fungal PCR-analysis used on an EDTA blood sample and consisting of two pan-fungal reactions and seven branch-specific reactions. Regarding invasive T. asahii infection, this PCR array could considerably shorten time to diagnosis and switch to a targeted therapy with triazoles.

Electric commercial vehicles can contribute significantly to sustainable transportation. However, they are still perceived as being less economically viable than internal combustion engine vehicles. To this end, we analyze the deployment of electric commercial vehicles in retail mid-haul logistics fleets for current and future technology scenarios. We develop a novel assessment methodology that combines total cost of ownership calculations with a rich location-routing model. We consider integrated strategic network design and operational routing decisions over a multi-period time horizon, accounting for mixed fleets of electric and conventional vehicles and battery degradation. To solve this problem, we develop a novel matheuristic that embeds a state-of-the-art metaheuristic to take operational routing decisions. With this framework, we analyze a possible transition towards electrified logistics fleets. Starting with a real-world case, we perform sensitivity analyses based on a technology roadmap and further network structures. We discuss cost structures, the time-dependent nature of investment decisions, operational characteristics, and potential emissions savings. We show that in certain cases an electrification of mid-haul logistics fleets is operationally feasible, economically viable, and provides environmental advantages.

Fungal eye infections can lead to loss of vision and blindness. The disease is most prevalent in the tropics, although case numbers in moderate climates are increasing as well. This study aimed to determine the dominating filamentous fungi causing eye infections in Germany and their antifungal susceptibility profiles in order to improve treatment, including cases with unidentified pathogenic fungi. As such, we studied all filamentous fungi isolated from the eye or associated materials that were sent to the NRZMyk between 2014 and 2020. All strains were molecularly identified and antifungal susceptibility testing according to the EUCAST protocol was performed for common species. In total, 242 strains of 66 species were received. Fusarium was the dominating genus, followed by Aspergillus, Purpureocillium, Alternaria, and Scedosporium. The most prevalent species in eye samples were Fusarium petroliphilum, F. keratoplasticum, and F. solani of the Fusarium solani species complex. The spectrum of species comprises less susceptible taxa for amphotericin B, natamycin, and azoles, including voriconazole. Natamycin is effective for most species but not for Aspergillus flavus or Purpureocillium spp. Some strains of F. solani show MICs higher than 16 mg/L. Our data underline the importance of species identification for correct treatment.

The genus Sporothrix contains both species pathogenic to humans and animals as well as environmental fungi. S. humicola, a member of the latter S. pallida clade, has previously been reported only from soil. We have isolated this dimorphic fungus from multiple cutaneous lesions in two endangered marsupials native to Tasmania. Clinical appearance resembled cutaneous sporotrichosis, highlighting the principle pathogenic potential. Identification was based on partial ITS, β-tubulin and calmodulin gene sequencing. Keywords: Sporothrix humicola, Eastern quoll, Dasyurus viverrinus, Dermatomycosis, MALDI-TOF MS

Mucormycoses are life-threatening infections that affect patients suffering from immune deficiencies. We performed phagocytosis assays confronting various strains of Lichtheimia species with alveolar macrophages, which form the first line of defence of the innate immune system. To investigate 17 strains from four different continents in a comparative fashion, transmitted light and confocal fluorescence microscopy was applied in combination with automated image analysis. This interdisciplinary approach enabled the objective and quantitative processing of the big volume of image data. Applying machine-learning supported methods, a spontaneous clustering of the strains was revealed in the space of phagocytic measures. This clustering was not driven by measures of fungal morphology but rather by the geographical origin of the fungal strains. Our study illustrates the crucial contribution of machine-learning supported automated image analysis to the qualitative discovery and quantitative comparison of major factors affecting host-pathogen interactions. We found that the phagocytic vulnerability of Lichtheimia species depends on their geographical origin, where strains within each geographic region behaved similarly, but strongly differed amongst the regions. Based on this clustering, we were able to also classify clinical isolates with regard to their potential geographical origin.

Battery electric vehicles as well as renewable energy are two key factors that can contribute significantly to sustainable development within the transportation and the energy sector. However, the market introduction of these technologies results in new challenges, especially with regard to the interaction between both sectors. So far, neither location models for charging stations nor load flow models for the electrical grid consider these interactions sufficiently. Thus, an integration of planning problems from both sectors is needed in order to exploit potential synergies and to avoid negative impacts. In this paper, we present such an integrated planning approach to locate charging infrastructure for battery electric vehicles considering interactions with the electrical grid. Herein, we combine a charging station location model and a power flow model with integrated energy stores. We aim at determining a network configuration that satisfies the charging demand of battery electric vehicles, herein maximizing the benefits and minimizing the negative impacts resulting from the interactions of the two sectors. To demonstrate the benefit of our integrated planning approach, we apply it to an illustrative case and present results of a sensitivity analysis. We derive managerial insights regarding the interdependencies of the number of sited charging stations and the installed storage capacity based on renewable energy generation and charging demand.