bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-OLT PON-based open access network for multi-service performance tuning via the Event-Horizon algorithm
Authors: Rawshan Fahmida , Hossen Monir , Islam Md. Rafiqul , Park Youngil 
Published: February 2023

A multi-optical line terminal (multi-OLT) passive optical network (PON) is gaining attention for its multi-access, wide coverage, and integration capabilities. It outperforms conventional single OLT PON, reducing operational complexities, packet delay, and loss. A novel multi-OLT PON-based open-access network (OAN) architecture is proposed that integrates various service providers (SPs) as well as different access networks. Optical network unit structure is also designed to support differential access. The challenging issue here is to incorporate heterogeneous SPs and provoke downstream service with their application diversity. This paper presents what we believe is a novel algorithm named Event-Horizon (EH) to afford heterogeneous downstream services from different SPs for IEEE PONs [Ethernet PON (EPON) and 10 gigabit EPON (10G EPON)]. It incites SP competitiveness and ensures a user experience of seamless migration from service to service. Downstream resource allocation is an atypical issue in the PON area. There are reported numerous online schemes with prediction for the upstream side. Since network data is highly bursty and unpredictable, the EH algorithm uses the machine-learning-based bootstrapping method as its prediction tool. The algorithm improves downstream performance by four distinctive features. First, bandwidth is guaranteed among shared SPs according to service level agreements. Second, bandwidth is allocated for reported data; then excess bandwidth is reallocated as predicted (by bootstrapping) differed data. Third, a donor SP preserves margin before excess bandwidth release, which is a nonlinear process featuring network dynamics. Fourth, the margin satisfaction factor is formulated for tuning multi-service user satisfaction according to quality of service. The simulation is performed by a model OAN showing an emergency medical wireless sensor network (WSN) as the master shareholder OLT and a fiber to the home (FTTH) as a subsidiary one. Performance tuning on the margin reservation of 1% for the WSN case study shows 99.4% network efficiency with maximum jitter of 50 µs up to the full load owing 97.26% throughput. Network delay justifies CISCO and ITU-T requirements for real-time IP traffic. FTTH experiences the packet loss of 0.68% using the EH algorithm at the full load, maintaining WSN emergency service packet loss<0.003%.
Spiral waveguide Bragg grating modulator on thin-film Z-cut lithium niobate
Authors: Ghoname Amr O. , Hassanien Ahmed E. , Chow Edmond , Goddard Lynford L. , Gong Songbin 
Published: February 2023

Next-generation photonic integrated circuits require compact electro-optic modulators (EOMs) that achieve high performance and efficient use of the on-chip area simultaneously. We demonstrate a compact EOM based on a spiral-shaped waveguide Bragg grating on thin-film lithium niobate. The modulator utilizes the grating’s optical filter characteristics along with electro-optic tuning of the central Bragg wavelength to achieve simple and efficient intensity modulation. The spiral Bragg gratings were realized on Z-cut lithium niobate and modulated using top and bottom electrodes. The integrated design wrapped a 2.2 mm long grating into a 120×120µm2 area. The modulator bandgap, with an extinction ratio of over 35 dB at 1550 nm, could be efficiently tuned with a sensitivity of 8.36 pm/V and a 3 dB operating bandwidth of 25 GHz.
Dual narrow surface lattice resonances in Si/SiO2 nanopillar dimer arrays
Authors: Huang Xiaodan , Shao Guojian 
Published: February 2023

Si/SiO2 nanopillar dimer arrays are proposed to form two narrow surface lattice resonances (SLRs). One (named SLR1) mainly comes from the coupling between single Si/SiO2 nanopillar dimers’ electric dipole resonance and arrays’ diffraction waves. Another (named SLR2) mainly comes from the coupling between single Si/SiO2 nanopillar dimers’ magnetic dipole resonance and arrays’ diffraction waves. In the array, Si nanopillar dimers are on SiO2 nanopillar dimers, and SiO2 nanopillar dimers are on a quartz substrate. The simulated results reveal that the two SLRs’ linewidths can be as small as 2.6 nm. However, for the Si/SiO2 nanopillar array without dimers, only one SLR can be formed. Compared to the SLR of the Si/SiO2 nanopillar array, the SLRs’ intensity of the Si/SiO2 nanopillar dimer array is stronger and the SLRs’ linewidth of the Si/SiO2 nanopillar dimer array is smaller. The Si/SiO2 nanopillar dimers’ height and diameter, the gap of dimers, and the arrays’ period are all important to regulate the two SLRs. This work is important to the design of micro–nano photonic devices based on multiple SLRs.
Novel ferroelectric liquid crystals derived from lactic acid
Authors: Ichihashi M. , Kikuchi M. , Takeshita F. , Terashima K. , Furukawa K. , Inukai T. 
Published: February 2023

Optically active compounds of the following chemical structures were synthesized from lactic acids:

R
1

—
(
CORE
)
—

OCH

2

CH

∗

(

CH

3

)

OC
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O
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(1)

R
2

—
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CORE
)
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OCH

2

C
*

H

(

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)

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)

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H

(

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O
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R
2

(2)
(R1, the alkyl or alkoxy group; R2, alkyl group).
Ultra-low-loss multi-layer 8 × 8 microring optical switch
Authors: Li Xin , Gao Wei , Lu Liangjun , Chen Jianping , Zhou Linjie 
Published: February 2023

Microring-based optical switches are promising for wavelength-selective switching with the merits of compact size and low power consumption. However, the large insertion loss, the high fabrication, and the temperature sensitivity hinder the scalability of silicon microring optical switch fabrics. In this paper, we utilize a three-dimensional (3D) microring-based optical switch element (SE) on a multi-layer Si3N4-on-SOI platform to realize high-performance large-scale optical switch fabrics. The 3D microring-based SE consists of a Si/Si3N4 waveguide overpass crossing in the bottom and the top layers, and Si3N4 dual-coupled microring resonators (MRRs) in the middle layer. The switch is calibration-free and has low insertion loss. With the 3D microring-based SEs, we implement an 8×8 crossbar optical switch fabric. As the resonance wavelengths of all SEs are well aligned, only one SE needs to be turned on in each routing path, which greatly reduces the complexity of the switch control. The optical transmission spectra show a box-like shape, with a passband width of ∼69  GHz and an average on-state loss of ∼0.37  dB. The chip has a record-low on-chip insertion loss of 0.52–2.66 dB. We also implement a non-duplicate polarization-diversity optical switch by using the bidirectional transmission characteristics of the crossbar architecture, which is highly favorable for practical applications. 100 Gb/s dual-polarization quadrature-phase-shift-keying (DP-QPSK) signal is transmitted through the switch without significant degradation. To the best of our knowledge, this is the first time that 3D MRRs have been used to build highly scalable polarization-diversity optical switch fabrics.
The identification of mediating effects using genome-based restricted maximum likelihood estimation
Authors: Rietveld Cornelius A. , de Vlaming Ronald , Slob Eric A. W. 
Published: February 2023

Mediation analysis is commonly used to identify mechanisms and intermediate factors between causes and outcomes. Studies drawing on polygenic scores (PGSs) can readily employ traditional regression-based procedures to assess whether traitMmediates the relationship between the genetic component of outcomeYand outcomeYitself. However, this approach suffers from attenuation bias, as PGSs capture only a (small) part of the genetic variance of a given trait. To overcome this limitation, we developed MA-GREML: a method for Mediation Analysis using Genome-based Restricted Maximum Likelihood (GREML) estimation.Using MA-GREML to assess mediation between genetic factors and traits comes with two main advantages. First, we circumvent the limited predictive accuracy of PGSs that regression-based mediation approaches suffer from. Second, compared to methods employing summary statistics from genome-wide association studies, the individual-level data approach of GREML allows to directly control for confounders of the association betweenMandY. In addition to typical GREML parameters (e.g., the genetic correlation), MA-GREML estimates (i) the effect ofMonY, (ii) thedirect effect(i.e., the genetic variance ofYthat is not mediated byM), and (iii) theindirect effect(i.e., the genetic variance ofYthat is mediated byM). MA-GREML also provides standard errors of these estimates and assesses the significance of the indirect effect.We use analytical derivations and simulations to show the validity of our approach under two main assumptions,viz., thatMprecedesYand that environmental confounders of the association betweenMandYare controlled for. We conclude that MA-GREML is an appropriate tool to assess the mediating role of traitMin the relationship between the genetic component ofYand outcomeY. Using data from the US Health and Retirement Study, we provide evidence that genetic effects on Body Mass Index (BMI), cognitive functioning and self-reported health in later life run partially through educational attainment. For mental health, we do not find significant evidence for an indirect effect through educational attainment. Further analyses show that the additive genetic factors of these four outcomes do partially (cognition and mental health) and fully (BMI and self-reported health) run through an earlier realization of these traits.
Maternal prenatal screening programs that predict trisomy 21, trisomy 18, and neural tube defects in offspring
Authors: Chen Yiming , Ning Wenwen , Shi Yezhen , Chen Yijie , Zhang Wen , Li Liyao , Wang Xiaoying 
Published: February 2023

Objective
To determine the efficacy of three different maternal screening programs (first-trimester screening [FTS], individual second-trimester screening [ISTS], and first- and second-trimester combined screening [FSTCS]) in predicting offspring with trisomy 21, trisomy 18, and neural tube defects (NTDs).

Methods
A retrospective cohort involving 108,118 pregnant women who received prenatal screening tests during the first (9–13+6 weeks) and second trimester (15–20+6 weeks) in Hangzhou, China from January–December 2019, as follows: FTS, 72,096; ISTS, 36,022; and FSTCS, 67,631 gravidas.

Result
The high and intermediate risk positivity rates for trisomy 21 screening with FSTCS (2.40% and 5.57%) were lower than ISTS (9.02% and 16.14%) and FTS (2.71% and 7.19%); there were statistically significant differences in the positivity rates among the screening programs (all P < 0.05). Detection of trisomy 21 was as follows: ISTS, 68.75%; FSTCS, 63.64%; and FTS, 48.57%. Detection of trisomy 18 was as follows; FTS and FSTCS, 66.67%; and ISTS, 60.00%. There were no statistical differences in the detection rates for trisomy 21 and 18 among the 3 screening programs (all P > 0.05). The positive predictive values (PPVs) for trisomy 21 and 18 were highest with FTS, while the false positive rate (FPR) was lowest with FSTCS.

Conclusion
FSTCS was superior to FTS and ISTS screening and substantially reduced the number of high risk pregnancies for trisomy 21 and 18; however, FSTCS was not significantly different in detecting fetal trisomy 21 and 18 and other confirmed cases with chromosomal abnormalities.
Effect of MBSR, DBT and CBT on the hypertension patients with depression/anxiety: Protocol of a systematic review and Bayesian network meta-analysis
Authors: Zhang Yan , Zhang Hailiang , Zhang Yong , Yang Zijiao , Wang Lingling , Pan Weimin , Dai Runjing , Ju Qianqian , Ren Dong , Bao Shisan , Fan Jingchun 
Published: February 2023

Introduction
Hypertension, one of the most common chronic diseases worldwide, usually requires lifetime managing blood pressure (BP) with medications. Due to quite large number of hypertension patients co-exist with depression and/or anxiety, and non-cooperated with medical instruction, consequently management of BP is impaired with serious complications, resulting in compromised quality of life. Consequently quality of life of such patients is impaired with serious complications. Therefore, management of depression and/or anxiety is equally important as the treatment of hypertension. Depression and/or anxiety are independent risk factors of hypertension, which is supported by the finding that there is close correlation between hypertension are depression/or anxiety. Psychotherapy (non-drug treatment) maybe useful for hypertensive patients with depression and/or anxiety to improve their negative emotions. We aim to quantify the effective of psychological therapies in the management of hypertension patients with depression or anxiety, by comparing and ranking a network meta-analysis (NMA).

Materials and methods
Literature search for randomized controlled trials (RCTs) will be performed in five electronic databases from inception to December 2021, including PubMed, the Cochrane library, Embase, Web of Science, and China Biology Medicine disc (CBM). The search terms mainly include “hypertension”, “mindfulness-based stress reduction” (MBSR), “cognitive behavioral therapy” (CBT) and “dialectical behavior therapy” (DBT). Cochrane Collaboration quality assessment tool will be used for the risk of bias assessment. A Bayesian network meta-analysis will be performed, using WinBUGS 1.4.3, and Stata 14 will be applied to draw the network diagram, while RevMan 5.3.5 will be used to produce funnel plot for assessing the risk of publication bias. Recommended rating, development and grade methodology will also be utilized to assess the quality of evidence.

Results
Effect of MBSR, CBT and DBT will be evaluated by traditional meta-analysis directly and Bayesian network meta-analysis indirectly. Our study will provide the evidence on the efficacy and safety of psychological treatments in the hypertension patients with anxiety. There is no research ethical requirement because this is a systematic review of published literature. The results of this study will be published in a peer-reviewed journal.

Trial registration
Prospero registration number: CRD42021248566.
The impact of higher levels of autistic traits on risk of hikikomori (pathological social withdrawal) in young adults
Authors: Brosnan Mark , Gavin Jeff 
Published: February 2023

BackgroundHikikomori is an extreme state of social withdrawal, originally identified in Japan but more recently recognised internationally. Many countries imposed restrictions during the COVID-19 pandemic which may have had a detrimental impact on those at risk of hikikomori, specifically young adults and those with high levels of autistic traits.AimsTo explore whether levels of autistic traits mediate the relationship between psychological wellbeing and hikikomori risk. We also looked at whether autistic traits mediated between lockdown experiences (e.g. not leaving the house) and hikikomori risk.Methods646 young people (aged 16–24) from a wide range of countries completed an online questionnaire assessing psychological wellbeing, autistic traits and experiences of lockdown for this cross-sectional study.ResultsAutistic traits mediated the relationship between both psychological wellbeing and hikikomori risk, as well as frequency of leaving the house during lockdown and hikikomori risk. Greater hikikomori risk was associated with poor psychological wellbeing, higher autistic traits and leaving the house less frequently during the COVID-19 pandemic.ConclusionsThese findings suggest similarities with Japanese hikikomori research and are consistent with suggestions that psychological wellbeing and COVID-19 restrictions are associated with increased hikikomori risk in young adults, and both associations are mediated by higher levels of autistic traits.
The Prediction of Religiosity on Students’ Academic Dishonesty
Authors: Oktaviyani Devi , Sunawan Sunawan , Khairkhah Khairuddin 
Published: February 2023

Purpose – The relationship between students’ level of religiosity with their academic dishonesty in previous research was found inconsistent. The purpose of the present study is to clarify the relationship between religiosity with academic dishonesty.
Design/methods/approach – This study implemented a correlational design that involved 251 (60,6% female) Islamic High School students in Batang District, Central Java, selected by using cluster random sampling. Data on religiosity was collected using the Centrality of Religiosity Scale (TCR), and academic dishonesty data were assessed using the Academic Dishonesty Scale (ADS).
Findings – The results showed that religiosity predicted a decrease in academic dishonesty. Furthermore, this study also confirms that there are three dimensions (out of 5 dimensions of religiosity) that significantly predict academic dishonesty, namely ideology, private practice, and experience, while the other two dimensions, namely intellect and public practice, have no correlation with academic dishonesty.
Research implications/limitations – The implications of these findings are presented for strengthening collaboration between school counselors and religious education teachers to decrease students’ academic dishonesty through strengthening the level of student religiosity in its various dimensions so that religiosity is not seen as just a ritual of worship.
Originality/value – This study has clarified and confirmed the relationship between religiosity and academic dishonesty, particularly the three dimensions of religiosity that contribute to explaining academic dishonesty.
The Relationship between Religious Attitudes and Perseverance in Learning in Islamic Religious Education Lessons in Junior High Schools
Authors: Alimni Alimni , Amin Alfauzan , Kurniawan Dwi Agus , Perdana Rahmat , Pratama Wahyu Adi , Triani Elza 
Published: February 2023

Purpose – This study aims to determine the relationship between religious attitudes and learning perseverance of students of SMP 1 Bengkulu City and SMP 1 Jambi City on the subject of Islamic Religious Education.
Design/methods/approach – The research design is an associative quantitative research method with a correlational research design. The number of samples of junior high school students studied amounted to 140.
Findings – It was found that the results of the T-test and the correlation test showed a significant comparison and there was a relationship between Attitude and Perseverance in Student Learning of SMP 1 Bengkulu City and SMP 1 Jambi City on Islamic Religious Education Subjects.
Research implications/limitations – The implication of this research is that it can be used as a reference in taking follow-up actions in solving problems regarding the religious character of students and students' perseverance in learning. The author realizes that this study still has shortcomings, such as the sample used is only 2 schools and 2 different cities. The variables studied in this study were only variables of Religious Attitude and Student Learning Diligence in Islamic Religious Education subjects. In addition, there are many other indicators that have not been used.
Originality/value – This research is expected to be used by educators as a reference regarding the relationship between religious attitudes and students' persistence in learning, especially in the subject of Islamic Religious Education.
SubStrat
Authors: Lazebnik Teddy , Somech Amit , Weinberg Abraham Itzhak 
Published: February 2023

Automated machine learning (AutoML) frameworks have become important tools in the data scientist's arsenal, as they dramatically reduce the manual work devoted to the construction of ML pipelines. Such frameworks intelligently search among millions of possible ML pipelines - typically containing feature engineering, model selection, and hyper parameters tuning steps - and finally output an optimal pipeline in terms of predictive accuracy.
However, when the dataset is large, each individual configuration takes longer to execute, therefore the overall AutoML running times become increasingly high.

To this end, we present SubStrat, an AutoML optimization strategy that tackles the data size, rather than configuration space. It wraps existing AutoML tools, and instead of executing them directly on the entire dataset, SubStrat uses a genetic-based algorithm to find a small yet representative data
subset
that preserves a particular characteristic of the full data. It then employs the AutoML tool on the small subset, and finally, it refines the resulting pipeline by executing a restricted, much shorter, AutoML process on the large dataset. Our experimental results, performed on three popular AutoML frameworks, Auto-Sklearn, TPOT, and H2O show that SubStrat reduces their running times by 76.3% (on average), with only a 4.15% average decrease in the accuracy of the resulting ML pipeline.
Multi-Analyst Differential Privacy for Online Query Answering
Authors: Pujol David , Sun Albert , Fain Brandon , Machanavajjhala Ashwin 
Published: February 2023

Most differentially private mechanisms are designed for the use of a single analyst. In reality, however, there are often multiple stakeholders with different and possibly conflicting priorities that must share the same privacy loss budget. This motivates the problem of equitable budget-sharing for multi-analyst differential privacy. Our previous work defined desiderata that any mechanism in this space should satisfy and introduced methods for budget-sharing in the offline case where queries are known in advance.
We extend our previous work on multi-analyst differentially private query answering to the case of online query answering, where queries come in one at a time and must be answered without knowledge of the following queries. We demonstrate that the unknown ordering of queries in the online case results in a fundamental limit in the number of queries that can be answered while satisfying the desiderata. In response, we develop two mechanisms, one which satisfies the desiderata in all cases but is subject to the fundamental limitations, and another that randomizes the input order ensuring that existing online query answering mechanisms can satisfy the desiderata.
Excalibur
Authors: Gubner Tim , Boncz Peter 
Published: February 2023

In recent years, hardware has become increasingly diverse, in terms of features as well as performance. This poses a problem for complex software in general and database systems in particular. To achieve top-notch performance, we need to exploit hardware features, but do not fully know which behave best on the current, and more-so future, machines. Specializing query execution methods for many diverse hardware platforms will significantly increase database software complexity and also poses a physical query optimization problem that cannot be solved robustly with static cost models.
In this paper, we propose a new query execution architecture addressing these problems. Based on the flexible domain-specific language VOILA, it can generate thousands of different flavors from a single code-base. As an abstraction, a virtual machine (VM) allows hiding physical execution details, such that the VM can transparently switch between different execution tactics within each query, applied at a fine granularity. We show rules to describe a search space for good tactics, and describe efficient search strategies, that limit the overhead of adaptive JIT code generation and compilation. The VM starts executing each query in full vectorized code style, but adaptively replaces (parts of) query pipelines by code fragments compiled using different execution flavors, exploring this search space and exploiting the best tactics found, casting adaptive query execution into a Multi-Armed Bandit (MAB) problem. Excalibur, our prototype, outperforms open-source systems by up to 28X and the state-of-the-art system Umbra by up to 1.8X. In specific queries Excalibur performs up to 2X faster than static flavors.