Seismic productivity of blasts: A case-study of the Khibiny Massif

2020 ◽  
pp. 14-18
Author(s):  
S. V. Baranov ◽  
◽  
S. A. Zhukova ◽  
P. A. Korchak ◽  
P. N. Shebalin ◽  
...  

The authors study the property of production-scale blasts to induce seismic events classified as micro shocks, rock bursts and earthquakes caused by sudden slips along faults. The study area is the production performance zone of Apatit’s Kirovsk Branch. It is situated in the southeast of the Khibiny Massif on the Kola Peninsula and is subjected to continuous autonomous seismicity monitoring. The subject of the research is the production blasts and seismic events recorded by the seismic monitoring station of Apatit’s Kirovsk Branch between January 1996 and June 2019. Blasting-induced seismic events were identified using the nearest neighbor method and the seismicity-dependent proximity function of the space–time–magnitude (energy), calculated with respect to the blasts. The threshold of the proximity function to assume a seismic event as the blast-induced event was selected using the model-independent method of seismic catalog randomization. It is shown that the number of blasting-induced seismic events—blasting productivity—obeys an exponential distribution irrespective of magnitudes or occurrence depths of the studied events. The obtained result conforms with the earlier determined productivity law for natural earthquakes on a global and regional scale, as well as for mining-induced seismicity in the Khibiny Massif. Accordingly, the productivity distribution is governed by the properties of a medium and is independent of the source mechanism of a triggering event (explosion, seismicity). The paper presents the research findings supported by the Russian Foundation for Basic Research, Project No. 19-05-00812, and in the framework of State Contract No. 007-00186-18-00 with the Kola Branch of the Geophysical Service of the Russian Academy of Sciences.

2019 ◽  
Author(s):  
Alice Winsor ◽  
Heather D Flowe ◽  
Travis Morgan Seale-Carlisle ◽  
Isabella Killeen ◽  
Danielle Hett ◽  
...  

Children are frequently witnesses of crime. In the witness literature and legal systems, children are often deemed to have unreliable memories. Yet, in the basic developmental literature, young children can monitor their memory. To address these contradictory conclusions, we reanalysed the confidence-accuracy relationship in basic and applied research. Confidence provided considerable information about memory accuracy, from at least age 8, but possibly younger. We also conducted an experiment where children in young- (4–6 years), middle- (7–9 years), and late- (10–17 years) childhood (N=2,205) watched a person in a video, and then identified that person from a police lineup. Children provided a confidence rating (an explicit judgement), and used an interactive lineup—in which the lineup faces can be rotated—and we analyzed children’s viewing behavior (an implicit measure of metacognition). A strong confidence-accuracy relationship was observed from age 10, and an emerging relationship from age 7. A constant likelihood ratio signal-detection model can be used to understand these findings. Moreover, in all ages, interactive viewing behavior differed in children who made correct versus incorrect suspect identifications. Our research reconciles the apparent divide between applied and basic research findings and suggests that the fundamental architecture of metacognition that has previously been evidenced in basic list-learning paradigms also underlies performance on complex applied tasks. Contrary to what is believed by legal practitioners, but similar to what has been found in the basic literature, identifications made by children can be reliable when appropriate metacognitive measures are used to estimate accuracy.


2020 ◽  
Vol 21 (22) ◽  
pp. 8870 ◽  
Author(s):  
Jakub Mlost ◽  
Marta Bryk ◽  
Katarzyna Starowicz

Cannabis has a long history of medical use. Although there are many cannabinoids present in cannabis, Δ9tetrahydrocannabinol (Δ9-THC) and cannabidiol (CBD) are the two components found in the highest concentrations. CBD itself does not produce typical behavioral cannabimimetic effects and was thought not to be responsible for psychotropic effects of cannabis. Numerous anecdotal findings testify to the therapeutic effects of CBD, which in some cases were further supported by research findings. However, data regarding CBD’s mechanism of action and therapeutic potential are abundant and omnifarious. Therefore, we review the basic research regarding molecular mechanism of CBD’s action with particular focus on its analgesic potential. Moreover, this article describes the detailed analgesic and anti-inflammatory effects of CBD in various models, including neuropathic pain, inflammatory pain, osteoarthritis and others. The dose and route of the administration-dependent effect of CBD, on the reduction in pain, hyperalgesia or allodynia, as well as the production of pro and anti-inflammatory cytokines, were described depending on the disease model. The clinical applications of CBD-containing drugs are also mentioned. The data presented herein unravel what is known about CBD’s pharmacodynamics and analgesic effects to provide the reader with current state-of-art knowledge regarding CBD’s action and future perspectives for research.


2020 ◽  
Vol 23 (3) ◽  
pp. 178-180
Author(s):  
Gianluca Serafini ◽  
Alice Trabucco ◽  
Andrea Amerio ◽  
Andrea Aguglia ◽  
Mario Amore

Abstract The study of Roy and colleagues recently accepted for publication in International Journal of Neuropsychopharmacology is a very interesting report investigating the role of specific microRNAs (miRNAs) in vulnerability or resistance to major depressive disorder in a specific brain region (e.g., amygdala). MiRNAs may act as a mega-controller of gene expression being involved in the pathogenesis of major neuropsychiatric conditions. Interestingly, some of the altered miRNAs (e.g., hsa-miR-425-3p, miR-425, miR-674-3p, and miR-873-3p) identified in this study were found to be dysregulated even in existing studies, but several methodological issues may hamper the translation of basic research findings in clinical studies. MiRNAs are proposed as possible biomarkers of disease and treatment response to disentangle the biological complexity underlying major affective disorders. The main implications regarding the present findings are discussed.


2017 ◽  
Vol 38 (4) ◽  
pp. 564-575 ◽  
Author(s):  
Michael J.R. Butler

Purpose The purpose of this paper is to highlight the potential implications and non-implications for leadership and organization development of a recent systematic review of empirical developments in organizational cognitive neuroscience (OCN). Design/methodology/approach Butler et al.’s (2016) systematic review of 40 empirical articles related to OCN is re-interpreted in terms of its potential to reveal (non-) implications for practice. OCN is critically discussed, then related to the research findings from studies with two methodological designs. Findings At this stage of OCN’s emergence, it appears that neuroimaging and physiology-based research methods have equal potential in their implications for practice, though hormonal data poses ethical public interest dilemmas. Both methods cannot be reduced to specific forms of application to practice, but they set an aspirational direction for the future development of leadership and organizations. Practical implications There appear to be two paces of translational activity – practitioners are moving more quickly than academics in applying OCN to practice. It is suggested that a meeting of minds may be needed to ensure that any risks associated with applying OCN to practice are minimized or eliminated. Social implications Inter-disciplinary research, like OCN, requires a social consensus about how basic research in cognitive neuroscience can be applied to organizations. A think tank will provide opportunities for deeper engagement and co-production between academics and practitioners. Originality/value Critically exploring the potential implications of OCN for practice, by basing the discussion on a systematic review of empirical developments.


2019 ◽  
Vol 116 (52) ◽  
pp. 26280-26287 ◽  
Author(s):  
Serge Picaud ◽  
Deniz Dalkara ◽  
Katia Marazova ◽  
Olivier Goureau ◽  
Botond Roska ◽  
...  

Retinal degenerative diseases caused by photoreceptor cell death are major causes of irreversible vision loss. As only primates have a macula, the nonhuman primate (NHP) models have a crucial role not only in revealing biological mechanisms underlying high-acuity vision but also in the development of therapies. Successful translation of basic research findings into clinical trials and, moreover, approval of the first therapies for blinding inherited and age-related retinal dystrophies has been reported in recent years. This article explores the value of the NHP models in understanding human vision and reviews their contribution to the development of innovative therapeutic strategies to save and restore vision.


2017 ◽  
Vol 18 (4) ◽  
pp. 469-489 ◽  
Author(s):  
Melissa A Currie ◽  
Janni Sorensen

Case studies are an effective vehicle for telling important stories that may have broader implications, but how is the research study made relevant, or generalizable, to other places or events? This paper discusses the upscaling of Action Research where Action Research was the starting point at the local level that led to additional layers with larger, regional scale implications. The story behind the development process and resulting built form of Windy Ridge, a relatively new subdivision in Charlotte, North Carolina dubbed a “Neighborhood Built to Fail,” presents a compelling story. We trace the development of knowledge around three topics originating in Action Research and how we scaled those topics up to have policy implications: (1) owner occupancy and absentee landlords; (2) stability, instability, and neighborhood resiliency; and (3) zoning changes and environmental justice issues. We reflect on implications for practitioners and academics based on several years of neighborhood partnership and how Action Research can reveal structural issues at work within communities. Action Research findings provided a research- and evidence-based platform from which to advocate for neighborhood change and the motivation for the extended research. This approach produced an expanding research model emanating from Action Research data and questions originating with residents.


2019 ◽  
Vol 107 (1) ◽  
pp. 25-40 ◽  
Author(s):  
Zbigniew Szczerbowski

AbstractSeismic events in the area of Poland are related mostly to copper and coal mining, and they are regarded as the most dangerous natural hazard. Although development of geomechanical modelling as the development of geophysical methods determining seismic hazard are evident, low predictability of the time-effect relationship still remains. Geomechanical models as geophysical data analysis highlight the interaction between parts of rock mass or allow to reconstruct the way of rock mass destruction and to understand the processes that take place in the high-energy tremors.However, the association of larger mining tremors with pre-existing geological features has been reported by many investigators; in geomechanical practice, investigations of rock mass condition concentrate on this problem in the local scale. Therefore, the problem of relations between high-energy seismic events in Legnica–Głogów Copper District (LGCD) and regional scale deformations of terrain surface resulting from possible tectonic activity is discussed in this paper. The GNSS data evaluated from the observations of ASG-EUPOS (Active Geodetic Network – EUPOS) stations in the area of LGCD and in the adjacent areas is analysed in this study. Temporal variation of distances between the stations and evaluated on that base so called apparent strain was combined with the occurrence of high-energy tremors. Consequently, after the examination and analysis of occurrences of mining tremors, it is found that high-energy seismic events and periods of strain accumulation evaluated from GPS/GNSS data have temporal relations. Although the seismic events were triggered by mining, nearly all the events with energy E > 108 J occurred in the periods when the analysed stations’ positions demonstrated a decrease in the baseline length.


2021 ◽  
Vol 56 (6) ◽  
pp. 337-340
Author(s):  
Giovanni Dosi

AbstractThis article discusses the medical/therapeutical responses to the COVID-19 pandemic and their political economy context. First, the very quick development of several vaccines highlights the richness of the basic knowledge waiting for therapeutical exploitation. Such knowledge has largely originated in public or non-profit institutions. Second, symmetrically, there is longer-term evidence that the private sector (essentially big pharma) has decreased its investment in basic research in general and has long been uninterested in vaccines in particular. Only when flooded with an enormous amount of public money did it become eager to undertake applied research, production scale-up and testing. Third, the political economy of the underlying public-private relationship reveals a profound dysfunctionality with the public being unable to determine the rates and direction of innovation, but at the same time confined to the role of payer of first and last resort, with dire consequences for both advanced, and more so developing countries. Fourth, on normative grounds, measures like ad hoc patent waivers are certainly welcome, but this will not address the fundamental challenge, involving a deep reform of the intellectual property rights regimes and their international protection.


2021 ◽  
Author(s):  
Hideyuki Shimizu ◽  
Manabu Kodama ◽  
Masaki Matsumoto ◽  
Yasuko Orba ◽  
Michihito Sasaki ◽  
...  

SUMMARYAlthough numerous promising therapeutic targets for human diseases have been discovered, most have not been successfully translated into clinical practice1. A bottleneck in the application of basic research findings to patients is the enormous cost, time, and effort required for high-throughput screening of potential drugs2 for given therapeutic targets. Recent advances in 3D docking simulations have not solved this problem, given that 3D protein structures with sufficient resolution are not always available and that they are computationally expensive to obtain. Here we have developed LIGHTHOUSE, a graph-based deep learning approach for discovery of the hidden principles underlying the association of small-molecule compounds with target proteins, and we present its validation by identifying potential therapeutic compounds for various human diseases. Without any 3D structural information for proteins or chemicals, LIGHTHOUSE estimates protein-compound scores that incorporate known evolutionary relations and available experimental data. It identified novel therapeutics for cancer, lifestyle-related disease, and bacterial infection. Moreover, LIGHTHOUSE predicted ethoxzolamide as a therapeutic for coronavirus disease 2019 (COVID-19), and this agent was indeed effective against alpha, beta, gamma, and delta variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that are rampant worldwide. Given that ethoxzolamide is already approved for several diseases, it could be rapidly deployed for the treatment of patients with COVID-19. We envision that LIGHTHOUSE will bring about a paradigm shift in translational medicine, providing a bridge from bench side to bedside.


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