Tourism and arctic observation systems : Exploring the relationships

The Arctic is affected by global environmental change and also by diverse interests from many economic sectors and industries. Over the last decade, various actors have attempted to explore the options for setting up integrated and comprehensive trans-boundary systems for monitoring and observing these impacts. These Arctic Observation Systems (AOS) contribute to the planning, implementation, monitoring and evaluation of environmental change and responsible social and economic development in the Arctic. The aim of this article is to identify the two-way relationship between AOS and tourism. On the one hand, tourism activities account for diverse changes across a broad spectrum of impact fields. On the other hand, due to its multiple and diverse agents and far-reaching activities, tourism is also well-positioned to collect observational data and participate as an actor in monitoring activities. To accomplish our goals, we provide an inventory of tourism-embedded issues and concerns of interest to AOS from a range of destinations in the circumpolar Arctic region, including Alaska, Arctic Canada, Iceland, Svalbard, the mainland European Arctic and Russia. The article also draws comparisons with the situation in Antarctica. On the basis of a collective analysis provided by members of the International Polar Tourism Research Network from across the polar regions, we conclude that the potential role for tourism in the development and implementation of AOS is significant and has been overlooked.

Intelligent Sensor Systems for Structural Health Monitoring Applications

The convergence between the recent developments in sensing technologies, data science, signal processing and advanced modelling has fostered a new paradigm to the Structural Health Monitoring (SHM) of engineered structures, which is the one based on intelligent sensors, i.e., embedded devices capable of stream processing data and/or performing structural inference in a self-contained and near-sensor manner. To efficiently exploit these intelligent sensor units for full-scale structural assessment, a joint effort is required to deal with instrumental aspects related to signal acquisition, conditioning and digitalization, and those pertaining to data management, data analytics and information sharing. In this framework, the main goal of this Thesis is to tackle the multi-faceted nature of the monitoring process, via a full-scale optimization of the hardware and software resources involved by the {SHM} system. The pursuit of this objective has required the investigation of both: i) transversal aspects common to multiple application domains at different abstraction levels (such as knowledge distillation, networking solutions, microsystem {HW} architectures), and ii) the specificities of the monitoring methodologies (vibrations, guided waves, acoustic emission monitoring). The key tools adopted in the proposed monitoring frameworks belong to the embedded signal processing field: namely, graph signal processing, compressed sensing, ARMA System Identification, digital data communication and TinyML.

Embedded representations of social interactions

Social interactions have been the focus of social science research for a century, but their study has recently been revolutionized by novel data sources and by methods from computer science, network science, and complex systems science. The study of social interactions is crucial for understanding complex societal behaviours. Social interactions are naturally represented as networks, which have emerged as a unifying mathematical language to understand structural and dynamical aspects of socio-technical systems. Networks are, however, highly dimensional objects, especially when considering the scales of real-world systems and the need to model the temporal dimension. Hence the study of empirical data from social systems is challenging both from a conceptual and a computational standpoint. A possible approach to tackling such a challenge is to use dimensionality reduction techniques that represent network entities in a low-dimensional feature space, preserving some desired properties of the original data. Low-dimensional vector space representations, also known as network embeddings, have been extensively studied, also as a way to feed network data to machine learning algorithms. Network embeddings were initially developed for static networks and then extended to incorporate temporal network data. We focus on dimensionality reduction techniques for time-resolved social interaction data modelled as temporal networks. We introduce a novel embedding technique that models the temporal and structural similarities of events rather than nodes. Using empirical data on social interactions, we show that this representation captures information relevant for the study of dynamical processes unfolding over the network, such as epidemic spreading. We then turn to another large-scale dataset on social interactions: a popular Web-based crowdfunding platform. We show that tensor-based representations of the data and dimensionality reduction techniques such as tensor factorization allow us to uncover the structural and temporal aspects of the system and to relate them to geographic and temporal activity patterns.

Mechanical behaviour and durability assessment of Fibre Reinforced Cementitious Matrix (FRCM) strengthening systems.

In recent years, the seismic vulnerability of existing masonry buildings has been underscored by the destructive impacts of earthquakes. Therefore, Fibre Reinforced Cementitious Matrix (FRCM) retrofitting systems have gained prominence due to their high strength-to-weight ratio, compatibility with substrates, and potential reversibility. However, concerns linger regarding the durability of these systems when subjected to long-term environmental conditions. This doctoral dissertation addressed these concerns by studying the effects of mild temperature variations on three FRCM systems, featuring basalt, glass, and aramid fibre textiles with lime-based mortar matrices. The study subjected various specimens, including mortar triplets, bare textile specimens, FRCM coupons, and single-lap direct shear wallets, to thermal exposure. A novel approach utilizing embedded thermocouple sensors facilitated efficient monitoring and active control of the conditioning process. A shift in the failure modes was obtained in the single lap-direct shear tests, alongside a significant impact on tensile capacity for both textiles and FRCM coupons. Subsequently, bond tests results were used to indirectly calibrate an analytical approach based on mode-II fracture mechanics. A comparison between Cohesive Material Law (CML) functions at various temperatures was conducted for each of the three systems, demonstrating a good agreement between the analytical model and experimental curves. Furthermore, the durability in alkaline environment of two additional FRCM systems, characterized by basalt and glass fibre textiles with lime-based mortars, was studied through an extensive experimental campaign. Tests conducted on single yarn and textile specimens after exposure at different durations and temperatures revealed a significant impact on tensile capacity. Additionally, FRCM coupons manufactured with conditioned textile were tested to understand the influence of aged textile and curing environment on the final tensile behavior. These results contributed significantly to the existing knowledge on FRCM systems and could be used to develop a standardized alkaline testing protocol, still lacking in the scientific literature.

Directly training spiking neural networks for cyber-physical systems: from supervised to reinforcement learning

Spiking Neural Networks (SNNs) are bio-inspired Artificial Neural Networks (ANNs) utilizing discrete spiking signals, akin to neuron communication in the brain, making them ideal for real-time and energy-efficient Cyber-Physical Systems (CPSs). This thesis explores their potential in Structural Health Monitoring (SHM), leveraging low-cost MEMS accelerometers for early damage detection in motorway bridges. The study focuses on Long Short-Term SNNs (LSNNs), although their complex learning processes pose challenges. Comparing LSNNs with other ANN models and training algorithms for SHM, findings indicate LSNNs' effectiveness in damage identification, comparable to ANNs trained using traditional methods. Additionally, an optimized embedded LSNN implementation demonstrates a 54% reduction in execution time, but with longer pre-processing due to spike-based encoding. Furthermore, SNNs are applied in UAV obstacle avoidance, trained directly using a Reinforcement Learning (RL) algorithm with event-based input from a Dynamic Vision Sensor (DVS). Performance evaluation against Convolutional Neural Networks (CNNs) highlights SNNs' superior energy efficiency, showing a 6x decrease in energy consumption. The study also investigates embedded SNN implementations' latency and throughput in real-world deployments, emphasizing their potential for energy-efficient monitoring systems. This research contributes to advancing SHM and UAV obstacle avoidance through SNNs' efficient information processing and decision-making capabilities within CPS domains.

An Embedded In-Cabin Lightweight High-Performance 3D Gaze Estimation System

Gaze estimation has gained interest in recent years for being an important cue to obtain information about the internal cognitive state of humans. Regardless of whether it is the 3D gaze vector or the point of gaze (PoG), gaze estimation has been applied in various fields, such as: human robot interaction, augmented reality, medicine, aviation and automotive. In the latter field, as part of Advanced Driver-Assistance Systems (ADAS), it allows the development of cutting-edge systems capable of mitigating road accidents by monitoring driver distraction. Gaze estimation can be also used to enhance the driving experience, for instance, autonomous driving. It also can improve comfort with augmented reality components capable of being commanded by the driver's eyes. Although, several high-performance real-time inference works already exist, just a few are capable of working with only a RGB camera on computationally constrained devices, such as a microcontroller. This work aims to develop a low-cost, efficient and high-performance embedded system capable of estimating the driver's gaze using deep learning and a RGB camera. The proposed system has achieved near-SOTA performances with about 90% less memory footprint. The capabilities to generalize in unseen environments have been evaluated through a live demonstration, where high performance and near real-time inference were obtained using a webcam and a Raspberry Pi4.

Design and Implementation of Single phase 230V to Three Phase Inverter Based on the Embedded System STM-32 Applied to motor control

In the field of Power Electronics, several types of motor control systems have been developed using STM microcontroller and power boards. In both industrial power applications and domestic appliances, power electronic inverters are widely used. Inverters are used to control the torque, speed, and position of the rotor in AC motor drives. An inverter delivers constant-voltage and constant-frequency power in uninterruptible power sources. Because inverter power supplies have a high-power consumption and low transfer efficiency rate, a three-phase sine wave AC power supply was created using the embedded system STM32, which has low power consumption and efficient speed. It has the capacity of output frequency of 50 Hz and the RMS of line voltage. STM32 embedded based Inverter is a power supply that integrates, reduced, and optimized the power electronics application that require hardware system, software, and application solution, including power architecture, techniques, and tools, approaches capable of performance on devices and equipment. Power inverters are currently used and implemented in green energy power system with low energy system such as sensors or microcontroller to perform the operating function of motors and pumps. STM based power inverter is efficient, less cost and reliable. My thesis work was based on STM motor drives and control system which can be implemented in a gas analyser for operating the pumps and motors. It has been widely applied in various engineering sectors due to its ability to respond to adverse structural changes and improved structural reliability. The present research was designed to use STM Inverter board on low power MCU such as NUCLEO with some practical examples such as Blinking LED, and PWM. Then we have implemented a three phase Inverter model with Steval-IPM08B board, which converter single phase 230V AC input to three phase 380 V AC output, the output will be useful for operating the induction motor.

A Microleakage Study Of Gutta-percha/ah Plus And Resilon/real Self-etch Systems After Different Irrigation Protocols.

The development and maintenance of the sealing of the root canal system is the key to the success of root canal treatment. The resin-based adhesive material has the potential to reduce the microleakage of the root canal because of its adhesive properties and penetration into dentinal walls. Moreover, the irrigation protocols may have an influence on the adhesiveness of resin-based sealers to root dentin. The objective of the present study was to evaluate the effect of different irrigant protocols on coronal bacterial microleakage of gutta-percha/AH Plus and Resilon/Real Seal Self-etch systems. One hundred ninety pre-molars were used. The teeth were divided into 18 experimental groups according to the irrigation protocols and filling materials used. The protocols used were: distilled water; sodium hypochlorite (NaOCl)+eDTA; NaOCl+H3PO4; NaOCl+eDTA+chlorhexidine (CHX); NaOCl+H3PO4+CHX; CHX+eDTA; CHX+ H3PO4; CHX+eDTA+CHX and CHX+H3PO4+CHX. Gutta-percha/AH Plus or Resilon/Real Seal Se were used as root-filling materials. The coronal microleakage was evaluated for 90 days against Enterococcus faecalis. Data were statistically analyzed using Kaplan-Meier survival test, Kruskal-Wallis and Mann-Whitney tests. No significant difference was verified in the groups using chlorhexidine or sodium hypochlorite during the chemo-mechanical preparation followed by eDTA or phosphoric acid for smear layer removal. The same results were found for filling materials. However, the statistical analyses revealed that a final flush with 2% chlorhexidine reduced significantly the coronal microleakage. A final flush with 2% chlorhexidine after smear layer removal reduces coronal microleakage of teeth filled with gutta-percha/AH Plus or Resilon/Real Seal SE.

Does The Reciproc File Remove Root Canal Bacteria And Endotoxins As Effectively As Multifile Rotary Systems?

To evaluate the effectiveness of Reciproc for the removal of cultivable bacteria and endotoxins from root canals in comparison with multifile rotary systems. The root canals of forty human single-rooted mandibular pre-molars were contaminated with an Escherichia coli suspension for 21 days and randomly assigned to four groups according to the instrumentation system: GI - Reciproc (VDW); GII - Mtwo (VDW); GIII - ProTaper Universal (Dentsply Maillefer); and GIV -FKG Race(™) (FKG Dentaire) (n = 10 per group). Bacterial and endotoxin samples were taken with a sterile/apyrogenic paper point before (s1) and after instrumentation (s2). Culture techniques determined the colony-forming units (CFU) and the Limulus Amebocyte Lysate assay was used for endotoxin quantification. Results were submitted to paired t-test and anova. At s1, bacteria and endotoxins were recovered in 100% of the root canals investigated (40/40). After instrumentation, all systems were associated with a highly significant reduction of the bacterial load and endotoxin levels, respectively: GI - Reciproc (99.34% and 91.69%); GII - Mtwo (99.86% and 83.11%); GIII - ProTaper (99.93% and 78.56%) and GIV - FKG Race(™) (99.99% and 82.52%) (P < 0.001). No statistical difference were found amongst the instrumentation systems regarding bacteria and endotoxin removal (P > 0.01). The reciprocating single file, Reciproc, was as effective as the multifile rotary systems for the removal of bacteria and endotoxins from root canals.

Photoelastic Analysis Of Fixed Partial Prosthesis Crown Height And Implant Length On Distribution Of Stress In Two Dental Implant Systems.

The aim of this study was to evaluate by photoelastic analysis stress distribution on short and long implants of two dental implant systems with 2-unit implant-supported fixed partial prostheses of 8 mm and 13 mm heights. Sixteen photoelastic models were divided into 4 groups: I: long implant (5 × 11 mm) (Neodent), II: long implant (5 × 11 mm) (Bicon), III: short implant (5 × 6 mm) (Neodent), and IV: short implants (5 × 6 mm) (Bicon). The models were positioned in a circular polariscope associated with a cell load and static axial (0.5 Kgf) and nonaxial load (15°, 0.5 Kgf) were applied to each group for both prosthetic crown heights. Three-way ANOVA was used to compare the factors implant length, crown height, and implant system (α = 0.05). The results showed that implant length was a statistically significant factor for both axial and nonaxial loading. The 13 mm prosthetic crown did not result in statistically significant differences in stress distribution between the implant systems and implant lengths studied, regardless of load type (P > 0.05). It can be concluded that short implants showed higher stress levels than long implants. Implant system and length was not relevant factors when prosthetic crown height were increased.

Dentine Bond Strength And Antimicrobial Activity Evaluation Of Adhesive Systems.

This study evaluated the dentine bond strength (BS) and the antibacterial activity (AA) of six adhesives against strict anaerobic and facultative bacteria. Three adhesives containing antibacterial components (Gluma 2Bond (glutaraldehyde)/G2B, Clearfil SE Protect (MDPB)/CSP and Peak Universal Bond (PUB)/chlorhexidine) and the same adhesive versions without antibacterial agents (Gluma Comfort Bond/GCB, Clearfil SE Bond/CSB and Peak LC Bond/PLB) were tested. The AA of adhesives and control groups was evaluated by direct contact method against four strict anaerobic and four facultative bacteria. After incubation, according to the appropriate periods of time for each microorganism, the time to kill microorganisms was measured. For BS, the adhesives were applied according to manufacturers' recommendations and teeth restored with composite. Teeth (n=10) were sectioned to obtain bonded beams specimens, which were tested after artificial saliva storage for one week and one year. BS data were analyzed using two-way ANOVA and Tukey test. Saliva storage for one year reduces the BS only for GCB. In general G2B and GCB required at least 24h for killing microorganisms. PUB and PLB killed only strict anaerobic microorganisms after 24h. For CSP the average time to eliminate the Streptococcus mutans and strict anaerobic oral pathogens was 30min. CSB showed no AA against facultative bacteria, but had AA against some strict anaerobic microorganisms. Storage time had no effect on the BS for most of the adhesives. The time required to kill bacteria depended on the type of adhesive and never was less than 10min. Most of the adhesives showed stable bond strength after one year and the Clearfil SE Protect may be a good alternative in restorative procedures performed on dentine, considering its adequate bond strength and better antibacterial activity.

Self-etch Adhesive Systems: A Literature Review.

This paper presents the state of the art of self-etch adhesive systems. Four topics are shown in this review and included: the historic of this category of bonding agents, bonding mechanism, characteristics/properties and the formation of acid-base resistant zone at enamel/dentin-adhesive interfaces. Also, advantages regarding etch-and-rinse systems and classifications of self-etch adhesive systems according to the number of steps and acidity are addressed. Finally, issues like the potential durability and clinical importance are discussed. Self-etch adhesive systems are promising materials because they are easy to use, bond chemically to tooth structure and maintain the dentin hydroxyapatite, which is important for the durability of the bonding.

Influence of different adhesive systems on the pull-out bond strength of glass fiber posts

This in vitro study evaluated the tensile bond strength of glass fiber posts (Reforpost - Angelus-Brazil) cemented to root dentin with a resin cement (RelyX ARC - 3M/ESPE) associated with two different adhesive systems (Adper Single Bond - 3M/ESPE and Adper Scotchbond Multi Purpose (MP) Plus - 3M/ESPE), using the pull-out test. Twenty single-rooted human teeth with standardized root canals were randomly assigned to 2 groups (n=10): G1- etching with 37% phosphoric acid gel (3M/ESPE) + Adper Single Bond + #1 post (Reforpost - Angelus) + four #1 accessory posts (Reforpin - Angelus) + resin cement; G2- etching with 37% phosphoric acid gel + Adper Scotchbond MP Plus + #1 post + four #1 accessory posts + resin cement. The specimens were stored in distilled water at 37°C for 7 days and submitted to the pull-out test in a universal testing machine (EMIC) at a crosshead speed of 0.5 mm/min. The mean values of bond strength (kgf) and standard deviation were: G1- 29.163 ± 7.123; G2- 37.752 ±13.054. Statistical analysis (Student's t-test; a=0.05 showed no statistically significant difference (p<0.05) between the groups. Adhesive bonding failures between resin cement and root canal dentin surface were observed in both groups, with non-polymerized resin cement in the apical portion of the post space when Single Bond was used (G1). The type of adhesive system employed on the fiber post cementation did not influence the pull-out bond strength.

Shear bond strength of self-etch and total-etch bonding systems at different dentin depths

The purpose of this study was to evaluate the dentin shear bond strength of four adhesive systems (Adper Single Bond 2, Adper Prompt L-Pop, Magic Bond DE and Self Etch Bond) in regards to buccal and lingual surfaces and dentin depth. Forty extracted third molars had roots removed and crowns bisected in the mesiodistal direction. The buccal and lingual surfaces were fixed in a PVC/acrylic resin ring and were divided into buccal and lingual groups assigned to each selected adhesive. The same specimens prepared for the evaluation of superficial dentin shear resistance were used to evaluate the different depths of dentin. The specimens were identified and abraded at depths of 0.5, 1.0, 1.5 and 2.0 mm. Each depth was evaluated by ISO TR 11405 using an EMIC-2000 machine regulated at 0.5 mm/min with a 200 Kgf load cell. We performed statistical analyses on the results (ANOVA, Tukey and Scheffé tests). Data revealed statistical differences (p < 0.01) in the adhesive and depth variation as well as adhesive/depth interactions. The Adper Single Bond 2 demonstrated the highest mean values of shear bond strength. The Prompt L-Pop product, a self-etching adhesive, revealed higher mean values compared with Magic Bond DE and Self Etch Bond adhesives, a total and self-etching adhesive respectively. It may be concluded that the shear bond strength of dentin is dependent on material (adhesive system), substrate depth and adhesive/depth interaction.

Comparative study of chemical and mechanical retentive systems for bonding of indirect composite resin to commercially pure titanium

This study evaluated the effect of chemical and mechanical surface treatments for cast metal alloys on the bond strength of an indirect composite resin (Artglass) to commercially pure titanium (cpTi). Thirty cylindrical metal rods (3 mm diameter x 60 mm long) were cast in grade-1 cpTi and randomly assigned to 6 groups (n=5) according to the received surface treatment: sandblasting; chemical treatment; mechanical treatment - 0.4 mm beads; mechanical treatment - 0.6 mm beads; chemical/mechanical treatment - 0.4 mm; and chemical/mechanical treatment - 0.6 mm beads. Artglass rings (6.0 mm diameter x 2.0 mm thick) were light cured around the cpTi rods, according manufacturer's specifications. The specimens were invested in hard gypsum and their bond strength (in MPa) to the rods was measured at fracture with a universal testing machine at a crosshead speed of 2.0 mm/min and 500 kgf load cell. Data were analyzed statistically by one-way ANOVA and Tukey test (a=5%). The surface treatments differed significantly from each other (p<0.05) regarding the recorded bond strengths. Chemical retention and sandblasting showed statistically similar results to each other (p=0.139) and both had significantly lower bond strengths (p<0.05) than the other treatments. In conclusion, mechanical retention, either associated or not to chemical treatment, provided higher bond strength of the indirect composite resin to cpTi.