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Predictive article recommendation using natural language processing and machine learning to support evidence updates in domain-specific knowledge graphs

ObjectivesDescribe an augmented intelligence approach to facilitate the update of evidence for associations in knowledge graphs.MethodsNew publications are filtered through multiple machine learning study classifiers, and filtered publications are combined with articles already included as evidence in the knowledge graph. The corpus is then subjected to named entity recognition, semantic dictionary mapping, term vector space modeling, pairwise similarity, and focal entity match to identify highly related publications. Subject matter experts review recommended articles to assess inclusion in the knowledge graph; discrepancies are resolved by consensus.ResultsStudy classifiers achieved F-scores from 0.88 to 0.94, and similarity thresholds for each study type were determined by experimentation. Our approach reduces human literature review load by 99%, and over the past 12 months, 41% of recommendations were accepted to update the knowledge graph.ConclusionIntegrated search and recommendation exploiting current evidence in a knowledge graph is useful for reducing human cognition load.

Reconciling coffee productivity and natural vegetation conservation in an agroecosystem landscape in Brazil

Politicians have approved significant changes to the Brazilian Forest Code (Brazilian Law n. 12.651/2012), providing partial pardons for illegal deforestation in 2012. Nonetheless, the New Forest Code (NFC) may cause economic harm, since ecosystem services may be affected, and the productivity of several crops may end up decreasing. Here, we explored two sets of factors, one at a narrow-scale – the loss of close natural vegetation cover – and another at a wide-scale considering implications at a landscape level to measure the effects of the presence/absence of forest remnants, and consequently, of pollinators, on coffee productivity. The narrow-scale perspective used manipulative experiments in ten coffee plantations, and the wide-scale perspective considered secondary data on coffee productivity in planted and native forests of 61 municipalities to test the hypotheses: i) coffee branches with pollinator access are more productive; ii) coffee crops in contact with native forest remnants are more productive; iii) coffee plants located near to native forest remnants are more productive; iv) coffee productivity increases with the municipality area occupied by native forest remnants, and, v) coffee productivity decreases with the municipality area occupied by Eucalyptus spp. At the narrow-scale, we detected 32 % higher coffee productivity when pollinators were present (hypothesis i) and 15 % higher productivity when forest remnants were in contact with the plantation (hypothesis ii), but no differences related to forest remnants in the broader area (hypothesis iii). At the wide-scale, we observed that a higher amount of native forest cover increased coffee productivity (hypothesis iv), while increased Eucalyptus spp. plantations reduced coffee productivity (hypothesis v). The corroboration of hypotheses i, ii, and iv illustrates the importance of animal pollination and native vegetation remnants fr coffee productivity. The findings for hypothesis v reinforce that Eucalyptus spp. plantations are not good surrogates for native vegetation as part of management recovery action for deforested areas. Following the New Forest Code’s recommendations in Article 22 (Chapter IV, Section II), the preservation of native vegetation, species diversity, and native species regeneration should be attended to in legally instituted natural reserves. Our findings improve discernment that natural areas' devastation or its coverage using planted forest may reduce productivity levels of coffee plantations, representing a disruption of natural complexity, of organisms' connectivity, and consequently of ecosystem services as the pollination and pollinator-dependent crops' productivity, as the coffee.

A Light Recommendation Algorithm of We-Media Articles Based on Content

Since the explosive growth of we-medias today, personalized recommendation is playing an increasingly important role to help users to find their target articles in vast amounts of data. Deep learning, on the other hand, has shown good results in image processing, computer vision, natural language processing, and other fields. But it's a relative blank in the application of we-media articles recommendation. Combining the new features of we-media articles, this paper puts forward a recommendation algorithm of we-media articles based on topic model, Latent Dirichlet Allocation (LDA), and deep learning algorithm, Recurrent Neural Networks (RNNs). Experiments on the real datasets show that the combined method outperforms the traditional collaborative filtering recommendation and non-personalized recommendation method.

The Search for a Result-Oriented Public Sector Reform in Ghana: A Myth or Reality?

The Article Examined Whether Public Sector Reform In Ghana Is A Myth Or Reality. It Emerged That Since Independence In 1957, Successive Governments Implemented Both Socialist And Market-Oriented Public Sector Reforms; However, None Of These Reforms Yielded The Expected Outcome. Hence, The New Patriotic Party On Winning Political Power Initiated The National Public Sector Reform Strategy. This Reform Aimed At Using The Public Sector As The Catalyst To Stimulate The Private Sector For Job Creation And National Development. The Study Found That The Reform Made Some Gains. However, Excessive Partisanship, Narrow Political Commitment, Donor-Funding, The Time Boundedness Of The Reform And Focus On Only 16 Ministries, Departments And Agencies Militated Against It Success Hence Public Sector Reform Is A Myth In Ghana. The Article Recommends Commitment To The Directive Principles Of State Policy As The Panacea To Effectiveness Of Public Sector Reforms In Ghana.

American College of Preventive Medicine Statement on Prioritizing Prevention in Opioid Research.

Research is the foundation of evidence-based health care that motivates innovations in clinical interventions and public health. Prior and current research on opioid use has focused mainly on individual patient-physician relationships, opioid use disorder and treatment, and overdose responses. This article recommends 3 priorities for future research and investigates why, from clinical and ethical standpoints, future research should be directed toward building the capacity and increasing the effectiveness of population-based programs and improving prevention strategies.

Using distributed raspberry PIs to enable low-cost energy-efficient machine learning algorithms for scientific articles recommendation

In recent decades, machine learning has become a crucial factor in terms of automating business operations and assisting in the decision-making process within an organization. With the huge volume of data generated at an unprecedented rate has motivated researchers and industry analysts to constantly develop effective and efficient analytical models machine learning techniques. This study adds to the data mining community by evaluating some of the most significant text mining techniques and presenting a predictive model that will supposedly ease the process of literature review for researchers. In addition, it compares the execution of the model in terms of cost, energy consumption, accuracy and scalability in three different environments, namely, google cloud instance, google cloud functions and distributed raspberry PIs. Results yielded in our study showed that distributed Raspberry PIs can have a highly positive impact in terms of lowering costs and being energy efficient. On one hand, we found out that machine learning algorithms can be adapted and run on distributed raspberry PIs with low cost and low energy consumption compared to cloud alternatives. On the other hand, this solution does not offer great scalability and it requires more time on management, deployment and configuration. The distributed Raspberry PIs also showed bad performance on execution time compared to the other alternatives when comes to high processing power.

From appeal to transgression: problems of modern discourse of religious Transitions

Globalization processes, which are aimed at forming a single language of different cultures, raise problems of modern identity and its transformation. The process of self-identification is complex and depends on the existing worldview, so the transformation of identity entails a change in the worldview, and vice versa. In other words, such transformation can be seen as transgressive processes, which is clearly demonstrated in the example of religious practice.The religious worldview is rather stable, but significant changes are observed today. Influenced by syncretism fashion, new religious practices start blurring the boundaries of the world confessions that have been formed over the centuries, replacing the sacrament of conversion with an act of uncontrolled religious transgression, which is especially characteristic of believers who do not feel a special craving for integral system of dogmas.The authors used the term transgression to fix the phenomenon of crossing the impassable border between the possible and the impossible, leading in some cases to a breakthrough beyond the boundaries of everyday commonness and generally accepted norms. This process is both constructive and destructive, but it is destructive to social norms. Therefore, special attention is paid to the act of religious transgression related to the transition to another faith, which makes it necessary to study in the framework of the article bans and recommendations designed to create a limit of impassability on the borders of world confessions. Based on the comparative analysis of various rules and regulations adopted in Judaism, Islam and Christianity in order to regulate believers’ behavior, the social effect on the formation of the individual religious worldview is analyzed.

Statistical Inference for Online Decision Making: In a Contextual Bandit Setting

Online decision making problem requires us to make a sequence of decisions based on incremental information. Common solutions often need to learn a reward model of different actions given the contextual information and then maximize the long-term reward. It is meaningful to know if the posited model is reasonable and how the model performs in the asymptotic sense. We study this problem under the setup of the contextual bandit framework with a linear reward model. The ε-greedy policy is adopted to address the classic exploration-and-exploitation dilemma. Using the martingale central limit theorem, we show that the online ordinary least squares estimator of model parameters is asymptotically normal. When the linear model is misspecified, we propose the online weighted least squares estimator using the inverse propensity score weighting and also establish its asymptotic normality. Based on the properties of the parameter estimators, we further show that the in-sample inverse propensity weighted value estimator is asymptotically normal. We illustrate our results using simulations and an application to a news article recommendation dataset from Yahoo!. Supplementary materials for this article are available online.

The Relationship Between Urbanization and Household Income

As urbanization has occurred without the attendant growth and development spillovers in underdeveloped nations including Ethiopia, the phenomenon brought undesirable social and economic consequences. This article investigates the relationship between urbanization and urban household income and housing problem. Structural equation modeling was used to run mediation analysis. Correlation and regression analyses were also carried out to measure the direction and magnitude of the effect of the independent variable on the dependent. Regression analysis results indicate the existence of a significant direct effect of urbanization on limitations in income generating capacity of citizens. This article recommends taking policy measures to include development agendas of small and medium towns into regional plans as they absorb the influx to large cities and can help migrants experience the challenging complex urban life step by step. In addition, a policy intervention in the area of land tenure system and real estate development is required before the housing problems gets worsened.

Growth Narrative of Bangladesh Economy

Bangladesh has made impressive progress and undergone structural changes over the last five decades despite resource constraints and various social and political challenges. However, while in the long-term, its economic growth is remarkable, the short-term performance is somewhat disappointing. Moreover, while the average and aggregate numbers paint an inspiring image, disaggregated indicators do not often support the apparent good health of the economy. This paper brings out two issues: (i) what have been the growth drivers of Bangladesh economy, and (ii) what have been the outcomes of growth. It also makes a number of recommendations for maintaining, expediting and sustaining the growth momentum. The article recommends for more employment generation in the formal sector, reduction of inequality, mobilization of higher domestic resources, energizing private investment, and above all, ensuring good governance. The paper emphasizes on continuous institutional reforms to improve the quality of growth and ensure distributional justice in Bangladesh.

‘It’s Important for Us to Know How to Do Teamwork’: Perceptions of Chinese International Hospitality Students Regarding Teamwork Skills

ABSTRACT This article investigates the perceptions held by Chinese international students at one Australian university regarding the importance of teamwork skills for entry-level positions in the Chinese hotel industry and the development of these skills. The findings from 19 semi-structured interviews demonstrate that most respondents feel that it is crucial for Chinese international students to develop teamwork skills for the Chinese hotel industry. Even though some respondents reported positive experiences working on university assignments with other students of different nationalities, others felt that cross-cultural teamwork was challenging due to their perceived weak English language skills and lack of creative ideas. Some students also mentioned that they would like their university lecturers and tutors to assist them in the formation and facilitation of teams. The article recommends structured interventions regarding cross-cultural teamwork and continuous English language teaching to familiarize the Chinese international students with the challenges that they may face.

Reviewer Blinding in Peer Review

Reviewer Blinding in Peer Review

A poststructural analysis of study abroad as teacher preparation pedagogy: Thinking through theory for generative practice

ABSTRACT Scholarship in teacher education reflects study abroad as established pedagogy and part of ‘best practices’ in preparing K-12 teachers for diverse classrooms. Three discourses dominate the literature to affirm the positive role of study abroad: (a) changing White preservice teachers’ perceptions of self and others; (b) increasing their multicultural knowledge and global-mindedness; and, (c) developing competencies for culturally responsive classroom practice. In drawing from several scholars, this article uses poststructural analysis to trouble the above discourses that articulate study abroad within normalizing conceptions of self and other, universal worldview of multicultural knowledge and global-mindedness, and fixed conceptualization of culturally responsive teaching, so that new ways of thinking about disciplinary knowledge and pedagogical practice emerge. This article recommends teacher education pedagogies include critical frames of analyses when interpreting study abroad experiences for thinking through theory for generative practice and reclaiming epistemic reflexivity in how we do research.

Article Recommendation and Comics Story Representation for Twitter User Based Preferences

Twitter is an interesting platform for the dissemination of news. The real-time nature and brevity of the tweets are conductive to sharing of information related to important events as they unfold.Numerous consumer reviews of topics are now available on the Internet. Automatically identifies the important aspects of topics from online consumer reviews. Our method provides an efficient way to accurately categorize comic topic recommendation without need of external data, enabling news organizations to discover breaking news in real-time, or to quickly identify viral memes that might enrich marketing decisions, among others. We filter the stream of incoming tweets to remove junk tweets using a text classification algorithm.We also compare the performance of different supervised SVM text classification algorithms for this task. This study concentrates on analyzing potential and dynamic user correlations, based on topic-aware similarity and behavioral influence, which may help us to discover communities in social networking sites.

When Is a Suboptimal Approach to Cancer Screening Better Than None?

Cancer care in low-resource regions is complex, as resources and infrastructure for cancer care and prevention are limited. Mortality rates for breast cancer in particular are higher in regions where treatments are unavailable, unaffordable, or cost ineffective. Clinical breast examination is a reasonable screening approach, although its effects on mortality have not yet been shown. This article recommends focusing on early detection of symptomatic disease (ie, downstaging) and treatment of early detected breast cancers with potentially curative strategies.

Making Emergency Use of Experimental Vaccines Safer.

Ethical and logistical challenges of deploying experimental vaccines in humanitarian emergencies are exacerbated by a paucity of safety and efficacy data. For outbreaks caused by pathogens with high mortality rates and few treatments, such as Ebola virus disease, not offering access to experimental vaccines with some evidence of efficacy can also be ethically suspect. This article recommends (1) gathering more preclinical data about experimental vaccines' safety and (2) improving research infrastructure to enable participation of a wide range of subjects in affected communities over long trial periods. Motivating these goals would facilitate clearer definitions of population vulnerability and risk acceptability.

Review of Automatic Detection and Classification Techniques for Cetacean Vocalization

Cetaceans have elicited the attention of researchers in recent decades due to their importance to the ecosystem and their economic values. They use sound for communication, echolocation and other social activities. Their sounds are highly non-stationary, transitory and range from short to long sounds. Passive acoustic monitoring (PAM) is a popular method used for monitoring cetaceans in their ecosystems. The volumes of data accumulated using PAM are usually big, so they are difficult to analyze using manual inspection. Therefore different techniques with mixed outcomes have been developed for the automatic detection and classification of signals of different cetacean species. So far, no single technique developed is perfect to detect and classify the vocalizations of over 82 known species due to variability in time-frequency, difference in the amplitude among species and within species' vocal repertoire, physical environment, among others. The accuracy of any detector or classifier depends on the technique adopted as well as the nature of the signal to be analyzed. In this article, we review the existing techniques for the automatic detection and classification of cetacean vocalizations. We categorize the surveyed techniques, while emphasizing the advantages and disadvantages of these techniques. The article suggests possible research directions that can improve existing detection and classification techniques. In addition, the article recommends other suitable techniques that can be used to analyze non-linear and non-stationary signals such as the cetaceans' signals. Several research have been dedicated to this topic, however, there is no review of these past results that gives a quick overview in the area of cetacean detection and classification. This review will help researchers and practitioners in the field to make insightful decisions based on their requirements.

News Recommendation Systems - Accomplishments, Challenges & Future Directions

News publishers have decreased disseminating news through conventional newspapers and have migrated to the use of digital means like websites and purpose-built mobile applications. It is observed that news recommendation systems can automatically process lengthy articles and identify similar articles for readers considering predefined criteria. The objectives of the current work are to identify and classify the challenges in news recommendation domain, to identify state-of-the-art approaches and classify on the application domain, to identify datasets used for evaluation and their sources, the evaluation approaches used and to highlight the challenges explicitly addressed. The literature is thoroughly studied over the time span of 2001-2019 and shortlisted 81 related studies, broadly classified into six categories and discussed. The analysis showed that 60% of news recommendation system adopted a hybrid approach, 66% studies little talk about datasets, and addresses a few challenges from a long list of challenges in the news domain. This article is the first in the field to draw a comprehensive big picture of news recommendation and explore different dimensions covered in the studies. The last section presents the future research opportunities that lead to improving the recommendation of news articles in the news domain.

Anti-crisis function: the innovative development and competitiveness

The article focuses on the innovative development of the economy through ensuring expenses to Research and Development at the level of established international standards. In its turn, the innovative development justifies the strengthening of the competitiveness of the national economy. In the article, such data as The Innovation Development Index, Research and Development Index, as well as The International Competitiveness Index provided by specialized international financial institutions and organizations are used. Based on these data, some indicators for the period 2010-2018 were analyzed. In addition, the article describes the ways of preventing economic crises through innovative development of the economy and justifies lower costs for realizing anti-crisis programs associated with innovative development. In particular, the funds spent by some countries under the anti-crisis programs of the global-financial crisis of 2008 were analyzed. These funds were compared with the funds spent on innovative development of the economy in these countries. As a result, it was determined that the anti-crisis programs cost several times more than innovative development cost. Also, it shows the relationship between the indices of global innovation development, global Research and Development expenditures and global competitiveness. The analysis of the top ten countries in these three indices is given. As a result of this analysis, the strengths and weaknesses of the countries with the highest results on all three indices were systematically studied. At the end of the article, scientific conclusions and practical recommendations are given, based on the analysis of the factors that played a key role in the success of the countries ranking in the top in the three indices, and the aspects that are not yet fully used.

Time, Place, and Manner Restrictions on Speech

The category of time, place, and manner restrictions on speech, as supposedly distinct from absolute bans, appears to be central to free speech law. Even a modest examination of the case law, however, suggests the arbitrariness of any such distinction. Any familiar time, place, or manner restriction on speech can be reasonably re-described as an absolute ban on speech, and vice versa. Any differences in how the relevant regulations of speech should be judicially tested, whether by differing degrees of rigor or otherwise, are correspondingly arbitrary. This Article recommends abandoning any attempt to substantively distinguish between time, place, and manner restrictions and absolute prohibitions of speech. The three currently used judicial tests for presumed content-neutral restrictions on the supposed time, place, and manner of speech should be substantially revised and consolidated. Any replacement test should then de-emphasize concerns for any degree of narrowness of tailoring, focusing instead on whether the regulated speakers are now meaningfully worse off, in terms of their own free speech values, given whatever channels of communication remain available to them after the speech regulation in question has been imposed.