Miracle-dz/UniFAR-FTUs huggingface dataset:
Parental Socialization, Delinquency during Adolescence and Adjustment in Adolescents and Adult Children

Although parental socialization has an influence on child development, current research is questioning which combination of parental strictness and warmth acts as protective or risk factors, especially during adolescence when the child is more vulnerable. The sample was 2125 participants, 58.7% female, divided into four age groups: adolescents (28.57%), young adults (28.38%), middle-aged adults (23.95%), and older adults (19.11%). The families were classified into four parenting styles: neglectful, indulgent, authoritative, and authoritarian according to their warmth and strictness scores. The psychosocial adjustment was measured by children’s scores on academic/professional self-concept, self-esteem, delinquency during adolescence, and benevolence values. A MANOVA 4 × 2 × 4 was applied with parenting styles, sex, and age group as independent variables. The results showed that, for adolescents and adult children, only parenting styles characterized by warmth (i.e., indulgent, and authoritative) were found to factor against delinquency during adolescence and benefit greater academic/professional self-concept, self-esteem, and benevolence values, while parenting without warmth (i.e., authoritarian, and neglectful) were identified as risk factors. Contrary to classical research, the present findings seriously question the universal benefits of strict parenting as the only optimal strategy to protect not only against delinquency, but also to foster an adequate self and the internalization of social values.
Circular Polarized Quasi-Self-Complementary Antenna for Spectrum Sensing and IoT

The proposed work exhibits the design and performance analysis of a circular polarized quasi-self-complementary antenna for spectrum sensing applications in modern wireless systems. The antenna exhibits dual band response in frequency ranges 3.82 to 6.47 GHz and 7.61 to 8.45 GHz. The antenna is circular polarized in the sub-6 GHz frequency range from 4.2 to 4.8 GHz. The identification of available spectrum is useful for dynamic allocation in 5G and higher technologies. The antenna proposed here has peak gain 3.5 dBic and an efficiency >80% and >70 % in the two bands. It has an electrical size equal to $0.55\lambda_{0}\times 0.55\lambda_{0}\times 0.0024\lambda_{0}$.
Quantum Field Theory in Graphene

This is a short nontechnical introduction to applications of the Quantum Field Theory methods to graphene. We derive the Dirac model from the tight binding model and describe calculations of the polarization operator (conductivity). Later on, we use this quantity to describe the Quantum Hall Effect, light absorption by graphene, the Faraday effect, and the Casimir interaction.
Technical Note - Approximating Systems Fed by Poisson Processes with Rapidly Changing Arrival Rates

In many operations management settings, the arrival process to the system exhibits clear nonstationarities. These nonstationarities may arise as a consequence of time-of-day effects, day-of-week effects, seasonalities, or stochastic fluctuations in the arrival rate. Tools that are developed for performance prediction and decision making when systems are stationary may not be valid in the nonstationary environment. This paper provides a generic, closed-form, and simple approximation tool for when the nonstationarities are caused by rapid fluctuations in the arrival processes.
Optical modeling of light trapping using an ITO-based electrodynamic dust shield structure

Optimal design of light-trapping coatings for PV cells is essential for enhancing absorption of light in active layers. Some conductive polymer coatings can serve as an electrodynamic dust shield (EDS), e.g., for a lunar PV module. This paper discusses an approach to optical modeling of nanostructured surfaces for light trapping. PV structures include thin EDS and light-trapping layers and much thicker optically transparent spacer and active pn-junction layers. We used a combination of physical optics for the nanosurface and the transfer-matrix method for the whole structure. Examples illustrate how absorption can be improved over a range of incidence angles or wavelengths by nanopatterning an ITO layer.
An AI based Formulated Feedback-System for Interpreting Conclusive Emotions for A Group of People

Understanding emotions of people in a group is an essential facet of learning in today's time. Lot of information about emotional state, feeling and identity of human beings is conveyed via facial expression. Emotion recognition is a striking and demanding problem which in turn can help harness insights about individual and organizational behavior and can add big value to various businesses ranging from education, hospitality, entertainment, eateries, etc. In our research paper, we have proposed an AI rooted Emotion detection and recognition feedback system using mathematical solutions. AI based proposed solution will be self -governing and will be freewheeling from gender and age of human being in emotion detection and recognition, unlike past systems, which have largely failed to provide. This proposed solution system will greatly increase the potential to use the recognized emotion data from a wider applicability perspective and giving scope for customization as per customer's business requirement. In this study paper, a unique AI based emotion recognition detection mathematical solution system is proposed to analyze the behavior/reaction of people in a group. Proposed solution system will act as a feedback system and is able to amass multiple faces, extract respective emotions and formulate the detected emotions through proposed solution system to give aggregated behavior/emotion of the group as a whole.
Highly Efficient Adsorption of Tetracycline Using Chitosan-Based Magnetic Adsorbent

Herein, tetracycline adsorption employing magnetic chitosan (CS·Fe3O4) as the adsorbent is reported. The magnetic adsorbent was synthesized by the co-precipitation method and characterized through FTIR, XRD, SEM, and VSM analyses. The experimental data showed that the highest maximum adsorption capacity was reached at pH 7.0 (211.21 mg g−1). The efficiency of the magnetic adsorbent in tetracycline removal was dependent on the pH, initial concentration of adsorbate, and the adsorbent dosage. Additionally, the ionic strength showed a significant effect on the process. The equilibrium and kinetics studies demonstrate that Sips and Elovich models showed the best adjustment for experimental data, suggesting that the adsorption occurs in a heterogeneous surface and predominantly by chemical mechanisms. The experimental results suggest that tetracycline adsorption is mainly governed by the hydrogen bonds and cation–π interactions due to its pH dependence as well as the enhancement in the removal efficiency with the magnetite incorporation on the chitosan surface, respectively. Thermodynamic parameters indicate a spontaneous and exothermic process. Finally, magnetic chitosan proves to be efficient in TC removal even after several adsorption/desorption cycles.
Can a Commercial Screening Tool Help Select Better Teachers?

Improving teacher selection is an important strategy for strengthening the quality of the teacher workforce. As districts adopt commercial teacher screening tools, evidence is needed to understand these tools’ predictive validity. We examine the relationship between Frontline Education’s TeacherFit instrument and newly hired teachers’ outcomes. We find that a 1 SD increase on an index of TeacherFit scores is associated with a 0.06 SD increase in evaluation scores. However, we also find evidence that teachers with higher TeacherFit scores are more likely to leave their hiring schools the following year. Our results suggest that TeacherFit is not necessarily a substitute for more rigorous screening processes that are conducted by human resources officials, such as those documented in recent studies.
Uniform exponential mixing for congruence covers of convex cocompact hyperbolic manifolds

Let $\Gamma$ be a Zariski dense convex cocompact subgroup contained in an arithmetic lattice of $\operatorname{SO}(n, 1)^{\circ}$. We prove uniform exponential mixing of the geodesic flow for congruence covers of the hyperbolic manifold $\Gamma \backslash \mathbb{H}^n$ avoiding finitely many prime ideals. This extends the work of Oh-Winter who proved the result for the $n = 2$ case. Following their approach, we use Dolgopyat's method for the proof of exponential mixing of the geodesic flow. We do this uniformly over congruence covers by establishing uniform spectral bounds for the congruence transfer operators associated to the geodesic flow. This requires another key ingredient which is the expander machinery due to Bourgain-Gamburd-Sarnak extended by Golsefidy-Varj\'{u}.
Impact of Soft Errors on High Performance Autoencoders for Cyberattack Detection

Detecting anomalous messages generated by cyberattacks is essential for IoT based critical applications (e.g., finance, healthcare, manufacturing, etc.), in order to guarantee high levels of security and availability. Autoencoder-based anomaly detection has been proven effective in detecting the presence of messages altered by malicious attacks. To guarantee low detection latency, autoencoders” algorithms are typically executed by HW accelerators implemented by nanotechnology. However, such HW accelerators are susceptible to soft errors (SEs), that may occur during their in-field operation. In this paper, we analyze the impact of SEs on the effectiveness of autoencoders in detecting anomalous messages generated by cyberattacks. As an example, we consider autoencoders trained to discriminate credit card legal and illegal transactions. We show that SEs do not decrease system's security, but may reduce system's availability of the 70%, so that proper solutions to avoid the detrimental impact of SEs on system's availability should be devised for autoencoders implemented by high performance HW accelerators.
A New Vernier Machine With Compensatory Permanent Magnet Array

Vernier machines (VM) are widely used in direct drive field for its simple structure and high torque density at low operation speed. In order to increase torque quality furtherly and reduce the cogging torque and torque ripple, pole-shaping has been an alternative approach applied in VM. However, pole shaping brings manufacturing difficulty, which limits the development of pole-shaping in machine design. A new VM with compensatory PM array (CPMVM) is proposed, which can provide high quality torque production. The compensatory PM array consists of several PMs with different thickness, which is used to optimize the airgap flux density for high quality torque. Compared to the conventional pole-shaping, the proposed machine can achieve high sinusoidal airgap flux density distribution without increasing equivalent airgap length in magnetic circuit. The proposed CPMVM and the conventional VM are designed sharing the identical key design parameters and optimized by multi-objective evolutionary algorithm. The back electromagnetic force and torque production of the designed machines are analyzed using finite element analysis (FEA). The FEA-predicted results indicate that the proposed CPMVMs exhibit good inhibitory capacity for torque ripple and have high PM utilization.
Structure, spectra and variability of some GPS radio sources

We report the results of multifrequency-VLBI observations of GHz-Peaked-Spectrum (GPS) radio sources. The VLBI structure and component spectra of some GPS sources are presented. Our VLBI results show that about 80% of the GPS galaxies exhibit a compact double or CSO-like structure, white the GPS quasars tend to show a core-jet. The component spectra of the GPS galaxies are often steep/convex, and the core has a flat spectrum but it is usually hidden or weak. In addition, we studied the variability of GPS sources by comparing new flux density measures, acquired with the Urumqi 25-m telescope at 4.85 GHz, with previous 87GB data. The results show that 44% of the GPS quasars varied higher than 10% in passed 20 years, while the fraction is only 12% for the GPS galaxies meaning that the GPS quasars are much more variable than GPS galaxies. In total, 25% of GPS sources show > 10% variability at 4.85 GHz in our sample.
A central limit theorem for the length of the longest common subsequences in random words

Let $(X_i)_{i \geq 1}$ and $(Y_i)_{i\geq1}$ be two independent sequences of independent identically distributed random variables taking their values in a common finite alphabet and having the same law. Let $LC_n$ be the length of the longest common subsequences of the two random words $X_1\cdots X_n$ and $Y_1\cdots Y_n$. Under a lower bound assumption on the order of its variance, $LC_n$ is shown to satisfy a central limit theorem. This is in contrast to the limiting distribution of the length of the longest common subsequences in two independent uniform random permutations of $\{1, \dots, n\}$, which is shown to be the Tracy-Widom distribution.
Development of Highly Uniform and Reproducible DI-O3 layers for Photovoltaic Applications and Beyond

We demonstrate the development and characterization of ozonated oxide (DI-O3) for applications in photovoltaics and beyond. The growth of DI-O3 is investigated by varying 1) the sample orientation in a wafer cassette. , 2) growth time and 3) ozone concentration in parts-per-million (ppm); while the thickness and uniformity of DI-O3 layer on the entire 100 mm diameter are characterized by the multi-wavelength ellipsometer equipped with a wafer mapping capability. DI-O3 samples grown horizontally in the wafer cassette provide better uniformity than vertically grown counterparts (i.e., ±1.62% compared to ±8.02% across 100 mm diameter). A modest increase in DI-O3 thickness is observed with increasing growth time (i.e., from 1 min to 3 min and 10 min). An average of 0.06 nm and 0.10 nm of DI-O3 thickness. , respectively. , is increased when the growth time is increased by 2 min and 7 min. Varying ozone concentration from 3.5 ppm to 15 ppm. , on the other hand. , is observed with a minimal effect on DI-O3 growth. Thanks to the growth technique (horizontal orientation and continuous dissolved ozone flow) and parameters (15 ppm., 420 mI/min flow and 30°C of dissolved ozone) used in this contribution. , we demonstrate the reproducibility of growing DI-O3 with 1.53±0.01 nm and < 3% uniformity on multiple 100 diameter wafers.
High mobility ambipolar MoS2 field-effect transistors: Substrate and dielectric effects

We fabricate MoS2 field effect transistors on both SiO2 and polymethyl methacrylate (PMMA) dielectrics and measure charge carrier mobility in a four-probe configuration. For multilayer MoS2 on SiO2, the mobility is 30–60 cm2/Vs, relatively independent of thickness (15–90 nm), and most devices exhibit unipolar n-type behavior. In contrast, multilayer MoS2 on PMMA shows mobility increasing with thickness, up to 470 cm2/Vs (electrons) and 480 cm2/Vs (holes) at thickness ∼50 nm. The dependence of the mobility on thickness points to a long-range dielectric effect of the bulk MoS2 in increasing mobility.
Failure Probability due to Radiation-induced Effects in FinFET SRAM Cells under Process Variations

This work studies radiation-induced effects in Fin-FET technology, the leading technology in advanced nodes for high-end embedded systems. Technology computer-aided design (TCAD) tools are used to evaluate soft-error robustness to radiation-induced effects of FinFET SRAM cells with the fin height (HFIN) and the number of fins (NFIN). HFIN and NFIN are two critical parameters in the development of newer technologies. The ion-strike direction and the process variations are considered. An analytical method to evaluate the failure probability of the memory cell due to radiation-induced effects under process variations is proposed. TCAD tools are used to quantify the amount of collected and critical charges of the memory cells used to evaluate the failure probability. The proposed method can be used to get insight into the robustness behavior of the memory cell with HFIN and NFIN and guide the required HFIN and NFIN in the development of new FinFET technologies.
Causality in Econometrics: Choice vs Chance

This essay describes the evolution and recent convergence of two methodological approaches to causal inference. The first one, in statistics, started with the analysis and design of randomized experiments. The second, in econometrics, focused on settings with economic agents making optimal choices. I argue that the local average treatment effects framework facilitated the recent convergence by making key assumptions transparent and intelligible to scholars in many fields. Looking ahead, I discuss recent developments in causal inference that combine the same transparency and relevance.
Joint Operation Strategy of Electrochemical Energy Storage Station Participating in Multi-type Electricity Markets

As the proportion of renewable energy continues to increase, the need for flexible power resources in new power systems also increases. As a relatively mature energy storage technology, electrochemical energy storage can realize the transfer of electricity in time and space, and suppress the problems caused by renewable energy’s randomness, volatility, and intermittency. The relevant market-oriented price mechanism is gradually improving to enhance the enthusiasm for the investment and construction of electrochemical energy storage stations. However, the operation strategy of electrochemical energy storage stations in the new power system has not been analyzed. Considering the price fluctuations in the electricity market, based on the conditional value-at-risk model, a joint operation strategy model for electrochemical energy storage to participate in the electric energy market and ancillary service market is proposed. First, through the forecast of the electricity market price, a typical electricity price scenario is formed after sampling and aggregation. Then, according to the proposed operation strategy model, the capacity allocation results of different markets are obtained. The example analysis is carried out in combination with the actual situation of the electrochemical energy storage station to verify the effectiveness models. Finally, the influence of different risk preferences and market prices on the income of the power station is analyzed.
Conservation laws and laser cooling of atoms

The straightforward application of energy and linear momentum conservation to the absorption/emission of photons by atoms allows us to establish the essential features of laser cooling of two level atoms at low laser intensities. The lowest attainable average kinetic energy of the atoms depends on the ratio Γ / E R ? > between the natural linewidth and the recoil energy and tends to ER as Γ / E R ? > tends to zero (in one dimension). This treatment, like the quantum mechanical ones, is valid for any value of the ratio Γ / E R ? > and contains the semiclassical theory of laser cooling as the limiting case in which E R ≪ Γ ? > .
Infrared spectra and chemical abundance of methyl propionate in icy astrochemical conditions

We carried out an experiment in order to obtain the InfraRed (IR) spectra of methyl propionate (CH3CH2COOCH3) in astrochemical conditions and present the IR spectra for future identification of this molecule in the InterStellar Medium (ISM). The experimental IR spectrum is compared with the theoretical spectrum and an attempt was made to assign the observed peak positions to their corresponding molecular vibrations in condensed phase. Moreover, our calculations suggest that methyl propionate must be synthesized efficiently within the complex chemical network of the ISM and therefore be present in cold dust grains, awaiting identification.
A Qualitative Study of Drug Treatment Conformity Behavior among Young Drug Users Who Are in Recovery in China

In response to social concerns about young drug users, this study aimed to qualitatively explore the types of drug treatment conformity behaviors and the processes of behavior formation among this population. Twenty-one young drug users were selected through purposive sampling, in-depth interviews were conducted using a semi-structured approach, and the data were then analyzed. The social conformity theory is used as the framework of the analysis, and the results indicate that drug treatment behaviors can be differentiated by the three types of motivation that produce conformity with drug treatment: the cognitive, affective, and utilitarian. These three types of motivations produce three types of conformity, respectively: drug treatment abidance, drug treatment compliance, and drug treatment obedience. They are affected by informational social influences, normative influences of significant others, and normative structural levels, respectively. We also propose a model of the information processing involved in drug treatment conformity. Based on an in-depth analysis of the characteristics and formation processes of the three different types of conformity, intervention strategies are proposed. This study has important guiding significance for helping young drug users maintain their drug rehabilitation ethics and successfully return to society.
Reliability Assessment Methodologies for ANN-based Systems

In recent decades, deep learning (DL)-based solutions have gained a great deal of interest in industry and academia due to their outstanding computational capabilities. The usage of electronic devices running applications based on Artificial Neural Networks (ANNs) is spreading in several areas, including safety-critical applications such as self-driving cars, robots, and space applications. ANNs are often regarded as inherently robust and fault-tolerant, being brain-inspired and redundant computing models. However, to use them safely in human contexts, there is a compelling need to assess their reliability. Indeed, when they are deployed on resource-constrained hardware devices, single physical faults might jeopardize the activity of multiple neurons, leading to undesirable results. Since reliability assessment is becoming a growing concern, many efforts have been made in recent decades to propose efficient approaches to assess ANN-based systems reliability. The intent of this article is to overview the main reliability assessment methodologies for ANN-based systems, focusing mainly on Fault Injection techniques used to evaluate the ANN resilience at different abstraction levels.