bluuebunny/crossref_metadata_2025 huggingface dataset:
Longitudinal changes in wellbeing amongst breastfeeding women in Australia and New Zealand during the COVID-19 pandemic
Authors: Sakalidis Vanessa S. , Rea Alethea , Perrella Sharon L. , McEachran Jacki , Collis Grace , Miraudo Jennifer , Prosser Stuart A. , Gibson Lisa Y. , Silva Desiree , Geddes Donna T.
Published: August 2022

The COVID-19 pandemic has impacted new mothers’ wellbeing and breastfeeding experience. Women have experienced changes in birth and postnatal care and restricted access to their support network. It is unclear how these impacts may have changed over time with shifting rates of infection and policies restricting movement and access to services in Australia and New Zealand. This study investigated the longitudinal effect of the COVID-19 pandemic on breastfeeding and maternal wellbeing in Australia and New Zealand. Mothers (n = 246) completed an online survey every 4 weeks for 6 months that examined feeding methods, maternal mental wellbeing, worries, challenges, and positive experiences during the pandemic. Mothers maintained high full breastfeeding rates at 4 months (81%) which decreased to 37% at 6 months. Perceived low milk supply contributed to the earlier cessation of full breastfeeding. Poor infant sleep was associated with stress, perinatal anxiety, mental wellbeing, and breastfeeding status. Although mothers initially reported that lockdowns helped with family bonding and less pressure, prolonged lockdowns appeared to have adverse effects on access to social networks and extended family support.

   Conclusion: The results highlight the changing dynamic of the pandemic and the need for adaptable perinatal services which allow mothers access to in-person services and their support network even in lockdowns. Similarly, access to continuous education and clinical care remains critical for women experiencing concerns about their milk supply, infant sleep, and their own wellbeing.

What is Known:• The COVID-19 pandemic and lockdown restrictions have significantly affected perinatal mental health, disrupted maternal services, and subsequent breastfeeding.

What is New:• In Australia and New Zealand, breastfeeding women experienced challenges to their mental wellbeing, sleep, and breastfeeding, which was likely exacerbated over time by the pandemic. Lockdowns, while initially beneficial for some families, became detrimental to maternal support and wellbeing.
The efficacy of modified binding technique for renorrhaphy during robotic partial nephrectomy: surgical and functional outcomes from single-center experience
Authors: Wang Zhi-Yu , Zhang Wei , Yu Shuan-Bao , Zhan Yong-Hao , Fan Ya-Feng , Zhang Xue-Pei
Published: August 2022

Background

To compare the traditional single-layer and double-layer suture renorrhaphy with modified “Binding” suture renorrhaphy (whole rim of the wound was closed by the all-layer flow suture starting from the parenchyma cut edges to hilum, followed by the final defect closure) in robotic partial nephrectomy (RPN) for treating localized renal cell carcinoma in our large institutional experience.

Methods

We retrospectively reviewed clinical data of 406 consecutive patients who underwent RPN from May 2018 and December 2020 in our center. The demographic and oncologic outcome variables were compared between different renal reconstruction groups and the effect of these suture techniques on renal function outcomes was also evaluated.

Results

For the single-layer group, median operative time and warm ischemic time were significantly less than that of the double-layer and “Binding” groups (p < 0.001), while the significantly lower eGFR drop (p = 0.014) was also detected within postoperative 3 months from baseline, but this difference lost its statistical significance from 3th month to the last follow-up. The changes in postoperative creatinine values were clinically insignificant among the three groups. In a sub-analysis over 258 patients with moderate/high nephrometry score, those patients who underwent “Binding” suture had an undifferentiated warm ischemic time, estimated blood loss, and length of hospitalization stay with a decreased risk of Grade III complications (postoperative hemorrhage requiring intervention) and improved renal function recovery during the whole follow-up.

Conclusion

Single-layer suture renorrhaphy may be associated with better renal functional preservation and could prove to be reliable in patients with low-complexity tumor (RENAL score ≤ 6). Patients with moderate/high-complexity tumor (RENAL score ≥ 7) might represent a subgroup of patients having a functional benefit after “Binding” suture renorrhaphy even in the long-term period.

Graphical abstract
Paragangliome der A. carotis
Authors: Erhart Philipp , Körfer Daniel , Hoffmann-Wieker Carola , Gieldon Laura , Dikow Nicola , Wielpütz Mark Oliver , Plinkert Peter Karl , Kender Zoltan , Szendrödi Julia , Schaaf Christian Patrick , Böckler Dittmar
Published: August 2022

Paragangliome im Kopf-Hals-Bereich sind seltene Tumoren und treten sowohl sporadisch als auch hereditär auf. Sie können Systemerkrankungen darstellen und sollten interdisziplinär abgeklärt werden. Nach internistischen, radiologischen und genetischen Gesichtspunkten lassen sich Niedrig-/und Hochrisikopatienten identifizieren. Klinische Herausforderungen sind eine mögliche Metastasierung, multilokuläre Manifestationen und Rezidive. Hereditäre Paragangliome können im Rahmen einer Disposition zusammen mit weiteren Tumorerkrankungen auftreten. Der vorliegende Artikel soll relevante Aspekte zu Paragangliomen der A. carotis zusammenfassen und einen praktikablen Algorithmus zu Diagnostik, Therapie und Nachsorge liefern.
Orthodontic shear bond strength and ultimate load tests of CAD/CAM produced artificial teeth
Authors: Roser Christoph J. , Rückschloß Thomas , Zenthöfer Andreas , Rammelsberg Peter , Lux Christopher J. , Rues Stefan
Published: August 2022

Objectives

To investigate whether artificial CAD/CAM processed (computer-aided design/manufacturing) teeth could be a feasible option for the production of dental in vitro models for biomechanical testing.

Material and methods

Disks (n = 10 per group) made from two different CAD/CAM-materials, one fiber-reinforced composite (FRC; Trinia, Bicon) and one polymethylmethacrylate-based resin (PMMA; Telio CAD, Ivoclar Vivadent), as well as bovine teeth (n = 10), were tested for their shear bond strength (SBS) and scored according to the adhesive remnant index (ARI). In addition, CAD/CAM-manufactured lower incisor teeth were tested for their ultimate load (Fu).

Results

With regard to SBS, both PMMA (17.4 ± 2.2 MPa) and FRC (18.0 ± 2.4 MPa) disks showed no significant difference (p = 0.968) compared to bovine disks (18.0 ± 5.4 MPa). However, the samples differed with regard to their failure mode (PMMA: ARI 4, delamination failure; FRC: ARI 0 and bovine: ARI 1.6, both adhesive failure). With regard to Fu, FRC-based teeth could withstand significantly higher loads (708 ± 126 N) than PMMA-based teeth (345 ± 109 N) (p < 0.01).

Conclusion

Unlike PMMA-based teeth, teeth made from FRC showed sufficiently high fracture resistance and comparable SBS. Thus, FRC teeth could be a promising alternative for the production of dental in vitro models for orthodontic testing.

Clinical relevance

CAD/CAM-processed teeth made from FRC enable the use of standardized geometry and constant material properties. Using FRC teeth in dental in vitro studies has therefore the potential to identify differences between various treatment options with rather small sample sizes, while remaining close to the clinical situation.
The Ethics of Sharing: Does Generosity Erode the Competitive Advantage of an Ecosystem Firm?
Authors: Alam Muhammad Aftab , Rooney David , Lundmark Erik , Taylor Murray
Published: August 2022

Innovation ecosystems are formed by interconnected firms that coalesce in interdependent networks to jointly create value. Such ecosystems rely on the norm of reciprocity—the give-and-take ethos of sharing knowledge-based resources. It is well established that an ecosystem firm can increase its competitive advantage by increasing interconnectedness with partners. However, much research has focused heavily on the positive role of inbound openness or ‘taking’ resources from ecosystem partners. The positive role of outbound openness or ‘giving’ resources to ecosystem partners remained less explored and often misunderstood as eroding competitive advantage. We address this gap by first developing a conceptual model about the mediating role of inbound openness and outbound openness in the relationship between a firm’s ecosystem interconnectedness and competitive advantage. We then test this model on a large sample (n = 794 managers) from Silicon Valley (USA) and Macquarie Business Park (Australia). Results indicate that outbound openness is a more important mediator than inbound openness for ecosystem firms seeking competitive advantage. Our findings suggest that the effect of outbound openness goes beyond merely generating tit-for-tat reciprocity to generating strategic benefits in their own right. The study adds to knowledge about the ethics of innovation ecosystems by showing that outbound openness to partners improves competitive advantage. Ecosystem firms, thus, do well by doing good when they increase their outbound openness.
When explainable AI meets IoT applications for supervised learning
Authors: Djenouri Youcef , Belhadi Asma , Srivastava Gautam , Lin Jerry Chun-Wei
Published: August 2022

This paper introduces a novel and complete framework for solving different Internet of Things (IoT) applications, which explores eXplainable AI (XAI), deep learning, and evolutionary computation. The IoT data coming from different sensors is first converted into an image database using the Gamian angular field. The images are trained using VGG16, where XAI technology and hyper-parameter optimization are introduced. Thus, analyzing the impact of the different input values in the output and understanding the different weights of a deep learning model used in the learning process helps us to increase interpretation of the overall process of IoT systems. Extensive testing was conducted to demonstrate the performance of our developed model on two separate IoT datasets. Results show the efficiency of the proposed approach compared to the baseline approaches in terms of both runtime and accuracy.
Incomplete MaxSAT approaches for combinatorial testing
Authors: Ansótegui Carlos , Manyà Felip , Ojeda Jesus , Salvia Josep M. , Torres Eduard
Published: August 2022

We present a Satisfiability (SAT)-based approach for building Mixed Covering Arrays with Constraints of minimum length, referred to as the Covering Array Number problem. This problem is central in Combinatorial Testing for the detection of system failures. In particular, we show how to apply Maximum Satisfiability (MaxSAT) technology by describing efficient encodings for different classes of complete and incomplete MaxSAT solvers to compute optimal and suboptimal solutions, respectively. Similarly, we show how to solve through MaxSAT technology a closely related problem, the Tuple Number problem, which we extend to incorporate constraints. For this problem, we additionally provide a new MaxSAT-based incomplete algorithm. The extensive experimental evaluation we carry out on the available Mixed Covering Arrays with Constraints benchmarks and the comparison with state-of-the-art tools confirm the good performance of our approaches.
Brief Alcohol Interventions are Effective through 6 Months: Findings from Marginalized Zero-inflated Poisson and Negative Binomial Models in a Two-step IPD Meta-analysis
Authors: Mun Eun-Young , Zhou Zhengyang , Huh David , Tan Lin , Li Dateng , Tanner-Smith Emily E. , Walters Scott T. , Larimer Mary E.
Published: August 2022

To evaluate and optimize brief alcohol interventions (BAIs), it is critical to have a credible overall effect size estimate as a benchmark. Estimating such an effect size has been challenging because alcohol outcomes often represent responses from a mixture of individuals: those at high risk for alcohol misuse, occasional nondrinkers, and abstainers. Moreover, some BAIs exclusively focus on heavy drinkers, whereas others take a universal prevention approach. Depending on sample characteristics, the outcome distribution might have many zeros or very few zeros and overdispersion; consequently, the most appropriate statistical model may differ across studies. We synthesized individual participant data (IPD) from 19 studies in Project INTEGRATE (Mun et al., 2015b) that randomly allocated participants to intervention and control groups (N = 7,704 participants, 38.4% men, 74.7% White, 58.5% first-year students). We sequentially estimated marginalized zero-inflated Poisson (Long et al., 2014) or negative binomial regression models to obtain covariate-adjusted, study-specific intervention effect estimates in the first step, which were subsequently combined in a random-effects meta-analysis model in the second step. BAIs produced a statistically significant 8% advantage in the mean number of drinks at both 1–3 months (RR = 0.92, 95% CI = [0.85, 0.98]) and 6 months (RR = 0.92, 95% CI = [0.85, 0.99]) compared to controls. At 9–12 months, there was no statistically significant difference in the mean number of drinks between BAIs and controls. In conclusion, BAIs are effective at reducing the mean number of drinks through at least 6 months post intervention. IPD can play a critical role in deriving findings that could not be obtained in original individual studies or standard aggregate data meta-analyses.
How should the respiration rate be counted in cattle?
Authors: Dißmann L. , Heinicke J. , Jensen K. C. , Amon T. , Hoffmann G.
Published: August 2022

Respiration rate (RR) is a proficient indicator to measure the health status of cattle. The common method of measurement is to count the number of respiratory cycles each minute based on flank movements. However, there is no consistent method of execution. In previous studies, various methods have been described, including counting flank movements for 15 s, 30 s or 60 s as well as stopping the time for 5 or 10 breaths. We assume that the accuracy of the aforementioned methods differs. Therefore, we compared their precision with an RR sensor, which was used as the reference method in this study. Five scientists from the fields of agricultural science and veterinary medicine quantified the flank movement according to each of the five methods mentioned above. The results showed that with an average RR of 30 breaths per minute (bpm), all methods showed a high correlation to the values of the RR sensor. However, counting breaths for 60 s had the highest level of conformity with the RR sensor (Lin`s concordance correlation coefficient: 0.96) regardless of the level of RR. With rising RR, the inaccuracy increased significantly for the other four investigated methods, especially when counting 5 and 10 breaths. Therefore, we would recommend that counting for 60 s should be used as the standard method for future studies due to its high precision regardless of the level of RR.
What’s age got to do with it? The effect of board member age diversity: a systematic review
Authors: Gardiner Elliroma
Published: August 2022

The current research is a systematic review of 54 empirical papers from 1996 to 2022 which aim to investigate whether board member age diversity influences a firm’s financial and non-financial outcomes. Analysis of the extant research reveals board member age diversity to be an inconsistent predictor of both the financial and non-financial performance of a firm. Apart from CSR performance, which was found to more consistently be positively associated with age diversity, most studies included in the review failed to identify age diversity as a significant predictor of firm outcomes, however several positive, negative and curvilinear relationships were found by some studies. The lack of a consistent trend of significant associations may indicate that age diverse boards perform no better or worse than non-diverse boards or, more likely, given the inconsistent pattern of results, this research highlights that there may be other factors, such as team processes or task characteristics, which differentially impact whether age diversity has a positive, negative, curvilinear or no effect on outcomes. The current work is the first to systematically evaluate the available data on board age diversity and provides a clear account of what is known and what is not known about the relationship between board member age diversity and financial and non-financial outcomes. This study offers important insights and practical recommendations to researchers, HRM practitioners and policy makers interested in understanding how board composition factors influence the performance of corporate boards.
PrEdictive value of coMbined pre-test proBability and blOod gas anaLysis In pulmonary emboliSM—the EMBOLISM study
Authors: Meusel Moritz , Pätz Toni , Gruber Kim , Kupp Sebastian , Jensch Philipp-Johannes , Saraei Roza , Fürschke Alexander , Sayk Friedhelm , Eitel Ingo , Wolfrum Sebastian
Published: August 2022

In patients with suspected pulmonary embolism (PE), the number of unnecessary computed tomography pulmonary angiography (CTPA) scans remains high, especially in patients with low pre-test probability (PTP). So far, no study showed any additional benefit of capillary blood gas analysis (BGA) in diagnostic algorithms for PE. In this retrospective analysis of patients with suspected PE and subsequent CTPA, clinical data, D-dimer levels and BGA parameters (including standardized PaO2) were analyzed. Logistic regression analyses were performed to identify independent predictors for PE and reduce unnecessary CTPA examinations in patients with low PTP according to Wells score. Of 1538 patients, PE was diagnosed in 433 patients (28.2%). The original Wells score (odds ratio: 1.381 [95% CI 1.300–1.467],p < 0.001) and standardized PaO2 (odds ratio: 0.987 [95% CI 0.978–0.996],p = 0.005) were independent predictors for PE. After cohort adjustment for low PTP a D-dimer cut-off < 1.5 mg/L (278 patients (18.1%) with 18 PE (6.5%)) was identified in which a standardized PaO2 > 65 mmHg reduced the number of unnecessary CTPA by 31.9% with a 100% sensitivity. This approach was further validated in additional 53 patients with low PTP. In this validation group CTPA examinations were reduced by 32.7%. No patient with PE was missed. With our novel algorithm combining BGA testing with low PTP according to Wells score, we were able to increase the D-Dimer threshold to 1.5 mg/L and reduce CTPA examinations by approximately 32%.
Systemic Therapy for Gastrointestinal Stromal Tumor: Current Standards and Emerging Challenges
Authors: Huang Wen-Kuan , Wu Chiao-En , Wang Shang-Yu , Chang Ching-Fu , Chou Wen-Chi , Chen Jen-Shi , Yeh Chun-Nan
Published: August 2022

Opinion statement

Gastrointestinal stromal tumor (GIST), though rare, is the most common mesenchymal tumors of the gastrointestinal tract. KIT or PDGFRα mutation plays as an oncogenic driver in the majority of GISTs. Surgical resection is the only curative treatment for localized disease. The discovery of imatinib with promising anti-tumor effect and successive tyrosine kinase inhibitors (TKI), including second-line sunitinib and third-line regorafenib, revolutionized the management of advanced and metastatic GIST over the past two decades. Recently, ripretinib and avapritinib were approved for the fourth line setting and for PDGFRA exon 18-mutant GIST in first-line setting, respectively. Despite multi-line TKIs exerted ability of disease control, drug resistance remained an obstacle for preventing rapid disease progression. Experimental TKIs or novel therapeutic targets may further improve treatment efficacy. Immune checkpoint inhibitors such as anti-programmed cell death protein-1 (PD1) and anti-CTL-associated antigen 4 (CTLA-4) showed moderate response in early phase trials composed of heavily pretreated patients. KIT/PDGFRα wild-type GISTs are generally less sensitive to imatinib and late-line TKIs. Recent studies demonstrated that targeting fibroblast growth factor receptor signaling may be a potential target for the wild-type GISTs.
AIF Overexpression Aggravates Oxidative Stress in Neonatal Male Mice After Hypoxia–Ischemia Injury
Authors: Li Tao , Sun Yanyan , Zhang Shan , Xu Yiran , Li Kenan , Xie Cuicui , Wang Yong , Wang Yafeng , Cao Jing , Wang Xiaoyang , Penninger Josef M. , Kroemer Guido , Blomgren Klas , Zhu Changlian
Published: August 2022

There are sex differences in the severity, mechanisms, and outcomes of neonatal hypoxia–ischemia (HI) brain injury, and apoptosis-inducing factor (AIF) may play a critical role in this discrepancy. Based on previous findings that AIF overexpression aggravates neonatal HI brain injury, we further investigated potential sex differences in the severity and molecular mechanisms underlying the injury using mice that overexpress AIF from homozygous transgenes. We found that the male sex significantly aggravated AIF-driven brain damage, as indicated by the injury volume in the gray matter (2.25 times greater in males) and by the lost volume of subcortical white matter (1.71 greater in males) after HI. As compared to females, male mice exhibited more severe brain injury, correlating with reduced antioxidant capacities, more pronounced protein carbonylation and nitration, and increased neuronal cell death. Under physiological conditions (without HI), the doublecortin-positive area in the dentate gyrus of females was 1.15 times larger than in males, indicating that AIF upregulation effectively promoted neurogenesis in females in the long term. We also found that AIF stimulated carbohydrate metabolism in young males. Altogether, these findings corroborate earlier studies and further demonstrate that AIF is involved in oxidative stress, which contributes to the sex-specific differences observed in neonatal HI brain injury.
Chemogenetic and Optogenetic Manipulations of Microglia in Chronic Pain
Authors: Parusel Sebastian , Yi Min-Hee , Hunt Christine L. , Wu Long-Jun
Published: August 2022

Chronic pain relief remains an unmet medical need. Current research points to a substantial contribution of glia-neuron interaction in its pathogenesis. Particularly, microglia play a crucial role in the development of chronic pain. To better understand the microglial contribution to chronic pain, specific regional and temporal manipulations of microglia are necessary. Recently, two new approaches have emerged that meet these demands. Chemogenetic tools allow the expression of designer receptors exclusively activated by designer drugs (DREADDs) specifically in microglia. Similarly, optogenetic tools allow for microglial manipulationviathe activation of artificially expressed, light-sensitive proteins. Chemo- and optogenetic manipulations of microgliain vivoare powerful in interrogating microglial function in chronic pain. This review summarizes these emerging tools in studying the role of microglia in chronic pain and highlights their potential applications in microglia-related neurological disorders.
Microplastic Contamination of Composts and Liquid Fertilizers from Municipal Biowaste Treatment Plants: Effects of the Operating Conditions
Authors: Steiner Thomas , Möller Julia N. , Löder Martin G. J. , Hilbrig Frank , Laforsch Christian , Freitag Ruth
Published: August 2022

High-caloric-value household biowaste is an attractive substrate for the production of biogas and fertilizer. Most household biowaste is contaminated by plastics, typically in the form of bags and foils from packaging. Operators of municipal biowaste treatment plans take great care to remove these contaminants, often at the cost of reducing the organic material entering the process. This study compares the residual plastic contamination of fertilizer (composts, digestates) from biowaste treatment plants with compost produced from greenery and digestates produced by agricultural biogas plants processing manure and energy crops. While the fertilizers from the agricultural biogas plants and greenery composts were minimally contaminated by plastic, we found considerable numbers of plastic fragments in the composts/fertilizers from the biowaste treatment plants. Moreover, while certainly being influenced by the quality of the incoming biowaste, this residual contamination appeared to depend largely on the operating conditions. In particular, shredding of the incoming material increased the degree of contamination. Sieving was an efficient method for the removal of fragments > 5 mm but was less efficient for the removal of smaller fragments. In view of the number of the recovered fragments in that size range, it is likely that still none of the finished composts surpassed the current dry weight limits imposed for the plastic contamination of high-quality composts with fragments > 1 mm in Europe (0.3% of dry weight) nor even in Germany (0.1% of dry weight). The contamination of the liquid fertilizer produced via anaerobic digestion by three of the investigated biowaste treatment plants (up to 10,000 particles with a size between 10 and 1000 μm−1) may pose a more serious concern.

Graphical Abstract
The exosome: a review of current therapeutic roles and capabilities in human reproduction
Authors: Dimik Marko , Abeysinghe Pevindu , Logan Jayden , Mitchell Murray
Published: August 2022

Exosomes are nano-vesicles (30–150 nm) which may be useful as therapeutic delivery vehicles and as diagnostic biomarkers. Exosomes are produced naturally within the human body and therefore are not prone to immunogenicity effects which would otherwise destroy unelicited foreign bodies. Clinically, they have been regarded as ideal candidates for applications relating to biomarker developments for the early detection of different diseases. Furthermore, exosomes may be of interest as potential drug delivery vehicles, which may improve factors such as bioavailability of loaded molecular cargo, side effect profiles, off-target effects, and pharmacokinetics of drug molecules. In this review, the therapeutic potential of exosomes and their use as clinical biomarkers for early diagnostics will be explored, alongside exosomes as therapeutic delivery vehicles. This review will evaluate techniques for cargo loading, and the capacity of loaded exosomes to improve various reproductive disease states. It becomes important, therefore, to consider factors such as loading efficiency, loading methods, cell viability, exosomal sources, exosome isolation, and the potential therapeutic benefits of exosomes. Issues related to targeted drug delivery will also be discussed. Finally, the variety of therapeutic cargo and the application of appropriate loading methods is explored, in the context of establishing clinical utility.

Graphical abstract

Exosomes have more recently been widely accpeted as potential tools for disease diagnostics and the targeted delivery of certain therapeutic molecules–and in due time exosomes will be utilised more commonly within the clinical setting. Specifically, exosomal biomarkers can be identified and related to various detrimental conditions which occur during pregnancy. Considering, this review will explore the potential future of exosomes as both diagnostic tools and therapeutic delivery vehicles to treat related conditions, including the challenges which exist towards incorporating exosomes within the clinical environment to benefit patients.
Optimisation of Preventive Maintenance Regime Based on Failure Mode System Modelling Considering Reliability
Authors: Alamri Theyab O. , Mo John P. T.
Published: August 2022

Today, the ability to maintain a continuous complex system operation is viewed as a key attribute for ensuring uninterrupted revenue contribution and the survival of a business. Many industrial organisations have come to understand that by having an effective plan of maintenance, the efficiency and reliability of a system can be improved, while costs can be minimised and revenue-generating production can continue. The novelty of this paper is based on using failure modes and effects analysis (FMEA) to develop a holistic preventive maintenance schedule for a complete system. A system can be modelled as a series and parallel arrangement of subsystems and components, and failure of different components of the system can be determined from their life expectancy. The objective is to ensure continuity of production output while maintaining a high level of system reliability and minimising the total maintenance costs. The reliability of a complete system is analysed using the Weibull failure-time distribution. By using the exhaustive search optimisation method, the maintenance cost is minimised by determining the optimal replacement interval for each FMEA block, subject to system reliability. Based on the results obtained from a case study, it is shown that the approach in this paper can ensure the continuity of production output during maintenance activities, reduce system maintenance costs, and achieve maximum system reliability. This holistic approach can be applied to any form of complex system, and at every step of the process.
Uniform bounds for the number of powers in arithmetic progressions
Authors: Hajdu L. , Papp Á.
Published: August 2022

We give sharp, in some sense uniform bounds for the number of $$\ell $$
ℓ
-th powers and arbitrary powers among the first N terms of an arithmetic progression, for N large enough.
Decarbonising the automotive sector: a primary raw material perspective on targets and timescales
Authors: Petavratzi Evi , Gunn Gus
Published: August 2022

Decarbonisation of the automotive sector will require increased amounts of raw materials such as lithium, cobalt, nickel and rare earth elements. Consequently, it is crucial to assess whether supply will be able to meet forecast demand within the required timescale. The automotive sector relies on complex global supply chains comprising four tiers. We have developed an integrated timeline from tier 4 (supply of raw materials) through to tier 1, the production of electric vehicles (EVs). Numerous factors, mainly economic, political, social and environmental, influence the duration of tier 4 leading to considerable variation between projects. However, our analysis demonstrates that it commonly takes more than 30 years from initial exploration to EV production. Tier 4, which is often neglected by the automotive industry, may account for 20 years of that period. This suggests that raw material supply is unlikely to match the projected demand from electrification of the automotive sector up to 2030. Reducing the duration of tier 4 will be difficult, although governments and industry can mitigate supply risks in various ways. These include multi-disciplinary international research across the supply chain and the transformation of research findings into policy and best practice. Supply chain convergence, with businesses across the supply chain working to develop long-term plans for secure and sustainable supply, will also be beneficial. In addition, global stakeholders should work together to resolve ESG challenges to supply. All these measures depend on the availability of researchers and industry personnel with appropriate skills and knowledge.
The Influence of Knowledge, Trust, and Perceived Risk on Firefighters’ Preparedness and Willingness to Respond to Nuclear Emergencies: The Case of South Korea
Authors: Choi Jongan , Lee Sangkyu , Choi HaeYoun
Published: August 2022

At the site of nuclear accidents, firefighters situated near nuclear power plants (NPPs) assume responsibility for suppressing fires and rescuing workers from leaked radiation. Their timely responses to nuclear emergencies can prevent or minimize the catastrophic impacts of these accidents. Despite their important role in nuclear emergency management, little is known about the factors that influence firefighters’ nuclear emergency responses. We recruited 179 Korean firefighters (96% male) situated near NPPs. We examined whether and how knowledge regarding nuclear accidents and trust in the authorities operating nuclear power plants were related to firefighters’ risk perceptions of nuclear accidents to predict their preparedness and willingness to respond to nuclear emergencies. Our results indicate that trust moderated the effect of knowledge on the perceived risk of nuclear accidents, and that the perceived risk mediated the relationship between knowledge and firefighters’ preparedness and willingness to respond to nuclear emergencies. The results revealed a pattern of moderated mediation, in which perceived risk mediated the indirect effect of knowledge on preparedness and willingness when the firefighters’ trust was low, but not when it was high.
Nutrient Removal by Algae-Based Wastewater Treatment
Authors: Nguyen Luong N. , Aditya Lisa , Vu Hang P. , Johir Abu Hasan , Bennar Lucia , Ralph Peter , Hoang Ngoc B. , Zdarta Jakub , Nghiem Long D.
Published: August 2022

Algae cultivation complements wastewater treatment (WWT) principles as the process uptakes nutrients while assimilates CO2 into biomass. Thus, the application of algae-based WWT is on the upward trajectory as more attention for recovery nutrients and CO2 capture while reducing its economic challenge in the circular economy concept. However, the complexity of wastewater and algal ecological characteristics induces techno-economic challenges for industry implementation. Algae-based WWT relies totally on the ability of algae to uptake and store nutrients in the biomass. Therefore, the removal efficiency is proportional to biomass productivity. This removal mechanism limits algae applications to low nutrient concentration wastewater. The hydraulic retention time (HRT) of algae-based WWT is significantly long (i.e. > 10 days), compared to a few hours in bacteria-based process. Phototrophic algae are the most used process in algae-based WWT studies as well as in pilot-scale trials. Application of phototrophic algae in wastewater faces challenges to supply CO2 and illumination. Collectively, significant landscape is required for illumination. Algae-based WWT has limited organic removals, which require pretreatment of wastewaters before flowing into the algal process. Algae-based WWT can be used in connection with the bacteria-based WWT to remove partial nutrients while capturing CO2. Future research should strive to achieve fast and high growth rate, strong environmental tolerance species, and simple downstream processing and high-value biomass. There is also a clear and urgent need for more systematic analysis of biomass for both carbon credit assessment and economic values to facilitate identification and prioritisation of barriers to lower the cost algae-based WWT.

Graphical abstract
A Realist Evaluation of Residential Treatment of Adults with Substance use Disorder: Development of an Initial Programme Theory
Authors: De Salis Henry F. , Martin Rachelle , Bell Elliot , Newton-Howes Giles
Published: August 2022

Residential treatment of addiction remains a key element in addictions management, though high rates of attrition and relapse are reported, and underlying mechanisms of change remain unclear. This study aimed to complete the first stage of a realist evaluation—to develop an initial programme theory that would explain possible contexts and mechanisms of change leading to outcomes from a residential treatment programme for substance use disorders. Realist evaluation using key informant interviews and document review. Residential treatment centre in New Zealand. Four key informants (managers and caseworkers). Retroductive analysis (inductive and deductive) of semi-structured interviews and content analysis of documents. We identified one intermediate outcome of identity change that contributed to successful completion of residential treatment. The mechanisms leading to these outcomes were the development of a sense of belonging to the recovery community and a sense of hope and purpose. These mechanisms were activated in contexts including supportive and structured culture (staff and peers) and the absence of chaos. We developed an initial programme theory to explain successful completion of a residential treatment for SUD. Theories like this are important because practitioners can use them to increase the likelihood of replication of successful treatment. We found that realist evaluation provides researchers with appropriate philosophy and methods with which to explore and start to unravel some of the complexity within residential treatment for addictions.
Recent Ice Trends in Swiss Mountain Lakes: 20-year Analysis of MODIS Imagery
Authors: Tom Manu , Wu Tianyu , Baltsavias Emmanuel , Schindler Konrad
Published: August 2022

Depleting lake ice is a climate change indicator, just like sea-level rise or glacial retreat. Monitoring Lake Ice Phenology (LIP) is useful because long-term freezing and thawing patterns serve as sentinels to understand regional and global climate change. We report a study for the Oberengadin region of Switzerland, where several small- and medium-sized mountain lakes are located. We observe the LIP events, such as freeze-up, break-up and ice cover duration, across two decades (2000–2020) from optical satellite images. We analyse the time series of MODIS imagery by estimating spatially resolved maps of lake ice for these Alpine lakes with supervised machine learning. To train the classifier we rely on reference data annotated manually based on webcam images. From the ice maps, we derive long-term LIP trends. Since the webcam data are only available for two winters, we cross-check our results against the operational MODIS and VIIRS snow products. We find a change in complete freeze duration of $$-\,0.76$$

-

0.76

and $$-\,0.89$$

-

0.89

days per annum for lakes Sils and Silvaplana, respectively. Furthermore, we observe plausible correlations of the LIP trends with climate data measured at nearby meteorological stations. We notice that mean winter air temperature has a negative correlation with the freeze duration and break-up events and a positive correlation with the freeze-up events. Additionally, we observe a strong negative correlation of sunshine during the winter months with the freeze duration and break-up events.
Text/Körper: Der Fincken Ritter (1560)
Authors: Fuhrmann Daniela , Kohler Kathia
Published: August 2022

Der Artikel schlägt eine Neulektüre des Fincken Ritter vor, einer 1560 anonym erschienenen Flugschrift, die aufgrund ihres unmöglichen Inhalts sowie der wilden Aneinanderreihung von Gattungstraditionen, Motiven und Topoi gemeinhin zur Unsinnspoesie gezählt wird. Entgegen der Forschung, die sich überwiegend der vom Text angeblich betriebenen Zersetzung von Sinn widmete, argumentiert der Artikel, dass sich mit Blick auf die zentrale Körpermotivik eine neue Perspektive einstellen lässt: Über die Körperlichkeit des titelgebenden Helden erhält das Herleiten, Erproben und Einüben von Eigenlogiken auf Ebene der Erzählverfahren Anschauung. Nicht nur der Held muss sich in einer verkehrten Welt bewähren, bevor er geboren werden kann. Auch das Erzählen davon bildet sich schrittweise aus und schöpft sich in enger Auseinandersetzung mit tradierten Modellen eine Welt eigenen Regeln und Rechts. Dieses Argument wird an drei Momenten der vielgestaltig inszenierten Körperlichkeit entwickelt: Die handlungsantreibende Nahrungssuche des Helden deutet das Modell des Stoffwechsels als Anschluss an tradierte Materie neu. In den drastischen Versehrungen des Helden eröffnet sich das Erzählen einen auktorialen Spielraum zwischen seinem erlebenden und erzählenden Ich. Über Klang-Körper schließlich werden Modelle der Textvervielfältigung und -zirkulation reflektiert. Alle drei Körperübungen zielen darauf, das Verhältnis von Erzählposition und davon abhängigem Weltentwurf zu durchdenken. So wird die körperliche figura des Finkenritters zur poetologischen Reflexionsfigur des Fincken Ritter.
Measures of noncompactness in the space of regulated functions on an unbounded interval
Authors: Dudek Szymon , Olszowy Leszek
Published: August 2022

In this paper, we formulate a criterion for relative compactness in the space of regulated functions on an unbounded interval and not necessarily bounded. Next we construct measure of noncompactness in this space and investigate its properties. The presented measure is simpler and more convenient to use than all known so far in space of regulated functions on an unbounded interval. Moreover, we show the applicability of the measure of noncompactness in proving the existence of solutions of some Volterra type integral equation.
Soil liquefaction assessment by using hierarchical Gaussian Process model with integrated feature and instance based domain adaption for multiple data sources
Authors: Guo Hongwei , Rabczuk Timon , Zhu Yanfei , Cui Hanyin , Su Chang , Zhuang Xiaoying
Published: August 2022

For soil liquefaction prediction from multiple data sources, this study designs a hierarchical machine learning model based on deep feature extraction and Gaussian Process with integrated domain adaption techniques. The proposed model first combines deep fisher discriminant analysis (DDA) and Gaussian Process (GP) in a unified framework, so as to extract deep discriminant features and enhance the model performance for classification. To deliver fair evaluation, the classifier is validated in the approach of repeated stratified K-fold cross validation. Then, five different data resources are presented to further verify the model’s robustness and generality. To reuse the gained knowledge from the existing data sources and enhance the generality of the predictive model, a domain adaption approach is formulated by combing a deep Autoencoder with TrAdaboost, to achieve good performance over different data records from both the in-situ and laboratory observations. After comparing the proposed model with classical machine learning models, such as supported vector machine, as well as with the state-of-art ensemble learning models, it is found that, regarding seismic-induced liquefaction prediction, the predicted results of this model show high accuracy on all datasets both in the repeated cross validation and Wilcoxon signed rank test. Finally, a sensitivity analysis is made on the DDA-GP model to reveal the features that may significantly affect the liquefaction.
Factors influencing halide vacancy transport in perovskite solar cells
Authors: Woo Young Won , Jung Young-Kwang , Kim Gee Yeong , Kim Sunghyun , Walsh Aron
Published: August 2022

Ion migration in inorganic and hybrid organic-inorganic metal halide perovskites causes unusual phenomena in photovoltaic devices, such as current-voltage hysteresis and photoinduced phase transformations. It is now well established that metal halide perovskites are mixed ionic-electronic conductors and halide ions are mobile at room temperature. The effect of various physical stimuli like light, heat, pressure, and applied bias can affect the distribution and movement of ions. However, the impact of each stimulus is not understood as the measured response includes a combination of factors. We explore, using first-principles density functional theory (DFT), halide migration mediated by vacancies in model cubic phases of CsPbX3 (X = Cl, Br, I) and systematically control the electronic, chemical, and mechanical conditions. We assess the potential energy landscape for ion migration and how device-relevant conditions and compositional engineering can influence the physical behaviour of halide perovskites.
Bayesian Geostatistical Modeling to Assess Malaria Seasonality and Monthly Incidence Risk in Eswatini
Authors: Dlamini Sabelo Nick , Fall Ibrahima Socé , Mabaso Sizwe Doctor
Published: August 2022

Eswatini is on the brink of malaria elimination and had however, had to shift its target year to eliminate malaria on several occasions since 2015 as the country struggled to achieve its zero malaria goal. We conducted a Bayesian geostatistical modeling study using malaria case data. A Bayesian distributed lags model (DLM) was implemented to assess the effects of seasonality on cases. A second Bayesian model based on polynomial distributed lags was implemented on the dataset to improve understanding of the lag effect of environmental factors on cases. Results showed that malaria increased during the dry season with proportion 0.051 compared to the rainy season with proportion 0.047 while rainfall of the preceding month (Lag2) had negative effect on malaria as it decreased by proportion − 0.25 (BCI: − 0.46, − 0.05). Night temperatures of the preceding first and second month were significantly associated with increased malaria in the following proportions: at Lag1 0.53 (BCI: 0.23, 0.84) and at Lag2 0.26 (BCI: 0.01, 0.51). Seasonality was an important predictor of malaria with proportion 0.72 (BCI: 0.40, 0.98). High malaria rates were identified for the months of July to October, moderate rates in the months of November to February and low rates in the months of March to June. The maps produced support-targeted malaria control interventions. The Bayesian geostatistical models could be extended for short-term and long-term forecasting of malaria supporting-targeted response both in space and time for effective elimination.
Achieving a Data-Driven Risk Assessment Methodology for Ethical AI
Authors: Felländer Anna , Rebane Jonathan , Larsson Stefan , Wiggberg Mattias , Heintz Fredrik
Published: August 2022

The AI landscape demands a broad set of legal, ethical, and societal considerations to be accounted for in order to develop ethical AI (eAI) solutions which sustain human values and rights. Currently, a variety of guidelines and a handful of niche tools exist to account for and tackle individual challenges. However, it is also well established that many organizations face practical challenges in navigating these considerations from a risk management perspective within AI governance. Therefore, new methodologies are needed to provide a well-vetted and real-world applicable structure and path through the checks and balances needed for ethically assessing and guiding the development of AI. In this paper, we show that a multidisciplinary research approach, spanning cross-sectional viewpoints, is the foundation of a pragmatic definition of ethical and societal risks faced by organizations using AI. Equally important are the findings of cross-structural governance for implementing eAI successfully. Based on evidence acquired from our multidisciplinary research investigation, we propose a novel data-driven risk assessment methodology, entitled DRESS-eAI. In addition, through the evaluation of our methodological implementation, we demonstrate its state-of-the-art relevance as a tool for sustaining human values in the data-driven AI era.