bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Characteristic State of Rockfill Materials and the Evolution Mechanism at the Microscopic Scale
Authors: Cui Yunchao , Zhang Lingkai , Shi Chong , Zhang Runhan
Published: May 2024

In this study, the real particle morphology of rockfill materials is obtained through three-dimensional scanning technology, and flexible boundary conditions are established by coupling the discrete element method and the finite element method. Then, a large-scale three-axis numerical simulation test is carried out on the rockfill materials to study the macroscopic mechanical properties and the change rule of the microscopic view of the rockfill materials in different characteristic states. The macroscopic results show that the stress–strain curves of the rockfill materials can be divided into softening and hardening curves. The phase transition, peak, and critical states of the softening-type curves show different mechanical properties, but no clear distinction between the characteristic state changes can be seen in the hardening-type curves. The microscopic results show that the displacement of the upper and lower parts of the flexible boundary of the softening curve increases with loading, and there is no obvious displacement in the middle part, but the middle particles undergo rotational deformation. An “X” shear band appears, and the strength of the force chain and the coordination number tend to increase first and then decrease. The flexible boundary displacements of the hardening-type curves are similar to those of the softening-type curves, but the central particles show a large number of cleavages instead of shear zones, and the force chain strength and coordination number levels show a continuous upward trend.
BIM Policy Trends in Europe: Insights from a Multi-Stage Analysis
Authors: Mitera-Kiełbasa Ewelina , Zima Krzysztof
Published: May 2024

This study offers a detailed analysis of building information modelling (BIM) policy and implementation across Europe, significantly contributing to the sector’s digital transformation. By collating data from governmental, academic, and industry sources, it identifies key trends and evaluates the effectiveness of BIM policies in advancing technology within construction. A systematic literature review and text mining across major databases revealed an increasing focus on sustainability, particularly “life cycle assessment” and “energy efficiency”, aligning with the Industry 5.0 initiative. The research shows that 35% of European countries have or plan to introduce BIM mandates, highlighting BIM’s crucial role in enhancing construction practices and influencing policy frameworks. Insights from this study are valuable for researchers, practitioners, and policymakers, guiding the adoption and operationalization of BIM and emphasizing the need for thorough market preparation, including funding, training, and standardization. Additionally, the study suggests a correlation between a country’s economic development and its propensity to enforce BIM mandates. Future research could explore regional policy variations and delve into the theoretical aspects of policy adoption and innovation diffusion to further understand BIM uptake dynamics.
Raw Material Purchasing Optimization Using Column Generation
Authors: Gao Zhen , Li Danning , Wang Danni , Yu Zengcai
Published: May 2024

The raw material purchasing (RMP) problem is to determine the purchasing quantities of raw materials in given periods or cycles. Raw material purchasing optimization is crucial for large-scale steel plants because it is closely related to the supply of raw materials and cost savings. The raw material purchasing of large-scale steel enterprises is characterized by many varieties, large quantities, and high costs. The RMP objective is to minimize the total purchasing cost, consisting of the price of raw materials, purchasing set-up costs, and inventory costs, and meet product demand. We present a mixed integer linear programming (MILP) model and a column generation (CG) solution for the resulting optimization problem. The column generation algorithm is the generalization of the branch and bound algorithm while solving the linear programming (LP) relaxation of MILP using column generation (CG), and its advantage is to handle large-sized MILPs. Experimental results show the effectiveness and efficiency of the solution.
Trajectory Tracking of Nonlinear Systems with Convex Input Constraints Based on Tracking Control Lyapunov Functions
Authors: Satoh Yasuyuki
Published: May 2024

Trajectory tracking control of input-constrained systems is an essential problem in many control applications, including robotics. In this paper, we propose a constrained tracking controller for input affine nonlinear systems with convex input constraints based on tracking control Lyapunov functions (TCLFs). To deal with general convex input constraints, we first solve a convex optimization problem that minimizes the time derivative of TCLFs subject to convex input constraints; we refer to its optimal solution as minimizing input. Then, the proposed trajectory tracking is constructed by using the minimizing input and an appropriate scaling function. We prove that the proposed controller locally achieves trajectory tracking and satisfies the given convex input constraints. Finally, we demonstrate the effectiveness of the proposed controller by numerical simulations of a wheeled mobile robot.
The Evaluation of Pipeline Protection Influenced by Causeway Embankment Using the Finite Element Method (FEM)
Authors: Irmawan Mudji , Yudoprasetyo Kohar , Refani Afif Navir , Indrasurya Kusuma , Parwita Dewa Ngakan Putu Ananda
Published: May 2024

The construction of embankments over very soft to soft clay, such as reclamation projects, is on the rise. One such development is the reclamation project in the District Manyar, Gresik region of East Java. The seabed in this area is predominantly composed of soft clay. Reclamation involves the construction of a causeway that intersects with a gas pipeline at a depth of 5 m from the seabed. The embankment construction will undoubtedly impact the surrounding area. This study focuses on analyzing the impact of embankment in a reclamation area on soft soil on the underlying pipeline and designing pipeline protection. As a result of this study, the safety factor at each construction stage exceeds the planned safety factor of 1.5. The maximum settlement that occurs in the soil beneath the pipe is 26.91 mm. The maximum stress sustained by the corrugated steel plate (CSP) is 35,499.79 kN/m2, with a lateral deformation of 41.37 mm. The maximum stress occurring on the concrete footing slab is 123.40 kN/m2, which is smaller than the allowable bearing capacity of 128.61 kN/m2.
Effects of Hiking-Dependent Walking Speeds and Slopes on Spatiotemporal Gait Parameters and Ground Reaction Forces: A Treadmill-Based Analysis in Healthy Young Adults
Authors: Kafetzakis Ioannis , Konstantinou Ilias , Mandalidis Dimitris
Published: May 2024

Hiking offers both recreational enjoyment and physical challenges, requiring speed adjustments when traversing uphill and downhill slopes. These adjustments prompt compensatory responses in kinematics and kinetics to mitigate fatigue and musculoskeletal strains. The study aimed to explore the impact of slope-specific walking speeds on spatiotemporal gait parameters, vertical ground reaction forces (vGRFs), and position of the center of pressure (COP) during uphill and downhill walking. Thirty-two healthy individuals completed five 4-min walks on an instrumented treadmill set to 0% (level), +10%, and +20% (uphill), and −10% and −20% (downhill), slopes, at 5.0, 3.5, 2.5, 5.0 and 3.5 km h−1, respectively. Uphill walking led to reduced stride length and cadence, increased foot rotation, step time, and durations of stance, swing, and double-stance phases. Conversely, downhill walking exhibited decreased step length, step time, and durations of stance, swing, and double-stance phases but increased step width and cadence compared to level walking. Speed adjustments to accommodate slope led to reduced vGRFs for uphill and downhill walking. Additionally, the COP shifted forward during uphill and backward during downhill walking and displaced laterally as walking became more demanding. The observed responses indicate adaptations aimed at maintaining postural control, reducing excessive load application, and optimizing energy expenditure on sloping terrain.
A Vision-Based Bolt Looseness Detection Method for a Multi-Bolt Connection
Authors: Deng Lin , Sa Ye , Li Xiufang , Lv Miao , Kou Sidong , Gao Zhan
Published: May 2024

Many vision-based bolt looseness detection methods that directly observe the bolts have been developed. However, these methods have many limitations in terms of the conditions and processes of their implementation. To address these problems, this paper proposed a fully automated vision-based bolt looseness detection method for a rigid multi-bolt connection. The proposed method combines digital shearing speckle pattern interferometry (DSSPI) and recurrent neural network (RNN) and involves capturing speckle fringe patterns under various looseness cases using the DSSPI system and classifying these patterns with an RNN model to detect the loose bolts. The proposed method can detect all the bolts within the measured surface at one time, which is efficient. On the other hand, it eliminates the need for prior information such as the initial angle and position of each bolt. It can even detect unseen bolts in multi-bolt connections, making it applicable for connections in complex structures in which occlusion often occurs. Additionally, the method eliminates the complex process of distortion rectification. These features make the method achieve a single-judgment time (four bolts at one detection) of only 4.70 millisecond with a detection accuracy over 99%, which has potential for the real-time detection of loose bolts in multi-bolt connections.
Anaerobic Co-Digestion of Food Waste and Microalgae at Variable Mixing Ratios: Enhanced Performance, Kinetic Analysis, and Microbial Community Dynamics Investigation
Authors: Pan Zhiyong , Sun Xuan , Huang Yali , Liang Tian , Lu Jilai , Zhang Limin , Qi Chuang
Published: May 2024

There is an urgent need for clean recycling strategies to address the increase in food waste (FW) and the harvesting of microalgae (MA). In this study, biogas production potential and operational stability were evaluated by testing combinations of FW and MA mixed at five different ratios. Co-digestion of FW and MA improved substrate biodegradability, achieving a decomposition rate of 0.45/d (FW/MA = 1:1), which is 1.25 to 1.55 times higher than that of MA or FW alone. Co-digestion of FW and MA resulted in a synergistic effect, improving biogas yield by 2.04–26.86%. Four mathematical models were applied to estimate biological degradation and biogas production kinetics, and the Cone model performed better than the other models in terms of reliability and accuracy. The abundance of Bacteroidetes, Firmicutes, and Synergistetes peaked at FW/MA = 1:1. At the same ratio, the genera Methanospirillum, Methanocorpusculum, and Methanomethylovorans were also found to have increased in abundance. The optimal ratio was found to be 1:1 for co-digestion of FW and MA, which is a feasible approach for simultaneous bioenergy production and biomass waste co-disposal.
Denoising Multiscale Back-Projection Feature Fusion for Underwater Image Enhancement
Authors: Qu Wen , Song Yuming , Chen Jiahui
Published: May 2024

In recent decades, enhancing underwater images has become a crucial challenge when obtaining high-quality visual information in underwater environment detection, attracting increasing attention. Original underwater images are affected by a variety of underwater environmental factors and exhibit complex degradation phenomena such as low contrast, blurred details, and color distortion. However, most encoder-decoder-based methods fail to restore the details of underwater images due to information loss during downsampling. The noise in images also influences the recovery of underwater images with complex degradation. In order to address these challenges, this paper introduces a simple but effective denoising multiscale back-projection feature fusion network, which represents a novel approach to restoring underwater images with complex degradation. The proposed method incorporates a multiscale back-projection feature fusion mechanism and a denoising block to restore underwater images. Furthermore, we designed a multiple degradation knowledge distillation strategy to extend our method to enhance various types of degraded images, such as snowy images and hazy images. Extensive experiments on the standard datasets demonstrate the superior performance of the proposed method. Qualitative and quantitative analyses validate the effectiveness of the model compared to several state-of-the-art models. The proposed method outperforms previous deep learning models in recovering both the blur and color bias of underwater images.
OBU for Accurate Navigation through Sensor Fusion in the Framework of the EMERGE Project
Authors: Zuriarrain Sosa Angel Luis , Ioannucci Valeria , Pratesi Marco , Alesii Roberto , Albanese Carlo , Valentini Francesco , Cinque Elena , Martinelli Alessio , Brizzi Michele
Published: May 2024

With the development of advanced driver assistance systems (ADAS) and autonomous vehicles (AV), recent years have seen an increasing evolution of onboard sensors and communication interfaces capable of interacting with available infrastructures, including satellite constellations, road structures, modern and heterogeneous network systems (e.g., 5G and beyond) and even adjacent vehicles. Consequently, it is essential to develop architectures that cover data fusion (multi–sensor approach), communication, power management, and system monitoring to ensure accurate and reliable perception in several navigation scenarios. Motivated by the EMERGE project, this paper describes the definition and implementation of an On Board Unit (OBU) dedicated to the navigation process. The OBU is equipped with the Xsens MTi–630 AHRS inertial sensor, a multi–constellation/multi–frequency Global Navigation Satellite System (GNSS) receiver with the u–blox ZED–F9P module and communication interfaces that afford access to the PointPerfect augmentation service. Experimental results show that GNSS, with corrections provided by augmentation, affords centimetre accuracy, with a Time To First Fix (TTFF) of about 30 s. During the on–road tests, we also collect: the output of fusion with inertial sensor data, monitoring information that assess correct operation of the module, and the OBU power consumption, that remains under 5 W even in high–power operating mode.
Lidar Complex for Control of the Ozonosphere over Tomsk, Russia
Authors: Nevzorov Alexey A. , Nevzorov Alexey V. , Kharchenko Olga , Romanovskii Yaroslav O.
Published: May 2024

We present a union of three measurement systems on the basis of the Siberian lidar station and mobile ozone lidar. The lidars are designed for studying the ozonosphere using the method of differential absorption and scattering, as well as for studying aerosol fields using elastic single scattering. The systems are constructed on the basis of Nd:YAG lasers (SOLAR) and an Nd:YAG laser (LOTIS TII), a XeCl laser (Lambda Physik) and receiving telescopes assembled using the Kassegrain system with a diameter 0.35 m and the Newtonian 0.5 m system. Lidars operate in photon-counting mode and record lidar signals with a spatial resolution from 1.5 m to 160 m at sensing wavelengths of 299/341 nm in the altitude range of ~0.1–12 km and ~5–20, and at 308/353 nm in the altitude range of ~15–45 km. The union of these three measurement systems was used to carry out field experiments of atmospheric lidar sensing in Tomsk and to present the results of retrieving the vertical profile of the ozone concentration. In this study, coverage of the entire ozonosphere by the lidars was carried out for the first time in Russia.
Ural Blocking and the Amplitude of Wintertime Cold Surges over North China Detected by a Cooling Algorithm
Authors: Yang Zifan , Huang Wenyu , Chen Ruyan , Lin Daiyu , Wang Bin , Ma Wenqian
Published: May 2024

A new algorithm is proposed to estimate the cooling amplitude over North China induced by each Ural blocking event. Taking full account of potential transient temperature rises during the cooling process and the lag time of cooling relative to the blocking, this algorithm provides more detailed analysis which should not be possible by using former methods. The amplitude of the Ural blocking-related cooling events is found to have a broad distribution. Further, although most Ural blocking events lead to severe cold surges over North China, the number of Ural blocking events that do not induce significant cooling over North China cannot be ignored. The possible reasons for the wide range in cooling amplitude are explored in terms of the lifetimes and geographical centers of the blocking highs, the circulation patterns preceding the onset of the cooling events, and the snowfall associated with cooling events. Larger amplitude cooling events occur in Ural blocking highs that have longer lifetimes and northwestward displacements of their geographical centers. The northward displacement of a Ural blocking center favors the advection of extremely cold air from the Arctic regions, which accumulates in West Siberia and subsequently gives rise to the most severe cold surges over North China. The lack of activities of cold surges before the blocking-related cooling events not only amplifies the cooling amplitude directly, but also increases the occurrence probabilities of snowfalls through its modulation on the local specific humidity. The increased albedo and subsequent snow-melt induced cooling further amplify the cooling amplitude.
The Estimation of Different Kinds of Integral Inequalities for a Generalized Class of Convex Mapping and a Harmonic Set via Fuzzy Inclusion Relations and Their Applications in Quadrature Theory
Authors: Althobaiti Ali , Althobaiti Saad , Vivas Cortez Miguel
Published: May 2024

The relationship between convexity and symmetry is widely recognized. In fuzzy theory, both concepts exhibit similar behavior. It is crucial to remember that real and interval-valued mappings are special instances of fuzzy-number-valued mappings (F-N-V-Ms), as fuzzy theory relies on the unit interval, which is crucial to resolving problems with interval analysis and fuzzy number theory. In this paper, a new harmonic convexities class of fuzzy numbers has been introduced via up and down relation. We show several Hermite–Hadamard (H⋅H) and Fejér-type inequalities by the implementation of fuzzy Aumann integrals using the newly defined class of convexities. Some nontrivial examples are also presented to validate the main outcomes.
Cross-Stitch Networks for Joint State of Charge and State of Health Online Estimation of Lithium-Ion Batteries
Authors: Yao Jiaqi , Neupert Steven , Kowal Julia
Published: May 2024

As a superior solution to the developing demand for energy storage, lithium-ion batteries play an important role in our daily lives. To ensure their safe and efficient usage, battery management systems (BMSs) are often integrated into the battery systems. Among other critical functionalities, BMSs provide information about the key states of the batteries under usage, including state of charge (SOC) and state of health (SOH). This paper proposes a data-driven approach for the joint online estimation of SOC and SOH utilizing multi-task learning (MTL) approaches, particularly highlighting cross-stitch units and cross-stitch networks. The proposed model is able to achieve an accurate estimation of SOC and SOH in online applications with optimized information sharing and multi-scale implementation. Comprehensive results on training and testing of the model are presented. Possible improvements for future work are also discussed in the paper.
Development of Context-Based Sentiment Classification for Intelligent Stock Market Prediction
Authors: Smatov Nurmaganbet , Kalashnikov Ruslan , Kartbayev Amandyk
Published: May 2024

This paper presents a novel approach to sentiment analysis specifically customized for predicting stock market movements, bypassing the need for external dictionaries that are often unavailable for many languages. Our methodology directly analyzes textual data, with a particular focus on context-specific sentiment words within neural network models. This specificity ensures that our sentiment analysis is both relevant and accurate in identifying trends in the stock market. We employ sophisticated mathematical modeling techniques to enhance both the precision and interpretability of our models. Through meticulous data handling and advanced machine learning methods, we leverage large datasets from Twitter and financial markets to examine the impact of social media sentiment on financial trends. We achieved an accuracy exceeding 75%, highlighting the effectiveness of our modeling approach, which we further refined into a convolutional neural network model. This achievement contributes valuable insights into sentiment analysis within the financial domain, thereby improving the overall clarity of forecasting in this field.
Delayed Union and Nonunion: Current Concepts, Prevention, and Correction: A Review
Authors: Bowers Kristin M. , Anderson David E.
Published: May 2024

Surgical management of fractures has advanced with the incorporation of advanced technology, surgical techniques, and regenerative therapies, but delayed bone healing remains a clinical challenge and the prevalence of long bone nonunion ranges from 10 to 15% of surgically managed fractures. Delayed bone healing arises from a combination of mechanical, biological, and systemic factors acting on the site of tissue remodeling, and careful consideration of each case’s injury-related, patient-dependent, surgical, and mechanical risk factors is key to successful bone union. In this review, we describe the biology and biomechanics of delayed bone healing, outline the known risk factors for nonunion development, and introduce modern preventative and corrective therapies targeting fracture nonunion.
Unsupervised Segmentation of Knee Bone Marrow Edema-like Lesions Using Conditional Generative Models
Authors: Yu Andrew Seohwan , Yang Mingrui , Lartey Richard , Holden William , Ok Ahmet Hakan , Khan Sameed , Kim Jeehun , Winalski Carl , Subhas Naveen , Chaudhary Vipin , Li Xiaojuan
Published: May 2024

Bone marrow edema-like lesions (BMEL) in the knee have been linked to the symptoms and progression of osteoarthritis (OA), a highly prevalent disease with profound public health implications. Manual and semi-automatic segmentations of BMELs in magnetic resonance images (MRI) have been used to quantify the significance of BMELs. However, their utilization is hampered by the labor-intensive and time-consuming nature of the process as well as by annotator bias, especially since BMELs exhibit various sizes and irregular shapes with diffuse signal that lead to poor intra- and inter-rater reliability. In this study, we propose a novel unsupervised method for fully automated segmentation of BMELs that leverages conditional diffusion models, multiple MRI sequences that have different contrast of BMELs, and anomaly detection that do not rely on costly and error-prone annotations. We also analyze BMEL segmentation annotations from multiple experts, reporting intra-/inter-rater variability and setting better benchmarks for BMEL segmentation performance.
Comparative Analysis of the Gut Microbiota of Bat Species with Different Feeding Habits
Authors: Mena Canata Diego Antonio , Benfato Mara Silveira , Pereira Francielly Dias , Ramos Pereira María João , Hackenhaar Fernanda Schäfer , Mann Michele Bertoni , Frazzon Ana Paula Guedes , Rampelotto Pabulo Henrique
Published: May 2024

Bats are a diverse and ecologically important group of mammals that exhibit remarkable diversity in their feeding habits. These diverse feeding habits are thought to be reflected in the composition and function of their gut microbiota, which plays important roles in nutrient acquisition, immune function, and overall health. Despite the rich biodiversity of bat species in South America, there is a lack of microbiome studies focusing on bats from this region. Such studies could offer major insights into conservation efforts and the preservation of biodiversity in South America. In this work, we aimed to compare the gut microbiota of four bat species with different feeding habits from Southern Brazil, including nectarivorous, frugivorous, insectivorous, and hematophagous bats. Our findings demonstrate that feeding habits can have a significant impact on the diversity and composition of bat gut microbiotas, with each species exhibiting unique metabolic potentials related to their dietary niches. In addition, the identification of potentially pathogenic bacteria suggests that the carriage of microbial pathogens by bats may vary, depending on feeding habits and host-specific factors. These findings provide novel insights into the relationship between bat feeding habits and gut microbiota composition, highlighting the need to promote diverse habitats and food sources to support these ecologically important species.
A Full-Length Transcriptome and Analysis of the NHL-1 Gene Family in Neocaridina denticulata sinensis
Authors: Xing Kefan , Li Huimin , Wang Xiongfei , Sun Yuying , Zhang Jiquan
Published: May 2024

Neocaridina denticulata sinensis has emerged as a promising model organism for basic studies in Decapod. However, the current transcriptome information on this species is based on next-generation sequencing technologies, which are limited by a short read length. Therefore, the present study aimed to generate a full-length transcriptome assembly of N. denticulata sinensis utilizing the PacBio Sequel Ⅱ platform. The resulting transcriptome assembly comprised 5831 transcripts with an N50 value of 3697 bp. Remarkably, 90.5% of these transcripts represented novel isoforms of known genes. The transcripts were further searched against the NR, SwissProt, KEGG, KOG, GO, NT, and Pfam databases. A total of 24.8% of the transcripts can be annotated across all seven databases. Additionally, 1236 alternative splicing events, 344 transcription factors, and 124 long non-coding RNAs (LncRNAs) were predicted. Based on the alternative splicing annotation results, a RING finger protein NHL-1 gene from N. denticulata sinensis (NdNHL-1) was identified. There are 15 transcripts in NdNHL-1. The longest transcript is 4995 bp in length and encodes a putative protein of 1665 amino acids. A phylogenetic analysis showed its close relationship with NHL-1 from other crustacean species. This report represents the full-length transcriptome of N. denticulata sinensis and will facilitate research on functional genomics and environmental adaptation in this species.
The Role of Natural Products in Diabetic Retinopathy
Authors: Zhao Yuxuan , Chen Yi , Yan Naihong
Published: May 2024

Diabetic retinopathy (DR) is one of the most severe complications of diabetes mellitus and potentially leads to significant visual impairment and blindness. The complex mechanisms involved in the pathological changes in DR make it challenging to achieve satisfactory outcomes with existing treatments. Diets conducive to glycemic control have been shown to improve outcomes in diabetic patients, thus positioning dietary interventions as promising avenues for DR treatment. Investigations have demonstrated that natural products (NPs) may effectively manage DR. Many types of natural compounds, including saponins, phenols, terpenoids, flavonoids, saccharides, alkaloids, and vitamins, have been shown to exert anti-inflammatory, antioxidant, anti-neovascular, and antiapoptotic effects in vivo and in vitro. Nevertheless, the clinical application of NPs still faces challenges, such as suboptimal specificity, poor bioavailability, and a risk of toxicity. Prospective clinical studies are imperative to validate the therapeutic potential of NPs in delaying or preventing DR.
Ovarian Stem Cells for Women’s Infertility: State of the Art
Authors: Grettka Krzysztof , Idzik Katarzyna , Lewandowska Katarzyna , Świętek Ksena , Palini Simone , Silvestris Franco
Published: May 2024

Today, women’s infertility is considered a social disease in females, occurring not only as an effect of POF (premature ovarian failure) but also as CTRI (cancer treatment-related infertility) in oncologic patients. Several procedures for FP (fertility preservation) are currently adopted to prevent this condition, mostly based on utilization of retrieved eggs from the patients with subsequent IVF (in vitro fertilization) or cryopreservation. However, great interest has recently been devoted to OSCs (ovarian stem cells), whose isolation from female ovaries, followed by their in vitro culture, led to their maturation to OLCs (oocyte-like cells), namely, neo-oocytes comparable to viable eggs suitable for IVF. Translation of these data to FP clinical application creates new hope in the treatment of infertility. Thus, in line with the significant progress in using stem cells in the regenerative medicine field, neo-oogenesis via OSCs, which is currently unapplicable in fertility preservation procedures, will provide novel possibilities for young and adult females in motherhood programs in the future.
Biomarkers and Signaling Pathways Implicated in the Pathogenesis of Idiopathic Multicentric Castleman Disease/Thrombocytopenia, Anasarca, Fever, Reticulin Fibrosis, Renal Insufficiency, and Organomegaly (TAFRO) Syndrome
Authors: Sumiyoshi Remi , Koga Tomohiro , Kawakami Atsushi
Published: May 2024

Idiopathic multicentric Castleman disease (iMCD) and TAFRO syndrome present a variety of symptoms thought to be caused by excessive inflammatory cytokines and chemokines, but the underlying mechanisms are unknown. iMCD is broadly classified into two types: iMCD-NOS and iMCD-TAFRO, which have distinct laboratory findings, pathological features, and responses to treatments. It is thought that iMCD-NOS, particularly the IPL type, responds favorably to IL-6 inhibitors due to its IL-6-centric profile. iMCD-TAFRO frequently progresses acutely and seriously, similar to TAFRO syndrome. Elevated levels of cytokines, including IL-1β, TNF-α, IL-10, and IL-23, as well as chemokines like CXCL13 and CXCL-10 (especially in iMCD-TAFRO), SAA, and VEGF, have been linked to the disease’s pathology. Recent research has identified key signaling pathways including PI3K/Akt/mTOR and JAK-STAT3, as well as those regulated by type I IFN, as crucial in iMCD-TAFRO. These results suggest that dominant pathways may vary between subtypes. Further research into the peripheral blood and lymph nodes is required to determine the disease spectrum of iMCD-NOS/iMCD-TAFRO/TAFRO syndrome.
Clinicopathological Characteristics and Disease Chronicity in Glomerular Diseases: A Decade-Long Study at Romania’s Largest Kidney Biopsy Reference Center
Authors: Pană Nicolae , Ștefan Gabriel , Stancu Simona , Zugravu Adrian , Ciurea Otilia , Petre Nicoleta , Mircescu Gabriel , Căpușă Cristina
Published: May 2024

Glomerular diseases (GDs), significant causes of end-stage kidney disease, are better understood through epidemiological studies based on kidney biopsies (KBs), which provide important insights into their prevalence and characteristics. This study aims to analyze the clinicopathological features of GDs diagnosed from 2008 to 2017 at Romania’s largest reference center. In this decade-long study, 1254 adult patients diagnosed with GDs were included. The local previously validated renal histopathological prognostic score was calculated for each KB using four histopathologic lesions: global glomerulosclerosis, tubular atrophy, interstitial fibrosis and fibrocellular/fibrous crescents. The mean patient age was 50 years, with a male predominance (57%). The primary referral reasons were nephrotic syndrome (46%), nephritic syndrome (37%), chronic kidney disease (12%), asymptomatic urinary abnormalities (4%), and acute kidney injury (1%). Immunoglobulin A nephropathy (IgAN) was the most frequently diagnosed GD (20%), aligning with frequencies reported in European registries. Diabetic glomerular nephropathy was the most common secondary GD (10%). It also presented the highest median renal histopathological prognostic score (2), indicating a poorer prognosis. Lower eGFR and higher proteinuria were independently associated with higher scores. This decade-long study highlights IgAN as the most frequent GD diagnosed by KB. Diabetic glomerular nephropathy was identified as the most common secondary GD. The renal histopathological prognostic score, notably high in diabetic glomerular nephropathy patients, was correlated with lower eGFR and higher proteinuria, underlining its clinical relevance.
Evaluating Ovarian Cancer Chemotherapy Response Using Gene Expression Data and Machine Learning
Authors: Amniouel Soukaina , Yalamanchili Keertana , Sankararaman Sreenidhi , Jafri Mohsin Saleet
Published: May 2024

Background: Ovarian cancer (OC) is the most lethal gynecological cancer in the United States. Among the different types of OC, serous ovarian cancer (SOC) stands out as the most prevalent. Transcriptomics techniques generate extensive gene expression data, yet only a few of these genes are relevant to clinical diagnosis. Methods: Methods for feature selection (FS) address the challenges of high dimensionality in extensive datasets. This study proposes a computational framework that applies FS techniques to identify genes highly associated with platinum-based chemotherapy response on SOC patients. Using SOC datasets from the Gene Expression Omnibus (GEO) database, LASSO and varSelRF FS methods were employed. Machine learning classification algorithms such as random forest (RF) and support vector machine (SVM) were also used to evaluate the performance of the models. Results: The proposed framework has identified biomarkers panels with 9 and 10 genes that are highly correlated with platinum–paclitaxel and platinum-only response in SOC patients, respectively. The predictive models have been trained using the identified gene signatures and accuracy of above 90% was achieved. Conclusions: In this study, we propose that applying multiple feature selection methods not only effectively reduces the number of identified biomarkers, enhancing their biological relevance, but also corroborates the efficacy of drug response prediction models in cancer treatment.
Biocompatibility and Osteogenic Activity of Samarium-Doped Hydroxyapatite—Biomimetic Nanoceramics for Bone Regeneration Applications
Authors: Balas Mihaela , Badea Madalina Andreea , Ciobanu Steluta Carmen , Piciu Florentina , Iconaru Simona Liliana , Dinischiotu Anca , Predoi Daniela
Published: May 2024

In this study, we report on the development of hydroxyapatite (HAp) and samarium-doped hydroxyapatite (SmHAp) nanoparticles using a cost-effective method and their biological effects on a bone-derived cell line MC3T3-E1. The physicochemical and biological features of HAp and SmHAp nanoparticles are explored. The X-ray diffraction (XRD) studies revealed that no additional peaks were observed after the integration of samarium (Sm) ions into the HAp structure. Valuable information regarding the molecular structure and morphological features of nanoparticles were obtained by using Fourier-transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS). The elemental composition obtained by using energy-dispersive X-ray spectroscopy (EDS) confirmed the presence of the HAp constituent elements, Ca, O, and P, as well as the presence and uniform distribution of Sm3+ ions. Both HAp and SmHAp nanoparticles demonstrated biocompatibility at concentrations below 25 μg/mL and 50 μg/mL, respectively, for up to 72 h of exposure. Cell membrane integrity was preserved following treatment with concentrations up to 100 μg/mL HAp and 400 μg/mL SmHAp, confirming the role of Sm3+ ions in enhancing the cytocompatibility of HAp. Furthermore, our findings reveal a positive, albeit limited, effect of SmHAp nanoparticles on the actin dynamics, osteogenesis, and cell migration compared to HAp nanoparticles. Importantly, the biological results highlight the potential role of Sm3+ ions in maintaining cellular balance by mitigating disruptions in Ca2+ homeostasis induced by HAp nanoparticles. Therefore, our study represents a significant contribution to the safety assessment of both HAp and SmHAp nanoparticles for biomedical applications focused on bone regeneration.
Utilizing a Disposable Sensor with Polyaniline-Doped Multi-Walled Carbon Nanotubes to Enable Dopamine Detection in Ex Vivo Mouse Brain Tissue Homogenates
Authors: Rajarathinam Thenmozhi , Jayaraman Sivaguru , Seol Jaeheon , Lee Jaewon , Chang Seung-Cheol
Published: May 2024

Disposable sensors are inexpensive, user-friendly sensing tools designed for rapid single-point measurements of a target. Disposable sensors have become more and more essential as diagnostic tools due to the growing demand for quick, easy-to-access, and reliable information related to the target. Dopamine (DA), a prevalent catecholamine neurotransmitter in the human brain, is associated with central nervous system activities and directly promotes neuronal communication. For the sensitive and selective estimation of DA, an enzyme-free amperometric sensor based on polyaniline-doped multi-walled carbon nanotubes (PANI-MWCNTs) drop-coated disposable screen-printed carbon electrodes (SPCEs) was fabricated. This PANI-MWCNTs-2/SPCE sensor boasts exceptional accuracy and sensitivity when working directly with ex vivo mouse brain homogenates. The sensor exhibited a detection limit of 0.05 μM (S/N = 3), and a wide linear range from 1.0 to 200 μM. The sensor’s high selectivity to DA amidst other endogenous interferents was recognized. Since the constructed sensor is enzyme-free yet biocompatible, it exhibited high stability in DA detection using ex vivo mouse brain homogenates extracted from both Parkinson’s disease and control mice models. This research thus presents new insights into understanding DA release dynamics at the tissue level in both of these models.
A Portable Fluorescent Lateral Flow Immunoassay Platform for Rapid Detection of FluA
Authors: Chen Xu , Huang Xuhui , Kanwal Saima , Wang Jian , Wen Jing , Zhang Dawei
Published: May 2024

The spread of the FluA virus poses significant public health concerns worldwide. Fluorescent lateral flow immunoassay (LFIA) test strips have emerged as vital tools for the early detection and monitoring of influenza infections. However, existing quantitative virus-detection methods, particularly those utilizing smartphone-based sensing platforms, encounter accessibility challenges in resource-limited areas and among the elderly population. Despite their advantages in speed and portability, these platforms often lack user-friendliness for these demographics, impeding their widespread utilization. To address these challenges, this study proposes leveraging the optical pick-up unit (OPU) sourced from commercial optical drives as a readily available fluorescence excitation module for the quantitative detection of antibodies labeled with quantum-dot fluorescent microspheres. Additionally, we utilize miniaturized and high-performance optical components and 3D-printed parts, along with a customized control system, to develop an affordable point-of-care testing (POCT) device. Within the system, a stepping motor scans the test strip from the T-line to the C-line, enabling the calculation of the fluorescence-intensity ratio between the two lines. This simple yet effective design facilitates rapid and straightforward field or at-home testing for FluA. The proposed prototype platform demonstrates promising performance, achieving a limit of detection (LOD) of 2.91 ng/mL, a total detection time of no more than 15 min, and dimensions of 151 mm × 11.2 mm × 10.8 mm3. We believe that the proposed approach holds great potential for improving access to an accurate influenza diagnosis.
Fluorescence Multi-Detection Device Using a Lensless Matrix Addressable microLED Array
Authors: Moro Victor , Canals Joan , Moreno Sergio , Higgins-Wood Steffen , Alonso Oscar , Waag Andreas , Prades J. Daniel , Dieguez Angel
Published: May 2024

A Point-of-Care system for molecular diagnosis (PoC-MD) is described, combining GaN and CMOS chips. The device is a micro-system for fluorescence measurements, capable of analyzing both intensity and lifetime. It consists of a hybrid micro-structure based on a 32 × 32 matrix addressable GaN microLED array, with square LEDs of 50 µm edge length and 100 µm pitch, with an underneath wire bonded custom chip integrating their drivers and placed face-to-face to an array of 16 × 16 single-photon avalanche diodes (SPADs) CMOS. This approach replaces instrumentation based on lasers, bulky optical components, and discrete electronics with a full hybrid micro-system, enabling measurements on 32 × 32 spots. The reported system is suitable for long lifetime (>10 ns) fluorophores with a limit of detection ~1/4 µM. Proof-of-concept measurements of streptavidin conjugate Qdot™ 605 and Amino PEG Qdot™ 705 are demonstrated, along with the device ability to detect both fluorophores in the same measurement.
Advances in the Development of New Drugs and Treatment Targets for Brain Cancers
Authors: Ibarra Luis Exequiel , Milla Sanabria Laura Natalia , Arias-Ramos Nuria
Published: May 2024

Brain tumors are a significant concern for the global medical community, with over 300,000 cases reported annually worldwide [...]
Exploring the Relationship between Turkish Mothers’ Parenting and Psychological Well-Being in Early Childhood: The Role of Child Emotion Regulation and Dysregulation
Authors: Kılıç Ceren , Yüksel Doğan Raziye , Metin Emine Nilgün
Published: May 2024

Although the importance of psychological well-being in early childhood is emphasized, the number of studies conducted with children and adolescents in this field is less than those carried out with adults. The present study aimed to explore the role of child emotion regulation in the relationship between parenting and psychological well-being among a sample of Turkish preschoolers aged 5–6. It further examines the mediating role of emotion regulation. The sample consisted of 416 mothers with children aged 5–6 (Mage = 5.38, SD = 0.48; 50% girls-boys). We collected the data using the Multidimensional Assessment of Parenting Scale (MAPS), the Emotion Regulation Checklist (ERC), and the Psychological Well-Being Scale for Children (PWBS-C). The findings revealed significant relationships among parenting practices (positive/negative), the child’s emotion regulation/dysregulation, and the child’s psychological well-being. Moreover, the findings revealed that positive parenting, directly and indirectly, affects children’s psychological well-being through children’s emotion regulation. On the other hand, findings disclosed that negative parenting has both a direct and indirect impact on children’s psychological well-being through children’s emotion regulation. Overall, the study may shed light on a possible process in which positive parenting boosts a child’s emotional regulation and psychological well-being among preschoolers.
The Effect of Corporate Social Responsibility on Workplace Safety: The Significance of Employees’ Moral Identity
Authors: Hong Yunsook , Roh Taewoo
Published: May 2024

Corporate social responsibility (CSR) has gained significant attention from researchers and practitioners due to its potential impact on employee attitudes and behaviors. This study investigates the influence of CSR on employee safety behavior, examining the mediating effects of job stress and organizational identification, as well as the moderating role of moral identity. We conducted a three-wave time-lagged survey among 236 South Korean employees. Participants were recruited through a research company using stratified random sampling. Data were collected at three time points, each separated by a 4–5-week interval. Structural equation modeling (SEM) was used to test the hypothesized relationships. The findings support all of the hypothesized relationships. CSR was positively related to safety behavior and negatively related to job stress. Job stress was negatively related to organizational identification, which in turn was positively related to safety behavior. The sequential mediation of job stress and organizational identification was significant. Moral identity moderated the relationship between CSR and job stress, such that the negative effect of CSR on job stress was stronger for employees with a high moral identity. This study contributes to the CSR literature by examining the impact of CSR on safety behavior and the underlying mechanisms and boundary conditions of this relationship. The findings suggest that organizations can promote employee safety behavior by implementing CSR initiatives, which can reduce job stress and enhance organizational identification. Organizations should also consider the role of employees’ moral identity when designing and communicating CSR initiatives.
Study of Structural Seismic Damage Considering Seasonal Frozen Soil–Structure Interaction
Authors: Bian Xuyang , Wang Guoxin
Published: May 2024

Frozen soil may cause structures to have different damage statuses, as revealed by earthquakes in northeastern China. ABAQUS (2019), a numerical simulation software application, was adopted to systematically and deeply study the structural seismic response, considering seasonal frozen soil–structure interaction under different ground motion intensities and soil ambient temperatures. The results showed firstly that the variation in soil ambient temperature had a great influence on the seismic response of the structure, as indicated by the damage status of the structure obtained through numerical simulation. Secondly, through further analysis of the numerical simulation results, the influence amplitude of different soil temperatures on the structural seismic response was quantitatively analyzed and systematically summarized. Finally, the structural seismic damage with negative ambient temperature could be significantly lower than that with positive temperature normally. Additionally, such an internal change mechanism was also objectively analyzed to verify the reliability of the conclusion.
Using Cement and Calcium Lignosulfonate to Improve the Mechanical Properties and Microstructure of Loess in a Seasonal Freezing Zone
Authors: Wang Qiusheng , Li Yunjie , Li Pei , Qi Yunpeng
Published: May 2024

The cement composite calcium lignosulfonate is used to enhance the mechanical properties and the freeze–thaw resistance of loess. Based on an unconfined compressive test under different freeze–thaw cycles, the influence of cement dosage, curing age, and freeze–thaw cycles on compressive strength are discussed. The results indicate that the strength of loess can increase by up to 13 times, and the loss of strength is reduced from 72% to 28% under the reinforcement of cement dosage and curing age. The loss of strength is mainly concentrated in the initial 5 freeze–thaw cycles, and the structure gradually stabilizes after 10 freeze–thaw cycles. In addition, according to the X-ray diffraction test, it is found that the stabilized loess exhibits a comparatively more stable mineral composition. The scanning electron microscope results reveal that hydration products enveloped the soil particles, forming a mesh structure that strengthens the connection between the soil particles. The freeze–thaw damage makes the small and medium pores turn into large pores in loess, while the stabilized loess changes micro and small pores into small and medium pores, with no large pores found. It is feasible to improve loess with the cement composite calcium lignosulfonate, which can provide references for the reinforcement treatment of loess.