Miracle-dz/UniFAR-FTUs huggingface dataset:
SPECIAL ISSUE ON INTRASPECIFIC VARIATION IN PLANT FUNCTIONAL TRAITS Effects of intrinsic environmental predictability on intra-individual and intra-population variability of plant reproductive traits and eco-evolutionary consequences

• Background and Aims It is widely accepted that changes in the environment affect mean trait expression, but little is known about how the environment shapes intra-individual and intra-population variance. Theory suggests that intra-individual variance might be plastic and under natural selection, rather than reflecting developmental noise, but evidence for this hypothesis is scarce. Here, we experimentally tested whether differences in intrinsic environmental predictability affect intra-individual and intra-population variability of different reproductive traits, and whether intra-individual variability is under selection. • Methods Under field conditions, we subjected Onobrychis viciifolia to more and less predictable precipitation over 4 generations and 4 years. We analysed effects on the coefficient of intra-individual variation (CV i-i ) and the coefficient of intra-population variation (CV i-p ), assessed whether the coefficients of intra-individual variation (CsV i-i ) are under natural selection and tested for transgenerational responses (ancestor environmental effects on offspring). • Key Results Less predictable precipitation led to higher CsV i-i and CsV i-p , consistent with plastic responses. The CsV i-i of all studied traits were under consistent stabilizing selection, and precipitation predictability affected the strength of selection and the location of the optimal CV i-i of a single trait. All CsV i-i differed from the optimal CV i-i and the maternal and offspring CsV i-i were positively correlated, showing that there was scope for change. Nevertheless, no consistent transgenerational effects were found in any of the three descendant generations, which contrasts with recent studies that detected rapid transgenerational responses in the trait means of different plant species. This suggests that changes in intra-individual variability take longer to evolve than changes in trait means, which may explain why high intra-individual variability is maintained, despite the stabilizing selection. • Conclusions The results indicate that plastic changes of intra-individual variability are an important determinant of whether plants will be able to cope with changes in environmental predictability induced by the currently observed climatic change.
Rethinking Work: a Research Odyssey into Robotics Process Automation Dynamic

: In an era defined by technological innovation, "Rethinking Work" embarks on a comprehensive research odyssey to explore the intricate dynamics of Robotics Process Automation (RPA) and its profound impact on the modern workplace. This research delves beyond the surface-level efficiencies associated with RPA, seeking to uncover the nuanced transformations it introduces to the very fabric of work. The study begins by establishing a theoretical foundation, examining the historical evolution of automation and contextualizing RPA within the broader landscape of digital transformation. Moving beyond mere mechanization, the research scrutinizes how RPA redefines organizational structures, employee roles, and the nature of tasks in diverse industries. The research methodology incorporates a multifaceted approach, drawing insights from case studies, interviews, and empirical data analysis. By synthesizing findings from organizations that have embraced RPA and those still navigating its implementation, the research aims to provide a nuanced understanding of the challenges, opportunities, and strategic considerations inherent in this transformative journey.
ScholarWorks@UARK ScholarWorks@UARK

Regression analysis can be an effective way of examining performance in the marathon event. By splitting up the race into segments or in runner terminology “splits” the significance of each segment as it relates to the total finish time can be explored. Because the idea of splits is already ingrained into the minds of runners, it makes intuitive sense to use these as the metrics to define a race. Additionally, marathons generally make participant age and gender date publicly available which can then be used to find trends within specific demographics. This tailors trends to smaller groups of people, making the lessons from these trends more easily applied during the marathon. The most popular warning within the marathon community is that of the “fast start” which is translated to mean running faster than your average pace at the beginning of the race and consequently slowing down through the remainder of the race. Because of this, after segregating our data into four subsets, each runner’s pace in the first 10 kilometers (23.66%) of the race was plotted against their total finish time. In three out of the four subsets of the data the anecdote appeared to be clearly substantiated as runners who started slowest in relation to their mean race pace tended to have lower total finish times, and finish time generally increased as the percentage above mean race pace of runners increased.
in Claw-Free Graphs

The Hamiltonian Cycle problem asks if an n -vertex graph G has a cycle passing through all vertices of G . This problem is a classic NP -complete problem. So far, ﬁnding an exact algorithm that solves it in O ∗ ( α n ) time for some constant α < 2 is a notorious open problem. For a claw-free graph G , ﬁnding a hamiltonian cycle is equivalent to ﬁnding a closed trail (eulerian subgraph) that dominates the edges of some associated graph H . Using this translation we obtain two exact algorithms that solve the Hamiltonian Cycle problem for the class of claw-free graphs: one algorithm that uses O ∗ (1 . 6818 n ) time and exponential space, and one algorithm that uses O ∗ (1 . 8878 n ) time and polynomial space.
Physical activity and cognitive function in individuals over 60 years of age: a systematic review

Background: It is unclear whether physical activity in later life is beneficial for maintenance of cognitive function. We performed a systematic review examining the effects of exercise on cognitive function in older individuals, and present possible mechanisms whereby physical activity may improve cognition. Methods: Sources consisted of PubMed, Medline, CINAHL, the Cochrane Controlled Trials Register, and the University of Washington, School of Medicine Library Database, with a search conducted on August 15, 2012 for publications limited to the English language starting January 1, 2000. Randomized controlled trials including at least 30 participants and lasting at least 6 months, and all observational studies including a minimum of 100 participants for one year, were evaluated. All subjects included were at least 60 years of age. Results: Twenty-seven studies met the inclusion criteria. Twenty-six studies reported a positive correlation between physical activity and maintenance or enhancement of cognitive function. Five studies reported a dose-response relationship between physical activity and cognition. One study showed a nonsignificant correlation. Conclusion: The preponderance of evidence suggests that physical activity is beneficial for cognitive function in the elderly. However, the majority of the evidence is of medium quality with a moderate risk of bias. Larger randomized controlled trials are needed to clarify the association between exercise and cognitive function and to determine which types of exercise have the greatest benefit on specific cognitive domains. Despite these caveats, the current evidence suggests that physical activity may help to improve cognitive function and, consequently, delay the progression of cognitive impairment in the elderly.
Comparative Analysis of Cu and Ag doped ZnO: Influence of Doping Concentration and Annealing Temperature on Optical and Electrical Properties

: In this work, Cu-doped and Ag-doped zinc oxide films were deposited using the sol-gel method. The impact of annealing temperature and doping concentration on optical and electrical properties were examined. It was noted that the annealing temperature has less effect on both the Cu-doped and Ag-doped zinc oxide films optical band gap energy. The minimum resistivity for Ag doped ZnO was From the study it was understood that Ag doped ZnO has lower resistivity as compared to Cu doped ZnO both at different doping concentrations and annealing temperatures.
Evaluation of Corneal Endothelium Function by Combined Evaluation of Corneal Endothelium Function by Combined Measurement of Corneal Volume and Specular Microscopy before Measurement of Corneal Volume and Specular Microscopy before and after Phacoemulsification and after Phacoemulsification

Background: Clarity of the cornea is fundamental for pure vision following cataract surgery including phacoemulsification . The pumping action of corneal endothelial cells acts to maintain this clarity through maintaining the corneal stroma dehydrated, so integrity of this cell layer function is very important for corneal clarity. Aim of work: To evaluate endothelial cell layer function before and after phacoemulsification by assessment of changes in density of endothelial cell and corneal volume of central corneal ring of 10 mm diameter. Patient and methods: A prospective interventional study was performed during the period from September2019 to December 2019 at Sayed Galal University Hospital. A total of 22 eyes from15 subjects, aged 50 -65 years old, both genders were involved. All patients had an uneventful phacoemulsification for immature senile cataract. Patients were evaluated pre and postoperatively by Topcon® SP-1P specular microscope for cell density and by SIRIUS® 3D rotating Scheimpflug &amp; topography system for corneal volume of central 10 mm ring Results: Our results demonstrated that specular endothelial cell density decreased significantly and Central corneal volume increased significantly after phacoemulsification. Cell density changes Showed a reverse proportional correlation with corneal volume changes. Conclusion: The increase in corneal volume following phacoemulsification can indicate the degree of the endothelial damage. A single anatomical or functional test may not be sufficient for definite evaluation of endothelial dysfunction after phacoemulsification.
UvA-DARE (Digital Academic Repository) Sequential simulation-based inference for gravitational wave signals

The current and upcoming generations of gravitational wave experiments represent an exciting step forward in terms of detector sensitivity and performance. For example, key upgrades at the LIGO, Virgo and KAGRA facilities will see the next observing run (O4) probe a spatial volume around four times larger than the previous run (O3), and design implementations for e.g. the Einstein Telescope, Cosmic Explorer and LISA experiments are taking shape to explore a wider frequency range and probe cosmic distances. In this context, however, a number of very real data analysis problems face the gravitational wave community. For example, it will be crucial to develop tools and strategies to analyse (amongst other scenarios) signals that arrive coincidentally in detectors, longer signals that are in the presence of non-stationary noise or other shorter transients, as well as noisy, potentially correlated, coherent stochastic backgrounds. With these challenges in mind, we develop peregrine , a new sequential simulation-based inference approach designed to study broad classes of gravitational wave signal. In this work, we describe the method and implementation, before demonstrating its accuracy and robustness through direct comparison with established likelihood-based methods. Speciﬁcally, we show that we are able to fully reconstruct the posterior distributions for every parameter of a spinning, precessing compact binary coalescence using one of the most physically detailed and computationally expensive waveform approximants ( SEOBNRv4PHM ). Crucially, we are able to do this using only 2% of the waveform evaluations that are required in e.g. nested sampling approaches. Finally, we provide some outlook as to how this level of simulation eﬃciency and ﬂexibility in the statistical analysis could allow peregrine to tackle these current and future gravitational wave data analysis problems.
On syntactical graphs-of-words

A graph-of-words is a graph representation of natural language text based on proximity in the linear text reading order: the vertices are the words, and edges are induced by 𝑘 left and right neighbours of the words. Vertices representing same or similar words are then contracted. We propose graphs-of-words where edges are instead induced on paths in the syntax trees (we investigate both dependency and constituency trees). We discuss some properties, advantages, and disadvantages of classic and new graphs-of-words on texts extracted from literature, as well as from a technical Q&A database
A GAP that Divides [version 1; peer review: 3 approved]

Cytokinesis in metazoan cells is mediated by an actomyosin-based contractile ring that assembles in response to activation of the small GTPase RhoA. The guanine nucleotide exchange factor that activates RhoA during cytokinesis, ECT-2, is highly regulated. In most metazoan cells, with the notable exception of the early Caenorhabditis elegans embryo, RhoA activation and furrow ingression require the centralspindlin complex. This exception is due to the existence of a parallel pathway for RhoA activation in C. elegans . Centralspindlin contains CYK-4 which contains a predicted Rho family GTPase-activating protein (GAP) domain. The function of this domain has been the subject of considerable debate. Some publications suggest that the GAP domain promotes RhoA activation (for example, Zhang and Glotzer, 2015; Loria, Longhini and Glotzer, 2012), whereas others suggest that it functions to inactivate the GTPase Rac1 (for example, Zhuravlev et al ., 2017). Here, we review the mechanisms underlying RhoA activation during cytokinesis, primarily focusing on data in C. elegans. We highlight the importance of considering the parallel pathway for RhoA activation and detailed analyses of cyk-4 mutant phenotypes when evaluating the role of the GAP domain of CYK-4.
Identification of small-scale discontinuities based on dip-oriented gradient energy entropy coherence estimation

Locating small-scale discontinuities is one of the most challenging geophysical tasks; these subtle geological features are significant since they are often associated with subsurface petroleum traps. Subtle faults, fractures, unconformities, reef textures, channel boundaries, thin-bed boundaries and other structural and stratigraphic discontinuities have subtle geological edges which may provide lateral variation in seismic expression. Among the different geophysical techniques available, 3D seismic discontinuity attributes are particularly useful for highlighting discontinuities in the seismic data. Traditional seismic discontinuity attributes are sensitive to noise and are not very appropriate for detecting small-scale discontinuities. Thus, we present a dip-oriented gradient energy entropy (DOGEE) coherence estimation method to detect subtle faults and structural features. The DOGEE coherence estimation method uses the gradient structure tensor (GST) algorithm to obtain local dip information and construct a gradient correlation matrix to calculate gradient energy entropy. The proposed DOGEE coherence estimation method is robust to noise, and also improves the clarity of fault edges. It is effective for small-scale discontinuity characterisation and interpretation. We have proposed a dip-oriented gradient energy entropy (DOGEE) coherence method to detect subtle faults and structural features. Theoretical synthetic datasets and a real dataset show that our proposed method is not only robust to noise, but also improves the clarity of small-scale discontinuities.
Applicability of Mel-Cepstrum-Related Features for Action Recognition Based on Data from Impulse-Radar Sensors

This paper is devoted to research on the application of impulse-radar technology for unobtrusive monitoring of elderly persons. The applicability of mel-cepstrum-related features for action recognition by an impulse-radar-based monitoring system is explored. The data from the impulse-radar sensors are first transformed into the monitored person's three-dimensional coordinates which are then used to calculate features characterising that person's movement. The findings from the real-world experiments show that the proposed set of features can be used to improve the accuracy of recognition of actions such as walking, sitting and lying down.
Highly Reliable, Stable, and Store Energy Efficient 8T/9T-2D-2MTJ NVSRAMs

Non-Volatile SRAMs exhibit zero static power loss which is eminent for future on-chip memories. Thus, in this brief, two simple and scalable designs of NVSRAM (8T&9T-2D-2MTJ) having key properties (high speed, low dynamic power, stability and reliability) have been investigated. To make the circuit scalable, the perpendicular magneto anisotropy (PMA) based magnetic tunnel junction (MTJ) (works on the spin transfer torque (STT) & spin orbit torque (SOT) interplay phenomenon) are used as an NV cell in the proposed circuit. A small pulse of current is required for store and restore operation of NV cell, which can effectively accommodate through cross coupled inverters, makes external write circuitry redundant and reduce the complexity of bit cell. The 8T/9T-2MTJ circuit provides an approximate 38%/35% decrease in store delay along with 7%/32% power efficiency as compared to existing NVSRAMs. The hold and write stability of 8T-2MTJ cell is better. However, the read stability of 9T-2MTJ cell is better. The physics-based field-free STT-SOT MTJ model and 40 nm UMC CMOS design kit based NVSRAM make the circuit practically viable. The Process variation analysis and monte carlo analysis suggests that the proposed NVSRAMs are reliable for a wide range (−25 °C to 125 °C) of temperatures and supply voltages. The 8*8 array design of proposed NVSRAMs shows promising results for dense memory architecture.
Multi-source Analysis of AI Vulnerabilities: Methodology and Algorithms of Data Collection

The initial stage of assessing the cybersecurity of artificial intelligence (AI) systems and tools for cyber-physical systems is the collecting, processing and integrating of vulnerability data from relevant and reliable information sources using Big Data tools. The article provides a classification of sources of information about vulnerabilities of AI systems. The possibilities of automatic scanning of these sources using software scanners are analyzed. The analysis methodology and data structures are proposed, and the necessary set of data for further storing and analyzing is selected. Algorithms for direct collection of vulnerability data from various sources are developed. The directions of further research on the development of algorithms and software tools for aggregation, filtering, processing and integration of multisource data on vulnerabilities of AI systems are substantiated.
Case Report: Colon malignant tumor caused by retroperitoneal small round cell undifferentiated sarcoma

Small round cell undifferentiated sarcoma is a rare and highly invasive group of malignant bone and soft tissue tumors, often associated with a high misdiagnosis rate. The patient in this case was a 34-year-old male who presented with a two-month history of abdominal pain that worsened over the past two weeks. Elevated levels of tumor markers CA19-9 and CA72-4 were observed. Imaging revealed a substantial, well-vascularized mass in the lower left abdomen, located in the posterior abdominal cavity, invading the descending colon and the root of the small mesentery, and infiltrating the serous layer. The lesion was extensively resected without any postoperative complications. Microscopic examination indicated a combination of mucinous adenocarcinoma (approximately 30%) and small round cell undifferentiated sarcoma (approximately 70%). The patient was followed up for six months, and one month after surgery, a recurrence of the tumor was observed in the left paracolonic sulcus area, with metastases to the abdominal wall, peritoneum, and medial iliac muscles. Chemotherapy and targeted therapy were administered, and the patient currently survives with the presence of tumors. Small round cell undifferentiated sarcoma is an uncommon and highly invasive tumor, and clinical surgeons need to raise their awareness and realize to the maximum extent possible that this disease can be described through a multi-modal combination of immunohistochemistry and genetic test to improve diagnostic accuracy and reduce missed diagnoses. Further research in the field of biology is necessary to explore targeted drugs specifically suitable for this disease.
Advances in Predicting Drug Functions: A Decade-Long Survey in Drug Discovery Research

Drug function study is vital in current drug discovery, design, and development. Determining the drug functions of a novel drug is time-consuming, complicated, expensive, and requires many experts and clinical testing phases. The computational-based drug function prediction activity has recently become more attractive due to its capability to reduce drug development design complexity, time, human resources, cost, chemical waste, and the risk of failure. The evolution of the computational model has advanced as an effective tool for predicting and analyzing drug functions, which are derived from Medical Subject Headings (MeSH). However, predicting drug functions still faces several difficulties. Therefore, an exhaustive literature survey was conducted that discusses the application of computational methods to predict drug functions in the past decade. Additionally, this paper discusses the utilization of drug functions as an input feature to predict adverse drug reactions and disease classification. This work also provides an overview of the computational models with their performance, multi-label problem transformation methods, drug properties, and their sources needed for the task of drug function prediction. Finally, unsolved issues, research gaps, and difficulties with the drug function prediction task have been summarized.
Enhancement of 8 Leads Small Outline Integrated Circuit Package with AuPd Coated Cu Wire Bonding for Automotive Devices

Paper present a study enhancement of wire bonding process for automotive device in integrated circuit package with 2N AuPd coated Cu wire (2NAuPdCu). Wire bonding is electrical connection between pad and leadframe. In present, Au wire is recently use for interconnection while the gold price still exorbitant and caused concern to the wire bonding cost. Cu wire is low price and consider to be an alternative for automotive device but still concern in term of corrosion and reliability. Recently, 4N AuPd coated Cu wire (4NAuPdCu) material have been introduced for automotive device but still encounter the reliability problem. The 2NAuPdCu wire is develop version for more reliability enhancement and consider to use for alternative wire of automotive device. In the experiment, Au wire, 4NAuPdCu wire and 2NAuPdCu wire were used for wire bonding process on 8 leads Small Outline Integrated Circuit Package (SOIC) to compare wire bond ability. Analysis, this package tested wire bond ability and reliability. The results performed well in wire bond ability and reliability for 2NAuPdCu wire with comparing Au wire and 4NAuPdCu wire. Therefore, 2NAuPdCu wire can enhanced the qualify and reliability for 8 leads SOIC package for automotive device.