Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Replacing Fishmeal with Plukenetia volubilis Cake on Growth, Digestive Enzymes, and Body Composition in Whiteleg Shrimp (Litopenaeus vannamei)

A feeding trial was carried out on a shrimp farm located in the Santa Rosa province of El Oro, Ecuador, with four isonitrogenous and isolipidic experimental diets, designed with increasing levels of substitution of fish meal by P. voluvilis, (D-0), 15% (D-15), 25% (D-25), and 50% (D-50). The obtained results indicated that the 50% replacement with P. volubilis in practical diets had no noticeable negative effects on the growth performance of L. vanameii juveniles. The total weight of shrimps fed with 25% and 50% diets (16.04 g and 16.72 g, respectively) and the abdomen weight (10.32 g) of shrimps fed with the D-50 diet were high, with significant differences regarding those fed with the D-0 diet. No adverse effects on muscle composition were found. Significant differences were observed only in groups D-25 (for chymotrypsin) and D-50 (chymotrypsin and alkaline protease). Trypsin and amylase activity was not affected by the inclusion of P. volubilis. The results of this experiment indicated that P. volubilis cake is a possible alternative to fish meal in shrimp feeding; however, it should be studied in more depth to establish the maximum replacement percentage and to identify the adequate treatments to eliminate antinutritional factors.
Measurement of Spin Correlation in Top Quark Pair Production at ATLAS

This thesis presents a study of spin correlation in ttˉ production in the ATLAS detector, in proton-proton collisions, corresponding to an integrated luminosity of 4:7fb\(^1\), with a centre of mass energy of \(\surd\)s = 7 TeV. Both the dilepton and single lepton channels are considered, the latter providing a greater challenge due to the necessity to reconstruct the down-type quark resulting from the W boson decay. A simple technique is employed to reconstruct single lepton ttˉ events, with the transverse angle between the charged lepton and down-type quark used as a probe of the spin correlation. In the dilepton channel, the transverse angle between both charged leptons is used. The extracted value of spin correlation in each channel is consistent with Standard Model predictions, with the result in the e\(\mu\) channel alone sufficient to exclude a model without spin correlation at 7:8\(\sigma\). Also described is the author's contribution to the maintenance and development of the Atlantis Event Display.
Detecting Human Actions in Drone Images Using YoloV5 and Stochastic Gradient Boosting

Human action recognition and detection from unmanned aerial vehicles (UAVs), or drones, has emerged as a popular technical challenge in recent years, since it is related to many use case scenarios from environmental monitoring to search and rescue. It faces a number of difficulties mainly due to image acquisition and contents, and processing constraints. Since drones’ flying conditions constrain image acquisition, human subjects may appear in images at variable scales, orientations, and occlusion, which makes action recognition more difficult. We explore low-resource methods for ML (machine learning)-based action recognition using a previously collected real-world dataset (the “Okutama-Action” dataset). This dataset contains representative situations for action recognition, yet is controlled for image acquisition parameters such as camera angle or flight altitude. We investigate a combination of object recognition and classifier techniques to support single-image action identification. Our architecture integrates YoloV5 with a gradient boosting classifier; the rationale is to use a scalable and efficient object recognition system coupled with a classifier that is able to incorporate samples of variable difficulty. In an ablation study, we test different architectures of YoloV5 and evaluate the performance of our method on Okutama-Action dataset. Our approach outperformed previous architectures applied to the Okutama dataset, which differed by their object identification and classification pipeline: we hypothesize that this is a consequence of both YoloV5 performance and the overall adequacy of our pipeline to the specificities of the Okutama dataset in terms of bias–variance tradeoff.
Magnetic Molecularly Imprinted Polymers for the Rapid and Selective Extraction and Detection of Methotrexatein Serum by HPLC-UV Analysis

In this work, novel selective recognition materials, namely magnetic molecularly imprinted polymers (MMIPs), were prepared. The recognition materials were used as pretreatment materials for magnetic molecularly imprinted solid-phase extraction (MSPE) to achieve the efficient adsorption, selective recognition, and rapid magnetic separation of methotrexate (MTX) in the patients’ plasma. This method was combined with high-performance liquid chromatography–ultraviolet detection (HPLC–UV) to achieve accurate and rapid detection of the plasma MTX concentration, providing a new method for the clinical detection and monitoring of the MTX concentration. The MMIPs for the selective adsorption of MTX were prepared by the sol–gel method. The materials were characterized by transmission electron microscopy, Fourier transform-infrared spectrometry, X-ray diffractometry, and X-ray photoelectron spectrometry. The MTX adsorption properties of the MMIPs were evaluated using static, dynamic, and selective adsorption experiments. On this basis, the extraction conditions were optimized systematically. The adsorption capacity of MMIPs for MTX was 39.56 mgg−1, the imprinting factor was 9.40, and the adsorption equilibrium time was 60 min. The optimal extraction conditions were as follows: the amount of MMIP was 100 mg, the loading time was 120 min, the leachate was 8:2 (v/v) water–methanol, the eluent was 4:1 (v/v) methanol–acetic acid, and the elution time was 60 min. MTX was linear in the range of 0.00005–0.25 mg mL−1, and the detection limit was 12.51 ng mL−1. The accuracy of the MSPE–HPLC–UV method for MTX detection was excellent, and the result was consistent with that of a drug concentration analyzer.
Causal links between hot money and investment markets: evidence from small-scale economy

Hot money is generally associated with economic and financial tur-moil in emerging economies. In this backdrop, a number of studies document the causal links between hot money and financial markets. Accordingly, the study examines the causal relationship among hot money, equities, and real estate assets in the small-scale economy of Pakistan. For this purpose, we employ various time series techniques such as the JJ Co-integration test, Granger causality tests, Impulse Response Functions (IRF), and Variance Decomposition Analysis (VDC). The findings validate the long-term association between speculative funds and underlying investment markets. The results uncover unidirectional causality from investment markets to hot money in Pakistan. However, the lack of a bi-directional relationship among the underlying variables indicates that hot money is not a major driver of soaring prices in equities and real estate assets. Alternatively, developing the underlying markets attracts speculative cash inflows into the economy. The findings of the study highlight some useful implications for investors and regulators. For instance, the study ’ s findings present valuable insights for international investors seeking diversification opportunities in small-scale economies such as Pakistan. Also, the regulators in the underlying economy can utilize the study findings to formulate an optimal model to manage international capital flows.
Evaluation of 5-[(Z)-(4-nitrobenzylidene)]-2-(thiazol-2-ylimino)-4-thiazolidinone (Les-6222) as Potential Anticonvulsant Agent

It was determined that the studied 5-[(Z)-(4-nitrobenzylidene)]-2-(thiazol-2-ylimino)-4-thiazolidinone (Les-6222) affects the cyclooxygenase pathway of the arachidonic acid cascade, the markers of damage to neurons on models of PTZ kindling. In the model of chronic epileptogenesis in mice (pentylenetetrazole kindling), a 4-thiazolidinone derivative showed high anticonvulsant activity, which is weaker than the effect of sodium valproate and higher than Celecoxib. The mentioned compound has a pronounced anti-inflammatory effect in the brain on the background of the PTZ kindling, reliably inhibiting COX-1 and COX-2. The predominant inhibition of COX-2 by 44.5% indicates this enzyme’s high selectivity of Les-6222. According to the molecular docking study results, the studied compound revealed the properties of COX-1/COX-2 inhibitor and especially 5-LOX/FLAP. The decreasing content of 8-isoprostane in the brain of mice of the Les-6222 group indicates a beneficial effect on cell membranes in the background of oxidative stress during the long-term administration of PTZ. In addition, Les-6222 significantly decreased the content of neuron-specific enolase, indicating neuroprotective properties in the background of chronic epileptogenesis. The obtained results experimentally substantiate the feasibility of further developing Les-6222 as a promising anticonvulsant agent.
Image registration by maximization of mutual information based on edge width matching using particle swarm optimization

Mutual information (MI) based image registration has been found to be quite effective in many medical image applications. However, standard MI hampers the convergence of registration transformation parameters since it contains local maxima. In this paper, a novel registration method is proposed. At first,MI based on edge width matching is computed to avoid great change of joint probability distribution and get less local maxima. Particle swarm optimization (PSO), which combines local search methods with global ones balancing exploration and exploitation, is done to search the optimal registration parameter.PSO has less computational complexity as its complex behavior follows only a few simple rules. It could avoid local maxima and reach global optimal results. This method is applicable to a variety of multimodal images, and suitable to different interpolation methods. Theoretical analysis and experiments show that this method is effective and accurate to register multimodal medical images.
PD-1 Alleviates Cisplatin-Induced Muscle Atrophy by Regulating Inflammation and Oxidative Stress

Skeletal muscle atrophy is an important characteristic of cachexia, which can be induced by chemotherapy and significantly contributes to functional muscle impairment. Inflammation and oxidative stress are believed to play important roles in the muscle atrophy observed in cachexia, but whether programmed cell death protein 1 (PD-1) is affected by this condition remains unclear. PD-1 is a membrane protein that is expressed on the surface of many immune cells and plays an important role in adaptive immune responses and autoimmunity. Thus, we investigated the role and underlying mechanism of PD-1 in cisplatin-induced muscle atrophy in mice. We found that PD-1 knockout dramatically contributed to skeletal muscle atrophy. Mechanistically, we found that E3 ubiquitin-protein ligases were significantly increased in PD-1 knockout mice after cisplatin treatment. In addition, we found that PD-1 knockout significantly exacerbated cisplatin-induced skeletal muscle inflammation and oxidative stress. Moreover, we found that there were significant increases in ferroptosis-related and autophagy-related genes in PD-1 knockout mice after cisplatin treatment. These data indicate that PD-1 plays an important role in cisplatin-induced skeletal muscle atrophy.
Effect of Impregnation with Natural Shellac Polymer on the Mechanical Properties of Fast-Growing Chinese Fir

Fast-growing Chinese fir wood has shortfalls such as loose structure and low strength because it grows faster than natural trees. Resin impregnation is a great way to increase the strength of fast-growing fir. However, the resin used for impregnation is a kind of urea-formaldehyde resin, phenolic formaldehyde resin, melamine formaldehyde resin, and the like, which introduce harmful substances such as formaldehyde or phenolic into the wood. In this paper, Chinese fir wood was impregnated with natural shellac polymer, and the effects of impregnation variables on the mechanical properties of the wood were examined. The increase in strength in compression perpendicular to grain (SCPG) of wood samples impregnated with 15% shellac solution achieved a maximum value of 39.01%, but the modulus of rupture (MOR) was slightly reduced. The effects of the impregnation pressure, time, and their interaction were investigated by the response surface method (RSM). ANOVA analysis revealed that the impregnation pressure and time and the interaction between the two seemed to have a significant effect on ∆SCPG. Based on the response face model, the corresponding optimal parameters obtained are 1.0 MPa and 16.0 min for impregnation pressure and time, respectively. By impregnating fir wood with the above optimal conditions, the SCPG increased by 85.78%, whereas the MOR decreased by the least amount.
Comparing the SDSS and VLBI quasar and galaxy positions

A direct link between a radio and an optical reference frame can be established by position measurements of common objects. The International Celestial Reference Frame (ICRF) is defined by the positions of 212 compact extragalactic radio sources regularly observed with Very Long Baseline Interferometry (VLBI). At present, spaceand ground-based all-sky optical astrometric catalogues do not reach the magnitude limit needed for the detection of the majority of sources studied with VLBI. The HIPPARCOS reference frame in the optical is linked to the ICRF indirectly through relative astrometric measurements of a few radio stars with respect to nearby radio-loud active galactic nuclei (AGNs). In the next decade, sensitive space-based optical astrometry missions (e.g. Gaia) will observe thousands of VLBI-detected quasars, thus providing a direct link between the radio and optical reference frames. Such a link is essential not only for astrometry, but for astrophysical applications as well. The high-resolution structure of the AGNs observed at different electromagnetic wavelengths can only be registered correctly if the coordinates are expressed in consistent systems. Although the Sloan Digital Sky Survey (SDSS) does not provide high-accuracy astrometric data in the optical, its faint magnitude limit allows us to directly compare the positions of a sample of 735 radio sources (quasars or galaxies). For these objects, ICRF radio positions are available at milli-arcsecond (mas) accuracy or better from the ICRF lists and the VLBA Calibrator Surveys (VCS). We confirm that the SDSS coordinates are in general accurate down to ∼ 60 mas in both right ascension and declination. We find indications that the optical and radio brightness peaks are not necessarily coincident for some of the objects.
Managing where you are: agglomeration economies, managerial industry experience and innovation in South-East Asia

ABSTRACT It is well-established that firms leverage both internal and external resources for their innovation activities. Even though the role of agglomeration economies in shaping the external resources available to firms has been particularly well-studied it is still unclear whether it is diversity or specialisation within agglomerations that drives firm innovativeness. We suggest that both do but that their relations with firm innovativeness are moderated by managerial industry experience. Using data from four South-East Asian economies we find that managers with more industry experience are better able to make the most of where they are, leveraging the opportunities afforded by their geographic environment. This finding is most pronounced in rural areas where firms with inexperienced managers almost never innovate, whereas half of the firms with experienced managers do. This suggests that future agglomeration research should be attentive to firm-level idiosyncrasies.
The Effect of Bariatric Surgery on Sexuality: Experiences of Obese Men in Turkey

Abstract Sexuality is an important aspect of quality of life and also a critical part of a relationship. Because social and cultural factors may affect sexual life, it is believed that the effects of bariatric surgery on male sexuality in different cultures need to be evaluated. The aim of this qualitative study was to explore sexual experiences of Turkish obese men who underwent bariatric surgery. Semi-structured, face-to-face interviews were conducted with 12 men who underwent bariatric surgery at a training and research hospital in Istanbul, Turkey. Interviews were recorded, transcribed, and analyzed thematically. This sample of men described sexual dysfunction that lead to relationship problems before surgery. Physical health problems, difficulties at work such as stigma, and sexual problems were the factors that men decided to have bariatric surgery. Obese men stated that satisfaction in both sexual and emotional life improved after surgery. Along with the overall quality of life, improvements in the sexual life of obese men are one of the important effects of bariatric surgery that should be known.
An Adaptive Spectral Algorithm for the Recovery of Overlapping Communities in Networks

This paper presents combinatorial spectral clustering, a simple spectral algorithm designed to identify overlapping communities in networks. The algorithm is based on geometric properties of the spectrum of the expected adjacency matrix in a random graph model that we call stochastic blockmodel with overlap (SBMO). An adaptive version of the algorithm, that does not require the knowledge of the number of hidden communities, is proved to be consistent under the SBMO when the degrees in the graph are (slightly more than) logarithmic. The algorithm is shown to perform well on simulated data and on real-world graphs with known overlapping communities.
Poor Spontaneous Recovery of Aphemia Accompanied by Damage to the Anterior Segment of the Left Arcuate Fasciculus: A Case Report

Aphemia is a rare and special type of speech disorder, and the mechanisms underlying the occurrence and recovery remain unclear. Here, we present a clinical case of poor spontaneous recovery of aphemia, with the anterior segment of the left arcuate fasciculus server damaged and the posterior segment intact, as detected by diffusion tensor imaging. Aphemia could be caused by the disruption of the cortical and subcortical language circuits. In particular, our data support the view that damage to the anterior segment of the left arcuate fasciculus may result in poor spontaneous recovery from speech production deficits and that an intact posterior segment seems to be crucial for supporting residual language comprehension ability in patients with post-stroke aphasia. Collectively, these data imply the importance of the left arcuate fasciculus during recovery from the language disorder in the subacute stage of stroke.
A Model for the Strings of Eta Carinae

We propose a model based on ionization shadows to explain the formation of the long and narrow strings of Eta Carinae. Five strings are known, all located along the symmetry axis outside the Homunculus. The model assumes that each string is formed in a shadow behind a dense clump near the symmetry axis. The surrounding gas is ionized first, becomes much hotter, and compresses the gas in the shadow. This leads to the formation of a radial, dense, long, and narrow region, i.e., a string. Later the neutral material in the strings is ionized, and becomes brighter. Still later it re-expands, and we predict that in about 200 years the strings will fade. The condition for the model to work is that the ionization front, due to the diffuse ionizing recombination radiation of the surrounding gas, proceeds into the shadow at a velocity slower than the compression speed. From that we get a condition on the mass loss rate of the mass loss episode that formed the strings, which should be less than 10^{-4} Mo/year. The model can also explain the strings in the planetary nebula NGC 6543.
A study of work-integrated learning experience of hospitality and tourism management students in Guangdong under the COVID-19 pandemic

PurposeThis paper aims to explore students’ work-integrated learning experience. Particularly, students’ application of knowledge and improvement of multiple skills in work-integrated learning, their influence on positive industry image change due to the COVID-19 pandemic, and students’ desired career prospect were explored.Design/methodology/approachA questionnaire survey with valid responses from 168 undergraduate students in hospitality and tourism management was conducted in four colleges/universities in Guangdong, China in 2021. PLS-SEM method was used to analyze the data.FindingsIt was found that students’ multiple skills had improved through application of knowledge in work-integrated learning. Skill improvement helped form positive industry image change and shape future career prospect. However, such positive industry image change did not impact students’ career prospect directly.Originality/valueToday, work-integrated learning has become one of the most valuable opportunities for students in hospitality and tourism management to gain industry experience. However, recent literature has largely examined the negative impacts of COVID-19, whereas few studies have examined the positive aspects of work-integrated learning.
Comparative Analysis of DoS Attack Detection in KDD CUP99 using Machine Learning Classifier Algorithms

The Internet of Things models are vulnerable is still wreaking havoc on commercial and critical sectors. The heterogeneity of different devices in IoT and their broad expansion has resulted in the emergence of numerous threats for security and privacy, severely impeding the collection, analysis, and correlation of IoT-centric data. With the fast growth of threats and the diversity of attack, IoT systems face significant hurdles in detecting security flaws and attacks. With the increase in the number of IoT devices, the volume of traffic generated by IoT-based assaults has been steadily increasing. One of the most serious IoT risks is the IoT botnet attack, which tries to commit genuine, efficient, and successful cybercrimes. Botnets have emerged as a key concern in IoT landscape, owing to the significant damages these collections of compromised IoT devices cause. Botnets are probably the most common form of the Internet's harmful traffic. It's dangerous because a large number of infected hosts are working together to focus on a single target. An efficient model to detect attacks in IoT is required so as to take corrective actions at the faster pace. In this paper, Machine learning models including Gaussian Naive Bayes, SVM, Gradient Boosting, Logistic Regression, One vs Rest, Random Forest, Decision tree, KNN and SGD are implemented on KDD CUP99 dataset to detect Denial-of–services attack. Decision tree model is found to be efficient model to classify the attacks at quicker pace and higher accuracy.