bluuebunny/crossref_metadata_2025 huggingface dataset:
Pirfenidone and Nintedanib in Pulmonary Fibrosis: Lights and Shadows
Authors: Chianese Maria , Screm Gianluca , Salton Francesco , Confalonieri Paola , Trotta Liliana , Barbieri Mariangela , Ruggero Luca , Mari Marco , Reccardini Nicolò , Geri Pietro , Hughes Michael , Lerda Selene , Confalonieri Marco , Mondini Lucrezia , Ruaro Barbara
Published: June 2024

Pirfenidone and Nintedanib are specific drugs used against idiopathic pulmonary fibrosis (IPF) that showed efficacy in non-IPF fibrosing interstitial lung diseases (ILD). Both drugs have side effects that affect patients in different ways and have different levels of severity, making treatment even more challenging for patients and clinicians. The present review aims to assess the effectiveness and potential complications of Pirfenidone and Nintedanib treatment regimens across various ILD diseases. A detailed search was performed in relevant articles published between 2018 and 2023 listed in PubMed, UpToDate, Google Scholar, and ResearchGate, supplemented with manual research. The following keywords were searched in the databases in all possible combinations: Nintedanib; Pirfenidone, interstitial lung disease, and idiopathic pulmonary fibrosis. The most widely accepted method for evaluating the progression of ILD is through the decline in forced vital capacity (FVC), as determined by respiratory function tests. Specifically, a decrease in FVC over a 6–12-month period correlates directly with increased mortality rates. Antifibrotic drugs Pirfenidone and Nintedanib have been extensively validated; however, some patients reported several side effects, predominantly gastrointestinal symptoms (such as diarrhea, dyspepsia, and vomiting), as well as photosensitivity and skin rashes, particularly associated with Pirfenidone. In cases where the side effects are extremely severe and are more threatening than the disease itself, the treatment has to be discontinued. However, further research is needed to optimize the use of antifibrotic agents in patients with PF-ILDs, which could slow disease progression and decrease all-cause mortality. Finally, other studies are requested to establish the treatments that can stop ILD progression.
Chemical and Biological Characterization of the Ethyl Acetate Fraction from the Red Sea Marine Sponge Hymedesmia sp.
Authors: El Sayed Zeinab I. , Hassan Wafaa H. B. , Abdel-Aal Mahmoud M. , Al-Massarani Shaza M. , Abdel-Mageed Wael M. , Basudan Omer A. , Parveen Mehtab , Abdelsalam Eman , Abdelaziz Sahar
Published: June 2024

Hymedesmiidae is one of the largest families of marine sponges and stands out as an exceptional source of variable metabolites with diverse biological activities. In this study, the ethyl acetate fraction (HE) of a Hymedesmia sp. marine sponge from the Red Sea, Egypt, was analyzed for the first time using Ultra-performance liquid chromatography electrospray ionization tandem mass spectrometry (UPLC-ESI-MS/MS) analysis. The analysis tentatively identified 29 compounds in this fraction, including the isolation and identification of six compounds (two pyrimidine nucleosides, one purine, and two pyrimidine bases in addition to one cerebroside) for the first time. The structures of the isolated compounds were established by 1D and 2D NMR (nuclear magnetic resonance), MS (mass spectrometry), and IR (infrared) spectroscopy. Furthermore, the cytotoxic, antioxidant, and antimicrobial activities of the ethyl acetate fraction were evaluated in vitro. The fraction exhibited strong DPPH scavenging activity with an IC50 of 78.7 µg/mL, compared to ascorbic acid as a positive control with an IC50 of 10.6 µg/mL. It also demonstrated significant cytotoxic activity with IC50 values of 13.5 µg/mL and 25.3 µg/mL against HCT-116 and HEP-2 cell lines, respectively, compared to vinblastine as a positive control with IC50 values of 2.34 µg/mL and 6.61 µg/mL against HCT-116 and HEP-2, respectively. Additionally, the ethyl acetate fraction displayed promising antibacterial activity against S. aureus with a MIC value of 62.5 µg/mL, compared to ciprofloxacin as a positive control with MIC values of 1.56 µg/mL for Gram-positive bacteria and 3.125 µg/mL for Gram-negative bacteria. It also exhibited activity against E. coli and P. aeruginosa with MIC values of 250 µg/mL and 500 µg/mL, respectively. Briefly, this is the first report on the biological activities and secondary metabolite content of the ethyl acetate fraction of Hymedesmia sp. marine sponge, emphasizing the potential for further research against resistant bacterial and fungal strains, as well as different cancer cell lines. The ethyl acetate fraction of Hymedesmia sp. is a promising source of safe and unique natural drugs with potential therapeutic and pharmaceutical benefits.
[68Ga]FAPI PET for Imaging and Treatment Monitoring in a Preclinical Model of Pulmonary Fibrosis: Comparison to [18F]FDG PET and CT
Authors: Ji Hao , Song Xiangming , Lv Xiaoying , Shao Fuqiang , Long Yu , Song Yangmeihui , Song Wenyu , Qiao Pengxin , Gai Yongkang , Jiang Dawei , Lan Xiaoli
Published: June 2024

Purpose: This study aimed to evaluate the feasibility of using [68Ga]-fibroblast-activating protein inhibitor (FAPI) positron emission tomography (PET) imaging for diagnosing pulmonary fibrosis in a mouse model. We also examined its value in monitoring treatment response and compared it with traditional [18F]-fluorodeoxyglucose (FDG) PET and computed tomography (CT) imaging. Methods: A model of idiopathic pulmonary fibrosis was established using intratracheal injection of bleomycin (BLM, 2 mg/kg) into C57BL/6 male mice. For the treatment of IPF, a daily oral dose of 400 mg/kg/day of pirfenidone was administered from 9 to 28 days after the establishment of the model. Disease progression and treatment efficacy were assessed at different stages of the disease every week for four weeks using CT, [18F]FDG PET, and [68Ga]FAPI PET (baseline imaging performed at week 0). Mice were sacrificed and lung tissues were harvested for hematoxylin-eosin staining, picrosirius red staining, and immunohistochemical staining for glucose transporter 1 (GLUT1) and FAP. Expression levels of GLUT1 and FAP in pathological sections were quantified. Correlations between imaging parameters and pathological quantitative values were analyzed. Results: CT, [18F]FDG PET and [68Ga]FAPI PET revealed anatomical and functional changes in the lung that reflected progression of pulmonary fibrosis. In untreated mice with pulmonary fibrosis, lung uptake of [18F]FDG peaked on day 14, while [68Ga]FAPI uptake and mean lung density peaked on day 21. In mice treated with pirfenidone, mean lung density and lung uptake of both PET tracers decreased. Mean lung density, [18F]FDG uptake, and [68Ga]FAPI uptake correlated well with quantitative values of picrosirius red staining, GLUT1 expression, and FAP expression, respectively. Conclusions: Although traditional CT and [18F]FDG PET reflect anatomical and metabolic status in fibrotic lung, [68Ga]FAPI PET provides a means of evaluating fibrosis progression and monitoring treatment response.
Cerebroprotective Effects of the TLR4-Binding DNA Aptamer ApTOLL in a Rat Model of Ischemic Stroke and Thrombectomy Recanalization
Authors: Aliena-Valero Alicia , Hernández-Jiménez Macarena , López-Morales Mikahela A. , Tamayo-Torres Eva , Castelló-Ruiz María , Piñeiro David , Ribó Marc , Salom Juan B.
Published: June 2024

ApTOLL, a TLR4 modulator aptamer, has demonstrated cerebroprotective effects in a permanent ischemic stroke mouse model, as well as safety and efficacy in early phase clinical trials. We carried out reverse translation research according to STAIR recommendations to further characterize the effects and mechanisms of ApTOLL after transient ischemic stroke in rats and to better inform the design of pivotal clinical trials. Adult male rats subjected to transient middle cerebral artery occlusion were treated either with ApTOLL or the vehicle intravenously at different doses and time-points. ApTOLL was compared with TAK-242 (a TLR4 inhibitor). Female rats were also studied. After neurofunctional evaluation, brains were removed for infarct/edema volume, hemorrhagic transformation, and histologic determinations. Peripheral leukocyte populations were assessed via flow cytometry. ApTOLL showed U-shaped dose-dependent cerebroprotective effects. The maximum effective dose (0.45 mg/kg) was cerebroprotective when given both before reperfusion and up to 12 h after reperfusion and reduced the hemorrhagic risk. Similar effects occurred in female rats. Both research and clinical ApTOLL batches induced slightly superior cerebroprotection when compared with TAK-242. Finally, ApTOLL modulated circulating leukocyte levels, reached the brain ischemic tissue to bind resident and infiltrated cell types, and reduced the neutrophil density. These results show the cerebroprotective effects of ApTOLL in ischemic stroke by reducing the infarct/edema volume, neurofunctional impairment, and hemorrhagic risk, as well as the peripheral and local immune response. They provide information about ApTOLL dose effects and its therapeutic time window and target population, as well as its mode of action, which should be considered in the design of pivotal clinical trials.
Use of Transient Transfection for cGMP Manufacturing of eOD-GT8 60mer, a Self-Assembling Nanoparticle Germline-Targeting HIV-1 Vaccine Candidate
Authors: Sharma Vaneet K. , Menis Sergey , Brower Evan T. , Sayeed Eddy , Ackland Jim , Lombardo Angela , Cottrell Christopher A. , Torres Jonathan L. , Hassell Thomas , Ward Andrew B. , Tsvetnitsky Vadim , Schief William R.
Published: June 2024

We describe the current Good Manufacturing Practice (cGMP) production and subsequent characterization of eOD-GT8 60mer, a glycosylated self-assembling nanoparticle HIV-1 vaccine candidate and germline targeting priming immunogen. Production was carried out via transient expression in the human embryonic kidney 293 (HEK293) cell line followed by a combination of purification techniques. A large-scale cGMP (200 L) production run yielded 354 mg of the purified eOD-GT8 60mer drug product material, which was formulated at 1 mg/mL in 10% sucrose in phosphate-buffered saline (PBS) at pH 7.2. The clinical trial material was comprehensively characterized for purity, antigenicity, glycan composition, amino acid sequence, and aggregation and by several safety-related tests during cGMP lot release. A comparison of the purified products produced at the 1 L scale and 200 L cGMP scale demonstrated the consistency and robustness of the transient transfection upstream process and the downstream purification strategies. The cGMP clinical trial material was tested in a Phase 1 clinical trial (NCT03547245), is currently being stored at −80 °C, and is on a stability testing program as per regulatory guidelines. The methods described here illustrate the utility of transient transfection for cGMP production of complex products such as glycosylated self-assembling nanoparticles.
Effects of Surface IR783 Density on the In Vivo Behavior and Imaging Performance of Liposomes
Authors: Long Qianqian , Zhao Xinmin , Gao Lili , Liu Mengyuan , Pan Feng , Gao Xihui , Zhan Changyou , Chen Yang , Wang Jialei , Qian Jun
Published: June 2024

Background: Nanoparticles conjugated with fluorescent probes have versatile applications, serving not only for targeted fluorescent imaging but also for evaluating the in vivo profiles of designed nanoparticles. However, the relationship between fluorophore density and nanoparticle behavior remains unexplored. Methods: The IR783-modified liposomes (IR783-sLip) were prepared through a modified ethanol injection and extrusion method. The cellular uptake efficiency of IR783-sLip was characterized by flow cytometry and fluorescence microscope imaging. The effects of IR783 density on liposomal in vivo behavior were investigated by pharmacokinetic studies, biodistribution studies, and in vivo imaging. The constitution of protein corona was analyzed by the Western blot assay. Results: Dense IR783 modification improved cellular uptake of liposomes in vitro but hindered their blood retention and tumor imaging performance in vivo. We found a correlation between IR783 density and protein corona absorption, particularly IgM, which significantly impacted the liposome performance. Meanwhile, we observed that increasing IR783 density did not consistently improve the effectiveness of tumor imaging. Conclusions: Increasing the density of modified IR783 on liposomes is not always beneficial for tumor near-infrared (NIR) imaging yield. It is not advisable to prematurely evaluate novel nanomaterials through fluorescence dye conjugation without carefully optimizing the density of the modifications.
Co-Amorphization of Acemetacin with Basic Amino Acids as Co-Formers for Solubility Improvement and Gastric Ulcer Mitigation
Authors: Hou Jiayue , Zhao Peixu , Wang Yanfei , Jiang Xiwei , Fu Qiang
Published: June 2024

Acemetacin (ACM) is a new non-steroidal anti-inflammatory drug with anti-inflammatory, analgesic, and antipyretic effects. However, the poor water solubility and gastrointestinal side effects limit its use. Recently, the co-amorphous (CAM) strategy has attracted great interest to improve solubility for poorly water-soluble drugs, and basic amino acids have the potential to protect the gastrointestinal tract. In order to develop a highly efficient and low-toxic ACM formulation, we prepared ACM CAM systems, with basic amino acids (lysine, arginine, and histidine) as co-formers, using a cryo-milling method. The solid-state behaviors of the ACM CAM systems were characterized by polarizing light microscopy, differential scanning calorimetry, and powder X-ray diffraction. Fourier transform infrared spectroscopy and molecular docking were carried out to understand the formation mechanism. Moreover, the gastro-protective effects of ACM CAM systems were evaluated in a rat gastric ulcer model. The results demonstrated that the CAM systems improved the dissolution rates of ACM compared with the neat amorphous counterpart. Furthermore, ACM CAM systems are significantly effective in mitigating the ACM-induced gastric ulcer in rats, and the ulcer inhibition rates were almost 90%. More importantly, this study provided a useful method for mitigating drug-induced gastrointestinal damage and broadened the applications of drug–amino acid CAM systems.
Impact of Time on Parameters for Assessing the Microstructure Equivalence of Topical Products: Diclofenac 1% Emulsion as a Case Study
Authors: Mañez-Asensi Andreu , Hernández Mª Jesús , Mangas-Sanjuán Víctor , Salvador Ana , Merino-Sanjuán Matilde , Merino Virginia
Published: June 2024

The demonstration of bioequivalence proposed in the European Medicines Agency’s (EMA’s) draft guideline for topical products with the same qualitative and quantitative composition requires the confirmation of the internal structure equivalence. The impact of the shelf-life on the parameters proposed for internal structure comparison has not been studied. The objectives of this work were: (1) to quantify the effect of the time since manufacturing on the mean value and variability of the parameters proposed by the EMA to characterize the internal structure and performance of topical formulations of a complex topical formulation, and (2) to evaluate the impact of these changes on the assessment of the microstructure equivalence. A total of 5 batches of a topical emulgel containing 1% diclofenac diethylamine were evaluated 5, 14, and 23 months after manufacture. The zero-shear viscosity (η0), viscosity at 100 s−1 (η100), yield stress (σ0), elastic (G′) and viscous (G″) moduli, internal phase droplet size and in vitro release of the active ingredient were characterized. While no change in variability over time was detected, the mean value of all the parameters changed, especially the droplet size and in vitro release. Thus, combining data from batches of different manufacturing dates may compromise the determination of bioequivalence. The results confirm that to assess the microstructural similarity of complex formulations (such as emulgel), the 90% confidence interval limit for the mean difference in rheological and in vitro release parameters should be 20% and 25%, respectively.
Inhibition of SARS-CoV-2-Induced NLRP3 Inflammasome-Mediated Lung Cell Inflammation by Triphala-Loaded Nanoparticle Targeting Spike Glycoprotein S1
Authors: Chittasupho Chuda , Umsumarng Sonthaya , Srisawad Kamonwan , Arjsri Punnida , Phongpradist Rungsinee , Samee Weerasak , Tingya Wipawan , Ampasavate Chadarat , Dejkriengkraikul Pornngarm
Published: June 2024

The COVID-19 pandemic, caused by SARS-CoV-2, poses a significant global health threat. The spike glycoprotein S1 of the SARS-CoV-2 virus is known to induce the production of pro-inflammatory mediators, contributing to hyperinflammation in COVID-19 patients. Triphala, an ancient Ayurvedic remedy composed of dried fruits from three plant species—Emblica officinalis (Family Euphorbiaceae), Terminalia bellerica (Family Combretaceae), and Terminalia chebula (Family Combretaceae)—shows promise in addressing inflammation. However, the limited water solubility of its ethanolic extract impedes its bioavailability. In this study, we aimed to develop nanoparticles loaded with Triphala extract, termed “nanotriphala”, as a drug delivery system. Additionally, we investigated the in vitro anti-inflammatory properties of nanotriphala and its major compounds, namely gallic acid, chebulagic acid, and chebulinic acid, in lung epithelial cells (A549) induced by CoV2-SP. The nanotriphala formulation was prepared using the solvent displacement method. The encapsulation efficiency of Triphala in nanotriphala was determined to be 87.96 ± 2.60% based on total phenolic content. In terms of in vitro release, nanotriphala exhibited a biphasic release profile with zero-order kinetics over 0–8 h. A549 cells were treated with nanotriphala or its active compounds and then induced with 100 ng/mL of spike S1 subunit (CoV2-SP). The results demonstrate that chebulagic acid and chebulinic acid are the active compounds in nanotriphala, which significantly reduced cytokine release (IL-6, IL-1β, and IL-18) and suppressed the expression of inflammatory genes (IL-6, IL-1β, IL-18, and NLRP3) (p < 0.05). Mechanistically, nanotriphala and its active compounds notably attenuated the expression of inflammasome machinery proteins (NLRP3, ASC, and Caspase-1) (p < 0.05). In conclusion, the nanoparticle formulation of Triphala enhances its stability and exhibits anti-inflammatory properties against CoV2-SP-induction. This was achieved by suppressing inflammatory mediators and the NLRP3 inflammasome machinery. Thus, nanotriphala holds promise as a supportive preventive anti-inflammatory therapy for COVID-19-related chronic inflammation.
Antitumoral-Embedded Biopolymeric Spheres for Implantable Devices
Authors: Grumezescu Valentina , Gherasim Oana , Gălățeanu Bianca , Hudiță Ariana
Published: June 2024

The bioactive surface modification of implantable devices paves the way towards the personalized healthcare practice by providing a versatile and tunable approach that increase the patient outcome, facilitate the medical procedure, and reduce the indirect or secondary effects. The purpose of our study was to assess the performance of composite coatings based on biopolymeric spheres of poly(lactide-co-glycolide) embedded with hydroxyapatite (HA) and methotrexate (MTX). Bio-simulated tests performed for up to one week evidenced the gradual release of the antitumor drug and the biomineralization potential of PLGA/HA-MTX sphere coatings. The composite materials proved superior biocompatibility and promoted enhanced cell adhesion and proliferation with respect to human preosteoblast and osteosarcoma cell lines when compared to pristine titanium.
Biopolymers Take Center Stage in Wound Healing Advancements
Authors: Orive Gorka , Desimone Martín Federico
Published: June 2024

The human body possesses a remarkable ability to heal itself from injuries [...]
Humility and Realism in Quantum Physics and Metaphysics
Authors: Bondi Damiano
Published: June 2024

The aim of this paper is to discuss some of the main philosophical and metaphysical implications of quantum physics, especially those which concern the issues of epistemic humility and ontological realism. My thesis is that the impossibility of reaching an objective knowledge of nature does not imply the renunciation of ontological realism, but rather encourages scientists to adopt an attitude of epistemic humility. The argument firstly presents the main theories of quantum physics currently discussed, focusing on the measurement problem and its ontological implications. Afterwords, the issues of objectivity and realism are properly addressed. In the end, we discuss statistics as the new form of scientific epistemology, along with the concept of potentiality as the fundamental category of quantum metaphysics. Throughout, we establish some parallelisms between quantum physics theories and theology to show that, when human beings investigate the foundations of reality, some thought patterns, some core problems, and some possible solutions resemble one another, regardless of the specific perspective and language with which they are formulated.
Melito of Sardis on Tyranny and the Reign of Marcus Aurelius
Authors: Kyriacou Chrysovalantis
Published: June 2024

The article examines perceptions of tyranny in Melito’s On Pascha and Apology, both written under Marcus Aurelius (161–180). This is the first systematic treatment of a key theme in Melito, approached not only from a theological perspective but also in the context of the Second Sophistic and Roman political developments. By proposing a more precise dating for On Pascha, we trace the development and consistency of Melito’s thought and arguments in regard to the relationship between Roman Empire and Christian communities in Asia Minor during the second half of the second century CE.
Christianity and Anthropogenic Climate Change: A Broad Overview of the Catholic Church’s Response and Some Reflections for the Future
Authors: Roccia Mariana
Published: June 2024

Religions play a key role in shaping our worldviews, values, and behaviours and this includes our interactions with the environment. Fuelled by the development of the technocratic paradigm, Christianity has historically received a bad reputation for perpetuating anti-environmental views. Nonetheless, the development of ecotheological strands and the emergence of faith-based organisations focusing on climate justice have aided in producing the much-needed environmental reformulations. As such, this paper seeks to provide a broad overview of the role of Christianity in shaping worldviews, from those hindering environmental action to more contemporary ecotheological approaches discussing climate change, particularly Pope Francis’ encyclical Laudato si’. Christianity’s preparedness to navigate climate change will be theorised in relation to empirical evidence and the work of European faith-based organisations, as well as the methodological opportunities that the field of ecolinguistics can offer to inform effective communication.
Quantitative Assessment of Volcanic Thermal Activity from Space Using an Isolation Forest Machine Learning Algorithm
Authors: Corradino Claudia , Malaguti Arianna Beatrice , Ramsey Micheal S. , Del Negro Ciro
Published: June 2024

Understanding the dynamics of volcanic activity is crucial for volcano observatories in their efforts to forecast volcanic hazards. Satellite imager data hold promise in offering crucial insights into the thermal behavior of active volcanoes worldwide, facilitating the assessment of volcanic activity levels and identifying significant changes during periods of volcano unrest. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, aboard NASA’s Terra and Aqua satellites, provides invaluable data with high temporal and spectral resolution, enabling comprehensive thermal monitoring of eruptive activity. The accuracy of volcanic activity characterization depends on the quality of models used to relate the relationship between volcanic phenomena and target variables such as temperature. Under these circumstances, machine learning (ML) techniques such as decision trees can be employed to develop reliable models without necessarily offering any particular or explicit insights. Here, we present a ML approach for quantifying volcanic thermal activity levels in near real time using thermal infrared satellite data. We develop an unsupervised Isolation Forest machine learning algorithm, fully implemented in Google Colab using Google Earth Engine (GEE) which utilizes MODIS Land Surface Temperature (LST) data to automatically retrieve information on the thermal state of volcanoes. We evaluate the algorithm on various volcanoes worldwide characterized by different levels of volcanic activity.
Virtual Sensor for On-Line Hardness Assessment in TIG Welding of Inconel 600 Alloy Thin Plates
Authors: Górka Jacek , Jamrozik Wojciech , Wyględacz Bernard , Kiel-Jamrozik Marta , Ferreira Batalha Gilmar
Published: June 2024

Maintaining high-quality welded connections is crucial in many industries. One of the challenges is assessing the mechanical properties of a joint during its production phase. Currently, in industrial practice, this occurs through NDT (non-destructive testing) conducted after the production process. This article proposes the use of a virtual sensor, which, based on temperature distributions observed on the joint surface during the welding process, allows for the determination of hardness distribution across the cross-section of a joint. Welding trials were conducted with temperature recording, hardness measurements were taken, and then, neural networks with different hyperparameters were tested and evaluated. As a basis for developing a virtual sensor, LSTM networks were utilized, which can be applied to time series prediction, as in the analyzed case of hardness value sequences across the cross-section of a welded joint. Through the analysis of the obtained results, it was determined that the developed virtual sensor can be applied to predict global temperature changes in the weld area, in terms of both its value and geometry changes, with the mean average error being less than 20 HV (mean for model ~35 HV). However, in its current form, predicting local hardness disturbances resulting from process instabilities and defects is not feasible.
Assessing Trail Running Biomechanics: A Comparative Analysis of the Reliability of StrydTM and GARMINRP Wearable Devices
Authors: Berzosa César , Comeras-Chueca Cristina , Bascuas Pablo Jesus , Gutiérrez Héctor , Bataller-Cervero Ana Vanessa
Published: June 2024

This study investigated biomechanical assessments in trail running, comparing two wearable devices—Stryd Power Meter and GARMINRP. With the growing popularity of trail running and the complexities of varied terrains, there is a heightened interest in understanding metabolic pathways, biomechanics, and performance factors. The research aimed to assess the inter- and intra-device agreement for biomechanics under ecological conditions, focusing on power, speed, cadence, vertical oscillation, and contact time. The participants engaged in trail running sessions while wearing two Stryd and two Garmin devices. The intra-device reliability demonstrated high consistency for both GARMINRP and StrydTM, with strong correlations and minimal variability. However, distinctions emerged in inter-device agreement, particularly in power and contact time uphill, and vertical oscillation downhill, suggesting potential variations between GARMINRP and StrydTM measurements for specific running metrics. The study underscores that caution should be taken in interpreting device data, highlighting the importance of measuring with the same device, considering contextual and individual factors, and acknowledging the limited research under real-world trail conditions. While the small sample size and participant variations were limitations, the strength of this study lies in conducting this investigation under ecological conditions, significantly contributing to the field of biomechanical measurements in trail running.
Assistive Systems for Visually Impaired Persons: Challenges and Opportunities for Navigation Assistance
Authors: Okolo Gabriel Iluebe , Althobaiti Turke , Ramzan Naeem
Published: June 2024

The inability to see makes moving around very difficult for visually impaired persons. Due to their limited movement, they also struggle to protect themselves against moving and non-moving objects. Given the substantial rise in the population of those with vision impairments in recent years, there has been an increasing amount of research devoted to the development of assistive technologies. This review paper highlights the state-of-the-art assistive technology, tools, and systems for improving the daily lives of visually impaired people. Multi-modal mobility assistance solutions are also evaluated for both indoor and outdoor environments. Lastly, an analysis of several approaches is also provided, along with recommendations for the future.
On the Generalizability of Time-of-Flight Convolutional Neural Networks for Noninvasive Acoustic Measurements
Authors: Saini Abhishek , Greenhall John James , Davis Eric Sean , Pantea Cristian
Published: June 2024

Bulk wave acoustic time-of-flight (ToF) measurements in pipes and closed containers can be hindered by guided waves with similar arrival times propagating in the container wall, especially when a low excitation frequency is used to mitigate sound attenuation from the material. Convolutional neural networks (CNNs) have emerged as a new paradigm for obtaining accurate ToF in non-destructive evaluation (NDE) and have been demonstrated for such complicated conditions. However, the generalizability of ToF-CNNs has not been investigated. In this work, we analyze the generalizability of the ToF-CNN for broader applications, given limited training data. We first investigate the CNN performance with respect to training dataset size and different training data and test data parameters (container dimensions and material properties). Furthermore, we perform a series of tests to understand the distribution of data parameters that need to be incorporated in training for enhanced model generalizability. This is investigated by training the model on a set of small- and large-container datasets regardless of the test data. We observe that the quantity of data partitioned for training must be of a good representation of the entire sets and sufficient to span through the input space. The result of the network also shows that the learning model with the training data on small containers delivers a sufficiently stable result on different feature interactions compared to the learning model with the training data on large containers. To check the robustness of the model, we tested the trained model to predict the ToF of different sound speed mediums, which shows excellent accuracy. Furthermore, to mimic real experimental scenarios, data are augmented by adding noise. We envision that the proposed approach will extend the applications of CNNs for ToF prediction in a broader range.
Smart Wireless Transducer Dedicated for Use in Aviation Laboratories
Authors: Kabala Tomasz , Weremczuk Jerzy
Published: June 2024

Reliable testing of aviation components depends on the quality and configuration flexibility of measurement systems. In a typical approach to test instrumentation, there are tens or hundreds of sensors on the test head and test facility, which are connected by wires to measurement cards in control cabinets. The preparation of wiring and the setup of measurement systems are laborious tasks requiring diligence. The use of smart wireless transducers allows for a new approach to test preparation by reducing the number of wires. Moreover, additional functionalities like data processing, alarm-level monitoring, compensation, or self-diagnosis could improve the functionality and accuracy of measurement systems. A combination of low power consumption, wireless communication, and wireless power transfer could speed up the test-rig instrumentation process and bring new test possibilities, e.g., long-term testing of moving or rotating components. This paper presents the design of a wireless smart transducer dedicated for use with sensors typical of aviation laboratories such as thermocouples, RTDs (Resistance Temperature Detectors), strain gauges, and voltage output integrated sensors. The following sections present various design requirements, proposed technical solutions, a study of battery and wireless power supply possibilities, assembly, and test results. All presented tests were carried out in the Components Test Laboratory located at the Łukasiewicz Research Network–Institute of Aviation.
Evaluation of a Voltametric E-Tongue Combined with Data Preprocessing for Fast and Effective Machine Learning-Based Classification of Tomato Purées by Cultivar
Authors: Magnani Giulia , Giliberti Chiara , Errico Davide , Stighezza Mattia , Fortunati Simone , Mattarozzi Monica , Boni Andrea , Bianchi Valentina , Giannetto Marco , De Munari Ilaria , Cagnoni Stefano , Careri Maria
Published: June 2024

The potential of a voltametric E-tongue coupled with a custom data pre-processing stage to improve the performance of machine learning techniques for rapid discrimination of tomato purées between cultivars of different economic value has been investigated. To this aim, a sensor array with screen-printed carbon electrodes modified with gold nanoparticles (GNP), copper nanoparticles (CNP) and bulk gold subsequently modified with poly(3,4-ethylenedioxythiophene) (PEDOT), was developed to acquire data to be transformed by a custom pre-processing pipeline and then processed by a set of commonly used classifiers. The GNP and CNP-modified electrodes, selected based on their sensitivity to soluble monosaccharides, demonstrated good ability in discriminating samples of different cultivars. Among the different data analysis methods tested, Linear Discriminant Analysis (LDA) proved to be particularly suitable, obtaining an average F1 score of 99.26%. The pre-processing stage was beneficial in reducing the number of input features, decreasing the computational cost, i.e., the number of computing operations to be performed, of the entire method and aiding future cost-efficient hardware implementation. These findings proved that coupling the multi-sensing platform featuring properly modified sensors with the custom pre-processing method developed and LDA provided an optimal tradeoff between analytical problem solving and reliable chemical information, as well as accuracy and computational complexity. These results can be preliminary to the design of hardware solutions that could be embedded into low-cost portable devices.
Fine-YOLO: A Simplified X-ray Prohibited Object Detection Network Based on Feature Aggregation and Normalized Wasserstein Distance
Authors: Zhou Yu-Tong , Cao Kai-Yang , Li De , Piao Jin-Chun
Published: June 2024

X-ray images typically contain complex background information and abundant small objects, posing significant challenges for object detection in security tasks. Most existing object detection methods rely on complex networks and high computational costs, which poses a challenge to implement lightweight models. This article proposes Fine-YOLO to achieve rapid and accurate detection in the security domain. First, a low-parameter feature aggregation (LPFA) structure is designed for the backbone feature network of YOLOv7 to enhance its ability to learn more information with a lighter structure. Second, a high-density feature aggregation (HDFA) structure is proposed to solve the problem of loss of local details and deep location information caused by the necked feature fusion network in YOLOv7-Tiny-SiLU, connecting cross-level features through max-pooling. Third, the Normalized Wasserstein Distance (NWD) method is employed to alleviate the convergence complexity resulting from the extreme sensitivity of bounding box regression to small objects. The proposed Fine-YOLO model is evaluated on the EDS dataset, achieving a detection accuracy of 58.3% with only 16.1 M parameters. In addition, an auxiliary validation is performed on the NEU-DET dataset, the detection accuracy reaches 73.1%. Experimental results show that Fine-YOLO is not only suitable for security, but can also be extended to other inspection areas.
Depth-Guided Bilateral Grid Feature Fusion Network for Dehazing
Authors: Li Xinyu , Qiao Zhi , Wan Gang , Zhu Sisi , Zhao Zhongxin , Fan Xinnan , Shi Pengfei , Wan Jin
Published: June 2024

In adverse foggy weather conditions, images captured are adversely affected by natural environmental factors, resulting in reduced image contrast and diminished visibility. Traditional image dehazing methods typically rely on prior knowledge, but their efficacy diminishes in practical, complex environments. Deep learning methods have shown promise in single-image dehazing tasks, but often struggle to fully leverage depth and edge information, leading to blurred edges and incomplete dehazing effects. To address these challenges, this paper proposes a deep-guided bilateral grid feature fusion dehazing network. This network extracts depth information through a dedicated module, derives bilateral grid features via Unet, employs depth information to guide the sampling of bilateral grid features, reconstructs features using a dedicated module, and finally estimates dehazed images through two layers of convolutional layers and residual connections with the original images. The experimental results demonstrate the effectiveness of the proposed method on public datasets, successfully removing fog while preserving image details.
The Reliability and Validity of the OneStep Smartphone Application for Gait Analysis among Patients Undergoing Rehabilitation for Unilateral Lower Limb Disability
Authors: Marom Pnina , Brik Michael , Agay Nirit , Dankner Rachel , Katzir Zoya , Keshet Naama , Doron Dana
Published: June 2024

An easy-to-use and reliable tool is essential for gait assessment of people with gait pathologies. This study aimed to assess the reliability and validity of the OneStep smartphone application compared to the C-Mill-VR+ treadmill (Motek, Nederlands), among patients undergoing rehabilitation for unilateral lower extremity disability. Spatiotemporal gait parameters were extracted from the treadmill and from two smartphones, one on each leg. Inter-device reliability was evaluated using Pearson correlation, intra-cluster correlation coefficient (ICC), and Cohen’s d, comparing the application’s readings from the two phones. Validity was assessed by comparing readings from each phone to the treadmill. Twenty-eight patients completed the study; the median age was 45.5 years, and 61% were males. The ICC between the phones showed a high correlation (r = 0.89–1) and good-to-excellent reliability (ICC range, 0.77–1) for all the gait parameters examined. The correlations between the phones and the treadmill were mostly above 0.8. The ICC between each phone and the treadmill demonstrated moderate-to-excellent validity for all the gait parameters (range, 0.58–1). Only ‘step length of the impaired leg’ showed poor-to-good validity (range, 0.37–0.84). Cohen’s d effect size was small (d < 0.5) for all the parameters. The studied application demonstrated good reliability and validity for spatiotemporal gait assessment in patients with unilateral lower limb disability.
A Review of Wearable Optical Fiber Sensors for Rehabilitation Monitoring
Authors: Li Xiangmeng , Li Yongzhen , Wei Huifen , Wang Chaohui , Liu Bo
Published: June 2024

As the global aging population increases, the demand for rehabilitation of elderly hand conditions has attracted increased attention in the field of wearable sensors. Owing to their distinctive anti-electromagnetic interference properties, high sensitivity, and excellent biocompatibility, optical fiber sensors exhibit substantial potential for applications in monitoring finger movements, physiological parameters, and tactile responses during rehabilitation. This review provides a brief introduction to the principles and technologies of various fiber sensors, including the Fiber Bragg Grating sensor, self-luminescent stretchable optical fiber sensor, and optic fiber Fabry–Perot sensor. In addition, specific applications are discussed within the rehabilitation field. Furthermore, challenges inherent to current optical fiber sensing technology, such as enhancing the sensitivity and flexibility of the sensors, reducing their cost, and refining system integration, are also addressed. Due to technological developments and greater efforts by researchers, it is likely that wearable optical fiber sensors will become commercially available and extensively utilized for rehabilitation.
A Novel Network Framework on Simultaneous Road Segmentation and Vehicle Detection for UAV Aerial Traffic Images
Authors: Xiao Min , Min Wei , Yang Congmao , Song Yongchao
Published: June 2024

Unmanned Aerial Vehicle (UAV) aerial sensors are an important means of collecting ground image data. Through the road segmentation and vehicle detection of drivable areas in UAV aerial images, they can be applied to monitoring roads, traffic flow detection, traffic management, etc. As well, they can be integrated with intelligent transportation systems to support the related work of transportation departments. Existing algorithms only realize a single task, while intelligent transportation requires the simultaneous processing of multiple tasks, which cannot meet complex practical needs. However, UAV aerial images have the characteristics of variable road scenes, a large number of small targets, and dense vehicles, which make it difficult to complete the tasks. In response to these issues, we propose to implement road segmentation and on-road vehicle detection tasks in the same framework for UAV aerial images, and we conduct experiments on a self-constructed dataset based on the DroneVehicle dataset. For road segmentation, we propose a new algorithm C-DeepLabV3+. The new algorithm introduces the coordinate attention (CA) module, which can obtain more accurate segmentation target location information and make the segmentation target edges more continuous. Also, the improved algorithm introduces the cascade feature fusion module to prevent the loss of detail information in road segmentation and to obtain better segmentation performance. For vehicle detection, we propose an improved algorithm S-YOLOv5 by adding a parameter-free lightweight attention module SimAM. Finally, the proposed road segmentation–vehicle detection framework is utilized to unite the C-DeepLabV3+ and S-YOLOv5 algorithms for the implementation of the serial tasks. The experimental results show that on the constructed ViDroneVehicle dataset, the C-DeepLabV3+ algorithm has an mPA value of 98.75% and an mIoU value of 97.53%, which can better segment the road area and solve the problem of occlusion. The mAP value of the S-YOLOv5 algorithm has an mAP value of 97.40%, which is more than YOLOv5’s 96.95%, which effectively reduces the vehicle omission and false detection rates. By comparison, the results of both algorithms are superior to multiple state-of-the-art methods. The overall framework proposed in this paper has superior performance and is capable of realizing high-quality and high-precision road segmentation and vehicle detection from UAV aerial images.
Intelligent Sensing of Thermal Error of CNC Machine Tool Spindle Based on Multi-Source Information Fusion
Authors: Yang Zeqing , Liu Beibei , Zhang Yanrui , Chen Yingshu , Zhao Hongwei , Zhang Guofeng , Yi Wei , Zhang Zonghua
Published: June 2024

Aiming at the shortcomings of single-sensor sensing information characterization ability, which is easily interfered with by external environmental factors, a method of intelligent perception is proposed in this paper. This method integrates multi-source and multi-level information, including spindle temperature field, spindle thermal deformation, operating parameters, and motor current. Firstly, the internal and external thermal-error-related signals of the spindle system are collected by sensors, and the feature parameters are extracted; then, the radial basis function (RBF) neural network is utilized to realize the preliminary integration of the feature parameters because of the advantages of the RBF neural network, which offers strong multi-dimensional solid nonlinear mapping ability and generalization ability. Thermal-error decision values are then generated by a weighted fusion of different pieces of evidence by considering uncertain information from multiple sources. The spindle thermal-error sensing experiment was based on the spindle system of the VMC850 (Yunnan Machine Tool Group Co., LTD, Yunnan, China) vertical machining center of the Yunnan Machine Tool Factory. Experiments were designed for thermal-error sensing of the spindle under constant speed (2000 r/min and 4000 r/min), standard variable speed, and stepped variable speed conditions. The experiment’s results show that the prediction accuracy of the intelligent-sensing model with multi-source information fusion can reach 98.1%, 99.3%, 98.6%, and 98.8% under the above working conditions, respectively. The intelligent-perception model proposed in this paper has higher accuracy and lower residual error than the traditional BP neural network perception and wavelet neural network models. The research in this paper provides a theoretical basis for the operation, maintenance management, and performance optimization of machine tool spindle systems.
The Impact of Urbanization on Industrial Transformation and Upgrading: Evidence from Early 20th Century China
Authors: Wan Jiale , Wang Qimeng , Miao Shuangyou
Published: June 2024

Urbanization is key to advancing national modernization and regional socioeconomic sustainable development. This paper empirically investigates the impact of urbanization on industrial transformation and upgrading in early 20th-century China, based on historical data from the initial stages of China’s economic development. We utilized industrial and commercial data from China spanning 1910 to 1927 to construct a fixed-effect model, incorporating instrumental variables to ascertain the causal relationship between urbanization and industrial transformation and upgrading. Additionally, this study tested the hypotheses concerning the effects of human capital and transportation scale, which are identified as the primary channels influencing this relationship. Our findings reveal that (1) the development of urbanization in modern China has significantly promoted industrial transformation and upgrading, and this conclusion remains valid under various robustness tests and the examination of instrumental variables. (2) The improvement in urbanization levels has a more obvious promoting effect on secondary industry, commercial enterprises, and small and medium-sized enterprises, and the positive effect of urbanization on industrial transformation and upgrading is most prominent in the eastern region. (3) Modern Chinese urbanization promoted industrial transformation and upgrading by improving the level of human capital and expanding the scale of transportation. This paper provides historical empirical evidence to study the current social urbanization and industrial policy formulation.