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Source code is essential for researchers to reproduce the methods and replicate the results of artificial intelligence (AI) papers. Some organizations and researchers manually collect AI papers with available source code to contribute to the AI community. However, manual collection is a labor-intensive and time-consuming task. To address this issue, we propose a method to automatically identify papers with available source code and extract their source code repository URLs. With this method, we find that 20.5% of regular papers of 10 top AI conferences published from 2010 to 2019 are identified as papers with available source code and that 8.1% of these source code repositories are no longer accessible. We also create the XMU NLP Lab README Dataset, the largest dataset of labeled README files for source code document research. Through this dataset, we have discovered that quite a few README files have no installation instructions or usage tutorials provided. Further, a large-scale comprehensive statistical analysis is made for a general picture of the source code of AI conference papers. The proposed solution can also go beyond AI conference papers to analyze other scientific papers from both journals and conferences to shed light on more domains. [ABSTRACT FROM AUTHOR]

This paper contains original data on the composition and structure of Oligochaeta communities in the zone of influence of wastewater from a pulp and paper mill (the Vychegda River, Northern Dvina River basin). Forty species and forms of oligochaetes have been identified. We have found species which had been earlier identified only in tributary floodplain water bodies and lakes of the Vychegda River basin. According to the diversity index (Shannon index (HN) and Simpson index (DS)), evenness index (Pielow index (E)), and Whittaker (βw) indices, the studied section of the river exceeds the control section in regards to species diversity. There is a significant increase in abundance and biomass of oligochaetes in comparison to the section upstream the river. Based on a correlation analysis between the quantitative development indicators of oligochaetes and the environmental parameters (type of substrate, presence of algal growths and macrophytes, depth, and chemical composition), an assessment of biotopic confinement of species (Fj), and the conjugate between species (rA), we found that the distribution of oligochaetes in the study area largely depends on the type of substrate. According to the results of the assessment of diversity and distribution of oligochaetes in the zone of influence of wastewater from a pulp and paper mill, the appearance of technogenic areas with an artificial substrate along the bank line leads to changes in the composition, diversity, and quantitative development characteristics of benthic organisms. [ABSTRACT FROM AUTHOR]

Background: Great variation has been observed in the composition of the normal microbiota of the ocular surface, and therefore, in addition to differences in detection techniques, the method of collecting ocular surface specimens has a significant impact on the test results.The goal of this study is to ascertain whether the eye surface microbial communities detected by two different sampling methods are consistent and hence explore the feasibility of using tear test paper instead of conjunctival swabs to collect eye surface samples for microbial investigation. Materials and methods: From July 15, 2021, to July 30, 2021, nonirritating tear test strips and conjunctival swabs of both eyes were used in 158 elderly people (> 60 years old) (79 diabetic and 79 nondiabetic adults) in Xinjing Community for high-throughput sequencing of the V3-V4 region of the 16S rRNA gene. The composition of the microbial communities in tear test paper and conjunctival swab samples was analyzed. Results: There was no statistically significant difference in Alpha diversity of ocular surface microorganisms represented by tear strip and conjunctival swab in diabetic group (P > 0.05), but there was statistically significant difference in Alpha diversity of ocular surface microorganisms detected by tear strip and conjunctival swab in nondiabetic group (P < 0.05). There were statistically significant differences in Beta diversity of ocular surface microorganisms detected by two sampling methods between diabetic group and nondiabetic group (P < 0.05). There were statistically significant differences in ocular surface microorganisms detected by tear strip method between diabetic group and nondiabetic group (P < 0.05), but there was no statistically significant difference in conjunctival swab method (P > 0.05). Conclusions: Tear test paper and conjunctival swabs detect different compositions of microbes through two different techniques of eye surface microbe sampling. Tear test paper cannot completely replace conjunctival swab specimens for the study of microbes related to eye surface diseases. [ABSTRACT FROM AUTHOR]

From many years, studies on psychoanalysis were built within a Newtonian framework. Today, with updated contemporary knowledge about quantum physics, we have the opportunity to bring a deeper appreciation to the study of psychoanalysis. Based on the contemporary development of quantum mechanics, I sought to demonstrate how these developments are compatible with psychoanalytic psychotherapy. By illustrating the supervised psychotherapy case below, I sketch a line of thought about a quantum-like modeling in psychoanalytic psychotherapy, specifically in the psychoanalytic listening. Finally, I have proposed ‘Quantum Listening’ eventually transmitting this quantum-like perspective of psychoanalytic listening to the rest of the psychoanalyst community and psychiatrist society in general. Through this paper, I hope to demonstrate how quantum physics is applicable to psychoanalysis. Although it is hard to know how much credence is given to the concept ‘Quantum Listening’, it does add motivation for a more comprehensive understanding of psychoanalytic listening. This short and basic paper is a preliminary to ‘Quantum Listening’ and further research will be carried out afterwards. [ABSTRACT FROM AUTHOR]

Numerous prior studies claimed that social enterprises had a beneficial effect (social impact) on addressing society's social problems. However, there is little evidence to support that statement. How well is this enterprise able to give an impact on solving social problems? Does it have any indicators that can prove the validity of its social impact? Therefore, this study aims to explore the literature review on social enterprise and their social impact, as well as to identify a few measurements to assess the social impact. Hence, the writing of this article was conducted based on reviewing the published literature including articles and journals which are relevant to the topic that can be accessed through online databases. Scopus, Science Direct and Google Scholar have been used for searching the articles needed. The search terms include "social enterprise" OR "social business" OR "social entrepreneurship" AND "Social impact" OR "measuring impact" OR "social impact measurement". This conceptual paper was motivated to get a deeper understanding of the social impact measurement employed by social enterprises. From the discussion, we have clearly defined the definition of social impact from different perspectives, including the importance of measuring the social impact among social enterprises has also been discussed briefly. Reviewed articles revealed that there is a wide range of methods for measuring social impact but in this article, we are focusing on three approaches only there are: balanced scorecard (BSC), social return on investment (SROI), and cost-benefit analysis (CBA) in this paper. This study summarises that measuring the social impact is becoming an essential determination for social enterprises as the key indicators of their performance to the communities or to the potential investors or funders. The study also suggests recommending further study of the social impact measurements that need to be discussed in depth and detail. This study's hope can attract more academicians to stimulate more research on this topic, specifically in measuring methods from Malaysia's perspective. The implication of this study forms a clear understanding of the social impact and a few of the measurements that can be used in measuring the impact of social enterprise. [ABSTRACT FROM AUTHOR]

This policy recommendation proposes the implementation of the Terrorism, Radicalisation and Extremism Disclosure Scheme (TREDS) as an additional measure to Prevent and counter violent extremism and terrorism in the United Kingdom. TREDS represents a viable mechanism for a responsible adult (‘the applicant’) to make a disclosure request to joint local authority and Police Prevent teams where they feel an individual (‘the subject’) may pose a risk to a young or vulnerable person (‘the person at-risk’) in relation to terrorism, radicalisation or extremism. A successful disclosure is intended to empower the ‘applicant’ to take proactive steps to safeguard the ‘person at risk’ from the risk of harm posed by the ‘subject’, and would include, where reasonable, proportionate, and necessary, information about a ‘subject’s terrorism related criminal offending history, including any Police intelligence held relating to terrorist group affiliations, associations or activities. TREDS takes inspiration from disclosure schemes already employed to safeguard and protect children and vulnerable people from other crime types such as The Domestic Violence Disclosure Scheme (DVDS), also known as Clare’s Law; and the Child Sexual Offender Disclosure Scheme (CSODS), known as Sarah’s Law. The Terrorism, Radicalisation and Extremism Disclosure Scheme (TREDS) was designed by the author of this policy recommendation between June 2018 and February 2019 in response to the decline in public or community reporting of concerns related to terrorism, radicalisation and extremism. This decline is evidenced by Home Office statistics, which identify that of the 7,318 total referrals made in 2017/18, just 292 (4%) came from communities (Home Office, 2018). TREDS represents a distinct departure from existing reporting processes, and is underpinned by the principle of two-way information sharing between the public and authorities. This signifies a seismic shift toward a more inclusive and reciprocal relationship, and one which is likely to better empower individuals and communities to report concerns as and when they arise.

Expert finding is crucial for a wealth of applications in both academia and industry. Given a user query and trove of academic papers, expert finding aims at retrieving the most relevant experts for the query, from the academic papers. Existing studies focus on embedding-based solutions that consider academic papers’ textual semantic similarities to a query via document representation and extract the top-n experts from the most similar papers. Beyond implicit textual semantics, however, papers’ explicit relationships (e.g., co-authorship) in a heterogeneous graph (e.g., DBLP) are critical for expert finding, because they help improve the representation quality. Despite their importance, the explicit relationships of papers generally have been ignored in the literature. In this article, we study expert finding on heterogeneous graphs by considering both the explicit relationships and implicit textual semantics of papers in one model. Specifically, we define the cohesive (k, P)-core community of papers w.r.t. a meta-path P (i.e., relationship) and propose a (k, P)-core based document embedding model to enhance the representation quality. Based on this, we design a proximity graph-based index (PGIndex) of papers and present a threshold algorithm (TA)-based method to efficiently extract top-n experts from papers returned by PG-Index. We further optimize our approach in two ways: (1) we boost effectiveness by considering the (k, P)-core community of experts and the diversity of experts’ research interests, to achieve high-quality expert representation from paper representation; and (2) we streamline expert finding, going from “extract top-n experts from top-m (m > n) semantically similar papers” to “directly return top-n experts”. The process of returning a large number of top-m papers as intermediate data is avoided, thereby improving the efficiency. Extensive experiments using real-world datasets demonstrate our approach’s superiority. [ABSTRACT FROM AUTHOR]

Neutrinos are one of the most promising messengers for signals of new physics Beyond the Standard Model (BSM). On the theoretical side, their elusive nature, combined with their unknown mass mechanism, seems to indicate that the neutrino sector is indeed opening a window to new physics. On the experimental side, several long-standing anomalies have been reported in the past decades, providing a strong motivation to thoroughly test the standard three-neutrino oscillation paradigm. In this Snowmass21 white paper, we explore the potential of current and future neutrino experiments to explore BSM effects on neutrino flavor during the next decade. [ABSTRACT FROM AUTHOR]