bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the Surface Quality and Temperature in Grinding of Acrylic-Based Resin
Authors: Haider Syed Mustafa , Hussain Abbas , Abbas Muntazir , Khan Shaheryar Atta , Sarfraz Shoaib
Published: June 2024

Polymeric resins are becoming increasingly popular in medical and engineering applications due to their properties, such as their low weight, high strength, corrosion resistance, non-allergenicity, and extended service life. The grinding process is used to convert these materials into desired products, offering high accuracy and surface quality. However, grinding generates significant heat, which can potentially degrade the material. This study investigates the grinding of acrylic-based resins, specifically focusing on the interplay between the grind zone temperature and surface finish. The low glass transition temperature (57 °C) of the acrylic necessitates the precise control of the grinding parameters (spindle speed, feed rate, depth of cut, and grinding wheel grain size), to maintain a low temperature and achieve high-quality machining. Thermal imaging and thermocouples were employed to measure the grind zone temperature under various grinding conditions. This study investigates the influence of four parameters: spindle speed, feed rate, depth of cut, and grinding wheel grain size. The best surface finish (Ra: 2.5 µm) was obtained by using a finer-grained (80/Ø 0.18 mm) grinding wheel, combined with slightly adjusted parameters (spindle speed: 11.57 m/s, feed rate: 0.406 mm/rev, depth of cut: 1.00 mm), albeit with a slightly higher grind zone temperature (~54 °C). This study highlighted the importance of balancing the grind zone temperature and surface finish for the optimal grinding of acrylic-based resins. Further, this research finds that by carefully controlling the grinding parameters, it is possible to achieve both a high surface quality and prevent material degradation. The research findings could be highly valuable for optimizing the grinding process for various medical and engineering applications.
A Microscopy Evaluation of Emergence Profile Surfaces of Dental Custom CAD-CAM Implant Abutments and Dental Implant Stock Abutments
Authors: Târtea Daniel Adrian , Manolea Horia Octavian , Ionescu Mihaela , Gîngu Oana , Amărăscu Marina Olimpia , Popescu Adrian Marcel , Mercuţ Veronica , Popescu Sanda Mihaela
Published: June 2024

Recently, due to the high demand for dental implants, the use of dental implant stock abutments has increased significantly, especially dental custom CAD/CAM implant abutments milled by dental technicians in their laboratories. The purpose of this study is to analyze the surface quality of the emergence profile of dental custom CAD/CAM implant abutments made by a non-industrial milling machine, compared to original and compatible dental implant stock abutments made by industrial machines. Thirty dental implant abutments were divided into six study lots. Lot 1 (control group): original dental implant stock abutments—industrial machined; lot 2 (study group): compatible dental implant stock abutments—industrial machined; lots 3, 4, 5, and 6 (study groups): compatible custom CAD/CAM dental implant abutments—non-industrial milled with hyperDENT CAM software and Paragon Tools. The Nikon SMZ745T stereomicroscope was used to analyze the emergence profile surface of each dental implant abutment. The structure of the analyzed surfaces did not show significant differences between original and compatible abutments that were industrially machined. As for the customized dental implant abutments, the greatest similarity with the original was obtained for lot 6, and a significant statistical difference was obtained for lot 4. Stepover and Feed Rate parameters of the milling process influenced the surface roughness of the emergence profile for the customized dental implant abutments. The digital technology of non-industrial milling compatible custom CAD/CAM dental implant abutments is reliable and within the correct milling parameters.
Beyond the Silicon Valley of the East: Exploring Portfolio Diversification with India and MINT Economies
Authors: Özdurak Caner , Hekim Derya
Published: June 2024

In the past few decades, India’s tech industry has boomed, making it a leader in the digital world. Today, India has many big tech companies, well-trained software developers, and cutting-edge technology like AI and cloud computing. This success shows India’s innovative spirit and makes the country a good example for other developing nations. However, global portfolio managers often overlook potential diversification opportunities beyond India’s dynamic stock market. This study investigates the viability of MINT (Mexico, Indonesia, Nigeria, and Turkey) as diversification targets, specifically analyzing spillover effects and volatility dynamics between their stock markets and that of India. Leveraging vector autoregressions (VARs) and dynamic conditional correlation (DCC)–GARCH models, we uncover intricate relationships. Further, DCC–GARCH analysis reveals varying degrees of volatility spillover, offering valuable insights for risk management. Our findings suggest that MINT economies, particularly Mexico and Turkey, hold promise for Indian portfolio diversification. By strategically incorporating these markets, investors can potentially mitigate India-specific risks and enhance portfolio returns. We urge global portfolio managers to consider Turkey as a viable diversification avenue, acknowledging the nuanced market growth dynamics highlighted in this study.
Comparative Analysis of Gold, Art, and Wheat as Inflation Hedges
Authors: Binh Nguyen Thi Thanh
Published: June 2024

This study confirms gold’s role as a reliable inflation hedge while introducing new insights into lesser-explored assets like art and wheat. Using advanced methodologies such as the ARDL framework and LSTM deep learning, it conducts a detailed analysis of inflation-hedging dynamics, exploring non-linear relationships and unexpected inflation impacts across various asset classes. The findings reveal complex dynamics. Gold demonstrates strong long-term inflation hedging potential. The negative coefficient for the US dollar index suggests that gold acts as a hedge against currency depreciation. Furthermore, a positive relationship between gold returns and inflation during high inflation periods highlights its effectiveness in protecting purchasing power. Art presents a more intricate picture. Long-term analysis suggests a weak mean-reverting tendency, but a negative relationship with inflation, potentially linked to economic downturns. Interestingly, unexpected inflation positively correlates with art returns in the long run, hinting at its potential inflation-hedging abilities. No statistically significant connection between wheat prices and overall inflation was observed; the short-run analysis reveals a dynamic interplay between inflation, real GDP growth, and wheat prices at different time points.
Is Smarter Better? A Moral Judgment Perspective on Consumer Attitudes about Different Types of AI Services
Authors: Fan Qingji , Dai Yan , Wen Xue
Published: June 2024

AI is considered a key driver of industrial transformation and a strategic technology that will shape future development. With AI services continuing to permeate various sectors, concerns have emerged about the ethics of AI. This study investigates the effects of different types of AI services (mechanical, thinking, and affective AI services) on consumers’ attitudes through offline and online AI service experiments. We also construct a model to explore the mediating roles of identity threat and perceived control. The findings reveal that mechanical AI services negatively affect consumers’ attitudes while thinking and affective AI services have a positive effect. Additionally, we explore how consumers’ attitudes vary across different service scenarios and ethical judgments (utilitarianism and deontology). Our findings could offer practical guidance for enterprises providing AI services.
Spatio-Temporal Land-Use/Cover Change Dynamics Using Spatiotemporal Data Fusion Model and Google Earth Engine in Jilin Province, China
Authors: Liu Zhuxin , Han Yang , Zhu Ruifei , Qu Chunmei , Zhang Peng , Xu Yaping , Zhang Jiani , Zhuang Lijuan , Wang Feiyu , Huang Fang
Published: June 2024

Jilin Province is located in the northeast of China, and has fragile ecosystems, and a vulnerable environment. Large-scale, long time series, high-precision land-use/cover change (LU/CC) data are important for spatial planning and environmental protection in areas with high surface heterogeneity. In this paper, based on the high temporal and spatial fusion data of Landsat and MODIS and the Google Earth Engine (GEE), long time series LU/CC mapping and spatio-temporal analysis for the period 2000–2023 were realized using the random forest remote sensing image classification method, which integrates remote sensing indices. The prediction results using the OL-STARFM method were very close to the real images and better contained the spatial image information, allowing its application to the subsequent classification. The average overall accuracy and kappa coefficient of the random forest classification products obtained using the fused remote sensing index were 95.11% and 0.9394, respectively. During the study period, the area of cultivated land and unused land decreased as a whole. The area of grassland, forest, and water fluctuated, while building land increased to 13,442.27 km2 in 2023. In terms of land transfer, cultivated land was the most important source of transfers, and the total area share decreased from 42.98% to 38.39%. Cultivated land was mainly transferred to grassland, forest land, and building land, with transfer areas of 7682.48 km2, 8374.11 km2, and 7244.52 km2, respectively. Grassland was the largest source of land transfer into cultivated land, and the land transfer among other feature types was relatively small, at less than 3300 km2. This study provides data support for the scientific management of land resources in Jilin Province, and the resulting LU/CC dataset is of great significance for regional sustainable development.
Evaluation of the Thermal Environment Based on the Urban Neighborhood Heat/Cool Island Effect
Authors: Qi Li , Hu Yuanman , Bu Rencang , Li Binglun , Gao Yue , Li Chunlin
Published: June 2024

Under rapid urbanization, the urban heat island (UHI) effect is increasing, which poses a serious threat to human settlements. Changes in neighborhood land surface temperature (LST) reflect the UHI effect at a finer scale, with implications for the thermal comfort of residents. Landsat images were used to analyze the distribution of the urban neighborhood heat/cool island (UNHI/UNCI) within the fourth ring area of Shenyang City. Three-dimensional buildings and the urban functional zones (UFZs) were combined to explore the relationships with the UNHI and UNCI. Using boosted regression trees to analyze the relative importance of UFZs in the UNHI and UNCI, the results showed a significant lowering effect on the neighborhood LST with increased building height, which may be due to the fact of more architectural shadows generated by higher buildings. As the size of the green space patches increased, the cooling amplitude and the influence distance had an increasing trend. Industrial and public service zones had the most significant effect on the UNHI, with influences of 30.46% and 19.35%, respectively. In comparison, green space zones and water contributed the most to the UNCI effect, with influences of 18.75% and 11.95%, respectively. These results will provide urban decision-makers with crucial information on mitigating UHI problems through urban planning.
Assessment of the Implementation Effects of Main Functional Area Planning in the Yangtze River Economic Belt
Authors: Wei Ming , Chen Wen , Wang Yi
Published: June 2024

The Yangtze River Economic Belt, relying on the golden waterway of the Yangtze River, serves not only as a vital industrial and urban stronghold in China but also bears the significant responsibility of the Yangtze River’s major conservation efforts. The implementation of the main functional zones within the economic belt can provide regional synergies for development and protection through the optimization and organization of spatial structures, which is conducive to promoting the green and high-quality development of the Yangtze River Economic Belt in accordance with local conditions. In pursuit of these objectives, this paper utilizes multi-source data and selects corresponding indicators based on the main form of functional zoning to analyze the land protection and development patterns of the Yangtze River Economic Belt and to assess the effectiveness of the main functional zone planning implementation. The findings reveal that the enactment of main functional area planning has incrementally enhanced the level of land development and conservation in terms of certain aspects across the Yangtze River Economic Belt. This is evidenced by the burgeoning expansion of construction land in areas earmarked for optimization and pivotal development, bolstered by robust population and economic concentration capabilities, alongside a surge in per capita output. Moreover, ecological lands within critical ecological function zones exhibited signs of rejuvenation. Nonetheless, the outcomes are not universally aligned with the anticipated goals: the expanse of arable land in primary agricultural production zones has contracted, accompanied by a downturn in the proportion of grain output; the proliferation of construction land within key ecological function zones continues unabated, and ecological lands have experienced reductions over various intervals. The main functional zones have yet to fully embrace and enact protective strategies, highlighting an urgent need for more formidable institutional frameworks to guarantee their rigorous enforcement.
Measurement and Spatio–Temporal Pattern Evolution of Urban–Rural Integration Development in the Chengdu-Chongqing Economic Circle
Authors: Liu Hao , Lu Gaojie , Luo Kui , Zong Huiming
Published: June 2024

This paper focuses on the level of urban–rural integration development and its spatio–temporal evolution patterns in the Chengdu-Chongqing Economic Circle. It constructs an evaluation indicator system encompassing five dimensions: population, economy, society, ecology, and space. By comprehensively using statistical data and multi-source spatio–temporal data and employing methods such as the entropy method, ESDA, obstacle degree model, and various statistical techniques, the study measures and analyzes the level of urban–rural integration development at three time points: 2010, 2015, and 2020. The findings are as follows: (1) The overall level of urban–rural integration is low, predominantly at low to lower-middle levels, with a clear core-periphery spatial pattern where central urban areas such as Chengdu’s central seven districts and Chongqing’s central urban districts are high-value cores, whereas peripheral and central regional areas are less integrated. (2) From 2010 to 2020, there was a steady increase in integration levels, transitioning from a single-core to a more dynamic point-axis structure with emerging regional growth poles. However, this transition was accompanied by reduced inequality of urban–rural integration within each city, while disparities among central urban areas within its cities gradually increased. (3) The analysis of obstacles across dimensions indicates that spatial integration faces the most significant barriers, mainly due to geographical conditions and development constraints in southwestern mountainous counties. In contrast, barriers to economic and social integration, though initially lower, have gradually increased, highlighting imbalances between economic growth and social service provision. Overall, this study not only provides a systematic measurement and analytical framework for the integration and development of urban and rural areas in the Chengdu-Chongqing Economic Circle but also offers theoretical and empirical support for global research and practice on urban–rural integration. Additionally, it proposes targeted policy recommendations.
Carbon Balance Zoning and Spatially Synergistic Carbon Reduction Pathways—A Case Study in the Yangtze River Delta in China
Authors: Guo Hui , Sun Wei
Published: June 2024

The concept of major function-oriented zones is highly compatible with the idea of spatially synergistic carbon reduction. In this study, 2005–2020 is taken as the research period, and 305 counties in the Yangtze River Delta (YRD) region are taken as the research unit. The S0M-K-means clustering model and GeoDetector are adopted on the basis of carbon emission/absorption accounting to analyse the spatial and temporal variations in the carbon balance in the YRD region. Furthermore, carbon balance zoning and influencing factors are analysed. Then, a regional spatially synergistic carbon reduction pathway is proposed. The results show that carbon absorption in the YRD region struggles to offset carbon emissions; the regional carbon imbalance is gradually becoming worse; and each county’s carbon emission/absorption shows a significant spatial imbalance. Optimised development zones and key development zones are high-value agglomerations of carbon emissions, while the main sources of carbon sinks in the YRD region are the key ecological functional zones. The YRD region has 87 high carbon control zones, 167 carbon emission optimisation zones, and 51 carbon sink functional zones, which are further subdivided into 9 types of carbon balance zones in accordance with the major function-oriented zones (MFOZs). Based on the driving factors of carbon balance changes in the YRD region, this study proposes differentiated spatially synergistic carbon reduction paths for each zone in accordance with the carbon balance zones. As the Yangtze River Delta is an essential engine for China’s economic development, the study of its carbon balance is highly relevant in formulating differentiated low-carbon development pathways for each functional zone and promoting regional spatially synergistic carbon reduction to realise the target of “dual-carbon” development.
Vaporization Enthalpies and Vapor Pressures of 5α-Androstane and 5α-Cholestane by Correlation Gas Chromatography
Authors: Fischer-Lodike Christian , Albinsaad Mohammad , Chickos James S.
Published: June 2024

Vaporization enthalpies and vapor pressures of 5α-androstane and 5α-cholestane are reported using correlation gas chromatography (CGC). The results for 5α-cholestane are compared to both estimated and experimental values reported previously for 5α-cholestane. The results are generally in agreement with the literature within the reported uncertainties. A simple method for reducing the amount of curvature in logarithm plots of vapor pressures as a function of K/T when using n-alkanes as standards in CGC experiments is also reported. This may prove useful in evaluating vapor pressures of rigid hydrocarbons at high temperatures.
The Influence of the Design and Technological Parameters of Polymer-Based Multipolar Magnets with SrFeO Hard Magnetic Filler on the Residual Magnetic Properties
Authors: Rösel Uta , Drummer Dietmar
Published: June 2024

Multipolar bonded magnets based on a thermoset matrix provide the opportunity to expand the applications of bonded magnets, especially within the drive technology industry, in terms of the high thermal and chemical resistance, along with a higher utilisation of the magnetic potential. To realize the application of polymer bonded magnets based on thermosets within the drive technology industry, general design parameters in terms of the material, the process parameters, and the tool concept are needed. These allow for a fundamental realization of multipolar bonded magnets with complex geometries in drive technologies, based on thermosets as the matrix material. This paper investigates the impact of the material (matrix material and filler grade), the process conditions (holding pressure (ph) and heating time (th)), and the tool concept (gating position and system, sleeve material, pole division, and sample thickness) on the magnetic properties in terms of the remanence (BR) and the deviation (Δs) of the pole division, as well as the orientation of the fillers in the middle of the pole and at the pole pitch. For each parameter, an optimised value is derived. In the majority of the cases, this value is equal in terms of the magnetic properties and the orientation. In terms of the sleeve material and the sample thickness, the ideal value differs between the two criteria. Therefore, an optimised value for each criterion, as well as an overall value, is defined. In terms of the material, PF, along with a high filler grade; in terms of the process conditions, a high holding pressure (ph) and a low heating time (th); and in terms of the tool concept, a two-pinpoint gating system, located in the middle of the pole, a Ferro-Titanit-Cromoni sleeve material, a high pole division, as well as small sample thickness, should be selected to improve the properties of polymer bonded magnets based on thermosets.
Using Deep Q-Learning to Dynamically Toggle between Push/Pull Actions in Computational Trust Mechanisms
Authors: Lygizou Zoi , Kalles Dimitris
Published: June 2024

Recent work on decentralized computational trust models for open multi-agent systems has resulted in the development of CA, a biologically inspired model which focuses on the trustee’s perspective. This new model addresses a serious unresolved problem in existing trust and reputation models, namely the inability to handle constantly changing behaviors and agents’ continuous entry and exit from the system. In previous work, we compared CA to FIRE, a well-known trust and reputation model, and found that CA is superior when the trustor population changes, whereas FIRE is more resilient to the trustee population changes. Thus, in this paper, we investigate how the trustors can detect the presence of several dynamic factors in their environment and then decide which trust model to employ in order to maximize utility. We frame this problem as a machine learning problem in a partially observable environment, where the presence of several dynamic factors is not known to the trustor, and we describe how an adaptable trustor can rely on a few measurable features so as to assess the current state of the environment and then use Deep Q-Learning (DQL), in a single-agent reinforcement learning setting, to learn how to adapt to a changing environment. We ran a series of simulation experiments to compare the performance of the adaptable trustor with the performance of trustors using only one model (FIRE or CA) and we show that an adaptable agent is indeed capable of learning when to use each model and, thus, perform consistently in dynamic environments.
Motor PHM on Edge Computing with Anomaly Detection and Fault Severity Estimation through Compressed Data Using PCA and Autoencoder
Authors: Choi Jong Hyun , Jang Sung Kyu , Cho Woon Hyung , Moon Seokbae , Kim Hyeongkeun
Published: June 2024

The motor is essential for manufacturing industries, but wear can cause unexpected failure. Predictive and health management (PHM) for motors is critical in manufacturing sites. In particular, data-driven PHM using deep learning methods has gained popularity because it reduces the need for domain expertise. However, the massive amount of data poses challenges to traditional cloud-based PHM, making edge computing a promising solution. This study proposes a novel approach to motor PHM in edge devices. Our approach integrates principal component analysis (PCA) and an autoencoder (AE) encoder achieving effective data compression while preserving fault detection and severity estimation integrity. The compressed data is visualized using t-SNE, and its ability to retain information is assessed through clustering performance metrics. The proposed method is tested on a custom-made experimental platform dataset, demonstrating robustness across various fault scenarios and providing valuable insights for practical applications in manufacturing.
A Deep Learning Approach for Stochastic Structural Plane Generation Based on Denoising Diffusion Probabilistic Models
Authors: Meng Han , Qi Xiaoyu , Mei Gang
Published: June 2024

The stochastic structural plane of a rock mass is the key factor controlling the stability of rock mass. Obtaining the distribution of stochastic structural planes within a rock mass is crucial for analyzing rock mass stability and supporting rock slopes effectively. The conventional Monte Carlo method generates each parameter of stochastic structural planes separately without considering the correlation between the parameters. To address the above problem, this study novelly uses the denoising diffusion probabilistic model (DDPM) to generate stochastic structural planes. DDPM belongs to the deep generative model, which can generate stochastic structural planes without assuming the probability distribution of stochastic structural planes in advance. It takes structural plane parameters as an integral input into the model and can automatically capture the correlations between structural plane parameters during generation. This idea has been used for stochastic structural plane generation of the Oernlia slope in the eastern part of Straumsvatnet Lake, Nordland County, north-central Norway. The accuracy was verified by descriptive statistics (i.e., histogram, box plot, cumulative distribution curve), similarity measures (i.e., mean square error, KL divergence, JS divergence, Wasserstein distance, Euclidean distance), error analysis, and the linear regression plot. Moreover, the linear regression plots between the dip direction and the dip angle verified that DDPM can effectively and automatically capture the correlation between parameters.
Topology Design and Operation of Distribution Network Based on Multi-Objective Framework and Heuristic Strategies
Authors: Li Qingxia , Huang Shengjun , Zhang Xueyang , Li Wenhua , Wang Rui , Zhang Tao
Published: June 2024

This work elucidates a methodological approach employed in the process of planning the expansion of distribution network (DN) lines, wherein the amalgamation of system reconfiguration capabilities with operational equilibrium and reliability is paramount. The expansion proposals for the DN and the radial operation schemes post-expansion are encompassed. We formulate a bi-objective DN planning optimization model that concurrently addresses resource optimization configuration and operational optimization. Subsequently, the NSGA-II algorithm is employed to solve the optimization model, providing a coordinated presentation of multiple alternative solutions. However, this problem diverges from conventional bi-objective optimization problems due to its nature as a bi-objective optimization problem with embedded sub-optimization problem, consequently imposing a substantial computational burden. To address this issue, heuristic algorithms are designed to optimize system operational configuration, which is regarded as a sub-optimization problem. The proposed metric, model, and algorithms are validated on two case studies using the IEEE 33-bus and 70-bus test systems. Notably, the proposed method achieves solution efficiency by over 200 times compared to existing methods.
Robust Constrained Cooperative Control for Multiple Trains
Authors: Hu Qijie , Fan Xinyu , Wei Yue
Published: June 2024

This paper investigates robust constrained cooperative control for multiple trains, taking into account disturbances, velocity and control input constraints, and nonlinear operation resistances. A robust constrained cooperative control algorithm is employed, utilizing position information from neighboring trains to ensure each train operates within the desired formation. The effects of external disturbances are examined through multiple transformations and the convexity of stochastic matrices, resulting in an error bound for the final relative positions. This error boundary is correlated with the parameters of the system matrix, initial state conditions, and disturbance amplitudes. The theoretical findings are substantiated with a numerical example.
Modal Discontinuous Galerkin Simulations of Richtmyer–Meshkov Instability at Backward-Triangular Bubbles: Insights and Analysis
Authors: Alsaeed Salman Saud , Singh Satyvir
Published: June 2024

This paper investigates the dynamics of Richtmyer–Meshkov instability (RMI) in shocked backward-triangular bubbles through numerical simulations. Two distinct gases, He and SF6, are used within the backward-triangular bubble, surrounded by N2 gas. Simulations are conducted at two distinct strengths of incident shock wave, including Ms=1.25 and 1.50. A third-order modal discontinuous Galerkin (DG) scheme is applied to simulate a physical conservation laws of two-component gas flows in compressible inviscid framework. Hierarchical Legendre modal polynomials are employed for spatial discretization in the DG platform. This scheme reduces the conservation laws into a semi-discrete set of ODEs in time, which is then solved using an explicit 3rd-order SSP Runge–Kutta scheme. The results reveal significant effects of bubble density and Mach numbers on the growth of RMI in the shocked backward-triangular bubble, a phenomenon not previously reported. These effects greatly influence flow patterns, leading to intricate wave formations, shock focusing, jet generation, and interface distortion. Additionally, a detailed analysis elucidates the mechanisms driving vorticity formation during the interaction process. The study also thoroughly examines these effects on the flow fields based on various integral quantities and interface characteristics.
Posidonia oceanica (L.) Delile Is a Promising Marine Source Able to Alleviate Imiquimod-Induced Psoriatic Skin Inflammation
Authors: Micheli Laura , Vasarri Marzia , Degl’Innocenti Donatella , Di Cesare Mannelli Lorenzo , Ghelardini Carla , Emiliano Antiga , Verdelli Alice , Caproni Marzia , Barletta Emanuela
Published: June 2024

Psoriasis is a chronic immune-mediated inflammatory cutaneous disease characterized by elevated levels of inflammatory cytokines and adipokine Lipocalin-2 (LCN-2). Recently, natural plant-based products have been studied as new antipsoriatic compounds. We investigate the ability of a leaf extract of the marine plant Posidonia oceanica (POE) to inhibit psoriatic dermatitis in C57BL/6 mice treated with Imiquimod (IMQ). One group of mice was topically treated with IMQ (IMQ mice) for 5 days, and a second group received POE orally before each topical IMQ treatment (IMQ-POE mice). Psoriasis Area Severity Index (PASI) score, thickness, and temperature of the skin area treated with IMQ were measured in both groups. Upon sacrifice, the organs were weighed, and skin biopsies and blood samples were collected. Plasma and lesional skin protein expression of IL-17, IL-23, IFN-γ, IL-2, and TNF-α and plasma LCN-2 concentration were evaluated by ELISA. PASI score, thickness, and temperature of lesional skin were reduced in IMQ-POE mice, as were histological features of psoriatic dermatitis and expression of inflammatory cytokines and LCN-2 levels. This preliminary study aims to propose P. oceanica as a promising naturopathic anti-inflammatory treatment that could be introduced in Complementary Medicine for psoriasis.
Marine-Derived Lipases for Enhancing Enrichment of Very-Long-Chain Polyunsaturated Fatty Acids with Reference to Omega-3 Fatty Acids
Authors: Karia Mahejbin , Kaspal Mona , Alhattab Mariam , Puri Munish
Published: June 2024

Omega-3 fatty acids are essential fatty acids that are not synthesised by the human body and have been linked with the prevention of chronic illnesses such as cardiovascular and neurodegenerative diseases. However, the current dietary habits of the majority of the population include lower omega-3 content compared to omega-6, which does not promote good health. To overcome this, pharmaceutical and nutraceutical companies aim to produce omega-3-fortified foods. For this purpose, various approaches have been employed to obtain omega-3 concentrates from sources such as fish and algal oil with higher amounts of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). Among these techniques, enzymatic enrichment using lipase enzymes has gained tremendous interest as it is low in capital cost and simple in operation. Microorganism-derived lipases are preferred as they are easily produced due to their higher growth rate, and they hold the ability to be manipulated using genetic modification. This review aims to highlight the recent studies that have been carried out using marine lipases for the enrichment of omega-3, to provide insight into future directions. Overall, the covalent bond-based lipase immobilization to various support materials appears most promising; however, greener and less expensive options need to be strengthened.
Impact of Norepinephrine and Dopamine Infusion on Renal Arterial Resistive Index during Pre-Emptive Living Donor Kidney Transplantation: Propensity Score Matching Analysis
Authors: Huh Jaewon , Kwon Hyejin , Park Hunwoo , Park Sun Cheol , Yun Sang Seob , Chae Min Suk
Published: June 2024

Background: Living donor kidney transplantation (LDKT) is a crucial treatment for end-stage renal disease, with pre-emptive LDKT (transplantation before dialysis initiation) offering significant benefits in graft function and patient survival. The selection of a vasopressor during LDKT, particularly between norepinephrine and dopamine, and its impact on renal arterial hemodynamics measured using the renal arterial resistive index (RARI) is poorly understood. Methods: This retrospective observational cohort study enrolled 347 eligible pre-emptive LDKT recipients from the Seoul St. Mary’s Hospital between January 2019 and June 2023. Utilizing propensity score matching (PSM), the patients were categorized into dopamine and norepinephrine groups to compare the effects of these vasopressors on the intraoperative RARI, postoperative estimated glomerular filtration rate (eGFR), and hourly urine output. The RARI was measured via the Doppler ultrasonography of the renal hilum and parenchyma post-graft vascular and ureteral anastomoses. Results: The preoperative differences in the recipients’ and donors’ characteristics were mitigated following PSM. The dopamine group exhibited higher intraoperative RARI values at the renal hilum (0.77 ± 0.11 vs. 0.66 ± 0.13, p < 0.001) and parenchyma (0.71 ± 0.1 vs. 0.6 ± 0.1, p < 0.001) compared to those of the norepinephrine group. However, these differences were not statistically significant on postoperative day 7. The norepinephrine infusion adjusted for the propensity scores was associated with significantly lower odds of an RARI > 0.8 (hilum: OR = 0.214, 95% CI = 0.12–0.382, p < 0.001; parenchyma: OR = 0.1, 95% CI = 0.029–0.348, p < 0.001). The early postoperative outcomes showed a higher eGFR (day 1: 30.0 ± 13.3 vs. 25.1 ± 17.4 mL/min/1.73 m2, p = 0.004) and hourly urine output (day 1: 41.8 ± 16.9 vs. 36.5 ± 14.4 mL/kg/h, p = 0.002) in the norepinephrine group. Furthermore, the long-term outcomes were comparable between the groups. Conclusions: Norepinephrine infusion during pre-emptive LDKT is associated with more favorable intraoperative renal arterial hemodynamics, as evidenced by a lower RARI and improved early postoperative renal function compared to those of dopamine. These findings suggest a potential preferential role for norepinephrine in optimizing perioperative management and early graft functions in LDKT recipients. Given the retrospective nature of this study, further prospective studies are needed to confirm these observations. Additionally, the study limitations include the potential for unmeasured confounding factors and the inability to determine causality due to its observational design.
Observation of the Transition Phenomenon of High-Density Cell Distribution in a Two-Dimensional Microspace of the Unicellular Green Alga Chlamydomonas reinhardtii
Authors: Goda Yuka , Yamashita Kyohei , Aono Tetsuo , Aizawa Kentaro , Hashimoto Masafumi , Tokunaga Eiji
Published: June 2024

Understanding the spatial distribution (SD) of unicellular organisms is crucial for comprehending population dynamics and adaptive strategies at the microbial scale. These behaviors include the formation of ordered structures through intercellular interactions and the broader implications for ecosystem interactions. In this study, the spatial distribution of the motile unicellular alga Chlamydomonas reinhardtii was investigated, with a focus on high-density conditions approximated by an area fraction of φ = 10%. Cell counting was carried out by image analysis, which applies the quasi-two-dimensional observation technique developed in our previous studies to analyze cell interactions in microspaces with thicknesses of 80 µm and 200 µm using both variance-to-mean ratio (VMR) and Eberhardt statistics (ES). The study reveals that experimental results, when evaluated using both VMR and ES, confirmed a similar trend and a density-dependent transition in cellular interaction. This transition ranges from swarming at lower densities to dispersal at higher densities, with a critical boundary observed at approximately φ = 8%. The findings suggest that cell behavior in dense populations shifts due to limited space and resources, offering a new perspective on the adaptive strategies of cells. These insights could enhance understanding of the mechanisms governing cell behavior in crowded environments.
Evaluation of Chemical and Physical Triggers for Enhanced Photosynthetic Glycerol Production in Different Dunaliella Isolates
Authors: Keil Linda , Qoura Farah Mitry , Breitsameter Jonas Martin , Rieger Bernhard , Garbe Daniel , Brück Thomas Bartholomäus
Published: June 2024

The salt-tolerant marine microalgae Dunaliella tertiolecta is reported to generate significant amounts of intracellular glycerol as an osmoprotectant under high salt conditions. This study highlights the phylogenetic distribution and comparative glycerol biosynthesis of seven new Dunaliella isolates compared to a D. tertiolecta reference strain. Phylogenetic analysis indicates that all Dunaliella isolates are newly discovered and do not relate to the D. tertiolecta reference. Several studies have identified light color and intensity and salt concentration alone as the most inducing factors impacting glycerol productivity. This study aims to optimize glycerol production by investigating these described factors singularly and in combination to improve the glycerol product titer. Glycerol production data indicate that cultivation with white light of an intensity between 500 and 2000 μmol m−2 s−1 as opposed to 100 μmol m−2 s−1 achieves higher biomass and thereby higher glycerol titers for all our tested Dunaliella strains. Moreover, applying higher light intensity in a cultivation of 1.5 M NaCl and an increase to 3 M NaCl resulted in hyperosmotic stress conditions, providing the highest glycerol titer. Under these optimal light intensity and salt conditions, the glycerol titer of D. tertiolecta could be doubled to 0.79 mg mL−1 in comparison to 100 μmol m−2 s−1 and salt stress to 2 M NaCl, and was higher compared to singularly optimized conditions. Furthermore, under the same conditions, glycerol extracts from new Dunaliella isolates did provide up to 0.94 mg mL−1. This highly pure algae-glycerol obtained under optimal production conditions can find widespread applications, e.g., in the pharmaceutical industry or the production of sustainable carbon fibers.
The Role of Microbes in Surgical Decision Making for Infective Endocarditis: Mitral Valve Repair or Replacement?
Authors: Mikus Elisa , Fiorentino Mariafrancesca , Sangiorgi Diego , Pascale Renato , Costantino Antonino , Nocera Chiara , Calvi Simone , Tenti Elena , Tremoli Elena , Tripodi Alberto , Savini Carlo
Published: June 2024

Background: The benefits of mitral repair versus replacement for endocarditis are inconclusive. This study compares outcomes of patients with infective endocarditis undergoing mitral valve repair versus replacement and investigates the impact of microbial etiology. Methods: All 251 patients undergoing mitral valve surgery for active endocarditis between 2010 and 2023 were enrolled, 180 (71.7%) replacement and 71 (28.3%) repair. To adjust for imbalances, inverse probability of treatment weighting was applied and 187 patients were obtained. Results: The analysis between groups, following the application of inverse probability of treatment weighting, showed no statistically significant differences across all considered outcomes. Early and late death was observed respectively in 6 (8.5%) and 11 (15.5%) patients in the repair group versus 24 (13.3%) and 45 (25.0%) in the replacement group without statistical significance (p = 0.221 and p = 0.446). Relapse occurred in six patients (8.5%) in the repair group after a median time of 4.0 months and in six (3.3%) in the replacement after 6.9 months (p = 0.071). Conclusions: Surgical strategy in mitral endocarditis has no effect on major postoperative complications, mortality, or medium/long-term survival. Staphylococcus aureus and Coagulase-negative Staphylococci represent a risk for early mortality and relapse. However, mitral valve repair for endocarditis can be pursued when it ensures the complete eradication of all infected tissue, particularly in cases caused by Streptococcus infection, in young patients, and after a minimum of 18 days of antibiotic therapy.
Pyrite-Goethite Alteration in Supergene Oxidation Processes in Till: Elemental Distribution and Evaluation of Goethite Usability as a Fingerprinting Tool for Vectoring Mineral Deposits
Authors: Taivalkoski Atte , Ranta Jukka-Pekka , Sarala Pertti , Moilanen Marko , Nikkola Paavo , Soukka Tapio
Published: June 2024

In the formerly glaciated terrains in the northern hemisphere and countries such as Finland, till is the most common sediment covering the bedrock. Specifically, indicator or heavy mineral studies utilising till as a vector for mineral deposits undercover have been successful. The pyrite trace-element composition from in situ mineral analyses has been shown to be an effective discriminator between different mineral deposit types, and this has led to research using heavy mineral pyrite in till to identify potential mineral deposits in a given area. However, pyrite is easily oxidised in till beds, and thus, alternative methods should be considered. Goethite pseudomorphs are more commonly found in the till sediments as remnants after pyrite oxidation. This study evaluates trace element compositions of goethitised pyrite recovered in the till beds from central Lapland in northern Finland. Intra-grain trace-elemental variations gathered using laser-ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) between the intact pyrite core and oxidised rim demonstrated complex dynamics and variations between different trace-element values. For example, Cu, V and Mn exhibited elevated trace-element values in the goethite rim compared to the pyrite core. However, elemental ratios such as Ni/As and Co/Ni remain stable between the pyrite core and oxidised rim. Therefore, these ratios have the potential to be used as a discriminating tool between the pyrite core and oxidised rim. In addition, nanoscale variabilities using focused ion beam (FIB) and transmission electron microscopy (TEM) were utilised to inspect possible nano inclusions within the studied heavy mineral grain. The FIB and TEM studies revealed a nanocrystalline pyrite nodule observation within the goethite rim.
In Situ Carbonate U-Pb Dating of Gold and Mercury Deposits in the Youjiang Metallogenic Province, SW China, and Implications for Multistage Mineralization
Authors: Li Jinwei , Zhuo Yuzhou , Guo Yitong , Lu Xinyue , Hu Xinlu
Published: June 2024

The Youjiang metallogenic province (YMP) is a famous ore-concentrating area in South China, known for its substantial Carlin-type gold deposits, antimony deposits, and mercury deposits. Previous studies have yielded conflicting views regarding the ages of mineralization in this area, particularly regarding the occurrence of Yanshanian versus Indosinian ore-forming events during the Mesozoic era. To resolve these discrepancies, this study utilized in situ LA-ICP-MS U-Pb dating on carbonate minerals from the Lannigou Carlin-type Au deposit, the Lanmuchang Hg-(Tl) deposit, and the Sixiangchang Hg deposit to accurately determine their mineralization ages. Our results indicate that the three deposits formed at 137 ± 9 Ma, ~97 Ma, and 454 ± 21 Ma, respectively. By integrating previously reported geochronological data, we propose that the low-temperature Au-As-Sb-Hg-Tl deposits in the YMP were formed during two major periods, Late Triassic and Late Jurassic to Cretaceous, with the latter being more prevalent. Additionally, there was a Paleozoic hydrothermal mercury mineralization event at the northeastern edge of this region. These newly acquired data significantly enhance our understanding of multistage, low-temperature mineralization events in the YMP. Our study also demonstrates that in situ carbonate U-Pb dating is an excellent method for investigating the timing of low-temperature mineralization events.
Novel Biological-Based Strategy for Synthesis of Green Nanochitosan and Copper-Chitosan Nanocomposites: Promising Antibacterial and Hematological Agents
Authors: Mohamed Hadeer I. , Mahmoud Nesrine M. R. , Ramadan Abeer , Al-Subaie Abeer M. , Ahmed Somia B.
Published: June 2024

Two novel samples of nanoparticles based on chitosan were greenly synthesized using pomegranate peel extract. The extract served as a nanoparticle precursor, facilitating the precipitation of nanosized chitosan through the ionic gelation method. Additionally, by mixing the green chitosan nanoparticles with copper ions, a nanoscale composite of chitosan and copper oxide was also produced. Structural and morphological investigations (FTIR, XRD, SEM, EDX, and TGA analyses) were performed for greenly synthesized chitosan nanoparticles and their copper oxide composite to determine all the significant characteristics of those nanoparticles. In addition, both samples were tested using some biological investigations, such as antimicrobial activity and hematological effects. The antimicrobial tests yielded promising results for both the green chitosan nanoparticles and the CuO composite when tested using two bacterial strains and two fungal strains. Moreover, the results showed that using a similar concentration of both green-based chitosan samples resulted in a slightly larger inhibition zone and a lower minimum inhibition concentration (MIC) for the copper oxide chitosan composite compared to the chitosan nanoparticles for all microorganisms included in the test. The mean count of blood components (RBCs and platelets), clotting time, and cholesterol levels in three different blood samples were used to indicate the hematological activity of both greenly synthesized nanoparticles. The results verified a slight reduction in blood component count after the addition of green chitosan nanoparticles, but the chitosan copper oxide composite did not have a noticeable effect on the three blood samples. The chitosan nanoparticles were able to cause a considerable reduction in clotting time and cholesterol levels for all blood samples, thus acting as procoagulants. However, the mixing of CuO with chitosan nanoparticles prolonged the rate of clotting in blood samples from hypercholesteremic individuals, and thus, the mixture acted as an anticoagulant agent.