Miracle-dz/UniFAR-FTUs huggingface dataset:
Disordered high-dimensional optimal control

Mean field optimal control problems are a class of optimization problems that arise from optimal control when applied to the many body setting. In the noisy case one has a set of controllable stochastic processes and a cost function that is a functional of their trajectories. The goal of the optimization is to minimize this cost over the control variables. Here we consider the case in which we have N stochastic processes, or agents, with the associated control variables, which interact in a disordered way so that the resulting cost function is random. The goal is to find the average minimal cost for N → ∞, when a typical realization of the quenched random interactions is considered. We introduce a simple model and show how to perform a dimensional reduction from the infinite dimensional case to a set of one dimensional stochastic partial differential equations of the Hamilton–Jacobi–Bellman and Fokker–Planck type. The statistical properties of the corresponding stochastic terms must be computed self-consistently, as we show explicitly.
A comparison on the use of Perlin-noise and Gaussian noise based augmentation on X-ray classification of lung cancer patient

The use of deep learning in medical image classification has become an important study in the past few years. The proper use of this method, however, is still hindered by many problems, one of it being the imbalance of dataset available for training which resulted in small-set database. In this study, the effect of noise-based augmentation on the performance of deep learning based classification will be studied. The noises which were used for the augmentation method were Perlin-noise and Gaussian noise. The modality of medical image used in this study is X-ray. 174 X-ray images (87 cancer, 87 normal) were used in this study and will be classified by using transfer learning from previously trained deep learning architecture. The deep learning architecture used was vgg-19. The images were divided into two groups, 138 (69 cancer, 69 normal) images were used for training phase and 36 (18 cancer, 18 normal) were images used for testing phase. Three deep learning models were used for the classification tasks, the first one was retrained to classify the original images, the second one was retrained by using mix of original images and images with Perlin-noise, and the third one was retrained by using mix of original images and images with Gaussian noise. The results showed that the three models returned similar accuracy of 0.8 which indicate that the use of noise-based augmentation can increase the performance of deep learning in classifying medical images with small set training database.
Thermal environment analysis for TianQin

TianQin is a proposed space-borne gravitational wave observatory in high geocentric orbits, exposed to radiating heat sources in space. Due to the stringent thermal stability requirements from the key payloads, the analysis of space thermal environment is of great importance. This paper studies the incident thermal radiation onto the TianQin satellites from the Sun–Earth–Moon system. The solar constant fluctuation (SCF) and the Earth’s land-type features, based on the meteorological data, are considered, and an analytic function of lunar surface temperature is used. The analysis includes the solar radiation, the infrared radiation, and the albedo. The results are discussed in both time and frequency domains. The spectral analysis indicates that in the target frequency band of 0.1 mHz–1 Hz, the SCF plays a dominant role, and that the associated incident thermal disturbance is ∼5 W m−2 Hz−1/2 for TianQin, at the same level of the LISA in heliocentric orbits. In addition, the power spectra of the Earth’s and Moon’s heating fluctuation are given, both order-of-magnitude weaker than that of the solar radiation. The results may contribute to the thermal design and the noise analysis for TianQin.
POLITICAL PARTICIPATION AND SUBJECTIVE WELL-BEING: INDIVIDUALS' E-PARTICIPATION ACTIVITIES ON TWITTER IN TERMS OF LIFE SATISFACTION

Political studies on well-being often question the impact of political concepts on well-being. But a growing literature in recent years claims that, contrary to popular belief, well-being can also affect political participation. This new literature focuses more on traditional behaviors (e.g. voting, protest) of political participation. The effect of well-being on e-participation has not yet been studied. For this reason, the presented research explores the impact of well-being on e-participation behaviors performed on Twitter to contribute to the developing literature. The main purpose of the research is to test the impact of well-being on e-participation activities. For this purpose, I designed causal research that adopts the relational scanning model. I collected research data from 573 Turkish participants via a survey. Data were analyzed using the Structural Equation Model (SEM). The results show that well-being has a negative effect on political expression behaviors and positively affect policy following behavior. Well-being has no significant effect on the dimension of participation in local government. The results show that well-being also affects e-participation behaviors, so it offers a new perspective on the developing literature.
Differences in adaptive learning across the lifespan are driven by satisficing

Learning is pervasive across the human lifespan and essential for adaptive behavior. Children and older adults are often slower to learn cognitive tasks than young adults. Here we build on established theory formalizing learning as predictive inference and consider the possibility that age-related learning differences emerge from satisficing in this prediction problem – that is, accepting predictions that achieve some sufficient level of accuracy. In our computational formalization of this idea, beliefs are updated through an active process until reaching some criterion value of acceptability, which is set more liberally in children and older adults. In line with our model’s predictions, children and older adults showed frequent perseveration when asked to update beliefs from their previous values but were also more highly influenced by environmental manipulations of the starting value from which beliefs are updated. Our model and results provide a unifying perspective on seemingly contradictory findings showing developmental differences in the reliance on internal and external behavioral biases by suggesting that they both emerge from a liberal satisficing policy. Introduction Many of our decisions are guided by uncertain information that is not directly observable. For example, we can not directly perceive the quality of a new ice-cream parlor but have to learn about it by sampling different sorts of ice cream (Bolenz et al., 2017). While doing so, smaller differences in the experienced quality (small prediction errors) can be written off as expected daily fluctuations that should not fundamentally change our minds about the parlor’s quality. However, unexpectedly large deviations from our beliefs (large prediction errors) could indicate that the quality has systematically changed, for example, because the ice-cream parlor has a new owner. In this case, it may be necessary to update our beliefs more dramatically and consider a different ice-cream parlor. Such attributions of prediction errors to variability versus changepoints can be difficult in the face of uncertainty but are critical for controlling the degree to which new experiences influence learning. Previous work has identified normative mechanisms derived from principles of optimal Bayesian inference for implementing this sort of belief updating (Behrens et al., 2007; Meyniel and Dehaene, 2017;
Pregnancy-Related Hysterectomy for Peripartum Hemorrhage: A Literature Narrative Review of the Diagnosis, Management, and Techniques

Postpartum hemorrhage is a life-threatening situation, in which hysterectomy can be performed to prevent maternal death. However, it is associated with high rates of maternal morbidity and mortality and permanent infertility. The incidence of pregnancy-related hysterectomy varies across countries, but its main indications are the following: uterine atony and placenta spectrum (PAS) disorders. PAS disorder prevalence is rising during the last years, mainly due to the increased number of cesarean sections. As a result, obstetricians should be aware of the difficulties of this emergent condition and improve its accurate antenatal diagnosis rates, as well as its modern management strategies. Of course, special skills are required during a pregnancy-related hysterectomy, so these patients should be referred to centers of excellence in antenatal care, where a multidisciplinary team approach is followed. This study is a narrative review of the literature of the last 5 years (PubMed, Cochrane) regarding postpartum hemorrhage to offer obstetricians up-to-date knowledge on this pregnancy-related life-threatening issue. However, there is a lack of available high-quality data, because most published papers are retrospective case series or observational cohorts.
Quantum Walk Frameworks and Quantum Speedup of Markov Mixing

We give a novel quantum algorithm for Markov mixing, using ideas from two frameworks for quantising algorithms on reversible, discrete time Markov chains. The MNRS quantum walk framework (MNRS) is based on the spectral properties of Markov chains, and the Belovs electric network framework (Belovs) is based on the resistor network interpretation. Given a Markov chain with spectral gap δ and minimal stationary probability π∗, classical mixing takes O( 1 δ log 1 π∗ ) applications of the transition matrix. In line with quadratic speedups via quantum walks in other areas, Richter conjectured a quantum mixing time of O( 1 √ δ log 1 π∗ ) queries to the quantum walk operator. This problem is still open. We give a novel algorithm inspired by Belovs, which mixes in O( 1 √ δ′ + 1 √ δ ) queries, where δ′ is the spectral gap of the originial Markov chain modified by the addition of self loops. Our algorithm is as follows: we first mix to the stationary distribution of the modified Markov chain (self loops added). We then mix to the stationary distribution of the original chain. This process guarantees O(1) overlap between initial, intermediate and final state. We show that in certain cases this algorithm beats Richter’s conjecture, and we provide a means of quantifying when our algorithm might beat both existing algorithms and Richter’s conjecture in terms of Cheeger’s inequality, providing a link between quantum mixing times and Markovian bottlenecks. For cases where adding self loops does not asymptotically affect the spectral gap, our algorithm can be prepended to the MNRS quantum walk framework yielding a new spectral quantum walk framework that can start from an arbitrary initial state at no extra cost over MNRS. This is a feature of the Belovs’ framework absent from MNRS. That our algorithm is based on Belovs’ walk operator is suggestive of power in Belovs’ framework absent from MNRS.
Towards Red Emissive Systems Based on Carbon Dots

Carbon dots (C-dots) represent an emerging class of nontoxic nanoemitters that show excitation wavelength-dependent photoluminescence (PL) with high quantum yield (QY) and minimal photobleaching. The vast majority of studies focus on C-dots that exhibit the strongest PL emissions in the blue/green region of the spectrum, while longer wavelength emissions are ideal for applications such as bioimaging, photothermal and photodynamic therapy and light-emitting diodes. Effective strategies to modulate the PL emission of C-dot-based systems towards the red end of the spectrum rely on extensive conjugation of sp2 domains, heteroatom doping, solvatochromism, surface functionalization and passivation. Those approaches are systematically presented in this review, while emphasis is given on important applications of red-emissive suspensions, nanopowders and polymer nanocomposites.
Comparison of the clinical and radiological results of posterior cruciate ligament-retaining and posterior cruciate ligament-stabilized knee arthroplasties

DOI: 10.4328/ACAM.20360 Received: 2020-10-02 Accepted: 2020-11-01 Published Online: 2020-11-15 Printed: 2021-06-01 Ann Clin Anal Med 2021;12(6):617-620 Corresponding Author: Sezgin Bahadır Tekin,Department of Orthopedics, Dr. Ersin Arslan Education and Research Hospital, Gaziantep, Turkey. E-mail: sezgintekin1988@hotmail.com P: +90 5317916686 Corresponding Author ORCID ID: https://orcid.org/0000-0003-4740-9949 Abstract Aim: Total knee arthroplasty (TKA) is one of the most successful orthopedic surgeries. To further improve these outcomes, researchers have developed various types of prosthetics. This study aims to compare the clinical and radiological results of the common posterior cruciate ligament (PCL)-retaining (CR) and PCL-stabilized (PS) knee arthroplasties. Material and Methods: We retrospectively evaluated the data of patients that were diagnosed with gonarthrosis in our clinic and who underwent knee replacement. The patients were evaluated using the American Knee Society score (AKSS) and radiographic assessment. Results: There were a total of 115 subjects. Fifty-nine knees of 54 patients and 80 knees of 61 patients were included in the study. Forty-six of the 54 patients in the ligament-retaining group were female (86%) and 8 were male (14%). Fifty-two of the 61 patients in the ligament-stabilized group were female (85%) and 8 were male (15%). The mean age was 67.4 years (54-82) in the ligament-retaining group and 65.4 years (42-85) in the ligament-stabilized group. The mean follow-up time in both groups was 32.6 months (12-98). Discussion: The comparison of PCL-retaining and PCL-stabilized knee arthroplasties revealed that the ligament-stabilized group was superior in terms of the range of motion. The radiological examination revealed a difference in component alignment. The two groups did not differ significantly regarding other parameters.
Hollow-Core Optical Fibers

Today hollow-core optical fibers (HCF) are on the verge of surpassing the attenuation benchmark of silica single-mode optical fibers used in optical communication. Compared to solid-core optical fibers, HCFs exhibit ultra-low nonlinearity, high damage threshold, low latency and temperature insensitivity, making them ideal candidates for high-speed data communication, high-resolution sensing, high-power delivery and precise interferometry. The main challenges of low insertion loss, suppressed back-reflections and fundamental mode coupling must be addressed to incorporate HCFs into existing fiber-optic systems to fully exploit their potential. This paper provides an overview of the HCF history, from early papers in the 1980s, over the invention of photonicbandgap HCFs, to the recent achievements with antiresonant HCFs. Then light guiding mechanisms are presented and key HCF properties are discussed. Interconnection techniques to standard optical fibers are compared with respect to possible HCF applications. Fusion splicing results are presented with an alternative interconnection solution based on a modified fiber-array technique newly developed by our team. Finally, cutting-edge HCF applications that take advantage of our HCF interconnection, are discussed.
The association between entrepreneurship, management, and sustainable development in the mid- dle east: A systematic review and meta-analysis Azzam Abou-Moghlia and Ala Dandisa*

Article history: Received: December 12, 2020 Received in revised format: December 29 2020 Accepted: February 28, 2021 Available online: February 28, 2021 The study of entrepreneurship continues to expand as a field of inquiry and remains one of the most attractive realms of research in the field of management science. This study follows an evidencebased research approach and conducts a systematic review and meta-analysis on the entrepreneurship, management, and sustainable development in entrepreneurial firms working in the Middle East. The study has conducted a bibliometric search for outlining the systematic and empirical evidence on entrepreneurship, management, and sustainable development, and to examine the relevant literature from the particular domain, followed by PRISMA guidelines. Total of 25 articles were extracted dated from 2006 to 2020. One of the potential aspects regarding entrepreneurship, management, and sustainable development in the region was the introduction of entrepreneurial led family businesses that unlock the potential of the region. The rapid urbanization and population growth in the Middle East have put massive pressures on their environments. Entrepreneurship had a significant and positive impact on both sustainable development and management. Influenced by the entrepreneurial ecosystem, the Middle Eastern countries showed a dynamic performance at a macro level. This systematic review and meta-analysis provide information on the current state of the empirical entrepreneurship, management, and sustainable development literature. © 2021 by the authors; licensee Growing Science, Canada
Is small and medium-sized beautiful? The structure and evolution of family SMEs research

PurposeThe field of scientific research on small and medium-sized family businesses has been growing exponentially and the aim of this paper is to systematize the body of knowledge to develop an agenda for the future.Design/methodology/approachAdopting comparative bibliometric analyses on 155 articles (from 1989 until 2018) the authors provide a systematic assessment of the scientific research about small family firms, unveiling the structure and evolution of the field. Bibliographic coupling, co-citation analysis and co-occurrence analysis are adopted to identify the most influential studies and themes.FindingsFour clusters of research are reviewed: succession in family SMEs, performances of family SMEs, internationalization of family SMEs and organizational culture of family SMEs.Originality/valueThis paper contributes to the field of family SMEs by providing a systematic analysis of the scientific knowledge. Reviewing those clusters allows to providing avenues and reflections for future research and further practice.
MOLECULAR MECHANISM OF GROWTH DIVERSITY FOR THE FIRST HYBRID GENERATION INDIVIDUALS OF GRASS CARP (CTENOPHARYNGODON IDELLUS) (♀) × BARBEL CHUB

The first hybrid generation (F1) individuals of grass carp (Ctenopharyngodon idellus, ♀) × barbel chub (Squaliobarbus cunrriculus, ♂) commonly show obvious growth diversity, even though they are from the same parents and cultured in the same environment. To characterize the molecular mechanism of the growth diversity, the present study compared the expressions of growth-related genes of the fast-growth population (FGP) and slow-growth population (SGP). The expression of growth-inhibiting SRIF gene was significantly higher in the SGP hypophysis than in the FGP. The expressions of growth-promoting GHR and IGF-I genes in blood, GHR, IGF-I and IGF-II genes in liver, and IGF-I and IGF-II genes in muscle of the FGP were significantly higher than those of the SGP in liver. The results implied that hypernomic-expression of SRIF gene in hypophysis caused the expressions of GHR and IGF-I genes in blood, GHR, IGF-I and IGF-II genes in liver, and IGF-I and IGF-II genes in muscle of the SGP to be significantly lower than those in the FGP, which caused the lower growth of the SGP. These results provided valuable reference for studying the relationship between growth-related genes and fish growth, and the molecular mechanism of fish growth.
BEV Fast Charging Strategy Optimization

This paper presents different approaches to optimize battery electric vehicles (BEVs) fast charging strategy. A rule-based model was built to simulate BEV charging behavior. Monte Carlo analysis was performed to explore the potential variance of congestion at fast charging stations, which could cause longer than four-hour waiting at the most congested station. Genetic algorithm was performed to explore the potential minimum waiting time at fast charging stations, and it can decrease the waiting time at the most congested station to be shorter than one hour. A deterministic approach results in feasible suggestions that people could consider to take fast charging as soon as the state of charge is approaching 40-miles range while remaining relative short waiting time at charging stations.
Identification of nonlinear magnetic damping in vibrating coupled structures

Magnetic damped vibrations are obtained by coupling a conductive structure with a magnetic field. The induced damping force characteristic depends upon displacement and velocity. When the magnetic field is generated by permanent magnets, a good model of the damping characteristic requires the estimation of the eddy currents induced in the conductive parts and subsequently of the resulting Lorentz force acting on them. This force is unfortunately nonlinear as its magnitude depends both on frequency and amplitude of oscillations. Considering by hypothesis a harmonic motion of the system, a simulation of the magneto-dynamic phenomenon is performed by means of a partial element equivalent circuit of the conductive parts. The force characteristic is then used to fit a sinusoidal input describing function approximation. Results obtained by simulations are validated versus experimental measurements on a three degrees of freedom structure.
Full-Duplex Radio Technology in Military Applications: Practical Experiments (Suomeksi: Full-duplex radioteknologia sotilaskäytössä, Osahanke A)

Inspired by the recent advances in wireless in-band full-duplex (IBFD) communications in the civilian/commercial domain, this two-part feasibility study characterized whether and how the progressive same-frequency simultaneous transmit and receive (SF-STAR) capability of IBFD radio transceivers can be advantageous in military applications as well. Whereas IBFD operation could allow doubling spectral efficiency in two-way tactical communications, the SF-STAR capability may also revolutionize battlefield systems by integrating tactical communications and electronic warfare in the form of a multifunction military full-duplex radio (MFDR). The second part of the project reported herein demonstrated the practicability of selected military applications of the IBFD/SF-STAR capability with indoor and outdoor laboratory experiments.
The Impact of the Quality of Accounting Information on the Decisions of Entrepreneurs in Saudi Arabia

This research work examines the impact of the quality of accounting information on the decisions of entrepreneurs in the Eastern Province of Saudi Arabia. The focus is on how the internal decisions made in these enterprises are affected by accounting information which is characterised by high quality (relevance, reliability, comparability and consistency). The study used a questionnaire instrument, which targeted the managers of the SMEs across four Chambers in the Eastern Province. Pearson’s correlation coefficient was employed to provide a picture of the relationship between the variables. It was followed by multiple regression analysis to determine the direction and significance of the relationship between the variables and to test the hypotheses. The findings reveal a statistically significant positive impact of relevance, comparability and consistency of accounting information on decisions made by entrepreneurs in the Eastern Province. In addition, a statistically insignificant relationship was found in relation to the impact of reliability of accounting information on entrepreneurs’ decisions. The Saudi Organization for Certified Public Accountants should educate entrepreneurs on why the quality of accounting information is essential to their decisions. It should also ensure that every accountant in these enterprises is registered in its database and meets the acceptable conditions for practicing the accounting profession.