Flow updating: fault-tolerant aggregation for dynamic networks

Documento submetido para revisão pelos pares. A publicar em Journal of Parallel and Distributed Computing. ISSN 0743-7315

Development of Janus hydrogel microcapsules as novel biomaterials-stem cells construct for 3D co-culture applications

Co-cultures of two or more cell types and biodegradable biomaterials of natural origin have been successfully combined to recreate tissue microenvironments. Segregated co-cultures are preferred over conventional mixed ones in order to better control the degree of homotypic and heterotypic interactions. Hydrogel-based systems in particular, have gained much attention to mimic tissue-specific microenvironments and they can be microengineered by innovative bottom-up approaches such as microfluidics. In this study, we developed bi-compartmentalized (Janus) hydrogel microcapsules of methacrylated hyaluronic acid (MeHA)/methacrylated-chitosan (MeCht) blended with marine-origin collagen by droplet-based microfluidics co-flow. Human adipose stem cells (hASCs) and microvascular endothelial cells (hMVECs) were co-encapsulated to create platforms of study relevant for vascularized bone tissue engineering. A specially designed Janus-droplet generator chip was used to fabricate the microcapsules (<250â μm units) and Janus-gradient co-cultures of hASCs: hMVECs were generated in various ratios (90:10; 75:25; 50:50; 25:75; 10:90), through an automated microfluidic flow controller (Elveflow microfluidics system). Such monodisperse 3D co-culture systems were optimized regarding cell number and culture media specific for concomitant maintenance of both phenotypes to establish effective cell-cell (homotypic and heterotypic) and cell-materials interactions. Cellular parameters such as viability, matrix deposition, mineralization and hMVECs re-organization in tube-like structures, were enhanced by blending MeHA/MeCht with marine-origin collagen and increasing hASCs: hMVECs co-culture gradient had significant impact on it. Such Janus hybrid hydrogel microcapsules can be used as a platform to investigate biomaterials interactions with distinct combined cell populations.

Continuous-flow precipitation as a route to prepare highly controlled nanohydroxyapatite

[Excerpt] Hydroxyapatite Ca10(PO4)6(OH)2 (HAp) has been widely used for biomedical purposes because of its exceptional biocompatibility, bioactivity and osteoconductivity [1]. As these properties are directly related to HAp particles characteristics (size, morphology and purity), a very good control of the reaction conditions is required to obtain particles with the desired properties. Usually, HAp is synthesized by wet chemical precipitation in stirred tank batch reactors that often lead to inconsistencies in product specifications due to their low mixing efficiency [2]. (...)

Bacterial nanocellulose as a structured platform for conductive biopolymers

[Exert] Since the discovery that polyacetylene could be doped to the metallic state more than 3 decades ago, an ever-growing body of a multidisciplinary approach to material design, synthesis, and system integration has been evidenced. The present chapter will primarily review the emerging field of intrinsically conducting polymer and conductive polymer blends, with polyaniline and polypyrrole as the major representatives of conducting polymers. This survey will also address some of the potential areas for applications of such conductive polymer blends. Also, current results concerning the chemical polymerization of conducting polymers on bacterial nanocellulose (BNC) will be presented, including brief remarks on the rationale for the use of conductive BNC blends. This will be followed by a discussion on their properties and potential applications (...).

An evolutionary approach to the use of Petri net based models: from parallel controllers to HW/SW co-design

"A workshop within the 19th International Conference on Applications and Theory of Petri Nets - ICATPN’1998"

Predicting pre-triage waiting time in a maternity emergency room through data mining

An unsuitable patient flow as well as prolonged waiting lists in the emergency room of a maternity unit, regarding gynecology and obstetrics care, can affect the mother and child’s health, leading to adverse events and consequences regarding their safety and satisfaction. Predicting the patients’ waiting time in the emergency room is a means to avoid this problem. This study aims to predict the pre-triage waiting time in the emergency care of gynecology and obstetrics of Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto, situated in the north of Portugal. Data mining techniques were induced using information collected from the information systems and technologies available in CMIN. The models developed presented good results reaching accuracy and specificity values of approximately 74% and 94%, respectively. Additionally, the number of patients and triage professionals working in the emergency room, as well as some temporal variables were identified as direct enhancers to the pre-triage waiting time. The imp lementation of the attained knowledge in the decision support system and business intelligence platform, deployed in CMIN, leads to the optimization of the patient flow through the emergency room and improving the quality of services.