bluuebunny/crossref_metadata_2025 huggingface dataset:
Restoration of degraded waterlogged saline soil through subsurface drainage: Spatiotemporal soil salinity assessment using electromagnetic induction (EMI) and geographic information system (GIS) techniques
Authors: Narjary Bhaskar , Nand Viveka , Goswami Suraj , Prajapat Kailash , Bundela Devendra Singh , Kumar Satyendra
Published: May 2024

Reduction in soil salinity in the entire project area is a key indicator of proper functioning of the implemented subsurface drainage (SSD) projects. Electromagnetic induction (EMI) surveys were carried out to facilitate spatiotemporal assessment of soil salinity of a SSD project site in Kahni, Haryana (India). The surveys were conducted in two time frames: immediately after the start of SSD project in 2019 and after 2 years of successful operation in 2021. The collected data of 2 surveys was used to derive a depth‐specific calibrated correlation between the observed salinity (ECe) of collected soil samples and surveyed apparent electrical conductivity (ECa) observations in vertical (ECav) and horizontal (ECah) modes. Spatiotemporal analysis of soil salinity revealed notable changes in areas under different salinity classes over a period of 2 years, indicating the impact of SSD on soil desalinization. During the course of 2 years (2019–2021) of SSD operation, area under moderate salinity (4–8 dS m−1) in the top 0–0.15 m soil increased by 54.5% while it decreased by 40% and 6.6% under high (8–12 dS m−1) and very high (12–16 dS m−1) salinity classes. The rice and wheat yields were also enhanced by 24% and 7% respectively after 2 years operation of SSD in hitherto severally waterlogged saline soils. Overall findings of this study reinforce the scope of using EMI approach to quickly and effectively assess the efficacy of subsurface drainage. Creation of measurable soil salinity maps by proposed EMI and GIS techniques can help in planning and implementing site‐specific management strategies in saline soil reclamation projects.
Harnessing the Dual‐Mode Luminescence of Er/Yb Co‐Doped SrLaLiTeO6 Double Perovskite Phosphors for Remarkably Wide Range Temperature Sensing and NIR pc‐LEDs
Authors: Kaithrikkovil Varriam Pooja , Ganesanpotti Subodh
Published: May 2024

The ever‐increasing demand for efficient and economic photonic materials has hastened the quest for robust, multifunctional phosphors. Herein, a dual‐mode luminescent SrLaLiTeO6:Er3+, Yb3+ double perovskite phosphor whose concentration‐dependent up and down‐conversion luminescence are investigated and underlying mechanisms are discussed. Temperature‐dependent up‐conversion luminescence of 2H11/2→4I15/2 transition exhibits negative thermal quenching, owing to the thermalization process from the 4S3/2 level. Temperature dependent Raman analysis confirms a decrease in the phonon lifetime from 0.43 to 0.28 ps indicating an increased number of phonon decay channels, which explains the rapid thermal quenching of up‐conversion emission at elevated temperatures. The diverse thermal quenching of the thermally coupled levels contributes to the exceptionally high relative sensitivity of 4.49 %K−1 at 140 K. A maximum sensitivity, Sr of 0.84 %K−1 (698 K) is obtained from the Raman‐PL intensity ratio (RPIR) of the band (719 cm−1) and the 986 nm emission band (4I11/2→4I15/2) of Er3+. Hence, by employing multi‐mode temperature sensing techniques a single phosphor can be used for optical thermometry for a broad temperature range from 90 to 698 K. In addition, the Near Infra‐Red (NIR)‐II emission of Er3+ corresponding to 4I13/2→4I15/2 transition shows excellent thermal stability, maintaining 72% of the room temperature intensity at 500 K.
Enhancing the Properties of Chitosan–Pectin Hydrogels With Cellulose Nanowhiskers for Potential Applications in Wound Dressings
Authors: Ferrante Micaela , Álvarez Vera Alejandra , Narain Ravin , Ounkaew Artjima , González Jimena Soledad
Published: May 2024

Chitosan and pectin are employed here in the formation of biodegradable hydrogels. The addition of cellulose nanowhiskers (CNW) into the hydrogels is accomplished through two methods: by swelling, after the polymeric network formation (Method A), and inclusion in polymer solutions before gelation, with varying CNW content (Method B). Comprehensive physico–chemical, thermal, microscopic, gel fraction, and water vapor transmission analyses are conducted, complemented by antibacterial and viability assessments. CNWs are successfully synthesized and incorporated within the hydrogel by both methods. Moreover, the degradation temperature (Tmax) of hydrogels is higher with CNW (0% CNW: 205.5 °C, 10% CNW: 217.0 °C). CNW aggregates are observed in hydrogels with 20% and 30% content but no aggregation is observed with 4% and 10%. The antimicrobial properties are not affected by the addition of CNW, and the cytotoxicity tests reveal better results with 10% CNW compared with 20%. The study signifies the versatility of CNWs as effective reinforcements, influencing structural, thermal, and biological aspects of the hydrogels. The proposed methodology, emphasizing CNW incorporation, lays the groundwork for innovative biomaterials with promising medical implications. This investigation encourages further exploration and validation of these composite hydrogels in vivo for practical medical use in wound dressings.
Agarose Nanofiber by Electrospinning
Authors: Yoshida Hiroaki , Nagaoka Kiyonori , Ajiro Hiroharu
Published: May 2024

Agarose nanofiber with a diameter of 68 ± 33 nm is first prepared by electrospinning under an optimized condition of solvents with hexafluoroisopropanol/water (92.5/7.5, v/v). The results show the control of hydrogen bonding, which is important to prepare a nanoscale agarose material.
Selection of financing and selling modes in a green and capital‐constrained platform supply chain
Authors: Mu Zongyu , Ruan Longjie , Xia Yanfei , Sun Hao , Fu Yaping
Published: May 2024

Currently, manufacturers can collaborate with online platforms to better sell green products and also finance from platforms to relieve financial pressure. To cater to this trend, we establish a platform supply chain model by considering a manufacturer with capital constraints that invests in a green production program. Then, it can sell green products via the reselling or the agency channel on a platform and finance from a bank, the platform, or both. In this context, we examine the choices of financial strategies and selling channels from the perspectives of both parties, as well as the corresponding environmental benefit and social welfare. Our findings show that the manufacturer prefers bank financing in most cases when the bank's interest rate is smaller than that offered by the platform. However, in the reselling channel, the manufacturer may choose platform financing even if its interest rate is higher. The platform tends to provide the agency channel when the commission rate is within a reasonable range. It is possible to realize the highest environmental benefit and social welfare in specific regions where both parties agree on the financing and selling modes to maximize their profits. When the manufacturer has only partial access to bank financing, it can choose mixed financing. However, the manufacturer cannot always treat mixed financing as a complete replacement of bank financing.
Manufacturer encroachment in a platform supply chain: An analysis of synergy effect, dysergy effect, and mutual exclusivity effect
Authors: Chang Lu‐Yu , Mi Yue‐Yue , Wang Chuan‐Xu , Zhang Qing
Published: May 2024

The prosperity of internet sales is stimulating a phenomenal growth of retail platforms and manufacturer encroachment. Encroachment spawns channel competition, potentially threatening the platform's profit, which in turn induces a series of countermeasures by the platform. Motivated by this trend, we develop a game‐theoretical model to explore the strategic and tactical interactions between a manufacturer and a platform, in which the manufacturer determines encroachment strategy and quality differentiation tactic, and the platform determines sales mode strategy and information sharing tactic. We find that the manufacturer is profitable and the platform is damaged from encroachment. Furthermore, the manufacturer's quality differentiation tactic can propel the platform to select reselling that indirectly enhances post‐encroachment profitability. In contrast, sales mode and information sharing can be mono or jointly utilized by the platform to counter encroachment. Significantly, we provide a novel inspection method to systematically analyze the cumulative performance of the platform's two countermeasures by introducing the synergy effect, dysergy effect, and mutual exclusivity effect. Interestingly, we highlight that the performance of mono‐countermeasures may be even more effective than that of combined countermeasures to mitigate the platform's loss caused by encroachment. This finding enriches not only the analytic understanding of received wisdom about whether more countermeasures can invariably hold competition edges but also provides useful managerial guidelines for strategic interaction research. Moreover, the manufacturer's increased encroachment capabilities may promote the platform to shift from reselling to agency selling, which reveals that manufacturer encroachment may be a critical factor in the popularity of agency selling.
Needless electrospun collagen/hyaluronic acid nanofibers for skin moisturization: Research
Authors: Tören Elçin , Mazari Adnan Ahmed
Published: May 2024

This study investigated the potential of electrospun collagen/hyaluronic acid nanofibers for use in biomedicine and skincare. Needleless electrospinning technology employed in the production process resulted in nanofibers with consistent fiber diameters and improved mechanical properties. The composite nanofibers demonstrated impressive tensile strength and elongation capabilities, indicating a favorable interaction between collagen and hyaluronic acid (HA). Cellular assays revealed that the collagen/HA scaffolds facilitated superior cell adhesion and proliferation compared with the control scaffolds, indicating their biocompatibility and potential for tissue engineering. This biomaterial offers an environment‐friendly alternative to conventional skincare products by eliminating the need for preservatives and reducing waste. Although the initial costs are high, the long‐term benefits of material durability and active ingredient efficacy provide compelling cases for industrial adoption. Our findings suggest that collagen/HA nanofibers have the potential to be the next‐generation materials for regenerative medicine and skincare. Further research is required to optimize their production and assess the economic feasibility of skincare and tissue engineering applications.
Batch synthesis of 2,4,6‐trinitro‐3‐bromoanisole and its thermolysis and combustion performance
Authors: Song Xiao‐lan , Wang Yi , Jia Kang‐hui , Yu Zhi‐hong , Song Dan , An Chong‐wei , Li Feng‐sheng
Published: May 2024

A new carrier explosive TNBA was batch synthesized by a chemical method. The prepared samples were characterized using SEM, EDS, XRD, IR, XPS, nuclear magnetic resonance, and elemental analysis techniques. The enthalpy of formation of TNBA was measured using a specialized calorimeter that is specially used in testing of explosives and powders. The thermal decomposition performance of TNBA was tested by DSC technology. Meanwhile, the combustion performance of TNBA was also tested. The results of characterizations showed that the prepared sample was indeed TNBA. The enthalpy of formation of TNBA was determined as ΔHf,TNBA=+48.5 kJ/mol. At a heating rate of 20 °C/min, the thermal decomposition peak of TNBA is at TP=285.3 °C, and the activation energy is EK=91 kJ/mol, which is higher than the Tp and EK values of TNT. This indicates that TNBA is a relatively easy to decompose explosive, but the decomposition rate is not fast. The critical temperature for thermal explosion of TNBA reached Tb=247 °C, which is higher than the Tb value of TNT, slightly lower than the Tb value of DNAN, and significantly higher than the Tb value of DNTF, TNAZ, and MTNP. The combustion performance test results showed that the TNBA sample has the highest combustion pressure and the highest pressurization rate; and the TNBA sample has the highest combustion temperature; however, due to the high oxygen balance, the combustion heat of TNBA samples in excess pure oxygen is not the highest.
Theory study on catalytic hydrogenation of CO2 to formic acid over Si, N‐doped modified graphene quantum dots supported single atom Fe
Authors: Li Fangfang , Zhang Xunchao , Kang Lihua
Published: May 2024

Exploring suitable catalysts to catalyze the chemical transformation of CO2 molecules is essential to reduce CO2 levels. In this article, catalyst models of Fe‐C4, Fe‐N4, and Fe‐Si4 were constructed using the density functional theory (DFT) calculations, and the reaction mechanisms of CO2 hydrogenation over these three catalysts were calculated and analyzed. The results showed that the doping of N atoms lowered the energy barrier of the second hydrogenation step compared with that of Fe‐C4 catalyst, while the doping of Si atoms changed the electron distribution on the surface of the catalyst and formed new Si adsorption sites. And the Fe‐Si4 catalyst had a stronger ability to activate CO2 molecules as well as stronger catalytic performance compared with the Fe‐C4 and Fe‐N4 catalysts, which was mainly attributed to the synergistic catalytic effect between the doped Si atoms and the Fe metal atom.
Local Isomeric Polar Nanoclusters Enabled Superior Capacitive Energy Storage Under Moderate Fields in NaNbO3‐Based Lead‐Free Ceramics
Authors: Xie Aiwen , Hu Tengfei , Lei Junwei , Zhang Yi , Wei Xianbin , Fu Zhengqian , Zuo Ruzhong
Published: May 2024

The high‐field energy‐storage performance of dielectric capacitors has been significantly improved in recent years, yet the high voltage risks of device failure and large cost of insulation technology increase the demand for high‐performance dielectric capacitors at finite electric fields. Herein, a unique superparaelectric state filled with polar nanoclusters with various local symmetries for lead‐free relaxor ferroelectric capacitors is subtly designed through a simple chemical modification method, successfully realizing a collaborative improvement of polarization hysteresis, maximum polarization, and polarization saturation at moderate electric fields of 20–30 kV mm−1. Therefore, a giant recoverable energy density of ≈5.0 J cm−3 and a high efficiency of ≈82.1% are simultaneously achieved at 30 kV mm−1 in (0.9‐x)NaNbO3‐0.1BaTiO3‐xBiFeO3 lead‐free ceramics, showing a breakthrough progress in moderate‐field comprehensive energy‐storage performances. Moreover, superior charge–discharge performances of high‐power density ≈182 MW cm−3, high discharge energy density ≈4.3 J cm−3 and ultra‐short discharge time <70 ns as well as excellent temperature stability demonstrate great application potentials for dielectric energy‐storage capacitors in pulsed power devices. This work provides an effective and paradigmatic strategy for developing novel lead‐free dielectrics with high energy‐storage performance under finite electric fields.
Graphene Derived from Municipal Solid Waste
Authors: Silva Karla J. , Wyss Kevin M. , Teng Carolyn H. , Cheng Yi , Eddy Lucas J. , Tour James M.
Published: May 2024

Landfilling is long the most common method of disposal for municipal solid waste (MSW). However, many countries seek to implement different methods of MSW treatment due to the high global warming potential associated with landfilling. Other methods such as recycling and incineration are either limited to only a fraction of generated MSW or still produce large greenhouse gas emissions, thereby providing an unsustainable disposal method. Here, the production of graphene from treated MSW is reported that including treated wood waste, using flash Joule heating. Results indicated a 71%–83% reduction in global warming potential compared to traditional disposal methods at a net cost of −$282 of MSW, presuming the graphene is sold at just 5% of its current market value to offset the cost of the flash Joule heating process.
Alkaline‐Responsive, Self‐Healable, and Conductive Copolymer Composites with Enhanced Mechanical Properties Tailored for Wearable Tech
Authors: Chang Chia‐Wei , Wu Chia‐Ti , Lo Tse‐Yu , Chen Yu , Chang Chun‐Ting , Chen Huan‐Ru , Chang Chun‐Chi , Lee Lin‐Ruei , Tseng Yu‐Hsuan , Chen Jiun‐Tai
Published: May 2024

Despite significant advancements, current self‐healing materials often suffer from a compromise between mechanical robustness and functional performance, particularly in terms of conductivity and responsiveness to environmental stimuli. Addressing this issue, the research introduces a self‐healable and conductive copolymer, poly(ionic liquid‐co‐acrylic acid) (PIL‐co‐PAA), synthesized through free radical polymerization, and further optimized by incorporating thermoplastic polyurethane (TPU). This combination leverages the unique properties of each component, especially ion‐dipole interactions and hydrogen bonds, resulting in a material that exhibits exceptional self‐healing abilities and demonstrates enhanced mechanical properties and electrical conductivity. Moreover, the PIL‐co‐PAA/TPU films showcase alkaline‐responsive behavior, a feature that broadens their applicability in dynamic environments. Through systematic characterization, including thermogravimetric analysis, tensile testing, and electrical properties measurements, the mechanisms behind the improved performance and functionality of these films are elucidated. The conductivities and ultimate tensile strength (σuts) of the PIL‐co‐PAA/TPU films regain 80% under 8 h healing process. To extend the applications for wearable devices, the self‐healing properties of commercial cotton fabrics coated with the self‐healable PIL‐co‐PAA are also investigated, demonstrating both self‐healing and electrical properties. This study advances the understanding of self‐healable conductive polymers and opens new avenues for their application in wearable technology.
Advancing Nanomaterial Toxicology Screening Through Efficient and Cost‐Effective Quantitative Proteomics
Authors: Stobernack Tobias , Dommershausen Nils , Alcolea‐Rodríguez Víctor , Ledwith Rico , Bañares Miguel A. , Haase Andrea , Pink Mario , Dumit Verónica I.
Published: May 2024

Proteomic investigations yield high‐dimensional datasets, yet their application to large‐scale toxicological assessments is hindered by reproducibility challenges due to fluctuating measurement conditions. To address these limitations, this study introduces an advanced tandem mass tag (TMT) labeling protocol. Although labeling approaches shorten data acquisition time by multiplexing samples compared to traditional label‐free quantification (LFQ) methods in general, the associated costs may surge significantly with large sample sets, for example, in toxicological screenings. However, the introduced advanced protocol offers an efficient, cost‐effective alternative, reducing TMT reagent usage (by a factor of ten) and requiring minimal biological material (1 µg), while demonstrating increased reproducibility compared to LFQ. To demonstrate its effectiveness, the advanced protocol is employed to assess the toxicity of nine benchmark nanomaterials (NMs) on A549 lung epithelial cells. While LFQ measurements identify 3300 proteins, they proved inadequate to reveal NM toxicity. Conversely, despite detecting 2600 proteins, the TMT protocol demonstrates superior sensitivity by uncovering alterations induced by NM treatment. In contrast to previous studies, the introduced advanced protocol allows simultaneous and straightforward assessment of multiple test substances, enabling prioritization, ranking, and grouping for hazard evaluation. Additionally, it fosters the development of New Approach Methodologies (NAMs), contributing to innovative methodologies in toxicological research.
Improved ADRC Current Low‐Frequency Ripple Suppression Strategy Based on VFNF
Authors: Liu Yiyang , Li Weichao , Zhou Liang , Han Jinyang , Yang Zhennan , Zhao XiangLin
Published: May 2024

In the two‐stage inverter system, due to the space vector modulation (SVM), the midpoint potential of active neutral point clamped three‐level inverter system (ANPC‐TLIS) will have triple frequency fluctuation, under the influence of the closed‐loop control strategy, the fluctuation amplitude of the lithium battery energy storage system (LBESS) output current will increase. To reduce the low‐frequency output current fluctuation, a voltage loop strategy based on active disturbance rejection control (ADRC) with notch filter (NF)is proposed in this paper. In this scheme, the voltage outer‐loop control strategy not only maintains voltage stability, but also reduces the fluctuation amplitude of reference current. In addition, during the electromagnetic transient process, the LBESS output current fluctuation frequency is constantly changing because the power supply frequency required by linear motor is constantly changing. To solve this problem, the inverter output current frequency is feedforward to the LBESS controller, forming a variable frequency notch filter (VFNF). Finally, the effectiveness of the proposed strategy is verified by fixed‐frequency and variable frequency conditions experiments on RT‐LAB experimental platform. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
Long-term Safety and Efficacy of the Derivo Embolization Device in a Single-center Series
Authors: Goertz Lukas , Zopfs David , Kottlors Jonathan , Borggrefe Jan , Pennig Lenhard , Schlamann Marc , Kabbasch Christoph
Published: May 2024

Purpose

This study analyzes the long-term clinical and angiographic outcomes of the Derivo Embolization Device (DED), an advanced flow diverter device with an electropolished surface, for the treatment of intracranial aneurysms.

Methods

A consecutive series of 101 patients (mean age: 58 years, 72% female) treated with the DED for 122 aneurysms at a single center between 2017 and 2023 was retrospectively analyzed for major (change in National Institutes of Health Stroke Scale [NIHSS] score ≥ 4 points) and minor (change in NIHSS score < 4 points) neurological events, procedural morbidity (increase of at least one point on the modified Rankin Scale), and angiographic results.

Results

There were 14 (11%) recurrent aneurysms, 15 (12%) ruptured aneurysms, 26 (21%) posterior circulation aneurysms and 16 (13%) fusiform or dissecting aneurysms. Device deployment failed in 1 case (1%). Procedure-related symptomatic procedural complications consisted of 2 (2%) major events (1 major stroke and 1 vessel perforation with intracranial hemorrhage and infarction) and 6 minor events (6 minor strokes). Procedural morbidity was 5%. There were no late ischemic or hemorrhagic events during follow-up. Complete and favorable aneurysm occlusion was achieved in 54% (40/74) and 62% (46/74) at a mean of 5 months, 71% (27/38) and 87% (33/38) at a mean of 12 months, and 76% (25/33) and 97% (32/33) at a mean of 35 months, respectively.

Conclusion

The results demonstrate progressive aneurysm occlusion beyond 12 months after DED implantation with an almost 100% favorable occlusion rate. Procedural morbidity was low and there were no late complications.
Do not shut up and do dribble: social media and TV consumption
Authors: Pazzona Matteo , Spagnolo Nicola
Published: May 2024

This paper investigates the impact of social media interest and sentiment surrounding the 2020 National Basketball Association’s involvement with the Black Lives Matter movement on the television audience in the United States. Twitter (now known as X) serves as the chosen social media platform, and we determine the sentiment expressed in tweets (messages posted on Twitter) using the XLM-RoBERTa deep language model. Our primary findings indicate that the quantity of users’ posts does not significantly influence TV viewership; instead, the tone of the messages plays a crucial role. Positive messages supporting the NBA’s engagement correlate with an increase in the number of viewers, while those expressing opposition do not. We argue that this asymmetry may stem from a positive elasticity among casual (non-habitual) NBA viewers concerning positive sentiments toward NBA involvement. These viewers are likely to align with the NBA’s stances on civil rights and BLM. In contrast, the core NBA fan base exhibits inelastic demand and is unlikely to cease watching NBA games. A comprehensive set of robustness checks reinforces the validity of our key conclusions.
Structure constants in equivariant oriented cohomology of flag varieties
Authors: Goldin Rebecca , Zhong Changlong
Published: May 2024

We introduce generalized Demazure operators for the equivariant oriented cohomology of the flag variety, which have specializations to various Demazure operators and Demazure–Lusztig operators in both equivariant cohomology and equivariant K-theory. In the context of the geometric basis of the equivariant oriented cohomology given by certain Bott–Samelson classes, we use these operators to obtain formulas for the structure constants arising in different bases. Specializing to divided difference operators and Demazure operators in singular cohomology and K-theory, we recover the formulas for structure constants of Schubert classes obtained in Goldin and Knutson (Pure Appl Math Q 17(4):1345–1385, 2021). Two specific specializations result in formulas for the the structure constants for cohomological and K-theoretic stable bases as well; as a corollary we reproduce a formula for the structure constants of the Segre–Schwartz–MacPherson basis previously obtained by Su (Math Zeitschrift 298:193–213, 2021). Our methods involve the study of the formal affine Demazure algebra, providing a purely algebraic proof of these results.
Impact of body mass index on fracture severity, clinical, radiological and functional outcome in distal radius fractures: a retrospective observational study after surgical treatment
Authors: Kloberdanz Anna Lena , Meyer Jasmin , Kammermeier Kora , Strahl André , Schlickewei Carsten , Mader Konrad , Frosch Karl-Heinz , Yarar-Schlickewei Sinef
Published: May 2024

Introduction

Distal radius fracture (DRF) is one of the three most common fractures of the human body with increasing incidences in all groups of age. Known causes of increasing incidence, such as ageing of the population or increased obesity, have been described and discussed. So far, literature reports ambivalent effects of body mass index (BMI) on bone physiology. It is worthwhile to examine the influence of BMI on the outcome of fractures more detailed. This study aims to investigate the influence of an abnormal BMI on fracture severity and treatment, as well as clinical, radiological, and functional outcome to improve clinical decision making.

Materials and methods

A retrospective observational study was conducted on data obtained from patients, who underwent open reduction and internal fixation (ORIF) of a DRF at a local Level 1 Trauma Center between May 2018 and October 2021. Follow-up examinations were performed approximately 1 year after surgical fracture treatment, during which various questionnaires and functional measurements (CMS, DASH, NRS, ROM) were applied. In addition, postoperative complications were recorded and radiological examinations of the affected hand were performed. After excluding incomplete data sets and applying set exclusion criteria, the complete data of 105 patients were analyzed.

Results

74 patients were female and 31 male with significant difference in mean BMI [p = 0.002; female: 23.8 (SD ± 3.3), men: 26.2 (SD ± 3.9)]. Patients with higher BMI had significantly more severe fractures (p = 0.042). However, there was no significant difference in surgery time for fracture management. At follow-up, patients with lower BMI showed a smaller difference in hand strength between the fractured and the other hand (p = 0.017). The BMI had no significant effect on the clinical and radiological outcome.

Conclusion

Despite the ambivalent effects of BMI on the skeletal system, our findings indicate that a higher BMI is associated with more severe DRF. Thereby BMI does not correlate with surgery time for fracture treatment. Furthermore, no evidence of an influence on the clinical and radiological outcome could be detected.
In vitro evaluation of the percutaneous absorption of progesterone in anhydrous permeation-enhancing base using the Franz skin finite dose model and mass spectrometry
Authors: Banov Daniel , Song Guiyun , Ip Kendice , Seeley Erin H. , Linehan Stefan T. , Bassani Isabel , Ferron Gianna , Bassani August S. , Valdez Benigno C.
Published: May 2024

Progesterone is used for hormone replacement therapy through various routes of administration. This study was conducted to (a) evaluate the stability of progesterone in a proprietary anhydrous permeation-enhancing base (APEB) and the efficiency of its skin permeation, and (b) determine the appropriateness of mass spectrometry as a method of analysis for permeated progesterone. Using a proven stability-indicating ultra-performance liquid chromatographic method, the compounded hormone (100 mg progesterone/g APEB gel) was determined to be physically and chemically stable at room temperature for six months. Skin permeation analysis using the Franz skin finite dose model and mass spectrometry imaging showed an optical density of 1699 for the permeated progesterone compounded in APEB and 550 for the permeated progesterone in a water containing VBC, which is a statistically significant different (P = 0.029). The study suggests that APEB can be used as a compounding base for effective skin permeation of progesterone, and mass spectrometry is a reliable method for visualization and quantitative analysis of permeated progesterone.
Acute skin toxicity and self-management ability among Chinese breast cancer radiotherapy patients: a qualitative study
Authors: Lu Xiaomeng , Yin Yunteng , Geng Wenhui , Liu Lei , Liu Fengxia , Zhang Zhenye
Published: May 2024

Objectives

Radiation dermatitis is the most common reaction to radiotherapy, almost all breast cancer patients receive radiotherapy on an outpatient basis. Currently, there are no studies on the experience of radiation dermatitis and the ability to self-manage it. Therefore, we aimed to use qualitative approaches to gain a deeper understanding of the actual experiences and self-management ability in order to provide a reference for further improving the effectiveness of self-management and to optimize symptom management strategies.

Methods

A descriptive qualitative study was conducted using purposive sampling to select 17 breast cancer patients undergoing radiotherapy. Semi-structured interviews were conducted from September to November 2023. The Colaizzi seven-step analysis method was used to classify the data into summarized themes.

Results

Four themes were identified from the interview responses: (1) multiple self-reported skin symptoms in breast cancer patients with radiation dermatitis; (2) the multidimensional impact on patient’s quality of life, especially pruritus, ulceration; (3) the ability to self-manage radiation dermatitis: strong mental toughness, positive response, and self-doubt; (4) challenges faced: concerns about radiotherapy side effects and recurrence, targeted symptom management and continuity of care after the radiotherapy.

Conclusions

Healthcare professionals should consider patients’ self-reported symptoms when assessing radiation dermatitis. For pruritus and pain, we can enhance precision symptom management to improve patients’ quality of life. By utilizing information technology tools, we can increase breast cancer patients’ ability and confidence in managing radiation dermatitis effectively while enhancing accurate symptom management during radiotherapy.
Application of machine learning to model the pressure poisson equation for fluid flow on generic geometries
Authors: Sousa Paulo , Afonso Alexandre , Veiga Rodrigues Carlos
Published: May 2024

This study addresses the importance of enhancing traditional fluid-flow solvers by introducing a Machine Learning procedure to model pressure fields computed by standard fluid-flow solvers. The conventional approach involves enforcing pressure–velocity coupling through a Poisson equation, combining the Navier–Stokes and continuity equations. The solution to this Poisson equation constitutes a substantial percentage of the overall computational cost in fluid flow simulations, therefore improving its efficiency can yield significant gains in computational speed. The study aims to create a versatile method applicable to any geometry, ultimately providing a more efficient alternative to the conventional pressure solver. Machine Learning models were trained with flow fields generated by a Computational Fluid Dynamics solver applied to the confined flow over multiple geometries, namely wall-bounded cylinders with circular, rectangular, triangular, and plate cross-sections. To achieve applicability to any geometry, a method was developed to estimate pressure fields in fixed-shape blocks sampled from the flow domain and subsequently assemble them to reconstruct the entire physical domain. The model relies on multilayer perceptron neural networks combined with Principal Component Analysis transformations. The developed Machine Learning models achieved acceptable accuracy with errors of around 3%. Furthermore, the model demonstrated enhanced computational efficiency, outperforming the classical PISO algorithm by up to 30 times.
On the hydrodynamic derivatives with respect to heading angle for ship maneuvering in a canal
Authors: Yasukawa H. , Sano M.
Published: May 2024

This study focused on the equation of motion, hydrodynamic derivatives, and course stability with respect to ship maneuvering in a canal. Based on the potential theory, a consistent linearized equation of motion was derived when a ship maneuvers near the center line of a canal with a symmetrical cross-section and uniform length. In the new equation of motion, hydrodynamic derivatives for the lateral force and yaw moment with respect to ship heading angle $$\psi$$
ψ
($$Y_\psi$$

Y
ψ

, $$N_\psi$$

N
ψ

) appear, which have not been considered in existing studies. $$Y_\psi$$

Y
ψ

and $$N_\psi$$

N
ψ

are measured by captive tests using a container ship model in a canal model, and they are significant. Furthermore, the course stability criterion for ships in the canal was derived by considering the $$Y_\psi$$

Y
ψ

and $$N_\psi$$

N
ψ

, and the course stability was investigated. As a result, we found that the effect of $$Y_\psi$$

Y
ψ

and $$N_\psi$$

N
ψ

on course stability cannot be neglected when the water depth becomes shallower. In case of the studied container ship, the consideration of $$Y_\psi$$

Y
ψ

and $$N_\psi$$

N
ψ

causes the ship to shift to the course stable direction.
Unravelling the dynamics of technology integration in mathematics education: A structural equation modelling analysis of TPACK components
Authors: Li Mao , Li Bingqing
Published: May 2024

This quantitative study examined the dynamics of the Technological Pedagogical Content Knowledge (TPACK) framework within mathematics education, centring on the role of Contextual Knowledge (XK). The research, conducted with middle school mathematics teachers in Chongqing, China, employed structural equation modelling (SEM) to explore the relationships between various TPACK components. The study establishes discriminant validity and demonstrates an excellent fit for the SEM model. Notably, it uncovers significant correlations within the TPACK framework, with a special emphasis on the influence of XK. The findings indicate that XK, in conjunction with Pedagogical Knowledge (PK), Pedagogical Content Knowledge (PCK), and Technological Content Knowledge (TCK), considerably impacts the overall TPACK construct. The research highlights the critical influence of XK on key TPACK components, such as Technological Pedagogical Knowledge (TPK), PCK, and TPACK itself. These results underline the importance of integrating XK in professional development programs focused on TPACK, accentuating its vital role in effectively integrating technology in mathematics education. This study significantly contributes to the academic understanding of TPACK’s complex dynamics. It provides essential insights for enhancing technology integration in mathematics education, offering valuable guidance for educational practitioners and policymakers.
Family Life Courses, Uncertain Futures, and the Changing World of Work: State-of-the-Art and Prospects
Authors: Matysiak Anna , Vignoli Daniele
Published: May 2024

Labour markets in post-industrial countries have been undergoing tremendous transformations in the last two decades, substantially changing the conditions in which young adults take family decisions and raise children. Whilst these changes create new opportunities, they also generate risks which potentially foster uncertain futures and affect individuals’ opportunities to earn income, provide care for family members, and make long-term commitments. This Special Issue aims to stimulate the debate on the effects of rapid labour market transformations and growing uncertainty on families in contemporary wealthiest countries. Its articles suggest that economic uncertainty, the threat of unemployment or precarious employment, and financial difficulties lead to fertility postponement and increase the risk of union disruption. These effects intensify when labour market deregulation goes in tandem with labour market dualization and become more pronounced during periods of economic hardship, such as economic recessions or the COVID-19 pandemic. In addition, the effects of economic activity on family-related behaviours have become less gendered as women increasingly gain economic independence. Finally, it appears that highly educated workers and members of the upper social classes face increasingly better conditions for realising their fertility intentions than their lower-educated counterparts and those of the lower social classes. In this introductory article, we review the theoretical premises and the empirical evidence to provide a comprehensive background on what labour force participation and its conditions imply for family life courses. We then introduce the articles collected in this Special Issue and conclude with a discussion on prospects for future research.
Multi-resource allocation and care sequence assignment in patient management: a stochastic programming approach
Authors: Yao Xinyu , Shehadeh Karmel S. , Padman Rema
Published: May 2024

To mitigate outpatient care delivery inefficiencies induced by resource shortages and demand heterogeneity, this paper focuses on the problem of allocating and sequencing multiple medical resources so that patients scheduled for clinical care can experience efficient and coordinated care with minimum total waiting time. We leverage highly granular location data on people and medical resources collected via Real-Time Location System technologies to identify dominant patient care pathways. A novel two-stage Stochastic Mixed Integer Linear Programming model is proposed to determine the optimal patient sequence based on the available resources according to the care pathways that minimize patients’ expected total waiting time. The model incorporates the uncertainty in care activity duration via sample average approximation.We employ a Monte Carlo Optimization procedure to determine the appropriate sample size to obtain solutions that provide a good trade-off between approximation accuracy and computational time. Compared to the conventional deterministic model, our proposed model would significantly reduce waiting time for patients in the clinic by 60%, on average, with acceptable computational resource requirements and time complexity. In summary, this paper proposes a computationally efficient formulation for the multi-resource allocation and care sequence assignment optimization problem under uncertainty. It uses continuous assignment decision variables without timestamp and position indices, enabling the data-driven solution of problems with real-time allocation adjustment in a dynamic outpatient environment with complex clinical coordination constraints.
Discriminatory Types and Homogenising Relevances: A Schutzian Perspective on Oppression
Authors: Hedges Tris , De Biasio Sabrina
Published: May 2024

In this paper, we draw on Alfred Schutz’s theoretical framework to better understand how oppression is enacted through discriminatory acts. By closely examining the role of typifications and relevances in our experience of others, and by supplementing this analysis with contemporary social scientific resources, we argue that a Schutzian perspective on oppression yields important phenomenological insights. We do this in three key steps. Firstly, we contextualise Equality and the Meaning Structure of the Social World within Schutz’s broader body of work, elucidating his central conditions of discrimination. Secondly, we highlight the limitations of Schutz’s account, in how it fails to capture more peripheral, subtle, and implicit oppressive practices. Finally, we introduce two underexplored insights derived from Schutz’s framework: the role of relevances in understanding the motivational underpinnings of implicit biases, and the connection between self-typification and stereotype threat. With this multidimensional approach, we hope to enhance our understanding of oppression whilst bridging gaps in Schutz’s original conceptualization.
Exploring Students’ Generative AI-Assisted Writing Processes: Perceptions and Experiences from Native and Nonnative English Speakers
Authors: Wang Chaoran
Published: May 2024

Generative artificial intelligence (AI) can create sophisticated textual and multimodal content readily available to students. Writing intensive courses and disciplines that use writing as a major form of assessment are significantly impacted by advancements in generative AI, as the technology has the potential to revolutionize how students write and how they perceive writing as a fundamental literacy skill. However, educators are still at the beginning stage of understanding students’ integration of generative AI in their actual writing process. This study addresses the urgent need to uncover how students engage with ChatGPT throughout different components of their writing processes and their perceptions of the opportunities and challenges of generative AI. Adopting a phenomenological research design, the study explored the writing practices of six students, including both native and nonnative English speakers, in a first-year writing class at a higher education institution in the US. Thematic analysis of students’ written products, self-reflections, and interviews suggests that students utilized ChatGPT for brainstorming and organizing ideas as well as assisting with both global (e.g., argument, structure, coherence) and local issues of writing (e.g., syntax, diction, grammar), while they also had various ethical and practical concerns about the use of ChatGPT. The study brought to front two dilemmas encountered by students in their generative AI-assisted writing: (1) the challenging balance between incorporating AI to enhance writing and maintaining their authentic voice, and (2) the dilemma of weighing the potential loss of learning experiences against the emergence of new learning opportunities accompanying AI integration. These dilemmas highlight the need to rethink learning in an increasingly AI-mediated educational context, emphasizing the importance of fostering students’ critical AI literacy to promote their authorial voice and learning in AI-human collaboration.
Constrained Markov Decision Processes with Non-constant Discount Factor
Authors: Jasso-Fuentes Héctor , Prieto-Rumeau Tomás
Published: May 2024

This paper studies constrained Markov decision processes under the total expected discounted cost optimality criterion, with a state-action dependent discount factor that may take any value between zero and one. Both the state and the action space are assumed to be Borel spaces. By using the linear programming approach, consisting in stating the control problem as a linear problem on a set of occupation measures, we show the existence of an optimal stationary Markov policy. Our results are based on the study of both weak-strong topologies in the space of occupation measures and Young measures in the space of Markov policies.
A Final Value Problem with a Non-local and a Source Term: Regularization by Truncation
Authors: Mondal Subhankar
Published: May 2024

This paper is concerned with recovering the solution of a final value problem associated with a parabolic equation involving a non linear source and a non-local term, which to the best of our knowledge has not been studied earlier. It is shown that the considered problem is ill-posed, and thus, some regularization method has to be employed in order to obtain stable approximations. In this regard, we obtain regularized approximations by solving some non linear integral equations which is derived by considering a truncated version of the Fourier expansion of the sought solution. Under different Gevrey smoothness assumptions on the exact solution, we provide parameter choice strategies and obtain the error estimates. A key tool in deriving such estimates is a version of Grönwalls’ inequality for iterated integrals, which perhaps, is proposed and analysed for the first time.
TraumaFlow—development of a workflow-based clinical decision support system for the management of severe trauma cases
Authors: Neumann Juliane , Vogel Christoph , Kießling Lisa , Hempel Gunther , Kleber Christian , Osterhoff Georg , Neumuth Thomas
Published: May 2024

Purpose

The treatment of severely injured patients in the resuscitation room of an emergency department requires numerous critical decisions, often under immense time pressure, which places very high demands on the facility and the interdisciplinary team. Computer-based cognitive aids are a valuable tool, especially in education and training of medical professionals. For the management of polytrauma cases, TraumaFlow, a workflow management-based clinical decision support system, was developed. The system supports the registration and coordination of activities in the resuscitation room and actively recommends diagnosis and treatment actions.

Methods

Based on medical guidelines, a resuscitation room algorithm was developed according to the cABCDE scheme. The algorithm was then modeled using the process description language BPMN 2.0 and implemented in a workflow management system. In addition, a web-based user interface that provides assistance functions was developed. An evaluation study was conducted with 11 final-year medical students and three residents to assess the applicability of TraumaFlow in a case-based training scenario.

Results

TraumaFlow significantly improved guideline-based decision-making, provided more complete therapy, and reduced treatment errors. The system was shown to be beneficial not only for the education of low- and medium-experienced users but also for the training of highly experienced physicians. 92% of the participants felt more confident with computer-aided decision support and considered TraumaFlow useful for the training of polytrauma treatment. In addition, 62% acknowledged a higher training effect.

Conclusion

TraumaFlow enables real-time decision support for the treatment of polytrauma patients. It improves guideline-based decision-making in complex and critical situations and reduces treatment errors. Supporting functions, such as the automatic treatment documentation and the calculation of medical scores, enable the trauma team to focus on the primary task. TraumaFlow was developed to support the training of medical students and experienced professionals. Each training session is documented and can be objectively and qualitatively evaluated.