bluuebunny/crossref_metadata_2025 huggingface dataset:
Infrared Thermography in Wound Care, Surgery, and Sports Medicine: A Review
Authors: Ramirez-GarciaLuna Jose L. , Bartlett Robert , Arriaga-Caballero Jesus E. , Fraser Robert D. J. , Saiko Gennadi
Published: March 2022

For many years, the role of thermometry was limited to systemic (core body temperature) measurements (e.g., pulmonary catheter) or its approximation using skin/mucosa (e.g., axillary, oral, or rectal) temperature measurements. With recent advances in material science and technology, thermal measurements went beyond core body temperature measurements and found their way in many medical specialties. The article consists of two primary parts. In the first part we overviewed current clinical thermal measurement technologies across two dimensions: (a) direct vs. indirect and (b) single-point vs. multiple-point temperature measurements. In the second part, we focus primarily on clinical applications in wound care, surgery, and sports medicine. The primary focus here is the thermographic imaging modality. However, other thermal modalities are included where relevant for these clinical applications. The literature review identified two primary use scenarios for thermographic imaging: inflammation-based and perfusion-based. These scenarios rely on local (topical) temperature measurements, which are different from systemic (core body temperature) measurements. Quantifying these types of diseases benefits from thermographic imaging of an area in contrast to single-point measurements. The wide adoption of the technology would be accelerated by larger studies supporting the clinical utility of thermography.
Using Machine Learning Models to Predict Hydroponically Grown Lettuce Yield
Authors: Mokhtar Ali , El-Ssawy Wessam , He Hongming , Al-Anasari Nadhir , Sammen Saad Sh. , Gyasi-Agyei Yeboah , Abuarab Mohamed
Published: March 2022

Prediction of crop yield is an essential task for maximizing the global food supply, particularly in developing countries. This study investigated lettuce yield (fresh weight) prediction using four machine learning (ML) models, namely, support vector regressor (SVR), extreme gradient boosting (XGB), random forest (RF), and deep neural network (DNN). It was cultivated in three hydroponics systems (i.e., suspended nutrient film technique system, pyramidal aeroponic system, and tower aeroponic system), which interacted with three different magnetic unit strengths under a controlled greenhouse environment during the growing season in 2018 and 2019. Three scenarios consisting of the combinations of input variables (i.e., leaf number, water consumption, dry weight, stem length, and stem diameter) were assessed. The XGB model with scenario 3 (all input variables) yielded the lowest root mean square error (RMSE) of 8.88 g followed by SVR with the same scenario that achieved 9.55 g, and the highest result was by RF with scenario 1 (i.e., leaf number and water consumption) that achieved 12.89 g. All model scenarios having Scatter Index (SI) (i.e., RMSE divided by the average values of the observed yield) values less than 0.1 were classified as excellent in predicting fresh lettuce yield. Based on all of the performance statistics, the two best models were SVR with scenario 3 and DNN with scenario 2 (i.e., leaf number, water consumption, and dry weight). However, DNN with scenario 2 requiring less input variables is preferred. The potential of the DNN model to predict fresh lettuce yield is promising, and it can be applied on a large scale as a rapid tool for decision-makers to manage crop yield.
Dual RNA Sequencing Reveals the Genome-Wide Expression Profiles During the Compatible and Incompatible Interactions Between Solanum tuberosum and Phytophthora infestans
Authors: Li Honghao , Hu Rongping , Fan Zhonghan , Chen Qinghua , Jiang Yusong , Huang Weizao , Tao Xiang
Published: March 2022

Late blight, caused byPhytophthora infestans(P. infestans), is a devastating plant disease.P. infestansgenome encodes hundreds of effectors, complicating the interaction between the pathogen and its host and making it difficult to understand the interaction mechanisms. In this study, the late blight-resistant potato cultivar Ziyun No.1 and the susceptible potato cultivar Favorita were infected withP. infestansisolate SCPZ16-3-1 to investigate the global expression profiles during the compatible and incompatible interactions using dual RNA sequencing (RNA-seq). Most of the expressed Arg-X-Leu-Arg (RXLR) effector genes were suppressed during the first 24 h of infection, but upregulated after 24 h. Moreover,P. infestansinduced more specifically expressed genes (SEGs), including RXLR effectors and cell wall-degrading enzymes (CWDEs)-encoding genes, in the compatible interaction. The resistant potato activated a set of biotic stimulus responses and phenylpropanoid biosynthesis SEGs, including kirola-like protein, nucleotide-binding site-leucine-rich repeat (NBS-LRR), disease resistance, and kinase genes. Conversely, the susceptible potato cultivar upregulated more kinase, pathogenesis-related genes than the resistant cultivar. This study is the first study to characterize the compatible and incompatible interactions betweenP. infestansand different potato cultivars and provides the genome-wide expression profiles for RXLR effector, CWDEs, NBS-LRR protein, and kinase-encoding genes.
The Ribosomal DNA Loci of the Ancient Monocot Pistia stratiotes L. (Araceae) Contain Different Variants of the 35S and 5S Ribosomal RNA Gene Units
Authors: Stepanenko Anton , Chen Guimin , Hoang Phuong T. N. , Fuchs Jörg , Schubert Ingo , Borisjuk Nikolai
Published: March 2022

The freshwater plant water lettuce (Pistia stratiotes L.) grows in warm climatic zones and is used for phytoremediation and biomass production. P. stratiotes belongs to the Araceae, an ecologically and structurally diverse early monocot family, but the phylogenetic relationships among Araceae members are poorly understood. Ribosomal DNAs (rDNAs), including the 35S and 5S rDNA, encode the RNA components of ribosomes and are widely used in phylogenetic and evolutionary studies of various plant taxa. Here, we comprehensively characterized the chromosomal locations and molecular organization of 35S and 5S rDNA genes in water lettuce using karyological and molecular methods. Fluorescence in situ hybridization revealed a single location for the 35S and 5S rDNA loci, each on a different pair of the species’ 28 chromosomes. Molecular cloning and nucleotide sequencing of 35S rDNA of P. stratiotes, the first representative Araceae sensu stricto in which such a study was performed, displayed typical structural characteristics. The full-length repeat showed high sequence conservation of the regions producing the 18S, 5.8S, and 25S rRNAs and divergence of the internal transcribed spacers ITS1 and ITS2 as well as the large intergenic spacer (IGS). Alignments of the deduced sequence of 18S rDNA with the sequences available for other Araceae and representatives of other clades were used for phylogenetic analysis. Examination of 11 IGS sequences revealed significant intra-genomic length variability due to variation in subrepeat number, with four types of units detected within the 35S rDNA locus of the P. stratiotes genome (estimated size 407 Mb/1C). Similarly, the 5S rDNA locus harbors gene units comprising a conserved 119-bp sequence encoding 5S rRNA and two types of non-transcribed spacer (NTS) sequences. Type I was classified into four subtypes, which apparently originated via progressive loss of subrepeats within the duplicated NTS region containing the 3’ part of the 5S rRNA gene. The minor Type II NTS is shorter than Type I and differs in nucleotide composition. Some DNA clones containing two or three consecutive 5S rDNA repeats harbored 5S rDNA genes with different types of NTSs, confirming the mosaic composition of the 5S rDNA locus.
Detection and Analysis of Syntenic Quantitative Trait Loci Controlling Cell Wall Quality in Angiosperms
Authors: Pancaldi Francesco , Vlegels Dennis , Rijken Hugo , van Loo Eibertus N. , Trindade Luisa M.
Published: March 2022

Translational genomics can enable a quicker improvement of orphan crops toward novel agricultural applications, including the advancement of orphan biomass species for cultivation on marginal lands. In this sense, cell wall quality is a preeminent breeding target. However, tools to efficiently project genetic data on target traits across large sets of species are currently missing. This study aimed at closing this gap by developing a strategy to project a set of cell wall QTLs across a large group of plants by using genome synteny. This strategy is suited for large-scale analyses and detected 362 syntenic cell wall QTLs (SQTLs) across 74 angiosperms, including several (orphan) biomass species. SQTLs analyses revealed that they span large portions of the initial cell wall QTLs and are extensively conserved across diverse species. Moreover, numerous QTLs cell wall genes were conserved through SQTLs, including genes displaying allelic variation associated with cell wall composition. Functional analyses showed that highly conserved genes of SQTLs include important cell wall transcription factors and genes involved in the remodeling of cell wall polymers. For some of these gene families, SQTLs indicated the presence of differentially conserved genomic contexts for different gene members, highlighting their utility as a tool to pinpoint gene targets that maximize the likelihood of functional gene conservation. Overall, the results of this study can facilitate “universal” approaches for breeding (orphan) biomass crops, while the strategy for QTLs translation can be applied to other sets of traits and species, helping to unlock the potential of orphan species.
Exploration and Strategy Analysis of Mental Health Education for Students in Sports Majors in the Era of Artificial Intelligence
Authors: Liang Liang , Zheng Yong , Ge Qiluo , Zhang Fengrui
Published: March 2022

This study aims to explore new educational strategies suitable for the mental health education of college students. Big data and artificial intelligence (AI) are combined to evaluate the mental health education of college students in sports majors. First, the research status on the mental health education of college students is introduced. The internet of things (IoT) on mental health education, a structure based on big data and convolutional neural network (CNN), is constructed. Next, the survey design and questionnaire survey are carried out. Finally, the questionnaire data are analyzed and compared with the mental health status under traditional education. The results show that the CNN model has good accuracy and ability to distinguish symptoms, so it can be applied to the existing psychological work in colleges. In the symptom comparison survey, under the traditional education and big data network, the number of college students with mild mental health problems is found to be 158 (84.9%) and 170 (91.4%), respectively. It indicates that the number of college students with moderate mental health problems decreases significantly. In the comparative investigation of the severity of mental problems, the number of students with normal mental health, subhealth, and serious mental health problems under the background of traditional mental health education is 125 (67.2%), 56 (30.1%), and 5 (2.7%), respectively. The mental health status of college students under the influence of big data networks on mental health education is better than that of traditional mental health education. There are 140 students with normal mental health, a year-on-year increase of 16.7%. In the comparative survey of specific mental disorders, students with obsessive-compulsive symptoms under traditional mental health education account for 22.0% of the total sample, having the largest proportion. In the subhealth psychological group under the big data network on mental health education, the number of hostile students decreases by 7, which is the psychological factor with the most obvious improvement. Hence, the proposed path of mental health education is feasible.
The Effect of Task Difficulty and Self-Contribution on Fairness Consideration: An Event-Related Potential Study
Authors: Xu Liyan , Wang Biye , Guo Wei
Published: March 2022

Self-contribution may be an influential factor in fairness consideration and consequent behavioral decisions. Few studies have investigated simultaneous effects of task difficulty and self-contribution on fairness consideration outcomes and associated neurophysiological responses. To elucidate modulation effects of task difficulty and self-contribution on fairness consideration, 30 recruited participants played a modified ultimatum game (UG) while undergoing event-related potential measurements. A 2 (task difficulty: hard vs. easy) × 3 (contribution: other-contribution vs. both-contribution vs. self-contribution) × 2 (fairness type: fair vs. unfair) within-subject design was adopted. A significant interaction between fairness type and contribution was observed in the behavioral data, with unfair offers being more acceptable in the other-contribution condition than in the self-contribution or both-contribution conditions. In the early processing time window, feedback-related negative magnitudes were greater in the hard condition than in the easy condition. P300 responses were more pronounced when participants contributed equally to the proposer than in the self- and other-contribution conditions. These results demonstrated that individuals’ decisions are influenced by their own effort contributions relative to those of others in cooperative contexts.
High-Performance Work Practices and Employee Wellbeing—Does Health-Oriented Leadership Make a Difference?
Authors: Hauff Sven , Krick Annika , Klebe Laura , Felfe Jörg
Published: March 2022

This paper sheds further light on the contextual boundaries in the relationship between high-performance work practices (HPWPs) and employee wellbeing. In particular, we analyze whether this relationship is moderated by health-oriented leadership behavior (i.e., staff care) which describes the extent to which leaders value, are aware of, and protect their followers’ health at work. Our analyses are based on employee data (N = 1,345) from Germany, covering two points in time. Findings show positive associations between HPWPs and happiness-related (i.e., engagement, commitment) and health-related (i.e., general health, physical health complaints, mental health complaints, strain) wellbeing outcomes. The positive relationship between HPWPs and employee wellbeing is weaker the more employees experience leadership behavior in terms of staff care. Thus, our results provide further evidence for a substitutive or compensatory effect between HRM and leadership.
Improving Alzheimer's Disease Detection for Speech Based on Feature Purification Network
Authors: Liu Ning , Yuan Zhenming , Tang Qingfeng
Published: March 2022

Alzheimer's disease (AD) is a neurodegenerative disease involving the decline of cognitive ability with illness progresses. At present, the diagnosis of AD mainly depends on the interviews between patients and doctors, which is slow, expensive, and subjective, so it is not a better solution to recognize AD using the currently available neuropsychological examinations and clinical diagnostic criteria. A recent study has indicated the potential of language analysis for AD diagnosis. In this study, we proposed a novel feature purification network that can improve the representation learning of transformer model further. Though transformer has made great progress in generating discriminative features because of its long-distance reasoning ability, there is still room for improvement. There exist many common features that are not indicative of any specific class, and we rule out the influence of common features from traditional features extracted by transformer encoder and can get more discriminative features for classification. We apply this method to improve transformer's performance on three public dementia datasets and get improved classification results markedly. Specifically, the method on Pitt datasets gets state-of-the-art (SOTA) result.
Assessment of the Current Surveillance System for Human Leptospirosis in Ecuador by Decision Analytic Modeling
Authors: Calero María Laura , Monti Gustavo
Published: March 2022

Leptospirosis is a globally disseminated zoonotic disease with no national surveillance systems. On the other hand, surveillance is crucial for improving population health, and surveillance systems produce data that motivates action. Unfortunately, like many other countries, Ecuador put in place a monitoring system that has never been tested. The goal of this study was to use scenario tree modeling to assess the sensitivity of Ecuador's current national surveillance system to human leptospirosis as the basis for an economic assessment of the system. We created a decision-tree model to analyze the current system's sensitivity. The inputs were described as probabilities distributions, and the model assessed the program's sensitivity as an output. The model also considers the geographical and weather variations across Ecuador's three continental regions: Andean, Amazonia, and the Coast. Several data sources were used to create the model, including leptospirosis records from Ecuador's Ministry of Public Health, national and international literature, and expert elicitation, all of which were incorporated in a Bayesian framework. We were able to determine the most critical parameters influencing each scenario's output (CSU) sensitivity through sensitivity analysis. The Coast region had the best sensitivity scenario, with a median of 0.85% (IC 95% 0.41–0.99), followed by the Amazonia with a median of 0.54% (CI 95% 0.18–0.99) and the Andes with a median of 0.29% (CI 95% 0.02–0.89). As per the sensitivity study, the most influential criteria on the system's sensitivity were “Attendance or probability of going to a health center” and “probability of having symptoms,” notably for the Coast and Amazonia Regions.
Initial Development and Psychometric Evidence of Physical Education Grit Scale (PE-Grit)
Authors: Guelmami Noomen , Chalghaf Nasr , Tannoubi Amayra , Puce Luca , Azaiez Fairouz , Bragazzi Nicola Luigi
Published: March 2022

Background

Grit is a key concept in positive psychology and educational science. The construct measures two related constructs that are interest and effort. Several instruments have been developed to measure this construct in professional and educational contexts, but no tools have been developed considering specific contexts such as physical education and sport.

Objectives

The objective of this study is to develop and test a measurement scale to assess Grit in the context of physical education and sport.

Methods

Two exploratory (Phase 1) and confirmatory (Phase 2) samples were administered the 16-item PE-Grit scale in Arabic. In addition, the confirmatory sample also was administered the R-SPQ-2F two-factor learning approaches scale. The factor structure was examined first by exploratory factor analysis on the first sample and then by confirmatory factor analysis on the second sample. Reliability testing was performed by checking internal consistency simultaneously by the three indices: McDonald's ω, Cronbach's α and Gutmann's λ6. Concurrent validity was checked by Pearson's correlation between the PE-Grit and the two dimensions of the SPQ-2F.

Results

After the exploratory factor analysis, which identified the factors and gave a preliminary validation of the designed instrument, confirmatory factor analysis was performed on three hierarchical models to be able to identify the best fitting model. A third-order hierarchical model with two physical and academic components each formed by interest and effort presented the best fit indices: chi X2 = 192.95 (p < 0.01), and the X2/DF = 1.36; GFI = 0.99; AGFI = 0.99; CFI and TLI close to 1; RMSEA = 0.025. In addition, McDonald's ω, internal consistency, and Gutmann's λ6 ranged from 0.78 to 0.86 for all four scale dimensions.

Conclusion

The PE-Grit scale displays adequate factor structure, good reliability, and acceptable concurrent validity and can be administered to assess Grit in physical education and sport students.
Health Benefits of Air Quality Improvement: Empirical Research Based on Medical Insurance Reimbursement Data
Authors: Li Ding , Xiao Han , Ma Shuang , Zhang Jiangxue
Published: March 2022

Measuring the health benefits of air quality improvement is a new perspective for evaluating government investment in pollution control. Improving air quality can reduce the burden on medical insurance funds and patients themselves; however, patients with higher reimbursement rates are more affected by air quality changes. This study calculated health benefits using medical insurance reimbursement data from a sample city in China. The results show that for every 10 μg/m3 decrease in PM2.5, patients' average medical cost will decrease by CNY 1,699 (USD 263.6), and the loss of ordinary working and living time will decrease by 1.24 days. PM2.5 has a more significant impact on patients with chronic respiratory diseases and inpatients with circulatory diseases. Suppose the city's annual PM2.5 concentration drops to the national standard of 35 μg/m3. In that case, it will bring more than CNY 1.28 billion (USD 198 million) in health benefits, accounting for 18% of the city's annual investment in environmental protection.
Transfer Across Different Machines by Transfer Function Estimation
Authors: Matania Omri , Klein Renata , Bortman Jacob
Published: March 2022

A digital twin is a promising evolving tool for prognostic health monitoring. However, in rotating machinery, the transfer function between the rotating components and the sensor distorts the vibration signal, hence, complicating the ability to apply a digital twin to new systems. This paper demonstrates the importance of estimating the transfer function for a successful transfer across different machines (TDM). Furthermore, there are few algorithms in the literature for transfer function estimation. The current algorithms can estimate the magnitude of the transfer function without its original phase. In this study, a new approach is presented that enables the estimation of the transfer function with its phase for a gear signal. The performance of the new algorithm is demonstrated by measured signals and by a simulated transfer function.
Power Amplification for Jumping Soft Robots Actuated by Artificial Muscles
Authors: Fernandes Minori Adriane , Jadhav Saurabh , Chen Haojin , Fong Samantha , Tolley Michael T.
Published: March 2022

Robots composed of soft materials can passively adapt to constrained environments and mitigate damage due to impact. Given these features, jumping has been explored as a mode of locomotion for soft robots. However, for mesoscale jumping robots, lightweight and compact actuation are required. Previous work focused on systems powered by fluids, combustion, smart materials, electromagnetic, or electrostatic motors, which require one or more of the following: large rigid components, external power supplies, components of specific, pre-defined sizes, or fast actuation. In this work, we propose an approach to design and fabricate an electrically powered soft amplification mechanism to enable untethered mesoscale systems with continuously tunable performance. We used the tunable geometry of a liquid crystal elastomer actuator, an elastic hemispherical shell, and a pouch motor for active latching to achieve rapid motions for jumping despite the slow contraction rate of the actuator. Our system amplified the power output of the LCE actuator by a factor of 8.12 × 103 with a specific power of 26.4 W/kg and jumped to a height of 55.6 mm (with a 20 g payload). This work enables future explorations for electrically untethered soft systems capable of rapid motions (e.g., jumping).
Translocal Mobilization of Housing Commons. The Example of the German Mietshäuser Syndikat
Authors: Hölzl Corinna
Published: March 2022

We are currently observing an international trend toward the establishment of non-profit-oriented, collaborative, and self-managed housing models. In this respect, knowledge concerning commoning has been circulating globally with initiatives mutually interacting. This is also true for the Mietshäuser Syndikat, which by now comprises some 171 permanently decommodified houses in Germany and has been transferred to the legal spaces of several neighboring states (Austria, France, Netherlands, and Czech Republic). Against this background, this paper addresses the question of how housing commons such as the Syndikat circulate translocally and what role spatial learning processes and network dynamics play in that regard. Conceptually, the study refers to the spatialities of social movements. Participatory observations at (inter-)national meetings as well as network graph-assisted interviews with key actors of the Syndikat model represent the central methods of the study. The findings illustrate that (1) solidary knowledge transfers via key actors who take on advisory and network functions, (2) open physical, and (3) virtual meeting points facilitate a moderate diffusion and permanent adaptations of the housing commons model. A process of “assembling, dis-assembling, re-assembling along the way” (McCann and Ward,2012) thus unfolds. However, the findings illustrate that these mechanisms are not strong enough to compensate unequal relations of power and resources—among other in view of local pre-conditions.
Physical and Paste Properties Comparison of Four Snacks Produced by High Protein Quinoa Flour Extrusion Cooking
Authors: Muñoz-Pabon Karen Sofia , Parra-Polanco Astrid Soraya , Roa-Acosta Diego Fernando , Hoyos-Concha Jose Luis , Bravo-Gomez Jesus Eduardo
Published: March 2022

Extrusion cooking is used to produce puffed snacks based on cereals and feed ingredients. Because of its nutritional properties, quinoa flour has been employed to prepare various types of foods. This study evaluates the effects of including hyper-protein quinoa flour obtained through abrasive milling in four formulations cooked at 27% moisture content and processed in a laboratory level single screw extruder to determine their physical, textural, and pasting properties. The results indicated that additional hyper-protein quinoa flour in the cereal mixture reduced 47% the expansion index (EI), while the extrudate density (ED) and hardness increased 54 and 130%, respectively. After the extrusion process, the water absorption index (WAI), water solubility index (WSI) increased by more than 100%. The addition of hyper-protein quinoa flour (25–37%) did not affect the WAI, but an increase in the WSI was observed. The quinoa flour extrusion process generated changes on the color mainly in the L parameter, which decreased in the extruded snacks with quinoa flour inclusion (51.49), compared to the snack without inclusion (62.68). Changing the integrity of the starch granules and associated proteins, causing a decrease in the viscosity peaks during heating and subsequent cooling. The extruded samples revealed stability in the retrogradation process. Extruded snacks from quinoa could be an alternative approach to produce feed ingredients with high protein contents.
Accuracy of the Horizontal Calibrator in Correcting Leg Length and Restoring Femoral Offset in Total Hip Arthroplasty
Authors: Chen Xing , Xing Shuxing , Zhu Zhiyong , Wang Huisheng , Yu Zhongshen , Bai Xizhuang , Li Xi
Published: March 2022

Background

Limb length discrepancy (LLD) is one of the most common postoperative complications and can cause serious consequences. Poor recovery of femoral offset (OD) will result in weakness of the patient's external rotator muscles and affect the patient's postoperative function. The study is aimed to present a simple approach that compensates for the shortcomings of previous measuring devices and combines the advantages of different measuring devices to provide more accurate limb length and femoral offset restoration in total hip arthroplasty (THA).

Methods

This study was a prospective controlled trial involving 89 patients with THA. Group I (n = 44) was used for intraoperative measurement of THA with our self-designed horizontal calibrator. Group II (n = 45) was measured by a traditional freehand technique. The main outcome indicators were measured on the Neusoft PACS, including LLD, femoral offset deviation, and operative time. IBM SPSS 23.0 was used for data analysis.

Results

The independent sample t-test was performed for all the data. The operative time, preoperative radiographic LLD, and OD of Group I and Group II had no statistical significance. Postoperative LLD of Group I and Group II were 2.5 ± 2.1 mm (range −5.7 to 8.3 mm) and 6.2 ± 4.3 mm (range −18.0 to 15.2 mm), and the independent sample t-test data of both (P < 0.001; 95% CI = −5.1, −2.2) showed statistical significance. In Group I, there were 38 THAs with LLD <5 mm, accounting for 86% and there were 44 THAs with LLD <10 mm, accounting for 100%. In Group II, there were 20 THAs with LLD <5 mm, accounting for 44%. There were 36 THAs with LLD <10 mm, covering for 80%. There was no significant difference in postoperative femoral offset and OD.

Conclusion

The horizontal calibrator can provide more accurate limb length and femoral offset recovery in THA. It is a simple surgical technique that does not add additionally surgical costs and does not significantly increase operative time, providing a new solution for surgeons to resolve postoperative LLD and restore femoral offset.
Quantitative Clarification of Stable Ignition Region for HKP110 Green Hypergolic Bipropellant
Authors: Hatai Keigo , Nagata Taiichi
Published: March 2022

As a candidate for a green hypergolic bipropellant, the combination of highly concentrated hydrogen peroxide and fuel with dissolved sodium borohydride has been widely studied. In this study, a drop test using such a green hypergolic bipropellant was conducted to investigate the stable ignition region in terms of the mixture ratio. As a result, stagnation phenomena of flame growth were observed in high mixture ratio conditions. In addition, impinging-jet tests using a windowed chamber were conducted with the green hypergolic bipropellant to observe the ignition phenomena inside the combustion chamber. As a result, unstable ignition phenomena were observed in oxidizer-lead injection cases. Besides the unstable ignition, hard starts occurred several times during the test series. Data analysis demonstrated that controlling the transient mixture ratio in the early phase of injection is essential for preventing unstable ignition and hard starts. The quantitative threshold of mixture ratio for stable ignition was clarified based on the test results.
Design Evolution and Wind Tunnel Tests of a Three-Lifting Surface Regional Transport Aircraft
Authors: Cusati Vincenzo , Corcione Salvatore , Ciliberti Danilo , Nicolosi Fabrizio
Published: March 2022

This paper deals with the experimental assessment of the aerodynamic characteristics of an innovative large turboprop aircraft. The configuration is a three-lifting surfaces airplane with rear engine installation at tail tips, conceived to carry up to 130 passengers and targeting a minimum economic and environmental impact, which is competitive with regional jets on short and medium hauls. The three-lifting surfaces layout is the output of previous research made by the authors, and it has been selected to fully comply with the market and design constraints. An experimental test campaign was required to validate the aerodynamics, stability, and control of this innovative configuration. From the results of the first campaign, it appeared that the aircraft had insufficient longitudinal and directional stability. Thus, the authors worked to improve these characteristics, updating the design and executing a second wind tunnel test campaign. The evolution of the design is described in the first part of the paper. In the second part, the authors discuss the aerodynamic interference effects among aircraft components, detailing how the combined downwash coming from both the canard and wing, as well as their wakes, affects the empennage aerodynamics. Experimental tests have revealed a significant reduction of the longitudinal stability due to canard additional downwash, especially at low attitudes. Furthermore, it was found that the canard generates a non-linearity on the aircraft directional stability derivative at moderate sideslip angles because of its tip vortex impinging on the vertical tail. Despite the detrimental interference due to the canard, the updated aircraft proved to be statically stable with sufficient margin at the most rearward center of gravity. Lessons learned in this research may be useful to aerodynamicists and aircraft designers facing similar issues.
Ramifications of the HLA-I Allelic Reactivity of Anti-HLA-E*01:01 and Anti-HLA-E*01:03 Heavy Chain Monoclonal Antibodies in Comparison with Anti-HLA-I IgG Reactivity in Non-Alloimmunized Males, Melanoma-Vaccine Recipients, and End-Stage Renal Disease Patients
Authors: Ravindranath Mepur H. , Ravindranath Narendranath M. , El Hilali Fatiha , Selvan Senthamil R. , Filippone Edward J.
Published: March 2022

Serum anti-HLA-I IgG are present in non-alloimmunized males, cancer patients, and transplant recipients. Anti-HLA-I antibodies are also present in intravenous immunoglobulin (IVIg), prepared from the plasma of thousands of healthy donors. However, the HLA-Ia reactivity of IVIg diminishes markedly after passing through HLA-E HC-affinity columns, suggesting that the HLA-I reactivity is due to antibodies formed against HLA-E. Hence, we examined whether anti-HLA-E antibodies can react to HLA-I alleles. Monoclonal IgG antibodies (mAbs) against HCs of two HLA-E alleles were generated in Balb/C mice. The antibodies were analyzed using multiplex bead assays on a Luminex platform for HLA-I reactivity. Beads coated with an array of HLA heterodimers admixed with HCs (LABScreen) were used to examine the binding of IgG to different HLA-Ia (31-HLA-A, 50-HLA-B, and 16-HLA-C) and Ib (2-HLA-E, one each of HLA-F and HLA-G) alleles. A striking diversity in the HLA-Ia and/or HLA-Ib reactivity of mAbs was observed. The number of the mAbs reactive to (1) only HLA-E (n = 25); (2) all HLA-Ib isomers (n = 8); (3) HLA-E and HLA-B (n = 5); (4) HLA-E, HLA-B, and HLA-C (n = 30); (5) HLA-E, HLA-A*1101, HLA-B, and HLA-C (n = 83); (6) HLA-E, HLA-A, HLA-B, and HLA-C (n = 54); and (7) HLA-Ib and HLA-Ia (n = 8), in addition to four other minor groups. Monospecificity and polyreactivity were corroborated by HLA-E monospecific and HLA-I shared sequences. The diverse HLA-I reactivity of the mAbs are compared with the pattern of HLA-I reactivity of serum-IgG in non-alloimmunized males, cancer patients, and ESKD patients. The findings unravel the diagnostic potential of the HLA-E monospecific-mAbs and immunomodulatory potentials of IVIg highly mimicking HLA-I polyreactive-mAbs.
New Glycosylated Polyene Macrolides: Refining the Ore from Genome Mining
Authors: Caffrey Patrick , Hogan Mark , Song Yuhao
Published: March 2022

Glycosylated polyene macrolides include effective antifungal agents, such as pimaricin, nystatin, candicidin, and amphotericin B. For the treatment of systemic mycoses, amphotericin B has been described as a gold-standard antibiotic because of its potent activity against a broad spectrum of fungal pathogens, which do not readily become resistant. However, amphotericin B has severe toxic side effects, and the development of safer alternatives remains an important objective. One approach towards obtaining such compounds is to discover new related natural products. Advances in next-generation sequencing have delivered a wealth of microbial genome sequences containing polyene biosynthetic gene clusters. These typically encode a modular polyketide synthase that catalyzes the assembly of the aglycone core, a cytochrome P450 that oxidizes a methyl branch to a carboxyl group, and additional enzymes for synthesis and attachment of a single mycosamine sugar residue. In some cases, further P450s catalyze epoxide formation or hydroxylation within the macrolactone. Bioinformatic analyses have identified over 250 of these clusters. Some are predicted to encode potentially valuable new polyenes that have not been uncovered by traditional screening methods. Recent experimental studies have characterized polyenes with new polyketide backbones, previously unknown late oxygenations, and additional sugar residues that increase water-solubility and reduce hemolytic activity. Here we review these studies and assess how this new knowledge can help to prioritize silent polyene clusters for further investigation. This approach should improve the chances of discovering better antifungal antibiotics.
The Role of Nitric Oxide in Stem Cell Biology
Authors: Caballano-Infantes Estefanía , Cahuana Gladys Margot , Bedoya Francisco Javier , Salguero-Aranda Carmen , Tejedo Juan R.
Published: March 2022

Nitric oxide (NO) is a gaseous biomolecule endogenously synthesized with an essential role in embryonic development and several physiological functions, such as regulating mitochondrial respiration and modulation of the immune response. The dual role of NO in embryonic stem cells (ESCs) has been previously reported, preserving pluripotency and cell survival or inducing differentiation with a dose-dependent pattern. In this line, high doses of NO have been used in vitro cultures to induce focused differentiation toward different cell lineages being a key molecule in the regenerative medicine field. Moreover, optimal conditions to promote pluripotency in vitro are essential for their use in advanced therapies. In this sense, the molecular mechanisms underlying stemness regulation by NO have been studied intensively over the current years. Recently, we have reported the role of low NO as a hypoxia-like inducer in pluripotent stem cells (PSCs), which supports using this molecule to maintain pluripotency under normoxic conditions. In this review, we stress the role of NO levels on stem cells (SCs) fate as a new approach for potential cell therapy strategies. Furthermore, we highlight the recent uses of NO in regenerative medicine due to their properties regulating SCs biology.
Circular Hazelnut Protection by Lignocellulosic Waste Valorization for Nanopesticides Development
Authors: Schiavi Daniele , Ronchetti Riccardo , Di Lorenzo Veronica , Salustri Mirko , Petrucci Camilla , Vivani Riccardo , Giovagnoli Stefano , Camaioni Emidio , Balestra Giorgio M.
Published: March 2022

Hazelnut represents a relevant agro-food supply chain in many countries worldwide. Several biological adversities threaten hazelnut cultivation, but among them bacterial blight is one of the most feared and pernicious since its control can be achieved only by prevention through the observation of good agricultural practices and the use of cupric salts. The aim of this work was to evaluate the lignocellulosic biomasses obtained from hazelnut pruning and shelling residues as a renewable source of cellulose nanocrystals and lignin nanoparticles and to investigate their antimicrobial properties against hazelnut bacterial blight. Cellulose nanocrystals were obtained through an acid hydrolysis after a chemical bleaching, while lignin nanoparticles were synthesized by a solvent–antisolvent method after an enzymatic digestion. Both collected nanomaterials were chemically and morphologically characterized before being tested for their in vitro and in vivo antibacterial activity and biocompatibility on hazelnut plants. Results indicated the selected biomasses as a promising starting material for lignocellulosic nanocarriers synthesis, confirming at the same time the potential of cellulose nanocrystals and lignin nanoparticles as innovative tools to control hazelnut bacterial blight infections without showing any detrimental effects on the biological development of treated hazelnut plants.
Technical Analysis of the Masonry of the Bargello’ Palace, Florence (Italy)
Authors: Coli Massimo , Ciuffreda Anna Livia , Donigaglia Tessa
Published: March 2022

This study defines the assemblage, materials, and mechanical parameter of the XIV century Bargello Palace at Florence (Italy). For this purpose, according to the rule in force, NDT and LDT had been performed on the Bargello walls, namely: direct observations, georadar, ultrasonic, thermic, DAC-test, and endoscopy. The results outline that the Bargello masonries are well done, as use in Florence in the XIV–XV centuries; they are solid walls, made in tightly sealed flat quoins, with external facing and internal plastering, and with a percentage of stones to mortar equal to about 70%. The results allow assigning of the Bargello’s masonry to one of the categories provided by the rules in force, with the relative mechanical parameter values for the need of a seismic verification assessment.
Cardiac Magnetic Resonance Left Ventricle Segmentation and Function Evaluation Using a Trained Deep-Learning Model
Authors: Guo Fumin , Ng Matthew , Roifman Idan , Wright Graham
Published: March 2022

Cardiac MRI is the gold standard for evaluating left ventricular myocardial mass (LVMM), end-systolic volume (LVESV), end-diastolic volume (LVEDV), stroke volume (LVSV), and ejection fraction (LVEF). Deep convolutional neural networks (CNNs) can provide automatic segmentation of LV myocardium (LVF) and blood cavity (LVC) and quantification of LV function; however, the performance is typically degraded when applied to new datasets. A 2D U-net with Monte-Carlo dropout was trained on 45 cine MR images and the model was used to segment 10 subjects from the ACDC dataset. The initial segmentations were post-processed using a continuous kernel-cut method. The refined segmentations were employed to update the trained model. This procedure was iterated several times and the final updated U-net model was used to segment the remaining 90 ACDC subjects. Algorithm and manual segmentations were compared using Dice coefficient (DSC) and average surface distance in a symmetric manner (ASSD). The relationships between algorithm and manual LV indices were evaluated using Pearson correlation coefficient (r), Bland-Altman analyses, and paired t-tests. Direct application of the pre-trained model yielded DSC of 0.74 ± 0.12 for LVM and 0.87 ± 0.12 for LVC. After fine-tuning, DSC was 0.81 ± 0.09 for LVM and 0.90 ± 0.09 for LVC. Algorithm LV function measurements were strongly correlated with manual analyses (r = 0.86–0.99, p < 0.0001) with minimal biases of −8.8 g for LVMM, −0.9 mL for LVEDV, −0.2 mL for LVESV, −0.7 mL for LVSV, and −0.6% for LVEF. The procedure required ∼12 min for fine-tuning and approximately 1 s to contour a new image on a Linux (Ubuntu 14.02) desktop (Inter(R) CPU i7-7770, 4.2 GHz, 16 GB RAM) with a GPU (GeForce, GTX TITAN X, 12 GB Memory). This approach provides a way to incorporate a trained CNN to segment and quantify previously unseen cardiac MR datasets without needing manual annotation of the unseen datasets.
Nanotechnology Applications towards Sustainable Road Surface Maintenance and Effective Asset Protection, Generating Rapid Employment Opportunities in a Post COVID-19 Era
Authors: Jordaan Gerrit J. , Steyn Wynand J. vdM.
Published: March 2022

The developing world has been faced with high rates of unemployment, exacerbated by extended enforced lockdowns due to the pandemic. Pressure is mounting for drastic intervention to accelerate economic growth and to provide employment opportunities. Most of these countries are faced with inadequate road transport facilities in support of economic growth. The construction of high-order roads in support of economic growth requires high degrees of compliance with limited opportunities for increased labour content. However, many of the existing surfaced roads are notoriously lacking periodic preventative maintenance operations needed to preserve the integrity of road surfaces to protect pavement structures against water ingress and resultant rapid deterioration. This article demonstrates the ability of available, proven nanotechnologies to restore the water-resistant properties of already compromised road surfacings. It is shown that traditionally used road products can substantially be improved (in terms of strength properties and resistance to environmental factors) through the addition of applicable nanotechnology modifiers. These modified products can be applied at ambient temperatures, ideally suited for labour intensive applications as demonstrated, showing several examples of actual applications. A combination of modified existing technologies is recommended to partially restore severely compromised road surfacings, especially applicable to secondary and tertiary urban road networks. The implementation of the recommended restoration programmes can go a long way towards road asset preservation, while simultaneously addressing the urgent need for rapid employment generation.
Attentive Octave Convolutional Capsule Network for Medical Image Classification
Authors: Zhang Hong , Li Zhengzhen , Zhao Hao , Li Zan , Zhang Yanping
Published: March 2022

Medical image classification plays an essential role in disease diagnosis and clinical treatment. More and more research efforts have been dedicated to the design of effective methods for medical image classification. As an effective framework, the capsule network (CapsNet) can realize translation equivariance. Lots of current research applies capsule networks in medical image analysis. In this paper, we propose an attentive octave convolutional capsule network (AOC-Caps) for medical image classification. In AOC-Caps, an AOC module is used to replace the traditional convolution operation. The purpose of the AOC module is to process and fuse the high- and low-frequency information in the input image simultaneously, and weigh the important parts automatically. Following the AOC module, a matrix capsule is used and the expectation maximization (EM) algorithm is applied to update the routing weights. The proposed AOC-Caps and comparative methods are tested on seven datasets, including PathMNIST, DermaMNIST, OCTMNIST, PneumoniaMNIST, OrganMNIST_Axial, OrganMNIST_Coronal, and OrganMNIST_Sagittal, which are from MedMNIST. In the experiments, baselines include the traditional CNN models, automated machine learning (AutoML) methods, and related capsule network methods. The experimental results demonstrate that the proposed AOC-Caps achieves better performance on most of the seven medical image datasets.
Quiescence of Human Monocytes after Affinity Purification: A Novel Method Apt for Monocyte Stimulation Assays
Authors: Nguyen Minh-Thu , Schellerhoff Leonhard Hubert , Niemann Silke , Schaumburg Frieder , Herrmann Mathias
Published: March 2022

Several methods to isolate monocytes from whole blood have been previously published, with different advantages and disadvantages. For the purpose of cytokine release assessment upon external stimulation, the use of monocyte preparations consisting of non-activated cells is prerequisite. Affinity-isolated monocyte preparations from peripheral blood mononuclear cells (PBMCs), obtained via positive or negative selection using magnetic beads, released pro-inflammatory cytokines such as TNF-α and IL-6 even without adding external stimuli, hindering any assessment of an effect of bacterial lipoproteins on cell stimulation. Hence, the cell preparation protocol was modified by adding a quiescence step on repellent surface culture plates, dampening any monocyte pre-activation. This protocol now provides a robust method to prepare silent yet fully activatable, pure monocyte populations for further use in stimulus-elicited activation experiments.