Miracle-dz/UniFAR-FTUs huggingface dataset:
Chapter Six. Sacamefotos And Tejedoras: Frontstage Performance And Backstage Meaning In A Peruvian Context

For the past fifteen years, women from the mountain communities of the Pisaq district have been coming to the village on market days so that tourists can take their pictures. These women (sacamefotos) pose as 'authentic' people who present a certain, essentialized aspect of the cultural heritage. This chapter analyses how these comuneras present themselves to tourists (frontstage) and the processes that occur when tourists are not around ('backstage'). Another interesting phenomenon in this region is that nowadays women from the mountain communities sell their weavings (tejidos) directly to tourists instead of selling them to Piseno market dwellers, as they did in the past. The chapter provides an insight into the societal consequences and cultural outcomes of tourism in a Peruvian Andean context. It is based on an analysis of sacamefotos, tejedoras and tejedora-sacamefotos at the two most visited tourist sites in Pisaq: the marketplace and the ruins.Keywords: comuneras; cultural heritage; Peruvian Andean context; Pisaq; Piseno market; sacamefotos; tejedoras; tourists (frontstage)
Cardiac Troponin Release after Exercise in Healthy Young Athletes: A Systematic Review

Cardiac troponin (cTn) is a recognized marker used to assess damage to the heart muscle. Actual research has indicated that the levels of cTn increase after doing exercise in individuals who are in good health, and this is believed to be a result of a normal cellular process rather than a pathological one. The main goal of this study was to investigate the evidence of a postexercise release of cTn in child and adolescent athletes (6–17.9 years old) of different ages, sex, and sports disciplines. The Web of Science, MEDLINE, and Scopus databases were used to conduct the research up to March 2023. Three hundred and twenty-eight records were identified from the databases, however, only twenty-three studies were included in the review after being screened and quality-assessed by two independent authors. The gender, age of the participants, maturational status, and training level of the participants, the timing of sample collection, the exercise modality, and the number of participants with values above the cut-off reference were the data analyzed. Males, older young people, and individual sports seemed to have higher levels of serum cTn after practice exercise. Different methodologies, analyzers, and cut-off reference values make it difficult to compare the data among studies.
Practical AI Cases for Solving ESG Challenges

Artificial intelligence (AI) is a rapidly advancing area of research that encompasses numerical methods to solve various prediction, optimization, and classification/clustering problems. Recently, AI tools were proposed to address the environmental, social, and governance (ESG) challenges associated with sustainable business development. While many publications discuss the potential of AI, few focus on practical cases in the three ESG domains altogether, and even fewer highlight the challenges that AI may pose in terms of ESG. The current paper fills this gap by reviewing practical AI applications with a main focus on IT and engineering implementations. The considered cases are based on almost one hundred publicly available research manuscripts and reports obtained via online search engines. This review involves the study of typical business and production problems associated with each ESG domain, gives background details on several selected cases (such as carbon neutrality, land management, and ESG scoring), and lists challenges that the smart algorithms can pose (such as fake news generation and increased electricity consumption). Overall, it is concluded that, while many practical cases already exist, AI in ESG is still very far away from reaching its full potential; however, one should always remember that AI itself can lead to some ESG risks.
Role of Citrullus colocynthis and Psidium guajava Mediated Green Synthesized Silver Nanoparticles in Disease Resistance against Aeromonas hydrophila Challenge in Labeo rohita

Green synthesis of metallic nanoparticles is an auspicious method of preparing nanoparticles using plant extracts that have lesser toxicity to animal cells and the host. In the present work, we analyzed the antibacterial activity of Citrullus colocynthis and Psidium guajava-mediated silver nanoparticles (Cc-AgNPs and Pg-AgNPs, respectively) against Aeromonas hydrophila (A. hydrophila) in an in vivo assay employing Labeo rohita (L. rohita). L. rohita were divided into six groups for both Cc-AgNPs and Pg-AgNPs treatments separately: Control, A. hydrophila infected, A. hydrophila + Ampicillin, A. hydrophila + Cc/Pg-AgNPs (25 µg/L), A. hydrophila + Cc/Pg-AgNPs (50 µg/L), and A. hydrophila + Cc/Pg-AgNPs (75 µg/L). Changes in different bio-indicators such as hematological, histological, oxidative stress, and cytokine analysis were observed. Interestingly, the infected fish treated with both types of AgNPs (Cc-AgNPs and Pg-AgNPs) exhibited a higher survival rate than the untreated infected fish and demonstrated signs of recovery from the infection, providing a compelling indication of the positive impact of phytosynthesized AgNPs. Disruptions in hematological and histological parameters were found in the infected fish. Both Cc-AgNPs and Pg-AgNPs showed recovery on the hematological and histological parameters. Analysis of oxidative stress and cytokine markers also revealed provoking evidence of the positive impact of Cc-AgNPs and Pg-AgNPs treatment against disease progression in the infected fish. The major finding of the study was that the higher concentrations of the nanoparticles (50 µg/L in the case of Cc-AgNPs and 75 µg/L in the case of Pg-AgNPs) were more effective in fighting against disease. In conclusion, our work presents novel insights for the use of green-synthesized AgNPs as economic and innocuous antibacterial candidates in aquaculture.
Thermal Spray Technology

Trinity College Dublin, e University of Dublin, Department of Mechanical and Manufacturing Engineering, Parsons Building, Dublin 2, Ireland Institute of Plasma Physics, e Czech Academy of Sciences, Za Slovankou 1782/3, 182 00 Prague, Czech Republic Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Zhejiang, China State Key Laboratory of Solidification Processing, Shaanxi Key Laboratory of Friction Welding Technologies, School of Materials Science and Engineering, Northwestern Polytechnical University, Xi’an 710072, China LERMPS, ICB UMR 6303, CNRS, University of Bourgogne Franche-Comté, UTBM, F-90010 Belfort, France
Interaction between dissolved organic carbon and fungal network governs carbon mineralization in paddy soil under co-incorporation of green manure and biochar

Legume crops in rice cultivation are typically rotated and incorporated into the soil as green manure to improve soil fertility. Biochar has recently been co-incorporated with green manure to simultaneously stimulate soil organic carbon (SOC) mineralization and increase carbon (C) sequestration. However, few studies examine the effects of the co-incorporation of biochar and green manure on C cycling and the underlying microbial mechanisms in paddy fields. In this study, the effects of the co-incorporation of green manure and biochar on C mineralization, dissolved organic carbon (DOC) characteristics, and microbial community structures were investigated. A pot study was conducted with three treatments: inorganic NPK (NPK), inorganic NPK + green manure (GM), and inorganic NPK + green manure + biochar (GMC). Organic amendments significantly increased cumulative C mineralization, with amounts in the order GMC (3,434 mg·kg−1) > GM (2,934 mg·kg−1) > NPK (2,592 mg·kg−1). Fertilizer treatments had similar effects on DOC concentrations, with amounts in the order GMC (279 mg·kg−1) > GM (255 mg·kg−1) > NPK (193 mg·kg−1). According to fluorescence spectra, the highest microbial humic acid-like fraction and biological index were also in GMC. Co-incorporation of green manure and biochar shifted the composition of bacterial and fungal communities but more importantly, increased fungal network complexity and decreased bacterial network complexity. The increase in fungal network complexity with the increase in DOC concentrations and microbially derived components was the dominant factor in promoting C mineralization. Overall, this study reveals the underlying biochemical mechanism, the interaction between DOC and fungal network of C cycling in paddy soil under the co-incorporation of green manure and biochar management, and provides fundamental knowledge for exploring effective approaches to improve soil fertility and health in the future.
Emerging Developments in Separation Techniques and Analysis of Chiral Pharmaceuticals

Chiral separation, the process of isolating enantiomers from a racemic mixture, holds paramount importance in diverse scientific disciplines. Using chiral separation methods like chromatography and electrophoresis, enantiomers can be isolated and characterized. This study emphasizes the significance of chiral separation in drug development, quality control, environmental analysis, and chemical synthesis, facilitating improved therapeutic outcomes, regulatory compliance, and enhanced industrial processes. Capillary electrophoresis (CE) has emerged as a powerful technique for the analysis of chiral drugs. This review also highlights the significance of CE in chiral drug analysis, emphasizing its high separation efficiency, rapid analysis times, and compatibility with other detection techniques. High-performance liquid chromatography (HPLC) has become a vital technique for chiral drugs analysis. Through the utilization of a chiral stationary phase, HPLC separates enantiomers based on their differential interactions, allowing for the quantification of individual enantiomeric concentrations. This study also emphasizes the significance of HPLC in chiral drug analysis, highlighting its excellent resolution, sensitivity, and applicability. The resolution and enantiomeric analysis of nonsteroidal anti-inflammatory drugs (NSAIDs) hold great importance due to their chiral nature and potential variations in pharmacological effects. Several studies have emphasized the significance of resolving and analyzing the enantiomers of NSAIDs. Enantiomeric analysis provides critical insights into the pharmacokinetics, pharmacodynamics, and potential interactions of NSAIDs, aiding in drug design, optimization, and personalized medicine for improved therapeutic outcomes and patient safety. Microfluidics systems have revolutionized chiral separation, offering miniaturization, precise fluid control, and high throughput. Integration of microscale channels and techniques provides a promising platform for on-chip chiral analysis in pharmaceuticals and analytical chemistry. Their applications in techniques such as high-performance liquid chromatography (HPLC) and capillary electrochromatography (CEC) offer improved resolution and faster analysis times, making them valuable tools for enantiomeric analysis in pharmaceutical, environmental, and biomedical research.
Niksar Ve Pazar İlçelerinde Yetişen Bazı Ceviz Tiplerinin Meyve Özellikleri

The study was carried out at villages of Niksar and Pazar counties, in September and October 1991. Fruit samples collected from 53 walnut types. These fruit samples were inspected for fruit quality characters such as fruit shape, fruit weight, kernel percentage, kernel rottenness, kernel color , kernel fullness, shell thickness, shell color, shell roughness. Light-yellow colored kernel ratios of the inspected walnut types ranged from 20 to 100 percent . The kernel rottenness wasn’t seen in 46 walnut types. The empty fruit wasn’t come out in 51 walnut types. The shelled fruit weight averages varied between 6.44 and 14.46 gr. The shelled fruit weight average of totally 53 walnut types is 10.50 gr. The kernel weight averages varied betwean 2.13 and 7.13 gr. The shell thickness of the fruit types which were sampled is betwen 0.54 and 1.50 mm. The kernel fullness average of the walnut types was found as 3.58.
Research on Triple Interleaved Bidirectional DC/DC Converter Based on Second-Order Linear Active Disturbance Rejection

The traditional PI controller has a considerable ability to improve the robustness of the interleaved dc/dc converter drive. However, the PI control strategy has its specific antidisturbance range. To further expand the antidisturbance range and improve the robustness to disturbance, a second-order linear active disturbance rejection control (LADRC) strategy is proposed to achieve high-performance current-sharing and antidisturbance capabilities of the triple interleaved bidirectional dc/dc converter in steady and dynamic states. The simulation and experimental results show that compared with the traditional PI control, the current-sharing strategy based on second-order LADRC has better rapidity, robustness, and adaptability.
Spin C-STRUCTURES AND SEIBERG-WITTEN EQUATION

The mathematical part of Seiberg Witten theory is now a powerful tool in the framework of smooth geometry of low dimensions. Using the celebrated equations introduced by E. Witten in [1] one could establish a number of new results and reprove known ones. In the original paper [1] the author first of all reproves Donaldson fundamental results which ensure us that there are exist homeomorphic but not diffeomorphic smooth compact 4 dimensional manifolds. The key point is that for any Kahler manifold one has nontriviality of the invariant (which is called Seiberg Witten invariant) while for almost all ”topomodels” the invariant is trivial (we’ll give all the definitions and constructions below). This fact itself destroys a number of physically philosophical speculations about the structure of Universe; usually they discussed what is the topological structure and what is the manifold which corresponds (and represents) our world. But now if say the famous Poincare smooth conjecture is not true (one can suppose it because despite of the huge attempts to prove it we have not yet any answer on this question) then the discussion would be illuminated by new colors. The problem arose is not only what is the manifold but additionally which smooth structure plays on. For example usual R looks like a bad joke: Donaldson proved that it admits continuum set of different smooth structures. And it doesn’t matter what a metric one uses on this R, euclidean or lorentzian. But not only known results were proved using the new invariant. For the Donaldson theory it was usual to compute the Donaldson invariants in the framework of algebraic geometry. Almost all examples in [23] come in this way. It was established by Taubes that Seiberg Witten invariants are related as well with symplectic geometry — in [3] he proves that for any symplectic manifold with b2 > 1 the associated canonical class is the basic one. The proof was so simple and natural that it was conjected that the symplectic geometry is exactly the subject containing all non trivial cases for the Seiberg Witten invariants. This suggestion was disproved almost immediately by Taubes himself together with D. Kotschik and J. Morgan in [5], but the counterexample is a 4 dimensional manifold with nontrivial fundamental group. It means that one can correct the suggestion just imposing the condition of simply connectedness. There are many courses now in the Seiberg Witten theory (we mention in the References a number of these lectures or surveys) so I hadn’t in mind to present a textbook composed of the materials which can be derived from the library. I want just to add some geometrical facts and constructions whose presence simplifying
A Method for Recognizing Full Forwarding Dense False Target Jamming in the Absence of Label Information

Full forwarding dense false target jamming signals correlate highly with real target echoes, and their training samples are difficult to obtain, constraining radars from effectively identifying real and false target echoes. To overcome this challenging problem, this article systematically analyzes and studies the frequency response characteristics of the radar and jammer and models their influence on the amplitude–frequency features of the real and false target echoes. Then, positive-unlabeled learning (PU learning)-based algorithm is proposed to solve the jamming signal recognition problem of missing label information. The core idea of this algorithm is to obtain the amplitude–frequency response features of the two signal types for initial dataset construction and then use the support vector machine (SVM) to estimate the class prior probabilities of each echo to reconstruct a new training dataset. After that, a dual-channel feature fusion network (1DCNN-LSTM) is introduced, comprising a 1-D convolutional neural network (1DCNN) and a long short-term memory (LSTM) network to improve further recognition accuracy. The effectiveness of the proposed features and the PU-1DCNN-LSTM algorithm is demonstrated through simulated and measured experiments, revealing that the proposed method can guarantee a recognition accuracy of 98.4% on the measured data.
Digital-Health Monitoring System for Healthy Aging Using Gait Biomarkers

Healthy aging is crucial for socioeconomic independence and quality living. Nevertheless, age-related gait variations result in mobility issues influencing human walk. Hence, studying lower-limb functionality with aging aids in sustaining good mobility. This work analyzed collected gait and ankle joint data of 80 healthy participants (21–60 years) using a developed G-Eva (system for gait evaluation) system during dynamic walking. Thereafter, data are preprocessed followed by feature extraction and selection using statistical, correlation, and relative importance analysis. With aging, gait variability is observed in walking speed, thus, a weighted majority-voting ensemble model (MVens) is proposed for age and gender prediction of middle-aged individuals to overcome imbalance influence. MVens model is able to achieve an accuracy of 90% for predicting age-related gait deterioration and 96.25% for gender estimation. It has also been demonstrated that among middle-aged adults, spatiotemporal parameters show significant changes followed by symmetry and variability analysis with aging as opposed to older adults. However, other significantly contributing features include differences in spatiotemporal and gait variability parameters followed by symmetry for gender prediction. Thus, the developed system with the proposed MVens model can be used for early diagnosis of mobility and joint-health disorders for initiation of timely intervention and rehabilitation.
Epistemic Uncertainty and Model Transparency in Rock Facies Classification Using Monte Carlo Dropout Deep Learning

Although Deep Learning (DL) architectures have been used as efficient prediction tools in a variety of domains, they frequently do not care about the uncertainty in the predictions. This may prevent them from being used in practical applications. In seismic reservoir characterisation, predicting facies from seismic data is typically viewed as an inverse uncertainty quantification issue. The goal of the current study is to analyse the dependability of rock facies classification model in order to quantify the uncertainty while maintaining the high accuracy by using and evaluating monte carlo dropout based deep learning (MCDL), a computationally efficient technique. The proposed method is unique since it can quantify the epistemic uncertainty of the classified facies in blind or unseen well conditioned on Seismic attributes in the bayesian approximation achieved by MCDL framework. The findings show that MC dropout is successful in terms of accuracy and reliability, with a blind test F1-scores of 98% and 82% in predicting facies from synthetic and seismic datasets respectively. Moreover, the applications in a 2D section indicate that the internal regions of the seismic sections are generally classified with less epistemic uncertainty than their boundaries, as calculated from the different realizations of the MCDL network. For comparison, a plain DL and support vector machine (SVM) are also implemented and the findings suggest that our method outperformns the other models in comparison which indicates the potential of the model to be implemented in a robust rock facies classification.
Packet Level Performance of 5G NR System Under Blockage and Micromobility Impairments

With the introduction of the Integrated Access and Backhaul (IAB) technology by 3GPP, the last mile in beyond 5G cellular systems will be characterized by multiple wireless backhaul links between the user equipment and base station. In such multi-hop configurations, packet latency becomes a dominant factor characterizing the quality of service (QoS) delivered to the users. At the same time, directional communications at millimeter wave (mmWave) frequencies are prone to frequent outages caused by blockage and micromobility leading to periods of silence and subsequent rate compensation. In this paper, we are interested in assessing the impact of mmWave propagation specifics on the delay and medium access control (MAC) buffer overflow performance at a 5G NR IAB network node. To this aim, we first propose a continuous-time Markov chain model for the bitrate provided by such a system that explicitly accounts for mmWave-specific propagation. Then, by formulating a queuing model of packet transmission, we characterize the mean packet delay experienced by a traffic source. Our results illustrate that the mean delay and MAC buffer overflow probability at the NR BS interface is a step function that is not strictly decreasing due to the packet encapsulation specifics of the modulation and coding (MCS) adaptation mechanism. Further, these metrics are non-negligible even for the system having a sufficient amount of resources. For IAB architecture, where the access link may not be available the mean delay increases exponentially even when the arrival rate is adjusted to the available resources.