bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hybrid manufacturing-remanufacturing system of essential commodity in the context of COVID-19
Authors: Bhide Amol Vasant , Akarte Milind M. 
Published: July 2022

Purpose
This paper aims to assess the feasibility of a hybrid manufacturing and remanufacturing system (HMRS) for essential commodities in the context of COVID-19. Specifically, it emphasises using HMRS based on costs associated with various manufacturing activities.

Design/methodology/approach
The combination of mathematical model and system dynamics is used to model the HMRS system. The model was tried on sanitiser bottle manufacturing to generalise the result.

Findings
The remanufacturing cost is higher because of reverse logistics, inspection and holding costs. Ultimately remanufacturing costs turn out to be lesser than the original manufacturing the moment system attains stability.

Practical implications
The study put forth the reason to encourage remanufacturing towards sustainability through government incentives.

Originality/value
The study put forth the feasibility of the HMRS system for an essential commodity in the context of a covid pandemic. The research implemented system dynamics for modelling and validation.
Opening the black boxes: financial algorithms and multi-paradigmatic research in information technology
Authors: Schinckus Christophe , Gasparin Marta , Green William 
Published: July 2022

Purpose
This paper aims to contribute to recent debates about financial knowledge by opening the black box of its algorithmization to understand how information systems can address the major challenges related to interactions between algorithmic trading and financial markets.

Design/methodology/approach
The paper analyses financial algorithms in three steps. First, the authors introduce the phenomenon of flash crash; second, the authors conduct an epistemological analysis of algorithmization and identify three epistemological regimes – epistemic, operational and authority – which differ in terms of how they deal with financial information. Third, the authors demonstrate that a flash crash emerges when there is a disconnection between these three regimes.

Findings
The authors open the black box of financial algorithms to understand why flash crashes occur and how information technology research can address the problem. A flash crash is a very rapid and deep fall in security prices in a very short time due to an algorithmic misunderstanding of the market. Thus, the authors investigate the problem and propose an interdisciplinary approach to clarify the scope of algorithmization of financial markets.

Originality/value
To manage the misalignment of information and potential disconnection between the three regimes, the authors suggest that information technology can embrace the complexity of the algorithmization of financial knowledge by diversifying its implementation through the development of a multi-sensorial platform. The authors propose sonification as a new mechanism for capturing and understanding financial information. This approach is then presented as a new research area that can contribute to the way financial innovations interact with information technology.
Low-carbon tourism: determining domestic tourist perception from Thailand: Tourism Agenda 2030
Authors: Fakfare Pipatpong , Wattanacharoensil Walanchalee 
Published: July 2022

Purpose
Underpinned by three-factor theory, this study aims to: examine the dynamics (asymmetry) of multi-quality low-carbon attributes towards the Thai tourists’ perception and prioritise carbon-tourism attributes on the basis of impact-range performance and asymmetric analysis.

Design/methodology/approach
The study applies a multi-method approach to derive the low-carbon tourism (LCT) items before conducting exploratory factor analysis to identify the underlying dimensions. Impact range performance analysis and impact asymmetry analysis were carried out to explore the asymmetric or symmetric relationship associated with tourists’ perception of LCT.

Findings
Findings reveal the three dimensions of the LCT attributes. Out of the 29 attributes, nine are regarded as “must-have” categories, such that tourists will be disappointed at the efforts of a low-carbon destination if these attributes are missing, but they will feel neutral if the attributes are present. Six LCT attributes fall into the “hybrid” category, such that tourists will appreciate if they perceive these attributes to be available for LCT and feel disappointed if these attributes are not or poorly offered. Fourteen attributes are considered under the “value-added” category, meaning tourists will only appreciate if they encounter these attributes at the destination, and the lack thereof will not cause any dissatisfaction or negative perception from tourists.

Originality/value
Through the multi-quality asymmetric analysis, the study provides deep insights into the degree of perception of the 29 LCT attributes. The study offers tangible guidelines to destination authorities and pinpoints the necessity to provide attributes, especially in the “hybrid” and “must-have” categories, to avoid tourists’ negative perceptions when they visit a low-carbon destination.
Functional composition of plant communities mediates biomass effects on ecosystem service recovery across an experimental dryland restoration network
Authors: Balazs Kathleen R. , Munson Seth M. , Butterfield Bradley J. 
Published: July 2022

Abstract

Land degradation can result in a loss of critical ecosystem services that we often seek to restore through re‐establishment of desired plant communities. Trait‐based approaches have the potential to target specific ecosystem services based on associations between the functional composition of plant communities and ecosystem properties that serve as indicators of those services.

The effect of functional composition on ecosystem recovery may depend on the amount of restored plant biomass, itself a supporting service frequently targeted in restoration efforts. Yet, interactions between functional composition and biomass are not formally integrated into trait‐based analytical frameworks.

We tested the hypothesis that functional composition of plant communities both drives, and interacts with, biomass production to influence indicators of soil functioning and weed suppression across a network of degraded dryland restoration experiments. This networked approach allowed us to identify generalized effects of functional composition on ecosystem recovery across a range of dryland climate conditions.

Climate had a substantial effect on ecosystem indicators, with weed cover and soil surface stability increasing in more arid climates, water infiltration increasing with precipitation, and aggregate structure increasing with less freezing. After accounting for climate effects across study sites, we found significant effects of community‐weighted mean (CWM) trait values on biomass, particularly a positive effect of leaf carbon‐to‐nitrogen ratio, and of CWM‐biomass interactions on other ecosystem indicators. Cover of exotic species was reduced in restored communities with a combination of low leaf dry matter content and high biomass, soil water infiltration increased with lower specific root length and high biomass, and soil aggregate stability increased with higher root dry matter content and high biomass, among other effects. Functional diversity had no significant effects on any ecosystem indicators.

Synthesis: The influence of community functional composition on ecosystem properties increases with community biomass, particularly in disturbed or low productivity systems. This suggests that active management should not only focus on trait values that optimize individual ecosystem indicators but also how those functional strategies are complementary or counter to those that increase biomass.

Read the free Plain Language Summary for this article on the Journal blog
Predators minimize energy costs, rather than maximize energy gains under warming: Evidence from a microcosm feeding experiment
Authors: Meehan Matthew L. , Turnbull Kurtis F. , Sinclair Brent J. , Lindo Zoë 
Published: July 2022

Abstract

Climate warming may alter predator–prey interactions and predator feeding behaviour due to increased metabolic demands. How predators meet these increased demands may depend on trade‐offs in prey energy content and body size, handling time and other functional constraints.

We tested hypotheses associated with these trade‐offs with the predatory mite Stratiolaelaps scimitus, and three prey that differed in body size, energy content, and defenses (Folsomia candida, Oppia nitens, and Carpoglyphus lactis). We estimated metabolic rate, predation in choice and no choice feeding trials, movement rate, and lipid and protein content for all four species at 16°C and 24°C. We used these data to estimate the predator's energy demands and compared these to estimated energy intake in the choice feeding trials.

Predators had greater metabolic demands at 24°C than at 16°C, but temperature did not affect predator or prey movement rates. Warming decreased lipid content, but not protein content, of all three prey species, leading to lower energy content for C. lactis and O. nitens, but not F. candida. In both feeding trials at 24°C, predators increased their feeding on the smaller, energy‐poor C. lactis, but not the larger, energy‐rich F. candida, resulting in lower estimated energy intake. S. scimitus did not feed on O. nitens at either temperature.

Predators increasingly fed on small‐bodied prey under warming and not the large‐bodied prey despite the potential for greater energetic gains from larger prey. We posit that predators minimized energy lost during feeding through lower handling costs associated with C. lactis, rather than maximize energy gain. We conclude that selection of prey based on body size changes with temperature as a trade‐off for predators to balance increased metabolic demands. As predators provide top‐down control and regulate energy flow through the consumption of their prey, changes to predator feeding behaviour with climate warming may affect food web dynamics and ecosystem‐level processes.

Read the free Plain Language Summary for this article on the Journal blog.
Review of United States laws pertaining to the recovery and analysis of human skeletal remains
Authors: Carter Melinda L. , Newman Justine L. , Seidemann Ryan M. , Reedy Edward A. 
Published: July 2022

AbstractHuman skeletal remains (HSR) are routinely excavated from archeological contexts and analyzed by experts in human osteology. Contrarily, HSR in medicolegal contexts are usually recovered by law enforcement officers and examined by pathologists with limited osteological training. To examine legal requirements for expertise, we reviewed laws in the United States regarding the recovery and analysis of HSR from archeological sites, unmarked graves, and medicolegal contexts. Of the 50 states, 19 (38%) have laws stating that an anthropologist with osteological training should be involved in the recovery or analysis of HSR from an archeological context. Fifteen of those 16 states have laws requiring a minimum level of education to be a qualified skeletal analyst. In contrast, only one state, Texas, requires an anthropologist who handles forensic cases to have a doctoral degree. Including Texas, only eight states (16%) have laws that encourage but do not mandate consultation with a forensic anthropologist for medicolegal skeletal cases. Louisiana and Washington have state‐funded laboratories, expert forensic anthropologists, and effective protocols for handling forensic cases. Due process and human rights concerns at stake in criminal cases require that those recovering and analyzing modern HSR have an equal or higher level of expertise than those working with archeological remains. Yet, legislators assume that law enforcement and pathologists are adequately trained. Because court standards demand expert testimony based on accepted methodologies and standard levels of competency, forensic anthropologists have a professional responsibility to engage with lawmakers to draft legislation to ensure proper handling of all skeletal cases.
Metastatic lipoblastoma‐like tumour
Authors: Chia Misté (Rong Hui) , Windsor Morgan 
Published: July 2022

AbstractIntroductionLipoblastoma‐like tumours (LLT) are uncommon and their biologic nature is not well‐understood. Complete resection of the primary lesion is usually curative. This is the first reported case of metastatic LLT.Case presentation and managementThis patient originally had a large primary resected from the vulva. She subsequently developed tumours in multiple areas including her right pleura and lung. These were resected and pathology was consistent with LLT. On follow‐up imaging, there was evidence of metastatic disease.ConclusionThe patient is currently undergoing detailed molecular analysis in the hope of detecting a molecular target. Given the infrequent occurrence of LLT, its behaviour is not well understood. Longer duration of follow up is required and prognostic markers need to be identified to better direct treatment.
Occurrence of complications in patients restored with implants
Authors: Cecchinato Denis , Marino Massimiliano , Håkansson Jan , Lindhe Jan , Derks Jan 
Published: July 2022

AbstractObjectivesTo determine the occurrence and clustering of complications in subjects restored with fixed implant‐supported prostheses.MethodsIn the present retrospective case series, 241 subjects treated at one clinical centre and provided with 729 implants were included. A clinical and radiographic examination was performed after a mean follow‐up period of 4.8 ± 2.0 years. Additional information on occurrence of technical (chipping, loss of retention, fracture of components) and biological complications (marginal bone loss, implant loss) during follow‐up was extracted from patient records. For each type of complication and complications overall, regression analyses were performed to identify potential risk factors. Cox regression analyses were used to evaluate time to event for implant loss and technical complications.ResultsIn all, 30% of the 241 patients presented with at least one complication of technical and/or biological character during the follow‐up period. Technical complications affected 19.5% of subjects, while 14.1% presented with marginal bone loss >2 mm. Implant loss occurred in 4.6% of subjects. While technical complications were noted already early during the maintenance period (<1200 days), implant loss typically occurred during a later phase. A small subgroup of subjects (7.9%) experienced more than one type of complication.ConclusionsComplications occurred frequently and the most common type of complication was of technical character. Technical and biological complications occurred independently of each other.
Framing co‐productive conservation in partnership with Arctic Indigenous peoples
Authors: Buschman Victoria Qutuuq 
Published: July 2022

AbstractIndigenous communities at the front lines of climate change and biodiversity loss are increasingly shaping the conservation of lands, waters, and species. The Arctic is a hotbed for emerging local, national, and international conservation efforts, and researchers, managers, and communities alike will benefit from a framework that improves approaches to Indigenous partnerships. Co‐productive conservation is a framework that encompasses both the co‐production of knowledge and the co‐production of public services to pursue ethically conscious, culturally relevant, and fully knowledge‐based approaches to biodiversity concerns. Co‐productive conservation recognizes that conservation can be practiced in a way that embodies Indigenous perspectives, knowledge, rights, priorities, and livelihoods. Six iterative and reflexive co‐production processes (i.e., co‐planning, co‐prioritizing, co‐learning, co‐managing, co‐delivering, and co‐assessing) focus on the human dimensions that allow research, management, and conservation to affect change. By opening discussions on how to structure conservation efforts in partnership with Indigenous communities, the conservation community can move away from narratives that perceive Indigenous participation as an obligation or part of an ethical narrative and instead embrace a process that broadens the evidence base and situates conservation within Indigenous contexts.
Longitudinal nonlinear mixed effects modeling of EGFR mutations in ctDNA as predictor of disease progression in treatment of EGFR‐mutant non‐small cell lung cancer
Authors: Janssen Julie M. , Verheijen Remy B. , van Duijl Tirsa T. , Lin Lishi , van den Heuvel Michel M. , Beijnen Jos H. , Steeghs Neeltje , van den Broek Daan , Huitema Alwin D. R. , Dorlo Thomas P. C. 
Published: July 2022

AbstractCorrelations between increasing concentrations of circulating tumor DNA (ctDNA) in plasma and disease progression have been shown. A nonlinear mixed effects model to describe the dynamics of epidermal growth factor receptor (EGFR) ctDNA data from patients with non‐small cell lung cancer (NSCLC) combined with a parametric survival model were developed to evaluate the ability of these modeling techniques to describe ctDNA data. Repeated ctDNA measurements on L858R, exon19del, and T790M mutants were available from 54 patients with EGFR mutated NSCLC treated with erlotinib or gefitinib. Different dynamic models were tested to describe the longitudinal ctDNA concentrations of the driver and resistance mutations. Subsequently, a parametric time‐to‐event model for progression‐free survival (PFS) was developed. Predicted L858R, exon19del, and T790M concentrations were used to evaluate their value as predictor for disease progression. The ctDNA dynamics were best described by a model consisting of a zero‐order increase and first‐order elimination (19.7/day, 95% confidence interval [CI] 14.9–23.6/day) of ctDNA concentrations. In addition, time‐dependent development of resistance (5.0 × 10−4, 95% CI 2.0 × 10−4–7.0 × 10−4/day) was included in the final model. Relative change in L858R and exon19del concentrations from baseline was identified as most significant predictor of disease progression (p = 0.001). The dynamic model for L858R, exon19del, and T790M concentrations in ctDNA and time‐to‐event model adequately described the observed concentrations and PFS data in our clinical cohort. In addition, it was shown that nonlinear mixed effects modeling is a valuable method for the analysis of longitudinal and heterogeneous biomarker datasets obtained from clinical practice.
Sjögren’s syndrome
Authors: André Fiona , Böckle Barbara C. 
Published: July 2022

SummarySjögren’s syndrome (SjS) is an autoimmune disease characterized by the triad of sicca symptoms, fatigue and pain. This diagnosis is usually made in women at the average age of 60 years. Diagnosis is made when sicca symptoms persist for more than three months, after the exclusion of possible differential diagnoses, and using the ACR/EULAR 2016 classification criteria for SjS. Many organs can be affected in the course of this disease. Xerosis cutis and pruritus are the most common skin manifestations, followed by leukocytoclastic vasculitis and subacute cutaneous lupus erythematosus. In addition, SjS patients often have myoarthralgia and neuropsychiatric symptoms. In the long term, attention must be paid to the increased risk of cardiovascular disease and lymphoma. Due to the multiorgan involvement in SjS patients, interdisciplinary care is required.
Novel predictors of daily fluctuations in glycemia and self‐management in adolescents and young adults with type 1 diabetes
Authors: Messer Laurel H. , Vigers Tim , Pyle Laura , Fivekiller Emily , Wadwa R. Paul , Hernandez Teri L. , Cook Paul F. 
Published: July 2022

AbstractAimsTo understand morning biopsychosocial factors that predict glycemia, adherence, and goal attainment in adolescents and young adults (AYA) with type 1 diabetes (T1D) on a daily basis.MethodsEight‐eight AYA (mean 17.6 ± 2.6 years, 54% female, HbA1c 7.9 ± 1.4%, diabetes duration 8.5 ± 4.5 years) with T1D who use Continuous Glucose Monitoring (CGM) completed a 2‐week prospective study. Participants chose a self‐management goal to focus on during participation. For six days, participants prospectively completed a 25‐item Engagement Prediction Survey to assess biopsychosocial factors to predict daily diabetes outcomes and an end‐of‐day Goal Survey. Lasso and mixed‐model regression were used to determine items in the Engagement Prediction Survey most predictive of perceived goal attainment, CGM Time‐in‐Range (TIR, 70–180 mg/dl), sensor mean glucose, number of insulin boluses and hyperglycemia response (bolus within 30 min of high alert or glucose <200 mg/dl within 2 hours).ResultsA 7‐item model (including current glucose, planning/wanting to manage diabetes, wanting to skip self‐management, feeling good about self, health perception and support needs) explained 16.7% of the daily variance in TIR, 18.6% of mean sensor glucose, 2.1% of the number of boluses, 14% of hyperglycemia response, and 28.7% of goal attainment perceptions. The mean absolute change in day‐to‐day TIR was 16%, sensor glucose was 30 mg/dl, and the number of boluses was 2. AYA reported more positive Engagement Prediction Survey responses on mornings when they awoke with lower glucose levels.ConclusionsMorning biopsychosocial state factors predict glycemic and adherence outcomes in AYA with diabetes and could be a novel intervention target for future behavioural interventions.
Higher susceptibility to 6 Hz corneal kindling and lower responsiveness to antiseizure drugs in mouse models of Alzheimer's disease
Authors: Vande Vyver Maxime , Barker‐Haliski Melissa , Aourz Najat , Nagels Guy , Bjerke Maria , Engelborghs Sebastiaan , De Bundel Dimitri , Smolders Ilse 
Published: July 2022

AbstractObjectiveEpileptic spikes and seizures seem present early in the disease process of Alzheimer's disease (AD). However, it is unclear how soluble and insoluble amyloid beta (Aβ) and tau proteins affect seizure development in vivo. We aim to contribute to this field by assessing the vulnerability to 6 Hz corneal kindling of young female mice from two well‐characterized transgenic AD models and by testing their responsiveness to selected antiseizure drugs (ASDs).MethodsWe used 7‐week‐old triple transgenic (3xTg) mice that have both amyloid and tau mutations, and amyloid precursor protein Swedish/presenillin 1 dE9 (APP/PS1) mice, bearing only amyloid‐related mutations. We assessed the absence of plaques via immunohistochemistry and analyzed the concentrations of both soluble and insoluble forms of Aβ1–42 and total tau (t‐tau) in brain hippocampal and prefrontal cortical tissue. Seven‐week‐old mice of the different genotypes were subjected to the 6 Hz corneal kindling model. After kindling acquisition, we tested the anticonvulsant effects of three marketed ASDs (levetiracetam, brivaracetam, and lamotrigine) in fully kindled mice.ResultsNo Aβ plaques were present in either genotype. Soluble Aβ1–42 levels were increased in both AD genotypes, whereas insoluble Aβ1–42 concentrations were only elevated in APP/PS1 mice compared with their respective controls. Soluble and insoluble forms of t‐tau were increased in 3xTg mice only. 3xTg and APP/PS1 mice displayed more severe seizures induced by 6 Hz corneal kindling from the first stimulation onward and were more rapidly kindled compared with control mice. In fully kindled AD mice, ASDs had less‐pronounced anticonvulsive effects compared with controls.SignificanceMutations increasing Aβ only or both Aβ and tau in the brain enhance susceptibility for seizures and kindling in mice. The effect of ASDs on seizures measured by the Racine scale is less pronounced in both investigated AD models and suggests that seizures of young AD mice are more difficult to treat.