bluuebunny/crossref_metadata_2025 huggingface dataset:
Real Estate Development Feasibility and Hurdle Rate Selection
Authors: Moorhead Matthew , Armitage Lynne , Skitmore Martin
Published: April 2024

Real estate developers typically assess potential projects using feasibility analyses and industry-standard heuristics, which include capital costs, return on costs, and a subjective risk measure. This study explores real estate developers’ decision-making practices in selecting hurdle rates and common feasibility analysis techniques, surveying 225 Australian and New Zealand developers. The main findings are that most developers use specific ‘go/no-go’ hurdle rate mechanisms irrespective of primary real estate type, with the majority using margin on development cost (MDC) or internal rate of return (IRR); the boundaries between traditional speculative development and real estate investment through the use of securitization methods have become blurred; many developers use both quantitative metrics, with qualitative methods and specific structural checks to manage the risks involved; and the two most frequent methods of determining site value prior to acquisition are the residual land value and discounted cash flow methods. Most place a heavy reliance on industry-accepted heuristics and do not have a predetermined process and method for altering or adapting the chosen hurdle rates and benchmarks. This research provides a contribution to property development practice from the Antipodean perspective which until now has been more focused on the UK view, enabling more generalized application internationally.
Research on Pathology Information Management of Educational Architectural Heritage Based on Digital Technology: The Case of James Jackson Gymnasium
Authors: Wang Hechi , He Xinyi , Yan Zhaoyi , Lei Siyu , Luo Shengzhong , Lei Jingjing , Zhou Qi
Published: April 2024

Rapid advances in technology have led to an increasing demand for this type of information in the field of cultural heritage and architectural conservation. The article aims to use digital technology to obtain, record, store, and display accurate and intuitive information about architectural heritage for daily management and repair of that heritage. This article conducts a comprehensive and in-depth study of the pathology information from the James Jackson Gymnasium, a typical case of the modern educational architectural heritage of Wuhan. Research contents include obtaining point cloud data through 3D scanning, constructing Building Information Modeling (BIM) 3D models and pathological information models to visualize the affected parts, using the Monument Damage Diagnostic System (MDDS) to establish a pathological information map management system, using virtual simulation technology and digital repair technology to diagnose and repair the affected parts, and establishing a systematic architectural pathology information database to explore the causes of architectural pathology from a multidisciplinary perspective. The authors aim to gradually promote this method and build a systematic pathological information database of architectural heritage. This utilizes the sharing characteristics of information technology to transcend the barriers of time and space and provide important support for heritage protection and pathology management. The Architectural Pathology Information Management System is proposed as an innovative solution to promote the sustainable conservation of architectural heritage through digital technology.
Emerging Therapies in Kirsten Rat Sarcoma Virus (+) Non-Small-Cell Lung Cancer
Authors: Karachaliou Anastasia , Kotteas Elias , Fiste Oraianthi , Syrigos Konstantinos
Published: April 2024

Kirsten rat sarcoma virus (KRAS) is the most frequently found oncogene in human cancers, including non-small-cell lung cancer (NSCLC). For many years, KRAS was considered “undruggable” due to its structure and difficult targeting. However, the discovery of the switch II region in the KRAS-G12C-mutated protein has changed the therapeutic landscape with the design and development of novel direct KRAS-G12C inhibitors. Sotorasib and adagrasib are FDA-approved targeted agents for pre-treated patients with KRAS-G12C-mutated NSCLC. Despite promising results, the efficacy of these novel inhibitors is limited by mechanisms of resistance. Ongoing studies are evaluating combination strategies for overcoming resistance. In this review, we summarize the biology of the KRAS protein and the characteristics of KRAS mutations. We then present current and emerging therapeutic approaches for targeting KRAS mutation subtypes intending to provide individualized treatment for lung cancer harboring this challenging driver mutation.
Chromatin Profiles Are Prognostic of Clinical Response to Bortezomib-Containing Chemotherapy in Pediatric Acute Myeloid Leukemia: Results from the COG AAML1031 Trial
Authors: van Dijk Anneke D. , Hoff Fieke W. , Qiu Yihua , Hubner Stefan E. , Go Robin L. , Ruvolo Vivian R. , Leonti Amanda R. , Gerbing Robert B. , Gamis Alan S. , Aplenc Richard , Kolb Edward A. , Alonzo Todd A. , Meshinchi Soheil , de Bont Eveline S. J. M. , Horton Terzah M. , Kornblau Steven M.
Published: April 2024

The addition of the proteasome inhibitor bortezomib to standard chemotherapy did not improve survival in pediatric acute myeloid leukemia (AML) when all patients were analyzed as a group in the Children’s Oncology Group phase 3 trial AAML1031 (NCT01371981). Proteasome inhibition influences the chromatin landscape and proteostasis, and we hypothesized that baseline proteomic analysis of histone- and chromatin-modifying enzymes (HMEs) would identify AML subgroups that benefitted from bortezomib addition. A proteomic profile of 483 patients treated with AAML1031 chemotherapy was generated using a reverse-phase protein array. A relatively high expression of 16 HME was associated with lower EFS and higher 3-year relapse risk after AML standard treatment compared to low expressions (52% vs. 29%, p = 0.005). The high-HME profile correlated with more transposase-accessible chromatin, as demonstrated via ATAC-sequencing, and the bortezomib addition improved the 3-year overall survival compared with standard therapy (62% vs. 75%, p = 0.033). These data suggest that there are pediatric AML populations that respond well to bortezomib-containing chemotherapy.
Anderson–Fabry Disease Homozygosity: Rare Case of Late-Onset Variant
Authors: Dostalova Gabriela , Januska Jaroslav , Veselá Michaela , Reková Petra , Taborska Anna , Pleva Martin , Zemanek David , Linhart Aleš
Published: April 2024

Anderson–Fabry Disease (AFD) is a rare, X-linked lysosomal storage disorder caused by a mutation in the α-Galactosidase A gene resulting in α-Galactosidase A enzyme (α-Gal A) deficiency. The metabolic defect leads to the progressive accumulation of glycosphingolipids and the structural and functional impairment of affected organs. Due to the inheritance pattern, male patients are hemizygous with more severe manifestations of the disease as compared to females who, in most cases, are heterozygous with delayed and variable clinical presentation caused by uneven X-chromosome inactivation. Fabry disease cases are often identified by targeted screening programs in high-risk groups, such as in patients with end-stage renal disease, premature stroke, or unexplained cardiomyopathy. Here, we describe a unique case of a homozygous female patient identified by a nationwide screening program in hypertrophic cardiomyopathy patients. Before the systematic screening, the patient had a diagnosis of hypertrophic obstructive cardiomyopathy and was treated accordingly, including with alcohol septal ablation to reduce the obstructive gradient. The confirmation of Fabry disease led to the discovery of the same variant in several members of her family. The identified variant was c.644A>G, p.Asn215Ser (p.N215S), which is known to cause predominant cardiac involvement with late onset of the disease. This variant is amenable to oral therapy with the small-molecule chaperone migalastat, which was started and then interrupted due to the recurrence of the patient’s migraine and then re-initiated again after two years. During this period, the patient received enzyme replacement therapy with agalsidase beta but developed progressively worsening venous access. Our case illustrates the importance of the systematic screening of patients with clinical evidence of hypertrophic cardiomyopathy in whom the routine diagnostic process fails to discover Fabry disease, in particular variants with late-onset cardiac manifestations. Many of the late-onset variants are amenable to orally active therapy with migalastat, which significantly improves the comfort of the treatment. Its long-term results are being analyzed by a large international “Follow-me” registry, which was designed to verify the validity of pivotal trials with migalastat in Fabry disease.
Potential Roles of Specific Subclasses of Premotor Interneurons in Spinal Cord Function Recovery after Traumatic Spinal Cord Injury in Adults
Authors: Dominguez-Bajo Ana , Clotman Frédéric
Published: April 2024

The differential expression of transcription factors during embryonic development has been selected as the main feature to define the specific subclasses of spinal interneurons. However, recent studies based on single-cell RNA sequencing and transcriptomic experiments suggest that this approach might not be appropriate in the adult spinal cord, where interneurons show overlapping expression profiles, especially in the ventral region. This constitutes a major challenge for the identification and direct targeting of specific populations that could be involved in locomotor recovery after a traumatic spinal cord injury in adults. Current experimental therapies, including electrical stimulation, training, pharmacological treatments, or cell implantation, that have resulted in improvements in locomotor behavior rely on the modulation of the activity and connectivity of interneurons located in the surroundings of the lesion core for the formation of detour circuits. However, very few publications clarify the specific identity of these cells. In this work, we review the studies where premotor interneurons were able to create new intraspinal circuits after different kinds of traumatic spinal cord injury, highlighting the difficulties encountered by researchers, to classify these populations.
Inflammation and Exosomes in Fabry Disease Pathogenesis
Authors: Coelho-Ribeiro Bruna , Silva Helena G. , Sampaio-Marques Belém , Fraga Alexandra G. , Azevedo Olga , Pedrosa Jorge , Ludovico Paula
Published: April 2024

Fabry Disease (FD) is one of the most prevalent lysosomal storage disorders, resulting from mutations in the GLA gene located on the X chromosome. This genetic mutation triggers glo-botriaosylceramide (Gb-3) buildup within lysosomes, ultimately impairing cellular functions. Given the role of lysosomes in immune cell physiology, FD has been suggested to have a profound impact on immunological responses. During the past years, research has been focusing on this topic, and pooled evidence strengthens the hypothesis that Gb-3 accumulation potentiates the production of pro-inflammatory mediators, revealing the existence of an acute inflammatory process in FD that possibly develops to a chronic state due to stimulus persistency. In parallel, extracellular vesicles (EVs) have gained attention due to their function as intercellular communicators. Considering EVs’ capacity to convey cargo from parent to distant cells, they emerge as potential inflammatory intermediaries capable of transporting cytokines and other immunomodulatory molecules. In this review, we revisit the evidence underlying the association between FD and altered immune responses and explore the potential of EVs to function as inflammatory vehicles.
Protecting Orthopaedic Implants from Infection: Antimicrobial Peptide Mel4 Is Non-Toxic to Bone Cells and Reduces Bacterial Colonisation When Bound to Plasma Ion-Implanted 3D-Printed PAEK Polymers
Authors: Kruse Hedi Verena , Chakraborty Sudip , Chen Renxun , Kumar Naresh , Yasir Muhammad , Lewin William T. , Suchowerska Natalka , Willcox Mark D. P. , McKenzie David R.
Published: April 2024

Even with the best infection control protocols in place, the risk of a hospital-acquired infection of the surface of an implanted device remains significant. A bacterial biofilm can form and has the potential to escape the host immune system and develop resistance to conventional antibiotics, ultimately causing the implant to fail, seriously impacting patient well-being. Here, we demonstrate a 4 log reduction in the infection rate by the common pathogen S. aureus of 3D-printed polyaryl ether ketone (PAEK) polymeric surfaces by covalently binding the antimicrobial peptide Mel4 to the surface using plasma immersion ion implantation (PIII) treatment. The surfaces with added texture created by 3D-printed processes such as fused deposition-modelled polyether ether ketone (PEEK) and selective laser-sintered polyether ketone (PEK) can be equally well protected as conventionally manufactured materials. Unbound Mel4 in solution at relevant concentrations is non-cytotoxic to osteoblastic cell line Saos-2. Mel4 in combination with PIII aids Saos-2 cells to attach to the surface, increasing the adhesion by 88% compared to untreated materials without Mel4. A reduction in mineralisation on the Mel4-containing surfaces relative to surfaces without peptide was found, attributed to the acellular portion of mineral deposition.
The Role of Fatty Acid Synthase in the Vascular Smooth Muscle Cell to Foam Cell Transition
Authors: Bogan Bethany J. , Williams Holly C. , Holden Claire M. , Patel Vraj , Joseph Giji , Fierro Christopher , Sepulveda Hugo , Taylor W. Robert , Rezvan Amir , San Martin Alejandra
Published: April 2024

Vascular smooth muscle cells (VSMCs), in their contractile and differentiated state, are fundamental for maintaining vascular function. Upon exposure to cholesterol (CHO), VSMCs undergo dedifferentiation, adopting characteristics of foam cells—lipid-laden, macrophage-like cells pivotal in atherosclerotic plaque formation. CHO uptake by VSMCs leads to two primary pathways: ABCA1-mediated efflux or storage in lipid droplets as cholesterol esters (CEs). CE formation, involving the condensation of free CHO and fatty acids, is catalyzed by sterol O-acyltransferase 1 (SOAT1). The necessary fatty acids are synthesized by the lipogenic enzyme fatty acid synthase (FASN), which we found to be upregulated in atherosclerotic human coronary arteries. This observation led us to hypothesize that FASN-mediated fatty acid biosynthesis is crucial in the transformation of VSMCs into foam cells. Our study reveals that CHO treatment upregulates FASN in human aortic SMCs, concurrent with increased expression of CD68 and upregulation of KLF4, markers associated with the foam cell transition. Crucially, downregulation of FASN inhibits the CHO-induced upregulation of CD68 and KLF4 in VSMCs. Additionally, FASN-deficient VSMCs exhibit hindered lipid accumulation and an impaired transition to the foam cell phenotype following CHO exposure, while the addition of the fatty acid palmitate, the main FASN product, exacerbates this transition. FASN-deficient cells also show decreased SOAT1 expression and elevated ABCA1. Notably, similar effects are observed in KLF4-deficient cells. Our findings demonstrate that FASN plays an essential role in the CHO-induced upregulation of KLF4 and the VSMC to foam cell transition and suggest that targeting FASN could be a novel therapeutic strategy to regulate VSMC phenotypic modulation.
Cell Senescence-Independent Changes of Human Skin Fibroblasts with Age
Authors: Fullard Nicola , Wordsworth James , Welsh Ciaran , Maltman Victoria , Bascom Charlie , Tasseff Ryan , Isfort Robert , Costello Lydia , Scanlan Rebekah-Louise , Przyborski Stefan , Shanley Daryl
Published: April 2024

Skin ageing is defined, in part, by collagen depletion and fragmentation that leads to a loss of mechanical tension. This is currently believed to reflect, in part, the accumulation of senescent cells. We compared the expression of genes and proteins for components of the extracellular matrix (ECM) as well as their regulators and found that in vitro senescent cells produced more matrix metalloproteinases (MMPs) than proliferating cells from adult and neonatal donors. This was consistent with previous reports of senescent cells contributing to increased matrix degradation with age; however, cells from adult donors proved significantly less capable of producing new collagen than neonatal or senescent cells, and they showed significantly lower myofibroblast activation as determined by the marker α-SMA. Functionally, adult cells also showed slower migration than neonatal cells. We concluded that the increased collagen degradation of aged fibroblasts might reflect senescence, the reduced collagen production likely reflects senescence-independent processes.
Electrochemical Sensors, Biosensors, and Optical Sensors for the Detection of Opioids and Their Analogs: Pharmaceutical, Clinical, and Forensic Applications
Authors: Fakayode Sayo O. , Brady Pamela Nicole , Grant Cidya , Fernand Narcisse Vivian , Rosado Flores Peter , Lisse Catrena Higginbothan , Bwambok David K.
Published: April 2024

Pharmaceutical opioids are intravenously or orally administered analgesics. While they are effective in relieving chronic and acute pain, their narrow window of therapeutic use contributes to the high occurrence of abuse. The associated abuse of this family of drugs can be correlated to the increase in dependency, overdose, and death of users. The negative effects of opioids extend beyond the physical and psychological effects experienced by the user to their unregulated synthesis and sale, which contribute to socioeconomic challenges and are a biproduct of this global public health epidemic. From clinical to point-of-care applications, the detection and real-time monitoring of this family of drug is critical in the fight to decrease abuse and improve use in clinical settings. Chromatographic separations and chromatography–mass spectrometry are traditional methods of opioid analyses, but the high cost, long analysis time, and absence of portability highlight the need for the development of fast, in situ, point-of-care analysis, or of community drug monitoring services. This review highlights recent electrochemical and optical (FTIR, Raman, colorimetric, and fluorescent) advances and biosensors for pharmaceutical and illicit opioid analysis. Specifically, an emphasis is placed on the detection of opioids and their metabolites in biological samples and in vitro cellular assays for clinical diagnosis and forensic applications. The challenges and prospects of the role of electrochemical sensors, biosensors, and optical sensors for opioid analysis in promoting clinical diagnosis, forensic study, point-of-care, and community drug monitoring services to reduce harm are also provided.
Egyptian Pediatric Guidelines for the Management of Children with Isolated Thrombocytopenia Using the Adapted ADAPTE Methodology—A Limited-Resource Country Perspective
Authors: Mokhtar Galila , Abdelbaky Ashraf , Adly Amira , Ezzat Dina , Abdel Hakeem Gehan , Hassab Hoda , Youssry Ilham , Ragab Iman , Sherief Laila M. , Zakaria Marwa , Hesham Mervat , Salama Niveen , Salah Nouran , Afifi Rasha A. A. , El-Ashry Rasha , Makkeyah Sara , Adolf Sonia , Amer Yasser S. , Omar Tarek E. I. , Bussel James , Abd El Raouf Eman , Atfy Mervat , Ellaboudy Mohamed , Florez Ivan
Published: April 2024

Background: Thrombocytopenia is a prevalent presentation in childhood with a broad spectrum of etiologies, associated findings, and clinical outcomes. Establishing the cause of thrombocytopenia and its proper management have obvious clinical repercussions but may be challenging. This article provides an adaptation of the high-quality Clinical Practice Guidelines (CPGs) of pediatric thrombocytopenia management to suit Egypt’s health care context. Methods: The Adapted ADAPTE methodology was used to identify the high-quality CPGs published between 2010 and 2020. An expert panel screened, assessed and reviewed the CPGs and formulated the adapted consensus recommendations based on the best available evidence. Discussion: The final CPG document provides consensus recommendations and implementation tools on the management of isolated thrombocytopenia in children and adolescents in Egypt. There is a scarcity of evidence to support recommendations for various management protocols. In general, complete clinical assessment, full blood count, and expert analysis of the peripheral blood smear are indicated at initial diagnosis to confirm a bleeding disorder, exclude secondary causes of thrombocytopenia and choose the type of work up required. The International Society of Hemostasis and thrombosis–Bleeding assessment tool (ISTH-SCC BAT) could be used for initial screening of bleeding manifestations. The diagnosis of immune thrombocytopenic purpura (ITP) is based principally on the exclusion of other causes of isolated thrombocytopenia. Future research should report the outcome of this adapted guideline and include cost-analysis evaluations.
Nur77 Mediates Anaphylaxis by Regulating miR-21a
Authors: Jo Hyein , Jeoung Jaewhoon , Shim Kyeonghee , Jeoung Dooil
Published: April 2024

Nur77 belongs to the NR4A subfamily of orphan nuclear hormone receptors. It has been shown to play important roles in metabolism, cancer progression, cellular differentiation, and the regulation of immune process. However, there has yet to be research reporting on the role of Nur77 in allergic inflammations such as anaphylaxis. This study aimed to identify molecules that could mediate allergic inflammations. To this end, we performed RNA sequencing analysis employing bone marrow-derived mast cells (BMMCs). Antigen (DNP-HSA) stimulation increased the expression levels of transcription factors such as Nr4a3 (NOR1), Nr4a1 (Nur77), and Nr4a2 (Nurr1). We focused our study on Nur77. Antigen stimulation increased the expression of Nur77 in a time- and dose-dependent manner in rat basophilic leukemia cells (RBL2H3). The downregulation of Nur77 prevented both antigen-induced increase in β-hexosaminidase activity as well as hallmarks of allergic reactions such as HDAC3, COX2, and MCP1 in RBL2H3 cells. Nur77 was necessary for both passive cutaneous anaphylaxis (PCA) and passive systemic anaphylaxis (PSA). TargetScan analysis predicted that miR-21a would be a negative regulator of Nur77. miR-21a mimic negatively regulated PCA and PSA by inhibiting the hallmarks of allergic reactions. ChIP assays showed that c-JUN could bind to the promoter sequences of Nur77. Antigen stimulation increased the expression of c-JUN in RBL2H3 cells. Altogether, our findings demonstrate the regulatory role played by Nur77-miR-21a loop in allergic inflammations such as anaphylaxis, making this the first report to present the role played by Nur77 in an allergic inflammation. Our results suggest that Nur77 and miR-21 might serve as targets for developing anti-allergy drugs.
Optimization of Milling Process Parameters for Fe45 Laser-Clad Molded Parts Based on the Nondominated Sorting Genetic Algorithm II
Authors: Zhou Jun , Shu Linsen , Li Anjun , Hu Ning , Gong Jiangtao
Published: April 2024

The milling process parameters of laser-clad molded parts have an essential influence on improving the surface quality of the coating. Generally speaking, optimizing a single property often leads to a reduction in another property. In this paper, we systematically investigated a milling process parameter optimization method for Fe45 laser-clad molded parts, and designed L9 (33) sets of orthogonal experiments by taking the spindle speed, feed rate, and cutting depth as input variables, and taking the milling force and material removal rate as optimization indices. The significance ranking of the milling process was analyzed by using the extreme difference method. Then, the multi-objective optimization of the milling process was realized by using the NSGA-II algorithm with the empirical index model as the objective function. The optimum milling parameters obtained were N = 2000 r/min, V = 120.0266 mm/min, and P = 0.45 mm. Finally, the reliability of the optimization results of the algorithm was proved by comparing and verifying the optimal results obtained from the algorithm with the optimal process obtained from the extreme difference analysis. The results provide a theoretical basis for the selection of milling parameters and parameter optimization of laser fusion-coated Fe45 alloys.
Toward Optimal Virtualization: An Updated Comparative Analysis of Docker and LXD Container Technologies
Authors: Silva Daniel , Rafael João , Fonte Alexandre
Published: April 2024

Traditional hypervisor-assisted virtualization is a leading virtualization technology in data centers, providing cost savings (CapEx and OpEx), high availability, and disaster recovery. However, its inherent overhead may hinder performance and seems not scale or be flexible enough for certain applications, such as microservices, where deploying an application using a virtual machine is a longer and resource-intensive process. Container-based virtualization has received attention, especially with Docker, as an alternative, which also facilitates continuous integration/continuous deployment (CI/CD). Meanwhile, LXD has reactivated the interest in Linux LXC containers, which provides unique operations, including live migration and full OS emulation. A careful analysis of both options is crucial for organizations to decide which best suits their needs. This study revisits key concepts about containers, exposes the advantages and limitations of each container technology, and provides an up-to-date performance comparison between both types of containers (applicational vs. system). Using extensive benchmarks and well-known workload metrics such as CPU scores, disk speed, and network throughput, we assess their performance and quantify their virtualization overhead. Our results show a clear overall trend toward meritorious performance and the maturity of both technologies (Docker and LXD), with low overhead and scalable performance. Notably, LXD shows greater stability with consistent performance variability.
Kidney and Liver Predictors of Adults Hospitalized with COVID-19 Infection
Authors: Boulos Mariana , Sbeit Moeen , Basheer Maamoun , Ben Arie Guy , Mirkin Yuval , Assy Nimer
Published: April 2024

SARS-CoV-2 damages not only the lungs, but also the liver and kidney. Most critically ill COVID-19 patients have liver and kidney dysfunctions. The early identification of patients with COVID-19 who will develop severe or critical disease symptoms is important for delivering proper and early treatment. This research studies the correlation of liver and kidney function indexes and COVID-19 outcomes. Electronic medical record data from 391 patients diagnosed with COVID-19 in the COVID-19 Department, Galilee Medical Center, Nahariya, Israel were collected. Epidemiological, clinical, laboratory, and imaging variables were analyzed. The liver and kidney enzyme indexes were measured upon admission and discharge. A correlation between laboratory levels and severity and mortality of COVID-19 patients was undertaken. This study included 391 COVID-19 patients, 258 mild patients and 133 severe patients. Multivariate stepwise regression analyses and discriminant analyses were used to identify and validate powerful predictors. The main outcome was death or invasive ventilation. Three factors, namely higher urea nitrogen (BUN) and IL-6, and lower albumin levels, were the most powerful predictors of mortality, and classified the results (survival vs. death) correctly in 85% of cases (diagnostic accuracy) with a sensitivity of 88% and a specificity 55%. Compared with mild patients, severe patients had lower albumin (ALB), higher alanine aminotransferase (ALT), aspartate aminotransferase (AST) and BUN (all p < 0.001). COVID-19 patients, especially severe patients, have damage to liver and kidney function. BUN, IL-6 and albumin are factors predicting mortality while fibrinogen and AST could be independent factors for predicting the severity of COVID-19.
The Fossil Record and Diversity of Pycnodontiform Fishes in Non-Marine Environments
Authors: Cawley John J. , Kriwet Jürgen
Published: April 2024

Pycnodont fishes were a successful clade of neopterygian fishes that are predominantly found in shallow marine deposits. However, throughout their long 180 million year reign (Late Triassic–end Eocene), they made multiple incursions into both brackish and freshwater environments. This fossil record mostly consists of fragmentary dental material, but articulated specimens are known from Early Cretaceous lacustrine localities in Spain. This review article aims to document all non-marine occurrences of Pycnodontiformes throughout most of the Mesozoic and early Paleogene. This review highlights two interesting trends in the history of non-marine habitat colonization by pycnodonts: (1) a huge spike in non-marine occurrences during the Cretaceous; and (2) that most occurrences in non-marine localities occurred at the latest Cretaceous period, the Maastrichtian. The high number of colonization events within the Cretaceous lines up with extreme climatic events, such as high temperatures resulting in high sea levels which regularly flooded continental masses, allowing pycnodonts easier access to non-marine habitats. The increased presence of pycnodonts in brackish and freshwater habitats during the Maastrichtian might have played a role in their survival through the K/Pg extinction event. Freshwater habitats are not as vulnerable as marine ecosystems to environmental disturbance as the base of their food chain relies on detritus. Pycnodonts might have used such environments as a refuge and began to occupy marine waters after the K/Pg extinction event.
Characterizing Microheterogeneity in Liquid Mixtures via Local Density Fluctuations
Authors: Lass Michael , Kenter Tobias , Plessl Christian , Brehm Martin
Published: April 2024

We present a novel approach to characterize and quantify microheterogeneity and microphase separation in computer simulations of complex liquid mixtures. Our post-processing method is based on local density fluctuations of the different constituents in sampling spheres of varying size. It can be easily applied to both molecular dynamics (MD) and Monte Carlo (MC) simulations, including periodic boundary conditions. Multidimensional correlation of the density distributions yields a clear picture of the domain formation due to the subtle balance of different interactions. We apply our approach to the example of force field molecular dynamics simulations of imidazolium-based ionic liquids with different side chain lengths at different temperatures, namely 1-ethyl-3-methylimidazolium chloride, 1-hexyl-3-methylimidazolium chloride, and 1-decyl-3-methylimidazolium chloride, which are known to form distinct liquid domains. We put the results into the context of existing microheterogeneity analyses and demonstrate the advantages and sensitivity of our novel method. Furthermore, we show how to estimate the configuration entropy from our analysis, and we investigate voids in the system. The analysis has been implemented into our program package TRAVIS and is thus available as free software.
“They Don’t Really Care”: STEM Doctoral Students’ Unsupportive Interactions with Faculty and Institutions
Authors: Hernandez Theresa Elpidia , Posselt Julie
Published: April 2024

Increasing the representation of racially minoritized groups and women in STEM graduate education is insufficient to make STEM fields and academia inclusive and equitable spaces, where all feel supported and thrive. This study was motivated by a phenomenological examination of support for graduate students, focusing on programs that admitted and graduated higher proportions of underrepresented students than their fields. We used negative case analysis to document the interplay of interpersonal and institutional interactions that define what racially/gender minoritized students experience as unsupportive. Guided by an intersectional interpretation of structuration, we uncovered three mechanisms—withholding support, doing racialized and/or gendered harm, and neglecting to take action when students faced known threats/harm—that underlie the unsupportive experiences faced by graduate students of color and women in STEM doctoral education. This typology of unsupportive mechanisms, alongside an understanding of positive types of support, can help practitioners and scholars rethink what constitutes support, moving toward creating equitable and inclusive graduate education.
Early Parenting Interactions and First-Time Mothers’ Postnatal Depression and Parental Competence
Authors: Leong Rachel W. E. , Gill Davinder , Barlas Joanna , Lin Patrick K. F.
Published: April 2024

Objectives: Schema Therapy, an approach that integrates cognitive-behavioural and attachment principles, helps us understand the impact of early interactions with caregivers on adult mental health. These early interactions can be assessed through Schema Therapy-informed tools; however, these tools have yet to be used with a postnatal population, which represents a period of vulnerability for new mothers. Therefore, the present study aimed to evaluate the impact of positive and negative early parenting interactions on a first-time mother’s mental health and her sense of competence during the postnatal period, using recently revised and newly developed Schema Therapy-informed tools. Design: This is a cross-sectional study. Method: First-time mothers (N = 220) participated in an online survey within 12 months post-birth. Participants completed the Positive Parenting Schema Inventory (PPSI), Young Parenting Inventory—Revised (YPI-R2), Edinburgh Postnatal Depression Scale (EPDS), and Parenting Sense of Competence (PSOC) scale. The data were analysed using hierarchical multiple regression and mediational analysis. Results: Negative early interactions with mothers and fathers led to greater postnatal depressive symptomology, while positive early interactions with mothers led to fewer postnatal depressive symptoms. Mediation analyses revealed that postnatal depressive symptoms mediated early parenting interactions and participants’ sense of parenting competence as a new mother. Conclusions: The protective effects of positive early interactions with caregivers can help first-time mothers’ postnatal emotional adjustment and their sense of competence through diminished postnatal depressive symptoms. However, the enduring effects of negative early interactions with caregivers can contribute to a first-time mother’s risk of developing postnatal depression and negatively affect her sense of parental competence.
Enhancing Magnetic Material Data Analysis with Genetic Algorithm-Optimized Variational Mode Decomposition
Authors: Jin Xinlei , Qian Quan
Published: April 2024

As the application of machine learning technology in predicting and optimizing material performance continues to grow, handling the electromagnetic data of magnetic materials, especially in removing unavoidable data noise and accurately extracting resonance peaks in the imaginary part of electromagnetic information, has become a significant challenge. These steps are crucial for revealing the deep electromagnetic behavior of materials and optimizing their performance. In response to this challenge, this study introduces an innovative approach—Genetic Algorithm-Optimized Variational Mode Decomposition for Signal Enhancement (GAO-VMD-SE). This method, through the Variational Mode Decomposition (VMD) technique optimized by genetic algorithms, not only effectively reduces noise in the data, thereby improving the Signal-to-Noise Ratio (SNR) and reducing the Mean Absolute Error (MAE), but also significantly enhances the hidden resonance peak information in complex permittivity and permeability data to achieve a comprehensive improvement in key performance indicators. Experimental results prove that this method surpasses traditional analysis techniques in key performance metrics such as the peak width ratio, peak overlap ratio, and the number of peaks. Especially in identifying characteristic peaks related to the Snoek limit, GAO-VMD-SE can effectively reveal the peak features hidden in complex data, thus providing important insights for evaluating the performance of materials at specific frequencies. Moreover, the effectiveness of this method in denoising not only enhances the quality and accuracy of material data analysis but also achieves a 1% to 10% enhancement in peak information extraction. This optimized data processing capability and versatility make GAO-VMD-SE not only suitable for evaluating the performance of magnetic materials but also show significant practical application value in processing spectral data and other time series signal data applications.
Adjusting Optical Polarization with Machine Learning for Enhancing Practical Security of Continuous-Variable Quantum Key Distribution
Authors: Zhou Zicheng , Guo Ying
Published: April 2024

An available trick to mitigate the interference of environmental noise in quantum communications is to modulate signals with time-polarization multiplexing. Conversely, due to effects of the atmospheric turbulence in free space, the polarization of signals fluctuates randomly, resulting in feasible information leakage when direct polarization demultiplexing is carried out at the receiver, drowning out the noise-contained signals. For enhancing the practical security of the continuous-variable quantum key distribution (CVQKD), we propose a machine learning (ML) approach for optimization of the dynamic polarization control (DPC) of signals transmitted through atmospheric turbulence. An optimal DPC scheme can be adaptively adjusted with ML algorithms, which is based on the received signals at the receiver for solving the loophole problem of information leakage since it provides an accurate response to the polarization changes regarding the anamorphic signals. The performance of the CVQKD system can be increased in terms of secret key rates and maximal transmission distance as well. Numerical simulation shows the positive effect of the ML-based DPC while taking into account the secret key rate of the CVQKD system. The ML-based DPC effectively reduces the feasibility of information leakage and hence results in an increased secret key rate of the practical CVQKD system.
Research on Wireless Power Transfer Method for Intelligent Sensing Device of Non-Directly Buried Distribution Cables
Authors: He Xinxin , Zhang Zhifeng , Zhou Hao , Xu Mingming , Niu Rongze , Jing Liwei
Published: April 2024

This paper presents a study on the impact of circuit parameters on the transmission of electrical energy in wireless power transfer systems designed for intelligent sensing devices within the urban electric power Internet of Things (IoT). Relying on the essential principles of resonant mutual inductance models, the paper conducts an analytical investigation into the phenomena of power-frequency splitting characteristics, efficiency-frequency splitting characteristics, and efficacy synchronization characteristics within wireless energy transmission technologies. The investigation includes a detailed analysis of a wireless power transfer system model operating at 100 kHz, delineating how varying circuit parameters influence the system’s efficiency. Via the utilization of graphical software and computational programming for simulation modeling, this research delved into the dynamics between key parameters such as equivalent load and coupling coefficient and their influence on distinct splitting phenomena. This rigorous approach substantiated the validity of the proposed power-frequency and efficiency-frequency splitting characteristics outlined in the study. Based on the analytical results, it is shown that selecting an appropriate equivalent load or utilizing impedance matching networks to adjust the equivalent load to a suitable size is crucial in consideration of the system’s output power, voltage withstand level, and transmission efficiency. The research findings provide a theoretical basis for the design of wireless power supply systems for non-directly buried cable front-end sensing devices.
Multivariate Time Series Feature Extraction and Clustering Framework for Multi-Function Radar Work Mode Recognition
Authors: Fan Ruozhou , Zhu Mengtao , Zhang Xiongkui
Published: April 2024

Multi-Function Radars (MFRs) are sophisticated sensors with great agility and flexibility in adapting their transmitted waveform and control parameters. The recognition of MFR work modes based on the intercepted pulse sequences plays an important role in interpreting the functional purpose and threats of a non-cooperative MFRs. However, due to the increased flexibility of MFRs, radar work modes with emerging new modulations and control parameters always appear, and the supervised classification method suffers performance degradation or even failure. Unsupervised learning and clustering of MFR pulse sequences becomes urgent and important. This paper establishes a unified multivariate MFR time series feature extraction and clustering framework for MFR work mode recognition. At first, various features are collected to form the feature set. The feature set includes features extracted through deep learning based on recurrent auto-encoders, multidimensional time series toolkit features, and manually crafted features for radar inter-pulse modulations. Subsequently, several feature selection algorithms, combined with different clustering and classification methods, are used for the selection of an “optimal” feature subset. Finally, the effectiveness and superiority of the proposed framework and selected features are validated through simulated and measured datasets. In the simulated dataset containing 20 classes of work modes, under the most severe non-ideal conditions, we achieve a clustering purity of 73.46% and an NMI of 84.28%. In the measured dataset with seven classes of work modes, we achieve a clustering purity of 86.96% and an NMI of 90.10%.
An Active Distribution Grid Exceedance Testing and Risk-Planning Simulation Based on Carbon Capture and Multisource Data from the Power Internet of Things
Authors: Wu Jinghan , Wang Kun , Wang Tianhao , Ma Shiqian , Gong Hansen , Hu Zhijian , Gong Qingwu
Published: April 2024

In order to achieve peak carbon and carbon neutrality targets, a high number of distributed power sources have been connected to distribution networks. How to realize the planning of a distribution network containing integrated energy under the condition of carbon capture and complete the exceedance test of the distribution network under the condition of accessing a large number of distributed generators has become an urgent problem. To solve the above problem while promoting sustainable development, this work proposes an active distribution network risk-planning model based on multisource data from carbon capture and the Power Internet of Things. The model calculates the semi-invariants of each order of the node state vectors and branch circuit current vectors and then utilizes Gram–Charlier-level expansion to obtain the exceeding probability density function and the probability distribution functions of the node voltages and line powers in the distribution network. Combined with multisource data, an active distribution network with an integrated energy system designed for carbon capture was modeled. According to the risk scenario of the distribution network, the nonconvex constraints in the model were simplified by second-order cone relaxation, and the optimal planning scheme of the distribution network was solved by combining the Gurobi solver with the risk index as the first-level objective and the economic benefit as the second-level objective. The simulation results of a coupled network consisting of a 39-node distribution network and an 11-node transportation network verified the effectiveness of the proposed model.
An Abnormal Account Identification Method by Topology Feature Analysis for Blockchain-Based Transaction Network
Authors: Yue Yuyu , Zhang Jixin , Zhang Mingwu , Yang Jia
Published: April 2024

Cryptocurrency, as one of the most successful applications of blockchain technology, has played a vital role in promoting the development of the digital economy. However, its anonymity, large scale of cryptographic transactions, and decentralization have also brought new challenges in identifying abnormal accounts and preventing abnormal transaction behaviors, such as money laundering, extortion, and market manipulation. Recently, some researchers have proposed efficient and accurate abnormal transaction detection based on machine learning. However, in reality, abnormal accounts and transactions are far less common than normal accounts and transactions, so it is difficult for the previous methods to detect abnormal accounts by training with such an imbalance in abnormal/normal accounts. To address the issues, in this paper, we propose a method for identifying abnormal accounts using topology analysis of cryptographic transactions. We consider the accounts and transactions in the blockchain as graph nodes and edges. Since the abnormal accounts may have special topology features, we extract topology features from the transaction graph. By analyzing the topology features of transactions, we discover that the high-dimensional sparse topology features can be compressed by using the singular value decomposition method for feature dimension reduction. Subsequently, we use the generative adversarial network to generate samples like abnormal accounts, which will be sent to the training dataset to produce an equilibrium of abnormal/normal accounts. Finally, we utilize several machine learning techniques to detect abnormal accounts in the blockchain. Our experimental results demonstrate that our method significantly improves the accuracy and recall rate for detecting abnormal accounts in blockchain compared with the state-of-the-art methods.
Non-Fragile Prescribed Performance Control of Robotic System without Function Approximation
Authors: Zhang Jianjun , Han Pengyang , Wu Zhonghua , Su Bo , Yang Jinxian , Shi Juan
Published: April 2024

In order to address the fragility issues associated with the current prescribed performance control (PPC) strategy and ensure both transient and steady-state performance of the tracking error, a non-fragility prescribed performance control scheme is proposed. A non-fragile prescribed performance control method for robotic systems with model uncertainties and unknown disturbances is developed. This method not only addresses the inherent vulnerability defects of the existing prescribed performance control but also effectively reduces the computational complexity of the controller. Firstly, addressing the fragility issues of existing PPC, a new non-fragile prescribed performance control strategy is proposed. To address the fragile issue with the current PPC, the shift function is employed to handle the tracking error. Based on the non-fragile PPC mentioned above, a new prescribed performance controller is designed without the requirement for approximation or estimation. This effectively reduces the complexity of controller design. At last, the feasibility of achieving non-fragile prescribed performance is verified through stability analysis, and the superiority of the designed controller is confirmed through simulation comparisons. The results show that the designed controller effectively resolves the control singularity issue arising from the inherent limitations of the PPC.