bluuebunny/crossref_metadata_2025 huggingface dataset:
Antenatal Growth, Gestational Age, Birth, Enteral Feeding, and Blood Citrulline Levels in Very Low Birth Weight Infants
Authors: Obayashi Midori , Iwata Sachiko , Okuda Tomoya , Mori Ichita , Nakane Shigeharu , Togawa Yasuko , Sugimoto Mari , Togawa Takao , Muramatsu Kanji , Saitoh Shinji , Sugiura Takahiro , Iwata Osuke
Published: February 2024

Early enteral nutrition using reliable biomarkers of intestinal function must be established to improve neurodevelopmental outcomes in very low birth weight infants (VLBWIs). Serum citrulline levels reflect the intestinal function in adults. To elucidate the relationship among antenatal growth, postnatal enteral nutrition, and blood citrulline levels, a retrospective single-center observational study was conducted on 248 VLBWIs born between April 2014 and March 2021. A mixed effect model and post hoc simple slope analysis were used to estimate the correlations between clinical variables and citrulline levels at Early (day 5.1) and Late (day 24.3) postnatal ages. Greater gestational age, birth weight, and amount of enteral nutrition at the time of blood sampling were associated with lower citrulline levels at the Early postnatal age and higher citrulline levels at the Late postnatal age. Provided that Early citrulline levels predominantly reflect the consequence of antenatal citrulline metabolism, it is suggested that fetal growth and maturation are likely to promote citrulline catabolism in utero and its synthesis after birth. With additional insights into the temporal transition point wherein the maturation-dependent balance of citrulline metabolism shifts from catabolism-dominant to synthesis-dominant, citrulline emerges as a potential biomarker for assessing intestinal function and gastrointestinal disorders.
Calcium Deficiency Decreases Bone Mass without Affecting Adiposity in Ovariectomized Rats Fed a High-Fat Diet
Authors: Cao Jay J. , Gregoire Brian R.
Published: February 2024

Obesity induced by a high-fat (HF) diet increases bone resorption and/or decreases bone formation, resulting in reduced bone mass and strength in various animal models. Studies showed that Ca intake is a modifiable factor for osteoporosis and obesity. This study investigated whether Ca deficiency affects bone structure and adiposity in ovariectomized (OVX) rats fed a HF diet. We hypothesized that Ca deficiency further decreases bone mass and increases fat mass in HF-fed OVX rats. Forty-seven OVX at 6-month-old were randomly assigned to four groups in a 2 × 2 factorial design: normal-fat (NF, 10% fat as energy) or HF (45% fat as energy) diet with either low Ca (LC, 1 g/4057 kcal) or normal Ca (NC, 6 g/4057 kcal). In addition, 12 sham-operated rats at 6 months old were fed a NFNC diet as a control for the OVX procedure. Rats were fed the respective diet for 4 months. Dietary Ca content did not affect body weight, fat mass, lean mass, food intake, energy intake, and serum cytokines. Compared to NC, LC resulted in lower tibial bone volume/total volume (BV/TV, p < 0.01), connectivity density (p < 0.01), trabecular number (Tb.N, p = 0.01), bone mineral density (BMD, p < 0.01), and femur weight (p < 0.01), femur content of Ca (p < 0.01), Cu (p = 0.03), Zn (p < 0.01), and greater trabecular separation (Tb.Sp, p < 0.01) at proximal tibia indicating bone structure deterioration. Compared to rats on the NF diet, animals fed the HF had lower BV/TV (p = 0.03) and Tb.N (p < 0.01) with greater body weight (p < 0.01), fat mass (p < 0.01), Tb.Sp (p = 0.01), the content of Ca, Cu, and Zn in the femur, and serum leptin (p < 0.01). There were no significant interactions between Ca and fat for body composition and bone structural parameters. Compared to Sham, OVX resulted in greater body weight and fat mass. The trabecular bone structure of the tibia, but not the cortical bone, was significantly impaired by the OVX procedure. These data indicate that inadequate Ca intake and a high-fat diet have independent negative effects on bone structure and that Ca deficiency does not affect adiposity in OVX rats.
Correction: Furukawa et al. Long-Term Soft-Food Rearing in Young Mice Alters Brain Function and Mood-Related Behavior. Nutrients 2023, 15, 2397
Authors: Furukawa Masae , Tada Hirobumi , Raju Resmi , Wang Jingshu , Yokoi Haruna , Yamada Mitsuyoshi , Shikama Yosuke , Matsushita Kenji
Published: February 2024

In the original publication [...]
Artificial Reef Deployment Reduces Diving Pressure from Natural Reefs—The Case of Introductory Dives in Eilat, Red Sea
Authors: Shashar Nadav , Oren Asa , Neri Re’em , Waizman Omer , Chernihovsky Natalie , Tynyakov Jenny
Published: February 2024

Artificial reefs have been suggested as alternative dive sites to mitigate human pressure on natural reefs. Despite the conceptual appeal of artificial reefs, there is a paucity of empirical evidence regarding their effectiveness in achieving this objective. Here, we report that a small artificial reef deployed adjacent to a local coral marine protected area caused a shift in the routes taken by introductory dives and nearly eliminated their visitations to the natural fringing reef within the MPA. This behavioral shift among divers persisted for more than a decade following the AR deployment. These findings underscore the efficacy of well-designed and appropriately located artificial reefs as valuable instruments in the conservation of coral reefs.
High Glucose Induces Oxidative Stress That Alters Glycocalyx Proteoglycan Levels in Primary Rat Retinal Microvascular Endothelial Cells and in Isolated Ophthalmic Arteries
Authors: Alvarez Ivan A. , Lee Minsup , Eshaq Randa S. , Leskova Wendy , Harris Norman R.
Published: February 2024

Our purpose in this study was to identify the role played by oxidative stress in the changes to proteoglycans that occur under hyperglycemic conditions, using primary rat retinal microvascular endothelial cells (RRMEC) and cultured ophthalmic arteries. The cells and blood vessels obtained from rats were cultured in normal glucose (5.6 mM) and high glucose (25 mM) with or without N-acetylcysteine (NAC), an antioxidant. Intracellular oxidative stress was determined by measuring dihydroethidium (DHE) fluorescence and malondialdehyde (MDA)-modified protein levels. mRNA and protein levels were evaluated using quantitative real-time polymerase chain reaction and immunoblot, respectively. High glucose increased levels of glypican-1 mRNA and protein. The level of syndecan-1 mRNA also was increased, but its protein level was decreased, by high glucose. Evaluation of DHE and MDA showed that high glucose increased oxidative stress. These changes caused by high glucose were significantly reversed by NAC treatment. Matrix metalloproteinase-9 (MMP-9) levels, which increased under high glucose conditions, were suppressed by NAC treatment. Oxidative stress caused by hyperglycemia may be responsible for significant changes to the ocular endothelial glycocalyx.
The SMILE Effect in the Beam Propagation Direction Affects the Beam Shaping of a Semiconductor Laser Bar Array
Authors: Zhang Hongyou , Hu Yu , Peng Shuihai , Liu Yong
Published: February 2024

Near-field bending of a laser diode bar (i.e., the SMILE effect) degrades the laser beam brightness, adversely affecting optical coupling and beam shaping. Previous reports mainly focused on the two-dimensional near-field bending of a laser diode bar. However, the near-field bending of a laser diode bar not only occurs in the laser bar growth direction, but also in the beam propagation direction. The present article proposes the three-dimensional near-field bending of a laser diode array, which is commonly known as the three-dimensional spatial SMILE effect. Through theoretical and simulated investigations, it has been found that a laser bar array not only deforms in the fast axis direction to cause the traditional two-dimensional SMILE effect but also experiences an additional deformation of approximately 2 μm in the laser emission direction simultaneously. Due to the SMILE effect in the beam propagation direction, not all emitters are aligned in a straight line, and some emitters experience defocusing during collimation. Consequently, there is an increase in the residual divergence angle and beam width, resulting in a degradation of the laser bar array’s beam quality. According to the theoretical calculations, ZEMAX simulations, and experimental results, for a FAC (fast axis collimation) with a focal length of 300 μm, the divergence angle of single emitter after collimating in the fast axis increases from 4.95 mrad to 6.46 mrad when the offsetting of the working distance between the incident beam waist and FAC lens increases from 0 μm to 2 μm.
Enhanced THz Circular-Polarization Detection in Miniaturized Chips with Chiral Antennas
Authors: Li Fangzhe , Zhou Jing , Deng Jie , Shen Jinyong , Zhu Tianyun , Jing Wenji , Dai Xu , Ye Jiexian , Zhang Yujie , Huang Junwei , Chen Xiaoshuang
Published: February 2024

Recent advancements in terahertz (THz) wave technology have highlighted the criticality of circular-polarization detection, fostering the development of more compact, efficient on-chip THz circular-polarization detectors. In response to this technological imperative, we presented a chiral-antenna-integrated GaAs/AlGaAs quantum well (QW) THz detector. The chiral antenna selectively couples the incident light of a specific circular-polarization state into a surface-plasmon polariton wave that enhances the absorptance of the QWs by a factor of 12 relative to a standard 45° faceted device, and reflects a significant amount of the incident light of the orthogonal circular-polarization state. The circular-polarization selectivity is further enhanced by the QWs with a strong intrinsic anisotropy, resulting in a circular-polarization extinction ratio (CPER) as high as 26 at 6.52 THz. In addition, the operation band of the device can be adjusted by tuning the structural parameters of the chiral structure. Moreover, the device preserves a high performance for oblique incidence within a range of ±5°, and the device architecture is compatible with a focal plane array. This report communicates a promising approach for the development of miniaturized on-chip THz circular-polarization detectors.
Evaluation of the Thermal Stability and Micro-Modification Mechanism of SBR/PP-Modified Asphalt
Authors: Zhang Qing , Hou Dehua , Li Zhongyu , Wang Hainian , Dong Shi
Published: February 2024

To evaluate the thermal stability of composite polymer-modified asphalt, thermoplastic elastomer styrene-butadiene rubber (SBR)/polypropylene (PP) pellets were prepared using a hot-melt blending technique, with butyl rubber powder and waste polypropylene pellets as raw materials. The effects of different evaluation indexes on the thermal stability of SBR/PP-modified asphalt were investigated using a frequency scan test and a multi-stress creep recovery (MSCR) test, and the compatibility of SBR/PP particles with asphalt was studied using the Cole–Cole diagram and microstructure images. The tests show that, firstly, the performance grade (PG) classification of asphalt can be improved by adding an SBR/PP thermoplastic elastomer to enhance the adaptability of asphalt in high- and low-temperature environments, and the evaluation separation index can reflect the high-temperature storage stability of composite-modified asphalt more reasonably. Additionally, the larger the rubber-to-plastic ratio the worse the high-temperature thermal stability of composite-modified asphalt. Moreover, the addition of additives to the composite particles can promote the SBR/PP particles in the asphalt to be more uniformly dispersed, forming a more desirable microstructure and improving the thermal stability of composite-modified asphalt. Ultimately, the semicircular curve of the Cole–Cole diagram can reflect the compatibility characteristics of the two-phase structure of SBR/PP-modified asphalt, which can be used as an auxiliary index to evaluate the compatibility of polymer-modified asphalt.
Molecularly Mixed Composite Membranes for Gas Separation Based on Macrocycles Embedded in a Polyimide
Authors: Vuono Danilo , Clarizia Gabriele , Ferreri Loredana , Consoli Grazia Maria Letizia , Zampino Daniela Clotilde , Scalzo Giuseppina , Petralia Salvatore , Bernardo Paola
Published: February 2024

Polyimides are a polymer class that has been extensively investigated as a membrane material for gas separation owing to its interesting permselective properties in a wide range of operation temperatures and pressures. In order to improve their properties, the addition of different filler types is currently studied. p-tert-Butylcalix[n]arene macrocycles (PTBCs) with different cavity sizes (PTBC4, PTBC6, PTBC8) were used as fillers in a commercial thermoplastic polyimide, with a concentration in the range 1–9 wt%, to develop nanocomposite membranes for gas separation. The selected macrocycles are attractive organic compounds owing to their porous structure and affinity with organic polymers. The nanocomposite membranes were prepared in the form of films in which the polymeric matrix is a continuous phase incorporating the dispersed additives. The preparation was carried out according to a pre-mixing approach in a mutual solvent, and the solution casting was followed by a controlled solvent evaporation. The films were characterized by investigating their miscibility, morphology, thermal and spectral properties. The gas transport through these films was examined as a function of the temperature and also time. The results evidenced that the incorporation of the chosen nanoporous fillers can be exploited to enhance molecular transport, offering additional pathways and promoting rearrangements of the polymeric chains.
Impact of Doxycycline Addition on Activated Sludge Microflora and Microbial Communities
Authors: Djelal Hayet , Haddouche Djouza , Lebreton Megane , Barros Vanessa , Villegas Cristian , Dabert Patrick
Published: February 2024

Municipal wastewater treatment plants (WWTPs) are exposed to high concentrations of micropollutants that can impact conventional activated sludge treatment. The consequences of this include failure to meet discharge standards and the disintegration of flocs, leading to poor sludge settleability. This lab-scale study focuses on the influence of doxycycline, an antibiotic widely used against human and animal diseases, on protozoa, metazoa, and bacterial communities under sludge growing conditions. Doxycycline was added to the mixed liquor of a communal WWTP up to 0, 100, 200, and 400 mg of doxycycline L−1 and incubated in batch conditions for 23 days. The regular addition of nutrient and carbon sources was preformed every 2 days to prevent sludge starvation. Sludge growth, conductivity, and settleability were measured and compared to sludge microbial community structure, determined by microscopic observations and high-throughput 16S rDNA sequencing. The high doxycycline concentration negatively impacted settleability and correlated with a decrease in bacterial diversity and floc disintegration. The addition of doxycycline promoted the enrichment of Proteobacteria Brevundimonas sp., Luteibacter anthropi, and the Bacteroidetes Chryseobacterium massoliae. These species are known to be resistant to a wide spectrum of antibiotics, including tetracyclines. A study of a larger scale may be conducted based on this study’ results.
Work Stress and Psychoactive Substance Use among Correctional Officers in the USA
Authors: Jayawardene Wasantha , Kumbalatara Chesmi , Jones Alsten , McDaniel Justin
Published: February 2024

Background: Correctional officers’ life expectancy in the U.S. is 59 years, compared to the population average of 75 years. Correctional officers have higher suicide rates than others and carry a higher risk for substance use. This study examined relationships between work stress, psychoactive substance use, and preferred venues for treatment. Methods: Secondary analysis was conducted on 2017–2018 data from interviews with correctional officers, randomly sampled from prisons within Massachusetts and Texas. Independent sample t-test, multinomial logistic regression, and mediation effect model were used for analysis. Results: Of the 1083 participants (mean age = 38.6), 71.4% were males, 62.9% were White, 17.0% were veterans, and 46.7% worked in maximum-security prisons, among which 70.8% used alcohol and 17.2% sedatives in the last month. While 52.3% did not prefer receiving stress management services from the department, 32.9% did not prefer receiving from outside. Alcohol and sedative use were associated positively with work stress and counterproductive workplace behaviors, and negatively with organizational citizenship and task performance. Preferred treatment varied based on work stress and substance use. Conclusions: Work stress and psychoactive substance use among correctional officers are multifactorial. Interventions should be tailored to officers’ needs and preferred treatment venues. Prison reform should address the needs of not only inmates, but also officers.
Geometric Aspects of Mixed Quantum States Inside the Bloch Sphere
Authors: Alsing Paul M. , Cafaro Carlo , Felice Domenico , Luongo Orlando
Published: February 2024

When studying the geometry of quantum states, it is acknowledged that mixed states can be distinguished by infinitely many metrics. Unfortunately, this freedom causes metric-dependent interpretations of physically significant geometric quantities such as the complexity and volume of quantum states. In this paper, we present an insightful discussion on the differences between the Bures and the Sjöqvist metrics inside a Bloch sphere. First, we begin with a formal comparative analysis between the two metrics by critically discussing three alternative interpretations for each metric. Second, we explicitly illustrate the distinct behaviors of the geodesic paths on each one of the two metric manifolds. Third, we compare the finite distances between an initial state and the final mixed state when calculated with the two metrics. Interestingly, in analogy with what happens when studying the topological aspects of real Euclidean spaces equipped with distinct metric functions (for instance, the usual Euclidean metric and the taxicab metric), we observe that the relative ranking based on the concept of a finite distance between mixed quantum states is not preserved when comparing distances determined with the Bures and the Sjöqvist metrics. Finally, we conclude with a brief discussion on the consequences of this violation of a metric-based relative ranking on the concept of the complexity and volume of mixed quantum states.
A Critical Review on the Application of Recycled Carbon Fiber to Concrete and Cement Composites
Authors: Bhandari Manan , Nam Il-Woo
Published: February 2024

Carbon fiber (CF) exhibit extraordinary properties, such as high specific and tensile strength, high elastic modulus, light weight, and weather resistance, which has led to a rapid increase in the use of CF in sectors such as aerospace, sports equipment, energy storage, automotive, construction, and wind energy applications. However, the increase in CF applications has led to a massive production of CF waste. As CF is non-biodegradable, it results in CF accumulation in landfills. CF waste is a rapidly growing ecological hazard because of its high energy consumption and expensive production methods. The properties of carbon fibers can be preserved even after recycling given the development of recycling technology; therefore, multiple studies have been conducted to demonstrate the effect of recycled carbon fiber (RCF) in different composites such as cement-based composites. This review presents the results of studies conducted on the application of RCF to cement composites and analyzes those results to investigate the effect of RCF on the properties of cement composites such as mechanical properties (compressive strength, flexural strength, and tensile strength), fracture characteristics (fracture toughness and fracture energy), electrical properties, and workability. Overall, the studies demonstrated a positive trend in the application of RCF to cement composites.
Satellite Synthetic Aperture Radar, Multispectral, and Infrared Imagery for Assessing Bridge Deformation and Structural Health—A Case Study at the Samuel de Champlain Bridge
Authors: Cusson Daniel , Stewart Helen
Published: February 2024

A space-borne remote sensing method was applied, validated, and demonstrated in a case study on the Samuel de Champlain Bridge in Montreal, Canada. High-resolution C-band radar satellite imagery was analyzed using the Persistent Scatterer Interferometric Synthetic Aperture Radar technique to derive bridge displacements and compare them against theoretical estimates. Multispectral and long-wave thermal infrared satellite imagery acquired during the InSAR observation period and historical environmental data were analyzed to provide context for the interpretation and understanding of InSAR results. Thermal deformation measurements compared well with their theoretical estimates based on known bridge geometry and ambient temperature data. Non-thermal deformation measurements gave no evidence of settlement during the 2-year monitoring period, as would normally be expected for a newly constructed bridge with its foundation on bedrock. The availability of environmental data obtained from multispectral and thermal infrared satellite imagery was found to be useful in providing context for the bridge stability assessment. Ambient temperature measurements from thermal infrared satellite imagery were found to be a suitable alternative in cases where data from in situ temperature sensors or nearby weather stations are not available or not fit for purpose. No strong correlation was found between the river conditions and bridge deformation results from the InSAR analysis; this is partly due to the fact that most of these effects act along the river flow in the north–south direction, to which the satellite sensor is not sensitive.
GSA-SiamNet: A Siamese Network with Gradient-Based Spatial Attention for Pan-Sharpening of Multi-Spectral Images
Authors: Gao Yi , Qin Mengjiao , Wu Sensen , Zhang Feng , Du Zhenhong
Published: February 2024

Pan-sharpening is a fusion process that combines a low-spatial resolution, multi-spectral image that has rich spectral characteristics with a high-spatial resolution panchromatic (PAN) image that lacks spectral characteristics. Most previous learning-based approaches rely on the scale-shift assumption, which may not be applicable in the full-resolution domain. To solve this issue, we regard pan-sharpening as a multi-task problem and propose a Siamese network with Gradient-based Spatial Attention (GSA-SiamNet). GSA-SiamNet consists of four modules: a two-stream feature extraction module, a feature fusion module, a gradient-based spatial attention (GSA) module, and a progressive up-sampling module. In the GSA module, we use Laplacian and Sobel operators to extract gradient information from PAN images. Spatial attention factors, learned from the gradient prior, are multiplied during the feature fusion, up-sampling, and reconstruction stages. These factors help to keep high-frequency information on the feature map as well as suppress redundant information. We also design a multi-resolution loss function that guides the training process under the constraints of both reduced- and full-resolution domains. The experimental results on WorldView-3 satellite images obtained in Moscow and San Juan demonstrate that our proposed GSA-SiamNet is superior to traditional and other deep learning-based methods.
Assessing Satellite-Derived Shoreline Detection on a Mesotidal Dissipative Beach
Authors: Cabezas-Rabadán Carlos , Almonacid-Caballer Jaime , Benavente Javier , Castelle Bruno , Del Río Laura , Montes Juan , Palomar-Vázquez Jesús , Pardo-Pascual Josep E.
Published: February 2024

The accuracy and robustness of the shoreline definition from satellite imagery on different coastal types are crucial to adequately characterising beach morphology and dynamics. However, the generic and widespread application of satellite-derived shoreline algorithms is limited by the lack of robust methods and parameter assessments. This work constitutes a quantitative and comprehensive assessment of the satellite-derived waterlines from Sentinel-2 by using the novel SAET tool (Shoreline Analysis and Extraction Tool) on the exposed and mesotidal beach of La Victoria (Cádiz, SW Spain). The diverse parameters available in SAET, such as water indexes, thresholding methods, morphological filters, and kernel sizes, were combined to define water/land interface positions that were compared against coincident video-derived waterlines. Satellite-derived waterline errors are found to be affected by extraction parameters, as well as by the oceanographic and morphological conditions at the time of the image acquisition. The application of a morphological erosion filter on the water mask, which tends to shift the extracted waterline seawards and reduce bias, is the best solution at the dissipative site of La Victoria Beach. Moreover, using a 3 × 3 kernel size consistently shows higher accuracies than a larger kernel. Although there was no parameter combination showing the best skill for all dates, the employment of the Automated Water Extraction Index for images with no shadows (AWEInsh) with a threshold = 0, erosion morphological filter, and 3 × 3 kernel was, overall, the best combination of extraction parameters for this beach (average waterline RMSE of 5.96 m). The combination of the Modified Normalised Difference Water Index (MDNWI) with the Otsu thresholding also led to similar positions of the resulting waterlines and offered good accuracies. In line with other recent research efforts, our work stresses the lack of generic shoreline extraction solutions that can be applied automatically at a global level and the necessity to adapt and validate the extraction methodologies to the different types of coastlines.
Global and Multiscale Aggregate Network for Saliency Object Detection in Optical Remote Sensing Images
Authors: Huo Lina , Hou Jiayue , Feng Jie , Wang Wei , Liu Jinsheng
Published: February 2024

Salient Object Detection (SOD) is gradually applied in natural scene images. However, due to the apparent differences between optical remote sensing images and natural scene images, directly applying the SOD of natural scene images to optical remote sensing images has limited performance in global context information. Therefore, salient object detection in optical remote sensing images (ORSI-SOD) is challenging. Optical remote sensing images usually have large-scale variations. However, the vast majority of networks are based on Convolutional Neural Network (CNN) backbone networks such as VGG and ResNet, which can only extract local features. To address this problem, we designed a new model that employs a transformer-based backbone network capable of extracting global information and remote dependencies. A new framework is proposed for this question, named Global and Multiscale Aggregate Network for Saliency Object Detection in Optical Remote Sensing Images (GMANet). In this framework, the Pyramid Vision Transformer (PVT) is an encoder to catch remote dependencies. A Multiscale Attention Module (MAM) is introduced for extracting multiscale information. Meanwhile, a Global Guiled Brach (GGB) is used to learn the global context information and obtain the complete structure. Four MAMs are densely connected to this GGB. The Aggregate Refinement Module (ARM) is used to enrich the details of edge and low-level features. The ARM fuses global context information and encoder multilevel features to complement the details while the structure is complete. Extensive experiments on two public datasets show that our proposed framework GMANet outperforms 28 state-of-the-art methods on six evaluation metrics, especially E-measure and F-measure. It is because we apply a coarse-to-fine strategy to merge global context information and multiscale information.
Real-Time Measurement of CH4 in Human Breath Using a Compact CH4/CO2 Sensor
Authors: Lin Yueyu , Manalili Dexter , Khodabakhsh Amir , Cristescu Simona M.
Published: February 2024

The presence of an elevated amount of methane (CH4) in exhaled breath can be used as a non-invasive tool to monitor certain health conditions. A compact, inexpensive and transportable CH4 sensor is thus very interesting for this purpose. In addition, if the sensor is also able to simultaneously measure carbon dioxide (CO2), one can extract the end-tidal concentration of exhaled CH4. Here, we report on such a sensor based on a commercial detection module using tunable diode laser absorption spectroscopy. It was found that the measured CH4/CO2 values exhibit a strong interference with water vapor. Therefore, correction functions were experimentally identified and validated for both CO2 and CH4. A custom-built breath sampler was developed and tested with the sensor for real-time measurements of CH4 and CO2 in exhaled breath. As a result, the breath sensor demonstrated the capability of accurately measuring the exhaled CH4 and CO2 profiles in real-time. We obtained minimum detection limits of ~80 ppbv for CH4 and ~700 ppmv for CO2 in 1.5 s measurement time.
Recent Progress in MEMS Fiber-Optic Fabry–Perot Pressure Sensors
Authors: Chen Ye , Lu Dongqin , Xing Huan , Ding Haotian , Luo Junxian , Liu Hanwen , Kong Xiangxu , Xu Fei
Published: February 2024

Pressure sensing plays an important role in many industrial fields; conventional electronic pressure sensors struggle to survive in the harsh environment. Recently microelectromechanical systems (MEMS) fiber-optic Fabry–Perot (FP) pressure sensors have attracted great interest. Here we review the basic principles of MEMS fiber-optic FP pressure sensors and then discuss the sensors based on different materials and their industrial applications. We also introduce recent progress, such as two-photon polymerization-based 3D printing technology, and the state-of-the-art in this field, e.g., sapphire-based sensors that work up to 1200 °C. Finally, we discuss the limitations and opportunities for future development.
Simple Binding and Dissociation of a Sialoglycoprotein Using Boronic Acid-Modified Functional Interfaces on Microparticles
Authors: Horiguchi Yukichi , Yasuura Masato , Ashiba Hiroki , Tan Zheng Lin , Fukuda Takashi
Published: February 2024

An overexpression of sialic acid is an indicator of metastatic cancer, and selective detection of sialic acid shows potential for cancer diagnosis. Boronic acid is a promising candidate for this purpose because of its ability to specifically bind to sialic acid under acidic conditions. Notably, the binding strength can be easily modulated by adjusting the pH, which allows for a simple dissociation of the bound sialic acid. In this study, we developed 5-boronopicolinic acid (5-BPA)-modified magnetic particles (BMPs) to selectively capture sialic acid biomolecules. We successfully captured fetuin, a well-known sialoglycoprotein, on BMPs at >104 molecules/particle using an acetate buffer (pH 5.0). Facile dissociation then occurred when the system was changed to a pH 7.6 phosphate buffer. This capture-and-release process could be repeated at least five times. Moreover, this system could enrich fetuin by more than 20 times. In summary, BMPs are functional particles for facile purification and concentration through the selective capture of sialic acid proteins and can improve detection sensitivity compared with conventional methods. This technology shows potential for the detection of sialic acid overexpression by biological particles.
Temperature Hotspot Detection on Printed Circuit Boards (PCBs) Using Ultrasonic Guided Waves—A Machine Learning Approach
Authors: Yule Lawrence , Harris Nicholas , Hill Martyn , Zaghari Bahareh , Grundy Joanna
Published: February 2024

This paper addresses the challenging issue of achieving high spatial resolution in temperature monitoring of printed circuit boards (PCBs) without compromising the operation of electronic components. Traditional methods involving numerous dedicated sensors such as thermocouples are often intrusive and can impact electronic functionality. To overcome this, this study explores the application of ultrasonic guided waves, specifically utilising a limited number of cost-effective and unobtrusive Piezoelectric Wafer Active Sensors (PWAS). Employing COMSOL multiphysics, wave propagation is simulated through a simplified PCB while systematically varying the temperature of both components and the board itself. Machine learning algorithms are used to identify hotspots at component positions using a minimal number of sensors. An accuracy of 97.6% is achieved with four sensors, decreasing to 88.1% when utilizing a single sensor in a pulse–echo configuration. The proposed methodology not only provides sufficient spatial resolution to identify hotspots but also offers a non-invasive and efficient solution. Such advancements are important for the future electrification of the aerospace and automotive industries in particular, as they contribute to condition-monitoring technologies that are essential for ensuring the reliability and safety of electronic systems.
A Concept of a Plug-In Simulator for Increasing the Effectiveness of Rescue Operators When Using Hydrostatically Driven Manipulators
Authors: Typiak Rafał
Published: February 2024

The introduction of Unmanned Ground Vehicles (UGVs) into the field of rescue operations is an ongoing process. New tools, such as UGV platforms and dedicated manipulators, provide new opportunities but also come with a steep learning curve. The best way to familiarize operators with new solutions are hands-on courses but their deployment is limited, mostly due to high costs and limited equipment numbers. An alternative way is to use simulators, which from the software side, resemble video games. With the recent expansion of the video game engine industry, currently developed software becomes easier to produce and maintain. This paper tries to answer the question of whether it is possible to develop a highly accurate simulator of a rescue and IED manipulator using a commercially available game engine solution. Firstly, the paper describes different types of simulators for robots currently available. Next, it provides an in-depth description of a plug-in simulator concept. Afterward, an example of a hydrostatic manipulator arm and its virtual representation is described alongside validation and evaluation methodologies. Additionally, the paper provides a set of metrics for an example rescue scenario. Finally, the paper describes research conducted in order to validate the representation accuracy of the developed simulator.
A 28 GHz GaN 6-Bit Phase Shifter MMIC with Continuous Tuning Calibration Technique
Authors: Seo Soyeon , Lee Jinho , Lee Yongho , Shin Hyunchol
Published: February 2024

A 28 GHz digitally controlled 6-bit phase shifter with a precision calibration technique in GaN high-electron mobility transistor (HEMT) technology is presented for Ka-band phased-array systems and applications. It comprises six stages, in which stages 1 and 2 for 5.625° and 11.25° are designed in the form of a switched-line circuit, and stages 3, 4, and 5 for 22.5°, 45°, and 90° are designed in the form of a switched-filter circuit. The final stage 6 for 180° is designed in a single-to-differential balun followed by a single-pole double-throw (SPDT) switch for achieving an efficient phase inversion. A novel continuous tuning calibration technique is proposed to improve the phase accuracy. It controls the gate bias voltage of off-state HEMTs at the stage 6 SPDT switch for fine calibration of the output phase. Fabricated in a 0.15 μm GaN HEMT process using a die size of 1.75 mm2, the circuit produces 64 phase states at 28 GHz with a 5.625° step. The experimental results show that the Root-Mean-Square (RMS) phase error is significantly improved from 8.56° before calibration to 1.08° after calibration. It is also found that the calibration does not induce significant changes for other performances such as the insertion loss, RMS amplitude error, and input-referred P1dB. This work successfully demonstrates that the GaN technology can be applied to millimeter-wave high-power phased-array transceiver systems.
Multi-Method Technics and Deep Neural Networks Tools on Board ARGO USV for the Geoarchaeological and Geomorphological Mapping of Coastal Areas: The Case of Puteoli Roman Harbour
Authors: Mattei Gaia , Aucelli Pietro P. C. , Ciaramella Angelo , De Luca Luigi , Greco Alberto , Mellone Gennaro , Peluso Francesco , Troisi Salvatore , Pappone Gerardo
Published: February 2024

The ARGO-USV (Unmanned Surface Vehicle for ARchaeological GeO-application) is a technological project involving a marine drone aimed at devising an innovative methodology for marine geological and geomorphological investigations in shallow areas, usually considered critical areas to be investigated, with the help of traditional vessels. The methodological approach proposed in this paper has been implemented according to a multimodal mapping technique involving the simultaneous and integrated use of both optical and geoacoustic sensors. This approach has been enriched by tools based on artificial intelligence (AI), specifically intended to be installed onboard the ARGO-USV, aimed at the automatic recognition of submerged targets and the physical characterization of the seabed. This technological project is composed of a main command and control system and a series of dedicated sub-systems successfully tested in different operational scenarios. The ARGO drone is capable of acquiring and storing a considerable amount of georeferenced data during surveys lasting a few hours. The transmission of all acquired data in broadcasting allows the cooperation of a multidisciplinary team of specialists able to analyze specific datasets in real time. These features, together with the use of deep-learning-based modules and special attention to green-compliant construction phases, are the particular aspects that make ARGO-USV a modern and innovative project, aiming to improve the knowledge of wide coastal areas while minimizing the impact on these environments. As a proof-of-concept, we present the extensive mapping and characterization of the seabed from a geoarchaeological survey of the underwater Roman harbor of Puteoli in the Gulf of Naples (Italy), demonstrating that deep learning techniques can work synergistically with seabed mapping methods.
Custom Loss Functions in XGBoost Algorithm for Enhanced Critical Error Mitigation in Drill-Wear Analysis of Melamine-Faced Chipboard
Authors: Bukowski Michał , Kurek Jarosław , Świderski Bartosz , Jegorowa Albina
Published: February 2024

The advancement of machine learning in industrial applications has necessitated the development of tailored solutions to address specific challenges, particularly in multi-class classification tasks. This study delves into the customization of loss functions within the eXtreme Gradient Boosting (XGBoost) algorithm, which is a critical step in enhancing the algorithm’s performance for specific applications. Our research is motivated by the need for precision and efficiency in the industrial domain, where the implications of misclassification can be substantial. We focus on the drill-wear analysis of melamine-faced chipboard, a common material in furniture production, to demonstrate the impact of custom loss functions. The paper explores several variants of Weighted Softmax Loss Functions, including Edge Penalty and Adaptive Weighted Softmax Loss, to address the challenges of class imbalance and the heightened importance of accurately classifying edge classes. Our findings reveal that these custom loss functions significantly reduce critical errors in classification without compromising the overall accuracy of the model. This research not only contributes to the field of industrial machine learning by providing a nuanced approach to loss function customization but also underscores the importance of context-specific adaptations in machine learning algorithms. The results showcase the potential of tailored loss functions in balancing precision and efficiency, ensuring reliable and effective machine learning solutions in industrial settings.
Determination of Topiramate and Carbamazepine in Plasma by Combined Dispersive Liquid–Liquid Microextraction and Gas Chromatography–Mass Spectrometry
Authors: Cabarcos-Fernández Pamela , Tabernero-Duque María Jesús , Álvarez-Freire Iván , Bermejo-Barrera Ana María
Published: February 2024

Dispersive liquid–liquid microextraction, an environmentally friendly extraction technique, followed by gas chromatography–mass spectrometry operating in selected ion monitoring (SIM) mode, is here presented for the simultaneous determination of two anticonvulsant drugs in plasma, Topiramate and Carbamazepine. Experimental parameters affecting the recovery of the proposed extraction method, such as the extraction and dispersion solvent, the extraction and dispersion volume, the sample amount, the pH of the aqueous phase, the ultrasound time, the centrifugation time and ionic strength, were investigated. The limits of detection for Topiramate and Carbamazepine were 0.01 and 0.025 µg mL−1, and the limits of quantification were 0.025 µg mL−1 and 0.05 µg mL−1, respectively. The method is shown to be selective, accurate, precise and linear over the concentration ranges of 0.025–8 µg mL−1 for Topiramate and 0.05–3 µg mL−1 for Carbamazepine. The extraction recovery of the analytes ranged from 91.5% to 113.9%. The analytical method was successfully applied to real plasma samples received by the Forensic Toxicology Service of the Forensic Science Institute of Santiago de Compostela.
Using Various Models for Predicting Soil Organic Carbon Based on DRIFT-FTIR and Chemical Analysis
Authors: Thabit Fatma N. , Negim Osama I. A. , AbdelRahman Mohamed A. E. , Scopa Antonio , Moursy Ali R. A.
Published: February 2024

Soil organic carbon (SOC) is a crucial factor influencing soil quality and fertility. In this particular investigation, we aimed to explore the possibility of using diffuse reflectance infrared fourier transform spectroscopy (DRIFT-FTIR) in conjunction with machine-learning models, such as partial least squares regression (PLSR), artificial neural networks (ANN), support vector regression (SVR) and random forest (RF), to estimate SOC in Sohag, Egypt. To achieve this, we collected a total of ninety surface soil samples from various locations in Sohag and estimated the total organic carbon content using both the Walkley-Black method and DRIFT-FTIR spectroscopy. Subsequently, we used the spectral data to develop regression models using PLSR, ANN, SVR, and RF. To evaluate the performance of these models, we used several evaluation parameters, including root mean square error (RMSE), coefficient of determination (R2), and ratio of performance deviation (RPD). Our survey results revealed that the PLSR model had the most favorable performance, yielding an R2 value of 0.82 and an RMSE of 0.006%. In contrast, the ANN, SVR, and RF models demonstrated moderate to poor performance, with R2 values of 0.53, 0.27, and 0.18, respectively. Overall, our study highlights the potential of combining DRIFT-FTIR spectroscopy with multivariate analysis techniques to predict SOC in Sohag, Egypt. However, additional studies and research are needed to improve the accuracy or predictability of machine-learning models incorporated into DRIFT-FTIR analysis and to compare DRIFT-FTIR analysis techniques with conventional soil chemical measurements.
Methodology for Modernizing Local Gas-Fired District Heating Systems into a Central District Heating System Using Gas-Fired Cogeneration Engines—A Case Study
Authors: Czajor Dawid , Amanowicz Łukasz
Published: February 2024

Sustainability can be achieved by improving process efficiency, among other methods. In the case of heat supply systems for cities, one of the ways to increase the efficiency of fuel use, and thus reduce resource consumption and greenhouse gas emissions, is the generation of heat and electricity in one process—the use of cogeneration (CHP). The main goal of this paper is to deliver the methodology for a step-by-step modernization process for local gas-fired heating plants through the use of gas cogeneration engines in common central district heating systems. The presented methodology was applied on the basis of a real system located in north-western Poland (case study from Białogard). The profitability of cogeneration was simulated against the background of changing gas prices. The financial and environmental profit from modernization was calculated. The technical requirements that had to be met in order to adapt the existing heating system to cooperation with the new energy source were also presented. The importance of selecting the supply and return temperature of water in the heating system after modernization was emphasized. Based on investment experience, we show that installing a cogeneration engine improves a company’s financial result by 33% (calculated as the difference between the revenue from the sale of energy and the cost of gas only) and is less harmful to the environment, among other benefits, significantly reducing CO2 emissions by 78%.
Digital Financial Inclusion and Innovation of MSMEs
Authors: Sun Jingwen , Zhang Jie
Published: February 2024

Digital inclusive finance is a new type of financial service that combines digital finance with inclusive finance. It is of great significance for improving the accessibility of financial services for small- and medium-sized enterprises and promoting their development. In this paper, we merge the Peking University Digital Financial Inclusion Index of China with the innovation data of micro-, small-, and medium-sized enterprises (MSMEs) from the National Bureau of Statistics, verify the facilitating effect of the development of digital financial inclusion on the technological innovation of MSMEs, and explain the mechanism of the influence of digital finance on the innovation of MSMEs from the perspective of alleviating financing constraints and promoting consumption. Digital inclusive finance has a promoting effect on the technological innovation of enterprises of different technological levels, but the support for high-tech enterprises is still insufficient. The heterogeneity analysis found that there are significant differences in the regional effects of digital financial inclusion; the central and western regions compared to the eastern region have better performance of digital inclusive finance to promote enterprise innovation.
Specifics of Creating a Public Transport Demand Model for Low-Density Regions: Lithuanian Case
Authors: Ranceva Justina , Ušpalytė-Vitkūnienė Rasa
Published: February 2024

A transport model usually consists of a demand model and an available transport network model. The purpose of this article is to identify the key specifics for the development of a regional public transport (PT) demand model and to point out the differences from the urban PT demand model. The traditional four-step transport planning demand model consists of trip generation, trip distribution, modal split, and assignment. This article consists of PT model development, calibration, and validation. A PTV VISUM macroscopic modeling program is used for this research. As a result, this article presents basic suggestions for how a PT demand model should be developed in regions. The presented suggestions for developing a PT demand model can be applied to any low-density region. The rest of the article is structured as follows: (1) Background: presents a literature analysis of the four-step model, modal splits, and the features of the PTV VISUM program; (2) Methods: describes the considered region of Lithuania and the data of the developed model; describes the four-step model, which is adapted to the Lithuanian region; (3) Results: presents the results and main suggestions for creating a PT demand model; and (4) Conclusions: presents the main conclusions of the study.