bluuebunny/crossref_metadata_2025 huggingface dataset:
Cu/ZrO2 Catalyst Modified with Y2O3 for Effective and Stable Dehydration of Glycerol to Acetol
Authors: Liang Zhoubing , Li Huan , Xie Jianrong , Ye Songshou , Zheng Jinbao , Zhang Nuowei
Published: January 2024

Glycerol is a main by-product of biodiesel production, and its further processing is essential for the biorefinery. In this paper, a highly active and stable catalyst for the catalytic dehydration of glycerol to acetol is obtained by modifying a Cu-Zr (ZrO2 supported Cu) catalyst with Y2O3 using a co-precipitation method. It is found that the addition of Y2O3 effectively enhances the catalytic performance of Cu-Zr. Cu-Zr reaches the highest selectivity (82.4%) to acetol at 24 h. However, the selectivity decreases to 70.1% at 36 h. The conversion also decreases from 99.2 to 91.1%. Cu-Zr-Y exhibits very high activity and very good stability. During a 250 h reaction, no deactivation is observed, and the conversion and selectivity remains ~100% and ~85%, respectively. The catalysts are characterized by XRD, TEM, H2-TPR, and NH3-TPD. The results reveal that Y2O3 not only improves the dispersion of Cu and the acidity of the catalyst but also restrains the agglomeration of Cu particles and assists retaining the main structure of support under reaction conditions. The high dispersion, high acidity content, and stable structure contributes to the excellent catalytic performance of Cu-Zr-Y.
Characterization of Neutral Lipids of the Oleaginous Alga Micractinum inermum
Authors: Banskota Arjun H. , Hui Joseph P. M. , Jones Alysson , McGinn Patrick J.
Published: January 2024

An oleaginous microalga Micractinum inermum isolated from Mariana Lake, AB, Canada was cultured in a 1000 L photobioreactor with an f/2 medium to study its lipid content and neutral lipid profile. Algal biomass was collected at the stationary phase contained a significant amount of lipids (44.2%), as determined by Folch’s method. The lipid was fractionated into neutral lipid, glycolipid and phospholipid fractions. The neutral lipid constitutes almost 77.3% of the total lipid species and is mainly composed of triacylglycerols (TAGs) determined by a proton NMR study. UHPLC-HRMS analysis allows us for the first time to identify 81 TAGs in the neutral lipid fraction of M. inermum. The fatty acid acyl side chains were identified based on fragment ions observed in MSMS analysis. TAGs with fatty acid acyl chains 18:1/18:1/18:1, 18:1/18:1/16:0, 18:2/18:1/16:0, and 18:2/18:2/18:0 were the major ones among the identified TAGs. Fatty acid analysis further supports the fact that oleic acid was the major fatty acid present in the neutral lipid fraction of M. inermum constituting 41.7%, followed by linoleic acid at 21.5%, and palmitic acid at 21.2%. The saturated and monounsaturated fatty acids were 67.8% or higher in the lipid fraction. Long-chain fatty acids were only present in a minor quantity. The results clearly demonstrate that M. inermum is an excellent source for TAGs.
Potato Resistant Starch Type 1 Promotes Obesity Linked with Modified Gut Microbiota in High-Fat Diet-Fed Mice
Authors: Zhang Weiyue , Zhang Nana , Guo Xinxin , Fan Bei , Cheng Shumei , Wang Fengzhong
Published: January 2024

Obesity has become a major disease that endangers human health. Studies have shown that dietary interventions can reduce the prevalence of obesity and diabetes. Resistant starch (RS) exerts anti-obesity effects, alleviates metabolic syndrome, and maintains intestinal health. However, different RS types have different physical and chemical properties. Current research on RS has focused mainly on RS types 2, 3, and 4, with few studies on RS1. Therefore, this study aimed to investigate the effect of RS1 on obesity and gut microbiota structure in mice. In this study, we investigated the effect of potato RS type 1 (PRS1) on obesity and inflammation. Mouse weights, as well as their food intake, blood glucose, and lipid indexes, were assessed, and inflammatory factors were measured in the blood and tissues of the mice. We also analyzed the expression levels of related genes using PCR, with 16S rRNA sequencing used to study intestinal microbiota changes in the mice. Finally, the level of short-chain fatty acids was determined. The results indicated that PRS1 promoted host obesity and weight gain and increased blood glucose and inflammatory cytokine levels by altering the gut microbiota structure.
Design, Synthesis, and Evaluation of New Hybrid Derivatives of 5,6-Dihydro-4H-pyrrolo[3,2,1-ij]quinolin-2(1H)-one as Potential Dual Inhibitors of Blood Coagulation Factors Xa and XIa
Authors: Skoptsova Anna A. , Geronikaki Athina , Novichikhina Nadezhda P. , Sulimov Alexey V. , Ilin Ivan S. , Sulimov Vladimir B. , Bykov Georgii A. , Podoplelova Nadezhda A. , Pyankov Oleg V. , Shikhaliev Khidmet S.
Published: January 2024

Cardiovascular diseases caused by blood coagulation system disorders are one of the leading causes of morbidity and mortality in the world. Research shows that blood clotting factors are involved in these thrombotic processes. Among them, factor Xa occupies a key position in the blood coagulation cascade. Another coagulation factor, XIa, is also a promising target because its inhibition can suppress thrombosis with a limited contribution to normal hemostasis. In this regard, the development of dual inhibitors as new generation anticoagulants is an urgent problem. Here we report the synthesis and evaluation of novel potential dual inhibitors of coagulation factors Xa and XIa. Based on the principles of molecular design, we selected a series of compounds that combine in their structure fragments of pyrrolo[3,2,1-ij]quinolin-2-one and thiazole, connected through a hydrazine linker. The production of new hybrid molecules was carried out using a two-stage method. The reaction of 5,6-dihydropyrrolo[3,2,1-ij]quinoline-1,2-diones with thiosemicarbazide gave the corresponding hydrazinocarbothioamides. The reaction of the latter with DMAD led to the target methyl 2-(4-oxo-2-(2-(2-oxo-5,6-dihydro-4H-pyrrolo[3,2,1-ij]quinolin-1(2H)-ylidene)hydrazineyl)thiazol-5(4H)-ylidene)acetates in high yields. In vitro testing of the synthesized molecules revealed that ten of them showed high inhibition values for both the coagulation factors Xa and XIa, and the IC50 value for some compounds was also assessed. The resulting structures were also tested for their ability to inhibit thrombin.
Synthesis of Zinc Nanoparticles by the Gas Condensation Method in a Non-Contact Crucible and Their Physical–Chemical Characterization
Authors: Markov Artyom N. , Kapinos Alexander A. , Petukhov Anton N. , Dokin Egor S. , Emelyanov Artem V. , Abarbanel Nataliia V. , Zarubin Dmitriy M. , Golovacheva Anna A. , Suvorov Sergey S. , Barysheva Alexandra V. , Grachev Pavel P. , Vorotyntsev Ilya V. , Vorotynstev Andrey V.
Published: January 2024

This work explored the zinc nanoparticles obtained by the one-stage induction flow levitation method. A 10 kW tube generator with an operating frequency of 440 kHz was used. The process used 8 mm diameter zinc granules (2 g weight) with a purity of 99.9%. Zinc wire was fed to replace the evaporated metal from the granule surface. This method productivity was 30 g/h of nanoparticles. In addition, various methods were used to characterize the resulting nanoparticles: scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-Ray fluorescence analysis (XRF), dynamic light scattering (DLS), porosimetry and inductively coupled plasma atomic emission spectroscopy (ICP-MS). The resulting nanoparticle size, determined by SEM and porosimetry, was 350 nm, while the size of the primary crystallites was 21 nm. The amount of impurities in the resulting nanoparticles did not exceed 1000 ppm.
Emerging Trends and Translational Challenges in Drug and Vaccine Delivery
Authors: Kumar Prashant , Agrahari Vibhuti
Published: January 2024

Drug and vaccine delivery have received considerable attention in recent years [...]
3D-Printed Alginate/Pectin-Based Patches Loaded with Olive Leaf Extracts for Wound Healing Applications: Development, Characterization and In Vitro Evaluation of Biological Properties
Authors: Patitucci Francesco , Motta Marisa Francesca , Dattilo Marco , Malivindi Rocco , Leonetti Adele Elisabetta , Pezzi Giuseppe , Prete Sabrina , Mileti Olga , Gabriele Domenico , Parisi Ortensia Ilaria , Puoci Francesco
Published: January 2024

Traditional wound dressings may lack suitability for diverse wound types and individual patient requirements. In this context, this study aimed to innovate wound care by developing a 3D-printed patch using alginate and pectin and incorporating Olive Leaf Extract (OLE) as an active ingredient. Different polymer-to-plasticizer ratios were systematically examined to formulate a printable ink with optimal viscosity. The resultant film, enriched with OLE, exhibited a substantial polyphenolic content of 13.15 ± 0.41 mg CAE/g, showcasing significant antioxidant and anti-inflammatory properties. Notably, the film demonstrated potent scavenging abilities against DPPH, ABTS, and NO radicals, with IC50 values of 0.66 ± 0.07, 0.47 ± 0.04, and 2.02 ± 0.14 mg/mL, respectively. In vitro release and diffusion studies were carried out and the release profiles revealed an almost complete release of polyphenols from the patch within 48 h. Additionally, the fabricated film exhibited the capacity to enhance cell motility and accelerate wound healing, evidenced by increased collagen I expression in BJ fibroblast cells. Structural assessments affirmed the ability of the patch to absorb exudates and maintain the optimal moisture balance, while biocompatibility studies underscored its suitability for biomedical applications. These compelling findings endorse the potential application of the developed film in advanced wound care, with the prospect of tailoring patches to individual patient needs.
Correction: Velasco-Amo et al. Use of traC Gene to Type the Incidence and Distribution of pXFAS_5235 Plasmid-Bearing Strains of Xylella fastidiosa subsp. fastidiosa ST1 in Spain. Plants 2022, 11, 1562
Authors: Velasco-Amo María Pilar , Arias-Giraldo Luis F. , Olivares-García Concepción , Denancé Nicolás , Jacques Marie-Agnès , Landa Blanca B.
Published: January 2024

In the original publication [...]
Sucrose and Mannans Affect Arabidopsis Shoot Gravitropism at the Cell Wall Level
Authors: Pozhvanov Gregory , Suslov Dmitry
Published: January 2024

Gravitropism is the plant organ bending in response to gravity. Gravitropism, phototropism and sufficient mechanical strength define the optimal position of young shoots for photosynthesis. Etiolated wild-type Arabidopsis seedlings grown horizontally in the presence of sucrose had a lot more upright hypocotyls than seedlings grown without sucrose. We studied the mechanism of this effect at the level of cell wall biomechanics and biochemistry. Sucrose strengthened the bases of hypocotyls and decreased the content of mannans in their cell walls. As sucrose is known to increase the gravitropic bending of hypocotyls, and mannans have recently been shown to interfere with this process, we examined if the effect of sucrose on shoot gravitropism could be partially mediated by mannans. We compared cell wall biomechanics and metabolomics of hypocotyls at the early steps of gravitropic bending in Col-0 plants grown with sucrose and mannan-deficient mutant seedlings. Sucrose and mannans affected gravitropic bending via different mechanisms. Sucrose exerted its effect through cell wall-loosening proteins, while mannans changed the walls’ viscoelasticity. Our data highlight the complexity of shoot gravitropism control at the cell wall level.
Effectiveness and Selectivity of Pre- and Post-Emergence Herbicides for Weed Control in Grain Legumes
Authors: Kousta Angeliki , Katsis Christos , Tsekoura Anastasia , Chachalis Dimosthenis
Published: January 2024

Grain legumes represent important crops for livestock feed and contribute to novel uses in the food industry; therefore, the best cultivation practices need to be assessed. This study aimed to identify herbicides to meet the current need for controlling broadleaf weeds without phytotoxicity in the grain legume crop per se. Field experiments were undertaken during the 2019 and 2020 growing seasons and laid out in a randomized complete block design with three replicates as follows: four grain legume crops (vetch, pea, faba bean, and white lupine) and nine pre-emergence (PRE) or post-emergence selective (POST) herbicide treatments (PRE: aclonifen, pendimethalin plus clomazone, metribuzin plus clomazone, benfluralin, terbuthylazine plus pendimethalin, S-metolachlor plus pendimethalin, flumioxazin; POST: pyridate, imazamox) alongside weedy check plots. Plant phytotoxicity, crop dry matter, yield features, weed presence, and weed dry matter were assessed during the experiments. There was differential efficacy among the nine herbicide treatments; the weed control was more effective in the case of Veronica arvensis L. and Sonchus spp. L. compared with Chenopodium album L., Sinapis arvensis L., and Silibum marianum L. regardless of the herbicide treatment. The most effective PRE herbicide was flumioxazin, which had the greatest control over the majority of weeds (>70%) resulting in the lowest total weed biomass. The second-best treatment was benfluralin and the mixture of terbuthylazine plus pendimethalin (both had only limited control in S. arvensis). The best POST herbicide was imazamox, with only limited control in S. arvensis. The tested herbicides caused low to medium and transient levels of phytotoxicity mainly in vetch and secondly in peas but not in faba beans and lupines. Concerning all weed management treatments, benfluralin resulted in the highest grain yields for all four grain legume crops during both growing seasons. Among grain legumes, vetch had the highest competitive ability against weeds, whereas peas were the least tolerant against weed competition.
Thermokinetic and Chemorheology of the Geopolymerization of an Alumina-Rich Alkaline-Activated Metakaolin in Isothermal and Dynamic Thermal Scans
Authors: Aversa Raffaella , Ricciotti Laura , Perrotta Valeria , Apicella Antonio
Published: January 2024

Alkaline sodium hydroxide/sodium silicate-activating high-purity metakaolin geopolymerization is described in terms of metakaolin deconstruction in tetrahedral hydrate silicate [O[Si(OH)3]]− and aluminate [Al(OH)4]− ionic precursors followed by their reassembling in linear and branched sialates monomers that randomly copolymerize into an irregular crosslinked aluminosilicate network. The novelty of the approach resides in the concurrent thermo-calorimetric (differential scanning calorimetry, DSC) and rheological (dynamic mechanical analysis, DMA) characterizations of the liquid slurry during the transformation into a gel and a structural glassy solid. Tests were run either in temperature scan (1 °C/min) or isothermal (20 °C, 30 °C, 40 °C) cure conditions. A Gaussian functions deconvolution method has been applied to the DSC multi-peak thermograms to separate the kinetic contributions of the oligomer’s concurrent reactions. DSC thermograms of all tested materials are well-fitted by a combination of three overlapping Gaussian curves that are associated with the initial linear low-molecular-weight (Mw) oligomers (P1) formation, oligomers branching into alumina-rich and silica-rich gels (P2), and inter- and intra-molecular crosslinking (P3). The loss factor has been used to define viscoelastic behavioral zones for each DMA rheo-thermogram operated in the same DSC thermal conditions. Macromolecular evolution and viscoelastic properties have been obtained by pairing the deconvoluted DSC thermograms with the viscoelastic behavioral zones of the DMA rheo-thermograms. Two main chemorheological behaviors have been identified relative to pre- and post-gelation separation of the viscoelastic liquid from the viscoelastic solid. Each comprises three behavioral zones, accounting for the concurrently occurring linear and branching oligomerization, aluminate-rich and silica-rich gel nucleations, crosslinking, and vitrification. A “rubbery plateau” in the loss factor path, observed for all the testing conditions, identifies a large behavioral transition zone dividing the incipient gelling liquid slurry from the material hard setting and vitrification.
“Since I’ve Been Ill, I Live Better”: The Emergence of Latent Spirituality in the Biographical Pathways of Illness
Authors: Pannofino Nicola Luciano
Published: January 2024

Spirituality can be a crucial resource to draw on to make sense of critical situations that mark a turning point in individual and collective biographies. In these cases, a ritual and symbolic response to the trauma may occur, bringing to the surface a «latent spirituality», that is, a tacit propensity towards the sacred that manifests itself in unexpected ways, even in those who do not normally believe or practice, in extraordinary situations that engender fear, anomie or disorientation and that have profound existential repercussions. This article aims to investigate the latent spirituality in the face of the critical event represented by the onset of severe disease, based on the analysis of spiritual illness narratives collected in Italy through qualitative interviews with oncological patients. The narratives show how the condition of suffering can bring to light an unexpressed spirituality, consisting of the revitalization of previous traditional faith or the elaboration of an innovative lay spirituality. Data confirm how pathology constitutes a biographical fracture, accompanied by questions and needs of a religious and spiritual nature. In contrast to the prevailing approach in the medical humanities where spirituality is interpreted as a starting resource to which sufferers resort to cope toward the disease, these results indicate that the spiritual dimension is an emerging aspect along the therapeutic pathway and that it is transformed by reflecting the temporality of the biographical experience of illness.
Self-Attention Generative Adversarial Network Interpolating and Denoising Seismic Signals Simultaneously
Authors: Ding Mu , Zhou Yatong , Chi Yue
Published: January 2024

In light of the challenging conditions of exploration environments coupled with escalating exploration expenses, seismic data acquisition frequently entails the capturing of signals entangled amidst diverse noise interferences and instances of data loss. The unprocessed state of these seismic signals significantly jeopardizes the interpretative phase. Evidently, the integration of attention mechanisms and the utilization of generative adversarial networks (GANs) have emerged as prominent techniques within signal processing owing to their adeptness in discerning intricate global dependencies. Our research introduces a pioneering approach for reconstructing and denoising seismic signals, amalgamating the principles of self-attention and generative adversarial networks—hereafter referred to as SAGAN. Notably, the incorporation of the self-attention mechanism into the GAN framework facilitates an enhanced capacity for both the generator and discriminator to emulate meaningful spatial interactions. Subsequently, leveraging the feature map generated by the self-attention mechanism within the GAN structure enables the interpolation and denoising of seismic signals. Rigorous experimentation substantiates the efficacy of SAGAN in simultaneous signal interpolation and denoising. Initially, we benchmarked SAGAN against prominent methods such as UNet, CNN, and Wavelet for the concurrent interpolation and denoising of two-dimensional seismic signals manifesting varying levels of damage. Subsequently, this methodology was extended to encompass three-dimensional seismic data. Notably, performance metrics reveal SAGAN’s superiority over comparative methods. Specifically, the quantitative tables exhibit SAGAN’s pronounced advantage, with a 3.46% increase in PSNR value over UNet and an impressive 11.90% surge compared to Wavelet. Moreover, the RMSE values affirm SAGAN’s robust performance, showcasing an 11.54% reduction in comparison to UNet and an impressive 29.27% decrement relative to Wavelet, hence unequivocally establishing the SAGAN method as a preeminent choice for seismic signal recovery.
Research on Multiple-AUVs Collaborative Detection and Surrounding Attack Simulation
Authors: Wen Zhiwen , Wang Zhong , Zhou Daming , Qin Dezhou , Jiang Yichen , Liu Junchang , Dong Huachao
Published: January 2024

Due to limitations in operational scope and efficiency, a single Autonomous Underwater Vehicle (AUV) falls short of meeting the demands of the contemporary marine working environment. Consequently, there is a growing interest in the coordination of multiple AUVs. To address the requirements of coordinated missions, this paper proposes a comprehensive solution for the coordinated development of multi-AUV formations, encompassing long-range ferrying, coordinated detection, and surrounding attack. In the initial phase, detection devices are deactivated, employing a path planning method based on the Rapidly Exploring Random Tree (RRT) algorithm to ensure collision-free AUV movement. During the coordinated detection phase, an artificial potential field method is applied to maintain AUV formation integrity and avoid obstacles, dynamically updating environmental probability based on formation movement. In the coordinated surroundings attack stage, predictive capabilities are enhanced using Long Short-Term Memory (LSTM) networks and reinforcement learning. Specifically, LSTM forecasts the target’s position, while the Deep Deterministic Policy Gradient (DDPG) method controls AUV formation. The effectiveness of this coordinated solution is validated through an integrated simulation trajectory.
Were Frailty Identification Criteria Created Equal? A Comparative Case Study on Continuous Non-Invasively Collected Neurocardiovascular Signals during an Active Standing Test in the Irish Longitudinal Study on Ageing (TILDA)
Authors: Xue Feng , Knight Silvin , Connolly Emma , O’Halloran Aisling , Shirsath Morgana Afonso , Newman Louise , Duggan Eoin , Kenny Rose Anne , Romero-Ortuno Roman
Published: January 2024

Background: In this observational study, we compared continuous physiological signals during an active standing test in adults aged 50 years and over, characterised as frail by three different criteria, using data from The Irish Longitudinal Study on Ageing (TILDA). Methods: This study utilised data from TILDA, an ongoing landmark prospective cohort study of community-dwelling adults aged 50 years or older in Ireland. The initial sampling strategy in TILDA was based on random geodirectory sampling. Four independent groups were identified: those characterised as frail only by one of the frailty tools used (the physical Frailty Phenotype (FP), the 32-item Frailty Index (FI), or the Clinical Frailty Scale (CFS) classification tree), and a fourth group where participants were not characterised as frail by any of these tools. Continuous non-invasive physiological signals were collected during an active standing test, including systolic (sBP) and diastolic (dBP) blood pressure, as well as heart rate (HR), using digital artery photoplethysmography. Additionally, the frontal lobe cerebral oxygenation (Oxy), deoxygenation (Deoxy), and tissue saturation index (TSI) were also non-invasively measured using near-infrared spectroscopy (NIRS). The signals were visualised across frailty groups and statistically compared using one-dimensional statistical parametric mapping (SPM). Results: A total of 1124 participants (mean age of 63.5 years; 50.2% women) were included: 23 were characterised as frail only by the FP, 97 by the FI, 38 by the CFS, and 966 by none of these criteria. The SPM analyses revealed that only the group characterised as frail by the FI had significantly different signals (p < 0.001) compared to the non-frail group. Specifically, they exhibited an attenuated gain in HR between 10 and 15 s post-stand and larger deficits in sBP and dBP between 15 and 20 s post-stand. Conclusions: The FI proved to be more adept at capturing distinct physiological responses to standing, likely due to its direct inclusion of cardiovascular morbidities in its definition. Significant differences were observed in the dynamics of cardiovascular signals among the frail populations identified by different frailty criteria, suggesting that caution should be taken when employing frailty identification tools on physiological signals, particularly the neurocardiovascular signals in an active standing test.
An Improved Spectral Subtraction Method for Eliminating Additive Noise in Condition Monitoring System Using Fiber Bragg Grating Sensors
Authors: Liu Qi , Yu Yongchao , Han Boon Siew , Zhou Wei
Published: January 2024

The additive noise in the condition monitoring system using fiber Bragg grating (FBG) sensors, including white Gaussian noise and multifrequency interference, has a significantly negative influence on the fault diagnosis of rotating machinery. Spectral subtraction (SS) is an effective method for handling white Gaussian noise. However, the SS method exhibits poor performance in eliminating multifrequency interference because estimating the noise spectrum accurately is difficult, and it significantly weakens the useful information components in measured signals. In this study, an improved spectral subtraction (ISS) method is proposed to enhance its denoising performance. In the ISS method, a reference noise signal measured by the same sensing system without working loads is considered the estimated noise, the same sliding window is used to divide the power spectrums of the measured and reference noise signals into multiple frequency bands, and the formula of spectral subtraction in the standard SS method is modified. A simulation analysis and an experiment are executed by using simulated signals and establishing a vibration test rig based on the FBG sensor, respectively. The statistical results demonstrate the effectiveness and feasibility of the ISS method in simultaneously eliminating white Gaussian noise and multifrequency interference while well maintaining the useful information components.
Heart Rate Variability to Automatically Identify Hyperbaric States Considering Respiratory Component
Authors: Peláez-Coca María Dolores , Hernando Alberto , Lozano María Teresa , Bolea Juan , Izquierdo David , Sánchez Carlos
Published: January 2024

This study’s primary objective was to identify individuals whose physiological responses deviated from the rest of the study population by automatically monitoring atmospheric pressure levels to which they are exposed and using parameters derived from their heart rate variability (HRV). To achieve this, 28 volunteers were placed in a dry hyperbaric chamber, where they experienced varying pressures from 1 to 5 atmospheres, with five sequential stops lasting five minutes each at different atmospheric pressures. The HRV was dissected into two components: the respiratory component, which is linked to respiration; and the residual component, which is influenced by factors beyond respiration. Nine parameters were assessed, including the respiratory rate, four classic HRV temporal parameters, and four frequency parameters. A k-nearest neighbors classifier based on cosine distance successfully identified the atmospheric pressures to which the subjects were exposed to. The classifier achieved an 88.5% accuracy rate in distinguishing between the 5 atm and 3 atm stages using only four features: respiratory rate, heart rate, and two frequency parameters associated with the subjects’ sympathetic responses. Furthermore, the study identified 6 out of 28 subjects as having atypical responses across all pressure levels when compared to the majority. Interestingly, two of these subjects stood out in terms of gender and having less prior diving experience, but they still exhibited normal responses to immersion. This suggests the potential for establishing distinct safety protocols for divers based on their previous experience and gender.
American Sign Language Recognition and Translation Using Perception Neuron Wearable Inertial Motion Capture System
Authors: Gu Yutong , Oku Hiromasa , Todoh Masahiro
Published: January 2024

Sign language is designed as a natural communication method to convey messages among the deaf community. In the study of sign language recognition through wearable sensors, the data sources are limited, and the data acquisition process is complex. This research aims to collect an American sign language dataset with a wearable inertial motion capture system and realize the recognition and end-to-end translation of sign language sentences with deep learning models. In this work, a dataset consisting of 300 commonly used sentences is gathered from 3 volunteers. In the design of the recognition network, the model mainly consists of three layers: convolutional neural network, bi-directional long short-term memory, and connectionist temporal classification. The model achieves accuracy rates of 99.07% in word-level evaluation and 97.34% in sentence-level evaluation. In the design of the translation network, the encoder-decoder structured model is mainly based on long short-term memory with global attention. The word error rate of end-to-end translation is 16.63%. The proposed method has the potential to recognize more sign language sentences with reliable inertial data from the device.
Remote Photoplethysmography and Motion Tracking Convolutional Neural Network with Bidirectional Long Short-Term Memory: Non-Invasive Fatigue Detection Method Based on Multi-Modal Fusion
Authors: Kong Lingjian , Xie Kai , Niu Kaixuan , He Jianbiao , Zhang Wei
Published: January 2024

Existing vision-based fatigue detection methods commonly utilize RGB cameras to extract facial and physiological features for monitoring driver fatigue. These features often include single indicators such as eyelid movement, yawning frequency, and heart rate. However, the accuracy of RGB cameras can be affected by factors like varying lighting conditions and motion. To address these challenges, we propose a non-invasive method for multi-modal fusion fatigue detection called RPPMT-CNN-BiLSTM. This method incorporates a feature extraction enhancement module based on the improved Pan–Tompkins algorithm and 1D-MTCNN. This enhances the accuracy of heart rate signal extraction and eyelid features. Furthermore, we use one-dimensional neural networks to construct two models based on heart rate and PERCLOS values, forming a fatigue detection model. To enhance the robustness and accuracy of fatigue detection, the trained model data results are input into the BiLSTM network. This generates a time-fitting relationship between the data extracted from the CNN, allowing for effective dynamic modeling and achieving multi-modal fusion fatigue detection. Numerous experiments validate the effectiveness of the proposed method, achieving an accuracy of 98.2% on the self-made MDAD (Multi-Modal Driver Alertness Dataset). This underscores the feasibility of the algorithm. In comparison with traditional methods, our approach demonstrates higher accuracy and positively contributes to maintaining traffic safety, thereby advancing the field of smart transportation.
Multilevel Pain Assessment with Functional Near-Infrared Spectroscopy: Evaluating ΔHBO2 and ΔHHB Measures for Comprehensive Analysis
Authors: Khan Muhammad Umar , Sousani Maryam , Hirachan Niraj , Joseph Calvin , Ghahramani Maryam , Chetty Girija , Goecke Roland , Fernandez-Rojas Raul
Published: January 2024

Assessing pain in non-verbal patients is challenging, often depending on clinical judgment which can be unreliable due to fluctuations in vital signs caused by underlying medical conditions. To date, there is a notable absence of objective diagnostic tests to aid healthcare practitioners in pain assessment, especially affecting critically-ill or advanced dementia patients. Neurophysiological information, i.e., functional near-infrared spectroscopy (fNIRS) or electroencephalogram (EEG), unveils the brain’s active regions and patterns, revealing the neural mechanisms behind the experience and processing of pain. This study focuses on assessing pain via the analysis of fNIRS signals combined with machine learning, utilising multiple fNIRS measures including oxygenated haemoglobin (ΔHBO2) and deoxygenated haemoglobin (ΔHHB). Initially, a channel selection process filters out highly contaminated channels with high-frequency and high-amplitude artifacts from the 24-channel fNIRS data. The remaining channels are then preprocessed by applying a low-pass filter and common average referencing to remove cardio-respiratory artifacts and common gain noise, respectively. Subsequently, the preprocessed channels are averaged to create a single time series vector for both ΔHBO2 and ΔHHB measures. From each measure, ten statistical features are extracted and fusion occurs at the feature level, resulting in a fused feature vector. The most relevant features, selected using the Minimum Redundancy Maximum Relevance method, are passed to a Support Vector Machines classifier. Using leave-one-subject-out cross validation, the system achieved an accuracy of 68.51%±9.02% in a multi-class task (No Pain, Low Pain, and High Pain) using a fusion of ΔHBO2 and ΔHHB. These two measures collectively demonstrated superior performance compared to when they were used independently. This study contributes to the pursuit of an objective pain assessment and proposes a potential biomarker for human pain using fNIRS.
A Cross-Sectional Observational Pilot Study of the Main Risk Factors Related to Lower Back Pain in Spanish Hospitality Workers
Authors: Zamorano García Melania , Santamaría Gema , Seco-Casares Marina , Celorrio San Miguel Ana M. , Lantarón-Caeiro Eva , García Juan F. , Fernández-Lázaro Diego
Published: January 2024

Lower back pain (LBP) describes pain of indeterminate duration between the lower edge of the ribs and the buttocks. LBP hinders movement, quality of life, and mental well-being, and limits work activities and engagement with family and friends. LBP represents a public health problem, and most workers are expected to experience LBP symptoms throughout their working lives. The study’s main objective was to characterize LBP in the hospitality population of the province of León, Spain, determining the risk factors. A pilot study with a cross-sectional observational design was developed following the guidelines of Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) for 150 Spanish hotel workers. Sociodemographic and lifestyle, occupational, and clinical data related to LBP were obtained through surveys. The annual prevalence of LBP in this study was 87.1% which was higher in women. A significant relationship (p < 0.05) was obtained between sex, income, smoking, sleep quality, and all labor variables with LBP. In addition, the Fear Avoidance Beliefs Questionnaire (FABQ) results revealed that 49% of the participants had a score > 14. Also, 83.3% of patients with >6 annual LBP crises suffered from sciatica. Once the results were known, preventive intervention would be needed to reduce these main risk factors for LBP for hospitality workers.
Headspace Solid-Phase Micro-Extraction Method Optimization and Evaluation for the Volatile Compound Extraction of Bronchoalveolar Lung Lavage Fluid Samples
Authors: Gao Antao , Nouri Nina , Stevenson Keisean , Zemanick Edith T. , Nick Jerry A. , Hill Jane E.
Published: January 2024

Headspace solid-phase micro-extraction (HS-SPME) is a prevalent technique in metabolomics and volatolomics research. However, the performance of HS-SPME can vary considerably depending on the sample matrix. As a result, fine-tuning the parameters for each specific sample matrix is crucial to maximize extraction efficacy. In this context, we conducted comprehensive HS-SPME optimization for bronchoalveolar lavage fluid (BALF) samples using two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-ToFMS). Our exploration spanned several HS-SPME parameters, including vial size, dilution factor, extraction time, extraction temperature, and ionic strength. The 10 mL vial size, no sample dilution, extraction time of 50 min, extraction temperature of 45 °C, and 40% salt were identified as the optimized parameters. The optimized method was then evaluated by a pair-wise comparison of ten sets of samples. The results revealed that the optimized method yielded an increase of 340% in total peak area and an increase of 80% in total peak number. Moreover, enhancements were observed across nine major chemical classes in both peak area and number. Notably, the optimized method also doubled the number of volatile compounds consistently detected across BALF samples, from 52 to 108.
Tourism Urbanisation in Metropolitan Fringe: Insights from the Tourist City of Lavasa in Pune, India
Authors: Hambarde Anubandh , Shinde Kiran
Published: January 2024

This paper examines the processes surrounding tourism-led urbanisation in the periphery of a metropolitan region using the case of Pune—a metropolitan city in India. Pune houses five million people and its hinterlands were amalgamated in 2016 into the Pune Metropolitan Region (PMR) administered by Pune Metropolitan Region Development Authority. We used a geographical perspective of core-periphery focusing on “destination-bound” and “citybound” angles for conceptualising tourism in PMR. We draw attention to the significance of “destination-bound” flows from the core to the periphery using a detailed study of Lavasa city—a tourism destination located 60 km southwest of Pune. A morphological study of the Lavasa tourism sub-region was conducted using temporal mapping and direct observations at two scales: within the Lavasa city, and along the road connecting Lavasa with Pune city. The findings show how a “tourism corridor” is created when the destination at the periphery is a tourist attraction. The corridor is characterised by informal tourism activities that are outside the reach of the tourism policy. We argue that tourism sub-regions generate settlements and landscapes in the peripheries of metropolitan regions, particularly around natural resources. These leisure spaces in the periphery and hinterlands contribute to the distinct territoriality of metropolitan regions.
White Paper on Textile Fibre Recycling Technologies
Authors: Stubbe Birgit , Van Vrekhem Stijn , Huysman Sofie , Tilkin Rémi G. , De Schrijver Isabel , Vanneste Myriam
Published: January 2024

As both governments and customers push for sustainable and recyclable textile products, textile companies will have to change their linear business model to a circular one. The aim of the present work is to help these companies take action by providing an update of the state-of-the-art of textile recycling technologies. Extensive desktop research was performed in order to prepare an overview of existing textile recycling technologies, their current state, and projected developments, also including facilitating technologies for sorting and disintegration of textile products, as well as virtual platforms that connect stakeholders and inform consumers.
Regional Products and Sustainability
Authors: Haid Marco , Albrecht Julia N. , Tangl Pascal , Plaikner Alexander
Published: January 2024

The production, sale, and consumption of regional products can positively influence a region’s sustainable development. Despite this significance, there is little research on how consumers perceive regional products using a sustainability lens. This study investigates the perception of regional products in terms of sustainability and related customer purchasing behaviour. Qualitative, semi-structured interviews were conducted with 18 participants in Tyrol, Austria. Data analysis employs a deductive-inductive coding approach and shows a high awareness of sustainability among respondents. The main reasons for purchasing regional products are supporting the local economy and regional agriculture. Shorter transport routes or the cultural landscape maintenance are also important factors due to environmental concerns. Most participants report that sustainability was a decisive factor in their purchase decision pertaining to regional products. Regional products and sustainability are thus intertwined from a customer perspective and are shown to have decisive roles in related purchasing behaviour.
Review: Microemulsions for the Sustainable Development of EOR
Authors: Hu Haibin , Zhang Qun , Tian Maozhang , Li Yuan , Han Xu , Guo Rui
Published: January 2024

Global oil and gas resources are declining continuously, and sustainable development has become a common challenge worldwide. In terms of environmental protection and economic benefits, the application of microemulsions for enhanced oil recovery often requires fewer chemical agents, showing distinct advantages. This paper analyzes the application prospects and trends of middle-phase microemulsions in tertiary oil recovery. The properties of middle-phase microemulsions are introduced, and an overview of the historical development, theoretical framework, influencing factors, and preparation methods of emulsions are provided. From the perspective of oil displacement systems, this paper reviews the selection and characterization methods of emulsions, as well as the interaction mechanisms between emulsions and reservoirs, proposing future research directions. The focus of the paper is on the evaluation and characterization of emulsions, the mechanisms of micro-oil displacement, and the application of advanced CT scanning technology, which gives a new understanding of wettability changes, capillary forces, and miscible solubilization processes, contributing to the reduction in displacement costs and the improvement of economic benefits. In conclusion, the middle-phase microemulsion flooding technique can significantly enhance oil recovery through the comprehensive action of various mechanisms and has been widely used in oil field development.
Implementation of BIM Data in CityGML—Research and Perspectives for Creating a QGIS Plugin for Spatial Analysis: Experience from Poland
Authors: Janisio-Pawłowska Dorota , Pawłowski Wojciech
Published: January 2024

The subject of this research was to develop an effective strategy for combining various data sources, including the feasibility of implementing BIM in CityGML into an existing system supported by the GIS program. The study analyzed the path for converting BIM files to the CityGML format and the course of transmission of this data and data from the completed queries to the GIS program. An overview of external sources, map services, tools for acquiring accurate information about the terrain, and IT tools that could potentially be used was also carried out. The collected data proved deficiencies in the geospatial information of the analyzed area, defining the type of missing data necessary for the planned analyses. The results made it possible to determine further work and the basis for developing a plugin for the QGIS program. The plugin should facilitate energy efficiency, urban, and architectural analyses. The article also discusses the future opportunities for developing research directions for developing new 3D models of cities and collecting data for analysis. The analyses took into account the directions of geometric changes in 3D models as the result of the rapid development of digital tools. Ultimately, this research demonstrated the development demand for modern digital tools in the context of spatial and urban analysis, emphasizing the dynamic evolution in the field of GIS and the prospects of accelerating work on the integration of spatial data and their analysis thanks to the possibility of using open-source programs and our own efforts for their expansion.
Evaluating Intra-Field Spatial Variability for Nutrient Management Zone Delineation through Geospatial Techniques and Multivariate Analysis
Authors: Salem Haytham Mohamed , Schott Linda R. , Piaskowski Julia , Chapagain Asmita , Yost Jenifer L. , Brooks Erin , Kahl Kendall , Johnson-Maynard Jodi
Published: January 2024

This research study underscores the importance of effectively managing soil nutrients in a site-specific manner to enhance crop productivity while considering the spatial variability of the soil. The objective is to identify subfields with similar soil characteristics, referred to as management zones (MZs), to promote sustainable land utilization. This study was conducted in two central pivot fields located in Southern Idaho, USA, where barley and sugar beets were grown. Soil samples were collected from each field in a grid pattern and analyzed for various chemical properties. These properties included soil pH, organic matter, cation exchange capacity, excess lime, electrical conductivity, total inorganic nitrogen, phosphorus, potassium, calcium, magnesium, zinc, iron, manganese, copper, and boron. Descriptive statistics and normality assessments were performed, and the coefficient of variation was calculated to assess the heterogeneity of soil properties, revealing significant variability. To determine the spatial variability of soil properties, ordinary kriging was used revealing diverse spatial patterns for each location and soil variable examined with moderate to strong spatial dependence. To develop the MZs, a combination of principal component analysis and fuzzy k-means clustering was utilized, and specific parameters that represented the overall variability of soil properties in each field were identified. Based on the identified parameters, two clusters were created in each field. The first management zone (MZ1) exhibited lower values of soil pH, excess lime content, and electrical conductivity compared to the MZ2. Consequently, higher crop productivity was observed in MZ1 in both fields. The biomass yields of barley and sugar beets in MZ1 surpassed those in MZ2. This study highlights the effectiveness of the methodology employed to delineate MZs, which can be instrumental in precise soil nutrient management and maximizing crop productivity.
Exploring the Role of Digital Transformation and Breakthrough Innovation in Enhanced Performance of Energy Enterprises: Fresh Evidence for Achieving Sustainable Development Goals
Authors: Yu Yang , Ren Fangrong , Ju Yun , Zhang Jingyi , Liu Xiaoyan
Published: January 2024

The energy sector’s digital evolution is a critical micro-reflection of the digital economy’s architecture and an essential tactical pathway for achieving sustainable development goals. However, the value of digital change in regard to how effectively energy firms’ core business functions is not yet apparent. This research utilizes textual analysis to quantify the textual intensity of energy enterprises’ digitization. Applying data gathered from A-share listed firms in Shanghai and Shenzhen from 2010 to 2021 and based upon the fixed-effects panel model and mediated effects model, we assess the impact of digitization on critical business performance and evaluate the research themes’ variability from business and geographical viewpoints using a full-sample strategy. We derive three notable findings. First, the digital development of energy enterprises significantly improves the performance of their core businesses and exhibits some fluctuating characteristics. Second, the digitization of energy enterprises greatly increases the input and output of enterprise innovation, thereby improving the efficiency of their core business in the two main ways of breakthrough innovation. Third, there is a nonlinear relationship between the performance of energy enterprises’ core businesses and their digital transformation, meaning there is just one threshold consequence that diminishes after crossing the threshold. Digital transformation enables energy companies to carry out cross-border cooperation and integrate innovative resources, thereby improving corporate performance and promoting sustainable development. This paper offers relevant insights for more effective fostering of digital transformation and can help spur enterprises to seek out distinctive and ground-breaking innovation models.