bluuebunny/crossref_metadata_2025 huggingface dataset:
Explainability in medicine in an era of AI-based clinical decision support systems
Authors: Pierce Robin L. , Van Biesen Wim , Van Cauwenberge Daan , Decruyenaere Johan , Sterckx Sigrid
Published: September 2022

The combination of “Big Data” and Artificial Intelligence (AI) is frequently promoted as having the potential to deliver valuable health benefits when applied to medical decision-making. However, the responsible adoption of AI-based clinical decision support systems faces several challenges at both the individual and societal level. One of the features that has given rise to particular concern is the issue of explainability, since, if the way an algorithm arrived at a particular output is not known (or knowable) to a physician, this may lead to multiple challenges, including an inability to evaluate the merits of the output. This “opacity” problem has led to questions about whether physicians are justified in relying on the algorithmic output, with some scholars insisting on the centrality of explainability, while others see no reason to require of AI that which is not required of physicians. We consider that there is merit in both views but find that greater nuance is necessary in order to elucidate the underlying function of explainability in clinical practice and, therefore, its relevance in the context of AI for clinical use. In this paper, we explore explainability by examining what it requires in clinical medicine and draw a distinction between the function of explainability for the current patient versus the future patient. This distinction has implications for what explainability requires in the short and long term. We highlight the role of transparency in explainability, and identify semantic transparency as fundamental to the issue of explainability itself. We argue that, in day-to-day clinical practice, accuracy is sufficient as an “epistemic warrant” for clinical decision-making, and that the most compelling reason for requiring explainability in the sense of scientific or causal explanation is the potential for improving future care by building a more robust model of the world. We identify the goal of clinical decision-making as being to deliver the best possible outcome as often as possible, and find—that accuracy is sufficient justification for intervention for today’s patient, as long as efforts to uncover scientific explanations continue to improve healthcare for future patients.
Mild cognitive impairment is associated with low copy number of ribosomal genes in the genomes of elderly people
Authors: Veiko Natalia N. , Ershova Elizaveta S. , Veiko Roman V. , Umriukhin Pavel E. , Kurmyshev Marat V. , Kostyuk Georg P. , Kutsev Sergey I. , Kostyuk Svetlana V.
Published: September 2022

Introduction: Mild cognitive impairments (MCI) accompanying aging are associated with oxidative stress. The ability of cells to respond to stress is determined by the protein synthesis level, which depends on the ribosomes number. Ribosomal deficit was documented in MCI. The number of ribosomes depends, together with other factors, on the number of ribosomal genes copies. We hypothesized that MCI is associated with low rDNA CN in the elderly person genome.

Materials and Methods: rDNA CN and the telomere repeat (TR) content were determined in the DNA of peripheral blood leukocytes of 93 elderly people (61–91 years old) with MCI and 365 healthy volunteers (16–91 years old). The method of non-radioactive quantitative hybridization of DNA with biotinylated DNA probes was used for the analysis.

Results: In the MCI group, rDNA CN (mean 329 ± 60; median 314 copies, n = 93) was significantly reduced (p < 10–15) compared to controls of the same age with preserved cognitive functions (mean 412 ± 79; median 401 copies, n = 168) and younger (16–60 years) control group (mean 426 ± 109; median 416 copies, n = 197). MCI is also associated with a decrease in TR DNA content. There is no correlation between the content of rDNA and TR in DNA, however, in the group of DNA samples with rDNA CN > 540, TR content range was significantly narrowed compared to the rest of the sample.

Conclusion: Mild cognitive impairment is associated with low ribosomal genes copies in the elderly people genomes. A low level of rDNA CN may be one of the causes of ribosomal deficit that was documented in MCI. The potential possibilities of using the rDNA CN indicator as a prognostic marker characterizing human life expectancy are discussed.
Mechanical properties of PVC-based wood–plastic composites effected by temperature
Authors: Li Jile , Huo Ruili , Liu Wenyi , Fang Hai , Jiang Lei , Zhou Ding
Published: September 2022

Compared with traditional wooden building materials, polyvinyl chloride (PVC)-based wood–plastic composites have advantages of good weather resistance, easy processing capability, energy conservation, and environmental protection and have been popular and widely used in the field of civil construction and garden engineering in recent years. Due to the difference in the thermal expansion coefficient between its component materials, the stress will accumulate in the wood–plastic composites (WPCs) when the temperature changes, which will affect the mechanical properties of the material and structure. In order to explore the changes in mechanical properties of WPCs under different temperatures and achieve a safe and controllable design, the differential scanning calorimetry (DSC) method was used in this study to measure the glass transition temperature of the WPC between 78.45°C and 88.30°C, and the glass transition temperature (Tg) was about 83.54°C. The tensile, compressive, and bending mechanical property tests of PVC-based wood–plastic composite materials under different temperatures were carried out in the ambient temperature chamber to obtain the failure characteristics, the load–displacement curve, and the influence of temperature on their mechanical properties.
Upregulation of circ_0008812 and circ_0001583 predicts poor prognosis and promotes breast cancer proliferation
Authors: Lin Hong , Long Fangyi , Zhang Xiqian , Wang Pinghan , Wang Ting
Published: September 2022

Background: Accumulating evidence suggests that circular RNAs (circRNAs) are highly correlated with tumor progression and pathogenesis in breast cancer. Whereas, their regulatory roles and corresponding mechanisms in breast cancer are still not exhaustive. Thus, we intended to establish circRNA-mediated competive endogenous RNA (ceRNA) network to uncover the possible roles and clinical implications of circRNAs in breast cancer.

Methods: Microarray and RNA-sequencing (RNA-seq) data were download from GEO and TCGA database to screen for differentially expressed RNAs (DEcircRNAs, DEmiRNAs, DEmRNAs) in breast cancer. By implementing online databases, we established ceRNA networks, performed gene set enrichment analysis, constructed protein-protein interaction (PPI) networks, and assessed the expression levels and prognostic significance of hub genes. Subsequently, we explored the functions of prognosis-related genes and constructed gene-drug interaction networks. Finally, the functional roles of DEcircRNAs in breast cancer were revealed via MTT and colony formation assay.

Results: Based on the identified 8 DEcircRNAs, 25 miRNAs and 216 mRNAs, a ceRNA regulatory network was established. Further analysis revealed that prominent enrichments were transcription factor binding, transforming growth factor-beta (TGF-β) and Apelin signaling pathway etc. PPI network and survival curves analysis showed that elevated levels of hub genes (RACGAP1 and KPNA2) were associated with poorer prognosis. They were found to be positively relevant to cell cycle and proliferation. Then a prognostic sub-network of ceRNA was constructed, consisting of 2 circRNAs, 4 miRNAs and 2 mRNAs. The gene-drug interaction network showed that numerous drugs could regulate the expression of these two prognosis-related genes. Functional experiments showed that depletion of circ_0008812 and circ_0001583 could significantly inhibit the proliferation of MCF-7 cells.

Conclusion: Our study constructed 4 prognostic regulatory axes that are significantly correlated with tumor prognosis in breast cancer patients, and uncover the roles of circ_0008812 and circ_0001583 in breast cancer, providing a new perspective into the molecular mechanisms of breast cancer pathogenesis.
Aggregation behavior of nanoparticles: Revisiting the phase diagram of colloids
Authors: Bini Margherita , Brancolini Giorgia , Tozzini Valentina
Published: September 2022

Surface functionalization of metal nanoparticles (NPs), e.g., using peptides and proteins, has recently attracted a considerable attention in the field of design of therapeutics and diagnostics. The possibility of diverse functionalization allows them to selectively interact with proteins, while the metal core ensures solubility, making them tunable therapeutic agents against diseases due to mis-folding or aggregation. On the other hand, their action is limited by possible self-aggregation, which could be, however, prevented based on the full understanding of their phase diagram as a function of the environmental variables (temperature, ionic strength of the solution, concentration) and intrinsic characteristics (size, charge, amount, and type of functional groups). A common modeling strategy to study the phase behavior is to represent the NPs as spheres interacting via effective potentials implicitly accounting for the solvation effects. Their size put the NPs into the class of colloids, albeit with particularly complex interactions including both attractive and repulsive features, and a consequently complex phase diagram. In this work, we review the studies exploring the phases of these systems starting from those with only attractive or repulsive interactions, displaying a simpler disperse-clustered-aggregated transitions. The phase diagram is here interpreted focusing on the universal aspects, i.e., those dependent on the general feature of the potentials, and available data are organized in a parametric phase diagram. We then consider the potentials with competing attractive short range well and average-long-range repulsive tail, better representing the NPs. Through the proper combination of the attractive only and repulsive only potentials, we are able to interpret the appearance of novel phases, characterized by aggregates with different structural characteristics. We identify the essential parameters that stabilize the disperse phase potentially useful to optimize NP therapeutic activity and indicate how to tune the phase behavior by changing environmental conditions or the NP chemical–physical properties.
Comparative pharmacokinetic study of the five anti-inflammatory active ingredients of Inula cappa in a normal and an LPS-induced inflammatory cell model
Authors: Huang Jing , Chen Ruixing , Zhou Jie , Zhang Qing , Xue Cun , Li Yueting , Zheng Lin , Huang Yong , Wang Qun , Chen Yi , Gong Zipeng
Published: September 2022

Inula cappa is a commonly used medicine in the Miao area of Guizhou Province in China. We established an in vitro inflammatory model of mouse macrophage RAW264.7 cells to study the different pharmacokinetics of five anti-inflammatory active ingredients in the I. cappa extract namely luteolin (LUT), chlorogenic acid (CA), cryptochlorogenic acid (CCA), 3,4-dicaffeoylquinic acid (3,4-DCQA) and 4,5-dicaffeoylquinic acid (4,5-DCQA), in a normal and an inflammatory cell model. First, RAW264.7 cells were treated in vitro with l μg/mL lipopolysaccharide (LPS) for 24 h to establish an inflammatory cell model. Then, the pharmacokinetic characteristics of the five ingredients were compared in normal and inflammatory cells after treatment with 200 μg/ml and 800 μg/ml of I. cappa extracts. After treatment with 1 μg/ml LPS for 24 h, the volume of RAW264.7 cells was increased, the morphology was changed, the antennae were obvious, and the secretion of inflammatory factors nitric oxide and TNF-α was increased. The pharmacokinetics results showed that the five ingredients in normal and inflammatory cells exhibited an increase in Cmax and AUC values with increasing doses, and the Cmax and AUC values of five ingredients were positively correlated with the extract concentration. Each of these five ingredients presented nonlinear pharmacokinetic characteristics. After treatment with 200 μg/ml of I. cappa extract, the uptake of five ingredients increased in inflammatory cells, Tmax was prolonged, MRT and t1/2 were prolonged, and CL_F and Vz_F were decreased, while after treatment with 800 μg/ml of I. cappa extract, the uptake of five ingredients decreased, Tmax was prolonged, absorption was faster, and MRT and t1/2 were prolonged. The five analyzed components in I. cappa extract exerted different effects on normal cells and LPS-induced inflammatory cells. Compared to normal cells, the uptake of five ingredients in inflammatory cells was faster and the AUC and Cmax values increased with increasing doses, showing a dose-dependent nonlinear pharmacokinetic profile. These results indicate that the pharmacokinetic effects of the five analyzed ingredients in I. cappa extract are changed in the inflammatory state.
Modeling analysis of the temperature profile and trapped annular pressure induced by thermal-expanded liquid in a deep gas well
Authors: Zhang Bo , Zheng Yushan , Deng Jinrui , Lu Nu , Cao Lihu , Wang Qing , Luo Lihong
Published: September 2022

The trapped annular pressure (TAP) caused by thermal expansion is one of the serious challenges for the safe production of a deep gas well. Therefore, this article proposes a model to calculate the temperature profile of the deep gas well based on the heat transfer process and the gas properties. With the help of the temperature model, the TAP in the tubing–casing annulus is analyzed according to the annular fluid distribution and the volume consistence law. The results indicate that the temperature inside the tubing string decreases faster under higher bottom hole pressure. When the tubing–casing annulus is totally filled with the annular protection liquid, the TAP continues increasing with the production rate. Considering the high production rate, the TAP is inevitable and high enough to damage the integrity of the deep gas well. The nitrogen gas mitigates the TAP by reducing the annular liquid volume and providing the extra space to accommodate the thermal-expanded annular liquid. A good mitigation performance can be achieved no matter how large the production rate is. The mitigation performance can be divided into the fast-decreasing stage, the efficient control stage, and the stable stage. These three stages occur as the nitrogen gas column length increases. The compression of the nitrogen gas volume plays a major role in the fast decrease stage while the reduction of the annular liquid plays a major role in the stable stage. For the best cost-effectiveness, the nitrogen gas column is recommended in the efficient control stage and should not exceed 15%.
Tunable perfect optical absorption in truncated photonic crystals with lossy defects
Authors: Yan Runze , Li Junyang , Zhou Haiyang , Zhao Ying , Liu Fen , Wu Ailing , Du Guiqiang
Published: September 2022

We theoretically investigate tunable optical absorption properties of photonic crystals containing lossy materials as defects. It is found that a lossy defect can induce one or multiple perfect absorption peaks in the bandgap of photonic crystals and the number of the peaks mainly depends on the thickness of the defect layer. On the one hand, multiple complete absorption peaks can also emerge in the photonic bandgap when multiple lossy defects are inserted within the photonic crystals, and the resonant wavelengths of absorption peaks can be modulated by changing the distances among the defects. On the other hand, the optical absorption away from resonant wavelengths is nearly zero in the whole visible range. Such nanostructures can be used to engineer novel optical devices such as tunable single-channel and multi-channel perfect optical absorbers.
Faraday effect in CoPt-CaF2 nanogranular films with hard magnetic property for magnetic-field-free faraday devices
Authors: Kobayashi Nobukiyo , Iwasa Tadayoshi , Ikeda Kenji , Arai Ken-Ichi
Published: September 2022

Magneto-optical Faraday devices, such as optical isolators, require a structure to apply a magnetic field to the incorporated magneto-optical material. The application of a magnetic field hinders the miniaturization and integration of these devices. Nanogranular films show Faraday rotation angles up to 40 times larger than Bi-YIG in the optical communication band (1,550 nm). Nanogranular films are submicron-to several-micrometer-thick and contribute to the miniaturization and integration of optical devices. Here, we introduce (Co-Pt)–(CaF2) nanogranular films exhibiting a magnetic-field-free magneto-optical Faraday effect, which are Co3Pt alloy that are hard magnets with residual magnetization. These nanogranular films exhibit the Faraday effect without requiring a magnetic field owing to their residual magnetization.
A unified method for constructing developable surface pencils interpolating characteristic curves
Authors: Wang Jun , Chen Miaochao , Wang Dongyin
Published: September 2022

Developable surface is a simple and common surface in surface modeling. Geodesic, line of curvature, asymptotic curve, and D-type curve are important characteristic curves on the surfaces. This study gives a unified method for constructing developable surface pencils interpolating these four kinds of characteristic curves. Given a regular space curve R(r), we derive a new condition that a surface pencil P (r, t) interpolating R(r) is developable. The result shows that the condition completely depends on a univalent function λ and an angle θ. By choosing different λ and θ, we can not only control the shape of P (r, t), but also make R(r) become any kind of characteristic curve on P (r, t). Furthermore, we take natural and conjugate curve pairs as those characteristic curves to construct developable surface pairs. Finally, an example of a slant helix shows that the proposed unified method is more general than other methods, and has good interactivity and convenience.
The optimal exercise modality and intensity for hemodialysis patients incorporating Bayesian network meta-analysis and systematic review
Authors: Song Yangyang , Chen Lei , Wang Meng , He Quan , Xue Jinhong , Jiang Hongli
Published: September 2022

Background: Physical inactivity is highly prevalent in patients with hemodialysis, and a large body of evidence reported the positive effect of different exercise modalities on their health outcomes. However, the effective dosage of exercise for hemodialysis patients still requires verification.

Objective: We aimed to determine the most effective exercise intensity and modality for improvements in physical function, blood pressure control, dialysis adequacy, and health-related quality of life for hemodialysis patients.

Design: Systematic review with network meta-analysis of randomized trials.

Data sources: Five electronic databases (PubMed, EMBASE, Web of Science, Cochrane CENTRAL, and Scopus) were searched for randomized controlled trials. Data extraction and quality appraisal were conducted by two authors independently. Data were analyzed by the R (version.3.6.2) and the Stata (version.15.0).

Result: We included 1893 patients involving four exercise modalities and six exercise intensities. Combined training (aerobic exercise plus resistance exercise) has been the top-ranking exercise modality for improving the 6-min walk test (6MWT) (surface under the cumulative ranking curve analysis (SUCRA) score, 90.63), systolic blood pressure control (SUCRA score, 77.35), and diastolic pressure control (SUCRA score, 90.56). Moreover, the top-ranking exercise intensity was moderate–vigorous for 6MWT (SUCRA score, 82.36), systolic blood pressure (SUCRA score, 77.43), and diastolic blood pressure (SUCRA score, 83.75). Regarding dialysis adequacy and health-related quality of life, we found no exercise modality or intensity superior to the placebo.

Conclusion: This network meta-analysis indicated that combined training and moderate–vigorous intensity might be the most effective interventions to improve 6MWT and blood pressure control. This finding helps further guide clinical exercise prescriptions for hemodialysis patients.

Systematic Review Registration: [https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD42021268535].
Hydrocarbon chemistry in the atmosphere of a Warmer Exo-Titan
Authors: Adams Danica , Luo Yangcheng , Yung Yuk L.
Published: September 2022

Hosting a ∼1.5 bar N2 atmosphere and reducing atmospheric composition, Titan has the energy sources needed to drive disequilibrium chemistry and hosts an aerosol layer which shields the surface from incident UV radiation. This world draws parallels to an early Earth-like world (although ∼200 K cooler), and the atmospheric chemistry may be capable of forming relevant prebiotic species. Exo-Titan worlds at close-in orbits host photochemistry relevant to habitability with rich hydrocarbon chemistry. We investigate the effect of stellar type of the host star, equilibrium temperature, incident radiation, and vertical transport efficiency on the production of higher-order hydrocarbons. We find a greater incident radiation (a closer orbit) increases the rate of methane photolysis as well as photolysis of hydrocarbons. A larger H2 abundance and warmer temperature increases the rate of the back reaction H2 + CH3 → CH4 + H, and the temperature dependence is so great that CH3 recycles back into CH4 instead of forming C2H6. A larger H2 abundance and warmer temperature also encourages interesting cycling between C2H2, C2H3, and C2H4via reactions with atomic H.
Characterization of glucose metabolism in breast cancer to guide clinical therapy
Authors: Mei Yingying , Zhao Lantao , Jiang Man , Yang Fangfang , Zhang Xiaochun , Jia Yizhen , Zhou Na
Published: September 2022

Background

Breast cancer (BRCA) ranks as a leading cause of cancer death in women worldwide. Glucose metabolism is a noticeable characteristic of the occurrence of malignant tumors. In this study, we aimed to construct a novel glycometabolism-related gene (GRG) signature to predict overall survival (OS), immune infiltration and therapeutic response in BRCA patients.

Materials and methods

The mRNA sequencing and corresponding clinical data of BRCA patients were obtained from public cohorts. Lasso regression was applied to establish a GRG signature. The immune infiltration was evaluated with the ESTIMATE and CIBERSORT algorithms. The drug sensitivity was estimated using the value of IC50, and further forecasted the therapeutic response of each patient. The candidate target was selected in Cytoscape. A nomogram was constructed via the R package of “rms”.

Results

We constructed a six-GRG signature based on CACNA1H, CHPF, IRS2, NT5E, SDC1 and ATP6AP1, and the high-risk patients were correlated with poorer OS (P = 2.515 × 10−7). M2 macrophage infiltration was considerably superior in high-risk patients, and CD8+ T cell infiltration was significantly higher in low-risk patients. Additionally, the high-risk group was more sensitive to Lapatinib. Fortunately, SDC1 was recognized as candidate target and patients had a better OS in the low-SDC1 group. A nomogram integrating the GRG signature was developed, and calibration curves were consistent between the actual and predicted OS.

Conclusions

We identified a novel GRG signature complementing the present understanding of the targeted therapy and immune biomarker in breast cancer. The GRGs may provide fresh insights for individualized management of BRCA patients.
Irregular Workpiece Template-Matching Algorithm Using Contour Phase
Authors: Su Shaohui , Wang Jiadong , Zhang Dongyang
Published: September 2022

The current template-matching algorithm can match the target workpiece but cannot give the position and orientation of the irregular workpiece. Aiming at this problem, this paper proposes a template-matching algorithm for irregular workpieces based on the contour phase difference. By this, one can firstly gain the profile curve of the irregular workpiece by measuring its radius in orderly fashion and then, calculate the similarity of the template workpiece profile and the target one by phase-shifting and finally, compute the rotation measure between the two according to the number of phase movements. The experimental results showed that in this way one could not only match the shaped workpiece in the template base accurately, but also accurately calculate the rotation angle of the irregular workpiece relative to the template with the maximum error controlled within 1%.
Non-Interactive Decision Trees and Applications with Multi-Bit TFHE
Authors: Paul Jestine , Tan Benjamin Hong Meng , Veeravalli Bharadwaj , Aung Khin Mi Mi
Published: September 2022

Machine learning classification algorithms, such as decision trees and random forests, are commonly used in many applications. Clients who want to classify their data send them to a server that performs their inference using a trained model. The client must trust the server and provide the data in plaintext. Moreover, if the classification is done at a third-party cloud service, the model owner also needs to trust the cloud service. In this paper, we propose a protocol for privately evaluating decision trees. The protocol uses a novel private comparison function based on fully homomorphic encryption over the torus (TFHE) scheme and a programmable bootstrapping technique. Our comparison function for 32-bit and 64-bit integers is 26% faster than the naive TFHE implementation. The protocol is designed to be non-interactive and is less complex than the existing interactive protocols. Our experiment results show that our technique scales linearly with the depth of the decision tree and efficiently evaluates large decision trees on real datasets. Compared with the state of the art, ours is the only non-interactive protocol to evaluate a decision tree with high precision on encrypted parameters. The final download bandwidth is also 50% lower than the state of the art.
Active Fault-Tolerant Control for Quadrotor UAV against Sensor Fault Diagnosed by the Auto Sequential Random Forest
Authors: Ai Shaojie , Song Jia , Cai Guobiao , Zhao Kai
Published: September 2022

Active disturbance rejection control (ADRC) is a model-independent method widely used in passive fault-tolerant control of the quadrotor unmanned aerial vehicle. While ADRC’s effectiveness in actuator fault treatment has been proven, its tolerance to sensor faults requires improvements. In this paper, an ADRC-based active fault-tolerant control (AFTC) scheme is proposed to control the flying attitude against sensor fault for reliability enhancement. Specifically, a semi-model-dependent state tracker is raised to reduce the influence of slow tracking, and accentuate the sensor fault even in varying maneuvers. Derived from the random forest, an enhanced method named auto sequential random forest is designed and applied to isolate and identify faults in real time. Once the tolerance compensation is generated with the fault information, a high-performance AFTC is achieved. The simulation results show that the proposed method can effectively follow the residual when a sensor fault and a change of maneuver occur concurrently. Precise fault information is obtained within 0.04 s, even for small faults on the noise level. The diagnosis accuracy is greater than 86.05% (100% when small faults are excluded), and the identification precision exceeds 97.25%. The short settling time (0.176 s when the small fault is excluded) and modest steady-state error validate the advanced and robust tolerance performance of the proposed AFTC method.
A Novel Deep Learning-Based Relabeling Architecture for Space Objects Detection from Partially Annotated Astronomical Images
Authors: Dumitrescu Florin , Ceachi Bogdan , Truică Ciprian-Octavian , Trăscău Mihai , Florea Adina Magda
Published: September 2022

Space Surveillance and Tracking is a task that requires the development of systems that can accurately discriminate between natural and man-made objects that orbit around Earth. To manage the discrimination between these objects, it is required to analyze a large amount of partially annotated astronomical images collected using a network of on-ground and potentially space-based optical telescopes. Thus, the main objective of this article is to propose a novel architecture that improves the automatic annotation of astronomical images. To achieve this objective, we present a new method for automatic detection and classification of space objects (point-like and streaks) in a supervised manner, given real-world partially annotated images in the FITS (Flexible Image Transport System) format. Results are strongly dependent on the preprocessing techniques applied to the images. Therefore, different techniques were tested including our method for object filtering and bounding box extraction. Based on our relabeling pipeline, we can easily follow how the number of detected objects is gradually increasing after each iteration, achieving a mean average precision of 98%.
Assessment of Potential Conflict Detection by the ATCo
Authors: Delgado-Aguilera Jurado Raquel , Gómez Comendador Víctor Fernando , Zamarreño Suárez María , Pérez Moreno Francisco , Verdonk Gallego Christian Eduardo , Arnaldo Valdés Rosa María
Published: September 2022

The main goal of this article is to analyse the probability of detecting potential conflicts by the Air Traffic Controller (ATCo). The ATCo ensures the safety of aircraft and one of its main functions is collision avoidance. Collision avoidance is known as separation provision and this term means assuring the safe distance between each aircraft by sides, vertical and longitudinal minimums of separation. The air traffic controller must ensure a high level of airspace capacity. The work performance is related to high demands on individual characteristics, knowledge, skills and, of course, air traffic characteristics. In addition to analysing the probability of detecting potential conflicts, the study of the most influential factors on this safety event is considered of special relevance since the ATCo represents the last executive section of the air traffic control system and failure to detect potential conflicts could lead to a possible infringement of the minimum separation distances between aircraft or even a collision. In order to carry out this approach, Bayesian Networks will be used due to their high predictive capacity. In addition, a dual approach based on knowledge and real operational data provided by an ANSP will be used. These data are one of the great advantages of this study compared to those included in the current literature.
Spectrum of Corona Discharges and Electric Arcs in Air under Aeronautical Pressure Conditions
Authors: Riba Jordi-Roger
Published: September 2022

Due to the increase in electrical power demand, future more electric and all-electric aircraft designs will operate at higher voltage levels compared to current aircraft. Due to higher voltage levels and reduced operating pressure, insulation systems will be at risk. Air is the main insulating medium, and it is well known that its dielectric strength decreases considerably with operating pressure. Although electrical discharges can be detected by different techniques, optical methods are very attractive due to their sensitivity and immunity to acoustic and electromagnetic noise typical of aeronautical environments. This work analyzes the UV-visible spectrum of corona discharges and electric arcs in the 10–100 kPa pressure range, which covers most of the aeronautical applications, due to the lack of experimental data for this pressure range. The data presented in this work are important to select the most suitable optical sensors to detect electrical discharges at an early stage, before significant damage occurs. This approach will help implement preventive maintenance plans and increase aircraft safety. The results presented in this paper can also be applied to other areas, such as monitoring of discharges in power lines, particularly those located in high-altitude regions.
Biogas in Uganda and the Sustainable Development Goals: A Comparative Cross-Sectional Fuel Analysis of Biogas and Firewood
Authors: Mukisa Phiona Jackline , Ketuama Chama Theodore , Roubík Hynek
Published: September 2022

Biogas technology has the potential to achieve at least eight of the Sustainable Development Goals (SDGs). This study assessed household biogas consumption against firewood and its socioeconomic and environmental impacts with regard to achieving the SDGs in the Iganga District, Uganda. In addition, factors hindering the adoption of biogas technology were assessed. Data were collected from 314 respondents using a questionnaire, interview, and observation. A mixed analytical approach combined descriptive analysis, multivariate analysis of variance and one-way analysis of variance tests to compare the impacts of biogas and firewood use and identify factors hindering the adoption of biogas technology. Results show that biogas consumption contributed to higher socioeconomic, health and environmental benefits than firewood. Biogas positively impacted SDG7, and indirectly, SDGs 2, 3, 5, 6, 8, 9, and 13. An estimated 46.9% of households perceive biogas as a clean fuel. The factors motivating biogas consumption include its smoke-free nature, women and children having more time to engage in other development activities and reduced time spent on cooking. In conclusion, biogas offers higher impacts on SDGs compared to firewood. Reviewing the current national renewable energy promotion frameworks to provide biogas subsidies to households and investors can contribute to increasing biogas consumption in households.
A Fast Deployable Instance Elimination Segmentation Algorithm Based on Watershed Transform for Dense Cereal Grain Images
Authors: Liang Junling , Li Heng , Xu Fei , Chen Jianpin , Zhou Meixuan , Yin Liping , Zhai Zhenzhen , Chai Xinyu
Published: September 2022

Cereal grains are a vital part of the human diet. The appearance quality and size distribution of cereal grains play major roles as deciders or indicators of market acceptability, storage stability, and breeding. Computer vision is popular in completing quality assessment and size analysis tasks, in which an accurate instance segmentation is a key step to guaranteeing the smooth completion of tasks. This study proposes a fast deployable instance segmentation method based on a generative marker-based watershed segmentation algorithm, which combines two strategies (one strategy for optimizing kernel areas and another for comprehensive segmentation) to overcome the problems of over-segmentation and under-segmentation for images with dense and small targets. Results show that the average segmentation accuracy of our method reaches 98.73%, which is significantly higher than the marker-based watershed segmentation algorithm (82.98%). To further verify the engineering practicality of our method, we count the size distribution of segmented cereal grains. The results keep a high degree of consistency with the manually sketched ground truth. Moreover, our proposed algorithm framework can be used as a great reference in other segmentation tasks of dense targets.
Automatic Tandem Dual BlendMask Networks for Severity Assessment of Wheat Fusarium Head Blight
Authors: Gao Yichao , Wang Hetong , Li Man , Su Wen-Hao
Published: September 2022

Fusarium head blight (FHB) disease reduces wheat yield and quality. Breeding wheat varieties with resistance genes is an effective way to reduce the impact of this disease. This requires trained experts to assess the disease resistance of hundreds of wheat lines in the field. Manual evaluation methods are time-consuming and labor-intensive. The evaluation results are greatly affected by human factors. Traditional machine learning methods are only suitable for small-scale datasets. Intelligent and accurate assessment of FHB severity could significantly facilitate rapid screening of resistant lines. In this study, the automatic tandem dual BlendMask deep learning framework was used to simultaneously segment the wheat spikes and diseased areas to enable the rapid detection of the disease severity. The feature pyramid network (FPN), based on the ResNet-50 network, was used as the backbone of BlendMask for feature extraction. The model exhibited positive performance in the segmentation of wheat spikes with precision, recall, and MIoU (mean intersection over union) values of 85.36%, 75.58%, and 56.21%, respectively, and the segmentation of diseased areas with precision, recall, and MIoU values of 78.16%, 79.46%, and 55.34%, respectively. The final recognition accuracies of the model for wheat spikes and diseased areas were 85.56% and 99.32%, respectively. The disease severity was obtained from the ratio of the diseased area to the spike area. The average accuracy for FHB severity classification reached 91.80%, with the average F1-score of 92.22%. This study demonstrated the great advantage of a tandem dual BlendMask network in intelligent screening of resistant wheat lines.
A Study on the Calibration of Wheat Seed Interaction Properties Based on the Discrete Element Method
Authors: Sugirbay Adilet , Hu Guang-Rui , Chen Jun , Mustafin Zhasulan , Muratkhan Marat , Iskakov Ruslan , Chen Yu , Zhang Shuo , Bu Lingxin , Dulatbay Yerassyl , Mukhamed Bauyrzhan
Published: September 2022

The interaction properties of the seeds have to be calibrated to simulate the realistic behavior of the seed bulk. Here, a simple and accurate calibration method of DEM interaction properties of seeds with adequate equipment to simulate each seed’s behavior remains a challenge. In this research, the rotary drum is chosen as simple equipment to calibrate particle–particle and particle–material interaction properties, as there is a lack of research on whether the rotary drum is adequate equipment to calibrate particle–material interaction properties. Therefore, this article calibrates particle–particle and particle–material static and rolling interaction coefficients using a rotary drum. The calibration of particle–material static and rolling friction coefficients are described using the rotating drum with a 45 degrees inclination. The particle–particle static and rolling friction coefficients were calibrated according to the angle of repose when the rotary drum is vertical.
Quantitative Trait Analysis Shows the Potential for Alleles from the Wild Species Arachis batizocoi and A. duranensis to Improve Groundnut Disease Resistance and Yield in East Africa
Authors: Essandoh Danielle A. , Odong Thomas , Okello David K. , Fonceka Daniel , Nguepjop Joël , Sambou Aissatou , Ballén-Taborda Carolina , Chavarro Carolina , Bertioli David J. , Leal-Bertioli Soraya C. M.
Published: September 2022

Diseases are the most important factors reducing groundnut yields worldwide. In East Africa, late leaf spot (LLS) and groundnut rosette disease (GRD) are the most destructive diseases of groundnut. Limited resistance is available in pure pedigree cultivated groundnut lines and novel sources of resistance are required to produce resistant new varieties. In this work, 376 interspecific lines from 3 different populations derived from crosses with the wild species A. duranensis, A. ipaënsis, A. batizocoi and A. valida were phenotyped for 2 seasons and across 2 locations, Serere and Nakabango, in Uganda. Several genotypes showed a higher yield, a larger seed, an earlier flowering, and similar resistance to the local cultivar checks. Genotypic data was used to construct a linkage map for the AB-QTL population involving the cross between Fleur11 and [A. batizocoi x A. duranensis]4x. This linkage map, together with the phenotypic data was used to identify quantitative trait loci controlling disease resistance. These lines will be useful in combining good agronomic traits and stacking disease resistance to improve the groundnut crop in sub-Saharan Africa.
Molecular Basis of Resistance to Mesosulfuron-Methyl in a Black-Grass (Alopecurus myosuroides Huds.) Population from China
Authors: Qin Xiangyang , Yang Cheng , Hu Mengmeng , Duan Yunxia , Zhang Na , Wang Jinxin , Wang Hengzhi , Liu Weitang
Published: September 2022

Black-grass (Alopecurus myosuroides Huds.) is a common weed in Chinese wheat fields, and has become troublesome due to its evolution of herbicide resistance. One black-grass population (HN-14) collected from a wheat field where herbicides were applied was suspected to be resistant (R) to mesosulfuron-methyl. This study aims to establish a cross-resistance pattern and explore potential resistance mechanisms. The results of a whole-plant dose response assay showed that the resistant (R) population had a high of resistance to mesosulfuron-methyl (33-fold); meanwhile, no synergism of P450s activity inhibitor malathion was observed. The sequencing results revealed that ALS resistance mutation Trp-574-Leu occurred in R plants. The results of in vitro ALS enzyme activity assays also supported that the extractable ALS from R plants were 23.22-fold resistant to mesosulfuron-methyl. In the light of the “R” resistance rating system, HN-14 has evolved RRR and RR resistance to fenoxaprop-P-ethyl, clodinafop-propargyl, haloxyfop-methyl, and fluazifop-P-butyl and R? (resistance may be developing) to pinoxaden, however remains sensitive to imazethapyr, quizalofop-P-ethyl, tralkoxydim, and isoproturon. These results indicated that the mesosulfuron-methyl resistance in the black-grass population HN-14 was driven by a target-site mechanism rather than a nontarget (at least P450s-mediated) mechanism.
GIS-Based Cropland Suitability Prediction Using Machine Learning: A Novel Approach to Sustainable Agricultural Production
Authors: Radočaj Dorijan , Jurišić Mladen
Published: September 2022

The increasing global demand for food has forced farmers to produce higher crop yields in order to keep up with population growth, while maintaining sustainable production for the environment. As knowledge about natural cropland suitability is mandatory to achieve this, the aim of this paper is to provide a review of methods for suitability prediction according to abiotic environmental criteria. The conventional method for calculating cropland suitability in previous studies was a geographic information system (GIS)-based multicriteria analysis, dominantly in combination with the analytic hierarchy process (AHP). Although this is a flexible and widely accepted method, it has significant fundamental drawbacks, such as a lack of accuracy assessment, high subjectivity, computational inefficiency, and an unsystematic approach to selecting environmental criteria. To improve these drawbacks, methods for determining cropland suitability based on machine learning have been developed in recent studies. These novel methods contribute to an important paradigm shift when determining cropland suitability, being objective, automated, computationally efficient, and viable for widespread global use due to the availability of open data sources on a global scale. Nevertheless, both approaches produce invaluable complimentary benefits to cropland management planning, with novel methods being more appropriate for major crops and conventional methods more appropriate for less frequent crops.
Exploring the Simultaneous Effect of Total Ion Concentration and K:Ca:Mg Ratio of the Nutrient Solution on the Growth and Nutritional Value of Hydroponically Grown Cichorium spinosum L.
Authors: Voutsinos-Frantzis Orfeas , Ntatsi Georgia , Karavidas Ioannis , Neofytou Ioannis , Deriziotis Konstantinos , Ropokis Andreas , Consentino Beppe Benedetto , Sabatino Leo , Savvas Dimitrios
Published: September 2022

Nutrient-efficient plants and agricultural systems could tackle issues resulting from conventional agriculture. Spiny chicory (Cichorium spinosum L.), a very adaptive, wild edible vegetable, is gaining commercial interest as a functional food. Floating-raft hydroponics is a method commonly used for the commercial cultivation of leafy vegetables due to numerous advantages compared to soil cultivation. In this paper, the simultaneous effects of different potassium, calcium and magnesium ratios and different electrical conductivity (EC) levels on the growth and mineral composition of hydroponically grown C. spinosum were investigated. Four nutrient solutions (NS) were compared, two NS with low EC (L, 2.4 dS/m) and two with high EC (H, 3.6 dS/m) with K:Ca:Mg ratios of either 50:40:10 or 40:50:10. The results showed no interactions between the two factors. No significant effects were observed on the fresh and dry weight, leaf number and leaf area. High EC levels increased the K content and decreased the Mn and Zn content in the leaf tissues. The 40:50:10 ratio led to increased Ca content in plant tissues. The Nitrate-N was only affected by the EC level and was increased under H conditions, whereas the total-N was not affected.
Interpreting Variety–Location–Fertilizer Interactions to Enhance Foxtail Millet Productivity in Northern China
Authors: Cui Jihan , Xia Xueyan , Zhao Yu , Liu Meng , Xiao Nuoya , Guo Shuai , Lu Yiwei , Li Junxia , Wei Zhimin , Gao Fangchao , Yang Ping , Li Shunguo
Published: September 2022

Foxtail millet (Setaria italica (L.) P. Beauv.) is an important traditional cereal crop in dryland ecological agriculture in China and is widely grown in India, the United States, and Nigeria. It is of significance to understand the variety–location–fertilizer (V–L–F) interaction for highly efficient production. Therefore, a two-year field experiment was conducted with six varieties in five locations, and data were analyzed by combined ANOVA analysis, redundancy analysis (RDA), and additive main multiplicative interaction (AMMI). The results showed that the mean sum of squares was significantly different among years, locations, varieties, fertilizations, and their interactions, except for Y–V and V–F interactions. The contributions of various factors to yield variation varied, location was the largest contributor (38.7%), followed by year (33.6%), and variety and fertilizer contributed 7.1% and 3.2%, respectively. JI25 was widely adapted, and its yield was stable and higher than that of others over diverse environments in two years. The RDA results showed that two principal components explained more than 66.1% of the yield variance, while more than 63.0% of the variances were clustered in the first factor. Excessive single rainfall or total rainfall and air temperature (especially minimum temperature) were significantly associated with the millet yield. The results offered an important reference for variety layout, natural resource potential mining, and formulation of efficient green cultural practices.