Miracle-dz/UniFAR-FTUs huggingface dataset:
Blockchain-Based Architecture Design for Personal Health Record: Development and Usability Study

Background The importance of blockchain-based architectures for personal health record (PHR) lies in the fact that they are thought and developed to allow patients to control and at least partly collect their health data. Ideally, these systems should provide the full control of such data to the respective owner. In spite of this importance, most of the works focus more on describing how blockchain models can be used in a PHR scenario rather than whether these models are in fact feasible and robust enough to support a large number of users. Objective To achieve a consistent, reproducible, and comparable PHR system, we build a novel ledger-oriented architecture out of a permissioned distributed network, providing patients with a manner to securely collect, store, share, and manage their health data. We also emphasize the importance of suitable ledgers and smart contracts to operate the blockchain network as well as discuss the necessity of standardizing evaluation metrics to compare related (net)works. Methods We adopted the Hyperledger Fabric platform to implement our blockchain-based architecture design and the Hyperledger Caliper framework to provide a detailed assessment of our system: first, under workload, ranging from 100 to 2500 simultaneous record submissions, and second, increasing the network size from 3 to 13 peers. In both experiments, we used throughput and average latency as the primary metrics. We also created a health database, a cryptographic unit, and a server to complement the blockchain network. Results With a 3-peer network, smart contracts that write on the ledger have throughputs, measured in transactions per second (tps) in an order of magnitude close to 102 tps, while those contracts that only read have rates close to 103 tps. Smart contracts that write also have latencies, measured in seconds, in an order of magnitude close to 101 seconds, while that only read have delays close to 100 seconds. In particular, smart contracts that retrieve, list, and view history have throughputs varying, respectively, from 1100 tps to 1300 tps, 650 tps to 750 tps, and 850 tps to 950 tps, impacting the overall system response if they are equally requested under the same workload. Varying the network size and applying an equal fixed load, in turn, writing throughputs go from 102 tps to 101 tps and latencies go from 101 seconds to 102 seconds, while reading ones maintain similar values. Conclusions To the best of our knowledge, we are the first to evaluate, using Hyperledger Caliper, the performance of a PHR blockchain architecture and the first to evaluate each smart contract separately. Nevertheless, blockchain systems achieve performances far below what the traditional distributed databases achieve, indicating that the assessment of blockchain solutions for PHR is a major concern to be addressed before putting them into a real production.
The Impact of Genital Ulcers on HIV Transmission Has Been Underestimated—A Critical Review

In the early 1990s, several observational studies determined that genital ulcer disease (GUD), in either the index or the exposed person, facilitates HIV transmission. Several meta-analyses have since presented associated risk ratios (RR) over the baseline per-act transmission probability (PATP) usually in the range of 2–5. Here we review all relevant observational studies and meta-analyses, and show that the estimation of RRs was, in most cases, biased by assuming the presence of GUD at any time during long follow-up periods, while active genital ulcers were present in a small proportion of the time. Only two studies measured the GUD co-factor effect in PATPs focusing on acts in which ulcers were present, and both found much higher RRs (in the range 11–112). We demonstrate that these high RRs can be reconciled with the studies on which currently accepted low RRs were based, if the calculations are restricted to the actual GUD episodes. Our results indicate that the effect of genital ulcers on the PATP of HIV might be much greater than currently accepted. We conclude that the medical community should work on the assumption that HIV risk is very high during active genital ulcers.
Use of Different Organic Carbon Sources in Cynara cardunculus Cells: Effects on Biomass Productivity and Secondary Metabolites

Cynara cardunculus (Asteraceae family) is a perennial plant native to Mediterranean regions. This plant represents a source of high-value compounds, such as polyphenols and fatty acids that have several industrial applications. However, in vitro plant cell cultures can represent a valid alternative to in-field cultivation and facilitate the extraction of metabolites of commercial interest. Generally, sucrose is the main sugar used for plant cell cultures, but other carbon sources can be considered. Here, we investigated the potential use of alternative organic carbon sources, such as galactose, maltose, glucose, glycerol, fructose, lactose, and starch, for the cultivation of C. cardunculus cells. Moreover, cardoon cells were collected, and an extraction of polyphenols and oils was performed to study the effects of different carbon sources on the production of bioactive molecules. This study provided evidence that cardoon cell growth can be supported by carbon sources other than sucrose. However, the carbon source inducing optimum growth, did not necessarily induce the highest production of high-value compounds.
Dynamics of power systems with wind power generation and the fractional frequency transmission system

Under pressure for low carbon emissions and environmental protection, large scale wind farms are constructed and integrated into power systems to meet energy demands. On the other hand, the long distance transmission for large scale wind power and conventional power plants is another technical issue in modern power systems. These two challenges stimulate the research and development of wind energy and the fractional frequency transmission system (FFTS). Thus, the research of this thesis focuses on the dynamics of power systems with wind power generation and the FFTS. This thesis can be divided into the following three parts: Firstly, the influence of wind farms on the subsynchronous resonance (SSR) of conventional power systems is systematically examined. Both eigenvalue analysis and time domain simulations are conducted to examine the influence of wind farms. Secondly, the FFTS is proposed to deliver the energy from large scale offshore wind farms. The small signal stability of the FFTS with wind farms is studied. To improve the damping performance, a proper controller for the FFTS is also proposed. Thirdly, the FFTS is also applied in grid interconnections. The power flow controller for the FFTS is also proposed in this application.
An Overview of Polymer-Supported Catalysts for Wastewater Treatment through Light-Driven Processes

In recent years, alarm has been raised due to the presence of chemical contaminants of emerging concern (CECs) in water. This concern is due to the risks associated with their exposure, even in small amounts. These complex compounds cannot be removed or degraded by existing technologies in wastewater treatment plants. Therefore, advanced oxidation processes have been studied, with the objective of developing a technology capable of complementing the conventional water treatment plants. Heterogenous photocatalysis stands out for being a cost-effective and environmentally friendly process. However, its most common form (with suspended catalytic particles) requires time-consuming and costly downstream processes. Therefore, the heterogeneous photocatalysis process with a supported catalyst is preferable. Among the available supports, polymeric ones stand out due to their favorable characteristics, such as their transparency, flexibility and stability. This is a relatively novel process; therefore, there are still some gaps in the scientific knowledge. Thus, this review article aims to gather the existing information about this process and verify which questions are still to be answered.
Human Polymorphonuclear Cells Support Zika Virus to Cross Endothelial Monolayer and Access Bloodstream

The rapid spread of new outbreaks of human infection caused by Zika virus (ZIKV) has raised many global concerns since 2016. Despite the increasing knowledge of this virus, data on the pathogenesis of ZIKV are still missing. In particular, it is still unknown how the virus crosses the endothelial monolayer and gets access to the bloodstream. In the present work, we used human umbilical vein endothelial cells (HUVECs) as a model to study ZIKV infection in vitro. We demonstrated that HUVECs are an optimal reservoir for viral replication, as they were able to sustain ZIKV infection up to two weeks, without showing a cytopathic effect. In order to evaluate the integrity of endothelial monolayer, immunofluorescence was performed on mock-infected or ZIKV-infected cells ± peripheral blood mononuclear cells (PBMCs) or polymorphonuclear cells (PMN), 48 h p.i. , by using an anti-VE-Cadherin antibody, a major adherence protein that maintains the integrity of intercellular junctions. In addition to infection, we noted that the presence of some components of the immune system, such as PMNs, played an important role in altering the endothelial monolayer in cell junctions, suggesting that presence at the site of infection probably promotes the spread of ZIKV in vivo in the bloodstream.
Energy Community in Action—Energy Citizenship Contract as Tool for Climate Neutrality

Cities are responsible for 65% of energy consumption and for the 70% of CO2 emissions. Incisive actions are fundamental to bring cities towards climate neutrality by 2050 working by and for the citizens. For this reason, the “100 climate-neutral cities Mission” anticipates the target of climate neutrality by 2030. The objective of this paper, developed within the H2020 GRETA project—GReen Energy Transition Actions (GA101022317), is to investigate energy communities and climate city contracts as key interventions to face the ambitious goal of implementing citizens-centered and climate-neutral cities. To achieve this objective, this paper is structured as follows: (1) an updated framework of European and Italian legislation concerning energy communities; (2) an overview of climate city contracts’ definition and key aspects; (3) a selection and analysis of energy communities’ case studies; (4) a description of already developed pilot climate city contracts. The results provide more advanced knowledge about EU energy communities strategies and about the possible contractual agreements that can guarantee commitment between parties and can allow the active participation of citizens in the energy system. The lessons learned contribute to the application in the GRETA Italian case study, whose first participation activities are also described in the paper.
A 9 T SRAM cell with data-independent read bitline leakage and improved read sensing margin for low power applications

Read decoupled SRAM cells were proposed to address the conflicting read and write requirements in conventional 6 T SRAM cells. However, even read decoupled SRAM cells face several challenges like degraded cell stability, data dependent read bitline (RBL) leakage, deteriorated RBL swing which causes the failure in read sensing at scaled voltages. Therefore, in this work, we propose a read decoupled 9 T SRAM cell which improves the read performance. The proposed cell utilizes decoupled read port that significantly improves the read delay, I ON/I OFF ratio, bitline leakage as compared to the existing read decoupled cells. The proposed read buffer, having only one transistor in the read path, offers much lower read delay as compared to the existing read buffers. The RBL leakage in the proposed design is also data independent, which significantly improves the RBL sensing margin. We analyse and compare the proposed SRAM cell with existing cells using HSPICE simulations with 16 nm FinFET PTM technology. We observe that at a voltage of V DD = 0.35 V, the proposed SRAM cell offers ∼55% smaller read delay with only 8% increase in leakage power as compared to conventional 6 T cell. However, the proposed SRAM cell incurs smallest leakage penalty and offers fastest read operation than the existing read buffer based SRAM cells. Attributed to the negligible bitline leakage in the proposed cell, it offers the highest RBL sensing voltage attributed to closeness of RBL voltage for read ‘1’ to V DD as compared with the other cells. Monte Carlo simulations are also carried out to confirm the robustness of the proposed design under process-voltage-temperature variations. We observe that the proposed SRAM cell is robust and supports voltage scaling and hence could be an attractive choice for low voltage and low power applications.
Design of Optical Interconnect Transceiver Circuits and Network-on-chip Architectures for Inter- and Intra-chip Communication

The rapid expansion in data communication due to the increased multimedia applications and cloud computing services necessitates improvements in optical transceiver circuitry power efficiency as these systems scale well past 10 Gb/s. In order to meet these requirements, a 26 GHz transimpedance amplifier (TIA) is presented in a 0.25-μm SiGe BiCMOS technology. It employs a transformer-based regulated cascode (RGC) input stage which provides passive negative-feedback gain that enhances the effective transconductance of the TIA’s input common-base transistor; reducing the input resistance and providing considerable bandwidth extension without significant noise degradation or power consumption. The TIA achieves a 53 dBΩ single-ended transimpedance gain with a 26 GHz bandwidth and 21.3 pA/ √ Hz average input-referred noise current spectral density. Total chip power including output buffering is 28.2 mW from a 2.5 V supply, with the core TIA consuming 8.2 mW, and the chip area including pads is 960 μm × 780 μm. With the advance of photonic devices, optical interconnects becomes a promising technology to replace the conventional electrical channels for the high-bandwidth and power efficient inter/intra-chip interconnect. Second, a silicon photonic transceiver is presented for a silicon ring resonator-based optical interconnect architecture in a 1V standard 65nm CMOS technology. The transmitter circuits incorporate high-swing drivers with non-linear pre-emphasis and automatic bias-based tuning for resonance wavelength stabilization. An optical forwarded-clock adaptive inverter-based transimpedance amplifier (TIA) receiver trades-off power for varying link budgets by employing an on-die eye monitor and scaling the TIA supply for the required sensitivity. At 5Gb/s operation, the ring modulator under 4Vpp driver achieves 12.7dB extinction ratio with 4.04mW power consumption, while
Nine-level inverter with lesser number of power semiconductor switches using dSPACE

In this paper, a single-phase nine-level multilevel inverter (MLI) topology is created in which reduced number of switches, diodes and gate driver circuits can be used so as to obtain higher output voltage levels. Due to this configuration, the blocking voltage value across the switches will also get reduced. In this proposed single-phase MLI topology, increase in output voltage levels can be observed whenever there is increment in the number of switches in the configuration. Proper mathematical modeling and analysis of the voltage waveform of the proposed inverter have been done for a 9-level MLI. MATLAB platform is used for modeling and simulation of the MLI. Modulation index is varied in order to observe various outcomes through simulation. The proposed nine-level inverter configuration is experimentally evaluated in the laboratory for various modulation indices so as to validate the simulation results. Comparison of this topology is done with the classical MLIs in order to illustrate its advantages.
Predicting Citywide Crowd Dynamics at Big Events: A Deep Learning System

Event crowd management has been a significant research topic with high social impact. When some big events happen such as an earthquake, typhoon, and national festival, crowd management becomes the first priority for governments (e.g., police) and public service operators (e.g., subway/bus operator) to protect people’s safety or maintain the operation of public infrastructures. However, under such event situations, human behavior will become very different from daily routines, which makes prediction of crowd dynamics at big events become highly challenging, especially at a citywide level. Therefore in this study, we aim to extract the “deep” trend only from the current momentary observations and generate an accurate prediction for the trend in the short future, which is considered to be an effective way to deal with the event situations. Motivated by these, we build an online system called DeepUrbanEvent, which can iteratively take citywide crowd dynamics from the current one hour as input and report the prediction results for the next one hour as output. A novel deep learning architecture built with recurrent neural networks is designed to effectively model these highly complex sequential data in an analogous manner to video prediction tasks. Experimental results demonstrate the superior performance of our proposed methodology to the existing approaches. Lastly, we apply our prototype system to multiple big real-world events and show that it is highly deployable as an online crowd management system.
Cognitive Considerations in Major Depression: Evaluating the Effects of Pharmacotherapy and ECT on Mood and Executive Control Deficits

Deficits in the executive control of attention greatly impact the quality of life of patients diagnosed with major depressive disorder (MDD). However, attentional deficits are often underemphasized in clinical contexts compared with mood-based symptoms, and a comprehensive approach for specifically evaluating and treating them has yet to be developed. The present study evaluates the efficacy of bifrontal electroconvulsive therapy (ECT) combined with drug therapy (DT) in alleviating mood-related symptomatology and executive control deficits in drug-refractory MDD patients and compares these effects with those observed in MDD patients undergoing DT only. The Hamilton Rating Scale for Depression and the Lateralized Attentional Network Test-Revised were administered across two test sessions to assess treatment-related changes in mood-based symptoms and conflict processing, respectively, in patients undergoing ECT + DT (n = 23), patients undergoing DT (n = 33), and healthy controls (n = 40). Although both groups showed an improvement in mood-based symptoms following treatment and a deficit in conflict processing estimated on error rate, a post-treatment reduction of an executive control deficit estimated on RT was solely observed in the ECT + DT patient group. Furthermore, Bayesian correlational analyses confirmed the dissociation of mood-related symptoms and of executive control measures, supporting existing literature proposing that attentional deficits and mood symptoms are independent aspects of MDD. The cognitive profile of MDD includes executive control deficits, and while both treatments improved mood-based symptoms, only ECT + DT exerted an effect on both measures of the executive control deficit. Our findings highlight the importance of considering the improvement in both mood and cognitive deficits when determining the efficacy of therapeutic approaches for MDD.
A Study on the Level of Effectiveness of Multimedia Content as Instructional Methodologies to Improve the Quality of Students Learning Experience during COVID-19 Pandemic

With our current situation we became all content creator and through the advancement of technology, schools are also advancing their teaching strategy by utilizing multimedia presentations that would benefit the students. Interactive Multimedia Learning is now a teaching strategy that utilizes visual and audio annotations for the students to comprehend the lessons in an easy and fast manner. The study aims to examine and analyse the effects of interactive multimedia learning on student’s performance in class. The research utilized a quantitative research design that focused more on numerical data. A survey questionnaire administered and distributed to the participants. A total of 30 students from the different Higher Educational Institution the province of Ilocos Norte were involved in the study. Cluster sampling was utilized to give more opportunities for different students to share their insights regarding the topic. Results of the study showed that most of the students stated that multimedia learning contributed to their creativity in performance tasks and they became more focused and motivated due to the presence of creative and aesthetic graphics provided by multimedia. It also made them more independent and participative because the graphics are engaging and appealing to them. However, some students revealed that not all of their classes utilize multimedia learning tool. It was also revealed that there are students who are still engaged in board discussions and plain-text modules.
Fault detection of electrolyzer plate based on improved Mask R-CNN and infrared images

Non-ferrous metals are very important strategic resources, and electrolysis is an essential step in refining non-ferrous metals. In the electrolysis process, plate short circuit is the most common fault, which seriously affects output and energy consumption. The rapid and accurate detection of faulty plates is of great significance to the metal refining process. Given the weak generalization ability and complex feature rule design of traditional object detection algorithms, and the poor detection effect of existing deep learning models in infrared images with many interference factors, an improved Mask R-CNN-based fault detection algorithm is proposed to improve the generation strategy and non-maximum suppression algorithm of proposals to reduce the missed detection. We also propose a globally generalized intersection over union loss function to characterize better the position and scale relationship between the predicted box and target box, which is beneficial to the bounding box regression. The experimental results show that the improved model has an accuracy rate 10.4% higher than the original model, reaching 86.8%. Compared with the common one- and two-stage object detection models, the improved model has a stronger detection ability. This algorithm has some reference value for the accurate detection and location of electrolytic cell faults.
Endosseous Dental Implant Materials and Clinical Outcomes of Different Alloys: A Systematic Review

In recent years, implantology has made significant progress, as it has now become a safe and predictable practice. The development of new geometries, primary and secondary, of new surfaces and alloys, has made this possible. The purpose of this review is to analyze the different alloys present on the market, such as that in zirconia, and evaluate their clinical differences with those most commonly used, such as those in grade IV titanium. The review, conducted on major scientific databases such as Scopus, PubMed, Web of Science and MDPI yielded a startling number of 305 results. After the application of the filters and the evaluation of the results in the review, only 10 Randomized Clinical Trials (RCTs) were included. Multiple outcomes were considered, such as Marginal Bone Level (MBL), Bleeding on Probing (BoP), Survival Rate, Success Rate and parameters related to aesthetic and prosthetic factors. There are currently no statistically significant differences between the use of zirconia implants and titanium implants, neither for fixed prosthetic restorations nor for overdenture restorations. Only the cases reported complain about the rigidity and, therefore, the possibility of fracture of the zirconium. Certainly the continuous improvement in these materials will ensure that they could be used safely while maintaining their high aesthetic performance.