Systematic Pattern Research Articles

Crop Monitoring Using Sentinel-2 and UAV Multispectral Imagery: A Comparison Case Study in Northeastern Germany

Monitoring within-field crop variability at fine spatial and temporal resolution can assist farmers in making reliable decisions during their agricultural management; however, it traditionally involves a labor-intensive and time-consuming pointwise manual process. To the best of our knowledge, few studies conducted a comparison of Sentinel-2 with UAV data for crop monitoring in the context of precision agriculture. Therefore, prospects of crop monitoring for characterizing biophysical plant parameters and leaf nitrogen of wheat and barley crops were evaluated from a more practical viewpoint closer to agricultural routines. Multispectral UAV and Sentinel-2 imagery was collected over three dates in the season and compared with reference data collected at 20 sample points for plant leaf nitrogen (N), maximum plant height, mean plant height, leaf area index (LAI), and fresh biomass. Higher correlations of UAV data to the agronomic parameters were found on average than with Sentinel-2 data with a percentage increase of 6.3% for wheat and 22.2% for barley. In this regard, VIs calculated from spectral bands in the visible part performed worse for Sentinel-2 than for the UAV data. In addition, large-scale patterns, formed by the influence of an old riverbed on plant growth, were recognizable even in the Sentinel-2 imagery despite its much lower spatial resolution. Interestingly, also smaller features, such as the tramlines from controlled traffic farming (CTF), had an influence on the Sentinel-2 data and showed a systematic pattern that affected even semivariogram calculation. In conclusion, Sentinel-2 imagery is able to capture the same large-scale pattern as can be derived from the higher detailed UAV imagery; however, it is at the same time influenced by management-driven features such as tramlines, which cannot be accurately georeferenced. In consequence, agronomic parameters were better correlated with UAV than with Sentinel-2 data. Crop growers as well as data providers from remote sensing services may take advantage of this knowledge and we recommend the use of UAV data as it gives additional information about management-driven features. For future perspective, we would advise fusing UAV with Sentinel-2 imagery taken early in the season as it can integrate the effect of agricultural management in the subsequent absence of high spatial resolution data to help improve crop monitoring for the farmer and to reduce costs.

Transition to Modular System during the Pandemic: A Study from a Distant EFL Program

Modular systems, which involve several self-contained modules where skills and knowledge are developed in separate units throughout the program, are gaining popularity in teaching English as a foreign language (EFL). This qualitative study aimed to reveal language instructors’ and administrators’ experiences and opinions about an online modular teaching system adopted newly due to the pandemic in an English preparatory program of a tertiary level of a state university in Turkey. Data were gathered through individual semi-structured interviews from with five instructors and three administrators and observations of online classrooms. Thematic analysis was utilized to form systematic patterns from the data. The results revealed that although the modular system provided clear goals and objectives for both instructors and learners, a number of challenges and obstacles were experienced, stemming primarily from the online implementation of the modular system, such as learners’ lack of engagement in the absence of physical classroom environment, online assessment, and instructors’ increased workload. These issues led to confusion for instructors regarding the true nature of the modular system. It could be concluded that it would be more productive to implement the modular system as a hybrid model, allowing for some face-to-face interaction and assessment, rather than relying solely on the online mode.

Analysis of low-energy impact damage to epoxy resin film based on surface damage characteristics

For fiber reinforced epoxy resin composites, when low-energy impact events occur, although the surface damage of the structure is invisible, a large area of delamination might have appeared inside. In order to detect these less noticeable impact damages, epoxy resin is intended to be used as an indicative coating to show obvious surface characteristics when the impact damage occurs. On that basis, the main purpose of this study is to establish the correspondence between the damage patterns of the epoxy resin film and the low-energy impact. First, a three-dimensional progressive finite element model was established and the impact damage mechanism of the film was analyzed. Then both numerical simulation and experimental investigation were conducted for the low-energy impact response of the film, and they were in good agreement with each other. The results showed that the damage characteristics of the epoxy resin film were clearly visible and changed regularly with the impact, as reflected by the fact that the damage area, the number of cracks and the crack distribution obviously depended on the magnitude of the impact energy. Therefore, the established simulation model can be used to predict and obtain systematic damage patterns of the film and offers the potential to evaluate the invisible impact damage of composite structures based on the regular damage patterns if the film is used as the indicative coating.

A perfect model study on the reliability of the added small-scale information in regional climate change projections

The issue of the added value (AV) of high resolution regional climate models is complex and still strongly debated. Here, we approach AV in a perfect model framework within a 16-member single model initial condition ensemble with the regional climate model RACMO2 embedded in the global climate model EC-Earth2.3. In addition, we also used an ensemble produced by a pseudo global warming (PGW) approach. Results for winter temperature and precipitation are investigated from two different perspectives: (1) a signal-to-noise perspective analysing the systematic response to changing emission forcings versus internal climate variability, and (2) a prediction perspective aimed at predicting a 30-year future climate state. Systematic changes in winter temperature and precipitation contain fine-scale response patterns, but in particular for precipitation these patterns are small compared to internal variability. Therefore, single members of the ensemble provide only limited information on these systematic patterns. However, they can be estimated more reliably from PGW members because of the stronger constraints on internal variability. From the prediction perspective, we analysed AV of fine-scale information by comparing three prediction pairs. This analysis shows that there is AV in the fine-scale information for temperature, yet for precipitation adding fine-scale changes generally deteriorates the predictions. Using only the large-scale change (without fine scales) from a single ensemble member as a delta change on top of the present-day climate state, already provides a robust estimate of the future climate state and therefore can be used as a simple benchmark to measure added value.

Flexible Acceptance Condition of Generics from a Probabilistic Viewpoint: Towards Formalization of the Semantics of Generics

Formalization of the semantics of generics has been considered extremely challenging for their inherent vagueness and context-dependence that hinder a single fixed truth condition. The present study suggests a way to formalize the semantics of generics by constructing flexible acceptance conditions with comparative probabilities. Findings from our in-depth psycholinguistic experiment show that two comparative probabilities—cue validity and prevalence—indeed construct the flexible acceptance conditions for generics in a systematic manner that can be applied to a diverse types of generics: Acceptability of IS_A relational generics is mostly determined by prevalence without interaction with cue validity; feature-describing generics are endorsed acceptable with high cue validity, albeit mediated by prevalence; and acceptability of feature-describing generics with low cue validity is mostly determined by prevalence irrespective of cue validity. Such systematic patterns indicate a great potential for the formalization of the semantics of generics.

Molecular-level insights into the surface-induced assembly of functional bacterial amyloid

Protein coating material is important in many technological fields. The interaction between carbon nanomaterial and protein is especially interesting since it makes the development of novel hybrid materials possible. Functional bacterial amyloid (FuBA) is promising as a coating material because of its desirable features, such as well-defined molecular structure, robustness against harsh conditions, and easily engineerable functionality. Here, we report the systematic assembly of the functional amyloid protein, CsgA, from Escherichia coli (E. coli) on graphite. We characterize the assemblies using scanning tunneling microscopy (STM) and show that CsgA forms assemblies according to systematic patterns, dictated by the graphite lattice. In addition, we show that graphite flakes induce the fibrillization of CsgA, in vitro, suggesting a surface-induced conformational change of CsgA facilitated by the graphite lattice. Using coarse-grained molecular dynamics simulations, we model the adhesion and lamellar formation of a CsgA-derived peptide and conclude that peptides are adsorbed both as monomers and smaller aggregates leading initially to unordered graphite-bound aggregates, which are followed by rearrangement into lamellar structures. Finally, we show that CsgA-derived peptides can be immobilized in very systematic assemblies and their molecular orientation can be tuned using a small chaperone-like molecule. Our findings have implications for the development of FuBA-based biosensors, catalysts, and other technologies requiring well-defined protein assemblies on graphite.

Relative validity and reproducibility of a semi-quantitative food frequency questionnaire to assess fruit and vegetable consumption in school-aged children.

BackgroundSince the beneficial effects of fruit and vegetable (FV) consumption on health are well known due to the synergy of their nutrients and non-nutrients, it is crucial to have good tools to assess the FV intake. A food frequency questionnaire (FFQ) is an adequate method to estimate FV consumption, but it is necessary to relate this dietary method to the geographic and cultural environment. Therefore, this study presented the development of a semi-quantitative FFQ to estimate the FV intake in school-aged children who usually consume cooked homemade and school meals. It also aimed to evaluate the relative validity and reproducibility of the FFQ.MethodsSchool-aged children (baseline age 8 years) from 14 primary schools in the city of Zagreb participated in the study during the 2019/2020 school year. Parents/caregivers, together with the children, completed the FFQs and 3-day dietary records (3DDRs). The FFQ was designed to assess the consumption of eight food categories. The FFQ was validated using the 3DDR of 141 children (51.4% of boys), whereas the reproducibility test included the FFQ of 161 children (53.4% of boys).ResultsOf the eight food categories, FFQ overestimates the consumption of three and underestimates the consumption of three food categories (p < 0.05; Wilcoxon signed rank test) compared to the 3DDR. De-attenuated correlation coefficients estimated a significant relationship (0.217–0.384) between the FFQ and 3DDR. Cross-classification analysis revealed that overall, 28–41% of children were classified in the same quartile, whereas less than 10% of children were extremely misclassified for all food categories obtained from 3DDR and FFQ1. κw values showed fair agreement for all food categories. The Bland–Altman analysis results showed a relatively small bias for all food categories (median between -11.7 and -54.8 g), with no systematic patterns between the FFQ and 3DDR. No differences were found between food categories estimated with the FFQs on both occasions, and Spearman’s correlation coefficients ranged from 0.664 to 0.712 (p < 0.01). Cronbach’s alpha values (α > 0.700) indicate good internal consistency, and ICCs (range 0.724–0.826; p < 0.01) indicate good reproducibility of the FFQ.ConclusionThe results indicate reasonable relative validity and acceptable reproducibility of the FFQ for estimating FV consumption among school-aged children.

The ontogeny of children's social emotions in response to (un)fairness.

Humans have a deeply rooted sense of fairness, but its emotional foundation in early ontogeny remains poorly understood. Here, we asked if and when 4- to 10-year-old children show negative social emotions, such as shame or guilt, in response to advantageous unfairness expressed through a lowered body posture (measured using a Kinect depth sensor imaging camera). We found that older, but not younger children, showed more negative emotions, i.e. a reduced upper body posture, after unintentionally disadvantaging a peer on (4,1) trials than in response to fair (1,1) outcomes between themselves and others. Younger children, in contrast, expressed more negative emotions in response to the fair (1,1) split than in response to advantageous inequity. No systematic pattern of children's emotional responses was found in a non-social context, in which children divided resources between themselves and a non-social container. Supporting individual difference analyses showed that older children in the social context expressed negative emotions in response to advantageous inequity without directly acting on this negative emotional response by rejecting an advantageously unfair offer proposed by an experimenter at the end of the study. These findings shed new light on the emotional foundation of the human sense of fairness and suggest that children's negative emotional response to advantageous unfairness developmentally precedes their rejection of advantageously unfair resource distributions.

A user-centered approach to developing an AI system analyzing U.S. federal court data

We implemented a user-centered approach to the design of an artificial intelligence (AI) system that provides users with access to information about the workings of the United States federal court system regardless of their technical background. Presently, most of the records associated with the federal judiciary are provided through a federal system that does not support exploration aimed at discovering systematic patterns about court activities. In addition, many users lack the data analytical skills necessary to conduct their own analyses and convert data into information. We conducted interviews, observations, and surveys to uncover the needs of our users and discuss the development of an intuitive platform informed from these needs that makes it possible for legal scholars, lawyers, and journalists to discover answers to more advanced questions about the federal court system. We report on results from usability testing and discuss design implications for AI and law practitioners and researchers.

Differential richness inference for 16S rRNA marker gene surveys

BackgroundIndividual and environmental health outcomes are frequently linked to changes in the diversity of associated microbial communities. Thus, deriving health indicators based on microbiome diversity measures is essential. While microbiome data generated using high-throughput 16S rRNA marker gene surveys are appealing for this purpose, 16S surveys also generate a plethora of spurious microbial taxa.ResultsWhen this artificial inflation in the observed number of taxa is ignored, we find that changes in the abundance of detected taxa confound current methods for inferring differences in richness. Experimental evidence, theory-guided exploratory data analyses, and existing literature support the conclusion that most sub-genus discoveries are spurious artifacts of clustering 16S sequencing reads. We proceed to model a 16S survey’s systematic patterns of sub-genus taxa generation as a function of genus abundance to derive a robust control for false taxa accumulation. These controls unlock classical regression approaches for highly flexible differential richness inference at various levels of the surveyed microbial assemblage: from sample groups to specific taxa collections. The proposed methodology for differential richness inference is available through an R package, Prokounter.ConclusionsFalse species discoveries bias richness estimation and confound differential richness inference. In the case of 16S microbiome surveys, supporting evidence indicate that most sub-genus taxa are spurious. Based on this finding, a flexible method is proposed and is shown to overcome the confounding problem noted with current approaches for differential richness inference.Package availability: https://github.com/mskb01/prokounter

Ongoing landscape transience in the eastern Amazon Craton consistent with lithologic control of base level

AbstractGeomorphic features such as drainage captures, knickpoints, paleochannels, and wind‐gaps have long been observed in the Amazon region and typically thought to result from climate change and intraplate tectonics. The influence of rock type as a trigger of these landscape transients is largely overlooked. In the eastern Guiana Shield of the Amazon Craton, shield rivers flow over to the sedimentary rocks of the Amazon Basin across a sharp lithologic transition before their confluence with the Amazon River. This transition is marked by an expressive main escarpment (ME) formed over resistant sandstones of the basal units of the Amazon Sedimentary Basin. Here, systematic patterns of divide migration and river captures provide a natural laboratory to study the influence of rock type in landscape transience in a cratonic setting. Through quantitative geomorphologic analysis of the topography, drainage divides, and rivers, we investigate if this sharp lithologic transition contributed to the observed patterns of drainage rearrangement. The results revealed that rivers of larger drainage areas flowing across shorter lengths over the resistant rocks of the ME systematically capture neighbouring basins. We argue that, as tributaries draining the shield respond to downcutting and/or base‐level fall of the Amazon River, bedrock incision and knickpoint propagation are differentially slowed down by the resistant rocks according to their incision capacity, generating a series of transients such as drainage capture and divide migration. The widespread and systematic geomorphic features suggest this mechanism could be an important autogenic control of drainage network rearrangement in the Amazon region and other post‐orogenic landscapes as well. The protracted exhumation of resistant rocks in cratons and intraplate settings may keep landscapes in perpetual disequilibrium depending on their lithological complexity and offer an exceptional natural laboratory to study landscape dynamics associated with rock type.

Strategies for Avoiding Elementary School Students from Radicalism in Integrated Islamic Elementary School in West Sumatera

The Integrated Islamic Elementary School curriculum is considered exclusive, such as rejecting the ideology of other religions, claims of separation between Islam and the state and even believing in the government's evil conspiracy. Eradication of radicalism in schools is intended to narrow the space for movement, therefore the role of Integrated Islamic Elementary Schools (IIES) is very important in breaking away from the notion of radicalism. This study was conducted to answer the question of how the strategy of an integrated Islamic elementary school in integrating the curriculum, extracurricular activities, environmental creation and other activities to prevent radicalism is carried out. This is qualitative research with principals, teachers and students as the subject of documentation studies, and interviews, while data analysis is carried out with the stages of reduction, exploration, verification and contextualization of data. The result of this research is that research shows that the integration of the learning curriculum at IIES West Sumatra is divided into four types that strengthen the applicable curriculum for character strengthening, personal strengthening of students to face global challenges. Strategies in extracurricular activities are carried out with a structured and systematic pattern. The three strategies for creating the environment are pursued in an Islamic atmosphere, non-discriminatory, based on genetic characteristics, upholding ethical values, respecting cultural pluralism, and a polite culture for school members. The four strategies for routine, spontaneous and exemplary activities to prevent radicalism are carried out by strengthening character and integrating activities with learning activities, nurturing and habituation in the form of worship activities, order, neatness and cleanliness, eating and drinking. drinking, social behavior. So it can be concluded that there is no indication of the strengthening of radical ideology in IIES West Sumatra

Ethnicity as a social determinant of energy poverty: the case of Mexican indigenous population

ABSTRACT Despite an extensive literature on energy poverty, the prevalence of this problem in the indigenous populations is an underexplored area. Additionally, in Mexico and Latin America energy poverty is just an emerging research field. This paper contributes to mobilising the debate on energy poverty in indigenous populations, being the first to focus on ethnicity as a social determinant of energy poverty, and by providing elements to support progressive public policies targeting the most vulnerable populations. With a quantitative approach, an exploratory scope, and incorporating the ethnic approach as a multidisciplinary tool to diagnose and measure social inequalities, this paper analyses energy poverty in the Mexican indigenous population and measures the social inequities in energy experienced by these ethnic groups with respect to non-indigenous Mexican populations. Finding that the main efforts of the federal government have focused on electrification. However, the federative entities with the largest national proportion of the indigenous population, particularly Chiapas, Oaxaca, and Guerrero present a systematic pattern of social inequalities in all energy poverty dimensions, linked to the concentration of extreme multidimensional poverty. This is reflected in the high Energy Effort Rate, low availability of energy consumption goods and services, the exacerbated use of firewood or coal for cooking as a strategy of self-restraint to coping energy poverty, as well as a high housing precariousness, despite the high housing tenure rate. Concluding that in Mexico, due to historical Sate discrimination, ethnicity is a social determinant of energy poverty, and this could be accentuated in subgroups of the indigenous population.

Wafer map failure pattern recognition based on deep convolutional neural network

The objective of this paper is to propose a systematic failure pattern recognition for wafer map based on neural networks. A deep convolutional neural network (DCNN) model which includes the convolutional layer, batch normalization layer, Relu layer, maximum pooling layer, full connection layer, Softmax layer and classification layer is established for the problem of failure pattern recognition of wafer map. This model is an end-to-end 19-layer network, which can actively learn and automatically extract effective classification features. After grayscale and median filtering, the wafer map can be imported into the network for automatic failure classification without special feature extraction. On this basis, we build a dual-source DCNN structure by combining decision-level information entropy fusion. The verification results of the model in the actual wafer map database WM-811K show that the model exhibits good performance in identifying nine kinds of common failure patterns, and has advantages in identifying non-pattern wafer patterns without failure patterns. The dual-source DCNN structure has a better classification effect than the single-source DCNN structure, and the overall recognition accuracy of the dual-source DCNN structure reaches 98.34%.

Abstraction of Interpolative Reich-Rus-Ćirić-Type Contractions and Simplest Proof Technique

The concept of symmetry is a very vast topic that is involved in the studies of several phenomena. This concept enables us to discuss the phenomenon in some systematic pattern depending upon the type of phenomenon. Each phenomenon has its own type of symmetry. The phenomenon that is used in the discussion of this article is a symmetric distance-measuring function. This article presents the notions of abstract interpolative Reich-Rus-Ćirić-type contractions with a shrink map and examines the existence of ϕ-fixed points for such maps in complete metric space. These notions are defined through special types of simulation functions. The proof technique of the results presented in this article is easy to understand compared with the existing literature on interpolative Reich-Rus-Ćirić-type contractions.

Face specific inversion effects provide evidence for two subtypes of developmental prosopagnosia

Many studies have attempted to identify the perceptual underpinnings of developmental prosopagnosia (DP). The majority have focused on whether holistic and configural processing mechanisms are impaired in DP. However, previous work suggests that there is substantial heterogeneity in holistic and configural processing within the DP population; further, there is disagreement as to whether any deficits are face-specific or reflect a broader perceptual deficit. This study used a data-driven approach to examine whether there are systematic patterns of variability in DP that reflect different underpinning perceptual deficits. A group of individuals with DP (N = 37) completed a cognitive battery measuring holistic/configural and featural processing in faces and non-face objects. A two-stage cluster analysis on data from the Cambridge Face Perception Test identified two subgroups of DPs. Across several tasks, the first subgroup (N = 21) showed typical patterns of holistic/configural processing (measured via inversion effects); the second (N = 16) was characterised by reduced or abolished inversion effects compared to age-matched control participants (N = 91). The subgroups did not differ on tasks measuring upright face matching, object matching, non-face holistic processing, or composite effects. These findings indicate two separable pathways to face recognition impairment, one characterised by impaired configural processing and the other potentially by impaired featural processing. Comparisons to control participants provide some preliminary evidence that the deficit in featural processing may extend to some non-face stimuli. Our results demonstrate the utility of examining both the variability between and consistency across individuals with DP as a means of illuminating our understanding of face recognition in typical and atypical populations.

Systematicity and Stability Analysis of Land Use Change—Taking Jinan, China, as an Example

The study of the systematic stability of land use change is essential for regulating land use results and layout. This article took Jinan, China, as an example, and used the land transfer matrix to calculate the changing area and intensity based on remote sensing image maps and land use status maps, and then used the intensity analysis method to compare the changing intensity with the average intensity at three levels: interval level, land category level, and transition level. The systematicity and stability of land use changes from 2005 to 2018 in Jinan were analyzed using intensity analysis. The results showed that the intensity of land use change in Jinan led to a rapid change pattern from 2005 to 2010 and a slow change pattern from 2010 to 2018. The occupation of cultivated land by construction land in Jinan showed high activity, while the transition process of cultivated land to construction land and other land categories showed a steady, systematic change pattern, other land categories showed different trends and intensities of change, and the transition of forest land and other land categories showed stability in time scale. The results showed that the changes in construction land were mainly due to external influences, showing a systematic non-steady change pattern.

From improvisation to learning: How naturalness and systematicity shape language evolution

Silent gesture studies, in which hearing participants from different linguistic backgrounds produce gestures to communicate events, have been used to test hypotheses about the cognitive biases that govern cross-linguistic word order preferences. In particular, the differential use of SOV and SVO order to communicate, respectively, extensional events (where the direct object exists independently of the event; e.g., girl throws ball) and intensional events (where the meaning of the direct object is potentially dependent on the verb; e.g., girl thinks of ball), has been suggested to represent a natural preference, demonstrated in improvisation contexts. However, natural languages tend to prefer systematic word orders, where a single order is used regardless of the event being communicated. We present a series of studies that investigate ordering preferences for SOV and SVO orders using an online forced-choice experiment, where English-speaking participants select orders for different events i) in the absence of conventions and ii) after learning event-order mappings in different frequencies in a regularisation experiment. Our results show that natural ordering preferences arise in the absence of conventions, replicating previous findings from production experiments. In addition, we show that participants regularise the input they learn in the manual modality in two ways, such that, while the preference for systematic order patterns increases through learning, it exists in competition with the natural ordering preference, that conditions order on the semantics of the event. Using our experimental data in a computational model of cultural transmission, we show that this pattern is expected to persist over generations, suggesting that we should expect to see evidence of semantically-conditioned word order variability in at least some languages.

Domestic Violence: Awareness and Level of Knowledge among University Students

Domestic violence is not an isolated problem in Malaysia. The increase of domestic violence cases requires community members to be equally concerned about this problem. Thus, a quantitative study has been conducted to identify the level of awareness and knowledge of students including the provision of policies, rights, and services provided to victims. The questionnaire was utilized as a method of data collection among 132 students from Social Work Management Programs, Universiti Utara Malaysia. Students’ level of awareness and knowledge was measured and analyzed descriptively. Findings indicate students' level of awareness was at a moderate level while their level of knowledge regarding policies, rights, and services was at a low level. A small number of respondents were found to still have gender-stereotypical attitudes towards victims and predators in domestic violence cases. Thus, ongoing awareness and practical training programs through a systematic pattern of education are needed to help students increase their level of awareness and knowledge regarding domestic violence.

Kur’an’da Geçen “Necm/Nücûm” Kelimelerinin Analitik İncelemesi (Metin İçi Bağlam Çerçevesinde)

Kur’ân-ı Kerîm’deki sureler ile sureleri oluşturan âyetler arasında tevkîfî bir insicam ve tenasüp vardır. Bu sistematik örgü sadece âyet ve surelerin sıralamasında değil, aynı zamanda cümle ve pasajların birbirleri arasındaki anlam bağlantısında mevcuttur. Dolayısıyla her bir âyet, anlam bakımından bağlı olduğu diğer âyetlerle birlikte metin içi bağlam açısından semantik bir role sahiptir. Ayrıca Kur’ân’da geçen ümmet, necm ve kitâb gibi çok anlamlı kelimelerin hangi mana için kullanıldığı dış bağlam ile birlikte metnin iç bağlamından hareketle anlaşılabilir.&#x0D; Necm/nücûm kelimeleri Kur’ân’da birden fazla anlamda kullanılmıştır. Buna göre eş sesli bir kelime olan necm/nücûm kelimeleri Kur’ân’da dört yerde tekil, dokuz ayette ise çoğul olarak “nücûm” şeklinde on üç defa geçmektedir. Araştırmada bu kelime, kullanım bilim açısından metin içi bağlam merkezli olarak incelenmiş ve bu kelimelerin dokuz yerde “yıldız”, üç yerde “vahiy”, bir yerde “gövdesiz bitki” anlamlarında kullanıldığı belirlenmiştir.&#x0D; Yapılan dilbilimsel analiz neticesinde necm/nücûm kelimelerinin “yıldız” anlamında kullanıldığı âyetlerde bazen ay ve güneş ile birlikte, bazen de münferit olarak “teshîr/Allah’ın emrine boyun eğme” fiili ile birlikte kullanıldığı görülmüştür. “Yıldız” anlamında kullanıldığı bir yerde ise “bir durumu nasıl planlayıp idare edeceğini düşünmek” anlamındaki kalıp ifadeyi oluşturan kelime bütününden birisidir. Özellikle kadim tefsirlerde “gövdesiz bitki” anlamının verildiği bir yerde ise güneşle birlikte “secde etme” fiilinin öznesi olarak zikredildiği görülmektedir. “Vahiy” anlamına geldiği pasajlarda ise dizimbilim içerisinde siyak ve sibak karinesi gereğince Kur’ân âyetlerinin inişi ile ilgili konular içinde geçmektedir.&#x0D; Yukarıda yapılan tespitlerin bir neticesi olarak; Kur’ân’da geçen necm/nücûm maddelerinin metin içi bağlama dikkat edilmeden genellikle “yıldız” olarak anlaşıldığı dikkate alındığında, daha önce hakkında ayrıntılı bir spesifik bir çalışma yapılmayan bu alanda araştırmanın katkı sağlayacağı umulmaktadır. Ayrıca bu makalede ortaya konmaya çalışılan metodik yaklaşımın, çok anlamlı Kur’ân müfredatının, âyetler arasındaki dilsel anlam örgüleri çerçevesinde doğru bir şekilde anlaşılmasında yardımcı olması hedeflenmektedir.