Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Seismic Data Denoising via Deep Learning With Improved MCA-SCUNet

In hydrocarbon exploration, seismic data collected in the field inevitably encounter noise interference, which subsequently affects the data processing and interpretation. Recently, deep learning methods have gained widespread popularity in seismic denoising. Among these methods, the U-Net has shown some potential, but its performance in complex noise suppression needs further improvement due to the limitations of the U-Net structure. Moreover, the majority of existing noise suppression methods primarily focus on synthetic noises with single characteristics, such as Gaussian random noise and linear interference. To devise methods that can effectively suppress more intricate field noise, this article proposes a novel noise suppression method based on an encoder–decoder architecture called multiscale channel attention Swin Conv U-Net. Notably, it enhances the U-Net through the integration of the following two modules: 1) Swin-Conv block (SCB), which replaces the convolution operation of U-Net and integrates the nonlocal modeling ability of Swin Transformer (SwinT) and the local modeling ability of residual connection convolution layers to achieve multidimensional feature extraction, and 2) multiscale channel attention block (MCAB), which replaces skip connection modules between the encoder and the decoder in the U-Net with multichannel feature fusion to capture more complex channel dependencies. This article evaluates the proposed algorithm on both synthetic and field seismic data and compares the results with several established denoising methods. Our algorithm enhances the network’s noise perception capabilities and improves signal-to-noise ratio (SNR) and structural similarity index measure (SSIM) of seismic data. Finally, a concise discussion on the limitations of our method and potential avenues for enhancement is provided.
Generative Adversarial Network-Based Data Augmentation for Enhancing Wireless Physical Layer Authentication

Wireless physical layer authentication has emerged as a promising approach to wireless security. The topic of wireless node classification and recognition has experienced significant advancements due to the rapid development of deep learning techniques. The potential of using deep learning to address wireless security issues should not be overlooked due to its considerable capabilities. Nevertheless, the utilization of this approach in the classification of wireless nodes is impeded by the lack of available datasets. In this study, we provide two models based on a data-driven approach. First, we used generative adversarial networks to design an automated model for data augmentation. Second, we applied a convolutional neural network to classify wireless nodes for a wireless physical layer authentication model. To verify the effectiveness of the proposed model, we assessed our results using an original dataset as a baseline and a generated synthetic dataset. The findings indicate an improvement of approximately 19% in classification accuracy rate.
CRISPR/Cas9-Mediated Generation of Mutant Lines in Medicago truncatula Indicates a Symbiotic Role of MtLYK10 during Nodule Formation

Simple Summary Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) technology has become an important research tool for targeted mutagenesis in plants. However, the construction of mutants in the model legume Medicago truncatula remains challenging as it requires the combination of an efficient CRISPR/Cas9-mediated gene editing system for explants and specific tissue culture techniques for regeneration to whole plants. Here, we describe the construction of M. truncatula mutants using the Agrobacterium tumefaciens-mediated transformation of leaf explants. Regeneration to whole plants was performed at high efficiency (80%), and a gene editing efficiency of up to 70% was reached in the obtained plants. CRISPR/Cas9-mediated gene editing was achieved for three M. truncatula genes. Three mutant lines with knockout mutations in the LysM receptor kinase gene MtLYK10 were further characterized. Inoculation experiments with nitrogen-fixing Sinorhizobium meliloti bacteria indicated that root nodule formation was impaired in the constructed MtLYK10 mutants. In conclusion, we show that the described CRISPR/Cas9 system is suitable for efficient gene editing in M. truncatula and that MtLYK10 plays a role in nodule symbiosis. Abstract CRISPR/Cas9 systems are commonly used for plant genome editing; however, the generation of homozygous mutant lines in Medicago truncatula remains challenging. Here, we present a CRISPR/Cas9-based protocol that allows the efficient generation of M. truncatula mutants. Gene editing was performed for the LysM receptor kinase gene MtLYK10 and two major facilitator superfamily transporter genes. The functionality of CRISPR/Cas9 vectors was tested in Nicotiana benthamiana leaves by editing a co-transformed GUSPlus gene. Transformed M. truncatula leaf explants were regenerated to whole plants at high efficiency (80%). An editing efficiency (frequency of mutations at a given target site) of up to 70% was reached in the regenerated plants. Plants with MtLYK10 knockout mutations were propagated, and three independent homozygous mutant lines were further characterized. No off-target mutations were identified in these lyk10 mutants. Finally, the lyk10 mutants and wild-type plants were compared with respect to the formation of root nodules induced by nitrogen-fixing Sinorhizobium meliloti bacteria. Nodule formation was considerably delayed in the three lyk10 mutant lines. Surprisingly, the size of the rare nodules in mutant plants was higher than in wild-type plants. In conclusion, the symbiotic characterization of lyk10 mutants generated with the developed CRISPR/Cas9 protocol indicated a role of MtLYK10 in nodule formation.
The language network reliably ‘tracks’ naturalistic meaningful non-verbal stimuli

The language network, comprised of brain regions in the left frontal and temporal cortex, responds robustly and reliably during language comprehension but shows little or no response during many non-linguistic cognitive tasks (e.g., Fedorenko & Blank, 2020). However, one domain whose relationship with language remains debated is semantics—our conceptual knowledge of the world. Given that the language network responds strongly to meaningful linguistic stimuli, could some of this response be driven by the presence of rich conceptual representations encoded in linguistic inputs? In this study, we used a naturalistic cognition paradigm to test whether the cognitive and neural resources that are responsible for language processing are also recruited for processing semantically rich non-verbal stimuli. To do so, we measured BOLD responses to a set of ∼5-minute-long video and audio clips that consisted of meaningful event sequences but did not contain any linguistic content. We then used the inter-subject correlation (ISC) approach (Hasson et al., 2004) to examine the extent to which the language network ‘tracks’ these stimuli, i.e. exhibits stimulus-related variation. Across all the regions of the language network, non-verbal meaningful stimuli elicited reliable ISCs. These ISCs were higher than the ISCs elicited by semantically impoverished non-verbal stimuli (e.g., a music clip), but substantially lower than the ISCs elicited by linguistic stimuli. Our results complement earlier findings from controlled experiments (e.g., Ivanova et al., 2021) in providing further evidence that the language network shows some sensitivity to semantic content in non-verbal stimuli.
RESEARCH ON SOLUTIONS TO DETECT DISEASES ON ROSE LEAVES USING IMAGE PROCESSING TECHNIQUES

Ngày nay, kỹ thuật xử lý ảnh được vận dụng nhiều trong sản xuất nông nghiệp, đặc biệt là trên nông sản. Trong nghiên cứu này đề xuất giải pháp phát hiện bệnh trên lá hoa hồng bằng một giải thuật xử lý ảnh dựa trên đặc trưng của lá. Thuật toán này giúp phát hiện những vết bệnh trên lá của cây hoa hồng qua hình ảnh được thu thập từ vườn cây trồng. Phương pháp thực hiện theo các bước sau: thu thập ảnh mẫu, định dạng kích thước ảnh mẫu, tách vùng ảnh lá ra khỏi nền và sau đó chạy thuật toán SimpleBlobDector để phát hiện, khoanh vùng những ứng viên có khả năng là đốm bệnh. Thực nghiệm trên tập dữ liệu thu thập từ 500 hình ảnh cho thấy mô hình đạt độ chính xác 93,30%. Nghiên cứu này nhằm đưa ra một hướng đi mới trong việc phát hiện bệnh trên lá hoa hồng một cách tự động. Các ảnh nguồn và ảnh thu thập đã được chúng tôi thực hiện kiểm chứng với phương pháp đưa ra. Kết quả thu được chứng tỏ tính khả thi của phương pháp đề xuất.
SIMULATION AND EARLY WARNING OF NATURAL AND TECHNOGENIC INFLUENCES IN COASTAL AREAS IN THE SEA OF AZOV

In this work, the waves and currents generated by prognostic wind in the Sea of Azov are investigated using a three-dimensional nonlinear sigma-coordinate model. The mathematical model was also used for studying the transformation of passive admixture in the Sea of Azov, caused by the spatiotemporal variations in the fields of wind and atmospheric pressure, obtained from the prediction SKIRON model. Comparison of the results of numerical calculations and the data of field observations, obtained during the action of the wind on a number of hydrological stations was carried out. The evolutions of storm surges, velocities of currents and the characteristics of the pollution region at different levels of intensity of prognostic wind and stationary currents were found. The results of a comprehensive study allow reliably estimate modern ecological condition of offshore zones, develop predictive models of catastrophic water events and make science-based solutions to minimize the possible damage.
APPLY K-MEANS IN OUTLIER REMOVAL TO IMPROVE RICE LEAF DISEASE CLASSIFICATION PERFORMANCE USING MOBILENETV3 MODEL

Dân số tăng, quá trình đô thị hóa diễn ra nhanh chóng và diện tích đất nông nghiệp bị thu hẹp. Bệnh trên lá lúa được xem là nguyên nhân chính gây mất mùa, vì vậy việc chẩn đoán bệnh lá lúa sớm là quan trọng để giảm ảnh hưởng của chúng đối với năng suất, bảo đảm an ninh lương thực. Sử dụng công nghệ trong việc phát hiện và chẩn đoán các bệnh trên lá lúa là cần thiết. Nghiên cứu này đề xuất một phương pháp nhằm nâng cao độ chính xác của mô hình MobileNetV3. Phương pháp này bao gồm việc loại bỏ các hình ảnh trùng lặp và ngoại lệ sử dụng thuật toán K-Means. Tập dữ liệu sử dụng trong thí nghiệm được lấy từ một nguồn thứ cấp. Dữ liệu bao gồm 5932 hình ảnh của bốn loại bệnh phổ biến trên lá lúa. Ba tập dữ liệu khác nhau được tạo ra (Set-1, Set-2 và Set-3), tương ứng với ngưỡng bất thường 0,00, 0,05 và 0,06. Kết quả cho thấy, độ chính xác tăng đáng kể khi áp dụng phương pháp này. Độ chính xác Top-1 đã tăng từ 80,11% lên 86,85% và 87,69% tương ứng với Set-1, Set-2 và Set-3.
Antibiotic Resistance of Helicobacter pylori: Mechanisms and Clinical Implications

Helicobacter pylori is a pathogenic bacterium associated with various gastrointestinal diseases, including chronic gastritis, peptic ulcers, mucosa-associated lymphoid tissue lymphoma, and gastric cancer. The increasing rates of H. pylori antibiotic resistance and the emergence of multidrug-resistant strains pose significant challenges to its treatment. This comprehensive review explores the mechanisms underlying the resistance of H. pylori to commonly used antibiotics and the clinical implications of antibiotic resistance. Additionally, potential strategies for overcoming antibiotic resistance are discussed. These approaches aim to improve the treatment outcomes of H. pylori infections while minimizing the development of antibiotic resistance. The continuous evolution of treatment perspectives and ongoing research in this field are crucial for effectively combating this challenging infection.
Movement and interpretation of quantifiers in internally-headed relative clauses

This paper addresses the semantic typology of internally-headed relative clauses using a case study of two West African languages, Atchan (Kwa) and Bùlì (Gur). Both languages exhibit syntactically-similar relatives, involving overt movement of the head. However, quantifiers on the head are interpreted differently in the two languages. In Atchan, quantifiers on the relative-clause head take the entire relative clause as their restriction; in Bùlì, quantifiers on the head take only the head noun as their restriction. I propose that the former is interpreted via NP reconstruction and Trace Conversion, the latter via DP reconstruction. The empirical difference between these two languages motivates a revision to the typology developed by Grosu (2012), which tightly links head movement and the Atchan-like quantifier interpretation pattern. This work further supports a a modular view in which languages can adopt different strategies to interpret movement-involving structures.
Predicting the distribution of Vibrio vulnificus in Chesapeake Bay

Vibrio vulnificus is a gram-negative pathogenic bacterium endemic to coastal waters worldwide, and a leading cause of seafood related mortality. Because of human health concerns, understanding the ecology of the species and potentially predicting its distribution is of great importance. We evaluated and applied a previously published qPCR assay to water samples (n = 235) collected from the main-stem of the Chesapeake Bay (2007 – 2008) by Maryland and Virginia State water quality monitoring programs. Results confirmed strong relationships between the likelihood of Vibrio vulnificus presence and both temperature and salinity that were used to develop a logistic regression model. The habitat model demonstrated a high degree of concordance (93%), and robustness as subsequent bootstrapping (n=1000) did not change model output (P > 0.05). We forced this empirical habitat model with temperature and salinity predictions generated by a regional hydrodynamic modeling system to demonstrate its utility in future pathogen forecasting efforts in the Chesapeake Bay.
COVID-19 Pandemic and Food Insecurity Fuel the Mental Health Crisis in Africa

Objective: Providing country-level estimates for prevalence rates of Generalized Anxiety Disorder (GAD), COVID-19 exposure and food insecurity (FI) and assessing the role of persistent threats to survival—exemplified by exposure to COVID-19 and FI—for the mental health crisis in Africa. Methods: Original phone-based survey data from Mozambique, Sierra Leone, Tanzania and Uganda (12 consecutive cross-sections in 2021; n = 23,943) were analyzed to estimate prevalence rates of GAD. Logistic regression models and mediation analysis using structural equation models identify risk and protective factors. Results: The overall prevalence of GAD in 2021 was 23.3%; 40.2% in Mozambique, 17.0% in Sierra Leone, 18.0% in Tanzania, and 19.1% in Uganda. Both COVID-19 exposure (ORadj. 1.4; CI 1.3–1.6) and FI (ORadj 3.2; CI 2.7–3.8) are independent and significant predictors of GAD. Thus, the impact of FI on GAD was considerably stronger than that of COVID-19 exposure. Conclusion: Persistent threats to survival play a substantial role for mental health, specifically GAD. High anxiety prevalence in the population requires programs to reduce violence and enhance social support. Even during a pandemic, addressing FI as a key driver of GAD should be prioritized by policymakers.
Exploring the role of genomic instability in cancer and neurodegenerative disease through mouse models

Replication stress is an inherent source of DNA damage that living organisms suffer throughout their lives every time a cell divides. Our laboratory has previously contributed to this field by showing that replication stress can trigger ageing in mammals, and by showing that inhibition of the replication stress reponse kinase has potential anticancer activiy. In this context, the thesis of Maria has been focused on two independent questions. The first one was, can we make a mammalian model that limits the toxicity of replication stress? The second one was, can we identify tumors that have high levels of replication stress, and therefore wil be sensitive to ATR inhibitors?
Effect of Empirical Constant of Ramberg-Osgood Relation on the Buckling Strength of Transformer Inner Winding

The governing equation for determining the critical buckling stress of the inner winding of a transformer is nonlinear as well as non-polynomial. The non-polynomial nature of the equation is due to the non-integer value of an empirical constant denoted by ‘m’ which is present in the Ramberg-Osgood stress-strain relation. Therefore, the solution of the equation is to be determined by the numerical method like Newton-Raphson method for which an initial guess is required. In this letter, an investigation has been done to determine the effect of changing the existing non-integer value of ‘m’ to an integer value on the inner winding's critical buckling stress. With the integer value of the empirical constant, the equation becomes a polynomial, and then by determining the eigenvalues of polynomial's companion matrix, the roots of the polynomial have been determined. It is observed from the case studies that the result obtained with the integer value of the empirical constant is in close agreement with the non-integer value of the constant.
The study of the regulatory region of the Drosophila melanogaster Notch gene by new methods of directed genome editing

The Notch gene plays a key role in the development of organs and tissues of neuroectodermic origin, including the nervous system. In eukaryotic organisms, the Notch pathway is involved in cell fate determination. The Notch gene was first discovered in Drosophila melanogaster. In mammals, the family of Notch receptors includes four homologues. In humans, mutations in the Notch gene cause several hereditary diseases and carcinogenesis. Studies of the regulatory zone of the Notch gene in D. melanogaster have been conducted for several decades. We review their results and methods. The regulatory zone of the Notch gene is in the region of open chromatin state that corresponds to the 3C6/3C7 interband on the cytological map of polytene chromosomes of D. melanogaster salivary glands. The development of new methods for directed genome editing made it possible to create a system for introducing directed changes into the regulatory zone of the gene. Using the CRISPR/Cas9 system, we obtained a directed 4-kilobase deletion including the 5’-regulatory zone, promoter, and the first exon of the Notch gene and introduced the attP site into the first intron of the Notch gene. This approach enabled targeted changes of the sequence of the regulatory and promoter regions of the gene. Thus, it provided a new powerful tool for studies of Notch gene regulation and the organization of the open chromatin state.
The CLDAS soil moisture operation products applied to monitor soil drought

In 2012 a serious drought happened in China. In this paper,combined with the latest state surface soil and hydrological parameters,using the soil volumetric water content products of CMA Land Data Assimilation System( CLDAS-V1. 0), published in November of 2013, relative soil moisture in China in 2012 was calculated. Then,agricultural drought can be monitored based on the state standard of Agricultural Climate Center of China. The result shows that it can reflect the change of drought in all years,especially in Southw est Chia,South China,Northeast China and the Huanghuai and Jianghuai plains. It is believe that a temporal-spatial continuous real-time product can be made out to monitor the drought and to support agriculture development in China.
Malls designed for inclusion? Emotional experience of irritating aspects of the mallscape that distance consumers with disabilities

Purpose This study aims to identify the irritating aspects in the mall environment that impact shoppers with disability and explore the opportunities to design inclusive mall environments. Design/methodology/approach A mixed-methods design was used in which data collected using a survey (n = 1,434 shoppers with and without disability) were analyzed by structural equation modeling (SEM) and repeated-measures two-way ANOVA. In addition, qualitative data were obtained from critical incident technique (CIT) stories (n = 521) from shoppers with and without disability. Findings Mall environmental irritants evoke feelings of irritation that mediate the impacts of “inconvenient ambient conditions,” “the annoying socialscape” and “overwhelming design and atmospherics” on decreased mall-visit frequency. Compared with shoppers without disability, shoppers with disability suffer more from these irritating aspects of the mall environment, as evidenced by significantly greater high-activation unpleasant emotions. The “poor access and accessibility” category of irritants mainly affects the mall experiences of shoppers with disability. Practical implications Based on the findings, this study offers spatial-, temporal-, social-, material- and virtual-oriented recommendations for the design of inclusive retail spaces. The authors suggest that people with disability have a unique “lived experience” perspective on retail environments and that solutions should be co-created based on ongoing consultations with shoppers and employees with disability. Originality/value To the best of the authors’ knowledge, this study offers the first systematic, comprehensive comparison of the impact of environmental irritants on shoppers with and without disability and extends the literature on irritating aspects of retail environments from individual stores to malls.
Reuse of coir, peat, and wood fiber in strawberry production

Introduction Production of strawberries in greenhouses and polytunnels is gaining popularity worldwide. This study investigated the effect of reuse of coir and peat, two substrates commonly adapted to soilless strawberry production, as well as stand-alone wood fiber from Norway spruce, a promising substrate candidate. Methods The experiment was performed in a polytunnel at NIBIO Apelsvoll, Norway, and evaluated both virgin substrates, as well as spent materials that were used in one or two years. Yield, berry quality and plant architecture of the strawberry cultivar ‘Malling Centenary’ were registered. In addition, chemical and physical properties of virgin and reused substrates were investigated. Results While plants grown in peat and wood fiber had highest yield in the first year of production, the berry yield was slightly reduced when these substrates were utilized for the second and third time. However, yield was comparable to the yield level attained in new and reused coir. Interestingly, berries grown in wood fiber had a tendency to a higher sugar accumulation. This substrate also produced the highest plants. Stand-alone wood fiber was the substrate with the highest accumulation of nitrogen during the three consecutive production cycles. All three investigated materials revealed a trend for decreased potassium accumulation. Wood fiber is characterized by the highest percentage of cellulose, however after three years of production the cellulose content was reducedto the same levels as for coir and peat. Discussion Implementation of wood fiber as a growing medium, as well as general practice of substrate reuse can be therefore an achievable strategy for more sustainable berry production.