bluuebunny/crossref_metadata_2025_split huggingface dataset:
Does dispositional optimism affect entrepreneurial success? Evidence from Saudi Arabia
Authors: Ben Fatma Elhem , Dana Léo-Paul , Elleuch Souhir , Ben Mohamed Ezzeddine 
Published: January 2024

AbstractThis study explores the effect of dispositional optimism bias on entrepreneurial success. By reviewing a mixture of previous studies from different disciplines: psychology, business and economics, we predict that this bias can positively affect entrepreneurial success. Based on a sample of 255 entrepreneurs in the Kingdom of Saudi Arabia and using the LOT-R psychometric test to measure the level of dispositional optimism among entrepreneurs, the effect of this variable on entrepreneurial success was tested, and the results show that this bias positively affects entrepreneurial success. Entrepreneurial success was also measured through three different proxies: the level of entrepreneurs’ satisfaction with what has been achieved from their entrepreneurial projects, the variation in the number of employees, and sales growth and the results were stable. We also find that entrepreneurs’ experience, age, and gender can influence entrepreneurial success. Finally, we should view entrepreneurial success not only as a function of traditional variables but also as a function of psychological biases.
Robot-assisted vs laparoscopic bariatric procedures in super-obese patients: clinical and economic outcomes
Authors: Marincola Giuseppe , Procopio Priscilla Francesca , Pennestrì Francesco , Gallucci Pierpaolo , Voloudakis Nikolaos , Ciccoritti Luigi , Greco Francesco , Salvi Giulia , Prioli Francesca , De Crea Carmela , Raffaelli Marco 
Published: January 2024

AbstractThe increased operative time and costs represent the main limitations of robotic technology application to bariatric surgery. Robotic platforms may help the surgeon to overcome the technical difficulties in super-obese (SO, BMI ≥ 50 kg/m2) patients, in which multi-quadrant operations could be challenging. We aimed to evaluate the effect of robot-assisted (R) versus laparoscopic (L) approaches in Single Anastomosis Duodeno-Ileal Bypass with Sleeve Gastrectomy (SADI-S) and Roux-en-Y Gastric Bypass (RYGB) in SO and Super-Super Obese (SSO, BMI ≥ 60 kg/m2) patients in terms of outcomes and cost-effectiveness. Bariatric procedures performed from 2012 to 2023 were retrospectively reviewed. The inclusion criteria were BMI ≥ 50 kg/m2, primary SADI-S or RYGB. Operative time (OT), early complications, post-operative stay (POS), overall costs and follow-up data were analyzed. A subgroup analysis for surgical procedures and SSO patients was also performed. Among 4596 patients, 174 RYGB and 91 SADI-S in BMI ≥ 50 kg/m2 patients were selected. After Propensity Score Matching analysis, two groups of patients were identified (laparoscopic and robot-assisted), each one composed of 18 RYGB and 26 SADI-S. Intraoperative and post-operative complication rates and POS were comparable. Mean OT was longer in robotic procedures compared with laparoscopy (199.1 ± 65.7 and 109.5 ± 39.1 min, respectively, p < 0.001). The difference in OT was eliminated after only SSO patients were included in the analysis (172.7 ± 24.1 vs 152.6 ± 26.2 min for R-SADI-S and L-SADI-S, respectively, p = 0.107). Robotic surgeries were associated with higher costs (8134.6 ± 1886.7 and 2386.7 ± 388.2 € in R-RYGB and L-RYGB, respectively; 7996.6 ± 873.1 and 3954.6 ± 631.1 € in R-SADI-S and L-SADI-S). Despite increased costs, robotic approach may represent an added value in more complex cases such as SSO patients.
Ethnic disparities and COVID-19 pneumonia in Ireland: a single-centre descriptive study of hospitalised patients in a tertiary university teaching hospital
Authors: O’Regan Rhea , Harnedy Finbarr , Reynolds Bearach , Cormican Liam 
Published: January 2024

AbstractIn this study, we aim to describe the demographic, clinical and imaging characteristics, treatment course and subsequent outcomes of the first 116 cases presenting to a tertiary Dublin hospital with COVID-19 infection and to compare whether ethnic minority background was a risk factor for poorer disease outcomes in this cohort. Of 116 cases analysed, 100 (86%) patients presented from the community, 6 (5%) from care homes and 10 (9%) were existing inpatients. Fifty-four (46%) patients identified as being from an ethnic minority group. One hundred fourteen (98%) patients reported two or more symptoms at time of diagnosis with 81 (70%) patients having confirmed radiological findings of COVID-19 infection. Median duration of symptoms prior to hospital presentation was 6 days (IQR 3–10 days). The median age at presentation was 52 years (IQR 43–65). Co-morbidities recorded included hypertension, hyperlipidaemia, type 2 diabetes mellitus, underlying respiratory disease, previous or current malignancy and current smoker. Twenty-six patients (22%) required ICU admission, 20 (76.9%) of these were from all other ethnic groups combined and 6 (10%) from White Irish group. Adjusting for variables of age, ethnicity and gender, all other ethnic groups combined were five times more likely to require ICU admission than White Irish group (Table 5). Patients from all other ethnic groups combined admitted to ICU were significantly younger than patients from White Irish group (OR 50.85 vs 62.83,P = 0.012). Our hospital’s catchment area serves a wide-ranging and diverse population with many ethnic minority groups represented. Our data demonstrated that there was a significant overrepresentation of a younger cohort of patients from ethnic minority groups admitted to ICU with COVID-19 infection with less co-morbidities than that of the White Irish group.
A Review on the State of the Art in Frugivory and Seed Dispersal on Islands and the Implications of Global Change
Authors: Nogales Manuel , McConkey Kim R. , Carlo Tomás A. , Wotton Debra M. , Bellingham Peter J. , Traveset Anna , González-Castro Aarón , Heleno Ruben , Watanabe Kenta , Ando Haruko , Rogers Haldre , Heinen Julia H. , Drake Donald R. 
Published: January 2024

AbstractWe provide an overview of the current state of knowledge of island frugivory and seed dispersal and identify knowledge gaps that are important for fundamental research on—and applied conservation of—island ecosystems. We conducted a systematic literature search of frugivory and seed dispersal on islands, omitting large, continental islands. This revealed a total of 448 studies, most (75%) published during the last two decades, especially after 2010. Nearly 65% of them were focused on eight archipelagos. There is a paucity of studies in Pacific archipelagos near Asia and Australia, and in the Indian Ocean. Data on island frugivory and seed dispersal are diverse but highly uneven in geographic and conceptual coverage. Despite their limited biodiversity, islands are essential reservoirs of endemic plants and animals and their interactions. Due to the simplicity of insular ecosystems, we can assess the importance of seed dispersal theory and mechanisms at species and community levels. These include the ecological and biogeographical meaning and prevalence of non-standard mechanisms of seed dispersal on islands; the seed dispersal effectiveness and the relative roles of different frugivore guilds (birds and reptiles being the most important); and patterns of community organization and their drivers as revealed by interaction networks. Island systems are characterized by the extinction of many natives and endemics, and high rates of species introductions. Therefore, understanding how these losses and additions alter seed dispersal processes has been a prevailing goal of island studies and an essential foundation for the effective restoration and conservation of islands.
Interconnected or Disconnected? A Review of Sustainability, Resilience, and Sustainable Business Model Constructs in the Academic Business Literature
Authors: Kassier Liesel 
Published: January 2024

Abstract
The global climate change and resource depletion crisis require rethinking business models that drive the production and consumption of goods and services. This requires transdisciplinary and systemic reconfiguration and a critical evaluation of traditional economic, business, and management constructs. This research provides a systematic literature review of how the constructs of sustainability, resilience, and sustainable business models have been defined and applied in the economic, business, and management academic literature from 1990 until 2022. The key contributions of this paper are (1) a review of how sustainability, resilience, and sustainable business models have been defined in the literature, (2) an identification of the interfaces and lack thereof between these constructs, and (3) an outline of the gaps and limitations and need for further research to address the knowledge gaps.
RF energy harvesters for wireless sensors, state of the art, future prospects and challenges: a review
Authors: Khan Nasir Ullah , Khan Farid Ullah , Farina Marco , Merla Arcangelo 
Published: January 2024

AbstractThe power consumption of portable gadgets, implantable medical devices (IMDs) and wireless sensor nodes (WSNs) has reduced significantly with the ongoing progression in low-power electronics and the swift advancement in nano and microfabrication. Energy harvesting techniques that extract and convert ambient energy into electrical power have been favored to operate such low-power devices as an alternative to batteries. Due to the expanded availability of radio frequency (RF) energy residue in the surroundings, radio frequency energy harvesters (RFEHs) for low-power devices have garnered notable attention in recent times. This work establishes a review study of RFEHs developed for the utilization of low-power devices. From the modest single band to the complex multiband circuitry, the work reviews state of the art of required circuitry for RFEH that contains a receiving antenna, impedance matching circuit, and an AC-DC rectifier. Furthermore, the advantages and disadvantages associated with various circuit architectures are comprehensively discussed. Moreover, the reported receiving antenna, impedance matching circuit, and an AC-DC rectifier are also compared to draw conclusions towards their implementations in RFEHs for sensors and biomedical devices applications.
Response surface methodology for optimization of biodiesel production by the Penicillium commune NRC 2016 and its mutants
Authors: Abdelhamid Sayeda Abdelrazek , El-Shatoury Einas Hamed , Asker Mohsen Selim , Abd-El-Aal Samir Khalef , Attallah Ashraf Gamil , Abo Elsoud Mostafa M. , Mohamed Sahar Saleh 
Published: January 2024

Abstract
With increasing energy requirements and limited fuel resources, finding cheap renewable sources is essential. The objective of our current economic study is to enhance biodiesel production from the Penicillium commune, NRC 2016. Four mutagenic agents were used to improve the lipid production from P. commune NRC 2016: gamma radiation, ethyl methanesulfonate (EMS), ethidium bromide (Et Br), and sodium azide (NaN3). The Inter-Simple-Simplece Repeats molecular (ISSR) marker was used to compare the wild type of P. commune NRC 2016 and the resulting mutants. The results showed a major difference between the wild type and its mutants. Response surface methodology was used to optimize the culture conditions for lipid production by P. commune NRC 2016, and the induced mutants used hydrolysate that was produced from bagasse using Bacillus cereus 3SME. The maximum lipid content (g/l) for P. commune NRC 2016, P. commune NRC 2016–1, P. commune NRC 2016–2, and P. commune NRC 2016–3 were 2.01, 2.55, 1.71, and 2.27, respectively. Gas chromatographic analysis was used for biodiesel produced from P. commune NRC 2016 wild type, and its mutants were mainly C16–C18, which is suitable for transesterification. The physical properties, such as density, viscosity, cloud point, pour point, and cetane number, of the biodiesel from P. commune NRC 2016 and its mutants were similar to those of standard biodiesel and could be applied on a large scale. The biodiesels produced through P. commune NRC 2016 and its mutants can be utilized on a broad scale as eco-friendly products obtained from a low-cost carbon source.
The use of drone congregation behaviour for population surveys of the honey bee Apis cerana
Authors: Hagan Thomas , Lim Julianne , Buchmann Gabriele , Ding Guiling , Oldroyd Benjamin P. , Gloag Rosalyn 
Published: January 2024

AbstractHoney bees (Apis spp.) are important pollinators in many natural and agro-ecosystems across the world. Effective means of surveying wild populations are therefore key to their conservation and management. One available survey method infers honey bee colony density from the genotype of drones (males) sampled from sites known as Drone Congregation Areas (DCAs). While this approach has been commonly used for the Western honey bee (A. mellifera), its feasibility for other Apis species is unknown. Here, we investigate drone congregation behaviour in the Asian honey bee Apis cerana in north-east Australia and its suitability for inferring colony density. As this A. cerana population is invasive, surveys in this case can aid in monitoring the population’s growth and spread. Over 5 years, we identified 30 DCAs, many of which were stable across time. DCAs were sheltered areas beside tree-lines or openings in the forest canopy. A. cerana drones joined DCAs during 1–2-h afternoon intervals and could be sampled at heights of 2–24 m via adhesive lines attached to helium balloons carrying lures coated in queen pheromone. Drones were more likely to be present at a DCA as temperature increased, though abiotic factors did not predict overall drone abundance. Drones could be sampled in low numbers even where colony density was extremely low. Based on the genotyping and inferred sibship of drones sampled at DCAs between 2016 and 2021, we estimate population density in Australia’s A. cerana to be in the range 1.1–8.1 colonies/km2. This extrapolates to a total population size in the range 11,000–83,000 colonies, with more refined estimates requiring better knowledge of drone flight distance and the effect of habitat on colony density. We conclude that population surveys based on drones from DCAs are possible for A. cerana and propose that this approach be part of a toolkit of methods used to monitor Asian honey bee populations in both their native and invasive ranges.
A communication-based identification of critical drones in malicious drone swarm networks
Authors: Teng Min , Gao Chao , Wang Zhen , Li Xuelong 
Published: January 2024

AbstractAccurate identification of critical malicious drones is crucial for optimizing directed energy attacks and maximizing their effectiveness. However, current studies on critical drone identification are still in the preliminary stage and almost rely on the traditional centrality methods that do not address the distributed features of drone swarms. This leads to inaccurate identification of critical drones, resulting in the low efficiency of directed energy attacks. Therefore, this paper proposes a new critical drone identification method based on the distributed features, communication intensity, and communication scale of drones. Specifically, this paper first constructs a dynamic communication prediction network (DCPN) of drone swarms based on the 3D position and interaction range, which predicts the dynamic communication between drones. Then, this paper proposes a new method called dynamic giant connected component (GCC)-based scale-intensity centrality (DGSIC) that combines the local, global, and community structure of DCPN to identify critical nodes with stronger communication capabilities. The dynamic strategy involves the iterative identification of one critical node at each step, considering the evolving network configuration and ensuring the identified node remains the most critical in the present network. Additionally, the prioritization strategy is employed to identify the nodes within the GCC, which can significantly impact the network connectivity and communication. DGSIC optimizes the attack sequence for directed energy attacks, facilitating the rapid dissolution of malicious drone swarms. Extensive experiments in four simulated networks and eight real-world networks demonstrate the superior robustness and cascading failure performance of DGSIC.
Evolution characteristics of fracture volume and acoustic emission entropy of monzogranite under cyclic loading
Authors: Liu Liyuan , Zhang Zhou , Wang Tao , Zhi Sheng , Wang Jiong 
Published: January 2024

AbstractThe volume evolution behavior of rock fissures and the characteristics of acoustic emission under cyclic loading are critical for rock stability analysis. To study the volume change behavior of monzogranite fissures and the characteristics of acoustic emission signals under cyclic loading, we selected samples of monzogranite at − 1600 m from a gold mine located in the Jiaodong Peninsula at a depth of − 1600 m and investigated the samples using triaxial cyclic loading—unloading tests and acoustic emission monitoring. As the volume change behavior of the monzogranite fissures and acoustic emission signals were monitored and recorded, the calculated fracture volume strain ratio coefficient and acoustic emission entropy value were proposed to describe the evolution process of fissures inside the rock. The research results showed that the volume strain ratio curve of the rock fractures exhibited a logarithmic variation characteristic during the cyclic loading and unloading, and the fracture volume strain ratio better reflected the relative scale of the internal fracture strain in the rock to the total volume strain. The acoustic emission entropy value reflected the crack evolution behavior during the loading and failure processes, which was a rapid decline in the initial stage of loading and a rapid upward trend in the failure stage. The observed “V”-shaped change in the acoustic emission entropy can be used as an early warning for rock failure. The research results can provide theoretical guidance for rock stability analysis.
Temporal network compression via network hashing
Authors: Vaudaine Rémi , Borgnat Pierre , Gonçalves Paulo , Gribonval Rémi , Karsai Márton 
Published: January 2024

AbstractPairwise temporal interactions between entities can be represented as temporal networks, which code the propagation of processes such as epidemic spreading or information cascades, evolving on top of them. The largest outcome of these processes is directly linked to the structure of the underlying network. Indeed, a node of a network at a given time cannot affect more nodes in the future than it can reach via time-respecting paths. This set of nodes reachable from a source defines an out-component, which identification is costly. In this paper, we propose an efficient matrix algorithm to tackle this issue and show that it outperforms other state-of-the-art methods. Secondly, we propose a hashing framework to coarsen large temporal networks into smaller proxies on which out-components are more easily estimated, and then recombined to obtain the initial components. Our graph hashing solution has implications in privacy respecting representation of temporal networks.
Residential location choice: an investigation of transportation, public facilities, and social factors
Authors: Rajabi Hamed , Mirzahossein Hamid , Hosseinian Seyed Mohsen , Jin Xia 
Published: January 2024

AbstractResidential location choice is a crucial topic in transportation planning research since land use as well as residential land use can significantly affect a city's attractiveness for development and residence. Understanding the factors that influence households in their residential location choice is essential for policymakers to evaluate the effect of their decisions. In this study, the impact of transportation factors on the attractiveness of residential areas was investigated in Qazvin city, Iran, using the stated preference (SP) method and structural equation modeling (SEM). The results indicated that the type of housing and private house preference were significant factors influencing the residential location choice. Additionally, proximity to health centers, low pollution levels, and access to public transportation and taxi stations were the top priorities for residents when choosing a place to live. Notably, households with children in education had a greater emphasis on air pollution and the proximity to taxi stations, as these factors could affect their children's health and education. Overall, the findings suggested that transportation factors played a critical role in the residential location choice and that policymakers should prioritize public transportation and taxi services, as well as reduce pollution levels, to make residential areas more attractive and livable for Qazvin residents.
Assessing ChatGPT's use of person-first language in healthcare conversations
Authors: Hackl Ellen 
Published: January 2024

AbstractThe conversational chatbot ChatGPT has attracted significant attention from both the media and researchers due to its potential applications, as well as concerns surrounding its use. This study evaluates ChatGPT’s efficacy in healthcare education, focusing on the inclusivity of its language. Person-first language which prioritizes the individual over their medical condition, is an important component of inclusive language in healthcare.The aim of the present study was to test ChatGPT’s responses to non-inclusive, non-patient-first, judgmental, and often offensive language inputs. Provocative phrases based on a list of “do not use” recommendations for inclusive language were selected and used to formulate input questions. The occurrences of each provocative phrase or its substitute(s) within the responses generated by ChatGPT were counted to calculate the Person-First Index, which measures the percentage of person-first language.The study reveals that ChatGPT avoids using judgmental or stigmatized phrases when discussing mental health conditions, instead using alternative person-first language that focuses on individuals rather than their conditions, both in response to questions and in correcting English grammar. However, ChatGPT exhibits less adherence to person-first language in responses related to physiological medical conditions or addictions, often mirroring the language of the inputs instead of adhering to inclusive language recommendations. The chatbot used person-first language more frequently when referring to “people” rather than "patients."In summary, the findings show that despite the controversy surrounding its use, ChatGPT can contribute to promoting more respectful language, particularly when discussing mental health conditions.