Miracle-dz/UniFAR-FTUs huggingface dataset:
Controlled charge extraction—antiblooming capabilities in pnCCD imaging sensors

Blooming in a CCD occurs when the signal charges accumulating in a pixel exceed the pixel saturation level and spill over into adjacent pixels. They start to spill over the weakest threshold in the electric potential of the pixel structure resulting in a degradation of the spatial information. With antiblooming mechanisms, the spatial resolution of the incoming photons can be preserved, but the intensity information is lost in the overflowing pixels. For imaging experiments, relying on a precise image structure, the preservation of the spatial resolution at the expense of precise intensity information is a workable compromise. In contrast to insulated gate CCDs, notably MOSCCDs, the potential wells of the pixel array of a pnCCD are created by p+n junctions, allowing direct electric access to the pixel structure. This allows to directly drain off charges from the pixels and to define a drain level by applying the appropriate operation voltages. Charge packets from 1 000 to more than one billion signal electrons per readout frame were generated without observing a spillover into adjacent pixels. As soon as the saturation level of the pixel is reached, the excess charge carriers are removed through charge drains exclusively created with the modification of the electric potential of the pnCCD by the operation voltages. No additional antiblooming structures were implemented in the device and the pixel full well capacity of approximately 300 000 electrons in standard operation mode was preserved. A physical model of the antiblooming mechanism of pnCCDs with a pixel size of 75 μ m × 75 μ m was established by two-dimensional numerical device simulations and verified by experiments.
Solvo/hydrothermal upcycling of polyethylene plastic-waste into carbon-based nanocomposite for supercapacitor application

One of the most worrying environmental issues affecting all forms of life, the economy, and natural ecosystems globally is the accumulation of polyethylene (PE) plastic garbage. Creating peaceful and environmentally friendly alternatives to conventional disposal techniques, like transforming plastic waste into cherished carbonaceous nanomaterials, is of utmost importance considering this threat. The current study carefully employed a cleaner upcycling technique to create carbon-based nanomaterials (CNMs) for supercapacitors. Using solvothermal/hydrothermal synthetic techniques, the PE waste was transformed into CNMs used in energy storage supercapacitors application. With an energy density of 21.6 W h kg−1 and a current density of 0.25 A g−1, the electrochemical test showed a specific capacitance of 155.5 F g−1. Additionally, the materials demonstrated 98.5% capacitance retention after 9000 cycles at a constant current density of 1.0 A g−1. Abbreviations: AC: activated carbon; CNM: carbon nanomaterials; CV: cyclic voltammetry; EC: electrochemical system; EDLC: electrical double layer capacitor; EIS: electrochemical impedance spectroscopy; FESEM: field emission scanning electron microscopy; FTIR: Fourier transform infrared; GCD: galvanostatic charge–discharge; HDPE: high-density polyethene; KOH: potassium hydroxide; LLDPE: linear low-density polyethene; Mn: manganese; PE: polyethene; Rct: charge transfer resistance; SSA: specific surface area; TEM: transmission electron microscopy; TGA: thermogravimetric analysis; UV–VIS: ultraviolet–visible spectroscopy; XRD: X-ray diffraction Highlights The article explored a low-temperature and non-emission upcycling method of polyethylene plastic waste into carbon-based nanomaterials (CNMs). CNMs were characterised for physical–chemical properties using different characterisation techniques. The carbon material was used with other materials like activated carbon and manganese to produce nanocomposites tested for electrical double layer capacitor energy storage and exhibited higher energy density.
A Review of Machine Learning for Convective Weather

We present an overviewof recentwork on using artificial intelligence/machine learning techniques for forecasting convective weather and its associated hazards, including tornadoes, hail, wind, and lightning. These high-impact phenomena globally cause both massive property damage and loss of life yet they are quite challenging to forecast. Given the recent explosion in developing machine learning techniques across the weather spectrum and the fact that the skillful prediction of convective weather has immediate societal benefits, we present a thorough review of the current state of the art in artificial intelligence and machine learning techniques for convective hazards. Our review includes both traditional approaches, including support vector machines and decision trees as well as deep learning approaches. We highlight the challenges in developing machine learning approaches to forecast these phenomena across a variety of spatial and temporal scales. We end with a discussion of promising areas of future work for ML for convective weather, including a discussion of the need to create trustworthy AI forecasts that can be used for forecasters in real-time and the need for active cross-sector collaboration on testbeds to validate machine learning methods in operational situations.
Enhanced Understanding of MHD Dynamics & ELM Control Physics via 2D/3D ECE Imaging in KSTAR

Enhanced physical understanding of the nature of the Edge Localized Mode (ELM) instability in the H-mode regime of toroidal plasmas requires advanced diagnostic tools to visualize their dynamics. A high spatial and temporal resolution 2-D Electron Cyclotron Emission Imaging (ECEI) system [1] was utilized successfully characterize the real time dynamics of ELMs [2] including the growth, saturation and bursting process of this instability during two campaigns (2010 and 2011) of the Korean Superconducting Tokamak Advanced Research (KSTAR) device. The measured ELMs are validated with the synthetic images based on numerical simulations.
New Application to Microstrip Antennas with Metamaterial Substrates

The propagation characteristics of the rectangular microstrip patch antenna on metamaterial substrate are determined via full wave method, Transverse Transmission Line – TTL. Compared to other full wave methods, the TTL is an efficient tool to determine the resonant frequency, making possible a significant algebraic simplification of the equations involved in the process. Numerical results of resonant frequencies and return loss are found as functions of the metamaterial properties.
Semiconductor lasers with a continuous tuning range above in the nearest IR spectral region

We have developed two new types of lasers based on quantum-confined semiconductor optical amplifiers with an acousto-optic tunable filter in an external fibre ring cavity. The lasers offer continuous wavelength tuning ranges from 780 to 885 and from 880 to of cw output power, and a tuning rate up to at an instantaneous spectral linewidth less than .
Bouts d'un groupe opérant sur la droite, I : théorie algébrique

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ON BALANCED PRODUCTS OF DISTRIBUTIONS IN COLOMBEAU ALGEBRA

Results on singular products of Schwartz distributions on the Eu- clidean space R m are derived when the products are so 'balanced' that they exist in the distribution space. The results follow the idea of a known distribu- tional product introduced by Jan Mikusinski and are obtained in the Colombeau algebra of generalized functions. This algebra contains the distributions and the notion of 'association' permits obtaining results on the level of distributions.
New Stability Condition for Positive Switched Linear Systems

This paper addresses the asymptotic stability problem of positive switched linear systems under arbitrary switching signals. The main contribution of this paper lies in the following two aspects. First, a stability condition is derived for positive switched linear systems, which can be considered as a complement to the well known result in this field. Second, the method used in this paper is new, and it is helpful for studying the stability problems of various delayed systems. A numerical example illustrates the obtained result.
Chemically Synthesized AgNPs and Piriformospora indica Synergistically Augment Nutritional Quality in Black Rice

The use of biofertilizers has been the spotlight of research aiming to mitigate the food security threat as well as to restore the fertility of agricultural lands, for decades. Several studies are being conducted to unravel the role and mechanisms of plant growth-promoting microbes. In the present research, we evaluated the effect of silver nanoparticles (AgNPs) and Piriformospora indica on the growth and nutritional enhancement of black rice (Oryzae sativa. L.) individually and in combination. Among the different treatment conditions, the AgNPs + P. indica treatment led to a significant (p ≤ 0.05) increase in morphological and agronomic parameters. In comparison to the control, the percentage increase in plant height in AgNPs-treated black rice was 2.47%, while that for the treatment with only P. indica was 13.2% and that for the treatment with both AgNPs + P. indica was 30.9%. For the number of productive tillers, the effect of AgNPs in comparison to the control was non-significant; however, the effect of P. indica and AgNPs + P. indica showed a significant (p ≤ 0.05) increase of 13.2% and 30.9% in both the treatments, respectively. Gas chromatography mass spectrophotometry analysis of grains revealed that the contents of phenylalanine, tryptophan, and histidine (aromatic amino acids) were significantly (p ≤ 0.05) increased by 75%, 11.1%, and 50%, respectively, in P. indica-treated black rice. Nutrient profiling showed that macronutrients such as potassium, calcium, magnesium were found to be increased by 72.8%, 86.4% and 59.2%, respectively, in the treatment with AgNPs + P. indica in comparison to the control plants. Additionally, a significant (p ≤ 0.05) increase of 51.9% in anthocyanin content was observed in AgNPs + P. indica-treated black rice. The P. indica treatment also showed improved growth and augmented nutrient contents. From this study, we were able to understand that AgNPs + P. indica treatment would be a better plant growth-promoting factor and further evaluation would enable us to obtain a clear picture of its mechanisms of action.
A point base appraisal of fuzzy edge detection techniques in computer vision

Edge detection techniques play a vital role in performing computer vision tasks, especially in image processing. Nowadays the accuracy and power of the computer, it has received much attention of the research communities. Many researchers established the various fuzzy edge detection techniques, but still it is a challenging task of the researcher to detect the true edges completely from an image/blurred image. This paper discussed the recently entrenched edge detectors with their characteristics. Also, the accuracy of these edge detectors has been carried out in the context of the detection in a given image and the speed with the help of MATLAB software
Modeling the Transimpedance Amplitude and Phase of Wideband Cage-Type Current Shunts

The model for current shunts which was successfully applied in a previous work for frequencies up to 100 kHz is expanded here to compute the shunt transimpedance amplitude and phase for frequencies up to 10 MHz. The model is employed to verify recent experimental findings in this frequency range aiming at predicting/explaining such evidence. In general, there is good agreement for phase in the whole frequency range. Some differences between measured and predicted values do exist for amplitude but they are all within the uncertainties reported in the literature. Anyway, they deserve further investigation. Despite further work being needed to clarify matters, the model will be used in the design of such shunts for wideband applications.
Explainable Intrusion Detection for Cyber Defences in the Internet of Things: Opportunities and Solutions

The field of Explainable Artificial Intelligence (XAI) has garnered considerable research attention in recent years, aiming to provide interpretability and confidence to the inner workings of state-of-the-art deep learning models. However, XAI-enhanced cybersecurity measures in the Internet of Things (IoT) and its sub-domains, require further investigation to provide effective discovery of attack surfaces, their corresponding vectors, and interpretable justification of model outputs. Cyber defence involves operations conducted in the cybersecurity field supporting mission objectives to identify and prevent cyberattacks using various tools and techniques, including intrusion detection systems (IDS), threat intelligence and hunting, and intrusion prevention. In cyber defence, especially anomaly-based IDS, the emerging applications of deep learning models require the interpretation of the models’ architecture and the explanation of models’ prediction to examine how cyberattacks would occur. This paper presents a comprehensive review of XAI techniques for anomaly-based intrusion detection in IoT networks. Firstly, we review IDSs focusing on anomaly-based detection techniques in IoT and how XAI models can augment them to provide trust and confidence in their detections. Secondly, we review AI models, including machine learning (ML) and deep learning (DL), for anomaly detection applications and IoT ecosystems. Moreover, we discuss DL’s ability to effectively learn from large-scale IoT datasets, accomplishing high performances in discovering and interpreting security events. Thirdly, we demonstrate recent research on the intersection of XAI, anomaly-based IDS and IoT. Finally, we discuss the current challenges and solutions of XAI for security applications in the cyber defence perspective of IoT networks, revealing future research directions. By analysing our findings, new cybersecurity applications that require XAI models emerge, assisting decision-makers in understanding and explaining security events in compromised IoT networks.
Application of Composite Biomaterials from Chinese Herbal Medicine in the Field of Bone Tissue Engineering

Research into bone tissue engineering is increasing with advances in biomaterials. Natural products of plant origin have exciting therapeutic effects through multiple targets. The purpose of this article is to review the outstanding performance of herbal-derived natural products in bone tissue engineering. We have categorized herbal-derived natural products that exert different effects in bone tissue engineering into osteogenic, vascular, chondrogenic, anti-inflammatory and antibacterial. Natural products of plant origin are readily available and can be combined with biomaterials as bioactive molecules to complement each other and provide additional opportunities for bone tissue engineering. Finally, we discuss the challenges and opportunities for the development of plant composite biomaterials for bone tissue engineering and highlight emerging strategies in this field.
Direct Nanopore Sequencing of Human Cytomegalovirus Genomes from High-Viral-Load Clinical Samples

Nanopore sequencing is becoming increasingly commonplace in clinical settings, particularly for diagnostic assessments and outbreak investigations, due to its portability, low cost, and ability to operate in near real-time. Although high sequencing error rates initially hampered the wider implementation of this technology, improvements have been made continually with each iteration of the sequencing hardware and base-calling software. Here, we assess the feasibility of using nanopore sequencing to determine the complete genomes of human cytomegalovirus (HCMV) in high-viral-load clinical samples without viral DNA enrichment, PCR amplification, or prior knowledge of the sequences. We utilised a hybrid bioinformatic approach that involved assembling the reads de novo, improving the consensus sequence by aligning reads to the best-matching genome from a collated set of published sequences, and polishing the improved consensus sequence. The final genomes from a urine sample and a lung sample, the former with an HCMV to human DNA load approximately 50 times greater than the latter, achieved 99.97 and 99.93% identity, respectively, to the benchmark genomes obtained independently by Illumina sequencing. Thus, we demonstrated that nanopore sequencing is capable of determining HCMV genomes directly from high-viral-load clinical samples with a high accuracy.
Exploring the Functional Roles of Telomere Maintenance 2 in the Tumorigenesis of Glioblastoma Multiforme and Drug Responsiveness to Temozolomide

Glioblastoma multiforme (GBM) is a grade IV human glioma. It is the most malignant primary central nervous system tumor in adults, accounting for around 15% of intracranial neoplasms and 40–50% of all primary malignant brain tumors. However, the median survival time of GBM patients is still less than 15 months, even after treatment with surgical resection, concurrent chemoradiotherapy, and adjuvant chemotherapy with temozolomide (TMZ). Telomere maintenance 2 (TELO2) mRNA is highly expressed in high-grade glioma patients, and its expression correlates with shorter survival outcomes. Hence, it is urgent to address the functional role of TELO2 in the tumorigenesis and TMZ treatment of GBM. In this study, we knocked down TELO2 mRNA in GBM8401 cells, a grade IV GBM, compared with TELO2 mRNA overexpression in human embryonic glial SVG p12 cells and normal human astrocyte (NHA) cells. We first analyzed the effect of TELO2 on the Elsevier pathway and Hallmark gene sets in GBM8401, SVG p12, and NHA via an mRNA array analysis. Later, we further examined and analyzed the relationship between TELO2 and fibroblast growth factor receptor 3, cell cycle progression, epithelial–mesenchymal transient (EMT), reactive oxygen species (ROS), apoptosis, and telomerase activity. Our data showed that TELO2 is involved in several functions of GBM cells, including cell cycle progression, EMT, ROS, apoptosis, and telomerase activity. Finally, we examined the crosstalk between TELO2 and the responsiveness of TMZ or curcumin mediated through the TELO2–TTI1–TTI2 complex, the p53-dependent complex, the mitochondrial-related complex, and signaling pathways in GBM8401 cells. In summary, our work provides new insight that TELO2 might modulate target proteins mediated through the complex of phosphatidylinositol 3-kinase-related kinases in its involvement in cell cycle progression, EMT, and drug response in GBM patients.
Aging of Malbec Wines from Mendoza and California: Evolution of Volatile Composition

The search for strategies to improve the quality of Argentine Malbec wines has led to experimentation with production of wines that achieve superior sensory properties after prolonged bottle aging. During aging, a series of complex oxidation-reduction and polymerization reactions occur. These reactions, responsible for changing the sensory aspects of wines, can be influenced by a variety of factors (terroir, winemaking practices, storage conditions, etc.). Thus, understanding the chemical processes that take place during bottle aging could significantly impact the enol-ogy industry. This work evaluates the evolution of aromatic profiles over time in Malbec wines from Mendoza and California.
Abnormal Two-Stage Degradation Under Hot Carrier Injection With Lateral Double-Diffused MOS With 0.13-μm Bipolar-CMOS-DMOS Technology

In this work, the issue of abnormal two-stage hot carrier injection (HCI) degradation in n-type lateral double-diffused MOS (LDMOS) transistors is explored. The degradation mechanism is divided into two stages. The first stage is the electron injection into the interface layer (IL) caused by the impact ionization that occurs under the contact field plate (CFP), resulting in the degradation of the ON-current (<inline-formula> <tex-math notation="LaTeX">${I}_{\text {on}}{)}$ </tex-math></inline-formula>. The second stage of deterioration is the positive bias temperature instability (PBTI) effects caused by Joule heating, which leads to defects in the SiO<sub>2</sub>/Si interface, and injects electrons in the channel into SiO<sub>2</sub>, which increases the subthreshold swing (S.S) of the device and causes the threshold voltage (<inline-formula> <tex-math notation="LaTeX">${V}_{\text {th}}{)}$ </tex-math></inline-formula> to shift. It has been proved by temperature variation experiments and technology computer-aided design (TCAD) simulations that HCI will indeed produce severe PBTI effects and lead to device degradation during long-term HCI.
Functional Biomaterials for Local Control of Orthodontic Tooth Movement

Orthodontic tooth movement (OTM) occurs with the application of a controlled mechanical force and results in coordinated tissue resorption and formation in the surrounding bone and periodontal ligament. The turnover processes of the periodontal and bone tissue are associated with specific signaling factors, such as Receptor Activator of Nuclear factor Kappa-β Ligand (RANKL), osteoprotegerin, runt-related transcription factor 2 (RUNX2), etc., which can be regulated by different biomaterials, promoting or inhibiting bone remodeling during OTM. Different bone substitutes or bone regeneration materials have also been applied to repair alveolar bone defects followed by orthodontic treatment. Those bioengineered bone graft materials also change the local environment that may or may not affect OTM. This article aims to review functional biomaterials that were applied locally to accelerate OTM for a shorter duration of orthodontic treatment or impede OTM for retention purposes, as well as various alveolar bone graft materials which may affect OTM. This review article summarizes various types of biomaterials that can be locally applied to affect the process of OTM, along with their potential mechanisms of action and side effects. The functionalization of biomaterials can improve the solubility or intake of biomolecules, leading to better outcomes in terms of increasing or decreasing the speed of OTM. The ideal timing for initiating OTM is generally considered to be 8 weeks post-grafting. However, more evidence is needed from human studies to fully understand the effects of these biomaterials, including any potential adverse effects.