Performance and Power Estimation of STT-MRAM Main Memory with Reliable System-level Simulation

It is questionable whether DRAM will continue to scale and will meet the needs of next-generation systems. Therefore, significant effort is invested in research and development of novel memory technologies. One of the candidates for next-generation memory is Spin-Transfer Torque Magnetic Random Access Memory (STT-MRAM). STT-MRAM is an emerging non-volatile memory with a lot of potential that could be exploited for various requirements of different computing systems. Being a novel technology, STT-MRAM devices are already approaching DRAM in terms of capacity, frequency, and device size. Although STT-MRAM technology got significant attention of various major memory manufacturers, academic research of STT-MRAM main memory remains marginal. This is mainly due to the unavailability of publicly available detailed timing and current parameters of this novel technology, which are required to perform a reliable main memory simulation on performance and power estimation. This study demonstrates an approach to perform a cycle accurate simulation of STT-MRAM main memory, being the first to release detailed timing and current parameters of this technology from academia—essentially enabling researchers to conduct reliable system-level simulation of STT-MRAM using widely accepted existing simulation infrastructure. The results show a fairly narrow overall performance deviation in response to significant variations in key timing parameters, and the power consumption experiments identify the key power component that is mostly affected with STT-MRAM.

Triggermuscle: Exploring Weight Perception for Virtual Reality Through Adaptive Trigger Resistance in a Haptic VR Controller

It is challenging to provide users with a haptic weight sensation of virtual objects in VR since current consumer VR controllers and software-based approaches such as pseudo-haptics cannot render appropriate haptic stimuli. To overcome these limitations, we developed a haptic VR controller named Triggermuscle that adjusts its trigger resistance according to the weight of a virtual object. Therefore, users need to adapt their index finger force to grab objects of different virtual weights. Dynamic and continuous adjustment is enabled by a spring mechanism inside the casing of an HTC Vive controller. In two user studies, we explored the effect on weight perception and found large differences between participants for sensing change in trigger resistance and thus for discriminating virtual weights. The variations were easily distinguished and associated with weight by some participants while others did not notice them at all. We discuss possible limitations, confounding factors, how to overcome them in future research and the pros and cons of this novel technology.

Working Together Apart through Embodiment

Computer-mediated collaboration has long been a core research interest in CSCW and HCI. As online social spaces continue to evolve towards more immersive and higher fidelity experiences, more research is still needed to investigate how emerging novel technology may foster and support new and more nuanced forms and experiences of collaboration in virtual environments. Using 30 interviews, this paper focuses on what people may collaborate on and how they collaborate in social Virtual Reality (VR). We broaden current studies on computer-mediated collaboration by highlighting the importance of embodiment for co-presence and communication, replicating offline collaborative activities, and supporting the seamless interplay of work, play, and mundane experiences in everyday lives for experiencing and conceptualizing collaboration in emerging virtual environments. We also propose potential design implications that could further support everyday collaborative activities in social VR

Applications of Surfactants and Nanoparticles in Enhanced Oil Recovery Processes

The surfactant injection is considered as the EOR (Enhanced Oil Recovery) with the highest potential to recover oil from reservoirs due to its ability to reduce interfacial forces into the porous medium. However, the adsorption of this type of chemical on the surface of rocks is the main problem when a surfactant injection project is applied since the surfactant molecules would rather be placed on rock minerals instead of being the oil–water interface. Based on this fact, this chapter would be discussed the significance of surfactant injection as an EOR method, the types of surfactants used, the main mechanism and parameters involved in the surfactant adsorption on the rock, and its consequences in oil recovery. Likewise, the addition of nanoparticles to inhibit the adsorption of surfactants is another topic that will be covered as a novel technology to improve the efficiency of the EOR process.

Supply Restoration in Active Distribution Networks Based on Soft Open Points with Embedded DC Microgrids

As disturbances due to natural disasters or man-made attacks intensify awareness regarding power systems’ resilience enhancement, the scientific community concentrates on exploring state-of-the-art technologies for emergency supply restoration strategies. Recent studies are increasingly focusing on the expanded flexibility of soft open points (SOPs) compared to conventional tie-switches to increase the restoration rate of critical loads; however, the potential of this novel technology is not limited to this aspect, with SOPs being used to improve the voltage level and increase the hosting capacity of renewable energy sources (RESs). This paper proposes a deterministic model for the optimal coordination of SOPs and distributed resources in an active distribution network (ADN) aiming at re-establishing the energy supply to critical loads after a prolonged interruption occurrence. At the same time, the support of DC microgrids with integrated RESs, embedded in SOPs, for the restoration process is explored. The efficiency of the proposed optimization model is verified based on a 24-h analysis performed on the modified IEEE 33-bus system, while considering the load and generation uncertainties as well.

Augmented Reality-Assisted Spine Surgery: An Early Experience Demonstrating Safety and Accuracy with 218 Screws

Study Design Prospective cohort study. Objectives In spine surgery, accurate screw guidance is critical to achieving satisfactory fixation. Augmented reality (AR) is a novel technology to assist in screw placement and has shown promising results in early studies. This study aims to provide our early experience evaluating safety and efficacy with an Food and Drug Administration-approved head-mounted (head-mounted device augmented reality (HMD-AR)) device. Methods Consecutive adult patients undergoing AR-assisted thoracolumbar fusion between October 2020 and August 2021 with 2 -week follow-up were included. Preoperative, intraoperative, and postoperative data were collected to include demographics, complications, revision surgeries, and AR performance. Intraoperative 3D imaging was used to assess screw accuracy using the Gertzbein-Robbins (G-R) grading scale. Results Thirty-two patients (40.6% male) were included with a total of 222 screws executed using HMD-AR. Intraoperatively, 4 (1.8%) were deemed misplaced and revised using AR or freehand. The remaining 218 (98.2%) screws were placed accurately. There were no intraoperative adverse events or complications, and AR was not abandoned in any case. Of the 208 AR-placed screws with 3D imaging confirmation, 97.1% were considered clinically accurate (91.8% Grade A, 5.3% Grade B). There were no early postoperative surgical complications or revision surgeries during the 2 -week follow-up. Conclusions This early experience study reports an overall G-R accuracy of 97.1% across 218 AR-guided screws with no intra or early postoperative complications. This shows that HMD-AR-assisted spine surgery is a safe and accurate tool for pedicle, cortical, and pelvic fixation. Larger studies are needed to continue to support this compelling evolution in spine surgery.

The New Boundaries of 3D-Printed Clay Bricks Design: Printability of Complex Internal Geometries

The building construction sector is undergoing one of the most profound transformations towards the digital transition of production. In recent decades, the advent of a novel technology for the 3D printing of clay opened up new sustainable possibilities in construction. Some architectural applications of 3D-printed clay bricks with simple internal configurations are being developed around the world. On the other hand, the full potential of 3D-printed bricks for building production is still unknown. Scientific studies about the design and printability of 3D-printed bricks exploiting complex internal geometries are completely missing in the related literature. This paper explores the new boundaries of 3D-printed clay bricks realized with a sustainable extrusion-based 3D clay printing process by proposing a novel conception, design, and analysis. In particular, the proposed methodological approach includes: (i) conception and design; (ii) parametric modeling; (iii) simulation of printability; and (iv) prototyping. The new design and conception aim to fully exploit the potential of 3D printing to realize complex internal geometry in a 3D-printed brick. To this aim, the research investigates the printability of internal configuration generated by using geometries with well-known remarkable mechanical properties, such as periodic minimal surfaces. In conclusion, the results are validated by a wide prototyping campaign.

Gamification Tools to Facilitate Student Learning Engagement in Higher Education

Gamification is a novel technology that can potentially motivate student learning. This chapter reflects on the implementation of a gamified application to support students' learning in terms of learning important facts concerning their study program. The scope of the chapter refers to two design features in which tests were conducted on the different configurations in a field experiment among UK university students. The initial feature identified was feedback, where it was anticipated that engagement would increase, with tailored feedback having a greater impact than generic feedback. The next feature identified was circumventing users from binge gaming through session limits, as this may potentially prevent deep learning. The findings suggest that tailored feedback was less effective than generic feedback, contradicting the initial anticipation. Session limits were found to not circumvent binging without a reduction in sessions. The findings suggest that gaming properties of gamified applications could impact sustaining and encouraging play.

Enhancing Ammonium Oxidation Fluxes and Nitritation Efficiencies in MABRs: A Modeling Study

The membrane aerated biofilm reactor (MABR) is a novel technology based on gas-supplying membranes that supply dissolved O2 (DO) to biofilms growing on the membrane surface. The counter-diffusion of dissolved...