Miracle-dz/UniFAR-FTUs huggingface dataset:
Discovery and Characterization of MaK: A Novel Knottin Antimicrobial Peptide from Monochamus alternatus

Knottin-type antimicrobial peptides possess exceptional attributes, such as high efficacy, low vulnerability to drug resistance, minimal toxicity, and precise targeting of drug sites. These peptides play a crucial role in the innate immunity of insects, offering protection against bacteria, fungi, and parasites. Knottins have garnered considerable interest as promising contenders for drug development due to their ability to bridge the gap between small molecules and protein-based biopharmaceuticals, effectively addressing the therapeutic limitations of both modalities. This work presents the isolation and identification of a novel antimicrobial peptide derived from Monochamus alternatus. The cDNA encodes a 56-amino acid knottin propeptide, while the mature peptide comprises only 34 amino acids. We have labeled this knottin peptide as MaK. Using chemically synthesized MaK, we evaluated its hemolytic activity, thermal stability, antibacterial properties, and efficacy against nematodes. The results of this study indicate that MaK is an exceptionally effective knottin-type peptide. It demonstrates low toxicity, superior stability, potent antibacterial activity, and the ability to suppress pine wood nematodes. Consequently, these findings suggest that MaK has potential use in developing innovative therapeutic agents to prevent and manage pine wilt disease.
Localization in Tunnels Using Feature-based Scan Matching

In tunnel inspections, it is important to determine whether cracks and other deformations are caused by external forces. Therefore, point clouds at two different periods are compared to determine if any deformation has occurred and register these point clouds. In mobile mapping systems using global navigation satellite system (GNSS)/inertial measurement unit (IMU) navigation, tunnel point clouds are distorted due to accumulated errors. Therefore, it is not possible to compare the acquired raw point clouds with each other. Previously, point clouds were aligned manually, but this was time-consuming and expensive. In this work, we propose a positioning correction technique based on scan matching according to tunnel features and describe the evaluation results. The evaluation experiment showed the proposed method’s effectiveness, reducing the average error from 0.834 m to 0.063 m.
Ayahuasca-induced personal death experiences: prevalence, characteristics, and impact on attitudes toward death, life, and the environment

Introduction Despite an emerging understanding regarding the pivotal mechanistic role of subjective experiences that unfold during acute psychedelic states, very little has been done in the direction of better characterizing such experiences and determining their long-term impact. The present paper utilizes two cross-sectional studies for spotlighting – for the first time in the literature – the characteristics and outcomes of self-reported past experiences related to one’s subjective sense of death during ayahuasca ceremonies, termed here Ayahuasca-induced Personal Death (APD) experiences. Methods Study 1 (n = 54) reports the prevalence, demographics, intensity, and impact of APDs on attitudes toward death, explores whether APDs are related with psychopathology, and reveals their impact on environmental concerns. Study 2 is a larger study (n = 306) aiming at generalizing the basic study 1 results regarding APD experience, and in addition, examining whether APDs is associated with self-reported coping strategies and values in life. Results Our results indicate that APDs occur to more than half of those participating in ayahuasca ceremonies, typically manifest as strong and transformative experiences, and are associated with an increased sense of transcending death (study 1), as well as the certainty in the continuation of consciousness after death (study 2). No associations were found between having undergone APD experiences and participants’ demographics, personality type, and psychopathology. However, APDs were associated with increased self-reported environmental concern (study 1). These experiences also impact life in profound ways. APDs were found to be associated with increases in one’s self-reported ability to cope with distress-causing life problems and the sense of fulfillment in life (study 2). Discussion The study’s findings highlight the prevalence, safety and potency of death experiences that occur during ayahuasca ceremonies, marking them as possible mechanisms for psychedelics’ long-term salutatory effects in non-clinical populations. Thus, the present results join other efforts of tracking and characterizing the profound subjective experiences that occur during acute psychedelic states.
ANALYSIS OF SUSTAINABILITY PERFORMANCE, GREEN ACCOUNTING AND ESG DISCLOSURE ON FIRM VALUATION

Numbers of public companies whose shares are listed on Indonesia Stock Exchange is growing rapidly. The increase in public companies is phenomenon that describe the confidence of investors to invest in shares of public companies. Firm valuation is an important determining factor for stock investors to choose investment products. Currently firm value is not only seen from the company's ability to generate profits but also seen from other factors related to sustainability. This study aims to obtain empirical evidence on the influence of sustainability performance, green accounting and ESG disclosure on firm value. This study uses a quantitative approach and panel data regression on banking sector companies listed on the Indonesia Stock Exchange for the 2012-2021 period. The analysis technique uses ordinary least squares with statistical software. The results show that sustainability performance has a positive effect on firm value, while green accounting has a negative effect on firm value. On the other hand, ESG disclosure gives no impact on firm value. Sustainability performance and implementation of green accounting needs to be highlighted in order to have a positive impact on the company by increasing the effectiveness and efficiency of its implementation as well as integrating it into its operations.
Digital Depth: A Volumetric Speculation

Counter commonplace associations with superficial mediation and networked flatness, the digital seems to have its own peculiar depths, which range from the infrastructural (deep sea cables, deep packet inspection, crawl depth) to the metaphorical (Deep Web, deep learning, deepfakes). This article reviews recent discussions of digital depth and argues that this concept is central to understanding multiple aspects of digital media ranging from folk theorizations to technical expertise. What is digital depth? What is deep about digital media? How does this depth interface with volumes and scales beyond the digital? Through this effort, depth emerges as an underlying feature of deeply mediatized societies.
Sedimentation and vegetation history of a buried Meuse terrace during the Holocene in relation to the human occupation history (Limburg, the Netherlands)

Abstract During several archaeological excavations on a river terrace of the river Meuse near the village of Lomm (southeast Netherlands) information was gathered for a reconstruction of the sedimentation and vegetation history during the Holocene. Various geoarchaeological methods – geomorphological, micromorphological and botanical analyses – were applied, while accelerator mass spectrometry (AMS) 14C and optically stimulated luminescence (OSL) dating provided an accurate chronology for the sediments. During the Early Holocene, many former braided river channels were deepened due to climate amelioration. Later, river flow concentrated in one main river channel to the west, at the location of the modern Meuse. The other channels were only active during floods, and infilling continued until the Bronze Age. Because of the higher setting of the Lomm terrace, it was only occasionally flooded and therefore formed an excellent location for habitation. Humans adapted to the changing landscape, as most remains were found on the higher river terraces or their slopes, a short distance from the Maas river. The Lomm terrace was more or less continuously inhabited from the Mesolithic onwards. During the Early Holocene, river terraces were initially densely forested with birch and pine. From the Boreal (Mesolithic) onwards, dense mixed forests with deciduous shrubs and trees such as hazel, oak, elm and lime developed. During the Atlantic (Meso/Neolithic), the deciduous forests became dominated by oak. Due to human activities from the Late Subboreal (Late Bronze Age) onwards, forests slowly became more open, yet remained relatively dense in comparison to other Dutch areas. The botanical data, however, show that within the Lomm study area there was a large difference in the composition, distribution and openness of the vegetation. The spatial variation in openness came into existence during the Late Bronze Age, as soon as the higher areas started to be used for human activities (i.e. habitation, agriculture and livestock herding). Due to human activities, the northern part of the study area became very open during the Early Roman period. In the lower-situated areas of the southern part, however, forests remained present much longer, until the Early Middle Ages. Due to large-scale deforestation in the Lomm area and hinterland during the Roman period and Middle Ages, the sediment load of the river increased, large floods occurred and overbank sediments were deposited, burying the archaeological remains. The largest increase in sedimentation occurred after the Middle Ages.
THE ROLE OF MATTOANGING FARMER GROUP IN INCREASING MAIZE (Zea mays) PRODUCTION IN MASSEPE VILLAGE

This study aims to determine the role of the Mattoanging farmer group in increasing maize production in the Massepe Village. This quantitative descriptive research uses a non-experimental approach with a survey type. The research using a questionnaire obtained an average percentage in learning classes 72.3%, in collaboration vehicles of 75.8%, and production units of 81.2%. After being analyzed using the Rank-Spearman Correlation, the correlation coefficient in the learning class was 0.678. In cooperative vehicles, it is 0.683; in production units, it is 0.654. These three values indicate a strong relationship with a positive direction. The significance value obtained from the three variables is below 0.05 (α = 5%). This means that H0 is rejected and H1 is accepted, which means that there is a significant relationship between the role of the Mattoanging farmer group as a learning class, a vehicle for cooperation, and a production unit in increasing maize production in Massepe Village, Tellu Limpoe District, Sidenreng Rappang Regency.
Top management characteristics and comprehensive focus on budgeting

PurposeThis study examines how the strong emphasis placed on the purposes of budgeting, referring to a comprehensive focus on budgeting, is related to top managers' education and tenure while controlling for their functional positions in their respective firms and ages, as well as several company-specific predictors (information quality, firm size, information technology, importance of profit and strategy). Design/methodology/approachSurvey data were collected from senior managers of large manufacturing firms in Finland and Sweden.FindingsThe results suggest that academic business education is positively associated with a comprehensive focus on budgeting, but tenure as well as functional position in the company (Chief Financial Officer (CFO) or not) and age are not. Overall, the company-specific control variables in general and information quality in particular are shown to have greater explanatory power than the top management characteristics analyzed.Research limitations/implicationsThis study identifies several empirically supported factors that seem to contribute to a comprehensive focus on budgeting. The effects of information quality, business education, the importance of profit and firm size could be considered in future research.Practical implicationsAcademic business education matters more than the other top management characteristics analyzed. If organizations want to make comprehensive use of budgets, they should employ business graduates and be mindful of company-specific variables.Originality/valueThis study is the first to address a comprehensive focus on budgeting and some of its determinants. Future research could investigate a broader set of such determinants in different contexts.
Greedy knot selection algorithm for restricted cubic spline regression

Non-linear regression modeling is common in epidemiology for prediction purposes or estimating relationships between predictor and response variables. Restricted cubic spline (RCS) regression is one such method, for example, highly relevant to Cox proportional hazard regression model analysis. RCS regression uses third-order polynomials joined at knot points to model non-linear relationships. The standard approach is to place knots by a regular sequence of quantiles between the outer boundaries. A regression curve can easily be fitted to the sample using a relatively high number of knots. The problem is then overfitting, where a regression model has a good fit to the given sample but does not generalize well to other samples. A low knot count is thus preferred. However, the standard knot selection process can lead to underperformance in the sparser regions of the predictor variable, especially when using a low number of knots. It can also lead to overfitting in the denser regions. We present a simple greedy search algorithm using a backward method for knot selection that shows reduced prediction error and Bayesian information criterion scores compared to the standard knot selection process in simulation experiments. We have implemented the algorithm as part of an open-source R-package, knutar.
Comprehensive Study on High Resolution Aerial Image Classification to highlight Issues, potential Application, and Future Scope

In several fields, including remote sensing, medical imaging, surveillance, and object recognition, high-resolution picture categorization is vital. The availability of high-resolution images has presented fresh difficulties and chances for the advancement of advanced categorization methods. This paper provides an overview of the techniques, challenges, and applications along with the work done by several researchers in past years related to high-resolution image classification. When the target is aerial image classification then Feature Extraction, SVM, CNN, FCN are some of the available techniques. No single source is detailing the work so the purpose of writing the paper is to present a thorough analysis of the study so new researchers and beginners of this field may get perfect motivation to start their research work
Implications of tRNA abundance on translation elongation across bovine tissues

Introduction: Translation is a crucial stage of gene expression. It may also act as an additional layer of regulation that plays an important role in gene expression and function. Highly expressed genes are believed to be codon-biased to support increased protein production, in which quickly translated codons correspond to highly abundant tRNAs. Synonymous SNPs, considered to be silent due to the degeneracy of the genetic code, may shift protein abundance and function through alterations in translational efficiency and suboptimal pairing to lowly abundant tRNAs. Methods: Here, we applied Quantitative Mature tRNA sequencing (QuantM-tRNAseq) and ribosome profiling across bovine tissues in order to investigate the relationship between tRNA expression and slowed translation. Results: Moreover, we have identified genes modulated at transcriptional and/or translational levels underlying tissue-specific biological processes. We have also successfully defined pausing sites that depict the regulatory information encoded within the open reading frame of transcripts, which could be related to translation rate and facilitate proper protein folding. This work offers an atlas of distinctive pausing sites across three bovine tissues, which provides an opportunity to predict codon optimality and understand tissue-specific mechanisms of regulating protein synthesis.
Channel Modelling on Micro-Doppler Feature of a Pedestrian at 77 GHz

The advent of 6th-generation (6G) technology has led to a significant improvement in sensing capability due to the increased bandwidth. In this way, the micro-Doppler phenomenon can be explicitly observed. By further elucidation, it holds potential for application in target recognition within intelligent connected vehicles. Towards the above concerns, this work replicates the micro-Doppler effect under 77 GHz radar resulting from the swinging arm motion of pedestrians through the utilisation of the ray-tracing (RT) approach. The simulation is then calibrated to align with the measurements by adjusting the electromagnetic (EM) parameters. After that, the calibrated virtual environment is employed to comprehensively analyse the micro-Doppler features introduced by the swinging arm from different angles. The study replicated the observed micro-Doppler pattern of pedestrian swing arms under the radar using RT, offering a precise and effective approach for creating sensing channel data, which will meet the demands of extensive data necessary for the development of detection algorithms.
Characterization of the dynamic actions and scour estimation downstream of a dam

The study analyzes the expected changes in the Paute River, located in Ecuador, as a result of the construction of the Paute-Cardenillo Dam (owned by Celec Ep-Hidropaute). The dam will integrate the National Electric System of Ecuador with a total electricity installed capacity of 600 MW which will produce 13000 GWh per year. To evaluate the stability and safety of the structure, it is necessary to ascertain the shape and dimensions of the scour generated downstream from the dam. The scour, due to the operation of the spillway and outlets, is studied with three complementary procedures: empirical formulae obtained in models and prototypes, semi-empirical methodology based on pressure fluctuationserodibility index and computational fluid dynamics simulations.
Exact BER Performance Analysis of an Elementary Coding Techniques for NOMA System on AWGN Channel

Ultra-Reliable Low Latency Communication (URLLC) requirements of modern wireless communication systems have heightened the need for complexity reduction in data processing along with error detection and correction techniques. Motivated by this fact, we introduce a low-complexity coding scheme for Non-Orthogonal Multiple Access (NOMA). Furthermore, this work presents a comprehensive mathematical analysis of the proposed coded NOMA communication system and evaluates its Bit Error Rate (BER) performance in various scenarios. Our study showcases a precise match between practical and theoretical results, underlining the presented mathematical analysis precision. Moreover, we conduct a comparison between the proposed NOMA system and other coded and uncoded NOMA systems. This comparison highlights the superior performance of the proposed system, providing evidence of its potential to achieve the desired complexity reduction without compromising performance. Finally, in the same work environment, it is worth noting that the proposed system demonstrated superior performance compared to typical uncoded NOMA systems. It achieved a minimum improvement of 21 dB for the 1 st user and a 17 dB improvement for the 2 nd and 3 rd users.
Application of genetic algorithms to constrain near-source velocity structure for the 1989 Sichuan earthquakes

When a complex earthquake source process is studied using broadband body waveforms, a common problem is finding an adequate layered velocity model for the near-source structure. Tests with several existing crustal models are not sufficient or objective, but an enumerative search scheme to search through a whole possible model space is not practical. We study the feasibility of applying genetic algorithms (GA) to rapidly and effectively explore the model space to find an optimal model for the near-source structure. Our data set consists of multi-station broadband body waveforms of a simple event recorded at teleseismic distances. The near-source velocity structure is approximated by a layered model, and the model parameters include the layer thicknesses and velocities as well as the source depth forming a multi-parameter search space. Test results with synthetic data indicate that optimal models can be found using GA depending on the noise level. When the noise level is low, optimal models are well recovered with small uncertainty. Results with the data of the 1989 earthquakes of Sichuan Province, China, indicate that a three-layer velocity model obtained with GA is in agreement with regional models and better explains the observed waveforms.
Introduction: reconsidering Chinese citizenship: cultural roots and cultural reach

ABSTRACT The study of citizenship in China has become popular not only as a research topic but also as a praxis that seeks to influence citizenship-related policies and address structural injustice. Analysis of the trajectory of developing citizenship research over the decades indicates that scholarship focusing on socioeconomic injustice has affected various policy actions, and the struggle associated with the cultural dimension of citizenship seems to have intensified. This special issue deconstructs the state’s monolithic interpretation of culture and examines the cultural underpinnings of citizenship discourse and practice in China. We take a broad view of cultural traditions, which have been deeply rooted throughout history and have shaped the underlying relationships between the state, society, and citizens in modern China. The articles in this special issue reveal the culture-informed citizenship practices enacted by various actors, including the government forces, cultural minorities, and grassroots activists. They suggest that spirituality is a site of experiencing and negotiating citizenship in the Chinese context.
Dynamic Time Signature Recognition, Tempo Inference, and Beat Tracking Through the Metrogram Transform

This paper proposes a probabilistic approach for extracting time-varying and irregular time signature information from polyphonic audio extracts, subsequently providing beat and bar line positions given inferred time signature divisions. This is achieved via dynamically evaluating the beat tempo as a function of time through finding an optimal compromise in beat and bar alignment in the time and tempo domains. Time signature divisions are determined based on a new representation, termed the Metrogram, that presents time-varying information regarding rhythmic and metric periodicities in the Tempogram. Our methodology is characterised by its ability to provide a distribution over metric interpretations, offering insights into the diverse ways music can be rhythmically perceived. Results indicate high-level accuracy for a variety of polyphonic extracts containing irregular, complex, irrational, and time-varying time signatures. Accuracy rivalling state-of-the-art methodologies is also reported in a beat tracking task performed on the standard Ballroom Dataset. The paper offers insights into the field of dynamic time signature recognition and beat tracking, offering a valuable and versatile resource for the analysis, composition, and performance of music.