Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of different levels of iron sulfate on some haematological parameters of ship sturgeon, Acipenser nudiventris

The present study was conduct to examine different dietary levels of iron (FeSo4) on some haematological parameters of Ship sturgeon, Acipenser nudiventris including red blood cells (RBC), white blood cells (WBCs), differential WBCs, hematocrit (Hct), Hemoglobin (Hb), the mean corpuscular hemoglobin (MCH) and the mean corpuscular hemoglobin concentration (MCHC), the mean corpuscular volume (MCV), immunoglobulin (IgM), ferritin, transferrin and plasma Fe2+. Four experimental treatments and one control group with three replicates were considered for the experiment. The experimental treatments were fish fed by experimental diets containing different levels of FeSo4 i.e. 100, 200, 250, and 300 mg/kg diet. After 60 days, there were significant differences between experimental groups in terms of WBCs, lymphocytes, neutrophils, monocytes, eosinophils, MCH and MCHC, MCV, total plasma protein, IgM, ferritin, transferrin and plasma Fe2+ (P<0.05). In 100 mg.iron/kg.diet treatment, more levels of IgM and total plasma protein were observed compared to other experimental groups (P<0.05). The highest values of neutrophils, monocytes and MCHC were found in control fish whereas MCV, MCH and eosinophils values were higher in 200 mg iron/kg.diet treatment (P<0.05). Also, more WBCs were observed in 250 mg.iron/kg.diet treatment than in other groups (P<0.05). The values of lymphocytes, RBC, Hct, Hb, ferritin, transferrin and plasma Fe2+ were higher in fish fed by 300 mg.iron/kg.diet compared to other experimental groups (P<0.05). In conclusion, our results showed that the supplementation of ship sturgeon diet with high levels of iron enhances the RBC, Hct, Hb, ferritin, transferrin and plasma iron.
Prediction and comparison of the impact of COVID-19 epidemic on the financial industry of major countries based on neural intelligent algorithm

The global economy appears the trend of anti-globalization under the influence of COVID-19. Based on the input-output table of lead database from 2006 to 2020, this paper divides the factors that affect the development of financial industry in China, the United States and Russia into six aspects: price, intermediate input, household consumption, government consumption, export and import. ADGA-BP neural network model is proposed in this paper, which is based on six aspects of price, intermediate input, consumer, government consumption, export and import. The intermediate input is decomposed from the perspective of industrial structure to study the interrelationship between financial industry and other industries in the three countries. The results show that the intermediate input is the main factor in the development of financial industry in the three countries, but the source industries of the intermediate input are not the same; the two factors of household consumption and price are closely related to the development of financial industry in the three countries, and they all play a role in promoting China, while the relationship between household consumption and the United States and between price and Russia is reverse; Government consumption only has a significant impact on Russia; from the perspective of mutual influence, the mutual investment between the financial industry of China and the United States is relatively large, while the relationship between the Russian financial industry and the two countries is relatively weak. It shows that under the background of covid-19, the development of financial industry is affected.
Investigative biological therapies for primary Sjögren’s syndrome

Primary Sjögren’s syndrome (pSS) is a chronic, systemic autoimmune disease characterized by dryness of the eyes and mouth. The histological feature is mononuclear cell infiltration in exocrine glands, primarily salivary and lachrymal glands. As the disease progresses, some other tissues and organs may be involved and extraglandular manifestations ensue. The major current treatments are palliative and empirical, and in most cases the outcomes are not satisfactory. Emerging data indicate a critical role of lymphocytes in its development and progression. While pioneering work targeting B cells has demonstrated some encouraging results, more trials are warranted to validate the safety and efficacy. In addition, modulation of T cell function with abatacept ameliorates the severity of pSS. Furthermore, clinical trials to inhibit important cytokines involved in its formation have been carried out. In this article, we summarize and compare current biological therapies in order to find new and effective treatments for pSS.
Experiments on a two–dimensional laminar separation bubble

A two–dimensional separation bubble on a flat plate is studied experimentally by means of hot–wire anemometry and flow visualization. Separation of the laminar boundary layer on the plate is caused by an adverse pressure gradient imposed by a curved wall opposite to the plate. The instability of, and transition process in, the separation bubble are focused on. The bubble is found to be highly susceptible to high–frequency two–dimensional instability waves, which are studied under both natural and forced conditions. A similar development of these instability waves in the separation bubble is found in both cases. The exponential growth of the two–dimensional disturbances dominates the flow except for in the reattachment region, where large–scale three–dimensional structures appear. Some difficulties associated with experimental investigations of boundary–layer separation–bubble flows are discussed.
DeepMDP: A Novel Deep-Learning-Based Missing Data Prediction Protocol for IoT

Internet-of-Things (IoT) devices generate a vast amount of sensing data. The reliability of this data is a vital issue to ensure IoT service quality. However, IoT data usually suffers from missing and incomplete values due to various reasons, such as noise, collision, unstable network communication, equipment failure, and manual system closure. Transferring all IoT data to the cloud level to solve missing data problem may negatively affect network performance and service quality due to excessive latency, bandwidth limitation, and high communication costs. Therefore, missing data problem should be taken care of as early as possible by offloading tasks, such as data prediction or estimation closer to the edge devices in the network. In this article, we propose a missing data prediction protocol called DeepMDP for IoT systems with unreliable data sources, which can reduce the amount of data transmission and delay in the network significantly. The proposed protocol can work on resource-constrained IoT devices as well as fog and cloud servers. Besides, to evaluate the proposed protocol, we design a real-world testbed architecture called DeepArch consisting of edge, fog, and cloud layers. Under several application scenarios, we evaluate the efficiency of DeepMDP on the DeepArch platform. The experimental results show that the proposed protocol can significantly reduce the amount of data transmission and delay while accurately predicting missing data.
Viabilidade de diferentes taxas de alimentação para o cultivo de Astyanax bimaculatus

The objective of this study was to evaluate the growth performance and cost of Astyanax bimaculatus (yellow tail lambari) fed with different feeding rates. For such, 720 (4.06 ± 0.33 g) juvenile fish were fed with four different feeding rates (2.5, 4.0, 5.5, and 7.0% of biomass). After six weeks, growth performance and cost of the fish produced (in kg) were evaluated. Fish fed with 4.0 and 5.5% of the biomass showed the best growth performance and financial results; thus, these feed rates are the most attractive for Astyanax bimaculatus culture.
Technology for Product Design Knowledge Need Awareness Based on Design Context and Brain-computer Interface

： Aiming at the problem of automatic acquisition of designers’ knowledge needs during knowledge push process, a product design knowledge need awareness based on design context and brain-computer interface is proposed. The design knowledge need awareness framework is constructed based on design context and brain-computer interface. The design context is generated using dynamically captured design activity information. The design knowledge need domain is constructed based on brain-computer interface. The knowledge need anchor points are established according to the mapping relationship between design task and product structure, and current design content is obtained using design context to activate corresponding knowledge need anchor point. The types of knowledge needs are recognized by weighted Bayesian method. The proposed knowledge need awareness method is verified in the process of CNC machine tool digital design.
Computation of statistical solutions of hyperbolic systems of conservation laws

Statistical solutions are time-parameterized probability measures on spaces of integrable functions, that have been proposed recently as a framework for global solutions and uncertainty quantification for multi-dimensional hyperbolic system of conservation laws. By combining highresolution finite volume methods with a Monte Carlo sampling procedure, we present a numerical algorithm to approximate statistical solutions. Under verifiable assumptions on the finite volume method, we prove that the approximations, generated by the proposed algorithm, converge in an appropriate topology to a statistical solution. Numerical experiments illustrating the convergence theory and revealing interesting properties of statistical solutions, are also presented. We furthermore show that the multi-level Monte Carlo algorithm converges in the weak topology, and provide testable conditions for when the multi-level Monte Carlo algorithm outperforms the Monte Carlo algorithm. Finally we present the Alsvinn simulator, a fast multi general purpose graphical processing unit (GPGPU) finite volume solver for hyperbolic conservation laws in multiple space dimensions. Alsvinn has native support for uncertainty quantifications, and exhibits excellent scaling on top tier compute clusters.
Assessing and Validating Bank Customers Using Data Mining Algorithms for Loan Home

All over the world, the banking industry is one of the most important pillars ofnany country's economy and due to the provision of various financial and creditnservices, it plays a decisive role in the development and economic growth ofnthe country And it can be described as the driving force that accelerates,nbalances, and organizes the economy. Given that banks' capital is less than thentotal value of their assets, even if a percentage of the loans are not receivable,nBanks face bankruptcy risk. In order to reduce the volume of claims, Validationnof loan applicants can be very effective. Data mining techniques andnalgorithms are one of the methods of validating bank customers. In this study,nconsidering the current and past data of bank customers To receive Loanfacilities analyzed by data mining algorithms such as Decision trees, KNN,nSVM and Random Forest to identify good and bad customers. Finally, thenability of these algorithms to validate banking customers will be examined.According to the results, Random forest algorithm has a better ability toclassify customers.
Biological parameters of Spodoptera cosmioides Walker (Lepidoptera: Noctuidae) in cotton varieties

Arq. Inst. Biol., v.87, 1-7, e0352019, 2020 RESUMO: Spodoptera cosmioides Walker é uma espécie polífaga, resistente a inseticidas em várias regiões do país e, apesar de ocorrer em baixas densidades, é considerada uma praga potencial para as culturas de algodão, soja e feijão no cerrado. Neste trabalho, estudou-se a biologia comparada de S. cosmioides sobre o cultivar transgênico comercial de algodoeiro NuOPAL (Bollgard I, Evento 531) e sobre o cultivar isolinha convencional DeltaOPAL. O experimento foi desenvolvido em condições de laboratório (26 ± 1°C; UR: 70 ± 10%; fotofase: 12h) a partir de lagartas recém-eclodidas e individualizadas. Foram avaliados a duração e a viabilidade das fases imaturas, a duração do ciclo biológico, o peso de pupas, a razão sexual, a porcentagem de deformação de adultos e de adultos não liberados dos invólucros pupais, a longevidade de adultos, a fecundidade e viabilidade de ovos. Os parâmetros biológicos observados não diferiram significativamente em relação às duas cultivares, que proporcionaram alto consumo, alta assimilação, alta fecundidade e viabilidade à S. cosmioides.
De novo Microbial Biosynthesis of a Lactate Ester Platform

Green organic solvents such as lactate esters have broad industrial applications. Manufacturing and use of these biodegradable solvents from renewable feedstocks help benefit the environment. This study presents a microbial conversion platform for direct fermentative biosynthesis of lactate esters from fermentable sugars. To enable the de novo microbial biosynthesis of lactate esters, we first designed a sugar-to-lactate ester module, consisting of a lactate dehydrogenase (ldhA), a propionate CoA-transferase (pct), and an alcohol acyltransferase (AAT) to convert sugar to lactate esters. By generating a library of five sugar-to-lactate ester modules with divergent AATs, we screened for the best module(s) capable of producing a wide range of linear, branched, and aromatic lactate esters with an external alcohol supply. By co-introducing a sugar-to-lactate ester module and an alcohol (i.e., ethanol, isobutanol) module into a modular Escherichia coli (chassis) cell, we demonstrated for the first time the de novo microbial biosynthesis of ethyl and isobutyl lactate esters directly from glucose. In an attempt to enhance ethyl lactate production as a proof-of-study, we re-modularized the pathway into the upstream module to generate the ethanol and lactate precursors and the downstream module to generate lactyl-CoA and condense it with ethanol to produce the target ethyl lactate. By manipulating the metabolic fluxes of the upstream and downstream modules though plasmid copy numbers, promoters, ribosome binding sites, and environmental perturbation, we were able to probe and alleviate the metabolic bottlenecks by improving ethyl lactate production by 4.96-fold.
A CPW-FED TRIBAND ANTENNA FOR 2.4/3.5/5.5 GHZ APPLICATIONS

A novel and compact CPW-fed triband antenna suitable to support WLAN and WiMAX communications in 2.4/3.5/5.5 GHz bands is reported. The 5.5 GHz band extends from 4.9 to 5.94 GHz. So the proposed antenna can support the use of 4.94–4.99 GHz band allotted for fixed and mobile service (except aeronautical mobile service) for use in support of public safety and 5.85–5.925 GHz band for Dedicated Short-Range Communications (DSRC) services in the Intelligent Transportation System (ITS) radio service. Metallic radiating stub extending from the feed is used to excite the resonance at 2.4 GHz. An open slot in the stub and a pair of open slots in ground plane are used to excite the other resonances. An arc shaped parasitic element is also included in the design for improved radiation performance. The proposed antenna geometry is developed on FR4 glass epoxy substrate with relative permittivity 3.8 and loss tangent 0.02. The geometry is developed and optimized using High Frequency Structure Simulator and experimentally validated the results. Performance comparison of the proposed antenna with similar antennas in literature is presented. Measured radiation patterns and gain are also included in this paper.
New Technologies in Marketing as Competitive Advantage

Sophisticated technology is drastically changing the society including consumer behaviour and their purchasing patterns. Many companies are already actively combining IoT technology, mobile applications, smart home appliances and other consumer electronics devices in multiple marketing communication channels. Marketing Managers are increasingly starting to direct company's communication towards modern marketing channels such as mobile and online with traditional channels slowly being replaced. New technologies in retail marketing, such as NFC and Bluetooth LE, offer a wide range of opportunities for reaching consumers in various creative ways. Soon, integrated multi-channel marketing strategies will include a seamless flow of personalized brand's messages through a number of inter-connected channels. By recognizing the value of new technologies in marketing and by implementing them, companies can achieve strong competitive advantage and a greater return on investment.
Development Roadmap of Polymorphic Intelligence Network Technology Toward 2035

: The current infrastructure and technology systems of the Internet are facing major challenges in terms of intelligence, diversification, personalization, robustness, and efficiency. Thus, changing the network infrastructure and building a polymorphically definable intelligent network requires immediate attention. This work studies and determines the development trend in network technologies in China and abroad, proposes the development goal of a polymorphically definable intelligent network, and extracts a list of key cutting-edge technologies for future consideration. Based on these, a development roadmap is constructed for a polymorphically definable intelligent network in China for 2035. China should seek the research and development of key technologies, including network architecture, addressing and routing, full-dimensional definability, network intelligence, and network robust control, and guide the development of relevant industries through key contents, including core chips, products, and systems. Demonstration projects can be deployed to promote the implementation of intelligent network business, including projects concerning information infrastructure, vertical industry networks, space–earth integrated networks, and ubiquitous interconnections between humans and things. In addition, this paper proposes some suggestions on the guarantees of polymorphic definable intelligent networks in China from the perspectives of policy guarantee, scientific research platform support and joint research, international communication expansion, and human resource cultivation and employment.
La participation bien comprise

Le concept de participation, au cœur de l’ideal democratique, se decompose en trois moments : prendre part (s’engager), apporter une part (contribuer) et recevoir une part (reconnaissance). Ils peuvent servir de criteres a l’enquete sociale et permettent d’identifier differentes varietes d’injustice.
Identification of Geometric Parameters Influencing the Impedance Sensitivity of Piezoelectric Mass Sensors

For resonant mass sensors, a frequency sweeping procedure is usually required to identify the frequency shift in a relative frequency range, which is not suitable for detecting incremental mass. The impedance detection method can measure mass at a fixed frequency. To further explore such sensing mechanism, the main geometrical parameters influencing the impedance sensitivity have been carefully analyzed considering the electro-mechanical coupling effects, and a series of design rules have been proposed for improving sensitivity, e.g. increasing the cantilever length and piezoelectric thickness, which is contrary to the traditional method of minimizing the geometric size for frequency based sensors. Three macro-sized sensors with 21.0 mm, 26.0 mm and 30.0mm long cantilevers are fabricated, and the measured impedance sensitivities are <inline-formula> <tex-math notation="LaTeX">$212.7\Omega $ </tex-math></inline-formula>/mg, <inline-formula> <tex-math notation="LaTeX">$514.8\Omega $ </tex-math></inline-formula>/mg and <inline-formula> <tex-math notation="LaTeX">$737.4\Omega $ </tex-math></inline-formula>/mg that are increasing with the cantilever length, thus validating the design rules on cantilever length. However, the frequency sensitivities are 14.0 Hz/mg, 9.2 Hz/mg, and 7.2 Hz/mg that are decreasing with the cantilever length. Furthermore, the impedance sensitivity is much higher than the frequency sensitivity, and the design map of the sensor is presented as an overall guideline for structure optimization.
The Demographic and Economic Determinants of Financial Sustainability: An Analysis of Italian Local Governments

The aim of this study was to analyze the influence of demographic and economic variables on financial sustainability in Italian local governments (ILGs). Many international organizations have highlighted the importance of pursuing financial sustainability, and identifying what the factors impacting financial sustainability are, allowing to manage risk and opportunities as well as to support the decision-making process better. A total of 104 ILGs with more than 60,000 inhabitants were investigated for the year 2018. The adjusted income statements served as the dependent variable of a regression model for testing several demographic and economic variables. The results showed that demographic factors did not influence financial sustainability while, regarding the economic variables, there was a negative influence of financial autonomy and positive influence of the level of indebtedness. These values indicate a pathological scenario where local governments pursue short-term strategies that will impact future generations.
Quality of seeds and seedlings of Cedrela fissilis Vell. due to the biometry of berry and seeds in different origins

Cedrela fissilis is a Brazilian native species with outstanding use in the timber sector and in the recovery of degraded areas. There is a need for a better understanding of the differences and genetic gains that may exist in relation to different origins and progenies. The objective of the study was to analyze the biometry of fruits and seeds of Cedrela fissilis as a function of different origins and matrices related to the initial growth of seedlings, besides evaluating the best photoperiod in germination. The seeds were collected in matrices from two sources (Fernandes Pinheiro and Lapa) for biometry and the weight of one thousand seeds per matrix. Seeds of the two provenances were submitted to different photoperiods (12, 16 and 24 hours of white light and 24 hours in the dark), the germination and the germination rate index (ORI) was evaluated. The initial growth of the seedlings was evaluated through the measurement of morphological characteristics after every 30 days. The experiments were performed in a completely randomized design and the data submitted to analysis of variance at the 5% level, the averages being compared by the Tukey test and/or polynomial regression. There were biometric differences between fruits and seeds between the matrices, with no relation to the origin. Regarding the germination rate and ORI among the
Design and Analysis of a New Permeability-Modulated Interior Permanent-Magnet Synchronous Machine

In this article, to improve the adjustment ability of air gap flux, a new interior permanent magnet (IPM) synchronous machine with permeability modulation characteristics is proposed for electric vehicles’ (EVs) potential applications. The main trait of the machine structure is that a bridge between the rotor poles is intentionally established, which can produce a smooth magnetic path for the leakage flux. Thus, the flux leakage state can be adjusted by controlling the magnetic saturation of the bridge according to the machine load current. To clarify this feature, the machine performances are investigated by theoretical analysis and finite-element method. Finally, the designed machine is manufactured and its performances are verified by experiments. Both the simulation and experimental results prove that the torque of the proposed machine under loaded conditions can be flexibly adjusted by the magnetic permeability modulation without any complex control strategy.