bluuebunny/crossref_metadata_2025 huggingface dataset:
The Diagnosis and Treatment Approach for Oligo-Recurrent and Oligo-Progressive Renal Cell Carcinoma
Authors: Bekku Kensuke , Kawada Tatsushi , Sekito Takanori , Yoshinaga Kasumi , Maruyama Yuki , Yamanoi Tomoaki , Tominaga Yusuke , Sadahira Takuya , Katayama Satoshi , Iwata Takehiro , Nishimura Shingo , Edamura Kohei , Kobayashi Tomoko , Kobayashi Yasuyuki , Araki Motoo , Niibe Yuzuru
Published: December 2023

One-third of renal cell carcinomas (RCCs) without metastases develop metastatic disease after extirpative surgery for the primary tumors. The majority of metastatic RCC cases, along with treated primary lesions, involve limited lesions termed “oligo-recurrent” disease. The role of metastasis-directed therapy (MDT), including stereotactic body radiation therapy (SBRT) and metastasectomy, in the treatment of oligo-recurrent RCC has evolved. Although the surgical resection of all lesions alone can have a curative intent, SBRT is a valuable treatment option, especially for patients concurrently receiving systemic therapy. Contemporary immune checkpoint inhibitor (ICI) combination therapies remain central to the management of metastatic RCC. However, one objective of MDT is to delay the initiation of systemic therapies, thereby sparing patients from potentially unnecessary burdens. Undertaking MDT for cases showing progression under systemic therapies, known as “oligo-progression”, can be complex in considering the treatment approach. Its efficacy may be diminished compared to patients with stable disease. SBRT combined with ICI can be a promising treatment for these cases because radiation therapy has been shown to affect the tumor microenvironment and areas beyond the irradiated sites. This may enhance the efficacy of ICIs, although their efficacy has only been demonstrated in clinical trials.
Promises and Pitfalls of Next-Generation Treg Adoptive Immunotherapy
Authors: Christofi Panayiota , Pantazi Chrysoula , Psatha Nikoleta , Sakellari Ioanna , Yannaki Evangelia , Papadopoulou Anastasia
Published: December 2023

Regulatory T cells (Tregs) are fundamental to maintaining immune homeostasis by inhibiting immune responses to self-antigens and preventing the excessive activation of the immune system. Their functions extend beyond immune surveillance and subpopulations of tissue-resident Treg cells can also facilitate tissue repair and homeostasis. The unique ability to regulate aberrant immune responses has generated the concept of harnessing Tregs as a new cellular immunotherapy approach for reshaping undesired immune reactions in autoimmune diseases and allo-responses in transplantation to ultimately re-establish tolerance. However, a number of issues limit the broad clinical applicability of Treg adoptive immunotherapy, including the lack of antigen specificity, heterogeneity within the Treg population, poor persistence, functional Treg impairment in disease states, and in vivo plasticity that results in the loss of suppressive function. Although the early-phase clinical trials of Treg cell therapy have shown the feasibility and tolerability of the approach in several conditions, its efficacy has remained questionable. Leveraging the smart tools and platforms that have been successfully developed for primary T cell engineering in cancer, the field has now shifted towards “next-generation” adoptive Treg immunotherapy, where genetically modified Treg products with improved characteristics are being generated, as regards antigen specificity, function, persistence, and immunogenicity. Here, we review the state of the art on Treg adoptive immunotherapy and progress beyond it, while critically evaluating the hurdles and opportunities towards the materialization of Tregs as a living drug therapy for various inflammation states and the broad clinical translation of Treg therapeutics.
Thyroid Cancer Radiomics: Navigating Challenges in a Developing Landscape
Authors: Maurea Simone , Stanzione Arnaldo , Klain Michele
Published: December 2023

In a review from 2021 by Cao et al [...]
Identifying Lymph Nodes and Their Statuses from Pretreatment Computer Tomography Images of Patients with Head and Neck Cancer Using a Clinical-Data-Driven Deep Learning Algorithm
Authors: Huang Sheng-Yao , Hsu Wen-Lin , Liu Dai-Wei , Wu Edzer L. , Peng Yu-Shao , Liao Zhe-Ting , Hsu Ren-Jun
Published: December 2023

Background: Head and neck cancer is highly prevalent in Taiwan. Its treatment mainly relies on clinical staging, usually diagnosed from images. A major part of the diagnosis is whether lymph nodes are involved in the tumor. We present an algorithm for analyzing clinical images that integrates a deep learning model with image processing and attempt to analyze the features it uses to classify lymph nodes. Methods: We retrospectively collected pretreatment computed tomography images and surgery pathological reports for 271 patients diagnosed with, and subsequently treated for, naïve oral cavity, oropharynx, hypopharynx, and larynx cancer between 2008 and 2018. We chose a 3D UNet model trained for semantic segmentation, which was evaluated for inference in a test dataset of 29 patients. Results: We annotated 2527 lymph nodes. The detection rate of all lymph nodes was 80%, and Dice score was 0.71. The model has a better detection rate at larger lymph nodes. For those identified lymph nodes, we found a trend where the shorter the short axis, the more negative the lymph nodes. This is consistent with clinical observations. Conclusions: The model showed a convincible lymph node detection on clinical images. We will evaluate and further improve the model in collaboration with clinical physicians.
Feasibility Study Utilizing NanoString’s Digital Spatial Profiling (DSP) Technology for Characterizing the Immune Microenvironment in Barrett’s Esophagus Formalin-Fixed Paraffin-Embedded Tissues
Authors: Qurat-ul-Ain  , Frei Nicola F. , Khoshiwal Amir M. , Stougie Pim , Odze Robert , Camilleri-Broet Sophie , Ferri Lorenzo , Duits Lucas C. , Bergman Jacques , Stachler Matthew D.
Published: December 2023

Characterization of the Barrett’s esophagus (BE) microenvironment in patients with a known progression status, to determine how it may influence BE progression to esophageal adenocarcinoma (EAC), has been understudied, hindering both the biological understanding of the progression and the development of novel diagnostics and therapies. This study’s aim was to determine if a highly multiplex interrogation of the microenvironment can be performed on endoscopic formalin-fixed, paraffin-embedded (FFPE) samples, utilizing the NanoString GeoMx digital spatial profiling (GeoMx DSP) platform and if it can begin to identify the types of immune cells and pathways that may mediate the progression of BE. We performed a spatial proteomic analysis of 49 proteins expressed in the microenvironment and epithelial cells of FFPE endoscopic biopsies from patients with non-dysplastic BE (NDBE) who later progressed to high-grade dysplasia or EAC (n = 7) or from patients who, after at least 5 years follow-up, did not (n = 8). We then performed an RNA analysis of 1812 cancer-related transcripts on three endoscopic mucosal resections containing regions of BE, dysplasia, and EAC. Profiling with GeoMx DSP showed reasonable quality metrics and detected expected differences between epithelium and stroma. Several proteins were found to have an increased expression within NDBE biopsies from progressors compared to non-progressors, suggesting further studies are warranted.
Insight into Structural and Physicochemical Properties of ZrO2-SiO2 Monolithic Catalysts with Hierarchical Pore Structure: Effect of Zirconium Precursor
Authors: Maresz Katarzyna , Ciemięga Agnieszka , Bezkosty Patryk , Kornaus Kamil , Sitarz Maciej , Krzywiecki Maciej , Mrowiec-Białoń Julita
Published: December 2023

Zirconia–silica monolithic catalysts with hierarchical micro/macroporous structure were obtained in a sol-gel process combined with phase separation using inorganic salts, i.e., oxychloride, oxynitrate and sulphate, as a zirconium source. It was found that the use of zirconium oxychloride and prehydrolysis of tetraethoxysilane (TEOS) resulted in materials characterized by a well-developed continuous structure of macropores with a diameter of ca. 10 μm. For zirconium oxynitrate and sulfate modified materials, the prehydrolysis hardly affected the macropore size. The micropores with a diameter of 1.5 nm in the skeleton of all materials provided a large surface area of 550–590 m2/g. A high dispersion of zirconia in the silica skeleton in all studied materials was shown. However, the largest surface concentration of Lewis and Brönsted acid sites was found in the monolith synthesized with zirconium oxychloride. The monoliths were used as a core for continuous-flow microreactors and high catalytic activity was confirmed in the deacetalization of benzylaldehyde dimethyl acetal. The process was characterized by a high efficiency at low temperature, i.e., 35 °C.
Assessing the Effects of Refuse-Derived Fuel (RDF) Incorporation on the Extrusion and Drying Behavior of Brick Mixtures
Authors: Makrygiannis Ioannis , Tsetsekou Athena , Papastratis Orestis , Karalis Konstantinos
Published: December 2023

This study explores the potential benefits of incorporating Recycled Demolition Waste (RDF) as an additive in ceramic mass for the brick industry, with a focus on applications such as thermoblocks. The research underscores the significance of sustainable waste management practices and environmental conservation by diverting waste from landfills. RDF, exhibiting combustion properties above 550 °C, emerges as a valuable candidate for enhancing clay-based materials, particularly in the brick production process where firing temperatures exceed 850 °C. Conducted in two phases, the research initially concentrated on RDF preparation, RDF integration with clay materials, and its influence on extrusion and drying phases. Employing innovative techniques involving brick and tile industry machinery coupled with sand incorporation yielded promising results. The grounding of RDF particles to less than 1 mm not only facilitated the mixing process but also ensured stable grinding temperatures within the hammer mill, reducing operational costs. During extrusion, challenges associated with unprocessed RDF material were addressed by utilizing ground RDF, leading to a more efficient and cost-effective process with enhanced plasticity and reduced water requirements. Practical implications for brick plant operations were identified, promoting resource and energy savings. Drying behavior analysis revealed the positive impact of RDF integration, showcasing reduced sensitivity, decreased drying linear shrinkage, and improved density properties. RDF’s role as an inert additive resulted in a 5% reduction in density, enhancing porosity and thermal insulation properties, particularly in thermoblock applications. In the brick industry, where durability, thermal performance, and cost-efficiency are paramount, this study emphasizes the potential benefits of incorporating RDF into clay-based materials. While further research is needed to address the firing procedure of RDF as a brick mass additive, the initial findings underscore the promise of this approach for sustainable and environmentally responsible brick production. This study contributes to the literature by shedding light on the advantages and challenges of integrating RDF into clay-based products, supporting sustainability and waste reduction in construction and manufacturing. The findings provide valuable insights into the performance and feasibility of these mixtures, offering crucial information for industries striving to adopt eco-conscious production methods. This article not only outlines the applied methodology and experimental setup but also presents results related to the behavior of RDF-inclusive clay block mixtures in the production environment. Anticipated to exert considerable influence on future practices and policies, this research contributes to the growing body of knowledge concerning eco-friendly and sustainable manufacturing processes.
Rapid and Sensitive On-Site Detection of Fipronil in Foods Using Evanescent Wave Fluorescent Immunosensor
Authors: Li Yujing , Xu Wenjuan , Liu Jingjing , Zhang Erjing , Li Hejie , Zhang Yan , Zhang Jing , Li Chunsheng , Zhang Xiaoguang
Published: December 2023

Fipronil (FIP), a broad-spectrum phenylpyrazole insecticide, is highly toxic and threatens human health and ecological balance. Developing convenient, rapid, portable analytical technology for on-site and high-frequency testing of FIP is essential to reduce its damage. Herein, a monoclonal antibody (Clone F-3F6) against FIP, with high affinity and specificity, was produced using a novel immunogen, FIP-BSA, which was simply and directly synthesized by conjugating FIP with bovine serum albumin (BSA). Among the previously reported antibodies, F-3F6 acts more specifically against FIP. The FIP metabolites fipronil desulfinyl, fipronil sulfide, and fipronil sulfone showed lower cross-reactivity, and other pesticides were not recognized. To achieve high-frequency and on-site measurements of FIP, an evanescent wave fluorescence biosensor was built by integrating evanescent wave fluorescence technology, a functionalized fiber bioprobe, and a fluorescence-labeled F-3F6 antibody. The detection limit of FIP was 0.032 μg/L. The detection results of real milk and water samples showed that all the coefficients of variation were less than 10%, and the recovery ranged from 90 to 120%. The high reusability and stability of functionalized fiber bioprobe enables the accurate, cost-effective, high-frequency, and facile quantitative detection of FIP. This highly specific and reliable evanescent wave fluorescence biosensor will be well suited to the sensitive and high-frequency on-site analysis of only FIP in food.
Spectroscopy, a Tool for the Non-Destructive Sensory Analysis of Plant-Based Foods and Beverages: A Comprehensive Review
Authors: Basile Teodora , Mallardi Domenica , Cardone Maria Francesca
Published: December 2023

In recent years, there has been a significant rise in the popularity of plant-based products due to various reasons, such as ethical concerns, environmental sustainability, and health benefits. Sensory analysis is a powerful tool for evaluating the human appreciation of food and drink products. To link the sensory evaluation to the chemical and textural compositions, further quantitative analyses are required. Unfortunately, due to the destructive nature of sensory analysis techniques, quantitative evaluation can only be performed on samples that are different from those ingested. The quantitative knowledge of the analytical parameters of the exact sample ingested would be far more informative. Coupling non-destructive techniques, such as near-infrared (NIR) and hyperspectral imaging (HSI) spectroscopy, to sensory evaluation presents several advantages. The intact sample can be analyzed before ingestion, providing in a short amount of time matrices of quantitative data of several parameters at once. In this review, NIR and imaging-based techniques coupled with chemometrics based on artificial intelligence and machine learning for sensory evaluation are documented. To date, no review article covering the application of these non-destructive techniques to sensory analysis following a reproducible protocol has been published. This paper provides an objective and comprehensive overview of the current applications of spectroscopic and sensory analyses based on the state-of-the-art literature from 2000 to 2023.
Prophylaxis of Patent Ductus Arteriosus with Paracetamol in Extremely Low Gestational Age Newborns (ELGANs): A Single-Institution Observational Study in Vietnam
Authors: Nguyen Tinh Thu , Nguyen Dung Thi Ngoc , Pham Tam Thi Thanh , Oei Ju-Lee
Published: December 2023

Introduction: Prophylactic paracetamol for extremely low gestation age neonates (ELGAN, <27 weeks’ gestation) with symptomatic patent ductus arteriosus (sPDA) in high-income countries (HIC) reduces medical and surgical interventions. Its effectiveness in low-to-middle-income countries (LMIC) remains uncertain. This study assesses prophylactic paracetamol’s impact on sPDA interventions in ELGANs in an LMIC. Methods: This is a retrospective cohort study that compared a historical cohort of ELGANs that were treated with oral ibuprofen or intravenous paracetamol after diagnosis of sPDA (n = 104) with infants (n = 76) treated with prophylactic paracetamol (20 mg/kg loading, 7.5 mg/kg qid for 4 days), in a tertiary neonatal intensive care unit (NICU) in Vietnam. Oral ibuprofen or intravenous therapeutic paracetamol were administered if prophylactic paracetamol failed to close sPDA. Surgical ligation was conducted if targeted medical intervention failed, or the infant deteriorated from conditions attributable to sPDA. Results: In the historical cohort, 57 (55%) infants died within 7 days of life compared to 18 (24%) from the prophylactic cohort (p < 0.01). Of the survivors, 21 (45%) of the historical and 23 (39.7%) of the prophylactic cohort required surgical ligation (p = 0.6). Duration of hospitalization for survivors was lower in the prophylactic cohort (mean 74 vs. 97 days, p = 0.01). In the prophylactic cohort, 24 (41%) infants did not need further treatment while 34 (59%) required further treatment including ibuprofen and/or paracetamol 28 (48%) and surgical ligation 22 (38%). Conclusions: Prophylactic paracetamol for ELGAN in LMIC does not reduce the need for surgical ligation, sPDA rates, and other PDA-related morbidities in infants who survive beyond 7 days of age. It may reduce the risk of death and the duration of hospitalization but further study into the reasons behind this need to be determined with larger studies.
Clinical Significance of SOX10 Expression in Human Pathology
Authors: Bahmad Hisham F. , Thiravialingam Aran , Sriganeshan Karthik , Gonzalez Jeffrey , Alvarez Veronica , Ocejo Stephanie , Abreu Alvaro R. , Avellan Rima , Arzola Alejandro H. , Hachem Sana , Poppiti Robert
Published: December 2023

The embryonic development of neural crest cells and subsequent tissue differentiation are intricately regulated by specific transcription factors. Among these, SOX10, a member of the SOX gene family, stands out. Located on chromosome 22q13, the SOX10 gene encodes a transcription factor crucial for the differentiation, migration, and maintenance of tissues derived from neural crest cells. It plays a pivotal role in developing various tissues, including the central and peripheral nervous systems, melanocytes, chondrocytes, and odontoblasts. Mutations in SOX10 have been associated with congenital disorders such as Waardenburg–Shah Syndrome, PCWH syndrome, and Kallman syndrome, underscoring its clinical significance. Furthermore, SOX10 is implicated in neural and neuroectodermal tumors, such as melanoma, malignant peripheral nerve sheath tumors (MPNSTs), and schwannomas, influencing processes like proliferation, migration, and differentiation. In mesenchymal tumors, SOX10 expression serves as a valuable marker for distinguishing between different tumor types. Additionally, SOX10 has been identified in various epithelial neoplasms, including breast, ovarian, salivary gland, nasopharyngeal, and bladder cancers, presenting itself as a potential diagnostic and prognostic marker. However, despite these associations, further research is imperative to elucidate its precise role in these malignancies.
Expression of Human L-Dopa Decarboxylase (DDC) under Conditions of Oxidative Stress
Authors: Lotsios Nikolaos S. , Arvanitis Nikolaos , Charonitakis Alexandros G. , Mpekoulis George , Frakolaki Efseveia , Vassilaki Niki , Sideris Diamantis C. , Vassilacopoulou Dido
Published: December 2023

Oxidative stress is known to influence mRNA levels, translation, and proteolysis. The importance of oxidative stress has been demonstrated in several human diseases, including neurodegenerative disorders. L-Dopa decarboxylase (DDC) is the enzyme that converts L-Dopa to dopamine (DA). In spite of a large number of studies, little is known about the biological significance of the enzyme under physiological and pathological conditions. Here, we investigated the relationship between DDC expression and oxidative stress in human neural and non-neural cells. Oxidative stress was induced by treatment with H2O2. Our data indicated that mRNA and protein expression of DDC was enhanced or remained stable under conditions of ROS induction, despite degradation of total RNA and increased cytotoxicity and apoptosis. Moreover, DDC silencing caused an increase in the H2O2-induced cytotoxicity. The current study suggests that DDC is involved in the mechanisms of oxidative stress.
Hydrogen Attenuates Chronic Intermittent Hypoxia-Induced Cardiac Hypertrophy by Regulating Iron Metabolism
Authors: Song Jixian , Chen Qi , Xu Shan , Gou Yujing , Guo Yajing , Jia Cuiling , Zhao Chenbing , Zhang Zhi , Li Boliang , Zhao Yashuo , Ji Ensheng
Published: December 2023

The present study aimed to investigate the impact of hydrogen (H2) on chronic intermittent hypoxia (CIH)-induced cardiac hypertrophy in mice by modulating iron metabolism. C57BL/6N mice were randomly allocated into four groups: control (Con), CIH, CIH + H2, and H2. The mice were exposed to CIH (21–5% FiO2, 3 min/cycle, 8 h/d), and received inhalation of a hydrogen–oxygen mixture (2 h/d) for 5 weeks. Cardiac and mitochondrial function, levels of reactive oxygen species (ROS), and iron levels were evaluated. The H9C2 cell line was subjected to intermittent hypoxia (IH) and treated with H2. Firstly, we found H2 had a notable impact on cardiac hypertrophy, ameliorated pathological alterations and mitochondrial morphology induced by CIH (p < 0.05). Secondly, H2 exhibited a suppressive effect on oxidative injury by decreasing levels of inducible nitric oxide synthase (i-NOS) (p < 0.05) and 4-hydroxynonenal (4-HNE) (p < 0.01). Thirdly, H2 demonstrated a significant reduction in iron levels within myocardial cells through the upregulation of ferroportin 1 (FPN1) proteins (p < 0.01) and the downregulation of transferrin receptor 1 (TfR1), divalent metal transporter 1 with iron-responsive element (DMT1(+ire)), and ferritin light chain (FTL) mRNA or proteins (p < 0.05). Simultaneously, H2 exhibited the ability to decrease the levels of Fe2+ and ROS in H9C2 cells exposed to IH (p < 0.05). Moreover, H2 mediated the expression of hepcidin, hypoxia-inducible factor-1α (HIF-1α) (p < 0.01), and iron regulatory proteins (IRPs), which might be involved in the regulation of iron-related transporter proteins. These results suggested that H2 may be beneficial in preventing cardiac hypertrophy, a condition associated with reduced iron toxicity.
Examining the Heat Health Burden in Australia: A Rapid Review
Authors: Bhatta Manoj , Field Emma , Cass Max , Zander Kerstin , Guthridge Steven , Brearley Matt , Hines Sonia , Pereira Gavin , Nur Darfiana , Chang Anne , Singh Gurmeet , Trueck Stefan , Truong Chi , Wakerman John , Mathew Supriya
Published: December 2023

Extreme heat has been linked to increased mortality and morbidity across the globe. Increasing temperatures due to climatic change will place immense stress on healthcare systems. This review synthesises Australian literature that has examined the effect of hot weather and heatwaves on various health outcomes. Databases including Web of Science, PubMed and CINAHL were systematically searched for articles that quantitatively examined heat health effects for the Australian population. Relevant, peer-reviewed articles published between 2010 and 2023 were included. Two authors screened the abstracts. One researcher conducted the full article review and data extraction, while another researcher randomly reviewed 10% of the articles to validate decisions. Our rapid review found abundant literature indicating increased mortality and morbidity risks due to extreme temperature exposures. The effect of heat on mortality was found to be mostly immediate, with peaks in the risk of death observed on the day of exposure or the next day. Most studies in this review were concentrated on cities and mainly included health outcome data from temperate and subtropical climate zones. There was a dearth of studies that focused on tropical or arid climates and at-risk populations, including children, pregnant women, Indigenous people and rural and remote residents. The review highlights the need for more context-specific studies targeting vulnerable population groups, particularly residents of rural and remote Australia, as these regions substantially vary climatically and socio-demographically from urban Australia, and the heat health impacts are likely to be even more substantial.
Integrative Lighting Aimed at Patients with Psychiatric and Neurological Disorders
Authors: Zeng Xinxi , Soreze Thierry Silvio Claude , Ballegaard Martin , Petersen Paul Michael
Published: December 2023

The purpose of this paper is to investigate the impact of circadian lighting-induced melatonin suppression on patients with psychiatric and neurological disorders in hospital wards by using an ad-hoc metrology framework and the subsequent metrics formalized by the CIE in 2018. A measurement scheme was conducted in hospital ward rooms in the Department of Neurology, Zealand University Hospital, at Roskilde in Denmark, to evaluate the photometric and colorimetric characteristics of the lighting system, as well as its influence on the circadian rhythm of the occupants. The measurement scheme included point measurements and data logging, using a spectrophotometer mounted on a tripod with adjustable height to assess the newly installed circadian lighting system. The measured spectra were uploaded to the Luox platform to calculate illuminance, CCT, MEDI, etc., in accordance with the CIE S026 standard. Furthermore, the MLIT based on MEDI data logging results was calculated. In addition to CIE S026, we have investigated the usefulness of melatonin suppression models for the assessment of circadian performance regarding measured light. From the results, the lighting conditions in the patient room for both minimal and abundant daylight access were evaluated and compared; we found that access to daylight is essential for both illumination and circadian entrainment. It can be concluded that the measurement scheme, together with the use of the Luox platform and Canva template, is suitable for the accurate and satisfactory measurement of integrative lighting that aligns with CIE requirements and recommendations.
One-to-Many Simultaneous Secure Quantum Information Transmission
Authors: Andronikos Theodore , Sirokofskich Alla
Published: December 2023

This paper presents a new quantum protocol designed to transmit information from one source to many recipients simultaneously. The proposed protocol, which is based on the phenomenon of entanglement, is completely distributed and is provably information-theoretically secure. Numerous existing quantum protocols guarantee secure information communication between two parties but are not amenable to generalization in situations where the source must transmit information to two or more recipients. Hence, they must be executed sequentially two or more times to achieve the desired goal. The main novelty of the new protocol is its extensibility and generality to situations involving one party that must simultaneously communicate different, in general, messages to an arbitrary number of spatially distributed parties. This is achieved in the special way employed to encode the transmitted information in the entangled state of the system, one of the distinguishing features compared with previous protocols. This protocol can prove expedient whenever an information broker, say, Alice, must communicate distinct secret messages to her agents, all in different geographical locations, in one go. Due to its relative complexity compared with similar cryptographic protocols, as it involves communication among n parties and relies on |GHZn⟩ tuples, we provide an extensive and detailed security analysis so as to prove that it is information-theoretically secure. Finally, in terms of its implementation, the prevalent characteristics of the proposed protocol are its uniformity and simplicity, because it only requires CNOT and Hadamard gates and the local quantum circuits are identical for all information recipients.
Correction: López-Fuerte et al. Floristics and Biogeographical Affinity of Diatoms Attached to Sargassum fluitans (Børgesen) Børgesen and Sargassum natans (Linnaeus) Gaillon Arriving on Mexico’s Caribbean Coasts. Diversity 2022, 14, 758
Authors: López-Fuerte Francisco Omar , Siqueiros Beltrones David Alfaro , Martínez Yuriko Jocselin , Altamirano-Cerecedo María del Carmen
Published: December 2023

The authors would like to make the following corrections to the published paper [...]
Fractional Laplacian Spinning Particle in External Electromagnetic Field
Authors: Porto Claudio Maia , Godinho Cresus Fonseca de Lima , Vancea Ion Vasile
Published: December 2023

We construct a fractional Laplacian spinning particle model in an external electromagnetic field that generalizes a standard relativistic spinning particle model without anti-commuting spin variables. The one-dimensional fractional Laplacian in world-line variable λ governs the kinetic energy that is non-local in λ. The interaction between the particle’s charge and the electromagnetic four-potential is non-local in λ, while the interaction between the particle’s spin tensor and the electromagnetic field is standard. By applying the variational principle, we obtain the equations of motion for particle coordinates. We solve analytically the equations of motion in two particular cases: the constant electric and magnetic field. For more complex field configurations, the equations are, in general, non-local and non-linear. By making the assumption of a much weaker interaction term between the charge and four-potential compared with the interaction between spinning degrees of freedom and the electromagnetic field, we obtain approximate analytical solutions in the case of a quadratic electromagnetic potential.
School Reform: New Future-Ready Quality Outcomes and Proposed Measures
Authors: Ng David , Ku Daryl
Published: December 2023

As we increasingly emphasise the importance of developing future-ready outcomes for learners, we will need to also expand new capabilities to measure such outcomes. AI, big data, and analytics are examples of such new capabilities. Ideation is one of six habits of practice we have identified that will prepare students for the future. In this paper, we present a means to computationally appraise ideation quality as one such capability. We have developed a heuristic to appraise the ideation quality of university student essays using natural language processing, a branch of artificial intelligence concerned with the understanding of human languages. Our heuristic allows for ideation quality to be quickly quantified in the form of an ideation score. So, instead of going about the process blindly, we now have a means to provide a point of reference to allow students to give measured consideration to their ideation. Unlike a learning outcome, a future-ready habit is more of a predisposition. Consequently, it is not coherent with conventional assessments, which rather seek to evaluate than to guide. This heuristic represents an outcome of our evaluation of a new problem space in education and is, at the same time, a novel expansion into a space that exploits new capabilities.
Enhancing Outdoor Moving Target Detection: Integrating Classical DSP with mmWave FMCW Radars in Dynamic Environments
Authors: Chowdhury Debjyoti , Melige Nikhitha Vikram , Pal Biplab , Gangopadhyay Aryya
Published: December 2023

This paper introduces a computationally inexpensive technique for moving target detection in challenging outdoor environments using millimeter-wave (mmWave) frequency-modulated continuous-wave (FMCW) radars leveraging traditional signal processing methodologies. Conventional learning-based techniques for moving target detection suffer when there are variations in environmental conditions. Hence, the work described here leverages robust digital signal processing (DSP) methods, including wavelet transform, FIR filtering, and peak detection, to efficiently address variations in reflective data. The evaluation of this method is conducted in an outdoor environment, which includes obstructions like woods and trees, producing an accuracy score of 92.0% and precision of 91.5%. Notably, this approach outperforms deep learning methods when it comes to operating in changing environments that project extreme data variations.
Indoor Localization Based on Integration of Wi-Fi with Geomagnetic and Light Sensors on an Android Device Using a DFF Network
Authors: Sun Chao , Zhou Junhao , Jang Kyongseok , Kim Youngok
Published: December 2023

Sensor-related indoor localization has attracted considerable attention in recent years. The accuracy of conventional fingerprint solutions based on a single sensor, such as a Wi-Fi sensor, is affected by multipath interferences from other electronic devices that are produced as a result of complex indoor environments. Light sensors and magnetic (i.e., geomagnetic) field sensors can be used to enhance the accuracy of a system since they are less vulnerable to disturbances. In this paper, we propose a deep feedforward (DFF)-neural-network-based method, termed DFF-WGL, which integrates the data from the embedded Wi-Fi sensor, geomagnetic field sensor, and light sensor (WGL) in a smart device to localize the device in an indoor environment. DFF-WGL does not require complex and expensive auxiliary equipment, except for basic fluorescent lamps and low-density Wi-Fi signal coverage, conditions that are easily satisfied in modern offices or educational buildings. The proposed system was implemented on a commercial off-the-shelf android device, and performance was evaluated through an experimental analysis conducted in two different indoor testbeds, one measuring 60.5 m2 and the other measuring 38 m2, with 242 and 60 reference points, respectively. The results indicate that the model prediction with an input consisting of the combination of light, a magnetic field sensor, and two Wi-Fi RSS signals achieved mean localization errors of 0.01 m and 0.04 m in the two testbeds, respectively, compared with any subset of combination of sensors, verifying the effectiveness of the proposed DFF-WGL method.
Multi-Wavelength Path Loss Model for Indoor VLC with Mobile Human Blockage
Authors: Yin Yue , Tang Pan , Zhang Jianhua , Hu Zheng , Xia Liang , Liu Guangyi
Published: December 2023

Visible light communication (VLC) is one of the candidate technologies for the sixth generation (6G) networks. The path loss model is particularly important for link budget estimation and network planning in VLC. Due to the wideband nature and the extremely poor diffraction capacity of light, the path loss of the VLC channel is susceptible to wavelength dependence and blockage effect. In this paper, we propose a novel path loss model which can characterize the impact of wavelength dependence combined with mobile human blockage for both the single-LED (light emitting diode) and the multi-LED scenario. When there is no blockage in the channel, the multi-wavelength path loss under free space propagation is modeled with a small standard deviation of 0.262 in the single-LED scenario and a small root mean square error of 0.009 in the multi-LED scenario which indicates the high accuracy of the model. When considering the mobile human blockage, the blockage probability (BP) is modeled with full consideration of realistic human mobility and human body shadowing. The results indicate that the BP in single-LED scenario can reach 0.08, while the BP in multi-LED scenario is 0.022. This demonstrates that the distributed deployment of transmitters can effectively reduce the occurrence of the blockage state in VLC.
Introducing the UWF-ZeekDataFall22 Dataset to Classify Attack Tactics from Zeek Conn Logs Using Spark’s Machine Learning in a Big Data Framework
Authors: Bagui Sikha S. , Mink Dustin , Bagui Subhash C. , Madhyala Pooja , Uppal Neha , McElroy Tom , Plenkers Russell , Elam Marshall , Prayaga Swathi
Published: December 2023

This study introduces UWF-ZeekDataFall22, a newly created dataset labeled using the MITRE ATT&CK framework. Although the focus of this research is on classifying the never-before classified resource development tactic, the reconnaissance and discovery tactics were also classified. The results were also compared to a similarly created dataset, UWF-ZeekData22, created in 2022. Both of these datasets, UWF-ZeekDataFall22 and UWF-ZeekData22, created using Zeek Conn logs, were stored in a Big Data Framework, Hadoop. For machine learning classification, Apache Spark was used in the Big Data Framework. To summarize, the uniqueness of this work is its focus on classifying attack tactics. For UWF-ZeekdataFall22, the binary as well as the multinomial classifier results were compared, and overall, the results of the binary classifier were better than the multinomial classifier. In the binary classification, the tree-based classifiers performed better than the other classifiers, although the decision tree and random forest algorithms performed almost equally well in the multinomial classification too. Taking training time into consideration, decision trees can be considered the most efficient classifier.
Life Cycle Analysis of a Photovoltaic Power Plant Using the CED Method
Authors: Leda Patryk , Kruszelnicka Weronika , Leda Anna , Piasecka Izabela , Kłos Zbigniew , Tomporowski Andrzej , Flizikowski Józef , Opielak Marek
Published: December 2023

There is a significant demand for materials and energy throughout the manufacturing and construction of a solar power plant’s component parts. Electricity and fossil fuels are used in enormous quantities during the industrial processes in the photovoltaic power plant’s life cycle. It is then necessary to assess the energy needs, especially during production processes, to improve the efficiency of energy usage and management of natural resources from the global perspective. This will lead to a decrease in natural resource consumption and electricity demand. The main aim of this study was to assess the energy demand in the life cycle of the photovoltaic power plant and identify the most energy-intensive stages and components of this type of installation throughout its life cycle. The study of energy consumption in the whole life cycle was conducted for a 2 MW photovoltaic power plant situated in the northern region of Poland using the Life Cycle Assessment (LCA) methodology, particularly the Cumulative Energy Demand (CED) method. Two post-consumer management scenarios were investigated: recycling and landfilling. It was found that the life cycle of PV panels and the inverter station had the largest energy demand among all the components. This study revealed that, compared to recycling, the life cycle involving post-consumer management in the form of landfilling had a higher total energy demand of 4.09 × 107 MJ. The results of this investigation validate the benefits of recycling. Thus, recycling ought to be commonplace to improve the environment.
Numerical Methods to Evaluate Hyperelastic Transducers: Hexagonal Distributed Embedded Energy Converters
Authors: Niffenegger James Salvador , Boren Blake
Published: December 2023

Hexagonal distributed embedded energy converters, also known as hexDEECs, are centimeter-scale energy transducers that leverage variable capacitance to generate electricity when their hyperelastic structure is dynamically deformed. To better understand, characterize, and optimize hexDEEC designs, a series of numerical methods and techniques were developed to model the hyperelastic mechanics of hexDEECs, electrostatic properties, and electricity generation characteristics. The numerical methods developed for the hyperelastic structural analysis were corroborated by empirical results from another study, and the models and equations for capacitance, electrostatic forces, and electrical potential energy were derived from fundamental electrostatic equations. These methods and techniques were implemented within the STAR-CCM+ multiphysics software Version 2020.3 (15.06.008) environment. Results from this analysis revealed methodologies and techniques necessary to model the energy converters, which will enable future exploration and optimization of more specific designs and corresponding applications.
Distributed Integral Convex Optimization-Based Current Control for Power Loss Optimization in Direct Current Microgrids
Authors: Jiang Yajie , Cheng Siyuan , Wang Haoze
Published: December 2023

Due to the advantages of fewer energy conversion stages and a simple structure, direct current (DC) microgrids are being increasingly studied and applied. To minimize distribution loss in DC microgrids, a systematic optimal control framework is proposed in this paper. By considering conduction loss, switching loss, reverse recovery loss, and ohmic loss, the general loss model of a DC microgrid is formulated as a multi-variable convex function. To solve the objective function, a top-layer distributed integral convex optimization algorithm (DICOA) is designed to optimize the current-sharing coefficients by exchanging the gradients of loss functions. Then, the injection currents of distributed energy resources (DERs) are allocated by the distributed adaptive control in the secondary control layer and local voltage–current control in the primary layer. Based on the DICOA, a three-layer control strategy is constructed to achieve loss minimization. By adopting a peer-to-peer data-exchange strategy, the robustness and scalability of the proposed systematic control are enhanced. Finally, the proposed distribution current dispatch control is implemented and verified by simulations and experimental results under different operating scenarios, including power limitation, communication failure, and plug-in-and-out of DERs.
Numerical Modeling of Two-Phase Flow inside a Wet Flue Gas Absorber Sump
Authors: Vovk Nejc , Ravnik Jure
Published: December 2023

A numerical model of a flue gas scrubber sump is developed with the aim of enabling optimization of the design of the sump in order to reduce energy consumption. In this model, the multiphase flow of the continuous phase, i.e., water, and the dispersed phase, i.e., air bubbles, is considered. The air that is blown in front of the agitators, as well as the influence of the flow field of the agitators on the distribution of the dispersed phase and the recirculation pumps as outlet, is modeled. The bubble Sauter mean diameter is modeled using the population balance model. The model is used to analyze operating parameters such as the bubble retention time, the average air volume fraction, bubble Sauter mean diameter, the local distribution of the bubble size and the amount of air escaping from the pump outlets at two operating points. The purpose of the model is to simulate the two-phase flow in the sump of the flue gas scrubber using air dispersion technology with a combination of spargers and agitators, which, when optimized, reduces energy consumption by 33%. The results show that the homogeneity of air is lower in the bottom part of the absorber sump and that the amount of air escaping through recirculation pipes equals 1.2% of the total air blown into the absorber sump. The escaping air consists mainly of bubbles smaller than 6 mm. Additional operating point results show that halving the magnitude of the linear momentum source lowers the air retention, as well as the average homogeneity of the dispersed air.
Analysis of the Influence Factors of the Crude Oil Temperature Maintenance System of Solar Sewage Heat Pumps in Cold Regions
Authors: Zhu Shangwen , Gu Xiaohua , Duan Mengyi , Yu Feiyang , Zhao Danyi , Liu Siwen , Liu Yan
Published: December 2023

Traditional crude oil heating methods that use fossil fuels or electricity have the disadvantages of high consumption of nonrenewable resources, low energy utilization, and high carbon emissions. Therefore, it is urgent to develop green and sustainable crude oil heating technologies. In this paper, a solar synergistic sewage heat pump (SSHS) dual heat source crude oil temperature maintenance system is proposed. The system utilizes clean and sustainable solar energy to heat crude oil while combining sensible heat storage technology and the waste heat utilization technology of a sewage source heat pump to solve the unstable fluctuation of the solar heating problem. A simulation and analysis model is established to analyze the influencing factors of the SSHS, and the optimal operation scheme is provided. The results show that the efficiency of the solar collector decreases and the proportion of crude oil heating increases with an increase in the solar energy guarantee rate, while the unit flow rate of the pump has a large impact on the performance of the sewage source heat pump. In order to avoid energy waste, it is more appropriate to adopt a 30% guarantee rate and an A3 pump unit flow rate, under which the solar collector efficiency is 50.18%, the proportion of solar heating of crude oil is 47.16%, the average temperature of crude oil is 42.59 °C, and the COP of the sewage source heat pump is 4.65. Further increases in the COP of the wastewater source heat pump can be realized by increasing the temperature of the wastewater supply. The results of this study provide a valuable reference for the optimization of crude oil storage heating systems.
Analyzing Cultural Routes and Their Role in Advancing Cultural Heritage Management within Tourism: A Systematic Review with a Focus on the Integration of Digital Technologies
Authors: Iakovaki Eleftheria , Konstantakis Markos , Teneketzis Alexandros , Konstantakis George
Published: December 2023

This review constitutes a comprehensive systematic review analyzing cultural routes, with a particular focus on the concept of the cultural route as a tourist–cultural product. Within this framework, the paper offers an overview of contemporary technological challenges, concerns, and limitations. It thoroughly explores cutting-edge technologies pertaining to the promotion of cultural heritage, both in general and in the specific context of realizing the concept of the cultural route, a tourist–cultural service enriched by the utilization of new media. Additionally, it extensively references the latest techniques and models for enhancing the user experience of digital cultural tourism products. Moreover, the paper showcases existing digital platforms and tools that encapsulate and emphasize the notion of cultural tourism. It assesses the respective methodologies, technologies, and techniques employed in each case, accompanied by illustrative instances of their applications. Finally, an empirical evaluation was conducted focusing on user needs and expectations during a cultural route.
Understanding the Mental Health of Doctoral Students
Authors: Casey Chloe , Taylor Julia , Knight Fiona , Trenoweth Steven
Published: December 2023

Doctoral degrees include Doctor of Philosophy (PhD) and other professional doctorates such as Engineering Doctorate (EngD), Doctor of Education (EdD) or Doctor of Clinical Psychology (DClinPsy). Unlike undergraduate or postgraduate taught students, doctoral students focus upon a single, autonomous piece of research. Research indicates a high occurrence of mental health problems, mental distress, and symptoms of anxiety or depression in doctoral students. Additionally, there is concern that they may be less likely to disclose existing mental health problems or access support services than undergraduate or postgraduate taught students. This entry explores the known factors that contribute to the mental health of doctoral students studying in the United Kingdom.