bluuebunny/crossref_metadata_2025 huggingface dataset:
Downscaling Climatic Variables at a River Basin Scale: Statistical Validation and Ensemble Projection under Climate Change Scenarios
Authors: El-Samra Renalda , Haddad Abeer , Alameddine Ibrahim , Bou-Zeid Elie , El-Fadel Mutasem
Published: February 2024

Climatic statistical downscaling in arid and topographically complex river basins remains relatively lacking. To address this gap, climatic variables derived from a global climate model (GCM) ensemble were downscaled from a grid resolution of 2.5° × 2.5° down to the station level. For this purpose, a combination of multiple linear and logistic regressions was developed, calibrated and validated with regard to their predictions of monthly precipitation and daily temperature in the Jordan River Basin. Seasonal standardized predictors were selected using a backward stepwise regression. The validated models were used to examine future scenarios based on GCM simulations under two Representative Concentration Pathways (RCP4.5 and RCP8.5) for the period 2006–2050. The results showed a cumulative near-surface air temperature increase of 1.54 °C and 2.11 °C and a cumulative precipitation decrease of 100 mm and 135 mm under the RCP4.5 and RCP8.5, respectively, by 2050. This pattern will inevitably add stress to water resources, increasing management challenges in the semi-arid to arid regions of the basin. Moreover, the current application highlights the potential of adopting regression-based models to downscale GCM predictions and inform future water resources management in poorly monitored arid regions at the river basin scale.
The Crystal Structure and Physicochemical Properties of New Complexes Containing a CuII-LnIII-CuII Core
Authors: Cristóvão Beata , Osypiuk Dariusz , Mirosław Barbara
Published: February 2024

Three new cationic complexes, [Cu4Tb2(H2L)4(NO3)4(H2O)3](NO3)2·5.5H2O·2MeOH (1), [Cu4Ho2(H2L)4(NO3)4(H2O)3](NO3)2·7.5H2O (2), and [Cu4Er2(H2 L)4(NO3)4(H2O)3](NO3)2·7H2O·3MeOH (3), were synthesized and studied using elemental and TG/DTG/DSC analyses, single-crystal X-ray diffraction, and magnetic measurements. The structure analysis showed that 1–3 crystallize as (NO3)-bridged compounds and that the lanthanide(III) ion acts as a joint connecting two [CuH2L] coordination units. In each heterotrinuclear unit, an asymmetry in the degree of planarity of the bridging CuO2Ln fragments is observed. The CuII ions are five- and six-coordinate, with distorted square pyramidal and octahedral geometry, respectively, whereas the LnIII ions are nine-coordinate. The solvates 1–3 are stable at room temperature, and their desolvation process is consistent with the loss of water and/or methanol molecules. The temperature dependence of the magnetic susceptibility and the field-dependent magnetization indicate the weak ferromagnetic interaction between the paramagnetic centers CuII and TbIII/HoIII 1 and 2.
Habitat Impacts on the Golden Eagle’s Foraging Ecology and Nest Site Selection in Poland
Authors: Stój Marian , Kruszyk Robert , Zawadzka Dorota , Zawadzki Grzegorz
Published: February 2024

The Golden Eagle Aquila chrysaetos (hereafter GE) is one of Europe’s largest avian top predators. The present study recognizes the habitat characteristics and food composition of the GE in Poland. The research was carried out in the Polish part of the Carpathian Mountains. The GEs built nests mainly on old coniferous trees and strongly preferred the Silver Fir Abies alba. On average, within a 5 km buffer around the nest, forests covered about 2/3 of the area, while open land with villages was at 31% and water was about 1%. Birds preferred areas with less forest cover than in the random points, but the nests were significantly further from the countryside than the distance measured for the drawn points distributed in the GEs’ range in Poland. Their diet during the breeding season was assessed by analyzing pellets and food remains. The proportion of birds was 55.7%, mammals was 43.4%, and reptiles was 0.9%. The ten most common prey species included the Domestic Pigeon Columba livia, the Ural Owl Strix uralensis, the Tawny Owl Strix aluco, the Buzzard Buteo buteo, the Roe Deer Capreolus capreolus, the Martens Martes sp., and the Red Fox Vulpes vulpes, which composed 70% of food items. Our results showed that the GE is a top predator, as evidenced by the high share of other predators—both mammal and bird species—in its diet, which constituted about 34% of identified preys. The diet of the studied GE population showed geographical variation, suggesting local adaptations to available prey species. The share of Roe Deer increased from west to east, indicating a higher availability in the less urbanized eastern part of the country. An analysis of general food categories showed that, as latitude increased, the share of captured birds among prey of the GEs declined, while the percentage of forest prey increased. Pigeons were prey of the GEs mainly in the western part of their range. The GEs often captured species with nocturnal activity—owls and martens, which were identified in most of the GEs’ territories. The proportion of mammals in the diet of the GE increased with an increase in the proportion of open areas, while the abundance of birds of prey and owls in the diet correlated with a higher proportion of forests. The greatest threat to Poland’s GE population is the reduction in semi-open areas with low human activity and low human population densities.
Revolutionizing Drug Discovery: A Comprehensive Review of AI Applications
Authors: Dhudum Rushikesh , Ganeshpurkar Ankit , Pawar Atmaram
Published: February 2024

The drug discovery and development process is very lengthy, highly expensive, and extremely complex in nature. Considering the time and cost constraints associated with conventional drug discovery, new methods must be found to enhance the declining efficiency of traditional approaches. Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic knowledge and provides expedited solutions to complex challenges. Advancements in AI and machine learning (ML) techniques have revolutionized their applications to drug discovery and development. This review illuminates the profound influence of AI on diverse aspects of drug discovery, encompassing drug-target identification, molecular properties, compound analysis, drug development, quality assurance, and drug toxicity assessment. ML algorithms play an important role in testing systems and can predict important aspects such as the pharmacokinetics and toxicity of drug candidates. This review not only strengthens the theoretical foundation and development of this technology, but also explores the myriad challenges and promising prospects of AI in drug discovery and development. The combination of AI and drug discovery offers a promising strategy to overcome the challenges and complexities of the pharmaceutical industry.
Skin and Syntax: Large Language Models in Dermatopathology
Authors: Shah Asghar , Wahood Samer , Guermazi Dorra , Brem Candice E. , Saliba Elie
Published: February 2024

This literature review introduces the integration of Large Language Models (LLMs) in the field of dermatopathology, outlining their potential benefits, challenges, and prospects. It discusses the changing landscape of dermatopathology with the emergence of LLMs. The potential advantages of LLMs include a streamlined generation of pathology reports, the ability to learn and provide up-to-date information, and simplified patient education. Existing instances of LLMs encompass diagnostic support, research acceleration, and trainee education. Challenges involve biases, data privacy and quality, and establishing a balance between AI and dermatopathological expertise. Prospects include the integration of LLMs with other AI technologies to improve diagnostics and the improvement of multimodal LLMs that can handle both text and image input. Our implementation guidelines highlight the importance of model transparency and interpretability, data quality, and continuous oversight. The transformative potential of LLMs in dermatopathology is underscored, with an emphasis on a dynamic collaboration between artificial intelligence (AI) experts (technical specialists) and dermatopathologists (clinicians) for improved patient outcomes.
Kinase Fusions in Spitz Melanocytic Tumors: The Past, the Present, and the Future
Authors: Daruish Maged , Ambrogio Francesca , Colagrande Anna , Marzullo Andrea , Alaggio Rita , Trilli Irma , Ingravallo Giuseppe , Cazzato Gerardo
Published: February 2024

In recent years, particular interest has developed in molecular biology applied to the field of dermatopathology, with a focus on nevi of the Spitz spectrum. From 2014 onwards, an increasing number of papers have been published to classify, stratify, and correctly frame molecular alterations, including kinase fusions. In this paper, we try to synthesize the knowledge gained in this area so far. In December 2023, we searched Medline and Scopus for case reports and case series, narrative and systematic reviews, meta-analyses, observational studies—either longitudinal or historical, case series, and case reports published in English in the last 15 years using the keywords spitzoid neoplasms, kinase fusions, ALK, ROS1, NTRK (1-2-3), MET, RET, MAP3K8, and RAF1. ALK-rearranged Spitz tumors and ROS-1-rearranged tumors are among the most studied and characterized entities in the literature, in an attempt (although not always successful) to correlate histopathological features with the probable molecular driver alteration. NTRK-, RET-, and MET-rearranged Spitz tumors present another studied and characterized entity, with several rearrangements described but as of yet incomplete information about their prognostic significance. Furthermore, although rarer, rearrangements of serine–threonine kinases such as BRAF, RAF1, and MAP3K8 have also been described, but more cases with more detailed information about possible histopathological alterations, mechanisms of etiopathogenesis, and also prognosis are needed. The knowledge of molecular drivers is of great interest in the field of melanocytic diagnostics, and it is important to consider that in addition to immunohistochemistry, molecular techniques such as FISH, PCR, and/or NGS are essential to confirm and classify the different patterns of mutation. Future studies with large case series and molecular sequencing techniques are needed to allow for a more complete and comprehensive understanding of the role of fusion kinases in the spitzoid tumor family.
Diagnosis of Delayed Post-Hypoxic Leukoencephalopathy (Grinker’s Myelinopathy) with MRI Using Divided Subtracted Inversion Recovery (dSIR) Sequences: Time for Reappraisal of the Syndrome?
Authors: Newburn Gil , Condron Paul , Kwon Eryn E. , McGeown Joshua P. , Melzer Tracy R. , Bydder Mark , Griffin Mark , Scadeng Miriam , Potter Leigh , Holdsworth Samantha J. , Cornfeld Daniel M. , Bydder Graeme M.
Published: February 2024

Background: Delayed Post-Hypoxic Leukoencephalopathy (DPHL), or Grinker’s myelinopathy, is a syndrome in which extensive changes are seen in the white matter of the cerebral hemispheres with MRI weeks or months after a hypoxic episode. T2-weighted spin echo (T2-wSE) and/or T2-Fluid Attenuated Inversion Recovery (T2-FLAIR) images classically show diffuse hyperintensities in white matter which are thought to be near pathognomonic of the condition. The clinical features include Parkinsonism and akinetic mutism. DPHL is generally regarded as a rare condition. Methods and Results: Two cases of DPHL imaged with MRI nine months and two years after probable hypoxic episodes are described. No abnormalities were seen on the T2-FLAIR images with MRI, but very extensive changes were seen in the white matter of the cerebral and cerebellar hemisphere on divided Subtraction Inversion Recovery (dSIR) images. dSIR sequences may produce ten times the contrast of conventional inversion recovery (IR) sequences from small changes in T1. The clinical findings in both cases were of cognitive impairment without Parkinsonism or akinetic mutism. Conclusion: The classic features of DPHL may only represent the severe end of a spectrum of diseases in white matter following global hypoxic injury to the brain. The condition may be much more common than is generally thought but may not be recognized using conventional clinical and MRI criteria for diagnosis. Reappraisal of the syndrome of DPHL to include clinically less severe cases and to encompass recent advances in MRI is advocated.
Artificial Intelligence-Enhanced Quantitative Ultrasound for Breast Cancer: Pilot Study on Quantitative Parameters and Biopsy Outcomes
Authors: Kwon Hyuksool , Oh Seokhwan , Kim Myeong-Gee , Kim Youngmin , Jung Guil , Lee Hyeon-Jik , Kim Sang-Yun , Bae Hyeon-Min
Published: February 2024

Traditional B-mode ultrasound has difficulties distinguishing benign from malignant breast lesions. It appears that Quantitative Ultrasound (QUS) may offer advantages. We examined the QUS imaging system’s potential, utilizing parameters like Attenuation Coefficient (AC), Speed of Sound (SoS), Effective Scatterer Diameter (ESD), and Effective Scatterer Concentration (ESC) to enhance diagnostic accuracy. B-mode images and radiofrequency signals were gathered from breast lesions. These parameters were processed and analyzed by a QUS system trained on a simulated acoustic dataset and equipped with an encoder-decoder structure. Fifty-seven patients were enrolled over six months. Biopsies served as the diagnostic ground truth. AC, SoS, and ESD showed significant differences between benign and malignant lesions (p < 0.05), but ESC did not. A logistic regression model was developed, demonstrating an area under the receiver operating characteristic curve of 0.90 (95% CI: 0.78, 0.96) for distinguishing between benign and malignant lesions. In conclusion, the QUS system shows promise in enhancing diagnostic accuracy by leveraging AC, SoS, and ESD. Further studies are needed to validate these findings and optimize the system for clinical use.
Validation of Artificial Intelligence (AI)-Assisted Flow Cytometry Analysis for Immunological Disorders
Authors: Lu Zhengchun , Morita Mayu , Yeager Tyler S. , Lyu Yunpeng , Wang Sophia Y. , Wang Zhigang , Fan Guang
Published: February 2024

Flow cytometry is a vital diagnostic tool for hematologic and immunologic disorders, but manual analysis is prone to variation and time-consuming. Over the last decade, artificial intelligence (AI) has advanced significantly. In this study, we developed and validated an AI-assisted flow cytometry workflow using 379 clinical cases from 2021, employing a 3-tube, 10-color flow panel with 21 antibodies for primary immunodeficiency diseases and related immunological disorders. The AI software (DeepFlow™, version 2.1.1) is fully automated, reducing analysis time to under 5 min per case. It interacts with hematopatholoists for manual gating adjustments when necessary. Using proprietary multidimensional density–phenotype coupling algorithm, the AI model accurately classifies and enumerates T, B, and NK cells, along with important immune cell subsets, including CD4+ helper T cells, CD8+ cytotoxic T cells, CD3+/CD4−/CD8− double-negative T cells, and class-switched or non-switched B cells. Compared to manual analysis with hematopathologist-determined lymphocyte subset percentages as the gold standard, the AI model exhibited a strong correlation (r > 0.9) across lymphocyte subsets. This study highlights the accuracy and efficiency of AI-assisted flow cytometry in diagnosing immunological disorders in a clinical setting, providing a transformative approach within a concise timeframe.
Correlation between Serum Biomarkers and Lung Ultrasound in COVID-19: An Observational Study
Authors: Mousa Amne , Blok Siebe G. , Karssen Dian , Aman Jurjan , Annema Jouke T. , Bogaard Harm Jan , Bonta Peter I. , Haaksma Mark E. , Heldeweg Micah L. A. , Lieveld Arthur W. E. , Nanayakkara Prabath , Nossent Esther J. , Smit Jasper M. , Smit Marry R. , Vlaar Alexander P. J. , Schultz Marcus J. , Bos Lieuwe D. J. , Paulus Frederique , Tuinman Pieter R. ,   Amsterdam UMC COVID-19 Biobank Investigators
Published: February 2024

Serum biomarkers and lung ultrasound are important measures for prognostication and treatment allocation in patients with COVID-19. Currently, there is a paucity of studies investigating relationships between serum biomarkers and ultrasonographic biomarkers derived from lung ultrasound. This study aims to assess correlations between serum biomarkers and lung ultrasound findings. This study is a secondary analysis of four prospective observational studies in adult patients with COVID-19. Serum biomarkers included markers of epithelial injury, endothelial dysfunction and immune activation. The primary outcome was the correlation between biomarker concentrations and lung ultrasound score assessed with Pearson’s (r) or Spearman’s (rs) correlations. Forty-four patients (67 [41–88] years old, 25% female, 52% ICU patients) were included. GAS6 (rs = 0.39), CRP (rs = 0.42) and SP-D (rs = 0.36) were correlated with lung ultrasound scores. ANG-1 (rs = −0.39) was inversely correlated with lung ultrasound scores. No correlations were found between lung ultrasound score and several other serum biomarkers. In patients with COVID-19, several serum biomarkers of epithelial injury, endothelial dysfunction and immune activation correlated with lung ultrasound findings. The lack of correlations with certain biomarkers could offer opportunities for precise prognostication and targeted therapeutic interventions by integrating these unlinked biomarkers.
Recurrent Metastatic Pulmonary Synovial Sarcoma during Pregnancy: A Case Report and Literature Review
Authors: De Rocco Silvia , Di Biasi Jasmine , Fantasia Ilaria , Tabacco Sara , Ricevuto Enrico , Palumbo Pierpaolo , Imbergamo Ilenia , Ludovisi Manuela , Guido Maurizio
Published: February 2024

Primary pulmonary synovial sarcoma is a rare type of soft tissue tumor. Exceptionally it can occur during pregnancy, representing a challenge in management and treatment given its notable aggressiveness and the not infrequent incidence of maternal death. We report our case of metastatic recurrence of pulmonary synovial sarcoma during pregnancy, with the aim to emphasize the decision-making, diagnostic, and therapeutic multidisciplinary processes and the evolution of the pathology. Besides, we focused on the analysis of the limited literature data available on the topic.
Federated Learning Backdoor Attack Based on Frequency Domain Injection
Authors: Liu Jiawang , Peng Changgen , Tan Weijie , Shi Chenghui
Published: February 2024

Federated learning (FL) is a distributed machine learning framework that enables scattered participants to collaboratively train machine learning models without revealing information to other participants. Due to its distributed nature, FL is susceptible to being manipulated by malicious clients. These malicious clients can launch backdoor attacks by contaminating local data or tampering with local model gradients, thereby damaging the global model. However, existing backdoor attacks in distributed scenarios have several vulnerabilities. For example, (1) the triggers in distributed backdoor attacks are mostly visible and easily perceivable by humans; (2) these triggers are mostly applied in the spatial domain, inevitably corrupting the semantic information of the contaminated pixels. To address these issues, this paper introduces a frequency-domain injection-based backdoor attack in FL. Specifically, by performing a Fourier transform, the trigger and the clean image are linearly mixed in the frequency domain, injecting the low-frequency information of the trigger into the clean image while preserving its semantic information. Experiments on multiple image classification datasets demonstrate that the attack method proposed in this paper is stealthier and more effective in FL scenarios compared to existing attack methods.
Exploring Distributions of House Prices and House Price Indices
Authors: Liu Jiong , Farahani Hamed , Serota R. A.
Published: February 2024

We use house prices (HP) and house price indices (HPI) as a proxy to income distribution. Specifically, we analyze distribution of sale prices in the 1970–2010 window of over 116,000 single-family homes in Hamilton County, Ohio, including Cincinnati metro area of about 2.2 million people. We also analyze distributions of HPI, published by Federal Housing Finance Agency (FHFA), for nearly 18,000 US ZIP codes that cover a period of over 40 years starting in 1980’s. If HP can be viewed as a first derivative of income, HPI can be viewed as its second derivative. We use generalized beta (GB) family of functions to fit distributions of HP and HPI since GB naturally arises from the models of economic exchange described by stochastic differential equations. Our main finding is that HP and multi-year HPI exhibit a negative Dragon King (nDK) behavior, wherein power-law distribution tail gives way to an abrupt decay to a finite upper limit value, which is similar to our recent findings for realized volatility of S&P500 index in the US stock market. This type of tail behavior is best fitted by a modified GB (mGB) distribution. Tails of single-year HPI appear to show more consistency with power-law behavior, which is better described by a GB Prime (GB2) distribution. We supplement full distribution fits by mGB and GB2 with direct linear fits (LF) of the tails. Our numerical procedure relies on evaluation of confidence intervals (CI) of the fits, as well as of p-values that give the likelihood that data come from the fitted distributions.
Design of Metasurface-Based Photodetector with High-Quality Factor
Authors: Ki Yu , Jeon Hyeon , Kim Soo
Published: February 2024

The ability of fine-tuning wavelengths in a high-Q resonance has been applied to various optical applications, particularly that of the development of nanoscaled, ultrathin photodetectors that realize next-generation optical sensors. However, designing a nanopatterned surface in a photodetector to induce intriguing optical effects inevitably deteriorates the electrical properties due to the increased roughness and defects, which cause the significant recombination of the photogenerated carriers. Moreover, light absorption in a semiconductor fundamentally decreases the Q factor of a resonance and ultimately limits the spectral sharpness. Thus, there is a trade-off between the applications of nano-optics for the fine control of wavelengths and the matured photodetector platform for electrical stability. In this work, we propose an alternative type of optical design for a photodetector by effectively decoupling the functionality of nano-optics for high-Q resonances and the electrical properties of semiconductors for the extraction of efficient photocarriers. By optimally balancing the loss of scattered radiation in a high-Q resonance and the loss of absorption in a semiconductor, we achieve a nano-optics-based photodetector with high-Q absorption and polarization sensing without a significant deterioration in the electrical properties. We believe that the suggested design rule can be effectively applied for the realization of emerging nanoscaled photodetectors for various applications of next-generation optical sensors.
A Large Frequency Ratio Dual-Band Integrated Bandpass Filter Based on MCSICL Structure
Authors: Zhu Yu , Li Xiaochun
Published: February 2024

In this paper, a dual-band integrated bandpass filter (DI-BPF) based on a mode composite substrate integrated coaxial line (MCSICL) is proposed for a large frequency ratio. The low-frequency bandpass filter is formed by incorporating an SICL line and a gap into the MCSICL, operating in the fundamental mode of the MCSICL. The high-frequency bandpass filter is formed by introducing grounded vias into the MCSICL, operating in the first high-order mode of the MCSICL. To guide the design, the equivalent circuit models of the low- and high-frequency bandpass filters are built. Based on the equivalent circuit models, the DI-BPF is synthesized for a large frequency ratio. The transitions from the DI-BPF to ground coplanar waveguides (GCPWs) are designed for the low- and high-frequency bandpass filters. The DI-BPF with the transitions is fabricated by the printed circuit board (PCB) process. Measurement results indicate a large frequency ratio of 23.16, with the isolation between the low- and high-frequency bandpass filters exceeding 30 dB from dc to 50 GHz.
A Tunable Foreground Self-Calibration Scheme for Split Successive-Approximation Register Analog-to-Digital Converter
Authors: Park Joonsung , Lee Jiwon , Abraham Jacob A. , Kim Byoungho
Published: February 2024

The capacitor mismatch among diverse defects caused by variations in the manufacturing process significantly affects the linearity of the capacitor array used to implement the capacitive digital-to-analog converter (CDAC) in the successive-approximation register (SAR) analog-to-digital converter (ADC). Accordingly, the linearity of the SAR ADC is limited by that of capacitor array, resulting in serious yield loss. This paper proposes an efficient foreground self-calibration technique to enhance the linearity of the SAR ADCs by mitigating the capacitor mismatch based on the split ADC architecture along with variable capacitors. In this work, two ADC channels (i.e., ADC1 and ADC2) for the split ADC architecture include their capacitive DACs (CDACs) whose binary-weighted capacitor arrays consist of variable capacitors. A charge-sharing SAR ADC is used for each ADC channel. In the normal operation mode, their digital outputs are averaged to be the final ADC output, as in a conventional split ADC. In the calibration mode, every single binary-weighted capacitor for the two ADCs is sequentially calibrated by making parallel or/and antiparallel connection among two or thee capacitors from the two channels. For instance, because the capacitors of the CDACs ideally exhibit the binary-weighted relation as Cn=2×Cn−1, the variable capacitor Cn of ADC1 can be updated to be closest to the sum of Cn−1 of ADC1 and Cn−1 of ADC2 for the calibration. For the process, the two capacitor arrays of the two ADCs can be reconfigured to be connected to each other, so that the Cn of ADC1 can be connected with two of the Cn−1 of ADC1 and ADC2 in antiparallel. The two voltages at the top and the bottom plates of the CDAC are compared by a comparator of ADC1, and the comparison results are used to update Cn. This process is iterated, until Cn is in agreement with the sum of two of Cn−1. Finally, all the capacitors can be calibrated in this way to have the binary-weighted relation. The simulation results based on the proposed work with a split SAR ADC model verified that the proposed technique can be practically used, by showing that the total harmonic distortion and the signal-to-noise-and-distortion ratio were enhanced by 21.8 dB and 6.4 dB, respectively.
Linear Matrix Inequality-Based Robust Model Predictive Speed Control for a Permanent Magnetic Synchronous Motor with a Disturbance Observer
Authors: Kim Dae-Jin , Kim Byungki
Published: February 2024

In this paper, a linear matrix inequality (LMI)-based robust model predictive speed control (RMPSC) with a disturbance observer (DOB) is proposed to guarantee stability and control performance against the parameter uncertainty and disturbance of a permanent magnetic synchronous motor (PMSM). All external torques applied to the PMSM are defined as disturbance, estimated by the DOB, and used to construct the RMPSC method. The proposed DOB and RMPSC are determined by a multiple LMI-based optimization approach. Furthermore, parameter uncertainty within a certain range, due to manufacturing errors or aging deterioration, is considered and a systematic tuning method is proposed to obtain the optimal gains. Finally, an offline optimization method is developed that ensures a low computational load to enable real-time processing. Simulation results demonstrate the effectiveness and validity of the proposed control method.
Improving Carrier Transport Behavior in a Bilayer ETL for Enhanced Efficiency of Perovskite Solar Cells: An Investigation
Authors: Hsu Rui-Yun , Lai Yeong-Lin , Chou Yung-Hua , Syu Wei-Jhe
Published: February 2024

Perovskite solar cells (PSCs) are currently among the most promising solar cell technologies. A key component influencing their efficiency and stability is the electron transport layer (ETL). This study examined the carrier transport properties of various ETL materials, including TiO2, SnO2, and TiO2/SnO2 bilayer ETLs, to understand their effects on PSC performance. The study proposed a hypothesis that the bilayer design, integrating TiO2 and SnO2, enhances performance, and it used experimental results to substantiate this. Through analysis and discussion of the ETLs, the interface between perovskite (PVSK) and ETLs, and other PSC components, we gained insights into the carrier transport dynamics in PSCs with different ETL configurations. Our findings indicate that the TiO2/SnO2 bilayer ETL structure can significantly improve PSC performance by reducing current leakage, improving carrier transport, and minimizing carrier recombination. This enhancement is quantified by the increase in efficiency from 13.58% with a single-layer TiO2 ETL to 20.49% with the bilayer ETL.
Cyclic Homomorphic Encryption Aggregation (CHEA)—A Novel Approach to Data Aggregation in the Smart Grid
Authors: Sousa-Dias Daniel , Amyot Daniel , Rahimi-Kian Ashkan , Bashari Masoud , Mylopoulos John
Published: February 2024

The transactive energy market is an emerging development in energy economics built on advanced metering infrastructure. Data generated in this context is often required for market operations, while also being privacy sensitive. This dual concern has necessitated the development of various methods of obfuscation in order to maintain privacy while still facilitating operations. While data aggregation is a common approach in this context, many of the existing aggregation methods rely on additional network components or lack flexibility. In this paper, we introduce Cyclic Homomorphic Encryption Aggregation (CHEA), a secure aggregation protocol that eliminates the need for additional network components or complicated key distribution schemes, while providing additional capabilities compared to similar protocols. We validate our scheme with formal security analysis as well as a software simulation of a transactive energy network running the scheme. Results indicate that CHEA performs well in comparison to similar works, with minimal communication overheads. Additionally, CHEA retains all standard security properties held by other aggregation schemes, while improving flexibility and reducing infrastructural requirements. Our scheme operates on similar assumptions as other works, but current smart metering hardware lags in terms of processing power, making the scheme infeasible on the current generation of hardware. However, these capabilities should quickly advance to an accommodating state. With this in mind, and given the results, we believe CHEA is a strong candidate for aggregating transactive energy data.
Evidence for Soil Phosphorus Resource Partitioning in a Diverse Tropical Tree Community
Authors: Müller Robert , Elsenbeer Helmut , Turner Benjamin L.
Published: February 2024

Soil phosphorus (P) partitioning could contribute to species diversity and structure in plant communities, but field-scale evidence for P partitioning remains scarce. We hypothesized that the presence of P partitioning could be inferred from statistical associations between the spatial distributions of plants and chemical forms of bioavailable soil P. We investigated this in a diverse tropical tree community on Barro Colorado Island, Panama. We quantified potentially bioavailable forms of soil P by extraction in 2 mM citric acid followed by treatment with phosphatase enzymes. We then linked these P forms to the distribution of 189 tree species in a 50 ha forest dynamics plot by testing species–P associations against null models of random dispersal. We found that 20% of tree species were significantly (α = 0.05) associated with the depletion of at least one soil organic P fraction, although around half of these associations might be false rejections of the null hypothesis due to type I error. Species in the Fabaceae (legumes), which are known to express high rates of phosphatase in their roots, were most frequently associated with soil P fractions. We interpret our findings as evidence of widespread P partitioning at the community scale, affecting a relatively small proportion of tree species in this moderately fertile forest. We predict that stronger evidence of partitioning will be found at sites with lower P availability.
Ecosystem Services Value Realization and Ecological Industry Design in Scenic Areas of Karst in South China
Authors: Chang Huanhuan , Xiong Kangning , Zhu Dayun , Zhang Zhenzhen , Zhang Wenxiu
Published: February 2024

Ecosystem services (ESs) value realization and ecological industry (eco-industry) are essential components of regional development. Due to the vulnerability and non-renewability of natural landscape resources in Karst areas, once unreasonable resource development takes place, it is easy to pose threats and causes damage to its ecosystem. This article selects the grain data correction equivalent factor coefficients in Guizhou Province, China, and establishes accounting indicators for Karst scenic areas. It is found that the total economic value of ESs is as follows: Shanmuhe Scenic Area (CNY 5096.3 thousand) > DaXiaoQiKong Scenic Area (CNY 2778.6 thousand) > Huangguoshu Scenic Area (CNY 2130.7 thousand). Among them, the value of regulating services plays a dominant role in the composition of ESs, and the value of forests accounts for the largest proportion. Through web crawlers, tourism data can be acquired, and the Product–Experience–Feedback–Improvement (PEFI) model can be applied to reveal that tourists have a predominantly positive perception of Karst scenic areas. This indicates that karst landscape resources are deeply loved by domestic and foreign tourists, especially mountain, water and forest landscapes. Based on the results of the ES value accounting of the scenic area and the external perception data of tourists towards the scenic area, the eco-industry spatial layout development plan is formulated. According to local conditions, the development, construction, and protection of the scenic area are carried out, jointly promoting the realization of the ecological product value (EPV) of the Karst scenic area, to determine the optimal development direction of the eco-industry, and to promote the coordinated development of ecological resources and assets.
Plant-Based Alternatives Need Not Be Inferior: Findings from a Sensory and Consumer Research Case Study with Cream Cheese
Authors: Jaeger Sara R. , Jin David , Roigard Christina M.
Published: February 2024

Reliance on animal foods must be reduced to improve planetary and human well-being. This research studied plant-based cheese alternatives (PBCA) relative to dairy cheese in a consumer taste test with 157 consumers in New Zealand. A case study approach used cream cheese (commercially available) as the focal product category (2 PBCA, 2 dairy) and implemented a multi-response paradigm (hedonic, sensory, emotional, conceptual, situational). “Beyond liking” insights were established, including drivers of liking (sensory, non-sensory) and sensory drivers of non-sensory product associations. Two consumer segments were identified, of which the largest (n = 111) liked PBCA and dairy samples equally (6.5–6.7 of 9). In this PBCA Likers cluster, the key sensory drivers of liking were ‘creamy/smooth mouthfeel’, ‘dissolves quickly in mouth’, and ‘sweet’, while a significant penalty was associated with ‘mild/bland flavour’. The non-sensory data contributed additional consumer insights, including the four samples being perceived as differently appropriate for 9 of 12 use situations, with PBCA being regarded as less appropriate. In the limited confines of this case on cream cheese, the findings show that PBCA need not be inferior to their dairy counterparts despite a general narrative to the contrary. Of note, the results were obtained among participants who were open to eating a more PB diet but were not vegetarian or vegan.
Production of Novel Bigels from Cold Pressed Chia Seed Oil By-Product: Application in Low-Fat Mayonnaise
Authors: Alkabaa Abdulaziz S. , Akcicek Alican , Taylan Osman , Balubaid Mohammed , Alamoudi Mohammed , Gulzar Waqar Ahmad , Alidrisi Hisham , Dertli Enes , Karasu Salih
Published: February 2024

The objective of this study was to produce an innovative bigel formulation by combining glycerol monostearate (GMS) oleogel with hydrogels stabilized by various agents, including cold pressed chia seed oil by-product gum (CSG), gelatin (G), and whey protein concentrate (WPC). The findings indicated that the choice of hydrogel influenced the rheological, textural, and microstructural properties of the bigels. The G′ value of the bigel samples was higher than G″, indicating that all the bigels exhibited solid-like characteristics. In order to numerically compare the dynamic rheological properties of the samples, K′ and K″ values were calculated using the power law model. K′ values of the samples were found to be higher than K″ values. The K′ value of bigel samples was significantly affected by the hydrogel (HG)/oleogel ratio (OG) and the type of stabilizing agent used in the hydrogel formulation. As the OG ratio of bigel samples increased, the K′ value increased significantly (p < 0.05). The texture values of the samples were significantly affected by the HG/OG ratio (p < 0.05). The study’s findings demonstrated that utilizing CSG, G, and WPC at an OG ratio more than 50% can result in bigels with the appropriate hardness and solid character. The low-fat mayonnaise was produced by using these bigels. The low-fat mayonnaise showed shear-thinning and solid-like behavior with G′ values greater than the G″ values. Low-fat mayonnaise produced with CSG bigels (CSGBs) showed similar rheological properties to the full-fat mayonnaise. The results showed that CSG could be used in a bigel formulation as a plant-based gum and CSGB could be used as a fat replacer in low-fat mayonnaise formulation.
Food Behaviour and Metabolic Characteristics of Children and Adolescents with Type 1 Diabetes: Relationship to Glycaemic Control
Authors: Catamo Eulalia , Tornese Gianluca , Dovc Klemen , Tinti Davide , Di Tonno Raffaella , Cauvin Vittoria , Barbi Egidio , Franceschi Roberto , Bonfanti Riccardo , Rabbone Ivana , Battelino Tadej , Robino Antonietta
Published: February 2024

Diet is an essential element of treating and managing type 1 diabetes (T1D). However, limited research has examined food behaviour in children and adolescents with T1D and their relationship to glycaemic control. This study evaluated food behaviour, metabolic characteristics and their impact on the glycaemic control of children and adolescents with T1D. Two hundred and fifty-eight participants with T1D (6–15 years, duration of diabetes >1 year) were recruited. Demographic, anthropometric and clinical data were collected. Questionnaires on food neophobia and food preferences were administered. The Child Food Questionnaire (CFQ) also assessed parental feeding practices. An analysis of food behaviour showed that food neophobia was inversely associated with the liking of vegetables, fruits, fish, sweets and carbohydrates. Moreover, by analysing parental feeding practices, an inverse association of “Pressure to eat”, “Monitoring” and “Restriction” with liking for vegetables and carbohydrates emerged. Considering glycaemic control, increased food neophobia and the parent practices “Restriction”, “Pressure to eat” and “Concern about weight” were found in participants with glycated haemoglobin (HbA1c) values >8.5%. Finally, higher body mass index (BMI) and total cholesterol values were observed in subjects with HbA1c values >8.5%. These findings contribute to a better understanding of eating behaviour, metabolic status and their complex relationship with glycaemic control.
Ibuprofen-Loaded Silver Nanoparticle-Doped PVA Gels: Green Synthesis, In Vitro Cytotoxicity, and Antibacterial Analyses
Authors: Altınay Ezgi , Köse Fatma Zehra , Ateş Sezen Canım , Kızılbey Kadriye
Published: February 2024

In contrast to conventional drug delivery systems, controlled drug release systems employ distinct methodologies. These systems facilitate the release of active substances in predetermined quantities and for specified durations. Polymer hydrogels have gained prominence in controlled drug delivery because of their unique swelling–shrinkage behavior and ability to regulate drug release. In this investigation, films with a hydrogel structure were crafted using polyvinyl alcohol, a biocompatible polymer, and silver nanoparticles. Following characterization, ibuprofen was loaded into the hydrogels to evaluate their drug release capacity. The particle sizes of silver nanoparticles synthesized using a green approach were determined. This study comprehensively examined the structural properties, morphological features, mechanical strength, and cumulative release patterns of the prepared films. In vitro cytotoxicity analysis was employed to assess the cell viability of drug-loaded hydrogel films, and their antibacterial effects were examined. The results indicated that hydrogel films containing 5% and 10% polyvinyl alcohol released 89% and 97% of the loaded drug, respectively, by day 14. The release kinetics fits the Korsmeyer–Peppas model. This study, which describes nanoparticle-enhanced polyvinyl alcohol hydrogel systems prepared through a cost-effective and environmentally friendly approach, is anticipated to contribute to the existing literature and serve as a foundational study for future research.
Evaluation of Fused Deposition Modeling Materials for 3D-Printed Container of Dosimetric Polymer Gel
Authors: Lee Minsik , Noh Seonyeong , Shin Jun-Bong , Kwak Jungwon , Jeong Chiyoung
Published: February 2024

Accurate dosimetric verification is becoming increasingly important in radiotherapy. Although polymer gel dosimetry may be useful for verifying complex 3D dose distributions, it has limitations for clinical application due to its strong reactivity with oxygen and other contaminants. Therefore, it is important that the material of the gel storage container blocks reaction with external contaminants. In this study, we tested the effect of air and the chemical permeability of various polymer-based 3D printing materials that can be used as gel containers. A methacrylic acid, gelatin, and tetrakis (hydroxymethyl) phosphonium chloride gel was used. Five types of printing materials that can be applied to the fused deposition modeling (FDM)-type 3D printer were compared: acrylonitrile butadiene styrene (ABS), co-polyester (CPE), polycarbonate (PC), polylactic acid (PLA), and polypropylene (PP) (reference: glass vial). The map of R2 (1/T2) relaxation rates for each material, obtained from magnetic resonance imaging scans, was analyzed. Additionally, response histograms and dose calibration curves from the R2 map were evaluated. The R2 distribution showed that CPE had sharper boundaries than the other materials, and the profile gradient of CPE was also closest to the reference vial. Histograms and dose calibration showed that CPE provided the most homogeneous and the highest relative response of 83.5%, with 8.6% root mean square error, compared with the reference vial. These results indicate that CPE is a reasonable material for the FDM-type 3D printing gel container.
Recent Developments in 3D-(Bio)printed Hydrogels as Wound Dressings
Authors: Kammona Olga , Tsanaktsidou Evgenia , Kiparissides Costas
Published: February 2024

Wound healing is a physiological process occurring after the onset of a skin lesion aiming to reconstruct the dermal barrier between the external environment and the body. Depending on the nature and duration of the healing process, wounds are classified as acute (e.g., trauma, surgical wounds) and chronic (e.g., diabetic ulcers) wounds. The latter take several months to heal or do not heal (non-healing chronic wounds), are usually prone to microbial infection and represent an important source of morbidity since they affect millions of people worldwide. Typical wound treatments comprise surgical (e.g., debridement, skin grafts/flaps) and non-surgical (e.g., topical formulations, wound dressings) methods. Modern experimental approaches include among others three dimensional (3D)-(bio)printed wound dressings. The present paper reviews recently developed 3D (bio)printed hydrogels for wound healing applications, especially focusing on the results of their in vitro and in vivo assessment. The advanced hydrogel constructs were printed using different types of bioinks (e.g., natural and/or synthetic polymers and their mixtures with biological materials) and printing methods (e.g., extrusion, digital light processing, coaxial microfluidic bioprinting, etc.) and incorporated various bioactive agents (e.g., growth factors, antibiotics, antibacterial agents, nanoparticles, etc.) and/or cells (e.g., dermal fibroblasts, keratinocytes, mesenchymal stem cells, endothelial cells, etc.).
FGF23 Expression Is a Promising Immunohistochemical Diagnostic Marker for Undifferentiated Pleomorphic Sarcoma of Bone (UPSb)
Authors: Al-Hassi Hafid O. , Ali Naser M. , Cooke Hannah , De Silva Shamini , Brini Anna T. , Babu Pavithra , Sumathi Vaiyapuri , Morris Mark R. , Niada Stefania
Published: February 2024

Background: Undifferentiated pleomorphic sarcoma of bone (UPSb) is a rare primary bone sarcoma that lacks a specific line of differentiation. Distinguishing between UPSb and other malignant bone sarcomas, including dedifferentiated chondrosarcoma and osteosarcoma, is challenging due to their overlapping features. We have previously identified that UPSb tumours have elevated mRNA levels of Fibroblast Growth Factor 23 (FGF23) transcripts compared to other sarcomas including osteosarcoma. In the present study, we evaluated the specificity and practicality of FGF23 immunoreactivity as a specific diagnostic tool to differentiate UPSb tumours from osteosarcomas and dedifferentiated chondrosarcomas. Methods: A total of 10 UPSb, 10 osteosarcoma, and 10 dedifferentiated chondrosarcoma cases (all high-grade), were retrieved and immunohistochemistry for FGF23 was performed. Results: FGF23 protein was expressed at high levels in 80–90% of undifferentiated pleomorphic sarcoma of the bone cases, whereas it was expressed at significantly lower levels in dedifferentiated chondrosarcoma and osteosarcoma cases. A semiquantitative analysis, considering the intensity of immunoreactivity, confirmed significantly elevated FGF23 expression levels in UPSb tissues compared to those observed in osteosarcoma and dedifferentiated chondrosarcoma tissues. Conclusions: The results we present here suggest that FGF23 immunohistochemistry may be a useful tool to aid in differentiating UPSb from morphologically similar malignant bone sarcomas, especially in situations where sampling is restricted and there is limited clinical information available.