Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling Snake Microhabitat from Radiotelemetry Studies Using Polytomous Logistic Regression

-Multivariate analysis of snake microhabitat has historically used techniques that were derived under assumptions of normality and common covariance structure (e.g, discriminant function analysis, MANOVA). In this study, polytomous logistic regression (PLR), which does not require such assumptions, was developed to model habitat use patterns from snake radiotelemetry data. Two case study examples were used: the copperhead (Agkistrodon contortrix) in a forested habitat in Chesapeake, Virginia, and the cottonmouth (Agkistrodon piscivorus piscivorus) in a wetland habitat in Virginia Beach, Virginia. The model was developed based on grid-cell counts of the habitat used by adult snakes that were radiotracked for a minimum of one activity season (early spring through late fall). In addition to PLR modeling, a nonparametric MANOVA procedure based on ranked data from presence versus random sites was developed for comparative purposes. Although results were similar in terms of variables chosen by the models, nonparametric procedures lack predictive power, and conclusions drawn from them are sometimes questionable or difficult to interpret. Polytomous logistic regression provides a useful alternative to traditional modeling approaches that require ancillary data from random sites; PLR requires data only from sites used by snakes, and was developed based on use-intensity categorization. Suggestions for model implementation (e.g, in a
A Novel Fundamental and Harmonics Detection Method Based on State-Space Model for Power Electronics System

Harmonic current estimation is the key technology of power electronics systems to generate a harmonics reference current for harmonic control. In this paper, a novel fundamental and harmonic current detection method based on the state-space model (SSM) is introduced. The proposed SSM harmonics detection method has the ability to detect the positive sequence component (PSC), negative sequence component (NSC), and zero-sequence component (ZSC) of both fundamental and each order harmonics current with fast response and high accuracy separately, including the fundamental component, which is appealing for harmonics control in power electronic applications, such as active power filter (APF), unified power quality conditioner (UPQC), virtual synchronous generator (VSG), and so on. The correctness of the proposed SSM based harmonics detection method has been verified by simulation and experiment result, and it shows that the PSC, NSC, and ZCS of the grid fundamental and high order harmonic current can be detected quickly and accurately, which is important for harmonics analysis and control in the power electronics system.
Learning SDN traffic flow accurate models to enable queue bandwidth dynamic optimization

Software Defined Network (SDN) architectures decouple control and forwarding functionalities by enabling the network devices to be remotely configurable/programmable run-time by a controller. As a direct consequence identifying an accurate model of a network and forwarding devices is crucial in order to apply advanced control techniques to optimize the network performance. An enabling factor in this direction is given by recent results that appropriately combine System Identification and Machine Learning techniques to obtain predictive models using historical data retrieved from a network. In this paper we propose a novel methodology to learn, starting from historical data and appropriately combining ARX identification with Regression Trees and Random Forests, an accurate model of the dynamical input-output behavior of a network device that can be directly and efficiently used to optimally and dynamically control the bandwidth of the queues of switch ports, within the SDN paradigm. We compare our predictive model with Neural Network predictors and demonstrate the benefits in terms of Packet Losses reduction and Bandwidth savings in the Mininet network emulator environment.
Influence of the Acceptor Moiety on Nonlinear Optical Properties of Thiophene Derivatives

In this paper we report on the investigation of linear and nonlinear optical properties of six new thiophene derivatives (ThD) with a $\mathrm{D}-\pi-\mathrm{A}$ chemical structure. Chosen compounds contain the same electron-donating moiety and a $\pi$ -conjugated bridge build as covalently bonded benzothiophene and thiophene. As an electron-accepting part we used nitrophenyl and benzonitrile in ortho, meta and para positions. Selected ThDs were prepared as thin films with poly(methyl methacrylate) as a matrix in order to investigate the nonlinear optical properties. For a second and third harmonic generation (SHG/THG) we used Maker fringes method to estimate values of second and third order susceptibility. Photoinduced birefringence measurements were performed with typical Optical Kerr Effect (OKE) experiment.
Kiwifruit Leaf Disease Identification Using Improved Deep Convolutional Neural Networks

Brown spot, Mosaic and Anthracnose are three common kiwifruit leaf diseases, which causes serious economic losses in the kiwifruit industry. The timely and precise identification approach of kiwifruit leaf diseases is significant for controlling the spread of disease and ensuring the healthy growth of the kiwifruit industry. In this paper, a novel identification approach based on improved convolutional neural networks is proposed for kiwifruit leaf diseases. A dataset consisting of 11322 kiwifruit leaf images is firstly generated using image augmentation. And then, a novel CNNs-based model named Kiwi-ConvNet is built with Kiwi-Inception structures and dense connectivity strategy, which can enhance the capability of multi-scale feature extraction and ensure multi-dimensional feature fusion. Under the hold-out test set, the experimental results show that the proposed model realizes an accuracy of 98.54%, gaining a better accuracy of 2.29% and 9.51% than GoogLeNet and ResNet-20 respectively. This research indicates that the proposed model achieves accurate diagnosis of kiwifruit leaf diseases automatically, and provides a viable solution in the field of crop leaf disease identification with high recognition accuracy.
Heteroskedasticity Models for Financial Processes Modelling and Forecasting

This study is directed towards modelling financial processes which are widely available on financial markets and forecasting the prices of stock markets. It was approved many times that the financial market is really dynamically changeable, and variety of heteroskedastic models where chosen for studying for this reason. Such models as Autoregressive Moving Average (ARMA), Autoregressive Conditional Heteroskedastic Model (ARCH, and Generalized ARCH model (GARCH)), Exponential Generalized Model of Conditional Heteroscedastic Autoregression (EGARCH), Fractionally Integrated Generalized Model of Conditional Heteroskedastic Autoregression (FIGARCH) were discussed and investigated. An example of real data analysis from stock market illustrates the possibility and reasonability of application the heteroskedasticity models for predicting dynamics of variance.
Reliability of Fine-Pitch <5-μm-Diameter Microvias for High-Density Interconnects

Downscaling of package wiring has been the singular focus to achieve higher logic-memory interconnect density to meet next-generation needs for high-bandwidth computing. This article presents, for the first time, a systematic modeling and experimental study of sub-5-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula>-diameter microvia reliability. Geometry design considerations and build-up dielectric material properties in evaluating the microvia fatigue life are investigated. Finally, experimental thermal-cycling reliability results of sub-5-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula>-diameter microvias are correlated with the modeling results.
Self-Activation Neural Network Based on Self-Selective Memory Device With Rectified Multilevel States

In a digital–analog mixed neuromorphic system, various complex peripheral circuits may offset the integration and energy efficiency advantages of the dense crossbar. To simplify the peripheral circuits, a self-activation neural network (SANN) is proposed based on a passive crossbar array formed by the rectified memristive (ReMem) cell. The ReMem cell is a dual-mode resistive switching device with a VO2/TaOx bilayer structure. It shows a hybrid switching behavior including volatile threshold switching and multilevel nonvolatile resistive switching. This unique feature enables not only simultaneously self-selection and distributed activation, but also weight storage. The concept of SANN is theoretically examined, and a neural network is constructed and trained with SANN based on the proposed devices to perform recognition on handwritten digits in the MNIST database. Compared with neuromorphic computing systems using the CMOS-based activation module and additional selective element, the results show comparable recognition accuracy with reduced circuitry complexity. The proposed SANN can be a promising alternative to realize neural network computing systems with simplified peripheral circuits.
Effect of Magnetic Field on Microstructure and Properties of Smart Solder

The smart solder has been developed for the geometry control by the external magnetic field, which could be attractive for the application in the electronic packaging industry. However, the knowledge about the smart solder is still in a preliminary stage. In this paper, for the soldering of smart solder under an external magnetic field, the effect of Ni content and magnetic field on the wetting and spreading of solder was studied by melting the smart solder balls on a polished copper plate. The mechanism of magnetic field was analyzed for the wetting and spreading process of smart solders. The interfacial IMC between the smart solder and the copper plate was studied. The influence of the magnetic field on the interface morphology and phase of the IMC was analyzed. The mechanical properties, interface IMC and fracture morphology of copper soldering were compared with and without magnetic field, and the effect of magnetic field on the soldering joint was comprehensively analyzed.
Radiation-Induced Hypothyroidism in Patients with Oropharyngeal Cancer Treated with IMRT: Independent and External Validation of Five Normal Tissue Complication Probability Models

Simple Summary Hypothyroidism is a common complication of therapeutic irradiation in the neck area. Several dose-response models have been proposed to predict its’ occurrence based on clinical and radiomic features. We aimed to externally validate the results of five such models in a prospectively recruited cohort of 108 patients with oropharyngeal cancer. Two of the evaluated models, published by Rønjom et al. and by Boomsma et al., had satisfactory performance. Both models are based on mean thyroid dose and thyroid volume. Three remaining models, by Cella et al., Bakhshandeh et al. and Vogelius et al., performed significantly worse. Short-term change in the level of thyroid-stimulating hormone (TSH) after radiation therapy was not indicative of hypothyroidism development in long term. We conclude that the models by Rønjom et al. and by Boomsma et al. are feasible for long-term prediction of hypothyroidism in oropharyngeal cancer survivors treated with intensity-modulated radiation therapy. Abstract We aimed to externally validate five normal tissue complication probability (NTCP) models for radiation-induced hypothyroidism (RIHT) in a prospectively recruited cohort of 108 patients with oropharyngeal cancer (OPC). NTCP scores were calculated using original published formulas. Plasma thyrotropin (TSH) level was additionally assessed in the short-term after RT. After a median of 28 months of follow-up, thirty one (28.7%) patients developed RIHT. Thyroid mean dose and thyroid volume were significant predictors of RIHT: odds ratio equal to 1.11 (95% CI 1.03–1.19) for mean thyroid dose and 0.87 (95%CI 0.81–0.93) for thyroid volume in univariate analyses. Two of the evaluated NTCP models, published by Rønjom et al. and by Boomsma et al., had satisfactory performance with accuracies of 0.87 (95%CI 0.79–0.93) and 0.84 (95%CI: 0.76–0.91), respectively. Three remaining models, by Cella et al., Bakhshandeh et al. and Vogelius et al., performed significantly worse, overestimating the risk of RIHT in this patient cohort. A short-term TSH level change relative to baseline was not indicative of RIHT development in the follow-up (OR 0.96, 95%CI: 0.65–1.42, p = 0.825). In conclusion, the models by Rønjom et al. and by Boomsma et al. demonstrated external validity and feasibility for long-term prediction of RIHT in survivors of OPC treated with Intensity-Modulated Radiation Therapy (IMRT).
Process development of Large Size Embedded Silicon Fan-out (eSiFO) Package

With the development of new technologies such as IoT, 5G, AI&VR, automotive electronics, the urgent demand of high density, multichip integration packaging technology is increasing strongly. Fan-out technology has attracted much more attentions as a new advanced technology and grown explosively. The market scale of fan-out packaging is expected to grow to 3.8 billion US dollars with a CAGR of 19% in the next few years. In this paper, one package in a size of 20×20 mm and containing a 14×14mm large embedded die was successfully manufactured. Various key process such as cavity etching, die attach, vacuum lamination were developed. A test vehicle composed of several electrical measurement structures was designed with three different thicknesses: 70 um, 80 um and 90 um, which respectively realize different package thickness. In the test vehicles, daisy chains and other test units were established to measure electricity performance.
Nucleolar size regulates nuclear envelope shape in Saccharomyces cerevisiae

ABSTRACT Nuclear shape and size are cell-type specific. Change in nuclear shape is seen during cell division, development and pathology. The nucleus of Saccharomyces cerevisiae is spherical in interphase and becomes dumbbell shaped during mitotic division to facilitate the transfer of one nucleus to the daughter cell. Because yeast cells undergo closed mitosis, the nuclear envelope remains intact throughout the cell cycle. The pathways that regulate nuclear shape are not well characterized. The nucleus is organized into various subcompartments, with the nucleolus being the most prominent. We have conducted a candidate-based genetic screen for nuclear shape abnormalities in S. cerevisiae to ask whether the nucleolus influences nuclear shape. We find that increasing nucleolar volume triggers a non-isometric nuclear envelope expansion resulting in an abnormal nuclear envelope shape. We further show that the tethering of rDNA to the nuclear envelope is required for the appearance of these extensions. Summary: Nucleolar size influences nuclear shape in yeast. Nucleolar expansion triggers phospholipid biosynthesis leading to nuclear envelope shape abnormalities.
Research on the Organization Method of Topological Nodes Based on Mapping Matrix for Place Recognition

Inspired by the spatial cognition and localization mechanism of animals, this paper focuses on the organization method of topological nodes for place recognition. The topological map is constructed on the basis of graph by assigning each node with a set of features for localization, in which the inertial/visual odometer provides the required motion parameters. The mapping matrix between nodes and various features is constituted to realize effective organization and utilization of empirical knowledge. The availability criterion of empirical knowledge and the corresponding location error are established based on analysis of the mapping matrix, which provides a priori probability model required in data fusion applications. The topological map of a campus is constructed with scene features and the place recognition result is discussed, which shows the effectiveness of the proposed method.
Bereaved parents’ needs regarding hospital based bereavement care after the death of a child to cancer

Abstract The purpose of this study was to investigate the needs of bereaved parents in Greece (N = 56) regarding the provision of hospital based bereavement services after the death of their child to cancer. The participants did not receive formal or informal hospital based bereavement services. The majority of the parents (84%) stated that, given the opportunity, they would attend a bereavement program. Continuity of care in bereavement from the health care team, availability, individualized care, interdisciplinary approach and contact with other bereaved parents were described as key elements for the provision of bereavement services.
Factors affecting health-related quality of life among prostate cancer patients: A systematic review

Introduction Prostate cancer is recognized as the leading cause of malignancy-related incidence and mortality in the male population. The treatment regimens have long-term effects detrimental to the patient's quality of life. Hence, this review was aimed to determine the overall HRQOL and its associated among prostate cancer patients. Methods The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The databases searched were PubMed, Embase, Google Scholar and Cumulative Index to the Nursing and Allied Literature (CINAHL), which provided articles that were critically examined, yielding 52 studies that met the inclusion criteria for the systematic review. Results Out of 52 studies, 30 studies reported poor overall HRQOL in various domains after prostate cancer treatment. Contrastingly, 15 studies reported good overall quality of life after treatment. Among the various domains, sexual function was the most grossly affected functional score by the treatment modalities of prostate cancer. Nonetheless, seven studies showed that the absence of a significant change in the overall quality of life after treatment. According to the studies, older age, comorbidities, higher clinical stage, higher Gleason score, greater cancer severity, African American race, impaired mental health, neoadjuvant hormonal therapy and lower level of education were the major poor predictors of HRQOL among prostate cancer patients. Conclusion The overall HRQOL in prostate cancer patients was generally poor in various functional domains after treatment. Among the various domains, sexual function was the most grossly affected functional score by the treatment modalities of prostate cancer.
The Size Reducing of the Focal Spot with Super-Gauss Pulses Radiation Focusing by a Diffractive Axicon Demonstrated Using High-Performance Computer Systems

We investigated the change in the type of focal spot when pulsed radiation passed through the high-numerical-aperture diffractive axicon. The super-Gauss beam were considered as the input laser radiation with linear, circular and radial polarizations. Modeling of diffraction is numerically investigated by the finite difference time domain (FDTD) method. The formation of a compact light micro-needle with a minimum focal spot size of FWHM = 0. 46λ at a distance of 0. 41λ from the axicon was demonstrated in the case of radial polarization. Thus, we showed the preservation of the optimal focusing properties of cylindrically polarized beams in a pulsed mode, which is relevant for optical information transmission.
Exploration on Theoretical and Practical Projects of Software Architecture Course

It has been widely recognized that software architecture is one of the hard courses to teach in software engineering. First, it is usually difficult to update the knowledge written in textbooks with the rapidly developed practical progress. Accordingly, we need to teach students how to follow the state-of-the-art research works within both academic and industrial context. Secondly, due to the fact that students are lacking practical experience on the design and development of large-scale systems, it is difficult for them to deeply understand the theory and rationality of software architecture. Accordingly, we need to teach students how to cope with practical problems based on the learnt theoretical work. This paper presents our exploration on designing theoretical and practical projects of software architecture course for postgraduate students during the last ten years. We aim to improve students’ ability to investigate cutting-edge achievements and concerns in academia and industry, to understand, analyze, and design industrial software architecture based on open-source systems. Furthermore, we expect and encourage students’ potential to become software architects. This paper details our project setup and discusses the feedbacks, and shows the benefits of our projects.
Smart SE: Smart Systems and Services Innovative Professional Education Program

The Smart Systems and Services Innovative Professional Education (Smart SE) program is a certification program developed as part of the education network for the Practical information Technologies (enPiT-Pro) project, which is funded by the Japan Ministry of Education, Culture, Sports, Science and Technology. The Smart SE program provides industry professionals working in fields related to information and communication technology (ICT) with additional training and education in smart systems and services that utilize various technologies such as IoT, Cloud, Big Data, and Artificial Intelligence (AI) for businesses. Here, we illustrate its purpose, curriculum and features to respond to the needs of industrial professional education.
Exploring Entrepreneurs' Trust in Mobile Social Networking Services

In information technology (IT) research, the concept of trust has been a critical characteristic of user behavior. In addition, previous studies on online social networking have discussed usefulness, ease of use, social influence, privacy concerns, and risk as the major determinants of trust. With regard to trends in online ventures, few studies have focused on entrepreneurs' trust within the contexts of social networking services (SNSs). By building on recent research on trust in information systems (IS) related to SNSs, the present study examines Facebook and evaluates its influence on online entrepreneurs' trust. This study also advances a model regarding the performance expectancy of mobile Facebook Mentions (PEMFM), effort expectancy of mobile Facebook Mentions (EEMFM), social interaction (SI), privacy concerns on Facebook (PCF), perceived risk of online social activities (PROSA), and online entrepreneurs' trust in Facebook (OETF) by conducting interviews with domain experts. The findings indicate that PEMFM, EEMFM, SI, and PROSA determine online entrepreneurs' trust. Moreover, the results show that SI plays an important moderating role among PEMFM, EEMFM, and OETF.
A 390-GHz Outphasing Transmitter in 28-nm CMOS

This article presents a 390-GHz outphasing transmitter in 28-nm CMOS. Generating higher order modulation schemes at terahertz (THz) frequencies is very challenging due to the essential nonlinear elements needed to generate signals above Fmax. Harmonic outphasing could provide an answer for transmitters which use a multiplier last topology. The topology addresses both amplitude and phase distortion issues, which are inherent for multiplier-last architectures. The 5-bit on-chip outphasing symbol generator is sufficient to generate modulation schemes from OOK to 16-STAR QAM. The chip is packaged with a direct chip-to-waveguide interface thus providing easy RF access through the WR2.2 waveguide interface. The transmitter can deliver a peak measured output power of −16 dBm with a 3-dB IF bandwidth of 16.5 GHz. The maximum achieved data rate was 6 Gb/s.