bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of labour costs on wood harvesting costs and timber provision
Authors: Bont Leo G. , Schweier Janine , Temperli Christian 
Published: November 2023

AbstractEfficient forest operations are essential for forest enterprises, who provide wood and numerous ecosystem services for the society. Important factors influencing the efficiency of forest operations, and thus the harvesting costs, are the level of mechanization, the harvesting method applied, the forest road network, and the training of the labourers. The cost of labour, i.e. salaries, is another important driver of harvesting costs. However, its effect on and relative importance for overall harvesting costs is poorly described in the scientific literature. Thus, this study aims to analyse the influence of labour costs in more detail, especially on the country-wide wood harvesting potentials. In addition, we aimed to cross-compare the effect of labour costs with the effect of switching to a more efficient harvesting method. For this purpose, we calculated timber harvesting costs with varying salaries for all sample plots of the Swiss National Forest Inventory (NFI) for both, the currently applied harvesting method recorded in the NFI, and the potential best suitable harvesting method. A 1% change in labour costs affects harvesting costs by 0.33–0.77%, depending on the harvesting method applied. The influence is larger for systems that involve a large share of motor-manual work and for cable-based methods. Changing labour costs by ± 30% affects the number of plots for which timber harvesting is economically feasible, by 5 to 15 percent points. The effect of switching from the current to the best suitable harvesting method is comparable to that of reducing labour costs by 15–30%. These results indicate that the efficiency of wood harvesting can be increased with further mechanization and does not require cutting salaries of forestry personnel. In that, our results may inform forestry planning and policy making at regional to national level.
Optimization of rainfall thresholds for landslide early warning through false alarm reduction and a multi-source validation
Authors: Nocentini Nicola , Medici Camilla , Barbadori Francesco , Gatto Alessio , Franceschini Rachele , del Soldato Matteo , Rosi Ascanio , Segoni Samuele 
Published: November 2023

AbstractThis study proposes an innovative approach to develop a regional-scale landslide forecasting model based on rainfall thresholds optimized for operational early warning. In particular, it addresses two main issues that usually hinder the operational implementation of this kind of models: (i) the excessive number of false alarms, resulting in civil protection system activation without any real need, and (ii) the validation procedure, usually performed over periods too short to guarantee model reliability. To overcome these limitations, several techniques for reducing the number of false alarms were applied in this study, and a multiple validation phase was conducted using data from different sources. An intensity-duration threshold system for each of the five alert zones composing the Liguria region (Italy) was identified using a semiautomatic procedure called MaCumBA, considering three levels of criticality: low, moderate, and high. The thresholds were developed using a landslide inventory collected from online newspapers by a data mining technique called SECaGN. This method was chosen to account for only those events that echo on the Internet and therefore impact society, ignoring landslides occurred in remote areas, not of interest for civil protection intervention, which would adversely affect the model performance because they would result in false alarms. A calibration phase was performed to minimize the impact of false alarms, allowing at least one false alarm per year over the moderate criticality level. In addition, an innovative approach to include antecedent rainfall as the third dimension of the intensity-duration thresholds was applied, generating a consistent reduction in false alarms. The results were validated through an independent landslide inventory and were compared with (i) the alert issued by the regional civil protection agency to observe the improvements achieved with the proposed model and to evaluate to what extent the proposed model is consistent with the assessments of the civil protection and (ii) a dataset of the national states of emergency to verify the suitability of the developed thresholds for alerting citizens. The thresholds obtained showed high predictive capabilities, confirming their suitability for implementation in an operational landslide early warning system.
Basin boundary seismic effects in Mexico City southern region
Authors: Mayoral Juan Manuel , Pérez Mauricio 
Published: November 2023

AbstractRapid changes in geotechnical and geological ground conditions lead to significant ground motion variability. This condition mainly occurs at the so-called basin edges, where there is an abrupt transition between soft highly compressible soils and stiffer materials. This problem becomes more relevant in areas where ground subsidence drastically changes the dynamic response of high plasticity clay deposits, such as those found in Mexico City, due to fundamental site period evolution with time. This paper presents site response analyses at an abrupt transition area in the southeast Mexico City region, along the edges of the Xochimilco-Chalco lakes. Considerable damage associated with three-dimensional wave propagation effects was observed in this zone during the September 2017 Puebla-Mexico earthquake. A series of three-dimensional finite difference numerical models of the basin edge were developed to evaluate ground motion variability, considering topographic effects and soil non-linearities. Good agreement between the computed response and the observed damage during the 2017 Puebla-Mexico earthquake reconnaissance was found. In addition, several normal and subduction events with a return period of 250 years were considered to evaluate the effect that frequency content, and strong ground motion duration have on the soil response variability. From the results gathered here, it was established the relevance of accounting for three-dimensional wave propagation fields to assess site effects at basin-edge zones properly and to be able to implement proper risk mitigation measurements at these zones.
Defaults and effortful tasks
Authors: Behlen Lars , Himmler Oliver , Jäckle Robert 
Published: November 2023

AbstractNothing is known about the effectiveness of defaults when moving the target outcomes requires substantial effort. We conduct two field experiments to investigate how defaults fare in such situations: we change the university exam sign-up procedure in two study programs to “opt-out” (a) for a single exam, and (b) for many exams. Both interventions increase task uptake (exam sign-up). Concerning the outcomes which require effort, we find no effects for many exams. For a single exam, the opt-out increases task completion (exam participation) in the study program where the default arguably entails stronger endorsement. Within this program, the effects on successful task completion (exam passing) are heterogeneous: treated students who in the past were willing to communicate with the university (responsive individuals) invest more effort into exam preparation and are more likely to pass the exam than their control counterparts.For non-responsive individuals, we find increased sign-ups but no effects on the target outcomes. Defaults can thus be effective and may be an attractive policy option even when the target outcome requires substantial effort provision. It is, however crucial that the interventions target the appropriate individuals.
Combining machine learning and optimization for the operational patient-bed assignment problem
Authors: Schäfer Fabian , Walther Manuel , Grimm Dominik G. , Hübner Alexander 
Published: November 2023

AbstractAssigning inpatients to hospital beds impacts patient satisfaction and the workload of nurses and doctors. The assignment is subject to unknown inpatient arrivals, in particular for emergency patients. Hospitals, therefore, need to deal with uncertainty on actual bed requirements and potential shortage situations as bed capacities are limited. This paper develops a model and solution approach for solving the patient bed-assignment problem that is based on a machine learning (ML) approach to forecasting emergency patients. First, it contributes by improving the anticipation of emergency patients using ML approaches, incorporating weather data, time and dates, important local and regional events, as well as current and historical occupancy levels. Drawing on real-life data from a large case hospital, we were able to improve forecasting accuracy for emergency inpatient arrivals. We achieved up to 17% better root mean square error (RMSE) when using ML methods compared to a baseline approach relying on averages for historical arrival rates. We further show that the ML methods outperform time series forecasts. Second, we develop a new hyper-heuristic for solving real-life problem instances based on the pilot method and a specialized greedy look-ahead (GLA) heuristic. When applying the hyper-heuristic in test sets we were able to increase the objective function by up to 5.3% in comparison to the benchmark approach in [40]. A benchmark with a Genetic Algorithm shows also the superiority of the hyper-heuristic. Third, the combination of ML for emergency patient admission forecasting with advanced optimization through the hyper-heuristic allowed us to obtain an improvement of up to 3.3% on a real-life problem.
Transdisciplinary Learning Opportunities: Exploring Differences in Complex Thinking Skill Development Between STEM and Non-STEM Majors
Authors: Amelink Catherine T. , Grote Dustin M. , Norris Matthew B. , Grohs Jacob R. 
Published: November 2023

AbstractAs higher education institutions look to educate and graduate degree earners that have the skills and knowledge necessary to design, communicate, and collaborate in ways that allow for innovative solutions to complex socio-technical challenges, new approaches to educational efforts are being considered and implemented. Institutional responses have included new courses that have a transdisciplinary focus and embedded course experiences that use problem-based approaches coupled with cross-disciplinary team exposure. Often these initiatives have a singular thematic focus (i.e., sustainability). Little is known about the efficacy of transdisciplinary learning initiatives, especially those that encompass a breadth of thematic areas, as it relates to development of complex thinking skills and whether these learning environments provide for similar benefits across student majors. This study, conducted at a Research I university, was designed to address this gap in the literature by examining whether a university level learning initiative using transdisciplinary approaches was achieving desired goals to advance undergraduate students’ complex thinking skills. Findings among the respondents (n = 592) indicate that the initiative is advancing fundamental complex thinking skills in that specific courses allow students to learn about other disciplines and provide exposure to different disciplinary perspectives. However, results reveal that across all majors courses would benefit from increased real-world problem-based exposure and opportunities to interact with community stakeholders. Additionally, results suggest that undergraduates may need opportunities to develop a deeper understanding of the complexities that exist in cross-disciplinary collaboration, including how to develop integrated solutions that leverage the strengths of technical and non-technical approaches.
Design and Implementation of an IIoT Driven Information System: A Case Study
Authors: Gupta Shivam , Modgil Sachin , Bhushan Bharat , Sivarajah Uthayasankar , Banerjee Santanu 
Published: November 2023

AbstractInformation systems are critical for companies since they offer quick and easy access to complex and significant data in a structured manner to make informed and effective business decisions. Hence, the objective of this study is to conceptualize and implement an innovative information system in the case study organization. The study identified the requirements for Organizing Vision Theory (OVT) and developed architecture based on Organizational Information Processing Theory (OIPT). This architecture is designed and developed using the Industrial Internet of Things (IIoT) to support a self-organizing vision and enhanced information processing. The study’s contribution lies in developing and executing an integrative architecture of IIoT-driven information systems from the lenses of OVT and OIPT. Further, this study contributes by mapping OVT elements (such as transparency, continuity, and coherence) and OIPT elements (information processing needs and capabilities) to drive value and knowledge through a robust architecture of IIoT-driven information systems. The study also highlights the contribution of IIoT-based information systems to a new knowledge system, facilitating better decision-making by professionals.
Determinants of physical activity during cancer treatment: a longitudinal exploration of psycho-cognitive variables and physician counseling
Authors: Haussmann Alexander , Ungar Nadine , Tsiouris Angeliki , Schmidt Laura I. , Müller Jana , von Hardenberg Jost , Wiskemann Joachim , Steindorf Karen , Sieverding Monika 
Published: November 2023

AbstractIndividuals with cancer are recommended to engage in regular physical activity (PA) even during cancer therapy. The aim of this study was to explore how patient-reported physician PA counseling influences their PA intention and behavior in addition to psycho-cognitive determinants derived from the theory of planned behavior (TPB). A longitudinal study during cancer treatment was conducted among N = 115 patients with breast, prostate, or colorectal cancer (Mage = 58.0, SD = 11.5; 55.7% female). The median time since diagnosis was 2 months, and 19.1% were diagnosed with metastases. Participants provided information on PA counseling by their physicians and on psycho-cognitive variables of the TPB at three measurement points. Additionally, they wore accelerometers for seven days at baseline and three months later. Nearly half of participants (48%) reported basic PA counseling and 30% reported in-depth PA counseling. Patients in poorer health and with lower education reported significantly less in-depth counseling. In addition to patient self-efficacy in performing PA, only in-depth physician PA counseling, but not basic physician counseling, predicted intention for PA four weeks later. Patients’ PA three months after baseline was predicted by patients’ PA at baseline and their intention for PA. Overall, the PA level at baseline was identified as the most important predictor of PA three months later. Nevertheless, physicians seem to have the ability to increase their cancer patients' intention for PA by in-depth counseling.
Mathematical Modality: An Investigation in Higher-order Logic
Authors: Bacon Andrew 
Published: November 2023

AbstractAn increasing amount of contemporary philosophy of mathematics posits, and theorizes in terms of special kinds of mathematical modality. The goal of this paper is to bring recent work on higher-order metaphysics to bear on the investigation of these modalities. The main focus of the paper will be views that posit mathematical contingency or indeterminacy about statements that concern the ‘width’ of the set theoretic universe, such as Cantor’s continuum hypothesis. Within a higher-order framework I show that contingency about the width of the set-theoretic universe refutes two orthodoxies concerning the structure of modal reality: the view that the broadest necessity has a logic of , and the ‘Leibniz biconditionals’ stating that what is possible, in the broadest sense of possible, is what is true in some possible world. Nonetheless, I suggest that the underlying picture of modal set-theory is coherent and has attractions.
The pricing strategies of online grocery retailers
Authors: Aparicio Diego , Metzman Zachary , Rigobon Roberto 
Published: November 2023

AbstractThis paper documents the differences in pricing strategies between online and offline (brick-and-mortar) channels. We collect price data for identical products from leading online grocery retailers in the United States and complement it with offline data for the same products from scanner data. Our findings reveal a consistent pattern: online retailers exhibit higher price dispersion than their offline counterparts. More specifically, online grocers employ price algorithms that amplify price discrimination in three key dimensions: (1) over time (through frequent price changes), (2) across locations (by charging varying prices based on delivery zipcodes), and (3) across sellers (by setting dispersed prices for identical products across rival retailers).
The sound of respondents: predicting respondents’ level of interest in questions with voice data in smartphone surveys
Authors: Höhne Jan Karem , Kern Christoph , Gavras Konstantin , Schlosser Stephan 
Published: November 2023

AbstractWeb surveys completed on smartphones open novel ways for measuring respondents’ attitudes, behaviors, and beliefs that are crucial for social science research and many adjacent research fields. In this study, we make use of the built-in microphones of smartphones to record voice answers in a smartphone survey and extract non-verbal cues, such as amplitudes and pitches, from the collected voice data. This allows us to predict respondents’ level of interest (i.e., disinterest, neutral, and high interest) based on their voice answers, which expands the opportunities for researching respondents’ engagement and answer behavior. We conducted a smartphone survey in a German online access panel and asked respondents four open-ended questions on political parties with requests for voice answers. In addition, we measured respondents’ self-reported survey interest using a closed-ended question with an end-labeled, seven-point rating scale. The results show a non-linear association between respondents’ predicted level of interest and answer length. Respondents with a predicted medium level of interest provide longer answers in terms of number of words and response times. However, respondents’ predicted level of interest and their self-reported interest are weakly associated. Finally, we argue that voice answers contain rich meta-information about respondents’ affective states, which are yet to be utilized in survey research.
Radiation Belt Storm Probes Ion Composition Experiment (RBSPICE) Revisited: In-Flight Calibrations, Lessons Learned and Scientific Advances
Authors: Gkioulidou Matina , Mitchell Donald G. , Manweiler Jerry W. , Lanzerotti Louis J. , Gerrard Andrew J. , Ukhorskiy Aleksandr Y. , Keika Kunihiro , Mouikis Christopher G. , Kistler Lynn M. 
Published: November 2023

AbstractThe Radiation Belt Storm Probes Ion Composition Experiment (RBSPICE) on both the Van Allen Probes spacecraft is a time-of-flight versus total energy instrument that provided ion composition data over the ring current energy (∼7 keV to ∼1 MeV), and electrons over the energy range ∼25 keV to ∼1 MeV throughout the duration of the mission (2012 – 2019). In this paper we present instrument calibrations, implemented after the Van Allen Probes mission was launched. In particular, we discuss updated rate dependent corrections, possible contamination by “accidentals” rates, and caveats concerning the use of certain products. We also provide a summary of the major advances in ring current science, obtained from RBSPICE observations, and their implications for the future of inner magnetosphere exploration.
Sharp Instability Estimates for Bidisperse Convection with Local Thermal Non-equilibrium
Authors: Franchi Franca , Nibbi Roberta , Straughan Brian 
Published: November 2023

Abstract
We analyse a theory for thermal convection in a Darcy porous material where the skeletal structure is one with macropores, but also cracks or fissures, giving rise to a series of micropores. This is thus thermal convection in a bidisperse, or double porosity, porous body. The theory allows for non-equilibrium thermal conditions in that the temperature of the solid skeleton is allowed to be different from that of the fluid in the macro- or micropores. The model does, however, allow for independent velocities and pressures of the fluid in the macro- and micropores. The threshold for linear instability is shown to be the same as that for global nonlinear stability. This is a key result because it shows that one may employ linearized theory to ensure that the key physics of the thermal convection problem has been captured. It is important to realize that this has not been shown for other theories of bidisperse media where the temperatures in the macro- and micropores may be different. An analytical expression is obtained for the critical Rayleigh number and numerical results are presented employing realistic parameters for the physical values which arise.

Article Highlights

A two-temperature regime for a bidisperse Darcy porous medium is proposed to study the thermal convection problem.

The optimal result of coincidence between the linear instability and nonlinear stability critical thresholds is proven.

Numerical analysis enhances that the scaled heat transfer coefficient between the fluid and solid and the porosity-weighted conductivity ratio stabilize the problem significantly.
An Analysis of Risk Factors for Hearing Function in Adults Living with Human Immunodeficiency Virus in Gauteng, South Africa
Authors: Sebothoma Ben 
Published: November 2023

AbstractThe aim of this study was to explore risk factors for hearing loss or affecting hearing function in adults living with HIV. A quantitative cross-sectional design was employed. A non-probability purposive sampling method was used to select and recruit 132 participants aged 18 years and above from an HIV clinic within the Academic Hospital in Gauteng Province, South Africa. Participants’ hearing were tested using, video otoscopy, tympanometry, pure tones, and speech audiometry. Of the 22.73% prevalence of hearing loss in the sample, the multiple logistic regression, controlling for other variables, indicated that age (AOR) = 1.049; 95%CI: 1.0005 to 1.0978) (p-value = 0.048) and extended use of antiretroviral therapy (AOR) = 1.0073; 95%CI: 0.9312 to 1.0896)) (p-value = 0.856) were strongly associated with the development of hearing loss. Although the odds of male participants to have hearing loss was 2.3572 (95%CI: 0.9394 to 5.915) compared to females, this association was marginal (p-value = 0.068). Current findings provide evidence for the risk factors for hearing loss in adults living with HIV. Given that an extended use of ART and a higher number of CD4 are strongly associated with hearing loss, these findings raise important implications for a focused monitoring for this population in order to identify early signs of hearing loss and implement timeous intervention to reduce the potential impact of hearing loss.