bluuebunny/crossref_metadata_2025 huggingface dataset:
Accurate Inner Profile Measurement of a High Aspect Ratio Aspheric Workpiece Using a Two-Probe Measuring System
Authors: Hu Peng , Xiong Xin , Zhang Wen-Hao , Ju Bing-Feng , Chen Yuan-Liu
Published: July 2022

This paper presents a novel method for inner profile measurement and geometric parameter evaluation, such as the radius of the bottom, steepness and straightness of the steep sidewall of a high aspect ratio aspheric workpiece, by utilizing a two-probe measuring system, which includes a lateral displacement gauge for the inner steep sidewall profile measurement and an axial displacement gauge for the inner deep underside profile measurement. To qualify the measurement accuracy, the systematic errors associated with the measurement procedure, including the miscalibration, misalignment and the roundness error of the gauge probes, as well as the slide motion error of the four-axis motion platform, are all evaluated and separated from the measurement results. A point cloud registration algorithm is employed to stitch the evaluated inner sidewall profile and the inner underside profile to form an entire inner profile of the workpiece. To verify the performance of the newly proposed method, the inner profile of a high aspect ratio aspheric workpiece, which has a tapered cone shape with a maximum inner radius of 40 mm, a maximum inner depth of 140 mm and a steep sidewall angle approaching 85°, is measured in experiments. The measurement result is compared with that of a coordinate measuring machine (CMM), and the comparison verifies the feasibility of the proposed measurement system.
Lean Screening for Greener Energy Consumption in Retrofitting a Residential Apartment Unit
Authors: Rousali Christina , Besseris George
Published: July 2022

Buildings consume a large portion of the global primary energy. They are also key contributors to CO2 emissions. Greener residential buildings are part of the ‘Renovation Wave’ in the European Green Deal. The purpose of this study was to explore the usefulness of energy consumption screening as a part of seeking retrofitting opportunities in the older residential building stock. The objective was to manage the screening of the electromechanical energy systems for an existing apartment unit. The parametrization was drawn upon inspection items in a comprehensive electronic checklist—part of an official software—in order to incur the energy certification status of a residential building. The extensive empirical parametrization intends to discover retrofitting options while offering a glimpse of the influence of the intervention costs on the final screening outcome. A supersaturated trial planner was implemented to drastically reduce the time and volume of the experiments. Matrix data analysis chart-based sectioning and general linear model regression seamlessly integrate into a simple lean-and-agile solver engine that coordinates the polyfactorial profiling of the joint multiple characteristics. The showcased study employed a 14-run 24-factor supersaturated scheme to organize the data collection of the performance of the energy consumption along with the intervention costs. It was found that the effects that influence the energy consumption may be slightly differentiated if intervention costs are also simultaneously considered. The four strong factors that influenced the energy consumption were the automation type for hot water, the types of heating and cooling systems, and the power of the cooling systems. An energy certification category rating of ‘B’ was achieved; thus, the original status (‘C’) was upgraded. The renovation profiling practically reduced the energy consumption by 47%. The concurrent screening of energy consumption and intervention costs detected five influential effects—the automation type for water heating, the automation control category, the heating systems type, the location of the heating system distribution network, and the efficiency of the water heating distribution network. The overall approach was shown to be simpler and even more accurate than other potentially competitive methods. The originality of this work lies in its rareness, worldwide criticality, and impact since it directly deals with the energy modernization of older residential units while promoting greener energy performance.
IA-Mask R-CNN: Improved Anchor Design Mask R-CNN for Surface Defect Detection of Automotive Engine Parts
Authors: Zhu Haijiang , Wang Yinchu , Fan Jiawei
Published: July 2022

The detection of surface defects on automotive engine parts is an important part of automobile manufacturing quality assurance. The traditional detection methods rely on manual inspection and can be inaccurate and inefficient, while the existing deep learning-based methods, such as the Mask R-CNN detection method, have insufficient precision for detecting minor defects since the anchor scales design does not consider small defects. To overcome these shortcomings, this paper proposes an IA-Mask R-CNN detection method with an improved anchor scales design. First, an image dataset that contains 560 pictures of surface defects of automotive engine parts is established using a 1080P HDMI high-definition digital microscope capable of recording three million real pixels and labeled manually. Then, the anchor scales suitable for the surface defect detection of automotive engine parts are determined by labeled data analysis and used to improve the anchor design in Mask R-CNN. Finally, the proposed method is compared experimentally with the Faster R-CNN and Mask R-CNN, and qualitative and quantitative analyses are conducted. The experimental results show that, without increasing the number of parameters or training time of the Mask R-CNN, the proposed method performed better in detecting minor, as well as larger defects than the other detection methods.
A Computer-Assisted Approach Regarding the Optimization of the Geometrical Planning of Medial Opening Wedge High Tibial Osteotomy
Authors: Cofaru Ileana Ioana , Oleksik Mihaela , Cofaru Nicolae Florin , Branescu Andrei Horia , Haşegan Adrian , Roman Mihai Dan , Fleaca Sorin Radu , Dobrotă Robert Daniel
Published: July 2022

Opening wedge high tibial osteotomy (OWHTO) is a surgical procedure often used to eliminate the effects of knee osteoarthritis, a disease that is becoming more widespread worldwide. Optimizing the geometric planning of this operation is a very important preparatory step for the success of the intervention and rapid postoperative recovery. This optimization is performed in two main directions. The first direction evaluates the intraoperative behavior of the tibia during the osteotomy by optimizing four geometric parameters that characterize geometric planning. The second direction aims at a postoperative evaluation of the flat tibia-osteosynthesis assembly taking into account the optimal position on the medial–lateral articular line through which the corrected mechanical axis of the tongue passes and implicitly offloads the transfer from the medial area to the side of the knee. The research methods used are exclusively computer-assisted such as: computer-aided design (hereinafter CAD) for geometric modeling of the tibia taking into account the real bone structure, the finite element method (hereinafter FEM) for performing numerical analyses and design of the experiment (hereinafter DOE) for the design of the research. The results obtained are eloquent and clearly presented and can be important elements for orthopedic doctors at the geometric planning stage of the OWHTO.
Performances of the Synergy of Silica Fume and Waste Glass Powder in Ternary Blended Concrete
Authors: Yusuf Moruf Olalekan , Al-Sodani Khaled A. Alawi , AlAteah Ali H. , Al-Tholaia Mohammed M. H. , Adewumi Adeshina A. , Bakare Azeez Oladipupo , Usman Abdullahi Kilaco , Momohjimoh Ibrahim
Published: July 2022

The quest to enhance public health and the need for a reduction in the environmental solid wastes have prompted this study. Despite abundant studies on silica fume (SF or S) and waste glass powder (WGP or G), there is a need to understand the interaction of WGP with SF in the production of ordinary Portland cement (OPC or C)-based concrete using the water/binder ratio of 0.42. The investigated concrete comprised 90 wt.% of OPC and 10 wt.% of WGP+SF. The samples were denoted as C90GxS10−x such that x varied from 0–10 wt.% at the interval of 2.5. The findings revealed that an increase in the WGP/SF ratio enhanced the absorption of silica/glass blended concrete due to size incompatibility and proliferations of interfacial transition zones between the glass particle, silica fume and cement matrix. The density of fresh OPC concrete was higher than that of glass/silica blended concrete due to the difference in their relative densities. Incorporating WGP and SF in synergy enhanced silicate reorganization and led to a more amorphous binder and a reduction in hydroxyl-based compounds such as portlandite but caused microstructural heterogeneity in the morphology of the binder as obtained from XRD, FTIR and SEM/EDS results. The 28-day compressive strength of 46 MPa is achievable if the WGP and SF are kept within 2.5–5 wt.% and 5–7.5 wt.%, respectively. The study will foster the production of economic, environmental, and cost-efficient concrete.
Interlocking Settlement Induced by Widening Subgrade of Railway Line
Authors: Kim Dae Sang , Kim Ungjin , Park Young Kon
Published: July 2022

In areas where it is difficult to secure additional land for railways, a plan to increase rail transport capacity by widening existing embankments is required. When widening the embankment, additional stress is generated at the bottom of the existing embankment, resulting in an additional settlement (interlocking settlement) of the existing embankment. Reinforced subgrade for railways (RSR) is an efficient method for widening embankments without additional sites. In this study, an existing railway embankment in operation was widened using the RSR, with the interlocking settlement evaluated and analyzed during and after construction. Results show that a widened embankment using RSR can secure train operation stability on existing tracks, even in ground conditions including shallow soft layers. The interlocking settlement was mainly affected by the backfill load and hardly affected by the wall load of the RSR. In addition, it was confirmed that the interlocking settlement mainly occurred in the backfill construction and stabilization period of RSR construction and converged early.
Navigation Path Extraction and Experimental Research of Pusher Robot Based on Binocular Vision
Authors: Tian Fuyang , Hu Guozheng , Yu Sufang , Wang Ruixue , Song Zhanhua , Yan Yinfa , Li Fade , Wang Zhonghua , Yu Zhenwei
Published: July 2022

The pushing robot working in the complex farming environment encounters several problems. For example, the precision of its navigation path extraction is low, and its working quality is greatly affected by the weather. In view of this, a method of farm operation path extraction based on machine vision is proposed in this study in order to solve the problems above and realize the autonomous and intelligent operation of the robot. First of all, the RGB images of the working area in front of the robot are obtained by using an RGB camera installed on the machine. Then, the collected images are preprocessed by means of sky removal, denoising and grayscale transformation. After that, the image is segmented to obtain the front fence, feed belt and ground data. Finally, the navigation path is obtained by extracting the features of the feed belt. The test results show that the absolute deviation of the pushing robot at different initial lateral distances is less than ±15 cm, and the deviation between the actual navigation route and the target route is within the expected range. The absolute value of the maximum lateral deviation in five test areas is 8.9 cm, and the absolute value of the average maximum lateral deviation is 7.6 cm. These experimental results show that the pushing robot can work stably without disturbing the feeding of cows. Particle swarm optimization is used to optimize the parameters of the PID and find the optimal parameters. This makes the system balanced and more responsive. Through this test, it is found that the initial direction of the robot will have a certain impact on the path production and tracking efficiency, and this effect is more significant when the robot changes the working area or turns. In which case, the trajectory of the robot should be in such a way that it immediately faces the next row at a small angular deviation, thus ensuring smoother motion. The method proposed in this study can provide support for the automatic navigation of pushing robots in dairy farms.
A High-Precision Transfer of Time and RF Frequency via the Fiber-Optic Link Based on Secure Encryption
Authors: Guo Xinxing , Qiu Yanfeng , Liu Bo , Kong Weicheng , Liu Tao , Dong Ruifang , Zhang Shougang
Published: July 2022

This paper presents a high-precision transfer system of time and RF frequency via the fiber optic link based on secure encryption. On the basis of the two-way time transfer of optical fiber, a security strategy composed of an SM2 encryption algorithm is introduced, which can resist the security risk of time information being tampered with. The experimental results show that the developed picosecond-precision fiber-optic time transfer equipment can ensure high stability while realizing the encryption function. Time synchronization stability in terms of time deviation (TDEV) of 1 PPS can reach around 10.7 ps at 1 s and 7.1 ps at 10 s averaging time. The stability of the 10 MHz frequency can reach around 4.7 × 10−12 at 1 s and 1.1 × 10−12 at 10 s averaging time. There is no significant difference in time transfer accuracy, compared with unencrypted conditions. Furthermore, this paper realizes a ring time transfer network via a 150 km fiber-optic link with three nodes using three devices. The TDEV of 1PPS can reach around 20.8 ps at 1s averaging time. This paper provides a reference to establish a high-precision, safe, and stable time synchronization fiber network in the future.
Short-Term Electrical Load Forecasting Based on VMD and GRU-TCN Hybrid Network
Authors: Cai Changchun , Li Yuanjia , Su Zhenghua , Zhu Tianqi , He Yaoyao
Published: July 2022

With the continuous increase in user-side flexible controllable resources connected into a distribution system, the components of electrical load become too diverse and difficult to be accuracy forecasted. A short-term load forecast method that integrates variational modal decomposition (VMD), gated recurrent unit (GRU) and time convolutional network (TCN) into a hybrid network is proposed in this paper. Firstly, original electrical load sequence data with noise are decomposed into intrinsic IMF components with different frequencies and amplitudes based on the VMD method. Secondly, a combined load forecasting method based on the GRU and TCN network is proposed for the high and low-frequency load subsequent signals, respectively. Finally, the high and low-frequency signals forecasting results of the GRU and TCN network are rebuilt for the final load forecasting. The experiment results based on actual operation data (data set 1) and simulation data (data set 2), which show that the proposed method can reduce the forecasting error by 36.20% and 10.8%, respectively, in comparison with VMD-GRU. The reliability and accuracy of the proposed method is verified through the comparison with other methods such as LSTM, Prophet and XG Boost.
Influence of Wake Intensity on the Unsteady Flow Characteristics of the Integrated Aggressive Interturbine Duct
Authors: Lei Zhijun , Liu Hongrui , Li Gang , Gong Jianbo , Zhang Yanfeng , Lu Xingen , Xu Gang , Zhu Junqiang
Published: July 2022

The interturbine transition duct (ITD), located between the high-pressure (HP) and low-pressure (LP) turbines of aeroengines, tends to be designed as an aggressive ITD integrated with wide-chord struts to meet the requirements of civil aeroengines for high bypass ratios and thrust–weight ratios. This paper presents a detailed unsteady numerical investigation of the effects of the HP rotor trailing-edge radius on the unsteady flow characteristics in the integrated aggressive interturbine transition duct (AITD), including the transport and dissipation of HP rotor wakes, the control mechanism of HP rotor wakes on flow separation and the influence of wake parameters. A sweeping rod, with a nondimensional diameter ranging from d/s = 0.056~0.143 (based on the pitch (s) of wide-chord struts at the midspan) and a reduced frequency (f) of 1.07, is used to simulate the HP rotor wake to decouple its influence from other secondary flows. Using the k-ω SST turbulence model and gamma–theta transition model, a structured grid with 6.3 million nodes can achieve similar global results. The wake in the lower part of the AITD channel dissipates rapidly because of the stretching between its own circumferential motion and the radial upward secondary flow, especially for a small d/s. Only the residual wake in the upper part can reach wide-chord struts in the case with large d/s. A sweeping rod with a large d/s can reduce the radial pressure gradient in the AITD, inhibit the internal secondary flow to a certain extent, reduce the dissipation rate of the wake, enhance its suppression effect on flow separation on a wide-chord strut, and decrease the flow loss. However, the wake can also enhance the passage vortex due to the increasing circumferential pressure gradient in the wide-chord strut channel, resulting in increasing blade profile loss. In the scope of this study, the aerodynamic gain of the wake is still not enough to compensate for its loss increment (including its own dissipation loss). Therefore, selecting a small trailing-edge radius of the HP rotor is conducive to improving the aerodynamic performance of the integrated AITD.
Salt-Induced Homogeneous Liquid–Liquid Microextraction of Piroxicam and Meloxicam from Human Urine Prior to Their Determination by HPLC-DAD
Authors: Manousi Natalia , Tsiona Sotiria V. , Zacharis Constantinos K.
Published: July 2022

A salt-induced homogeneous liquid–liquid microextraction (SI-HLLME) protocol combined with high-performance liquid chromatography–diode array detection is presented for the first time for the determination of piroxicam and meloxicam in human urine. The main parameters affecting the performance of the sample preparation protocol were optimized by means of a two-step experimental design (i.e., 2-level fractional factorial design and Box–Behnken design). Following its optimization, the proposed method was thoroughly validated in terms of the total error concept in order to take into consideration the random and systematic errors. For the target analytes, accuracy profiles were constructed, and they were used as graphical decision-making tools. In all cases, the β-expectation tolerance intervals complied with the acceptance criteria of ±15%, proving that 95% of future results will fall within the defined bias limits. The limits of detection were 0.02 μg mL−1 and 0.03 μg mL−1 for piroxicam and meloxicam, respectively. The relative standard deviations were lower than 4.4% in all cases, and the mean relative biases ranged between −5.7 and 3.4% for both drugs. The proposed scheme is simple and rapid, while it is characterized by high sample throughput. Moreover, SI-HLLME requires reduced sample and reagent consumption, according to the requirements of Green Analytical Chemistry.
A Genetic Programming Approach for Economic Forecasting with Survey Expectations
Authors: Claveria Oscar , Monte Enric , Torra Salvador
Published: July 2022

We apply a soft computing method to generate country-specific economic sentiment indicators that provide estimates of year-on-year GDP growth rates for 19 European economies. First, genetic programming is used to evolve business and consumer economic expectations to derive sentiment indicators for each country. To assess the performance of the proposed indicators, we first design a nowcasting experiment in which we recursively generate estimates of GDP at the end of each quarter, using the latest business and consumer survey data available. Second, we design a forecasting exercise in which we iteratively re-compute the sentiment indicators in each out-of-sample period. When evaluating the accuracy of the predictions obtained for different forecast horizons, we find that the evolved sentiment indicators outperform the time-series models used as a benchmark. These results show the potential of the proposed approach for prediction purposes.
A Switched Variational Estimation Algorithm for Continuous Discrete Measurement Information Loss in Underwater Navigation: Linear versus Nonlinear
Authors: Song Xiang , Huang Haoqian , Ren Chunxiao
Published: July 2022

In various applications of automatic underwater vehicles (AUVs), it is necessary to acquire the real-time location and speed information of the AUV. However, the complicated and fluctuating marine environment leads to measurement information loss. The accuracy of noise measurement is vital for accurate state estimation, but it is difficult for traditional algorithms to acquire time-varying noise measurements. Due to inaccurate process models and measurement noise, the filtering performance becomes poor or even diverges. To address the problems above, a switched variational estimation filtering (SVEF) algorithm, which combines the advantages of both Gaussian filtering and the variational estimation (VE) method, is proposed. In SVEF, VE is embedded into a linear or nonlinear filtering algorithm. Owing to the continuous discrete underwater navigation model, the state vector is estimated by the SVEF in the case of measurement information loss, and the accurate position and velocity of the AUV are determined. The experimental results prove that the SVEF achieves better positioning precision and is more robust than other conventional algorithms for AUV applications.
Special Issue of the Manufacturing Engineering Society—2021 (SIMES-2021)
Authors: Trujillo Francisco Javier , Rodríguez-Prieto Álvaro
Published: July 2022

After the complete success of the first [...]
Can There Be Such a Thing as a Sociology of Works of Art and Literary Texts? A Very French Epistemological Debate
Authors: Lévy Clara , Quemin Alain
Published: July 2022

Is it possible to undertake a sociological analysis of works of art? This article considers the arguments for both the negative and positive answers to this question that emerged in France in a vivid manner at the turn of the millennium. It examines the main arguments exchanged by the supporters and detractors of this sub-discipline of the sociology of art, notably those relating to the problem of interpretation (how does one verify this process sociologically when it is applied to a work of art?) and to the ways of presenting evidence. The discussion of these various arguments does not lead to the conclusion that it is impossible to explore heuristically the sociology of artworks in a pertinent way but to an insistence on heightened vigilance and to the formulation of certain principles for the use of sociologists who engage with such objects, if sometimes without the requisite caution.
An Application of Artificial Neural Network to Evaluate the Influence of Weather Conditions on the Variation of PM2.5-Bound Carbonaceous Compositions and Water-Soluble Ionic Species
Authors: Pongpiachan Siwatt , Wang Qiyuan , Apiratikul Ronbanchob , Tipmanee Danai , Li Yu , Xing Li , Li Guohui , Han Yongming , Cao Junji , Macatangay Ronald C. , Poshyachinda Saran , Aekakkararungroj Aekkapol , Hashmi Muhammad Zaffar
Published: July 2022

Previous studies have determined biomass burning as a major source of air pollutants in the ambient air in Thailand. To analyse the impacts of meteorological parameters on the variation of carbonaceous aerosols and water-soluble ionic species (WSIS), numerous statistical models, including a source apportionment analysis with the assistance of principal component analysis (PCA), hierarchical cluster analysis (HCA), and artificial neural networks (ANNs), were employed in this study. A total of 191 sets of PM2.5 samples were collected from the three monitoring stations in Chiang-Mai, Bangkok, and Phuket from July 2020 to June 2021. Hotspot numbers and other meteorological parameters were obtained using NOAA-20 weather satellites coupled with the Global Land Data Assimilation System. Although PCA revealed that crop residue burning and wildfires are the two main sources of PM2.5, ANNs highlighted the importance of wet deposition as the main depletion mechanism of particulate WSIS and carbonaceous aerosols. Additionally, Mg2+ and Ca2+ were deeply connected with albedo, plausibly owing to their strong hygroscopicity as the CCNs responsible for cloud formation.
Optimization Study of Sampling Device for Semi-Volatile Oil Mist in the Industrial Workshop
Authors: Wang Yukun , Long Zhengwei , Zhang Hongsheng , Shen Xiong , Yu Tao
Published: July 2022

A large number of metalworking fluids in industrial manufacturing processes generate high-concentrations of oil mist pollution, which is a typical semi-volatile aerosol and is generally composed of liquid particles and volatile gas components. Long-term exposure to oil mist pollution brings a series of occupational diseases to workers. For the semi-volatile aerosol, the traditional filter sampling method will lead to particle volatilization, which underestimates the concentration of particles and overestimates the concentration of gas. Therefore, this study combined the advantages of the electrostatic method and the Tenax tube adsorption method, to develop a more accurate measurement technology. First, a dichotomous sampler that could efficiently separate the gas and liquid phases of aerosols was optimized through a numerical model, which was validated by literature results. Next, a test table for oil mist sampling was built with a sampler which was fabricated by 3D printing, and the performance of the sampler was evaluated. The results show that the sampling technique can separate the gas and particulate phases of the oil mist efficiently and accurately. Compared with the traditional single sampling methods, the new sampler can better determine the true concentration of oil mist.
Strong-Field Ionization Amplitudes for Atomic Many-Electron Targets
Authors: Fritzsche Stephan , Böning Birger
Published: July 2022

The strong-field approximation (SFA) has been widely applied in the literature to model the ionization of atoms and molecules by intense laser pulses. A recent re-formulation of the SFA in terms of partial waves and spherical tensor operators helped adopt this approach to account for realistic atomic potentials and pulses of different shape and time structure. This re-formulation also enables one to overcome certain limitations of the original SFA formulation with regard to the representation of the initial-bound and final-continuum wave functions of the emitted electrons. We here show within the framework of Jac, the Jena Atomic Calculator, how the direct SFA ionization amplitude can be readily generated and utilized in order to compute above-threshold ionization (ATI) distributions for many-electron targets and laser pulses of given frequency, intensity, polarization, pulse duration and carrier–envelope phase. Examples are shown for selected ATI energy, angular as well as momentum distributions in the strong-field ionization of atomic krypton. We also briefly discuss how this approach can be extended to incorporate rescattering and high-harmonic processes into the SFA amplitudes.
Identification of Secondary Biomechanical Abnormalities in the Lower Limb Joints after Chronic Transtibial Amputation: A Proof-of-Concept Study Using SPM1D Analysis
Authors: Alhossary Amr , Ang Wei Tech , Chua Karen Sui Geok , Tay Matthew Rong Jie , Ong Poo Lee , Murakami Tsurayuki , Quake Tabitha , Binedell Trevor , Wee Seng Kwee , Phua Min Wee , Wei Yong Jia , Donnelly Cyril John
Published: July 2022

SPM is a statistical method of analysis of time-varying human movement gait signal, depending on the random field theory (RFT). MovementRx is our inhouse-developed decision-support system that depends on SPM1D Python implementation of the SPM (spm1d.org). We present the potential application of MovementRx in the prediction of increased joint forces with the possibility to predispose to osteoarthritis in a sample of post-surgical Transtibial Amputation (TTA) patients who were ambulant in the community. We captured the three-dimensional movement profile of 12 males with TTA and studied them using MovementRx, employing the SPM1D Python library to quantify the deviation(s) they have from our corresponding reference data, using “Hotelling 2” and “T test 2” statistics for the 3D movement vectors of the 3 main lower limb joints (hip, knee, and ankle) and their nine respective components (3 joints × 3 dimensions), respectively. MovementRx results visually demonstrated a clear distinction in the biomechanical recordings between TTA patients and a reference set of normal people (ABILITY data project), and variability within the TTA patients’ group enabled identification of those with an increased risk of developing osteoarthritis in the future. We conclude that MovementRx is a potential tool to detect increased specific joint forces with the ability to identify TTA survivors who may be at risk for osteoarthritis.
Anti-EpCAM Functionalized I-131 Radiolabeled Biomimetic Nanocarrier Sodium/Iodide-Symporter-Mediated Breast-Cancer Treatment
Authors: Marshall Suphalak Khamruang , Panrak Yada , Makchuchit Naritsara , Jaroenpakdee Passara , Saelim Boonyisa , Taweesap Maneerat , Pachana Verachai
Published: July 2022

Currently, breast-cancer treatment has a number of adverse side effects and is associated with poor rates of progression-free survival. Therefore, a radiolabeled anti-EpCAM targeted biomimetic coated nanocarrier (EINP) was developed in this study to overcome some of the treatment challenges. The double emulsion method synthesized the poly(lactic-co-glycolic acid) (PLGA) nanoparticle with Na131I entrapped in the core. The PLGA nanoparticle was coated in human red blood cell membranes and labeled with epithelial cell adhesion molecule (EpCAM) antibody to enable it to target EpCAM overexpression by breast-cancer cells. Characterization determined the EINP size as 295 nm, zeta potential as −35.9 mV, and polydispersity as 0.297. EINP radiochemical purity was >95%. Results determined the EINP efficacy against EpCAM positive MCF-7 breast cancer at 24, 48, and 72 h were 69.11%, 77.84%, and 74.6%, respectively, demonstrating that the EINPs achieved greater cytotoxic efficacy supported by NIS-mediated Na131I uptake than the non-targeted 131INPs and Na131I. In comparison, fibroblast (EpCAM negative) treated with EINPs had significantly lower cytotoxicity than Na131I and 131INPs (p < 0.05). Flow cytometry fluorescence imaging visually signified delivery by EINPs specifically to breast-cancer cells as a result of anti-EpCAM targeting. Additionally, the EINP had a favorable safety profile, as determined by hemolysis.
Predicting Protein–Protein Interactions Based on Ensemble Learning-Based Model from Protein Sequence
Authors: Zhan Xinke , Xiao Mang , You Zhuhong , Yan Chenggang , Guo Jianxin , Wang Liping , Sun Yaoqi , Shang Bingwan
Published: July 2022

Protein–protein interactions (PPIs) play an essential role in many biological cellular functions. However, it is still tedious and time-consuming to identify protein–protein interactions through traditional experimental methods. For this reason, it is imperative and necessary to develop a computational method for predicting PPIs efficiently. This paper explores a novel computational method for detecting PPIs from protein sequence, the approach which mainly adopts the feature extraction method: Locality Preserving Projections (LPP) and classifier: Rotation Forest (RF). Specifically, we first employ the Position Specific Scoring Matrix (PSSM), which can remain evolutionary information of biological for representing protein sequence efficiently. Then, the LPP descriptor is applied to extract feature vectors from PSSM. The feature vectors are fed into the RF to obtain the final results. The proposed method is applied to two datasets: Yeast and H. pylori, and obtained an average accuracy of 92.81% and 92.56%, respectively. We also compare it with K nearest neighbors (KNN) and support vector machine (SVM) to better evaluate the performance of the proposed method. In summary, all experimental results indicate that the proposed approach is stable and robust for predicting PPIs and promising to be a useful tool for proteomics research.
Potential Methods of Targeting Cellular Aging Hallmarks to Reverse Osteoarthritic Phenotype of Chondrocytes
Authors: He Yuchen , Lipa Katelyn E. , Alexander Peter G. , Clark Karen L. , Lin Hang
Published: July 2022

Osteoarthritis (OA) is a chronic degenerative joint disease that causes pain, physical disability, and life quality impairment. The pathophysiology of OA remains largely unclear, and currently no FDA-approved disease-modifying OA drugs (DMOADs) are available. As has been acknowledged, aging is the primary independent risk factor for OA, but the mechanisms underlying such a connection are not fully understood. In this review, we first revisit the changes in OA chondrocytes from the perspective of cellular hallmarks of aging. It is concluded that OA chondrocytes share many alterations similar to cellular aging. Next, based on the findings from studies on other cell types and diseases, we propose methods that can potentially reverse osteoarthritic phenotype of chondrocytes back to a healthier state. Lastly, current challenges and future perspectives are summarized.
Revealing the Microbiome of Four Different Thermal Springs in Turkey with Environmental DNA Metabarcoding
Authors: Çelik Işılay , Keskin Emre
Published: July 2022

One of the most significant challenges for detecting microbial life in thermal springs by conventional techniques such as culturing is these places’ physicochemical (temperature, heavy metal content, pH, etc.) conditions. Data from several studies suggest that high-throughput DNA sequencing technologies can be used to perform more accurate and detailed microbiome analyses. The primary aim of this paper was to determine the microbiome in the thermal source by metabarcoding environmental DNA isolated from four different sources and reveal the reflection of differences caused by temperature and chemical content on the microbiome. DNA was extracted from water filtered with enclosed filters and using the Illumina high-throughput sequencing platform, V3 and V4 regions of the 16S rRNA gene were sequenced. The results showed a correlation between physicochemical conditions and microorganism composition of four different thermal springs. Springs with extremely high temperature (89–90 °C) were dominated by hyperthermophiles such as Hydrogenobacter and Thermus, while a spring with a high temperature (52 °C) was dominated by thermophiles such as Thermoanaerobaculum and Desulfurispora, and a spring with a low temperature (26 °C) and high salinity was dominated by halophiles and sulfur-oxidizers such as Hydrogenovibrio and Sulfirimonas. With this research, we observed many manipulable steps according to the work of interest. This study sought to obtain data that will help decide the right gene region and choose the optimal bioinformatic pipeline.
Genetic Diagnosis in a Cohort of Adult Patients with Inherited Metabolic Diseases: A Single-Center Experience
Authors: Lenzini Livia , Carraro Gianni , Avogaro Angelo , Vitturi Nicola
Published: July 2022

Inherited metabolic diseases (IMDs) are genetic conditions that result in metabolism alterations. Although research-based Next Generation Sequencing (NGS) testing for IMD has been recently implemented, its application in a clinical diagnostic setting remains challenging. Thus, we aimed at investigating the genetic diagnostic approach in a cohort of adult patients with IMDs referred to our adult metabolic unit. A retrospective analysis was performed collecting demographic, clinical, and genetic data of patients referred to the Adult Metabolic Unit in Padua from November 2017 to March 2022. In total, 108 adult patients (mean age: 33 years ± 17, 55% women) were enrolled in the study, and 83 (77%) of the patients transitioned from the pediatric metabolic clinics. The most prevalent groups of IMDs were disorders of complex molecule degradation (32 patients) and disorders of amino acid metabolism (31) followed by disorders of carbohydrates (26). Molecular genetic diagnosis was reported by 69 (64%) patients, with the higher rate reported by patients referred from specialty other than pediatric (88% vs. 55%). Almost all the subjects (92%) with disorders of complex molecule degradation had a genetic diagnosis. Patients with disorders of amino acid metabolism and disorders of carbohydrates had almost the same rate of genetic test (39% and 38%, respectively). Among the patients without a genetic diagnosis that we tested, two novel mutations in disease-associated genes were detected. In our single-center cohort, a consistent proportion (36%) of subjects with IMDs reaches the adulthood without a genetic demonstration of the disease. This lack, even if in some cases could be related to disease-specific diagnostic approach or to different disease onset, could be detrimental to patient management and impact to some of the specific needs of adult subjects.
Monoterpenes as Sirtuin-1 Activators: Therapeutic Potential in Aging and Related Diseases
Authors: Sousa Cátia , Mendes Alexandrina Ferreira
Published: July 2022

Sirtuin 1 (SIRT) is a class III, NAD+-dependent histone deacetylase that also modulates the activity of numerous non-histone proteins through deacylation. SIRT1 plays critical roles in regulating and integrating cellular energy metabolism, response to stress, and circadian rhythm by modulating epigenetic and transcriptional regulation, mitochondrial homeostasis, proteostasis, telomere maintenance, inflammation, and the response to hypoxia. SIRT1 expression and activity decrease with aging, and enhancing its activity extends life span in various organisms, including mammals, and improves many age-related diseases, including cancer, metabolic, cardiovascular, neurodegenerative, respiratory, musculoskeletal, and renal diseases, but the opposite, that is, aggravation of various diseases, such as some cancers and neurodegenerative diseases, has also been reported. Accordingly, many natural and synthetic SIRT1 activators and inhibitors have been developed. Known SIRT1 activators of natural origin are mainly polyphenols. Nonetheless, various classes of non-polyphenolic monoterpenoids have been identified as inducers of SIRT1 expression and/or activity. This narrative review discusses current information on the evidence that supports the role of those compounds as SIRT1 activators and their potential both as tools for research and as pharmaceuticals for therapeutic application in age-related diseases.
MicroRNA-138-5p Targets Pro-Apoptotic Factors and Favors Neural Cell Survival: Analysis in the Injured Spinal Cord
Authors: Maza Rodrigo M. , Barreda-Manso María Asunción , Reigada David , Silván Ágata , Muñoz-Galdeano Teresa , Soto Altea , del Águila Ángela , Nieto-Díaz Manuel
Published: July 2022

The central nervous system microRNA miR-138-5p has attracted much attention in cancer research because it inhibits pro-apoptotic genes including CASP3. We hypothesize that miR-138-5p downregulation after SCI leads to overexpression of pro-apoptotic genes, sensitizing neural cells to noxious stimuli. This study aimed to identify miR-138-5p targets among pro-apoptotic genes overexpressed following SCI and to confirm that miR-138-5p modulates cell death in neural cells. Gene expression and histological analyses revealed that the drop in miR-138-5p expression after SCI is due to the massive loss of neurons and oligodendrocytes and its downregulation in neurons. Computational analyses identified 176 potential targets of miR-138-5p becoming dysregulated after SCI, including apoptotic proteins CASP-3 and CASP-7, and BAK. Reporter, RT-qPCR, and immunoblot assays in neural cell cultures confirmed that miR-138-5p targets their 3′UTRs, reduces their expression and the enzymatic activity of CASP-3 and CASP-7, and protects cells from apoptotic stimuli. Subsequent RT-qPCR and histological analyses in a rat model of SCI revealed that miR-138-5p downregulation correlates with the overexpression of its pro-apoptotic targets. Our results suggest that the downregulation of miR-138-5p after SCI may have deleterious effects on neural cells, particularly on spinal neurons.
Bacterial and Viral Infections in Liver Transplantation: New Insights from Clinical and Surgical Perspectives
Authors: Shbaklo Nour , Tandoi Francesco , Lupia Tommaso , Corcione Silvia , Romagnoli Renato , De Rosa Francesco Giuseppe
Published: July 2022

End-stage liver disease patients undergoing liver transplantation are prone to develop numerous infectious complications because of immunosuppression, surgical interventions, and malnutrition. Infections in transplant recipients account for the main cause of mortality and morbidity with rates of up to 80%. The challenges faced in the early post-transplant period tend to be linked to transplant procedures and nosocomial infections commonly in bloodstream, surgical, and intra-abdominal sites. Viral infections represent an additional complication of immunosuppression; they can be donor-derived, reactivated from a latent virus, nosocomial or community-acquired. Bacterial and viral infections in solid organ transplantation are managed by prophylaxis, multi-drug resistant screening, risk assessment, vaccination, infection control and antimicrobial stewardship. The aim of this review was to discuss the epidemiology of bacterial and viral infections in liver transplants, infection control issues, as well as surgical frontiers of ex situ liver perfusion.
Clinical Significance of Preoperative Hematological Parameters in Patients with D2-Resected, Node-Positive Stomach Cancer
Authors: Park Jun Su , Yu Jeong Il , Lim Do Hoon , Nam Heerim , Kim Young Il , Lee Jeeyun , Kang Won Ki , Park Se Hoon , Kim Seung Tae , Hong Jung Yong , Sohn Tae Sung , Lee Jun Ho , An Ji Yeong , Choi Min Gew , Bae Jae Moon
Published: July 2022

The purpose of the present study was to investigate the clinical significance of preoperative hematological parameters in patients with advanced stomach cancer, and to explore who might benefit from adjuvant concurrent chemoradiotherapy (CCRT) compared to chemotherapy alone. Among 1032 patients with node-positive stomach cancer who had a confirmed diagnosis after complete D2 resection, and who received adjuvant chemotherapy alone or CCRT, a total of 692 patients was selected using propensity score matching. Among absolute neutrophil count, absolute lymphocyte count (ALC), absolute monocyte count (AMC), platelet count, neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and platelet-to-lymphocyte ratio, AMC was the most relevant prognostic factor for overall survival and recurrence-free survival (hazard ratio (HR) 1.674, 95% confidence interval (CI) 1.180–2.376; HR 1.908, 95% CI 1.650–2.695, respectively). In a subgroup with a high ALC, patients treated with adjuvant CCRT had a favorable recurrence-free survival (HR 0.620, 95% CI 0.393–0.980) compared to those treated with chemotherapy alone. Further study is needed to confirm our findings and to develop tailored adjuvant treatment.
Wearable Fetal ECG Monitoring System from Abdominal Electrocardiography Recording
Authors: Zhang Yuwei , Gu Aihua , Xiao Zhijun , Xing Yantao , Yang Chenxi , Li Jianqing , Liu Chengyu
Published: July 2022

Fetal electrocardiography (ECG) monitoring during pregnancy can provide crucial information for assessing the fetus’s health status and making timely decisions. This paper proposes a portable ECG monitoring system to record the abdominal ECG (AECG) of the pregnant woman, comprising both maternal ECG (MECG) and fetal ECG (FECG), which could be applied to fetal heart rate (FHR) monitoring at the home setting. The ECG monitoring system is based on data acquisition circuits, data transmission module, and signal analysis platform, which consists of low input-referred noise, high input impedance, and high resolution. The combination of the adaptive dual threshold (ADT) and the independent component analysis (ICA) algorithm is employed to extract the FECG from the AECG signals. To validate the performance of the proposed system, AECG is recorded and analyzed of pregnant women in three different postures (supine, seated, and standing). The result shows that the proposed system can record the AECG in different postures with good signal quality and high accuracy in fetal ECG and heart rate information. Sensitivity (Se), positive predictive accuracy (PPV), accuracy (ACC), and their harmonic mean (F1) are utilized as the metrics to evaluate the performance of the fetal QRS (fQRS) complexes extraction. The average Se, PPV, ACC, and F1 score are 99.62%, 97.90%, 97.40%, and 98.66% for the fQRS complexes extraction,, respectively. This paper shows the proposed system has a promising application in fetal health monitoring.
Biofilm Detection by a Fiber-Tip Ball Resonator Optical Fiber Sensor
Authors: Rakhimbekova Aida , Kudaibergenov Baizak , Moldabay Damir , Zharylgap Albina , Ajunwa Obinna M. , Marsili Enrico , Tosi Daniele
Published: July 2022

Bacterial biofilms are one of the most important challenges that modern medicine faces due to the difficulties of diagnosis, antibiotic resistance, and protective mechanisms against aggressive environments. For these reasons, methods that ensure the inexpensive and rapid or real-time detection of biofilm formation on medical devices are needed. This study examines the possibilities of using optical- and fiber-based biosensors to detect and analyze early bacterial biofilms. In this study, the biofilm-forming model organism Pseudomonas aeruginosa was inoculated on the surface of the optical sensor and allowed to attach for 2 h. The biosensors were made by a fiber-tip ball resonator, fabricated through a CO2 laser splicer on a single-mode fiber, forming a weak reflective spectrum. An optical backscatter reflectometer was used to measure the refractive index detected by the sensors during different growth periods. The early biofilm concentration was determined by crystal violet (CV) binding assay; however, such a concentration was lower than the detection limit of this assay. This work presents a new approach of biofilm sensing in the early attachment stage with a low limit of detection up to 10−4 RIU (refractive index units) or 35 ± 20 × 103 CFU/mL (colony formed units).
Cardiovascular Diseases in the Digital Health Era: A Translational Approach from the Lab to the Clinic
Authors: Sánchez de la Nava Ana María , Gómez-Cid Lidia , Ríos-Muñoz Gonzalo Ricardo , Fernández-Santos María Eugenia , Fernández Ana I. , Arenal Ángel , Sanz-Ruiz Ricardo , Grigorian-Shamagian Lilian , Atienza Felipe , Fernández-Avilés Francisco
Published: July 2022

Translational science has been introduced as the nexus among the scientific and the clinical field, which allows researchers to provide and demonstrate that the evidence-based research can connect the gaps present between basic and clinical levels. This type of research has played a major role in the field of cardiovascular diseases, where the main objective has been to identify and transfer potential treatments identified at preclinical stages into clinical practice. This transfer has been enhanced by the intromission of digital health solutions into both basic research and clinical scenarios. This review aimed to identify and summarize the most important translational advances in the last years in the cardiovascular field together with the potential challenges that still remain in basic research, clinical scenarios, and regulatory agencies.