Miracle-dz/UniFAR-FTUs huggingface dataset:
Cryptocurrency Portfolio Optimization by Neural Networks

Many cryptocurrency brokers nowadays offer a va-riety of derivative assets that allow traders to perform hedging or speculation. This paper proposes an effective algorithm based on neural networks to take advantage of these investment products. The proposed algorithm constructs a portfolio that contains a pair of negatively correlated assets. A deep neural network, which outputs the allocation weight of each asset at a time interval, is trained to maximize the Sharpe ratio. A novel loss term is proposed to regulate the network's bias towards a specific asset, thus enforcing the network to learn an allocation strategy that is close to a minimum variance strategy. Extensive experiments were conducted using data collected from Binance spanning 19 months to evaluate the effectiveness of our approach. The backtest results show that the proposed algorithm can produce neural networks that are able to make profits in different market situations.
Can a void mimic the Λ in ΛCDM?

We investigate Lemaítre-Tolman-Bondi (LTB) models, whose early time evolution and bang time are homogeneous and the distance-redshift relation and local Hubble parameter are inherited from the ΛCDM model. We show that the obtained LTB models and the ΛCDM model predict different relative local expansion rates and that the Hubble functions of the models diverge increasingly with redshift. The LTB models show tension between low redshift baryon acoustic oscillation and supernova observations and including Lyman-α forest or cosmic microwave background observations only accentuates the better fit of the ΛCDM model compared to the LTB model. The result indicates that additional degrees of freedom are needed to explain the observations, for example by renouncing spherical symmetry, homogeneous bang time, negligible effects of pressure, or the early time homogeneity assumption.
An Improved Phase Space Reconstruction Method-Based Hybrid Model for Chaotic Traffic Flow Prediction

Traffic flow is chaotic due to nonstationary realistic factors, and revealing the internal nonlinear dynamics of chaotic data and making high-accuracy predictions is the key to traffic control and inducement. Given that high-quality phase space reconstruction is the foundation of predictive modeling. Firstly, an improved C-C method based on the fused norm search domain is proposed to address the issue that the C-C method in the phase space reconstruction algorithm does not meet the Euclidean metric accuracy and reduces the reconstruction quality when the infinite norm metric is used. Secondly, to address the problem of insufficient learning ability of traditional convolutional combinatorial modeling for complex phase space laws of chaotic traffic flow, the high-dimensional phase space features are extracted using the layer-by-layer pretraining mechanism of convolutional deep belief networks (CDBNs), and the temporal features are extracted by combining with long short-term memory (LSTM). Finally, an improved probabilistic dynamic reproduction-based genetic algorithm (PDRGA) is proposed to address the problem of the hybrid model falling into a local optimum when learning the phase space law. Experiments are conducted in three aspects: phase space reconstruction quality analysis, comparison of optimization algorithm convergence, and prediction model performance comparison. The experimentation with two data sets demonstrates that the improved C-C method combines the advantages of the high accuracy metric of the L2 norm with the low operational complexity of the infinite norm, achieving a balance between reconstruction quality and algorithm efficiency. The proposed PDRGA optimization algorithm is a lightweight improvement of the traditional genetic algorithm (GA) and solves the problem that the model tends to fall into a local optimum by optimizing the initial weights of CDBN. Meanwhile, the five error evaluation indexes of the proposed PDRGA-CDBN-LSTM hybrid model are lower than those of the baseline model, providing a new modeling idea for chaotic traffic flow prediction.
Excitation of a broadband circularly polarized and arrow-shaped dipole antenna with high gain by an improved hybrid coupler

This paper proposed a novel wideband, circularly polarized crossed dipole antenna with high gain that utilizes an improved feeding work. The hybrid coupler exhibits both compact circuit configuration and a wide bandwidth (S11 ≤ −15 dB) of over 60% given a power distribution of −3.1 dB using a broadband coupled-line power divider and a 90° phase shifter with an impedance-open-stub. A phase deviation of 90° ± 5° was also observed over wideband. When excited by the wideband feed network, the circularly polarized crossed dipole antenna achieves an impedance bandwidth of 66.7% given S11 ≤ −15 dB and a 3 dB axial ratio bandwidth of 67%. Furthermore, the stable peak gain increased from 9 to 10.9 dBi between 1.07 and 1.7 GHz when a cylindrical cavity was connected to the ground. Moreover, the cross-polarization ratio in the wideband exceeds 25 dB. The simulated results of this study agree with the measured ones.
Too Time-Crunched to Seek Variety: The Influence of Parenting Motivation on Consumer Variety Seeking

Parenting motivation, the inspiration and drive to take care of one's children, is a powerful instinct for facilitating human reproduction. In a set of hypotheses, the authors address how, why, and among whom parenting motivation affects a pervasive decision-making tendency, namely, variety seeking. Six studies, including a large-scale panel data study and five online and lab studies, show that, when shopping, parenting motivation spurs feelings of time crunch that result in less variety seeking among consumers. The effect is diminished when time-saving parenting support exists (which reduces feelings of time crunch in parenting), when consumers are led to believe that they have sufficient time available for shopping, and when they do not have much loyalty to any brand offered in the choice set and thus cannot save time by simply choosing the top-of-mind product option. The current research thus contributes to the growing literature on how parenting motivation affects consumer decision making. In addition, it augments the literature on variety seeking by identifying an important factor that can influence it.
The UCSD/MIT hard X-ray and low energy gamma ray experiment for HEAO-A

An HEAO-A spacecraft is described which is scheduled for launch in April 1977 to survey the sky in the 0.15 keV to 10 MeV range of X-rays with improved sensitivity and angular resolution. The spectral and time variations of discrete sources, and the spectrum and isotropy of the diffuse component will be measured. A hard X-ray and low energy gamma ray experiment is described which will use as an array of seven (NaI)(Tl)/CsI(Na) phoswich detectors and eight large CsI(Na) shields. Detector events are pulse-height analyzed with a selectable time resolution of 0.1, 0.005, or 0.00002 sec. The instrument background is expected to be comprised of approximately equal parts of diffuse gamma rays entering the aperture, radioactive decay of spallation products, and gamma ray leakage through the shields. Detailed background predictions are presented, and sensitivity estimates indicate that the Crab nebula should be detected up to approximately 5 MeV. Approximate 1% isotropy limits for the diffuse component of cosmic gamma rays should be achieved, and its spectrum measured with improved precision.
Control and braiding of Majorana fermions bound to magnetic domain walls

We propose using a mobile magnetic domain wall as a host of zero-energy Majorana fermions in a spin-orbit coupled nanowire sandwiched by two ferromagnetic strips and deposited on an $s$-wave superconductor. The ability to control domain walls by thermal means allows to braid Majorana fermions nonintrusively, which obey non-Abelian statistics. The analytical solutions of Majorana fermions inside domain walls are obtained in the strong spin-orbit regime.
Model Identification and Model Based Analysis of Membrane Reactors

This work considers problems of model identification and model based analysis of membrane reactors. The parameter identification and optimal experimental design problems for gas transport through both single and multi-layer membranes have been investigated. A genetic algorithm has been improved to solve the corresponding global optimization problems. Nonlinear analysis has been performed for the steady state solution of membrane reactor models, and pattern formation has been studied. In chapter 2, the membrane reactor models considered in this work are introduced and discussed briefly. The identification of multi-layer membrane models, which is the focus of the first part of this work, is a difficult global optimization problem. Chapter 3 discusses methods for solving this problem. Since the objective function is non-convex, a traditional gradient based hill climbing algorithm is unable to locate the minima correctly. Therefore a global optimizer should be applied instead. However, the genetic algorithm that is used in this work becomes also inefficient in solving this problem because of the high correlation of the parameters. Chapter 3 first gives background of numerical algorithm for parameter identification and experimental design, and then is focused on improving the efficiency of genetic algorithm to solve the demanding global optimization problems. A new method with coordinate transformation is developed and applied successfully to the problems in chapter 4.
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We determine the CKM matrix-element magnitude $|V_{cb}|$ using $\overline{B}^0\to D^{*+}\ell^-\bar\nu_\ell$ decays reconstructed in $189 \, \mathrm{fb}^{-1}$ of collision data collected by the Belle II experiment, located at the SuperKEKB $e^+e^-$ collider. Partial decay rates are reported as functions of the recoil parameter $w$ and three decay angles separately for electron and muon final states. We obtain $|V_{cb}|$ using the Boyd-Grinstein-Lebed and Caprini-Lellouch-Neubert parametrizations, and find $|V_{cb}|_\mathrm{BGL}=(40.57\pm 0.31 \pm 0.95\pm 0.58)\times 10^{-3}$ and $|V_{cb}|_\mathrm{CLN}=(40.13 \pm 0.27 \pm 0.93\pm 0.58 )\times 10^{-3}$ with the uncertainties denoting statistical components, systematic components, and components from the lattice QCD input, respectively. The branching fraction is measured to be ${\cal B}(\overline{B}^0\to D^{*+}\ell^-\bar\nu_\ell)=(4.922 \pm 0.023 \pm 0.220)\%$. The ratio of branching fractions for electron and muon final states is found to be $0.998 \pm 0.009 \pm 0.020$. In addition, we determine the forward-backward angular asymmetry and the $D^{*+}$ longitudinal polarization fractions. All results are compatible with lepton-flavor universality in the Standard Model.
Alexithymia May Be Associated With Depression in Early-Stage Breast Cancer Patients

Background Depression, anxiety, or both are common in women with early-stage breast cancer (BC). A relationship is known between low perceived social support (PSS) and depression. We aimed to investigate the relationships between alexithymia, PSS, and Beck Depression Inventory (BDI) score in patients diagnosed with early-stage BC. Materials and methods A demographic and medical information form, BDI, the 20-item Toronto Alexithymia Scale (TAS-20), and the Multidimensional Scale of PSS (MSPSS) were given to 200 early-stage BC patients to respond. Two subgroups were created as group A (BDI score < 17) and group B (BDI score ≥ 17) and compared in terms of sociodemographic characteristics, TAS-20, and MSPSS scores. Results Twenty-six (18.1%), 48 (33.3%), and 26 (18.1%) patients were with high BDI scores, in low PSS status, and alexithymic, respectively. The median ages of the participants in group A and group B were 53.4 (interquartile range (IQR): 46-60.7) and 46 (IQR: 41.5-59) years, respectively (p = 0.083). The rates of single participants (26.9% versus 11%, p = 0.055), alexithymic participants (42.3% versus 12.7%, p = 0.001), low PSS levels (57.7% versus 28%, p = 0.018), psychiatric treatment history (46.2% versus 22%, p = 0.025), and patients with low income (57.7% versus 22.9%, p = 0.001) were higher in group B than in group A. In the multivariate regression model that contains the parameters mentioned above, psychiatric treatment history (odds ratio (OR): 2.758, 95% confidence interval (CI): 1.034-7.356, p = 0.043), low-income status (OR: 3.503, 95% CI: 1.336-9.182, p = 0.011), and alexithymia (OR: 3.482, 95% CI: 1.229-9.867, p = 0.019) were independent predictive factors for a high BDI. Conclusion Alexithymia and low PSS are significantly common in patients with prominent depressive symptoms in early-stage BC patients. Alexithymia may be associated with depression and may also have a role in depression pathogenesis in early-stage BC patients. New studies are needed to investigate whether there is a causal relationship between alexithymia and depression.
A deep Q-learning network based active object detection model with a novel training algorithm for service robots

This paper focuses on the problem of active object detection (AOD). AOD is important for service robots to complete tasks in the family environment, and leads robots to approach the target object by taking appropriate moving actions. Most of the current AOD methods are based on reinforcement learning with low training efficiency and testing accuracy. Therefore, an AOD model based on a deep Q-learning network (DQN) with a novel training algorithm is proposed in this paper. The DQN model is designed to fit the Q-values of various actions, and includes state space, feature extraction, and a multilayer perceptron. In contrast to existing research, a novel training algorithm based on memory is designed for the proposed DQN model to improve training efficiency and testing accuracy. In addition, a method of generating the end state is presented to judge when to stop the AOD task during the training process. Sufficient comparison experiments and ablation studies are performed based on an AOD dataset, proving that the presented method has better performance than the comparable methods and that the proposed training algorithm is more effective than the raw training algorithm.
Design of double-negative metamaterials using single-layer plasmonic structures

We propose a design for optical-frequency double-negative metamaterials (DMNs) in which the unit cell is formed by a single-layer plasmonic inclusion. By introducing some properly arranged stepwise modulations onto the inclusions, the effective permittivity and permeability of the material may become simultaneously negative due to the excitation of higher-order multipole plamonic (electrostatic) resonances. The approach opens a possibility to construct low-loss optical DNMs with great engineering simplicity.
On the Finite-Sample Biases in Nonparametric Testing for Variance Constancy

In this paper we analyse the small-sample size distortions of nonparametric CUSUM tests for variance stability resulting from the long-run variance estimation. The long-run variance estimator is a key factor necessary to ensure asymptotically pivotal test statistics. We discuss the large sample properties of these tests under standard and recently developed fixed- b bandwidth asymptotic theory for kernel heteroskedasticity and autocorrelation consistent (HAC) estimators, and analyse the finite sample performance for different data generation processes of major empirical relevance. Despite the good properties evidenced by the large-sample theory, important distortions may arise when the empirical processes exhibit strongly-persistent volatility and excess kurtosis even in relatively large samples. In this context, consistent (inconsistent) HAC estimators may lead to over-sized (under-sized) tests. Hence, nonparametric tests may lack power to distinguish between a strongly persistent -yet stationary- process and a process with a structural break.
Indonesian Blasphemy Law as Legal Forum for Renegotiating Indonesian Secularity

If secularism is described merely as the decline of religious roles in public spheres or religious privatization, then there would be difficulties to put the secular term on Indonesian history. The principle of divinity “Ketuhanan Yang Maha Esa” as adopted on the “Pancasila” as state ideology has become basis for religionization and rejecting any utterance of secularism at law, State institution, or other public domain. On the other hand, Indonesia as a democratic State as well as the most populous Muslim country in the world has never put the notion of Islamic state or theocracy as its State model. Its modernity is developed under the Western idea of law supremacy or the rule of law to which a democratic political system is laid down. This situation seems to be paradoxical in the view of both religionist or modernist due to its inconsistency to their strict concept especially on Islamic state and secularism. Or, is Indonesia another example of how religion and modernity has its multiplicity based its own historical reflexivity without making clash between religion and secularism? This article is intended to seek kind of distinction on Indonesian secularity based on how its blasphemy law developed and functioned under the framework of open-ended negotiation. The first epoch assumed as the place of negotiation on Indonesian secularity was taken place on initial stage of State’s formation around transition era of independence in 1945. Then, there have been several renegotiations afterward through multiple and overlapping instruments of development such as politics, economy, law, and culture. The blasphemy law as one of such instruments will be used to read how the relevant actors of Indonesian history has constructed their own concept of state and religion included its interrelationship characters as the basis for social and structural differentiation or distinction. The expected outcome of the reading and its analysis is to reveal any evidence of Indonesian particularity on secularization which may be related to the concept of multiple secularities.
Modelling Count Data with Excess Zeros: An Application to Health Care Utilisation Data

This study is concerned with the estimation of microeconometric models of health care utilisation. The data set consists of 14,706 individuals from the General Household Survey for Great Britain, and the dependent variable is the number of General Practitioner (GP) consultations over a 2-week period. A clear feature of this count variable is excess zeros, and it is essential to incorporate this feature in the modelling strategy. Accordingly, in addition to standard Poisson and negative binomial models, zero-inflated, two-part, and latent class models were estimated. The zero-inflated negative binomial model (ZINB) proved, on the basis of several selection criteria, to be superior to other models for this dataset. As anticipated, health related variables had significant effects in determining health care utilisation while socioeconomic variables appeared to be less important, according to the results from the preferred model. Some effects differ quite markedly between the different models, underlining the importance of the type of process used to identify the best-fitting one.
Microstructure Observation on the Interface between Warm Spray Deposited Titanium Powder and Steel Substrate

Titanium particles were deposited on a steel substrate by the impact of high velocity in warm spraying. In the process, nitrogen gas at various flow rates was mixed to control the temperature of a supersonic gas flow generated by combustion. TEM and other techniques were used to analyze the microstructure of the interface between the titanium coatings and the substrate. At the lower nitrogen flow rate, thick oxide double layers in the interface region were observed. The adhesive strength of the coating was high even at lower particles’ velocity possibly because the mechanical interlocking between the titanium particle and the substrate could be enhanced by the high deformability of heated particles. As the nitrogen flow rate increased, however, just a little oxide and a very thin oxide layer covering on the titanium splats were locally detected. The highly localized pressure and the resultant intensive shear stress generated within a titanium particle by the impact could reveal the fresh metal surface through break-up of the thin oxide films on the particle and the substrate. As a result, the metallic bonding between the deposited particle and the substrate was formed and increased the adhesive strength remarkably beyond a certain impact velocity.
Leptogenesis scenarios for natural SUSY with mixed axion-higgsino dark matter

Supersymmetric models with radiatively-driven electroweak naturalness require light higgsinos of mass ∼ 100–300 GeV . Naturalness in the QCD sector is invoked via the Peccei-Quinn (PQ) axion leading to mixed axion-higgsino dark matter. The SUSY DFSZ axion model provides a solution to the SUSY μ problem and the Little Hierarchy μ≪ m3/2 may emerge as a consequence of a mismatch between PQ and hidden sector mass scales. The traditional gravitino problem is now augmented by the axino and saxion problems, since these latter particles can also contribute to overproduction of WIMPs or dark radiation, or violation of BBN constraints. We compute regions of the TR vs. m3/2 plane allowed by BBN, dark matter and dark radiation constraints for various PQ scale choices fa. These regions are compared to the values needed for thermal leptogenesis, non-thermal leptogenesis, oscillating sneutrino leptogenesis and Affleck-Dine leptogenesis. The latter three are allowed in wide regions of parameter space for PQ scale fa∼ 1010–1012 GeV which is also favored by naturalness: fa ∼ √μMP/λμ ∼ 1010–1012 GeV . These fa values correspond to axion masses somewhat above the projected ADMX search regions.
Asymmetric tent map expansions II. Purely periodic points

where /3 a/(a 1) and the nonnegative integers ni are specified by the itinerary I(x)= L"RLnRLn. , which encodes the successive iterates T(’)(x) as being in the left interval [0, 1/a] (labelled L) or the half-open right interval (1/a, 1] (labelled R). For certain x the expansion (1.2) contains only finitely many R’s, and the corresponding itinerary is then I(x) L"oR RnRL; these numbers x are exactly the preperiodic points of 0, denoted Per0(T,). Part I studied the set Per(T) of the eventually periodic points of T and proved that for certain values of a, called special Pisot numbers, one has