bluuebunny/crossref_metadata_2025 huggingface dataset:
Study of Endocrine-Disrupting Chemicals in Infant Formulas and Baby Bottles: Data from the European LIFE-MILCH PROJECT
Authors: Nuti Francesca , Fernández Feliciana Real , Severi Mirko , Traversi Rita , Fanos Vassilios , Street Maria Elisabeth , Palanza Paola , Rovero Paolo , Papini Anna Maria
Published: November 2024

Exposure to endocrine-disrupting chemicals (EDCs) is inevitable, and growing scientific evidence indicates that even very low doses can negatively impact human health, particularly during pregnancy and the neonatal period. As part of the European project LIFE18 ENV/IT/00460, this study aims to identify the presence of EDCs in 20 infant formulas (both powdered and liquid) and the release from baby bottles and teats. Particularly, sensitization of young people and future parents towards the potential harmful effects of EDCs could significantly help to reduce exposure. Seven different UPLC-MS/MS methodologies and one ICP-AES were set up to quantify already assessed and suspected EDCs among 85 different chemicals (bisphenols, parabens, PAHs, phthalates, pesticides, herbicides and their main metabolites, PFAS, and metals). Results showed that in 2 out of 14 baby bottles, only anthracene and phenanthrene of the group of PAHs were released (10.68–10.81 ng/mL). Phthalates such as mono-ethyl phthalate (MEP) were found in 9 of 14 samples (0.054–0.140 ng/mL), while mono(2-ethyl-5-oxohexyl) phthalate (MeOHP) appeared in 2 samples (0.870–0.930 ng/mL). In accordance with current EU regulations, other chemicals were not detected in baby bottles and teats. However, bisphenols, parabens, PAHs, phthalates, PFAS, and metals were detected in infant formula, emphasizing the need for continued monitoring and public health interventions.
Synthesis of Novel Gefitinib-Conjugated 1,2,3-Triazole Derivatives and Their Effect of Inducing DNA Damage and Apoptosis in Tumor Cells
Authors: Wu Junfei , Huang Xu , Lu Shan , Wang Ziyi , Mao Longfei , Li Sanqiang
Published: November 2024

Compounds with rigid planar structures can insert into tumor cell DNA, thereby inducing DNA damage in tumor cells. In this study, quinazoline, a compound with a planar structure, was used as the core scaffold. A rigid planar 1,2,3-triazole moiety was introduced into its structure, and its activity was tested on HepG2 liver cancer cells. The results showed that most compounds exhibited inhibitory effects on HepG2 cells, and the IC50 values of the most effective compounds were 3.08 ± 0.37 μM and 3.60 ± 0.53 μM. We found that the designed compounds significantly upregulated the expression of γ-H2AX in tumor cells, inducing DNA damage while reducing PARP levels, thereby weakening the DNA damage repair capacity of tumor cells and leading to apoptosis. Additionally, these compounds inhibited the migration and invasion of HepG2 cells. One of the compounds was found to be low in toxicity in mice, suggesting its potential as a targeted DNA anti-tumor drug.
Carbon Nanotube–Phenyl Modified g-C3N4: A Visible Light Driven Efficient Charge Transfer System for Photocatalytic Degradation of Rhodamine B
Authors: Ghourichay Sahar Aghapour , Agbolaghi Samira , Corpino Riccardo , Ricci Pier Carlo
Published: November 2024

In this study, we report the synthesis and characterization of a novel photocatalyst composite composed of functionalized carbon nanotubes (f-CNT) and phenyl-modified graphitic carbon nitride (PhCN). The incorporation of the phenyl group extends the absorption range into the visible spectrum compared to pure g-C3N4. Additionally, the formation of the heterostructure in the f-CNT/PhCN composite exhibits improved charge transfer efficiency, facilitating the separation and transfer of photogenerated electron-hole pairs and reducing recombination rates. The photocatalytic performance of this composite was evaluated by the degradation of Rhodamine B (RhB) under visible light irradiation. The f-CNT/PhCN composite exhibits remarkable efficiency in degrading RhB, achieving 60% degradation after 4 h, and 100% after 24 h under low-power white LED excitation. This represents a substantial improvement over the non-functionalized CNT/PhCN composite, which shows much lower performance. In contrast, pure PhCN demonstrates very little activity. Structural and optical properties were characterized using X-ray diffraction (XRD), transmission electron microscopy (TEM), Raman spectroscopy, and UV–Vis spectroscopy. Time-resolved photoluminescence measurements were used to study the behavior of photoexcited carriers, confirming that the composite improves charge transfer efficiency for photogenerated carriers by approximately 30%. The results indicate that the functionalization of CNTs significantly enhances the photocatalytic properties of the composite, making f-CNT/PhCN a promising candidate for environmental remediation applications, particularly in the degradation of organic pollutants in wastewater.
Cajaninstilbene Acid and Its Derivative as Multi-Therapeutic Agents: A Comprehensive Review
Authors: Hou Wen , Huang Lejun , Wang Jinyang , Luyten Walter , Lai Jia , Zhou Zhinuo , Kang Sishuang , Dai Ping , Wang Yanzhu , Huang Hao , Lan Jinxia
Published: November 2024

Pigeon pea (Cajanus cajan (L.) Millsp.) is a traditional Chinese medicinal plant widely utilized in folk medicine due to its significant pharmacological and nutritional properties. Cajaninstilbene acid (CSA), a stilbene compound derived from pigeon pea leaves, has been extensively investigated since the 1980s. A thorough understanding of CSA’s mechanisms of action and its therapeutic effects on various diseases is crucial for developing novel therapeutic approaches. This paper presents an overview of recent research advancements concerning the biological activities and mechanisms of CSA and its derivatives up to February 2024. The review encompasses discussions on the in vivo metabolism of CSA and its derivatives, including antipathogenic micro-organisms activity, anti-tumor activity, systematic and organ protection activity (such as bone protection, cardiovascular protection, neuroprotection), anti-inflammatory activity, antioxidant activity, immune regulation as well as action mechanism of CSA and its derivatives. The most studied activities are antipathogenic micro-organisms activities. Additionally, the structure–activity relationships of CSA and its derivatives as well as the total synthesis of CSA are explored, highlighting the potential for developing new pharmaceutical agents. This review aims to provide a foundation for future clinical applications of CSA and its derivatives.
A CD Study of a Structure-Based Selection of N-Heterocyclic Bis-Carbene Gold(I) Complexes as Potential Ligands of the G-Quadruplex-Forming Human Telomeric hTel23 Sequence
Authors: Marzano Maria , Prencipe Filippo , Delre Pietro , Mangiatordi Giuseppe Felice , Travagliante Gabriele , Ronga Luisa , Piccialli Gennaro , Saviano Michele , D’Errico Stefano , Tesauro Diego , Oliviero Giorgia
Published: November 2024

Herein, we report the structure-based selection via molecular docking of four N-heterocyclic bis-carbene gold(I) complexes, whose potential as ligands for the hTel23 G-quadruplex structure has been investigated using circular dichroism (CD) spectroscopy, CD melting, and polyacrylamide gel electrophoresis (PAGE). The complex containing a bis(1,2,3,4,6,7,8,9-octahydro-11H-11λ3-pyridazino[1,2-a]indazol-11-yl) scaffold induces a transition from the hybrid (3 + 1) topology to a prevalent parallel G-quadruplex conformation, whereas the complex featuring a bis(2-(2-acetamidoethyl)-3λ3-imidazo[1,5-a]pyridin-3(2H)-yl) moiety disrupted the original G-quadruplex structure. These results deserve particular attention in light of the recent findings on the pathological involvements of G-quadruplexes in neurodegenerative diseases.
Comparison of the Minimum Inhibitory and Mutant Prevention Drug Concentrations for Pradofloxacin and 7 Other Antimicrobial Agents Tested Against Swine Isolates of Actinobacillus pleuropneumoniae and Pasteurella multocida
Authors: Blondeau Joseph M. , Fitch Shantelle D.
Published: November 2024

Pradofloxacin is a dual targeting, bactericidal fluoroquinolone recently approved for treating bacteria causing swine respiratory disease. Currently, an abundance of in vitro data does not exist for pradofloxacin. We determined the minimum inhibitory concentration (MIC) and mutant prevention concentrations (MPC) of pradofloxacin compared to ceftiofur, enrofloxacin, florfenicol, marbofloxacin, tildipirosin, tilmicosin and tulathromycin against swine isolates of Actinobacillus pleuropneumoniae and Pasteurella multocida. Overall, pradofloxacin had the lowest MIC and MPC values as compared to the other agents tested. For example, pradofloxacin MIC values for 50%, 90% and 100% of A. pleuropneumoniae strains were ≤0.016 µg/mL, ≤0.016 µg/mL and ≤0.016 µg/mL and for P. multocida were ≤0.016 µg/mL, ≤0.016 µg/mL and 0.031 µg/mL, respectively. The MPC values for 50%, 90% and 100% of A. pleuropneumoniae strains were 0.031 µg/mL, 0.063 µg/mL and 0.125 µg/mL and for P. multocida were ≤0.016 µg/mL, 0.031 µg/mL and 0.0.063 µg/mL, respectively. By MPC testing, all strains were at or below the susceptibility breakpoint. Based on MPC testing, pradofloxacin appears to have a low likelihood for resistance selection. This study represents the most comprehensive in vitro comparison of the above noted drugs and the first report for pradofloxacin and tildipirosin.
Design, Synthesis and Crystal Structure of a Novel Fluorescence Probe for Zn2+ Based on Pyrano[3,2-c] Carbazole
Authors: Xie Ziyin , Fang Qingwen , Xiao Shuzhen , Wang Jie , Lin Ping , Guo Chunmei , Cao Huihua , Yin Zhongping , Dong Lihong , Peng Dayong
Published: November 2024

Zinc is a trace element, which plays an important role in many biological processes. The deficiency of zinc will lead to many diseases. Thus, it is of great significance to develop fast and efficient quantitative detection technology for zinc ions. In this study, a novel fluorescence probe FP2 was designed for Zn2+ quantification based on pyrano[3,2-c] carbazole. The structure of FP2 was characterized by 1HNMR, 13CNMR, HRMS, and X-ray diffraction. In the HEPES buffer solution, FP2 is responsive to Zn2+ and greatly enhanced. The pH value and reaction time were investigated, and the optimum reaction conditions were determined as follows: the pH was 7~9 and the reaction time was longer than 24 min. Under the optimized conditions, the concentration of FP2 and Zn2+ showed a good linear relationship in the range of 0~10 μM, and the LOD was 0.0065 μmol/L. In addition, through the 1H NMR titration experiment, density functional theory calculation, and the job plot of FP2 with Zn2+ in the HEPES buffer solution, the binding mode of FP2 and Zn2+ was explained. Finally, the method of flame atomic absorption spectrometry (FAAS) and FP2 were used to detect the content of Zn2+ in the water extract of tea. The results showed that the FP2 method is more accurate than the FAAS method, which shows that the method described in this work could be used to detect the content of Zn2+ in practical samples and verify the practicability of this method.
Highly Efficient Reduction of Cr (VI) with C4H6O6
Authors: Peng Hao , Qin Zonghui , Jin Guixuan , Wang Jingjing , Qin Jielin , Ao Lihua , Li Bing
Published: November 2024

In this paper, tartaric acid (C4H6O6) was used as a reductant to treat chromium (VI)-containing solution. Several independent experimental parameters, including reaction temperature, concentration of H2SO4, concentration of C4H6O6 and reaction time, on the reduction process were studied. The results showed that 100% of the Cr (VI) could be reduced by C4H6O6 in a strong acidic environment under a high reaction temperature. All of the experimental parameters showed positive effects on the reduction process and followed the order [H2SO4] > [C4H6O6] > reaction temperature > reaction time. A higher concentration of tartaric acid and higher reaction temperature could facilitate the reduction process and reduce reaction time.
Let Us Build a Table: Decolonization, Institutional Hierarchies, and Prestige in Academic Communities
Authors: Oelofsen Rianna
Published: November 2024

If global higher education is truly committed to decolonization, there will have to be some radical changes. A decolonized university would increase the freedom of students and staff through undoing the legacy of the past, a past which was exclusive and homogenous. In order for this to materialize, universities must adopt a different consciousness. They must move away from the current culture that has privileged global north epistemic and pedagogical frameworks that serve to alienate the student from the global south. For universities to be able to undo the effects of the epistemic injustice that indigenous students have faced, the academy must approach education with a new mindfulness of whom it is that it is designed to serve. When we approach higher education with a consciousness of decolonization and a recognition of the identity of whom the education system is meant to serve, then management systems and epistemic and pedagogical frameworks in our universities cannot remain abstract in nature. Rather they must be fully cognizant of the students’ backgrounds, their social needs, and their academic needs. These cannot be mere considerations but must be the information which directs what is taught and how it is taught, for a just education system is not and can never be decontextualized. As Afro-communitarianism prescribes, decontextualization disregards the necessity of, and integral relationships to, others and the world. Any just pedagogical system must acknowledge the legitimacy of, and draw from, contributions in culture, knowledge, and perspective that come from the students themselves—both as individuals and as insiders of a particular class, culture, and indigenous group. It is in this symbiotic relationship where both the student and the educator can begin to be humanized again.
Trade-Off Regulation in Plant Growth and Stress Responses Through the Role of Heterotrimeric G Protein Signaling
Authors: Lee Horim
Published: November 2024

Unlike animals, plants are sessile organisms that cannot migrate to more favorable conditions and must constantly adapt to a variety of biotic and abiotic stresses. Therefore, plants exhibit developmental plasticity to cope, which is probably based on the underlying trade-off mechanism that allocates energy expenditure between growth and stress responses to achieve appropriate growth and development under different environmental conditions. Plant heterotrimeric G protein signaling plays a crucial role in the trade-off involved in the regulation of normal growth and stress adaptation. This review examines the composition and signaling processes of heterotrimeric G proteins in plants, detailing how they balance growth and adaptive responses in plant immunity and thermomorphogenesis through recent advances in the field. Understanding the trade-offs associated with plant G protein signaling will have significant implications for agricultural innovation, particularly in the development of crops with improved resilience and minimal growth penalties under environmental stress.
Deodeokaloid, a New Indole Alkaloid N-Glycoside and Bioactive Phenolic Compounds from the Roots of Codonopsis lanceolata
Authors: Cho Yeo Rang , Hong Joo-Hyun , Kang Dong-Min , Ko Yoon-Joo , Ahn Mi-Jeong , Kim Ki Hyun
Published: November 2024

Codonopsis lanceolata, commonly known as the bonnet bellflower or deodeok, is primarily found in Eastern Asia. Its roots have been used traditionally across Asia to treat various ailments such as bronchitis, coughs, asthma, and inflammation. In our ongoing efforts to discover bioactive natural products, a phytochemical investigation of the n-BuOH fraction of C. lanceolata root extracts led to the isolation and identification of a new indole alkaloid N-glycoside, deodeokaloid (D-indole-3-lactic acid N-β-D-glucopyranoside) (1), alongside known compounds tangshenoside I (2), tangshenoside IV (3), and chlorogenic acid (4) through HPLC purification. The structure of the new compound 1 was elucidated using 1D and 2D NMR spectroscopy and high-resolution electrospray ionization mass spectrometry (HR-ESIMS). Its absolute configuration was determined through a combination of DP4+ probability analysis and chemical reactions. The isolated compounds 1–4 were evaluated for their anti-Helicobacter pylori and antioxidant activities. In the anti-H. pylori assay, compound 3 showed antibacterial activity similar to that of quercetin as the positive control, inhibiting the bacterial growth by 36.8%. Compound 4 exhibited the most potent antioxidant activity, with an ABTS [2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonate)] radical scavenging activity of 1624.7 mmol TE/mol and a DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging capacity of 707.5 mmol Trolox equivalent (TE)/mol. Compounds 2–4 displayed significant intracellular reactive oxygen species (ROS) scavenging capacity in lipopolysaccharide-stimulated RAW 264.7 macrophage cells. This study highlights C. lanceolata roots as a promising natural source of bioactive compounds with potential therapeutic applications.
Optimizing Brassica oleracea L. Breeding Through Somatic Hybridization Using Cytoplasmic Male Sterility (CMS) Lines: From Protoplast Isolation to Plantlet Regeneration
Authors: Romero-Muñoz Miriam , Pérez-Jiménez Margarita
Published: November 2024

The Brassica oleracea L. species embrace important horticultural crops, such as broccoli, cauliflower, and cabbage, which are highly valued for their beneficial nutritional effects. However, the complexity of flower emasculation in these species has forced breeders to adopt biotechnological approaches such as somatic hybridization to ease hybrid seed production. Protoplasts entail a versatile tool in plant biotechnology, supporting breeding strategies that involve genome editing and hybridization. This review discusses the use of somatic hybridization in B. oleracea L. as a biotechnological method for developing fusion products with desirable agronomic traits, particularly cytoplasmic male sterile (CMS) condition. These CMS lines are critical for implementing a cost-effective, efficient, and reliable system for producing F1 hybrids. We present recent studies on CMS systems in B. oleracea L. crops, providing an overview of established models that explain the mechanisms of CMS and fertility restoration. Additionally, we emphasize key insights gained from protoplast fusion applied to B. oleracea L. breeding. Key steps including pre-treatments of donor plants, the main tissues used as sources of parental protoplasts, methods for obtaining somatic hybrids and cybrids, and the importance of establishing a reliable plant regeneration method are discussed. Finally, the review explores the incorporation of genome editing technologies, such as CRISPR-Cas9, to introduce multiple agronomic traits in Brassica species. This combination of advanced biotechnological tools holds significant promise for enhancing B. oleracea breeding programs in the actual climate change context.
Diagnosis and Treatment of Bronchopulmonary Lophomoniasis in a Patient with Persistent Granuloma: A Case Report
Authors: Mier-Briseño Antonio , Ramírez-Alanís Eloísa , Benavides-Huerto Miguel Armando , Lagunas-Rangel Francisco Alejandro
Published: November 2024

Background and Clinical Significance: Lophomonas is a multiflagellate anaerobic protozoan that usually inhabits the intestines of insects, mainly cockroaches. However, bronchopulmonary infections caused by this parasite have been increasingly reported worldwide in recent decades. We provide important information for the diagnosis of this disease, which often goes undetected and frequently leads to misdiagnosis and inadequate treatment. It is noteworthy that this is the third case reported in Mexico. Case Presentation: A 37-year-old male patient was hospitalized several times for pneumonia with a persistent granuloma in the right bronchial lobe. After extensive testing, the patient was diagnosed with bronchopulmonary lophomoniasis and successfully treated with metronidazole. Conclusions: Clinicians worldwide should be aware of the existence of lophomoniasis, especially in low-income regions with poor sanitation and high insect exposure. This parasitic infection, although rare, may be underestimated due to its nonspecific respiratory symptoms, which may mimic other infections.
Detection and Monitoring of Mining-Induced Seismicity Based on Machine Learning and Template Matching: A Case Study from Dongchuan Copper Mine, China
Authors: Wu Tao , Liu Zhikun , Yan Shaopeng
Published: November 2024

The detection and monitoring of mining-induced seismicity are essential for understanding the mechanisms behind earthquakes and mitigating seismic hazards. However, traditional underground seismic monitoring networks for mining-induced seismicity are challenging to install and operate, which has limited their widespread application. In recent years, an alternative approach has emerged: utilizing dense seismic arrays at the surface to monitor mining-induced seismicity. This paper proposes a rapid and efficient data processing scheme for the detection and monitoring of mining-induced seismicity based on the surface dense array. The proposed workflow includes machine learning-based phase picking and P-wave first-motion-polarity picking, followed by rapid phase association, precise earthquake location, and template matching for detecting small earthquakes to enhance the completeness of the earthquake catalog. Additionally, it also provides focal mechanism solutions for larger mining-induced events. We applied this workflow to the continuous waveform data from 90 seismic stations over a period of 27 days around the Dongchuan Copper Mine, Yunnan Province, China. Our results yielded 1536 high-quality earthquake locations and two focal mechanism solutions for larger events. By analyzing the spatiotemporal distribution of these events, we are able to investigate the mechanisms of the induced seismic clusters near the Shijiangjun and Lanniping deposits. Our findings highlight the excellent monitoring capability and application potential of the workflow based on machine learning and template matching compared with conventional techniques.
A Precise and Scalable Indoor Positioning System Using Cross-Modal Knowledge Distillation
Authors: Rizk Hamada , Elmogy Ahmed , Rihan Mohamed , Yamaguchi Hirozumi
Published: November 2024

User location has emerged as a pivotal factor in human-centered environments, driving applications like tracking, navigation, healthcare, and emergency response that align with Sustainable Development Goals (SDGs). However, accurate indoor localization remains challenging due to the limitations of GPS in indoor settings, where signal interference and reflections disrupt satellite connections. While Received Signal Strength Indicator (RSSI) methods are commonly employed, they are affected by environmental noise, multipath fading, and signal interference. Round-Trip Time (RTT)-based localization techniques provide a more resilient alternative but are not universally supported across access points due to infrastructure limitations. To address these challenges, we introduce DistilLoc: a cross-knowledge distillation framework that transfers knowledge from an RTT-based teacher model to an RSSI-based student model. By applying a teacher–student architecture, where the RTT model (teacher) trains the RSSI model (student), DistilLoc enhances RSSI-based localization with the accuracy and robustness of RTT without requiring RTT data during deployment. At the core of DistilLoc, the FNet architecture is employed for its computational efficiency and capacity to capture complex relationships among RSSI signals from multiple access points. This enables the student model to learn a robust mapping from RSSI measurements to precise location estimates, reducing computational demands while improving scalability. Evaluation in two cluttered indoor environments of varying sizes using Android devices and Google WiFi access points, DistilLoc achieved sub-meter localization accuracy, with median errors of 0.42 m and 0.32 m, respectively, demonstrating improvements of 267% over conventional RSSI methods and 496% over multilateration-based approaches. These results validate DistilLoc as a scalable, accurate solution for indoor localization, enabling intelligent, resource-efficient urban environments that contribute to SDG 9 (Industry, Innovation, and Infrastructure) and SDG 11 (Sustainable Cities and Communities).
Embedding AI-Enabled Data Infrastructures for Sustainability in Agri-Food: Soft-Fruit and Brewery Use Case Perspectives
Authors: Markovic Milan , Li Andy , Ayall Tewodros Alemu , Watson Nicholas J. , Bowler Alexander L. , Woods Mel , Edwards Peter , Ramsey Rachael , Beddows Matthew , Kuhnert Matthias , Leontidis Georgios
Published: November 2024

The agri-food sector is undergoing a comprehensive transformation as it transitions towards net zero. To achieve this, fundamental changes and innovations are required, including changes in how food is produced and delivered to customers, new technologies, data and physical infrastructures, and algorithmic advancements. In this paper, we explore the opportunities and challenges of deploying AI-based data infrastructures for sustainability in the agri-food sector by focusing on two case studies: soft-fruit production and brewery operations. We investigate the potential benefits of incorporating Internet of Things (IoT) sensors and AI technologies for improving the use of resources, reducing carbon footprints, and enhancing decision-making. We identify user engagement with new technologies as a key challenge, together with issues in data quality arising from environmental volatility, difficulties in generalising models, including those designed for carbon calculators, and socio-technical barriers to adoption. We highlight and advocate for user engagement, more granular availability of sensor, production, and emissions data, and more transparent carbon footprint calculations. Our proposed future directions include semantic data integration to enhance interoperability, the generation of synthetic data to overcome the lack of real-world farm data, and multi-objective optimisation systems to model the competing interests between yield and sustainability goals. In general, we argue that AI is not a silver bullet for net zero challenges in the agri-food industry, but at the same time, AI solutions, when appropriately designed and deployed, can be a useful tool when operating in synergy with other approaches.
Privacy-Preserving Detection of Tampered Radio-Frequency Transmissions Utilizing Federated Learning in LoRa Networks
Authors: Senol Nurettin Selcuk , Baza Mohamed , Rasheed Amar , Alsabaan Maazen
Published: November 2024

LoRa networks, widely adopted for low-power, long-range communication in IoT applications, face critical security concerns as radio-frequency transmissions are increasingly vulnerable to tampering. This paper addresses the dual challenges of privacy-preserving detection of tampered transmissions and the identification of unknown attacks in LoRa-based IoT networks. Leveraging Federated Learning (FL), our approach enables the detection of tampered RF transmissions while safeguarding sensitive IoT data, as FL allows model training on distributed devices without sharing raw data. We evaluated the performance of multiple FL-enabled anomaly-detection algorithms, including Convolutional Autoencoder Federated Learning (CAE-FL), Isolation Forest Federated Learning (IF-FL), One-Class Support Vector Machine Federated Learning (OCSVM-FL), Local Outlier Factor Federated Learning (LOF-FL), and K-Means Federated Learning (K-Means-FL). Using metrics such as accuracy, precision, recall, and F1-score, CAE-FL emerged as the top performer, achieving 97.27% accuracy and a balanced precision, recall, and F1-score of 0.97, with IF-FL close behind at 96.84% accuracy. Competitive performance from OCSVM-FL and LOF-FL, along with the comparable results of K-Means-FL, highlighted the robustness of clustering-based detection methods in this context. Visual analyses using confusion matrices and ROC curves provided further insights into each model’s effectiveness in detecting tampered signals. This research underscores the capability of federated learning to enhance privacy and security in anomaly detection for LoRa networks, even against unknown attacks, marking a significant advancement in securing IoT communications in sensitive applications.
Correction: Kaur, M.; Menon, C. Submillimeter Sized 2D Electrothermal Optical Fiber Scanner. Sensors 2023, 23, 404
Authors: Kaur Mandeep , Menon Carlo
Published: November 2024

The Editorial Office and Editorial Board of Sensors are jointly issuing a resolution and removal of the Journal Notice linked to this article [...]
Toward Improving Human Training by Combining Wearable Full-Body IoT Sensors and Machine Learning
Authors: Akter Nazia , Molnar Andreea , Georgakopoulos Dimitrios
Published: November 2024

This paper proposes DigitalUpSkilling, a novel IoT- and AI-based framework for improving and personalising the training of workers who are involved in physical-labour-intensive jobs. DigitalUpSkilling uses wearable IoT sensors to observe how individuals perform work activities. Such sensor observations are continuously processed to synthesise an avatar-like kinematic model for each worker who is being trained, referred to as the worker’s digital twins. The framework incorporates novel work activity recognition using generative adversarial network (GAN) and machine learning (ML) models for recognising the types and sequences of work activities by analysing an individual’s kinematic model. Finally, the development of skill proficiency ML is proposed to evaluate each trainee’s proficiency in work activities and the overall task. To illustrate DigitalUpSkilling from wearable IoT-sensor-driven kinematic models to GAN-ML models for work activity recognition and skill proficiency assessment, the paper presents a comprehensive study on how specific meat processing activities in a real-world work environment can be recognised and assessed. In the study, DigitalUpSkilling achieved 99% accuracy in recognising specific work activities performed by meat workers. The study also presents an evaluation of the proficiency of workers by comparing kinematic data from trainees performing work activities. The proposed DigitalUpSkilling framework lays the foundation for next-generation digital personalised training.
Instant-SFH: Non-Iterative Sparse Fourier Holograms Using Perlin Noise
Authors: Li David , Jabbireddy Susmija , Zhang Yang , Metzler Christopher , Varshney Amitabh
Published: November 2024

Holographic displays are an upcoming technology for AR and VR applications, with the ability to show 3D content with accurate depth cues, including accommodation and motion parallax. Recent research reveals that only a fraction of holographic pixels are needed to display images with high fidelity, improving energy efficiency in future holographic displays. However, the existing iterative method for computing sparse amplitude and phase layouts does not run in real time; instead, it takes hundreds of milliseconds to render an image into a sparse hologram. In this paper, we present a non-iterative amplitude and phase computation for sparse Fourier holograms that uses Perlin noise in the image–plane phase. We conduct simulated and optical experiments. Compared to the Gaussian-weighted Gerchberg–Saxton method, our method achieves a run time improvement of over 600 times while producing a nearly equal PSNR and SSIM quality. The real-time performance of our method enables the presentation of dynamic content crucial to AR and VR applications, such as video streaming and interactive visualization, on holographic displays.
Prediction and Elimination of Physiological Tremor During Control of Teleoperated Robot Based on Deep Learning
Authors: Chen Juntao , Zhang Zhiqing , Guan Wei , Cao Xinxin , Liang Ke
Published: November 2024

Currently, teleoperated robots, with the operator’s input, can fully perceive unknown factors in a complex environment and have strong environmental interaction and perception abilities. However, physiological tremors in the human hand can seriously affect the accuracy of processes that require high-precision control. Therefore, this paper proposes an EEMD-IWOA-LSTM model, which can decompose the physiological tremor of the hand into several intrinsic modal components (IMF) by using the EEMD decomposition strategy and convert the complex nonlinear and non-stationary physiological tremor curve of the human hand into multiple simple sequences. An LSTM neural network is used to build a prediction model for each (IMF) component, and an IWOA is proposed to optimize the model, thereby improving the prediction accuracy of the physiological tremor and eliminating it. At the same time, the prediction results of this model are compared with those of different models, and the results of EEMD-IWOA-LSTM presented in this study show obvious superior performance. In the two examples, the MSE of the prediction model proposed are 0.1148 and 0.00623, respectively. The defibrillation model proposed in this study can effectively eliminate the physiological tremor of the human hand during teleoperation and improve the control accuracy of the robot during teleoperation.
Mask-Guided Spatial–Spectral MLP Network for High-Resolution Hyperspectral Image Reconstruction
Authors: Han Xian-Hua , Wang Jian , Chen Yen-Wei
Published: November 2024

Hyperspectral image (HSI) reconstruction is a critical and indispensable step in spectral compressive imaging (CASSI) systems and directly affects our ability to capture high-quality images in dynamic environments. Recent research has increasingly focused on deep unfolding frameworks for HSI reconstruction, showing notable progress. However, these approaches have to break the optimization task into two sub-problems, solving them iteratively over multiple stages, which leads to large models and high computational overheads. This study presents a simple yet effective method that passes the degradation information (sensing mask) through a deep learning network to disentangle the degradation and the latent target’s representations. Specifically, we design a lightweight MLP block to capture non-local similarities and long-range dependencies across both spatial and spectral domains, and investigate an attention-based mask modelling module to achieve the spatial–spectral-adaptive degradation representationthat is fed to the MLP-based network. To enhance the information flow between MLP blocks, we introduce a multi-level fusion module and apply reconstruction heads to different MLP features for deeper supervision. Additionally, we combine the projection loss from compressive measurements with reconstruction loss to create a dual-domain loss, ensuring consistent optical detection during HS reconstruction. Experiments on benchmark HS datasets show that our method outperforms state-of-the-art approaches in terms of both reconstruction accuracy and efficiency, reducing computational and memory costs.
Assessing Changes in Motor Function and Mobility in Individuals with Parkinson’s Disease After 12 Sessions of Patient-Specific Adaptive Dynamic Cycling
Authors: Kim Younguk , Smith Brittany E. , Shigo Lara , Shaikh Aasef G. , Loparo Kenneth A. , Ridgel Angela L.
Published: November 2024

Background and Purpose: This pilot randomized controlled trial evaluated the effects of 12 sessions of patient-specific adaptive dynamic cycling (PSADC) versus non-adaptive cycling (NA) on motor function and mobility in individuals with Parkinson’s disease (PD), using inertial measurement unit (IMU) sensors for objective assessment. Methods: Twenty-three participants with PD (13 in the PSADC group and 10 in the NA group) completed the study over a 4-week period. Motor function was measured using the Kinesia™ sensors and the MDS-UPDRS Motor III, while mobility was assessed with the TUG test using OPAL IMU sensors. Results: The PSADC group showed significant improvements in MDS-UPDRS Motor III scores (t = 5.165, p < 0.001) and dopamine-sensitive symptoms (t = 4.629, p = 0.001), whereas the NA group did not improve. Both groups showed non-significant improvements in TUG time. IMU sensors provided continuous, quantitative, and unbiased measurements of motor function and mobility, offering a more precise and objective tracking of improvements over time. Conclusions: PSADC demonstrated enhanced treatment effects on PD motor function compared to NA while also reducing variability in individual responses. The integration of IMU sensors was essential for precise monitoring, supporting the potential of a data-driven, individualized exercise approach to optimize treatment outcomes for individuals with PD.
AI-Driven Electrical Fast Transient Suppression for Enhanced Electromagnetic Interference Immunity in Inductive Smart Proximity Sensors
Authors: Giangaspero Silvia , Nicchiotti Gianluca , Venier Philippe , Genilloud Laurent , Pirrami Lorenzo
Published: November 2024

Inductive proximity sensors are relevant in position-sensing applications in many industries but, in order to be used in harsh industrial environments, they need to be immune to electromagnetic interference (EMI). The use of conventional filters to mitigate these perturbations often compromises signal bandwidth, ranging from 100 Hz to 1.6 kHz. We have exploited recent advances in the field of artificial intelligence (AI) to study the ability of neural networks (NNs) to automatically filter out EMI features. This study offers an analysis and comparison of possible NN models (a 1D convolutional NN, a recurrent NN, and a hybrid convolutional and recurrent approach) for denoising EMI-perturbed signals and proposes a final model, which is based on gated recurrent unit (GRU) layers. This network is compressed and optimised to meet memory requirements, so that in future developments it could be implemented in application-specific integrated circuits (ASICs) for inductive sensors. The final RNN manages to reduce noise by 70% (MSEred) while occupying 2 KB of memory.
Fabry–Perot Effect Suppression in Gas Cells Used in THz Absorption Spectrometers. Experimental Verification
Authors: Raspopin George K. , Borisov Alexey V. , Cuisset Arnaud , Hindle Francis , Yakovlev Semyon V. , Kistenev Yury V.
Published: November 2024

A standard measuring gas cell used in absorption spectrometers is a cylinder enclosed by two transparent windows. The Fabry–Perot effects caused by multiple reflections of terahertz waves between these windows produce significant variations in the transmitted radiation intensity. Therefore, the Fabry–Perot effects should be taken into account to correctly measure absorption spectra in Bouguer law-based absorption spectroscopy. One approach to reducing the Fabry–Perot effects is based on inserting an additional external movable window with the standard measuring gas cell. This was proposed and numerically analyzed in our previous work. This paper is aimed at the experimental validation of this method when using amplitude modulation (AM) spectroscopy. Also, a comparison of the efficiency of reducing the Fabry–Perot effects using this method is experimentally compared to frequency modulation spectroscopy. The latter was shown to effectively reduce the Fabry–Perot effects compared to AM spectroscopy with the standard measuring gas cell, and the use of the external movable window was shown to further improve the elimination of Fabry–Perot effects.
No-Reference Objective Quality Metrics for 3D Point Clouds: A Review
Authors: Porcu Simone , Marche Claudio , Floris Alessandro
Published: November 2024

Three-dimensional (3D) applications lead the digital transition toward more immersive and interactive multimedia technologies. Point clouds (PCs) are a fundamental element in capturing and rendering 3D digital environments, but they present significant challenges due to the large amount of data typically needed to represent them. Although PC compression techniques can reduce the size of PCs, they introduce degradations that can negatively impact the PC’s quality and therefore the object representation’s accuracy. This trade-off between data size and PC quality highlights the critical importance of PC quality assessment (PCQA) techniques. In this article, we review the state-of-the-art no-reference (NR) objective quality metrics for PCs, which can accurately estimate the quality of generated and compressed PCs solely based on feature information extracted from the distorted PC. These characteristics make NR PCQA metrics particularly suitable in real-world application scenarios where the original PC data are unavailable for comparison, such as in streaming applications.
Estimation of Arterial Path Flow Considering Flow Distribution Consistency: A Data-Driven Semi-Supervised Method
Authors: Zhang Zhe , Cao Qi , Lin Wenxie , Song Jianhua , Chen Weihan , Ren Gang
Published: November 2024

To implement fine-grained progression signal control on arterial, it is essential to have access to the time-varying distribution of the origin–destination (OD) flow of the arterial. However, due to the sparsity of automatic vehicle identification (AVI) devices and the low penetration of connected vehicles (CVs), it is difficult to directly obtain the distribution pattern of arterial OD flow (i.e., path flow). To solve this problem, this paper develops a semi-supervised arterial path flow estimation method considering the consistency of path flow distribution by combining the sparse AVI data and the low permeability CV data. Firstly, this paper proposes a semi-supervised arterial path flow estimation model based on multi-knowledge graphs. It utilizes graph neural networks to combine some arterial AVI OD flow observation information with CV trajectory information to infer the path flow of AVI unobserved OD pairs. Further, to ensure that the estimation results of the multi-knowledge graph path flow estimation model are consistent with the distribution of path flow in real situations, we introduce a generative adversarial network (GAN) architecture to correct the estimation results. The proposed model is extensively tested based on a real signalized arterial. The results show that the proposed model is still able to achieve reliable estimation results under low connected vehicle penetration and with less observed label data.
Influence of Insulin Pen Needle Geometry on Pain Perception and Patient’s Acceptability: A Review
Authors: De Tommasi Francesca , Silvestri Sergio
Published: November 2024

Diabetes is one of the most common diseases worldwide, with an increasing number of people affected. Insulin therapy is still the major treatment for both Type 1 and Type 2 diabetes and has evolved from bulky syringes to modern insulin pens introduced in 1985. An insulin pen consists of three major parts: a cartridge, a single-use pen needle (PN), and a precision dosing mechanism. Initially, PNs were long and thick, causing great discomfort and concern. Thanks to advances in design, shorter and thinner needles have appeared on the market, improving patient acceptability and pain perception. Studies highlight the influence of PN geometry and other characteristics on injection-related pain, including length, diameter, bevel design, and hub. Despite a lack of specific international regulations for PN geometry, scientific publications have focused on exploring different PNs’ characteristics to optimize patient comfort and reduce pain. To guide the selection of suitable PNs, this review provides a round-up of literature research findings on the impact of PN geometry on pain perception and patient acceptability. Specifically, it provides an overview of the PN manufacturing process, current international regulations, and the state-of-the-art research on PN geometry affecting pain perception.
Assessment of Polycyclic Aromatic Hydrocarbon Exposure in Trainee Firefighters Using PAH CALUX Bioassay
Authors: Grünfeld Johanna , Møller Peter , Vogel Ulla , Jensen Simon Pelle , Kofoed-Sørensen Vivi , Andersen Maria Helena Guerra
Published: November 2024

This work investigated the application of a reporter gene bioassay in assessing polycyclic aromatic hydrocarbon (PAH) exposure in trainee firefighters. In the PAH CALUX bioassay, the PAH-induced activation of the aryl hydrocarbon receptor in a reporter cell line is recorded by increased luminescence. A repeated measurement study was performed, collecting urine and skin wipe samples at two baseline sessions (spring and autumn) and after three firefighting sessions: one with wood fuel, one with gas fuel, and one without fire. The bioassay response was expressed as benzo[a]pyrene equivalents, which was compared to levels of 16 EPA criteria PAHs in skin wipe samples and 8 hydroxylated PAHs (OH-PAHs) in urine samples quantified by chromatography–tandem mass spectrometry techniques. Benzo[a]pyrene equivalents and PAH levels in skin wipes indicated larger exposure to PAHs during the wood session compared to the other sessions. The urine bioassay showed non-significant effect sizes after all sessions, whereas the chemical analysis showed increased OH-PAH levels after the gas session. The non-significant changes observed for the session without fire suggest a negligible exposure from contaminated gear. In conclusion, the bioassay response for skin wipes shows that trainee firefighters were exposed to higher levels of potentially toxic PAHs during the wood fire training session.
The Environmental Hazards and Treatment of Ship’s Domestic Sewage
Authors: Zhang Yanan , Xian Bensen , Sun Wenkai , Lu Ruifang , Zhang Qin , Wang Mei , Xu Dandan , Liu Huili , Bai Shaoyuan , Fu Mingming
Published: November 2024

With the rapid development of the modern shipping field, the damage caused by ship pollution to the global inland waterways and marine ecosystems has attracted extensive attention from the international community. However, there are fewer reviews on the environmental hazards of domestic ship sewage and its treatment, and a systematic summary of the environmental hazards posed by ship domestic sewage and its treatment is lacking. Based on summarizing the various environmental hazards brought about by a ship’s domestic sewage and the corresponding treatment methods, this study elaborates, in detail, on the specific hazards of the main toxic and hazardous substances contained in a ship’s domestic sewage on the environment and organisms, and the treatment methods of the ship’s domestic sewage and their treatment effects, such as membrane bioreactor (MBR). It is also pointed out that MBR has great potential in the direction of ship domestic sewage treatment, and the solution of its membrane pollution and other problems as well as the exploration of the combination of MBR and other treatment methods will become the focus of future research. A theoretical reference is provided for the study of environmental problems caused by domestic sewage from ships and their treatment options.
Black Holes with a Cloud of Strings and Quintessence in a Non-Linear Electrodynamics Scenario
Authors: Nascimento Francinaldo Florencio do , Bezerra Valdir Barbosa , Toledo Jefferson de Morais
Published: November 2024

We obtain exact black hole solutions to Einstein gravity coupled with a nonlinear electrodynamics field, in the presence of a cloud of strings and quintessence, as sources. The solutions have four parameters, namely m, k, a, and α, corresponding to the physical mass of the black hole, the nonlinear charge of a self-gravitating magnetic field, the cloud of strings, and the intensity of the quintessential fluid. The consequences of these sources on the regularity or singularity of the solutions, on their horizons, as well as on the energy conditions, are discussed. We study some aspects concerning the thermodynamics of the black hole, by taking into account the mass, Hawking temperature, and heat capacity and show how these quantities depend on the presence of the cloud of strings and quintessence, in the scenario considered.