Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Implementation of Quasi-Direct-Drive Legs for a Frog-Like Jumping Robot

This study aims to design and optimize a motor-driven frog-like jumping robot leg for efficient vertical jumps and multiple consecutive horizontal jumps. We have conducted bionic research on frog legs' structure and motion characteristics and further explored their motion mechanism, providing new ideas and methods for designing and manufacturing robots with high mobility and adaptability. First, our research team designed a robot leg prototype based on the frog's body structure, optimized the robot using computer-aided design software, and selected a suitable motor-driven actuator. Secondly, the weight reduction optimization of the robot body is carried out regarding material selection and topology optimization to improve the robot's maneuverability and jump height. Finally, after manufacturing the prototype of the robot legs, the robot is experimentally verified. The results show that the robot legs can achieve efficient vertical jumps (the maximum height is 1.40 meters, about 7.8 times the length of the leg link). It can also jump multiple times consecutively, which is significant for applying robots in dangerous environments, search and rescue, and other fields.
Experimental Setups for Linear Feed Drive Predictive Maintenance: A Review

The manufacturing world has advanced to the fourth industrial revolution (4IR). Machine tools, especially computer numerical control (CNC) machine tools are an essential part of manufacturing. An important part of the 4IR is predictive maintenance (PM). PM is key in ensuring the availability and high quality of parts produced by machine tools. An important part of CNC machine tools is their feed drives. It is essential to implement PM to keep these components in good working order. Often PM methods will need to be developed and tested on experimental setups before they can be implemented in production. This work examines the literature on experimental setups for feed drive condition monitoring, fault detection and PM and seeks to disseminate and organize information about methods and equipment used in these setups. Three primary factors were analyzed from these papers: the methods used to implement wear and faults, the external loading methods, and which sensors were used and where the sensors were installed. This work seeks to aid others who wish to create their own experimental setup to easily access information about the experimental setups of previous works on linear feed drive PM. A few trends were observed after examining the literature. A large quantity of experimental setups studied faults in ball screws, specifically preload in ball screws. A wide variety of sensors were used, the most popular being accelerometers. There was a lack of methods to implement external loading, with most papers using adjustable worktable weights or magnetic brakes.
The Diversified Structure of Russian Practical Teaching in Colleges and Universities

Compared with other basic courses of the same kind, the teaching content of language practice course is the most comprehensive, including phonetic teaching. In terms of intonation, grammar and vocabulary, it can be said that Russian practice is the foundation of all other professional courses. Russian, as a practical Russian course with the most teaching time and content, its teaching effect depends on the application of teaching methods to a certain extent. According to the characteristics of Russian major in private colleges and universities, practical Russian activity class is constructed to optimize the teaching effect.
Role Strain and Coping among Caregivers

Background: Chronic kidney disease (CKD) is an emerging global public health problem. The disease is a component of a new epidemic of chronic conditions that replaced malnutrition and infection as the leading cause of mortality during the 21st century. A growing number of patients with chronic renal failure (CRF) rely on non – professional health care providers, such as family and friends, to manage their long term condition throughout the trajectory of CRF. This informal caregivers and experience stress, depression, lack of confidence and poor quality of life. Yet, the needs of caregivers are often neglected and under prioritized. Objectives: To assess the role strain and coping among caregivers of patients with chronic renal failure and find out the association of coping among caregivers of patients with sociodemographic variables Method: Quantitative research approach and descriptive research design was adopted. 100 caregivers were selected by Non – probability purposive sampling technique, who met the inclusion criteria. Self – structured socio-demographic proforma was used to collect sociodemographic data and self-structured rating scale for assessment of role strain and coping among caregivers. Results: The findings show showed that the majority of the study sample 64% having moderate coping, others 20% of study sample having poor coping and 16% of the study sample having good coping. The study also revealed that role strain and coping was statistically tested ( p=0.005) is statistically significant. The present study highlights the role of strain and coping among caregivers of patients with chronic renal failure. Conclusion: Based on the findings of the study, the majority of the samples having sometimes frustration. Most of the samples were moderate coping. There is an association between gender and relativity with the patients and weekly hemodialysis frequency with coping.
Application of Leadership Theories in Analyzing the Effects of Leadership Styles on Productivity in Philippine Higher Education Institutions

The type of leadership exemplified in educational organizations has a significant role to play in organizational success or failure. Using a correlational research design, we investigated the effects of leadership behaviors exhibited by leaders in various higher education institutions in the country (as perceived by 14 Filipino graduate scholars) on productivity (measured in terms of passing rates in board examinations in 2016). Results showed that the presence of more leadership behaviors (concerned with both productivity and people) are strongly associated with greater organizational productivity, while leaderfollower relationships and productivity did not show significant association. The educational leader’s people and task orientations were established to have complementary roles in predicting school productivity. The data derived from this study also showed consistent patterns with respect to the underlying relationships proposed by various trait and behavioral theories of leadership and through the application of the Leadership Grid.
Could triglyceride to high density lipoprotein-cholesterol ratio predict hepatosteatosis

Aim: The triglyceride / HDL cholesterol (TG/HDL-c) ratio is increased in a variety of diseases including, coronary heart disease and type 2 diabetes mellitus. However, its role in non-alcoholic hepatosteatosis is not well understood. In present study, we aimed to compare the TG/HDL-c levels of the patients with non-alcoholic hepatosteatosis to those of the healthy subjects. Methods: Medical data of the patients with non-alcoholic hepatosteatosis whom presented to the outpatient internal medicine clinics of our institution were retrospectively analyzed. Healthy subjects whom admissions to our clinics were due to check up were enrolled to the study as control group. TG/HDL-c of the groups compared. Results: TG/HDL-c level of the liver steatosis group (5 (2-22) %) was higher than the control group (2.7 (1-8) %), (p<0.001). TG/HDL-c was significantly and positively correlated with fasting blood glucose (r=0.31, p<0.001), C - reactive protein (r=0.25, p<0.001) and LDL-cholesterol (r=0.3, p<0.001) levels. A TG/HDL-c value greater than 3.1% has 91% sensitivity and 77% specificity in detecting hepatosteatosis. Conclusions: We suggest that TG/HDL-c ratio could be a useful marker of non-alcoholic hepatosteatosis due to its inexpensive and easy to assess nature.
A Novel Exploitation of Errors in Redundant Residue Number System Architecture

: Residue Number System (RNS) is an unweighted number system that symbolizes big integers with smaller numbers. It can perform operations in particular addition and multiplication in parallel. Because of this property, RNS is extensively used in communication, Finite Impulse Response (FIR), cryptography and signal processing devices. The transfer of data in digital channels is very important for some critical applications where accuracy is very important. In this study, we proposed a novel algorithm that is premised on the Hamming Distance (HD) and one of the reverse conversion methods, which is, the Chinese Remainder Theorem (CRT) and) as a joint technique for the detection and correction of multiple bit errors in RNS. The proposed algorithm provides a more efficient technique that improves on the hardware size and increases the processing speed with fewer iterations when compared with other state-of-the-art schemes. The work analyses the area and delay of the hardware architecture and compared with other similar schemes. The results indicated the effectiveness of our proposed scheme in terms of the area and delay specifications.
Twitter Spammer Detection

: Twitter is one such popular network where the short message communication (called tweets) has enticed a large number of users. Spammer tweets pose either as advertisements, scams and help perpetrate phishing attacks or the spread of malware through the embedded URLs. In this system initiate features which take advantage of the behavioral-entropy, profile characteristics, spam analysis for spammer’s detection in tweets. By taking a supervised approach to the problem, but leverage existing hash tags in the Twitter data for building training data. In this,
A DL-based estimation probability approach for VRU collision avoidance

Assisted/autonomous driving is nowadays a vivid sector for both research and industry, thanks to the advances made using artificial intelligence and the pervasive and fast communication achieved by the fifth generation (5G) of cellular networks. A fully connected environment where traveling on public roads is done with limited (or without) human intervention may increase road safety. In this work, we present a system to detect possible collisions among vehicles and between pedestrians and vehicles with the final aim of reduce traffic accidents. Our proposal is based on a trajectory prediction algorithm plus a method to estimate the collision probability. Deep learning and Monte Carlo algorithms are used, respectively. The promising results open future research extensions.
Influence of Acidic (H3PO4) and Alkaline (NaOH) Additives on the Catalytic Reductive Fractionation of Lignocellulose

Reductive catalytic fractionation of lignocellulose is a promising “lignin-first” biorefinery strategy wherein lignin is solvolytically extracted from the cell wall matrix and simultaneously disassembled, resulting in a stable lignin oil and a solid carbohydrate-rich residue. Herein, we report on the different influence of acidic (H3PO4) and alkaline (NaOH) additives on the Pd/C-catalyzed reductive processing of poplar wood in methanol (MeOH). It was found that the addition of small quantities of H3PO4 results in three rather than two product streams, since under acidic conditions both delignification and alcoholysis of hemicellulose are promoted, leaving behind a cellulose-rich pulp. The simultaneous acid-catalyzed fractionation of the carbohydrates into separate cellulose and hemicellulose streams provides opportunities for more efficient downstream conversion, as processing parameters can be tailored to the needs of both streams. Alkaline conditions, on the other hand, also enhance delignification, but.
Spectral analysis perspective of why misinformation containment is still an unsolved problem

Misinformation is still a major societal problem. The arrival of ChatGPT only added to the problem. This paper analyzes misinformation in the form of text from a spectral analysis perspective to find the answer to why the problem is still unsolved despite multiple years of research and a plethora of solutions in the literature. A variety of embedding techniques are used to represent information for the purpose. The diverse spectral methods used on these embeddings include t-distributed Stochastic Neighbor Embedding (t-SNE) and Principal Component Analysis (PCA). The analysis shows that misinformation is quite closely intertwined with genuine information and the machine learning algorithms are not as effective in separating the two despite the claims in the literature.
Density and Heat Capacity of Liquids from Speed of Sound

Two different methods for deriving the density and isobaric heat capacity of liquids in the subcritical pressure range, from the speed of sound, are recommended. In each method, corresponding set of differential equations relating these properties is solved as the initial boundary value problem (IBVP). The initial values are specified at the lowest pressure of the range and the boundary values along the saturation line. In the first method, numerical integration is performed along the paths connecting the Chebyshev points of the second kind between the minimum and maximum temperature at each pressure. In the second method, numerical integration is performed along the isotherms distributed in the same way, with the temperature range being extended to the saturation line after each integration step. The methods are tested with the following substances: Ar, N2, CO2, and CH4. The results obtained for the density and isobaric heat capacity have the average absolute deviation from the reference data of 0.0005% and 0.0219%, respectively. These results served as the initial values for deriving the same properties in the transcritical pressure range up to the pressure approximately twice as large as the critical pressure. The results obtained in this pressure range have respective deviations of 0.0019% and 0.1303%.
Investigation of structure interaction to nutrient properties and utilization in co-products after pellet processing at various conditions using advanced molecular spectroscopy

ABSTRACT The molecular infrared (micro)spectroscopy, developed as a rapid, non-destructive and non-invasive analytical technique, is able to reveal structure features at a molecular level and provide tissue structure and chemistry information simultaneously. However, to date, this analytical technique is seldomly used in study processing induced structure change in relation to nutrient properties, utilization, and delivery in livestock. The objective of this article was to review the inter-relationship between molecular structures with nutritive properties and nutrient delivery in co-products from bioenergy production after pelleted processing using vibrational molecular spectroscopy. First, this article reviews recent progress in pelleting process research, related to physical quality of pellets, utilization for animals, processing quality, and current nutrition evaluation methodologies for pelleting. The emphasis of this study focused on the effect of conditioning temperature and time of the pellet processing on molecular structure changes and nutrient properties and nutrient delivery. The methods for nutritive properties and nutrient delivery were reviewed, which included various in vitro, in situ, in vivo, and nutrient modeling techniques. The molecular spectroscopic techniques included globar-sourced and synchrotron-sourced molecular spectroscopic techniques. The molecular spectra analysis included univariate and multivariate molecular spectral analyses. The relationship between molecular structural changes and truly absorbed nutrient supply was quantified. The research provides an insight how inherent structure changes induced by pellet processing on a molecular basis affected nutrient properties, utilization, and availability.
ω♯-Algebras

Abstract This article explores a generalization of the algebraic theory of formal languages. Having, as starting point, the work of T. Colcombet on cost functions and stabilization monoids, and of Daviaud et al. on stabilization algebras, this class of algebras is extended to ω♯-algebras and ω♯-automata are also introduced. The equality problem for order ideals (of free ω♯-algebras) recognized by finite ω♯-algebras is answered positively in this context. Various results on formal languages and monoids are generalized to this setting of order ideals and ω♯-algebras. The class of cost functions is proved to be embeddable in the class of recognizable order ideals.
Toward automating post processing of aquatic sensor data

Sensors measuring environmental phenomena at high frequency commonly report anomalies related to fouling, sensor drift and calibration, and datalogging and transmission issues. Suitability of data for analyses and decision making often depends on manual review and adjustment of data. Machine learning techniques have potential to automate identification and correction of anomalies, streamlining the quality control process. We explored approaches for automating anomaly detection and correction of aquatic sensor data for implementation in a Python package (PyHydroQC). We applied both classical and deep learning time series regression models that estimate values, identify anomalies based on dynamic thresholds, and offer correction estimates. Techniques were developed and performance assessed using data reviewed, corrected, and labeled by technicians in an aquatic monitoring use case. Auto-Regressive Integrated Moving Average (ARIMA) consistently performed best, and aggregating results from multiple models improved detection. PyHydroQC includes custom functions and a workflow for anomaly detection and correction.
Whole-chromosome fusions in the karyotype evolution of Sceloporus (Iguania, Reptilia) are more frequent in sex chromosomes than autosomes

Whole-chromosome fusions play a major role in the karyotypic evolution of reptiles. It has been suggested that certain chromosomes tend to fuse with sex chromosomes more frequently than others. However, the comparative genomic synteny data are too scarce to draw strong conclusions. We obtained and sequenced chromosome-specific DNA pools of Sceloporus malachiticus, an iguanian species which has experienced many chromosome fusions. We found that four of seven lineage-specific fusions involved sex chromosomes, and that certain syntenic blocks which constitute the sex chromosomes, such as the homologues of the Anolis carolinensis chromosomes 11 and 16, are repeatedly involved in sex chromosome formation in different squamate species. To test the hypothesis that the karyotypic shift could be associated with changes in recombination patterns, we performed a synaptonemal complex analysis in this species and in Sceloporus variabilis (2n = 34). It revealed that the sex chromosomes in S. malachiticus had two distal pseudoautosomal regions and a medial differentiated region. We found that multiple fusions little affected the recombination rate in S. malachiticus. Our data confirm more frequent involvement of certain chromosomes in sex chromosome formation, but do not reveal a connection between the gonosome–autosome fusions and the evolution of recombination rate. This article is part of the theme issue ‘Challenging the paradigm in sex chromosome evolution: empirical and theoretical insights with a focus on vertebrates (Part II)’.
Long-term stochastic risk models: the sixth generation of modern actuarial models?

Abstract This paper discusses the use of modelling techniques for the purpose of risk management within life insurers. The key theme of the paper is that life insurance is long-term business and carries with it long-term risks, yet much of modern actuarial risk management is focussed on short-term modelling approaches. These typically include the use of copula simulation models within a 1-year Value-at-Risk (VaR) framework. The paper discusses the limitations inherent within the techniques currently used in the UK and discusses how the focus of the next generation of actuarial models may be on long-term stochastic projections. The scope of the paper includes a discussion of how existing techniques, together with new approaches, may be used to develop such models and the benefits this can bring. The paper concludes with a practical example of how a long-term stochastic risk model may be implemented.
RTT109 and Fun30 proteins mediate epigenetic regulation of the DNA damage response pathway in C. albicans

Fun30, an ATP-dependent chromatin remodeller, from S. cerevisiae mediates both regulation of gene expression as well as DNA damage response/repair. In this paper, we have characterized the biochemical and physiological function of Fun30 from the opportunistic fungi, C. albicans. Biochemically, the protein shows DNA-stimulated ATPase activity. Physiologically, the protein co-regulates transcription of RTT109, TEL1, MEC1, and SNF2-genes that encode for proteins involved in DNA damage response and repair pathway. The expression of FUN30, in turn, is regulated by histone H3 acetylation catalysed by Rtt109 encoded by RTT109. The RTT109Hz/FUN30Hz mutant strain shows sensitivity to oxidative stress and resistance to MMS as compared to the wild type strain. Quantitative PCR showed that the sensitivity to oxidative stress results from downregulation of MEC1, RAD9, MRC1 and RAD5 expression; ChIP experiments showed Fun30 but not H3ac regulates the expression of these genes in response to oxidative stress. In contrast, on treatment with MMS, the expression of RAD9 is upregulated and this upregulation is co-regulated by both Fun30 and H3 acetylation catalysed by Rtt109. Thus, Fun30 and H3 acetylation mediate the response of the fungal cell to genotoxic agents in C. albicans by regulating the expression of DNA damage response and repair pathway genes.
Competent immune responses to SARS-CoV-2 variants in older adults following mRNA vaccination

Aging is associated with a reduced magnitude of primary immune responses to vaccination and constriction of immune receptor repertoire diversity. Clinical trials demonstrated high efficacy of mRNA based SARS-CoV-2 vaccines in older adults but concerns about virus variant escape have not been well addressed. We have conducted an in-depth analysis of humoral and cellular immunity against an early-pandemic viral isolate and compared that to the P.1. (Gamma) and B.1. 617.2 (Delta) variants in <50 and >55 age cohorts of mRNA vaccine recipients. We have further measured neutralizing antibody titers for B.1. 617.1 (Kappa) and B.1. 595; a SARS-CoV-2 isolate bearing Spike mutation E484Q. As reported, robust immunity required the second dose of vaccine. Older vaccinees manifested robust cellular immunity against early-pandemic SARS-CoV-2 and more recent variants, which remained statistically comparable to the adult group. The older cohort had lower neutralizing capacity at the first time point following the second dose, but at later time points immunity was indistinguishable between them. While the duration of these immune responses remains to be determined over longer periods of time, these results provide reasons for optimism regarding vaccine protection of older adults against SARS-CoV-2 variants and inform thinking about boost vaccination with variant vaccines. eTOC summary Vaccine responses are often diminished with aging, but we found strong responses to SARS-CoV-2 in older adults following mRNA vaccination. T cell responses were not diminished when confronted by SARS-CoV-2 variants. Neutralizing Ab were reduced but not more than those in adults. Graphical Abstract Created with BioRender.com