Special Pattern Research Articles

Insights into the Associations Between Systolic Left Ventricular Rotational Mechanics and Left Atrial Peak Reservoir Strains in Healthy Adults from the MAGYAR-Healthy Study

Introduction: In systole, when the left ventricle (LV) twists, the left atrium (LA) behaves like a reservoir, having a special wall contractility pattern opposite to that of the LV wall. Accordingly, the objective of the present study was to investigate the associations between LV rotational mechanics and LA peak (reservoir) strains as assessed simultaneously by three-dimensional speckle-tracking echocardiography (3DSTE) under healthy conditions. Methods: In the present study, 157 healthy adults (mean age: 33.2 ± 12.7 years, 73 men) were involved. Complete two-dimensional Doppler echocardiography with 3DSTE-derived data acquisition were performed in all cases. The 3DSTE-derived LV rotational and LA strain parameters were determined at a later date. Results: Global LA peak reservoir circumferential (22.7 ± 6.4% vs. 27.6 ± 6.8%, p < 0.05) and area (57.8 ± 20.0% vs. 66.0 ± 22.7%, p < 0.05) strains proved to be reduced in the case of the highest vs. lowest basal LV rotation; other LA peak reservoir strains were not associated with increasing basal LV rotation. Global LA peak radial strain was highest in the case of the lowest vs. highest apical LV rotation (−19.2 ± 9.4% vs. −13.0 ± 8.2%, p < 0.05). Global LA peak reservoir 3D strain was lowest in the case of the highest vs. lowest apical LV rotation (−9.9 ± 6.8% vs. −5.0 ± 4.2%, p < 0.05). Only apical LV rotation proved to be significantly reduced in the case of the highest vs. lowest global LA peak reservoir 3D strain (8.12 ± 3.23° vs. 10.50 ± 3.44°, p < 0.05). Other global LA peak reservoir strains were not associated with basal and apical LV rotations. Conclusions: In LV systole, LV rotational mechanics is associated with LA deformation represented by LA peak (reservoir) strains even in healthy circumstances. While basal LV rotation is associated with LA widening, apical LV rotation is associated with LA thinning, suggesting the close cooperation of the LV and LA in systole even in healthy adults.

Multi-perspective API call sequence behavior analysis and fusion for malware classification

The growing variety of malicious software, i.e., malware, has caused great damage and economic loss to computer systems. The API call sequence of malware reflects its dynamic behavior during execution, which is difficult to disguise. Therefore, API call sequence can serve as a robust feature for the detection and classification of malware. The statistical analysis presented in this paper reveals two distinct characteristics within the API call sequences of different malware: (1) the API existence feature caused by frequent calls to the APIs with some special functions, and (2) the API transition feature caused by frequent calls to some special API subsequence patterns. Based on these two characteristics, this paper proposes MINES, a Multi-perspective apI call sequeNce bEhavior fuSion malware classification Method. Specifically, the API existence features from different perspectives are described by two graphs that model diverse rich and complex existence relationships between APIs, and we adopt the graph contrastive learning framework to extract the consistent shared API existence feature from two graphs. Similarly, the API transition features of different hops are described by the multi-order transition probability matrices. By treat each order as a channel, a CNN-based contrastive learning framework is adopted to extract the API transition feature. Finally, the two kinds of extracted features are fused to classify malware. Experiments on five datasets demonstrate the superiority of MINES over various state-of-the-arts by a large margin.

Analysis of Clinicopathological and Molecular Features of Microcystic, Elongated, and Fragmented Pattern Invasion in Endometrioid Endometrial Cancer.

Background: Microcystic, elongated, and fragmented (MELF) invasion is a special invasion pattern in endometrioid endometrial cancer (EEC). This study aimed to investigate the clinical, pathological, and molecular features of the MELF pattern and its prognostic value in patients with EEC. Materials and Methods: The clinical and pathological data of 342 patients with EEC were retrospectively collected at Peking University People's Hospital from January 2019 to December 2022. Some key clinicopathological features were evaluated, including the tumor grade, Federation of Gynecology and Obstetrics (FIGO) staging, cervical stromal involvement, lymph node status, and lymphatic vascular space infiltration (LVSI). Immunohistochemical staining and molecular tests were performed, and the relevant literature was reviewed. Results: The MELF pattern was more prevalent in low-grade EEC. A significant correlation was found between the MELF pattern and advanced FIGO staging, LVSI, the depth of myometrial invasion, cervical stromal involvement, and lymph node metastasis (LNM). The incidence of mismatch-repair-deficient (MMRd) proteins was much higher in the MELF group than in the no-MELF group. Molecular testing revealed that, after copy number-low (CNL), microsatellite instability-high (MSI-H) was the second-most frequent subtype in the MELF group. The recurrence risk did not significantly differ between the MELF and no-MELF groups, but the differences among the four molecular subtypes were statistically significant. However, the MELF group experienced a shorter recurrence time. Among the four molecular subtypes, the recurrence risk was the highest in the CNH subgroup, followed by the MSI-H subgroup. Conclusions: MELF is a special invasion pattern in EEC and is associated with distinct clinicopathological and molecular characteristics, including the latest 2023 FIGO staging. Further research is warranted to explore its implications for treatment strategies and patient outcomes.

Pragmatically oriented linguistic units in advertising of religious tours

INTRODUCTION. The relevance of the study is related to the study of the features of the implementation of tourist advertising in such a dynamically developing real segment as religion. The role of tourist advertising is increasing, and it is becoming especially important to study specific pragmatic oriented language units devoted to religious discourse. The purpose of the study is to identify lexical, morphological units and stylistic devices used in tourist religious discourse.MATERIALS AND METHODS. The research material was advertising texts promoting religious tours on the Internet. The collection and writing of factual material was carried out using conceptual analysis, interpretive analysis was used to determine and explain the linguistic features of religious advertising text.RESULTS AND DISCUSSION. The appeal to advertising texts promoting religious tours allowed to identify pragmatically oriented linguistic units. Religious discourse, oriented towards introducing a person to faith within the framework of a certain confession, contributes to the implementation of religious tours (pilgrimage, educational and pilgrimageeducational). Religious advertising discourse in the field of tourism can be oriented towards the discourses of consumer society, but at the same time give them new, religious and sacred outlines.CONCLUSION. The identified lexical units and stylistic means in tourist advertisements on the topic of religious tours allow us to consider that religious tourist advertisement has a number of characteristics inherent only to it and occupies its own special place among currently existing types of discourse. These advertisements can be considered special speech patterns of text aimed at implementing the pragmatic function of advertising messages.

Integrating brainstem and cortical functional architectures.

The brainstem is a fundamental component of the central nervous system, yet it is typically excluded from in vivo human brain mapping efforts, precluding a complete understanding of how the brainstem influences cortical function. In this study, we used high-resolution 7-Tesla functional magnetic resonance imaging to derive a functional connectome encompassing cortex and 58 brainstem nuclei spanning the midbrain, pons and medulla. We identified a compact set of integrative hubs in the brainstem with widespread connectivity with cerebral cortex. Patterns of connectivity between brainstem and cerebral cortex manifest as neurophysiological oscillatory rhythms, patterns of cognitive functional specialization and the unimodal-transmodal functional hierarchy. This persistent alignment between cortical functional topographies and brainstem nuclei is shaped by the spatial arrangement of multiple neurotransmitter receptors and transporters. We replicated all findings using 3-Tesla data from the same participants. Collectively, this work demonstrates that multiple organizational features of cortical activity can be traced back to the brainstem.

CLINICAL CASES OF SPITZOID NEOPLASMS

Spitz nevi account for about 2% of the total number of melanocytic skin neoplasms. There are benign Spitz nevi, atypical Spitz tumour, and malignant Spitz melanoma. These clinically similar lesions, usually represented by a flesh-coloured, pink or brownish-black spot or nodule, are often heavily vascularised, grow rapidly in size and change in structure, raising concerns about malignancy. Dynamic observations have revealed the possibility of long-term stabilisation and periods of regressive changes. Dermoscopy is used for early diagnosis due to the initially small size of nevi. When examining the magnified image of the tumour surface, the structure of the neoplasm is recognized. In the case of Spitz nevi, special patterns of “starburst” and “stardust” are identified, which allow to suspect the diagnosis and the period of involution, respectively. Pathohistologically, Spitz nevi are defined as melanocytic proliferations with large epithelioid or spindle-shaped melanocytes with large nuclei, vesicular chromatin and prominent nucleoli. However, the differentiation between different subtypes of spitzoid neoplasms remains a difficult issue. As of today, the review of H&E-stained structures still prevails over immunohistochemical and molecular genetic diagnostic methods. Even nowadays, Spitz nevi still cause difficulties in clinical and morphological diagnosis and management approaches. The publication considers several interesting cases from personal clinical practice. Case 1: Patient A, a 24-year-old woman. She complained of a single rash on the outer surface of the right thigh, which gradually increased in size over the last year. On clinical examination, a small erythematous, partially pigmented, heterogeneous nodule was observed in this area. The demonstrated Spitz nevus is heterogeneous in structure. Being in the phase of active growth, it showed an asymmetrical “starburst” pattern formed by vascular elements in a linear arrangement, and white reticular lines or structureless zones. Case 2: Patient B, 34 years old. A full examination of the right popliteal fossa revealed a heterogeneous spot up to 4 mm in diameter, which caused concern. A case of Spitz nevus is represented by a globular pattern in the centre and a reticular pattern on the periphery, which is more common for lesions that have been on the skin for some time, but no longer show signs of active growth. Case 3: Patient C, a 25-year-old woman, skin phototype 2, with a family history of skin tumours in several previous generations. The examination revealed a heterogeneous nodule of suspicious morphology in the left scapula. Dermoscopically, the above-described lesion is represented by two zones of different structure. The central zone has the signs of radial markings formed by various pattern elements; the polychromatic zone has areas of negative pigment network, white lines, dots and globules. There was also an eccentrically located area with a radially oriented hyperchromatic pigment network and a clear border along the outer edge. Most Spitz nevi are independent lesions, but some of them can be associated with other skin neoplasms. This is likely to be the example in the above-mentioned case, so it was the nevus-associated Spitz melanoma. Spitz nevi are an urgent problem of modern medicine. The similarity of the clinical, dermoscopic and pathological picture to malignant skin neoplasms causes diagnostic difficulties. Visual variability requires considerable clinical experience of a specialist.

New insights into the merging behavior of pedestrians: Quantification of lane competition level

Merging behavior is a complex crowd movement pattern caused by certain architectural features and has triggered serious crowd accidents worldwide. It is not uncommon to find such merging structures on the floor plans of some underground infrastructures, which deserve more detailed studies on special crowd movement patterns to enhance the safety level. Researchers have demonstrated that the unstable emotions and competitive behaviors of pedestrians during underground evacuation need to be taken into account due to the enclosed environment. However, there are no relevant studies focused on the competition characteristics among pedestrians during the merging process in a quantitative way. The comprehensiveness and systematization of the geometric features of typical merging structures, as well as the way to create the perception of competition and conflict among pedestrians during real emergencies also need to be improved. In this paper, we carried out a series of controlled experiments in symmetric and asymmetric merging structures with different channel widths and incentive levels to investigate crowd merging behavior with competition characteristics. The density and delay time within the merging area, as well as the time interval and lane changes before and after merging are analyzed. By introducing and modifying Simpson’s Diversity Index, we proposed a new method for quantifying the competition level among pedestrians during the merging process. It is concluded that the performance of the merging area is sensitive to the channel widths and the merging layouts, and the negative effect of unbalanced walking priority is more significant under high incentive level. The lane competition level during the merging process is correlated with the effects of various geometric features, movement layouts, and incentive levels. The method proposed in this paper brings new insights into the interpretation of merging scenarios and more studies on pedestrian dynamics. We hope that this study could serve as supplementary work for other modeling or field experiment methods to jointly provide more insights into the crowd management strategies in some underground infrastructures.

Functional specialization and distributed processing across marmoset lateral prefrontal subregions.

A prominent aspect of primate lateral prefrontal cortex organization is its division into several cytoarchitecturally distinct subregions. Neurophysiological investigations in macaques have provided evidence for the functional specialization of these subregions, but an understanding of the relative representational topography of sensory, social, and cognitive processes within them remains elusive. One explanatory factor is that evidence for functional specialization has been compiled largely from a patchwork of findings across studies, in many animals, and with considerable variation in stimulus sets and tasks. Here, we addressed this by leveraging the common marmoset (Callithrix jacchus) to carry out large-scale neurophysiological mapping of the lateral prefrontal cortex using high-density microelectrode arrays, and a diverse suite of test stimuli including faces, marmoset calls, and spatial working memory task. Task-modulated units and units responsive to visual and auditory stimuli were distributed throughout the lateral prefrontal cortex, while those with saccade-related activity or face-selective responses were restricted to 8aV, 8aD, 10, 46V, and 47. Neurons with contralateral visual receptive fields were limited to areas 8aV and 8aD. These data reveal a mixed pattern of functional specialization in the lateral prefrontal cortex, in which responses to some stimuli and tasks are distributed broadly across lateral prefrontal cortex subregions, while others are more limited in their representation.

Merging of quasi-bound states in the continuum and Wood anomalies in terahertz metasurfaces based on complementary periodic cross-shaped resonators

Metasurfaces provide an ideal platform for controlling the merging of multiple modes owing to trimmable periodic meta-atoms. In this work, a terahertz metasurface based on complementary periodic cross-shaped resonators (CPCRs) with mixed modes is demonstrated. The CPCRs support sharp quasi-bound states in the continuum (quasi-BICs) by introducing an offset parameter. The optical response of quasi-BICs such as frequency shift and Q-factor can be optimized by tuning offset parameters. As such parameter increases, a mixed mode originating from quasi-BICs and Wood anomalies appears. The merged resonance has a narrow bandwidth with steep edges and thus can serve as bandpass filters. Simulated electric field distributions reveal the special patterns for these modes. Owing to the effect of quasi-BICs, Wood anomalies exhibit different field patterns in contrast to those of pure modes. These results prove the possibility of multimode merging in metallic metasurfaces, which is beneficial for terahertz applications such as sensing and wave filters.

Mapping data-driven strategies in improving health care and patient satisfaction

Health services involve data analytics, central to healthcare service delivery, research, and planning. Based on the literature, this specific article seeks to enlighten the reader about data analytics in health services by discussing its advantages, shortcomings, and issues that come with it. Section one mapping outlines how data analytics optimizes the results of health service delivery through risk factor definition, disease detection, and case-by-case management. It helps inform disease trajectory, determine drug interaction, monitor disease, support decision-making, and enhance service delivery quality. The research also examines data analysis in health services, medicine, and pharmaceuticals. Several big data analytics applications have been identified as relevant to drug development, personalized medication, and specialized trials. Evaluations that rely on biomarkers differentiate between patients who are convenient for specific therapies, improving the patient's status and developing health care services. The third section also stresses the role of data analytics in enhancing efficiency and profitability. They involve detecting fraud, abuse, and unnecessary medical activities, creating savings and better financial returns. Data analytics also leads to identifying high-cost patients and ways of managing healthcare costs, increasing revenues and profitability. The fourth section discusses how big data complements traditional public health surveillance and outbreak platforms. It facilitates collecting data, analyzing different sources, and identifying special patterns or outliers to detect the outbreak early enough, contain it, or allocate resources to control it. It anticipates and addresses the dangers to the public's well-being and effectively controls episodes of infectious diseases. However, some key issues are associated with data analytics implementation, such as data quality, governance, privacy, bias, integration, expertise, and ethics, among others. Therefore, solving these challenges to achieve the optimum shifting of health service paradigms through data analytics in inpatient treatment, organizational management, and affordability is imperative.

Identification of Key Genes in Fetal Gut Development at Single-Cell Level by Exploiting Machine Learning Techniques.

The study of fetal gut development is critical due to its substantial influence on immediate neonatal and long-term adult health. Current research largely focuses on microbiome colonization, gut immunity, and barrier function, alongside the impact of external factors on these phenomena. Limited research has been dedicated to the categorization of developing fetal gut cells. Our study aimed to enhance our understanding of fetal gut development by employing advanced machine-learning techniques on single-cell sequencing data. This dataset consisted of 62,849 samples, each characterized by 33,694 distinct gene features. Four feature ranking algorithms were utilized to sort features according to their significance, resulting in four feature lists. Then, these lists were fed into an incremental feature selection method to extract essential genes, classification rules, and build efficient classifiers. Several important genes were recognized by multiple feature ranking algorithms, such as FGG, MDK, RBP1, RBP2, IGFBP7, and SPON2. These features were key in differentiating specific developing intestinal cells, including epithelial, immune, mesenchymal, and vasculature cells of the colon, duo jejunum, and ileum cells. The classification rules showed special gene expression patterns on some intestinal cell types and the efficient classifiers can be useful tools for identifying intestinal cells.

Chimera states and eigen microstates of nonidentical power-law coupled oscillators with heterogeneous phase lag

Chimera state is a special spatiotemporal patterns where coherent and incoherent states coexist, not only related to neuronal evolution but also to diseases such as parkinson, epilepsy, and schizophrenia. In many studies of biological networks, the interaction patterns between individuals often exhibit a scale-free heavy-tailed distribution. Hence, researches into chimera state within scale-free structures may help to understand the close relationship between function and structure in biological systems. Especially in neural systems, interactions between neurons depend on both electrical and chemical signals, naturally involving heterogeneous delay effects. In this study, we introduce power-law coupling, nonidentical natural frequency, and heterogeneous phase delay into the phase oscillator model, exploring the relationship between oscillator coupled strength, power-law exponent, and the emergence of chimera state. Other important thing is that we extend the Eigen Microstate (EM) method to investigate the criticality, attempting to reveal the mechanism of chimera state emergence through the mesoscopic structure of eigen microstate. We find that the critical analysis results of the EM method, relying solely on phase data, are entirely consistent with those obtained by the mean-field method, revealing the inevitable relationship between the emergence of chimera state and the structure–power law coupling. In addition, the spatiotemporal patterns of eigen microstate provide insights into the mesoscopic structure, can be used to distinguish spatial distribution of synchronization, chimera state, and disorder state, as well as their characteristic dynamics of oscillators. This expansion research of the EM method will advance the exploration of criticality in real oscillatory systems.

Identification of VvAGL Genes Reveals Their Network's Involvement in the Modulation of Seed Abortion via Responding Multi-Hormone Signals in Grapevines.

The formation of seedless traits is regulated by multiple factors. AGLs, which belong to the MADS-box family, were reported to be important regulators in this process; however, the underlying mechanism remains elusive. Here, we identified the VvAGL sub-family genes during the seed abortion process in seedless grapevine cv. 'JingkeJing' and found 40 differentially expressed VvAGL members and 1069 interacting proteins in this process. Interestingly, almost all members and their interacting proteins involved in the tryptophan metabolic pathway (K14486) and participated in the phytohormone signalling (KO04075) pathway, including the growth hormone (IAA), salicylic acid (SA), abscisic acid (ABA), cytokinin (CTK), and ethylene signalling pathways. The promoters of AGL sub-family genes contain cis-elements in response to hormones such as IAA, ABA, CTK, SA, and ETH, implying that they might respond to multi-hormone signals and involve in hormone signal transductions. Further expression analysis revealed VvAGL6-2, VvAGL11, VvAGL62-11, and VvAGL15 had the highest expression at the critical period of seed abortion, and there were positive correlations between ETH-VvAGL15-VvAGL6-2, ABA-VvAGL80, and SA-VvAGL62 in promoting seed abortion but negative feedback between IAA-VvAGL15-VvAGL6-2 and CTK-VvAGL11. Furthermore, many genes in the IAA, ABA, SA, CTK, and ETH pathways had a special expressional pattern in the seed, whereby we developed a regulatory network mediated by VvAGLs by responding to multihormonal crosstalk during grape seed abortion. Our findings provide new insights into the regulatory network of VvAGLs in multi-hormone signalling to regulate grape seed abortion, which could be helpful in the molecular breeding of high-quality seedless grapes.

The Chromosome-level Genome Provides Insights into the Evolution and Adaptation of Extreme Aggression.

Extremely aggressive behavior, as the special pattern, is rare in most species and characteristic as contestants severely injured or killed ending the combat. Current studies of extreme aggression are mainly from the perspectives of behavioral ecology and evolution, while lacked the aspects of molecular evolutionary biology. Here, a high-quality chromosome-level genome of the parasitoid Anastatus disparis was provided, in which the males exhibit extreme mate-competition aggression. The integrated multiomics analysis highlighted that neurotransmitter dopamine overexpression, energy metabolism (especially from lipid), and antibacterial activity are likely major aspects of evolutionary formation and adaptation for extreme aggression in A. disparis. Conclusively, our study provided new perspectives for molecular evolutionary studies of extreme aggression as well as a valuable genomic resource in Hymenoptera.

Do national innovation policies lead to technological specialization or diversification? The role of path dependence and spatial spillovers

Although most national innovation policy aim to promote urban innovation, their impact on technological specialization and diversification has not been thoroughly explored. This paper examines the impact of the National Innovation City Pilot Policy (NICPP) on technological specialization and diversification in Chinese cities, utilizing data from 282 cities between 2006 and 2019, and employing the difference-in-differences (DID) method. The results indicate that NICPP increases technological specialization while decreasing diversification in cities. The pathways to these outcomes include innovation path dependence, agglomeration effects, and a reduction in breakthrough innovations. Additionally, the policy's spatial spillovers contributed to technological specialization in peripheral areas. The study highlights the heterogeneity of policy effects, suggesting that cities with higher levels of initial specialization are more significantly impacted by these policies, while differences in resource endowment, geographical location, and city size lead to varying patterns of specialization. Moreover, the study verifies the synergistic effect of NICPP with other policies, where initiatives promoting high technology and environmental regulation work in conjunction with NICPP to enhance specialization in corresponding industries. This study offers a comprehensive analysis of the multifaceted impacts of NICPP, delivering theoretical insights and empirical evidence for strategic policy deployment, enhancing regional cooperation, and fostering synergies among policies.

MoTion: A new declarative object matching approach in Pharo

Pattern matching is an expressive way of matching data and extracting pieces of information from it. The recent inclusion of pattern matching in the Java and Python languages highlights that such a facility is more and more adopted by developers for everyday development. Other main stream programming languages also offer pattern matching capabilities as part of the language (Rust, Scala, Haskell, and OCaml), with different degrees of expressivity in what can be matched. In the meantime, in graphs, pattern matching takes a slightly different turn; it enhances the expressivity of the patterns that can be defined. Smalltalk currently offers little pattern matching capability to find specific objects inside a large graph of objects using a declarative pattern. In Pharo, the closest library to classical pattern matching that exists is the RBParseTreeSearcher, which allows to express specialized patterns over a Pharo Abstract Syntax Tree to find some inner node. The question arises of what features a flexible pattern matching language should have. In this paper, we review the features found in different existing pattern matching languages, both in General Purpose Languages (like Java) and in declarative graph pattern matching languages. We then describe MoTion, a new pattern matching engine for Pharo smalltalk, combining all these features. We discuss some aspects of MoTion’s implementation and illustrate its use with real case examples.

Compressive stochastic subspace identification: A modal parameter identification method suitable for compressive sampling

Stochastic subspace identification (SSI) and its variants are widely used in conventional structural health monitoring (SHM) owing to their high computation robustness and estimation accuracy. Conventional SHM is based on a Nyquist (high-rate and uniform) sampling dictated by Shannon–Nyquist sampling theorem. As data quantity of SHM is increasing with duration and equipment at an ever-growing rate and new applications of SHM with strict constricts on sampling are emerging one by one, sub-Nyquist sampling, also known as compressive sampling has increasingly been used in SHM in recent years. Therefore, despite the success of SSI method and its algorithmic variants, a significant drawback lies in their handling of sub-Nyquist data. To overcome this drawback, we set out to extend the applicable scenarios of SSI from Nyquist (high-rate/uniform) sampling to sub-Nyquist (low-rate/nonuniform) sampling. In this paper, we propose a compressive stochastic subspace identification (CSSI) which can identify modal parameters from sub-Nyquist/compressed data. Specifically, CSSI involves two aspects: covariance matrix reconstruction and system parameter identification. We find the complete covariance matrix in classic SSI can also be estimated/reconstructed by sub-Nyquist samples. More importantly, this reconstruction can be physically guaranteed through special sampling patterns without sparsity prior. Based on the above findings, we develop a compressed covariance sensing-based covariance matrix reconstruction technique and derive the optimal sub-Nyquist sampling pattern such that the reconstruction is hassle-free and efficient. Then, we perform modal parameter identification on the basis of the reconstructed covariance matrix. Finally, the effectiveness of CSSI is validated by simulations and experiments. In short, CSSI, as a new extension of SSI, can extract modal parameters at lower sampling rates than what is prescribed by the classic SSI. The implication of this is the possibility that CSSI for operational modal analysis will require fewer measurements thus it would reduce the storage requirement and the bandwidth for transmitting data.

Positive Transfer of Third Language Acquisition in English and French Sentence Patterns

Language takes sentences as the basic unit and sentence structures in different languages have their own characteristics. At present, with the in-depth development of economic globalization and the rapid enhancement of the demand for cross language communication, there are more and more trilingual users. Therefore, third language acquisition, as an emerging field of international and domestic research in recent years, has attracted extensive attention. As is known to all, the two languages, English and French, are closely related but different. Hence, in the process of learning French as a second foreign language, the positive and negative transfer of English to French is inevitable. Under the framework of third language acquisition and based on language transfer theory, this paper analyzes the positive transfer of sentence structure in the process of third language acquisition through the comparative analysis of four special sentence patterns in English and French, which is helpful for English majors to learn French as a second foreign language more concisely and efficiently.

Europe's orchard: The role of irrigation on the Spanish agricultural production

In the latter half of the twentieth century, Spanish agriculture witnessed sustained production growth, aligning with Western European levels after a period of lag in both production and productivity. This growth predominantly occurred in the warm, sunny provinces of southern and eastern Spain, which specialized in high-value crops such as fruits, vegetables, and olive oil. Various factors have been identified in the scientific literature as contributors to this transformation, including technological innovations, the internationalization of Spanish agriculture, domestic development, and advancements in irrigation. This paper aims to examine the impact of irrigation on Spanish agricultural production, focusing on the creation of regional and productive disparities since the mid-twentieth century. These diverse effects have been crucial in shaping the regional and product-specific specialization patterns that characterize the historical dynamism of Spanish agriculture. To that aim, we have compiled a comprehensive database containing detailed information on agricultural production values, irrigated and rainfed area and yields. The level of disaggregation of data, both in terms of production and regional breakdowns, enables us to identify specific regional and crop patterns. Additionally, this study highlights the significant and regionally varied transformations within the Spanish agricultural sector over the long term, which have had profound effects on rural areas.

Enhancing algal bloom forecasting: A novel framework for machine learning performance evaluation during periods of special temporal patterns

The evaluation of algal bloom forecasting models typically relies on error metrics that quantify the forecasting performance over the whole test set as a single number. Furthermore, the comparison with simple baseline methods is often omitted. To address this, we introduce a novel framework for Model performance Analysis and Visualization of time series forecasting (MAVts). MAVts incorporates novel algorithms for the automatic identification and visualization of time series periods of interest where the forecasting models are evaluated and compared with simple baseline methods. The application of MAVts on evaluating algal bloom forecasting models composed of sophisticated machine learning (ML) methods, reveals that in 85% of experiments a single error metric is not enough and only in 12.5% of experiments a ML model outperforms all baselines on all metrics and periods of interest. Thus, MAVts emerges as a valuable tool for analyzing and comparing ML models, advancing environmental management and protection.