Miracle-dz/UniFAR-FTUs huggingface dataset:
BRIEF COMMUNICATION: Impact of date of birth recording practises in genetic evaluation in New Zealand sheep

Introduction Accuracy of selection is an important feature for all breeding programs and genetic evaluation systems, with genetic gain infl uenced by the accuracy of the breeding values and by the selection decisions taken by the breeder. Accuracy of estimated breeding values (eBVs) are affected by the amount and quality of the pedigree and performance data recorded. With increasing use of breeding values based on across–fl ock analyses, the impact of various data recording practises used in sheep fl ocks needs investigation to ensure practises by any particular breeder do not adversely affect the whole analysis. Date of birth is used in the genetic evaluation process to correct performance traits, especially live weights, for non-genetic differences resulting from being born earlier or later in the season. However, recording of actual date of birth is not feasible in some farming systems due to the extensive farming environment, species or breed management diffi culties or management practises such as DNA parentage. Amer et al. (1999) and Johnson and Blair (2003) concluded that while genetic progress in sheep or deer would be compromised by lack of date of birth records, selection for growth traits could still be effective. The objective of this study was to determine the impact on estimated breeding values of different date-ofbirth recording practises currently used by New Zealand sheep breeders.
Sentiment analysis of reviews using Nature Inspired Algorithm

Social media now plays an important role is sharing the views or comments about a topic. These comments are available to the users for their processing and future decision making process. As the reviews contains mostly text or emojis, thus, these need to be processed properly to get meaningful information. Nature is always a source for information and knowledge. Many activities happens in the words, that help to classify the reviews or comments. In this paper, Genetic Algorithm (GA) is considered for processing the reviews. GA is based on the process of genetic evaluation. Different GA operations are implemented to get a better classification result. The reviews are processed using the proposed algorithms and finally, the confusion matrix is generated, which helps to generate the evaluation parameters to evaluate the results.
Characteristics of a Good Nursing Nomenclature from an Informatics Perspective

The purpose for which a nomenclature is designed dictates its characteristics. Very few clinical nomenclatures have been designed for use in automated record systems. For this reason, system designers have had to adapt existing nomenclatures and classification systems for use in the automated systems they develop. Researchers have delineated the characteristics of a "good" nomenclature for purposes of structured data capture, storage, analysis, and reporting. Some of these characteristics are: domain completeness granularity parsimony synonymy non-ambiguity v non-redundancy clinical utility multiple axes and combinatorial. In addition, the terms should have unique and context-free term identifiers, each term should have a definition, terms should be arranged hierarchically with the ability to have multiple parents, and it must be possible to map terms to other standard classifications. These concepts are defined and rationalized in the context of the functions expected of an automated record system.
Mediterranean Shrub Species as a Source of Biomolecules against Neurodegenerative Diseases

Neurodegenerative diseases are associated with oxidative stress, due to an imbalance in the oxidation-reduction reactions at the cellular level. Various treatments are available to treat these diseases, although they often do not cure them and have many adverse effects. Therefore, it is necessary to find complementary and/or alternative drugs that replace current treatments with fewer side effects. It has been demonstrated that natural products derived from plants, specifically phenolic compounds, have a great capacity to suppress oxidative stress and neutralize free radicals thus, they may be used as alternative alternative pharmacological treatments for pathological conditions associated with an increase in oxidative stress. The plant species that dominate the Mediterranean ecosystems are characterized by having a wide variety of phenolic compound content. Therefore, these species might be important sources of neuroprotective biomolecules. To evaluate this potential, 24 typical plant species of the Mediterranean ecosystems were selected, identifying the most important compounds present in them. This set of plant species provides a total of 403 different compounds. Of these compounds, 35.7% are phenolic acids and 55.6% are flavonoids. The most relevant of these compounds are gallic, vanillic, caffeic, chlorogenic, p-coumaric, and ferulic acids, apigenin, kaempferol, myricitrin, quercetin, isoquercetin, quercetrin, rutin, catechin and epicatechin, which are widely distributed among the analyzed plant species (in over 10 species) and which have been involved in the literature in the prevention of different neurodegenerative pathologies. It is also important to mention that three of these plant species, Pistacea lentiscus, Lavandula stoechas and Thymus vulgaris, have most of the described compounds with protective properties against neurodegenerative diseases. The present work shows that the plant species that dominate the studied geographic area can provide an important source of phenolic compounds for the pharmacological and biotechnological industry to prepare extracts or isolated compounds for therapy against neurodegenerative diseases.
Practical Implementation of Visual Navigation Based on Semantic Segmentation for Human-Centric Environments

This study focuses on visual navigation methods for autonomous mobile robots based on semantic segmentation results. The challenge is to perform the expected actions without being affected by the presence of pedestrians. Therefore, we implemented a semantics-based localization method that is not affected by dynamic obstacles and a direction change method at intersections that functions even with coarse-grain localization results. The proposed method was evaluated through driving experiments in the Tsukuba Challenge 2022, where a 290 m run including 10 intersections was achieved in the confirmation run section.
Dielectric Resonator Antenna Array With Extended Beam-Scanning Range Using Dielectric Superstrate

An E-plane cylindrical dielectric resonator antenna (DRA) array with a dielectric superstrate is investigated for wide-angle scanning applications. Each slot-coupled DRA element operates at its fundamental HEM11δ mode. The dielectric superstrate is loaded above the DRA array. By adjusting its dimension and position properly, the beamwidth of the center active element pattern is significantly broadened. Meanwhile, the mutual coupling effect among various elements is effectively reduced. Both the wide-beam element pattern and reduced mutual coupling level contribute to the improvement of the array beam-steering capability. Finally, our proposed E-plane DRA array has a wide range of ±80° with a scan loss of 3 dB.
A Review on Bioactive Anthraquinone and Derivatives as the Regulators for ROS

Anthraquinones are bioactive natural products, which are often found in medicinal herbs. These compounds exert antioxidant-related pharmacological actions including neuroprotective effects, anti-inflammation, anticancer, hepatoprotective effects and anti-aging, etc. Considering the benefits from their pharmacological use, recently, there was an upsurge in the development and utilization of anthraquinones as reactive oxygen species (ROS) regulators. In this review, a deep discussion was carried out on their antioxidant activities and the structure-activity relationships. The antioxidant mechanisms and the chemistry behind the antioxidant activities of both natural and synthesized compounds were furtherly explored and demonstrated. Due to the specific chemical activity of ROS, antioxidants are essential for human health. Therefore, the development of reagents that regulate the imbalance between ROS formation and elimination should be more extensive and rational, and the exploration of antioxidant mechanisms of anthraquinones may provide new therapeutic tools and ideas for various diseases mediated by ROS.
A K-band, varactor-tuned dynamic metasurface aperture for microwave computational imaging

We present a substrate-integrated waveguide-fed metasurface design for K-band microwave computational imaging. Integration of varactors into each metamaterial element enables grayscale control of the element’s resonant response, allowing for increased flexibility in the attainable radiation patterns over those of a binary metasurface using PIN diodes. We describe the element design and performance, and give preliminary experimental results.
Applying the Miles and Snow's business strategy typology to China's real estate development industry : a research framework

Strategy typologies have been widely employed to describe various business strategies within a given industry. However, few studies have applied this useful tool to China’s real estate industry. In this paper we examine business strategies of Chinese developers based on the strategy typology developed by Miles and Snow (Prospector-Analyzer-Defender-Reactor). In light of the classic SWOT framework, we examine the external and internal influences/constraints to the firms’ business strategy formulations by adopting two perspectives, i.e. the strategic choice and the resource-based view, in order to identify the antecedents of the business strategy types. Factors such as ‘perceived political/regulatory environmental uncertainty’, ‘guanxi with the local government’ and ‘market-linking and marketing capabilities’ are suggested as significant predictors of business strategies of Chinese real estate developers and five research hypotheses are proposed. The paper aims to contribute to a better understanding on China’s real estate market in general, and of the developers’ strategy making behaviors in particular.
Did the West Coast Port Dispute Contribute to the First-Quarter GDP Slowdown?

In this post, we examine how the labor dispute at the West Coast ports, which began in the middle of 2014, might have affected GDP growth. Although the dispute started as early as July 2014, major disruptions to international trade did not surface until 2015:Q1. By that time, export and import growth through the West Coast ports in the first quarter were 14 percentage points to 20 percentage points lower than growth through other ports.
Performance Evaluation of Virtual Network Service Function Deployment in Docker Containers

Currently, using Container technology to host network functions can leverage faster Virtual Network Function (VNF) installation and optimize resource utilization than Virtual Machine (VM) based virtualization technology. When these network functions run inside a container, these software instances are often known as Cloud-Native Network Functions (CNF). Network providers use VNFs with different functionality in a chain to provide a service to the end user. A set of ordered VNFs is termed a Service Function Chain (SFC). The problem of placing and chaining VNFs of an SFC onto a network topology to minimize a cost function is known as SFC Placement and Chaining. This paper demonstrates how to solve the problem of SFC placement and chaining in a container-based environment. Multiple CNFs are used to create multiple service chains. These SFC have deployed on the National Scientific Foundation Network (NSFNET) topology. The SFC path is calculated using the Ant Colony Optimization algorithm. We have selected end-to-end delay and operational cost as the cost function that is minimized using the ACO algorithm. Performance metrics like end-to-end delay, operational cost, and throughput are recorded. We compare these results to the mathematical model to prove that the experimental and theoretical values are coherent with one another. These results benefit the network operators to do a cost-benefit analysis using the theoretical method, without wasting their time and resources on setting up a full-scale experimental setup.
Modelado y simulación de planificadores de recursos radio para una red LTE

Una de las principales caracteristicas de LTE es la capacidad para realizar la asignacion dinamica de recursos de radio disponibles en el sistema, haciendo uso de diferentes algoritmos de planificacion. Este articulo describe el modelado de los tres algoritmos de planificacion de recursos de radio basicos en enlace descendente LTE conocidos como Round Robin, Proportional Fair y Maximun Rate, su implementacion en el Simulador Basico a Nivel de Sistema, y la simulacion de un escenario especifico para evaluar el rendimiento de cada algoritmo en capacidad (throughput) para una red LTE. Para cumplir con tal proposito se emplea una metodologia lineal secuencial, empezando con una breve descripcion de la tecnologia LTE para contextualizar al lector, seguidamente se detallan las fases de diseno e implementacion y finalmente se realizan procesos de simulacion y pruebas en dos escenarios LTE especificos, con el fin de evaluar el desempeno de cada uno de los planificadores de recursos radio implementados y determinar el impacto que tienen estas tecnicas en la capacidad (throughput) que se puede llegar a alcanzar en una red LTE. ABSTRACT One of the main features of LTE is the ability to perform the dynamic allocation of radio resources available in the system using different scheduling algorithms. This paper describes the modeling of the three basic radio resource scheduling algorithms in LTE downlink known as Round Robin, Proportional Fair and Maximun Rate, its implementation in the Basic System Level Simulator, and simulation on a specific scenario to evaluate the performance of each algorithm in capacity (throughput) for a LTE network. To accomplish this purpose a sequential linear method is used, beginning with a brief description of the LTE technology to contextualize the reader, then the phases of design and implementation are described and finally simulation and testing processes are performed on two specific scenarios LTE, in order to evaluate the performance of each radio resource scheduling algorithms modeled and to determine the impact of these techniques in the capacity (throughput) that can reach a LTE network.
Evaluating the Viscoelastic Behavior of Elastomers Using a Piezoelectric Tactile Sensor and an Optimization Approach

Elastomers, polymers, and human tissues are well-known viscoelastic materials whose behavior are hard to grasp. Several mathematical models, being linear and nonlinear, have been proposed to describe the elastic and viscous properties of viscoelastic materials. In this paper, we aim to characterize the dynamic properties of silicon rubber viscoelastic material with different mixing ratios. To this end, an experimental setup using a piezoelectric cantilever was used to apply force to the viscoelastic specimens, and an eddy current sensor was used to measure the displacement. We used the Standard Linear Solid (SLS) model and the hysteresis loop methods to formulate the relations between applied force, displacement, damping, and stiffness. Furthermore, an optimization approach was proposed to find the SLS model parameters by searching functions over the frequency domain. The obtained results agree with the related research. In addition, our approach differentiated between the tested specimens depending on damping and stiffness dynamic properties. The results have shown that the damping of the PDMS tested specimes decreases with increasing the frequency and the harder the elastomer the more damping it shows. Also, the stiffnesses of the SLS model increase by increasing the frequency and by increasing the hardness of the elastomer.
Barley Yellow Dwarf Virus Influences Its Vector’s Endosymbionts but Not Its Thermotolerance

The barley yellow dwarf virus (BYDV) of cereals is thought to substantially increase the high-temperature tolerance of its aphid vector, Rhopalosiphum padi, which may enhance its transmission efficiency. This is based on experiments with North American strains of BYDV and R. padi. Here, we independently test these by measuring the temperature tolerance, via Critical Thermal Maximum (CTmax) and knockdown time, of Australian R. padi infected with a local BYDV isolate. We further consider the interaction between BYDV transmission, the primary endosymbiont of R. padi (Buchnera aphidicola), and a transinfected secondary endosymbiont (Rickettsiella viridis) which reduces the thermotolerance of other aphid species. We failed to find an increase in tolerance to high temperatures in BYDV-infected aphids or an impact of Rickettsiella on thermotolerance. However, BYDV interacted with R. padi endosymbionts in unexpected ways, suppressing the density of Buchnera and Rickettsiella. BYDV density was also fourfold higher in Rickettsiella-infected aphids. Our findings indicate that BYDV does not necessarily increase the temperature tolerance of the aphid transmission vector to increase its transmission potential, at least for the genotype combinations tested here. The interactions between BYDV and Rickettsiella suggest new ways in which aphid endosymbionts may influence how BYDV spreads, which needs further testing in a field context.
Incentivizing the Collaboration Between Travelers and Power-Traffic Network Operators: An Asymmetric Nash Bargaining Approach

With the proliferation of electric vehicles and the deepened interdependence between power and traffic networks, tariff- and subsidy-based monetary incentives have been leveraged by network operators to shape vehicular&charging flow distributions to more closely align with network-level objectives. Travelers and network operators are generally regarded as two self-interested entities. As a result, the conflict between the system- and user-optimality usually forces travelers to bear an extra expenditure (either tariff payment or detour time) or requires network operators to dispense overmuch subsidies, both resulting in social welfare losses. The present work bridges this gap by designing a Cooperative Game based operation scheme that facilitates the collaboration between the two entities, in which collaborative travelers follow the social routing advice and then receive a certain level of reimbursement from network operators. To ensure a fair benefit allocation, we quantify the individual contribution as the difference of the path travel cost before and after the collaboration, then adopt the asymmetric Nash bargaining theory to settle the dispense of reimbursement. Numerical results on case studies indicate that the proposed model outperforms the subsidy-based non-cooperative Stackelberg Game in terms of promoting a win-win situation for both entities.
Evaluation of Antarctic sea ice thickness and volume during 2003–2014 in CMIP6 using Envisat and CryoSat-2 observations

Sea ice thickness (SIT), which is a crucial and sensitive indicator of climate change in the Antarctic, has a substantial impact on atmosphere-sea-ice-ocean interactions. Despite the slight thinning in SIT and reduction in sea ice volume (SIV) in the Antarctic in the recent decade, challenges remain in quantifying their changes, primarily because of the limited availability of high-quality long-term observational data. Therefore, it is crucial to accurately simulate Antarctic SIT and to assess the SIT simulation capability of state-of-the-art climate models. In this study, we evaluated historical simulations of SIT by 51 climate models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) using Envisat (ES) and CryoSat-2 (CS2) observations. Results revealed that most models can capture the seasonal cycles in SIV and that the CMIP6 multimodel mean (MMM) can reproduce the increasing and decreasing trends in the SIV anomaly based on ES and CS2 data, although the magnitudes of the trends in the SIV anomaly are underestimated. Additionally, the intermodel spread in simulations of SIT and SIV was found to be reduced (by 43%) from CMIP5 to CMIP6. Nevertheless, based on the CMIP6 MMM, substantial underestimations in SIV of 57.52% and 59.66% were found compared to those derived from ES and CS2 observations, respectively. The most notable underestimation in SIT was located in the sea ice deformation zone surrounding the northwestern Weddell Sea, coastal areas of the Bellingshausen and Amundsen seas, and the eastern Ross Sea. The substantial bias in the simulated SIT might result from deficiencies in simulating critical physical processes such as ocean heat transport, dynamic sea ice processes, and sea ice-ocean interactions. Therefore, increasing the model resolution and improving the representation of sea ice dynamics and the physical processes controlling sea ice-ocean interactions are essential for improving the accuracy of Antarctic sea ice simulation.
Repeat Patronage teori : Loyalitas Menonton Acara TV di Yogyakarta

Penelitian ini bertujuan untuk menganalisis perilaku loyalitas menonton tayangan acara televisi berdasarkan konsep model repeat patronage. Penelitian ini melibatkan 135 responden dengan penyebaran kuisioner secara online. Metode analisis menggunakan analisis model PLS. Hasil analisis menunjukkan evaluasi kognitif dan evaluasi afektif tidak berpengaruh signifikan pada loyalitas menonton acara televisi. Evaluasi konatif berpengaruh positif signifikan pada loyalitas menonton acara televisi. Norma sosial dan faktor situasional memberikan pengaruh positif pada loyalitas menonton acara televisi.
Towards Detecting and Quantifying Identity-Based Polarization in Online Content: A Deep-Learning Approach

Identity-based polarization is prevalent across many news outlets, and yet goes unnoticed by most readers. This separate form of polarization differs greatly from the typical ideology-based polarization, which is seen when two separate political parties solely disagree due to a policy difference. In this paper, we focus on a distinct kind of polarization that we call identity-based polarization. This is the act of refusing to focus on differences in ideology and instead focusing on individual or group identities such as race, sexuality and gender to form extreme opinions. The never-ending stream of online content through social media and news outlets has posed significant challenges to accurately understand, detect, and quantify identity-based polarization. If one cannot quantify, one cannot manage, and the health of our society, especially for the younger generation, suffers greatly. In the past, research has been done in detecting polarization in areas such as political bias, but such studies solely relied on sentiment analysis. In this paper, we take a vastly different approach as we first implement an entity-recognition system to detect identities in the article, and then as a follow up, we attempt to attribute polarization to the recognized entities using sentiment analysis. In addition, this paper leverages BERT (Bidirectional Encoder Representations from Transformers) and NLP (Natural Language Processing) techniques through the combination of sentiment analysis and a customized NER (Named-Entity-Recognition) system. In this way, this paper takes a novel and more scientific approach to accurately identifying and quantifying identity-based polarization. By utilizing news article data from five major news outlets, the final developed NER model achieved an F1 score of over 83%, and we uncovered a strong correlation between identity density in texts and extreme sentiment expressed in the text, with the correlation ranging from +0.48 to +0.68. This work is a first step towards managing identity-based polarization in online contents; it has significant societal and cultural implications, and may be readily extended to other kinds of polarization and be applied to other public media.