Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding Marine Biodegradation of Bio-Based Oligoesters and Plasticizers

The study reports the enzymatic synthesis of bio-based oligoesters and chemo-enzymatic processes for obtaining epoxidized bioplasticizers and biolubricants starting from cardoon seed oil. All of the molecules had MW below 1000 g mol−1 and were analyzed in terms of marine biodegradation. The data shed light on the effects of the chemical structure, chemical bond lability, thermal behavior, and water solubility on biodegradation. Moreover, the analysis of the biodegradation of the building blocks that constituted the different bio-based products allowed us to distinguish between different chemical and physicochemical factors. These hints are of major importance for the rational eco-design of new benign bio-based products. Overall, the high lability of ester bonds was confirmed, along with the negligible effect of the presence of epoxy rings on triglyceride structures. The biodegradation data clearly indicated that the monomers/building blocks undergo a much slower process of abiotic or biotic transformations, potentially leading to accumulation. Therefore, the simple analysis of the erosion, hydrolysis, or visual/chemical disappearance of the chemical products or plastic is not sufficient, but ecotoxicity studies on the effects of such small molecules are of major importance. The use of natural feedstocks, such as vegetable seed oils and their derivatives, allows the minimization of these risks, because microorganisms have evolved enzymes and metabolic pathways for processing such natural molecules.
Rapid, early, and potent Spike-directed IgG, IgM, and IgA distinguish asymptomatic from mildly symptomatic COVID-19 in Uganda, with IgG persisting for 28 months

Introduction Understanding how spike (S)-, nucleoprotein (N)-, and RBD-directed antibody responses evolved in mild and asymptomatic COVID-19 in Africa and their interactions with SARS-CoV-2 might inform development of targeted treatments and vaccines. Methods Here, we used a validated indirect in-house ELISA to characterise development and persistence of S- and N-directed IgG, IgM, and IgA antibody responses for 2430 SARS-CoV-2 rt-PCR-diagnosed Ugandan specimens from 320 mild and asymptomatic COVID-19 cases, 50 uninfected contacts, and 54 uninfected non-contacts collected weekly for one month, then monthly for 28 months. Results During acute infection, asymptomatic patients mounted a faster and more robust spike-directed IgG, IgM, and IgA response than those with mild symptoms (Wilcoxon rank test, p-values 0.046, 0.053, and 0.057); this was more pronounced in males than females. Spike IgG antibodies peaked between 25 and 37 days (86.46; IQR 29.47-242.56 BAU/ml), were significantly higher and more durable than N- and RBD IgG antibodies and lasted for 28 months. Anti-spike seroconversion rates consistently exceeded RBD and nucleoprotein rates. Spike- and RBD-directed IgG antibodies were positively correlated until 14 months (Spearman’s rank correlation test, p-values 0.0001 to 0.05), although RBD diminished faster. Significant anti-spike immunity persisted without RBD. 64% and 59% of PCR-negative, non-infected non-contacts and suspects, exhibited baseline SARS-CoV-2 N-IgM serological cross-reactivity, suggesting undetected exposure or abortive infection. N-IgG levels waned after 787 days, while N-IgM levels remained undetectable throughout. Discussion Lower N-IgG seroconversion rates and the absence of N-IgM indicate that these markers substantially underestimate the prior exposure rates. Our findings provide insights into the development of S-directed antibody responses in mild and asymptomatic infections, with varying degrees of symptoms eliciting distinct immune responses, suggesting distinct pathogenic pathways. These longer-lasting data inform vaccine design, boosting strategies, and surveillance efforts in this and comparable settings.
Dust in the core of the metal-rich globular cluster NGC 6356

We report the 3. 5σ detection of dust in the core of the metal-rich ([Fe/H] =−0.4) globular cluster NGC 6356. The dust mass in the core is ∼ 4–17 × 10−3 M⊙, depending on the dust equilibrium temperature. We rule out sputtering as a grain destruction mechanism in NGC 6356, unless grains are very small (∼30 A). We also place the upper limit of 6.6 × 10−3 on the CO-to-dust ratio in this cluster. This value is significantly smaller than the CO-to-dust ratio in the general Galactic interstellar medium, and in the outflows of evolved stars.
Botanical investigation of goats pastures on natural and replanted grasslands

There are new challenges for global agriculture due to the changing circumstances in natural and economical world. Many professionals mentioned that our current agricultural methods not suitable to produce proper amount and quality foods. We have to change from the conventional farming to a sustainable agriculture to reach a well performing global agriculture what consist local viable agro systems. The organic farming as one type of sustainable agriculture, is a developing sector where the market and economical competition is growing. There is an opportunity to produce high quality food without additives in Hungary based on the climate, good quality soil as well traditional plant and animal species. The hungarian government set better balance between animal husbandry and arable farming as target and focusing on family farming and organic farming.
Better Understanding of SN Ia from Near Infrared Observations

Abstract Type Ia supernovae (SN Ia) are explosions of white dwarfs whose distances can be measured to a precision of ~5% using luminosity information that is encoded in the light curve shape. This property has been very successfully exploited to measure the history of cosmic expansion and to infer the presence of dark energy. But to learn the properties of dark energy and determine whether it is different from the cosmological constant demands higher precision and better accuracy than optical light curves alone can provide. The largest systematic uncertainties come from light curve fitters, photometric calibration errors, and from poor knowledge of the scattering properties of dust along the line of sight. Efforts to use SN Ia spectra as luminosity indicators have had some success, but have not produced a big step forward. Fortunately, observations of SN Ia in the near infrared (NIR), from 1 to 2 microns, offer a very promising path to better knowledge of the Hubble constant, improved constraints on dark energy, and, possibly, a route to discriminating the progenitor paths for SN Ia explosions.
Energy-Efficient Collaborative Inference in MEC: A Multi-Agent Reinforcement Learning Based Approach

Collaborative inference enables mobile devices to offload the computation tasks and support computation-intensive perception services such as object detection with lower latency and higher energy efficiency. In the deep learning based perception in mobile edge computing (MEC), each mobile device has to choose the computation partition and the collaborative edge server. However, the optimal partition point and edge selection depend on the inference cost model of the specific deep learning architecture and the channel models from devices to edge servers, which are challenging to formulate in practical MEC. In this paper, we propose a multi-agent reinforcement learning based energy-efficient collaborative inference scheme for MEC to support perception services. The inference scheme applies multi-agent Q-learning to choose the partition point of the deep learning model and the collaborative edge server based on the state that consists of the task workload, the channel conditions, and the inference cost record. A Q-network on the central server approximates the long-term expected utilities or global Q-values under the states and policies of all mobile devices, which is the direction for each mobile device to update the Q-value under the local state-policy pair. Simulation results show that our proposed scheme reduces the inference latency and saves the total energy consumption for MEC.
Developing New High-Protein-Content Traditional-Type Greek Yoghurts Based on Jersey Cow Milk

In the past few years, Jersey cow milk has been considered an effective commodity for the production of dairy products, such as cheese and yoghurts, due to its high nutrient density. Initially, the microbial safety and physicochemical properties of pasteurized milk from Jersey cows raised in Evrofarma S.A. dairy facilities were monitored and compared to Holstein Friesian milk over a six-month period. Subsequently, a new traditional-type Greek yoghurt was prepared using Jersey cow milk andthe physicochemical, microbiological and sensory properties were monitored throughout its shelf time and compared to commercially available traditional-type Greek yoghurts made with Milk Protein Concentrate powder (MPC)-fortified Holstein Friesian milk. Our study confirmed the significantly higher fat (29.41%), protein (20.6%) and calcium content (19.9%) compared to Holstein Friesian milk. The new yoghurt demonstrated several technological advantages and shared similar physicochemical properties with the commercially available products. Importantly, high protein concentration (4.03 g/100 g) was documented without the addition of MPC. Finally, the new yoghurt was accepted during the preliminary sensory evaluation, while similar scores with the commercially available products were noted during the texture, flavour, aroma and overall quality assessment.
How Students Generate Patterns in Learning Algebra? A Focus on Functional Thinking in Secondary School Students

This research aims to describe secondary school students' functional thinking in generating patterns in learning algebra, particularly in solving mathematical word problems. In addressing this aim, a phenomenological approach was conducted to investigate the meaning of functional relationships provided by students. The data were collected from 39 ninth graders (13-14 years old) through a written test about generating patterns in linear functions. The following steps were conducting interviews with ten representative students to get detailed information about their answers to the written test. All students' responses were then analyzed using the thematic analysis software ATLAS.ti. The findings illustrate that students employed two types of approaches in solving the problem: recursive patterns and correspondence. Students favored the recursive patterns approach in identifying the pattern. They provided arithmetic computation by counting term-to-term but could not represent generalities with algebraic symbols. Meanwhile, students evidenced for correspondence managed to observe the relation between two variables and create the symbolic representation to express the generality. The study concludes that these differences exist due to their focus on identifying patterns: the recursive pattern students tend to see the changes in one variable, whereas the correspondence ones relate to the corresponding pair of variables.
Evaporative capillary instability for flow in porous media under the influence of axial electric field

We study the linear analysis of electrohydrodynamic capillary instability of the interface between two viscous, incompressible and electrically conducting fluids in a fully saturated porous medium, when the phases are enclosed between two horizontal cylindrical surfaces coaxial with the interface and, when there is mass and heat transfer across the interface. The fluids are subjected to a constant electric field in the axial direction. Here, we use an irrotational theory in which the motion and pressure are irrotational and the viscosity enters through the jump in the viscous normal stress in the normal stress balance at the interface. A quadratic dispersion relation that accounts for the growth of axisymmetric waves is obtained and stability criterion is given in terms of a critical value of wave number as well as electric field. It is observed that heat transfer has stabilizing effect on the stability of the considered system while medium porosity destabilizes the interface. The axial electric field has dual effect on the stability analysis.
Simplified intensity- and phase-modulated transmitter for modulator-free decoy-state quantum key distribution

Quantum key distribution (QKD) allows secret key exchange between two users with unconditional security. For QKD to be widely deployed, low cost and compactness are crucial requirements alongside high performance. Currently, the majority of QKD systems demonstrated rely on bulk intensity and phase modulators to generate optical pulses with precisely defined amplitude and relative phase difference—i.e., to encode information as signal states and decoy states. However, these modulators are expensive and bulky, thereby limiting the compactness of QKD systems. Here, we present and experimentally demonstrate a novel optical transmitter design to overcome this disadvantage by generating intensity- and phase-tunable pulses at GHz clock speeds. Our design removes the need for bulk modulators by employing directly modulated lasers in combination with optical injection locking and coherent interference. This scheme is, therefore, well suited to miniaturization and photonic integration, and we implement a proof-of-principle QKD demonstration to highlight potential applications.
The impact of digitalization on credit risk: the mediating role of financial inclusion (National Bank of Egypt (NBE) case study)

This article investigates potential direct and indirect impact of National Bank of Egypt (NBE) digitalization and its financial inclusion on credit risk. The methodology used in the study is an empirical technique through the collection of secondary data from the period between 2011 and 2021 in the Egyptian banking sector. To accomplish this, the study developed two hypotheses employing the empirical SEM model for testing whether there is a positive or negative impact for three chosen variables: digitalization, credit risk and financial inclusion. The investigational outcome shows that NBE digitalization has both direct and indirect impact through the mediator variable, financial inclusion. It also provides an understanding of the relationship between digitalization, credit and financial inclusion. The article proposes for future studies the impact of other Fintech factors directly and indirectly using the mediators on credit risk. The authors came up with many findings: first, financial inclusion indices can be built using portable money and banking services activities. Second, digitalization has a negative direct impact on credit risk. Also, digitalization has a positive indirect impact on credit risk through the mediator variable which is referred to as financial inclusion. Third, the model fit is adequate for the data being tested.
Effects of Shape and Scale in Mechanics of Elastic Interaction of Regular Rough Surfaces. a Theoretical Study

The formulation and solution of the plane problem of the elastic contact of surface roughness having two-scale regular asperities with a flat surface is considered. Small-scale asperities are simulated by special periodic curve with arbitrary waveform shape and large-scale asperities are simulated by a sine wave. On the basis of obtained solutions, the possible physical effects associated with the presence of arbitrary shaped small-scale asperities and roughness of larger scale in relation to calculation of elastic contact parameters are revealed.
A multi-angle analysis of injury induced by supplementation of soybean meal in Litopenaeus vannamei diets

Soybean meal is considered as one of the major components of Litopenaeus vannamei diets. However, most previous studies have focused on evaluating the effects of soybean meal on L. vannamei from the perspective of growth, physiology, and feed utilization; information regarding the analysis of serum metabolites, antioxidant and immune response, and intestinal microbiota is limited. Five diets were prepared, comprising 20% (T20), 28% (T28), 35% (T35), 42% (T42), and 50% (T50) soybean meal. A total of 600 shrimp were randomly distributed into 20 tanks (i.e., 30 shrimp per tank), with four tanks assigned to each dietary group. Shrimp were fed to apparent satiation during the 42-day feeding trial. The results showed that levels of serum globulin, alanine aminotransferase, and aspartate aminotransferase linearly increased (p < 0.01), but levels of high-density lipoprotein cholesterol linearly decreased (p < 0.001) as the proportion of soybean meal in the diet increased. Supplementation of shrimp diets with soybean meal linearly and quadratically increased (p < 0.05) serum total antioxidant capacity, levels of malondialdehyde, and activities of catalase, nitric oxide synthase and phenoloxidase. Hepatocytes in T35, T42, and T50 were shown to have different degrees of vacuolar degeneration, hepatic corpuscle atrophy, and star-like lumen loss. Dietary inclusion of soybean meal altered the composition of intestinal bacterial microbiota at phylum level, especially increasing the abundance of on other bacterial genera, whereas it had minimal impact on other bacterial genera and had no significant influence on the bacterial diversity. This study suggests that dietary supplementation of L. vannamei diets with soybean meal at concentrations exceeding 28% induces inflammation and oxidant damage of the hepatopancreas, and increases the risk of intestinal disease.
Asymptotic properties of the least-squares method for estimating transfer functions and disturbance spectra

The problem of estimating the transfer function of a linear system, together with the spectral density of an additive disturbance, is considered. The set of models used consists of linear rational transfer functions and the spectral densities are estimated from a finite-order autoregressive disturbance description. The true system and disturbance spectrum are, however, not necessarily of finite order. We investigate the properties of the estimates obtained as the number of observations tends to ∞ at the same time as the model order employed tends to ∞. It is shown that the estimates are strongly consistent and asymptotically normal, and an expression for the asymptotic variances is also given. The variance of the transfer function estimate at a certain frequency is related to the signal/noise ratio at that frequency and the model orders used, as well as the number of observations. The variance of the noise spectral estimate relates in a similar way to the squared value of the true spectrum.
Asymptotic descriptions of oblique coherent structures in shear flows

Exact coherent states in plane Couette flow are extended to an oblique parallelogram computational domain and the large-Reynolds-number asymptotic descriptions of the states are derived. When the tilt angle of the domain is increased, the states first obey vortex–wave interaction theory and then develop a new asymptotic structure. The latter asymptotic structure is characterized by a self-similar nonlinear interaction localized in the fluid layer. For the largest scale of the self-similar nonlinear structure, the theory predicts an inverse Reynolds number dependence for the tilt angle of the oblique pattern. That result is consistent with the numerical and experimental observations of the laminar–turbulent banded pattern in shear flows.
Intelligent priority based generation control for multi area system

ABSTRACT Increased innovation and automation for higher comfort level of living beings have stressed power sector for more units of power to be generated and supplied. To meet this demand, several generating stations are needed to be connected to supply this enormous load to end consumers. While interconnecting generated power of multi-area system, several problems are being encountered. In the current proposed work, 2-area interconnected power system has been considered and automatic generation control problem for single area loading and multi-area multi-type loading has been solved with the help of intelligent control strategy using TLBO algorithm. The proposed work has been processed and simulated in MATLAB and SIMULINK environment. Three types of loadings are considered in the proposed work. First one is single area fixed loading, second one is both area loading with different fixed load, and third one is increasing type load for fixed duration of time in single area. Based on the nature of severity of disturbances in power network, a fitness function has been designed for these multi-type of loadings to improve its transient response to avoid failure of synchronism and improve resiliency of power network to supply uninterrupted power to end consumers.
Stable generalization of convex functions

A kind of generalized convex functions is said to be stable with respect to some property (P) if this property is maintaincd during an arbitrary function from this class is disturbed by a linear functional with sufficiently small norm. Unfortunately. known generallzed convexities iike quasicunvexity, explicit quasiconvexity. and pseudoconvexity are not stable with respect to such optimization properties which are expected to be true by these generalizations, even if the domain ol the functions is compact. Therefore, we introduce the notion of s-quasiconvex functions. These functions are quasiconvex, explicitly quasicon vex. and pseudoconvex if they are continuously differentiable. Especially, the s-quasiconvexity is stable with respect to the following important properties: (Pl) all lower level sets are convex, (P2) each local minimum is a global minimum. and (P3) each stationary point is a global minimizer. In this paper, different aspects. of s–quasiconvexity and its stability are investigated.
The nexus between spatial structure and labour income: evidence from Vietnam

ABSTRACT Studies on spatial structure features and their influence are increasingly receiving great attention from scholars and policymakers as they play an essential role in any geographical area’s planning and economic development. Therefore, this study analyses the specific impact of spatial structure on labour income in a typical case in Vietnam. Using instrumental variables combined with two-stage least squares regression analysis (TSLS), the results from the study show the specific effects of spatial structure on labour income. Urbanization externalities are reflected in the size of the urban population, which positively impacts the labour income in the region. In contrast, the population dispersion in the decentralized model brings negative impacts. Besides, when the spatial structure of localities tends to be highly polycentric, it will have a negative impact on labour income; however, this effect is dominated by the size of the urban population.