Miracle-dz/UniFAR-FTUs huggingface dataset:
Sofware-Defined Space-Ground-Vehicle Integrated Network Architecture for Unconscious Payment

The continuous development trend of expressways urgently needs expressway sensing, which is required to be able to perceive unknown risk factors to ensure a safe and stable transportation environment as well as effectively and continuously monitor the safe operation of expressways. Using unconscious payment can greatly improve traffic efficiency and meet the development direction of intelligent transportation. However, charging errors occur when using unconscious payment, primarily because the expressway network fails to realize national networking. Most of the literature focuses on two aspects of sensing, transmission and computing, while research on the overall network architecture is lacking. A ground network cannot solve the network coverage problem in remote areas. Therefore, the basic infrastructure needed to realize expressway sensing includes both aerial and ground nodes, such as cars, roadside equipment, unmanned aerial vehicles, airships, and satellites. This network communication architecture requires effective management of infrastructure and support of various applications. The software-defined network has strong flexibility; thus, in this paper, we propose a software-defined space-ground-vehicle integrated network (SD-SGVIN) architecture that includes three layers: physical facility, logic control, and application. The SD-SGVIN can separate the highway sensing applications from the physical entity. All kinds of applications can acquire, transmit, and process vehicle data through a shared physical infrastructure. We discuss the design, implementation, and advantages of the proposed network structure, hoping to provide a new direction for the research and promotion of expressway sensing and unconscious payment.
Personality Traits and Coping Strategies Relevant to Posttraumatic Growth in Patients with Cancer and Survivors: A Systematic Literature Review

The possibility of positive psychological changes after cancer, namely, posttraumatic growth, is a growing field of research. Identifying personality traits and coping strategies related to posttraumatic growth may help find vulnerable individuals as well as promote helpful coping strategies to help more patients make positive changes at an early stage. The aim of this systematic literature review is to provide an overview of the quantitative data on coping strategies and personality traits associated with posttraumatic growth in patients with cancer and cancer survivors as well as the methods used in included studies. A systematic literature search was conducted using five databases (PubMed, PubPsych, PsycInfo, Web of Science, and PSYNDEXplus). The 70 reports of included studies assessed posttraumatic growth using questionnaires in a sample of patients with cancer or survivors. In addition, associations with a personality trait or coping strategy had to be examined cross-sectionally or longitudinally. All 1698 articles were screened for titles and abstracts by two authors, after which disputed articles were reviewed by a third author. Afterwards, articles were screened for full texts. Most studies had a cross-sectional design and used a sample of patients with breast cancer. Coping strategies have been researched more than personality factors. The personality traits of resilience, hardiness, dispositional positive affectivity, and dispositional gratitude seem to be related to posttraumatic growth, while the Big Five personality traits (openness to experience, conscientiousness, extraversion, agreeableness, neuroticism) have been less researched and/or seem to be unrelated. The use of social support, religious coping, positive reframing, and reflection during illness as coping strategies seems to be related to posttraumatic growth. The findings can be used for the development of interventions. Future studies should investigate associations longitudinally.
Application of Hidden Markov Models in Stock Forecasting

In this paper, we tested our methodology on the stocks of four representative companies: Apple, Comcast Corporation (CMCST), Google, and Qualcomm. We compared their performance to several stocks using the hidden Markov model (HMM) and forecasts using mean absolute percentage error (MAPE). For simplicity, we considered four main features in these stocks: open, close, high, and low prices. When using the HMM for forecasting, the HMM has the best prediction for the daily low stock price and daily high stock price of Apple and CMCST, respectively. By calculating the MAPE for the four data sets of Google, the close price has the largest prediction error, while the open price has the smallest prediction error. The HMM has the largest prediction error and the smallest prediction error for Qualcomm’s daily low stock price and daily high stock price, respectively.
Do Socio-economic Factors Drive Peer to Peer Lending? Analysis in Indonesia

: This study aims to analyse the determinant of p2p lending by examine the social and economic factors to accumulated loan disbursement. Since the increasing number of lender and borrower indicates the higher potential to grow, this study examines the factor affected significantly in p2p lending transactions. The data extracted from Financial Service Authority (OJK) report from 2019-2020 and The National Socioeconomic Survey (Susenas) from Central Bureau of Statistics (BPS). The analysis method uses OLS regression to test each of hypothesis. This study verified that there is relationship between social and economic factor especially formal labour and high education with accumulated loan of borrower. The result leads the regulation and fintech platform to make analysis of social-economic matter regards financial technology-based service. The result of this study has significant implication to p2p lending theoretically since it analyses the social and economic determinant factors by using the secondary data. Practically, the findings of the study could give additional information to reach and engage the user by identify social and economic factors. Few studies identified the determinant by using empirical analysis. Previous study mainly identified the determinant from qualitative reviews and the majority of the studies employ interview to address the determinant factor.
Cervical Tissue Hydration Level Monitoring by a Resonant Microwave Coaxial Probe

Cervical tissue hydration level is one of the most important parameters to monitor in the early diagnosis of preterm birth. Electrical-impedance-spectroscopy-based techniques are often used, but they suffer from limited accuracy. Open microwave coaxial probes have been widely used as a broadband dielectric characterization technique for human tissue samples due to their versatility, but with limited accuracy due to their nonresonant nature. In this work, a resonant microwave open coaxial probe with multiple harmonic resonances is proposed as a sensing platform for tissue-hydration-level monitoring. The mechanical design was analyzed and verified by finite-element full 3D electromagnetic simulation and experiments. Dominant sources of errors and the ways to mitigate them were discussed. In vitro experiments were carried out on human cervix samples to verify the precision and accuracy by comparing the results to a commercial skin-hydration sensor. The proposed sensor shows mean fractional frequency shift of (3.3 ± 0.3) × 10−4 per unit % over the entire data. This translates into an absolute frequency shift (ΔfN) of 252 ± 23 kHz/%, 455 ± 41 kHz/%, and 647 ± 57 kHz/% at second, fourth, and sixth harmonic resonance, respectively.
Molecular detection of HHV-1, HHV-2, HHV-5 and HBV in semen of fertile and infertile men by multiplex PCR method

Background and Objectives: A great diversity of factors including viruses such as human herpes virus 1&2 (HHV-1&2), human herpes virus 5 (HHV-5), and hepatitis B virus (HBV) play key roles in sterility and it is worth noting that male infertility accounts for nearly 50% of barrenness, globally. In this regard, we evaluated the prevalence of the aforementioned viruses in semen specimens of two distinct groups of men referred to Novin Infertility Center in Mashhad, Iran. Materials and Methods: In this cross-sectional study, 300 semen samples were collected from 150 infertile and 150 fertile men. Subsequently, genomic DNA was extracted before performing multiplex polymerase chain reaction (PCR). Eventually, the results were analyzed via SPSS Statistics V.16. 0. Results: Out of 300 specimens, 183 (61.1%) were positive at least for one of the forenamed viruses; genome detection of HHV-1&2, HHV-5, and HBV were 27%, 18%, 36.66%, and 4%, respectively. Conclusion: The current study found no correlation between infertility and HBV, HHV-5, and HHV-1&2, which may have to do with factors like sample size, the geographical distribution of the viruses, and the lifestyle (sexual behavior) of the participants. These results emphasize the implementation of such studies on a broader scale to determine the exact factors involved in infertility.
Development of Early Grade Indonesian E-Modules Using the Kvisoft Flipbook Maker Application

This article aims to 1) Produce products in the form of e-modules for Early Class Indonesian courses using the Kvisoft Flipbook Maker Application; 2) To find out the feasibility of developing an e-module based on the Kvisoft Flipbook Maker Application in the Early class Indonesian language course; 3) To find out students' responses to the development of e-modules based on the Kvisoft Flipbook Maker application in the Early Grade Indonesian course. The type of research conducted is research and development (R&D). The development model used in this study is a 4-D development model (four D Model), namely define activities, design activities, development activities and are validated by experts and see the practicality of e-module products. 1) The results of material expert validation obtained an average of 86% in the very feasible category. Second, media experts get an average of 93% in the very decent category. Third, linguists get an average of 87% with a very decent category. Then, in individual trials, students responded to this e-module in the very good category with an average percentage of 93%. In the small group trial, the students' responses were in the very good category with an average percentage of 92.25%. Meanwhile, in the limited field group trial, the criteria of "good" were obtained with an average score percentage of 87,08%. Based on this percentage, it can be concluded that this e-module is suitable to be used as teaching material for Indonesian language courses in the Early Class of HKBP Nommensen, Pematangsiantar University. Keywords: Kvisoft Flipbook Maker, E-Modules for Early Grade, Deveopment E-Modules
Ocular Artifacts Elimination From Multivariate EEG Signal Using Frequency-Spatial Filtering

The electroencephalogram (EEG) signals record electrical activities generated by the brain cells and are used as a state-of-the-art diagnosis tool for various neural disorders. However, the unwanted artifacts often contaminate the recorded EEG signals and disturb the interpretation of the neuronal activity. This article aims to propose an efficient automatic method to eliminate the ocular artifacts (OAs) from the multichannel EEG signals with novel frequency-spatial filtering. The method combines dictionary-based spatial filtering and frequency-based signal decomposition method, namely, empirical wavelet transform (EWT). The artifact dictionary needed for spatial filtering is isolated from the raw data by: 1) selecting the contaminated channels and 2) frequency-domain filtering. More precisely, the <inline-formula> <tex-math notation="LaTeX">$\delta $ </tex-math></inline-formula>-rhythms of identified highly contaminated channels are selected and placed into an artifact dictionary. Afterward, the <inline-formula> <tex-math notation="LaTeX">$\delta $ </tex-math></inline-formula>-rhythms of multichannel EEG signals are spatially filtered using the built dictionary to seclude the OAs within a limited number of components. Furthermore, the artifact components are eliminated and clean <inline-formula> <tex-math notation="LaTeX">$\delta $ </tex-math></inline-formula>-rhythms are recovered using the inverse spatial filtering technique. Finally, the clean <inline-formula> <tex-math notation="LaTeX">$\delta $ </tex-math></inline-formula>-rhythms are combined with other EEG rhythms to reconstruct the OA-free signals. The proposed method is applied to OA-contaminated synthetic and real multichannel EEG signals with a convincing performance as compared to state-of-the-art approaches. The proposed method removes the OAs without affecting the background EEG information. The proposed method can ease sensor signal interpretation and further processing, e.g., for BCI applications.
Immunoprotective Analysis of the NFA49590 Protein from Nocardia farcinica IFM 10152 Demonstrates Its Potential as a Vaccine Candidate

Nocardia is emerging as a serious and easily neglected pathogen in clinical practice with multidrug resistance that extends the treatment period for months or even years. This has led to the investigation of a vaccine approach to prevent Nocardia infections. However, studies on the protective proteins of Nocardia have not yet been carried out. In the present work, over 500 proteins in the supernatant of N. farcinica IFM10152 were identified by LC–MS/MS. In silico analysis of these proteins with a high content (score > 2000) predicted that NFA49590 was one of the conserved proteins in N. farcinica strains with potential antigenicity. After the rNFA49590 protein was cloned and expressed in E. coli (DE3) and purified using a Ni-NTA column, its good antigenicity was confirmed with sera from mice immunized with different Nocardia species by Western blot. Then we confirmed its ability to activate innate immunity by examining the phosphorylation status of ERK1/2, JNK, p38, and p65 and the cytokine levels of IL-6, TNF-α, and IL-10. Finally, we evaluated its immunoprotective effect in BALB/c mice, and we found that mice immunized with rNFA49590 protein exhibited high antibody titers, enhanced bacterial clearance ability, and generated robust protective effects from the N. farcinica challenge. These results offer strong support for the use of NFA49590 protein as a vaccine candidate and open the possibilities for the exploration of a large array of immunoprotective proteins.
Additional measurements and a refined analysis of the millimeter- and submillimeter-wave spectrum of methanol

A total of 414 previously unobserved millimeter- and submillimeter-wave transitions of (C-12)H3OH through J = 10 and v(t) = 2 are assigned. These data and previous measured spectral transitions are combined and fitted by a modified internal axis method (IAM) treatment in which the A and E substates are treated separately and a wide variety of new rotational-torsional interaction terms are employed. The modified IAM treatment reduces the overall rms deviation of the fits to the level of experimental accuracy. The resultant spectroscopic constants allow for the accurate prediction of 569 additional transitions through J = 12 or less. 25 refs.
Analysis of the Cell-Vertex Finite Volume Method for Hyperbolic Problems with Variable Coefficients

An analysis of the cell-vertex finite volume method is presented for a scalar linear hyperbolic equation with variable coefficients. The cell-vertex approximation is shown to be second-order convergent in the L2-norm and first-order convergent in the H1-norm, provided the exact solution belongs to H3 and the characteristic curves of the differential equation are transversal to mesh lines on the closure of the domain of integration. When characteristics are parallel to mesh lines on a subset of positive measure the scheme is only first-order convergent in the L2-norm. However, if transversality fails on part of the outflow boundary only, then the cell-vertex scheme is second-order convergent in a weighted L2-norm.
Analysis of Multistage Production Systems

The control of inventories of physical objects has been the theme of literally thousands of technical and trade journal articles during this century. Since Harris [1915] described the basic trade-offs that need to be made when making these control decisions, numerous models and algorithms have been devised that indicate how basic control parameters should be established. In his work, Harris, to our knowledge, provided the first derivation of the economic lot size formula, or economic order quantity (EOQ) formula. Later Raymond [1931] wrote the first full book on the topic of inventory control in which he explained, without the aid of mathematical theory, how extensions of the now classic EOQ problem could be implemented. It was not until the 1950s when more serious mathematical analyses of various inventory problems were undertaken. Whitin's [1953] stochastic version of the EOQ model and works by Arrow, Harris, & Marshak [1951], Dvoretzky, Kiefer, & Wolfowitz [1952, 1953] and Arrow, Karlin, & Scarf [1958] provided the mathematical basis for subsequent extensions of the single location model. Also see Chapter 1 of this volume. The first multi-stage models were developed at about the same time. The important works of Clark & Scarf [1960, 1962] and the papers found in the book edited by Scarf, Gilford, & Shelly [1963] generated considerable interest from both academics and practitioners. The orten quoted text by Hadley & Whitin [1963] and the survey paper by Veinott [1966] provide excellent summaries of many of these early modeling efforts. While rauch of this work concentrated on stochastic modeling, there was and currently is a strong interest in developing further extensions of Harris' basic EOQ model. These extensions include single item, single location models that consider backordering, finite production rates, and quantity discounts of several types, and multi-item models that represent joint replenishment problems and c o n -
Gel Cohesivity and Breast Augmentation: Applications to Clinical Practice

Abstract Matching breast implant gel cohesivity to the patient's needs based on anatomical and soft-tissue considerations and patient preferences is essential to optimizing aesthetic outcomes and patient satisfaction. Generally, gel cohesivity contributes to the feel and shape of the breast, which reflects volume distribution within the breast. Studies on the physical properties of silicone gel breast implants have established the relative cohesivity of implants from several manufacturers. Comprehensive patient education, tissue-based preoperative planning, and a thorough understanding of how implant properties may affect outcomes are recommended before breast augmentation. This review summarizes the literature on breast implant physical properties with a focus on gel cohesivity and translates gel cohesivity to practical considerations in choosing the right implant for the right patient in primary augmentation. Based on clinical experience, the authors generally recommend lower cohesivity implants for patients who desire a tapered upper pole or a natural appearance/“anatomic shape” as well as for those with a high BMI or a large amount of native breast tissue. Medium-cohesivity implants are most widely used and are appropriate for those with ptosis/augmentation mastopexy, patients with tight skin envelope, and for those seeking upper pole fullness. A high-cohesivity implant is recommended for patients desiring a round shape, patients with constricted lower poles, and patients with a postpartum loose envelope, a thin, soft tissue envelope, or fibrous breast tissue. Level of Evidence: 5
Estimation of direct effects for survival data by using the Aalen additive hazards model

Summary. We extend the definition of the controlled direct effect of a point exposure on a survival outcome, other than through some given, time‐fixed intermediate variable, to the additive hazard scale. We propose two‐stage estimators for this effect when the exposure is dichotomous and randomly assigned and when the association between the intermediate variable and the survival outcome is confounded only by measured factors, which may themselves be affected by the exposure. The first stage of the estimation procedure involves assessing the effect of the intermediate variable on the survival outcome via Aalen's additive regression for the event time, given exposure, intermediate variable and confounders. The second stage involves applying Aalen's additive model, given the exposure alone, to a modified stochastic process (i.e. a modification of the observed counting process based on the first‐stage estimates). We give the large sample properties of the estimator proposed and investigate its small sample properties by Monte Carlo simulation. A real data example is provided for illustration.
Mitigating Influence of Disinformation Propagation Using Uncertainty-Based Opinion Interactions

For decades, the spread of disinformation in online social networks (OSNs) has been a serious social issue. Disinformation via social media can easily mislead people’s beliefs toward or against an event that may mislead their behaviors based on the misbeliefs. The game theory approaches have been proposed under dynamic settings to limit the adverse influences of disinformation. It is a challenge to expand the users’ game strategies from the spreading decisions to the possible opinion updating choices. This work proposes a game-theoretic opinion framework that can formulate dynamic opinions by a belief model called Subjective Logic (SL) and provide opinion updates on five types of users’ interactions on OSN platforms. The opinions are updated based on user choices and user types through the game interactions among legitimate users, attackers, and a defender in an OSN. Via the extensive simulation experiments, the effectiveness of the opinion models of five decision-makers (DMs) is analyzed in terms of users believing or disbelieving disinformation in an epidemic model with parameter optimization. Our results show that while homophily-based DMs (H-DMs) introduce the highest opinion polarization, uncertainty-based DMs (U-DMs) can effectively filter untrustworthy users propagating disinformation.