bluuebunny/crossref_metadata_2025 huggingface dataset:
Fluid-acoustic monolithic simulation based on spectral element method to solve flows past a slotted circular cylinder at low Reynolds numbers
Authors: Zhuo Ya , Qin Guoliang , Ye Ximeng
Published: September 2024

Aerodynamic noise resulting from the flow around cylinders is a significant engineering challenge in aviation and wind engineering. The phenomenon of alternating vortex shedding in the flow leads to vibration and noise generation. However, accurately describing both the flow field and the sound field is challenging due to the significant difference in magnitude between them. To tackle this issue, this work introduces the application of the spectral element method (SEM) and flow-acoustic monolithic simulation for solving the two-dimensional compressible Navier–Stokes equations at low Reynolds numbers. This study is to investigate the reduction of flow-induced noise through the implementation of slotting technology on a circular cylinder. This study focuses on examining two different slit width ratios, s/d = 0.15 and 0.25, with a slit angle of attack of 0°. A comparative analysis is conducted between a complete circular cylinder and a slotted circular cylinder. The findings indicate that the slotted cylinder exhibits reduced intensity of vortex shedding and an extended region of downstream vortex generation compared to the complete cylinder. Notably, when s/d = 0.25, the slotted cylinder demonstrates minimal noise generation. Even at s/d = 0.15, a significant reduction in flow-induced noise is observed. These results highlight the potential of utilizing slotting technology on cylinders to effectively mitigate aerodynamic noise. The application of SEM and flow-acoustic monolithic simulation shows their relevance in analyzing and designing noise mitigation techniques in aerodynamics. This work can develop innovative solutions to reduce noise and improve the performance of various applications in aviation and wind engineering.
Experimental study of discharge current oscillations with dust particles
Authors: Patel Nidhi , Prasad G.
Published: September 2024

We present a detailed experimental study of discharge current oscillations in a planar cathode plasma with poly-dispersed alumina dust particles. The dominant frequency of oscillation depends on the discharge voltage, operating pressure, and amount of dust particles placed on the cathode. The power-law variation in the dominant frequency with different external operating parameters is presented. Experimental observations suggest that the dominant mechanism behind the generation of these oscillations is the cathode spot injection of sub-micron-sized dust particles. The cathode spots also aid in the generation of fine dust particles. The threshold limit on dust particle density dispersed on the cathode suggests that below the threshold limit, the fine particles depleting the electrons play an important role and lead to the generation of self-excited oscillations. Operating above the threshold limit, a stable dust cloud was observed together with the suppression of self-excited oscillations.
Research on single-phase grounding fault location technology in distribution networks based on impedance method
Authors: Wang Sha , Wei Shengkai
Published: September 2024

This article mainly introduces the impedance based single-phase grounding fault location method for distribution networks, including its theoretical basis, algorithm steps, and simulation verification. First, starting from the impedance analysis of the transmission line model, the method of accurately measuring the location of the fault point through phase domain analysis is explained. Next, the process of impedance analysis for single-phase grounding faults was described in detail, that is, how to solve the impedance of the grounding fault points by calculating the voltage and current signals. Then, the specific process of the impedance based grounding fault location algorithm was introduced, including the calculation of equivalent load impedance, the calculation of starting voltage and current, the calculation of grounding current, and the solution of fault point location. Finally, simulation verification was conducted using an IEEE 34 node distribution system example in a MATLAB/Simulink environment, and the results showed that the algorithm has high positioning accuracy, with a maximum error of within 3%.
Diversity and transition of periodic motion of a periodically excited soft-impacting machinery
Authors: Shi Yuqing , Yang Jiuhe
Published: September 2024

Dynamics of a periodically excited vibro-impact system with soft impacts is investigated. Essential features of period-one multi-impact motion group and correlated transition characteristics in low-frequency range are discussed in detail by the way of two-parameter bifurcation space providing qualitative domains for different periodic motions. The main focus is given to the effect of sensitive parameters including constraint stiffness k
0, clearance threshold b, and damping parameter ζ on the system response. The low-frequency characteristics in the finite-dimensional parameter space are particularly explored. It is found that the increase of k
0 induces multi-type bifurcation of period-one double-impact symmetrical motion, which induces a rich variety of periodic motions, and period-one multi-impact motion group orbit primarily exist in the small-clearance b and low-frequency ω zone. Based on the evolution irreversibility of adjacent period-one multi-impact orbit, the mechanism of singularies appearing in pairs and two different transition zones (hysteresis and liguliform zones) is studied, the result of which provides a theoretical reference value for the common low-frequency vibration instability phenomenon in the field of mechanical engineering. For small-damping coefficient ζ, period-one multi-impact motion has a large quantity, and the main bridge for the transition of adjacent period-one multi-impact motion is liguliform zone, which embraces period-one multi-impact asymmetrical motion and period-n multi-impact subharmonic motion and a certain chaotic zone. For large-damping coefficient ζ, the amount of period-one multi-impact motion group is reduced, and the main bridge for the transition of adjacent period-one multi-impact motion is hysteresis zone, where adjacent period-one multi-impact orbits can coexist according to initial conditions. As designing and renovating impact mechanical equipment, the reasonable matching law of dynamic parameters can be determined through two-parameter bifurcation space, which is conducive to making the system work in stable periodic motion and obtaining larger instantaneous impact velocity.
A nanosecond level current pulse capture taper optical fiber probe based on micron level nitrogen-vacancy color center diamond
Authors: Bian 卞 Yuchen 雨辰 , Mao 毛 Yangfan 扬帆 , Chen 陈 Honghao 鸿浩 , Ge 葛 Shiyu 仕宇 , Lu 卢 Wentao 文韬 , Wang 王 Chengkun 成坤 , An 安 Sihan 思瀚 , Du 杜 Guanxiang 关祥
Published: September 2024

This work demonstrates a micron-sized nanosecond current pulse probe using a quantum diamond magnetometer. A micron-sized diamond crystal affixed to a fiber tip is integrated on the end of a conical waveguide. We demonstrate real-time visualization of a single 100 nanosecond pulse and discrimination of two pulse trains of different frequencies with a coplanar waveguide and a home-made PCB circuit. This technique finds promising applications in the display of electronic stream and can be used as a pulse discriminator to simultaneously receive and demodulate multiple pulse frequencies. This method of detecting pulse current is expected to provide further detailed analysis of the internal working state of the chip.
PDMS/CNT electrodes with bioamplifier for practical in-the-ear and conventional biosignal recordings
Authors: Sanguantrakul Jongsook , Hemakom Apit , Soonrach Tharapong , Israsena Pasin
Published: September 2024

Objective. Potential usage of dry electrodes in emerging applications such as wearable devices, flexible tattoo circuits, and stretchable displays requires that, to become practical solutions, issues such as easy fabrication, strong durability, and low-cost materials must be addressed. The objective of this study was to propose soft and dry electrodes developed from polydimethylsiloxane (PDMS) and carbon nanotube (CNT) composites. Approach. The electrodes were connected with both conventional and in-house NTAmp biosignal instruments for comparative studies. The performances of the proposed dry electrodes were evaluated through electromyogram, electrocardiogram, and electroencephalogram measurements. Main results. Results demonstrated that the capability of the PDMS/CNT electrodes to receive biosignals was on par with that of commercial electrodes (adhesive and gold-cup electrodes). Depending on the type of stimuli, a signal-to-noise ratio of 5–10 dB range was achieved. Significance. The results of the study show that the performance of the proposed dry electrode is comparable to that of commercial electrodes, offering possibilities for diverse applications. These applications may include the physical examination of vital medical signs, the control of intelligent devices and robots, and the transmission of signals through flexible materials.
A low-swelling alginate hydrogel with antibacterial hemostatic and radical scavenging properties for open wound healing
Authors: Ma Xuebin , Fu Xiao , Meng Jianwen , Li Hongmei , Wang Fang , Shao Huarong , Liu Yang , Liu Fei , Zhang Daizhou , Chi Bo , Miao Jinlai
Published: September 2024

Development of a low-cost and biocompatible hydrogel dressing with antimicrobial, antioxidant, and low swelling properties is important for accelerating wound healing. Here, a multifunctional alginate hydrogel dressing was fabricated using the D-(+)-gluconic acid δ-lactone/CaCO3 system. The addition of hyaluronic acid and tannic acid (TA) provides the alginate hydrogel with anti-reactive oxygen species (ROS), hemostatic, and pro-wound healing properties. Notably, soaking the alginate hydrogel in a poly-ϵ-lysine (EPL) aqueous solution enables the alginate hydrogel to be di-crosslinked with EPL through electrostatic interactions, forming a dense network resembling ‘armor’ on the surface. This simple one-step soaking strategy provides the alginate hydrogel with antibacterial and anti-swelling properties. Swelling tests demonstrated that the cross-sectional area of the fully swollen multifunctional alginate hydrogel was only 1.3 times its initial size, thus preventing excessive wound expansion caused by excessive swelling. After 5 h of in vitro release, only 7% of TA was cumulatively released, indicating a distinctly slow-release behavior. Furthermore, as evidenced by the removal of 2,2-diphenyl-1-picrylhydrazyl free radicals, this integrated alginate hydrogel systems demonstrate a notable capacity to eliminate ROS. Full-thickness skin wound repair experiment and histological analysis of the healing site in mice demonstrate that the developed multifunctional alginate hydrogels have a prominent effect on extracellular matrix formation and promotion of wound closure. Overall, this study introduces a cost-effective and convenient multifunctional hydrogel dressing with high potential for clinical application in treating open wounds.
Mechanisms regulating trophic transfer in the Humboldt Upwelling System differ across time scales
Authors: Xue Tianfei , Frenger Ivy , Hauschildt Jaard , Oschlies Andreas
Published: September 2024

The Humboldt Upwelling System hosts a highly productive ecosystem with central importance for global fisheries, yet with strong seasonal and interannual variability in the planktonic base of the food chain ultimately affecting fish yield. Understanding the variability in energy transfer within the plankton community in the contemporary climate can provide valuable insights for future projections of planktonic dynamics. Therefore, we use a regional physical-biogeochemical ocean model simulation (CROCO-BioEBUS) from 1990 to 2010 to investigate the underlying mechanisms of seasonal and interannual variability of the trophic transfer. Our model simulations suggest that, on an interannual scale, variations in trophic transfer are governed by variations in the offshore surface flow that modulate the plankton cross-shore distribution. Weak offshore surface flow, as simulated during the El Niño period, allows the zooplankton to stay relatively close to the shore, leading to more efficient grazing and trophic transfer compared to years with strong offshore flow. This mechanism differs from the seasonal one, where the mixed layer depth is the primary driver of variations in plankton dynamics, including trophic transfer. Our results highlight that mechanisms controlling plankton trophic transfer differ across time scales, and thus stress that extrapolating solely from seasonal findings to understand long-term trophic transfer changes in the context of climate change may be insufficient.
The health and wellbeing co-benefits of policies and programs to address climate change in urban areas: a scoping review
Authors: Becvarik Z A , White L V , Lal A
Published: September 2024

Existing research suggests that a health-centred response to the climate crisis would support immediate and more ambitious action that minimises adverse health outcomes of climate change whilst providing additional co-benefits for population health. This review aimed to identify and assess literature that examines the health and wellbeing co-benefits of climate action in urban areas and to identify potential co-benefits that could be incorporated into policy or programme evaluation. We searched Scopus, PubMed and Web of Science, and screened titles, abstracts, and full-text. Peer-reviewed studies in English were included if they focused on health and wellbeing co-benefits of climate change adaptation and/or mitigation policies and programmes specific to urban areas. Our analysis found that all 39 studies in this review identified positive health and wellbeing co-benefits, with the majority focusing on transport policies and cross-sectoral mitigation and adaptation. All included studies employed a diverse array of modelling methodology, with multiple models and interdisciplinary approaches to evaluate co-benefits. Co-benefits ranged from reduced or avoided mortality and morbidity to social and economic health benefits. The degree of co-benefits differed according to the policies themselves; the policy sector; and vulnerability, demographic and/or geographic factors. Nine studies identified negative trade-offs of climate action. The review’s findings add to existing literature in support of the value and importance of assessing the health and wellbeing co-benefits of climate action. The review also highlights the need for further identification and quantification of a comprehensive set of health and wellbeing co-benefits, improved data reporting and granularity, as well as research evaluating the impact of climate action that considers how vulnerability, demographic, geographic or other factors interact with policy implementation. This research is critical in informing the cost-effective prioritisation and coordination of climate policies that maximise human health benefits and promote health equity by minimising trade-offs for vulnerable groups.
CSR And Health Care Management: Conceptual Approach Towards a Sustainable and Socially Responsible Organisation
Authors: Banerjee Ipsita
Published: September 2024

“Good Health and Well-being” is one of the prime Sustainable Development goals which was declared by UNDP as a crucial factor to improve the world. There is no doubt regarding the fact that health is an asset to human beings. Considering the recent covid-19 pandemic scenario it has been observed that in case of economically emerging nations, such as India, it is exceedingly difficult for the governments to singlehandedly look after the health care facilities. Now, it is already known that since 2013 (CSR), that is, Corporate Social Responsibility is a mandate for corporates having a Net worth of more than Rs. 500 crores. In this regard the present research has tried to explore the ways in which CSR activities can be used to enhance health communication for providing better health care facilities in India. The results derived from of this research have further highlighted the contribution of CSR done by pharmaceutical industry in SDG 3. The research methodology has been based on post-positivism philosophy where both qualitative and quantitative secondary data will be collected from CSR reports and relevant case studies. Thereafter, based on the Theoretical Framework of Triple Bottomline theory (People, Planet and Profit), the research has suggested relevant CSR policies which can contribute towards “Good Health and Well-being”.
Emission characterisation of motorcycles and the potential of co-benefits from selected development scenarios in the urban ecosystem of Hanoi, Vietnam
Authors: Tran Hien , Trung Dung Nghiem , Hoang Ngoc Khue Vu , Thoai Tam Nguyen , Ngoc Thao Nguyen Nguyen , Quoc Bang Ho
Published: September 2024

Motorcycles are the largest proportion of transport in Hanoi. This study focuses on the emission characteristics and initially evaluates the potential co-benefits of low emission zones (LEZ) applied to motorcycles in Hanoi. The International Vehicle Emissions (IVE) model was designed by the U.S. EPA to calculate emissions from motor vehicles and was used to find the emission factor, the important index for emission characteristics of motorcycle activities, in Hanoi. This study surveyed motorcycle technologies and activities in Hanoi with questionnaires, collected data from GPS devices, and counted traffic flow through video cameras and collaborators teams from 2021 to 2023. EFs for the typical pollutants and GHGs of motorcycles in Hanoi were determined. During running, EFruning is 0.053g/km with PM, 4.8 g/km for CO, 0.006 g/km for SO2, 0.13 g/km NOx, CO2 is 72.55 g/km and CH4 is 0.24 g/km, respectively. When starting, EFstart-up is 0.12 g/time with PM, CO is 12.24 g/time, SO2 is 0.0007 g/time, NOx is 1.05 g/time, CO2 is 6.96 g/time, CH4 is 0.53 g/time and N2O is 0.0009 g/time, respectively. Using the EMISENS model, inventory emissions were calculated at tier 3 for this source via the Bottom-up approach. The EMISENS model calculates emissions resulting from traffic, developed by Bang Ho et al in 2010 uses input data related to traffic activities and three emission factors found from the IVE model to calculate the emissions. The total emissions from motorcycle operations in Hanoi are approximately 5.3 thousand tons of PM and 4.6 million tons of CO2e. The proposed LEZ solution for motorcycles brings climate co-benefits of reducing 1.62 million tons CO2e in scenario 1 - limiting all day and 563.2 thousand tons CO2e in scenario 2 – limit operations from 3:00 p.m. to 8:00 p.m. in 2025. Co-benefits on the environment corresponding to the two scenarios with PM are 1990 and 692 tons. Reducing motorcycle operations during 5 peak hours at LEZ can reduce total emissions from motorcycles in Hanoi by 12%. Meanwhile, the proposed 24-hour LEZ for motorcycles in the area has the potential to reduce GHGs by 35%. These results show that reducing emissions from motorcycles brings climate and environmental co-benefits.
Sand dunes Groundwater Quality in the context of Climate Change: A Case Study of Phao Dai Hamlet, Tien Giang, Vietnam
Authors: Van Lam Giang , Van Tran Bao , Phuoc Ho Thanh
Published: September 2024

Climate change is currently the main cause for deteriorating freshwater sources worldwide. It has raised sea levels and fluctuated rainfall over the years, causing salinity intrusion among coastal areas. Therefore, sand dunes, one of the primary freshwater sources formed by depositing alluvium at higher sea level altitudes, have been affected by climate change. This study focused on the impact of climate conditions on the freshwater supply in these potential areas. Fifteen groundwater samples from 06 dug wells in Phao Dao hamlet, Tien Giang province, Vietnam, were collected monthly from August 2016 to March 2017 to be analyzed at the Institute of Coastal and Offshore Engineering (ICOE). The results showed that most of the nutrient-related analyzed parameters were within the thresholds of QCVN 09 – MT: 2015/BTNMT for groundwater use and QCVN 01:2009/ BYT for drinking water quality, but not salinity-related parameters. In addition, salinity, CaCO3, and TDS unpredictably fluctuated depending on the seasons and lowered from the coastal to inland areas.
Monte Carlo investigation of the nucleus size effect and cell’s oxygen content on the damage efficiency of protons
Authors: Mokari Mojtaba , Moeini Hossein , Eslamifar Mina
Published: September 2024

Living tissues could suffer different types of DNA damage as a result of being exposed to ionizing radiations. Monte Carlo simulations of the underlying interactions have been instrumental in predicting the damage types and the processes involved. In this work, we employed Geant4-DNA and MCDS for extracting the initial DNA damage and investigating the dependence of damage efficiency on the cell’s oxygen content. The frequency-mean lineal (

y
¯

F

) and specific (

z
¯

F

) energies were derived for a spherical volume of water of various diameters between 2 and 11.1 μm. This sphere would serve as the nucleus of a cell of 100 μm diameter, engulfed by a homogeneous beam of protons. These microdosimetric quantities were calculated assuming spherical samples of 1 μm diameter in MCDS. The simulation results showed that for 230 MeV protons, an increase in the oxygen content from 0 by 10% raised the frequency of single- and double-strand breaks and lowered the base damage frequency. The resulting damage frequencies appeared to be independent of nucleus diameter. For proton energies between 2 and 230 MeV,

y
¯

F

showed no dependence on the cell diameter and an increase of the cell size resulted in a decrease in

z
¯

F

.

An increase in the proton energy slowed down the decreasing rate of

z
¯

F

as a function of nucleus diameter. However, the ratio of

y
¯

F

values corresponding to two proton energies of choice showed no dependence on the nucleus size and were equal to the ratio of the corresponding

z
¯

F

values. Furthermore, the oxygen content of the cell did not affect these microdosimetric quantities. Contrary to damage frequencies, these quantities appeared to depend only on direct interactions due to deposited energies. Our calculations showed the near independence of DNA damages on the nucleus size of the human cells. The probabilities of different types of single and double-strand breaks increase with the oxygen content.
Distribution of mechanical properties of native human ligamentum flavum depending on histopathological changes
Authors: Samal Filip , Cerny Vojtech , Kujal Petr , Jezek Jakub , Skala-Rosenbaum Jiri , Sepitka Josef
Published: September 2024

This study aimed to characterize the mechanical properties of native human ligamentum flavum (LF) and correlate them with histopathological changes. Mechanical property gradients across the cranial, medial, and caudal regions of LF were mapped and compared with histological sections. We also compared lumbar spinal stenosis (LSS) samples with disc herniation (DH) samples as reference material to identify differences in mechanical properties and histopathological features. Our results revealed significant heterogeneity in LF mechanical properties, with local variations correlating with specific histopathological changes such as chondroid metaplasia and loss of elastic fibers. These findings underscore the importance of considering LF heterogeneity in mechanical characterization and provide insights into its behavior under pathological conditions.
Differential-phase-shift QKD with practical Mach–Zehnder interferometer
Authors: Mizutani Akihiro , Terashita Masanori , Matsubayashi Junya , Mori Shogo , Matsukura Ibuki , Tagawa Suzuna , Tamaki Kiyoshi
Published: September 2024

Differential-phase-shift (DPS) quantum key distribution stands as a promising protocol due to its simple implementation, which can be realized with a train of coherent pulses and a passive measurement unit. To implement the DPS protocol, it is crucial to establish security proofs incorporating practical imperfections in users’ devices, however, existing security proofs make unrealistic assumptions on the measurement unit using a Mach–Zehnder interferometer. In this paper, we enhance the implementation security of the DPS protocol by incorporating a major imperfection in the measurement unit. Specifically, our proof enables us to use practical beam splitters with a known range of the transmittance rather than the one with exactly 50%, as was assumed in the existing security proofs. Our numerical simulations demonstrate that even with fluctuations of

±
0.5
%

in the transmittance from the ideal value, the key rate degrades only by a factor of 0.57. This result highlights the feasibility of the DPS protocol with practical measurement setups.
Adaptive convolutional-LSTM neural network with NADAM optimization for intrusion detection in underwater IoT wireless sensor networks
Authors: S Arivumani Samson , M Nagarajan
Published: September 2024

Underwater IoT networks rely on sensor nodes to continuously monitor and collect real-time data from marine environments. The nodes in the underwater networks face security challenges in terms of intrusions. Intrusions are common in conventional wireless sensor networks as well as in underwater sensor networks. Intrusions like data tampering, node insertion, unauthorized access compromises the security and privacy of the network. The existing Intrusion Detection Systems (IDS) faces limitations while detecting intrusions in Underwater IoT Wireless Sensor Networks (UIoTWSN) due to the dynamic condition of underwater environment. To overcome this, a novel IDS for UIoTWSN is proposed by combining the features of advanced deep learning techniques in an optimized manner. The proposed hybrid model comprises convolutional LSTM network with NADAM optimizer to analyze the spatial and temporal features to detect the intrusions. To handle the dynamic nature of underwater sensor network and to improve the convergence speed of the proposed IDS, NADAM optimizer is integrated in this research work. Experimentations of the proposed model validates the higher accuracy of 96.7%, precision of 94.5% and recall of 95.2% which is better than the conventional techniques.
A novel image recognition based fault diagnostics of customized EV battery pack using optimized GoogLeNet
Authors: Dasari Hethu Avinash , A Rammohan
Published: September 2024

Diagnosing faults in Battery Management Systems is critical in ensuring rechargeable batteries’ safe and efficient operation. Various fault detection techniques have been developed to address this requirement. This paper focuses on a novel approach to fault diagnosis by utilizing a personalized battery pack and employing image recognition. This study collects three distinct types of fault data from the battery pack and transforms it into image format. These images are inputs to a sophisticated Optimized GoogLeNet model designed explicitly for fault detection in the Battery Management System. The model’s capability to accurately detect and classify different types of faults in the battery pack is thoroughly evaluated. The results generated by the developed model are compared with those produced by the AlexNet and GoogLeNet models. It is demonstrated that the Optimized GoogLeNet model exhibits superior performance in fault detection by obtaining an accuracy of 99.5%, marking a significant improvement over existing techniques. The findings establish that leveraging image-based techniques with advanced Deep learning algorithms holds promising potential for enhancing the accuracy and efficacy of fault diagnosis in personalized battery packs.
Towards sustainable energy: integrating ERA5 data for offshore wind farm planning in India
Authors: Anangapal Hari Bhaskaran , Victor Kirubakaran
Published: September 2024

India’s pursuit of offshore wind energy development, particularly along the Tamil Nadu coastline within its Exclusive Economic Zone (EEZ), faces significant spatial and economic challenges due to existing industrial activities and water depth limitations. Motivated by the need to optimize offshore wind resources and bridge the gap between onshore and offshore wind energy achievements, this study hypothesizes that ERA5 reanalysis wind data can be relied upon for assessing offshore wind resources and optimizing wind farm layouts, especially in the absence of measured data. The research employs methods such as comparing ERA5 data with empirical wind measurements, generating wind rose diagrams for layout optimization, and conducting a comprehensive financial analysis to estimate the Levelized Cost of Energy (LCoE). The results confirm the efficacy of ERA5 data, identifying an optimal wind farm layout with a capacity density of 5.17 MW per square kilometer, turbine spacing of 7.22 meters, and an LCoE of Rs. 8.84 per kWh. The study concludes that significant financial support and strategic policy interventions are essential for minimizing wake losses, optimizing capacity density, and fostering the long-term growth of India’s offshore wind energy sector, providing critical insights for policymakers, developers, and investors. The novelty of this research lies in its detailed exploration of spatial optimization and cost-effective strategies to enhance the techno-economic viability of offshore wind projects in India.
Long-term isoagglutinin monitoring after ABO-incompatible kidney transplantation
Authors: Kim Han Joo , Chung Yousun , Kim Hyungsuk , Ko Youngmin , Kim Young Hoon , Hwang Sang-Hyun , Oh Heung-Bum , Ko Dae-Hyun
Published: September 2024

Objectives

This study aimed to evaluate whether a 2-week period of daily isoagglutinin titer testing after ABO-incompatible kidney transplantation (ABOi-KT) is sufficient to ensure successful engraftment and to advocate for an extension of the monitoring duration in specific situations.

Methods

We reviewed patients from January 2022 to December 2023 at Asan Medical Center who underwent therapeutic plasma exchange (TPE) due to elevated ABO antibody titers and suspected acute antibody-mediated rejection (AMR) after ABOi-KT. Data collected included pre- and posttransplantation laboratory results, clinical and procedural information, imaging studies, and needle biopsy results of the renal graft.

Results

We encountered 3 cases of acute AMR 2 weeks after transplantation. All cases exhibited simultaneous increases in anti-ABO antibody isoagglutinin titers, creatinine, and C-reactive protein levels. Clinical signs, including fever, suggested possible infection, and renal graft biopsy, confirmed AMR in all cases. Two cases underwent graftectomy, while the third recovered renal function after conservative treatment, including TPE.

Conclusions

Our findings suggest that a 2-week monitoring period for isoagglutinin titers after ABOi-KT may not be sufficient to detect late AMR. Extending the monitoring duration and considering lifelong fresh-frozen plasma transfusion with graft-compatible blood types, along with periodic isoagglutinin titer testing in cases of suspected AMR, may improve long-term graft outcomes.
Emulations of Oncology Trials Using Real-World Data: A Systematic Literature Review
Authors: Rider Jennifer R , Wasserman Asher , Slipski Lukas , Carrigan Gillis , Harvey Raymond , Jiao Xiaolong , McRoy Lynn , Pace Nelson D , Becnel Lauren , Bruno Amanda , Eckert Joy C , Hodgkins Priscilla , Jain Purva , Merola David , Ovbiosa Osayi E , Natanzon Yanina , Pinheiro Simone , Quinn Jameson , Rodriguez-Watson Carla , Campbell Ulka ,   the Coalition to Advance RWE in RCT Emulations (CARE) Initiative
Published: September 2024

By evaluating published emulations of oncology RCTs studies in which both the active and comparator groups are sourced from RWD and target trial results are available for benchmarking, this systematic review aims to gain insight into factors related to emulation performance. Thirteen oncology emulation studies using various types of RWD were identified through an online database search of PubMed through 2022. Based on the ROBINS-I tool, most studies (N=8) had a serious risk of overall bias driven by risk of bias from confounding. Approximately half of the studies (N=6) fully proxied the RCT entry criteria. Of 11 RWD studies that provided sufficient detail to quantify emulation performance, the emulation HR estimate fell within the 95% CI of the trial estimate in 9 of the studies. There were no clear trends between risk of bias or degree to which the entry criteria were proxied and emulation performance. Findings may have been influenced by publication bias and researcher degrees of freedom, as only one emulation study pre-registered its protocol. Tools for comprehensively characterizing factors that affect emulation performance, including the real-world clinical context as it relates to the RCT research question, are needed to evaluate the feasibility of a RCT emulation.
Knockout of OsWOX13 moderately delays flowering in rice under natural long-day conditions
Authors: Kim Yeon-Ki
Published: September 2024

Plants are sensitive to photoperiods and are also equipped with systems to adjust their flowering time in response to various changes in the environment and developmental hormones. In the present study, previously generated rice OsWOX13 overexpression and newly generated OsWOX13 knockout lines constructed via CRISPR/Cas9 technology flowered 10 days earlier and 4-6 days later than the wild type, respectively. Quantitative real-time  polymerase chain reaction analyses revealed that OsWOX13 might be involved in drought escape responses through the b-ZIP TRANSCRIPTION FACTOR 23 signaling pathway during rice flowering via photoperiod signaling genes such as Grain number, plant height and heading date 7, Early heading date 1, RICE FLOWERING LOCUS T1, Heading date 3a, and MADS14. Future investigations of OsWOX13 may provide insight into how plants adjust their flowering under stress conditions and how OsWOX13 could be precisely controlled to achieve maximum productivity in rice breeding.
An algorithm for drug-resistant epilepsy in Danish national registers
Authors: Bølling-Ladegaard Eva , Dreier Julie W , Christensen Jakob
Published: September 2024

Patients with drug-resistant epilepsy (DRE) have increased risks of premature death, injuries, psychosocial dysfunction and a reduced quality of life. Identification of persons with DRE in administrative data can allow for effective large-scale research, and we therefore aimed to construct an algorithm for identification of DRE in Danish nation-wide health registers.

We used a previously generated sample of 525 persons with medical record-validated incident epilepsy between 2010 and 2019, of whom 80 (15%) fulfilled International League Against Epilepsy criteria of DRE at the time of the latest contact; this cohort was considered the gold standard. We linked information in the validated cohort to Danish national health registers and constructed register-based algorithms for identification of DRE cases. The accuracy of each algorithm was validated against the medical record-validated gold standard. We applied the best-performing algorithm according to test accuracy (F1 score) to a large cohort with incident epilepsy identified in the Danish National Patient Registry between 1995 and 2013 and performed descriptive and logistic regression analyses to characterize the cohort with DRE as identified by the algorithm.

The best-performing algorithm in terms of F1 score was defined as ‘fillings of prescriptions for ≥3 distinct antiseizure medications (ASMs) within 3 years or acute hospital visit with epilepsy/convulsions following fillings of prescriptions for two distinct ASMs’ (sensitivity 0.59, specificity 0.93, positive predictive value 0.59, negative predictive value 0.92, area under the receiver operating characteristic curve 0.77, and F1 score 0.595). Applying the algorithm to a register-based cohort of 83 682 individuals with incident epilepsy yielded 8650 cases (10.3%) with DRE. In multivariable logistic regression analysis, early onset of epilepsy, focal or generalized epilepsy, somatic co-morbidity and substance abuse were independently associated with risk of being classified with DRE.

We developed an algorithm for the identification of DRE in Danish national registers, which can be applied for a variety of research questions. We identified early onset of epilepsy, focal or generalized epilepsy, somatic co-morbidity and substance abuse as risk factors for DRE.
Associations between acute kidney injury and bone fractures: a retrospective cohort study
Authors: Cheikh Hassan Hicham I , Mulholland Bridie S , McAlister Brendan , Lambert Kelly , Murali Karumathil M , Moules Stephen , Mullan Judy
Published: September 2024

Background

Acute kidney injury (AKI) is common. An AKI episode may disrupt the normal mineral bone balance maintained by normal kidney function, thereby modifying the risk of developing bone fractures. However, it remains unclear whether an AKI episode is associated with the risk of bone fractures.

Methods

Using retrospective cohort study from an Australian Local Health District, we examined the association between an AKI episode and bone fractures using patient data between 2008 and 2017. Time-varying Cox proportional hazards and propensity-matched analysis were used to examine the association. Sensitivity analyses were undertaken to capture the impact of confirmed AKI status and AKI severity.

Results

Of 123 426 included patients, 14 549 (12%) had an AKI episode and 12 505 (10%) had a bone fracture. In the unadjusted analysis, AKI was associated with bone fractures [hazard ratio (HR) 1.99, 95% confidence interval (CI) 1.88–2.11]. This association persisted in the adjusted analysis (HR 1.50, 95% CI 1.41–1.59) and propensity-matched dataset (HR 1.71, 95% CI 1.59–1.83). The sensitivity analysis yielded similar results, with the AKI patients having a higher risk of fractures compared with no AKI patients in the adjusted analysis (HR 1.34, 95% CI 1.25–1.43) and in the propensity-matched dataset (HR 1.44, 95% CI 1.33–1.55). Similar results were seen in the subsidiary sensitivity analysis excluding patients without baseline creatinine. We did not find an increased risk of bone fractures with increasing AKI severity (P = .7). Interaction tests demonstrated a significant association between sex and age category with AKI status and fractures, but not CKD stage or osteoporosis.

Conclusions

AKI is associated with a greater risk of bone fractures. This could have implications for managing and screening for bone disease in patients post-AKI episode. This association should be examined in other cohorts and populations for verification.
Machine learning models for mortality prediction in critically ill patients with acute pancreatitis–associated acute kidney injury
Authors: Liu Yamin , Zhu Xu , Xue Jing , Maimaitituerxun Rehanguli , Chen Wenhang , Dai Wenjie
Published: September 2024

Background

The occurrence of acute kidney injury (AKI) was associated with an increased mortality rate among acute pancreatitis (AP) patients, indicating the importance of accurately predicting the mortality rate of critically ill patients with acute pancreatitis–associated acute kidney injury (AP-AKI) at an early stage. This study aimed to develop and validate machine learning–based predictive models for in-hospital mortality rate in critically ill patients with AP-AKI by comparing their performance with the traditional logistic regression (LR) model.

Methods

This study used data from three clinical databases. The predictors were identified by the Recursive Feature Elimination algorithm. The LR and two machine learning models—random forest (RF) and eXtreme Gradient Boosting (XGBoost)—were developed using 10-fold cross-validation to predict in-hospital mortality rate in AP-AKI patients.

Results

A total of 1089 patients from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) and eICU Collaborative Research Database (eICU-CRD) were included in the training set and 176 patients from Xiangya Hospital were included in the external validation set. The in-hospital mortality rates of the training and external validation sets were 13.77% and 54.55%, respectively. Compared with the area under the curve (AUC) values of the LR model and the RF model, the AUC value of the XGBoost model {0.941 [95% confidence interval (CI) 0.931–0.952]} was significantly higher (both P < .001) and the XGBoost model had the smallest Brier score of 0.039 in the training set. In the external validation set, the performance of the XGBoost model was acceptable, with an AUC value of 0.724 (95% CI 0.648–0.800). However, it did not differ significantly from the LR and RF models.

Conclusions

The XGBoost model was superior to the LR and RF models in terms of both the discrimination and calibration in the training set. Whether the findings can be generalized needs to be further validated.
Validating, Implementing, and Monitoring Machine Learning Solutions in the Clinical Laboratory Safely and Effectively
Authors: Spies Nicholas C , Farnsworth Christopher W , Wheeler Sarah , McCudden Christopher R
Published: September 2024

Background

Machine learning solutions offer tremendous promise for improving clinical and laboratory operations in pathology. Proof-of-concept descriptions of these approaches have become commonplace in laboratory medicine literature, but only a scant few of these have been implemented within clinical laboratories, owing to the often substantial barriers in validating, implementing, and monitoring these applications in practice. This mini-review aims to highlight the key considerations in each of these steps.

Content

Effective and responsible applications of machine learning in clinical laboratories require robust validation prior to implementation. A comprehensive validation study involves a critical evaluation of study design, data engineering and interoperability, target label definition, metric selection, generalizability and applicability assessment, algorithmic fairness, and explainability. While the main text highlights these concepts in broad strokes, a supplementary code walk-through is also provided to facilitate a more practical understanding of these topics using a real-world classification task example, the detection of saline-contaminated chemistry panels.

Following validation, the laboratorian's role is far from over. Implementing machine learning solutions requires an interdisciplinary effort across several roles in an organization. We highlight the key roles, responsibilities, and terminologies for successfully deploying a validated solution into a live production environment. Finally, the implemented solution must be routinely monitored for signs of performance degradation and updated if necessary.

This mini-review aims to bridge the gap between theory and practice by highlighting key concepts in validation, implementation, and monitoring machine learning solutions effectively and responsibly in the clinical laboratory.
Leisure-time activities and disability among Chinese community-dwelling oldest old: evidence from the Chinese Longitudinal Healthy Longevity Study
Authors: Zhong Wen-Fang , Wang Xiao-Meng , Liang Fen , Song Wei-Qi , Chen Zi-Ting , Li Zhi-Hao , Shen Qiao-Qiao , Shen Dong , Nan Ying , Xiang Jia-Xuan , Li Chuan , Ye Zi-Yu , Huang Hong-Jun , Wang Jia-Ye , Lv Yue-Bin , Shi Xiao-Ming , Mao Chen
Published: September 2024

With the acceleration of population aging, disability in older adults is a growing public health problem; however, little is known about the role of specific leisure-time activities in affecting disability. This study prospectively examined the association of leisure-time activities with disability among the Chinese oldest old. A total of 14 039 adults aged 80 years or older (median age of 89.8 years) were enrolled from the Chinese Longitudinal Healthy Longevity Survey from 1998 to 2014. Disability was defined as the presence of concurrent impairment in activities of daily living and physical performance. Cox proportional hazards models were used to estimate the associations between leisure-time activities and disability. During a mean of 4.2 years (2.7 years) of follow-up, 4487 participants developed disability. Compared with participants who never engaged in leisure-time activities, participants who engaged in almost daily activities, including gardening, keeping domestic animals or pets, playing cards or mahjong, reading books or newspapers, and watching TV or listening to the radio had a lower risk of disability, with HRs of 0.78 (0.69–0.88), 0.64 (0.58–0.70), 0.74 (0.63–0.86), 0.74 (0.65–0.84), and 0.84 (0.77–0.90), respectively. Moreover, the risk of disability gradually decreased with participation in an increasing number of those leisure-time activities (P for trend <0.001). Frequent engagement in leisure-time activities was associated with a lower risk of disability among the Chinese oldest old. This study highlights the importance of incorporating a broad range of leisure-time activities into the daily lives of older adults.
Developing a nationwide registry of UK veterans seeking help from sector charities—a machine learning approach to stratification
Authors: Serra Giuseppe , Tomietto Marco , McGill Andrew , Kiernan Matthew
Published: September 2024

The assistance to veterans in the UK is provided by the National Health Service and over 1800 military charities. These charities count services using different definitions and reporting systems, so to date a national registry of service usage does not exist. The aim of the Map Of Need Aggregation ResearCH study is to build a standardized registry of service usage data for the military charity sector. Data are completely anonymized by adopting a Secure Hashing Algorithm. A unique anonymous identifier is generated allowing both privacy protection and avoiding double counts. Data are standardized and linked with an automated process to create an aggregated dataset. The dataset describes the population, using both a priori and machine learning approaches. To date a total of 42 509 veterans with 128 423 needs are included. The mean age was 60.1 years, and 90% were male. 65% were receiving other benefits, 5% were homeless and 1% were in prison. 65% of the needs recorded concerned social wellbeing. 40% of veterans received assistance in at least two different years. The k-means clustering approach returned 4 subgroups of use that were identical to those created using a priori knowledge. The dataset is the most comprehensive source of veteran charity usage data in the UK to date. Service usage is generally homogenous among subgroups, but some differences were highlighted indicating that younger, non-officer veterans may be more at risk of presenting with more complex needs. These first useful insights can help allocate resources to build an effective preventive strategy for more complex cases.
Plasticity cannot fully compensate evolutionary differences in heat tolerance across fish species
Authors: Molina Andrés N , Carter Mauricio J , Rezende Enrico L
Published: September 2024

Understanding how evolution and phenotypic plasticity contribute to variation in heat tolerance is crucial to predicting responses to warming. Here, we analyze 272 thermal death time curves of 53 fish species acclimated to different temperatures and quantify their relative contributions. Analyses show that evolution and plasticity account, respectively, for 80.5% and 12.4% of the variation in elevation across curves, whereas their slope remained invariant. Evolutionary and plastic adaptive responses differ in magnitude, with heat tolerance increasing to 0.54 °C between species and 0.32 °C within species for every 1 °C increase in environmental temperatures. After successfully predicting critical temperatures under ramping conditions to validate these estimates, we show that fish populations can only partly ameliorate the impact of warming waters via thermal acclimation, and this deficit in plasticity could increase as the warming accelerates.