Miracle-dz/UniFAR-FTUs huggingface dataset:
An overview of the preclinical discovery and development of trastuzumab deruxtecan: a novel gastric cancer therapeutic

ABSTRACT Introduction Gastric cancer is common worldwide, and while multiple therapeutic options exist, the prognosis remains poor. Tumors may overexpress HER2. While targeting HER2 with trastuzumab provides a survival benefit, options following progression are limited. Subsequent trials of HER2-targeted agents failed to improve outcomes. Recently, DESTINY-Gastric01 demonstrated a survival benefit utilizing the antibody-drug conjugate (ADC) trastuzumab deruxtecan in gastric cancer patients that progressed on trastuzumab. Areas Covered /The authors give background to gastric cancer/HER2 and discuss prognostic implications of HER2 overexpression. They also describe initial trials of anti-HER2 therapy, resistance mechanisms, and ADC development/optimization. Finally, the authors review DESTINY-Gastric01 and provide future perspectives. Expert opinion While the 2010 ToGA trial demonstrated efficacy of trastuzumab in HER2 positive gastric cancer, subsequent trials of HER2-directed therapy have disappointed. Downregulation of HER2 after trastuzumab may play a role; however, trastuzumab deruxtecan maintains some efficacy in low-level HER2 expressing tumors. The DESTINY-Gastric01 cohort was from South Korea/Japan; authors have reported differences in gastric cancer risk factors/physiology between Eastern and Western populations. DESTINY-Gastric02 will evaluate trastuzumab deruxtecan in Western patients to confirm generalizability. Pulmonary side effects are notable;physicians must be cognizant of overlapping toxicities with combination therapy.
Side-effects of oxytocin in postpartum hemorrhage: a systematic review and meta-analysis.

OBJECTIVE To evaluate the side-effects of oxytocin for the prevention of postpartum hemorrhage (PPH) in randomized controlled trials (RCTs). METHODS Electronic databases (Web of Science, Embase, PubMed, Elsevier ScienceDirect, the Cochrane Library, and ClinicalTrials.gov) were searched from the beginning of indexing to Sep 2021. RCTs comparing oxytocin with non-oxytocin uterotonic agent(s) or non-pharmacologic interventions for the prevention of PPH were eligible. RESULTS Overall, sixty-one RCTs meeting the inclusion criteria were included, involving 68834 participants. Twenty-seven types of side-effects were reported in this study. There were 24, 35, or 2 trials assessed as high medium and low quality, respectively. Compared with non-oxytocin, oxytocin had significantly lower risk for shivering (RR=0.31, 95% CI=0.23-0.41, n=36680), fever (RR=0.27, 95% CI=0.20-0.37, n=34031), and diarrhea (RR=0.48, 95% CI=0.35-0.66, n=30883). Other side-effects were not found associated with oxytocin. CONCLUSION Oxytocin use was association with a significantly lower incidence of shivering, fever, and diarrhea events and did not increase risk of other side-effects during the third stage of labor. These observations may aid obstetricians and gynecologists in weighing up the benefits and risks associated with oxytocin in prevention and treatment of PPH during the third stage of labor.
Mating Disruption of Codling Moth (Lepidoptera: Tortricidael with Polyethylene Tube Dispensers: Determining Emission Rates and the Distribution of Fruit Injuries'

Emission characteristics of three sex pheromone components of codling moth. Cydia pomoflella (L.), from a polyethylene lube dispenser lIsed for mating disruption were determined and regression models predicting the emission rate of' each componeni as a function of temperature and accumulated degree hours above DoC were developed. Field experiments were conducted in small plots of apple during 1989-90 t.o measure intraseasonal changes in the distribution of fruit injury within pheromone· treated blocks. Fruit injury was < 0.5% in 0.4 ha plots treated with 1,000­ 4,000 dispensers per ha in 1989 except in plots situated along the border of the orchard adjacent to a non-pheromone-treated orchard with high levels of fTuit injury. In a separate orchard in 1990, the differential application of pheromone dispensers (2,000 per hal and insecticides was used to create four I-ha plots with moderate to high population densities of codling moth larvae during the first generation (50-fold range in densities of injured fruits per tree). Subsequently, all plots were treaLed with pheromone prior to the second generution. Fruit injury at harvest was < 1.0% for 'Delicious' in all plots except the highest density (HD) plot (4.0%), but was ca. 1.0% or higher for "Golden Delicious' in all plots (14% in the liD plot). The mean number of injured fruits per tree for 'Delicious' and 'Golden Delicious' illcr'eased 10 and 25 fold between generations in the plot adjacent to and within tOO m of the HD plot, respectively. Results from bot.h years demonstrated the effectiveness of mat.ing disruption in suppressing t.he populat.ion buildup of codling mot.h in plots of apple not exposed to immigration of mot.hs.
An ultra‐wide band diversity antenna with band‐rejection capability for imaging applications

In this paper, a 2‐element UWB‐MIMO antenna system is proposed for imaging applications. Each antenna element consists of semi‐circular slot excited by 50 Ω microstrip transmission lines. Two small stubs are used on both sides of the microstrip lines for better impedance matching at higher frequencies. The band‐rejection at WLAN (5.15–5.825 GHz) band is achieved through a U‐shaped slot in the feeding transmission line. The antenna works efficiently from 3.1 to 10.6 GHz, covering the entire standard UWB. Slots in the ground plane are introduced to improve the isolation level between the antenna elements. A minimum isolation of 20 dB is attained in the entire operating band. The proposed antenna has a size of 58 × 27 mm2 . Good agreement is obtained between simulated and measured results for reflection coefficient, isolation and consistent radiation patterns over the entire operating band that makes it promising candidate for medical imaging application in UWB.
Eight-year post-trial follow-up of health care and long-term care costs of tele-based health Eight-year post-trial follow-up of health care and long-term care costs of tele-based health coaching What This Study Adds

Objective: To evaluate the long-term effect of telephone health coaching on health care and long-term care (LTC) costs in type 2 diabetes (T2D) and coronary artery disease (CAD) patients. Data sources/study setting: Randomized controlled trial (RCT) data was linked to Finnish national health and social care registries and electronic health records (EHR). Post-trial eight-year economic evaluation was conducted. Study design: A total of 1,535 patients (≥ 45 years) were randomized to intervention (n=1034) and control groups (n=501). Intervention group received monthly telephone health coaching for 12 months. Usual health care and LTC were provided for both groups. Principal findings: Intention-to-treat analysis showed no significant change in total health and long-term care costs (intervention effect €1,248 [3% relative reduction], CI -6,347 to 2,217) in the intervention compared to the control group. There were also no significant changes among subgroups of patients with T2D or CAD. Conclusions: Health coaching had a non-significant effect on health care and long-term care costs in the 8-year follow-up among patients with T2D or CAD. More research is needed to study, which patient groups, at which state of the disease trajectory of T2D and cardiovascular disease, would best benefit from health coaching.
A phonetic pilot study of chirp, chatter, tweet and tweedle in three domestic cats

This study collected 257 vocalisations from three domestic cats when they were watching birds through the window. The sounds were subdivided into the types chatter, chirp, tweet and tweedle, and analysed for duration and F0. Variation was found within and between these types as well as within and between the three cats in both duration and F0. A tentative taxonomy of prey-observing cat vocalisations is suggested based on words used for bird sounds.
State of the art on ethical, legal, and social issues linked to audio- and video-based AAL solutions Details about this white paper

Ambient assisted living (AAL) technologies are increasingly presented and sold as essential smart additions to daily life and home environments that will radically transform the healthcare and wellness markets of the future. An ethical approach and a thorough understanding of all ethics in surveillance/monitoring architectures are therefore pressing. AAL poses many ethical challenges raising questions that will affect immediate acceptance and long-term usage. Furthermore, ethical issues emerge from social inequalities and their potential exacerbation by AAL, accentuating the existing access gap between high-income countries (HIC) and low and middle-income countries (LMIC). Legal aspects mainly refer to the adherence to existing legal frameworks and cover issues related to product safety, data protection, cybersecurity, intellectual property, and access to data by public, private, and government bodies. Successful privacy-friendly AAL applications are needed, as the pressure to bring Internet of Things (IoT) devices and ones equipped with artificial intelligence (AI) quickly to market cannot overlook the fact that the environments in which AAL will operate are mostly private (e.g., the home). The social issues focus on the impact of AAL technologies before and after their adoption. Future AAL technologies need to consider all aspects of equality such as gender, race, age and social disadvantages and avoid increasing loneliness and isolation among, e.g. older and frail people. Finally, the current power asymmetries between the target and general populations should not be underestimated nor should the discrepant needs and motivations of the target group and those developing and deploying AAL systems. Whilst AAL technologies provide promising solutions for the health and social care challenges, they are not exempt from ethical, legal and social issues (ELSI). A set of ELSI guidelines is needed to integrate these factors at the research and development stage.
Universal Dependencies and Semantics for English and Hebrew Child-directed Speech

While corpora of child speech and child-directed speech (CDS) have enabled major contributions to the study of child language acquisition, semantic annotation for such corpora is still scarce and lacks a uniform standard. We compile two CDS corpora—in English and Hebrew—with syntactic and semantic annotations. We employ a methodology that enforces a cross-linguistically consistent representation, building on recent advances in dependency representation and semantic parsing. Our semi-automatic syntactic annotation follows the Universal Dependencies standard (UD; de Marneffe et al., 2021), adapted to suit the CDS genre. To induce semantic forms, we develop an automatic method for transducing UD structures into sentential logical forms (LFs), e.g. figure 1. The two representations have complementary strengths: UD structures are language-neutral and support direct annotation, whereas LFs are neutral as to the syntax-semantics interface, and transparently encode semantic distinctions. What follows is a brief synopsis of the work, which is described in full in (Szubert et al., 2021).
Democratizing Creativity by Enhancing Imagery and Agency: A Review and Meta-Analysis

Creativity is a vital topic of various educational discourses, yet the support it receives within the school system is insufficient. This chapter focuses on four particular ways of making creativity more democratized, salient, and accessible in school settings. We start by exploring the educational benefits of egalitarian theoretical approaches to creativity. Then, we posit that democratization requires an equal focus on the cognitive aspects of creative potential and the motivational sphere of self-perception and self-regulation. Third, analyzing cognitive characteristics, we pay special attention to creative imagery: an understudied yet critical aspect of creative potential. By meta-analyzing available evidence from interventional studies, we show that there are multiple effective approaches to enhancing creative imagery, so—in a sense—supporting creative potential might be democratized as well by going beyond creativity training. Fourth, and finally, we discuss the possibilities of adapting so-called wise interventions for the educational psychology of creativity. We review available evidence of how to strengthen creative confidence and the perceived value of creativity among students, and how to make their creative self-regulation more effective.
Middle grades IRL: A collective self-study of practices and problems of practice in the context of middle grades teacher education

Abstract As middle grades teacher educators, we carry a responsibility to prepare pre-service teachers for the realities of practice ahead in their real-world classrooms. Similarly, middle school instructional coaches and specialists support in-service practitioners within the authentic context of their real world, real time experiences as teachers. In the roles of middle grades teacher educator and middle grades instructional coach, there can be a considerable focus on theories that underlie best practices, but what happens when theory and practice have untested connections or when theory and practice diverge? And, what happens if teacher education fails to focus on maintaining an authentic context in the real world? In The Successful Middle School, This We Believe, Bishop and Harrison put forth the importance of ensuring clear correlations between theory and practice, as the idea that professional learning for all staff [should be] relevant, long term, and job embedded. Within this descriptor of doing middle school successfully is a call to continuously examine connections and disconnections between classroom theory put forth by teacher educators and authentic, current middle grades practices. This article tells the story of a collective self-study between middle grades teacher educators who were seeking to interrogate connections and disconnections between theory and practice. In shared inquiry and critical reflection, we sought, not only to uncover problems of practice in our professional spheres, but also to confront the gaps that emerged between theory and practice, looking for ways to more explicitly connect our work with the middle grades In Real Life (IRL).
Invariant measures and statistical solutions for a nonautonomous nonlocal Swift–Hohenberg equation

This paper investigates a two-dimensional nonautonomous nonlocal Swift–Hohenberg equation with two kinds of kernels and studies the existence of invariant measures and statistical solutions, which are important research objects in the area of turbulence for fluid systems. The existence of weak solutions guarantees a norm-to-weak continuous process associated with the nonautonomous equation. We first prove the existence of the pullback attractor for the process via the pullback flattening. Then the unique existence of invariant measures is obtained by appropriate construction, so that the invariant measure is supported by this pullback attractor. This invariant measure is turned out to be exactly a statistical solution of the original nonlocal Swift–Hohenberg equation.
Spectroscopic ellipsometry for low-dimensional materials and heterostructures

Abstract Discovery of low-dimensional materials has been of great interest in physics and material science. Optical permittivity is an optical fingerprint of material electronic structures, and thus it is an important parameter in the study of the properties of materials. Spectroscopic ellipsometry provides a fast, robust, and noninvasive method for obtaining the optical permittivity spectra of newly discovered materials. Atomically thin low-dimensional materials have an extremely short vertical optical path length inside them, making the spectroscopic ellipsometry of low-dimensional materials unique, compared to traditional ellipsometry. Here, we introduce the fundamentals of spectroscopic ellipsometry for two-dimensional (2D) materials and review recent progress. We also discuss technical challenges and future directions in spectroscopic ellipsometry for low-dimensional materials.
Analysis of Customer Loyalty Using Artificial Neural Networks

The way to build artificial intelligence is not only the mathematical machine learning model which are stiff towards a new adaption. On other hand we do have deep learning technique which is capable of adapting the formulae by dynamic learning in which the artificial neural network plays a crucial role for data which are in matrix form so we are going to use artificial neural network for the classification of the churn modelling dataset.
The Eye Gaze Features and Preference of Teacher Image Existence in Junior High Students During Online Learning

Online learning has become widespread with the spread of infectious diseases. Due to its convenience, some movements plan to continue online education even after infectious disease has subsided. We focused on the ideal way of displaying teacher images during online learning. Our previous research confirmed that junior and senior high school students preferred teacher images more than graduate students and gazed longer at teacher images. In this paper, we increased the number of participants in the experiment to 53 for junior high school students and verified our previous results. Additionally, by analyzing the relationship between the preference for the teacher image existence, the correctness of the quiz answer, and the gaze point, it was shown that there was a possibility that the answer correctness and the preference for the teacher image were related.
Agriculture Assistant Chatbot Using Artificial Neural Network

As India has an agro-based economy, 58% of its population relies on agriculture as its primary method of livelihood. In spite of this, the economic survey for 2019–2020 indicates that agriculture growth in India has stagnated around 2.9% annually for the past 6 years. Considering the number of people in India still relying on it, it is a real concern. One of the prevailing issues is lack of right information. This problem can be solved by providing farmers with expert advice and relevant information (e.g. determine when to irrigate, how to sow seeds, and which pesticides to use effectively to increase the yields). In this paper, the proposed chatbot called AgroBot is a multi-user chat application. AgroBot can overcome this problem by allowing farmers to obtain the information they need to succeed in an ever-changing market and to enlarge with new technology and market demand in an easy-to-use manner. Farmers can communicate easily with the chatbot since the system uses NLP (Natural Language Processing) to identify and parse farmer inquiries, identify the main key words and their questions, identify the main keywords and compare them to the Knowledge Base, and provide the best possible results. The development of such a system would benefit farmers by allowing them to gain better information about agricultural practices and, as a result, increase agricultural productivity.
Planetary gearbox condition monitoring based on modulation analysis

The epicycle gearbox or planetary gearbox (PG) is a central power transmission systems of important machines such as helicopters and wind turbines which are mission critical and high cost systems. Condition monitoring (CM) has been explored extensively in recent years to avoid any unexpected interruptions and severe accidences caused by faults PGs. Although, considerable advancements in CM techniques, there still existed significant deficiency such as insensitivity, false diagnosis and high costs in implementing such techniques in industries. To improve CM techniques, therefore, this thesis focuses on an investigation of advanced signal analysis techniques such as higher order spectra (HOS) in order to achieve full characterisation of the nonlinear modulation processes of PG dynamics and thereby develop accurate diagnostic techniques. The lumped mass model is established for modelling the dynamic behaviour of the PG under investigation, which allows the vibration behaviours to be understood for analysing different abnormalities such as tooth breakages and gear errors. This paves the way for subsequent data analytics and fault diagnostics using modulation signal bispectrum (MSB) that allows the vibration data to be examined through HOS, but it is significantly efficient in characterising the multiple and nonlinear modulations of PG dynamics alongside superior noise reduction performance. Different degrees of misalignments in the PG drive system has been investigated and successfully diagnosed using MSB analysis of vibration measurements. Moreover, the investigation included detection of tooth breakage faults of different severities in both the sun and a planet gear. The tooth faults were diagnosed using the recently developed MSB through accurately representation and estimate of residual sidebands induced by these faults. Consequently, MSB analysis produces an accurate and reliable diagnosis in that it gives correct indication of the fault severity and location for wide operating conditions. Furthermore, these fault diagnosis practices allows the establishment of residual sideband analysis approach. These residual sidebands resulting from the out-of-phase superposition of vibration waves due to asymmetric, multiple meshing sources are much less influenced by gear errors than the in-phase sidebands due to faults or new occurrences of the symmetricity. MSB can provide an accurate characterisation of the residual sidebands and consequently produces consistent diagnosis as confirmed by both simulation and experiment.
Detecting trend motifs: an efficient framework for time series motif discovery

The task of finding similar patterns in a long time series, commonly called motifs, has received continuous and increasing attention from diverse scientific fields. Although numerous approaches have been proposed for motif discovery, they cannot discover the motifs in an exact and efficient manner. Furthermore, domain knowledge is required from the experts for those methods to predefine the pattern length, which is also quite objective. In addiction, it is very time-consuming to extract the exact motifs and sometimes the extracted motif has no specific meanings. Especially in the field of financial and hydrology, many studies are focused on whether there is a fixed pattern including trend information hidden in the data. To address the above problems, we proposed a framework to automatically discovery the trend motifs without predefining the length of patterns. It has four main steps, (1) singular spectrum analysis is first applied to removed noise; (2) segmentation by extracting extreme points is then employed to automatically obtain the unequal length of time series pattern; (3) symbolic aggregate approximation is introduced to discretize the data and transform them into string sequences; (4) finally, the trend motifs are selected by measuring their similarity. Experimental results on the real-world time-series datasets reveal that our framework fit well in different circumstances, indicating our proposed framework is effective for trend motif discovery.
Simulation Study on Bird Droppings Flashover of Catenary Insulator Based on Finite Element Method

Electrified railway plays a vital role in the development of the national economy, so preventing catenary trips caused by bird damage has become a key issue related to normal railway operation. In this paper, by using COMSOL Multiphysics, the simulation study of different falling conditions of bird droppings around the insulator of catfish was conducted, then it obtained the electric field and voltage distribution in the insulator space under three flashover conditions. Finally, after comparing the probability of flashover under different conditions, it provided a theoretical basis for the monitoring of insulator bird damage and operation state evaluation.