bluuebunny/crossref_metadata_2025 huggingface dataset:
Time-resolved investigation of nanometric cell membrane patches with a mid-infrared laser microscope
Authors: Intze Antonia , Temperini Maria Eleonora , Baldassarre Leonetta , Giliberti Valeria , Ortolani Michele , Polito Raffaella
Published: April 2023

The proton pump Bacteriorhodopsin (BR) undergoes repeated photocycles including reversible conformational changes upon visible light illumination. Exploiting the sensitivity of infrared (IR) spectra to the conformation, we have determined the reaction kinetic parameters of the conductive intermediate M for the wild-type protein and for its slow mutant D96N during its photocycle. Time-resolved IR micro-spectroscopy using an in-house developed confocal laser microscope operating in the mid-IR is employed to record absorption changes of 10−4 at wavelengths λ1 = 6.08 μm and λ2 = 6.35 μm, assigned to backbone and retinal structural modifications, respectively. Protein samples were embedded in dried lipid bilayers deposited on ultraflat gold supports to enhance the surface field. The signals were analyzed according to a simplified photocycle model with only two dominant states: the dark-adapted state BR* and the intermediate M. We obtained the excitation and relaxation times of the intermediate M from exponential fits to the absorption change time traces. Our results constitute a first step towards future plasmonic-assisted nanoscale time-resolved mid-IR spectrometers for the characterization of bioelectronic and light-harvesting nanodevices based on BR.
Comparison of ventilation defects quantified by Technegas SPECT and hyperpolarized 129Xe MRI
Authors: Radadia Nisarg , Friedlander Yonni , Priel Eldar , Konyer Norman B. , Huang Chynna , Jamal Mobin , Farncombe Troy , Marriott Christopher , Finley Christian , Agzarian John , Dolovich Myrna , Noseworthy Michael D. , Nair Parameswaran , Shargall Yaron , Svenningsen Sarah
Published: April 2023

Introduction: The ideal contrast agents for ventilation SPECT and MRI are Technegas and 129Xe gas, respectively. Despite increasing interest in the clinical utility of ventilation imaging, these modalities have not been directly compared. Therefore, our objective was to compare the ventilation defect percent (VDP) assessed by Technegas SPECT and hyperpolarized 129Xe MRI in patients scheduled to undergo lung cancer resection with and without pre-existing obstructive lung disease.

Methods: Forty-one adults scheduled to undergo lung cancer resection performed same-day Technegas SPECT, hyperpolarized 129Xe MRI, spirometry, and diffusing capacity of the lung for carbon monoxide (DLCO). Ventilation abnormalities were quantified as the VDP using two different methods: adaptive thresholding (VDPT) and k-means clustering (VDPK). Correlation and agreement between VDP quantified by Technegas SPECT and 129Xe MRI were determined by Spearman correlation and Bland-Altman analysis, respectively.

Results: VDP measured by Technegas SPECT and 129Xe MRI were correlated (VDPT: r = 0.48, p = 0.001; VDPK: r = 0.63, p < 0.0001). A 2.0% and 1.6% bias towards higher Technegas SPECT VDP was measured using the adaptive threshold method (VDPT: 23.0% ± 14.0% vs. 21.0% ± 5.2%, p = 0.81) and k-means method (VDPK: 9.4% ± 9.4% vs. 7.8% ± 10.0%, p = 0.02), respectively. For both modalities, higher VDP was correlated with lower FEV1/FVC (SPECT VDPT: r = −0.38, p = 0.01; MRI VDPK: r = −0.46, p = 0.002) and DLCO (SPECT VDPT: r = −0.61, p < 0.0001; MRI VDPK: r = −0.68, p < 0.0001). Subgroup analysis revealed that VDP measured by both modalities was significantly higher for participants with COPD (n = 13) than those with asthma (n = 6; SPECT VDPT: p = 0.007, MRI VDPK: p = 0.006) and those with no history of obstructive lung disease (n = 21; SPECT VDPT: p = 0.0003, MRI VDPK: p = 0.0003).

Discussion: The burden of ventilation defects quantified by Technegas SPECT and 129Xe MRI VDP was correlated and greater in participants with COPD when compared to those without. Our observations indicate that, despite substantial differences between the imaging modalities, quantitative assessment of ventilation defects by Technegas SPECT and 129Xe MRI is comparable.
Development and validation of a deep learning-based model to distinguish acetabular fractures on pelvic anteroposterior radiographs
Authors: Ye Pengyu , Li Sihe , Wang Zhongzheng , Tian Siyu , Luo Yi , Wu Zhanyong , Zhuang Yan , Zhang Yingze , Grzegorzek Marcin , Hou Zhiyong
Published: April 2023

Objective: To develop and test a deep learning (DL) model to distinguish acetabular fractures (AFs) on pelvic anteroposterior radiographs (PARs) and compare its performance to that of clinicians.

Materials and methods: A total of 1,120 patients from a big level-I trauma center were enrolled and allocated at a 3:1 ratio for the DL model’s development and internal test. Another 86 patients from two independent hospitals were collected for external validation. A DL model for identifying AFs was constructed based on DenseNet. AFs were classified into types A, B, and C according to the three-column classification theory. Ten clinicians were recruited for AF detection. A potential misdiagnosed case (PMC) was defined based on clinicians’ detection results. The detection performance of the clinicians and DL model were evaluated and compared. The detection performance of different subtypes using DL was assessed using the area under the receiver operating characteristic curve (AUC).

Results: The means of 10 clinicians’ sensitivity, specificity, and accuracy to identify AFs were 0.750/0.735, 0.909/0.909, and 0.829/0.822, in the internal test/external validation set, respectively. The sensitivity, specificity, and accuracy of the DL detection model were 0.926/0.872, 0.978/0.988, and 0.952/0.930, respectively. The DL model identified type A fractures with an AUC of 0.963 [95% confidence interval (CI): 0.927–0.985]/0.950 (95% CI: 0.867–0.989); type B fractures with an AUC of 0.991 (95% CI: 0.967–0.999)/0.989 (95% CI: 0.930–1.000); and type C fractures with an AUC of 1.000 (95% CI: 0.975–1.000)/1.000 (95% CI: 0.897–1.000) in the test/validation set. The DL model correctly recognized 56.5% (26/46) of PMCs.

Conclusion: A DL model for distinguishing AFs on PARs is feasible. In this study, the DL model achieved a diagnostic performance comparable to or even superior to that of clinicians.
Differential regulation of lymphatic junctional morphology and the potential effects on cardiovascular diseases
Authors: Peluzzo Amanda M. , Bkhache Meriem , Do Long Nguyen Hoang , Autieri Michael V. , Liu Xiaolei
Published: April 2023

The lymphatic vasculature provides an essential route to drain fluid, macromolecules, and immune cells from the interstitium as lymph, returning it to the bloodstream where the thoracic duct meets the subclavian vein. To ensure functional lymphatic drainage, the lymphatic system contains a complex network of vessels which has differential regulation of unique cell-cell junctions. The lymphatic endothelial cells lining initial lymphatic vessels form permeable “button-like” junctions which allow substances to enter the vessel. Collecting lymphatic vessels form less permeable “zipper-like” junctions which retain lymph within the vessel and prevent leakage. Therefore, sections of the lymphatic bed are differentially permeable, regulated in part by its junctional morphology. In this review, we will discuss our current understanding of regulating lymphatic junctional morphology, highlighting how it relates to lymphatic permeability during development and disease. We will also discuss the effect of alterations in lymphatic permeability on efficient lymphatic flux in health and how it may affect cardiovascular diseases, with a focus on atherosclerosis.
Comparison of online and in-person cognitive behavioral therapy in individuals diagnosed with major depressive disorder: a non-randomized controlled trial
Authors: Alavi Nazanin , Moghimi Elnaz , Stephenson Callum , Gutierrez Gilmar , Jagayat Jasleen , Kumar Anchan , Shao Yijia , Miller Shadé , Yee Caitlin S. , Stefatos Anthi , Gholamzadehmir Maedeh , Abbaspour Zara , Shirazi Amirhossein , Gizzarelli Tessa , Khan Ferwa , Patel Charmy , Patel Archana , Yang Megan , Omrani Mohsen
Published: April 2023

Objective

The increased prevalence of major depressive disorder (MDD) amid the COVID-19 pandemic has resulted in substantial growth in online mental health care delivery. Compared to its in-person counterpart, online cognitive behavioral therapy (e-CBT) is a time-flexible and cost-effective method of improving MDD symptoms. However, how its efficacy compares to in-person CBT is yet to be explored. Therefore, the current study compared the efficacy of a therapist-supported, electronically delivered e-CBT program to in-person therapy in individuals diagnosed with MDD.

Methods

Participants (n = 108) diagnosed with MDD selected either a 12 week in-person CBT or an asynchronous therapist-supported e-CBT program. E-CBT participants (n = 55) completed weekly interactive online modules delivered through a secure cloud-based online platform (Online Psychotherapy Tool; OPTT). These modules were followed by homework in which participants received personalized feedback from a trained therapist. Participants in the in-person CBT group (n = 53) discussed sessions and homework with their therapists during one-hour weekly meetings. Program efficacy was evaluated using clinically validated symptomatology and quality of life questionnaires.

Results

Both treatments yielded significant improvements in depressive symptoms and quality of life from baseline to post-treatment. Participants who opted for in-person therapy presented significantly higher baseline symptomatology scores than the e-CBT group. However, both treatments demonstrated comparable significant improvements in depressive symptoms and quality of life from baseline to post-treatment. e-CBT seems to afford higher participant compliance as dropouts in the e-CBT group completed more sessions on average than those in the in-person CBT group.

Conclusion

The findings support e-CBT with therapist guidance as a suitable option to treat MDD. Future studies should investigate how treatment accessibility is related to program completion rates in the e-CBT vs. in-person group.

Clinical Trial Registration

ClinicalTrials.Gov Protocol Registration and Results System (NCT04478058); clinicaltrials.gov/ct2/show/NCT04478058.
Data-driven evolutionary game models for the spread of fairness and cooperation in heterogeneous networks
Authors: Li Jing-Yi , Wu Wen-Hao , Li Ze-Zheng , Wang Wen-Xu , Zhang Boyu
Published: April 2023

Unique large-scale cooperation and fairness norms are essential to human society, but the emergence of prosocial behaviors is elusive. The fact that heterogeneous social networks prevail raised a hypothesis that heterogeneous networks facilitate fairness and cooperation. However, the hypothesis has not been validated experimentally, and little is known about the evolutionary psychological basis of cooperation and fairness in human networks. Fortunately, research about oxytocin, a neuropeptide, may provide novel ideas for confirming the hypothesis. Recent oxytocin-modulated network game experiments observed that intranasal administration of oxytocin to a few central individuals significantly increases global fairness and cooperation. Here, based on the experimental phenomena and data, we show a joint effect of social preference and network heterogeneity on promoting prosocial behaviors by building evolutionary game models. In the network ultimatum game and the prisoner’s dilemma game with punishment, inequality aversion can lead to the spread of costly punishment for selfish and unfair behaviors. This effect is initiated by oxytocin, then amplified via influential nodes, and finally promotes global cooperation and fairness. In contrast, in the network trust game, oxytocin increases trust and altruism, but these effects are confined locally. These results uncover general oxytocin-initiated mechanisms underpinning fairness and cooperation in human networks.
Cutaneous leishmaniasis situation analysis in the Islamic Republic of Iran in preparation for an elimination plan
Authors: Sharifi Iraj , Khosravi Ahmad , Aflatoonian Mohammad Reza , Salarkia Ehsan , Bamorovat Mehdi , Karamoozian Ali , Moghadam Mahmoud Nekoei , Sharifi Fatemeh , Afshar Abbas Aghaei , Afshari Setareh Agha Kuchak , Gharachorloo Faranak , Shirzadi Mohammad Reza , Amiri Behzad , Zainali Mohammad , Doosti Sara , Zamani Omid , Gouya Mohammad Mahdi
Published: April 2023

Iran has invariably been under the growing public health threat of cutaneous leishmaniasis (CL), a significant barrier to local development that hinders the prevention and control efforts toward eliminating the disease. So far, no comprehensive and in-depth epidemiological analysis of the CL situation has been carried out nationwide. This study aimed to employ advanced statistical models to analyze the data collected through the Center for Diseases Control and Prevention of Communicable Diseases during 1989–2020. However, we emphasized the current trends, 2013–2020, to study temporal and spatial CL patterns. In the country, the epidemiology of CL is incredibly intricate due to various factors. This fact indicates that the basic infrastructure, the preceding supports, and the implementation plan related to preventive and therapeutic measures need crucial support. The leishmaniasis situation analysis is consistent with desperate requirements for efficient information on the control program in the area. This review provides evidence of temporally regressive and spatially expanding incidence of CL with characteristic geographical patterns and disease hotspots, signifying an urgent need for comprehensive control strategies. This information could be a suitable model and practical experience in the Eastern Mediterranean Region, where over 80% of CL is reported.
New insights into maladaptive vascular responses to donor specific HLA antibodies in organ transplantation
Authors: Franco-Acevedo Adriana , Comes Johanna , Mack Julia J. , Valenzuela Nicole M.
Published: April 2023

Transplant vasculopathy (TV) causes thickening of donor blood vessels in transplanted organs, and is a significant cause of graft loss and mortality in allograft recipients. It is known that patients with repeated acute rejection and/or donor specific antibodies are predisposed to TV. Nevertheless, the exact molecular mechanisms by which alloimmune injury culminates in this disease have not been fully delineated. As a result of this incomplete knowledge, there is currently a lack of effective therapies for this disease. The immediate intracellular signaling and the acute effects elicited by anti-donor HLA antibodies are well-described and continuing to be revealed in deeper detail. Further, advances in rejection diagnostics, including intragraft gene expression, provide clues to the inflammatory changes within allografts. However, mechanisms linking these events with long-term outcomes, particularly the maladaptive vascular remodeling seen in transplant vasculopathy, are still being delineated. New evidence demonstrates alterations in non-coding RNA profiles and the occurrence of endothelial to mesenchymal transition (EndMT) during acute antibody-mediated graft injury. EndMT is also readily apparent in numerous settings of non-transplant intimal hyperplasia, and lessons can be learned from advances in those fields. This review will provide an update on these recent developments and remaining questions in our understanding of HLA antibody-induced vascular damage, framed within a broader consideration of manifestations and implications across transplanted organ types.
Whole genome sequencing and phylogenetic analysis of West Nile viruses from animals in New England, United States, 2021
Authors: Hyeon Ji-Yeon , Helal Zeinab H. , Appel Allison , Tocco Natalie , Hunt Amelia , Lee Dong-Hun , Risatti Guillermo R.
Published: April 2023

West Nile virus is a mosquito-borne Flavivirus which is the leading cause of global arboviral encephalitis. We sequenced WNVs from an American crow found in Connecticut and an alpaca found in Massachusetts which were submitted to the Connecticut Veterinary Medical Diagnostic Laboratory (CVMDL). We report here the complete protein-coding sequences (CDS) of the WNVs (WNV 21-3957/USA CT/Crow/2021 and WNV 21-3782/USA MA/Alpaca/2021) and their phylogenetic relationship with other WNVs recovered from across the United States. In the phylogenetic analysis, the WNVs from this study belonged to the WNV lineage 1. The WNV 21-3957/USA CT/Crow/2021 clustered with WNVs from a mosquito and birds in New York during 2007–2013. Interestingly, the virus detected in the alpaca, WNV 21-3782/USA MA/Alpaca/2021 clustered with WNVs from mosquitos in New York, Texas, and Arizona during 2012–2016. The genetic differences between the viruses detected during the same season in an American crow and an alpaca suggest that vector-host feeding preferences are most likely driving viral transmission. The CDS of the WNVs and their phylogenetic relationships with other WNVs established in this study would be useful as reference data for future investigations on WNVs. Seasonal surveillance of WNV in birds and mammals and the genetic characterization of detected viruses are necessary to monitor patterns of disease presentations and viral evolution within a geographical area.
Genomic inbreeding coefficients using imputed genotypes: assessing differences among SNP panels in Holstein-Friesian dairy cows
Authors: Dadousis Christos , Ablondi Michela , Cipolat-Gotet Claudio , van Kaam Jan-Thijs , Finocchiaro Raffaella , Marusi Maurizio , Cassandro Martino , Sabbioni Alberto , Summer Andrea
Published: April 2023

The objective of this study was to evaluate the effect of imputation of single nucleotide polymorphisms (SNP) on the estimation of genomic inbreeding coefficients. Imputed genotypes of 68,127 Italian Holstein dairy cows were analyzed. Cows were initially genotyped with two high density (HD) SNP panels, namely the Illumina Infinium BovineHD BeadChip (678 cows; 777,962 SNP) and the Genomic Profiler HD-150K (641 cows; 139,914 SNP), and four medium density (MD): GeneSeek Genomic Profiler 3 (10,679 cows; 26,151 SNP), GeneSeek Genomic Profiler 4 (33,394 cows; 30,113 SNP), GeneSeek MD (12,030 cows; 47,850 SNP) and the Labogena MD (10,705 cows; 41,911 SNP). After imputation, all cows had genomic information on 84,445 SNP. Seven genomic inbreeding estimators were tested: (i) four PLINK v1.9 estimators (F, Fhat1,2,3), (ii) two genomic relationship matrix (grm) estimators [VanRaden's 1st method, but with observed allele frequencies (Fgrm) and VanRaden's 3rd method that is allelic free and pedigree dependent (Fgrm2)], and (iii) a runs of homozygosity (roh) – based estimator (Froh). Genomic inbreeding coefficients of each SNP panel were compared with genomic inbreeding coefficients derived from the 84,445 imputation SNP. Coefficients of the HD SNP panels were consistent between genotyped-imputed SNP (Pearson correlations ~99%), while variability across SNP panels and estimators was observed in the MD SNP panels, with Labogena MD providing, on average, more consistent estimates. The robustness of Labogena MD, can be partly explained by the fact that 97.85% of the SNP of this panel is included in the 84,445 SNP selected by ANAFIBJ for routine genomic imputations, while this percentage for the other MD SNP panels varied between 55 and 60%. Runs of homozygosity was the most robust estimator. Genomic inbreeding estimates using imputation SNP are influenced by the SNP number of the SNP panel that are included in the imputed SNP, and performance of genomic inbreeding estimators depends on the imputation.
Sleep and cognition in aging dogs. A polysomnographic study
Authors: Mondino Alejandra , Catanzariti Magaly , Mateos Diego Martin , Khan Michael , Ludwig Claire , Kis Anna , Gruen Margaret E. , Olby Natasha J.
Published: April 2023

Introduction

Sleep is fundamental for cognitive homeostasis, especially in senior populations since clearance of amyloid beta (key in the pathophysiology of Alzheimer's disease) occurs during sleep. Some electroencephalographic characteristics of sleep and wakefulness have been considered a hallmark of dementia. Owners of dogs with canine cognitive dysfunction syndrome (a canine analog to Alzheimer's disease) report that their dogs suffer from difficulty sleeping. The aim of this study was to quantify age-related changes in the sleep-wakefulness cycle macrostructure and electroencephalographic features in senior dogs and to correlate them with their cognitive performance.

Methods

We performed polysomnographic recordings in 28 senior dogs during a 2 h afternoon nap. Percentage of time spent in wakefulness, drowsiness, NREM, and REM sleep, as well as latency to the three sleep states were calculated. Spectral power, coherence, and Lempel Ziv Complexity of the brain oscillations were estimated. Finally, cognitive performance was evaluated by means of the Canine Dementia Scale Questionnaire and a battery of cognitive tests. Correlations between age, cognitive performance and sleep-wakefulness cycle macrostructure and electroencephalographic features were calculated.

Results

Dogs with higher dementia scores and with worse performance in a problem-solving task spent less time in NREM and REM sleep. Additionally, quantitative electroencephalographic analyses showed differences in dogs associated with age or cognitive performance, some of them reflecting shallower sleep in more affected dogs.

Discussion

Polysomnographic recordings in dogs can detect sleep-wakefulness cycle changes associated with dementia. Further studies should evaluate polysomnography's potential clinical use to monitor the progression of canine cognitive dysfunction syndrome.
Cross-sectional analysis of Piroplasma species-infecting camel (Camelus dromedaries) in Egypt using a multipronged molecular diagnostic approach
Authors: Mahdy Olfat A. , Nassar Ahmed M. , Elsawy Bassma S. M. , Alzan Heba F. , Kandil Omnia M. , Mahmoud Mona S. , Suarez Carlos E.
Published: April 2023

Camel piroplasmosis is a tick-borne disease (TBD) caused by hemoprotozoan parasites. Hereby, we describe a cross-sectional study aiming at identifying Piroplasma spp.-infecting camels in Egypt using a multipronged molecular diagnostic approach. A total of 531 blood samples from camels (Camelus dromedarius) were collected from slaughterhouses at different governorates in Egypt for analysis during the period from June 2018 to May 2019. Piroplasma spp. was identified using microscopical examination and several different and sequential polymerase chain reaction (PCR) assays targeting the 18S rRNA genes. The overall prevalence of Piroplasma spp. in microscopical and molecular analyses in the samples was 11% (58/531) and 38% (203/531), respectively. Further discriminative multiplex PCR analysis targeting the 18S rRNA gene applied on all Piroplasma spp.-positive samples allowed the detection of Theileria equi (41%), Babesia caballi (5.4%), Babesia bigemina (0.5%), and Babesia bovis (4%). Additionally, the blast analysis of nested (n) PCR, targeting the V4 region, amplicon sequences resulted in the identification of B. vulpes (22%), Babesia sp. (9%), and Theileria sp. (3%). Overall, the results of this study confirmed the high prevalence of TBDs caused by several types of piroplasm hemoparasites in camel and suggests the need for future interventions aimed at improving the control of these potentially debilitating diseases that may be t-hreatening important economic resources and food security in Egypt.
Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya–Watson Regression
Authors: Konstantinov Andrei , Kirpichenko Stanislav , Utkin Lev
Published: April 2023

A new method for estimating the conditional average treatment effect is proposed in this paper. It is called TNW-CATE (the Trainable Nadaraya–Watson regression for CATE) and based on the assumption that the number of controls is rather large and the number of treatments is small. TNW-CATE uses the Nadaraya–Watson regression for predicting outcomes of patients from control and treatment groups. The main idea behind TNW-CATE is to train kernels of the Nadaraya–Watson regression by using a weight sharing neural network of a specific form. The network is trained on controls, and it replaces standard kernels with a set of neural subnetworks with shared parameters such that every subnetwork implements the trainable kernel, but the whole network implements the Nadaraya–Watson estimator. The network memorizes how the feature vectors are located in the feature space. The proposed approach is similar to transfer learning when domains of source and target data are similar, but the tasks are different. Various numerical simulation experiments illustrate TNW-CATE and compare it with the well-known T-learner, S-learner, and X-learner for several types of control and treatment outcome functions. The code of proposed algorithms implementing TNW-CATE is publicly available.
UAV Dynamic Object Tracking with Lightweight Deep Vision Reinforcement Learning
Authors: Nguyen Hy , Thudumu Srikanth , Du Hung , Mouzakis Kon , Vasa Rajesh
Published: April 2023

Several approaches have applied Deep Reinforcement Learning (DRL) to Unmanned Aerial Vehicles (UAVs) to do autonomous object tracking. These methods, however, are resource intensive and require prior knowledge of the environment, making them difficult to use in real-world applications. In this paper, we propose a Lightweight Deep Vision Reinforcement Learning (LDVRL) framework for dynamic object tracking that uses the camera as the only input source. Our framework employs several techniques such as stacks of frames, segmentation maps from the simulation, and depth images to reduce the overall computational cost. We conducted the experiment with a non-sparse Deep Q-Network (DQN) (value-based) and a Deep Deterministic Policy Gradient (DDPG) (actor-critic) to test the adaptability of our framework with different methods and identify which DRL method is the most suitable for this task. In the end, a DQN is chosen for several reasons. Firstly, a DQN has fewer networks than a DDPG, hence reducing the computational resources on physical UAVs. Secondly, it is surprising that although a DQN is smaller in model size than a DDPG, it still performs better in this specific task. Finally, a DQN is very practical for this task due to the ability to operate in continuous state space. Using a high-fidelity simulation environment, our proposed approach is verified to be effective.
An Enneagram Approach to Strategy
Authors: Tlemsani Issam , Mohamed Hashim Mohamed Ashmel , Matthews Robin , Ndrecaj Vera , Mason-Jones Rachel
Published: April 2023

This conceptual paper examines how Enneagram as a personality typing system could be adopted as a meta-model across multiple domains. The enneagram strategy is a structural typology that many organisations and individuals use to effectively understand their business profiles and interpersonal patterns, despite scholars showing concerns about its robustness and dynamism. This paper extends the argument as to how the mechanics of the Enneagram are intrinsically interrelated with (a) organisational systems and networks, (b) organisational grammar, (c) supply chains, and (d) creativity. It also emphasizes the importance/close association of the Enneagram tool with interdependence, business model, networks, statics, and system dynamics. The paper uses a combination of research methods (theoretical, exploratory, and descriptive) to evaluate the adaptability of the enneagram. The findings demonstrate that enneagram as a strategy could be applied to various business phenomena but requires more cross-domain empirical research. The enneagram can also be used to develop meta-models/toy models that can relate to the organisational outcomes by integrating tangible and intangible process assets. This paper reliably lays a set of principles/foundations to launch the enneagram approach to a complex, broad, systematic, and creative scope.
Aerodynamic Effects of a Wing Surface Heat Exchanger
Authors: Habermann Anaïs Luisa , Khot Ankit , Lampl David Emanuel , Perren Christof
Published: April 2023

One challenge for the design and analysis of hybrid electric aircraft configurations is an increased demand in the rejection of excess waste heat. A wing surface heat exchanger concept, which is explored as part of the IMOTHEP project, foresees transferring heat from the propulsive electrical components to the wing surface of the aircraft. Here, heat is mainly dissipated and transported by forced convection. The present study focuses on the analysis of the impact of heat rejection via the wing surface on the wing’s heat transfer and aerodynamic efficiency characteristics. For this purpose, RANS CFD studies of 2D airfoils and a 3D wing propeller geometry of a regional turboprop configuration in representative flight conditions (take off, cruise, and taxi in) are carried out. For each condition, the influence of defining parameters, such as altitude, freestream velocity, angle of attack, surface temperature, and propeller thrust is explored. It is shown that, when increasing the wing surface temperature compared against the freestream temperature, the aerodynamic efficiency of the wing deteriorates for all flight conditions. In reference cruise conditions for example, the lift-to-drag ratio decreases by 4%, while the average heat transfer coefficient is reduced by almost 20% when increasing the surface temperature by 300 K. Furthermore, the propeller slipstream enhances the wing’s heat transfer capacity significantly.
Research on the Pre-Warning Method of Aircraft Long Landing Based on the XGboost Algorithm and Operation Characteristics Clustering
Authors: Liu Yinfu , Sun Ruishan , He Peng
Published: April 2023

Long landing hazardous events (long landings) are regarded as the most common unsafe events during an aircraft’s landing phase and are significantly influenced by pilots’ leveling operations. This paper proposes a pre-warning method for long aircraft landings based on operation characteristics clustering to better prevent the occurrence of long landing events and develop pre-warning technology for long aircraft landings applicable to actual civil aviation aircraft operations. Based on the quick access recorder (QAR) flight data of a Boeing B737-800 fleet, the Gaussian mixture model (GMM) clustering method was employed to cluster, group, analyze, and evaluate the pilot operation characteristics utilizing the relative indicators of aircraft speed in the takeoff and landing phases as the measurement indices. Moreover, a long landing pre-warning model was developed based on the eXtreme Gradient Boosting (XGBoost) algorithm to account for the overall characteristics of various operations. The complete accuracy, recall ratio, and precision of the long landing pre-warning method based on pilot operation characteristics clustering reached 89.66%, 89.16%, and 92.50%, respectively, in the test of the pre-warning model, demonstrating a significant improvement over those of the pre-warning model without considering the operation characteristics and presenting a more effective pre-warning effect. Optimizing the long landing pre-warning model with pilot operation characteristics can effectively improve the model’s pre-warning capabilities, assist the crew in making accurate decisions, and prevent unsafe events during aircraft landing.
Droplet Collection Efficiency Regularity of NACA0012 Airfoil Based on the Eulerian Method
Authors: Wu Jie , Xu Quanyong , Wu Feng , Xia Quanzhong , Xu Qiannan , Li Shufeng
Published: April 2023

Obtaining droplet collection efficiency (DCE) is vital for icing numerical simulations. A droplet impact model based on the Eulerian two-phase flow model was established in this work to analyze the influence of different incoming flow parameters on DCE. Then, the mathematical regularity of the DCE distribution was explored using the parametric description, and the functional relation of the regularity between the incoming condition and the DCE distribution was accomplished. The results showed that the calculated DCE of NACA0012 and the two-dimensional cylinder matched well with the test data. The incoming flow velocity and droplet size, rather than the liquid water content (LWC) of the incoming flow, affected the collection efficiency significantly. The DCE distribution under different conditions was normalized to the same mathematical form with the peak collection efficiency and maximum position. The mathematical form had a highly normal distribution, which was expressed with good regularity of the Reynolds number and droplet diameter. Regularity can greatly reduce the amount of calculation and improve the calculation accuracy, which plays a positive role in the numerical prediction of the icing problem.
Risk Quantification and Visualization Method for Loss-of-Control Scenarios in Flight
Authors: Wang Guozhi , Pei Binbin , Xu Haojun , Lv Maolong , Zhao Zilong , Bu Xiangwei
Published: April 2023

This paper proposes a flight risk analysis method that combines risk assessment and visual deduction to study the causes of flight accidents, specifically the loss of control caused by failure factors. The goal is to explore the impact of these failure factors on loss-of-control events and illustrate the risk evolution under different scenarios in a clear and intuitive manner. To achieve this, the paper develops a failure scenario tree to guide flight simulations under different loss-of-control scenarios. The next step involves developing a multi-parameters risk assessment method that can quantify flight risk at each time step of the flight simulation. This assessment method uses entropy weight and a grey correlation algorithm to assign variable weights to the different parameters. Finally, the paper presents the visual deduction of the risk evolution process under different loss-of-control scenarios using a risk tree that concisely represents the time-series risk assessment results and failure logical chains. Taking three common failure factors (actuator failure, engine failure, and wing icing) as cases, the paper designs 25 different loss-of-control scenarios to demonstrate the flight risk analysis method. By comparing the risk evolution process under different loss-of-control scenarios, the paper explores the impact of the failure factors on flight safety. The analysis results indicate that this method combines risk analysis from both individual and global perspectives, enabling effective analysis of risk evolution in loss-of-control events.
Effects of Iron Nanoparticles Addition on Bacterial Community and Phytotoxicity in Aerobic Compost of Pig Manure
Authors: Yang Wenqing , Zhuo Qian , Zhong Yuanping , Chen Qinghua , Chen Zuliang
Published: April 2023

In China, the treatment of pig manure for land application is an important issue. In this paper, green synthesized iron nanoparticles (G-nFe) were evaluated for their effectiveness in the aerobic composting of pig manure. G-nFe were evenly mixed into the compost, and the pH and oxidation-reduction potential (ORP) of the compost in the presence of G-nFe both decreased. FTIR showed that G-nFe promoted the formation of humus during composting. The addition of G-nFe (200 mL kg−1) to the compost also promoted bacterial growth, significantly increasing the colony-forming units (CFU, up to 25.6 × 104 CFU mL−1) and OD600 (up to 0.634) in 5 days. Furthermore, G-nFe promoted the fermentation of the pig manure, thus reducing the phytotoxicity of the compost produced. For example, the final volatile solids (VS) degradation rate and seed germination index (GI) of the compost were the highest and reached 20.8% and 0.76%, respectively. Finally, G-nFe improved both the bacterial diversity and community richness of the compost. This indicated that the addition of G-nFe could result in the prolonging of the acidic fermentation time during composting, leading to increased compost maturity. Overall, the beneficial impact of G-nFe on compost was far greater than the potential harm to bacterial communities in the compost and perceived phytotoxicity.
Enhancing Zinnia (Zinnia elegans Jacq.) Seed Quality through Microwaves Application
Authors: Szopińska Dorota , Dorna Hanna
Published: April 2023

In organic farming, microwave irradiation can be used as an alternative to standard chemical seed treatment. The increase in temperature during this treatment may negatively affect the germination of low-quality seeds. The aim of the study was to evaluate the effect of microwaves on germination and the health of zinnia seeds using four seed samples varying in initial seed quality. Seeds were placed in a beaker with distilled water and irradiated at power output levels of 500, 650 and 750 W for 30, 35, 40, 45 and 50 s. Controls were untreated seeds, seeds treated with fungicide and seeds soaked in water for 30, 35, 40, 45 and 50 s. Germination and health tests were performed for controls and microwave-treated seeds. Analyzed samples differed in seed quality and response to microwave irradiation. Improvement in seed germination after microwave treatment was observed in three of the tested samples. The fungi Alternaria alternata, A. zinniae and Fusarium spp. prevailed on the seeds. Microwave treatment, especially at power outputs of 650 and 750 W, usually positively affected seed health, significantly increasing the number of seeds free of fungi, but when water temperature during treatment exceeded 60 °C significant deterioration in germination parameters was observed in all tested samples.
Host-Plant Switching Impacts Susceptibility and Biochemical Responses of Cnaphalocrocis medinalis to Abamectin and Chlorpyrifos
Authors: Guo Jiawen , Cheng Yisha , Zhao Xiaoyu , Qian Jianing , Lu Zhongxian , Lu Yanhui , Dan Yihao , Xu Hongxing , Wu Yan
Published: April 2023

Insect tolerance to insecticides is closely related to the host plant. Migratory insects flying downwind and landing randomly may face host-plant switching after migration. However, it is not clear whether host-plant switching affects the tolerance of migratory insects to insecticides. In the present work, Cnaphalocrocis medinalis, a migratory pest destructive to rice, was studied to explore this issue. The results show that the host-plant switch reduced the susceptibility of rice and wheat larvae populations to abamectin but increased that of wheat larvae populations to chlorpyrifos, indicating that host switching resulted in different tolerance to different insecticides. Enzyme activity determination showed that, although abamectin and chlorpyrifos affect the activities of detoxification enzymes (carboxylesterase, multifunctional oxidase, and glutathione S-transferases), antioxidant enzymes (superoxide dismutase, peroxidase, and catalase), and acetylcholinesterase at sublethal dosages, the effect depends on the host plant and insecticide species. Overall, our findings show that the induction of C. medinalis by host switching affects its susceptibility and biochemical responses to abamectin and chlorpyrifos. Insecticides against C. medinalis should be used with consideration of the potential impact of host switching. Reasonable selection and usages of insecticides can help in the resistance management and control of migratory insects.
Pathogenicity and Genetic Variations in Magnaporthe oryzae Isolates from One Rice Variety Planting in Paddy and Upland Fields
Authors: Wang Ziyi , Wu Qi , Guo Liwei , Pu Xin , Wang Chun , Shi Yuhan , Gan Yulu , Li Chengyun , Wang Yi
Published: April 2023

Rice is the most important crop for worldwide consumers. The water utilization of rice planting is more than 50% of agricultural water in China, and it is necessary to breed water-saving and drought-resistant rice. The rice variety Dianheyou 615 can be planted in the paddy and upland fields, which satisfies rice production farmers in mountainous regions of Yunnan. We aimed to explore the variations in Magnaporthe oryzae isolates collected from Dianheyou 615 planted in paddy or upland fields. Through pathogenicity tests, we found that most isolates had the highest pathogenicities, but there were no significant differences between the paddy and upland isolates. By a combination of monogenetic and elite rice lines, with a further resistance assessment, the monogenetic lines with Pi9, Diantun 506, and Lvhan 1 displayed better resistances. Moreover, we re-sequenced 15 isolates to explore their genetic variations. Our results showed that the source of the upland isolates may have been the offspring of the paddy isolates, but there were many genes with specifically found SNPs in two populations that would develop subdivisions after long-time planting. Overall, we compared the pathogenicities and genetic variations in blast isolates from the planting of Dianheyou 615 in paddy and upland fields, which provided references for the influence of the planting environment on population subdivisions.
Vernalization Promotes GA-Mediated Bolting Initiation via the Inhibition of ABA and JA Biosynthesis
Authors: Zhao Lijuan , Li Shengnan , Yu Qingyang , Zhang Chunxue , Wang Liumin , Jiang Yichen , Wu Zedong , Pi Zhi
Published: April 2023

To understand the relationship between vernalization and endogenous phytohormones on bolting, phytohormone levels and transcriptome changes were measured by LC-MS/MS and RNA sequencing before vernalization (CK), at the end of 16 weeks of vernalization (Vel) and at 5 days after vernalization (Re). A total of 32 phytohormone compounds significantly changed after vernalization; especially, the content of abscisic acid (ABA) and jasmonic acid (JA) was dramatically decreased more than sixteen and three times in the Vel and Re samples. In addition, GA19 accumulated after vernalization, while the content of GA53 and GA20 decreased. A total of 7471 differentially expressed genes (DEGs) were identified in response to vernalization. These DEGs were enriched with GO terms including response to stimulus (GO:0050896), response to hormone (GO:0009725) and shoot system development (GO:0048367). KEGG mapping indicated that 16, 13 and 11 DEGs were involved in gibberellic acid (GA), ABA and JA biosynthesis, suggesting a negative role of vernalization in phytohormone biosynthesis. Vernalization also repressed the expression of BvABFs and BvMYC2s, implying the inhibition of ABA and JA signalling. Additionally, vernalization plays a positive role in GA signalling, owing to the down-regulation of BvDELLAs. We also found that GA3-induced bolting could be retarded by exogenous ABA and methyl jasmonate (MeJA). In total, our results suggest that vernalization can promote GA-induced bolting by decreasing BvDELLA repressors of GA signalling and eliminating the antagonistic effects of ABA and JA.
Mealworm Frass as a Potential Organic Fertilizer in Synergy with PGP-Based Biostimulant for Lettuce Plants
Authors: Fuertes-Mendizábal Teresa , Salcedo Isabel , Huérfano Ximena , Riga Patrick , Estavillo José María , Ávila Blanco David , Duñabeitia Miren Karmele
Published: April 2023

This study explores the potential use of frass, the larval excrement residue obtained from mealworm rearing, as organic fertilizer for crops. Its high organic matter content means that its joint application with a biostimulant based on efficient microorganisms, favoring its mineralization, is of interest. An experiment with lettuce plants (Lactuca sativa L.) was conducted with two factors and six replicates under greenhouse conditions. The first factor was frass amendment at 0%, 1%, 2.5%, and 5% of the peat substrate, and the second factor was a Bacillus-based BS at two levels, with and without efficient microorganism application. The results reveal that frass shows great potential as an organic fertilizer, providing macronutrients and increasing lettuce aerial biomass, although its effect is mediated by the application rate. Rates of 2.5% or higher proved negative for lettuce plant growth, especially root development, probably due to an increased incidence of potentially pathogenic fungi. The negative effect of medium–high frass rates was counteracted by the addition of a PGP-based biostimulant, enhancing lettuce plant nutrient uptake, aerial biomass, and quality in terms of succulence, but also favoring microbial diversity in the rhizosphere, increasing the incidence of beneficial microorganisms, and decreasing potentially pathogenic fungi. This positive synergy observed between frass and the PGP-based biostimulant is of interest for the design of new organic fertilization strategies.
Modeling Soil–Plant–Machine Dynamics Using Discrete Element Method: A Review
Authors: Walunj Avdhoot , Chen Ying , Tian Yuyuan , Zeng Zhiwei
Published: April 2023

The study of soil–plant–machine interaction (SPMI) examines the system dynamics at the interface of soil, machine, and plant materials, primarily consisting of soil–machine, soil–plant, and plant–machine interactions. A thorough understanding of the mechanisms and behaviors of SPMI systems is of paramount importance to optimal design and operation of high-performance agricultural machinery. The discrete element method (DEM) is a promising numerical method that can simulate dynamic behaviors of particle systems at micro levels of individual particles and at macro levels of bulk material. This paper presents a comprehensive review of the fundamental studies and applications of DEM in SPMI systems, which is of general interest to machinery systems and computational methods communities. Important concepts of DEM including working principles, calibration methods, and implementation are introduced first to help readers gain a basic understanding of the emerging numerical method. The fundamental aspects of DEM modeling including the study of contact model and model parameters are surveyed. An extensive review of the applications of DEM in tillage, seeding, planting, fertilizing, and harvesting operations is presented. Relevant methodologies used and major findings of the literature review are synthesized to serve as references for similar research. The future scope of coupling DEM with other computational methods and virtual rapid prototyping and their applications in agriculture is narrated. Finally, challenges such as computational efficiency and uncertainty in modeling are highlighted. We conclude that DEM is an effective method for simulating soil and plant dynamics in SPMI systems related to the field of agriculture and food production. However, there are still some aspects that need to be examined in the future.
Local Agro-Environmental Conditions Impact Fruit Quality, Sensory Properties and Consumer Acceptance of Long Shelf-Life Tomatoes
Authors: Cammareri Maria , Sinesio Fiorella , Peparaio Marina , Pons Clara , Romero del Castillo Roser , Saggia Civitelli Eleonora , Vitiello Antonella , Granell Antonio , Casals Joan , Grandillo Silvana
Published: April 2023

European long shelf-life (LSL) tomato landraces can be classified into two main groups: the Italian group, including ‘Piennolo’ landraces, and the Spanish group, including the ‘Penjar’ and ‘Ramellet’ landraces. In this study, a partially common set of ‘Piennolo’ and ‘Penjar-Ramellet’ varieties was grown in Italy and Spain to evaluate the effect of different agro-environmental and storage conditions on fruit quality and shelf-life. Overall, both Italian and Spanish LSL genotypes lost their peculiar phenotype in terms of physicochemical properties and shelf-life behavior when not grown in their original agro-environment. To better understand the sensory attributes that drive consumers’ preferences, all varieties were characterized using descriptive sensory analysis combined with hedonic tests. The evaluations were conducted postharvest on raw and processed products according to the country’s culinary tradition (baked in Italy; spread on bread in Spain). Sensory description by trained panels conducted on raw and processed products highlighted different sensory profiles between the two LSL tomato groups. In the ‘Piennolo’ group, a reduction in sensory diversity among the genotypes was observed in the baked products compared to the raw ones, while this trend was not observed for the ‘Penjar-Ramellet’ group. None of the varieties fully met the consumers’ preferences.