bluuebunny/crossref_metadata_2025 huggingface dataset:
Ultraviolet-Ozone Treatment: An Effective Method for Fine-Tuning Optical and Electrical Properties of Suspended and Substrate-Supported MoS2
Authors: Sarcan Fahrettin , Armstrong Alex J. , Bostan Yusuf K. , Kus Esra , McKenna Keith P. , Erol Ayse , Wang Yue
Published: November 2023

Ultraviolet-ozone (UV-O3) treatment is a simple but effective technique for surface cleaning, surface sterilization, doping, and oxidation, and is applicable to a wide range of materials. In this study, we investigated how UV-O3 treatment affects the optical and electrical properties of molybdenum disulfide (MoS2), with and without the presence of a dielectric substrate. We performed detailed photoluminescence (PL) measurements on 1–7 layers of MoS2 with up to 8 min of UV-O3 exposure. Density functional theory (DFT) calculations were carried out to provide insight into oxygen-MoS2 interaction mechanisms. Our results showed that the influence of UV-O3 treatment on PL depends on whether the substrate is present, as well as the number of layers. Additionally, 4 min of UV-O3 treatment was found to be optimal to produce p-type MoS2, while maintaining above 80% of the PL intensity and the emission wavelength, compared to pristine flakes (intrinsically n-type). UV-O3 treatment for more than 6 min not only caused a reduction in the electron density but also deteriorated the hole-dominated transport. It is revealed that the substrate plays a critical role in the manipulation of the electrical and optical properties of MoS2, which should be considered in future device fabrication and applications.
The Potential of Vitamin K as a Regulatory Factor of Bone Metabolism—A Review
Authors: Wang Huakai , Ma Yongxi
Published: November 2023

Vitamin K (VK), a fat-soluble vitamin, is essential for the clotting of blood because of its role in the production of clotting factors in the liver. Moreover, researchers continue to explore the role of VK as an emerging novel bioactive molecule with the potential function of improving bone health. This review focuses on the effects of VK on bone health and related mechanisms, covering VK research history, homologous analogs, dietary sources, bioavailability, recommended intake, and deficiency. The information summarized here could contribute to the basic and clinical research on VK as a natural dietary additive and drug candidate for bone health. Future research is needed to extend the dietary VK database and explore the pharmacological safety of VK and factors affecting VK bioavailability to provide more support for the bone health benefits of VK through more clinical trials.
The Effect of Levagen+ (Palmitoylethanolamide) Supplementation on Symptoms of Allergic Rhinitis—A Double-Blind Placebo-Controlled Trial
Authors: Briskey David , Ebelt Phillippa , Rao Amanda
Published: November 2023

Background: Allergic rhinitis (AR) is an inflammatory, symptomatic disorder stimulated by antigen-specific immunoglobulin E inflammation in response to allergens. Current treatments include the use of corticosteroids and antihistamines to reduce inflammation by preventing histamine release. Palmitoylethanolamide (PEA) is reported to be an alternative treatment, shown to downregulate mast cell activation and increase the synthesis of endocannabinoid 2-Arachidonoylglycerol to reduce histamine and the symptoms of AR. Method: A double-blind, randomised, placebo-controlled clinical trial in which 108 participants presenting with seasonal AR were supplemented with either 350 mg of PEA (Levagen+) or a placebo daily for two weeks. Symptom scores were recorded using the reflective total nasal symptom score (rTNSS) twice a day (morning and evening) for the two weeks, and blood was taken at baseline and week 2. Results: 101 participants completed the study with no baseline group differences. No significant difference was seen between groups for allergy symptoms scores (rTNSS) throughout the 14 days of treatment. A sub-group analysis of participants scoring over four (mild-to-moderate) on the total rTNSS at baseline showed that Levagen+ significantly reduced scores compared to the placebo group. Only 36 participants had full sets of blood taken due to COVID-19. The pathology results showed a significant difference in change from baseline between groups. The Levagen+ group had a significant decrease from baseline in histamine, IL-4, IL-8, IL-10, and TNF-α. The placebo group only had a reduction in IL-4. Conclusion: The results of this study show that Levagen+ can alleviate AR symptoms, resulting in a reduction in histamine and inflammatory markers.
Synthesis of 2-Substituted Benzimidazole Derivatives as a Platform for the Development of UV Filters and Radical Scavengers in Sunscreens
Authors: Anichina Kameliya K. , Georgiev Nikolai I.
Published: November 2023

The modern trend in sunscreen products is towards the development of UV filters with multi-functional properties, to provide a broad shielding against ultraviolet radiation, antioxidant activity, and the prevention of skin cancer. Additionally, they should also be safe for humans as well as the environment. The benzimidazole heterocycle is a suitable platform for the development of such multifunctional molecules with potential application in cosmetic formulations, due to their ability to act as both UV protectors and reactive pharmacophores. This review presents for the first time the progress in the synthesis and optimization of benzimidazole compounds as UV sunscreen filters. The modifications to the substitution pattern of the lead compound and structure–activity relationships are discussed, as well as the synthetic approaches for the preparation of 2-substituted benzimidazoles. These aggregated data will be useful in future in the development of modern benzimidazole-based sunscreen.
Inhalation Dosage Forms: A Focus on Dry Powder Inhalers and Their Advancements
Authors: Magramane Sabrina , Vlahović Kristina , Gordon Péter , Kállai-Szabó Nikolett , Zelkó Romána , Antal István , Farkas Dóra
Published: November 2023

In this review, an extensive analysis of dry powder inhalers (DPIs) is offered, focusing on their characteristics, formulation, stability, and manufacturing. The advantages of pulmonary delivery were investigated, as well as the significance of the particle size in drug deposition. The preparation of DPI formulations was also comprehensively explored, including physico-chemical characterization of powders, powder processing techniques, and formulation considerations. In addition to manufacturing procedures, testing methods were also discussed, providing insights into the development and evaluation of DPI formulations. This review also explores the design basics and critical attributes specific to DPIs, highlighting the significance of their optimization to achieve an effective inhalation therapy. Additionally, the morphology and stability of 3 DPI capsules (Spiriva, Braltus, and Onbrez) were investigated, offering valuable insights into the properties of these formulations. Altogether, these findings contribute to a deeper understanding of DPIs and their development, performance, and optimization of inhalation dosage forms.
Formation Kinetics and Antimicrobial Activity of Silver Nanoparticle Dispersions Based on N-Reacetylated Oligochitosan Solutions for Biomedical Applications
Authors: Urodkova Ekaterina K. , Uryupina Ol’ga Ya. , Tikhonov Vladimir E. , Grammatikova Natalia E. , Bol’shakova Anastasia V. , Sinelshchikova Anna A. , Zvyagina Alexandra I. , Khmelenin Dmitry N. , Zhavoronok Elena S. , Senchikhin Ivan N.
Published: November 2023

The paper presents the results of the synthesis, a detailed kinetics study, and an investigation of the biological activity of silver nanoparticles (AgNPs) in aqueous solutions of N-reacetylated oligochitosan hydrochloride. UV–visible spectrophotometry and dynamic light scattering were employed to control silver ion reduction. The process was observed to follow a pseudo-first-order law. Transmission and scanning electron microscopy demonstrated that AgNPs ranging in size from 10 to 25 nm formed aggregates measuring 60 to 90 nm, with the aggregate surface coated by a 2–4 nm chitosan shell. X-ray microanalysis and powder X-ray diffractometry were used to study the phase composition, identifying two crystalline phases, nanocrystalline silver and AgCl, present in the dispersions. The antibacterial effect was assessed using the serial dilution method for dispersions with varying degrees of Ag+ conversion. Nanodispersions exhibited significant activity against Escherichia coli, Pseudomonas aeruginosa, Bacillus cereus, and Staphylococcus aureus. Interestingly, the activity did not appear to be heavily influenced by the presence of the AgCl phase or the concentration of Ag+ ions. These synthesized dispersions hold promise for the development of materials tailored for biomedical applications.
Fish Scale Gelatin Nanofibers with Helichrysum italicum and Lavandula latifolia Essential Oils for Bioactive Wound-Healing Dressings
Authors: Gaidau Carmen , Râpă Maria , Stanca Maria , Tanase Mariana-Luiza , Olariu Laura , Constantinescu Rodica Roxana , Lazea-Stoyanova Andrada , Alexe Cosmin-Andrei , Tudorache Madalina
Published: November 2023

Essential oils are valuable alternatives to synthetic antibiotics that have the potential to avoid the pathogen resistance side effects generated by leather. Helichrysum italicum and Lavandula latifolia essential oils combined with fish scale gelatin were electrospun using a coaxial technique to design new bioactive materials for skin wound dressings fabrication. Fish scale gelatins were extracted from carp fish scales using two variants of the same method, with and without ethylenediaminetetraacetic acid (EDTA). Both variants showed very good electrospinning properties when dissolved in acetic acid solvent. Fish scale gelatin nanofibers with Helichrysum italicum and Lavandula latifolia essential oil emulsions ensured low microbial load (under 100 CFU/g of total number of aerobic microorganisms and total number of yeasts and filamentous fungi) and the absence of Staphylococcus aureus ATCC 6538, Escherichia coli ATCC 10536, and Candida albicans ATCC 1023 as compared to fish scale gelatin without essential oils, which recommends them for pharmaceutical or topical applications. A scratch-test performed on human dermal fibroblasts proved that the biomaterials contributing to the wound healing process included fish scale gelatin nanofibers without EDTA (0.5% and 1%), fish scale gelatin nanofibers without EDTA and Lavandula latifolia essential oil emulsion (1%), fish scale gelatin nanofibers with EDTA (0.6%), and fish scale gelatin nanofibers with EDTA with Helichrysum italicum essential oil emulsion (1% and 2%).
Novel Nanoprobe with Combined Ultrasonography/Chemical Exchange Saturation Transfer Magnetic Resonance Imaging for Precise Diagnosis of Tumors
Authors: Ding Jieqiong , He Liu , Yang Lin , Cheng Liyuan , Zhao Zhiwei , Luo Binhua , Jia Yanlong
Published: November 2023

Given that cancer mortality is usually due to a late diagnosis, early detection is crucial to improve the patient’s results and prevent cancer-related death. Imaging technology based on novel nanomaterials has attracted much attention for early-stage cancer diagnosis. In this study, a new block copolymer, poly(ethylene glycol)-poly(l-lactide) diblock copolymer (PEG-PLLA), was synthesized by the ring-opening polymerization method and thoroughly characterized using Fourier transform infrared spectroscopy (FT-IR), proton nuclear magnetic resonance spectroscopy (H-NMR), X-ray diffraction (XRD), and thermogravimetric analysis (TGA). The obtained PEG-PLLA was used to prepare nanoparticles encapsulated with perfluoropentane and salicylic acid by the emulsion-solvent evaporation method, resulting in a new dual-mode nano-image probe (PEG-PLLA@SA·PFP). The zeta potential and mean diameter of the obtained nanoparticles were measured using dynamic light scattering (DLS) with a Malvern Zetersizer Nano. The in vitro biocompatibility of the PEG-PLLA nanoparticles was evaluated with cell migration, hemolysis, and cytotoxicity assays. Ultrasonic imaging was performed using an ultrasonic imaging apparatus, and chemical exchange saturation transfer (CEST) MRI was conducted on a 7.0 T animal scanner. The results of IR and NMR confirmed that the PEG-PLLA was successfully synthesized. The particle size and negative charge of the nanoparticles were 223.8 ± 2.5 nm and −39.6 ± 1.9 mV, respectively. The polydispersity of the diameter was 0.153 ± 0.020. These nanoparticles possessed good stability at 4 °C for about one month. The results of cytotoxicity, cell migration, and hemolysis assays showed that the carrier material was biocompatible. Finally, PEG-PLLA nanoparticles were able to significantly enhance the imaging effect of tumors by the irradiation of ultrasound and saturation by a radiofrequency pulse, respectively. In conclusion, these nanoparticles exhibit promising dual-mode capabilities for US/CEST MR imaging.
Temoporfin-Conjugated Upconversion Nanoparticles for NIR-Induced Photodynamic Therapy: Studies with Pancreatic Adenocarcinoma Cells In Vitro and In Vivo
Authors: Shapoval Oleksandr , Větvička David , Patsula Vitalii , Engstová Hana , Kočková Olga , Konefał Magdalena , Kabešová Martina , Horák Daniel
Published: November 2023

Upconverting nanoparticles are interesting materials that have the potential for use in many applications ranging from solar energy harvesting to biosensing, light-triggered drug delivery, and photodynamic therapy (PDT). One of the main requirements for the particles is their surface modification, in our case using poly(methyl vinyl ether-alt-maleic acid) (PMVEMA) and temoporfin (THPC) photosensitizer to ensure the colloidal and chemical stability of the particles in aqueous media and the formation of singlet oxygen after NIR irradiation, respectively. Codoping of Fe2+, Yb3+, and Er3+ ions in the NaYF4 host induced upconversion emission of particles in the red region, which is dominant for achieving direct excitation of THPC. Novel monodisperse PMVEMA-coated upconversion NaYF4:Yb3+,Er3+,Fe2+ nanoparticles (UCNPs) with chemically bonded THPC were found to efficiently transfer energy and generate singlet oxygen. The cytotoxicity of the UCNPs was determined in the human pancreatic adenocarcinoma cell lines Capan-2, PANC-01, and PA-TU-8902. In vitro data demonstrated enhanced uptake of UCNP@PMVEMA-THPC particles by rat INS-1E insulinoma cells, followed by significant cell destruction after excitation with a 980 nm laser. Intratumoral administration of these nanoconjugates into a mouse model of human pancreatic adenocarcinoma caused extensive necrosis at the tumor site, followed by tumor suppression after NIR-induced PDT. In vitro and in vivo results thus suggest that this nanoconjugate is a promising candidate for NIR-induced PDT of cancer.
Recent Advances in Micro- and Nano-Drug Delivery Systems Based on Natural and Synthetic Biomaterials
Authors: Harun-Or-Rashid Md. , Aktar Most. Nazmin , Hossain Md. Sabbir , Sarkar Nadia , Islam Md. Rezaul , Arafat Md. Easin , Bhowmik Shukanta , Yusa Shin-ichi
Published: November 2023

Polymeric drug delivery technology, which allows for medicinal ingredients to enter a cell more easily, has advanced considerably in recent decades. Innovative medication delivery strategies use biodegradable and bio-reducible polymers, and progress in the field has been accelerated by future possible research applications. Natural polymers utilized in polymeric drug delivery systems include arginine, chitosan, dextrin, polysaccharides, poly(glycolic acid), poly(lactic acid), and hyaluronic acid. Additionally, poly(2-hydroxyethyl methacrylate), poly(N-isopropyl acrylamide), poly(ethylenimine), dendritic polymers, biodegradable polymers, and bioabsorbable polymers as well as biomimetic and bio-related polymeric systems and drug-free macromolecular therapies have been employed in polymeric drug delivery. Different synthetic and natural biomaterials are in the clinical phase to mitigate different diseases. Drug delivery methods using natural and synthetic polymers are becoming increasingly common in the pharmaceutical industry, with biocompatible and bio-related copolymers and dendrimers having helped cure cancer as drug delivery systems. This review discusses all the above components and how, by combining synthetic and biological approaches, micro- and nano-drug delivery systems can result in revolutionary polymeric drug and gene delivery devices.
Remembering Hagar and Her Son (Gen 21: 9–21): A Narrative Reading of Helpless Victims and Hopeful Survivors in the Wheel of Providence
Authors: Boloje Blessing Onoriode
Published: November 2023

Narratives are fundamentals of storytelling. In Biblical literature, narratives do not only tell what happened (the context for God’s revelation), they also indicate why what happened matters (the purpose of history). Employing a narrative methodology and a hermeneutic of identification as an interpretive approach, this article explores the Hagar–Ishmael narrative in Genesis 21: 9–21 against the background of those who have been marginalized, exploited, excluded, trafficked, and sitting in a wilderness of despair, struggle, and mistreatment and are in need of survival. The exploration seeks to understand the narrative structure, plot, characters, and themes within the text. The Hagar–Ishmael position is too painfully close to the realities of many today. In this narrative account, one finds a pitiable scene of human suffering and misery, and yet it is bounded by divine mercy and compassion. The stream of helplessness and consequent hope of survival shows that, no matter how mistreated people might have been, they can rise above their “victimization” and embrace the promises of God by staving off defeat, shaking off despair, and vanquishing discouragement. Thus with a hermeneutic of identification, readers are encouraged to identify with the characters, situations, and experiences described in the biblical narrative.
Desiderio desideravi: A Prolegomena to Liturgical Formation? The Relationship between Pastoral Care and the Liturgy Itself in the Process of Formation in the Liturgy
Authors: Buttigieg Dorianne
Published: November 2023

Pope Francis’ apostolic letter Desiderio desideravi, promulgated in 2022, highlights the crux of the formation in the liturgy of the faithful. This has become especially poignant in a contemporary world, where the attribute of the symbol, stemming from a technological world, has stemmed the window into the transcendent (The double meaning of the verb "stem" is intentional). An important point is the role of formation through the liturgy itself. However, how does this formation of the liturgy through the liturgy itself have potential benefit for the faithful? Regarding the experience which the liturgy imparts to the participants, this cannot occur without the role and the dynamics of the whole person involved in the experience. This paper seeks to address the role of pastoral care and its relationship to worship and to show how said process of formation in the liturgy through the liturgy itself can yield the highest spiritual and transformative benefit.
The “Angel of Light at Work”: An Assessment of the Christian Mission in the Southern Hemisphere
Authors: Okitafumba Lokola Raphael
Published: November 2023

Today, it is commonplace to hear that Africa is the hope of Christianity. Using the Ignatian image of “the angel of light”, this paper proposes to qualify this belief. I will show that this belief is verified quantitively. However, the lack of authentic Christian witness makes the above assertion problematic. My analysis will focus on the tradition of the églises de réveil (awakening churches) in Francophone Africa, especially in the Democratic Republic of the Congo. This contemporary tradition is a hybrid Christian movement that combines Evangelical and Pentecostal attitudes. I will develop my analysis in three steps. First, I will discuss the nature of églises de réveil. Second, I will describe the modus operandi of these awakening churches. My discussion will indicate how this modus operandi works in urban and rural areas. Lastly, I will propose one perspective for authentic Christian growth. I will argue that a Christian mission needs to be radically Christocentric. This radical Christocentrism revolves around two major axes, namely a sign of contradiction vis-à-vis the world and a radical witness of the Gospel of Jesus Christ.
Reviving Premodern Africa? The Anointed Objects and the Magical Economy in Un(der)developed Africa
Authors: Banda Collium
Published: November 2023

African neo-Pentecostal prophets (ANPPs) address the issue of economic powerlessness in un(der)developed regions of Africa by reviving elements of the premodern African magical economy. They use anointed objects, such as anointed water, for economic purposes, while African Traditional Religions (ATR) use magical charms in their economic life. Therefore, with their anointed objects, ANPPs revive the premodern ATR worldview of the economy. This research is guided by the following question: in what ways do ANPPs’ anointed objects syncretise with the occult economy of African Traditional Religions (ATRs) in their responses to the prevailing economic powerlessness in African contexts? ANPPs perpetuate the magical economy practiced by premodern African societies who sought to alleviate their un(der)development by using magic to exert control over the spiritual world to acquire material wealth. Thus, ANPPs are challenged to adopt a scientifically informed response that empowers Africans to address structural elements that perpetuate un(der)development in contemporary Africa.
A Modified Iteration-Free SPGA Based on Removing the Linear Phase
Authors: Xie Yi , Luan Yuchen , Chen Longyong , Zhang Xin
Published: November 2023

In traditional Stripmap SAR imaging, the platform motion error will bring the phase error in the azimuthal direction to the image, which will have a series of effects on the imaging quality. The traditional autofocus algorithm—Stripmap Phase Gradient Algorithm (SPGA)—can estimate any order phase error above the second order in theory, but it is difficult to estimate the linear phase error, which leads to the discontinuity of the estimated phase error. It usually needs multiple iterations to focus an image, which is inefficient. Moreover, because the linear phase error cannot be estimated, the traditional SPGA cannot eliminate the target offset in the image, resulting in the distortion of the image in the azimuthal direction. According to the continuity of phase error, we propose a modified iteration-free SPGA based on removing the linear phase. Without iteration, the proposed autofocus algorithm can achieve comparable or even better results than traditional SPGA. In the simulation experiments, piecewise linear errors are added to the images of multiple targets. SPGA still fails to focus the image after six iterations. The average ILSR and ILSR are −7.11 dB and −3.99 dB, respectively, and the average number of point target drift is 8.42 pixels. The proposed algorithm optimizes the average ILSR and ILSR to −12.34 dB and −9.87 dB and reduces the average number of point target drift to 0.16 pixels. In the actual data processing, using image entropy as the evaluation criterion, the time consumption is only 19.25% of SPGA under the condition of achieving the same focusing quality.
A Satellite Observational Study of Topographical Effects on Daytime Shallow Convective Clouds
Authors: Xu Guoqiang , Fu Shizuo , Liu Jane , Shang Rong , Luo Yuanyuan
Published: November 2023

Shallow convective clouds (SCCs) frequently occur over mountainous terrain. However, previous studies have mostly focused on SCCs over flat surfaces. Here, the effects of mountainous terrains on the cloud size distributions (CSDs) and spatial distributions of SCCs are investigated using data obtained from the Landsat-8 satellite. We find that the CSDs are well-described by double power laws separated by scale breaks. The CSDs are controlled by two parameters, i.e., the scale breaks and the number of clouds with sizes between 0.2 and 1 times the scale breaks. We also find that the number of clouds generally increases with the elevation. In particular, the number of clouds larger than the scale breaks increases faster than that of the smaller clouds. The sizes of the larger clouds (the 90th and 95th percentiles) increase with the elevation, while the sizes of the smaller clouds are not sensitive to the elevation. It is suggested that the variations of cloud numbers and sizes with elevation should be used together with the CSDs to describe the cloud fields over mountainous terrains.
A Comparative Study of Landslide Susceptibility Mapping Using Bagging PU Learning in Class-Prior Probability Shift Datasets
Authors: Zhao Lingran , Ma Hangling , Dong Jiahui , Wu Xueling , Xu Hang , Niu Ruiqing
Published: November 2023

Landslide susceptibility mapping is typically based on binary prediction probabilities. However, non-landslide samples in modeling datasets are often unlabeled data, and the phenomenon of class-priori shift, that is, the proportion of landslide samples frequently deviates from real-world scenarios and is spatially heterogeneous. By comparing the classification performance and predicted probability distributions across multiple unbalanced datasets with known and unknown sample proportions, this study assesses the landslide susceptibility model’s generalization ability in the context of class-prior shifts. The study investigates the potential of Bagging PU Learning, a semi-supervised learning approach, in improving the generalization performance of landslide susceptibility models and proposes the Bagging PU-GDBT algorithm. Our findings highlight the effectiveness of Bagging PU Learning in enhancing the recall of landslides and the generalization capabilities of models on unbalanced datasets. This method reduces prediction uncertainties, especially in high and very high susceptibility zones. Furthermore, results emphasize the superiority of models trained on balanced datasets with 1:1 sample ratio for landslide susceptibility mapping over those trained on unbalanced datasets.
Causal Analysis of Physiological Sleep Data Using Granger Causality and Score-Based Structure Learning
Authors: Thomas Alex , Niranjan Mahesan , Legg Julian
Published: November 2023

Understanding how the human body works during sleep and how this varies in the population is a task with significant implications for medicine. Polysomnographic studies, or sleep studies, are a common diagnostic method that produces a significant quantity of time-series sensor data. This study seeks to learn the causal structure from data from polysomnographic studies carried out on 600 adult volunteers in the United States. Two methods are used to learn the causal structure of these data: the well-established Granger causality and “DYNOTEARS”, a modern approach that uses continuous optimisation to learn dynamic Bayesian networks (DBNs). The results from the two methods are then compared. Both methods produce graphs that have a number of similarities, including the mutual causation between electrooculogram (EOG) and electroencephelogram (EEG) signals and between sleeping position and SpO2 (blood oxygen level). However, DYNOTEARS, unlike Granger causality, frequently finds a causal link to sleeping position from the other variables. Following the creation of these causal graphs, the relationship between the discovered causal structure and the characteristics of the participants is explored. It is found that there is an association between the waist size of a participant and whether a causal link is found between the electrocardiogram (ECG) measurement and the EOG and EEG measurements. It is concluded that a person’s body shape appears to impact the relationship between their heart and brain during sleep and that Granger causality and DYNOTEARS can produce differing results on real-world data.
LocoBox: Modular Hardware and Open-Source Software for Circadian Entrainment and Behavioral Monitoring in Home Cages
Authors: Truong Vuong Hung , Myung Jihwan
Published: November 2023

Day–night locomotor activities are the most readily observed outputs of the circadian (~24-h period) clock in many animals. Temporal patterns of the light–dark schedule serve as input to the clock. While circadian activity patterns under various lighting conditions have been observed and documented, the full extent of circadian locomotor activities by genotype and entrainment remains uncharacterized. To facilitate large-scale, parallel cataloging of circadian input–output patterns, we created the LocoBox, an easy-to-construct and easy-to-operate system that can control environmental light with flexible entrainment scenarios combined with the T-cycle and measure locomotor activities in individual home cages. The LocoBox is made using economical, common components, and normal breeding cages can be used for long-term recording. We provide details of the components and blueprints, along with software programs for Arduino and a Python-based graphical user interface (GUI), so that the system can be easily replicated in other laboratories.
Development of a Simulation Model for Digital Twin of an Oscillating Water Column Wave Power Generator Structure with Ocean Environmental Effect
Authors: Kim Byungmo , Oh Jaewon , Min Cheonhong
Published: November 2023

This research article focuses on developing a baseline digital twin model for a wave power generator structure located in Yongsu-ri, Jeju-do, South Korea. First, this study performs a cause analysis on the discrepancy of the dynamic properties from the real structure and an existing simulation model and finds the necessity of modeling the non-structural masses and the environmental factors. The large amounts of the ballast are modeled in the finite element model to enhance the accuracy of the digital twin. Considering the influence of environmental factors such as tide level and wave direction, the added mass effect of structural members, one of the hydrodynamic effects, depending on the change of the ocean environments is calculated based on the rule of Det Norske Veritas and applied. The results indicate that non-structural mass components significantly impact the dynamic characteristics of the structure. Additionally, environmental factors have a greater effect on the dynamic behavior of the box-type structure compared to lightweight offshore structures.
Recognition of Arabic Air-Written Letters: Machine Learning, Convolutional Neural Networks, and Optical Character Recognition (OCR) Techniques
Authors: Nahar Khalid M. O. , Alsmadi Izzat , Al Mamlook Rabia Emhamed , Nasayreh Ahmad , Gharaibeh Hasan , Almuflih Ali Saeed , Alasim Fahad
Published: November 2023

Air writing is one of the essential fields that the world is turning to, which can benefit from the world of the metaverse, as well as the ease of communication between humans and machines. The research literature on air writing and its applications shows significant work in English and Chinese, while little research is conducted in other languages, such as Arabic. To fill this gap, we propose a hybrid model that combines feature extraction with deep learning models and then uses machine learning (ML) and optical character recognition (OCR) methods and applies grid and random search optimization algorithms to obtain the best model parameters and outcomes. Several machine learning methods (e.g., neural networks (NNs), random forest (RF), K-nearest neighbours (KNN), and support vector machine (SVM)) are applied to deep features extracted from deep convolutional neural networks (CNNs), such as VGG16, VGG19, and SqueezeNet. Our study uses the AHAWP dataset, which consists of diverse writing styles and hand sign variations, to train and evaluate the models. Prepossessing schemes are applied to improve data quality by reducing bias. Furthermore, OCR character (OCR) methods are integrated into our model to isolate individual letters from continuous air-written gestures and improve recognition results. The results of this study showed that the proposed model achieved the best accuracy of 88.8% using NN with VGG16.
A Versatile Approach to Polygonal Object Avoidance in Indoor Environments with Hardware Schemes Using an FPGA-Based Multi-Robot
Authors: Basha Mudasar , Siva Kumar Munuswamy , Chinnaiah Mangali Chinna , Lam Siew-Kei , Srikanthan Thambipillai , Janardhan Narambhatla , Hari Krishna Dodde , Dubey Sanjay
Published: November 2023

Service robots perform versatile functions in indoor environments. This study focuses on obstacle avoidance using flock-type indoor-based multi-robots. Each robot was developed with rendezvous behavior and distributed intelligence to perform obstacle avoidance. The hardware scheme-based obstacle-avoidance algorithm was developed using a bio-inspired flock approach, which was developed with three stages. Initially, the algorithm estimates polygonal obstacles and their orientations. The second stage involves performing avoidance at different orientations of obstacles using a heuristic based Bug2 algorithm. The final stage involves performing a flock rendezvous with distributed approaches and linear movements using a behavioral control mechanism. VLSI architectures were developed for multi-robot obstacle avoidance algorithms and were coded using Verilog HDL. The novel design of this article integrates the multi-robot’s obstacle approaches with behavioral control and hardware scheme-based partial reconfiguration (PR) flow. The experiments were validated using FPGA-based multi-robots.
Explainable Boosting Machine: A Contemporary Glass-Box Model to Analyze Work Zone-Related Road Traffic Crashes
Authors: Alahmadi Raed , Almujibah Hamad , Alotaibi Saleh , Elshekh Ali. E. A. , Alsharif Mohammad , Bakri Mudthir
Published: November 2023

Examining the factors contributing to work zone crashes and implementing measures to reduce their occurrence can significantly improve road safety. In this research, we utilized the explainable boosting machine (EBM), a modern glass-box machine learning (ML) model, to categorize and predict work zone-related crashes and to interpret the various contributing factors. The issue of data imbalance was also addressed by utilizing work zone crash data from the state of New Jersey, comprising data collected over the course of two years (2017 and 2018) and applying data augmentation strategies such synthetic minority over-sampling technique (SMOTE), borderline-SMOTE, and SVM-SMOTE. The EBM model was trained using augmented data and Bayesian optimization for hyperparameter tuning. The performance of the EBM model was evaluated and compared to black-box ML models such as combined kernel and tree boosting (KTBoost, python 3.7.1 and KTboost package version 0.2.2), light gradient boosting machine (LightGBM version 3.2.1), and extreme gradient boosting (XGBoost version 1.7.6). The EBM model, using borderline-SMOTE-treated data, demonstrated greater efficacy with respect to precision (81.37%), recall (82.53%), geometric mean (75.39%), and Matthews correlation coefficient (0.43). The EBM model also allows for an in-depth evaluation of single and pairwise factor interactions in predicting work zone-related crash severity. It examines both global and local perspectives, and assists in assessing the influence of various factors.
Rhizosheath: Roles, Formation Processes and Investigation Methods
Authors: Addesso Rosangela , Sofo Adriano , Amato Mariana
Published: November 2023

Climate change negatively affects crop productivity, threatening the survival of entire populations from many vulnerable hotspot regions of the world with the risk of exacerbating hunger, malnutrition and international inequality. Selecting plant species manifesting abiotic stress-tolerant adaptive traits represents a challenge towards ensuring that crops are more resistant and resilient to environmental perturbations. The rhizosheath, defined as the complex of root hair, exudates and soil that strongly adheres to plant roots, is a promising root adaptive trait in facing conditions of water and nutrient deficits, as well as acidic soil. Several beneficial ecological functions are attributed to the rhizosheath, such as enhancing water and nutrient uptake; protecting from dehydration, heat and acid stresses; and stimulating microbial activities. It has been described in several Angiosperm species, including crops grown in severe habitats. The aim of this review was to collect the relevant literature produced to date regarding rhizosheaths, focusing on (i) the various processes involved in its formation, including both physicochemical and biological ones; (ii) the evolutionary and ecological role of rhizosheaths; and (iii) the most frequently used methodologies for its investigation and characterization. The present work provides a comprehensive overview of this revolutionary root’s great agronomic importance in order to address future research aiming to fill the existing knowledge gaps and define a common and shared methodology.
Bio-Coated Graphitic Carbon Nitrides for Enhanced Nitrobenzene Degradation: Roles of Extracellular Electron Transfer
Authors: Wang Yuming , Li Yi , Wang Longfei , Zhang Wenlong , Bürgi Thomas
Published: November 2023

Graphitic carbon nitrides (g-C3N4) and microorganisms could collaboratively enhance photocatalytic properties or facilitate environmental depollution through coupled photocatalytic and biological reactions, which prevented the destruction of photocatalytic stresses to ecological systems and resulted in a sustainable technology for water remediation in rivers and lakes. However, the roles of bio-substances as well as electronic interactions between inorganic and organic systems were still unclear. Herein, g-C3N4, nitrogen-deficient g-C3N4 (ND-g-C3N4), and fluorinated g-C3N4 (F-g-C3N4) were coated with representative bacteria, i.e., Escherichia coli MG 1655, and characterized using integrated spectroscopic techniques. Photocatalytic activities were then evaluated through nitrobenzene degradation performance in an aqueous solution under visible light illumination. Nano-photocatalysts were observed to be adsorbed onto bio-aggregates, and surface hydrophilicity was convinced to be determined in the toxicity of photocatalysts in dark environments. Layered structures of ND-g-C3N4 and F-g-C3N4 were revealed in XRD spectra, and surface coverage of the Luria–Bertani medium was eliminated during E. coli cultivation. Hetero-junctions between photocatalysts and bio-substances were indicated in XPS results. Red-shifts for g-C3N4 and F-g-C3N4 materials as well as a slight blue-shift for ND-g-C3N4 were demonstrated in UV-vis spectra, which might be attributed to the destruction of nitrogen defects on ND-g-C3N4. Owing to the attached bio-substances, nitrobenzene removal could reach twice that with pristine photocatalysts, and ROS quantitative analysis confirmed that hydroxyl radicals were the determined reactive species degrading nitrobenzene in the water solution. The observation of more OH species generation indicated that extracellular electron transfer of E. coli reduced electron–hole recombination and provided reduction sites during photocatalytic degradation of nitrobenzene. This work proved additional electron-transfer paths and reaction mechanisms in hybridized photocatalytic and biological processes, which indicated that bio-activities could be a great promoter of material modification and the incorporation between inorganic and organic systems successfully showed an eco-friendly and sustainable pathway to utilize photocatalysts in natural water.
Carbon Emission Intensity and Its Abatement Choices: A Case of China Eastern
Authors: Xu Lei , Lu Zhenzhen , Kang Zhiping , Duan Yingwen , Zhang Junwei
Published: November 2023

Air transportation, which is a derived demand, is booming following the rapid development of the world economy, and carbon emissions from the air transportation industry, which takes fossil fuels as its main energy source, have been increasing. Therefore, with global warming attracting considerable attention, the issue of how to reduce carbon emissions from air transportation has become a hot issue. We take China Eastern Airlines Corporation Limited (China Eastern) as an example to analyze the main factors influencing airlines’ carbon emissions, specifically around the impact of airline internal operating indicators, such as available seat kilometers (ASK), passenger load factor (PLF), fuel consumption per unit passenger kilometer, the average age of operated aircraft, on-time performance (OTP), etc. This paper uses a correlation analysis, panel regression analysis, and other ways to explore the influence mechanism of the above factors on carbon emission intensity. The conclusions for China Eastern are the following: first, PLF has a significant negative relationship with carbon emission intensity; second, fuel consumption per passenger kilometer has a significant negative relationship with carbon emission intensity. Third, OTP has a significant positive relationship with carbon emission intensity. Fourth, fleet size has a significant positive relationship with carbon emission intensity. Finally, we propose several targeted carbon abatement measures for China Eastern, such as improving PLF and OTP, reducing fuel consumption per unit passenger kilometer, speeding up fleet renewal, etc.
A Decade of Innovation Ecosystem Development: Bibliometric Review of Scopus Database
Authors: Pilelienė Lina , Jucevičius Giedrius
Published: November 2023

The paper focuses on the bibliometric review of the Scopus database in the field of innovation ecosystem development, aiming to reveal the key trends in this fast-growing area of interdisciplinary research in terms of different quantitative and qualitative parameters. The bibliometric analysis followed PRISMA protocol guidelines for finding and extracting relevant scholarly papers based on the selected national, institutional, demographic, and scientific variables. The PRISMA procedure resulted in 401 selected open-access articles published on the topic of innovation ecosystem development from 2013 to 2023. The key findings indicate that research on innovation ecosystem development has seen late growth, which is a sign of still underexplored fields for potential pioneers. Researchers and institutions from the Nordic countries and the UK are most active as far as publications on innovation ecosystem development are concerned. However, researchers from the USA, Australia, and the UK dominate the citation records. Research collaborations help increase productivity and citation levels. The most cited articles fall into 4 clusters based on citations: innovation, smart tourism, digitalization, and entrepreneurship. Future research synergies can also be envisaged with the domains of digitalization, sustainable development, and the smart environment.
ADDovenom: Thermostable Protein-Based ADDomer Nanoparticles as New Therapeutics for Snakebite Envenoming
Authors: Menzies Stefanie K. , Arinto-Garcia Raquel , Amorim Fernanda Gobbi , Cardoso Iara Aimê , Abada Camille , Crasset Thomas , Durbesson Fabien , Edge Rebecca J. , El-Kazzi Priscila , Hall Sophie , Redureau Damien , Stenner Richard , Boldrini-França Johara , Sun Huan , Roldão António , Alves Paula M. , Harrison Robert A. , Vincentelli Renaud , Berger Imre , Quinton Loïc , Casewell Nicholas R. , Schaffitzel Christiane
Published: November 2023

Snakebite envenoming can be a life-threatening medical emergency that requires prompt medical intervention to neutralise the effects of venom toxins. Each year up to 138,000 people die from snakebites and threefold more victims suffer life-altering disabilities. The current treatment of snakebite relies solely on antivenom—polyclonal antibodies isolated from the plasma of hyperimmunised animals—which is associated with numerous deficiencies. The ADDovenom project seeks to deliver a novel snakebite therapy, through the use of an innovative protein-based scaffold as a next-generation antivenom. The ADDomer is a megadalton-sized, thermostable synthetic nanoparticle derived from the adenovirus penton base protein; it has 60 high-avidity binding sites to neutralise venom toxins. Here, we outline our experimental strategies to achieve this goal using state-of-the-art protein engineering, expression technology and mass spectrometry, as well as in vitro and in vivo venom neutralisation assays. We anticipate that the approaches described here will produce antivenom with unparalleled efficacy, safety and affordability.
A Prediction Model of Coal Seam Roof Water Abundance Based on PSO-GA-BP Neural Network
Authors: Dai Xue , Li Xiaoqin , Zhang Yuguang , Li Wenping , Meng Xiangsheng , Li Liangning , Han Yanbo
Published: November 2023

With the gradual increase of coal production capacity, the issue of water hazards in coal seam roofs is increasing in prominence. Accurate and effective prediction of the water content of the roof aquifer, based on limited hydrogeological data, is critical to the identification of the central area of prevention and control of coal seam roof water damage and the reduction of the incidence of such accidents in coal mines. In this paper, we establish a prediction model for the water abundance of the roof slab aquifer, using a PSO-GA-BP neural network. Our model is based on five key factors: aquifer thickness, permeability coefficient, core recovery, number of sandstone and mudstone interbedded layers, and fold fluctuation. The model integrates the genetic algorithm (GA) into the particle swarm optimization (PSO) algorithm, with the particle swarm optimization algorithm serving as the primary approach. It utilizes adaptive inertia weight and quadratic optimization of the weights and thresholds of the backpropagation neural network to minimize the output error threshold for the purpose of minimizing output errors. The prediction model is applied to hydrogeology and coal mine production for the first time. The model is trained using 100 data samples collected by the Surfer 13 software. These samples help to accurately predict the unit inflow of water. The model is then compared with traditional forecasting methods such as FAHP, BP, and GA-BP neural network models to determine its efficiency. The study found that the PSO-GA-BP neural network model accurately predicts aquifer water abundance with higher precision. The root mean square error (RMSE) of the test set is determined to be 8.7 × 10−4, and the fitting result is measured at 0.9999, indicating minimal error with actual values of the sample. According to the prediction results of the test set, the water abundance capacity of the No. 7 coal mine in Hami Danan Lake is divided, and it is found that the overall difference between the results and the actual value is small, which verifies the reliability of the model. According to the results of the water abundance division, strong water abundance areas are mainly concentrated in the third-partition area. This study provides a new method for the prediction of aquifer water abundance, improves the prediction accuracy of aquifer water abundance, reduces the cost of coal mine production, and provides a scientific evaluation method and a theoretical basis for the prevention and control of water disasters in coal seam roofs.