Miracle-dz/UniFAR-FTUs huggingface dataset:
Context-aware Spatial-Temporal Neural Network for Citywide Crowd Flow Prediction via Modeling Long-range Spatial Dependency

Crowd flow prediction is of great importance in a wide range of applications from urban planning, traffic control to public safety. It aims at predicting the inflow (the traffic of crowds entering a region in a given time interval) and outflow (the traffic of crowds leaving a region for other places) of each region in the city with knowing the historical flow data. In this article, we propose DeepSTN+, a deep learning-based convolutional model, to predict crowd flows in the metropolis. First, DeepSTN+ employs the ConvPlus structure to model the long-range spatial dependence among crowd flows in different regions. Further, PoI distributions and time factor are combined to express the effect of location attributes to introduce prior knowledge of the crowd movements. Finally, we propose a temporal attention-based fusion mechanism to stabilize the training process, which further improves the performance. Extensive experimental results based on four real-life datasets demonstrate the superiority of our model, i.e., DeepSTN+ reduces the error of the crowd flow prediction by approximately 10%–21% compared with the state-of-the-art baselines.
Diagnostic markers of local allergic rhinitis

Local allergic rhinitis is a new atopic disease recognized in modern allergy and rhinology. Its clinical symptoms are currently well described and compared with conventional allergic rhinitis, however, diagnostic and therapeutic protocols, including antigen-specific immunotherapy (ASIT), should be specified. Therefore, local allergic rhinitis often remains underdiagnosed and by mistake is referred to non-allergic rhinitis. Yet, the pathogenesis and mechanisms of allergen tolerance breakdown in this endotype of allergic rhinitis remain understudied. Researchers continue to study the network of tolerogenic cells and biomolecules, such as regulatory T cells, tolerogenic dendritic cells, interleukin (IL)-10, IL-35, transforming growth factor-β (TGF- b ), vegetative innervation of the nose, and neurotransmitters. The review focuses on diagnostic markers of local allergic rhinitis.
Polar lipids are linked to nanoparticles in xylem sap of temperate angiosperm species

Xylem sap of angiosperm species has been found to include low concentrations of polar lipids and nanoparticles, including surfactant-coated nanobubbles. Although the nanoparticles have been suggested to consist of polar lipids, no attempt has been made to determine if nanoparticle and lipid concentrations are related. Here, we examined concentrations of nanoparticles and lipids in xylem sap and contamination control samples of six temperate angiosperm species with a NanoSight device and based on mass spectrometry. We found (1) that the concentration of nanoparticles and lipids were both diluted when an increasing amount of sap was extracted, (2) that their concentrations were significantly correlated in three species, (3) that their concentrations were affected by vessel anatomy, and (4) that concentrations of nanoparticles and lipids were very low in contamination-control samples. Moreover, there was little seasonal difference, no freezing-thawing effect on nanoparticles, and little seasonal variation in lipid composition. These findings indicate that lipids and nanoparticles are related to each other, and largely do not pass interconduit pit membranes. Further research is needed to examine the formation and stability of nanoparticles in xylem sap in relation to lipid composition, and the complicated interactions among the gas, liquid, and solid phases in xylem conduits.
Peer Aggression and Sexual Harassment among Young Adolescents in a School Context: A Comparative Study between Finland and Turkey

The study investigates peer aggression and sexual harassment among young adolescents in Finland and Turkey. Sex differences and the interaction effect between country of residence and sex are also examined. A questionnaire was completed by 1,747 adolescents (1, 268 from Finland, 479 from Turkey, Mage = 14.1). Six different forms of aggression (physical, verbal, indirect, cyber, verbal sexual harassment, physical sexual harassment) were examined. More adolescents from Turkey, and more boys, were found to be involved in aggression as both victims and perpetrators compared to adolescents from Finland and girls. The interaction effect was significant between country of residence and sex with being a boy from Turkey was related to having the highest involvement in cyber aggression, verbal sexual harassment, and physical sexual harassment, as both victim and perpetrator. Regarding victimization from indirect aggression, girls from Finland scored higher than Turkish girls, while boys from Turkey scored higher than Finnish boys.
A model for the transient pulsation generation at the discharge of a screw compressor by a shock tube analogy

Although screw compressors (dry and wet) have been widely used in many applications (such as HVAC&R, petrochemical and gas transmission, plant air, etc.) for more than half a century, limited information is available regarding the genesis and mechanism of gas pulsations at pocket passing frequency (PPF) dominating at discharge side of these compressors [1]. The understanding of its physical nature, magnitude and affecting parameters, the location and moment of generation, and the velocity it propagates are all of fundamental, and will help to determine how it will interact with downstream components such as silencers and piping system, especially for accurately predicting downstream pulsation levels and excited vibration and noise at the higher multiples of the PPF. The primary goal of this paper is to apply the shock tube theory [2] to screw compressors during the transient generation phase of gas pulsations at discharge. It will reveal that the nature of gas pulsation is a combination of large amplitude compression waves (CW) and expansion waves (EW) accompanied with an induced fluid flow (IFF). The most dominant gas pulsation at discharge is directly caused by either an over compression (OC) or a under compression (UC) suddenly discharging to compressor outlet. Therefore its exact location and moment of generation, magnitude, travelling directions and velocity can all be predicted based on design parameters and operating conditions of those machines. With this knowledge, its interactions with the compressor cavity and downstream piping and silencer are conducted for a typical UC and case, and results are in good agreement with the test data of previous researchers. The analysis suggests that the shock tube model can provide a pedagogic tool in understanding the physics of the transient phase of pulsation generation and subsequent formation. As such it can provide valuable insight to developers of more precise CFD calculations and a comprehensive algorithm of gas pulsations in the future.
The complete chloroplast genome of Epimedium sutchuenense Franch. (Berberidaceae)

Abstract Epimedium L. is the largest herbaceous genus in the family Berberidaceae which comprises more than 60 species. Epimedium sutchuenense Franch. is narrowly inhabited in the Daba Mountains of China. In the current study, we assembled the first complete chloroplast genome of E. sutchuenense through Illumina paired-end sequencing. The complete chloroplast genome of E. sutchuenense was 157,218 bp in length and the total GC content was 38.78%. A total of 112 unique genes were identified, including 78 protein-coding genes, 30 tRNA genes and 4 rRNA genes. The phylogenetic analysis demonstrated that E. sutchuenense was sister to Epimedium wushanense T. S. Ying. Our results provided valuable information for further phylogenetic research and germplasm exploration of Epimedium genus.
Abundance and phenology drive plant–pollinator network responses to restoration in the Southern Atlantic rainforest in Brazil

Ecological restoration has been increasingly considering biotic interactions. Different restoration strategies usually rely on different composition and abundance of plants with potential impact on the establishment of plant–pollinator interactions. We evaluated the restoration of plant–pollinator interaction networks in young restoration areas in the South Atlantic rainforest, Brazil. We assessed the relative contribution of two restoration strategies (natural regeneration vs. reforestation), geographic distance, plant composition, pollinator composition, abundance of flowers and insects, and plant–pollinator temporal overlap, that is, phenological coupling, to predict the establishment of pairwise interactions. We expected that restoration strategies would indirectly affect the patterns (identity and frequency) of pairwise interactions due to their influence on the processes driving interactions. We sampled monthly pollinators and the plants they visited on six reforestation sites and six natural regeneration sites during 20 months. We surveyed flower abundance in summer. We analyzed the relative contribution of each factor to predict the identity and frequency of pairwise interactions using structural equation modeling. Contrary to expectations, the restoration strategy did not predict interactions, probably because the sites under restoration were surrounded by natural and conserved landscapes. Since we found no effect of restoration strategies on plant composition, abundance, and phenological coupling, the restoration strategy did not predict interactions. Phenological coupling explained more than half of the interaction patterns, representing the best predictor of interactions followed by abundance and plant composition. Therefore, these predictors should be considered to select plant species in restoration projects that encompass interactions and pollination services.
Factors associated with consistent bedtime routines and good sleep outcomes

ABSTRACT Bedtime routines have “strong” support for addressing bedtime behavior problems and sleep; however, little research has examined factors associated with bedtime routines and sleep quality. Parents of 155 children ages 3 to 5 were surveyed about their children’s bedtime routines, bedtime anxiety, compliance, and sleep quality. Regression models supported a simple indirect effect of bedtime routine consistency on sleep quality through bedtime anxiety, but not through compliance at bedtime. In a serial model, consistent bedtime routines were related to sleep quality through first bedtime anxiety and then compliance near bedtime. Clinically, results suggest that if parents can alleviate child anxiety around bedtime through routines, compliance around bedtime, and a good night sleep may follow.
Onodera's Prognostic Nutritional Index is a novel and useful prognostic marker for gastrointestinal stromal tumors

BACKGROUND Immunoinflammatory markers such as the peripheral blood neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR) have gained considerable attention as prognostic markers in gastrointestinal stromal tumors (GISTs). AIM To assess the prognostic value of Onodera’s Prognostic Nutritional Index (OPNI) for GISTs. METHODS All patients who had undergone surgical resection for a primary, localized GIST from 2009 to 2016 at our cancer center were initially and retrospectively identified. Recurrence-free survival (RFS) was calculated by the Kaplan-Meier method and compared by the log-rank test. We used multivariate Cox proportional hazard regression models to identify associations with outcome variables. RESULTS A total of 235 GISTs were identified and included for analysis under our inclusion criteria. Univariate and multivariate analyses both identified the OPNI as an independent prognostic marker, and the OPNI was associated with the primary site, tumor size, mitotic index, tumor rupture, necrosis, and modified NIH risk classification. Low OPNI (< 51.30; hazard ratio = 5.852; 95% confidence interval: 1.072–31.964; P = 0.0414) was associated with worse RFS. The 2- and 5-year RFS rates of the patients with a low OPNI were 92.83% and 76.22%, respectively, whereas 100% and 98.41% were achieved by the patients with a high OPNI. CONCLUSION The preoperative OPNI is a novel and useful prognostic marker for GISTs.
The Listening Zone of Human Electrocorticographic Field Potential Recordings

Abstract Intracranial electroencephalographic (icEEG) recordings provide invaluable insights into neural dynamics in humans because of their unmatched spatiotemporal resolution. Yet, such recordings reflect the combined activity of multiple underlying generators, confounding the ability to resolve spatially distinct neural sources. To empirically quantify the listening zone of icEEG recordings, we computed correlations between signals as a function of distance (full width at half maximum; FWHM) between 8752 recording sites in 71 patients (33 female) implanted with either subdural electrodes (SDEs), stereo-encephalography electrodes (sEEG), or high-density sEEG electrodes. As expected, for both SDEs and sEEGs, higher frequency signals exhibited a sharper fall off relative to lower frequency signals. For broadband high γ (BHG) activity, the mean FWHM of SDEs (6.6 ± 2.5 mm) and sEEGs in gray matter (7.14 ± 1.7 mm) was not significantly different; however, FWHM for low frequencies recorded by sEEGs was 2.45 mm smaller than SDEs. White matter sEEGs showed much lower power for frequencies 17–200 Hz (q < 0.01) and a much broader decay (11.3 ± 3.2 mm) than gray matter electrodes (7.14 ± 1.7 mm). The use of a bipolar referencing scheme significantly lowered FWHM for sEEGs, relative to a white matter reference or a common average reference (CAR). These results outline the influence of array design, spectral bands, and referencing schema on local field potential recordings and source localization in icEEG recordings in humans. The metrics we derive have immediate relevance to the analysis and interpretation of both cognitive and epileptic data.
Online and Distributed Robust Regressions with Extremely Noisy Labels

In today’s era of big data, robust least-squares regression becomes a more challenging problem when considering the extremely corrupted labels along with explosive growth of datasets. Traditional robust methods can handle the noise but suffer from several challenges when applied in huge dataset including (1) computational infeasibility of handling an entire dataset at once, (2) existence of heterogeneously distributed corruption, and (3) difficulty in corruption estimation when data cannot be entirely loaded. This article proposes online and distributed robust regression approaches, both of which can concurrently address all the above challenges. Specifically, the distributed algorithm optimizes the regression coefficients of each data block via heuristic hard thresholding and combines all the estimates in a distributed robust consolidation. In addition, an online version of the distributed algorithm is proposed to incrementally update the existing estimates with new incoming data. Furthermore, a novel online robust regression method is proposed to estimate under a biased-batch corruption. We also prove that our algorithms benefit from strong robustness guarantees in terms of regression coefficient recovery with a constant upper bound on the error of state-of-the-art batch methods. Extensive experiments on synthetic and real datasets demonstrate that our approaches are superior to those of existing methods in effectiveness, with competitive efficiency.
The complete chloroplast genome sequences of an endemic species of Urticaceae (Debregeasia hekouensis)

Abstract Debregeasia hekouensis, which belongs to the nettle family (Urticaceae), is a local endemic species in Hekou County, Yunnan Province, China. To provide a basis for the development of effective molecular markers for its conservation, we sequenced the chloroplast (cp) genome of D. hekouensis in the present study. The total length of the chloroplast(cp) genome was 155,941 bp, and exhibited a typical quadripartite structure, with a pair of IRs (inverted repeats; 25,664 bp in length) being separated by a small single copy (SSC) region of 19,085 bp and a large single copy (LSC) region of 85,528 bp. The cp genome contained a total of 112 genes, including 78 protein-coding genes, 30 tRNA genes, and 4 rRNA genes. The GC content of the entire cp genome, LSC region, SSC region, and IR region was 36.3%, 34.0%, 29.4%, and 42.7%, respectively. Phylogenetic analysis indicated that D. hekouensis is evolutionarily closer to Debregeasia orientalis and Debregeasia squamata.
Designing of Low-Power High-Speed Noise Immune CNTFET 1-Trit Unbalanced Ternary Subtractor

Ternary logic has been demonstrated as a superior contrasting option to binary logic. This paper presents a ternary subtractor circuit in which the input signal is converted into binary. The proposed design is implemented using Carbon Nanotube Field Effect Transistor (CNTFET), a forefront innovation. A correlation has been made in the proposed design on parameters like Power-Delay Product (PDP), Energy Delay Product (EDP), average power consumption, delay and static noise margin. Every one of these parameters is obtained by simulating the circuits on the HSPICE simulator. The proposed design indicates an improvement of 60.14%, 59.34%, 74.98% and 84.28%, respectively, in power consumption, delay, PDP and EDP individually in correlation with recent designs. The increased carbon nanotubes least affect the proposed subtractor design. In noise analysis, the proposed design outperformed all the existing designs.
Classical mathematical models for prediction of response to chemotherapy and immunotherapy

Classical mathematical models of tumor growth have shaped our understanding of cancer and have broad practical implications for treatment scheduling and dosage. However, even the simplest textbook models have been barely validated in real world-data of human patients. In this study, we fitted a range of differential equation models to tumor volume measurements of patients undergoing chemotherapy or cancer immunotherapy for solid tumors. We used a large dataset of 1472 patients with three or more measurements per target lesion, of which 652 patients had six or more data points. We show that the early treatment response shows only moderate correlation with the final treatment response, demonstrating the need for nuanced models. We then perform a head-to-head comparison of six classical models which are widely used in the field: the Exponential, Logistic, Classic Bertalanffy, General Bertalanffy, Classic Gompertz and General Gompertz model. Several models provide a good fit to tumor volume measurements, with the Gompertz model providing the best balance between goodness of fit and number of parameters. Similarly, when fitting to early treatment data, the general Bertalanffy and Gompertz models yield the lowest mean absolute error to forecasted data, indicating that these models could potentially be effective at predicting treatment outcome. In summary, we provide a quantitative benchmark for classical textbook models and state-of-the art models of human tumor growth. We publicly release an anonymized version of our original data, providing the first benchmark set of human tumor growth data for evaluation of mathematical models. Author Summary Mathematical oncology uses quantitative models for prediction of tumor growth and treatment response. The theoretical foundation of mathematical oncology is provided by six classical mathematical models: the Exponential, Logistic, Classic Bertalanffy, General Bertalanffy, Classic Gompertz and General Gompertz model. These models have been introduced decades ago, have been used in thousands of scientific articles and are part of textbooks and curricula in mathematical oncology. However, these models have not been systematically tested in clinical data from actual patients. In this study, we have collected quantitative tumor volume measurements from thousands of patients in five large clinical trials of cancer immunotherapy. We use this dataset to systematically investigate how accurately mathematical models can describe tumor growth, showing that there are pronounced differences between models. In addition, we show that two of these models can predict tumor response to immunotherapy and chemotherapy at later time points when trained on early tumor growth dynamics. Thus, our article closes a conceptual gap in the literature and at the same time provides a simple tool to predict response to chemotherapy and immunotherapy on the level of individual patients.
SECS Analysis of Nighttime Magnetic Perturbation Events Observed in Arctic Canada

Large changes of the magnetic field associated with magnetic perturbation events (MPEs) with amplitudes |ΔB| of hundreds of nT and 5–10 min duration have been frequently observed within a few hours of midnight. This study compares the statistical location of nighttime MPEs with |dB/dt| ≥ 6 nT/s within the auroral current system observed during 2015 and 2017 at two stations, Cape Dorset and Kuujjuarapik, in Eastern Canada. Maps of the two dimensional nightside auroral current system were derived using the Spherical Elementary Current Systems (SECS) technique. Analyses were produced at each station for all events, and for premidnight and postmidnight subsets. We examine four MPE intervals in detail, two accompanied by auroral images, and show the varying associations between MPEs and overhead ionospheric current systems including electrojets and the field‐aligned like currents. We find 225 of 279 MPEs occurred within the westward electrojet and only 3 within the eastward electrojet. For the premidnight MPEs 100 of 230 events occurred within the Harang current system while many of the remainder occurred within either the downward region 1 current system or the upward region 2 current system. Many of the 49 postmidnight MPEs occurred in either the downward region 1 (11 events) or upward region 2 current system (27 events). These result suggest that the source of MPEs in the premidnight sector is somewhere between the inner to mid plasma sheet and the source for the MPEs in the postmidnight sector is somewhere between the inner magnetosphere and the inner plasma sheet.
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هدف البحث الحالي تحليل محتوى كتب الكيمياء للمرحلة المتوسطة على وفق الذكاءات المتعددة ،ولتحقيق هذا الهدف استخدم الباحث المنهج الوصفي التحليلي. ،واعتمد اداةً لتحليل المحتوى – وحدة المساحة –لتحليل كل كتاب من كتب الكيمياء الثلاث -، وتم عرضها على الخبراء والمختصين في طرائق تدريس الكيمياء والقياس والتقويم ، وبعد التوافق على فقراتها تم اعتمادها كأداة تحليل ، واشتملت عينة البحث كتب الكيمياء للصفوف المتوسطة الثلاث. واستعملت الوسائل الاحصائية المناسبة لمعالجة المعلومات ومنها مربع كاي لإيجاد الفروق بين قيمة كل ذكاء ملاحظ في محتوى الموضوعات المتضمنة في كل كتاب من الكتب الثلاثة وقيمه المتوقعة ، وقد أظهرت نتائج البحث وجود فروق دالة احصائيا بين ما متوقع وملاحظ للذكاءات المتعددة للكتب الثلاث بشكل عام فيما عدا الذكاءات (الحركي ، الموسيقي ، والاجتماعي) التي لم تسجل اي تكرار ولم يتم تضمينها في الكتاب . ولم تظهر وجود فروق احصائية دالة عند مستوى (0.05) بين ما هو ملاحظ نتيجة لتحليل محتوى الكتب الثلاث ، والمتوقع تضمينه في الكتب المدرسية الثلاث لكيمياء المرحلة المتوسطة ، وقد خرج الباحث بعدد من الاستنتاجات والتوصيات اللازمة .