Small-scale drivers on plant and ant diversity in a grassland habitat through a multifaceted approach

Semi-natural grasslands are characterized by high biodiversity and require multifaceted approaches to monitor their biodiversity. Moreover, grasslands comprise a multitude of microhabitats, making the scale of investigation of fundamental importance. Despite their wide distribution, grasslands are highly threatened and are considered of high conservation priority by Directive no. 92/43/EEC. Here, we investigate the effects of small-scale ecological differences between two ecosites present within the EU habitat of Community Interest of semi-natural dry grasslands on calcareous substrates (6210 according to Dir. 92/43/EEC) occurring on a Mediterranean mountain. We measured taxonomic and functional diversity of plant and ant communities, evaluating the differences among the two ecosites, how these differences are influenced by the environment and whether vegetation affects composition of the ant community. Our results show that taxonomic and functional diversity of plant and ant communities are influenced by the environment. While vegetation has no effect on ant communities, we found plant and ant community composition differed across the two ecosites, filtering ant and plant species according to their functional traits, even at a small spatial scale. Our findings imply that small-scale monitoring is needed to effectively conserve priority habitats, especially for those that comprise multiple microhabitats.

The Implementation of the Precautionary Principle in Nuclear Safety Regulation: Challenges and Prospects

The precautionary principle has been implemented in many fields including environment protection, biological diversity, and climate change. In the field of international nuclear safety regulation, the implementation of this principle is in an ongoing process. Since Japan declared to discharge Fukushima nuclear waste water into the ocean, the precautionary principle was put on the stage, and some debates are invoked on it. As is observed by this article, the precautionary principle has not been effectively implemented in nuclear safety regulation, specifically in nuclear safety law making, law enforcement, and judicial application. The reasons can be found from two main challenges: indeterminacy of perceived risk level required to justify precautionary action and hard balance of national interest and community interest in nuclear safety. In a long-term perspective, the framework of international nuclear safety regulation has to respond to these challenges, both by clarifying the precautionary principle in legal binding nuclear safety documents and moving towards a more transparent, fair, and effective enforcement regime in order to promote safer, more sustainable, and efficient civilian nuclear utilization around the world.

Hybrid Approach to Corporate Sustainability Performance in Indonesia’s Cement Industry

This study aimed to create a solid framework for decision-making in Indonesia’s cement industry, emphasizing those factors which bring about the most impactful results. The framework was developed using the fuzzy Delphi method, the fuzzy decision-making trial and evaluation laboratory, and a fuzzy Kano model. This study builds a hierarchical structure to approach the impact of corporate sustainability performance. We classify important factors into causes or effects and further identify those factors which are critical to improving the performance of Indonesia’s cement industry. Although corporate sustainability performance is a crucial topic in today’s business environment, sustainability strategies remain underrated in Indonesia. We confirm the validity of 19 factors within the following dimensions: environmental impact, social sustainability, economic gain, technological feasibility, and institutional compliance. The sub-dimensions of community interest, risk-taking ability, and regulatory compliance were identified as causes of perceived risks and benefits. In contrast, the following factors were identified as critical to improving corporate sustainability performance: renewable energy resources, contributions to charity, the perception of management regarding technology as a differentiator, and firm readiness to collaborate with high-tech companies.

HLAncPred: A method for predicting promiscuous non-classical HLA binding sites

In the last two decades, ample of methods have been developed to predict the classical HLA binders in an antigen. In contrast, limited attempts have been made to develop methods for predicting binders for non-classical HLA; due to the scarcity of sufficient experimental data and lack of community interest. Of Note, non-classical HLA plays a crucial immunomodulatory role and regulates various immune responses. Recent studies revealed that non-classical HLA (HLA-E & HLA-G) based immunotherapies have many advantages over classical HLA based-immunotherapy, particularly against COVID-19. In order to facilitate the scientific community, we have developed an artificial intelligence-based method for predicting binders of non-classical HLA alleles (HLA-G and HLA-E). All the models were trained and tested on experimentally validated data obtained from the recent release of IEDB. The machine learning based-models achieved more than 0.98 AUC for HLA-G alleles on validation or independent dataset. Similarly, our models achieved the highest AUC of 0.96 and 0.88 on the validation dataset for HLA-E*01:01, HLA-E*01:03, respectively. We have summarized the models developed in the past for non-classical HLA binders and compared with the models developed in this study. Moreover, we have also predicted the non-classical HLA binders in the spike protein of different variants of virus causing COVID-19 including omicron (B.1.1.529) to facilitate the community. One of the major challenges in the field of immunotherapy is to identify the promiscuous binders or antigenic regions that can bind to a large number of HLA alleles. In order to predict the promiscuous binders for the non-classical HLA alleles, we developed a web server HLAncPred (https://webs.iiitd.edu.in/raghava/hlancpred), and a standalone package.Key PointsNon-classical HLAs play immunomodulatory roles in the immune system.HLA-E restricted T-cell therapy may reduce COVID-19 associated cytokine storm.In silico models developed for predicting binders for HLA-G and HLA-E.Identification of non-classical HLA binders in strains of coronavirusA webserver for predicting promiscuous binders for non-classical HLA allelesAuthor’s BiographyAnjali Dhall is currently working as Ph.D. in Bioinformatics from Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.Sumeet Patiyal is currently working as Ph.D. in Bioinformatics from Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.Gajendra P. S. Raghava is currently working as Professor and Head of Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.

A Late-time Galaxy-targeted Search for the Radio Counterpart of GW190814

GW190814 was a compact object binary coalescence detected in gravitational waves by Advanced LIGO and Advanced Virgo that garnered exceptional community interest due to its excellent localization and the uncertain nature of the binary’s lighter-mass component (either the heaviest known neutron star, or the lightest known black hole). Despite extensive follow-up observations, no electromagnetic counterpart has been identified. Here, we present new radio observations of 75 galaxies within the localization volume at Δt ≈ 35–266 days post-merger. Our observations cover ∼32% of the total stellar luminosity in the final localization volume and extend to later timescales than previously reported searches, allowing us to place the deepest constraints to date on the existence of a radio afterglow from a highly off-axis relativistic jet launched during the merger (assuming that the merger occurred within the observed area). For a viewing angle of ∼46° (the best-fit binary inclination derived from the gravitational wave signal) and assumed electron and magnetic field energy fractions of ϵ e = 0.1 and ϵ B = 0.01, we can rule out a typical short gamma-ray burst-like Gaussian jet with an opening angle of 15° and isotropic-equivalent kinetic energy 2 × 1051 erg propagating into a constant-density medium n ≳ 0.1 cm−3. These are the first limits resulting from a galaxy-targeted search for a radio counterpart to a gravitational wave event, and we discuss the challenges—and possible advantages—of applying similar search strategies to future events using current and upcoming radio facilities.

Persuading US White evangelicals to vaccinate for COVID-19: Testing message effectiveness in fall 2020 and spring 2021

The development of COVID-19 vaccines was an important breakthrough for ending the pandemic. However, people refusing to get vaccinated diminish the level of community protection afforded to others. In the United States, White evangelicals have proven to be a particularly difficult group to convince to get vaccinated. Here we investigate whether this group can be persuaded to get vaccinated. To do this, we leverage data from two survey experiments, one fielded prior to approval of COVID-19 vaccines (study 1) and one fielded after approval (study 2). In both experiments, respondents were randomly assigned to treatment messages to promote COVID-19 vaccination. In study 1, we find that a message that emphasizes community interest and reciprocity with an invocation of embarrassment for choosing not to vaccinate is the most effective at increasing uptake intentions, while values-consistent messaging appears to be ineffective. In contrast, in study 2 we observe that this message is no longer effective and that most messages produce little change in vaccine intent. This inconsistency may be explained by the characteristics of White evangelicals who remain unvaccinated vis à vis those who got vaccinated. These results demonstrate the importance of retesting messages over time, the apparent limitations of values-targeted messaging, and document the need to consider heterogeneity even within well-defined populations. This work also cautions against drawing broad conclusions from studies carried out at a single point in time during the COVID-19 pandemic.

No Provision Left Behind – Law of the Sea Convention’s Dispute Settlement System and Obligations Erga Omnes

The article argues that the Law of the Sea Convention’s (LOSC) dispute settlement system (DSS) is attuned only to certain types of disputes (bilateral) and does not allow for the effective enforcement of obligations erga omnes reflected in the Convention. Mechanisms established to address enforcement of communitarian norms specifically are scarce in international law and the traditional bilateral structure of adjudicatory dispute settlement circumscribes the ability of states to act as advocates of the international community to which obligations erga omnes are owed. The article identifies the obligations erga omnes reflected in the LOSC and assesses the extent to which its dispute settlement framework is suited to address their breach. It is submitted that some of the community interest obligations of the LOSC are “left behind” by the function of the system itself.

Identification and Classification of the Tea Samples by Using Sensory Mechanism and Arduino UNO

Tea is the most popular hot beverageworldwide. In 2020, the value of the global tea market was almost USD 200 billion, and is estimated to reach up to USD 318 billion by the year 2025. Tea has been included as part ofa regular diet for centuries because of its various health benefits. However, tea is acidic, and over-consumption causes heat problems, disturbance of the sleep cycle, tooth erosion, and low calcium absorption in the body. Strong tea concentration is very harmful and toxic. The safe consumption of tea should be guaranteed. The treatment applied in this research work is on sensory mechanisms and Arduino UNO. The objective of this paper is to find out community interest in a particular tea species and inform them about tea overdose.The acidity is mapped with tea taste in terms of strong, medium, and low flavors. Based on the data analysis, the results differentiatethe acidity level of black tea (pH: 3.89–4.08) as very high, green tea (pH: 4.68–4.70) is in the 2nd position, and the energy drink Herbalife Nutrition (pH: 5.59–5.64) is the least acidic comparatively, with a proportion ratio 1:10 of tea to water. Experimental analysis reveals that in the additives, lemon is most acidic, followed byginger, lemongrass, and Tulasi.