Miracle-dz/UniFAR-FTUs huggingface dataset:
On the scalability of data augmentation techniques for low-resource machine translation between Chinese and Vietnamese

ABSTRACT Neural Machine Translation (NMT) has constantly been shown to be a standard choice to build a translation system, in both academia and industry. For low-resource language pairs, data augmentation techniques have been widely used to tackle the data shortage problem in NMT. In this paper, we investigate the scaling behaviour of transformer-based NMT model to the increasing amount of synthetic data. Through the experiments, conducted in the Chinese-to-Vietnamese translation task, we aim to provide a guideline to the application of several methods such as back-translation, tagged back-translation, self-training and sentence concatenation in a low-resource, less-related language pair. Our results suggest that choosing the appropriate amount of synthetic data is a crucial task when building NMT systems. In addition, when combining methods, it is recommended to tag the data sources before training.
Risk factors associated with the discordance in kidney function decline rate in identical twins

Background The rate of kidney function decline is different for each individual regardless of any difference in the medical histories. This study set out to identify the risk factors for high discordance in kidney function decline in an identical twin cohort. Methods This study included 333 identical twins from the Korean Genome and Epidemiology Study who were categorized into two groups according to the estimated glomerular filtration rate (eGFR) decline: the slow and rapid progressor groups. The mean differences of variables were compared between the two groups. We calculated the difference in the annual eGFR change between twins and analyzed the risk factors associated with high discordance in twins who had > 5 mL/min/1.73 m2 /yr of the intra-twin difference in the annual eGFR decline. Identical twins with diabetes and baseline eGFR < 60 mL/min/1.73 m2 were excluded. Results The high discordance twins showed significant differences in body mass index; waist-to-hip ratio; total body fat percentage; and levels of blood hemoglobin, serum fasting glucose, albumin, triglyceride, and uric acid; however, there were no differences in low discordance twins. Multivariable logistic regression showed that blood hemoglobin level is the only significant factor associated with high discordance of eGFR decline in twins. Conclusions Blood hemoglobin level may play a role in the individual differences in kidney function decline.
A Mean-VaR Based Deep Reinforcement Learning Framework for Practical Algorithmic Trading

It is difficult to automatically produce trading signals based on previous transaction data and the financial status of assets because of the significant noise and unpredictability of capital markets. This paper proposes an innovative algorithm to solve the optimal portfolio problem in stock market trading activities. Our novel portfolio trading strategy utilizes three features to outperform other benchmark strategies in a real-market environment. First, we propose a mean-VaR portfolio optimization model, the solution of which is based on the actor-critic architecture. Unlike the existing literature that learns the expectation of cumulative returns, the critic module learns the cumulative returns distribution by quantile regression, and the actor module outputs the optimal portfolio weight by maximizing the objective function of the optimization model. Secondly, we use a linear transformation function to realize short selling to ensure investors have profit opportunities in the bear market. Third, A multi-process method, called Ape-x, was used to accelerate the speed of deep reinforcement learning training. To validate our proposed approach, we conduct backtesting for two representative portfolios and observe that the proposed model in this work is superior to the benchmark strategies.
A Grouping Design for Cascaded Coded Distributed Computing

In order to reduce the communication load in general distributed computing frameworks such as MapReduce Li et al. introduced coded distributed computing (CDC). The authors in [1] proposed a scheme for cascaded coded distributed computing on general networks. Although the numbers of input files and output functions in [1] are much less than those in [2], large numbers of input files and output functions are still required. In this paper, we present a new CDC scheme which 1) designs the assignments of input file and output function; 2) requires less number of input files and output functions compared with those in the scheme derived by [1]. Meanwhile, the ratio of communication load to that of the scheme in [1] is less than $\mathbf{the}\frac{4}{3}$.
Pansharpening Using Unsupervised Generative Adversarial Networks With Recursive Mixed-Scale Feature Fusion

Panchromatic sharpening (pansharpening) is an important technology for improving the spatial resolution of multispectral (MS) images. The majority of the models are implemented at the reduced resolution, leading to unfavorable results at the full resolution. Moreover, the complicated relationship between MS and panchromatic (PAN) images is often ignored in detail injection. For the mentioned problems, unsupervised generative adversarial networks with recursive mixed-scale feature fusion for pansharpening (RMFF-UPGAN) are modeled to boost the spatial resolution and preserve the spectral information. RMFF-UPGAN comprises a generator and two U-shaped discriminators. A dual-stream trapezoidal branch is designed in the generator to obtain multiscale information. Further, a recursive mixed-scale feature fusion subnetwork is designed. Perform a prior fusion on the extracted MS and PAN features of the same scale. A mixed-scale fusion is conducted on the prior fusion results of the fine scale and coarse scale. The fusion is executed sequentially in the aforementioned manner building a recursive mixed-scale fusion structure, and finally, generating key information. A compensation information mechanism is also designed for the reconstruction of key information to compensate for information. A nonlinear rectification block for the reconstructed information is developed to overcome the distortion induced by neglecting the complicated relationship between MS and PAN images. Two U-shaped discriminators are designed and a new composite loss function is defined. The presented model is validated using two satellite data and the outcomes reveal better than the prevalent approaches regarding both visual assessment and objective indicators.
Securing Network Information System Design: An Efficient Tool for DSP Undocumented Instruction Mining

As recently studied, the undocumented instructions in embedded processors that may cause catastrophic results for devices have become one of the main threats to system security. To tackle this issue, in this paper, we propose an undocumented instruction mining tool for digital signal processors named DSPUIM that can find out the undocumented instructions from the frequently used Digital Signal Processors (DSP) in network information systems. First, we analyzed the characteristics of the DSP instruction format to compress the instruction search space and improve the instruction search speed. Second, according to the public instruction set of DSPs, we built an instruction disassembly framework that helped us to identify all the undefined instructions. Finally, by testing the executability of undefined instructions automatically, we obtained the undocumented instructions for target DSPs. To demonstrate the effectiveness of our tool, we applied it on ten DSP processors of Texas Instruments (TI) and mined 335 undocumented instructions from them within 5 min. Some undocumented instructions have malicious functions, such as changing registers and denial of service, posing a security threat to the network devices using DSPs.
WildStress: exploring rich situational contexts for stress detection in the wild

Short-term experience of stress arousal can be useful in coping with everyday life tasks. However, undergoing intense stressful scenarios frequently and consistently can be damaging for mental and physical health. To detect such stressful scenarios physiological stress models were developed in lab conditions, but still showed poor results in daily life settings. Hence, leveraging rich contextual information about user’s daily life can help identify stress in uncontrolled daily life environments. To that end, this work details on our research direction, that is to use rich contextual data captured from users’ daily lives alongside physiological readings to timely detect in the wild stress.
Minimization of the error in the calculation of the steady state by shooting methods

The periodic steady state of a circuit can be calculated with a variety of algorithms. One of them is the (multiple-) shooting method. For good performance, the shooting analysis uses a higher order multistep backward-integration method for the computation. Normally, in the very first step, the Gear 1 integration formula is used because no information of previous discretization points are available. The next step can be calculated with the second-order formula. After the calculation of (k-1) successive time-steps, it is possible to switch to the desired (kth-order) integration formula. The switching introduces an error to the solution of the steady state, which can be observed by a subsequent Fourier transformation. This paper presents a straightforward method to suppress the problem by generating additional starting values. The novel formulation is compared with the conventional shooting method on two example circuits.
Combining x-ray real and reciprocal space mapping techniques to explore the epitaxial growth of semiconductors

In the present work, the importance of determining the strain states of semiconductor compounds with high accuracy is demonstrated. For the matter in question, new software titled LAPAs, the acronym for LAttice PArameters is presented. The lattice parameters as well as the chemical composition of Al1−x In x N and Ge1−x Sn x compounds grown on top of GaN- and Ge- buffered c-Al2O3 and (001) oriented Si substrates, respectively, are calculated via the real space Bond’s method. The uncertainties in the lattice parameters and composition are derived, compared and discussed with the ones found via x-ray diffraction reciprocal space mapping. Broad peaks lead to increased centroid uncertainty and are found to constitute up to 99% of the total uncertainty in the lattice parameters. Refraction correction is included in the calculations and found to have an impact of 0.001 Å in the lattice parameters of both hexagonal and cubic crystallographic systems and below 0.01% in the quantification of the InN and Sn contents. Although the relaxation degrees of the nitride and tin compounds agree perfectly between the real and reciprocal-spaces methods, the uncertainty in the latter is found to be ten times higher. The impact of the findings may be substantial for the development of applications and devices as the intervals found for the lattice match the condition of Al1−x In x N grown on GaN templates vary between ∼1.8% (0.1675–0.1859) and 0.04% (0.1708–0.1712) if derived via the real- and reciprocal spaces methods.
Structure and Technological Parameters’ Effect on MISFET-Based Hydrogen Sensors’ Characteristics

The influence of structure and technological parameters (STPs) on the metrological characteristics of hydrogen sensors based on MISFETs has been investigated. Compact electrophysical and electrical models connecting the drain current, the voltage between the drain and the source and the voltage between the gate and the substrate with the technological parameters of the n-channel MISFET as a sensitive element of the hydrogen sensor are proposed in a general form. Unlike the majority of works, in which the hydrogen sensitivity of only the threshold voltage of the MISFET is investigated, the proposed models allow us to simulate the hydrogen sensitivity of gate voltages or drain currents in weak and strong inversion modes, taking into account changes in the MIS structure charges. A quantitative assessment of the effect of STPs on MISFET performances (conversion function, hydrogen sensitivity, gas concentration measurement errors, sensitivity threshold and operating range) is given for a MISFET with a Pd-Ta2O5-SiO2-Si structure. In the calculations, the parameters of the models obtained on the basis of the previous experimental results were used. It was shown how STPs and their technological variations, taking into account the electrical parameters, can affect the characteristics of MISFET-based hydrogen sensors. It is noted, in particular, that for MISFET with submicron two-layer gate insulators, the key influencing parameters are their type and thickness. Proposed approaches and compact refined models can be used to predict performances of MISFET-based gas analysis devices and micro-systems.
Toward the Improvement of Silicon-Based Composite Electrodes via an In-Situ Si@C-Graphene Composite Synthesis for Li-Ion Battery Applications

Using Si as anode materials for Li-ion batteries remain challenging due to its morphological evolution and SEI modification upon cycling. The present work aims at developing a composite consisting of carbon-coated Si nanoparticles (Si@C NPs) intimately embedded in a three-dimensional (3D) graphene hydrogel (GHG) architecture to stabilize Si inside LiB electrodes. Instead of simply mixing both components, the novelty of the synthesis procedure lies in the in situ hydrothermal process, which was shown to successfully yield graphene oxide reduction, 3D graphene assembly production, and homogeneous distribution of Si@C NPs in the GHG matrix. Electrochemical characterizations in half-cells, on electrodes not containing additional conductive additive, revealed the importance of the protective C shell to achieve high specific capacity (up to 2200 mAh.g−1), along with good stability (200 cycles with an average Ceff > 99%). These performances are far superior to that of electrodes made with non-C-coated Si NPs or prepared by mixing both components. These observations highlight the synergetic effects of C shell on Si NPs, and of the single-step in situ preparation that enables the yield of a Si@C-GHG hybrid composite with physicochemical, structural, and morphological properties promoting sample conductivity and Li-ion diffusion pathways.
Expanding the Chemical Space of Arsenicin A-C Related Polyarsenicals and Evaluation of Some Analogs as Inhibitors of Glioblastoma Stem Cell Growth

The marine polyarsenical metabolite arsenicin A is the landmark of a series of natural and synthetic molecules characterized by an adamantane-like tetraarsenic cage. Arsenicin A and related polyarsenicals have been evaluated for their antitumor effects in vitro and have been proven more potent than the FDA-approved arsenic trioxide. In this context, we have expanded the chemical space of polyarsenicals related to arsenicin A by synthesizing dialkyl and dimethyl thio-analogs, the latter characterized with the support of simulated NMR spectra. In addition, the new natural arsenicin D, the scarcity of which in the Echinochalina bargibanti extract had previously limited its full structural characterization, has been identified by synthesis. The dialkyl analogs, which present the adamantane-like arsenicin A cage substituted with either two methyl, ethyl, or propyl chains, were efficiently and selectively produced and evaluated for their activity on glioblastoma stem cells (GSCs), a promising therapeutic target in glioblastoma treatment. These compounds inhibited the growth of nine GSC lines more potently than arsenic trioxide, with GI50 values in the submicromolar range, both under normoxic and hypoxic conditions, and presented high selectivity toward non-tumor cell lines. The diethyl and dipropyl analogs, which present favorable physical-chemical and ADME parameters, had the most promising results.
Primary Students’ Attitudes towards Peers with Disabilities in Physical Education in Saudi Arabia

The attitudes of students without disabilities toward their peers with disabilities are considered an important determinant of successful inclusion in physical education settings. Nonetheless, there is limited research on this topic in non-Western societies, especially in Arab contexts. Thus, to address this paucity in the literature, this study aimed to assess the general attitudes of Saudi students without disabilities towards their peers with disabilities and examine the associations between selected student-related variables (e.g., gender, age, type of school, school location, having a family member or a friend or a classmate with a disability, and having experience of playing with a person with a disability) and attitudes of students without disabilities. A total of 972 students aged 9–12 years old (Mage = 10.6; SD = 1.1; girls = 49.7%) completed the Arabic version of the Scale of Attitudes toward Students with Disabilities in Physical Education—Primary Education (SASDPE-PE). Data analysis indicated that, in general, participants reported positive attitudes toward their peers with disabilities in physical education classes. Despite boys being more likely to hold positive attitudes than girls, no significant difference between them existed. The results showed that 10-year-old participants reported more significantly positive attitudes than those in the other age groups. Participants attending public schools reported more significant positive attitudes toward their peers with disabilities in physical education classes compared to those attending private schools. Having a friend with a disability was linked to students without disabilities having positive attitudes towards their peers with disabilities. In contrast, having a family member or a classmate with disabilities and having played with a person with a disability were not related to such positive attitudes. The current study’s findings have significant implications for inclusive educational practices.
Radio wave scattering from the tropical mesosphere observed with the Jicamarca radar

Using the VHF radar (49.92 MHz) at Jicamarca (12.0°S, 76.9°W), radio wave scattering from the tropical mesosphere was observed for more than 60 hours on November 14–16, 1977. The 60- to 90-km region was probed at 2.5-km intervals in two antenna beam directions: the vertical and 3.45° from the zenith to the west. Strong aspect sensitive scattering that is accompanied by a marked positive correlation between the temporal variation of the echo power and the signal correlation time is observed below about 75 km as in previous measurements. Above that altitude, the correlation becomes negative while the scattering is virtually isotropic. This difference appears to be directly related to the stability of the atmosphere, and enhanced reflectivity regions seem to be narrow structures that are horizontally stratified below 75 km. The rms turbulent velocity fluctuations generally increase above 75 km. Signal correlation time depends upon the period of data used to calculate power spectra in the period of 10–60 s, suggesting that there exist substantial velocity fluctuations on short time scales.
Lockdown life - experiences of partners of individuals with an acquired brain injury during the COVID-19 pandemic: a qualitative study

Abstract Objectives: The present study sought to investigate the experience of individuals living with their partner with an acquired brain injury (ABI) during the first lock down period of the COVID-19 pandemic. Method: Semi-structured interviews were conducted with seven partners of individuals who had sustained a range of ABIs. Interviews were transcribed verbatim and thematic analysis was carried out by two of the researchers exploring the unique narratives. Results: ABI occurs within a relational framework, which means that it has repercussions not only for the individual but also the entire family system. COVID-19 prevented family systems (living separately) from coming together which negatively impacted them; however, it also slowed life down, with many people working from home with flexible arrangements in place which participants found to be beneficial. Three main themes emerged from the interview data: partner focus, slowing down and support networks. The narratives identified the struggles of having to continue their partner’s rehabilitation when face to face services could not visit the home, the importance of establishing routine, the positives of a slower paced life (due to COVID-19) that enabled them to build stronger relationships with their partners, and the difficulties of being separated from family and loved ones. Conclusion: This research suggests that it is imperative to consider individual experiences and choices. Some families benefited from reduced treatment and a slowed pace of life, whilst others may find this overwhelming and burdensome. The study makes recommendations for supporting couples after an ABI during the ongoing pandemic.
Abundance of ACVR1B transcript is elevated during septic conditions: Perspectives obtained from a hands-on reductionist investigation

Sepsis is a complex heterogeneous condition, and the current lack of effective risk and outcome predictors hinders the improvement of its management. Using a reductionist approach leveraging publicly available transcriptomic data, we describe a knowledge gap for the role of ACVR1B (activin A receptor type 1B) in sepsis. ACVR1B, a member of the transforming growth factor-beta (TGF-beta) superfamily, was selected based on the following: 1) induction upon in vitro exposure of neutrophils from healthy subjects with the serum of septic patients (GSE49755), and 2) absence or minimal overlap between ACVR1B, sepsis, inflammation, or neutrophil in published literature. Moreover, ACVR1B expression is upregulated in septic melioidosis, a widespread cause of fatal sepsis in the tropics. Key biological concepts extracted from a series of PubMed queries established indirect links between ACVR1B and “cancer”, “TGF-beta superfamily”, “cell proliferation”, “inhibitors of activin”, and “apoptosis”. We confirmed our observations by measuring ACVR1B transcript abundance in buffy coat samples obtained from healthy individuals (n=3) exposed to septic plasma (n = 26 melioidosis sepsis cases)ex vivo. Based on our re-investigation of publicly available transcriptomic data and newly generated ex vivo data, we provide perspective on the role of ACVR1B during sepsis. Additional experiments for addressing this knowledge gap are discussed.
A Spiral Array for OAM Mode Generation

This paper presents the generation of various OAM modes using novel spiral array of rectangular patch antennas. The proposed design ceases the requirement of a complex power dividing phased network. The presented OAM antenna is designed to resonate at 5.2 GHz for WLAN applications and can generate OAM beam with topology charge l = 0, ±1. A comparison study of the new OAM design with the conventional Uniform Circular Array (UCA) used for OAM modes generation is also presented.