Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial Patterns and Sensitivity of Intermittent Stream Drying to Climate Variability

Intermittent streams comprise much of the global river network, and are expected to become more prevalent with climate change. Characterizing the expansion and contraction of intermittency in stream networks, and understanding how sensitive these dynamics are to climatic variability, is critical for predicting the trajectory of hydrologic regimes in a changing climate. Here, we consider the spatial patterns of stream intermittency, focusing on wetted channel conditions at the end of the dry season, and identify land cover, physiographic, and climate variables that influence surface water presence and variability across years. We trained statistical models with wetted channel mapping data from 25 streams over 7 years to predict both the spatial and interannual variability of the wetted channel network. We then used the models to assess intermittent stream dynamics across the Russian River watershed in northern California, USA. We found that an average of 3.7% of the stream network was reliably dry, while 16.1% was reliably wet at the end of the dry season, with the remainder of the network exhibiting variability in wetted conditions in response to antecedent precipitation. Both climatic and landscape characteristics controlled the extent of the wetted network, particularly antecedent precipitation at seasonal and annual time scales, highlighting the role of hydrologic memory in this system. Given predictions of increased climate volatility, an improved understanding of the spatial patterns and stability of dry season conditions in intermittent streams can inform climate risk assessments and strategies for protecting biodiversity and the ecosystem services that intermittent streams support.
Combination of Near-Infrared Photoimmunotherapy Using Trastuzumab and Small Protein Mimetic for HER2-Positive Breast Cancer

Near-infrared photoimmunotherapy (NIR-PIT) is a promising cancer therapy based on a monoclonal antibody conjugated to a photosensitizer (IR700Dye) that is activated by near-infrared light irradiation. We previously reported on the use of NIR-PIT with a small protein mimetic, the Affibody molecule (6–7 kDa), instead of a monoclonal antibody. In this study, we investigated a combination of NIR-PIT for HER2-positive breast cancer cells (SK-BR3, MDA-MB361, and JIMT1) with HER2 Affibody-IR700Dye conjugate and trastuzumab-IR700Dye conjugate. HER2 Affibody and trastuzumab target different epitopes of the HER2 protein and do not compete. In vitro, the combination of NIR-PIT using both HER2 Affibody-IR700Dye conjugate and trastuzumab-IR700Dye conjugate induced necrotic cell death of HER2-positive breast cancer cells without damage to HER2-negative breast cancer cells (MCF7). It was more efficient than NIR-PIT using either the HER2 Affibody-IR700Dye conjugate alone or the trastuzumab-IR700Dye conjugate alone. Additionally, this combination of NIR-PIT was significantly effective against HER2 low-expressing cancer cells, trastuzumab-resistant cells (JIMT1), and brain metastatic cells of breast cancer (MDA-MB361). Furthermore, in vivo imaging exhibited the strong fluorescence intensity of both HER2 Affibody-IR700Dye conjugates and trastuzumab-Alexa488 conjugates in HER2-positive tumor, indicating that both HER2 Affibody and trastuzumab specifically bind to HER2-positive tumors without competing with each other. In conclusion, the combination of NIR-PIT using both HER2 Affibody and trastuzumab expands the targeting scope of NIR-PIT for HER2-positive breast cancer.
A Very Large Eddy Simulation of the Nonreacting Flow in a Single-Element Lean Direct Injection Combustor Using PRNS with a Nonlinear Subscale Model

Very large eddy simulation (VLES) of the nonreacting turbulent flow in a single-element lean direct injection (LDI) combustor has been successfully performed via the approach known as the partially resolved numerical simulation (PRNS/VLES) using a nonlinear subscale model. The grid is the same as the one used in a previous RANS simulation, which was considered as too coarse for a traditional LES simulation. In this study, we first carry out a steady RANS simulation to provide the initial flow field for the subsequent PRNS/VLES simulation. We have also carried out an unsteady RANS (URANS) simulation for the purpose of comparing its results with that of the PRNS/VLES simulation. In addition, these calculated results are compared with the experimental data. The present effort has demonstrated that the PRNS/VLES approach, while using a RANS type of grid, is able to reveal the dynamically important, unsteady large-scale turbulent structures occurring in the flow field of a single-element LDI combustor. The interactions of these coherent structures play a critical role in the dispersion of the fuel, hence, the mixing between the fuel and the oxidizer in a combustor.
Using Fractional Bernoulli Wavelets for Solving Fractional Diffusion Wave Equations with Initial and Boundary Conditions

In this paper, fractional-order Bernoulli wavelets based on the Bernoulli polynomials are constructed and applied to evaluate the numerical solution of the general form of Caputo fractional order diffusion wave equations. The operational matrices of ordinary and fractional derivatives for Bernoulli wavelets are set via fractional Riemann–Liouville integral operator. Then, these wavelets and their operational matrices are utilized to reduce the nonlinear fractional problem to a set of algebraic equations. For solving the obtained system of equations, Galerkin and collocation spectral methods are employed. To demonstrate the validity and applicability of the presented method, we offer five significant examples, including generalized Cattaneo diffusion wave and Klein–Gordon equations. The implementation of algorithms exposes high accuracy of the presented numerical method. The advantage of having compact support and orthogonality of these family of wavelets trigger having sparse operational matrices, which reduces the computational time and CPU requirements.
Inteligência competitiva: revisão sistemática da produção nacional

RESUMO Neste trabalho se objetivou realizar uma revisão da produção nacional, em periódicos nacionais de primeira linha, nas áreas de administração e de ciência da informação, sobre inteligência competitiva. O estudo é de abordagem qualitativa e de natureza descritiva, adotando como procedimento a revisão sistemática da literatura. Segundo os critérios de seleção, os resultados indicam que os estudos sobre IC são:escassos; preponderantemente referentes à esfera privada; predominantemente da área da ciência da informação;não possuem uma regularidade linear de publicação; e apresentam maior pico de publicação em 2013.
The Case of Tito and Soma Mukhopadhyay: Factitious Heroism by Proxy, Factitious Heroism, and Revealing the Deception Thereof for the Future of Autism Treatment

I reveal the masterful multifaceted communicative fraud that Soma Mukhopadhyay has engaged in with her profoundly autistic son Tito since 2000 on an array of major television programs, and in the presence of an array of scientists, physicians, and autism organization leaders who studied them, and which has not been observed by anyone else. Soma has deceived the public that her son has a normal if not advanced neurology and mind, and that all profoundly autistic persons may as well. She devised a variation of the treatment method and educational method that is referred to as Facilitated Communication, and refers to her method as the Rapid Prompting Method. By my having revealed the intricacy of the communicative fraud that she engages in with Tito, (a) the past, current, and future treatment methods and educational methods for autistic persons may be assessed more carefully by scientists, physicians, journalists, autism organization leaders, and others, and (b) the ways that autistic persons are conceived of may be proceeded with more carefully. I do not intend for my observational work, and ensuing conceptual work, to demonstrate to others that the particular fraud that Soma engages should be monitored for, but rather. that claims of, and demonstrations of, treatment methods and educational methods for autism be acutely visually and auditorily observed, such that the innumerable kinds of fraud that may be occurring are observed. The assessment of treatment methods and educational methods for autism with preexisting methodologies will likely result, as it did of Tito and Soma, in highly surreptitious fraud being overlooked, and perpetuated; and this entails the proliferation of mass deception.
Principles and Methods for Developing a MODSS Process for Farm Forestry

This chapter examines the application of a multi-objective decision-support system (MODSS) to farm forestry. A framework to aid and support decision-making in farm forestry and evaluate farm forestry options is proposed. This framework is developed from previous experiences of the authors and review of the relevant literature on MODSS, multi-criteria analysis (MCA) and community engagement and community participation. An example of a previous MODSS application and process is first described, before drawing on these and other sources to formulate a proposed process.
L'Oeil et l'esprit

L'œil et l'Esprit est le dernier écrit que Merleau-Ponty put achever de son vivant. Installé, pour deux ou trois mois, dans la campagne provençale, non loin d'Aix, au Tholonet, goûtant le plaisir de ce lieu qu'on sentait fait pour être habité, mais surtout, jouissant chaque jour du paysage qui porte à jamais l'empreinte de l'œil de Cézanne, Merleau-ponty réinterroge la vision, même temps que la peinture. Il cherche, une fois de plus, les mots du commencement, des mots, par exemple, capables de nommer ce qui fait le miracle du corps humain, son inexplicable animation, sitôt noué son dialogue muet avec les autres, le monde et lui-même - et aussi la fragilité de ce miracle. Claude Lefort
Development of an application for providing corneal topography reports based on artificial intelligence.

PURPOSE To develop an application (TopEye) in the iOS platform for mobile devices to allow the capture and interpretation of color maps generated by corneal topographers using artificial intelligence. METHODS In the execution, follow-up, and assessment of the project, we used the Scrum methodology and interactive and incremental development process for the project management and agile software development. The ge nerated diagnostic pattern bank consists of 1,172 examples of corneal topography, divided into 275 spherical, 302 symmetrical, 295 asymmetrical, and 300 irregular patterns (keratoconus). For the development of the artificial intelligence of the application, network training was established with 240 images of each pattern type, with a total of 960 patterns (81.91%). The remaining 212 images (18.09%) were used to test the application and will be used for the results. The process is semi-automatic, so the topographic image is captured with a smartphone, the examiner performs the contour of the corneal relief manually, and then the neural network performs the diagnosis. RESULTS The application diagnosed 201 cases (94.81%) correctly. In 212 images, the algorithm missed the classification of 11 cases (5.19%). The major error that occurred was in distinguishing between symmetrical and asymmetrical classes. In keratoconus screening, the application reached 95.00% sensitivity and 98.68% specificity. CONCLUSION The work resulted in obtaining an efficient application to capture topographic images using a smartphone camera and their interpretations through applied artificial intelligence.
Assessing the risk posed by oocysts in drinking water

A recent study of infection and illness in human volunteers subjected to controlled exposure to oocysts of Cryptosporidium parvum provided a suitable data base for dose-response analysis. The authors analyzed the study data, and using exponential and beta-poisson dose-response models, arrived at an estimate of the waterborne concentrations associated with various risk levels.
How To Use Neural Networks To Investigate Quantum Many-Body Physics

Over the past few years, machine learning has emerged as a powerful computational tool to tackle complex problems in a broad range of scientiﬁc disciplines. In particular, artiﬁcial neural networks have been successfully used to mitigate the exponential complexity often encountered in quantum many-body physics, the study of properties of quantum systems built from a large number of interacting particles. In this article, we review some applications of neural networks in condensed matter physics and quantum information, with particular emphasis on hands-on tutorials serving as a quick start for a newcomer to the ﬁeld. The prerequisites of this tutorial are basic probability theory and calculus, linear algebra, basic notions of neural networks, statistical physics, and quantum mechanics. The reader is introduced to supervised machine learning with convolutional neural networks to learn a phase transition, unsupervised learning with restricted Boltzmann machines to perform quantum tomography, and the variational Monte Carlo method with recurrent neural networks for approximating the ground state of a many-body Hamiltonian. For each algorithm, we brieﬂy review the key ingredients and their corresponding neural-network implementation, and show numerical experiments for a system of interacting Rydberg atoms in two dimensions.
Clinical significance and effect of lncRNA BBOX1-AS1 on the proliferation and migration of lung squamous cell carcinoma

Long non-coding RNAs (lncRNAs) have a role in the occurrence and development of lung squamous cell carcinoma (LUSC). lncRNA γ-butyrobetaine hydroxylase 1 (BBOX1)-antisense 1 (AS1) may contribute to disease development. However, there are no studies on the role of BBOX1-AS1 in LUSC to date. In the present study, an in-house gene microarray analysis was performed to detect the differentially expressed lncRNAs and mRNAs between three pairs of LUSC and normal lung tissues. Only one lncRNA, BBOX1-AS1, was differentially expressed in the in-house microarray and The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and ArrayExpress databases. Reverse transcription-quantitative PCR (RT-qPCR) was then performed and the original RNA-sequencing data from the TCGA, GEO and ArrayExpress datasets were used to determine the expression and clinical value of BBOX1-AS1 in LUSC. In addition, a Cell Counting Kit-8 assay, cell cycle analysis and scratch assay were performed to explore whether BBOX1-AS1 expression affected the proliferation and migration of LUSC cells in vitro. The results of the RT-qPCR analysis and data obtained from the TCGA database, GEO datasets, in-house gene microarray and standard mean deviation analysis all supported the upregulated expression level of BBOX1-AS1 in LUSC. Furthermore, silencing of BBOX1-AS1 inhibited the proliferation and migration of LUSC cells according to in vitro assays. In addition, the cells were arrested in S-phase after knockdown of BBOX1-AS1. In conclusion, the expression level of BBOX1-AS1 was upregulated in LUSC tissues. BBOX1-AS1 may exert an oncogenic effect on LUSC by regulating various biological functions. However, additional functional experiments should be performed to verify the exact mechanism.
A human factors analysis of the Stretch mobile manipulator robot

Assistive and mobile robots have potential to support everyday domestic tasks and enable independence for persons in the home. As a first step to evaluating this potential, we assessed the initial unboxing and setup of Hello Robot’s Stretch RE1– a novel mobile manipulator designed for domestic settings. All study procedures took place in the McKechnie Family LIFE Home, which is a smart home research facility on the University of Illinois Urbana-Champaign campus. We used subject matter experts (SMEs) and followed human factors principles to consider obstacles users with diverse needs and capabilities (e.g., older adults, persons with mobility disabilities) might encounter during the unboxing process. We then conducted 50 trials of user testing and critical task analyses in the LIFE home to assess the feasibility and usability for different use cases. Research team members controlled Stretch by using a game controller. We used Stretch to manipulate 15 different types of objects that would be part of domestic activities needed to live independently, such as tasks needed for meal preparation. We documented the frequency of errors, time spent manipulating the object, and informal qualitative feedback from teleoperators during and after each trial (using a think-aloud protocol). Implications for future domestic robot design using human factors approaches are discussed.
A Simulation Study on the New Transport Pathways of Global Tropopause Dust Layer

Previous study of the tropopause aerosol layer is focused on the region surrounding the Tibetan Plateau. However, other transport pathways of the tropopause aerosol layer remain unclear. In this study, by simulating the dusts from different dust sources individually, we detected the Ethiopian Plateau and the Rocky Mountains are two new transport pathways of the global tropopause dust layer (GTDL). In addition, the contributions of different dust sources to the GTDL were quantified, the mass concentration percentage of dusts originating from Indian Peninsula in the GTDL at 100 hPa is 31.5%, which is the largest, followed by those of dusts from Middle East and Northwestern East Asia, dusts from North Africa contribute 17.3% to the GTDL at 100 hPa, which is the smallest. Our results demonstrate the existence of multiple transport pathways of the tropopause aerosol layer and clearly provide the contributions of each dust source to the GTDL.
Live Help Systems

Due to the ever-changing technological landscape and the global integration of the Internet in schools, libraries, homes, and businesses, the content of this second edition changed significantly. Since many computer users are connected at both home and work, the Web has transformed communication; consumption patterns; and access to business, politicians, and neighbors halfway around the world. With numerous books on user-friendly Web sites, the editor's challenge was to deliver a volume with a radically different snapshot of the research being conducted at the beginning of the 21st century. The chapters in this book provide many answers to critical questions and propose thought-provoking research ideas for the future. Corporate and academic practitioners, as well as their doctoral fellows and graduate students from around the globe contributed their time, expertise, and unique research practices. Together, they collectively provide another comprehensive resource that the growing community of human factors and Web development experts can share. The editor's hope is that this book will inspire leading-edge research on accessible Web applications or other topics in the coming years.
Analysis of IDR requirements and History

This document analyses the current state of IDR routing with respect to RFC1126 and other IDR requirements and design efforts. It is the companion document to "Requirements for Inter-Domain Routing" [I-D.irtf-routing-reqs], which is a discussion of requirements for the future routing architecture and future routing protocols. Publication of this document is in accordance with the consensus of the active contributors the IRTF's Routing Research Group.
A MIM Waveguide Structure of a High-Performance Refractive Index and Temperature Sensor Based on Fano Resonance

A plasmonic refractive index nanosensor structure consisting of a metal-insulator-metal (MIM) waveguide with two symmetrical rectangle baffles coupled with a connected-concentric-double rings resonator (CCDRR) is presented. In this study, its transmission characteristics were investigated using the finite element method (FEM). The consequences, studied via simulation, revealed that the transmission spectrum of the system presents a sharp asymmetric Fano profile due to the destructive interference between the wide-band mode of two rectangle baffles on the bus waveguide and the narrow-band mode of the CCDRR. The effects of the geometric parameters of the structure on the transmission characteristics were investigated comprehensively. A sensitivity of 2260 nm/RIU and figure of merit (FOM) of 56.5 were the best levels of performance that the designed structure could achieve. In addition, the system could act as a sensor for use for temperature sensing, with a sensitivity that could reach 1.48 nm/°C. The designed structure advances with technology with new detection positions and has good application prospects in other high-sensitivity nanosensor fields, for example, acting as a biosensor to detect the hemoglobin level in the blood.
An Update on the Anticancer Activity of Xanthone Derivatives: A Review

The annual number of cancer deaths continues increasing every day; thus, it is urgent to search for and find active, selective, and efficient anticancer drugs as soon as possible. Among the available anticancer drugs, almost all of them contain heterocyclic moiety in their chemical structure. Xanthone is a heterocyclic compound with a dibenzo-γ-pyrone framework and well-known to have “privileged structures” for anticancer activities against several cancer cell lines. The wide anticancer activity of xanthones is produced by caspase activation, RNA binding, DNA cross-linking, as well as P-gp, kinase, aromatase, and topoisomerase inhibition. This anticancer activity depends on the type, number, and position of the attached functional groups in the xanthone skeleton. This review discusses the recent advances in the anticancer activity of xanthone derivatives, both from natural products isolation and synthesis methods, as the anticancer agent through in vitro, in vivo, and clinical assays.
Finite Element Modeling of Hot Stamping

Presented is a methodology for finite element modeling of the continuous press hardening of car components using ultra high strength steel. The methodology is not specific to a particular problem or any FE software package. The Numisheet 2008 benchmark problem BM03 was selected as the model problem to be solved. Although there are several commercial finite element computer codes available to model hot stamping, this paper presents results using LS‐DYNA. All modeling parameters, including thermal‐mechanical material property data and boundary condition data, are given.
Estimating Health-Related Quality of Life Based on Demographic Characteristics, Questionnaires, Gait Ability, and Physical Fitness in Korean Elderly Adults

The elderly population in South Korea accounted for 15.5% of the total population in 2019. Thus, it is important to study the various elements governing the process of healthy aging. Therefore, this study investigated multiple prediction models to determine the health-related quality of life (HRQoL) in elderly adults based on the demographics, questionnaires, gait ability, and physical fitness. We performed eight physical fitness tests on 775 participants wearing shoe-type inertial measurement units and completing walking tasks at slower, preferred, and faster speeds. The HRQoL for physical and mental components was evaluated using a 36-item, short-form health survey. The prediction models based on multiple linear regression with feature importance were analyzed considering the best physical and mental components. We used 11 variables and 5 variables to form the best subset of features underlying the physical and mental components, respectively. We laid particular emphasis on evaluating the functional endurance, muscle strength, stress level, and falling risk. Furthermore, stress, insomnia severity, number of diseases, lower body strength, and fear of falling were taken into consideration in addition to mental-health-related variables. Thus, the study findings provide reliable and objective results to improve the understanding of HRQoL in elderly adults.