bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of user‐interfaces for controlling movements of virtual minimally invasive surgical instruments
Authors: Shabir Dehlela , Anbatawi Malek , Padhan Jhasketan , Balakrishnan Shidin , Al‐Ansari Abdulla , Abinahed Julien , Tsiamyrtzis Panagiotis , Yaacoub Elias , Mohammed Amr , Deng Zhigang , Navkar Nikhil V. 
Published: April 2022

AbstractBackgroundRecent tele‐mentoring technologies for minimally invasive surgery (MIS) augments the operative field with movements of virtual surgical instruments as visual cues. The objective of this work is to assess different user‐interfaces that effectively transfer mentor's hand gestures to the movements of virtual surgical instruments.MethodsA user study was conducted to assess three different user‐interface devices (Oculus‐Rift, SpaceMouse, Touch Haptic device) under various scenarios. The devices were integrated with a MIS tele‐mentoring framework for control of both manual and robotic virtual surgical instruments.ResultsThe user study revealed that Oculus Rift is preferred during robotic scenarios, whereas the touch haptic device is more suitable during manual scenarios for tele‐mentoring.ConclusionA user‐interface device in the form of a stylus controlled by fingers for pointing in 3D space is more suitable for manual MIS, whereas a user‐interface that can be moved and oriented easily in 3D space by wrist motion is more suitable for robotic MIS.
Is Covid‐19 changing sustainable consumer behavior? A survey of Italian consumers
Authors: Dangelico Rosa Maria , Schiaroli Valerio , Fraccascia Luca 
Published: April 2022

AbstractSince the beginning of 2020, the world has been hit by the SARS‐CoV‐2 virus that causes Covid‐19. To hamper its spread, policymakers of many countries have put in place strong countermeasures, including lockdowns, that have led to significant changes in people's lifestyles and daily routines. This article aims at assessing the changes caused by Covid‐19 in sustainable consumer behavior under multiple perspectives, contributing to advance knowledge at the intersection between consumer dynamics and sustainable consumer behavior literature. A survey was conducted on 1.535 Italian consumers between December 2020 and February 2021. Respondents were asked to assess the extent to which their consumption behavior—purchase frequency, willingness to pay a premium price, sense of moral duty to purchase, social influence to purchase—related to several categories of sustainable products changed due to the pandemic, as well as the extent to which the pandemic impacted on many other aspects, including their environmental awareness, concern, and habits. Results show that Covid‐19 generated relevant changes. Consumers have increased their purchase frequency and willingness to pay for sustainable products, show growing attention to environmental issues, and behave more sustainably. Further, the extent of change is strongly affected by socio‐demographic variables, such as gender, age, income, and education. For instance, women reported a higher shift towards sustainable consumption and behavior than men. Understanding these changes is important to guide marketers and policymakers to respond promptly and effectively to them and to leverage on them to foster a transition towards a more sustainable society.
Calculating power for the Finkelstein and Schoenfeld test statistic for a composite endpoint with two components
Authors: Zhou Thomas J. , LaValley Michael P. , Nelson Kerrie P. , Cabral Howard J. , Massaro Joseph M. 
Published: April 2022

AbstractThe Finkelstein and Schoenfeld (FS) test is a popular generalized pairwise comparison approach to analyze prioritized composite endpoints (eg, components are assessed in order of clinical importance). Power and sample size estimation for the FS test, however, are generally done via simulation studies. This simulation approach can be extremely computationally burdensome, compounded by increasing number of composite endpoints and with increasing sample size. Here we propose an analytical solution to calculate power and sample size for commonly encountered two‐component hierarchical composite endpoints. The power formulas are derived assuming underlying distributions in each of the component outcomes on the population level, which provide a computationally efficient and practical alternative to the standard simulation approach. Monte Carlo simulation results demonstrate that performance of the proposed power formulas are consistent with that of the simulation approach, and have generally desirable objective properties including robustness to mis‐specified distributional assumptions. We demonstrate the application of the proposed formulas by calculating power and sample size for the Transthyretin Amyloidosis Cardiomyopathy Clinical Trial.
Alliance performance and subsequent make‐or‐ally choices: Evidence from the aircraft manufacturing industry
Authors: Ren Charlotte R. , Mulotte Louis , Dussauge Pierre , Anand Jaideep 
Published: April 2022

AbstractResearch SummaryWe examine how the performance of a firm's prior alliances influences its propensity to persist with the alliance mode or switch to independent operations in the context of new product introductions (NPIs). Drawing on the behavioral theory of the firm (BTOF), we argue that a firm's alliance performance has a U‐shaped effect on its likelihood of undertaking the subsequent NPI independently and that competitive intensity strengthens this U‐shaped relationship. We also predict that firms with above‐aspiration alliance performance are more likely to achieve breakthrough performance in the subsequent NPI if they switch to independence than if they continue to ally. Data on NPIs in the global aircraft manufacturing industry (1944–2000) support our hypotheses. Our study extends the alliance literature and contributes to research on how firm performance influences subsequent strategic choices.Managerial SummaryThe dilemma of whether to continue or exit an alliance or relationship is a common one for individuals, countries, and firms. Our study examines firms' strategic decision to switch to independent operations after having partnered with other firms. Using the aircraft product development context, we show that firms that make such a change in their strategy are the ones that performed either much better or much worse than what they expected. Firms with alliance performance close to their expectations tend to persist with their current strategy. Of the firms that change their strategy, the high performers benefit much more from changing their strategy than low performers. We provide insights regarding when it is preferable for managers to continue to ally or to switch to independence, especially in launching new products.
Enhanced Thermoelectric Power Factor in Carrier‐Type‐Controlled Platinum Diselenide Nanosheets by Molecular Charge‐Transfer Doping
Authors: Youn Seonhye , Kim Jeongmin , Moon Hongjae , Kim Jae‐Keun , Jang Juntae , Chang Joonyeon , Lee Takhee , Kang Keehoon , Lee Wooyoung 
Published: April 2022

Abstract2D transition metal dichalcogenides (TMDCs) have revealed great promise for realizing electronics at the nanoscale. Despite significant interests that have emerged for their thermoelectric applications due to their predicted high thermoelectric figure of merit, suitable doping methods to improve and optimize the thermoelectric power factor of TMDCs have not been studied extensively. In this respect, molecular charge‐transfer doping is utilized effectively in TMDC‐based nanoelectronic devices due to its facile and controllable nature owing to a diverse range of molecular designs available for modulating the degree of charge transfer. In this study, the power of molecular charge‐transfer doping is demonstrated in controlling the carrier‐type (n‐ and p‐type) and thermoelectric power factor in platinum diselenide (PtSe2) nanosheets. This, combined with the tunability in the band overlap by changing the thickness of the nanosheets, allows a significant increase in the thermoelectric power factor of the n‐ and p‐doped PtSe2 nanosheets to values as high as 160 and 250 µW mK−2, respectively. The methodology employed in this study provides a simple and effective route for the molecular doping of TMDCs that can be used for the design and development of highly efficient thermoelectric energy conversion systems.
A New Reversible Thermosensitive Liquid–Solid TENG Based on a P(NIPAM‐MMA) Copolymer for Triboelectricity Regulation and Temperature Monitoring
Authors: Feng Min , Kong Xiang , Feng Yange , Li Xiaojuan , Luo Ning , Zhang Liqiang , Du Changhe , Wang Daoai 
Published: April 2022

AbstractIntelligent and highly precise control of liquid–solid triboelectricity is of great significance for energy collection and electrostatic prevention. However, most of the traditional methods are irreversible and complex, greatly limiting their applicability. Here, a reversible thermosensitive liquid–solid triboelectric nanogenerator (L–S TENG) is assembled based on P(NIPAM‐MMA) (PNM) copolymer for tunable triboelectrification. Through temperature regulation, the conformation between acylamino and isopropyl groups changes with the interfacial wettability and triboelectricity of PNM. When the temperature rises from 20 to 60 °C, the contact angle of PNM rises from 22.49° to 82.08°, and the output of the PNM‐based L–S TENG shows a 27‐fold increase. In addition, this transformation is reversible and repeatable with excellent durability for up to 60 days. Other organic liquids, such as glycol, exhibit positive response to temperature for this PNM‐based L–S TENG. Polymers including polymethylmethacrylic, polytetrafluoroethylene, and polyimide are verified to not have such thermo‐sensitivity properties. In addition, a droplet‐based wireless warning system based on PNM is designed and actuated for monitoring specific temperature. The introduction of thermal PNM not only provides new material for reversible manipulation of L–S TENG, but also provides a new method for designing highly sensitive temperature warning sensors.
An experimental analysis of risk effects in attacker‐defender games
Authors: Holt Charles A. , Sahu Ricky , Smith Angela M. 
Published: April 2022

AbstractThis paper reports results of two‐person games in which a defender chooses between high and low alert states, and an attacker chooses whether to attack or wait. Low alerts and attacks are risky because successful attacks are costly for the defender and failed attacks are costly for the attacker. The Nash equilibrium, even allowing for risk aversion, has the stark property that a reduction in the attacker's cost has no effect on the attack probability. In contrast, high attack costs are associated with lower attack rates in a laboratory experiment conducted with monetary payoffs. The empirical analysis is focused on explaining strategic behavior as it is affected by risk aversion and behavioral “noise” in strategic best responses. A model incorporating both of these features outperforms others. Generalized comparative static results for changes in attack costs and risk aversion are proved in the context of a nonparametric quantal response equilibrium.
Forecasting lake‐/sea‐effect snowstorms, advancement, and challenges
Authors: Fujisaki‐Manome Ayumi , Wright David M. , Mann Greg E. , Anderson Eric J. , Chu Philip , Jablonowski Christiane , Benjamin Stanley G. 
Published: April 2022

AbstractLake‐/sea‐effect snow forms typically from late fall to winter when a cold air mass moves over the warmer, large water surface. The resulting intense snowfall has many societal impacts on communities living in downwind areas; hence, accurate forecasts of lake‐/sea‐effect snow are essential for safety and preparedness. Forecasting lake‐/sea‐effect snow is extremely challenging, but over the past decades the advancement of numerical forecast models and the expansion of observational networks have incrementally improved the forecasting capability. The recent advancement includes numerical forecast models with high spatiotemporal resolutions that allow simulating vigorous snowstorms at the kilometer‐scale and the frequent inclusion of radar observations in the model. This combination of more accurate weather prediction models as well as ground‐based and remotely sensed observations has aided operational forecasters to make better lake‐/sea‐effect snow forecasts. A remaining challenge is that many observations of precipitation, surface meteorology, evaporation, and heat supply from the water surface are still limited to being land‐based and the information over the water, particularly offshore, remains a gap. This primer overviews the basic mechanisms for lake‐/sea‐effect snow formation, evolution of forecast techniques, and challenges to be addressed in the future.This article is categorized under:
Science of Water > Water Extremes
Science of Water > Water and Environmental Change
Science of Water > Methods
Interplay between magnetism and transport in the CuCr1‐xTi1+xS4 thiospinel: evidence for a strong asymmetry between p‐ and n‐type transport
Authors: Hébert Sylvie , Lebedev Oleg , Maignan Antoine 
Published: April 2022

AbstractA series of SPS densified ceramics with five compositions of the CuCr1‐xTi1+xS4 thiospinel has been synthesized, with x close to 0. Their structural characterization by transmission electron microscopy confirms the spinel cubic structure and coupled EDX analysis reveals a homogeneous cation distribution which content follows x. Interestingly, the transport properties as attested by Seebeck and Hall coefficient measurements demonstrate the existence of a sign change of the majority charge carriers near x=0. Moreover, values of electrical resistivity are found to be much lower and metallic for x<0 than for x>0, the latter showing a variable range hopping mechanism. When combined to the thermal conductivity values, this leads to asymmetric thermoelectric figure of merit ZT values at 700 K, near 0.2 and 0.01 for p and n type sides, respectively. These p and n type regimes are also characterized by different magnitudes of negative magnetoresistance, and moreover, by a change of sign of the magnetothermopower at low T, from positive for p type to negative for electron doped compositions. This study shows the existence of a correlation between charges and spins for both n and p types of the CuCr1‐xTi1+xS4 thiospinel, leading to an unusual positive sign of magnetothermopower in the p type case.
Next-Generation Personalized Investment Recommendations
Authors: McCreadie Richard , Perakis Konstantinos , Srikrishna Maanasa , Droukas Nikolaos , Pitsios Stamatis , Prokopaki Georgia , Perdikouri Eleni , Macdonald Craig , Ounis Iadh 
Published: April 2022

AbstractRecent advances in Big Data and Artificial Intelligence have created new opportunities for AI-based agents, referred to as Robo-Advisors, to provide financial advice and recommendations to investors. In this chapter, we will introduce the concept of investment recommendation and describe how automated services for this task can be developed and tested. In particular, this chapter covers the following core topics: (1) the legal landscape for investment recommendation systems, (2) what financial asset recommendation is and what data it needs to function, (3) how to clean and curate that data, (4) approaches to build/train asset recommendation models and (5) how to evaluate such systems prior to putting them into production.
Personalized Portfolio Optimization Using Genetic (AI) Algorithms
Authors: Meier Roland , Danzinger René 
Published: April 2022

AbstractThis chapter presents a fintech-as-a-service (FaaS) solution, which enables financial advisors and wealth and asset managers to provide a “private banking-like service” to the general public. The chapter illustrates all the steps needed to structure this process as an online journey. The solution contains a full end-to-end process which advisors can use to support client advisory meetings and which can potentially also be used directly by the B2C user. To support the advisor accordingly and provide online advisory to the end customer, it is required that highly individual needs are taken into account and that truly individual and personalized portfolio proposals are generated. Traditional portfolio construction methods do not have the actual ability to take a wide range of individual preferences into account. Therefore, a new portfolio construction and optimization methodology based on “genetic algorithms” is being developed and presented in this chapter. The optimization process is built using artificial intelligence approaches. This allows optimization results to be explained based on the selected customer’s preferences. The solution is designed as an open framework, which enables additional fitness factors that represent user preferences in various dimensions to be added on a customized basis.
Personalized Finance Management for SMEs
Authors: Kotios Dimitrios , Makridis Georgios , Walser Silvio , Kyriazis Dimosthenis , Monferrino Vittorio 
Published: April 2022

AbstractThis chapter presents Business Financial Management (BFM) tools for Small Medium Enterprises (SMEs). The presented tools represent a game changer as they shift away from a one-size-fits-all approach to banking services and put emphasis on delivering a personalized SME experience and an improved bank client’s digital experience. An SME customer-centric approach, which ensures that the particularities of the SME are taken care of as much as possible, is presented. Through a comprehensive view of SMEs’ finances and operations, paired with state-of-the-art ML/DL models, the presented BFM tools act as a 24/7 concierge. They also operate as a virtual smart advisor that delivers in a simple, efficient, and engaging way business insights to the SME at the right time, i.e., when needed most. Deeper and better insights that empower SMEs contribute toward SMEs’ financial health and business growth, ultimately resulting in high-performance SMEs.
Cybersecurity and Fraud Detection in Financial Transactions
Authors: Aschi Massimiliano , Bonura Susanna , Masi Nicola , Messina Domenico , Profeta Davide 
Published: April 2022

AbstractFrauds in financial services are an ever-increasing phenomenon, and cybercrime generates multimillion revenues, therefore even a small improvement in fraud detection rates would generate significant savings. This chapter arises from the need to overcome the limitations of the rule-based systems to block potentially fraudulent transactions. After mentioning the limitations of rule-based approach, this chapter explains how machine learning is able to address many of these limitations and, more effectively, identify risky transactions. A novel AI-based fraud detection system – built over a Data Science and Machine Learning – is presented for the pre-processing of transaction data and model training in a batch layer (to periodically retrain the predictive model with new data) while in a stream layer, the real-time fraud detection is handled based on new input transaction data. The architecture presented makes this solution a valuable tool for supporting fraud analysts and for automating the fraud detection processes.
Risk Assessment for Personalized Health Insurance Products
Authors: Pnevmatikakis Aristodemos , Kanavos Stathis , Perikleous Alexandros , Kyriazakos Sofoklis 
Published: April 2022

AbstractThe way people lead their lives is considered an important factor in health. In this chapter, we describe a system to provide risk assessment based on behavior for the health insurance sector. The system processes real-world data (RWD) of individuals from their daily life that enumerate different aspects of behavior collection. The data have been captured using the Healthentia platform and a simulator that augments the actual dataset with synthetic data. Classifiers are built to predict variations of peoples’ well-being short-term outlook. Risk assessment services are provided to health insurance professionals by processing the classifier predictions in the long term while explaining the classifiers themselves provide insights on the coaching of the users of the service.
Leveraging Management of Customers’ Consent Exploiting the Benefits of Blockchain Technology Towards Secure Data Sharing
Authors: Miltiadou Dimitris , Pitsios Stamatis , Kasdaglis Spyros , Spyropoulos Dimitrios , Misiakoulis Georgios , Kossiaras Fotis , Skarbovsky Inna , Fournier Fabiana , Kapsoulis Nikolaos , Soldatos John , Perakis Konstantinos 
Published: April 2022

AbstractOpen banking holds the potential of expanding traditional banking data flows, placing the customer at its core and in control of their banking data, including their personal information. Consent management enables the tracking, monitoring and managing the personal data lifecycle in a GDPR compliant manner, and improves customers’ control over their data, empowering them to manage their consent throughout its lifecycle. However, traditional technologies have failed to become a key enabler of trust, due to multiple security/data tampering incidents. This chapter introduces a blockchain-empowered Consent Management System (CMS). It aims at presenting the design and implementation of a robust CMS, enabling the sharing of customers’ consent, thus facilitating the exchange and the utilization of customer data, across different banking institutions. The proposed CMS implementation will enable the financial institutions to effectively manage and share their customers’ consents in a transparent and unambiguous manner, ensuring compliance to PSD2 and GDRP, while lowering the barriers of secure data sharing.
Laparoscopic sacrohysteropexy versus vaginal sacrospinous hysteropexy as treatment for uterine descent: comparison of long-term outcomes
Authors: van Oudheusden Anique M.J. , Coolen Anne-Lotte W.M. , Hoskam Hilde , Veen Joggem , Bongers Marlies Y. 
Published: April 2022

Abstract
Introduction and hypothesis
Pelvic organ prolapse (POP) is a frequent occurring health issue, especially concerning elderly women. The objective of this study is to examine the long-term outcomes of laparoscopic sacrohysteropexy (LSH) and vaginal sacrospinous hysteropexy (SSHP) for treatment of uterine prolapse.

Methods
A retrospective study of patients who underwent a LSH or SSHP. Validated questionnaires and an outpatient examination visit were used to investigate the effects of both surgical treatments. The primary outcome was the composite outcome of success for the apical compartment, defined as no recurrence of uterine prolapse (POP-Q measurement C ≤ 0), no subjective recurrence of POP, and/or not requiring therapy for recurrent prolapse. Secondary outcomes were peri- and postoperative data, anatomical failure, prolapse beyond hymen, subjective outcomes, and disease-specific quality of life.

Results
We included 105 patients, 53 in the LSH group and 52 in the SSHP group. The overall response rate of the questionnaires was 83% (n = 87) after a mean follow-up time of 4.5 years (54.2 months; 95% CI 44.8–64.2 months) in the LSH group and 2.5 years (30.1 months; 95% CI 29.3–31.5 months) in the SSHP group. There were no clinically relevant differences between the study groups in composite outcome of success (p = 0.073), anatomical failure of the apical compartment (p = 0.711), vaginal bulge symptoms for which patients consulted professionals (p = 0.126), and patient satisfaction (p = 0.741). The operative time was longer in the LSH group (117 min; interquartile range (IQR) 110–123) compared to the SSHP group (67 minutes; IQR 60–73) (p < 0.001). The duration of hospital stay was also longer in the LSH group (4 days) than in the SSHP group (3 days) (p = 0.006).

Conclusions
LSH and SSHP seem to be equally effective after long-term follow-up in treating uterine prolapse in terms of objective and subjective recurrence.