Acute effects of three different stretching protocols on the Wingate test performance

The purpose of this study was to examine the acute effects of different stretching exercises on the performance of the traditional Wingate test (WT). Fifteen male participants performed five WT; one for familiarization (FT), and the remaining four after no stretching (NS), static stretching (SS), dynamic stretching (DS), and proprioceptive neuromuscular facilitation (PNF). Stretches were targeted for the hamstrings, quadriceps, and calf muscles. Peak power (PP), mean power (MP), and the time to reach PP (TP) were calculated. The MP was significantly lower when comparing the DS (7.7 ± 0.9 W/kg) to the PNF (7.3 ± 0.9 W/kg) condition (p \u3c 0.05). For PP, significant differences were observed between more comparisons, with PNF stretching providing the lowest result. A consistent increase of TP was observed after all stretching exercises when compared to NS. The results suggest the type of stretching, or no stretching, should be considered by those who seek higher performance and practice sports that use maximal anaerobic power

Complex Network Tools to Understand the Behavior of Criminality in Urban Areas

Complex networks are nowadays employed in several applications. Modeling urban street networks is one of them, and in particular to analyze criminal aspects of a city. Several research groups have focused on such application, but until now, there is a lack of a well-defined methodology for employing complex networks in a whole crime analysis process, i.e. from data preparation to a deep analysis of criminal communities. Furthermore, the "toolset" available for those works is not complete enough, also lacking techniques to maintain up-to-date, complete crime datasets and proper assessment measures. In this sense, we propose a threefold methodology for employing complex networks in the detection of highly criminal areas within a city. Our methodology comprises three tasks: (i) Mapping of Urban Crimes; (ii) Criminal Community Identification; and (iii) Crime Analysis. Moreover, it provides a proper set of assessment measures for analyzing intrinsic criminality of communities, especially when considering different crime types. We show our methodology by applying it to a real crime dataset from the city of San Francisco - CA, USA. The results confirm its effectiveness to identify and analyze high criminality areas within a city. Hence, our contributions provide a basis for further developments on complex networks applied to crime analysis.Comment: 7 pages, 2 figures, 14th International Conference on Information Technology : New Generation

From Compact Discs to Streaming: A Comparison of Eras within the Brazilian Market

The music industry has undergone many changes in the last few decades, notably since vinyl, cassettes and compact discs faded away as streaming platforms took the world by storm. This Digital evolution has made huge volumes of data about music consumption available. Based on such data, we perform cross-era comparisons between Physical and Digital media within the music market in Brazil. First, we build artists' success time series to detect and characterize hot streak periods, defined as high-impact bursts that occur in sequence, in both eras. Then, we identify groups of artists with distinct success levels by applying a cluster analysis based on hot streaks' features. We find the same clusters for both Physical and Digital eras: Spike Hit Artists, Big Hit Artists, and Top Hit Artists. Our results reveal significant changes in the music industry dynamics over the years by identifying the core of each era

Anticancer and Immunomodulatory Activities of a Novel Water-Soluble Derivative of Ellipticine

Cancer still remains a major public health concern around the world and the search for new potential antitumor molecules is essential for fighting the disease. This study evaluated the anticancer and immunomodulatory potential of the newly synthetized ellipticine derivate: sodium bromo-5,11-dimethyl-6H-pyrido[4,3-b]carbazole-7-sulfonate (Br-Ell-SO3Na). It was prepared by the chlorosulfonation of 9-bromoellipticine. The ellipticine-7-sulfonic acid itself is not soluble, but its saponification with sodium hydroxide afforded a water-soluble sodium salt. The cytotoxicity of Br-Ell-SO3Na was tested against cancerous (K562 cell line) and non-cancerous cells (Vero cell line and human peripheral blood mononuclear cells (PBMC)) using a Methylthiazoletetrazolium (MTT) assay. Cell cycle arrest was assessed by flow cytometry and the immunomodulatory activity was analyzed through an enzyme-linked immunosorbent assay (ELISA). The results showed that the Br-Ell-SO3Na molecule has specific anticancer activity (IC50 = 35 µM) against the K562 cell line, once no cytotoxicity effect was verified against non-cancerous cells. Cell cycle analysis demonstrated that K562 cells treated with Br-Ell-SO3Na were arrested in the phase S. Moreover, the production of IL-6 increased and the expression of IL-8 was inhibited in the human PBMC treated with Br-Ell-SO3Na. The results demonstrated that Br-Ell-SO3Na is a promising anticancer molecule attested by its noteworthy activity against the K562 tumor cell line and immunomodulatory activity in human PBMC cells

Aryl-capped lysine-dehydroamino acid dipeptide supergelators as potential drug release systems

Employing amino acids and peptides as molecular building blocks provides unique opportunities for generating supramolecular hydrogels, owing to their inherent biological origin, bioactivity, biocompatibility, and biodegradability. However, they can suffer from proteolytic degradation. Short peptides (<8 amino acids) attached to an aromatic capping group are particularly attractive alternatives for minimalistic low molecular weight hydrogelators. Peptides with low critical gelation concentrations (CGCs) are especially desirable, as the low weight percentage required for gelation makes them more cost-effective and reduces toxicity. In this work, three dehydrodipeptides were studied for their self-assembly properties. The results showed that all three dehydrodipeptides can form self-standing hydrogels with very low critical gelation concentrations (0.050.20 wt%) using a pH trigger. Hydrogels of all three dehydrodipeptides were characterised by scanning tunnelling emission microscopy (STEM), rheology, fluorescence spectroscopy, and circular dichroism (CD) spectroscopy. Molecular modelling was performed to probe the structural patterns and interactions. The cytotoxicity of the new compounds was tested using human keratinocytes (HaCaT cell line). In general, the results suggest that all three compounds are non-cytotoxic, although one of the peptides shows a small impact on cell viability. In sustained release assays, the effect of the charge of the model drug compounds on the rate of cargo release from the hydrogel network was evaluated. The hydrogels provide a sustained release of methyl orange (anionic) and ciprofloxacin (neutral), while methylene blue (cationic) was retained by the network.This work was supported by the Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Funding of CQUM (UID/QUI/00686/2019), IPC (UIDP/CTM/05256/2020 and UIDB/05256/2020) and REQUIMTE/LAQV (UIDB/50006/2020). L.H. acknowledges grant CEECINST/00156/2018. FCT, FEDER, PORTUGAL2020 and COMPETE2020 are also acknowl edged for funding under research project PTDC/QUI-QOR/29015/2017 (POCI-01-0145-FEDER 029015). TGC thanks FCT under the scope of the strategic funding of UIDB/04469/2020 unit, and LABBELS—Associate Laboratory in Biotechnology, Bioengineering and Microelectromechanical Systems, LA/P/0029/2020.info:eu-repo/semantics/publishedVersio

Collaboration-Aware Hit Song Prediction

In a streaming-oriented era, predicting which songs will be successful is a significant challenge for the music industry. Indeed, there are many efforts in determining the driving factors that contribute to a song’s success, and one potential solution could be incorporating artistic collaborations, as it allows for a wider audience reach. Therefore, we propose a multi-perspective approach that includes collaboration between artists as a factor for hit song prediction. Specifically, by combining online data from Billboard and Spotify, we tackle the problem as both classification and hit song placement tasks, applying five different model variants. Our results show that relying only on music-related features is not enough, whereas models that also consider collaboration features produce better results

Temporal Success Analyses in Music Collaboration Networks: Brazilian and Global Scenarios

Collaboration is a part of the music industry and has increased over recent decades; but little do we know about its effects on success and evolution. Our goal is to analyze how success has evolved over collaboration networks and compare its global scenario to a local, thriving one: the Brazilian music industry. Specifically, we build collaboration networks from data collected from Spotify's Global and Brazilian daily charts, analyze them and identify collaboration profiles in such networks. Analyses over their topological characteristics reveal collaboration patterns mapped into four different profiles: Standard, Niche, Ephemeral and Absent, where the two first have a higher level of success. Furthermore, we do deeper by evaluating the temporal evolution of such profiles through case studies: pop and k-pop globally, and pop and forró in Brazil. Overall, our findings emphasize the importance of collaboration profiles in assessing success, and show differences between the global and Brazilian scenarios