Miracle-dz/UniFAR-FTUs huggingface dataset:
eIF2B Bodies and their Role in the Control ofProtein Synthesis

The eukaryotic initiation factor 2B (eIF2B) serves as a vital control point within translation initiation. eIF2B initiates translation by exchanging GDP for GTP on eIF2. However, this mechanism may be attenuated in response to cellular stress by the phosphorylation of eIF2, which paradoxically enhances the translation of stress-specific mRNA to instigate a stress response. Autosomal recessive mutations within eIF2B result in the disease leukoencephalopathy with vanishing white matter (VWM). Current models of VWM disease suggest that abnormal eIF2B results in the cell being in a constant state of stress. However, previous biochemical studies have illustrated that VWM mutations not only decrease the catalytic activity of eIF2B, but can increase activity or not affect it at all. Furthermore, changes in the activity eIF2B do not correlate with disease severity. These observations suggest that there may be additional characteristics of eIF2B contributing to VWM pathogenesis which remain to be elucidated. In this study, we investigated whether the localisation of eIF2B to eIF2B bodies was integral for function. Using the yeast S. cerevisiae, we show that the regulatory subunit eIF2Bα is required for localisation. Interestingly, catalytic mutations in eIF2Bα localised eIF2B to several smaller foci, termed microbodies. In vivo FRAP analysis highlighted that eIF2 shuttles through microbodies slower than eIF2B bodies, indicating that localisation to eIF2B bodies may be required for full eIF2B activity. Surprisingly, phenotypes from eIF2Bα VWM missense mutations were highly variable in localisation, possibly recapitulating variable phenotypes observed in humans. The putative membrane proteins Mst27p, Erp4p and Sac1p have been shown to associate with eIF2B. We therefore investigated whether they were required for the formation of eIF2B bodies. Deletion of membrane proteins did not significantly alter eIF2B localisation. Surprisingly however, deletion of the PI(4)P Sac1p reduced rates of translation initiation independently of eIF2B, highlighting a link between membrane integrity and translational control.
Combating Biofilm Associated Infection In Vivo: Integration of Quorum Sensing Inhibition and Photodynamic Treatment based on Multidrug Delivered Hollow Carbon Nitride Sphere

Recently, quorum sensing (QS) inhibitors (QSIs) have been combined with antibiotics to enhance antibiofilm efficacy in vitro and in vivo. However, targeting QS signals alone is not enough to prevent bacterial infections. Drug resistance and recurrence of biofilms makes it difficult to eradicate. Herein, photodynamic therapy (PDT) is selected to unite QSIs and antibiotics. A synergistically antibiofilm system, which combines QSIs, antibiotics, and PDT based on hollow carbon nitride spheres (HCNSs) is envisaged. First, HCNS provides the multidrug delivering ability, enabling QSIs and antibiotics to be released in sequence. Subsequently, multistage releases sensitize bacteria effectively, potentiating the chemotherapeutic effects of the antibiotics. Finally, the integration of QSIs and PDT not only minimizes the possibility of drug resistance, but also overcomes the problem of limited mass and extension of PDT. Even after 48 h of incubation, the bacterial biofilm is obviously inhibited. And its biofilm disperse efficiency exceeds 48% (compared with QSI‐potentiated chemotherapy group) and 40% (compared with PDT group). Besides, the inhibition of the QS system influences phenotypes related to virulence factor production and surface hydrophobicity, which weaken biofilm invasion and formation. Eventually, this system is applied to disperse bacterial biofilm in vivo. Overall, PDT and QS modulation are devoted to eradicate drug resistance and recurrence of the biofilm.
A Note on Jain´s Digital Piracy Model: Horizontal vs Vertical Product Differentiation

We study how private intellectual property rights protection affects equilibrium prices and profits in a duopoly competition between firms that offer a product variety of distinct qualities (vertical product differentiation) in a setup that is closely related to that put forward by Jain (2008), where firms offer the same qualities in equilibrium (horizontal differentiation). Consumers may make a choice to buy a legal version, use an illegal copy (if they want to and can), or not use a product at all. Using an illegal version violates intellectual property rights protection and is thus punishable when disclosed. Thus, both private and public (copyright) intellectual property rights protection are available on scene.
Gravity Modeling of South Africa's Fruit Exports to Selected West African Countries

Exports are important drivers of economic growth and development. This study analyzed the factors influencing South Africa’s fruit exports to West African countries. The gravity model approach was used to analyse the data with panel data covering 1994 to 2016. The results showed that the model in its fixed effect panel data explained 60.5 percent of the fluctuations in South Africa’s fruits exports to West Africa. The results also indicate that imports’ GDP, population and South Africa’s production capacity had a positive association with South Africa’s fruit exports. On the other hand, the results indicated that importer’s Foreign Direct Investment, Ad-Valorem Equivalent, and inflation had negative impact on fruit exports. Therefore, the results suggest that South Africa should focus on its GDP and on countries with a growing GDP.
The EWMA Heston model

This paper introduces the exponentially weighted moving average (EWMA) Heston model, a Markovian stochastic volatility model able to capture a wide range of empirical features related to volatility dynamics while being more tractable for simulations than rough volatility models based on fractional processes. After presenting the model and its principal characteristics, our analysis focuses on the use of its associated Euler-discretization scheme as a time-series generator for Monte-Carlo simulations. Using this discretization scheme, and on the basis of S&P500 empirical time series, we show that the EWMA Heston model is overall consistent with market data, making it a credible alternative to other existing stochastic volatility models.
Dose Size Effect really exist in Indian financial market?

The present study is based on the study of one of the anomalies of the stock market. It aims to find out the presence of size effect on stock returns in the Indian stock market. The research is carried on studying the impact of the size of the company on the returns from its stock in the stock market (viz. National Stock Exchange). To conduct the study the market capitalization of the stocks is taken as the size of the company (i.e., Large Cap, Mid Cap and Small Cap). Returns from the stocks of 50 companies each from all the three sizes of the companies has been compared to prove the hypothesis. To study the impact of the size effect the daily returns from the stocks has been compared and further the respective abnormal returns have also been compared for an elaborate analysis. Moreover, the study focuses on finding answer to the question, “Can anybody outperform the market by designing size-based investment strategies? ” The present study is of immense use for the portfolio managers, asset management companies as well as individual investors. Stock prices of last five years have been taken for the study.
The Sraffian Supermultiplier and Cycles: Theory and Empirics

This paper provides a theoretical and empirical reassessment of supermultiplier theory. First, we show that, as a result of the passive role it assigns to investment, the Sraffian supermultiplier (SSM) predicts that the rate of utilization leads the investment share in a dampened cycle or, equivalently, that a convergent cyclical motion in the utilization-investment share plane would be counterclockwise. Second, impulse response functions from standard recursive vector autoregressions (VAR) for postwar US samples strongly indicate that the investment share leads the rate of utilization, or that these cycles are clockwise. These results raise questions about the key mechanism underlying supermultiplier theory.
Instinctive versus Reflective Trust in the European Central Bank

Political science research has established that trust in institutions, including central banks, is shaped by socio-economic and demographic factors, as well as by the assessment of institutional features and by slow-moving components such as culture. However, the role of cognitive processes has been largely neglected, especially in the analysis of central bank trust. In this paper we aim to address this gap focusing on the case of the European Central Bank (ECB). We introduce the concepts of "instinctive trust", which captures an on-the-spot judgement on the institution's trustworthiness, and of "reflective trust", which refers to a more pondered opinion on the matter. Using a survey experiment, we check whether deeper consideration about the ECB promotes more or less trust in the institution compared to an on-the-spot judgement. We find that reflective trust in the ECB is lower than instinctive trust. This result is mainly driven by women, and in particular by those who say they possess a low understanding of the central bank's policies.
Merger efficiencies and price effects in differentiated Cournot oligopoly

Suppose differentiated firms compete in quantities. This paper derives a formula for the minimum cost savings that would offset the incentive to increase price created by a merger. The formula depends only on pre-merger information on margins and demand slopes, and is invariant to demand and cost curvature. The paper then develops an algorithm to infer demand slopes -- and thus allow calibration of parameterized demand and cost curves -- from pre-merger data. While the Cournot model of quantity competition is commonly accompanied by an assumption that rivals' products are interchangeable, the inflexibility of this assumption and its implications opens the model to criticisms. The paper examines the advantages of relaxing the assumption of interchangeability, in particular greater consistency with pre-merger data and greater scope for profitable mergers. An extended numerical example illustrates the application of a differentiated Cournot model to a hypothetical industry.
Application of Artificial Neural Networks and Partial Least Square Regression to Predict Irrigated Land Soil Salinity in the Awash Basin, Ethiopia

Irrigation schemes in Awash Basin, Ethiopia, are severely affected by the buildup of soil salinity. Despite being an important basin for agricultural productivity, hundreds of fertile productive fields are turned into unproductive land every year. The main source of the salinity is shallow groundwater heightened by improper irrigation practices and management. However, salinity predictions have not been developed based on directly measured data for the basin. Therefore, this study aims to predict topsoil salinity in irrigated land from basic hydrological parameters using two machine learning algorithm approaches: Artificial neural networks (ANNs) and Partial least squares regression (PLSR). Data were collected during one year at four different irrigated fields. Irrigation water amount, water table depth, precipitation, and estimated canal seepage were considered for variable inputs. The groundwater table was measured by extended bucket auger drilling in four weeks intervals. Soil and water samples were taken for salinity analysis, and applied irrigation water was measured with an enclosed hydro-flume. Our results showed that ANNs were superior over PLSR in predicting soil salinity, explaining 64% vs. 46% of the variance in soil salinity with root mean square error (RMSE) of 0.15 vs. 0.86 dS/m. In both models, groundwater table depth is the most influential variable for soil salinity prediction, with relative contributions of 65% and 45% for PLSR and ANNs, respectively. The irrigation water source is non-saline river water; hence irrigation application and canal seepage do not have a direct significant implication for topsoil salinity buildup. However, these factors contribute to the rising groundwater table which has high salinity leading to soil salinization and, in further consequence, to the abandonment of the irrigated lands. Our study proves that the key to reducing salinity accumulation and productivity loss in Awash Basin irrigation schemes is sustaining the depth of the groundwater table in the area.
The Framework of Mechanics for Dynamic Behaviors of Fractional-Order Stochastic Dynamic Systems

The main goal of this paper is to establish a general framework for dynamic behaviors of coupled fractional-order stochastic dynamic systems of particles by using star-coupled models. In particular, the general mechanics on the dynamic behaviors related to the stochastic resonance (SR) phenomenon of a starcoupled harmonic oscillator subject to multiplicative fluctuation and periodic force in viscous media are established by considering couplings, memory effects, the occurring of synchronization linked to the occurring of SR induced. Here the noise is modeled with the fractional power kernel function and analytical expressions for the first moment of the stability between system responses and parameters in the long-time (of asymptotic stability) are also given. The theoretic and simulation results show the non-monotonic dependence between the response output gain and the input signal frequency, noise parameters provided by fractional-order stochastic dynamics are significant different by comparing those exhibited under the traditional integer-order stochastic dynamics, which indicates that the bona fide resonance and the generalized SR phenomena would appear. Furthermore, the fluctuation noise, the number of the particles for the systems, and the fractional order work together, producing more complex dynamic phenomena compared with the traditional integral-order systems. The theoretical analyses are supported by the corresponding numerical simulations, and thus it seems that the results established in this paper would provide a possible fundamental mathematical framework for the study of Schumpeter’s theory on the economic development under the “innovation and capital paradigm” and related disciplines. In particular, the framework established by this paper allows us at the first time logically concluding that “in principle. the ratio of SMEs growing up successfully is less than one third”, this is consistent with what the market has been observed commonly, but similar conclusion not available from the existing literature today. Finally, we like to point out that the framework established in this paper actually shows that under the basic model established in Section 2, through numerical simulation results given in sections 3 and 4, the fractional derivative in the interval (0; 1) as a basic tool, which can provide a new world with a more refined description of the market financial scene, such as in identifying risk factors or describing mechanics for enterprises’ growths more precisely with extra features compared with the traditional integer derivative one.
Histopathological Study of Benzene Exhaust Emission Effect on Organs of White Rats

The study designed on (20) white rats, the animals divided into (2) groups. The first group contain (10) rats act as control group, the second group contain (10) rats act as treated group, for (24) days continuously. The animals received for 1/4 hours per day to the benzene exhaust emissions which result from motor vehicle. The study showed that benzene emission cause damage and severs toxicity in tissue of lung, heart, liver, spleen, kidney and testis.
Another Superdense Sub-Neptune in K2-182 b and Refined Mass Measurements for K2-199 b and c

We combine multiple campaigns of K2 photometry with precision radial velocity measurements from Keck-HIRES to measure the masses of three sub-Neptune-sized planets. We confirm the planetary nature of the massive sub-Neptune K2-182 b (P b = 4.7 days, R b = 2.69 R ⊕) and derive refined parameters for K2-199 b and c (P b = 3.2 days, R b = 1.73 R ⊕ and P c = 7.4 days, R c = 2.85 R ⊕). These planets provide valuable data points in the mass–radius plane, especially as TESS continues to reveal an increasingly diverse sample of sub-Neptunes. The moderately bright (V = 12.0 mag) early K dwarf K2-182 (EPIC 211359660) was observed during K2 campaigns 5 and 18. We find that K2-182 b is potentially one of the densest sub-Neptunes known to date (20 ± 5 M ⊕ and 5.6 ± 1.4 g cm−3). The K5V dwarf K2-199 (EPIC 212779596; V = 12.3 mag), observed in K2 campaigns 6 and 17, hosts two recently confirmed planets. We refine the orbital and planetary parameters for K2-199 b and c by modeling both campaigns of K2 photometry and adding 12 Keck-HIRES measurements to the existing radial velocity data set (N = 33). We find that K2-199 b is likely rocky, at 6.9 ± 1.8 M ⊕ and 7.2−2.0+2.1 g cm−3, and that K2-199 c has an intermediate density at 12.4 ± 2.3 M ⊕ and 2.9−0.6+0.7 g cm−3. We contextualize these planets on the mass–radius plane, discuss a small but intriguing population of “superdense” sub-Neptunes (R p < 3 R ⊕, M p >20 M ⊕), and consider our prospects for the planets’ atmospheric characterization.
Sparsity in Partially Controllable Linear Systems

A fundamental concept in control theory is that of controllability, where any system state can be reached through an appropriate choice of control inputs. Indeed, a large body of classical and modern approaches are designed for controllable linear dynamical systems. However, in practice, we often encounter systems in which a large set of state variables evolve exogenously and indepen-dently of the control inputs; such systems are only partially controllable . The focus of this work is on a large class of partially controllable linear dynamical systems, speciﬁed by an underlying sparsity pattern. Our main results establish structural conditions and ﬁnite-sample guarantees for learning to control such systems. In particu-lar, our structural results characterize those state variables which are irrelevant for optimal control, an analysis which departs from classical control techniques. Our algorithmic results adapt techniques from high-dimensional statistics— speciﬁcally soft-thresholding and semiparametric least-squares—to exploit the underlying sparsity pattern in order to obtain ﬁnite-sample guarantees that signiﬁcantly improve over those based on certainty-equivalence. We also corroborate these theoretical improvements over certainty-equivalent control through a simulation study.
Trivial or impossible - dichotomous data difficulty masks model differences (on ImageNet and beyond)

"The power of a generalization system follows directly from its biases"(Mitchell 1980). Today, CNNs are incredibly powerful generalisation systems -- but to what degree have we understood how their inductive bias influences model decisions? We here attempt to disentangle the various aspects that determine how a model decides. In particular, we ask: what makes one model decide differently from another? In a meticulously controlled setting, we find that (1.) irrespective of the network architecture or objective (e.g. self-supervised, semi-supervised, vision transformers, recurrent models) all models end up with a similar decision boundary. (2.) To understand these findings, we analysed model decisions on the ImageNet validation set from epoch to epoch and image by image. We find that the ImageNet validation set, among others, suffers from dichotomous data difficulty (DDD): For the range of investigated models and their accuracies, it is dominated by 46.0%"trivial"and 11.5%"impossible"images (beyond label errors). Only 42.5% of the images could possibly be responsible for the differences between two models' decision boundaries. (3.) Only removing the"impossible"and"trivial"images allows us to see pronounced differences between models. (4.) Humans are highly accurate at predicting which images are"trivial"and"impossible"for CNNs (81.4%). This implies that in future comparisons of brains, machines and behaviour, much may be gained from investigating the decisive role of images and the distribution of their difficulties.
Effect of passive oxygen exposure during pressing and handling on the chemical and sensory attributes of Chardonnay wine

Background and Aims The significance of oxygen in winemaking has been well established, but knowledge gaps exist regarding the extent and impact passive oxygenation has on chemical and sensory properties during the initial stages. Methods and Results Using in‐press oxygen monitors, controlling oxygen exposure during the earliest stages of grape processing was shown to be highly effective. This work demonstrated that pressing management has far more impact on wine composition than handling management; the earliest and highest exposure to oxygen has the most profound impact on the composition of the resulting wine compared to the lower levels of repeated exposure typical of normal handling procedures. Furthermore, control of oxygen exposure during post‐pressing operations offers the possibility of modulating specific classes of compounds, described in sensory analysis as floral and confection. Conclusions Significant modulation of aromatic, phenolic and protein profiles of wine occurred through controlling oxygen exposure during the earliest stages of grape processing. Significance of the Study This work shows the possible stylistic potential and limitations of oxygen control, albeit with investment in press technology. The understanding of the relative influence of processing variables assessed in this work can be immediately applied by winemakers.
Assessment of Physical and Chemical Characteristics of Surface Water from River Niger, Illushi, Edo State, Nigeria

The physical and chemical characteristics of River Niger, Illushi an important fishing site in Edo State which is currently impacted by human activities, was investigated between the month of April and November, 2017. Surface water samples were collected from three (3) sampling stations covering a total distance of 2600metres from upstream to downstream, and a total of seventeen (17) physical/chemical parameters were investigated. Findings from this study revealed that Air temperature had an average mean value of 27±0.72 mg/L, Water temperature was 26.21±0.63 mg/L, the river was generally acidic with the average pH of 6.27±0.18, Turbidity was 107.28±30.9, Conductivity was 57.08±8.29, Total Dissolved Solid was 34.9±4.78, Total Suspended Solid was 71.7±21.17 mg/L, Alkalinity was 26.62±4.78 mg/L, Chloride was 17.29±1.41 mg/L, Hardness was 26.81±2.59 mg/L, Phosphate was 2.20±0.09 mg/L, Nitrate was 3.19±0.94 mg/L, Sulphate was 25.81±10.78 mg/L, Calcium was 8.69±1.74 mg/L, Magnesium was 2.66±0.39 mg/L, Dissolved Oxygen was 4.47±0.46 mg/L and Biochemical Oxygen Demand was 7.29±3.25 mg/L. This study depicts that turbidity, dissolved oxygen, biochemical oxygen demand, air, and water temperature were higher than the recommended limit for drinkable water. It, therefore, stresses the need for compliance of environmental laws to prevent the river from further deterioration. Keywords: Surface water, physicochemical parameters, River Niger, Illushi.