bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structural change in city systems evolution
Authors: Andersson Martin , Johansson Börje , Niedomysl Thomas 
Published: October 2024

AbstractThis paper analyzes city system dynamics, based on a theoretical framework relating interaction potentials to agglomeration economies and density externalities. It employs new historical time series data on population size of cities in Sweden over two centuries (1810–2010) and introduces two schematic growth factors: (i) the intra-city potential and (ii) the extra-city potential located in in rings encircling each city. The first factor is measured by each city’s population size, while the second is a vector of distance-discounted population size for each of a city’s urban rings. In this way, we can explain a city’s growth as a function of its interaction potential inside the city, as well as inside the first, second hand third ring. A robust finding is that cities with large ring potentials follow different development paths than those with small ring potentials. We also find clear evidence of structural change between the two centuries 1810–1910 and 1910–2010. In the first period, city growth is positively impacted by the size of the intra-city potential, whereas the same potential dampens or reduces the growth in the second period. Moreover, the ring potentials outside the city tend to switch from having negative growth stimulation in the first period to having positive stimulation in the second period.
Possible protective effect of natural flavanone naringenin-reduced graphene oxide nanosheets on nonalcoholic fatty liver disease
Authors: Abdelmoneim Doaa , Eldomany Ehab B. , El-Adl Mohamed , Farghali Ahmed , El-Sayed Gehad , El-Sherbini El Said 
Published: October 2024

AbstractUtilizing naringenin as a safe, natural compound for reducing graphene oxide and to determine whether Nar-RGO more effectively mitigates the harmful effects of HFFD-induced NAFLD compared to crude naringenin. Using a straightforward experimental setup, we utilize the bioactive flavonoid naringenin (NAR) as the reducing agent to synthesize naringenin-reduced graphene oxide nanosheets (Nar-RGO). Naringenin loading on graphene oxide was validated using electroscopic methods (SEM and TEM) and zeta potential measurements. Utilization of reduced graphene oxide for naringenin encapsulation resulted in a significant improvement in hepatic steatosis, insulin resistance, oxidative stress, and signs of inflammation in HFFD-induced NAFLD compared to crude naringenin. This study demonstrates that Nar-RGO exhibits significantly greater efficacy compared to free naringenin. Therefore, it can be used as a promising medicine in counteracting high-fat-fructose diet (HFFD)-induced NAFLD.
Long-Term Reproducibility of BMD-Measurements with Clinical QCT Using Simultaneous and Asynchronous Calibration Methods and Different Measurement and Reconstruction Protocols
Authors: du Mont Sophie , Barkmann Reinhard , Damm Timo , Peña Jaime , Reinhold Stefan , Both Marcus , Mainusch Meike , Glüer Claus-Christian 
Published: October 2024

AbstractOsteoporosis is underdiagnosed and undertreated. To improve timely fracture risk assessment optimized densitometry methods are required such as opportunistic spinal quantitative computed tomography (QCT). However, it is unclear how to best calibrate these scans and correct for potential scanner drift of QCT when used for monitoring bone mineral density (BMD) changes. We compared gold standard simultaneous calibration with asynchronous calibration methods, assessing mid-term (12 weeks) and long-term (1.5 years) reproducibility of BMD measurements. Cortical and trabecular compartments of the European Spine Phantom were studied with ten different protocols including low dose and high resolution (HR)-modes. Based on weekly phantom data, we compared simultaneous calibration to asynchronous single (termed global) or monthly calibration. The accuracy was better for trabecular measurements than for cortical measurements for all calibration methods. Reproducibility was excellent for all methods and slightly better for asynchronous than for simultaneous calibration both for trabecular and cortical bone. For HR protocols, reproducibility was better than for low dose measurements. In trabecular compartments averaged HR-BMD remained stable for global (− 0.1%/year, ns) but not for simultaneous calibration (− 1.5%/year, p < 0.001). No significant drifts could be detected for averaged low dose BMD (− 0.9 to + 0.8%/year) for either calibration method. Our data suggest that with regard to precision and accuracy measurements with asynchronous calibration are suitable for vertebral BMD assessment (no contrast agents) in clinical practice. Regular (e.g., monthly) stability tests using a calibration phantom could assure long term stability of at least 1 year.
Ultrasound innovations in abdominal radiology: techniques and clinical applications in pediatric imaging
Authors: Davis Laura May , Martinez-Correa Santiago , Freeman Colbey W. , Adams Caroline , Sultan Laith R. , Le David Q. , Lemessa Natae , Darge Kassa , Hwang Misun 
Published: October 2024

AbstractContrast-enhanced ultrasound, microvascular imaging, elastography, and fat quantification have varying degrees of utility, with some applications in the pediatric setting mirroring that in adults and having unique uses when applied to children in others. This review will present novel ultrasound technologies and the clinical context in which they are applied to the pediatric abdomen. New ultrasound technologies have a broad range of applications in clinical practice and represent a powerful diagnostic tool with the potential to replace other imaging modalities, such as magnetic resonance imaging and computed tomography, in specific cases.
A New Approach with Combined Microneedle and Sublative Fractional Radiofrequency for Photoaging Management: A Clinical, Histometric, and Immunohistochemical Study
Authors: El-Domyati Moetaz , Moawad Osama , Abdel-Wahab Hossam , Behairy Ezzeldin F. , Rezk Ahmed F. 
Published: October 2024

Abstract
Background
Fractional radiofrequency (FRF) has been reported to be effective in improving wrinkles. A combination of microneedle and sublative fractional radiofrequency (SFRF) may have the potential synergy to improve photoaged skin.

Objectives
To evaluate the efficacy and safety of combined microneedle and SFRF in photoaging management.

Methods
This prospective study included 12 subjects with moderate photoaging (skin phototype III–IV). The subjects received three consecutive combined microneedle and sublative FRF at 1-month intervals. Punch biopsies were obtained before and after three months of treatment. Routine H&E, Masson-trichrome, Orcein staining, histometric measurements, as well as Collagen type I and Elastin immunohistochemical staining were performed.

Results
Significant improvement was noticed regarding skin tightening and texture (p < 0.05), rhytides, and volunteers’ satisfaction (p < 0.001). Collagen fibers appeared better organized, with a significant increase in collagen type I (p = 0.001). Meanwhile, normal-appearing elastic fibers were restored, and a significant reduction in abnormal elastin was achieved (p = 0.0005).

Conclusion
Combined microneedle and sublative FRF may provide a new therapeutic approach for photoaged skin.

Level of Evidence II
For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.
Key Chemical Soil Parameters for the Assembly of Rhizosphere Bacteria Associated with Avocado Cv Hass Grafted on Landrace Rootstocks
Authors: Córdoba-Agudelo Mateo , Arboleda-Rivera Juan C. , Borrego-Muñoz David A. , Ramírez-Cuartas Camilo A. , Pérez-Jaramillo Juan E. 
Published: October 2024

AbstractAvocado cultivation holds significant economic importance in many countries, ranking Colombia as the fifth largest global producer. Particularly, the Hass cultivar plays a pivotal role in Colombia’s avocado industry, especially in the Department of Antioquia, the primary export region. This cultivar is grown under diverse soil and climate conditions and exhibits considerable genetic polymorphism due to the hybridization of varieties of agronomic significance, leading to a diverse array of landrace rootstocks. However, the role of soil conditions and rootstock genotype in structuring rhizosphere bacterial communities is still lacking. In addressing this knowledge gap, we investigated the influence of two soil conditions on the structure of rhizosphere bacterial communities associated with two landrace genotypes of Persea americana cv. Hass, utilizing 16S rRNA sequencing. Notably, no significant differences related to genotypes were observed. This study reports that the rhizosphere bacterial microbiome remains consistent across avocado landrace rootstocks, while variations in key parameters such as phosphorus, pH, Mg, and Ca drive distinct rhizosphere effects. Our results reveal that despite the soils having similar management, increases in these crucial parameters can lead to bacterial communities with lower alpha diversity and a more complex co-occurrence network. In addition, we found substantial variations in beta diversity, bacterial composition, and metagenome predictions between the two farms, underscoring the role of soil variables in shaping the bacterial microbiome. These findings provide valuable insights into the factors influencing the bacterial communities that may play a role in the health and productivity of crops with agro-industrial potential, such as Hass avocado.
Wirksamkeit und Sicherheit der neuen Generation der Excimer-Laser-Trabekulotomie bei einer heterogenen Patientenpopulation – 1-Jahres-Follow-up
Authors: Gniesmer Stefanie , Sonntag Svenja Rebecca , Grisanti Swaantje 
Published: October 2024

Zusammenfassung

Hintergrund
Mikroinvasive Verfahren haben sich in der Glaukomchirurgie etabliert und werden bevorzugt für Patienten mit nicht zu niedrigen Zieldruckwerten eingesetzt. Die Excimer-Laser-Trabekulotomie (ELT) stellt einen solchen minimal-invasiven Ansatz dar und kann mit einer Kataraktoperation kombiniert werden.

Ziel der Arbeit
Über 12 Monate wurden die Senkung des intraokularen Drucks (IOD), die Menge der drucksenkenden Lokaltherapie und das Auftreten unerwünschter Ereignisse mit dem neuen EliosTM-Verfahren (Elios Vision GmbH, Germering, Deutschland) anhand von Real-Life-Daten einer heterogenen Patientenpopulation, die eine ELT in Kombination mit einer Kataraktoperation (Phako-ELT) erhielt, analysiert.

Material und Methoden
Es wurden 20 Augen von 13 Patienten, die eine Phako-ELT erhalten haben, retrospektiv analysiert. Nach einer Standardphakoemulsifikation mit Hinterkammerlinsenimplantation wurden mit dem Excimer-Laser 10 Mikrokanäle angelegt. Die Patienten wurden über 12 Monate nachbeobachtet und der IOD, die drucksenkende Lokaltherapie und das Auftreten unerwünschter Ereignisse untersucht.

Ergebnisse
Das Durchschnittsalter lag bei 65 Jahren. Präoperativ betrug der IOD 17,5 (± 5,3) mm Hg. Die IOD-Senkung lag im Mittel bei 4,8 mm Hg (27,4 %, p < 0,001) am ersten postoperativen Tag, 3,2 mm Hg (18,3 %, p = 0,22) nach 6 Monaten und 2,5 mm Hg (14,3 %, p = 0,14) nach 12 Monaten. Die Drucksenker konnten von im Durchschnitt 3,2 (± 1,3) Wirkstoffen präoperativ auf 0,5 (± 0,9) an Tag 1 (p < 0,001), 1,9 (± 1,2) nach 6 Monaten (p = 0,008) und 2,2 (± 1,3) nach 12 Monaten (p = 0,013) reduziert werden.

Diskussion
In der hier untersuchten Kohorte ist die ELT in Kombination mit einer Kataraktoperation ein sicheres, minimal-invasives glaukomchirurgisches Verfahren, welches bei Patienten mit niedrigem Ausgangsdruck 1 Jahr postoperativ noch eine IOD-Senkung von 14,3 % aufweist, bei einer Reduktion der drucksenkenden Medikation um 1 Wirkstoff. Da bei der ELT kein Implantat zum Einsatz kommt und die Bindehaut unangetastet bleibt, sind Folgeeingriffe nicht beeinträchtigt und auch Filterkissenoperationen ohne Weiteres möglich.
A strategy of consistent X-ray and neutron double-difference pair distribution function analysis of nanoparticle dispersions
Authors: Thomä Sabrina L. J. , Neuefeind Joerg , Youngs Tristan G. A. , Zobel Mirijam 
Published: October 2024

AbstractIt has been demonstrated that the X-ray pair distribution function (PDF) formalism allows for the identification of very small signal contributions in multi-component systems by the difference and double-difference PDF (dd-PDF) approach. Due to their stronger interaction with light elements compared to X-rays, neutrons are often beneficial or complementary for the characterization of modern materials. Here, it is demonstrated that the dd-PDF strategy previously developed for X-ray PDF data can successfully be applied to neutron PDF data despite much lower count rates compared to X-rays. The dd-PDF strategy was employed for the investigation of aqueous iron oxide nanoparticle (IONP) dispersions. At the Near and InterMediate Range Order Diffractometer (NIMROD) at ISIS, the IONPs could even be investigated in pure water, whereas at the Nanoscale Ordered Materials Diffractometer (NOMAD) at SNS, heavy water had to be used, but additional information could be retrieved from modelling the data of IONP powder in the dry state and with adsorbed (heavy) water. The simple and robust approach can easily be adapted for the use in other multicomponent systems, like heterogenous catalysts or battery systems.
Graphical Abstract
Unraveling molecular characteristics and tumor microenvironment dynamics of neuroendocrine prostate cancer
Authors: Heimdörfer David , Artamonova Nastasiia , Culig Zoran , Heidegger Isabel 
Published: October 2024

AbstractProstate cancer (PCa) is the most prevalent malignancy and the second leading cause of cancer-related deaths among men. While adenocarcinoma of the prostate (adeno-PCa) is well-characterized, neuroendocrine prostate cancer (NEPC) remains poorly understood. Generally, NEPC is a rare but highly aggressive histological variant, however its limited patho-physiological understanding leads to insufficient treatment options associated with low survival rates for NEPC patients. Current treatments for NEPC, including platinum-based therapies, offer some efficacy, but there is a significant need for more targeted approaches. This review summarizes the molecular characteristics of NEPC in contrast to adeno-PCa, providing a comprehensive comparison. A significant portion of the discussion is dedicated to the tumor microenvironment (TME), which has recently been identified as a key factor in tumor progression. The TME includes various cells, signaling molecules, and the extracellular matrix surrounding the tumor, all of which play critical roles in cancer development and response to treatment. Understanding the TME’s influence on NEPC could uncover new avenues for innovative treatment strategies, potentially improving outcomes for patients with this challenging variant of PCa.
Robotic cytoreductive surgery and hyperthermic intraperitoneal chemotherapy: is there a benefit?
Authors: Sparkman Brian K. , Freudenberger Devon C. , Vudatha Vignesh , Trevino Jose G. , Khader Adam , Fernandez Leopoldo J. 
Published: October 2024

Abstract
Background
Open cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC) is a therapeutic option for the management of malignancies with peritoneal carcinomatosis and of peritoneal origin. Robotic surgery shows promise as a minimally invasive approach for select patients. We aimed to evaluate the differences in outcomes between robotic versus open CRS/HIPEC and hypothesized less morbidity and faster recovery in the robotic approach group.

Methods
We conducted a retrospective cohort study from our HIPEC database including all tumor origins. We included patients aged 18–89 years who underwent CRS/HIPEC for curative intent at a single institution between January 1, 2017, and December 31, 2023. Patients were stratified by open versus robotic-assisted surgery. Mann–Whitney U and Fisher Exact tests were used to compare differences in patient characteristics and outcomes.

Results
A total of 111 patients underwent CRS/HIPEC for curative intent, with 95 (85.6%) cases performed open and 16 (14.4%) robotically. The groups were demographically similar, except patients undergoing robotic CRS/HIPEC had a significantly higher median income ($83,845 vs. $70,519, p < 0.001). Rate of comorbidities and cancer type, including appendiceal, colorectal, and ovarian, were the same. The peritoneal carcinomatosis index and completion of cytoreduction score were similar between groups. Robotic approach was associated with statistically significant lower estimated blood loss (113 vs. 400 mL, p < 0.001) and postoperative transfusions (6.3% vs. 23.2%, p = 0.036). Total complications, readmission rates, and 30-day mortality were similar among groups, but the robotic group had a significantly shorter length of stay (5.5 vs. 9 d., p < 0.001).

Conclusion
Robotic CRS/HIPEC holds promise to decrease intraoperative blood loss, blood transfusions, and hospital stay while providing similar immediate postoperative outcomes in select patients. These results should be validated in the setting of a prospective trial and effects on long-term oncologic outcomes should be investigated.
Implicit sensing self-supervised learning based on graph multi-pretext tasks for traffic flow prediction
Authors: Sattarzadeh Ali Reza , Pathirana Pubudu Nishantha , Palaniswami Marimuthu 
Published: October 2024

Abstract
In recent years, spatio-temporal graph neural networks (GNNs) have successfully been used to improve traffic prediction by modeling intricate spatio-temporal dependencies in irregular traffic networks. However, these approaches may not capture the intrinsic properties of traffic data and can suffer from overfitting due to their local nature. This paper introduces the Implicit Sensing Self-Supervised learning model (ISSS), which leverages a multi-pretext task framework for traffic flow prediction. By transforming data into an alternative feature space, ISSS effectively captures both specific and general representations through self-supervised tasks, including contrastive learning and spatial jigsaw puzzles. This enhancement promotes a deeper understanding of traffic features, improved regularization, and more accurate representations. Comparative experiments on six datasets demonstrate the effectiveness of ISSS in learning general and discriminative features in both supervised and unsupervised modes. ISSS outperforms existing models, demonstrating its capabilities in improving traffic flow predictions while addressing challenges associated with local operations and overfitting. Comprehensive evaluations across various traffic prediction datasets, have established the validity of the proposed approach. Unsupervised learning scenarios have shown the improvements in RMSE for the METR-LA and PEMSBAY datasets of 0.39 and 0.35 for location-dependent and location-independent tasks, respectively. In supervised learning scenarios, for the same datasets, the improvements were 1.16 for location-dependent tasks and 0.55 for location-independent tasks.
Leveraging survival analysis in cost-aware deepnet for efficient hard drive failure prediction
Authors: Ahmed Jishan , Green II Robert C. 
Published: October 2024

Abstract
Many real-world datasets, such as those used for failure and anomaly detection, are severely imbalanced, with a relatively small number of failed instances compared to the number of normal instances. To address these issues, this paper leverages the Backblaze hard disk drives (HDDs) data and makes several contributions to hard drive failure prediction. This research explores 1D convolutional neural networks (CNN) to utilize the sequential nature of hard drive sensor data. The performance of 1D CNN models is compared to traditional machine learning (ML) algorithms, such as the synthetic minority over-sampling technique (SMOTE) and weighted logistic regression (WLR), demonstrating superior results, suggesting the potential effectiveness of the proposed approaches. In addition to these efforts, this paper aims to provide a comprehensive understanding of hard drive longevity and the critical factors contributing to their eventual failure through survival analysis. The 1D CNN models employ weighted binary cross-entropy (WCE) loss and modified focal loss (MFL) functions to manage class imbalanced issues commonly observed in hard drive data. The findings suggest that 1D CNN models outperform traditional ML models, with regularization techniques like dropout and early stopping proving effective in controlling overfitting. Notably, the 1D CNN model with WCE loss demonstrated the best overall performance with a

$$G_{mean}$$

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mean

of 0.692, successfully maximizing the FDR without increasing the FAR. In parallel, the research also employs Cox regression to identify key SMART parameters influencing drive failure. The high concordance index (c-index) of the Cox model (0.958) adds confidence to the insights derived. The research thus sets a solid groundwork for data center management strategies, with a future focus on practical implementation and evaluation of these findings.
Hardware-accelerated neural network model for early prediction of sudden cardiac arrest based on heart rate variability metrics
Authors: Pan Sheng-Yueh , Nguyen Duc Huy , Chao Paul C.-P. 
Published: October 2024

AbstractSudden Cardiac Arrest (SCA) constitutes a dire medical condition, marked by the abrupt cessation of effective blood circulation due to the heart's failure to contract properly. This leads to acute circulatory collapse, often culminating in loss of consciousness within an hour and potentially resulting in fatality within minutes if left unattended. Heart rate variability (HRV) serves as a critical biometric, derived from electrocardiogram (ECG) signals with ventricular depolarization waves to further calculate the R-R Intervals (RRIs). These intervals provide the basis for extracting various characteristics of cardiac rhythm, encompassing time-domain, frequency-domain, and nonlinear features. This study presents a neural network-based classification algorithm that leverages HRV metrics to categorize patients into SCA and Normal Sinus Rhythm (NSR) cohorts. The proposed neural network (NN) model showcased impressive results, achieving an accuracy of 96.23%, a sensitivity of 94.35%, and a specificity of 98.12% in detecting SCA, as evaluated through leave-one-subject-out analysis. In order to harness the benefits of hardware acceleration, the algorithm is implemented on a Field-Programmable Gate Array (FPGA). Its computational efficiency is subsequently benchmarked against traditional software-based methodologies. The hardware-level implementation is made possible in Verilog hardware description language (HDL) and was verified successfully with expected performance by register-transfer level (RTL) simulation via Vivado 2020.2.