bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study on the Residual Stress of the Co-Based Alloy Plasma Cladding Layer
Authors: Lai Youbin , Yue Xiang , Yue Wenwen
Published: July 2022

The distribution law of residual stress in multi-channel scanned plasma cladding of Co-based alloy under different process parameters was studied by means of simulation and tests, and the optimum process parameters were optimized. The simulation model of the plasma cladding stress field was established by ABAQUS software, and the influence law of the working current, scanning speed, and scanning mode on the residual stress of the Co-based alloy multi-channel scanning was studied. A set of optimal cladding process parameters were obtained. The residual stress of the cladding layer was measured by the blind hole method and compared with the stress value in the finite element model. The results show that there is residual tensile stress on the surface of the cladding layer. The residual stress along the direction of the scanning path is greater than that along the direction of the scan sequence. The residual stress increases with the increase of the working current. The scanning speed is greater, and the residual stress is smaller. The residual stress of the short-edge scanning is greater than that of the long-edge scanning. The residual stress of the successive scanning is greater than that of the reciprocating scanning. The long-edge reciprocating scanning is the best scanning mode. The best combination of process parameters is the working current of 90 A, the scanning speed of 100 mm/min, and the long-edge reciprocating scanning mode.
Therapeutic Potential of Marine Peptides in Prostate Cancer: Mechanistic Insights
Authors: Ahmed Salman , Alam Waqas , Jeandet Philippe , Aschner Michael , Alsharif Khalaf F. , Saso Luciano , Khan Haroon
Published: July 2022

Prostate cancer (PCa) is the leading cause of cancer death in men, and its treatment is commonly associated with severe adverse effects. Thus, new treatment modalities are required. In this context, natural compounds have been widely explored for their anti-PCa properties. Aquatic organisms contain numerous potential medications. Anticancer peptides are less toxic to normal cells and provide an efficacious treatment approach via multiple mechanisms, including altered cell viability, apoptosis, cell migration/invasion, suppression of angiogenesis and microtubule balance disturbances. This review sheds light on marine peptides as efficacious and safe therapeutic agents for PCa.
Depolymerized Fractions of Sulfated Galactans Extracted from Gracilaria fisheri and Their Antibacterial Activity against Vibrio parahaemolyticus and Vibrio harveyi
Authors: Kamble Manoj Tukaram , Rudtanatip Tawut , Soowannayan Chumporn , Nambunruang Boottoh , Medhe Seema Vijay , Wongprasert Kanokpan
Published: July 2022

Various seaweed sulfated polysaccharides have been explored for antimicrobial application. This study aimed to evaluate the antibacterial activity of the native Gracilaria fisheri sulfated galactans (NSG) and depolymerized fractions against the marine pathogenic bacteria Vibrio parahaemolyticus and Vibrio harveyi. NSG was hydrolyzed in different concentrations of H2O2 to generate sulfated galactans degraded fractions (SGF). The molecular weight, structural characteristics, and physicochemical parameters of both NSG and SGF were determined. The results revealed that the high molecular weight NSG (228.33 kDa) was significantly degraded to SGFs of 115.76, 3.79, and 3.19 kDa by hydrolysis with 0.4, 2, and 10% H2O2, respectively. The Fourier transformed spectroscopy (FTIR) and 1H− and 13C−Nuclear magnetic resonance (NMR) analyses demonstrated that the polysaccharide chain structure of SGFs was not affected by H2O2 degradation, but alterations were detected at the peak positions of some functional groups. In vitro study showed that SGFs significantly exerted a stronger antibacterial activity against V. parahaemolyticus and V. harveyi than NSG, which might be due to the low molecular weight and higher sulfation properties of SGF. SGF disrupted the bacterial cell membrane, resulting in leakage of intracellular biological components, and subsequently, cell death. Taken together, this study provides a basis for the exploitation and utilization of low-molecular-weight sulfated galactans from G. fisheri to prevent and control the shrimp pathogens.
Isolation and Characterization of Efficient Active Compounds Using High-Performance Centrifugal Partition Chromatography (CPC) from Anti-Inflammatory Activity Fraction of Ecklonia maxima in South Africa
Authors: Kim Hyun-Soo , Je Jun-Geon , An Hyesuck , Baek Kyunghwa , Lee Jeong Min , Yim Mi-Jin , Ko Seok-Chun , Kim Ji-Yul , Oh Gun-Woo , Kang Min-Cheol , Ham Young Min , Jeon You-Jin , Lee Dae-Sung
Published: July 2022

Ecklonia maxima is a brown seaweed, which is abundantly distributed in South Africa. This study investigated an efficient approach using high-performance centrifugal partition chromatography (HPCPC), which has been successfully developed for the isolation and purification of phlorotannins, eckmaxol, and dieckol from the ethyl acetate fraction of E. maxima (EEM). We evaluated EEM for its inhibitory effect against lipopolysaccharide (LPS)-induced inflammatory responses in zebrafish embryos. The separation of eckmaxol and dieckol from samples of EEM using HPCPC was found to be of high purity and yield under an optimal solvent system composed of n-hexane:ethyl acetate:methanol:water (2:7:3:7, v/v/v/v). To evaluate the anti-inflammatory efficacy of EEM containing active compounds, zebrafish embryos exposed to LPS were compared with and without EEM treatment for nitric oxide (NO) production, reactive oxygen species (ROS) generation, and cell death two days after fertilization. These evaluations indicate that EEM alleviated inflammation by inhibiting cell death, ROS, and NO generation induced by LPS treatment. According to these results, eckmaxol and dieckol isolated from brown seaweed E. maxima could be considered effective anti-inflammatory agents as pharmaceutical and functional food ingredients.
Prediction of Heart Function and Volume Status in End-Stage Kidney Disease Patients through N-Terminal Pro-Brain Natriuretic Peptide
Authors: Lee Kyung Ho , Moon Inki , Oh Young Seung , Yu Byung Chul , Park Moo Yong , Kim Jin Kuk , Choi Soo Jeong
Published: July 2022

Background and Objectives: N-terminal pro-brain natriuretic peptide (NT-proBNP) is a biomarker used to predict heart failure and evaluate volume status in hemodialysis (HD) patients. However, it is difficult to determine the cutoff value for NT-proBNP in HD patients. In this study, we analyzed whether NT-proBNP helps predict heart function and volume status in HD patients. Materials and Methods: This prospective observational study enrolled 96 end-stage kidney disease patients with HD. All patients underwent echocardiography and bioimpedance spectroscopy (BIS) after an HD session. Overhydration (OH) was measured by BIS. Laboratory data were obtained preHD, while serum NT-proBNP was measured after HD. Interventions for blood pressure control and dry weight control were performed, and NT-proBNP was re-assessed after a month. Results: There was an inverse correlation between NT-proBNP and ejection fraction (EF) (β = −0.34, p = 0.001). OH (β = 0.331, p = 0.001) and diastolic dysfunction (β = 0.226, p = 0.027) were associated with elevated NT-proBNP. In a subgroup analysis of diastolic dysfunction grade, NT-proBNP increased according to dysfunction grade (normal, 4177 pg/mL [2637–10,391]; grade 1, 9736 pg/mL [5471–21,110]; and grades 2–3, 26,237 pg/mL [16,975–49,465]). NT-proBNP showed a tendency toward a decrease in the ‘reduced dry weight’ group and toward an increase in the ‘increased dry weight’ group compared to the control group (ΔNT-proBNP, −210 pg/mL [−12,899 to 3142], p = 0.104; 1575 pg/mL [−113 to 6439], p = 0.118). Conclusions: We confirmed that NT-proBNP is associated with volume status as well as heart function in HD patients.
Inhibition of Microtubule Affinity Regulating Kinase 4 by Metformin: Exploring the Neuroprotective Potential of Antidiabetic Drug through Spectroscopic and Computational Approaches
Authors: Ashraf Ghulam , DasGupta Debarati , Alam Mohammad , Baeesa Saleh , Alghamdi Badrah , Anwar Firoz , Alqurashi Thamer , Sharaf Sharaf , Al Abdulmonem Waleed , Alyousef Mohammed , Alhumaydhi Fahad , Shamsi Anas
Published: July 2022

Microtubule affinity regulating kinase 4 (MARK4) regulates the mechanism of microtubules by its ability to phosphorylate the microtubule-associated proteins (MAP’s). MARK4 is known for its major role in tau phosphorylation via phosphorylating Ser262 residue in the KXGS motif, which results in the detachment of tau from microtubule. In lieu of this vital role in tau pathology, a hallmark of Alzheimer’s disease (AD), MARK4 is a druggable target to treat AD and other neurodegenerative disorders (NDs). There is growing evidence that NDs and diabetes are connected with many pieces of literature demonstrating a high risk of developing AD in diabetic patients. Metformin (Mtf) has been a drug in use against type 2 diabetes mellitus (T2DM) for a long time; however, recent studies have established its therapeutic effect in neurodegenerative diseases (NDs), namely AD, Parkinson’s disease (PD) and amnestic mild cognitive impairment. In this study, we have explored the MARK4 inhibitory potential of Mtf, employing in silico and in vitro approaches. Molecular docking demonstrated that Mtf binds to MARK4 with a significant affinity of −6.9 kcal/mol forming interactions with binding pocket’s critical residues. Additionally, molecular dynamics (MD) simulation provided an atomistic insight into the binding of Mtf with MARK4. ATPase assay of MARK4 in the presence of Mtf shows that it inhibits MARK4 with an IC50 = 7.05 µM. The results of the fluorescence binding assay demonstrated significant binding of MARK4 with a binding constant of 0.6 × 106 M−1. The present study provides an additional axis towards the utilization of Mtf as MARK4 inhibitor targeting diabetes with NDs.
Pharmacological Validation for the Folklore Use of Ipomoea nil against Asthma: In Vivo and In Vitro Evaluation
Authors: Alqahtani Taha , Parveen Sajida , Alghazwani Yahia , Alharbi Hanan M. , Gahtani Reem M. , Hussain Nadia , Rehman Kashif ur , Hussain Musaddique
Published: July 2022

Oxidative stress is the key factor that strengthens free radical generation which stimulates lung inflammation. The aim was to explore antioxidant, bronchodilatory along with anti-asthmatic potential of folkloric plants and the aqueous methanolic crude extract of Ipomoea nil (In.Cr) seeds which may demonstrate as more potent, economically affordable, having an improved antioxidant profile and providing evidence as exclusive therapeutic agents in respiratory pharmacology. In vitro antioxidant temperament was executed by DPPH, TFC, TPC and HPLC in addition to enzyme inhibition (cholinesterase) analysis; a bronchodilator assay on rabbit’s trachea as well as in vivo OVA-induced allergic asthmatic activity was performed on mice. In vitro analysis of 1,1-Diphenyl-2-picrylhydrazyl radical (DPPH) expressed as % inhibition 86.28 ± 0.25 with IC50 17.22 ± 0.56 mol/L, TPC 115.5 ± 1.02 mg GAE/g of dry sample, TFC 50.44 ± 1.06 mg QE/g dry weight of sample, inhibition in cholinesterase levels for acetyl and butyryl with IC50 (0.60 ± 0.67 and 1.5 ± 0.04 mol/L) in comparison with standard 0.06 ± 0.002 and 0.30 ± 0.003, respectively, while HPLC characterization of In.Cr confirmed the existence with identification as well as quantification of various polyphenolics and flavonoids i.e., gallic acid, vanillic acid, chlorogenic acid, quercetin, kaempferol and others. However, oral gavage of In.Cr at different doses in rabbits showed a better brochodilation profile as compared to carbachol and K+-induced bronchospasm. More significant (p < 0.01) reduction in OVA-induced allergic hyper-responses i.e., inflammatory cells grade, antibody IgE as well as altered IFN-α in airways were observed at three different doses of In.Cr. It can be concluded that sound mechanistic basis i.e., the existence of antioxidants: various phenolic and flavonoids, calcium antagonist(s) as well as enzymes’ inhibition profile, validates folkloric consumptions of this traditionally used plant to treat ailments of respiration.
Reduced Endocannabinoid Tone in Saliva of Chronic Orofacial Pain Patients
Authors: Haviv Yaron , Georgiev Olga , Gaver-Bracha Tal , Hamad Sharleen , Nemirovski Alina , Hadar Rivka , Sharav Yair , Aframian Doron J. , Brotman Yariv , Tam Joseph
Published: July 2022

Background: the endocannabinoid system (ECS) participates in many physiological and pathological processes including pain generation, modulation, and sensation. Its involvement in chronic orofacial pain (OFP) in general, and the reflection of its involvement in OFP in salivary endocannabinoid (eCBs) levels in particular, has not been examined. Objectives: to evaluate the association between salivary (eCBs) levels and chronic OFP. Methods: salivary levels of 2 eCBs, anandamide (AEA), 2-arachidonoylglycerol (2-AG), 2 endocannabinoid-like compoundsN-palmitoylethanolamine (PEA), N-oleoylethanolamine (OEA), and their endogenous precursor and breakdown product, arachidonic acid (AA), were analyzed using liquid chromatography/tandem mass spectrometry in 83 chronic OFP patients and 43 pain-free controls. The chronic OFP patients were divided according to diagnosis into musculoskeletal, neurovascular/migraine, and neuropathic pain types. Results: chronic OFP patients had lower levels of OEA (p = 0.02) and 2-AG (p = 0.01). Analyzing specific pain types revealed lower levels of AEA and OEA in the neurovascular group (p = 0.04, 0.02, respectively), and 2-AG in the neuropathic group compared to controls (p = 0.05). No significant differences were found between the musculoskeletal pain group and controls. Higher pain intensity was accompanied by lower levels of AA (p = 0.028), in neuropathic group. Conclusions: lower levels of eCBs were found in the saliva of chronic OFP patients compared to controls, specifically those with neurovascular/migraine, and neuropathic pain. The detection of changes in salivary endocannabinoids levels related to OFP adds a new dimension to our understanding of OFP mechanisms, and may have diagnostic as well as therapeutic implications for pain.
Formation of Carcinogens in Processed Meat and Its Measurement with the Usage of Artificial Digestion—A Review
Authors: Pogorzelska-Nowicka Ewelina , Kurek Marcin , Hanula Monika , Wierzbicka Agnieszka , Półtorak Andrzej
Published: July 2022

Meat is a rich source of various nutrients. However, it needs processing before consumption, what in turn generates formation of carcinogenic compounds, i.a., polycyclic aromatic hydrocarbons (PAH), nitrosamines (NOCs), and the most mutagenic heterocyclic aromatic amines (HAAs). It was widely found that many factors affect the content of carcinogens in processed meat. However, it has recently been discovered that after digestion free HAAs are released, which are not detectable before enzymatic treatment. It was established that the highest percentage of carcinogens is released in the small intestine and that its amount can be increased up to 6.6-fold. The change in free HAAs content in analyzed samples was dependent on many factors such as meat type, doneness, particle size of meat, and the enzyme concentration used for digestion. In turn, introduction of bacteria naturally occurring in the human digestive tract into the model significantly decreases total amount of HAAs. Contrary, the addition of food ingredients rich in polyphenols, fiber, and water (pepper powder, onions, apples) increases free HAAs’ release up to 56.06%. Results suggests that in vitro digestion should be an integral step of sample preparation. Artificial digestion introduced before chromatographic analysis will allow to estimate accurately the content of carcinogens in processed meat.
Pd(II) Binding Strength of a Novel Ambidentate Dipeptide-Hydroxypyridinonate Ligand: A Solution Equilibrium Study
Authors: Bíró Linda , Ozsváth András , Kapitány Réka , Buglyó Péter
Published: July 2022

A novel ambidentate dipeptide conjugate (H(L1)) containing N-donor atoms of the peptide part and an (O,O) chelate at the hydroxypyridinone (HP) ring is synthesized and characterized. It is hoped that this chelating ligand can be useful to obtain multitargeted Co(III)/Pt(II) dinuclear complexes with anticancer potential. The Pd(II) (as a Pt(II) model but with faster ligand exchange reactions) binding strength of the ligand was studied in an aqueous solution with the combined use of pH-potentiometry and NMR. In an equimolar solution, (L1)− was found to bind Pd(II) via the terminal amino and increasing number of peptide nitrogens of the peptide backbone over a wide pH range. At a 2:1 Pd(II) to ligand ratio, the presence of [Pd2H–x(L1)] (x = 1–4) species, with high stability and with the coordination of the (O,O) chelating set of the ligand, was detected. The reaction of H(L1) with [Co(tren)]3+ (tren = tris(2-aminoethyl)amine) indicated the exclusive binding of (L1)− via its (O,O) donor atoms to the metal unit, while treatment of the resulting Co-complex with Pd(II) afforded the formation of a Co/Pd heterobimetallic complex in solution with an (NH2, Namide) coordination of Pd(II). Shortening the peptide backbone in H(L1) by one peptide unit compared to the structurally similar ambidentate chelator consisting of three peptide bonds resulted in the slightly more favorable formation of the N-coordinated Pd(II) species, allowing the tailoring of the coordination properties.
What Are the Minimal Feeds Required for Starting Enteral Ibuprofen in Preterm Infants with PDA?
Authors: Surak Aimann , Hyderi Abbas
Published: July 2022

Ibuprofen is commonly used for the treatment of hemodynamically significant patent ductus arteriosus (PDA) in preterm infants. It seems that the oral formulation incurs a higher closure rate and has a better safety profile in preterm infants born > 26 weeks’ gestation. There is no consensus across Canadian centers regarding the minimum volume of enteral feeds required prior to starting ibuprofen for the treatment of patent ductus arteriosus, and the current practice is comfort-based depending on the centre and the local prevalence of neonatal morbidities.
COVID-19 Signs and Symptom Clusters in Long-Term Care Facility Residents: Data from the GeroCovid Observational Study
Authors: Malara Alba , Noale Marianna , Abbatecola Angela Marie , Borselli Gilda , Cafariello Carmine , Fumagalli Stefano , Gareri Pietro , Mossello Enrico , Trevisan Caterina , Volpato Stefano , Monzani Fabio , Coin Alessandra , Bellelli Giuseppe , Okoye Chukwuma , Del Signore Stefania , Zia Gianluca , Incalzi Raffaele Antonelli ,   on behalf of the GeroCovid LTCFs Working Group
Published: July 2022

Background: Long-term care facility (LTCF) residents often present asymptomatic or paucisymptomatic features of SARS-CoV-2 infection. We aimed at investigating signs/symptoms, including their clustering on SARS-CoV-2 infection and mortality rates associated with SARS-CoV-2 infection in LTCF residents. Methods: This is a cohort study of 586 aged ≥ 60 year-old residents at risk of or affected with COVID-19 enrolled in the GeroCovid LTCF network. COVID-19 signs/symptom clusters were identified using cluster analysis. Cluster analyses associated with SARS-CoV-2 infection and mortality were evaluated using logistic regression and Cox proportional hazard models. Results: Cluster 1 symptoms (delirium, fever, low-grade fever, diarrhea, anorexia, cough, increased respiratory rate, sudden deterioration in health conditions, dyspnea, oxygen saturation, and weakness) affected 39.6% of residents and were associated with PCR swab positivity (OR = 7.21, 95%CI 4.78–10.80; p < 0.001). Cluster 1 symptoms were present in deceased COVID-19 residents. Cluster 2 (increased blood pressure, sphincter incontinence) and cluster 3 (new-onset cognitive impairment) affected 20% and 19.8% of residents, respectively. Cluster 3 symptoms were associated with increased mortality (HR = 5.41, 95%CI 1.56–18.8; p = 0.008), while those of Cluster 2 were not associated with mortality (HR = 0.82, 95%CI 0.26–2.56; p = 730). Conclusions: Our study highlights that delirium, fever, and low-grade fever, alone or in clusters should be considered in identifying and predicting the prognosis of SARS-CoV-2 infection in older LTCF patients.
Bivariate Copula Trees for Gross Loss Aggregation with Positively Dependent Risks
Authors: Wójcik Rafał , Liu Charlie Wusuo
Published: July 2022

We propose several numerical algorithms to compute the distribution of gross loss in a positively dependent catastrophe insurance portfolio. Hierarchical risk aggregation is performed using bivariate copula trees. Six common parametric copula families are studied. At every branching node, the distribution of a sum of risks is obtained by discrete copula convolution. This approach is compared to approximation by a weighted average of independent and comonotonic distributions. The weight is a measure of positive dependence through variance of the aggregate risk. During gross loss accumulation, the marginals are distorted by application of insurance financial terms, and the value of the mixing weight is impacted. To accelerate computations, we capture this effect using the ratio of standard deviations of pre-term and post-term risks, followed by covariance scaling. We test the performance of our algorithms using three examples of complex insurance portfolios subject to hurricane and earthquake catastrophes.
Indoor MIMO-VLC Using Angle Diversity Transmitters
Authors: Qin Biao , Wen Wanli , Liu Min , Zhang Yanchao , Chen Chen
Published: July 2022

In this paper, we, for the first time, apply angle diversity transmitters (ADTs) to enhance the performance of multiple-input multiple-output visible light communication (MIMO-VLC) systems. The ADT is designed to consist of one center light emitting diode (LED) and multiple inclined side LEDs. We calculate the line-of-sight (LOS) channel gain of the MIMO-VLC system using ADTs and further derive the average achievable rate of the system. We show that the average achievable rate is related to both the inclination angle of the side LEDs and the spacing between two adjacent ADTs in the MIMO-VLC system. Simulations are conducted to verify that the average achievable rate of the ADT-enhanced MIMO-VLC system can be maximized by setting the optimal inclination angle of the side LEDs and the optimal spacing between adjacent ADTs. The obtained results further show that the average achievable rate of the ADT-enhanced MIMO-VLC system can be greatly improved when there are more LEDs in each ADT. Specifically, a substantial 42.9% average achievable rate improvement can be achieved by using the optimized ADT in comparison to using a conventional non-angle diversity transmitter.
Experimental Analysis of Commercial Optical Methods for Foot Measurement
Authors: Jäger Matthias C. , Eberhardt Jörg , Cunningham Douglas W.
Published: July 2022

Due to the increasing trend of online shopping, shoes are more and more often bought without being tried on. This leads to a strong increase in returns, which results in a high financial as well as ecological burden. To prevent this, feet can be measured either in the store or at home by various systems to determine the exact dimensions of the foot and derive an optimal shoe size. In this paper, we want to present an overview of the methods currently available on the market for the measurement of feet. The most important commercial systems are classified according to the underlying basic technology. Subsequently, the most promising methods were implemented and tested. The results of the different methods were finally compared to find out the strengths and weaknesses of each technology. After determining the measurement accuracy of the length and width for each measurement method and also comparing the general shape of the 3D reconstruction with the GT, it can be said that the measurement using a ToF sensor is currently the most robust, the easiest and, among other methods, the most accurate method.
What Can We Learn from Depth Camera Sensor Noise?
Authors: Haider Azmi , Hel-Or Hagit
Published: July 2022

Although camera and sensor noise are often disregarded, assumed negligible or dealt with in the context of denoising, in this paper we show that significant information can actually be deduced from camera noise about the captured scene and the objects within it. Specifically, we deal with depth cameras and their noise patterns. We show that from sensor noise alone, the object’s depth and location in the scene can be deduced. Sensor noise can indicate the source camera type, and within a camera type the specific device used to acquire the images. Furthermore, we show that noise distribution on surfaces provides information about the light direction within the scene as well as allows to distinguish between real and masked faces. Finally, we show that the size of depth shadows (missing depth data) is a function of the object’s distance from the background, its distance from the camera and the object’s size. Hence, can be used to authenticate objects location in the scene. This paper provides tools and insights into what can be learned from depth camera sensor noise.
Design Method for a Wideband Non-Uniformly Spaced Linear Array Using the Modified Reinforcement Learning Algorithm
Authors: Kang Seyoung , Kim Seonkyo , Park Cheolsun , Chung Wonzoo
Published: July 2022

In this paper, we present a design method for a wideband non-uniformly spaced linear array (NUSLA), with both symmetric and asymmetric geometries, using the modified reinforcement learning algorithm (MORELA). We designed a cost function that provided freedom to the beam pattern by setting limits only on the beam width (BW) and side-lobe level (SLL) in order to satisfy the desired BW and SLL in the wide band. We added the scan angle condition to the cost function to design the scanned beam pattern, as the ability to scan a beam in the desired direction is important in various applications. In order to prevent possible pointing angle errors for asymmetric NUSLA, we employed a penalty function to ensure the peak at the desired direction. Modified reinforcement learning algorithm (MORELA), which is a reinforcement learning-based algorithm used to determine a global optimum of the cost function, is applied to optimize the spacing and weights of the NUSLA by minimizing the proposed cost function. The performance of the proposed scheme was verified by comparing it with that of existing heuristic optimization algorithms via computer simulations.
Dynamic Segmentation of Sensor Events for Real-Time Human Activity Recognition in a Smart Home Context
Authors: Najeh Houda , Lohr Christophe , Leduc Benoit
Published: July 2022

Human activity recognition (HAR) is fundamental to many services in smart buildings. However, providing sufficiently robust activity recognition systems that could be confidently deployed in an ordinary real environment remains a major challenge. Much of the research done in this area has mainly focused on recognition through pre-segmented sensor data. In this paper, real-time human activity recognition based on streaming sensors is investigated. The proposed methodology incorporates dynamic event windowing based on spatio-temporal correlation and the knowledge of activity trigger sensor to recognize activities and record new events. The objective is to determine whether the last event that just happened belongs to the current activity, or if it is the sign of the start of a new activity. For this, we consider the correlation between sensors in view of what can be seen in the history of past events. The proposed algorithm contains three steps: verification of sensor correlation (SC), verification of temporal correlation (TC), and determination of the activity triggering the sensor. The proposed approach is applied to a real case study: the “Aruba” dataset from the CASAS database. F1 score is used to assess the quality of the segmentation. The results show that the proposed approach segments several activities (sleeping, bed to toilet, meal preparation, eating, housekeeping, working, entering home, and leaving home) with an F1 score of 0.63–0.99.
Two-Dimensional Position Tracking Using Gradient Magnetic Fields
Authors: Trinh Xuan Thang , Jeng Jen-Tzong , Nguyen Huu-Thang , Luong Van Su , Lu Chih-Cheng
Published: July 2022

In this work, a two-dimensional (2D) position-detection device using a single axis magnetic sensor combined with orthogonal gradient coils was designed and fabricated. The sensors used were an induction coil and a GMR spin-valve sensor GF807 from Sensitec Inc. The field profiles generated by the two orthogonal gradient coils were analyzed numerically to achieve the maximum linear range, which corresponded to the detection area of the tracking system. The two coils were driven by 1-kHz sine wave currents with a 90° phase difference to generate the fields with uniform gradients along the x- and y-axis in the plane of the tracking stage. The gradient fields were detected by a single-axis sensor incorporated with a digital dual-phase lock-in detector to retrieve the position information. A linearity correction algorithm was used to improve the location accuracy and to extend the linear range for position sensing. The mean positioning error was found to be 0.417 mm, corresponding to the relative error of 0.21% in the working range of 200 mm × 200 mm, indicating that the proposed tracking system is promising for applications requiring accurate control of the two-dimensional position.
A High-Power 3P3T Cross Antenna Switch with Low Harmonic Distortion and Enhanced Isolation Using T-Type Pull-Down Path for Cellular Mobile Devices
Authors: Hejazi Arash , Rad Reza E. , Asl S. A. Hosseini , Choi Kyung-Duk , Yoo Joon-Mo , Huh Hyungki , Kim Seokkee , Jung Yeonjae , Lee Kang-Yoon
Published: July 2022

This paper presents a radio frequency (RF) triple pole triple throw 3P3T cross antenna switch for cellular mobile devices. The negative biasing scheme was applied to improve the power-handling capability and linearity of the switch by increasing the maximum tolerable voltage drop across the drain and source and reverse biasing the parasitic junction diodes. To avoid signal reflection through the antenna in off-state, all the antenna ports were equipped with 50-ohm termination to provide the pull-down path. Considering the simultaneous operation of antenna ports in different switch cases, the presented T-type pull-down path demonstrated improvement of isolation by over 15 dB. Using stacked switches, the 3P3T handled the input power level of over 35 dBm. The chip was manufactured in 65 nm complementary metal oxide semiconductor (CMOS) silicon on insulator (SOI) technology with a die size of 790 × 730 µm. The proposed structure achieved insertion loss, isolation, and voltage standing wave ratio (VSWR) of less than −0.9 dB, −40 dB, and 1.6, respectively, when the input signal was 3.8 GHz. The measured results prove the implemented switch shows the second and third harmonic distortion performances of less than −60 dBm when the input power level and frequency are 25 dBm and 3.8 GHz, respectively.
Gaze Estimation Approach Using Deep Differential Residual Network
Authors: Huang Longzhao , Li Yujie , Wang Xu , Wang Haoyu , Bouridane Ahmed , Chaddad Ahmad
Published: July 2022

Gaze estimation, which is a method to determine where a person is looking at given the person’s full face, is a valuable clue for understanding human intention. Similarly to other domains of computer vision, deep learning (DL) methods have gained recognition in the gaze estimation domain. However, there are still gaze calibration problems in the gaze estimation domain, thus preventing existing methods from further improving the performances. An effective solution is to directly predict the difference information of two human eyes, such as the differential network (Diff-Nn). However, this solution results in a loss of accuracy when using only one inference image. We propose a differential residual model (DRNet) combined with a new loss function to make use of the difference information of two eye images. We treat the difference information as auxiliary information. We assess the proposed model (DRNet) mainly using two public datasets (1) MpiiGaze and (2) Eyediap. Considering only the eye features, DRNet outperforms the state-of-the-art gaze estimation methods with angular-error of 4.57 and 6.14 using MpiiGaze and Eyediap datasets, respectively. Furthermore, the experimental results also demonstrate that DRNet is extremely robust to noise images.
Smart Immunosensors for Point-of-Care Serological Tests Aimed at Assessing Natural or Vaccine-Induced SARS-CoV-2 Immunity
Authors: Fortunati Simone , Giannetto Marco , Giliberti Chiara , Bolchi Angelo , Ferrari Davide , Locatelli Massimo , Bianchi Valentina , Boni Andrea , De Munari Ilaria , Careri Maria
Published: July 2022

Innovative and highly performing smart voltammetric immunosensors for rapid and effective serological tests aimed at the determination of SARS-CoV-2 antibodies were developed and validated in human serum matrix. Two immunosensors were developed for the determination of immunoglobulins directed against either the nucleocapsid or the spike viral antigen proteins. The immunosensors were realized using disposable screen-printed electrodes modified with nanostructured materials for the immobilization of the antigens. Fast quantitative detection was achieved, with analysis duration being around 1 h. Signal readout was carried out through a smart, compact and battery-powered potentiostat, based on a Wi-Fi protocol and devised for the Internet of Things (IoT) paradigm. This device is used for the acquisition, storage and sharing of clinical data. Outstanding immunosensors’ sensitivity, specificity and accuracy (100%) were assessed, according to the diagnostic guidelines for epidemiological data. The overall performance of the sensing devices, combined with the portability of the IoT-based device, enables their suitability as a high-throughput diagnostic tool. Both of the immunosensors were validated using clinical human serum specimens from SARS-CoV-2 infected patients, provided by IRCCS Ospedale San Raffaele.
EIEN: Endoscopic Image Enhancement Network Based on Retinex Theory
Authors: An Ziheng , Xu Chao , Qian Kai , Han Jubao , Tan Wei , Wang Dou , Fang Qianqian
Published: July 2022

In recent years, deep convolutional neural network (CNN)-based image enhancement has shown outstanding performance. However, due to the problems of uneven illumination and low contrast existing in endoscopic images, the implementation of medical endoscopic image enhancement using CNN is still an exploratory and challenging task. An endoscopic image enhancement network (EIEN) based on the Retinex theory is proposed in this paper to solve these problems. The structure consists of three parts: decomposition network, illumination correction network, and reflection component enhancement algorithm. First, the decomposition network model of pre-trained Retinex-Net is retrained on the endoscopic image dataset, and then the images are decomposed into illumination and reflection components by this decomposition network. Second, the illumination components are corrected by the proposed self-attention guided multi-scale pyramid structure. The pyramid structure is used to capture the multi-scale information of the image. The self-attention mechanism is based on the imaging nature of the endoscopic image, and the inverse image of the illumination component is fused with the features of the green and blue channels of the image to be enhanced to generate a weight map that reassigns weights to the spatial dimension of the feature map, to avoid the loss of details in the process of multi-scale feature fusion and image reconstruction by the network. The reflection component enhancement is achieved by sub-channel stretching and weighted fusion, which is used to enhance the vascular information and image contrast. Finally, the enhanced illumination and reflection components are multiplied to obtain the reconstructed image. We compare the results of the proposed method with six other methods on a test set. The experimental results show that EIEN enhances the brightness and contrast of endoscopic images and highlights vascular and tissue information. At the same time, the method in this paper obtained the best results in terms of visual perception and objective evaluation.
Towards Portable MEMS Oscillators for Sensing Nanoparticles
Authors: Chellasivalingam Malar , Zielinski Arthur T. , Whitney Thomas S. , Boies Adam M. , Seshia Ashwin A.
Published: July 2022

This paper reports on the design, and implementation of piezoelectric-on-silicon MEMS resonators installed within a portable experimental setup for sensing nanoparticles in a laboratory environment. MEMS oscillators with a center frequency of approximately 5.999 MHz are employed for sensing 50 nm size-selected silver nanoparticles generated in the laboratory. The same experimental setup is then assembled to sense indoor particles that are present in the laboratory environment. The challenges associated with particle deposition as a result of assembling the portable experimental setup is highlighted. Furthermore, the MEMS oscillators demonstrate that the total mass of silver nanoparticles deposited onto the MEMS resonator surface using the inertial impaction technique-based experimental setup is approximately 7.993 nanograms. The total indoor particle mass accumulated on the MEMS resonator surface is estimated to be approximately 1.732 nanograms and 26.9 picograms for two different runs. The frequency resolution of the MEMS oscillator is estimated to be approximately 32 ppb and, consequently, the minimum detectable particle mass is approximately 60 femtograms for a 9.2 s integration time.
Comparison of Deep Learning Algorithms in Predicting Expert Assessments of Pain Scores during Surgical Operations Using Analgesia Nociception Index
Authors: Jean Wei-Horng , Sutikno Peter , Fan Shou-Zen , Abbod Maysam F. , Shieh Jiann-Shing
Published: July 2022

There are many surgical operations performed daily in operation rooms worldwide. Adequate anesthesia is needed during an operation. Besides hypnosis, adequate analgesia is critical to prevent autonomic reactions. Clinical experience and vital signs are usually used to adjust the dosage of analgesics. Analgesia nociception index (ANI), which ranges from 0 to 100, is derived from heart rate variability (HRV) via electrocardiogram (ECG) signals, for pain evaluation in a non-invasive manner. It represents parasympathetic activity. In this study, we compared the performance of multilayer perceptron (MLP) and long short-term memory (LSTM) algorithms in predicting expert assessment of pain score (EAPS) based on patient′s HRV during surgery. The objective of this study was to analyze how deep learning models differed from the medical doctors′ predictions of EAPS. As the input and output features of the deep learning models, the opposites of ANI and EAPS were used. This study included 80 patients who underwent operations at National Taiwan University Hospital. Using MLP and LSTM, a holdout method was first applied to 60 training patients, 10 validation patients, and 10 testing patients. As compared to the LSTM model, which had a testing mean absolute error (MAE) of 2.633 ± 0.542, the MLP model had a testing MAE of 2.490 ± 0.522, with a more appropriate shape of its prediction curves. The model based on MLP was selected as the best. Using MLP, a seven-fold cross validation method was then applied. The first fold had the lowest testing MAE of 2.460 ± 0.634, while the overall MAE for the seven-fold cross validation method was 2.848 ± 0.308. In conclusion, HRV analysis using MLP algorithm had a good correlation with EAPS; therefore, it can play role as a continuous monitor to predict intraoperative pain levels, to assist physicians in adjusting analgesic agent dosage. Further studies may consider obtaining more input features, such as photoplethysmography (PPG) and other kinds of continuous variable, to improve the prediction performance.
Quantitative Analysis Using Consecutive Time Window for Unobtrusive Atrial Fibrillation Detection Based on Ballistocardiogram Signal
Authors: Cheng Tianqing , Jiang Fangfang , Li Qing , Zeng Jitao , Zhang Biyong
Published: July 2022

Atrial fibrillation (AF) is the most common clinically significant arrhythmia; therefore, AF detection is crucial. Here, we propose a novel feature extraction method to improve AF detection performance using a ballistocardiogram (BCG), which is a weak vibration signal on the body surface transmitted by the cardiogenic force. In this paper, continuous time windows (CTWs) are added to each BCG segment and recurrence quantification analysis (RQA) features are extracted from each time window. Then, the number of CTWs is discussed and the combined features from multiple time windows are ranked, which finally constitute the CTW–RQA features. As validation, the CTW–RQA features are extracted from 4000 BCG segments of 59 subjects, which are compared with classical time and time-frequency features and up-to-date energy features. The accuracy of the proposed feature is superior, and three types of features are fused to obtain the highest accuracy of 95.63%. To evaluate the importance of the proposed feature, the fusion features are ranked using a chi-square test. CTW–RQA features account for 60% of the first 10 fusion features and 65% of the first 17 fusion features. It follows that the proposed CTW–RQA features effectively supplement the existing BCG features for AF detection.
Internet-of-Things-Enabled Smart Bed Rail for Application in Hospital Beds
Authors: Ould Solomon , Guertler Matthias , Hanna Pavlos , Bennett Nick S.
Published: July 2022

This article presents an atypical offline based LoRaWAN application for use in hospital settings, where the ability to maintain network connectivity during internet connection disruption is paramount. A prototype bed rail is demonstrated, providing advanced functionality compared to traditional bed rails. The manufactured prototype provides data to a nurses station reliably and operates under battery backup. The power consumption of the system under different transmission intervals was tested, allowing appropriate battery sizing for different applications to be specified accurately. It is expected that a single LoRaWAN gateway will be able to cover bed rails across an entire modern hospital, allowing minimal infrastructure cost to implement the device or application in a rapidly deployed field hospital.
Bimodal Release Two-In-One Clonazepam Matrix Lozenge Tablets for Managing Anxiety-Related Disorders: Formulation, Optimization and In Vivo Evaluation
Authors: Gomaa Eman , El Deeb Sami , Ibrahim Adel Ehab , Faisal Mennatullah M.
Published: July 2022

Clonazepam (CLZ), an antipsychotic drug reported for its efficiency in managing anxiety-related disorders, is being marketed only as conventional tablets. Some patients have abstention to swallow the conventional tablets; therefore, the proposed study was aimed at developing a buccal lozenge tablet by direct compression of two types of optimized granules. Conazepam’s water solubility was first enhanced by a solid dispersion technique for a fast and better dissolution of type 1 granules, while the impact of gelling polymers was investigated on controlled-release type 2 granules. The optimized formulae met the acceptable pharmacopeial limits for tablets’ evaluation. A differential scanning calorimetry study revealed the compatibility between the drug and used excipients. All formulae gave a burst release of CLZ in the first hour of investigation, followed by a sustained release over 24 h. The formula that showed the highest prolonged in vitro release (99.0 + 0.1%), following the Higuchi diffusion model (R2 = 0.99), was then selected for further study. The formula succeeded in controlling the induced stress in a rat model with a significant impact on the behavioral tests throughout the experiment. The results were further confirmed by a pharmacokinetic study that showed a significant increase in Cmax, Tmax, and AUC (1.5, 2, and 3.9 folds), respectively, compared to oral suspension. The newly proposed delivery system has proven a better efficacy with a reduced dosing frequency.
A Comprehensive Photocatalysis Study of Promising Zirconia/Laser-Induced Graphene Nanocomposite for Wastewater Treatment-Based Methylene Blue Pollution
Authors: Shaalan Nagih M. , Rashad Mohamed , Saber Osama , Alshoaibi Adil , Awada Chawki
Published: July 2022

In this paper, the photocatalytic effect of zirconia/laser-induced graphene on the degradation of methylene blue was comprehensively studied. The average particle size measured by HRTEM is 6 nm for both ZrO2 and ZrO2/G10 samples, which explains the high-quality TEM imaging of isolated squared sections of cubic particles. The weight percentages of Zr, O, and C elements using EDX were 72.16, 18.56, and 9.28, respectively. These results confirm the formation of binary composites. Moreover, Raman scattering exhibited that the spectrum of pure ZrO2 was difficult to be detected due to the high luminescence. However, ZrO2 vibration modes were detected for ZrO2-graphene nanocomposites at 1012, 615, 246, and 150 cm−1. A shift of the D- and G-bands of graphene were observed, where D-peak and G-peak were observed at 1370 and 1575 cm−1 for ZrO2/5G and, 1361 and 1565 cm−1 for ZrO2/10G, respectively. The shift is ascribed to the incorporation of graphene into the surface of the oxide material. Compared to ZrO2, the newly fabricated ZrO2-graphene nanocomposites have the advantage of increased photocatalytic effects. An adsorbent concentration of 5 and 10 mg·L−1 at room temperature over 240 min was observed to be suitable experimental conditions. The kinetic results indicate that the practical results obtained are well expressed by the first-order kinetic model at different concentrations. In addition, the results showed that the addition of graphene led to a significant degradation process increase. The results also showed the significant effect of the investigated ZrO2-graphene nanocomposites on the decomposition of methylene blue cation. The decomposition of cationic pollutants showed a synergistic effect of the ZrO2-graphene nanocomposites on wastewater treatment.
Deep Learning-Based Segmentation of Post-Mortem Human’s Olfactory Bulb Structures in X-ray Phase-Contrast Tomography
Authors: Meshkov Alexandr , Khafizov Anvar , Buzmakov Alexey , Bukreeva Inna , Junemann Olga , Fratini Michela , Cedola Alessia , Chukalina Marina , Yamaev Andrei , Gigli Giuseppe , Wilde Fabian , Longo Elena , Asadchikov Victor , Saveliev Sergey , Nikolaev Dmitry
Published: July 2022

The human olfactory bulb (OB) has a laminar structure. The segregation of cell populations in the OB image poses a significant challenge because of indistinct boundaries of the layers. Standard 3D visualization tools usually have a low resolution and cannot provide the high accuracy required for morphometric analysis. X-ray phase contrast tomography (XPCT) offers sufficient resolution and contrast to identify single cells in large volumes of the brain. The numerous microanatomical structures detectable in XPCT image of the OB, however, greatly complicate the manual delineation of OB neuronal cell layers. To address the challenging problem of fully automated segmentation of XPCT images of human OB morphological layers, we propose a new pipeline for tomographic data processing. Convolutional neural networks (CNN) were used to segment XPCT image of native unstained human OB. Virtual segmentation of the whole OB and an accurate delineation of each layer in a healthy non-demented OB is mandatory as the first step for assessing OB morphological changes in smell impairment research. In this framework, we proposed an effective tool that could help to shed light on OB layer-specific degeneration in patients with olfactory disorder.