bluuebunny/crossref_metadata_2025 huggingface dataset:
Darbo’s Fixed-Point Theorem: Establishing Existence and Uniqueness Results for Hybrid Caputo–Hadamard Fractional Sequential Differential Equations
Authors: Yaseen Muhammad , Mumtaz Sadia , George Reny , Hussain Azhar , Nabwey Hossam A.
Published: May 2024

This work explores the existence and uniqueness criteria for the solution of hybrid Caputo–Hadamard fractional sequential differential equations (HCHFSDEs) by employing Darbo’s fixed-point theorem. Fractional differential equations play a pivotal role in modeling complex phenomena in various areas of science and engineering. The hybrid approach considered in this work combines the advantages of both the Caputo and Hadamard fractional derivatives, leading to a more comprehensive and versatile model for describing sequential processes. To address the problem of the existence and uniqueness of solutions for such hybrid fractional sequential differential equations, we turn to Darbo’s fixed-point theorem, a powerful mathematical tool that establishes the existence of fixed points for certain types of mappings. By appropriately transforming the differential equation into an equivalent fixed-point formulation, we can exploit the properties of Darbo’s theorem to analyze the solutions’ existence and uniqueness. The outcomes of this research expand the understanding of HCHFSDEs and contribute to the growing body of knowledge in fractional calculus and fixed-point theory. These findings are expected to have significant implications in various scientific and engineering applications, where sequential processes are prevalent, such as in physics, biology, finance, and control theory.
Salinity Impact on Yield, Quality and Sensory Profile of ‘Pisanello’ Tuscan Local Tomato (Solanum lycopersicum L.) in Closed Soilless Cultivation
Authors: Cela Fatjon , Carmassi Giulia , Najar Basma , Taglieri Isabella , Sanmartin Chiara , Cialli Susanna , Ceccanti Costanza , Guidi Lucia , Venturi Francesca , Incrocci Luca
Published: May 2024

Tomatoes are globally renowned for their nutritional value and culinary versatility. However, environmental stresses, particularly salinity, present significant challenges to tomato production, impacting both yield and fruit quality. In light of these challenges, this study investigates the effect of salinity on yield and fruit quality of a local cultivar tomato named ‘Pisanello’ in a closed soilless rockwool cultivation system. Total yield, fruit size, and number were investigated in both control (10 mM of NaCl) and salinity-treated plants (salinity 1 (S1)~30 mM of NaCl and salinity 2 (S2)~60 mM of NaCl), alongside various physicochemical parameters in fully ripened tomato fruits. The results indicated a decrease in crop production with rising sodium chloride concentration in the nutrient solution (25% and 41% for S1 and S2 treatment, respectively). Conversely, salinity-treated fruits exhibited an increase in total phenolic content of +21.9% in S1 and +36.7% in S2 and in antioxidant capacity (+33.5% and +34.7%, for the S1 and S2 treatments, respectively). Salinity treatments registered in general higher quality parameters such as titratable acidity (+8.9 for S1 and +16.5% for S2), total soluble solids (+18.5% for S1 and +43.0% for S2) and fruit firmness (+30.7% for S1 and +60.3% for S2) in comparison with control tomato fruits. Sensory profile analysis further validated the preference for fresh consumption of tomato fruits grown with saline water. These findings suggests that salinity stress can enhance the nutritional quality and taste of the Pisanello tomato. Further investigation could explore the optimal NaCl concentration to balance tomato production and nutritional quality.
Functionalization of Strontium Ferrite Nanoparticles with Novel Chitosan–Schiff Base Ligand for Efficient Removal of Pb(II) Ions from Aqueous Media
Authors: Al-Wasidi Asma S. , Abdelrahman Ehab A.
Published: May 2024

Lead contamination in water poses significant health risks, making its removal imperative. In this study, magnetic strontium ferrite (SrFe12O19) nanoparticles were facilely synthesized by the Pechini sol–gel method and subsequently functionalized with a novel chitosan–Schiff base ligand to obtain a novel inorganic/organic nanocomposite for removing Pb(II) ions from aqueous solutions. The chitosan–Schiff base ligand was synthesized through the reaction of chitosan with 2,4,5-trihydroxybenzaldehyde. The presence of two X-ray diffraction (XRD) peaks at 2Ɵ = 10.5° and 2Ɵ = 20.5°, alongside the characteristic SrFe12O19 peaks, confirmed the functionalization of the nanoparticles with the ligand. Additionally, a significant decrease in the saturation magnetization value from 40.29 emu/g in pure SrFe12O19 nanoparticles to 17.32 emu/g in the nanocomposite further verified the functionalization. The presence of carbon (C) and nitrogen (N) atoms in the energy-dispersive X-ray (EDX) pattern of the nanocomposite, in addition to iron (Fe), strontium (Sr), and oxygen (O), also confirmed the functionalization. The nanocomposite’s maximum adsorption capacity for Pb(II) ions was 390.63 mg/g. Moreover, the adsorption process is endothermic, spontaneous, and chemical, occurring via complexation with -C=N and -OH groups, and it fits well with the Langmuir equilibrium isotherm and the pseudo-second-order kinetic equation.
The Microdeformation Fabric of Amphibole-Rich Peridotite in the Southern Mariana Trench and Its Influence on Seismic Anisotropy
Authors: Li Jingbo , Jin Zhenmin
Published: May 2024

Olivine, the most abundant mineral in the upper mantle, exhibits elastic anisotropy. Understanding the seismic anisotropy and flow patterns in the upper mantle hinges on the crystallographic preferred orientation (CPO) of olivine. Similarly, hydrous minerals, which also display elastic anisotropy, play a crucial role in explaining seismic anisotropy in numerous subduction zones. High-temperature and -pressure simple shear experiments reveal that the CPO of amphibole can lead to significant seismic anisotropy. In this study, peridotite samples originating from the southern end of the Mariana Trench, commonly containing amphibole, were analyzed. The microdeformation fabric and seismic anisotropy were examined. The results indicate a weak fabric strength in olivine, yet identifiable deformation fabrics of A/D, D, and AG were observed. Various dislocation structures suggest that olivine experiences complex deformation across various temperatures. Not only can the original slip system transform, but the melt/fluid resulting from melting also has a substantial impact on the peridotite. Deformation precedes the melt/rock interaction, resulting in a strong melt/rock reaction under near-static conditions. Furthermore, the modal content of amphibole significantly alters the seismic anisotropy of peridotite. An increase in amphibole content (types I, III, and IV) enhances seismic anisotropy, particularly for type I amphibole. Notably, the presence of type I fabric amphibole promotes the Vs1 polarization direction parallel to the trench in subduction zones, a phenomenon observed in other subduction zones. Therefore, when considering mantle peridotite regions rich in amphibole, the impact of amphibole on seismic anisotropy must be accounted for.
EGCG Suppresses Adipogenesis and Promotes Browning of 3T3-L1 Cells by Inhibiting Notch1 Expression
Authors: Wang Yinghao , Li Chunfeng , Peng Wenyuan , Sheng Jun , Zi Chengting , Wu Xiaoyun
Published: May 2024

Background: With the changes in lifestyle and diet structure, the incidence of obesity has increased year by year, and obesity is one of the inducements of many chronic metabolic diseases. Epigallocatechin gallate (EGCG), which is the most abundant component of tea polyphenols, has been used for many years to improve obesity and its complications. Though it has been reported that EGCG can improve obesity through many molecular mechanisms, EGCG may have many mechanisms yet to be explored. In this study, we explored other possible mechanisms through molecular docking and in vitro experiments. Methods: AutoDock Vina was selected for conducting the molecular docking analysis to elucidate the interaction between EGCG and Notch1, while molecular dynamics simulations were employed to validate this interaction. Then, the new regulation mechanism of EGCG on obesity was verified with in vitro experiments, including a Western blot experiment, immunofluorescence experiment, oil red O staining, and other experiments in 3T3-L1 adipocytes. Results: The molecular docking results showed that EGCG could bind to Notch1 protein through hydrogen bonding. In vitro cell experiments demonstrated that EGCG can significantly reduce the sizes of lipid droplets of 3T3-L1 adipocytes and promote UCP-1 expression by inhibiting the expression of Notch1 in 3T3-L1 adipocytes, thus promoting mitochondrial biogenesis. Conclusions: In this study, molecular docking and in vitro cell experiments were used to explore the possible mechanism of EGCG to improve obesity by inhibiting Notch1.
Synergistic Modulation of Sn-Based Perovskite Solar Cells with Crystallization and Interface Engineering
Authors: Sun Yunzhao , Song Yaoyao , Liu Mengfan , Zhang Huiyin
Published: May 2024

A high-quality Sn-based perovskite absorption layer and effective carrier transport are the basis for high-performance Sn-based perovskite solar cells. The suppression of Sn2+ oxidation and rapid crystallization is the key to obtaining high-quality Sn-based perovskite film. And interface engineering is an effective strategy to enhance carrier extraction and transport. In this work, tin fluoride (SnF2) was introduced to the perovskite precursor solution, which can effectively modulate the crystallization and morphology of Sn-based perovskite layer. Furthermore, the hole-transporting layer of PEDOT:PSS was modified with CsI to enhance the hole extraction and transport. As a result, the fabricated inverted Sn-based perovskite solar cells demonstrated a power conversion efficiency of 7.53% with enhanced stability.
Comprehensive Analysis Reveals the Difference in Volatile Oil between Bupleurum marginatum var. stenophyllum (Wolff) Shan et Y. Li and the Other Four Medicinal Bupleurum Species
Authors: Ma Yuzhi , Guo Xinwei , Wu Peiling , Li Yuting , Zhang Ruyue , Xu Lijia , Wei Jianhe
Published: May 2024

Volatile oil serves as a traditional antipyretic component of Bupleuri Radix. Bupleurum marginatum var. stenophyllum (Wolff) Shan et Y. Li belongs to the genus Bupleurum and is distinguished for its high level of saikosaponins and volatile oils; nonetheless, prevailing evidence remains inconclusive regarding its viability as an alternative resource of other official species. This study aims to systematically compare the volatile oil components of both dried and fresh roots of B. marginatum var. stenophyllum and the four legally available Bupleurum species across their chemical, molecular, bionics, and anatomical structures. A total of 962 compounds were determined via GC-MS from the dried roots; B. marginatum var. stenophyllum showed the greatest differences from other species in terms of hydrocarbons, esters, and ketones, which was consistent with the results of fresh roots and the e-nose analysis. A large number of DEGs were identified from the key enzyme family of the monoterpene synthesis pathway in B. marginatum var. stenophyllum via transcriptome analysis. The microscopic observation results, using different staining methods, further showed the distinctive high proportion of phloem in B. marginatum var. stenophyllum, the structure which produces volatile oils. Together, these pieces of evidence hold substantial significance in guiding the judicious development and utilization of Bupleurum genus resources.
Research Progress on the Degradation of Organic Pollutants in Wastewater via Ultrasound/Periodate Systems: A Review
Authors: Song Tiehong , Wang Zhe , Jiang Yi , Yang Shenggang , Deng Qiyuan
Published: May 2024

In recent years, the efficient removal of organic pollutants from wastewater has emerged as a critical area of global research interest. Against this backdrop, an array of innovative technologies for wastewater treatment has been developed. Among numerous advanced oxidation processes (AOPs), periodate (PI), an emerging oxidizing agent in AOPs, has garnered significant attention from researchers. Particularly, the integration of ultrasound (US)-activated PI systems has been recognized as an exceptionally promising approach for the synergistic degradation of organic pollutants in wastewater. In this paper, we conducted a thorough analysis of the mechanisms underlying the degradation of organic pollutants using the US/PI system. Furthermore, we comprehensively delineated the effects of ultrasonic power, periodate concentration, temperature, pH, coexisting inorganic ions, and dissolved organic matter on the removal efficiency of organic pollutants and summarized application cases of the US/PI system for the degradation of different pollutants. Finally, we also offered prospective discussions on the future trajectories of US/PI technology development.
Enhancement of Biodegradability of Chicken Manure via the Addition of Zeolite in a Two-Stage Dry Anaerobic Digestion Configuration
Authors: Kalogiannis Achilleas , Vasiliadou Ioanna A. , Tsiamis Athanasios , Galiatsatos Ioannis , Stathopoulou Panagiota , Tsiamis George , Stamatelatou Katerina
Published: May 2024

Leach bed reactors (LBRs) are dry anaerobic systems that can handle feedstocks with high solid content, like chicken manure, with minimal water addition. In this study, the chicken manure was mixed with zeolite, a novel addition, and packed in the LBR to improve biogas production. The resulting leachate was then processed in a continuous stirred tank reactor (CSTR), where most of the methane was produced. The supernatant of the CSTR was returned to the LBR. The batch mode operation of the LBR led to a varying methane production rate (MPR) with a peak in the beginning of each batch cycle when the leachate was rich in organic matter. Comparing the MPR in both systems, the peaks in the zeolite system were higher and more acute than in the control system, which was under stress, as indicated by the acetate accumulation at 2328 mg L−1. Moreover, the presence of zeolite in the LBR played a crucial role, increasing the overall methane yield from 0.142 (control experiment) to 0.171 NL CH4 per g of volatile solids of chicken manure entering the system at a solid retention time of 14 d. Zeolite also improved the stability of the system. The ammonia concentration increased gradually due to the little water entering the system and reached 3220 mg L−1 (control system) and 2730 mg L−1 (zeolite system) at the end of the experiment. It seems that zeolite favored the accumulation of the ammonia at a lower rate (14.0 mg L−1 d−1) compared to the control experiment (17.3 mg L−1 d−1). The microbial analysis of the CSTR fed on the leachate from the LBR amended with zeolite showed a higher relative abundance of Methanosaeta (83.6%) compared to the control experiment (69.1%). Both CSTRs established significantly different bacterial profiles from the inoculum after 120 days of operation (p < 0.05). Regarding the archaeal communities, there were no significant statistical differences between the CSTRs and the inoculum (p > 0.05).
Non-Substituted Imidazolium-Based Electrolytes as Potential Alternatives to the Conventional Acidic Electrolytes of Polyaniline-Based Electrode Materials for Supercapacitors
Authors: Al-Zohbi Fatima , Ghamouss Fouad , Jacquemin Johan , Schmaltz Bruno , Tabcheh Mohamad Fadel , Abarbri Mohamed , Cherry Khalil , Tran-Van François
Published: May 2024

Although disubstituted imidazolium cation is sterically crowded, hundreds of ionic liquids based on this cation have been reported as electrolytes for energy storage devices. In contrast to disubstituted imidazolium, non-substituted imidazolium is uncrowded sterically and has not yet been investigated as an electrolyte, to the best of our knowledge. Hence, imidazolium hydrogen sulfate [Imi][HSO4], in mixture with water, was studied as an electrolyte for PANI-based electrode materials. For comparison, pyrrolidinium with hydrogen sulfate or p-toluene sulfonate ([Pyrr][HSO4] or [Pyrr][PTS]), in mixture with water, were also investigated as alternatives to the conventional electrolyte (i.e., aqueous H2SO4) for PANI electrodes. Walden plots of binary mixture ionic liquid–water weight ratios with the optimal ionic conductivity (i.e., [Imi][HSO4]/water 48/52 wt% (195.1 mS/cm), [Pyrr][HSO4]/water 41/59 wt% (186.6 mS/cm), and [Pyrr][PTS]/water 48/52 wt% (43.4 mS/cm) along with the electrochemical performances of PANI in these binary mixtures showed that [Pyrr][HSO4]aq or [Imi][HSO4]aq are convenient electrolytes for PANI/PIL, as opposed to [Pyrr][PTS]aq. Furthermore, replacing the conventional aqueous electrolyte H2SO4 with [Imi][HSO4] aq increased the specific capacitance of PANI/PIL from 249.8 to 268.5 F/g at 15 mV/s. Moreover, PANI/PIL electrodes displayed a quasi-ideal capacitive behavior in [Imi][HSO4]aq (the correction factor of CPE4 was 0.99). This primary study has shown that non-substituted imidazolium as an electrolyte could enhance the electrochemical performances of PANI electrodes and could be a good alternative to the conventional electrolyte.
Metal–Flavonoid Interactions—From Simple Complexes to Advanced Systems
Authors: Walencik Paulina Katarzyna , Choińska Renata , Gołębiewska Ewelina , Kalinowska Monika
Published: May 2024

For many years, metal–flavonoid complexes have been widely studied as a part of drug discovery programs, but in the last decade their importance in materials science has increased significantly. A deeper understanding of the role of metal ions and flavonoids in constructing simple complexes and more advanced hybrid networks will facilitate the assembly of materials with tailored architecture and functionality. In this Review, we highlight the most essential data on metal–flavonoid systems, presenting a promising alternative in the design of hybrid inorganic–organic materials. We focus mainly on systems containing CuII/I and FeIII/II ions, which are necessary in natural and industrial catalysis. We discuss two kinds of interactions that typically ensure the formation of metal–flavonoid systems, namely coordination and redox reactions. Our intention is to cover the fundamentals of metal–flavonoid systems to show how this knowledge has been already transferred from small molecules to complex materials.
Chemical Composition, Nutritional, and Biological Properties of Extracts Obtained with Different Techniques from Aronia melanocarpa Berries
Authors: Piras Alessandra , Porcedda Silvia , Smeriglio Antonella , Trombetta Domenico , Nieddu Mariella , Piras Franca , Sogos Valeria , Rosa Antonella
Published: May 2024

This study investigates the chemical composition, nutritional, and biological properties of extracts obtained from A. melanocarpa berries using different extraction methods and solvents. Hydrodistillation and supercritical fluid extraction with CO2 allowed us to isolate fruit essential oil (HDEX) and fixed oil (SFEEX), respectively. A phenol-enriched extract was obtained using a mild ultrasound-assisted maceration with methanol (UAMM). The HDEX most abundant component, using gas chromatography-mass spectrometry (GC/MS), was italicene epoxide (17.2%), followed by hexadecanoic acid (12.4%), khusinol (10.5%), limonene (9.7%), dodecanoic acid (9.7%), and (E)-anethole (6.1%). Linoleic (348.9 mg/g of extract, 70.5%), oleic (88.9 mg/g, 17.9%), and palmitic (40.8 mg/g, 8.2%) acids, followed by α-linolenic and stearic acids, were the main fatty acids in SFEEX determined using high-performance liquid chromatography coupled with a photodiode array detector and an evaporative light scattering detector (HPLC-DAD/ELSD). HPLC-DAD analyses of SFEEX identified β-carotene as the main carotenoid (1.7 mg/g), while HPLC with fluorescence detection (FLU) evidenced α-tocopherol (1.2 mg/g) as the most abundant tocopherol isoform in SFEEX. Liquid chromatography-electrospray ionization-MS (LC-ESI-MS) analysis of UAMM showed the presence of quercetin-sulfate (15.6%, major component), malvidin 3-O-(6-O-p-coumaroyl) glucoside-4-vinylphenol adduct (pigment B) (9.3%), di-caffeoyl coumaroyl spermidine (7.6%), methyl-epigallocatechin (5.68%), and phloretin (4.1%), while flavonoids (70.5%) and phenolic acids (23.9%) emerged as the most abundant polyphenol classes. UAMM exerted a complete inhibition of the cholesterol oxidative degradation at 140 °C from 75 μg of extract, showing 50% protection at 30.6 μg (IA50). Furthermore, UAMM significantly reduced viability (31–48%) in A375 melanoma cells in the range of 500–2000 μg/mL after 96 h of incubation (MTT assay), with a low toxic effect in normal HaCaT keratinocytes. The results of this research extend the knowledge of the nutritional and biological properties of A. melanocarpa berries, providing useful information on specific extracts for potential food, cosmetic, and pharmaceutical applications.
Structural Analysis of the Large Stokes Shift Red Fluorescent Protein tKeima
Authors: Nam Ki Hyun , Xu Yongbin
Published: May 2024

The Keima family comprises large Stokes shift fluorescent proteins that are useful for dual-color fluorescence cross-correlation spectroscopy and multicolor imaging. The tKeima is a tetrameric large Stokes shift fluorescent protein and serves as the ancestor fluorescent protein for both dKeima and mKeima. The spectroscopic properties of tKeima have been previously reported; however, its structural basis and molecular properties have not yet been elucidated. In this study, we present the crystallographic results of the large Stokes shift fluorescent protein tKeima. The purified tKeima protein spontaneously crystallized after purification without further crystallization. The crystal structure of tKeima was determined at 3.0 Å resolution, revealing a β-barrel fold containing the Gln-Tyr-Gly chromophores mainly with cis-conformation. The tetrameric interfaces of tKeima were stabilized by numerous hydrogen bonds and salt–bridge interactions. These key residues distinguish the substituted residues in dKeima and mKeima. The key structure-based residues involved in the tetramer formation of tKeima provide insights into the generation of a new type of monomeric mKeima. This structural analysis expands our knowledge of the Keima family and provides insights into its protein engineering.
High-Resolution Retinal Imaging: Technology Overview and Applications
Authors: Mujat Mircea , Ferguson R. Daniel , Hammer Daniel X. , Patel Ankit H. , Iftimia Nicusor
Published: May 2024

Adaptive optics (AO) has been used in many applications, including astronomy, microscopy, and medical imaging. In retinal imaging, AO provides real-time correction of the aberrations introduced by the cornea and the lens to facilitate diffraction-limited imaging of retinal microstructures. Most importantly, AO-based retinal imagers provide cellular-level resolution and quantification of changes induced by retinal diseases and systemic diseases that manifest in the eye enabling disease diagnosis and monitoring of disease progression or the efficacy of treatments. In this paper, we present an overview of our team efforts over almost two decades to develop high-resolution retinal imagers suitable for clinical use. Several different types of imagers for human and small animal eye imaging are reviewed, and representative results from multiple studies using these instruments are shown. These examples demonstrate the extraordinary power of AO-based retinal imaging to reveal intricate details of morphological and functional characteristics of the retina and to help elucidate important aspects of vision and of the disruptions that affect delicate retinal tissue.
Effect of Collimation on Diffraction Signal-to-Background Ratios at a Neutron Diffractometer
Authors: Yu Dunji , Chen Yan , Conner David , Berry Kevin , Skorpenske Harley , An Ke
Published: May 2024

High diffraction signal-to-background ratios (SBRs), the ratio of diffraction peak integrated intensity over its background intensity, are desirable for a neutron diffractometer to acquire good statistics for diffraction pattern measurements and subsequent data analysis. For a given detector, while the diffraction peak signals primarily depend on the characteristics of the neutron beam and sample coherent scattering, the background largely originates from the sample incoherent scattering and the scattering from the instrument space. In this work, we investigated the effect of collimation on neutron diffraction SBRs of Si powder measurements using one high-angle area detector bank coupled with six different collimation configurations in a large and complex instrument space at the engineering materials diffractometer VULCAN, SNS, ORNL. The results revealed that the diffraction SBRs can be significantly improved by a proper coarse collimator that leaves no gap between the detector and the collimator, and the improvement of SBRs by a fine radial collimator was remarkable with a proper coarse collimator in place but not distinguishable without one. It was also found that the diffraction SBRs were not effectively improved by adding the neutron-absorbing element boron to the fine radial collimator body, which indicates that either the absorption of secondary scattered neutrons by the added boron is insignificant or the collimator base material (resin and ABS) alone attenuates background scattering sufficiently. These findings could serve as a useful reference for diffractometer developers and/or operators to optimize their collimation to achieve higher diffraction SBRs.
Combining Sound and Deep Neural Networks for the Measurement of Jump Height in Sports Science
Authors: Banchero Lucas , Lopez Jose J. , Pueo Basilio , Jimenez-Olmedo Jose M.
Published: May 2024

Jump height tests are employed to measure lower-limb muscle power of athletic and non-athletic populations. The most popular instruments for this purpose are jump mats and, in recent years, smartphone apps, which compute jump height through the manual annotation of video recordings and recently automatically using the sound produced during the jump to extract the flight time. In a previous work, the afore-mentioned sound systems were presented by the authors in which the take-off and landing events from the audio recordings of jump executions were obtained using classical signal processing. In this work, a more precise, noise-immune, and robust system, capable of working in the most unfavorable environments, is presented. The system uses a deep neural network trained specifically for this purpose. More than 300 jumps were recorded to train and validate the network performance. The ground truth was a jump mat, providing a slightly better accuracy in quiet and medium quiet environments but excellent accuracy in noisy and complicated ones. The developed audio-based system is a trustworthy instrument for measuring jump height accurately in any kind of environment, providing a perfect measurement tool that can be accessed through a mobile phone in the form of an app.
Real-Time Monitoring of Odour Emissions at the Fenceline of a Waste Treatment Plant by Instrumental Odour Monitoring Systems: Focus on Training Methods
Authors: Ratti Christian , Bax Carmen , Lotesoriere Beatrice Julia , Capelli Laura
Published: May 2024

Waste treatment plants (WTPs) often generate odours that may cause nuisance to citizens living nearby. In general, people are becoming more sensitive to environmental issues, and particularly to odour pollution. Instrumental Odour Monitoring Systems (IOMSs) represent an emerging tool for continuous odour measurement and real-time identification of odour peaks, which can provide useful information about the process operation and indicate the occurrence of anomalous conditions likely to cause odour events in the surrounding territories. This paper describes the implementation of two IOMSs at the fenceline of a WTP, focusing on the definition of a specific experimental protocol and data processing procedure for dealing with the interferences of humidity and temperature affecting sensors’ responses. Different approaches for data processing were compared and the optimal one was selected based on field performance testing. The humidity compensation model developed proved to be effective, bringing the IOMS classification accuracy above 95%. Also, the adoption of a class-specific regression model compared to a global regression model resulted in an odour quantification capability comparable with those of the reference method (i.e., dynamic olfactometry). Lastly, the validated models were used to process the monitoring data over a period of about one year.
A Method for Sensing Dielectric Properties of Thin and Flexible Conductive Biocomposites
Authors: Cataldo Andrea , Demitri Christian , Lamanna Leonardo , Masciullo Antonio , Schiavoni Raissa
Published: May 2024

This study investigates the dielectric properties of conductive biocomposites (CBs), which are integral to the development of advanced materials for flexible electronics and medical devices. A novel method employing Microwave Reflectometry (MR) is introduced, utilizing a miniaturized Vector Network Analyzer (m-VNA) and a dedicated sensing element (SE), to extract the dielectric properties of CBs. The method is grounded in a minimization principle, aligning the measured S11 reflection scattering parameter with its electromagnetic (EM) simulation, facilitating a refined process for determining the dielectric properties. The experimental setup was meticulously engineered, optimized, and validated using reference dielectric samples (RDSs) with known dielectric properties. The method was then applied to three innovative CBs, resulting in an accurate extrapolation of their dielectric properties. The findings highlight the method’s versatility, cost-efficiency, and applicability to ultra-thin and flexible biopolymer films, offering significant potential for advancements in flexible electronics and bio-sensing applications.
Encrypted Network Traffic Analysis and Classification Utilizing Machine Learning
Authors: Alwhbi Ibrahim A. , Zou Cliff C. , Alharbi Reem N.
Published: May 2024

Encryption is a fundamental security measure to safeguard data during transmission to ensure confidentiality while at the same time posing a great challenge for traditional packet and traffic inspection. In response to the proliferation of diverse network traffic patterns from Internet-of-Things devices, websites, and mobile applications, understanding and classifying encrypted traffic are crucial for network administrators, cybersecurity professionals, and policy enforcement entities. This paper presents a comprehensive survey of recent advancements in machine-learning-driven encrypted traffic analysis and classification. The primary goals of our survey are two-fold: First, we present the overall procedure and provide a detailed explanation of utilizing machine learning in analyzing and classifying encrypted network traffic. Second, we review state-of-the-art techniques and methodologies in traffic analysis. Our aim is to provide insights into current practices and future directions in encrypted traffic analysis and classification, especially machine-learning-based analysis.
Online Signature Biometrics for Mobile Devices
Authors: Roszczewska Katarzyna , Niewiadomska-Szynkiewicz Ewa
Published: May 2024

This paper addresses issues concerning biometric authentication based on handwritten signatures. Our research aimed to check whether a handwritten signature acquired with a mobile device can effectively verify a user’s identity. We present a novel online signature verification method using coordinates of points and pressure values at each point collected with a mobile device. Convolutional neural networks are used for signature verification. In this paper, three neural network models are investigated, i.e., two self-made light SigNet and SigNetExt models and the VGG-16 model commonly used in image processing. The convolutional neural networks aim to determine whether the acquired signature sample matches the class declared by the signer. Thus, the scenario of closed set verification is performed. The effectiveness of our method was tested on signatures acquired with mobile phones. We used the subset of the multimodal database, MobiBits, that was captured using a custom-made application and consists of samples acquired from 53 people of diverse ages. The experimental results on accurate data demonstrate that developed architectures of deep neural networks can be successfully used for online handwritten signature verification. We achieved an equal error rate (EER) of 0.63% for random forgeries and 6.66% for skilled forgeries.
Optical Goniometer Paired with Digital Monte Carlo Twin to Determine the Optical Properties of Turbid Media
Authors: Stolz Levin , Beutel Benedikt , Kienle Alwin , Foschum Florian
Published: May 2024

We present a goniometer designed for capturing spectral and angular-resolved data from scattering and absorbing media. The experimental apparatus is complemented by a comprehensive Monte Carlo simulation, meticulously replicating the radiative transport processes within the instrument’s optical components and simulating scattering and absorption across arbitrary volumes. Consequently, we were able to construct a precise digital replica, or “twin”, of the experimental setup. This digital counterpart enabled us to tackle the inverse problem of deducing optical parameters such as absorption and scattering coefficients, along with the scattering anisotropy factor from measurements. We achieved this by fitting Monte Carlo simulations to our goniometric measurements using a Levenberg–Marquardt algorithm. Validation of our approach was performed using polystyrene particles, characterized by Mie scattering, supplemented by a theoretical analysis of algorithmic convergence. Ultimately, we demonstrate strong agreement between optical parameters derived using our novel methodology and those obtained via established measurement protocols.
Instrumental Evaluation of the Effects of Vertebral Consolidation Surgery on Trunk Muscle Activations and Co-Activations in Patients with Multiple Myeloma: Preliminary Results
Authors: Montante Barbara , Zampa Benedetta , Balestreri Luca , Ciancia Rosanna , Chini Giorgia , Ranavolo Alberto , Rupolo Maurizio , Sawacha Zimi , Urbani Martina , Varrecchia Tiwana , Michieli Mariagrazia
Published: May 2024

Multiple myeloma (MM) patients complain of pain and stiffness limiting motility. To determine if patients can benefit from vertebroplasty, we assessed muscle activation and co-activation before and after surgery. Five patients with MM and five healthy controls performed sitting-to-standing and lifting tasks. Patients performed the task before and one month after surgery. Surface electromyography (sEMG) was recorded bilaterally over the erector spinae longissimus and rectus abdominis superior muscles to evaluate the trunk muscle activation and co-activation and their mean, maximum, and full width at half maximum were evaluated. Statistical analyses were performed to compare MM patients before and after the surgery, MM and healthy controls and to investigate any correlations between the muscle’s parameters and the severity of pain in patients. The results reveal increased activations and co-activations after vertebroplasty as well as in comparison with healthy controls suggesting how MM patients try to control the trunk before and after vertebroplasty surgery. The findings confirm the beneficial effects of vertebral consolidation on the pain experienced by the patient, despite an overall increase in trunk muscle activation and co-activation. Therefore, it is important to provide patients with rehabilitation treatment early after surgery to facilitate the CNS to correctly stabilize the spine without overloading it with excessive co-activations.
Proposal-Free Fully Convolutional Network: Object Detection Based on a Box Map
Authors: Su Zhihao , Adam Afzan , Nasrudin Mohammad Faidzul , Prabuwono Anton Satria
Published: May 2024

Region proposal-based detectors, such as Region-Convolutional Neural Networks (R-CNNs), Fast R-CNNs, Faster R-CNNs, and Region-Based Fully Convolutional Networks (R-FCNs), employ a two-stage process involving region proposal generation followed by classification. This approach is effective but computationally intensive and typically slower than proposal-free methods. Therefore, region proposal-free detectors are becoming popular to balance accuracy and speed. This paper proposes a proposal-free, fully convolutional network (PF-FCN) that outperforms other state-of-the-art, proposal-free methods. Unlike traditional region proposal-free methods, PF-FCN can generate a “box map” based on regression training techniques. This box map comprises a set of vectors, each designed to produce bounding boxes corresponding to the positions of objects in the input image. The channel and spatial contextualized sub-network are further designed to learn a “box map”. In comparison to renowned proposal-free detectors such as CornerNet, CenterNet, and You Look Only Once (YOLO), PF-FCN utilizes a fully convolutional, single-pass method. By reducing the need for fully connected layers and filtering center points, the method considerably reduces the number of trained parameters and optimizes the scalability across varying input sizes. Evaluations of benchmark datasets suggest the effectiveness of PF-FCN: the proposed model achieved an mAP of 89.6% on PASCAL VOC 2012 and 71.7% on MS COCO, which are higher than those of the baseline Fully Convolutional One-Stage Detector (FCOS) and other classical proposal-free detectors. The results prove the significance of proposal-free detectors in both practical applications and future research.
Multivariable Iterative Learning Control Design for Precision Control of Flexible Feed Drives
Authors: Wang Yulin , Hsiao Tesheng
Published: May 2024

Advancements in machining technology demand higher speeds and precision, necessitating improved control systems in equipment like CNC machine tools. Due to lead errors, structural vibrations, and thermal deformation, commercial CNC controllers commonly use rotary encoders in the motor side to close the position loop, aiming to prevent insufficient stability and premature wear and damage of components. This paper introduces a multivariable iterative learning control (MILC) method tailored for flexible feed drive systems, focusing on enhancing dynamic positioning accuracy. The MILC employs error data from both the motor and table sides, enhancing precision by injecting compensation commands into both the reference trajectory and control command through a norm-optimization process. This method effectively mitigates conflicts between feedback control (FBC) and traditional iterative learning control (ILC) in flexible structures, achieving smaller tracking errors in the table side. The performance and efficacy of the MILC system are experimentally validated on an industrial biaxial CNC machine tool, demonstrating its potential for precision control in modern machining equipment.
Impact of Pot Farming on Plant-Parasitic Nematode Control
Authors: Landi Silvia , Carletti Beatrice , Binazzi Francesco , Cacini Sonia , Nesi Beatrice , Resta Emilio , Roversi Pio Federico , Simoni Sauro
Published: May 2024

In the Pistoia Nursery-Ornamental Rural District (Italy), a leader in Europe in ornamental nurseries covering over 5200 hectares with over 2500 different species of plant, plant-parasitic nematodes represent a serious concern. The potential efficacy of a pot cultivation system using commercial substrates to control plant-parasitic nematodes was assessed. On two different plant species, two different pot cultivation managements, potted plants, and potted plants previously cultivated in natural soil were compared to plants only cultivated in natural soil. The entire soil nematode structure with and without plants was evaluated. The relationship between soil properties and soil nematode community was investigated. All the studied substrates were free from plant-parasitic nematodes. Regarding free-living nematodes, Peat–Pumice showed nematode assemblage established by colonizer and extreme colonizer bacterial feeders, whereas Peat–Perlite included both bacterial and fungal feeders, and, finally, coconut fiber also included omnivores and predators. In farming, the substrates rich in organic matter such as coconut fiber could still play an important role in suppressing plant-parasitic nematodes because of the abundance of free-living nematodes. In fact, they are of crucial importance in both the mineralization of organic matter and the antagonistic control of plant-parasitic nematodes. Potting systems equally reduce virus-vector nematodes and improve the prey/predator ratio favoring natural control.
An In Vitro Human Skin Test for Predicting Skin Sensitization and Adverse Immune Reactions to Biologics
Authors: Ahmed Shaheda Sameena , Ahmed Mohammed Mahid , Ishaq Abbas , Freer Matthew , Stebbings Richard , Dickinson Anne Mary
Published: May 2024

Biologics, including monoclonal antibodies (mAb), have proved to be effective and successful therapeutic agents, particularly in the treatment of cancer and immune-inflammatory conditions, as well as allergies and infections. However, their use carries an inherent risk of an immune-mediated adverse drug reaction. In this study, we describe the use of a novel pre-clinical human in vitro skin explant test for predicting skin sensitization and adverse immune reactions. The skin explant test was used to investigate the effects of therapeutic antibodies, which are known to cause a limited reaction in a small number of patients or more severe reactions. Material and Methods: Immune responses were determined by T cell proliferation and multiplex cytokine analysis, as well as histopathological analysis of skin damage (grades I–IV in increasing severity), predicting a negative (grade I) or positive (grade ≥ II) response for an adverse skin sensitization effect. Results: T cell proliferation responses were significantly increased in the positive group (p < 0.004). Multiplex cytokine analysis showed significantly increased levels of IFNγ, TNFα, IL-10, IL-12, IL-13, IL-1β, and IL-4 in the positive response group compared with the negative response group (p < 0.0001, p < 0.0001, p < 0.002, p < 0.01, p < 0.04, p < 0.006, and p < 0.004, respectively). Conclusions: Overall, the skin explant test correctly predicted the clinical outcome of 13 out of 16 therapeutic monoclonal antibodies with a correlation coefficient of 0.770 (p = 0.0001). This assay therefore provides a valuable pre-clinical test for predicting adverse immune reactions, including T cell proliferation and cytokine release, both associated with skin sensitization to monoclonal antibodies.
Inflaton Decay in No-Scale Supergravity and Starobinsky-like Models
Authors: Ema Yohei , Garcia Marcos A. G. , Ke Wenqi , Olive Keith A. , Verner Sarunas
Published: May 2024

We consider the decay of the inflaton in Starobinsky-like models arising from either an R+R2 theory of gravity or N=1 no-scale supergravity models. If Standard Model matter is simply introduced to the R+R2 theory, the inflaton (which appears when the theory is conformally transformed into the Einstein frame) couples to matter predominantly in Standard Model Higgs kinetic terms. This will typically lead to a reheating temperature of ∼3 × 109 GeV. However, if the Standard Model Higgs is conformally coupled to curvature, the decay rate may be suppressed and vanishes for conformal coupling ξ=1/6. Nevertheless, the inflaton decays through the conformal anomaly, leading to a reheating temperature of the order of 108 GeV. The Starobinsky potential may also arise in no-scale supergravity. In this case, the inflaton decays if there is a direct coupling of the inflaton to matter in the superpotential or to gauge fields through the gauge kinetic function. We also discuss the relation between the theories and demonstrate the correspondence between the no-scale models and the conformally coupled R+R2 theory (with ξ=1/6).
Mechanisms for Producing Primordial Black Holes from Inflationary Models beyond Fine-Tuning
Authors: Stamou Ioanna
Published: May 2024

In this study, we present an analysis of the fine-tuning required in various inflationary models in order to explain the production of Primordial Black Holes (PBHs). We specifically examine the degree of fine-tuning necessary in two prominent single-field inflationary models: those with an inflection point and those with step-like features in the potential. Our findings indicate that models with step-like features generally require less fine-tuning compared to those with an inflection point, making them more viable for consistent PBH production. An interesting outcome of these models is that, in addition to improved fine-tuning, they may also predict low-frequency signals that can be detected by pulsar timing array (PTA) collaborations. Additionally, we extend our analysis to multifield inflationary models to assess whether the integration of additional fields can further alleviate the fine-tuning demands. The study also explores the role of a spectator field and its impact on the fine-tuning process. Our results indicate that although mechanisms involving a spectator field can circumvent the issue of fine-tuning parameters for PBH production, both multifield models and models with step-like features present promising alternatives. While fine-tuning involves multiple considerations, our primary objective is to evaluate various inflationary models to identify the one that most naturally explains the formation of PBHs. Hence, this study introduces a novel approach by categorizing existing PBH mechanisms, paving the way for subsequent research to prioritize models that minimize the need for extensive fine-tuning.
Review and Evaluation of Automated Charging Technologies for Heavy-Duty Vehicles
Authors: Piedel Emma , Lauth Enrico , Grahle Alexander , Göhlich Dietmar
Published: May 2024

Automated charging technologies are becoming increasingly important in the electrification of heavy road freight transport, especially in combination with autonomous driving. This study provides a comprehensive analysis of automated charging technologies for electric heavy-duty vehicles (HDVs). It encompasses the entire spectrum of feasible technologies, including static and dynamic approaches, with each charging technology evaluated for its advantages, potentials, challenges and technology readiness level (TRL). Static conductive charging methods such as charging robots, underbody couplers, or pantographs show good potential, with pantographs being the most mature option. These technologies are progressing towards higher TRLs, with a focus on standardization and adaptability. While static wireless charging is operational for some prototype solutions, it encounters challenges related to implementation and efficiency. Dynamic conductive charging through an overhead contact line or contact rails holds promise for high-traffic HDV routes with the overhead contact line being the most developed option. Dynamic wireless charging, although facing efficiency challenges, offers the potential for seamless integration into roads and minimal wear and tear. Battery swapping is emerging as a practical solution to reduce downtime for charging, with varying levels of readiness across different implementations. To facilitate large-scale deployment, further standardization efforts are required. This study emphasizes the necessity for continued research and development to enhance efficiency, decrease costs and ensure seamless integration into existing infrastructures. Technologies that achieve this best will have the highest potential to significantly contribute to the creation of an efficiently automated and environmentally friendly transport sector.