bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of the efficacy of Biejia decoction pill combined with entecavir in the treatment of hepatitis B liver fibrosis/cirrhosis by VCTE
Authors: Wan Lijun , Hu Chungen , Wang Fenfen , Xu Kedong , Li Fan , He Bo , Wu Zhengqiang , Luo Linfei , Wen Zhili 
Published: November 2023

AbstractThe vibration controlled transient elastography (VCTE) technique was used to assess the effectiveness of a Biejia Decoction pill in combination with Entecavir in the treatment of hepatitis B liver fibrosis/cirrhosis. We randomly selected 120 patients to receive entecavir and 119 patients to receive both entecavir and Biejia Decoction Pill, which both with hepatitis B liver fibrosis/cirrhosis visited the Second Affiliated Hospital of Nanchang University between January 2019 and February 2022. The observation group got ETV (entecavir) and Biejia Decoction pills, whereas the control group received only standard ETV antiviral medication. Based on the grading of the VCTE detection value (LSM) initially diagnosed for patients with hepatitis B liver fibrosis/cirrhosis, we divided the patients into two subgroups of liver fibrosis and cirrhosis. In addition, patients with liver fibrosis were divided into mild and moderate subgroups according to their VCTE values. Patients were measured for liver hardness after three, six, nine, and twelve months of treatment with VCTE. Biejia Decoction Pill combined with ETV on HBV liver fibrosis/cirrhosis was evaluated by comparing patients' changes in liver hardness and HBV-DNA negative conversion rates before and after treatment in each group at the same baseline. The LSM (liver elasticity value) of the observation group and the control group after treatment was lower than that before treatment, and the difference was statistically significant (P < 0.0001); The LSM of the observation group after treatment was significantly lower than that of the control group, and the difference was also statistically significant (P = 0.0005 < 0.05). In the subgroup of liver fibrosis, the number of patients with moderate and severe liver fibrosis who completely reversed liver fibrosis after treatment in the treatment group was far more than that in the control group, and the difference between the two groups was statistically significant (χ2 = 4.82 P = 0.028 < 0.05) 。 When the treatment course was more than 9 months, the negative conversion rate of patients in the observation group reached 87.4%, which was higher than that in the control group (70.8%), and the difference was statistically significant (P = 0.002 < 0.05); After 12 months of treatment, the negative conversion rate of patients in the observation group was as high as 95%, which was significantly higher than 76.67% in the control group (P < 0.001). The degree of liver fibrosis was significantly improved when Biejia Decoction Pill was combined with ETV in patients with liver fibrosis/cirrhosis due to hepatitis B. The virological response rate to HBV-DNA increased with the prolongation of treatment, and the Biejia Decoction Pill assists with entecavir in antiviral therapy.
Efficacy of alumina nanoparticles as a controllable tool for mortality and biochemical parameters of Culex pipiens
Authors: El‑Barkey Nehad M. , Nassar Mostafa Y. , El‑Khawaga Aya H. , Kamel Aida S. , Baz Mohamed M. 
Published: November 2023

AbstractMosquitoes still pose a clear risk to human and animal health. Recently, nanomaterials have been considered one of the cost-effective solutions to this problem. Therefore, alumina nanoparticles (Al) were synthesized using an auto-combustion method, followed by calcination at 600 and 800 °C. Glucose (G) and sucrose (Su) were used as fuels and the combustion was performed at pH 2, 7, and 10. The as-synthesized Al2O3 nanoparticles were characterized by XRD, FTIR, SEM, and TEM. Alumina nanoparticles prepared using G and Su fuels at pH 7 and 800 °C (Al-G7-800 and Al-Su7-800) have crystallite sizes of 3.9 and 4.05 nm, respectively. While the samples (Al-G7-600 and Al-Su7-600) synthesized at pH 7 and 600 °C were amorphous. The prepared alumina nanoparticles were applied to the larval and pupal stages of Culex pipiens. The results showed that alumina nanoparticles cause higher mortality in the 1st larval instar than in all other larval instars and pupal stages of Culex pipiens after treatment at a high concentration of 200 ppm. Additionally, the larval duration after treatment with LC50 concentrations of alumina (Al-G7-800 and Al-Su7-800) was 31.7 and 23.6 days, respectively, compared to the control (13.3 days). The recorded data found that the content of glutathione-S-transferase, alkaline/acid phosphatase, β/α-esterase, and total protein were altered upon treatment with the LC50 concentration of alumina (Al-G7-800) nanoparticles. Based on these findings, alumina nanoparticles are a promising candidate as a potential weapon to control pests and mosquitoes.
Deep learning approach for denoising low-SNR correlation plenoptic images
Authors: Scattarella Francesco , Diacono Domenico , Monaco Alfonso , Amoroso Nicola , Bellantuono Loredana , Massaro Gianlorenzo , Pepe Francesco V. , Tangaro Sabina , Bellotti Roberto , D’Angelo Milena 
Published: November 2023

AbstractCorrelation Plenoptic Imaging (CPI) is a novel volumetric imaging technique that uses two sensors and the spatio-temporal correlations of light to detect both the spatial distribution and the direction of light. This novel approach to plenoptic imaging enables refocusing and 3D imaging with significant enhancement of both resolution and depth of field. However, CPI is generally slower than conventional approaches due to the need to acquire sufficient statistics for measuring correlations with an acceptable signal-to-noise ratio (SNR). We address this issue by implementing a Deep Learning application to improve image quality with undersampled frame statistics. We employ a set of experimental images reconstructed by a standard CPI architecture, at three different sampling ratios, and use it to feed a CNN model pre-trained through the transfer learning paradigm U-Net architecture with VGG-19 net for the encoding part. We find that our model reaches a Structural Similarity (SSIM) index value close to 1 both for the test sample (SSIM = $$0.87 \pm 0.02$$

0.87
±
0.02

) and in 5-fold cross validation (SSIM = $$0.92 \pm 0.07$$

0.92
±
0.07

); the results are also shown to outperform classic denoising methods, in particular for images with lower SNR. The proposed work represents the first application of Artificial Intelligence in the field of CPI and demonstrates its high potential: speeding-up the acquisition by a factor 20 over the fastest CPI so far demonstrated, enabling recording potentially 200 volumetric images per second. The presented results open the way to scanning-free real-time volumetric imaging at video rate, which is expected to achieve a substantial influence in various applications scenarios, from monitoring neuronal activity to machine vision and security.
Comparison of the optical behaviour of five different multifocal diffractive intraocular lenses in a model eye
Authors: Can Efe , Senel Esat Can , Holmström Sven T. S. , Piñero David P. 
Published: November 2023

AbstractThe purpose of this study was to investigate and compare the optical performance of five trifocal intraocular lenses (IOLs) following the ISO 11979-2 standards, analysing the impact of tilt and decentration. Five different diffractive trifocal IOLs were evaluated in this experimental study: Acriva Trinova (VSY-Biotechnology) (AT), FineVision HP (PhysIOL) (FVHP), AT LISA tri 839 MP (Zeiss) (ATLT), PanOptix TFNT00 IOL (Alcon) (PO), and Tecnis Synergy (J&J Vision) (TS). In-vitro optical quality analysis of them was performed with the Lambda PMTF system that has an aberration neutral cornea model (Lambda-X Ophthalmics). Measurements were performed on-axis, with 5º of IOL tilt and with 0.5 mm of IOL decentration using 543-nm monochromatic light. Finally, IOL dimensions and diffractive disk profile inspection was performed using the VisIOLA system (Rotlex). On-axis measurements showed a far through-focus MTF > 0.3 at 3 mm aperture, except for TS. FVHP and PO showed better far MTFs for larger apertures (3.75 mm and 4.5 mm) while AT showed good intermediate and near vision for such apertures. With 5º of IOL tilt, the better optical performance at all distances was found with AT for medium-sized pupils (3 mm) and an important reduction of MTF was found for ATLT and PO, especially in the intermediate focus. The induction of 0.5 mm of IOL decentration especially affected the intermediate focus of ATLT and TS and the far focus of FVHP and PO. IOL dimensions and diffractive profile were consistent with those described by the manufacturer. In conclusion, there are differences in the optical performance according to the pupil aperture of the five trifocal IOLs evaluated and this should be considered in clinical practice when selecting the most appropriate implant in each specific case. IOL tilt and decentration can affect significantly in most of the designs evaluated the performance of the IOL at intermediate vision range. It should be noted that measurements were made with an aberration-free cornea, being necessary future studies analysing the impact of different levels of corneal aberrations.
Mining cancer genomes for change-of-metabolic-function mutations
Authors: Tu Kevin J. , Diplas Bill H. , Regal Joshua A. , Waitkus Matthew S. , Pirozzi Christopher J. , Reitman Zachary J. 
Published: November 2023

AbstractEnzymes with novel functions are needed to enable new organic synthesis techniques. Drawing inspiration from gain-of-function cancer mutations that functionally alter proteins and affect cellular metabolism, we developed METIS (Mutated Enzymes from Tumors In silicoScreen). METIS identifies metabolism-altering cancer mutations using mutation recurrence rates and protein structure. We used METIS to screen 298,517 cancer mutations and identify 48 candidate mutations, including those previously identified to alter enzymatic function. Unbiased metabolomic profiling of cells exogenously expressing a candidate mutant (OGDHLp.A400T) supports an altered phenotype that boosts in vitro production of xanthosine, a pharmacologically useful chemical that is currently produced using unsustainable, water-intensive methods. We then applied METIS to 49 million cancer mutations, yielding a refined set of candidates that may impart novel enzymatic functions or contribute to tumor progression. Thus, METIS can be used to identify and catalog potentially-useful cancer mutations for green chemistry and therapeutic applications.
Repeated multi-domain cognitive training prevents cognitive decline, anxiety and amyloid pathology found in a mouse model of Alzheimer disease
Authors: Mehla Jogender , Deibel Scott H. , Karem Hadil , Hong Nancy S. , Hossain Shakhawat R. , Lacoursiere Sean G. , Sutherland Robert J. , Mohajerani Majid H. , McDonald Robert J. 
Published: November 2023

AbstractEducation, occupation, and an active lifestyle, comprising enhanced social, physical, and mental components are associated with improved cognitive functions in aged people and may delay the progression of various neurodegenerative diseases including Alzheimer’s disease. To investigate this protective effect, 3-month-old APPNL-G-F/NL-G-F mice were exposed to repeated single- or multi-domain cognitive training. Cognitive training was given at the age of 3, 6, & 9 months. Single-domain cognitive training was limited to a spatial navigation task. Multi-domain cognitive training consisted of a spatial navigation task, object recognition, and fear conditioning. At the age of 12 months, behavioral tests were completed for all groups. Then, mice were sacrificed, and their brains were assessed for pathology. APPNL-G-F/NL-G-F mice given multi-domain cognitive training compared to APPNL-G-F/NL-G-F control group showed an improvement in cognitive functions, reductions in amyloid load and microgliosis, and a preservation of cholinergic function. Additionally, multi-domain cognitive training improved anxiety in APPNL-G-F/NL-G-F mice as evidenced by measuring thigmotaxis behavior in the Morris water maze. There were mild reductions in microgliosis in the brain of APPNL-G-F/NL-G-F mice with single-domain cognitive training. These findings provide causal evidence for the potential of certain forms of cognitive training to mitigate the cognitive deficits in Alzheimer disease.
Enhancing alphafold-multimer-based protein complex structure prediction with MULTICOM in CASP15
Authors: Liu Jian , Guo Zhiye , Wu Tianqi , Roy Raj S. , Quadir Farhan , Chen Chen , Cheng Jianlin 
Published: November 2023

AbstractTo enhance the AlphaFold-Multimer-based protein complex structure prediction, we developed a quaternary structure prediction system (MULTICOM) to improve the input fed to AlphaFold-Multimer and evaluate and refine its outputs. MULTICOM samples diverse multiple sequence alignments (MSAs) and templates for AlphaFold-Multimer to generate structural predictions by using both traditional sequence alignments and Foldseek-based structure alignments, ranks structural predictions through multiple complementary metrics, and refines the structural predictions via a Foldseek structure alignment-based refinement method. The MULTICOM system with different implementations was blindly tested in the assembly structure prediction in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 as both server and human predictors. MULTICOM_qa ranked 3rd among 26 CASP15 server predictors and MULTICOM_human ranked 7th among 87 CASP15 server and human predictors. The average TM-score of the first predictions submitted by MULTICOM_qa for CASP15 assembly targets is ~0.76, 5.3% higher than ~0.72 of the standard AlphaFold-Multimer. The average TM-score of the best of top 5 predictions submitted by MULTICOM_qa is ~0.80, about 8% higher than ~0.74 of the standard AlphaFold-Multimer. Moreover, the Foldseek Structure Alignment-based Multimer structure Generation (FSAMG) method outperforms the widely used sequence alignment-based multimer structure generation.
Equivalence of knife‐edge diffraction model and uniform geometrical theory of diffraction applying Fresnel approximation for an absorbing screen
Authors: Du Xin , Takada Jun‐ichi 
Published: November 2023

AbstractThe knife‐edge diffraction model (KED) and the uniform geometrical theory of diffraction (UTD) have been widely used to predict the shadowing effect at millimetre‐wave (mmWave) bands. This letter proposes a mathematical derivation to rigorously prove that, for an absorbing screen, UTD applying the narrow‐angle Fresnel approximation is equivalent to KED. The simulation scenarios are designed to validate the proposal by comparing KED with UTD in the narrow‐angle (less than 20°) and wide‐angle (over 20°) regions at mmWave bands (20100 GHz). Simulated results agree with the proposal that KED is identical to UTD with a low error of less than 0.1 dB in the narrow‐angle region, while they have a difference with an error of over 1 dB in the wide‐angle region. In addition, the average computational time is measured and results in both UTD and KED taking approximately 8.0 ms for one test. From the proposal, it can be theoretically explained the differences and similarities between KED and UTD for an absorbing screen.
Towards low‐complexity state estimation for rigid bodies based on range difference measurements
Authors: Wang Yuwei , Sun Peng , Wang Zhi 
Published: November 2023

AbstractThe rigid body localization (RBL) technique is capable of estimating the state of a rigid body, including its translation and orientation, by utilizing the interactions between sensors and landmarks. The prevalent RBL methods employ precise time‐of‐flight measurements (or range measurements) to estimate the state. However, the clock offsets in range measurements in asynchronous networks are unavoidable, leading to performance degradation for state estimators. Therefore, range difference measurements have been adopted to solve the RBL problem. However, existing approaches struggle to achieve desirable performance while maintaining computational efficiency. To address this issue, a new closed‐form state estimator for asynchronous networks is introduced. The proposed algorithm leverages the Taylor‐series expansion technique to enhance accuracy while keeping computational overhead low. Numerical experiments demonstrate that the proposed method achieves state‐of‐the‐art performance with high computational efficiency under small Gaussian noises.
A compact differential branch‐line coupler using folded substrate integrated suspended parallel strip line
Authors: Shen Huajiao , Wang Yongqiang , Meng Fanyi , Ma Kaixue 
Published: November 2023

AbstractThis letter presents a compact fully differential branch‐line coupler. It is composed of folded substrate integrated suspended parallel strip line (SISPSL), which can generate slow‐wave effect and help reduce the circuit size. The used SISPSL type line is a fusion of double‐sided parallel‐strip line (DSPSL) and substrate integrated suspended line (SISL), which has the advantage of self‐packaging as compared with traditional DSPSL exposed to air. A DC to 30‐GHz differential transition from grounded coplanar waveguide (GCPW) to SISPSL is designed to test the SISPSL differential coupler. The implemented SISPSL branch‐line coupler has a compact size of 0.056 λg × 0.05 λg.
Additive margin networks with adaptive feature recalibration and its applications in Brain Stroke CT Image classification
Authors: Gao Qinling , Fu Hao , Zhao Xuejing , Ge Zhaoming 
Published: November 2023

AbstractIn this paper, an additive margin network with adaptive feature recalibration, AMNets, for handling a wide range of visual tasks, is proposed. The new AMNets consists of three improvements on convolutional neural networks: (1) squeeze‐and‐excitation mechanism was embedded into the the residual block of single layer to improve the performance of the classification, (2) softmax loss was replaced by the additive margin softmax loss to minimize intra‐class variance and maximize inter‐class variance, and (3) Adam optimizer was exploited to update iteratively the network parameters. Experiments on the Brain Stroke CT Image Dataset show that our additive margin network is quite effective to improve state‐of‐the‐art algorithms.
An improved acoustic transponder system via LCCLC impedance matching network and equalization control strategy
Authors: Yang Chunyuan , Zhang Shuhao , Wang Lei , Tian Wei , Zou Jie , Yang Chi , Lin Zehua 
Published: November 2023

AbstractThe underwater acoustic transducer (UAT) generates a large amount of reactive power during the operation, greatly limiting the output capability of the power amplifier. It is necessary to match the UAT and improve its load characteristics. The conventional design methods are not powerful enough to solve nonlinear or parameter‐sensitive problems, lacking enough convergence ability for the network design problem. This article proposes an optimization design method for LCCLC impedance matching network based on the improved chaos optimization algorithm and the corresponding equalization control strategy. First, the impedance model of the UAT is proposed, and then the matching principle of the LCCLC network is analyzed. Based on these, the optimization design for LCCLC network is described in detail. Then, to solve the problem of the calculation of the command signal, a control method based on the FIR filter principle is proposed. Finally, the proposed methods are verified by an experimental platform. The results show that the proposed design method and its corresponding control strategy successfully solve the matching and emission problems.
Monocular‐based collision avoidance system for unmanned aerial vehicle
Authors: Javaid Abdulrahman , Alduais Asaad , Shullar M. Hashem , Baroudi Uthman , Alnaser Mustafa 
Published: November 2023

AbstractObstacle avoidance based on a monocular camera is a challenging task due to the lack of 3D information for Unmanned Aerial Vehicle. Recent methods based on Convolutional Neural Networks for monocular depth estimation and obstacle detection become widely used. However, collision avoidance with depth estimation usually suffers from long computational time and low avoidance success rate. A new collision avoidance system is proposed which uses monocular camera and intelligent algorithm to avoid obstacles on real time processing. Several experiments have been conducted on crowded environments with several object types. The results show outstanding performance in terms of obstacles avoidance and system response time compared to contemporary approaches. This makes the proposed approach of high potential to be integrated in crowded environments.
Placentites ascendantes et non-ascendantes chez la jument : cas cliniques
Authors: Renaudin Catherine D. , Schnobrich Maria 
Published: November 2023

Les placentites représentent la cause la plus importante d’avortement d’origine infectieuse chez la jument. Elles sont, dans la plupart des cas, d’origine ascendante (infection par voie cervicale) mais peuvent aussi être d’origine non-ascendante (infection par voie hématogène des leptospires ou des bactéries du genre Nocardia). Dans cet article, nous décrivons quatre cas cliniques de placentites. Deux sont d’origine ascendante : une est traitée avec succès et l’autre est suivie d’un avortement. Les deux autres sont d’origine non-ascendante : l’une est une placentite due aux bactéries du genre Leptopsira et l’autre aux bactéries du genre Nocardia. Les signes cliniques, le diagnostic par échographie transrectal et transabdominal, le traitement et le devenir de chaque cas sont décrits en détail de façon à donner une conduire à tenir au praticien équin face à un cas de placentite.
Stationsäquivalente Behandlung (StäB) im Vergleich
mit vollstationärer Behandlung: 12-Monats-Follow-up Ergebnisse einer
mittels Propensity-Score gematchten retrospektiven
Kohortenstudie.
Authors: Nikolaidis Konstantinos , Weinmann Stefan , Döring Sophia , Fischer Lasse , Kleinschmidt Martin , Pfeiffer Jan , Multamäki Sari , Bühling-Schindowski Felix , Timm Jürgen , Bechdolf Andreas 
Published: November 2023

Zusammenfassung
Ziel der Studie Untersuchung der stationsäquivalenten
psychiatrischen Behandlung (StäB) im Vergleich zur
vollstationären psychiatrischen Behandlung hinsichtlich der
Inanspruchnahme psychiatrischer Leistungen im 12-Monats-Follow-Up-Zeitraum.
Methodik In einer retrospektiven Verlaufsstudie wurden 223 in StäB
behandelte Patient*innen (Interventionsgruppe/IG, n=223)
mit einer gematchten vollstationären Kontrollgruppe (KG, n=223)
anhand von Routinedaten verglichen.
Ergebnisse Die vollstationäre Wiederaufnahmerate in der IG war
signifikant um 11 % geringer als in der KG. Die Anzahl der
Behandlungstage in der IG war signifikant geringer als in der KG. In der IG
wurden erstmalig psychiatrische Leistungen der Institutsambulanz signifikant
häufiger in Anspruch genommen als in der KG.
Schlussfolgerung StäB scheint einer vollstationären
Behandlung überlegen zu sein, insbesondere im Hinblick auf das Risiko
einer erneuten vollstationären Aufnahme. Als Folge der StäB
lässt sich ein Effekt der Ambulantisierung beobachten.