Miracle-dz/UniFAR-FTUs huggingface dataset:
Kinetics of Resorcinol-Formaldehyde Condensation—Comparison of Common Experimental Techniques

Porous carbons, originated from resorcinol-formaldehyde (RF) gels, show high application potential. However, the kinetics and mechanism of RF condensation are still not well described. In this work, different methods (dynamic light scattering–DLS, Fourier transform infrared spectroscopy–FTIR, low field 1H nuclear magnetic resonance relaxometry–1H-NMR, and differential scanning calorimetry–DSC) were used to follow the isothermal RF condensation of mixtures varying in catalyst content (Na2CO3) and reactant concentration. The applicability and results obtained by the methods used differ significantly. The changes in functional groups can be followed by FTIR only at very early stages of the reaction. DLS enables the estimate of the growth of particles in reaction solution, but only before the solution becomes more viscous. Following the relaxation of 1H nuclei in water during RF condensation brings a different view on the system—this technique follows the properties of the present water that is gradually captured in polymeric gel. From this side, the process behaves similarly to the nucleation reaction, which is in contradiction to the n-order mechanism confirmed by other techniques. The widest range of applicability was found for DSC measurement of the freezing/melting behavior of the reaction mixture, which is possible to use without any limitations until full solidification. Furthermore, this approach enables us to follow the gradual formation and development of the gel through the intermediate undergoing glass transition.
Phase resetting in neural oscillators as a component of circuit analysis

Recordings of the membrane potential from a bursting neuron were used to reconstruct the phase resetting curve (PRC) for a limited set of perturbations. These perturbations were inhibitory synaptic conductance pulses able to shift the membrane potential below the most hyperpolarized level attained in the free running mode. We used a delay embedding method to unfold the limit cycle attractor. For the pulse amplitudes we studied, resetting was independent of amplitude of the perturbation but increased linearly with pulse duration. The predicted and the experimental PRCs show satisfactory agreement. The method was applied to only one pulse per cycle, but our results suggest it could easily be generalized to accommodate multiple inputs, and may ultimately aid us in the analysis of circuits that contain neural oscillators.
Early-predicting dropout of university students: an application of innovative multilevel machine learning and statistical techniques

ABSTRACT This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading Italian university.
Deep Stacking Network for Intrusion Detection

Preventing network intrusion is the essential requirement of network security. In recent years, people have conducted a lot of research on network intrusion detection systems. However, with the increasing number of advanced threat attacks, traditional intrusion detection mechanisms have defects and it is still indispensable to design a powerful intrusion detection system. This paper researches the NSL-KDD data set and analyzes the latest developments and existing problems in the field of intrusion detection technology. For unbalanced distribution and feature redundancy of the data set used for training, some training samples are under-sampling and feature selection processing. To improve the detection effect, a Deep Stacking Network model is proposed, which combines the classification results of multiple basic classifiers to improve the classification accuracy. In the experiment, we screened and compared the performance of various mainstream classifiers and found that the four models of the decision tree, k-nearest neighbors, deep neural network and random forests have outstanding detection performance and meet the needs of different classification effects. Among them, the classification accuracy of the decision tree reaches 86.1%. The classification effect of the Deeping Stacking Network, a fusion model composed of four classifiers, has been further improved and the accuracy reaches 86.8%. Compared with the intrusion detection system of other research papers, the proposed model effectively improves the detection performance and has made significant improvements in network intrusion detection.
A Novel Model for Implementing Internet of Things (IoT) in Iranian Hospitals

The Internet of Things (IOT) has led to ground-breaking changes in the healthcare industry as a promising technological solution. Yet, despite its many benefits, its application has always proven to be challenging. Hence, the purpose of this study is to identify the challenges of using the IOT with the intention of proposing a model for implementing Internet of Things in Iranian hospitals. This study was performed in three phases. In the first phase, the challenges of using the IoT were outlined and introduced. In the second phase the challenges of using the Internet of Things in Iranian hospitals (according to experts) was established during the completion of a two-round Delphi. In the last phase, a novel model for implementing the IoT in Iranian hospitals was proposed. The identified primary model consisted of six groups, namely privacy and security, Big data, hardware, network, software, and organizational-cultural and environmental issues with 78 challenges. Out of the 78 identified challenges, 46 were approved by experts as essential elements for providing IoT patterns in Iranian hospitals. The highest and lowest averages were related to the subgroups "Failure to provide regular IoT rules and programs by governments" and "Absence of single, integrated and efficient platforms with high data transfer capacity and fast processing", respectively. The final model for implementing IoT in Iranian hospitals was designed and presented using Edraw Max10.0. 4+Portable software. Providing this model can provide a sufficient basis, information and knowledge for policymakers, government authorities and managers of organizations to use the IoT in hospitals of Iran and other countries. Also, the application of the proposed model can result in the improved special capabilities in the realm of system design, and offer grounds for saving time and money as well as reducing failures in the initial design of IoT projects.
Plasma-induced micro breakdown in small-area MOSFETs

We investigated the impact of latent plasma-induced damage (PID) on the reliability of nMOSFETs with small gate area and gate-oxide thickness of 3.2 nm. To this purpose, we stressed 1500 devices with different antenna areas by using a staircase-like stress voltage and by monitoring the gate leakage at the gate voltage V/sub G/=+2 V. The stress was always stopped because of an abrupt jump in the gate current. The statistics obtained for the breakdown current are characterized by two different oxide-breakdown modes. The first is the well-known hard breakdown (HB), while the second one, which we called micro breakdown (MB), can be modeled as a double trap-assisted tunneling (D-TAT) mechanism and is characterized by a very small leakage current (around 100 pA at the gate voltage V/sub G/=2 V). In devices with large antenna, i.e., more prone to be damaged by plasma processing, the number of microbroken oxides is larger and breakdown occurs at lower voltages than in reference devices (non plasma damaged). Conversely, the hard breakdown statistics shows only a weak dependence on the gate antenna ratio of plasma damaged devices. This has been explained by considering the intrinsic nature of latent plasma-induced oxide defects, linked to the different generation mechanisms involved in micro breakdown and hard breakdown phenomena.
Aspects of collaborative social learning in the Australian Defence Force

The Enterprise Social Learning Architectures (ESLA) is investigating collaborative social learning within the Australian Defence Organisation (ADO). Processes that help to understand social learning within the strategic environment of the ADO are described. Although the paper deals with the defence environment, the findings can be generalised to other organisational settings, as it deals with understanding the issues inherent in building sustainable and adaptive learning organisations.
Full-Wave Sense-FET-Based Inductor-Current Sensor With Wide Dynamic Range for Buck Converters

This brief presents a full-wave inductor current sensor with wide dynamic range for buck converters. To extend the effective sensing range to zero or even negative current, an offset current is superimposed on the sensed inductor current. Besides, the adaptive-bias generator is applied to the proposed sensor with the aim to further suppress the variations of bandwidth and phase margin across the wide dynamic sensing range. Moreover, the seamless current sensing approach is introduced to achieve the smooth sensing waveform through the whole switching cycle. A buck converter with the proposed current sensor has been fabricated in a 0.18- $\mu \text{m}$ standard CMOS process. Compared with the fixed-biased counterpart, the loop bandwidth variation of the proposed sensor is merely 3.3 MHz across the current range from −200 mA to 1.2 A. Measurement results show that the response time is less than 20 ns for various loads and no glitches appear at the sensed current.
A new optical fibre sensor to assess the stability of geogrid-reinforced soil walls

ABSTRACT: It is not easy to assess the stability of vertical soil walls reinforced by geogrids during and after construction. This paper describes a unique monitoring system called an ‘optical fibre sensor geogrid' in which an optical fibre sensor is installed within a longitudinal member of a geogrid reinforcement material. The structure of the optical fibre sensor and the measuring method to record strain in the geogrid are described. Laboratory tests were first carried out to assess the accuracy of geogrid strain measurements using the optical fibre sensor method. Optical fibre sensor geogrids were then used to measure the strain in embedded geogrid layers in three reinforced soil walls constructed in the field. The system allows the stability of reinforced soil walls to be monitored continuously during and after construction, and a stability evaluation index to be assigned to the walls based on peak strain readings.
High throughput hemogram of T cells using digital holographic microscopy and deep learning

T cells of the adaptive immune system provide effective protection to the human body against numerous pathogenic challenges. Current labelling methods of detecting these cells, such as flow cytometry or magnetic bead labelling, are time consuming and expensive. To overcome these limitations, the label-free method of digital holographic microscopy (DHM) combined with deep learning has recently been introduced which is both time and cost effective. In this study, we demonstrate the application of digital holographic microscopy with deep learning to classify the key CD4+ and CD8+ T cell subsets. We show that combining DHM of varying fields of view, with deep learning, can potentially achieve a classification throughput rate of 78,000 cells per second with an accuracy of 76.2% for these morphologically similar cells. This throughput rate is 100 times faster than the previous studies and proves to be an effective replacement for labelling methods.
Preventing and Overcoming Resistance to PARP Inhibitors: A Focus on the Clinical Landscape

Simple Summary PARP inhibitors (PARPi) are current treatment options for patients with ovarian, breast, pancreatic or prostate cancer. Although PARPi have transformed the patient journey in these disease settings, resistance eventually develops, leaving them with limited therapeutic opportunities. In this review, we summarize the mechanisms of resistance to PARPi described in pre-clinical models, focusing on the most clinically relevant and proposing ways to tackle them. Abstract Poly(ADP-ribose) polymerase (PARP) inhibitors (PARPi) are now a first-line maintenance treatment in ovarian cancer and have been approved in other cancer types, including breast, pancreatic and prostate. Despite their efficacy, and as is the case for other targeted therapies, resistance to PARPi has been reported clinically and is generating a growing patient population of unmet clinical need. Here, we discuss the mechanisms of resistance that have been described in pre-clinical models and focus on those that have been already identified in the clinic, highlighting the key challenges to fully characterise the clinical landscape of PARPi resistance and proposing ways of preventing and overcoming it.
Compensating Gordon-Mollenauer phase noise by midlink optical phase conjugation for long-haul 40Gb/s CO-OFDM systems

Midlink optical phase conjugation (OPC) based on four wave mixing (FWM) in semiconductor optical amplifier (SOA) can be used to compensate for the nonlinearity phase noise, Gordon-Mollenauer effect, in CO-OFDM long-haul systems. Simulation of 40Gb/s CO-OFDM systems without optical dispersion compensation is presented and the Q factor can be increased by >6 dB through OPC.
Hypertension Control and Guideline-Recommended Target Blood Pressure Goal Achievement at an Early Stage of Hypertension in the UAE

(1) Background: The present study aimed to assess the changes in blood pressure (BP) within the first 6 months of treatment initiation in a newly treated hypertensive cohort and to identify the factors that are associated with achieving the target BP recommended by the American (ACC/AHA, 2017), European (ESC/ESH, 2018), United Kingdom (NICE, 2019), and International Society of Hypertension (ISH, 2020) guidelines. (2) Methods: We analyzed 5308 incident hypertensive outpatients across Abu Dhabi, United Arab Emirates (UAE), in 2017; each patient was followed up for 6 months. Hypertension was defined as a BP of 130/80 mmHg according to the ACC/AHA guidelines and 140/90 mmHg according to the ESC/ESH, NICE, and ISH guidelines. Multiple logistic regression was used to identify factors associated with achieving the guideline-recommended BP targets. (3) Results: At baseline, the mean BP was 133.9 ± 72.9 mmHg and 132.7 ± 72.5 mmHg at 6 months. The guideline-recommended BP targets were 39.5%, 43%, 65.6%, and 40.8%, according to the ACC/AHA, ESC/ESH, NICE, and ISH guidelines, respectively. A BMI of <25 kg/m2 was associated with better BP control according to the ACC/AHA (odds ratio (OR) = 1.26; 95% confidence interval (CI) = 1.07–1.49), ESC/ESH (OR = 1.27; 95% CI = 1.08–1.50), and ISH guidelines (OR = 1.22; 95% CI = 1.03–1.44). Hypertension treated in secondary care settings was more likely to achieve the BP targets recommended by the ACC/AHA (1.31 times), ESC/ESH (1.32 times), NICE (1.41 times), and ISH (1.34 times) guidelines. (4) Conclusions: BP goal achievement was suboptimal. BP control efforts should prioritize improving cardiometabolic goals and lifestyle modifications.
Exploring the Nature of the Antimicrobial Metabolites Produced by Paenibacillus ehimensis Soil Isolate MZ921932 Using a Metagenomic Nanopore Sequencing Coupled with LC-Mass Analysis

The continuous emergence of multidrug-resistant (MDR) pathogens poses a global threat to public health. Accordingly, global efforts are continuously conducted to find new approaches to infection control by rapidly discovering antibiotics, particularly those that retain activities against MDR pathogens. In this study, metagenomic nanopore sequence analysis coupled with spectroscopic methods has been conducted for rapid exploring of the various active metabolites produced by Paenibacillus ehimensis soil isolate. Preliminary soil screening resulted in selection of a Gram-positive isolate identified via 16S ribosomal RNA gene sequencing as Paenibacillus ehimensis MZ921932. The isolate showed a broad range of activity against MDR Gram-positive, Gram-negative, and Candida spp. A metagenomics sequence analysis of the soil sample harboring Paenibacillus ehimensis isolate MZ921932 (NCBI GenBank accession PRJNA785410) revealed the presence of conserved biosynthetic gene clusters of petrobactin, tridecaptin, locillomycin (β-lactone), polymyxin, and macrobrevin (polyketides). The liquid chromatography/mass (LC/MS) analysis of the Paenibacillus ehimensis metabolites confirmed the presence of petrobactin, locillomycin, and macrobrevin. In conclusion, Paenibacillus ehimensis isolate MZ921932 is a promising rich source for broad spectrum antimicrobial metabolites. The metagenomic nanopore sequence analysis was a rapid, easy, and efficient method for the preliminary detection of the nature of the expected active metabolites. LC/MS spectral analysis was employed for further confirmation of the nature of the respective active metabolites.
‘Heart-like’ cross-sectional shape can better improve the hemodynamics in spiral laminar flow graft for small-caliber bypass application: a numerical study

Abstract Small-caliber grafts remain disappointed in the long-term bypass surgeries of coronary and peripheral arterial diseases. In order to improve the hemodynamics in small-caliber artery bypass grafts (ABGs), an improved spiral laminar flow (improved-SLF) graft with a ‘heart-like’ cross-sectional shape was proposed and verified by computational fluid dynamics simulation in this study. The results show that such graft can indeed induce a spiral flow and enhance the WSS distribution on the graft section. Furthermore, the helically distributed ribbon of unfavorable WSS observed in the original SLF graft was eliminated in the improved-SLF graft due to its smoothed and gentle helical ridge. On the other hand, improved-SLF ABG improved the WSS distribution in the distal anastomosis as well, because it maintained the strength of spiral flow when entering the anastomosis region. Finally, the improved-SLF ABG slightly increased the pressure drop along the bypass due to its small change of the general graft structure. As a proof-of-concept study, it can be concluded that improved-SLF graft can not only evenly enhance the WSS distribution in the graft section, but also improve the hemodynamic environment in the distal anastomosis without significantly increasing the pressure drop along the bypass, indicating such new helical-type graft may be more suitable to be used in the small-caliber graft bypass surgeries.
Towards a conceptual model for online group work - addressing graduate skills development in online courses

In moving towards what Lemke (1996) terms the 'interactive learning paradigm', higher education has adopted group learning technologies as both the means and ends by which graduate attributes and group skills are evidenced and developed. In this light, learning is mediated by (and occurs through) language (Falk 1997; Gee 1997), and is distributed across a managed (but growing) range of people, sites, objects, technologies and time (Gee 1997). This paper details a more recent principle that has emerged in the form of flexible (anywhere, anyplace, anytime) learning that seems to fly in the face of accepted views of group learning technologies. Many universities now choose to offer ‘learning resources’ flexibly online. This paper describes the distribution architecture that enables this to happen, the discourses that drive it, and the limitations that plague it. In short, the paper examines whether Information and Communication Technologies (ICTs) are ‘robust’ enough to support, sustain and address industry, employer and government calls for greater attention to group skills development in university graduates. Data features an examination of respondent feedback (n=171) in an ‘online’ group work setting, and their subsequent ratings of group skills development over a 13 week period. This discussion offers an account of learner outcomes by adopting Kirkpatrick’s (1996) four levels of evaluation of learning as a classification scheme for determining learner satisfaction (Level One), the effectiveness of group skills learning transfer (Level Two), its impact on team practices (Level Three) and the appropriation of learning behaviours by group participants (Level Four). Data points to the need for an interactive model of group skills development that focuses on “the demands of the new world environment” (Blasi & Heinecke, 2000, p5), and that is capable of recognising new social presence and the production of social categories online.
Fiber-optic parametric amplifiers: Their advantages and limitations

Fiber-optic parametric amplifiers (FOPAs) can be used in lightwave systems for several signal-processing applications including optical amplification, phase conjugation, and wavelength conversion. In principle, FOPAs can provide high gain uniform over a wide wavelength range (> 100 nm). What is more, FOPAs add little noise to the amplified signal. FOPAs can have noise figure as low as 0 dBwhen operated in the phase-sensitive mode and 3 dB in the phase insensitive mode. However, in practice, these advantages of FOPAs are compromised. In this work, I investigate several factors that limit the performance of FOPAs, and propose practical schemes to minimize those limitations. FOPAs can provide a relatively large gain bandwidth because the gain spectrum of FOPAs is not determined by material resonances but by the phase-matching condition. For the same reason, FOPAs are very sensitive to perturbations stemming from fiber irregularities. One such irregularity is that fiber dispersion varies randomly along the fiber length. My numerical modeling showed that, because of such variations, FOPA gain spectrum cannot maintain its flatness and also that FOPA gain profile changes from one fiber to the other. Using stochastic methods, an analytic theory is developed that can predict an “average gain spectrum. ” This analytic theory can be used to show that flatness of FOPA gain is recovered at the expense of reducing the gain bandwidth. Another fiber irregularity that affects FOPA gain spectrum is the residual birefringence. During the fiber-drawing process, the cross section of fiber core inevitably deviates from perfect circular symmetry. As a result, all non-polarization maintaining fibers exhibit residual birefringence. Both the magnitude of birefringence and the direction of
Bit-serial realizations of a class of nonlinear filters based on positive Boolean functions

It is shown that the function of a stack filter can be realized in k-step recursive use of one binary processing circuit. The time-area complexity of the proposed filter is O(k) as compared with O(2/sup k/) for stack filters. The proposed digital realizations are simple and modular in structure, and suitable for VLSI implementation. Analog/digital (A/D) hybrid realizations have the advantage that there is no need for an A/D converter array when the original signals come from an integrated sensor array. An experimental digital rank-order filter with a window size of three and arbitrary number of input bits is designed and implemented in a 3- mu m double-metal polysilicon gate CMOS process. The chip has been fabricated and measurement results are correct with a clock frequency of up to 110 MHz. >