The Yin and Yang of epigenetics in the field of nanoparticles

Nanoparticles (NPs) have become a very exciting research avenue, with multitudinous applications in various fields, including the biomedical one, whereby they have been gaining considerable interest as drug carriers able...

HOTSPOT: An Ad Hoc Teamwork Platform for Mixed Human-Robot Teams

Ad hoc teamwork is a research topic in multi-agent systems whereby an agent (the "ad hoc agent") must successfully collaborate with a set of unknown agents (the "teammates") without any prior coordination or communication protocol. However, research in ad hoc teamwork is predominantly focused on agent-only teams, but not in agent-human teams, which we believe is an exciting research avenue and has enormous application potential in human-robot teams. This paper will tap into this potential by proposing HOTSPOT, the first framework for ad hoc teamwork in human-robot teams. Our framework comprises two main modules, addressing the two key challenges in the interaction between a robot acting as the ad hoc agent and human teammates. First, a <i>decision-theoretic module</i> that is responsible for all task-related decision making (task identification, teammate identification, and planning). Second, a <i>communication module</i> that uses natural language processing in order to parse all communication between the robot and the human. To evaluate our framework, we use a task where a mobile robot and a human cooperatively collect objects in an open space, illustrating the main features of our framework in a real-world task.

HOTSPOT: An Ad Hoc Teamwork Platform for Mixed Human-Robot Teams

Ad hoc teamwork is a research topic in multi-agent systems whereby an agent (the "ad hoc agent") must successfully collaborate with a set of unknown agents (the "teammates") without any prior coordination or communication protocol. However, research in ad hoc teamwork is predominantly focused on agent-only teams, but not in agent-human teams, which we believe is an exciting research avenue and has enormous application potential in human-robot teams. This paper will tap into this potential by proposing HOTSPOT, the first framework for ad hoc teamwork in human-robot teams. Our framework comprises two main modules, addressing the two key challenges in the interaction between a robot acting as the ad hoc agent and human teammates. First, a <i>decision-theoretic module</i> that is responsible for all task-related decision making (task identification, teammate identification, and planning). Second, a <i>communication module</i> that uses natural language processing in order to parse all communication between the robot and the human. To evaluate our framework, we use a task where a mobile robot and a human cooperatively collect objects in an open space, illustrating the main features of our framework in a real-world task.

Is agricultural revitalization possible through the climate-smart agriculture: a systematic review and citation-based analysis

PurposeThis paper seeks to identify the prevailing streams in the research of climate-smart agriculture in order to help to conceptualize this new scientific notion and assist in drawing clear borders between climate-smart agriculture, agricultural sustainability and resilience.Design/methodology/approachIn order to conceptualize the climate-smart agriculture (CSA), the current research provides an in-depth bibliometric analysis indicating the prospective research directions in CSA. The findings of this paper are important in guiding the research on creation of climate-smart agriculture across different regions.FindingsThe notion of the CSA covers three main objectives: increased productivity, enhanced resilience and reduced environmental footprint of agriculture. It is found that due to its novelty, the climate-smart notion does not always have its defined research agenda and is considered to be both a constituent part of some other scientific framework (e.g. sustainability) and an independent research avenue.Originality/valueThis paper presents an in-depth analysis of the literature on the CSA. The linkages among the concepts, research centers and research strands are identified via the citation-based analysis.

Versus Arthritis Musculoskeletal Disorders Research Advisory Group Priority Setting Exercise Protocol

Involving research users in setting priorities for musculoskeletal research is essential to raise awareness of the unmet needs for MSK research, to ensure research outcomes are patient-centred and relevant, have a high likelihood of resulting in patient benefit, reduce research waste and increase research value and impact. In 2018, Versus Arthritis convened an MSK Disorders Research Advisory Group (RAG) which included people with arthritis, health care professionals and researchers in MSK, in order to identify and prioritise research areas with a long-term aim of improving quality and impact of MSK research. On further review, there were few previous prioritisation approaches in this area looking across discovery science to more clinical research, at important research questions which might be common to a range of disorders or approaches incorporating input at all stages of the process by a range of stakeholders including people with arthritis. The group identified that more work to define research priorities in these areas was justified and designed a research priority setting process for MSK disorders. This manuscript documents the methodology that was developed by the group for this process.MethodsFollowing a review, the Child Health and Nutrition Research Initiative (CHNRI) method for research prioritisation was selected as best aligning with the needs of this process. The group agreed on adaptations to the CHNRI approach, context, purpose and remit of the exercise and identified through consensus four priority research Domains: Mechanisms of disease; Diagnosis (including early diagnosis) and measuring the impact of these disorders; Living well with MSK disorders and Successful Translation. From all published CHNRI scoring criteria for generated research avenues or themes of research, the group identified six which were most relevant to this process. To ensure accessibility of the survey and scoring, these were refined to three: Equity (considered cross cutting, not scored but considered throughout the process), Importance (Will research in this area have potential to lead to important new knowledge) and Impact (Might research in this area make a difference). Importance and Impact were to be scored on a scale of 1-10 for each research avenue with equal weighting of these two criteria in the subsequent generation of a total score.Data collectionFollowing ethical approval, an electronic first survey asking for important research uncertainties in the four research domains and any other areas will be distributed to all stakeholders (people with arthritis, researchers in all stages of MSK disorders research, healthcare professionals, industry e.g. pharmaceutical and medical technology companies, research funders, healthcare providers, government policy makers and charities). The next step is to consolidate all the gathered research uncertainties from the first survey into finalised research domains and avenues. Uncertainties will be summarised using deductive thematic analysis and organised into possible themes which will then be considered and refined by each of four appointed subgroups within the RAG. Following group and lay review and refinement of the wording including tests of readability, the second survey including this full list of research avenues will be submitted for ethical approval. The second survey will be completed by the same range of stakeholders as the first survey, both those who previously completed and new respondents. Respondents will be invited to rate each research avenue using the two scoring criteria, with the avenues presented in a random sequence to avoid bias.Analysis PlanAll available data will be analysed, from all respondents completing the survey in full and all partial respondents. For each research avenue, a mean criterion score will be calculated for each of the two criteria from all available survey responses (considering the number of respondents in each case), and then the two mean criterion scores will be summed to create a total score. Response rates and missing data for scoring of avenues will be reported. The primary prioritisation output of this exercise will be to produce a single ranked list of these total scores of research avenues, from highest to lowest. The most highly ranked avenues will be highlighted, for example the top five to top ten overall and from each research domain, with the exact number and nature of this depending on the distribution of the data. Respondent characteristics will be summarised including self-identified stakeholder group, age group, gender and ethnic background, to describe the diversity and representation within the survey respondents as far as possible.Dissemination planFindings will be communicated in a number of formats, both written and spoken, to ensure accessibility to all stakeholders, and will also be used by the charity in internal strategy development. Dissemination will include the submission of a manuscript to a peer-reviewed journal.

Unsupervised discovery of thin-film photovoltaic materials from unlabeled data

Quaternary chalcogenide semiconductors (I2-II-IV-X4) are key materials for thin-film photovoltaics (PVs) to alleviate the energy crisis. Scaling up of PVs requires the discovery of I2-II-IV-X4 with good photoelectric properties; however, the structure search space is significantly large to explore exhaustively. The scarcity of available data impedes even many machine learning (ML) methods. Here, we employ the unsupervised learning (UL) method to discover I2-II-IV-X4 that alleviates the challenge of data scarcity. We screen all the I2-II-IV-X4 from the periodic table as the initial data and finally select eight candidates through UL. As predicted by ab initio calculations, they exhibit good optical conversion efficiency, strong optical responses, and good thermal stabilities at room temperatures. This typical case demonstrates the potential of UL in material discovery, which overcomes the limitation of data scarcity, and shortens the computational screening cycle of I2-II-IV-X4 by ~12.1 years, providing a research avenue for rapid material discovery.

Links between Regulatory Systems of ROS and Carbohydrates in Reproductive Development

To thrive on the earth, highly sophisticated systems to finely control reproductive development have been evolved in plants. In addition, deciphering the mechanisms underlying the reproductive development has been considered as a main research avenue because it leads to the improvement of the crop yields to fulfill the huge demand of foods for the growing world population. Numerous studies revealed the significance of ROS regulatory systems and carbohydrate transports and metabolisms in the regulation of various processes of reproductive development. However, it is poorly understood how these mechanisms function together in reproductive tissues. In this review, we discuss mode of coordination and integration between ROS regulatory systems and carbohydrate transports and metabolisms underlying reproductive development based on the hitherto findings. We then propose three mechanisms as key players that integrate ROS and carbohydrate regulatory systems. These include ROS-dependent programmed cell death (PCD), mitochondrial and respiratory metabolisms as sources of ROS and energy, and functions of arabinogalactan proteins (AGPs). It is likely that these key mechanisms govern the various signals involved in the sequential events required for proper seed production.

PSL Eye: Predicting the Winning Team in Pakistan Super League (PSL) Matches

Pakistan Super League (PSL) is a well-known T20 cricket league with millions of viewers. With this large viewer base, predicting the outcome of PSL matches opens a new research avenue for academic researchers. In this paper, we collect PSL data from relevant sources and generate a validated data set for machine learning experiments. We implement the “PSL Eye” solution which employs Neural Networks (NNs) to predict the match winning team. We preprocess the dataset to eliminate the extra variables then we tune the hyper parameters of NN. After acquiring the optimal values of hyper parameters, we run our NN based PSL Eye to obtain the final results. The overall accuracy of PSL-Eye with testing data set is 82% which is very promising and shows the importance of NN in predicting PSL match outcome.

A Study of Human Attitude, Persuasion And Ethics Towards The Adoptation Of Sustainable Technology Among Malaysian SMEs

This research investigates the impact of human attitudes, human persuasion and human ethics towards the adoption of sustainable technology among the small and medium-sized enterprises (SMEs) in Malaysia. There is a lacuna in the literature of the focusing on the human factors (attitudes, persuasions and ethical belief) of adoption of sustainable technology in the SMEs context in emerging economy such as Malaysia. The study develops a comprehensive model of sustainable technology adoption considering the strengths and limitations of the existing models. The main theories utilized this paper include the theory of reasoned action (TRA), theory of planned behavior (TPB), attribution theory (AT), environmental attitudes model and the triple bottom line model. The theoretical framework developed for this study is based on the premise of the above theories. A total of 234 sample taken from 2369 SMEs in Malaysia. The major finding of this research suggest that affective attitudes, cognitive attitudes, reasoned persuasion, sentimental persuasion, anthropocentrism and altruism significantly impact adoption mechanism of sustainable technology in a Malaysian setting. These findings are later highlighted in this paper. The implications, limitations and future research avenue are highlighted in the paper.

Traditional uses of Ethno-medicinal Plants in Chittagong Hill Tracts (CHTs), Bangladesh: A Review

Objective: Traditional medicines are of great importance to villagers and also now a day to modern drugs. Scientists are trying to explore new drug resources along with the modern drugs to support drug treatment strategy to be more effective and merely natural. Nature is the rich source of many essential bioactive compounds with more specificity and less side effects and thus, traditional medicines are got attention to the pharmacists. There are lots of medicinal plants with scientific evidences in Chittagong Hill Tracts (CHTs) region, but all that information have not yet been compiled as a review. Keeping this in mind, a review attempt has been taken by focusing on traditional medicine used mostly by the indigenous population of Chittagong Hill Tracts region, which is also a rich source of biodiversity of Bangladesh. Methods: Research articles based on various traditional medicines focusing CHTs region were taken in consideration to compile the data sources in this review article. Results and Conclusion: Peoples in CHTs are using various types of medicinal plants obtained from their surroundings and have been using from long since with traditional reputation. In this review, we focused on such medicinal plants along with their scientific evidences, which would attract lots of scientists to work more to unveil a new research avenue in drug development.