Miracle-dz/UniFAR-FTUs huggingface dataset:
Surface-Electrode Ion Trap With Ground Structures for Minimizing the Dielectric Loss in the Si Substrate

The surface-electrode ion trap is one of the key devices in modern ion-trapping apparatus to host the ion qubits for quantum computing. Surface traps fabricated on the silicon substrate have the versatility for complex electrode fabrication with 3-D integration capability. However, Si-induced dielectric loss has to be considered in trap design, and a ground structure is being incorporated to mitigate this concern. In this article, surface-electrode ion trap is fabricated using the standard Cu back-end process on a 300-mm Si wafer platform. Several process novelties are demonstrated: 1) the use of electroplated Cu/Au layers using microfabrication techniques to form the surface electrodes; 2) the use of dry etching to form the fine-gap oxide trench between the electrodes for reducing the charge-induced stray electric field; 3) the use of Cu mesh ground structure to enhance the resonance performance of the trap; and 4) process optimization to minimize the undercut in Cu/Au electrodes. Promising electrical properties are obtained from the fabricated ion trap with a leakage current failure rate of < 10% on a 300-mm wafer. Two trap types designed with radio-frequency (RF) linewidth of 80 and $40~\mu \text{m}$ are evaluated for their resonance performance with and without the ground plane. By incorporating ground plane into the ion trap, the resonance performances are significantly improved with an output power increment of 11 and 13 dB and $Q$ factor increment of 2 and 6 for the corresponding trap types.
Versatile Regulator or Integrator RNA-binding Protein TLS/FUS Works for Phase Separation on Regulation of the Human Genome - In Relation to Liposarcoma and ALS

This review article aims at comprehensive understanding of biological functions of RNA-binding proteins (RBPs) and cognate RNAs. For showing the divergent and dispersed aspects of RBP functions of the human genome in living cells, RBP TLS/FUS is chosen for these topics. Recent discovery of TLS as a phase transition or phase separation inducer presents previously unprecedented models regarding phase separation and enhancer functions in the genome. Trends in research altered up to interests or desire of scientists. Research activities of TLS/FUS have been dramatically drifted across over the last century. TLS was identified as a fusion gene product of TLS-CHOP of liposarcoma in 1993. Before announcement of the human genome draft, there were compelling desires to hunt novel genes. Gene cloning from libraries was one of prevalent activities at that time. Next wave came with describing TLS as a causative gene for familial amyotrophic lateral sclerosis (ALS). Investigation of lethal neurodegenerative disease, ALS has social impact. Elucidation of onset of ALS has progressed rapidly. Latest discovery with TLS is its solute for phase separation and phase transition into aggregation. The phase separation and resultant aggregation are pointed out in relation to the onset of ALS. Then, people rush to search for tide of TLS to phase separation in link to cause for ALS. Analysis of the phase separation could provide a novel outline for long distant regulation of gene in the genome. In this review article, the author focuses emerging trendy targets of a versatile molecule TLS and discuss scientific needs behind these orientation for a specific molecule in biological sciences.
Extraction, correlation, and abstraction of event data for process mining

Process mining provides a rich set of techniques to discover valuable knowledge of business processes based on data that was recorded in different types of information systems. It enables analysis of end‐to‐end processes to facilitate process re‐engineering and process improvement. Process mining techniques rely on the availability of data in the form of event logs. In order to enable process mining in diverse environments, the recorded data need to be located and transformed to event logs. The journey from raw data to event logs suitable for process mining can be addressed by a variety of methods and techniques, which are the focus of this article. In particular, techniques proposed in the literature to support the creation of event logs from raw data are reviewed and classified. This includes techniques for identification and extraction of the required event data from diverse sources as well as their correlation and abstraction.
Functional in vivo characterization of zebrafish sox10 enhancers in melanoma and neural crest

The re-emergence of a neural crest transcriptional program, including Sox10 upregulation, is a key step in melanoma initiation in humans and zebrafish. We hypothesize that epigenetic regulation of sox10 modulates melanoma initiation. ATAC-Seq analysis of zebrafish melanoma tumors identifies recurrently open chromatin domains near sox10. Reporter constructs for each putative sox10 enhancer were examined in zebrafish embryos for neural crest activity and in stable transgenic lines for melanoma activity. One element, peak5 (23 kilobases upstream of sox10), drives EGFP reporter expression in a subset of neural crest cells, Kolmer-Agduhr neurons, and early melanoma patches and tumors with high specificity. A ∼200 bp region, conserved across the Cyprinidae family (fish), is required for peak5 activity in neural crest and melanoma, and contains dimeric SoxE binding sites essential for neural crest activity. Our work identifies a novel melanoma transcriptional enhancer, expanding our knowledge of epigenetic regulation of neural crest identity in melanoma.
Kulttuuri kunnan toiminnassa 2019 hyvinvoinnin ja terveyden edistämisen näkökulmasta

Terveyden ja hyvinvoinnin laitos, opetusja kulttuuriministeriö ja Suomen Kuntaliitto selvittivät kulttuuritoimintaan, erityisesti hyvinvointia ja terveyttä edistävään kulttuuritoimintaan liittyviä toimenpiteitä, resursseja ja toimintakäytäntöjä kunnissa ensimmäistä kertaa tiedonkeruulla keväällä 2019. Kulttuuri kunnan toiminnassa -tiedonkeruu on osa Terveyden edistämisen vertailutietojärjestelmää (TEAviisari), joka muodostuu eri toimintojen (perusterveydenhuolto, liikunta, perusopetus, toisen asteen koulutus, kuntajohto ja nyt uutena kulttuuri) kokonaisuudesta. Tiedonkeruun tavoitteena on vahvistaa kulttuuritoiminnan sekä taiteen ja kulttuurin keinoin tapahtuvan hyvinvoinnin ja terveyden edistämistyön tietopohjaa sekä toiminnan arviointia kunnassa. Jatkossa tiedot kerätään joka toinen vuosi.
Capacity-building model for nurses in carrying out family-based health service at selected primary care units in Northern Thailand

The process of using a family-based health service is one that can strengthen and develop primary care services. Nurses, as key professionals in primary care services, are expected to provide care that focuses on families in community settings. This study intended to achieve a change in practice in primary care units regarding family-based health service. Participatory action research using an enhancement approach was utilized as the study methodology. Participants were seven nurses from two primary care unit networks, eighteen primary care unit staff, twenty-five volunteers, five community leaders, fifty-three families and public health administrators, public health technical officers, nurses from other units, and local organization administrators. Data were collected through focus group discussions, interviews, participant observation, document survey and keeping a research journal. Throughout research processes, participants were facilitated and encouraged to develop, to implement and to evaluate their nursing practice, based on the evidence gathered during the study. Strategies to empower nurses and maintain a family-based health service were: 1) partnership, 2) commitment, 3) building capacity, 4) debriefing meetings, 5) communication and mutual learning, and 6) participation in community activities. The study suggests that developing family-based health service is a shared responsibility amongst health care providers, local community organizations, communities and families with nurses at the center of this collaboration and the first point of contact.
Estimating the eect of retirement on mental health via panel discontinuity designs

This article explores the potential effects of retirement on mental health and health care utilisation isolating sources of potential heterogeneity in treatment effect. To estimate the effects of retirement, we devise a new identifying strategy that combines kink and regression discontinuity designs with panel data methods. Our method is then applied to the British Household Panel Survey, a rich representative longitudinal survey. It is found that retirement has a small impact on primary care use, but overall has little effect on mental health.
Fusion of Sentinel-1 with Official Topographic and Cadastral Geodata for Crop-Type Enriched LULC Mapping Using FOSS and Open Data

Accurate crop-type maps are urgently needed as input data for various applications, leading to improved planning and more sustainable use of resources. Satellite remote sensing is the optimal tool to provide such data. Images from Synthetic Aperture Radar (SAR) satellite sensors are preferably used as they work regardless of cloud coverage during image acquisition. However, processing of SAR is more complicated and the sensors have development potential. Dealing with such a complexity, current studies should aim to be reproducible, open, and built upon free and open-source software (FOSS). Thereby, the data can be reused to develop and validate new algorithms or improve the ones already in use. This paper presents a case study of crop classification from microwave remote sensing, relying on open data and open software only. We used 70 multitemporal microwave remote sensing images from the Sentinel-1 satellite. A high-resolution, high-precision digital elevation model (DEM) assisted the preprocessing. The multi-data approach (MDA) was used as a framework enabling to demonstrate the benefits of including external cadastral data. It was used to identify the agricultural area prior to the classification and to create land use/land cover (LULC) maps which also include the annually changing crop types that are usually missing in official geodata. All the software used in this study is open-source, such as the Sentinel Application Toolbox (SNAP), Orfeo Toolbox, R, and QGIS. The produced geodata, all input data, and several intermediate data are openly shared in a research database. Validation using an independent validation dataset showed a high overall accuracy of 96.7% with differentiation into 11 different crop-classes.
On Neural Architectures for Astronomical Time-series Classification with Application to Variable Stars

Despite the utility of neural networks (NNs) for astronomical time-series classification, the proliferation of learning architectures applied to diverse data sets has thus far hampered a direct intercomparison of different approaches. Here we perform the first comprehensive study of variants of NN-based learning and inference for astronomical time series, aiming to provide the community with an overview on relative performance and, hopefully, a set of best-in-class choices for practical implementations. In both supervised and self-supervised contexts, we study the effects of different time-series-compatible layer choices, namely the dilated temporal convolutional neural network (dTCNs), long-short term memory NNs, gated recurrent units and temporal convolutional NNs (tCNNs). We also study the efficacy and performance of encoder-decoder (i.e., autoencoder) networks compared to direct classification networks, different pathways to include auxiliary (non-time-series) metadata, and different approaches to incorporate multi-passband data (i.e., multiple time series per source). Performance—applied to a sample of 17,604 variable stars (VSs) from the MAssive Compact Halo Objects (MACHO) survey across 10 imbalanced classes—is measured in training convergence time, classification accuracy, reconstruction error, and generated latent variables. We find that networks with recurrent NNs generally outperform dTCNs and, in many scenarios, yield to similar accuracy as tCNNs. In learning time and memory requirements, convolution-based layers perform better. We conclude by discussing the advantages and limitations of deep architectures for VS classification, with a particular eye toward next-generation surveys such as the Legacy Survey of Space and Time, the Roman Space Telescope, and Zwicky Transient Facility.
The complete chloroplast genome of an ornamental orchid, Vanda coerulescens (Orchidaceae)

Abstract Though the chloroplast genomes of several Vanda species have been sequenced, there is little information about the complete chloroplast (cp) genome of Vanda coerulescens. Herein, we established the cp genome of V. coerulescens. The chloroplast genome circle was 149,410 bp in length, with the structure of an 85,954 bp large single-copy (LSC) region and a 11,526 bp small single-copy (SSC) region, which separated by two inverted repeat (IRs) regions of 25,965 bp. It encoded 130 genes, including 74 protein-coding genes, 38 tRNA genes and 8 rRNA genes. The overall GC-content of the whole plastome is 36.7%, whereas the corresponding values of the LSC, SSC, and IR regions ranged from 28.2% to 43.1%. In addition, the phylogenetic analysis base on 20 chloroplast genomes of Orchidaceae indicates that V. brunnea is closely related to V. coerulescens. This announcement of the complete V. coerulescens cp genome sequence could provide valuable information for further genetic modification and phylogenetic study in Vanda genus.
Study on Sustainable Development of Microfinance Institutions from the Perspective of Inclusive Finance—Based on MFI Data in Countries along the Belt and Road

ABSTRACT Practical experience and research on microfinance in various countries around the world show that microfinance institutions (MFIs) have had a profound impact on poverty alleviation, addressing the difficulty of lending in rural areas and promoting the development of small and medium-size enterprises. Based on data covering a hundred MFIs in twenty-two countries along the Belt and Road (In diplomatic documents, the English version of “the Belt and Road” is “the Silk Road Economic Belt and the 21st-Century Maritime Silk Road”, which can be abbreviated as “B&R”) from 2014 to 2016, this paper studies the micro- and macro-level factors that affect the sustainable development of MFIs from the perspective of inclusive finance. The results show that the return on assets, credit depth of information index have significant positive effects on the sustainable development of MFIs. However, average loan balance, total expense to asset, risk asset ratio more than thirty days’ overdue and rural population to total population have significant negative effects on the sustainable development of MFIs. MFIs’ sustainability are significant regional differences.
Epicardial Fat Thickness May be Used in the Differential Diagnosis of Atrioventricular Nodal Re-entrant and Atrioventricular Re-entrant Tachycardia

Giris: Epikardiyal yag kalinligi (EYK) aritmik olaylarda rolu oldugu bilinmektedir. Biz bu calismada supraventrikuler aritmilerin ayirici tanisinda EYK’nin kullanilabilirligini arastirdik. Hastalar ve Yontem: Klinigimize carpinti sikayeti ile basvuran veya yuzeyel EKG’de SVT tanisi olan ve elektrofizyolojik calisma (EFC) yapilmis 259 hasta dahil edildi. Hastalarin demografik, ekokardiyografik verileri ile birlikte EFC ile belirlenmis tanilari kaydedildi. Bulgular: Calismamiza; 88 adet kontrol, 95 adet AVNRT ve 66 adet AVRT’li hastayi dahil ettik. TTE verileri karsilastirildiginda ise; epikardiyal yag kalinligi (p= 0.001) AVRT’li hasta grubunda anlamli oranda artmis olarak tespit edildi. Binominal lojistik regresyon analizinde EYK bagimsiz prediktor olarak tespit edildi (OR:2.2 %95 GA: 1.456-5.478, p< 0.001). Yapilan ROC analizinde, EYK kesim degeri 15 mm olarak alindiginda %77.3 sensitivite ve %58.9 spesifite ile AVNRT, AVRT ayriminin yapilabilecegi tespit edildi. Sonuc: Epikardiyal yag kalinligi AVRT’li hastalarda artmis olabilir ve ayirici tanida kullanilabilir.
Trimet Graph Optimization (TGO) based methodology for Scalability and Survivability in Wireless Networks

Wireless networks gain popularity in recent years with tremendous growth in Wi-Fi, 5G cellular, V2X, Low-power wide-area, Wireless-sensing, Millimeter-wave, Backscatter networks. The common problem we identified in the above technologies is scalability and survivability will affect the performance of the systems. The current development demands for an improvement in traditional topologies. The above challenges cannot be addressed by a star, wheel, full mesh chain, ring, and etc. due to lack of scalability, survivability and resilience properties. These problems can be addressed in different ways by using machine learning, AI, game theory, etc. In this paper graph theory techniques were applied because this method is well equipped with mathematical techniques that provide a systematic alternative to traditional topologies. Physical features like cost, latency, congestion, survivability, resilience are correlated with graph invariants like node degree, diameter, average distance, and edge betweenness and Wiener impact. The above-mentioned Scalability, survivability problems are applied on backhaul, wireless networks respectively. Finally, a general framework was designed for wireless networks using the NetworkX package in python.
Complete reconstruction of the unbinding pathway of an anticancer drug by conventional unbiased molecular dynamics simulation

Understanding the details of unbinding mechanism of small molecule drugs is an inseparable part of rational drug design. Reconstruction of the unbinding pathway of small molecule drugs, todays, can be achieved through molecular dynamics simulations. Nonetheless, simulating a process in which a drug unbinds from its receptor demands lots of time, mostly up to several milliseconds. This amount of time is neither reasonable nor affordable; therefore, many researchers utilize various biases that there are still many doubts about their trustworthiness. In this work we have utilized short-run simulations, replicas, to make such time-consuming process cost effective. By replicating those snapshots of the trajectories which, after careful analyses, were selected as potential candidates we increased our system’s efficiency considerably. As a matter of fact, we have implemented a sort of human bias, inspecting trajectories visually, to achieve multiple unbinding events. We would like to call this stratagem, replicating of potent snapshots, “rational sampling” as it is, in fact, benefiting from human logic. In our case, an anticancer drug, the dasatinib, completely unbounded from its target protein, c-Src kinase, in only 392.6 ns, and this was gained without applying any internal biases and potentials which can increase error level. Thus, we achieved important structural details that can alter our viewpoint as well as assist drug designers.
The complete mitochondrial genome of Montipora efflorescens (Scleractinia: Acroporidae)

Abstract The complete mitogenome of the Sclreractinia, Montipora efflorescens Bernard, 1897 was sequenced for the first time. It had 17,887 bp, with 13 protein-coding genes, and two rRNA and two tRNA genes. Composition of M. efflorescens mitogenome was identical to that of typical Scleractinians. In conclusion, the complete mitogenome may provide detailed information on coral phylogeny.
L'impact des nouveaux traitements sur la prevention du VIH

This article studies the interaction between two individual decisions in the context of sexually transmitted diseases: on the one hand, the choice the of risk level, on the other hand, the decision to get tested. Our angle here is economic epidemiology, which aims at identifying the essential arbitrages that involve private decisions. Since testing opens access to treatments for a disease, it reduces the private cost of risk taking, all the more so when available treatments are more efficacious. From this, it stems that improvements in treatmentds can spur an increase in the risk level, by diminishing the cost associated with risk for those individuals who have opted for testing. An empirical analysis based on data from the San Francisco Stop Aids Project confirms this theoretical prediction. The apparition, during the year 1996, of new treatments against HIV coincided with an increaese in risky behavior within the tested population (test group) but not within the population that had not undertaken testing (control group).
Seeing bias in irony: How recipients infer speakers’ stereotypes from their ironic remarks about social-category members

We study whether recipients draw inferences about speakers’ stereotypic impressions from their ironic (vs. literal) remarks. Following up on the Irony Bias, we conducted two experiments in which participants were exposed (in writing or sound-recording) to only either literal remarks or irony referring to either positive or negative behaviors of an unknown social category. Results of both experiments show that participants recognize speakers’ biased impressions from their pattern of irony use. When speakers made ironic remarks about category members’ positive behaviors (but not about negative behaviors), participants inferred that speakers had a more negative impression of the category, and that they perceived higher essentialism of negative (vs. positive) behaviors. The impression participants perceived in speakers’ biased communication pattern did not translate to participants’ own reported category impression. We discuss various factors that may determine when a recognized stereotypic view in a speaker contributes to the formation and maintenance of stereotypic impressions.
Comment: Models as Approximations.

We congratulate Andreas Buja and his coauthors on their thought provoking and ambitious work, “Models as Approximations, Parts I and II”. This work deeply examines the meaning of model robustness, the consequences of model misspecification, and culminates in the formulation and development of the notion of “well-specified” regression. Although the regressors-as-fixed point of view of regression has dominated statistical practice, the work of Buja, et al., adds to a growing literature on the implications of random regressors and model misspecification on inference and prediction. We do not endeavor to nor intend to enumerate those here but will mention a few to give a sense of the literature. For example, Sen & Sen (2014) provided a valuable omnibus test for simultaneously checking the assumption of independence between the error and predictor variables and the goodness­ of-fit of the parametric model; Rosset & Tibshirani (2018) explored covariate randomness in statistical prediction and applications to covariance penalties; and residual-based goodness­ of-fit assessments using a directional test have been explored in Stute (1997).