Action observation combined with conventional training improves the rugby lineout throwing performance: A pilot study

Combining action observation (AO) and physical practice contributes to motor skill learning, and a number of studies pointed out the beneficial role of AO training in improving the motor performance and the athletes' movement kinematics. The aim of this study was to investigate if AO combined with immediate conventional training was able to improve motor performance and kinematic parameters of a complex motor skill such as the lineout throw, a gesture that represents a key aspect of rugby, that is unique to this sport. Twenty elite rugby players were divided into 2 groups. The AO group watched a 5-min video-clip of an expert model performing the lineout throw towards a target at 7 m distance and, immediately after the AO, this group executed the conventional training, consisting of 6 repetitions x 5 blocks of throws. The CONTROL group performed only the conventional lineout training. Intervention period lasted 4 weeks, 3 sessions/week. The AO group showed significant improvements in throwing accuracy (i.e. number of throws hitting the target), whilst no significant changes were observed in the CONTROL group. As concerns kinematic parameters, hooker's arm mean velocity significantly increased in both groups, but the increase was higher in AO group compared to CONTROL group. Ball velocity significantly increased only in the AO group, whereas ball angle release and ball spinning significantly decreased in both groups, with no differences between groups. Finally, no significant changes in knee and elbow angles were observed. Our results showed that the combination of AO and conventional training was more effective than a conventional training alone in improving the performance of elite rugby players, in executing a complex motor skill, such as the lineout. This combined training led to significant improvements in throwing accuracy and in hooker's and ball's kinematic parameters. Since AO can be easily implemented in combination with conventional training, the results of this study can encourage coaches in designing specific lineout training programs, which include AO cognitive training

Data collection and advanced statistical analysis in phytotoxic activity of aerial parts exudates of Salvia spp

In order to define the phytotoxic potential of Salvia species a database was developed for fast and efficient data collection in screening studies of the inhibitory activity of Salvia exudates on the germination of Papaver rhoeas L. and Avena sativa L.. The structure of the database is associated with the use of algorithms for calculating the usual germination indices reported in the literature, plus the newly defined indices (Weighted Average Damage, Differential Weighted Average Damage, Germination Weighted Average Velocity) and other variables usually recorded in experiments of phytotoxicity (LC50, LC90). Furthermore, other algorithms were designed to calculate the one-way ANOVA followed by Duncan's multiple range test to highlight automatically significant differences between the species. The database model was designed in order to be suitable also for the development of further analysis based on the artificial neural network approach, using Self-Organising Maps (SOM)

Phytotoxic activity of Salvia x jamensis.

A study has been carried out on the surface exudate of Salvia x jamensis, which showed a significant phytotoxic activity against Papaver rhoeas L. and Avena sativa L.. Bioguided separation of the exudate yielded active fractions from which 3β-hydroxy-isopimaric acid (1), hautriwaic acid (2), betulinic acid (3), 7,8β-dihydrosalviacoccin (4), isopimaric acid (5), 14α-hydroxy-isopimaric acid (7), 15,16-epoxy-7α,10β-dihydroxy-clerod-3,13(16),14-trien-17,12;18,19-diolide (8), cirsiliol (5,3′,4′-trihydroxy-6,7-dimethoxyflavone, 9) and two new neoclerodane diterpenes (6 and 10) were isolated. The structures of 6 and 10 were identified as 15,16-epoxy-10β-hydroxy-clerod-3,13(16),14-trien-17,12;18,19-diolide and 15,16-epoxy-7α,10-dihydroxy-clerod-2,13(16),14-trien-17,12;18,19-diolide respectively on the basis of spectroscopic data analysis. All compounds, but 7, 8 and 10, were active in inhibiting the germination of the tested species

NUP98-fusion transcripts characterize different biological entities within acute myeloid leukemia: A report from the AIEOP-AML group.

In the last years, collaborative studies have joined to link the degree of genetic heterogeneity of acute myeloid leukemia (AML) to clinical outcome,1, 2 allowing risk stratification before therapy and guiding post-induction treatment of children with AML. So far, still half of these patients, whose disease is usually characterized by a grim prognosis, lack a known biomarker offering opportunities of targeted treatment

Embodied language learning and cognitive bootstrapping: methods and design principles

Co-development of action, conceptualization and social interaction mutually scaffold and support each other within a virtuous feedback cycle in the development of human language in children. Within this framework, the purpose of this article is to bring together diverse but complementary accounts of research methods that jointly contribute to our understanding of cognitive development and in particular, language acquisition in robots. Thus, we include research pertaining to developmental robotics, cognitive science, psychology, linguistics and neuroscience, as well as practical computer science and engineering. The different studies are not at this stage all connected into a cohesive whole; rather, they are presented to illuminate the need for multiple different approaches that complement each other in the pursuit of understanding cognitive development in robots. Extensive experiments involving the humanoid robot iCub are reported, while human learning relevant to developmental robotics has also contributed useful results. Disparate approaches are brought together via common underlying design principles. Without claiming to model human language acquisition directly, we are nonetheless inspired by analogous development in humans and consequently, our investigations include the parallel co-development of action, conceptualization and social interaction. Though these different approaches need to ultimately be integrated into a coherent, unified body of knowledge, progress is currently also being made by pursuing individual methods

Destruction of chemical warfare surrogates using a portable atmospheric pressure plasma jet

Today’s reality is connected with mitigation of threats from the new chemical and biological warfare agents. A novel investigation of cold plasmas in contact with liquids presented in this paper demonstrated that the chemically reactive environment produced by atmospheric pressure plasma jet (APPJ) is potentially capable of rapid destruction of chemical warfare agents in a broad spectrum. The decontamination of three different chemical warfare agent surrogates dissolved in liquid is investigated by using an easily transportable APPJ. The jet is powered by a kHz signal source connected to a low-voltage DC source and with He as working gas. The detailed investigation of electrical properties is performed for various plasmas at different distances from the sample. The measurements of plasma properties in situ are supported by the optical spectrometry measurements, whereas the high performance liquid chromatography measurements before and after the treatment of aqueous solutions of Malathion, Fenitrothion and Dimethyl Methylphosphonate. These solutions are used to evaluate destruction and its efficiency for specific neural agent simulants. The particular removal rates are found to be from 56% up to 96% during 10 min treatment. The data obtained provide basis to evaluate APPJ’s efficiency at different operating conditions. The presented results are promising and could be improved with different operating conditions and optimization of the decontamination process

Glycosaminoglycans: What Remains To Be Deciphered?

Glycosaminoglycans (GAGs) are complex polysaccharides exhibiting a vast structural diversity and fulfilling various functions mediated by thousands of interactions in the extracellular matrix, at the cell surface, and within the cells where they have been detected in the nucleus. It is known that the chemical groups attached to GAGs and GAG conformations comprise “glycocodes” that are not yet fully deciphered. The molecular context also matters for GAG structures and functions, and the influence of the structure and functions of the proteoglycan core proteins on sulfated GAGs and vice versa warrants further investigation. The lack of dedicated bioinformatic tools for mining GAG data sets contributes to a partial characterization of the structural and functional landscape and interactions of GAGs. These pending issues will benefit from the development of new approaches reviewed here, namely (i) the synthesis of GAG oligosaccharides to build large and diverse GAG libraries, (ii) GAG analysis and sequencing by mass spectrometry (e.g., ion mobility-mass spectrometry), gas-phase infrared spectroscopy, recognition tunnelling nanopores, and molecular modeling to identify bioactive GAG sequences, biophysical methods to investigate binding interfaces, and to expand our knowledge and understanding of glycocodes governing GAG molecular recognition, and (iii) artificial intelligence for in-depth investigation of GAGomic data sets and their integration with proteomics