Applications For Many Years Research Articles

Optically stimulated luminescence detectors for LET determination and dosimetry in ion beam therapy

Optically stimulated luminescence detectors (OSLDs) have been utilized for various dosimetry applications for many years. The use of Al2O3:C OSLDs for proton dosimetry began over a decade ago, taking advantage of the correlation between the ionization density of the radiation field and the ratio of intensities of the material’s two emission bands. The correlation allows for determining both linear energy transfer (LET) and dose in proton beams, with corrections for ionization quenching derived from the LET. However, the previous methodology for proton dosimetry and simultaneous LET determination with Al2O3:C OSLDs was cumbersome and occasionally associated with large uncertainties, while carbon beam dosimetry posed further challenges due to an elevated LET.This paper reviews the recent advancements in ion beam dosimetry and LET determination using OSLDs. Employing Al2O3:C,Mg OSLDs alongside improved, automatized read-out techniques, and the use of other radiation quality metrics than averaged LET, has removed most of the previous obstacles for ion beam dosimetry with OSLDs.The feasibility of simultaneous LET determination and dosimetry in ion beams is demonstrated through two case studies involving realistic proton and carbon ion therapy scenarios.

Regulation of both Bulk and Surface Structure by W/S Co‐Doping for Li‐Rich Layered Cathodes with Remarkable Voltage and Capacity Stability

AbstractLithium‐rich layered oxides (LLOs) have gained significant attention due to their high capacity of over 250 mAh g−1, which originates from the charge compensation of oxygen anions activated under high voltage. However, the charge compensation of oxygen anions is prone to over‐oxidation, leading to serious irreversible oxygen release, surface‐interface reactions, and structural evolution. These detriments make LLOs undergo fast voltage decay and capacity fading, which have hindered their practical applications for many years. Herein, this work develops a multifunctional co‐doping strategy and constructs W─O bonds with strong bonding interaction and covalence, low bond energy Li─S bonds with non‐binding electrons near the Fermi level, and continuous and homogeneous surface spinel‐like layer induced by W/S co‐doping. Their synergistic effect significantly mitigates the irreversible oxygen release and surface‐interface reactions and improves structural stability of Li‐rich layered cathodes. Thus, the designed and prepared Co‐free Li‐rich layered cathode (Li1.232Mn0.574Ni0.191W0.003O1.995S0.005) delivers superior voltage and capacity stability. Its capacity retention after 400 cycles is as large as 86%, and its voltage decay rate from the 10th to the 400th cycle is only 0.626 mV cycle−1.

Reconfigurable Cellulose Acetate‐Based Thermosets Cross‐Linked with Diboronic Acid

AbstractCellulose acetate (CA) has found broad applications for many years. However, the development of mechanically strengthened CA materials without losing the processibility in solution remains quite difficult. In this work, novel CA thermosets are reported that can be readily constructed by employing alkyl diboronic acid as a crosslinking agent, which has allowed convenient reconfiguration of CA networks without demanding catalysts or harsh processing conditions. Various properties including thermal stability, creeping resistance, rheological and mechanical strength have been successfully improved by using small amounts (1–5 wt%) of diboronic acid. The dynamic cross‐linked network based on boron chemistry has facilitated solution processing during three times of recycling. Control experiments have shown that alkyl diboronic acid can deliver superior mechanical strength to CA as compared to aryl diboronic acid or single‐arm alkyl boronic acid. Based on the importance of CA materials, this work should be attractive to the design of reprocessible CA thermosets with high performance.

A Low-Cost Low-Power LoRa Mesh Network for Large-Scale Environmental Sensing

Sustainability and climate monitoring efforts create a need for long-term in-situ sensing of large geographic areas. However, environmental monitoring in remote areas of developing countries remains impeded by a lack of low-cost, scalable IoT solutions. Whereas IoT systems for in-situ sensing abound, they mostly are either low-cost or suitable for large areas, but not both. In this paper, we present a low-cost low-power network solution for in-situ sensing of areas up to hundreds of square kilometers. Taking advantage of LoRa technology, we develop a self-organizing mesh network that can be scaled to a hundred and more nodes. Scalability is achieved by developing methods that mitigate packet collisions during data collection. We present a protocol, called CottonCandy, with which nodes self-organize in a spanning-tree network topology in a distributed fashion. A power profile on a custom-built circuit board shows that CottonCandy nodes can run thousands of duty cycles on 2 AA batteries, sufficient to operate for years in many applications. Using off-the-shelf components, the cost of a CottonCandy node is less than US-$ 15. Evaluations by simulation show that CottonCandy networks with 100 nodes achieve a packet delivery ratio of >90%. Measurements of an outdoor deployment with 15 nodes corroborate the high packet delivery ratio in a real-life setting.

Server-side Cross-site Scripting Detection Powered by HTML Semantic Parsing Inspired by XSS Auditor

Cross-site Scripting attacks have been a perennial threat to web applications for many years. Conventional practices to prevent cross-site scripting attacks revolve around secure programming and client-side prevention techniques. However, client-side preventions are still prone to bypasses as the inspection is done on the user’s browser, so an adversary can alter the inspection algorithm to come up with the bypasses or even manipulate the victim to turn off the security measures. This decreases the effectiveness of the protection and leads to many web applications are still vulnerable to cross-site scripting attacks. We believe that XSS Auditor, which was pre-installed in Google Chrome browser for more than 9 years, is a great approach in combating and preventing XSS attacks. Hence, in this paper, we proposed a novel approach to thoroughly identify two types of cross-site scripting attacks through server-side filter implementation. Our proposed approach follows the original XSS Auditor mechanism implemented in Google Chrome. However, instead of placing the detection system on the client side, we design a detection mechanism that checks HTTP requests and responses as well as database responses for possible XSS attacks from the server side. From 500 payloads used to evaluate the proposed method, 442 payloads were classified correctly, thus showing that the proposed method was able to reach 88.4% accuracy. This work showed that the proposed approach is very promising in protecting users from devastating Cross-site Scripting attacks.

LIDAR ASSESSMENTS AND MAPPING FOR KLANG VALLEY: A CASE STUDY AT JINJANG DISTRICT, SELANGOR

Abstract. Light Detection and Ranging (LiDAR) technology has become a significant factor in producing up-to-date and accurate topographic data in the current world. LiDAR technology has been used for years for many applications, including the efficient creation of digital model for large scale, high accuracy mapping. This technology offers fast, accurate, expedient and cost-effective ways of capturing wide area elevation information to produce highly detailed digital model of the earth. LiDAR is based on airborne laser scanners enables to acquire dense and accurate 3D data of the surveyed area, i.e., the Digital Surface Model (DSM). This paper presents an exploratory study to assess the accuracy of constructed DTM (Digital Terrain Model) and evaluating ground height without surface features using LiDAR Digital Surface Model (DSM). The study area comprised of an undulated area situated at Jinjang in the Klang Valley region, Malaysia covering an area of one kilometre square. LiDAR DSM and DTM constructed and derived from LiDAR were critically assessed with reference to the USGS Map Accuracy Standards. The accuracy of derived DSM and DTM were evaluated using ground control points derived from conventional surveying technique. The constructed models were accessed quantitatively and qualitatively.

Hybrid Convolutional Neural Network Method for Robust Brain Stroke Diagnosis and Segmentation

Artificial intelligence with deep learning methods have been employed by a majority of researchers in medical image classification and segmentation applications for many years. In this study, hybrid convolutional neural network (CNN) model has been proposed for diagnosing of brain stroke from the dataset consisting of the computed tomography (CT) brain images. The model inspired from C-Net consists of multiple concatenation layers of the networks, and prevents the concatenation of convolutional feature maps to evince the mapping process. The structures of the convolutional index and residual shortcuts of the INet model are also integrated into the proposed CNN model. In output layer of the model, it is split into two classes as whether there is a stroke or not in a brain image, and then the region of the stroke in the image is segmented. Tremendous analyzes have been conducted in terms of many benchmarks using Python programming. The proposed method shows better performances rather than some other current CNN-based methods by 99.54% accuracy and 99.1% Matthews correlation coefficient (MCC) in the diagnosis of brain stroke. The proposed method can alleviate the work of most medical staffs and facilitate the process of the patient’s remedy.

Thermoluminescent response of LaAlO3:Pr3+ under X-ray beams effect

Thermoluminescent (TL) dosimeters are the most used, since they can store information, due to exposure to radiation. Rare earth doped lanthanum aluminate (LaAlO3) ceramic has attracted great attention in recent years for many applications because it shows excellent properties such as thermal stability, color light emission as well as high thermoluminescent intensity. In the present work, TL glow curve under diagnostic X-ray beam was obtained. According to the literature, procedures in interventional cardiology are Thermoluminescent glow curve was analyzed using a Harshaw 3500 TL reader coupled to a personal computer for storage information and future analysis. For irradiation processes was used a diagnostic X-ray source Siemens 256-slice computed tomography (CT) Somaton drive model. TL response of trivalent praseodymium doped lanthanum aluminate as a function of dopant concentration was increasing as concentrations of Pr3+ ion in LaAlO3 was increased. The increase in TL glow peak sensitivity was increased up to 2 % concentration of Pr3+ ion. This TL glow curve exhibited a broad peak centered at 190°C and little shoulder which is consider as the second peak centered at 260°C respectively. The nature of the glow curve form in samples is attributed to at least one type of the trap with relates at least one type of the defect. After experimental results LaAlO3:Pr3+ can be used as thermoluminescent material for diagnostic X-ray beams measurements.

On the possible realization of a complex‐order capacitive impedance and its applications

SummaryThe fractional‐order Laplace operator has been used in recent years in many applications including the synthesis of fractional‐order capacitors and inductors as well as in fractional‐order filter design. However, the synthesis and application of fractional‐order impedances with a complex‐order proportional to have not received similar attention. In this work, we report on the possibility of synthesizing capacitive impedances with complex orders and explain the meaning of such impedances. Applications in realizing a complex order integrator and a complex order high‐pass filter are demonstrated supported by circuit simulation results.

Biochemical characterization and detection of antitumor activity of l-asparaginase from thermophilic Geobacillus kaustophilus DSM 7263T

L-asparaginases, which are oncolytic enzymes, have been used in clinical applications for many years. These enzymes are also important in food processing industry due to their potential in acrylamide-mitigation. In this study, the gene for l-asparaginase (GkASN) from a thermophilic bacterium, Geobacillus kaustophilus, was cloned and expressed in E. coli Rosetta™2 (DE3) cells utilizing the pET-22b(+) vector. The 6xHis-tag attached enzyme was purified and analyzed both biochemically and structurally. The molecular mass of GkASN was determined as ∼36 kDa by SDS-PAGE, Western Blotting, and MALDI-TOF MS analyses. Optimum temperature and pH for the enzyme was determined as 55 °C and 8.5, respectively. The enzyme retained 89% of its thermal stability at 37 °C and 75% at 55 °C after 6 h of incubation. The enzyme activity was inhibited in the presence of Cu2+, Fe3+, Zn2+, and EDTA, while the activity was enhanced in the presence of Mn2+, Mg2+, and thiol group protective agents such as 2-mercaptoethanol and DTT. The structural modeling analysis demonstrated that the catalytic residues of the enzyme were partially similar to other asparaginases. The therapeutic potential of GkASN was tested on hepatocellular carcinoma cells, a solid cancer type with high mortality rate and rapidly increasing incidence in recent years. We showed that the GkASN-induced asparagine deficiency effectively reduced the metastatic synergy in HCC SNU387 cells on a xCELLigence system with differentiated epithelial Hep3B and poorly differentiated metastatic mesenchymal HCC SNU387 cells.

Development and validation of a surface profiling system for end of line monitoring of microstructured elastomer seals based on chromatic confocal microscopy

Chromatic confocal surface profilometry has been a widespread technique in industrial applications for many years. Beside excellent resolution and speed, the contactless measuring capability make it ideal in applications where no physical contact is possible, (e.g. measurement of fluid levels), or where physical contact could damage the part to be inspected (e.g. high precision lenses or coatings). Since these systems rely on the spectral analysis of the reflected light, if the reflectance of the examined specimen is low, the measurement speed and accuracy can substantially degrade. In this paper, we present a high-intensity chromatic confocal surface profiling system based on an infrared superluminescent diode and custom designed optics. Due to its very small etendue, the superluminescent source allows orders of magnitude higher illumination intensity than conventional LED sources. We mounted the designed optics on a 5-axis precision positioning stage, which allows topography measurements along 5° of freedom on complex shaped samples, with a wide focus range (>350 μm) and a high scanning speed (>10 kHz). The paper presents the design procedure and the figures of merit of the device, and measurement results of microstructured elastomer samples are also shown.

M2SPL: Generative multiview features with adaptive meta-self-paced sampling for class-imbalance learning

Class-imbalance learning is an important research area and draws continued attention in various real-world applications for many years. Undersampling is a key method of class-imbalance learning in order to obtain a balanced class distribution, but it may discard potentially crucial samples and may be influenced by outliers or noises in imbalanced data. Multiview learning methods have shown that models trained on different views can help each other to improve their performances and robustness, but the existing imbalance learning approaches rely only on single-view samples. In this paper, we propose a multiview feature imbalance sampling method via meta self-paced learning (M2SPL) to effectively choose high-quality samples and separate adjacent features to improve the robustness of the trained model. There are two advantages of our proposed method: (1) An adaptive reweight generation process acts as a pivotal part in our M2SPL. The adaptive density-based reweight samples learning mechanism considers noisy and intractable samples to improve the robustness of model. (2) The multiview feature learning can avoid the large value of the loss function to learn a robust model from original data, and can enhance the discrimination capability of the model. Comparison with the existing sampling approaches shows that our proposed M2SPL approach significantly improves the classification performance, with increases in the F1-score and G-mean of 15.4% and 12.5%, respectively, on average. Finally, our experimental results pass the Friedman and Holm tests, indicating that our model has a significant improvement over existing methods.

Emergence of Glass Solutions for 5G and Heterogeneous Integration

Abstract Glass has been of great interest for advanced packaging and RF applications for many years. Since glass is an insulator, it provides low loss performance particularly at high frequencies in the mmWave. The low roughness and ability to form in thin and large area formats provide opportunities for fine line spacing to enable miniaturization and cost-effectiveness. The challenge to glass adoption has been to establish high volume manufacturing operations. Leveraging the Viaffirm® temporary bond process provides many advantages to enable use of existing processes to fabricate thin glass substrates. Here we describe the process and examples of how it has been used to enable manufacture of devices on thin glass substrates.

One-Minute Deep Breathing Assessment and its Relationship to 24-Hour HRV Measurements

Heart rate variability (HRV), the change in the time intervals between adjacent heartbeats, is an emergent property of interdependent regulatory systems that operates on different time scales to adapt to environmental and psychological challenges. Low age-adjusted HRV has been confirmed as a strong, independent predictor of future health problems in both healthy people and patients with a wide range of diseases that correlate with all-cause mortality. Twenty-four–hour HRV recordings are considered the gold standard and have greater predictive power on health risk than short-term recordings. However, it is not always practical or cost effective to obtain 24-hour HRV recordings, and short-term recordings have been widely used in research and clinical applications for many years. This article will report on the first in a series of research investigations on short-term HRV assessments. The first study examined the correlations between a 10-minute resting state, a 1-minute paced deep breathing protocol, response to handgrip, and 24-hour HRV measures in 28 healthy individuals. Based on the results of the initial study, the primary study examined the correlations between the 1-minute paced deep breathing assessment and 24-hour measures in a general population of 805 individuals. Overall, the findings from the studies suggested that the 1-minute paced deep breathing assessments were highly correlated with 24-hour measures of vagally mediated HRV and very-low-frequency power. The findings from this study suggest that the 1-minute paced deep breathing protocol is an ideal short-term assessment that can be used in a health risk screening context. When low values are observed, it is recommended that a 24-hour assessment be conducted.

THz Sensing of Human Skin: A Review of Skin Modeling Approaches.

The non-ionizing and non-invasive nature of THz radiation, combined with its high sensitivity to water, has made THz imaging and spectroscopy highly attractive for in vivo biomedical applications for many years. Among them, the skin is primarily investigated due to the short penetration depth of THz waves caused by the high attenuation by water in biological samples. However, a complete model of skin describing the THz–skin interaction is still needed. This is also fundamental to reveal the optical properties of the skin from the measured THz spectrum. It is crucial that the correct model is used, not just to ensure compatibility between different works, but more importantly to ensure the reliability of the data and conclusions. Therefore, in this review, we summarize the models applied to skin used in the THz regime, and we compare their adaptability, accuracy, and limitations. We show that most of the models attempt to extract the hydration profile inside the skin while there is also the anisotropic model that displays skin structural changes in the stratum corneum.

A Comprehensive Review on Ulvan Based Hydrogel and Its Biomedical Applications.

Ulvan is a natural sulfated polysaccharide obtained from marine green algae composed of 3-sulfated rhamnoglucuronan as the main component. It has a unique chemical structure that rich of L-rhamnosa, D-glucuronic acid, and L-iduronic acid. Ulvan has a similar structure to glycosaminoglycans (GAGs) in mammals including chondroitin sulfate, dermatan sulfate, and heparan sulfate that has broad range applications for many years. Here, we provide an overview of ulvan based hydrogels for biomedical applications. Hydrogels are one of ulvan advances in polymer science for application in drug delivery, tissue engineering, and wound healing. This review presented an overview about functional information of ulvan based hydrogels and the promising potential in biomedicals collected from published papers in Scopus, PubMed, and Google Scholar. Other important aspects concerning properties, hydrogel-forming mechanisms, and ulvan based hydrogel developments were reported as well. As conclusion, ulvan showed interesting properties in forming hydrogels and promising advances in biomedical applications.

A detailed mechanism for the initial hypergolic reaction in liquid hydrazine/nitrogen tetroxide mixtures based on quantum chemistry calculations

This work determined a chemical mechanism for the early stage of hypergolic ignition following contact between hydrazine (N2H4) and nitrogen tetroxide (N2O4), both in the liquid state. Such mixtures have been used in thrusters for spacecraft applications for many years, and the effective development and use of such propellants requires an understanding of their detonation-like ignition under various conditions. Liquid-phase reactions were investigated using quantum chemical calculations at the CBS-QB3//ωB97X-D/SMD level of theory, and the results showed that the energy barrier to the reaction N2H4 + N2O4 → NH2NHNO2 + HNO2 was much lower than values predicted for the same reaction in the gas phase. Based on these results, a detailed kinetic model for the liquid-phase reaction was constructed and employed to predict the temperature increase obtained from N2H4/N2O4 propellants under pre-mixed and adiabatic conditions. The time to reach the N2H4 boiling point of 114 °C was estimated at approximately 0.06 μs, which explains the rapid formation of a vapor phase in previous droplet pool tests. Analyses of the rate of production and the temperature sensitivity established that the N2H4 + N2O4 → NH2NHNO2 + HNO2 step plays the most important role in triggering a series of subsequent reactions, and thus determines the rate of temperature rise.

Different ion mobility-mass spectrometry coupling techniques to promote metabolomics.

Metabolomics has become increasingly popular in recent years for many applications ranging from clinical diagnosis, human health to biotechnological questioning. Despite technological advances, metabolomic studies are still currently limited by the difficulty of identifying all metabolites, a class of compounds with great chemical diversity. Although lengthy chromatographic analyses are often used to obtain comprehensive data, many isobar and isomer metabolites still remain unresolved, which is a critical point for the compound identification. Currently, ion mobility spectrometry is being explored in metabolomics as a way to improve metabolome coverage, analysis throughput and isomer separation. In this review, all the steps of a typical workflow for untargeted metabolomics are discussed considering the use of an ion mobility instrument. An overview of metabolomics is first presented followed by a brief description of ion mobility instrumentation. The ion mobility potential for complex mixture analysis is discussed regarding its coupling with a mass spectrometer alone, providing gas-phase separation before mass analysis as well as its combination with different separation platforms (conventional hyphenation but also multidimensional ion mobility couplings), offering multidimensional separation. Various instrumental and analytical conditions for improving the ion mobility separation are also described. Finally, data mining, including software packages and visualization approaches, as well as the construction of ion mobility databases for the metabolite identification are examined.

Investigation of Optical and Diode Parameters of 9-[(5-Nitropyridin-2-Aminoethyl) Iminiomethyl]-Anthracene Thin Film

The optical, structural and electrical behavior of thin films has been a highly important topic in scientific works and technological applications for many years. Because of this importance, the characteristic behaviors of the film forms are continuously investigated by producing different materials. The goal of the present study is to address in detail the evaluation of the optical properties of 9-[(5-nitropyridin-2-aminoethyl) iminiomethyl]-anthracene (NAMA) organic material and also its use in diode application. For that, the NAMA material known as an organic semiconductor has been synthesized from the reaction between 2-(2-aminoethylamino)-5-nitropyridine and 9-antracene carboxaldehyde under mild reaction conditions. Then, the material dissolved in an organic solvent was grown in thin film form using drop casting on soda-lime glass substrate. Furthermore, the transmittance and reflectance spectra of the grown film were measured in the wavelengths ranging from 200 nm to 2400 nm. The fundamental optical constants such as absorption coefficient ( $$ \alpha $$ ), optical band energy gap ( $$ E_{\text{g}} $$ ), refractive index ( $$ n $$ ) and the dielectric parameters of the thin film were calculated from the optical spectrum values obtained. The optical band gap energy of the film was found as 2.72 eV from standard optical analysis. However, the dispersion parameters were determined in regard to the Wemple-DiDomenico single oscillator model, and the dispersion energy ( $$ E_{\text{d}} $$ ) and the single oscillator energy ( $$ E_{0} $$ ) were found as 14.12 eV and 6.80 eV, respectively. In addition, the Au/NAMA/n-Si/In Schottky diode to determine the electrical parameters was fabricated and the values of ideality factor and barrier height of the fabricated device were obtained as 2.61 eV and 0.724 eV, respectively.

Modelling evaporator in organic Rankine cycle using hybrid GD-LSE ANFIS and PSO ANFIS techniques

Internal combustion engines (ICEs) are likely to be used in heavy-duty applications for many years and it is important to continue improving their efficiency. One approach is to recover waste heat from the exhaust of heavy-duty diesel engines (HDDEs) using waste heat recovery (WHR) technologies. WHR based on Organic Rankine Cycle (ORC) is a promising technology, which offers potential to reduce the fuel consumption of HDDEs by transferring the wasted thermal energy to alternative useful electrical or mechanical energy. In the ORC, the evaporator is considered the most critical component, because it has a high thermal inertia. Previous numerical models of evaporator are computationally expensive due to non-linearity of evaporator governing equations and cannot be deployed for real-time control applications. This study uses an Adaptive Network-based Fuzzy Inference System (ANFIS) modelling technique to provide efficient control-oriented evaporator models for prediction of heat source and refrigerant temperatures at the evaporator outlet. Hybrid gradient decent, least square estimate (GD-LSE) and particle swarm optimization (PSO) algorithms for training the ANFIS model have been investigated and show that training ANFIS using the PSO method results in an improvement in accuracy. Furthermore, the systematic and adaptive approach of the ANFIS modelling technique makes the procedure of evaporator modelling less dependent on expert knowledge, reducing the modelling effort.