Miracle-dz/UniFAR-FTUs huggingface dataset:
Small ruminant production systems in Mexico and their effect on productive sustainability

In the small ruminant sector, there is a great interest in measuring and improving their production systems and their environmental performance, since its great adaptability and inhabits a wide variety of ecosystems, with a great biodiversity of food resources, grazing in turn, generates economic-productive and environmental benefits. However, unplanned management and overexploitation of the natural resources of these areas have caused erosion, water depletion and even desertification, in the same manner intensive production systems and intensive agriculture that feeds these farming systems. To compare scientific innovations in the sustainability of the different production systems of small ruminants a bibliometric analysis was carried out to describe the advantages and disadvantages of the management of extensive, semi-intensive and intensive-stable production systems in the sustainability of small ruminants. There is concern in society about the environmental impact of animal production systems and that these have been carried out in a sustainable way. This trend influences the production of sheep, goats, and white-tailed deer, which are develop in intensive, semi-extensive and extensive systems. Due to the pressure to increase the volume and efficiency of production and to cope with demand, intensive systems are best suited, but face greater environmental such emission of greenhouse gases (GHGs), which contribute to global warming and animal environmental problems. On the other hand, semi-extensive and extensive systems also emit GHGs, however are associated with greater animal welfare and cleaner production. However, are affected by seasonal variations for forage production to maintain production levels.
Autonomous Socially Assistive Drones Performing Personalized Dance Movement Therapy: An Adaptive Fuzzy-Logic-Based Control Approach for Interaction with Humans

Novel personalized and affordable approaches are needed in order to provide efficient therapeutic interventions for people with autism spectrum disorder. In this paper, we introduce a new category of socially assistive robots, i.e., socially assistive drones (SADs) for therapeutic interactions with humans. SADs autonomously perform and engage humans in dance movement therapy (DMT), a therapeutic approach that - when personalized and adapted carefully - has proven to be effective for various people with autism spectrum disorder. The main focus of this paper is on developing adaptive, personalized, and interactive control approaches based on fuzzy logic, which allows for efficiently incorporating nonlinearities into the dynamics and for directly introducing the expert (linguistic) knowledge into the control system. The developed approaches are implemented via a small quadcopter in real-life interactions with 10 participants. The results of the case study prove the excellent performance of the SAD in adapting and personalizing its decisions with respect to each user and thus keeping them engaged in the proposed DMT plans.
Imputation of Missing Covariates in Randomized Controlled Trials with Continuous Outcomes: Simple, Unbiased and Efficient Methods

ABSTRACT The literature on dealing with missing covariates in nonrandomized studies advocates the use of sophisticated methods like multiple imputation (MI) and maximum likelihood (ML)-based approaches over simple methods. However, these methods are not necessarily optimal in terms of bias and efficiency of treatment effect estimation in randomized studies, where the covariate of interest (treatment group) is independent of all baseline (pre-randomization) covariates due to randomization. This has been shown in the literature, but only for missingness on a single baseline covariate. Here, we extend the situation to multiple baseline covariates with missingness and evaluate the performance of MI and ML compared with simple alternative methods under various missingness scenarios in RCTs with a quantitative outcome. We first derive asymptotic relative efficiencies of the simple methods under the missing completely at random (MCAR) scenario and then perform a simulation study for non-MCAR scenarios. Finally, a trial on chronic low back pain is used to illustrate the implementation of the methods. The results show that all simple methods give unbiased treatment effect estimation but with increased mean squared residual. It also turns out that mean imputation and the missing-indicator method are most efficient under all covariate missingness scenarios and perform at least as well as MI and LM in each scenario.
Locomotion Modes and Environmental Features Recognition Using Laser Distance Sensors

Recognition of locomotion mode (LM) has been used to control the lower limb powered prosthetic and orthotic devices for navigating autonomously on a variety of terrains. In addition, the knowledge of environmental features (EFs) can be utilized to modulate the joint kinetics of prosthetic devices in a precise manner. In this article, a novel LM recognition strategy has been proposed along with EFs estimation utilizing a combination of laser distance sensors (LDSs) and inertial measurement units (IMUs). LM was classified from outputs of eight sensors, i.e., six LDSs and two IMUs, utilizing support vector machine (SVM) followed by a majority voting scheme. A cloud of points was generated in the sagittal plane, which was further used to determine the EFs leveraging curve fitting techniques. The efficiency of the proposed method was tested with six healthy subjects and for a variety of LMs, such as walking on the level-ground, ramp, and stairs. The overall accuracy of LM classification and EF estimation was found to be equal to 97.85% and 95.36%, respectively. The proposed study is an accurate, computationally inexpensive, and cost-effective solution and can be used efficiently to control lower limb prosthetic devices. The novelty of this study is the simplification of the LM classification and EF estimation methods compared to a camera-based technique to facilitate real-time control of powered prostheses.
Double-E-Triple-H-Shaped NRI-Metamaterial for Dual-Band Microwave Sensing Applications

This paper presents a new Double-E-Triple-H-Shaped NRI (negative refractive index) metamaterial (MM) for dual-band microwave sensing applications. Here, a horizontal H-shaped metal structure is enclosed by two face-to-face E-shaped metal structures. This double-E-H-shaped design is also encased by two vertical H-shaped structures along with some copper links. Thus, the Double-E-Triple-H-Shaped configuration is developed. Two popular substrate materials of Rogers RO 3010 and FR-4 were adopted for analyzing the characteristics of the unit cell. The proposed structure exhibits transmission resonance inside the S-band with NRI and ENG (Epsilon Negative) metamaterial properties, and inside the C-band with ENG and MNG (Mu Negative) metamaterial properties. A good effective medium ratio (EMR) of 8.06 indicates the compactness and effectiveness of the proposed design. Further analysis has been done by changing the thickness of the substrate material as well and a significant change in the effective medium ratio is found. The validity of the proposed structure is confirmed by an equivalent circuit model. The simulated result agrees well with the calculated result. For exploring microwave sensing applications of the proposed unit cell, permittivity and pressure sensitivity performance were investigated in different simulation arrangements. The compact size, effective parameters, high sensitivity and a good EMR represent the proposed metamaterial as a promising solution for S-band and C-band microwave sensing applications.
An experimental study of exhaust hydrocarbon emissions from a spark ignition engine

The control of hydrocarbon emissions from spark ignition engines is important and there is a need for a better understanding of the mechanisms contributing to this source of emissions. The absorption/desorption mechanism is believed to be a significant contributor to hydrocarbon emissions. The aim of the project has been to validate the absorption/desorption model experimentally. Modelling studies predict that sufficient fuel vapour is absorbed into the cylinder wall oil film on the compression and early firing strokes with subsequent desorption late in the expansion stroke to seriously affect hydrocarbon emissions in the exhaust, as temperatures are too low for adequate oxidation. The experimental investigation which follows develops a method to allow accurate measurement of hydrocarbon specie levels in the exhaust of a spark ignition engine. The object of the experiment was to detect and measure differences in hydrocarbon levels for two fuels, Iso-octane and Iso-pentane, at identical engine conditions and therefore establish whether the absorption/desorption effect is significant to hydrocarbon emissions. The theory behind this relies upon the varying solubilities of both fuels in a given oil with temperature wh ich shoul d refl ect a varyi ng base fuel hydrocarbon emissions level for each fuel if absorption/desorption is in fact taking place. Samples of exhaust were taken from a Ricardo-hydra test engine and analysed chromatographically. Experimental results (which compare favourably with prediction from modell ing studies) indicate about 30 percent of total hydrocarbons are due to the absorption/desorption mechanism. In conclusion, the results suggest that the solubility of the fuel in the engine oil has a significant effect on hydrocarbon levels in the exhaust.
An Empirical Analysis of New Rules Adopted Under Regulation National Market System: Pilot Phase Period Implementation Results

We examine changes in quote competition, trade aggressiveness, trading costs, volume, and abnormal returns during the pilot 90 The BRC Academy Journal of Business Vol. 6, No. 1 phase period of new price protection measures for both NYSE and NASDAQ stocks subject to new rules imposed under SEC Regulation NMS. We find that NYSE stocks exhibit less quote competition, increased fragmentation, and negative abnormal returns following the implementation of the new rules. Changes in trade aggressiveness and trading costs are not significant. NASDAQ stocks exhibit decreased trading costs and increased fragmentation following implementation of the new rules. These changes reflect the nature of the new regulations.
The Role of Calcium Signaling in Melanoma

Calcium signaling plays important roles in physiological and pathological conditions, including cutaneous melanoma, the most lethal type of skin cancer. Intracellular calcium concentration ([Ca2+]i), cell membrane calcium channels, calcium related proteins (S100 family, E-cadherin, and calpain), and Wnt/Ca2+ pathways are related to melanogenesis and melanoma tumorigenesis and progression. Calcium signaling influences the melanoma microenvironment, including immune cells, extracellular matrix (ECM), the vascular network, and chemical and physical surroundings. Other ionic channels, such as sodium and potassium channels, are engaged in calcium-mediated pathways in melanoma. Calcium signaling serves as a promising pharmacological target in melanoma treatment, and its dysregulation might serve as a marker for melanoma prediction. We documented calcium-dependent endoplasmic reticulum (ER) stress and mitochondria dysfunction, by targeting calcium channels and influencing [Ca2+]i and calcium homeostasis, and attenuated drug resistance in melanoma management.
New insights into the central sympathetic hyperactivity post‐myocardial infarction: Roles of METTL3‐mediated m6A methylation

Ventricular arrhythmias (VAs) triggers by sympathetic nerve hyperactivity contribute to sudden cardiac death in myocardial infarction (MI) patients. Microglia‐mediated inflammation in the paraventricular nucleus (PVN) is involved in sympathetic hyperactivity after MI. N6‐methyladenosine (m6A), the most prevalent mRNA and epigenetic modification, is critical for mediating cell inflammation. We aimed to explore whether METTL3‐mediated m6A modification is involved in microglia‐mediated sympathetic hyperactivity after MI in the PVN. MI model was established by left coronary artery ligation. METTL3‐mediated m6A modification was markedly increased in the PVN at 3 days after MI, and METTL3 was primarily located in microglia by immunofluorescence. RNA‐seq, MeRIP‐seq, MeRIP‐qPCR, immunohistochemistry, ELISA, heart rate variability measurements, renal sympathetic nerve activity recording and programmed electrical stimulation confirmed that the elevated toll‐like receptor 4 (TLR4) expression by m6A modification on TLR4 mRNA 3'‐UTR region combined with activated NF‐κB signalling led to the overwhelming production of pro‐inflammatory cytokines IL‐1β and TNF‐α in the PVN, thus inducing the sympathetic hyperactivity and increasing the incidence of VAs post‐MI. Targeting METTL3 attenuated the inflammatory response and sympathetic hyperactivity and reduced the incidence of VAs post‐MI.
Autoencoder-aided analysis of low-dimensional Hilbert spaces

Keywords: feedforward autoencoder, low-dimensional Hilbert spaces, numerical ground-state estimation We study the applicability of feedforward autoencoders in determining the ground state of a quantum system from a noisy signal provided in a form of random superpositions sampled from a low-dimensional subspace of the system’s Hilbert space. The proposed scheme relies on a minimum set of assumptions: the presence of a finite number of orthogonal states in the samples and a weak statistical dominance of the targeted ground state. The provided data is compressed into a two-dimensional feature space and subsequently analyzed to determine the optimal approximation to the true ground state. The scheme is applicable to single- and many-particle quantum systems as well as in the presence of magnetic frustration.
Joint Partial Crosstalk Cancellation and Spectrum Management for xDSL Systems with Data Rate Constraints

Abstract xDSL systems have to be able to support an always increasing amount of high-rate applications. To make the applications run stably, service providers need to be capable of guaranteeing these high data rates to their customers at a limited amount of available computational complexity usable for crosstalk cancellation. In order to be able to support high data rate targets with a low amount of computational complexity, partial crosstalk cancellation was combined with spectrum management techniques. A selection procedure was found, which jointly chooses the canceled crosstalkers and the transmit powers for each user on each tone by interlacing Iterative Water Filling (IWF) and a newly developed successive crosstalk selection algorithm for partial crosstalk cancellation, which takes into account the data rate requirements of the users. It distributes the available computational complexity in an intelligent way, so that data rate requirements are fulfilled. With the joint procedure savings in computational complexity are achieved.
Morbimortalidade por COVID-19 associada a condições crônicas, serviços de saúde e iniquidades: evidências de sindemia

RESUMO Objetivo. Identificar os fatores correlacionados à incidência e mortalidade por COVID-19 e verificar situações de sindemia em escala global. Métodos. Realizou-se um estudo ecológico de casos e óbitos confirmados de COVID-19 a partir de informações coletadas do European Center for Disease Prevention and Control em 2019 e 2020. Para a caracterização dos países, utilizaram-se indicadores do Banco Mundial e Worldometer Coronavirus. Foram realizadas análises descritivas e de correlação entre as variáveis independentes para posteriormente realizar o modelo de regressão linear múltipla, com o objetivo de identificar os fatores correlacionados à incidência e mortalidade por COVID-19. Resultados. Obtiveram-se dados de 185 países. A média da incidência dos casos foi de 16 482/mil habitantes, enquanto a média para mortalidade por COVID-19 foi de 291/mil habitantes, sendo América do Norte e Leste Asiático e Pacífico as regiões que apresentaram maiores e menores índices, respectivamente. Identificouse correlação positiva da taxa de incidência com proporção da população com idade de 15 a 64 anos, população urbana, desigualdade conforme Índice de Gini e com seis das sete regiões analisadas (exceto Leste Asiático e Pacífico). A taxa de mortalidade apresentou correlação negativa com a população de 0 a 14 anos e positiva com população urbana, desigualdade conforme índice de Gini e todas as regiões analisadas, exceto Leste Asiático e Pacífico. Conclusões. A morbimortalidade da COVID-19 esteve correlacionada à carga de condições crônicas, ao envelhecimento da população e à baixa capacidade dos serviços de saúde para testagem e oferta de leitos hospitalares, quadro agravado em países ou regiões com elevada desigualdade social, caracterizando uma situação de sindemia.
Rough Registration of BIM Element Projection for Construction Progress Tracking

Monitoring construction progress is essential for project management. A variety of excellent automatic schedule acquisition methods have been proposed, particularly 3D reconstruction. However, both laser-based and image-based 3D reconstruction methods rely on point clouds which have some inherent defects. In this study, a rough registration method was proposed to obtain construction progress. The method does not generate point clouds during the entire process but determines the actual construction progress by registering the target detection results and the projection of building information model elements. The method was tested at the construction sites of commercial and residential buildings. The experimental results indicated that the registration accuracy reached 95.13%. The average external parameter calibration time and the registration time of each image are 18.57s and 50.59ms, respectively. Compared to similar 3D reconstruction methods, the proposed method is realistic, fast, and simple. This provides a promising method for 3D reconstruction from unordered construction-site images.
Current Differential Protection Criterion Using Steady Currents for Heavy-load Line With High Fault Resistance

It is analyzed that the criterion of current differential protection using steady currents is not able to operate at internal faults under the condition of high fault resistance and heavy-loads due to through currents.An improved steady current differential protection criterion is proposed.The sensitivities of these two criteria are analytically compared.The improved criterion possesses higher sensitivity at an internal ground fault with fault resistance and is especially superior on the conventional one under the condition of high fault resistance and heavy-loads.Simulation of faults and the two protection criteria on a 750 kV line proves that the proposed criterion has achieved a great improvement on the abilities of detecting high resistance internal faults in the heavy-load condition with guarantee of security at external faults.It is a proper current differential protection criterion for EHV\UHV transmission lines.
Improving Hydrodynamic Model for Zero Speed Bionic Fin Stabilizer

The single analytical method is used in modeling the existing hydrodynamic force model for zero speed fin stabilizers,where the effect of the fin thickness and shape on the hydrodynamic model is ignored during the modeling process and the analysis of the vortex drag is also crude.These problems result in not only more parameters to be determined in the model,but also great difference between the model and the real situation.In view of these problems,the composite method of the numerical and the analytical approaches is used to improve the hydrodynamic force model and its old modeling method in order to make the modified model more exact,and without loss of engineering practicability.Finally,the theoretical calculation value is compared with that from the FLUENT,and the advantages of the modified model and modeling method are demonstrated.
A SURVEY ON CONCEPTUAL ADVANCEMENTS IN SENTIMENT ANALYSIS

Sentiment analysis is defined as the process of computationally identifying and categorizing the opinions expressed in the written text to analyze the writer’s attitude and finding out whether the written text is positive, negative or neutral in nature. Over the past few years, it attracted a great deal of attentions from both academia and industry due to many challenging research problems and a wide range of applications. These opinions are generally obtained in text format through various databases such as twitter, customer forum, and complaint websites. In these survey paper we have studied and shown the advancements of the sentiment analysis overs the past few years and have inhabited the growth of various concepts under it. This paper gives a review of various facts about the different perceptions related to sentiment analysis and opinion mining. We have also suggested a system as a future scope which works on the analysis of various opinions and creates a module that can handle multiple entities and queries related to it.
Current Therapy in Inflammatory Bowel Disease:
Why and How We Need to Change?

During the last few decades, major progress has been made in the treatment of the two major forms of inflammatory bowel disease (IBD): Crohn’s disease and ulcerative colitis. However, the success of the most advanced forms of therapy is at best 50%, and most patients lose responsiveness with time and need to switch to alternative medications. This denotes that a therapeutic ceiling has been reached and brand new approaches are badly needed. This commentary first briefly reviews current and recent therapeutic approaches for Crohn’s disease and ulcerative colitis, pointing out their limitations. This is followed by an objective evidence-based discussion of why the current approaches are far from optimal, and the commentary is concluded by proposing how to change IBD treatment based on the holistic concept of network medicine, and how to implement precision medicine for IBD using artificial intelligence-based multi-omics analyses.