Distinct Levels Research Articles

Impact of applied and preceding pressure on performance and reversible swelling of lithium-ion pouch cells with varying microporous separators

During the compression of battery cells in battery pack production, high forces occur temporarily due to the viscoelastic behavior of the cell components. The magnitude of these forces depends on the compression speed. Shortening the production time and, thus, increasing the compression speed is desirable for cost reduction. However, it must be ensured that the cells are not negatively affected by increased forces during production. The impact of these preceding forces, acting on the cell before operation, and the applied force during operation on the performance and the reversible swelling of 5Ah NMC811/graphite lithium-ion pouch cells are investigated in this study. To this end, a universal compression testing machine was adapted to enable high-precision thickness measurements under defined constant pressure and temperature conditions. In addition, the effects of different microporous separators manufactured via dry process and wet process in an otherwise identical cell configuration were investigated. In the test procedure, the pressure was incrementally increased from 0.01MPa to 2.5MPa. Each measurement was performed at the distinct constant pressure levels, followed by a subsequent measurement at a reference pressure of 0.2MPa to evaluate the impact of the preceding step. The results revealed that elevated preceding pressures on the cell can reduce the discharge rate capability on higher C-rates by up to 11%. The discharge rate capability of the cells with the wet-processed separator was more significantly influenced by increasing applied and preceding pressure than for those with the dry-processed separator. It was found that the reversible swelling of the cell was reduced by applying higher pressures, whereas elevated preceding pressure increased the reversible swelling. The results of this study suggest that cells should not be subjected to excessive forces before operation, for instance, during battery pack production, as this can negatively affect performance and swelling behavior. Furthermore, the mechanical stability of the separator during the pack production process should also be considered when designing a cell.

Heterogeneous uncertainty matters! Evidence based on firms' cost management decisions

The literature traditionally treats the uncertainty firms encounter as a whole, neglecting the inherent heterogeneity of uncertainty that prevails in the real world. To address this critical issue, this study employs natural language processing methods to decompose uncertainty into three distinct levels: firm-level, industry-level, and macro-level uncertainty. We then examine the impact of heterogeneous uncertainty on corporate decision-making from a cost management perspective. Our findings indicate that while uncertainty as a whole increases cost stickiness, this effect mainly stems from firm-level uncertainty rather than industry-level and macro-level uncertainty. These findings suggest that firms only respond to uncertainty when they perceive uncertainty at the firm level. Cross-sectional tests indicate that the impact of uncertainty on cost stickiness is more pronounced when firms face higher adjustment costs, lower financing constraints, and lower competitive pressures than otherwise. Additionally, uncertainty diminishes firms' cost elasticity, curtailing their production flexibility. Collectively, our results provide insights into comprehending the internal mechanisms of firms' decision-making in the face of uncertainty.

Non-linear charged dS spacetime and its thermodynamics and Schottky Anomaly

Abstract In this paper, firstly, the conditions and existence region for the coexistence of the black hole and cosmological horizons in Non-linear charged dS (NLC-dS) spacetime are discussed, subsequently, the thermodynamic quantities for which the boundary conditions are satisfied in spacetime in the coexistence region of the two horizons are discussed, and the effective thermodynamic quantities in the NLC-dS spacetime in the coexistence region with two horizons are presented. Based on these, the heat capacity in the coexistence region with two horizons is addressed, the behavior of the heat capacity in the NLC-dS spacetime in the aforementioned region is found to exhibit the characteristics of Schottky specific heat. In order to investigate the intrinsic reason of the heat capacity in spacetime, regarding the two horizons in the NLC-dS spacetime as two distinct energy levels, consequently, the microscopic particles at different horizons exhibit disparate energies. Using the heat capacity relationship between the two-energy level in an ordinary thermodynamic system, the heat capacity in dS spacetime is discussed, it is observed that the behavior of the heat capacity is analogous to that of the two-energy levels in an ordinary thermodynamic system. The number of microscopic particles in the two-level system is approximated by comparing the maximum value of the heat capacity of the system with the maximum value obtained by treating the two horizons in the NLC-dS spacetime as a two-energy-level system of two distinct energies. This conclusion reflects the quantum properties of the coexistence region with two horizons in the NLC-dS spacetime. It provides a new avenue for further study of the thermodynamic properties of black holes and the quantum properties of de Sitter spacetime.

Relationship between perceived value, attitudes, and academic motivation in distance learning among nursing students in rural areas

BackgroundNursing students manifest a distinct level of intellect and comprehension, impacting their attitudes and perceived significance of distance learning in education. This study examined the attitudes, perceived value, and academic motivation surrounding distance learning among Jordanian nursing students, offering insights crucial to optimizing their educational journey.MethodsA descriptive cross-sectional design was used. A convenience sample of 298 undergraduate Jordanian nursing students was recruited from two public universities in rural cities in south Jordan. Data were collected via self-reported instruments (June 2022 to August 2022). A Pearson correlation and independent t-test were used to examine the relationship between variables.ResultsThe mean age of students was 20.9 years (SD = 1.16), and most students have a low perceived value of distance learning (n = 181, 60.7%). Most students (n = 179, 60.1%) have negative attitudes toward distance learning, and only 39.9% reflected positive attitudes. More than half of the participants (n = 166, 55.7%) reflected less academic motivation toward distance learning. Positive significant relationships were found between students’ perceived value of distance learning and their attitudes and academic motivation toward distance learning; low perceived value of distance learning was related significantly with low attitudes (r = 0.844, p < 0.01) and less academic motivation toward it (r = 0.721, p < 0.01).ConclusionNursing students’ perceived value, attitudes, and academic motivation toward DL in rural regions is inadequate. Educators must provide valuable visions to expand the quality of health education in rural universities and improve health care.

Genome-wide analysis and expression characteristics of Small Auxin-up RNAs genes in flax (Linum usitatissimum L.)

Plant auxin is crucial in regulating many aspects of plant growth and development. Small Auxin-up RNAs (SAURs) genes act as the main early auxin response genes and are involved in regulating plant growth and development. Flax is a well-known fiber and oil crop; thus, our study provided a systematic bioinformatics analysis of the SAUR family in flax, including basic parameters, gene structure, chromosomal location, phylogenetic analysis, and cis-acting element analysis. Based on genomic information, 86 LusSAUR genes were identified and separated into eight groups. The gene structure analysis revealed that only two LusSAUR genes have introns. The cis-acting elements related to hormones and stress were abundant in the promoter region of LusSAUR members. Based on the gene expression oligo microarray, LusSAUR genes had tissue-specific expression characteristics in eight different tissues. Quantitative real-time PCR analysis indicated that 10 selected LusSAUR genes could be quickly upregulated following treatment with IAA. The 10 genes displayed distinctive expression levels under hormone treatment (MeJA, ABA, SA) and abiotic stress (PEG, NaCl, CdCl2). This study provides a foundation for further investigations for functional analysis of LusSAURs in flax. Furthermore, it will provide useful insights for further research into the molecular mechanism of regulating hormones and environmental signals in flax growth and development.

Joint [Formula: see text] and Image Reconstruction in Low-Field MRI by Physics-Informed Deep-Learning.

We present a model-based image reconstruction approach based on unrolled neural networks which corrects for image distortion and noise in low-field ( B0 ∼ 50 mT) MRI. Utilising knowledge about the underlying physics, a novel network architecture (SH-Net) is introduced which involves the estimation of spherical harmonic coefficients to guarantee a spatially smooth field map estimate. The SH-Net is integrated in an end-to-end trainable model which jointly estimates the B0-field map as well as the image. Experiments were conducted on retrospectively simulated low-field data of human knees. We compare our model to different model-based approaches at distinct noise levels and various B0-field distributions. Our results show that our physics-informed neural network approach outperforms the purely model-based methods by improving the PSNR up to 11.7% and the RMSE up to 86.3%. Our end-to-end trained model-based approach outperforms existing methods in reconstructing image and B0-field maps in the low-field regime. low-field MRI is becoming increasingly more popular as it enables access to MR in challenging situations such as intensive care units or resource poor areas. Our method allows for fast and accurate image reconstruction in such low-field imaging with B0-inhomogeneity compensation under a wide range of various environmental conditions.

What is generative in generative artificial intelligence? A design-based perspective

Generative artificial intelligence (GenAI) models have attracted tremendous interest since the advent of ChatGPT, raising numerous opportunities and challenges. However, their generative power has not yet been studied, leaving open the question of what is truly generated by these tools. This paper addresses this question and precisely characterizes the generativity behind GenAI models. Owing to the latest advancements in engineering design, we first propose a framework for uncovering the various types of generativity. Then, we consider the main families of GenAI models and systematically analyze them to characterize their generativity within this framework. By doing so, we highlight the existence of two distinct generative levels in GenAI: one leading to the generation of new artifacts and the other leading to the generation of GenAI models themselves. We are also able to characterize the generativity of both of these levels, thus specifically confirming the generative power of GenAI and opening research avenues toward human-GenAI collaboration.

Associations between health literacy proficiencies and health-related quality of life and GP visits among young people in Norway: a population-based cross-sectional study.

Despite globally increased attention from policymakers and being recognised as a critical determinant of health, health literacy (HL) research in young people (YP) remains limited. This study aims to describe HL in YP across person factors and explore the associations between HL and health-related quality of life (HRQoL) and the number of visits to general practitioners (GP visits). Cross-sectional study. Population-based data collection applying country representative strata in Norway. 890 participants aged 16-25 years. Rasch modelling and Wright's method were used to identify statistically distinct levels of HL proficiency. Multiple linear regression and negative binomial regression models were applied to explore the associations between HL and HRQoL, and between HL and GP visits, respectively. Among YP, HL was statistically significantly associated with HRQoL and the number of GP visits, when adjusting for age, gender, education, self-perceived social status and financial deprivation. For every logit increase in HL, the number of GP visits decreased by 22%. Four statistically distinct levels of HL proficiency were identified for the 12-item HLS19-YP12 scale, started from a cut-point of 23, 30, 37 and 44 out of 48. Relatedly, 70% of respondents were observed at or below level 2 (30-36 points), indicating a varying lack of central skills. The span from lowest (1) to highest (4) HL level was associated with a decrease of 2.1 GP visits per year and an increase of .12 on the EQ-5D index. This study provides new empirical insights into the impact of HL in YP. Identified cut-points for the HLS19-YP12 may contribute to simplifying the process of adapting information and communication for various HL skills. The study also suggests the need for more efforts in HL policy and structural intervention development to enhance YP health and well-being.

Intact ultrafast memory consolidation in adults with autism and neurotypicals with autism traits.

The processes of learning and memory consolidation are closely interlinked. Therefore, to uncover statistical learning in autism spectrum disorder (ASD), an in-depth examination of memory consolidation is essential. Studies of the last five years have revealed that learning can take place not only during practice but also during micro (<1 min) rests between practice blocks, termed micro offline gains. The concept of micro offline gains refers to performance improvements during short rest periods interspersed with practice, rather than during practice itself. This phenomenon is crucial for the acquisition and consolidation of motor skills and has been observed across various learning contexts. Numerous studies on learning in autism have identified intact learning but there has been no investigation into this fundamental aspect of memory consolidation in autistic individuals to date. We conducted two studies with two different samples: 1) neurotypical adults with distinct levels of autistic traits (N = 166) and 2) ASD-diagnosed adults (nASD = 22, nNTP = 20). Participants performed a well-established probabilistic learning task, allowing us to measure two learning processes separately in the same experimental design: statistical learning (i.e., learning probability-based regularities) and visuomotor performance (i.e., speed-up regardless of probabilities). Here we show considerable individual differences in offline (between blocks) changes during statistical learning and between-blocks improvement during visuomotor performance. However, cumulative evidence from individual studies suggests that the degree of autistic traits and ASD status are not associated with micro offline gains, suggesting that, like statistical learning, rapid memory consolidation is intact.

Multistage selective diagenesis increasing poro-perm properties of Anisian sponge-microbial-coral patch reefs and adjacent facies in the Muschelkalk of Upper Silesia, southern Poland

Carbonate rocks, particularly reefs and circum-reef facies, are significant reservoir rocks whose reservoir properties depend on their primary composition and diagenetic history. This paper reconstructs the influence of multistage selective diagenesis on the pore system evolution and porosity-permeability properties of the Anisian tropical reef system (Karchowice and Diplopora Beds) in the Muschelkalk of Upper Silesia, southern Poland, using field and slab observations, standard and cathodoluminescence petrography, bulk and SIMS carbon and oxygen stable isotope analyses, porosity-permeability plug study, and computer image analysis of macroporosity (> 5 mm across). The reef system comprises two distinct levels of sponge-microbial(-coral) reef mounds surrounded by diverse bioclastic, peloidal, coated-grain, and micritic facies rich in Balanoglossites burrows. The strata experienced complex diagenetic alterations related to various fluids (marine, evaporitic, meteoric) and diagenetic environments (shallow substratal, burial, telogenetic), including (in chronological order): 1) early-marine precipitation of isopachous fibrous rims; 2) early dissolution during emersion; 3) brine-reflux dolomitization; 4) patchy silicification; 5) recrystallization; 6) burial calcite cementation by heated marine fluid; 7) deposition of vadose silt; 8) meteoric calcite cementation; 9) chemical compaction; 10) fracturing; and 11) final karstification, dedolomitization, FeO precipitation, and Liesegang ring formation by meteoric water during Cenozoic telogenesis. Many processes were selective and affected the same (more permeable) parts of the rocks. The strata exhibit porosities reaching 50% (combined plug porosity of 6–35% and macroporosity of up to 20%) and plug permeabilities of 0.07–70 mD, with the highest values occurring in the reefs and burrowed facies. The dominant late-stage telogenic dissolution pores originated from selective removal of dolomitized micrite within burrows and between sponge-microbial automicrite as well as dolomite crystals. The study illustrates the transition of the reef system from tight to porous due to multistage selective diagenesis and fluid flow, which enhanced subtle permeability differences between various types of micrite. This is the first case where four different fluids (dolomitizing, early dissolving, calcite-forming, and late dissolving) selectively migrated through the same rock parts at different times and modified them one after another.

Computational modeling of air pollutants for aquatic risk: Prediction of ecological toxicity and exploring structural characteristics

Assessing the aquatic toxicity originating from air pollutants is essential in sustaining water resources and maintaining the ecosystem's safety. Quantitative structure-activity relationship (QSAR) models provide a computational tool for predicting pollutant toxicity, facilitating the identification/evaluation of the contaminants and identifying responsible structural fragments. One-vs-all (OvA) QSAR is a tailored approach to address multi-class QSAR problems. The study aims to determine five distinct levels of aquatic hazard categories for airborne pollutants using OvA-QSAR modeling containing 254 air contaminants. This QSAR analysis reveals the critical descriptors of air pollutants to target for molecular modification. Various factors, including the selection of relevant mechanistic descriptors, data quality, and outliers, determine the reliability of QSAR models. By employing feature selection and outlier identification approaches, the robustness and accuracy of our QSAR models were significantly increased, leading to more reliable predictions in chemical hazard assessment. The results revealed that models using the Random Forest algorithm performed the best based on the selected descriptors, with internal and external validation accuracy ranging from 71.90% to 97.53% and 76.47%–98.03%, respectively. This study indicated that the aquatic risk of air contaminants might be attributed predominantly to their sp3/sp2 carbon ratio, hydrogen-bond acceptor capability, hydrophilicity/lipophilicity, and van der Waals volumes. These structures can be critical in developing innovative strategies to mitigate or avoid the chemicals' harmful effects. Supporting air quality improvement, this study contributes to the rapid implementation of measures to protect aquatic ecosystems affected by air pollution.

Expression levels and stoichiometry of Hnf1β, Emx2, Pax8 and Hnf4 influence direct reprogramming of induced renal tubular epithelial cells

Generation of induced renal epithelial cells (iRECs) from fibroblasts offers great opportunities for renal disease modeling and kidney regeneration. However, the low reprogramming efficiency of the current approach to generate iRECs has hindered potential therapeutic application and regenerative approach. This could be in part attributed to heterogeneous and unbalanced expression of reprogramming factors (RFs) Hnf1β (H1), Emx2 (E), Pax8 (P), and Hnf4α (H4) in transduced fibroblasts. Here, we establish an advanced retroviral vector system that expresses H1, E, P, and H4 in high levels and distinct ratios from bicistronic transcripts separated by P2A. Mouse embryonic fibroblasts (MEFs) harboring Cdh16-Cre; mT/mG allele are utilized to conduct iREC reprogramming via directly monitoring single cell fate conversion. Three sets of bicistronic RF combinations including H1E/H4P, H1H4/EP, and H1P/H4E have been generated to induce iREC reprogramming. Each of the RF combinations gives rise to distinct H1, E, P, and H4 expression levels and different reprogramming efficiencies. The desired H1E/H4P combination that results in high expression levels of RFs with balanced stoichiometry. substantially enhances the efficiency and quality of iRECs compared with transduction of separate H1, E, P, and H4 lentiviruses. We find that H1E/H4P-induced iRECs exhibit the superior features of renal tubular epithelial cells, as evidenced by expressing renal tubular-specific genes, possessing endocytotic arrogation activity and assembling into tubules along decellularized kidney scaffolds. This study establishes H1E/H4P cassette as a valuable platform for future iREC studies and regenerative medicine.

Action expectancy modulates activity in the mirror neuron system and mentalizing system

Action understanding involves two distinct processing levels that engage separate neural mechanisms: perception of concrete kinematic information and recognition of abstract action intentions. The mirror neuron system and the mentalizing system have both been linked to concrete action and abstract information processing, but their specific roles remain debatable. Here, we conducted a functional magnetic resonance imaging study with 26 participants who passively observed expected and unexpected actions. We performed whole-brain activation, region of interest, and effective connectivity analyses to investigate the neural correlates of these actions. Whole-brain activation analyses revealed that expected actions were associated with increased activation in the left medial superior frontal gyrus, while unexpected actions were linked to heightened activity in the left supramarginal gyrus, left superior parietal lobule, right inferior temporal gyrus, and left middle frontal gyrus. Region of interest analyses demonstrated that the left ventral premotor cortex exhibited greater activation during the observation of expected actions compared to unexpected actions, while the left inferior frontal gyrus, left superior parietal lobule, and left precuneus showed stronger activation during the observation of unexpected actions. Effective connectivity was observed between the left ventral premotor cortex and the left angular gyrus, left intraparietal sulcus, left dorsal premotor cortex, and left ventromedial prefrontal cortex with the middle frontal gyrus when observing unexpected, but not expected, actions. These findings suggest that expected actions are primarily processed by the mirror neuron system, whereas unexpected actions engage both the mirror neuron system and the mentalizing system, with these systems playing complementary roles in the understanding of unexpected actions.

Revisiting the conceptualization of social sustainability from a health promotion perspective: a scoping review.

Both social sustainability and health promotion emphasize the development of local communities that satisfy human needs and enhance health and well-being. This scoping review aimed to identify frameworks, components, and operationalizations of social sustainability described in peer-reviewed articles and systematize the results from a health promotion perspective. Six databases were searched for relevant articles following the JBI methodology and PRISMA guidelines. Articles were included if they provided a unique framework for social sustainability, that is, a conceptual model outlining the essential components of this concept. Information concerning the components of social sustainability and their operationalizations was analyzed through a six-step narrative synthesis. The final step involved categorizing the operationalizations of social sustainability into distinct levels by employing a socio-ecological model as an analytical tool. This review identified 22 articles presenting a social sustainability framework. The frameworks covered 11 components, of which social equity, safety, and neighborhood quality were the most frequent, while only five included health and well-being. The frameworks commonly provided practical interpretations of the concept with limited theoretical considerations. Furthermore, the identified operationalizations revealed a diverse understanding of social sustainability, encompassing all levels of the socio-ecological model applied. Health promotion research can offer theoretical and empirical insights that enhance the understanding of social sustainability, especially how societal, physical, and social determinants of health and well-being interact to create socially sustainable places. Likewise, the social sustainability literature may provide valuable knowledge underscoring the importance of contextual factors of health and well-being within the field of health promotion.

Visual search and real-image similarity: An empirical assessment through the lens of deep learning.

The ability to predict how efficiently a person finds an object in the environment is a crucial goal of attention research. Central to this issue are the similarity principles initially proposed by Duncan and Humphreys, which outline how the similarity between target and distractor objects (TD) and between distractor objects themselves (DD) affect search efficiency. However, the search principles lack direct quantitative support from an ecological perspective, being a summary approximation of a wide range of lab-based results poorly generalisable to real-world scenarios. This study exploits deep convolutional neural networks to predict human search efficiency from computational estimates of similarity between objects populating, potentially, any visual scene. Our results provide ecological evidence supporting the similarity principles: search performance continuously varies across tasks and conditions and improves with decreasing TD similarity and increasing DD similarity. Furthermore, our results reveal a crucial dissociation: TD and DD similarities mainly operate at two distinct layers of the network: DD similarity at the intermediate layers of coarse object features and TD similarity at the final layers of complex features used for classification. This suggests that these different similarities exert their major effects at two distinct perceptual levels and demonstrates our methodology's potential to offer insights into the depth of visual processing on which the search relies. By combining computational techniques with visual search principles, this approach aligns with modern trends in other research areas and fulfils longstanding demands for more ecologically valid research in the field of visual search.

Discovery of Multiple Light-Harvesting States of the Photosynthetic Protein PE545.

Cryptophytes are photosynthetic microalga that flourish in a remarkable diversity of natural environments by using pigment-containing proteins with absorption maxima tuned to each ecological niche. While this diversity in the absorption has been well established, the subsequent photophysics is highly sensitive to the local protein environment and so may exhibit similar variation. Thermal fluctuations of the protein conformation are expected to introduce photophysical heterogeneity of the pigments that may have evolved important functional properties in a manner similar to that of the absorption. However, such heterogeneity is averaged out in ensemble measurements and, therefore, has not yet been probed. Here, we report single-molecule measurements of phycoerythrin 545 (PE545), the prototypical cryptophyte antenna protein, in its native dimeric form. A conformational ensemble was resolved consisting of distinct photophysical states with different light-harvesting properties. Proteins that did not quench, partially quenched, or fully quenched absorbed light were observed. Light intensity increased the quenched-state population of the dimer, potentially as a mechanism to deal with the extreme light intensities found in aqueous environments. Cross-linking, which mimics local interactions, introduces this light-dependent functionality while also suppressing other conformational dynamics. The cellular organization can, therefore, actively modulate the protein conformation and dynamics, selecting for distinct levels of light harvesting. Thus, the complex conformational equilibrium provides an additional mechanism for cryptophytes and likely other photosynthetic organisms to optimize solar energy capture and conversion.

Stepwise Isolation of Diverse Metabolic Cell Populations Using Sorting by Interfacial Tension (SIFT).

We present here a passive and label-free droplet microfluidic platform to sort cells stepwise by lactate and proton secretion from glycolysis. A technology developed in our lab, Sorting by Interfacial Tension (SIFT), sorts droplets containing single cells into two populations based on pH by using interfacial tension. Cellular glycolysis lowers the pH of droplets through proton secretion, enabling passive selection based on interfacial tension and hence single-cell glycolysis. The SIFT technique is expanded here by exploiting the dynamic droplet acidification from surfactant adsorption that leads to a concurrent increase in interfacial tension. This allows multiple microfabricated rails at different downstream positions to isolate cells with distinct glycolytic levels. The device is used to correlate sorted cells with three levels of glycolysis with a conventional surface marker for T-cell activation. As glycolysis is associated with both disease and cell state, this technology facilitates the sorting and analysis of crucial cell subpopulations for applications in oncology, immunology and immunotherapy.

Detection of Chicken Freshness Utilizing VNIR, SWIR Spectroscopy, and Data Fusion

In light of the escalating demand for enhanced chicken quality and safety, there is an imperative need for an advanced methodology that can accurately and expeditiously ascertain the freshness of chicken. This study endeavors to harness hyperspectral imaging (HSI) technology, in synergy with machine learning and deep learning algorithms, to innovate a non-destructive method for the assessment of chicken freshness. In this study, chicken freshness was categorized into three distinct levels based on a comprehensive range of evaluation criteria specific to chicken freshness. Subsequent to preprocessing the spectra data, a discriminative model for chicken freshness predicated on Visible and Near-Infrared (VNIR,400-1000 nm) and Short-Wave Infrared (SWIR, 900-1700 nm) spectra was formulated utilizing both the raw and the preprocessed datasets. Consequently, key wavelengths were discerned via feature wavelengths selecting within the full spectra wavelengths, culminating in the establishment of the feature-wavelength model. The outcomes indicate that the VNIR-ResNet model, incorporating Normalization preprocessing, outperforms other full-spectra models, boasting an accuracy rate of 98.31%. Following feature wavelengths modeling, the precision of the feature selecting augmented by CARS and SPA was enhanced to 98.87%, respectively. Subsequently, a fusion model is developed through the application of a data fusion technique, the accuracy of data-layer fusion modeling was 98.87%, surpassing that derived from a singular data source, albeit the efficacy of feature-layer fusion modeling fell short of ideal. In summary, considering factors such as the cost and volume of hyperspectral data, the models such as MN-ResNet based on VNIR and MN-CARS-ResNet based on feature selecting emerge as more cost-effective and pragmatic solutions.

Leaf-whorl inoculation with Sporisorium reilianum may overcome field resistance of maize.

Maize yield is threatened by increasing incidences of head smut disease caused by Sporisorium reilianum. To help breeders identify S. reilianum-resistant maize lines, the availability of efficient screening systems would be an advantage. Here we assessed maize lines with distinct levels of field resistance against head smut disease in greenhouse experiments using two different inoculation techniques. Addition of mixtures of mating-compatible sporidia to the soil at seedling stage of the plant did not lead to plant disease, and we could detect only marginal amounts of fungal DNA in apical meristems at eighteen days after sowing. Inoculation of the maize lines by leaf-whorl inoculation led to both high disease incidence and prominent levels of fungal DNA in apical meristems in all tested maize lines regardless of their field resistance levels. Thus, S. reilianum entering the plant via the leaf whorl can escape existing resistance mechanisms of currently known field-resistant maize lines. Since field-resistant lines are also resistant to inoculation via teliospore-contaminated soil, we propose teliospore addition to seeds at the time of sowing (rather than leaf-whorl inoculation of seedlings) combined with quantitative detection of fungal DNA in apical meristems, as an efficient screening procedure to discover field-resistant lines. However, screening maize plants for resistance against the leaf-whorl inoculation method might be promising for the discovery of novel resistance mechanisms needed to develop durably resistant maize lines.

An Examination of Etho-Poetic Reading Scenes in the Works of Jorge Luis Borges and Pascal Quignard

This paper examines reading scenes in the works of Jorge Luis Borges and Pascal Quignard with the objective of studying the thematization and presentation of the etho-poetic aspects of reading in contemporary literature. An introductory chapter presents an overview of recent reading theories and the concept of the ‘reading scene’, which originated in writing studies (Campe, Barthes, Stingelin et al.) as well as the notion of ‘etho-poetics’ (Barthes, Foucault). Thereafter, the analysis turn to two works by Jorge Luis Borges, &amp;lt;i&amp;gt;La biblioteca de Babel&amp;lt;/i&amp;gt; and &amp;lt;i&amp;gt;El libro de arena,&amp;lt;/i&amp;gt; and then to Pascal Quignard’s &amp;lt;i&amp;gt;Lectio&amp;lt;/i&amp;gt; and his novella &amp;lt;i&amp;gt;Le lecteur&amp;lt;/i&amp;gt;. The objective of this paper is to define the different ways in which reading and life are intertwined, examining this relationship at three distinct levels: Firstly, at the level of creating literature out of reading, which represents a crucial element of the poetics of both Borges and Quignard. As will be demonstrated, both authors make extensive reference to Proust’s &amp;lt;i&amp;gt;Sur la lecture&amp;lt;/i&amp;gt;. Secondly, the relationship between reading experiences and life will be examined in the context of the diegetic world. Thirdly, at the level of the reception, metalepsis functions as a means of inciting the concrete reader to consider reading from an etho-poetic perspective. In addition to these parallels, it can be assumed that in the texts of Borges, the transformative potential of the reading act is depicted as commensurate with the social life of the readers. In contrast, Quignard’s work illustrates the etho-poetic dimension of reading as an asocial practice, dissociating the reader from the social context.