Miracle-dz/UniFAR-FTUs huggingface dataset:
Tree-Rings Reveal Accelerated Yellow-Cedar Decline with Changes to Winter Climate after 1980

Research Highlights: Yellow-cedar decline on the island archipelago of Haida Gwaii is driven by warm winter temperatures and low winter precipitation, which is caused by anthropogenic climate change and exacerbated by the positive phase of the Pacific Decadal Oscillation (PDO). Background and Objectives: Declining yellow-cedars are limited by physiological drought during the growing season, caused by freezing damage to fine roots through a complex pathway identified by research in Alaska. Given this, we hypothesized: (1) yellow-cedars on Haida Gwaii were limited by the winter climate. (2) Trees of different health classes were responding differently to climatic variation. (3) Changing climate-growth relations would vary among phases of the PDO. Materials and Methods: We sampled 15 stands exhibiting crown symptoms and developed three regional chronologies from trees that were healthy, had crown or tree-ring symptoms of decline, and trees that had died. We tested for growth responses to inter-annual and multi-decadal variation in climate among trees of different health statuses using correlation functions and wavelet analyses. Results: The three chronologies had similar patterns from the early 1500s to 1900s and responded to climate in the same way, with multi-decadal variability, and common narrow marker years. Climate-growth responses among trees of different health statuses diverged after the 1976/1977 switch in the PDO. Warm growing season temperatures facilitated the growth of trees in the healthy chronology. By contrast, growth of trees that showed symptoms of decline or had died was negatively associated with low winter precipitation. After 1986, growth of trees in the declining chronology decreased sharply and mortality increased, which is concurrent with the warmest winter temperatures and consistent with the root-freezing hypothesis from Alaska. Conclusions: Yellow-cedar decline is driven by climate change, exacerbated by the PDO. Warming winter temperatures, accelerated by anthropogenic climate change, have led to dieback and death of yellow-cedars, even with the temperate ocean-moderated climate of Haida Gwaii.
Rethinking Neural Network Quantization

Quantization reduces computation costs of neural networks but suffers from performance degeneration. Is this accuracy drop due to the reduced capacity, or inefficient training during the quantization procedure? After looking into the gradient propagation process of neural networks by viewing the weights and intermediate activations as random variables, we discover two critical rules for efficient training. Recent quantization approaches violates the two rules and results in degenerated convergence. To deal with this problem, we propose a simple yet effective technique, named scale-adjusted training (SAT), to comply with the discovered rules and facilitates efficient training. We also analyze the quantization error introduced in calculating the gradient in the popular parameterized clipping activation (PACT) technique. Through SAT together with gradient-calibrated PACT, quantized models obtain comparable or even better performance than their full-precision counterparts, achieving state-of-the-art accuracy with consistent improvement over previous quantization methods on a wide spectrum of models including MobileNet-V1/V2 and PreResNet-50.
Flexible Text Modeling with Semi-Implicit Latent Representations

Variational autoencoders (VAEs) have been used recently to learn probabilistic representations in many natural language processing (NLP) applications. Training deficiency has been witnessed when an auto-regressive decoder is used: the learned latent codes becomes almost identical to the prior distribution (termed “posterior collapse,” resulting in a vanishing of the Kullback-Leibler term in the variational expression). We hypothesize that the source of deficiency is due partially to the approximate Gaussian posterior often used in variational inference. We use semiimplicit (SI) representations for the latent distributions of the natural languages. It extends the commonly used Gaussian distribution family, by mixing the variational parameter with a flexible implicit distribution. The increasing representational power of SI is demonstrated on two NLP tasks, showing that it provides more informative latent codes in language modeling, and generates more diverse dialog responses.
The Uncanny Valley: The Original Essay by Masahiro Mori-IEEE Spectrum

(http://www.ieeeras.org/ram.html) IEEE Robotics & Automation Magazine Energy Editor's note: More than 40 years ago, Masahiro Mori, then a robotics professor at the Tokyo Institute of Technology, wrote an essay on how he envisioned people's reactions to robots that looked and acted almost human. In particular, he hypothesized that a person's response to a humanlike robot would abruptly shift from empathy to revulsion as it approached, but failed to attain, a lifelike appearance. This descent into eeriness is known as the uncanny valley. The essay appeared in an obscure Japanese journal called in 1970, and in subsequent years it received almost no attention. More recently, however, the concept of the uncanny valley has rapidly attracted interest in robotics and other scientific circles as well as in popular culture. Some researchers have explored its implications for human-robot interaction and computer-graphics animation, while others have investigated its biological and social roots. Now interest in the uncanny valley should only intensify, as technology evolves and researchers build robots that look increasingly human. Though copies of Mori's essay have circulated among researchers, a complete version hasn't been widely available. This is the first publication of an English translation that has been authorized and reviewed by Mori. [
Financial Reporting Quality and Information Asymmetry: Evidence from the Chinese Stock Market

This paper examines the effect of earnings quality on information flow in the Chinese domestic Aand foreign B-share markets. I find that A-share returns predict B-share returns, suggesting that domestic investors have an information advantage over foreign investors. The ability of Ashare returns to predict B-share returns is negatively correlated with earnings quality, and the negative correlation is robust to controlling for other stock characteristics associated with the firm information environment. Further, I find that the ability of A-share returns to predict Bshare returns decreases significantly in the month after earnings announcements, and that the reduction is only significant for firms with high earnings quality. My results also indicate that earnings quality is negatively correlated with the B-share discount, suggesting that foreign investors are willing to pay more when they face less information disadvantage. These results are consistent with the theory that high quality disclosure of public information can reduce uninformed (foreign) investors’ information disadvantage relative to informed (local) investors and reduce cost of equity. Given that information asymmetry between domestic and foreign investors can deter foreign investment, my results suggest providing high quality accounting information can facilitate foreign investment. JEL classification: G15, F21, M41
Prevalence and classification of drug-drug interactions in intensive care patients

Objective: To identify, quantify and classify drug-drug interactions among the medications most frequently dispensed in the adult ICU of a large private tertiary care hospital over a period of 30 days. Methods: Collection of data from an electronic database on consumption and drug-drug interactions of the 50 most frequently dispensed medications. results: During the period studied, 395 commercial brands were dispensed, representing 258 active ingredients, classified into ten large groups and 36 subgroups according to Anatomical Therapeutic Chemical criteria. Four hundred and nine drug-drug interactions were identified 174 were severe and 235 moderate. The drug-drug interactions were classified as pharmacokinetic (30%), neurologic (22%), and cardiologic (18%), and together accounted for 70% of drug-drug interactions tracked with the Micromedex Healthcare Series® electronic database. The other interactions were classified as hematologic, renal, endocrine/metabolic, respiratory, muscular, gastrointestinal, hepatic, and others, comprising the remaining 30%. Conclusion: Drug-drug interactions are very common in ICU patients. They may potentially produce a significant economic and clinical impact. The use of electronic computerized systems allows a better approach for medical prescriptions making it possible to prevent and intervene in cases of harmful interactions and adverse events even before medications are dosed.
Including of Field Beans as Protein Source in Feed Ration for Dairy Goat

As soybean and rape cake is quite expensive protein sources, alternative protein sources like field bean seeds have been successfully used in diets for ruminants. The aim of the study was to evaluate the field bean feeding options and the impact on goat milk productivity and quality. The dietary treatments were as follows: 1st control group received concentrate which contained rape cake as the main proteinous feed; and 2nd trial group received concentrate 0.80 kg per day per goat, containing field beans as the main proteinous feed in substitution of rape cake. In basic ration for both the control and trial group was observed a relatively high energy (10.3 12.4% of requirement) deficit Including of field beans in feed ration made it possible to optimize slightly feed ration. Including of beans in feed ration did not lead to an increase in goat milk productivity. Milk yield decreased in both groups, but in the trial group productivity decline was more rapid than in control group. Significant decrease in the number of milk somatic cells by 29% was observed in the trial group, where animals received field beans as protein source. Keywords— filed bean, goat, milk, protein.
Standardized Questionnaires for User Experience Evaluation: A Systematic Literature Review

Standardized questionnaires are one of the methods used to evaluate User Experience (UX). Standardized questionnaires are composed of an invariable group of questions that users answer themselves after using a product or system. They are considered reliable and economical to apply. The standardized questionnaires most recognized for UX evaluation are AttrakDiff, UEQ, and meCUE. Although the structure, format, and content of each of the questionnaires are known in detail, there is no systematic literature review (SLR) that categorizes the uses of these questionnaires in primary studies. This SLR presents the eligibility protocol and the results obtained by reviewing 946 papers from four digital databases, of which 553 primary studies were analyzed in detail. Different characteristics of use were obtained, such as which questionnaire is used more extensively, in which geographical context, and the size of the sample used in each study, among others.
Gang of Eight: A Defect Taxonomy for Infrastructure as Code Scripts

Defects in infrastructure as code (IaC) scripts can have serious consequences, for example, creating large-scale system outages. A taxonomy of IaC defects can be useful for understanding the nature of defects, and identifying activities needed to fix and prevent defects in IaC scripts. The goal of this paper is to help practitioners improve the quality of infrastructure as code (IaC) scripts by developing a defect taxonomy for IaC scripts through qualitative analysis. We develop a taxonomy of IaC defects by applying qualitative analysis on 1,448 defect-related commits collected from open source software (OSS) repositories of the Openstack organization. We conduct a survey with 66 practitioners to assess if they agree with the identified defect categories included in our taxonomy. We quantify the frequency of identified defect categories by analyzing 80,425 commits collected from 291 OSS repositories spanning across 2005 to 2019. Our defect taxonomy for IaC consists of eight categories, including a category specific to IaC called idempotency (i.e., defects that lead to incorrect system provisioning when the same IaC script is executed multiple times). We observe the surveyed 66 practitioners to agree most with idempotency. The most frequent defect category is configuration data i.e., providing erroneous configuration data in IaC scripts. Our taxonomy and the quantified frequency of the defect categories may help in advancing the science of IaC script quality.
Professionalism and Job Performance Among Nurses in General Hospitals, Mandalay Region, The Republic of the Union of Myanmar

ความเป็นวิชาชีพและการปฏิบัติงานของพยาบาลเป็นองค์ประกอบส�าคัญในการให้การพยาบาลกับผู้ ป่วย และอาจมีผลต่อคุณภาพของการให้การพยาบาล การศึกษาเชิงพรรณนาหาความสัมพันธ์ครั้งนี้มี วตัถปุระสงค์เพื่อศึกษาระดบัของความเป็นวิชาชพีและการปฏบิัตงิาน ความสัมพนัธร์ะหวา่งความเป็นวิชาชพี และการปฏิบัติงานตามบทบาทหน้าท่ีและการปฏิบัติงานตามบริบทในพยาบาลโรงพยาบาลทั่วไปในเขต มัณฑะเลย์ สาธารณรัฐแห่งสหภาพเมียนมาร์ กลุ่มตัวอย่างของการศึกษานี้คือพยาบาล 263 คนที่ท�างานใน โรงพยาบาลทั่วไป 5 แห่งในเขตมัณฑะเลย์ เครื่องมือที่ใช้ในการศึกษาวิจัยในครั้งนี้ได้แก่ แบบวัดระดับความ เป็นวิชาชีพของฮอล ซ่ึงปรับปรุงโดยสนิเซค (1972) และ แบบวัดระดับการปฏิบัติงานของพยาบาลฉบับย่อ ของกรีนสเลด (2008) การวิเคราะห์ข้อมูลโดยใช้สถิติเชิงพรรณนาและสัมประสิทธิ์สหสัมพันธ์แบบอันดับของ เพียร์สัน ผลการวจิยัพบว่าระดบัของความเป็นวชิาชพีในพยาบาลอยู ใ่นระดบัปานกลาง (x _ =85.76, SD=7.75), ระดับของการปฏิบัติงานตามบทบาทหน้าที่และการปฏิบัติงานตามบริบทในพยาบาลอยู่ในระดับปานกลาง (x _ =48.75, SD=12.08, x _ =51.38, SD=13.50) และ ยงัพบความสมัพันธ์เชิงบวกอย่างมนียัส� าคญัระหว่างความ เป็นวชิาชีพและการปฏบิตังิานตามบทบาทหน้าที ่(r=0.361, p<0.01) และการปฏบิตังิานตามบรบิทในพยาบาล (r=0.324, p<0.01) ผลการวจัิยเหล่านี ส้ามารถน� าไปใช้ในการพฒันากลยทุธ์การปรบัปรงุความเป็นวชิาชพีและผลการปฏบิติั งานซึ่งมีอิทธิพลต่อคุณภาพการดูแล
Eleventh-Hour Earnings Management and Financial Reporting Timeliness

Prior studies find that firms that delay earnings announcements tend to release unfavorable news, and investors consequently react negatively when firms delay earnings announcements. However, these findings do not explain why investors discount delayed earnings, even after controlling for the earnings news, and why firms sometimes announce good news late. Motivated by theory in Trueman (1990) that attempts to explain these two phenomena, we examine whether firms announcing earnings abnormally late is indicative of last-minute earnings manipulation. Consistent with post fiscal year-end activities driving announcement delays, we find no relation between measures of real earnings management and late announcements. However, we find evidence that late announcers with good news exhibit higher discretionary accruals. Using a lastchance earnings management measure based on tax expense manipulation, we find strong evidence that firms announcing good news with a delay tend to engage in more income-increasing eleventhhour earnings management. Consistent with Trueman’s (1990) theory that last-minute earnings management helps explain why investors discount delayed earnings announcements, even after holding fixed unexpected earnings news, we find that the negative relation between earnings announcement returns and announcement delays is driven by late announcing firms relying on tax expense manipulation to beat analysts’ expectations.
Do the Scirus-Google test

The very definition of a catchment points to the concept of the water cycle: the catchment is a landscape unit where all outflowing water is derived from precipitation falling on the surface of the catchment. A catchment may be defined in the horizontal sense by the topographical water divide and vertically in some arbitrary way (for instance, as the zone of intensive biological and biogeochemical activity between unweathered and impermeable bedrock up to tree tops).
Automated Method of Road Extraction from Aerial Images Using a Deep Convolutional Neural Network

Updating road networks using remote sensing imagery is among the most important topics in city planning, traffic management and disaster management. As a good alternative to manual methods, which are considered to be expensive and time consuming, deep learning techniques provide great improvements in these regards. One of these techniques is the use of deep convolution neural networks (DCNNs). This study presents a road segmentation model consisting of a skip connection of U-net and residual blocks (ResBlocks) in the encoding part and convolution layers (Conv. layer) in the decoding part. Although the model uses fewer residual blocks in the encoding part and fewer convolution layers in the decoding part, it produces better image predictions in comparison with other state-of-the-art models. This model automatically and efficiently extracts road networks from high-resolution aerial imagery in an unexpansive manner using a small training dataset.
Patenting performance in SMEs with endogenous venture capital financing

Empirical evidence on the effect of venture capital involvement on firms’ patent productivity has been mixed. We aim to assess this effect through simultaneous models that predict firms’ ability to attract venture capital likelihood and its relation to the likelihood to patent and the number of patents applied for and being granted. While prior research has estimated these equations separately, we allow for endogeneity of venture capital investment. Only in simple models with separate equations we confirm prior findings of a positive impact of venture capital on patenting, which has been interpreted as coaching or “smart money”. If we account for endogeneity, this effect becomes insignificant or negative. Our results support the view that venture capital follows patent signals to invest in companies with commercially viable products instead of actively contributing to patent production after the investment. Other relevant predictors for patenting activities are market size and product development time. Expected growth plays a minor role, whereas strong industry competition increases the number of patents if the firm is patenting, but not the likelihood to patent.
Localizing the Information Source in a Network

Information and content can spread in social networks analogous to how diseases spread between organisms. Identifying the source of an outbreak is challenging when the infection times are unknown. We consider the problem of detecting the source of a rumor that spread randomly in a network according to a simple diffusionmodel, the susceptible-infected (SI) exponential time model. The infection times are unknown. Only the set of nodes that propagated the rumor before a certain time is known. Since evaluating the likelihood of spreads is computationally prohibitive, we propose a simple and efficient procedure to approximate the likelihood and select a candidate rumor source. We empirically demonstrate our method out-performs the Jordan center procedure in various random graphs and a real-world network.
Type III interferons: Balancing tissue tolerance and resistance to pathogen invasion

Type III IFNs, or IFN-λ, are the latest addition to the IFN family. Thanks to a restricted pattern of expression of their receptor and to unique immunomodulatory properties, IFN-λ stimulates pathogen clearance while, at the same time, curbing inflammation to maintain barrier integrity.
Pattern electroretinography in patients with unilateral acute central serous chorioretinopathy

Background To evaluate the pattern electroretinography (PERG) in patients with acute central serous chorioretinopathy (CSCR) at baseline and after spontaneous resolution. Methods A total of 32 patients (mean ± SD age: 38.8 ± 8.2-years, 71.9 per cent female) with unilateral acute CSCR and spontaneous resolution during follow‐up period were included. The unaffected eyes of the study patients comprised the control group. The best‐corrected visual acuity, PERG and optical coherence tomography findings were recorded both at baseline and following spontaneous resolution at two to four months. Results The P50 and N95 amplitudes of the affected eyes were significantly lower than the control group both at baseline and after CSCR resolution (p < 0.001 for each). A significant increase was noted in both P50 and N95 amplitudes of the affected eyes from baseline to post‐resolution (p < 0.001 for each). Subfoveal choroidal thickness was significantly higher in the affected eyes as compared with control eyes both at the baseline and after CSCR resolution along with a significant decrease in the affected eyes from baseline to post‐resolution (p < 0.001 for each). The central retinal thickness was higher in the affected eyes as compared with the control eyes at baseline (p = 0.009), along with a significant decrease in the affected eyes from baseline to post‐resolution (p < 0.001). Between the baseline P50 amplitude and the visual acuities of the affected eyes, a strong correlation was noted at baseline (r = −0.691, p < 0.001) and a moderate correlation was noted after CSCR resolution (r = −0.422, p = 0.031). Conclusions In conclusion, our findings revealed an association of CSCR with impaired P50 and N95 amplitudes and a significant improvement but not a complete recovery in both parameters after CSCR resolution. Our findings emphasise potential utility of PERG in the electrophysiological evaluation of functional impairment in CSCR patients and the likelihood of P50 amplitude to have a prognostic value in CSCR.
Siponimod therapy implicates Th17 cells in a preclinical model of subpial cortical injury.

Subpial demyelination is a specific hallmark of multiple sclerosis (MS) and a correlate of disease progression. Although the mechanism(s) that mediate pathogenesis in the subpial compartment remain unclear, it has been speculated that inflammation in the overlying meninges may be associated with subpial injury. Here we show that adoptive transfer of proteolipid protein-primed Th17 cells into SJL/J recipient mice induces subpial demyelination associated with microglial/macrophage activation, disruption of the glial limitans and evidence of an oxidative stress response. This pathology was topologically associated with foci of immune cells in the meninges and occurred in the absence of measurable anti-MOG IgM or IgG antibodies. To test the role of brain-infiltrating leukocytes on subpial injury, we modulated sphingosine 1-phosphate (S1P) receptor1,5 activity with BAF312 (siponimod) treatment. Administration of BAF312, even after adoptively transferred T cells had entered the brain, significantly ameliorated clinical EAE and diminished subpial pathology, concomitant with a selective reduction in the capacity of transferred T cells to make Th17 cytokines. We conclude that sustained subpial cortical injury is associated with the capacity for brain-resident T cells to produce Th17 cytokines, and this pathological process occurs in an S1P receptor1,5-dependent manner.