bluuebunny/crossref_metadata_2025 huggingface dataset:
Peer Support Needs and Preferences for Digital Peer Navigation among Adolescent and Young Adults with Cancer: A Canadian Cross-Sectional Survey
Authors: Bender Jacqueline L. , Puri Natasha , Salih Sarah , D’Agostino Norma M. , Tsimicalis Argerie , Howard A. Fuchsia , Garland Sheila N. , Chalifour Karine , Drake Emily K. , Marrato Anthony , McKean Nikki L. , Gupta Abha A.
Published: February 2022

Adolescents and young adults (AYA) with cancer desire peer support and require support programs that address their unique needs. This study investigated the need for, and barriers to, peer support and preferences for digital peer navigation among AYA. A cross-sectional survey was administered to AYA, diagnosed with cancer between the ages of 15–39, at a cancer center and through social media. Descriptive summary statistics were calculated. Participants (n = 436) were on average 31.2 years (SD = 6.3), 3.3 years since-diagnosis (SD = 3.8), and 65% (n = 218) were women. Over three-quaters (n = 291, 76.6%) desired peer support from cancer peers, but 41.4% (n = 157) had not accessed peer support. Main access barriers were: Inconvenience of in-person support groups (n = 284, 76.1%), finding AYA with whom they could relate (n = 268, 72.4%), and finding AYA-specific support programs (n = 261, 70.4%). Eighty-two percent (n = 310) desired support from a peer navigator through a digital app, and 63% (n = 231) were interested in being a peer navigator. Participants indicated a greater need for emotional (n = 329, 90.1%) and informational support (n = 326, 89.1%) than companionship (n = 284, 78.0%) or practical support (n = 269, 73.6%) from a peer navigator. Foremost peer matching characteristics were cancer-type (n = 329, 88.4%), specific concerns (n = 317, 86.1%), and age-at-diagnosis (n = 316, 86.1%). A digital peer navigation program was desired by over 80% of a large Canadian sample of AYA and could potentially overcome the barriers AYA experience in accessing peer support. The design of a peer navigation program for AYA should consider the matching characteristics and multidimensional support needs of AYA.
Experiences of People with Cancer from Rural and Remote Areas of Western Australia Using Supported Accommodation in Perth While Undergoing Treatment
Authors: Chua Andrette , Nguyen Evelyn , Puah Li Lin , Soong Justin , Keesing Sharon
Published: February 2022

The aim of the study was to explore the lived experiences of people diagnosed with cancer from rural and remote areas of Western Australia, who utilise supported accommodation services whilst undergoing treatment in the capital city (Perth). Methods A qualitative phenomenological approach was used in this study. Ten participants were recruited using purposive sampling, who were aged between 35–65 years, were diagnosed with cancer within the previous three months and used accommodation services within the past 12 months. Semi-structured in-depth interviews were conducted with a duration of approximately 45–60 min via Zoom, FaceTime or phone call. Interview data was transcribed, thematically analysed and coded into relevant themes. Results: Three overarching themes were derived from the interviews–“It’s harder to have cancer when you have to relocate for treatment,” “The paradoxical experience of staying at the accommodation,” and “Feeling grateful for the support offered’. Conclusions: People diagnosed with cancer who have to relocate during treatment require emotional, logistical, and social supports. Cancer accommodation services are essential in enabling individuals to continue engaging in meaningful occupations and maintain their quality of life. Our study highlights the need for cancer accommodation services to consider the complex needs of individuals completing treatment for cancer in locations away from their usual homes.
Inertial Measurement Units (IMUs) in Mobile Robots over the Last Five Years: A Review
Authors: Samatas Gerasimos G. , Pachidis Theodore P.
Published: February 2022

Robots and especially mobile robots have experienced rapid growth, making them part of everyday life. An inertial measurement unit (IMU), which is a set of sensors, plays an important role in mobile robots’ navigation. Data collected by the IMU sensors on a robot are properly converted and useful information is calculated concerning, i.e., position, orientation, and acceleration. With the advancement of technology, IMUs have been transformed from large and complex devices into small, flexible, and efficient ones. The main sensors included in an IMU are the gyroscope, the accelerometer, and the magnetometer. Additionally, there are other sensors such as a barometer, a temperature sensor, a pressure sensor, or even an attitude sensor. The components that an IMU consists of are many and the main differences concern the technology they integrate, the designer purpose, and the specifications set by the manufacturer. The purpose of this review is a comparative presentation of 42 IMU models from 7 different manufacturers over the last five years comparing main features such as structure details, connectivity, and communication protocols. Moreover, statistical results are quantitatively and qualitatively presented providing a future user the possibility to select the proper IMU.
Visual Assessment of Blood Plasma versus Optical Transmittance and Refractive Index Measurements for Quantifying Lipemia
Authors: Márquez-Islas Roberto , Pérez-Pacheco Argelia , Quispe-Siccha Rosa , Salazar-Nieva Laura Beatriz , García-Valenzuela Augusto
Published: February 2022

Today, visual classification of the degree of lipemia in blood samples is frequently performed in clinical laboratories. However, achieving standardization of this classification at low cost and with fewer resources is an objective that is still under development. In this work, a comparison is made between the visual inspection and optical measurements of blood plasma for quantifying lipemia. The plasma refractive index’s real part was measured using an Abbe refractometer and transmittance measurements were made at a 589 nm wavelength and wavelengths ranging from 320 to 1100 nm in the spectral region, respectively. Taking the slope of the transmittance spectrum at two specific wavelengths, it is possible to establish a more standardized selection criterion and implement it quickly using low-cost optical devices. Furthermore, using the proposed transmittance-spectrum-slope method, statistically significant differences (p < 0.05) were found between healthy blood samples and lipemia 1, 2, 3, and 4. However, there were no statistical differences between lipemia 1 and 2.
High-Density UAV-LiDAR in an Integrated Crop-Livestock-Forest System: Sampling Forest Inventory or Forest Inventory Based on Individual Tree Detection (ITD)
Authors: Corte Ana , da Cunha Neto Ernandes , Rex Franciel , Souza Deivison , Behling Alexandre , Mohan Midhun , Sanquetta Mateus , Silva Carlos , Klauberg Carine , Sanquetta Carlos , Veras Hudson , de Almeida Danilo , Prata Gabriel , Zambrano Angelica , Trautenmüller Jonathan , de Moraes Anibal , Karasinski Mauro , Broadbent Eben
Published: February 2022

Lidar point clouds have been frequently used in forest inventories. The higher point density has provided better representation of trees in forest plantations. So we developed a new approach to fill this gap in the integrated crop-livestock-forest system, the sampling forest inventory, which uses the principles of individual tree detection applied under different plot arrangements. We use a UAV-lidar system (GatorEye) to scan an integrated crop-livestock-forest system with Eucalyptus benthamii seed forest plantations. On the high density UAV-lidar point cloud (>1400 pts. m2), we perform a comparison of two forest inventory approaches: Sampling Forest Inventory (SFI) with circular (1380 m2 and 2300 m2) and linear (15 trees and 25 trees) plots and Individual Tree Detection (ITD). The parametric population values came from the approach with measurements taken in the field, called forest inventory (FI). Basal area and volume estimates were performed considering the field heights and the heights measured in the LiDAR point clouds. We performed a comparison of the variables number of trees, basal area, and volume per hectare. The variables by scenarios were submitted to analysis of variance to verify if the averages are considered different or equivalent. The RMSE (%) were calculated to explain the deviation between the measured volume (filed) and estimated volume (LiDAR) values of these variables. Additionally, we calculated rRMSE, Standard error, AIC, R2, Bias, and residual charts. The basal area values ranged from 7.40 m2 ha−1 (C1380) to 8.14 m2 ha−1 281 (C2300), about −5.9% less than the real value (8.65 m2 ha−1). The C2300 scenario was the only one whose confidence interval (CI) limits included the basal area real. For the total stand volume, the ITD scenario was the one that presented the closer values (689.29 m3) to the real total value (683.88 m3) with the real value positioned in the CI. Our findings indicate that for the stand conditions under study, the SFI approach (C2300) that considers an area of 2300 m2 is adequate to generate estimates at the same level as the ITD approach. Thus, our study should be able to assist in the selection of an optimal plot size to generate estimates with minimized errors and gain in processing time.
A Bounded Measure for Estimating the Benefit of Visualization (Part II): Case Studies and Empirical Evaluation
Authors: Chen Min , Abdul-Rahman Alfie , Silver Deborah , Sbert Mateu
Published: February 2022

Many visual representations, such as volume-rendered images and metro maps, feature a noticeable amount of information loss due to a variety of many-to-one mappings. At a glance, there seem to be numerous opportunities for viewers to misinterpret the data being visualized, hence, undermining the benefits of these visual representations. In practice, there is little doubt that these visual representations are useful. The recently-proposed information-theoretic measure for analyzing the cost–benefit ratio of visualization processes can explain such usefulness experienced in practice and postulate that the viewers’ knowledge can reduce the potential distortion (e.g., misinterpretation) due to information loss. This suggests that viewers’ knowledge can be estimated by comparing the potential distortion without any knowledge and the actual distortion with some knowledge. However, the existing cost–benefit measure consists of an unbounded divergence term, making the numerical measurements difficult to interpret. This is the second part of a two-part paper, which aims to improve the existing cost–benefit measure. Part I of the paper provided a theoretical discourse about the problem of unboundedness, reported a conceptual analysis of nine candidate divergence measures for resolving the problem, and eliminated three from further consideration. In this Part II, we describe two groups of case studies for evaluating the remaining six candidate measures empirically. In particular, we obtained instance data for (i) supporting the evaluation of the remaining candidate measures and (ii) demonstrating their applicability in practical scenarios for estimating the cost–benefit of visualization processes as well as the impact of human knowledge in the processes. The real world data about visualization provides practical evidence for evaluating the usability and intuitiveness of the candidate measures. The combination of the conceptual analysis in Part I and the empirical evaluation in this part allows us to select the most appropriate bounded divergence measure for improving the existing cost–benefit measure.
A Confidential QR Code Approach with Higher Information Privacy
Authors: Lin Pei-Yu , Lan Wen-Shao , Chen Yi-Hui , Wu Wen-Chuan
Published: February 2022

In present times, barcode decoders on mobile phones can extract the data content of QR codes. However, this convenience raises concerns about security issues when using QR codes to transmit confidential information, such as e-tickets, coupons, and other private data. Moreover, current secret hiding techniques are unsuitable for QR code applications since QR codes are module-oriented, which is different from the pixel-oriented hiding manner. In this article, we propose an algorithm to conceal confidential information by changing the modules of the QR Code. This new scheme designs the triple module groups based on the concept of the error correction capability. Additionally, this manner can conceal two secret bits by changing only one module, and the amount of hidden confidential information can be twice the original amount. As a result, the ordinary data content (such as URL) can be extracted correctly from the generated QR code by any barcode decoders, which does not affect the readability of scanning. Furthermore, only authorized users with the secret key can further extract the concealed confidential information. This designed scheme can provide secure and reliable applications for the QR system.
BMEFIQA: Blind Quality Assessment of Multi-Exposure Fused Images Based on Several Characteristics
Authors: Shi Jianping , Li Hong , Zhong Caiming , He Zhouyan , Ma Yeling
Published: February 2022

A multi-exposure fused (MEF) image is generated by multiple images with different exposure levels, but the transformation process will inevitably introduce various distortions. Therefore, it is worth discussing how to evaluate the visual quality of MEF images. This paper proposes a new blind quality assessment method for MEF images by considering their characteristics, and it is dubbed as BMEFIQA. More specifically, multiple features that represent different image attributes are extracted to perceive the various distortions of MEF images. Among them, structural, naturalness, and colorfulness features are utilized to describe the phenomena of structure destruction, unnatural presentation, and color distortion, respectively. All the captured features constitute a final feature vector for quality regression via random forest. Experimental results on a publicly available database show the superiority of the proposed BMEFIQA method to several blind quality assessment methods.
Methodology to Differentiate Legume Species in Intercropping Agroecosystems Based on UAV with RGB Camera
Authors: Parra Lorena , Mostaza-Colado David , Marin Jose F. , Mauri Pedro V. , Lloret Jaime
Published: February 2022

Mixed crops are one of the fundamental pillars of agroecological practices. Row intercropping is one of the mixed cropping options based on the combination of two or more species to reduce their impacts. Nonetheless, from a monitoring perspective, the coexistence of different species with different characteristics complicates some processes, requiring a series of adaptations. This article presents the initial development of a procedure that differentiates between chickpea, lentil, and ervil in an intercropping agroecosystem. The images have been taken with a drone at the height of 12 and 16 m and include the three crops in the same photograph. The Vegetation Index and Soil Index are used and combined. After generating the index, aggregation techniques are used to minimize false positives and false negatives. Our results indicate that it is possible to differentiate between the three crops, with the difference between the chickpea and the other two legume species clearer than that between the lentil and the ervil in images gathered at 16 m. The accuracy of the proposed methodology is 95% for chickpea recognition, 86% for lentils, and 60% for ervil. This methodology can be adapted to be applied in other crop combinations to improve the detection of abnormal plant vigour in intercropping agroecosystems.
AEI-DNET: A Novel DenseNet Model with an Autoencoder for the Stock Market Predictions Using Stock Technical Indicators
Authors: Albahli Saleh , Nazir Tahira , Mehmood Awais , Irtaza Aun , Alkhalifah Ali , Albattah Waleed
Published: February 2022

Predicting stock market prices is an important and interesting task in academic and financial research. The volatile nature of the stock market means that predicting stock market prices is a challenging task. However, recent advancements in machine learning, especially in deep learning techniques, have made it possible for researchers to use such techniques to predict future stock trends based on historical financial data, social media news, financial news, and stock technical indicators (STIs). This work focused on the prediction of closing stock prices based on using ten years of Yahoo Finance data of ten renowned stocks and STIs by using 1D DenseNet and an autoencoder. The calculated STIs were first used as the input for the autoencoder for dimensionality reduction, resulting in less correlation between the STIs. These STIs, along with the Yahoo finance data, were then fed into the 1D DenseNet. The resultant features obtained from the 1D DenseNet were then used as input for the softmax layer residing inside the 1D DenseNet framework for the prediction of closing stock prices for short-, medium-, and long-term perspectives. Based on the predicted trends of the stock prices, our model presented the user with one of three suggested signals, i.e., buy, sell, or hold. The experimental results showed that the proposed approach outperformed the state-of-the-art techniques by obtaining a minimum MAPE value of 0.41.
Lattice Spacing, Morphology, Properties, and Quasi—In Situ Impedance of Ternary Lithium-Ion Batteries at a Low Temperature
Authors: Zhang Mingsai , Fu Ping , Wu Junfei , Wang Hao
Published: February 2022

The study about the low-temperature performance of lithium-ion batteries (LIB) is of great significance at extreme temperatures, such as polar scientific research, space exploration, deep-sea exploration, military fields, and so on. In this study, normal devices and symmetrical devices were fabricated by ternary Li(Ni0.5Mn0.3Co0.2)O2 as cathode and graphite as anode at 25 and −20 °C. The results show that the specific discharge capacity of normal device is up to 120 mAh g−1 at 1 C and 25 °C. The specific capacity and energy density at 0.2 C and −20 °C are 106.05 mAh g−1 and 376.53 mWh g−1, respectively, which can reach 92.82% of that at 1 C and 25 °C. The value of activation energy Ea of the interface reaction of the LIB is calculated to be 63.72 kJ/mol by the Arrhenius equation. When the temperature dropped from 25 to −20 °C, the lattice spacing of Li1−x(Ni0.5Mn0.3Co0.2)O2 hardly changed, while the lattice spacing (002) of graphite reduces 0.00248 Å. In addition, some cracks were observed on the charged cathode at −20 °C. We carried out quasi-in situ electrochemical impedance spectroscopy (EIS) when the voltages of normal device discharged to 3.8, 3.6, 3.4, 3.2, and 3.0 V. Unlike the relationship of voltage–resistance at 25 °C, the values of the series resistance (Rs), charge transfer resistance (Rct), and ion transfer resistance (Rit) gradually decrease as the voltage decreases at −20 °C. Compared with the resistance of the symmetrical device based on the anode at 25 °C, the values of Rs and Rit at −20 °C both obviously increase. The main reason of performance degradation for normal device at −20 °C is large ion transfer resistance and the decrease of lattice spacing of the graphite (002).
Study of Parameters and Theory of Sucrose Dust Explosion
Authors: Jiang Juju , Li Xiaoquan , Liang Siting , Zhong Yuankun , Yang Lei , Hao Peng , Soar Jeffrey
Published: February 2022

To investigate the parameters of sucrose dust explosion, the minimum ignition energy (MIE) and minimum ignition temperature (MIT) were evaluated. The experiments tested the MIE of sucrose dust under different conditions of dust quantity, ignition delay time (IDT), and powder injection pressure (PIP). The experiments tested the MIT of different particle sizes. The results demonstrate that the MIE of sucrose powder under three conditions was an open-up quadratic polynomial. When the dust quantity, the IDT, and PIP were 0.5 g (417 g/m3), 90 ms, and 150 kPa, respectively, the MIE was 58.9 mJ, 62.6 mJ, and 52.4 mJ. The MIT was positively correlated with the particle size of sucrose dust, and the MIT was 340 °C. At the molecular level, the “O–H” bonds of the sucrose molecule hydroxyl groups were broken by the discharge of electrodes or high temperature to generate H2. The combustion of H2 caused the explosion to spread to the surrounding sucrose dust and made the deposited dust rise, forming an interlocking explosion. The explosion would not stop until the dust concentration dropped below the lowest explosion limit. The results of this study can provide guidance for sucrose enterprises to prevent dust explosion accidents.
Modeling and Simulation of Batch Sugarcane Alcoholic Fermentation Using the Metabolic Model
Authors: Acorsi Renam Luis , De Giovanni Matheus Yuri Gritzenco , Olivo José Eduardo , Andrade Cid Marcos Gonçalves
Published: February 2022

The present work sought to implement a model different from the more traditional ones for the fermentation process of ethanol production by the action of the fungus Saccharomyces cerevisiae, using a relevant metabolic network based on the glycolytic Embden–Meyerhof–Parnas route, also called “EMP”. We developed two models to represent this phenomenon. In the first model, we used the simple and unbranched EMP route, with a constant concentration of microorganisms throughout the process and glucose as the whole substrate. We called this first model “SR”, regarding the Portuguese name “sem ramificações”, which means “no branches”. We developed the second model by simply adding some branches to the SR model. We called this model “CR”, regarding the Portuguese name “com ramificações”, which means “with branches”. Both models were implemented in MATLABTM software considering a constant temperature equal to 32 °C, similar to that practiced in sugar and ethanol plants, and a wide range of substrate concentrations, ranging from 30 to 100 g/L, and all the enzymes necessary for fermentation were already expressed in the cells so all the enzymes showed a constant concentration throughout the fermentation. The addition of common branches to the EMP route resulted in a considerable improvement in the results, especially predicting ethanol production closer to what we saw experimentally. Therefore, the results obtained are promising, making adjustments consistent with experimental data, meaning that all the models proposed here are a good basis for the development of future metabolic models of discontinuous fermentative processes.
Maternal Uniparental Isodisomy of Chromosome 4 and 8 in Patients with Retinal Dystrophy: SRD5A3-Congenital Disorders of Glycosylation and RP1-Related Retinitis Pigmentosa
Authors: Tachibana Nobutaka , Hosono Katsuhiro , Nomura Shuhei , Arai Shinji , Torii Kaoruko , Kurata Kentaro , Sato Miho , Shimakawa Shuichi , Azuma Noriyuki , Ogata Tsutomu , Wada Yoshinao , Okamoto Nobuhiko , Saitsu Hirotomo , Nishina Sachiko , Hotta Yoshihiro
Published: February 2022

Purpose: Uniparental disomy (UPD) is a rare chromosomal abnormality. We performed whole-exosome sequencing (WES) in cases of early-onset retinal dystrophy and identified two cases likely caused by UPD. Herein, we report these two cases and attempt to clarify the clinical picture of retinal dystrophies caused by UPD. Methods: WES analysis was performed for two patients and their parents, who were not consanguineous. Functional analysis was performed in cases suspected of congenital disorders of glycosylation (CDG). We obtained clinical case data and reviewed the literature. Results: In case 1, a novel c.57G>C, p.(Trp19Cys) variant in SRD5A3 was detected homozygously. Genetic analysis suggested a maternal UPD on chromosome 4, and functional analysis confirmed CDG. Clinical findings showed early-onset retinal dystrophy, intellectual disability, and epilepsy. In case 2, an Alu insertion (c.4052_4053ins328, p.[Tyr1352Alafs]) in RP1 was detected homozygously. Maternal UPD on chromosome 8 was suspected. The clinical picture was consistent with RP1-related retinitis pigmentosa. Although the clinical features of retinal dystrophy by UPD may vary, most cases present with childhood onset. Conclusions: There have been limited reports of retinal dystrophy caused by UPD, suggesting that it is rare. Genetic counseling may be encouraged in pediatric cases of retinal dystrophy.
Hematological Ratios Are Associated with Acute Kidney Injury and Mortality in Patients That Present with Suspected Infection at the Emergency Department
Authors: de Hond Titus A. P. , Ocak Gurbey , Groeneweg Leonie , Oosterheert Jan Jelrik , Haitjema Saskia , Khairoun Meriem , Kaasjager Karin A. H.
Published: February 2022

The early recognition of acute kidney injury (AKI) is essential to improve outcomes and prevent complications such as chronic kidney disease, the need for renal-replacement therapy, and an increased length of hospital stay. Increasing evidence shows that inflammation plays an important role in the pathophysiology of AKI and mortality. Several inflammatory hematological ratios can be used to measure systemic inflammation. Therefore, the association between these ratios and outcomes (AKI and mortality) in patients suspected of having an infection at the emergency department was investigated. Data from the SPACE cohort were used. Cox regression was performed to investigate the association between seven hematological ratios and outcomes. A total of 1889 patients were included, of which 160 (8.5%) patients developed AKI and 102 (5.4%) died in <30 days. The Cox proportional-hazards model revealed that the neutrophil-to-lymphocyte ratio (NLR), segmented-neutrophil-to-monocyte ratio (SMR), and neutrophil-lymphocyte-platelet ratio (NLPR) are independently associated with AKI <30 days after emergency-department presentation. Additionally, the NLR, SMR and NLPR were associated with 30-day all-cause mortality. These findings are an important step forward for the early recognition of AKI. The use of these markers might enable emergency-department physicians to recognize and treat AKI in an early phase to potentially prevent complications.
Prediction of Acute Kidney Injury by Cystatin C and [TIMP-2]*[IGFBP7] after Thoracic Aortic Surgery with Moderate Hypothermic Circulatory Arrest
Authors: Pilarczyk Kevin , Panholzer Bernd , Huenges Katharina , Salem Mohamed , Jacob Toni , Cremer Jochen , Haneya Assad
Published: February 2022

(1) Background: Acute kidney injury (AKI) is a common complication following thoracic aortic surgery (TAS), with moderate hypothermic circulatory arrest (MHCA). However, prediction of AKI with classical tools remains uncertain. Therefore, it was the aim of the present study to evaluate the role of new biomarkers in patients after MHCA. (2) Methods: 101 consecutive patients were prospectively enrolled. Measurements of urinary [TIMP-2]*[IGFBP7] and Cystatin C in the blood were performed perioperatively. Primary endpoint was the occurrence of AKI stage 2 or 3 (KDIGO-classification) within 48 h after surgery (AKI group). (3) Results: Mean age of patients was 69.1 ± 10.9 years, 35 patients were female (34%), and 13 patients (13%) met the primary endpoint. Patients in the AKI group had a prolonged ICU-stay (6.9 ± 7.4 days vs. 2.5 ± 3.1 days, p < 0.001) as well as a higher 30-day-mortality (9/28 vs. 1/74, p < 0.001). Preoperative serum creatinine (169.73 ± 148.97 μmol/L vs. 89.74 ± 30.04 μmol/L, p = 0.027) as well as Cystatin C (2.41 ± 1.54 mg/L vs. 1.13 ± 0.35 mg/L, p = 0.029) were higher in these patients. [TIMP-2]*[IGFBP7] increased significantly four hours after surgery (0.6 ± 0.69 mg/L vs. 0.37 ± 0.56 mg/L, p = 0.03) in the AKI group. Preoperative Cystatin C (AUC 0.828, p < 0.001) and serum creatinine (AUC 0.686, p = 0.002) as well as [TIMP-2]*[IGFBP7] 4 h after surgery (AUC 0.724, p = 0.020) were able to predict postoperative AKI. The predictive capacity of Cystatin C was superior to serum creatinine (p = 0.0211) (4) Conclusion: Cystatin C represents a very sensitive and specific biomarker to predict AKI in patients undergoing thoracic surgery with MHCA even before surgery, whereas the predictive capacity of [TIMP-2]*[IGFBP7] is only moderate and inferior to that of serum creatinine.
Build Surface Roughness and Internal Oxide Concentration for Laser Powder Bed Fusion of IN718
Authors: Smith Lonnie A. , Pistorius Petrus Christiaan
Published: February 2022

Oxidation of hot spatter during laser powder bed fusion results in the deposition of oxides on the build surface. In the case of IN718—as studied in this work—the oxide is alumina. While some of this surface oxide may be incorporated in the build, an oxygen mass balance indicates some oxygen removal during the building process. This work tested an expected effect of the roughness of the build surface on the concentration of micron-sized oxide inclusions that are incorporated in test coupons during building. The roughness of the build surface responded to changes in hatch spacing, in line with a simple geometric model of the overlap between adjacent beads. Samples with deeper grooves retained more oxide, resulting in a much larger concentration of oxide inclusions within the samples. The conclusion is that parts with lower inclusion concentrations can be produced by decreasing the hatch spacing, at the cost of a lower build rate.
Multi-Omics Characterization of a Human Stem Cell-Based Model of Cardiac Hypertrophy
Authors: Johansson Markus , Ulfenborg Benjamin , Andersson Christian X. , Heydarkhan-Hagvall Sepideh , Jeppsson Anders , Sartipy Peter , Synnergren Jane
Published: February 2022

Cardiac hypertrophy is an important and independent risk factor for the development of cardiac myopathy that may lead to heart failure. The mechanisms underlying the development of cardiac hypertrophy are yet not well understood. To increase the knowledge about mechanisms and regulatory pathways involved in the progression of cardiac hypertrophy, we have developed a human induced pluripotent stem cell (hiPSC)-based in vitro model of cardiac hypertrophy and performed extensive characterization using a multi-omics approach. In a series of experiments, hiPSC-derived cardiomyocytes were stimulated with Endothelin-1 for 8, 24, 48, and 72 h, and their transcriptome and secreted proteome were analyzed. The transcriptomic data show many enriched canonical pathways related to cardiac hypertrophy already at the earliest time point, e.g., cardiac hypertrophy signaling. An integrated transcriptome–secretome analysis enabled the identification of multimodal biomarkers that may prove highly relevant for monitoring early cardiac hypertrophy progression. Taken together, the results from this study demonstrate that our in vitro model displays a hypertrophic response on both transcriptomic- and secreted-proteomic levels. The results also shed novel insights into the underlying mechanisms of cardiac hypertrophy, and novel putative early cardiac hypertrophy biomarkers have been identified that warrant further investigation to assess their potential clinical relevance.
Predator-Prey Interactions between Nonnative Juvenile Largemouth Bass (Micropterus salmoides) and Local Candidate Prey Species in the Pearl River Delta: Predation Capacity, Preference and Growth Performance
Authors: Luo Du , Ye Minghao , Yang Dingtian
Published: February 2022

An ontogenetic dietary shift is crucial for the survival and growth of piscivorous largemouth bass (LB). However, there is much to learn about the predator-prey interaction during the switching process. We carried out a series of indoor experiments to examine the predation capacity, predation preference, and growth performance of exotic juvenile LB feeding on candidate prey species in the Pearl River Delta. The widely distributed oriental river prawn (Macrobranchium nipponense), barcheek goby (Ctenogobius giurinus), western mosquitofish (Gambusia affinis), silver carp (Hypophthalmichthys molitrix), and mud carp (Cirrhinus molitorella), with relatively similar total lengths, were selected as potential prey based on their availability and habitat use. Our results show that predation capacity and preference varied quantitatively and qualitatively among prey species. The number of oriental river prawns killed was significantly less than that of fish species, comparing the 1st hour with the 24th hour (p < 0.01). The feeding rhythm of LB varied significantly from crayfish to fish. Numerically, Jacobs’ selection index reinforced LB’s special preference for predating G. affinis. Although there were obvious variations in predation capacity and feed selection, no statistically significant growth differences were detected among LB groups feeding on live M. nipponense, G. affinis, H. molitrix, and C. molitorella (p < 0.05). These findings suggest that the successful ontogenetic dietary shift of juvenile LB may depend on the availability and vulnerability of local fish species. Further study on the reproductive phenology of potential fish prey may help to predict LB’s establishment.
Advanced Surface Treatment Technologies for Metallic Alloys
Authors: Vizureanu Petrica
Published: February 2022

The main objective of this Special Issue was to publish outstanding papers presenting cutting-edge research in the field of surface treatment technologies for metallic alloys and their understanding [...]
Parallel Tubular Channel Angular Pressing (PTCAP) Processing of the Cu-20.7Zn-2Al Tube
Authors: Abd El Aal Mohamed Ibrahim , Gadallah Elshafey Ahmed
Published: February 2022

Commercial Al-brass tube was successfully processed by Parallel Tubular Channel Angular Pressing (PTCAP) in 2 passes under an imposed strain of 1.49 per pass. The effect of the number of PTCAP passes on the microstructure and the mechanical properties (hardness, tensile, and wear mass loss) of the Al-brass tubes was fully investigated. The average grain size of the as-received tube decreased to 1.28 μm after up to two passes of PTCAP with a mixture of ultrafine grain (UFG) and coarse grain (CG). The annealed tubes’ tensile strength and Vickers hardness increased by 237.65% and 175.6%, respectively, after two passes. In addition, a ductile fracture occurred with a clear necking. The fracture surface morphology indicated an apparent decrease in dimple size after PTCAP processing, combined with a decrease in ductility. Moreover, the wear mass loss decreased with increasing number of PTCAP passes due to the decrease in the grain size, and the increase of the hardness of the tubes was enhanced after PTCAP processing.
Formation and Dissociation of CH4 and CO2 Hydrates in Presence of a Sediment Composed by Pure Quartz Mixed with Ti23 Particles
Authors: Gambelli Alberto Maria , Stornelli Giulia , Di Schino Andrea , Rossi Federico
Published: February 2022

The present research deals with the formation and dissociation of methane and carbon dioxide hydrates in a confined environment (small—size reactor) and in presence of a porous sediment of pure quartz impregnated with Ti23 particles. This research is part of a wider study aimed at verifying the possibility to use metallic powders, produced via gas-atomization for applications in additive manufacturing, as additives during the production/dissociation of gas hydrates. The porous medium was used to ensure the presence of Ti23 particles in the whole volume and not only in the lowest portion of the internal volume. For both the guest compounds considered, two Ti23 concentrations were explored, respectively, 8.68 and 26.04 wt%. Under the thermodynamic point of view, the dissociation process well approximated the phase equilibrium (defined with values collected from literature) for both compounds. In addition, the amount of gas trapped into hydrates, evaluated as a function of the initial amount of gas inserted inside the reactor, did not show relevant changes. Conversely, the presence of Ti23 was found to reduce the induction time for both components, thus allowing to define it as a kinetic promoter for the process. Such tendency was found to increase with the concentration.
Studying the Influence of Silica Fume on Bond Strength of the PCM-Concrete Interface under Shear Stress Condition
Authors: Mizan Mahmudul Hasan , Matsumoto Koji
Published: February 2022

The polymer cement mortar (PCM) overlay method is a promising solution for strengthening deteriorated concrete structures in which the occurrence of premature debonding at the interfaces prevents the strengthened structures from achieving full serviceability. The purpose of this study is to improve the concrete–PCM interfacial bond to prevent premature debonding. There are two main focuses of this study: (i) investigation of the effectiveness of adding 5% silica fume to PCM in forming a chemical connection between concrete and PCM, based on a direct single-surface shear test using two roughness levels of concrete (smooth and rough) and microstructure analysis and (ii) performance evaluation of the bond between substrate concrete and a PCM overlay with/without silica fume at early ages and with different moisture conditions at the interface, based on a bi-surface shear test using rough substrate concrete surface. The inclusion of 5% silica fume with PCM caused an improvement in the interfacial strength (approximately 113% relative to the normal PCM in cases of without primer), with a smooth concrete substrate surface where mechanical bonding had less influence. In addition, lower Ca/Si values in the interface of modified 5% silica PCM specimens compared to the normal PCM specimens quantified by energy-dispersive X-ray spectroscopy (EDS) indicate the formation of a chemical connection at the concrete–PCM interface by transforming harmful Ca(OH)2 into more C-S-H which strongly improves the bonding strength. As a repair layer mortar, the positive influence of silica fume in modified 5% silica PCM specimens was also found at early ages and with different moisture conditions at the interface compared to the normal PCM. In conclusion, the addition of silica fume to the PCM caused chemical connection at the concrete–PCM interface and improved the interfacial performance.
Physicochemical Properties of Dentine Subjected to Microabrasive Blasting and Its Influence on Bonding to Self-Adhesive Prosthetic Cement in Shear Bond Strength Test: An In Vitro Study
Authors: Szerszeń Marcin , Higuchi Julia , Romelczyk-Baishya Barbara , Górski Bartłomiej , Łojkowski Witold , Pakieła Zbigniew , Mierzwińska-Nastalska Elżbieta
Published: February 2022

The aim of this in vitro study was to assess the influence of microabrasive blasting on the physicochemical properties of dentine and shear bond strength (SBS) of self-adhesive resin cement (Maxcem Elite, Kerr, Orange, CA, USA) bonded to the dentine surface. Ninety cylindrical specimens with exposed dentine of human teeth were prepared and divided into three randomized, parallel sample sets A, B, and C. Groups B and C were subjected to abrasive blasting using a micro-sandblasting device (Microetcher IIa, Danville Materials, Carlsbad, CA, USA) with two gradations of Al2O3 abrasives (Group B, abrasion with a gradation of 50 μm; group C, abrasion with a gradation of 27 μm). SEM imaging, profilometry, chemical composition analysis, contact angle measurements, surface free energy, and SBS tests were performed. The resulting data were statistically analyzed using the Statistica software (ver. 13.3, Tibco Software Inc., Palo Alto, CA, USA). Microabrasive blasting caused changes in surface topography, structural features, and the connection strength between the dentin surface and self-adhesive prosthetic cement. Air microabrasion through the multifactorial positive reorganization of the treated surface of dentine is recommended as a pretreatment method in fixed prosthodontics adhesive cementation protocols.
Back-Propagation Neural Network Optimized by K-Fold Cross-Validation for Prediction of Torsional Strength of Reinforced Concrete Beam
Authors: Lyu Zhaoqiu , Yu Yang , Samali Bijan , Rashidi Maria , Mohammadi Masoud , Nguyen Thuc N. , Nguyen Andy
Published: February 2022

Due to the limitation of sample size in predicting the torsional strength of Reinforced Concrete (RC) beams, this paper aims to discuss the feasibility of employing a novel machine learning approach with K-fold cross-validation in a small sample range, which combines the advantages of a Genetic Algorithm (GA) and a Neural Network (NN) to predict the torsional strength of RC beams. This research study not only utilizes the application of a Back Propagation (BP) neural network and the Gene Algorithm-Back Propagation (GA-BP) neural network in the prediction of the torsional strength of the RC beam, but it also investigates neural network parameter optimization, including connection weights and thresholds, using K-fold cross-validation. The root mean square error (RMSE), mean absolute error (MAE), mean square error (MSE), mean absolute percentage error (MAPE) and correlation coefficient (R2) are among the evaluation metrics used to assess the performance of the trained model. To elaborate on the superiority of the proposed network models in predicting the torsional strength of RC beams, a parametric study is conducted by comparing the proposed model to three commonly used empirical formulae from existing design codes. The comparative findings of this research study demonstrate that the performance of the BP neural network is highly similar to that of design codes; however, its accuracy is inadequate. After improving the weights and thresholds by k-fold cross-validation and GA, the prediction of the BP neural network shows higher consistency with the actual measured values. The outcome of this study can be used as a theoretical reference for the optimal design of RC beams in practical applications.
Local Coordination Environment of 3d and 4d Transition Metal Ions in LiCl-KCl Eutectic Mixture
Authors: Fuller Jon , Phillips William , An Qi , Gakhar Ruchi
Published: February 2022

In this study, the structure and coordination environment of two 3d transition elements (Ni and Cr) is investigated in a molten chloride salt system. Electronic absorption spectroscopy was employed to elucidate their coordination environment in 3LiCl-2KCl eutectic salt, as a function of temperature. Density functional theory (DFT) modeling was used to determine the coordination environment of the transition metal species in the eutectic composition as well as the optical spectra computationally. The Ni2+and Cr3+ exist in a tetrahedral and octahedral coordination environment, respectively, in eutectic salt. The spectra thus obtained were compared with the experimental data; a reasonable qualitative agreement was obtained between experimental and computational Ni2+ and Cr3+spectra, and the coordination of both elements in the eutectic composition were in excellent agreement with the experimentally determined results. Computational results were also obtained for two 4d elements, Mo3+ and Nb3+, with both quantum molecular dynamics (QMD) and hybrid functional optical spectra indicating octahedral coordination.
Positive Effects of a Perovskite Film on the Radioluminescence Properties of a ZnO:Ga Crystal Scintillator
Authors: He Shiyi , Li Yang , Chen Liang , Jin Tong , Liu Linyue , Ruan Jinlu , Ouyang Xiaoping
Published: February 2022

To improve the radioluminescence (RL) performance of ZnO:Ga (GZO) crystal scintillators and overcome the challenge of their self-absorption, we proposed a two-layer composite scintillator consisting of a GZO wafer and a 70 nm lead halide perovskite film(CsPbBr3, CH3NH3PbBr3). The effects of the perovskite film on the RL properties were studied. The results showed that the perovskite quantum dot film substantially changed the RL spectrum of GZO and prevented self-absorption. The RL of the samples were enhanced by 66% to 151% through the photoluminescence (PL) of the perovskite film, while the energy-resolving power and spatial-resolving power were maintained at the same level as that of GZO image converters. The present experiments and discussions confirmed that the perovskite film improved the RL, and this study suggests a new wavelength regulation method among scintillators, converters, and back-end optical devices. The applications of perovskites in the field of radiation detection and imaging have been extended.
Converting Sewage Water into H2 Fuel Gas Using Cu/CuO Nanoporous Photocatalytic Electrodes
Authors: Hadia N. M. A. , Abdelazeez Ahmed Adel A. , Alzaid Meshal , Shaban Mohamed , Mohamed S. H. , Hoex Bram , Hajjiah Ali , Rabia Mohamed
Published: February 2022

This work reports on H2 fuel generation from sewage water using Cu/CuO nanoporous (NP) electrodes. This is a novel concept for converting contaminated water into H2 fuel. The preparation of Cu/CuO NP was achieved using a simple thermal combustion process of Cu metallic foil at 550 °C for 1 h. The Cu/CuO surface consists of island-like structures, with an inter-distance of 100 nm. Each island has a highly porous surface with a pore diameter of about 250 nm. X-ray diffraction (XRD) confirmed the formation of monoclinic Cu/CuO NP material with a crystallite size of 89 nm. The prepared Cu/CuO photoelectrode was applied for H2 generation from sewage water achieving an incident to photon conversion efficiency (IPCE) of 14.6%. Further, the effects of light intensity and wavelength on the photoelectrode performance were assessed. The current density (Jph) value increased from 2.17 to 4.7 mA·cm−2 upon raising the light power density from 50 to 100 mW·cm−2. Moreover, the enthalpy (ΔH*) and entropy (ΔS*) values of Cu/CuO electrode were determined as 9.519 KJ mol−1 and 180.4 JK−1·mol−1, respectively. The results obtained in the present study are very promising for solving the problem of energy in far regions by converting sewage water to H2 fuel.
Efficient Malware Classification by Binary Sequences with One-Dimensional Convolutional Neural Networks
Authors: Lin Wei-Cheng , Yeh Yi-Ren
Published: February 2022

The rapid increase of malware attacks has become one of the main threats to computer security. Finding the best way to detect malware has become a critical task in cybersecurity. Previous work shows that machine learning approaches could be a solution to address this problem. Many proposed methods convert malware executables into grayscale images and apply convolutional neural networks (CNNs) for malware classification. However, converting malware executables into images could twist the one-dimensional structure of binary codes. To address this problem, we explore the bit and byte-level sequences from malware executables and propose efficient one-dimensional (1D) CNNs for the malware classification. Our experiments evaluate our proposed 1D CNN models with two benchmark datasets. Our proposed 1D CNN models achieve better performance from the experimental results than the existing 2D CNNs malware classification models by providing smaller resizing bit/byte-level sequences with less computational cost.