Miracle-dz/UniFAR-FTUs huggingface dataset:
Mitoapocynin Attenuates Organic Dust Exposure-Induced Neuroinflammation and Sensory-Motor Deficits in a Mouse Model

Increased incidences of neuro-inflammatory diseases in the mid-western United States of America (USA) have been linked to exposure to agriculture contaminants. Organic dust (OD) is a major contaminant in the animal production industry and is central to the respiratory symptoms in the exposed individuals. However, the exposure effects on the brain remain largely unknown. OD exposure is known to induce a pro-inflammatory phenotype in microglial cells. Further, blocking cytoplasmic NOX-2 using mitoapocynin (MA) partially curtail the OD exposure effects. Therefore, using a mouse model, we tested a hypothesis that inhaled OD induces neuroinflammation and sensory-motor deficits. Mice were administered with either saline, fluorescent lipopolysaccharides (LPSs), or OD extract intranasally daily for 5 days a week for 5 weeks. The saline or OD extract-exposed mice received either a vehicle or MA (3 mg/kg) orally for 3 days/week for 5 weeks. We quantified inflammatory changes in the upper respiratory tract and brain, assessed sensory-motor changes using rotarod, open-field, and olfactory test, and quantified neurochemicals in the brain. Inhaled fluorescent LPS (FL-LPS) was detected in the nasal turbinates and olfactory bulbs. OD extract exposure induced atrophy of the olfactory epithelium with reduction in the number of nerve bundles in the nasopharyngeal meatus, loss of cilia in the upper respiratory epithelium with an increase in the number of goblet cells, and increase in the thickness of the nasal epithelium. Interestingly, OD exposure increased the expression of HMGB1, 3- nitrotyrosine (NT), IBA1, glial fibrillary acidic protein (GFAP), hyperphosphorylated Tau (p-Tau), and terminal deoxynucleotidyl transferase deoxyuridine triphosphate (dUTP) nick end labeling (TUNEL)-positive cells in the brain. Further, OD exposure decreased time to fall (rotarod), total distance traveled (open-field test), and olfactory ability (novel scent test). Oral MA partially rescued olfactory epithelial changes and gross congestion of the brain tissue. MA treatment also decreased the expression of HMGB1, 3-NT, IBA1, GFAP, and p-Tau, and significantly reversed exposure induced sensory-motor deficits. Neurochemical analysis provided an early indication of depressive behavior. Collectively, our results demonstrate that inhalation exposure to OD can cause sustained neuroinflammation and behavior deficits through lung-brain axis and that MA treatment can dampen the OD-induced inflammatory response at the level of lung and brain.
DYNAMIC SIMULATION AND FINITE ELEMENT ANALYSIS OF THE MAXILLARY BONE INJURY AROUND DENTAL IMPLANT DURING CHEWING DIFFERENT FOOD

Since a long term patency of the dental implant has a direct relationship with their biomechanical performance, it is of vital important to understand the stresses and deformations that happen during chewing around the dental implant and bone. However, this model so far has not been well realized and this is why in this study we aim to establish a Finite Element (FE) model to analyse the stresses and deformations. A trajectory approach has been used to implement the action of muscles into the mode. To do this, a cornflake bio is mounted between the teeth and force applied until the breakage of the food in mouth. Furthermore, an experimental study was performed using the Digital Image Correlation (DIC) method and a set of three markers used to verify the numerical observations. The results revealed that in the maxillary bones, the maximum stresses were located within the cortical bone surrounding the implant and within the neck of implant. In addition, as the elastic modulus of the food is increased the stress in cortical bone increased accordingly. The results also revealed that the highest stress in the system is 74% of the yield stress while this value has been reported as 41% in previous studies.
Topological design using multivariate laminate stackings for tailored fiber placement

In structural optimization of fiber-reinforced composites, unidirectional design material is normally applied due to its high anisotropy character. Using volume constraints to save weight often results in truss-like frameworks with defined tension and shear loaded areas, while the latter one is often neglected or improperly described with unidirectional material. Here, a method is proposed to extend the material design space to a continuously variable domain between UD and cross-ply laminates which is simultaneously optimized with topology. This allowed us to increase the design improvement and create smoother material distributions which is more beneficial for fiber placement technologies such as Tailored Fiber Placement. Parameter studies have been performed to investigate the effects of variable shear properties and different design spaces on the structural performance of the final designs, concluding with classical benchmarks to validate the proposed method.
Innovative Knitted Fabrics Containing Lateral Propagation Optical Fibres Designed for Children with Autism – Preliminary Stud

The article presents an analysis of preliminary research on the functionalisation of knitted fabrics in such a way that they can perform a therapeutic function and be used as a chromotherapy tool for children with autism. Knitted fabric with optical fibres comprisesan innovative approach to the topic of helping the sick and their families, where colour therapy treatment can be performed at home, following the recommendations of the attending physician or therapist.
Nutraceutical Importance of Dietary Curcumin, Its Analogues in Restricting Melanoma Growth and Modulation of Multiple Targets

Objectives: Melanoma is one the most lethal form of skin cancer with a survival rate of less than 5% and thus possesses biggest challenge for its therapy among research scientists. The Melanoma progression within a tumor is guided by multiple mechanisms, thereby hindering the development of successful therapies. Therefore, there is a urgent demand to identify potential targets against melanoma cancer cells as well as to develop potent inhibitors in order to reduce melanoma at the very onset of cancer cell growth through targeting mutidrug resistance. It is well reported that curcumin is acting as inhibitor for metastasis of melanoma cancer cells. The most potential target of melanoma cancer cells has to be identified in order to reduce the relapse as well as to overcome multidrug drug resistance. Methods: In this study, the potency of curcumin analogues as well as their interaction with potential targets was identified by insilico approaches.Their efficacy has been examined through invitro assay. Results: Based on both invitro and insilico studies, few curcumin analogues have shown higher inhibitory activity against melanoma cancer cells than curcumin. Conclusion: The present study predicts some novel curcumin analogues that can act as potent inhibitor of melanoma cancer cells.
Branching points for transition pathways: How actors respond to stresses and challenges.

This paper describes initial analysis of branching points on a set of transition pathways to a UK low carbon electricity future by 2050. As described in other papers in this special issue, we are exploring and analysing a set of core transition pathways, based on alternative governance patterns in which the ‘logics’ of market actors, government actors and civil society actors, respectively dominate. This core pathway analysis is enhanced by analyses of branching points within and across the pathways, which informs how competition between different logics plays out at key decision points. Branching points are defined as key decision points at which choices made by actors, in response to internal or external stresses or triggers, determine whether and in what ways the pathway is followed. A set of initial branching points for our three core transition pathways is identified through project and stakeholder workshops, and drawing on analysis of actors’ choices and responses at past branching points in energy system transitions. The potential responses of the actors are identified at these branching points, and risk mitigation strategies are formulated for the dominant actors to reinforce that pathway, as well as opportunities for actors to move away from the pathway.
Joint Air-to-Ground Scheduling in UAV-Aided Vehicular Communication: A DRL Approach With Partial Observations

The unmanned aerial vehicle (UAV)-aided vehicular communication can be greatly facilitated by joint optimization of UAV trajectory design and vehicle assignment. While most existing works are based on the full observation of system state, we consider the partial observability with predicting the vehicles’ trajectories. The vehicle trajectory prediction and joint optimization problem are modeled as a Partially-Observable Markov Decision Process (POMDP). To deal with the non-Markovian of the POMDP, we construct a new deep recurrent Q-network (DRQN) framework based on deep Q-network (DQN) algorithm and Long Short Term Memory (LSTM) layer. Simulation results demonstrate that the proposed DRQN-based scheme is fast convergent and outperforms the baseline schemes in terms of the sum spectral efficiency.
Efficient Hardware Design and Implementation of the Voting Scheme-Based Convolution

Due to a point cloud’s sparse nature, a sparse convolution block design is necessary to deal with its particularities. Mechanisms adopted in computer vision have recently explored the advantages of data processing in more energy-efficient hardware, such as the FPGA, as a response to the need to run these algorithms on resource-constrained edge devices. However, implementing it in hardware has not been properly explored, resulting in a small number of studies aimed at analyzing the potential of sparse convolutions and their efficiency on resource-constrained hardware platforms. This article presents the design of a customizable hardware block for the voting convolution. We carried out an in-depth analysis to determine under which conditions the use of the voting scheme is justified instead of dense convolutions. The proposed hardware design achieves an energy consumption about 8.7 times lower than similar works in the literature by ignoring unnecessary arithmetic operations with null weights and leveraging data dependency. Access to data memory was also reduced to the minimum necessary, leading to improvements of around 55% in processing time. To evaluate both the performance and applicability of the proposed solution, the voting convolution was integrated into the well-known PointPillars model, where it achieves improvements between 23.05% and 80.44% without a significant effect on detection performance.
Resear ch on the Components of Childr en's Educational Game Achievement System

Under the background of the rapid development of digital educational games, we have to evidently research the elements of the achievement system of children’s DEG (Digital Educational Game), and analyze the relations between the elements and make a profound study on the achievement system and its components on the impact of player’s attitude. Compared with the existing research, the research contents and methods are innovative and reliable. The results show that players have a positive attitude towards the DEG achievement system, DEG achievement system has important value and role for educational games. Which is made of five elements: symbol, reward, logic, social interaction
Highly Sensitive Detection and Control of a Nanowire Mechanical Resonator Using an Optical Microcavity

Semiconductor nanowires have a rod-like structure that is too thin to be seen by the naked eye. This fine structure strongly confines photons and electrons, enabling us to use quantum nano-optoelectric properties to control photons and electrons individually. Semiconductor nanowires also function as nanomechanical resonators when their flexural motion is available. To achieve new opto-electro-mechanical hybrid quantum devices, NTT laboratories have developed technology to detect and control nanowire mechanical motion with high sensitivity.
Safety and Efficacy of Medicinal Plants Used to Manufacture Herbal Products with Regulatory Approval in Uganda: A Cross-Sectional Study

Introduction The Uganda National Drug Authority requires phytochemical screening, freedom from microbial contamination, and evidence of safety and efficacy of the constituent plants to register herbal products. Since Uganda has no pharmacopeia, safety, efficacy, and plant processing information are not readily available. We documented the plant materials used to manufacture products in Uganda and established evidence of their safety and efficacy and availability of monographs. Methods The NDA register of herbal products was reviewed, and a product list was extracted. The herbal products were purchased from local pharmacies, and their labels were studied to identify plant ingredients and drug use. Literature was reviewed to document evidence of the safety and efficacy of the plant materials concerning manufacturer's claims. Also, the WHO and available African Pharmacopeia were searched to establish the availability of the plant monographs. Results Of the 84 NDA-registered local products, only 18 were obtained from the market; 82% were indicated for respiratory tract disorders. Thirty-three plant materials were listed with Eucalyptus globulus Labill, being the commonest. Several in vitro and in vivo studies demonstrate efficacy, thus supporting the use of the selected plant species for empirical treatment as stated on the product label. While most plants were safe, some species such as Albizia coriaria Oliv. had dose-dependent toxicities that cannot be predicted in combinations. The WHO, African Pharmacopoeia, and West African Herbal Pharmacopoeia had only 16 plant monographs of the 33 plants of interest. Nevertheless, Aloe vera (L.) Burm.f. , Azadirachta indica A.Juss. , Zingiber officinale Roscoe, and Allium sativum L. monographs were published by all three pharmacopoeias. Conclusions Preclinical evidence of safety and efficacy exists in the literature for most of the plants used to manufacture registered herbal products in Uganda. More specific bioassays and clinical trials are required for the products to provide conclusive evidence of safety and toxicity. Monographs are urgently needed for the Ugandan plants.
Diagnostic performance of synthetic magnetic resonance imaging in the prognostic evaluation of rectal cancer.

Background Numerous factors are related to the prognosis of rectal cancer, including T stage, N stage, metastasis, extramural venous invasion (EMVI), circumferential resection margin (CRM), and tumor differentiation. However, it is still a challenge to precisely evaluate them before therapy; therefore, we investigate whether synthetic magnetic resonance imaging and apparent diffusion coefficient (ADC) values could help predict the prognostic factors of rectal cancer. Methods Eighty-seven patients (55 men and 32 women; mean age, 59±11 years) with pathologically confirmed rectal cancer were enrolled. Preoperative quantitative metrics, including T1, T2, proton density (PD), and ADC values, were measured with diffusion-weighted imaging (DWI) acquired by a single-shot echo-planar sequence and synthetic magnetic resonance imaging acquired by a multi-dynamic multi-echo sequence at 3.0 T, in patients with rectal cancer by two radiologists. We evaluated the diagnostic performance of synthetic magnetic resonance imaging using the independent sample t-test or Mann-Whitney U test and receiver operating characteristic (ROC) curve and multivariate logistic regression analyses and compared the area under the ROC curve of quantitative values using the DeLong test. Results The T2 and PD values showed a significant reduction among patients with poor differentiation and lymph node metastasis in rectal cancer. The area under the ROC curve values of T2 and PD values for predicting magnetic resonance imaging N stage and differentiation were 0.734, 0.682, and 0.673, 0.686, respectively. Moreover, combining T2 and PD values for magnetic resonance imaging N stage slightly improved the area under the ROC curve value of 0.774 (95% CI, 0.673-0.876). In the present study, the ADC and T1 values were not significant in the differentiation or clinical stage of rectal cancer (RC). Conclusions Quantitative T2 and PD values obtained by synthetic magnetic resonance imaging might be used for evaluating prognostic factors of rectal cancer noninvasively. Furthermore, combining T2 and PD values further improved the diagnostic performance of magnetic resonance imaging N staging in rectal cancer. The ADC and T1 values were not significant in the differentiation or clinical stage of RC.
A new parametric 3D human body modeling approach by using key position labeling and body parts segmentation

The current three-dimensional human models used in the apparel industry are mostly rigid and lack semantic information on body positions and body parts. Therefore, it is difficult for designers to make accurate, fast and effective designs from these models. This paper proposes a new parametric three-dimensional human body model based on key position labeling and optimized body parts segmentation. First, by using experts’ professional knowledge, we manually realize accurate human body data measurements as well as their interpretation and classification, and extract relevant human body features. After deep analysis, measured data irrelevant to body shape have been excluded by designers. Furthermore, the relation between body shapes and body features have been modeled. Second, based on this relational model, we label key positions on the corresponding three-dimensional body model obtained by scanning and segmenting the whole three-dimensional human body into semantically interpretable body parts. In this way, two databases have been created, enabling us to identify features of all segmented body parts, whose combination corresponds to the whole body shape. Third, for a specific consumer, his/her personalized three-dimensional human model can be obtained by taking a very few number of body measurements on himself/herself, making an appropriate combination of the identified body parts, and adjusting parameters of all involved body parts. By comparing the proposed labeled and segmented three-dimensional human model and the existing human models through a number of experiments, the proposed model leads to more relevant results with high accuracy and high visual quality related to real human body shapes.
The Investigation and Comparison of Sensory Attributes of Smear-Ripened and Mold-Ripened Cheeses

The objectives of this review are to be aware of the differences between the smear-ripened and mold-ripened cheeses and to compare the sensory attributes of smear-ripened and blue-vein cheeses. Sensory attributes of cheese occupy a prominent place for the desirable overall quality of smear-ripened and blue-vein cheeses. Smear-ripened cheeses characterized by a smooth and brittle texture. Furthermore, smear-ripened cheeses have common grittiness characteristics, also slightly salty and sour flavor compared to blue-vein cheeses. Blue-vein cheeses are characterized by a softer, creamy texture and stronger smells when goat milk is used. Blue-vein cheeses have a fresh, clean, somewhat salty and acid with a slightly bitter tastes compared to smear-ripened cheeses. Finally, the differences in sensory attributes of smear-ripened and blue-vein cheeses such as texture, aroma, and flavor, can make them useful to determine the quality of cheeses. ■ keyword :∣Cheese∣Sensory Attributes∣Smear-ripened∣Mold-ripened∣Consumer References∣ 한국콘텐츠학회논문지 '19 Vol. 19 No. 4 676
Differential Hydraulic Properties and Primary Metabolism in Fine Root of Avocado Trees Rootstocks

Avocados (Persea americana Mill.) are one of the crops with the highest water footprints in Chile and the production is at risk due to severe and frequent droughts. The current production is mostly based on sexually (seed) propagated rootstocks, while clonally propagated rootstocks are on the rise. In a recent study, we found differences in aerial, root growth and water use efficiency between trees grown on these two different rootstocks under controlled continuous fertigation and environmental conditions. In this study, we further describe possible mechanisms which drive the differences. Avocado cv. “Hass” grafted on “Dusa” (D, clonally propagated) and “Mexicola” (M, sexually propagated) rootstocks and different root segments (3, 5 and 8 cm from root tip) were investigated using a combination of hydraulic measurements and polar metabolite (GC-MS) techniques. The results show significant differences in root hydraulic properties, indicating that “Mexicola” fine roots have higher water uptake capacity. The polar metabolites analysis revealed 13 compounds significantly different between rootstocks while nine were found significantly different among root segments. Principal component analysis (PCA) revealed differences between rootstocks and root segments. The data presented here highlight the importance of considering key physiological knowledge in avocado rootstocks breeding programs to be better prepared for future challenging environmental conditions.
EXTENDING THE APPLICABILITY OF INEXACT GAUSS–NEWTON METHOD FOR SOLVING UNDERDETERMINED NONLINEAR LEAST SQUARES PROBLEMS

The aim of this paper is to extend the applicability of Gauss-Newton method for solving underdetermined nonlinear least squares prob- lems in cases not covered before. The novelty of the paper is the introduction of a restricted convergence domain. We ﬁnd a more precise location where the Gauss-Newton iterates lie than in earlier studies. Consequently the Lipschitz constants are at least as small as the ones used before. This way and under the same computational cost, we extend the local as well the semilocal convergence of Gauss-Newton method. The new develop- mentes are obtained under the same computational cost as in earlier studies, since the new Lipschitz constants are special cases of the constants used before. Numerical examples further justify the theoretical results.
Beta and Alpha Regularizers of Mish Activation Functions for Machine Learning Applications in Deep Neural Networks

A very complex task in deep learning such as image classification must be solved with the help of neural networks and activation functions. The backpropagation algorithm advances backward from the output layer towards the input layer, the gradients often get smaller and smaller and approach zero which eventually leaves the weights of the initial or lower layers nearly unchanged, as a result, the gradient descent never converges to the optimum. We propose a two-factor non-saturating activation functions known as Bea-Mish for machine learning applications in deep neural networks. Our method uses two factors, beta (β) and alpha (α), to normalize the area below the boundary in the Mish activation function and we regard these elements as Bea. Bea-Mish provide a clear understanding of the behaviors and conditions governing this regularization term can lead to a more principled approach for constructing better performing activation functions. We evaluate Bea-Mish results against Mish and Swish activation functions in various models and data sets. Empirical results show that our approach (Bea-Mish) outperforms native Mish using SqueezeNet backbone with an average precision (AP50val) of 2.51% in CIFAR-10 and top-1accuracy in ResNet-50 on ImageNet-1k. shows an improvement of 1.20%.