The prices of open access publishing: the composition of APC across different fields of sciences

Modern media technologies paved the way to the open access movement. Instead of the traditional academic subscription and publishing model, which allowed few big publishers to charge excessive publishing fees, the open access model raises the hope for a fair system, where scientific content is freely accessible and thus the dissemination of research work becomes possible at little cost. However, previous literature pointed out that big publishers seem to be able to preserve their market power when going from the subscription-based model to the open access model. In this paper, we take a closer look at the differences across disciplines. The publication routines in Social Sciences, Physical Sciences, Life Sciences and Health Sciences differ to a substantial extent. On these grounds, we test whether there are also differences in the explanations for the article processing charges (APC) across these disciplines. For doing so, we combined various data sources such as the dataset of the “Directory of Open Access”, the “OpenAPC Initiative” and the “CiteScore Metrics”. Our regression results show that the differences across the four fields in terms of publication habits and endowment levels allow publishers to exploit their market power to different extents

Drivers of article processing charges in open access

Large publishing companies have been dominating scientific publishing for long, which leads to high subscription fees and inhibited access to scientific knowledge. At digital era, the opportunity of an unrestricted access appears feasible, because the cost of publishing should be low. It is no longer the readers and libraries to pay subscription fees, but scientific organizations and authors themselves who pay for the cost of having their article published. As the data shows, there is a tremendous variance of article processing charges (APC) across journals, which obviously cannot be explained by the costs. One of the explanatory variables could be reputation, but it only contributes less than 5% to the variance in APC. This study is meant to shed light on the various determinants of APC. Based on data from the OpenAPC Initiative, the Directory of Open Access Journals, the Journal Impact Factor and the Essential Science Indicators of Web of Science, we employ ANOVA and multivariate regressions. The results show that market power plays an important role to explain APCs, inter alia, through market concentration, market position of individual publishers (publisher size), and the choice of hybrid publishing model

The brave new world of digital personal assistants: benefits and challenges from an economic perspective

The paper applies economic theories to give an overview of the emerging phenomenon of digital personal assistants (DPAs). A DPA is an intelligent automated system that interacts with the user through a dialogue in natural language, and meanwhile applying third-party services to obtain information and perform various actions. We analyze the benefits of increasing usage of DPAs, such as reduction of transaction costs, enhanced organization efficiency, procompetitive effects, and boosting the e-commerce economy. Besides benefits, however, adopting DPA in life may also contain some risks and downsides, which may reduce the positive welfare effects or even lead to decreasing welfare: biased services, market power on the DPA market and economic dependence on a dominant DPA, potential leveraging of DPA suppliers’ market power into neighboring markets, personalized data (ab)use and privacy, media bias and manipulation of public opinion

Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning

Large Language Models (LLMs) have shown impressive capabilities, yet they still struggle with math reasoning. In this work, we propose CoT-Influx, a novel approach that pushes the boundary of few-shot Chain-of-Thoughts (CoT) learning to improve LLM mathematical reasoning. Motivated by the observation that adding more concise CoT examples in the prompt can improve LLM reasoning performance, CoT-Influx employs a coarse-to-fine pruner to maximize the input of effective and concise CoT examples. The pruner first selects as many crucial CoT examples as possible and then prunes unimportant tokens to fit the context window. A math reasoning dataset with diverse difficulty levels and reasoning steps is used to train the pruner, along with a math-specialized reinforcement learning approach. As a result, by enabling more CoT examples with double the context window size in tokens, CoT-Influx significantly outperforms various prompting baselines across various LLMs (LLaMA2-7B, 13B, 70B) and 5 math datasets, achieving up to 4.55% absolute improvements. Remarkably, without any fine-tuning, LLaMA2-70B with CoT-Influx surpasses GPT-3.5 and a wide range of larger LLMs (PaLM, Minerva 540B, etc.) on the GSM8K. CoT-Influx serves as a plug-and-play module for LLMs and is compatible with most existing reasoning prompting techniques, such as self-consistency and self-verification

Visual analysis of alpine meadow research trends and hotspots based on VOS viewer

In order to reveal the overall research progress in the field of alpine meadows. In this study, a visual clustering analysis of the literature was conducted using VOS viewer software. The English literature related to alpine meadow was searched in the Web of Science database with publication dates limited to 2020–2021, and 3,607 papers were retrieved from the Web of Science using Excel software. By analyzing the basic profiles of annual publication volume, publication country/region, publication journal, publication institution, publication author, and keywords, the hot spots and development trends of alpine meadow research were derived. The data show that China is the top global country for alpine meadow research in the world, the institution with the most publications in Chinese Acad Sci, and the most publications are by Huakun Zhou from China (81 articles); “enzymes”, “climate change” and “microorganisms” are the current hot spots for alpine meadow research. This study analyzes the publication situation, research hotspots and research trends in the field of alpine meadow research to provide a reference for the academic research on alpine meadows for those related to this field

Pentyl (E)-3-(3,4-dihy­droxy­phen­yl)acrylate

In the mol­ecule of the title compound, C14H18O4, the C=C double bond is in an E configuration. The mol­ecule is almost planar (r.m.s. deviation of all non-H atoms = 0.04 Å). An intra­molecular O—H⋯O hydrogen bond occurs. In the crystal, inter­molecular O—H⋯O inter­actions link the mol­ecules into ribbons extending in [110]

MONITORING CROP GROWTH STATUS BASED ON OPTICAL SENSOR

Abstract: In order to detect the growth status and predict the yield of the crop, crop growth monitor measuring nitrogen content in the plant is developed based on optical principle. The monitor measures the spectral reflectance of the plant canopy at the 610 nm and 1220 nm wavebands, and then calculates the nitrogen content in the plant with the measured data. The field test was carried out to evaluate performance of the monitor. A portable multi-spectral radiometer named Crop Scan was used to measure the reflectance as a reference instrument. The result shows that the leaf reflectance measured by the monitor has a close linear correlation with that measured by Crop Scan at the 610 nm waveband (R2 = 0.7604), but the correlation between them is needed to be improved at the 1220 nm waveband. The hardware and the software of the monitor are also explained in detail. It is still need to be improved to satisfy the demand of ground-based remote sensing in precision farming

Characterization of Human Coronavirus Etiology in Chinese Adults with Acute Upper Respiratory Tract Infection by Real-Time RT-PCR Assays

BACKGROUND: In addition to SARS associated coronaviruses, 4 non-SARS related human coronaviruses (HCoVs) are recognized as common respiratory pathogens. The etiology and clinical impact of HCoVs in Chinese adults with acute upper respiratory tract infection (URTI) needs to be characterized systematically by molecular detection with excellent sensitivity. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we detected 4 non-SARS related HCoV species by real-time RT-PCR in 981 nasopharyngeal swabs collected from March 2009 to February 2011. All specimens were also tested for the presence of other common respiratory viruses and newly identified viruses, human metapneumovirus (hMPV) and human bocavirus (HBoV). 157 of the 981 (16.0%) nasopharyngeal swabs were positive for HCoVs. The species detected were 229E (96 cases, 9.8%), OC43 (42 cases, 4.3%), HKU1 (16 cases, 1.6%) and NL63 (11 cases, 1.1%). HCoV-229E was circulated in 21 of the 24 months of surveillance. The detection rates for both OC43 and NL63 were showed significantly year-to-year variation between 2009/10 and 2010/11, respectively (P<0.001 and P = 0.003), and there was a higher detection frequency of HKU1 in patients aged over 60 years (P = 0.03). 48 of 157(30.57%) HCoV positive patients were co-infected. Undifferentiated human rhinoviruses and influenza (Flu) A were the most common viruses detected (more than 35%) in HCoV co-infections. Respiratory syncytial virus (RSV), human parainfluenza virus (PIV) and HBoV were detected in very low rate (less than 1%) among adult patients with URTI. CONCLUSIONS/SIGNIFICANCE: All 4 non-SARS-associated HCoVs were more frequently detected by real-time RT-PCR assay in adults with URTI in Beijing and HCoV-229E led to the most prevalent infection. Our study also suggested that all non-SARS-associated HCoVs contribute significantly to URTI in adult patients in China