Miracle-dz/UniFAR-FTUs huggingface dataset:
Universal Scaling for Recovery of Fourier's Law in Low-Dimensional Solids under Momentum Conservation

Fourier's law governing the heat conduction has been considered to be broken in low(one or two)-dimensional momentum-conserving systems, based on the theory of the semi-macroscopic fluidic continuum. It is predicted that the heat conductivity in those systems should diverge in the thermodynamic long-wavelength limit. However, recent molecular-dynamic studies have reported a considerable number of counterexamples where the intensive property of the heat conductivity and thus Fourier's law recover in low-dimensional momentum-conserving systems. To answer the conundrum lying between the semi-macroscopic theory and the microscopic numerics, in this paper, I refine the previous semi-macroscopic fluid analysis by introducing the elastic response. Based on the fluctuating elastodynamic equation, the mode-coupling and dynamic renormalization-group analyses show that the non-zero acoustic wave speeds result in the recovery of Fourier's law by destabilizing a previously known fixed point keeping the hyper-scaling between the heat conductivity and kinetic viscosity. The theory based on the dynamic renormalization-group further predicts the size scale of beginning the recovery of Fourier's law. The prediction is supported by the numerical experiments of Fermi-Pasta-Ulam(FPU)-$\beta$ lattices, the data of which are collapsed to the predicted scaling function for the recovery of Fourier's law without any fitting parameters. The provided theory and numerics suggest the universality of the recovery of Fourier's law in the low-dimensional solids, which eventually include the one-dimensional fluids sharing the same governing equations with one-dimensional solids.
Nexus between Public Debts, Poverty and Unemployment Rates in Nigeria: A Vector AutoRegression (VAR) Approach

Notwithstanding the upsurge in public debts, it is absurd and worrisome to note that socioeconomic indicators like poverty and unemployment have shown gloomy pictures in Nigeria. The absurd situation makes it unclear on the precise nexus between public debts and unemployment rate on the one hand and poverty rate on the other hand. Consequently, this paper analysed the nexus between public debts, poverty and unemployment in Nigeria. Secondary data of public debts (measured by internal and external debts), poverty and unemployment rates were obtained from the Central Bank of Nigeria statistical bulletin and National Bureau of Statistics during the period 1981-2021. Using an unrestricted vector auto-regression model, the study indicated that neither internal nor external debts had any significant impact on poverty; however, they influence the level of unemployment rates in Nigeria. Impliedly, most of the public debts incurred within the period of investigation were not growth-oriented and could partly be explained by the fact that most of the borrowings were mainly to finance trade deficits, which were mainly consumable goods. The paper recommended that the current debt-togross domestic product ratio of less than 20 percent should be sustained to ensure that debt remains within the internationally recommended threshold for developing economies like Nigeria. Also, future public borrowings should be targeted at specified productive sectors of the economy that would engender growth in the long-run in terms of job creation and poverty alleviation; this can be achieved via the procedure of tying every public borrowing to specific growth-driving project that are oriented towards job creation and alleviation of poverty
Finite-time stability of discrete-time switched delay systems with nonlinear disturbances

This paper investigates finite-time stability (FTS) for discrete-time switched delay systems with nonlinear disturbances, where the disturbances may have stronger nonlinearities. Based on novel inequality technique and average dwell time approach, several new stability criteria are obtained which guarantee that the state trajectory does not exceed a certain threshold over a pre-specified finite-time interval. An example is provided to illustrate the effectiveness of the theoretical results.
An Inverse Source Problem for Singular Parabolic Equations with Interior Degeneracy

The main purpose of this work is to study an inverse source problem for degenerate/singular parabolic equations with degeneracy and singularity occurring in the interior of the spatial domain. Using Carleman estimates, we prove a Lipschitz stability estimate for the source term provided that additional measurement data are given on a suitable interior subdomain. For the numerical solution, the reconstruction is formulated as a minimization problem using the output least squares approach with the Tikhonov regularization. The Fréchet differentiability of the Tikhonov functional and the Lipschitz continuity of the Fréchet gradient are proved. These properties allow us to apply gradient methods for numerical solution of the considered inverse source problem.
Implementing Ethnic Studies Courses to Fight the Spike in Anti-Asian Acts

Abstract Recent surveys suggest that the anti-Asian attacks that began during the COVID-19 pandemic may continue to occur. One of the ways school leaders can respond to this problem is by implementing ethnic studies courses. Unfortunately, organizers of social movements sometimes thwart efforts to increase ethnic studies courses, claiming that this type of curriculum is anti-White. But since well-taught ethnic studies courses are designed to benefit all students, this claim is based on misconceptions. In this paper, I clarify how ethnic studies courses benefit students from all ethnic and racial groups and why more of these courses need to be implemented to fight the recent rise in anti-Asian attacks.
Is practice good enough? Retrieval benefits students with ADHD but does not compensate for poor encoding in unmedicated students

Introduction A significant proportion of currently enrolled college students receive support for attention deficit/hyperactivity disorder (ADHD) and these students are often at risk of academic failure. Retrieval practice or self-testing is an effective, accessible, and affordable tool for improving academic performance. Three recent studies found conflicting results with regards to the effectiveness of retrieval practice in this population. Methods The present study compared 36 individuals with ADHD to 36 controls. Participants studied Swahili-English word pairs that varied in difficulty. Half of the pairs were repeatedly studied, and the other half repeatedly tested. Results On a final test, all participants showed a benefit of retrieval practice relative to restudy and participant status did not moderate the effect. However, unmedicated individuals with ADHD performed worse overall, both during the encoding phase and on the final test, whereas medicated participants were not significantly different from controls. Discussion An examination of self-reported encoding strategies found unmedicated participants used fewer deep strategies at encoding, consistent with prior work on ADHD and memory. Although retrieval practice is effective in this group, improved strategy use may be necessary to ensure performance that is fully equivalent to that of students without ADHD.
Alterations of Purinergic Receptors Levels and Their Involvement in the Glial Cell Morphology in a Pre-Clinical Model of Autism Spectrum Disorders

Recent data suggest that defects in purinergic signalling are a common denominator of autism spectrum disorders (ASDs), though nothing is known about whether the disorder-related imbalance occurs at the receptor level. In this study, we investigated whether prenatal exposure to valproic acid (VPA) induces changes in purinergic receptor expression in adolescence and whether it corresponds to glial cell activation. Pregnant dams were subjected to an intraperitoneal injection of VPA at embryonic day 12.5. In the hippocampi of adolescent male VPA offspring, we observed an increase in the level of P2X1, with concomitant decreases in P2X7 and P2Y1 receptors. In contrast, in the cortex, the level of P2X1 was significantly reduced. Also, significant increases in cortical P2Y1 and P2Y12 receptors were detected. Additionally, we observed profound alterations in microglial cell numbers and morphology in the cortex of VPA animals, leading to the elevation of pro-inflammatory cytokine expression. The changes in glial cells were partially reduced via a single administration of a non-selective P2 receptor antagonist. These studies show the involvement of purinergic signalling imbalance in the modulation of brain inflammatory response induced via prenatal VPA exposure and may indicate that purinergic receptors are a novel target for pharmacological intervention in ASDs.
Experimental Study of Low Velocity Impact Response of Carbon/Basalt Hybrid Filament Wound Composite Pipes

In this study, the impact damage resistance of carbon/basalt hybrid fiber reinforced polymer pipes was experimentally investigated under low velocity impact loading. The composite pipes, composed of thin plastic liner of HDPE wrapped with eight layers of plies at constant winding angle of [[Formula: see text]55[Formula: see text]/90[Formula: see text]/[Formula: see text]55[Formula: see text]/90[Formula: see text]], were fabricated through filament winding technique. Eight pipe configurations with different stacking sequence and fiber content proportion were studied. Specimens cut from the original pipes were tested in a drop weight impact machine under two levels of impact energies, 50[Formula: see text]J and 100[Formula: see text]J, in order to predict the impact response and induced damage resistance of the pipe. The damage of the tested pipes was assessed based on the force-displacement, force-time histories, the energy absorption mechanism, as well as the micrographs captured by scanning electron microscope (SEM) for the specimens. The results indicate that the impact resistance behavior was highly affected by the stacking sequence of the layers and partly affected by the fiber content ratio. Positioning the basalt fiber on the impacted side enhances the energy absorption mechanism for both levels of imposed energies, while improving the impact resistance. The addition of 50% basalt fiber can slightly increase the impact resistance compared to the addition of 25% basalt fiber. However, specimens with 25% basalt fiber showed lower peak force, lower damage area and lower energy absorption.
On Outlier Rejection Phenomena in Bayes Inference

SUMMARY Inference is considered for a location parameter given a random sample. Outliers are not explicitly modelled, but rejection of extreme observations occurs naturally in any Bayesian analysis of data from distributions with suitably thick tails. For other distributions outlier rejection behaviour can never occur. These phenomena motivate new definitions of outlier-proneness and outlier-resistance. The definitions and methodology are Bayesian but the conclusions also have meaning for nonBayesians because they are proved for arbitrary prior distributions. Thus, for example, the t distribution is said to be outlier-prone because it is shown that any admissible inference procedure applied to a t sample will effectively ignore extreme outlying observations regardless of prior information. On the other hand, the normal distribution, for example, is said to be outlier-resistant because it never allows outlier rejection, regardless of prior information.
Frequency Domain Modeling and Performance Analysis of Injection-Locked LC Oscillator

This brief proposes a frequency domain model for injection-locked LC oscillators by introducing the impulse sensitivity function (ISF) and injection factor, analyzes the effect of the injection pulse width and injection position on oscillator performance based on this model, and derives an equation that can guide the design and optimization of oscillators. The model fills the gap in the field of frequency domain models for injection-locked LC oscillators. Based on the above model, a clock generator circuit structure operating at 14 GHz, combining a phase-locked loop with an injection-locked oscillator, is designed and measured based on a 65-nm cmos process. The circuit achieves better phase noise performance by optimizing the two parameters, which verifies the accuracy of the proposed model.
Psilocybin Therapy for Major Depressive Disorder: A Systematic Review

Introduction: Major depressive disorder (MDD) is a prevalent and complex mood disorder. Its psychotherapies often involve delayed treatment-response times, while its pharmacotherapies can cause unwanted side effects. In recent years, there has been a resurgence in psychedelic research with a specific interest in the potential of psilocybin for treating MDD. Therefore, this systematic review was performed to evaluate the effectiveness of psilocybin therapy at moderate (15±5 mg/70 kg) to high (25 ± 5 mg/70 kg) doses in the psychiatric treatment of MDD. Methods: The review included a literature search using PubMed (Medline), SCOPUS, Web of Science, and Medline (Ovid) databases from January 1, 2013, to February 28, 2023. Seven studies were included following the inclusion and exclusion criteria (e.g., moderate to high dosing psilocybin treatment, peer-reviewed, moderate to severe depression, control/delayed treatment groups, and non-directive therapy during psilocybin sessions). Studies were excluded using PRISMA guidelines and appraised using the Critical Appraisal Skills Programme checklists. Results: The primary outcomes assessed included changes in depression scores on validated diagnostic tools and secondary outcomes that supported depression remission (e.g., improved well-being and rumination scores, and decreased anxiety scores). Psilocybin was found to reduce depression symptoms in moderate single-dose contexts and have minimal reported side effects at high doses. A positive relationship was observed between the quality of psilocybin-induced experiences and the reduction in depressive symptoms. Additionally, a dose-response relationship was found between moderate (15±5 mg/70 kg) and high-dose psilocybin (25 ± 5 mg/70 kg), with greater improvements generally seen in higher dose conditions. Discussion: This review suggests that psilocybin can be an effective treatment option for MDD. Psilocybin shows meaningful improvements in depression scores with the potential to treat psychiatric conditions concurrent to depression. The non-directive therapy approach during high-dose sessions enabled unique psychedelic and personal experiences, potentially allowing more profound and individualized therapy. Reported side effects were minimal, and suggestions for future studies are provided. Conclusion: Psilocybin therapy was found to reduce depression levels and improve secondary outcomes that support depression remission, indicating efficacy for MDD and other depressive conditions. Despite seeming promising, further research is required before introducing PAP options to mainstream clinical practice.
Ego Depletion Sensitivity as the Mediator Between Avoidance Temperaments and Subjective Vitality

: The present study examined the mediating role of ego depletion sensitivity between temperaments and subjective vitality. The sample of the present research consisted of 210 undergraduate students of the University of Sargodha. Temperament, ego depletion sensitivity, and subjective vitality were operationalized through Approach-Avoidance Temperament Questionnaire (Elliot & Thrash, 2010), Depletion Sensitivity Scale (Salmon et al., 2014), and Subjective Vitality Scale (Ryan & Frederick, 1997), respectively. Correlation analysis depicted that ego depletion sensitivity was positively correlated with avoidance temperament and negatively correlated with subjective vitality. Furthermore, ego depletion sensitivity mediated between avoidance temperament and subjective vitality. Implications of the study along with its limitations and suggestions were discussed.
Two-Phase Bubble Columns: A Comprehensive Review

We present a comprehensive literature review on the two-phase bubble column; in this review we deeply analyze the flow regimes, the flow regime transitions, the local and global fluid dynamics parameters, and the mass transfer phenomena. First, we discuss the flow regimes, the flow regime transitions, the local and global fluid dynamics parameters, and the mass transfer. We also discuss how the operating parameters (i.e., pressure, temperature, and gas and liquid flow rates), the operating modes (i.e., the co-current, the counter-current and the batch modes), the liquid and gas phase properties, and the design parameters (i.e., gas sparger design, column diameter and aspect ratio) influence the flow regime transitions and the fluid dynamics parameters. Secondly, we present the experimental techniques for studying the global and local fluid dynamic properties. Finally, we present the modeling approaches to study the global and local bubble column fluid dynamics, and we outline the major issues to be solved in future studies.
Hybrid and Decentralized Local Market Design Considering Joint Energy and Reserve Trading

Power market players are becoming more proactive as distributed energy resources rise, which encourages the employment of local energy markets (LEMs) in modern power systems. In this environment, community-based markets (CBMs) and peer-to-peer (P2P) trading are two innovative designs developed for LEMs. However, each has significant drawbacks, such as slow rate convergence and unpredictable system behavior for P2P architecture, as well as obtaining and optimizing large-scale data in CBM. This research proposes a novel architecture for LEM based on cooperative energy trading and a reserve market, which can overcome the shortcomings of existing designs. Two-stage modeling is proposed, and the consensus alternate direction method of multipliers is utilized to clear the market in a decentralized manner to demonstrate the players' preferences, preserve privacy, and distribute the computation burden. Moreover, the model analyzes Tokyo's Japan Electric Power Exchange market. To highlight its benefits, the proposed structure is compared to other structures. According to the findings, CBM and P2P transaction volumes are 12.78% and 71.9% less than the proposed architecture, respectively. The proposed design's imports and exports are 35.1% and 38.2% lower than CBMs, and overall imports and exports are 77.88% and 74.24% less than P2P.
Compact Ultra-­Wideband Planar Inverted F Antenna on Laminated Paper­-Based Substrate with Reduced Specific Absorption Rate

This paper presents a laminated paper-based Planar Inverted F Antenna (PIFA) for wireless body area network (WBAN) applications. The major challenges like providing adequate thickness, uniformity of surface, and water wet ability associated with paper substrate have been transcended in this antenna design by laminating the substrate with a transparent sheet. The simulated and measured reflection coefficients of the fabricated antenna in free space and on human arm are remarkably good, validating the prototype’s utility. It can operate effectively in GSM, WMTS, GPS, DCS, ISM, WiMAX, HIPERLAN, WLAN, and UWB frequency bands with S11 less than -10 dB and the gain ranging from 0.94 to 9.53 dB (free space) and 1.03 to 6.07 dB (on-body). The electrical size of the proposed antenna is 0.16 λg x 0.12 λg at 0.7 GHz with a group delay below 2.3 ns over the desired frequency bands. The performance characteristics are also investigated on-body and it encompasses most of the desired frequency bands for the body area network. This paper also analyses the specific absorption rate (SAR) of the designed antenna by placing it on a tissue-layered human arm model, which is 0.64 Watt/kg, complying with the SAR safety guidelines.
New Capabilities for Prediction of High‐Latitude Ionospheric Scintillation: A Novel Approach With Machine Learning

As societal dependence on transionospheric radio signals grows, space weather impact on these signals becomes increasingly important yet our understanding of the effects remains inadequate. This challenge is particularly acute at high latitudes where the effects of space weather are most direct and no reliable predictive capability exists. We take advantage of a large volume of data from Global Navigation Satellite Systems (GNSS) signals, increasingly sophisticated tools for data‐driven discovery, and a machine learning algorithm known as the support vector machine (SVM) to develop a novel predictive model for high‐latitude ionospheric phase scintillation. This work, to our knowledge, represents the first time an SVM model has been created to predict high‐latitude phase scintillation. We use the true skill score to evaluate the SVM model and to establish a benchmark for high‐latitude ionospheric phase scintillation prediction. The SVM model significantly outperforms persistence (i.e., current and future scintillation are identical), doubling the predictive skill according to the true skill score for a 1‐hr lead time. For a 3‐hr lead time, persistence is comparable to a random chance prediction, suggesting that the memory of the ionosphere in terms of high‐latitude plasma irregularities is on the order of, or shorter than, a few hours. The SVM model predictive skill only slightly decreases between the 1‐ and 3‐hr predictive tasks, pointing to the potential of this method. Our findings can serve as a foundation on which to evaluate future predictive models, a critical development toward the resolution of space weather impact on transionospheric radio signals.
Novel insights into D-Pinitol based therapies: a link between tau hyperphosphorylation and insulin resistance

Alzheimer’s disease is a neurodegenerative disorder characterized by the amyloid accumulation in the brains of patients with Alzheimer’s disease. The pathogenesis of Alzheimer’s disease is mainly mediated by the phosphorylation and aggregation of tau protein. Among the multiple causes of tau hyperphosphorylation, brain insulin resistance has generated much attention, and inositols as insulin sensitizers, are currently considered candidates for drug development. The present narrative review revises the interactions between these three elements: Alzheimer’s disease-tau-inositols, which can eventually identify targets for new disease modifiers capable of bringing hope to the millions of people affected by this devastating disease.