bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effectiveness of Imipenem–Relebactam against Ceftazidime-Avibactam Resistant Variants of the KPC-2 β-Lactamase
Authors: Papp-Wallace Krisztina M. , Barnes Melissa D. , Taracila Magdalena A. , Bethel Christopher R. , Rutter Joseph D. , Zeiser Elise T. , Young Katherine , Bonomo Robert A.
Published: May 2023

Background: Ceftazidime-avibactam was approved by the FDA to treat infections caused by Enterobacterales carrying blaKPC-2. However, variants of KPC-2 with amino acid substitutions at position 179 have emerged and confer resistance to ceftazidime-avibactam. Methods: The activity of imipenem-relebactam was assessed against a panel of 19 KPC-2 D179 variants. KPC-2 and the D179N and D179Y variants were purified for biochemical analyses. Molecular models were constructed with imipenem to assess differences in kinetic profiles. Results: All strains were susceptible to imipenem–relebactam, but resistant to ceftazidime (19/19) and ceftazidime-avibactam (18/19). KPC-2 and the D179N variant hydrolyzed imipenem, but the D179N variant’s rate was much slower. The D179Y variant was unable to turnover imipenem. All three β-lactamases hydrolyzed ceftazidime at varying rates. The acylation rate of relebactam for the D179N variant was ~2.5× lower than KPC-2. Poor catalytic turnover by the D179Y variant precluded the determination of inhibitory kinetic parameters. Acyl-complexes with imipenem and ceftazidime were less prevalent with the D179N variant compared to the D179Y variant, supporting the kinetic observations that the D179Y variant was not as active as the D179N variant. Relebactam was slower to form an acyl-complex with the D179Y variant compared to avibactam. The D179Y model with imipenem revealed that the catalytic water molecule was shifted, and the carbonyl of imipenem was not within the oxyanion hole. Conversely in the D179N model, imipenem was oriented favorably for deacylation. Conclusions: Imipenem–relebactam overcame the resistance of the D179 variants, suggesting that this combination will be active against clinical isolates harboring these derivatives of KPC-2.
Thermodynamic Behavior of As, Pb, and As during the Vacuum Carbothermal Reduction of Copper Anode Slime
Authors: Deng Juhai , Zha Guozheng , Liu Dachun , He Jilin , Jiang Wenlong
Published: May 2023

The use of copper anode slime (CAS) for the removal of lead, bismuth, and arsenic is the key to recovering precious metals. In this paper, vacuum differential gravimetry experiments combined with thermodynamic equilibrium calculations reveal the effects of the temperature, system pressure, and carbon concentration on the interactions among Pb, Bi, and As during reduction. The carbon content is a direct factor limiting the reduction reactions of sulfate and arsenate phases, and affects the presence of arsenate reduction products. When the carbon content of the system is insufficient, As mainly exists as oxides in the reduction products, and the form of arsenic gradually converts to monomers with increasing carbon content. The reduction product Bi2S3 gradually converts to Bi and BiS as the temperature increases. The effect of temperature on arsenate is mainly related to the phase of the Pb- and Bi-containing reduction products. Moreover, vacuum differential gravimetry experiments were performed to verify the phase transformation of As, Pb, and Bi in CAS during vacuum carbon thermal reduction.
Heavy Metals in Post-Exploitation Reservoirs—The Bagry Lake Case Study (Poland)
Authors: Bielski Andrzej , Czaplicka Anna
Published: May 2023

The paper presents the research study on the concentration of Fe, Mn, Cu, Pb, Zn, Cd and Ca in the sediment as well as in the supernatant (layer of water just above the sediment) of the Bagry Lake, Cracow (Poland); Ca was not included in the supernatant analysis. There are a number of works in the literature on the concentrations of metals in the water environment of flow-through dam reservoirs and factors influencing their distribution. These reservoirs were created for various purposes, e.g., water supply, flood protection, leveling the flows in the rivers and recreational purposes. Since it is difficult to find information on metals and factors influencing their distribution in the aquatic environment of post-exploitation reservoirs, this work aims to fill this gap. The additional purpose of the work was to assess the potential influence of metals’ presence in the sediment of Bagry Lake on benthic organisms. Correlations between metals in the sediment and their volatile and mineral fractions as well as in particle size fractions of ≥0.06 mm and <0.06 mm were determined. Except for cadmium, metals showed a positive correlation with the sediment volatile fraction of granulometry <0.06 mm (a clay-silty fraction). It has been shown that metals, in both supernatant and sediment, are of an anthropogenic origin related to previous on-lake operations, as well as a nearby modern technical infrastructure. Statistical models were used to measure the strength of relationships between the concentration of various metals in the sediments. A cluster analysis was used to study interactions between the concentration of metals in supernatant, in sediment and in its volatile and mineral fractions as well as in fractions with different granulation. It was found that individual metals and sediment fractions form pairs of quite strong clusters, e.g., Fe sediments and Mn sediments, Fe supernatant and Mn supernatant, Cu supernatant and Pb supernatant, volatile fraction and mass fraction of particles < 0.06 mm and mineral fraction and mass fraction of particles ≥ 0.06 mm. The equilibrium model “supernatant—sediment mineral fraction—sediment volatile fraction” was developed for metals in various granulometric fractions of the sediment as well as in the supernatant. The model estimated a metal concentration in both fractions of the sediment (separately) as well as an impact they had on the metal concentration in the supernatant. It also showed how changes in a metal’s concentration in both fractions are reflected in concentrations of metals in the aquatic environment.
OISE: Optimized Input Sampling Explanation with a Saliency Map Based on the Black-Box Model
Authors: Wang Zhan , Joe Inwhee
Published: May 2023

With the development of artificial intelligence technology, machine learning models are becoming more complex and accurate. However, the explainability of the models is decreasing, and much of the decision process is still unclear and difficult to explain to users. Therefore, we now often use Explainable Artificial Intelligence (XAI) techniques to make models transparent and explainable. For an image, the ability to recognize its content is one of the major contributions of XAI techniques to image recognition. Visual methods for describing classification decisions within an image are usually expressed in terms of salience to indicate the importance of each pixel. In some approaches, explainability is achieved by deforming and integrating white-box models, which limits the use of specific network architectures. Therefore, in contrast to white-box model-based approaches that use weights or other internal network states to estimate pixel saliency, we propose the Optimized Input Sampling Explanation (OISE) technique based on black-box models. OISE uses masks to generate saliency maps that reflect the importance of each pixel to the model predictions, and employs black-box models to empirically infer the importance of each pixel. We evaluate our method using deleted/inserted pixels, and extensive experiments on several basic datasets show that OISE achieves better visual performance and fairness in explaining the decision process compared to the performance of other methods. This approach makes the decision process clearly visible, makes the model transparent and explainable, and serves to explain it to users.
A Framework for Urban Last-Mile Delivery Traffic Forecasting: An In-Depth Review of Social Media Analytics and Deep Learning Techniques
Authors: Laynes-Fiascunari Valeria , Gutierrez-Franco Edgar , Rabelo Luis , Sarmiento Alfonso T. , Lee Gene
Published: May 2023

The proliferation of e-commerce in recent years has been driven in part by the increasing ease of making purchases online and having them delivered directly to the consumer. However, these last-mile delivery logistics have become complex due to external factors (traffic, weather, etc.) affecting the delivery routes’ optimization. Intelligent Transportation Systems (ITS) also have a challenge that contributes to the need of delivery companies for traffic sensors in urban areas. The main purpose of this paper is to propose a framework that closes the gap on accurate traffic prediction tailored for last-mile delivery logistics, leveraging social media analysis along with traditional methods. This work can be divided into two stages: (1) traffic prediction, which utilizes advanced deep learning techniques such as Graph Convolutional and Long-Short Term Memory Neural Networks, as well as data from sources such as social media check-ins and Collaborative Innovation Networks (COINs); and (2) experimentation in both short- and long-term settings, examining the interactions of traffic, social media, weather, and other factors within the model. The proposed framework allows for the integration of additional analytical techniques to further enhance vehicle routing, including the use of simulation tools such as agent-based simulation, discrete-event simulation, and system dynamics.
Design of a Power Converter for Solar Energy Storage System
Authors: Yan Yih-Her , Chang Yong-Nong , Wu Yan-Yong
Published: May 2023

This paper presents a single-stage three-port isolated power converter that enables energy conversion among a renewable energy port, a battery energy storage port, and a DC grid port. The proposed converter integrates an interleaved synchronous rectifier boost circuit and a bidirectional full-bridge circuit into a single-stage architecture, which features four power conversion modes, allowing energy adjustment for both the renewable energy and the battery storage energy ports when power is supplied by the renewable energy port. It also features bidirectional functionality that allows the battery storage energy port to provide energy storage through the DC grid port, thereby providing uninterrupted power supply functionality. The converter uses four power switches and two inductors to boost and convert energy from the renewable energy port to the battery storage energy port or to the DC grid port through the bidirectional full-bridge circuit. The converter is also capable of 1 kW power energy conversion by utilizing an adjustable duty cycle with a fixed frequency of 100 kHz and phase-shift control through a built-in pulse width modulation control module of a TMS320F28 series digital signal processor. According to the experimental results, the converter developed in this study can achieve a conversion efficiency of up to 94%.
Physicochemical and Microbiological Changes Associated with Processing in Dry-Cured Tuna
Authors: Sánchez-Parra Mónica , Ordóñez-Díaz José L. , Pérez-Aparicio Jesús , Moreno-Rojas José M.
Published: May 2023

Dry-cured tuna is a traditional product manufactured in the Mediterranean region of Spain, known as mojama. The traditional salting-drying elaboration process attributes new organoleptic characteristics to the final product, changing its flavor, color, and nutritional value. This study aimed to evaluate the changes in physicochemical, biochemical, and microbiological parameters taking place during the process. The physicochemical parameters were affected by the processing steps (salting, salt-washing, and drying), except for total acidity and pH. The water activity value and relative moisture percentage decreased to 0.86 and 33.03%, respectively. Moreover, the addition of salt and the drying step increased the water-holding capacity. The lipid oxidation values increased from raw tuna loins to the final product (1.37 vs. 5.56 mg malondialdehyde/kg). Moreover, the total volatile basic nitrogen values increased in the final product, fundamentally due to the concentration effect caused by the water loss, although may also be due to the degradation of proteins during processing. The microbiological analysis showed that the values obtained in the dry-cured tuna were below the limits established by the reference regulation for dry-cured fish products.
Special Issue on Multiphase Flows in Microfluidics: Fundamentals and Applications
Authors: Lin Jianzhong
Published: May 2023

Microfluidics, a cutting-edge field involving various applications in advanced materials, new energy, single-cell/single-molecule studies, human health, biomedicine, and so forth, has advanced rapidly in the last two decades [...]
Study on the Mechanical Properties and Hydration Behavior of Steel Slag–Red Mud–Electrolytic Manganese Residue Based Composite Mortar
Authors: Zhou Libo , Chen Ping , Hu Cheng , Xia Haiyang , Liang Zhifeng
Published: May 2023

The functional and mechanical properties of steel slag (SS)–red mud (RM)–electrolytic manganese residue (EMR)-based composite mortar under different matching ratio conditions were investigated in this paper to examine the synergistic cementing effect among multiple solid wastes. The hydration characteristics of the composite mortar and its microstructure were characterized by the heat of hydration assessment, X-ray diffraction, thermogravimetric analysis, and other tests. The results of the study showed that compared with the pure cement group, 30% SS alone will inhibit the hydration reaction of the slurry, thus reducing the mechanical properties of the mortar, while compounding the appropriate amount of RM, and EMR can effectively reduce the negative impact of SS on the mechanical properties of the mortar. The flexural and compressive strengths of the composite mortar at 28 d were the highest when 15% of SS, 12% of RM, and 3% of EMR were mixed, which were 7.2 MPa and 41.4 MPa at 28 d, respectively. Compared with the test group with 30% SS alone, the flexural and compressive strengths increased by 18.0% and 25.5%. This is mainly because the incorporation of RM and EMR not only plays the role of physical filling, but the free alkali in RM and sulfate material in EMR can also compoundly stimulate the hydration activity of SS to produce more calcium alumina (AFt) and hydrated calcium silicate (C–S–H gel), thus improving the microstructure of mortar, which makes the overall decrease of 26.35% of multiharmful and harmful pores and the overall increase of harmless and less harmful pores of composite mortar specimens of 43.57%.
Automatic Classification of Coronary Stenosis Using Feature Selection and a Hybrid Evolutionary Algorithm
Authors: Gil-Rios Miguel-Angel , Chalopin Claire , Cruz-Aceves Ivan , Lopez-Hernandez Juan-Manuel , Hernandez-Gonzalez Martha-Alicia , Solorio-Meza Sergio-Eduardo
Published: May 2023

In this paper, a novel method for the automatic classification of coronary stenosis based on a feature selection strategy driven by a hybrid evolutionary algorithm is proposed. The main contribution is the characterization of the coronary stenosis anomaly based on the automatic selection of an efficient feature subset. The initial feature set consists of 49 features involving intensity, texture and morphology. Since the feature selection search space was O(2n), being n=49, it was treated as a high-dimensional combinatorial problem. For this reason, different single and hybrid evolutionary algorithms were compared, where the hybrid method based on the Boltzmann univariate marginal distribution algorithm (BUMDA) and simulated annealing (SA) achieved the best performance using a training set of X-ray coronary angiograms. Moreover, two different databases with 500 and 2700 stenosis images, respectively, were used for training and testing of the proposed method. In the experimental results, the proposed method for feature selection obtained a subset of 11 features, achieving a feature reduction rate of 77.5% and a classification accuracy of 0.96 using the training set. In the testing step, the proposed method was compared with different state-of-the-art classification methods in both databases, obtaining a classification accuracy and Jaccard coefficient of 0.90 and 0.81 in the first one, and 0.92 and 0.85 in the second one, respectively. In addition, based on the proposed method’s execution time for testing images (0.02 s per image), it can be highly suitable for use as part of a clinical decision support system.
Evaluating the Potential of an Oral-Based Bioguard to Estimate Heart Rate Using Photoplethysmography
Authors: de Almeida e Bueno Leonardo , Walls Victoria C. , Bergmann Jeroen H. M.
Published: May 2023

The reliable monitoring of heart rate during intense exercise is imperative to effectively manage training loads while providing insights from a healthcare perspective. However, current technologies perform poorly in contact sports settings. This study aims to evaluate the best approach for heart rate tracking using photoplethysmography sensors embedded into an instrumented mouthguard (iMG). Seven adults wore iMGs and a reference heart rate monitor. Several sensor placements, light sources and signal intensities were explored for the iMG. A novel metric related to the positioning of the sensor in the gum was introduced. The error between the iMG heart rate and the reference data was assessed to obtain insights into the effect of specific iMG configurations on measurement errors. Signal intensity was found to be the most important variable for error prediction, followed by the sensor light source, sensor placement and positioning. A generalized linear model combining an infrared light source, at an intensity of 5.08 mA, and a frontal placement high in the gum area resulted in a heart rate minimum error of 16.33%. This research shows promising preliminary results for the use of oral-based heart rate monitoring, but highlights the need for the careful consideration of sensor configurations within these systems.
Porous Colorimetric Microneedles for Minimally Invasive Rapid Glucose Sampling and Sensing in Skin Interstitial Fluid
Authors: Zeng Qingya , Xu Mengxin , Hu Weilun , Cao Wenyu , Zhan Yujie , Zhang Yuxin , Wang Qingqing , Ma Tao
Published: May 2023

Though monitoring blood glucose (BG) is indispensable for regulating diabetes, the frequent pricking of the finger by the commonly used fingertip blood collection causes discomfort and poses an infection risk. Since glucose levels in skin interstitial fluid (ISF) correlate with blood glucose levels, monitoring glucose in the skin ISF can be a viable alternative. With this rationale, the present study developed a biocompatible porous microneedle capable of rapid sampling, sensing, and glucose analysis in ISF in a minimally invasive manner, which can improve patient compliance and detection efficiency. The microneedles contain glucose oxidase (GOx) and horseradish peroxidase (HRP), and a colorimetric sensing layer containing 3,3′,5,5′-tetramethylbenzidine (TMB) is on the back of the microneedles. After penetrating rat skin, porous microneedles harvest ISF rapidly and smoothly via capillary action, triggering the production of hydrogen peroxide (H2O2) from glucose. In the presence of H2O2, HRP reacts with TMB contained in the filter paper on the back of microneedles, causing an easily visible color shift. Further, a smartphone analysis of the images quickly quantifies glucose levels in the 50–400 mg/dL range using the correlation between color intensity and glucose concentration. The developed microneedle-based sensing technique with minimally invasive sampling will have great implications for point-of-care clinical diagnosis and diabetic health management.
Powered Mobility Device Use and Developmental Change of Young Children with Cerebral Palsy
Authors: Logan Samuel W. , Sloane Bethany M. , Kenyon Lisa K. , Feldner Heather A.
Published: May 2023

Mobility is a fundamental human right and is supported by the United Nations and the ON Time Mobility framework. The purpose of this study was to understand the effect of a powered mobility intervention on developmental changes of children with cerebral palsy (CP). This study was a randomized, crossover clinical trial involving 24 children (12–36 months) diagnosed with CP or with high probability of future CP diagnosis based on birth history and current developmental status. Children received the Explorer Mini and a modified ride-on car in randomized order, each for 8 weeks. The Bayley Scales of Infant and Toddler Development—4th Edition was administered at baseline, mid-study, and end-of-study. Raw change scores were used for analysis. Total minutes of use per device was categorized as low or high use for analysis based on caregiver-reported driving diaries. Explorer Mini: The high use group exhibited significantly greater positive change scores compared to the low use group on receptive communication, expressive communication, and gross motor subscales (p < 0.05). Modified ride-on car: No significant differences between low and high use groups. Regardless of device, low use was associated with no significant developmental change and high use was associated with positive developmental changes. Mobility access is critical to maximize the development of children with CP and may be augmented by using powered mobility devices. Results may have implications for the development of evidence-based guidelines on dosage for powered mobility use.
Engineering Surface Properties of CuO/Ce0.6Zr0.4O2 Catalysts for Efficient Low-Temperature Toluene Oxidation
Authors: Wang Mingyue , Zhang Qiulin , Zou Meilin , Wang Jingge , Zhu Danrui , Liu Jiaying , Wang Junwei , Zuo Yang , Chen Jianjun , Ning Ping
Published: May 2023

The development of superior low-temperature catalytic performance and inexpensive catalysts for the removal of volatile organic compounds (VOCs) is crucial for their industrial application. Herein, CuO/Ce0.6Zr0.4O2 catalysts calcinated at different temperatures (Cu/CZ-X, X represented calcination temperature) were prepared and used to eliminate toluene. It can be found that Cu/CZ-550 presented the highest low-temperature catalytic activity, with the lowest temperature (220 °C) 50% conversion of toluene, the highest normalized reaction rate (3.1 × 10−5 mol·g−1·s−1 at 180 °C) and the lowest apparent activation energy value (86.3 ± 4.7 kJ·mol−1). Systematically, the surface properties analysis results showed that the optimum redox property, abundant oxygen vacancies, and plentiful surface Ce3+ species over Cu/CZ-550 were associated with the strong interaction between Cu and support could significantly favor the adsorption and activation of toluene, thus resulting in its superior catalytic performance.
Tailoring of Three-Atom Metal Cluster Catalysts for Ammonia Synthesis
Authors: Wang Shuo , Zhao Tingting , Yan Likai
Published: May 2023

Electrocatalytic nitrogen reduction reaction (NRR) can realize the green production of ammonia while developing electrocatalysts with high selectivity and ability is still an ongoing challenge. Two-dimensional (2D) graphitic carbon nitride (CN) frameworks can provide abundant hollow sites for stably anchoring several transition metal (TM) atoms to facilitate single-cluster catalysis, promising to overcome the problems of low activity and poor selectivity in the process of ammonia synthesis. Herein, extensive density functional theory (DFT) calculations were performed to investigate the feasibility of six bimetallic triatomic clusters FexMoy (x = 1, 2; x + y = 3) supported on C6N6, C2N, and N-doped porous graphene (NG) as NRR electrocatalysts. Through a systematic screening strategy, we found that the Fe2Mo–NG possesses the highest activity with a limiting potential of –0.36 V through the enzymatic mechanism and could be the promising catalyst for NH3 synthesis. The Fe2Mo moiety in Fe2Mo–NG moderately regulates the electron transfer between reaction intermediates and NG, which is ascribed to enhanced performance. This work accelerates the rational design of catalysts in the field of NRR and contributes to broadening the understanding of cluster catalysis.
Characterization and High-Temperature Oxidation Behavior of Ni–20Cr Deposits Fabricated by Cold Spray-Based Additive Manufacturing
Authors: Singh Parminder , Singh Surinder , Singh Harpreet , Calla Eklavya , Grewal Harpreet , Arora Harpreet , Krishnamurthy Anand
Published: May 2023

Hot corrosion is a critical problem in a wide range of high-temperature applications. Ni–20Cr alloy is frequently used in such applications owing to its good hot-corrosion resistance. In the current work, thick Ni–20Cr plates in a thickness range of 6–10 mm were fabricated using cold spray-based additive manufacturing (CSAM). High-pressure cold spraying was used with nitrogen as the propellant gas. Pre- (substrate heating, SH) and post-heat treatments (hot isostatic pressing, HIP) were also performed to comprehend the changes in the deposit properties. The deposits were subjected to microstructural and mechanical characterization to explore the potential of cold spraying for CSAM of Ni–20Cr standalone products. The cold-sprayed plates were successfully developed without any oxide formation. HIP treatment was found to be useful to reduce porosity. The cold-sprayed substrate-heated Ni–20Cr deposits exhibited excellent oxidation resistance at a high temperature of 900 °C.
Microstructure Refinement of EB-PVD Gadolinium Zirconate Thermal Barrier Coatings to Improve Their CMAS Resistance
Authors: Mikulla Christoph , Steinberg Lars , Niemeyer Philipp , Schulz Uwe , Naraparaju Ravisankar
Published: May 2023

Rare-earth zirconates are proven to be very effective in restricting the CMAS attack against thermal barrier coatings (TBCs) by forming quick crystalline reaction products that seal the porosity against infiltration. The microstructural effects on the efficacy of Electron Beam-Physical Vapor Deposition gadolinium zirconate (EB-PVD GZO) against CMAS attack are explored in this study. Four distinct GZO microstructures were manufactured and the response of two selected GZO variants to different CMAS and volcanic ash melts was studied for annealing times between 10 min and 50 h at 1250 °C. A significant variation in the microstructural characteristics was achieved by altering substrate temperature and rotation speed. A refined microstructure with smaller intercolumnar gaps and long feather arms lowered the CMAS infiltration by 56%–72%. Garnet phase, which formed as a continuous layer on top of apatite and fluorite, is identified as a beneficial reaction product that improves the CMAS resistance.
Thermal Decomposition and Solidification Characteristics of BFFO
Authors: Luo Yiming , Ju Ronghui , Li Bingbo , Meng Junjiong , Wang Xuanjun
Published: May 2023

A novel energetic material, Bifurazano [3,4-b: 3′,4′-f] furoxano [3″,4″-d] oxacyclo-heptatriene (BFFO), has been investigated regarding two aspects, namely its thermal decomposition and solidification characteristics. The DSC curves indicate that the peak temperature of BFFO decomposition process is 271.1 °C under the static pressure of 2 MPa and the volatility of BFFO at 120 °C is significantly lower than that of TNT, DNAN and DNTF. The solidification curve indicates that the solidification of BFFO is a basic linear uniform solidification process, which is obviously different from that of TNT, DNAN and DNTF. In addition, the facet of BFFO appears much smoother and fewer defects are observed in the solidified body after solidification via CT and SEM. The reduction in solidification defects also further improves the mechanical properties of BFFO, with significant improvements in compressive and tensile strength compared to DNTF, DNAN and TNT. In summary, BFFO is a potential melt-cast carrier explosive with excellent thermal stability, solidification characteristics and mechanical properties.
Feasibility of Renal Blood Flow Measurement Using 64Cu-ATSM PET/MRI: A Quantitative PET and MRI Study
Authors: Nishikawa Yudai , Takahashi Naoki , Nishikawa Sho , Shimamoto Yuki , Nishimori Kazuhisa , Kobayashi Mamiko , Kimura Hideki , Tsujikawa Tetsuya , Kasuno Kenji , Mori Tetsuya , Kiyono Yasushi , Okazawa Hidehiko , Iwano Masayuki
Published: May 2023

This study aimed to evaluate the renal blood flow (RBF) in patients with chronic kidney disease (CKD) using 64Cu(II)-diacetyl-bis(4-methylthiosemicarbazonate) (64Cu-ATSM) for positron emission tomography (PET)/magnetic resonance imaging (MRI). We included five healthy controls (HCs) and ten patients with CKD. The estimated glomerular filtration rate (eGFR) was calculated from the serum creatinine (cr) and cystatin C (cys) levels. The estimated RBF (eRBF) was calculated using the eGFR, hematocrit, and filtration fraction. A single dose of 64Cu-ATSM (300–400 MBq) was administered for RBF evaluation, and a 40 min dynamic PET scan was performed with simultaneous arterial spin labeling (ASL) imaging. PET-RBF images were obtained from the dynamic PET images at 3 min after injection using the image-derived input function method. The mean eRBF values calculated from various eGFR values differed significantly between the patients and HCs; both groups also differed significantly in terms of the RBF values (mL/min/100 g) measured using PET (151 ± 20 vs. 124 ± 22, p < 0.05) and ASL-MRI (172 ± 38 vs. 125 ± 30, p < 0.001). The ASL-MRI-RBF was positively correlated with the eRBFcr-cys (r = 0.858, p < 0.001). The PET-RBF was positively correlated with the eRBFcr-cys (r = 0.893, p < 0.001). The ASL-RBF was positively correlated with the PET-RBF (r = 0.849, p < 0.001). 64Cu-ATSM PET/MRI demonstrated the reliability of PET-RBF and ASL-RBF by comparing them with eRBF. This is the first study to demonstrate that 64Cu-ATSM-PET is useful for assessing the RBF and is well correlated with ASL-MRI.
Fetal Health State Detection Using Interval Type-2 Fuzzy Neural Networks
Authors: Abiyev Rahib , Idoko John Bush , Altıparmak Hamit , Tüzünkan Murat
Published: May 2023

Diagnosis of fetal health is a difficult process that depends on various input factors. Depending on the values or the interval of values of these input symptoms, the detection of fetal health status is implemented. Sometimes it is difficult to determine the exact values of the intervals for diagnosing the diseases and there may always be disagreement between the expert doctors. As a result, the diagnosis of diseases is often carried out in uncertain conditions and can sometimes cause undesirable errors. Therefore, the vague nature of diseases and incomplete patient data can lead to uncertain decisions. One of the effective approaches to solve such kind of problem is the use of fuzzy logic in the construction of the diagnostic system. This paper proposes a type-2 fuzzy neural system (T2-FNN) for the detection of fetal health status. The structure and design algorithms of the T2-FNN system are presented. Cardiotocography, which provides information about the fetal heart rate and uterine contractions, is employed for monitoring fetal status. Using measured statistical data, the design of the system is implemented. Comparisons of various models are presented to prove the effectiveness of the proposed system. The system can be utilized in clinical information systems to obtain valuable information about fetal health status.
Deep versus Handcrafted Tensor Radiomics Features: Prediction of Survival in Head and Neck Cancer Using Machine Learning and Fusion Techniques
Authors: Salmanpour Mohammad R. , Rezaeijo Seyed Masoud , Hosseinzadeh Mahdi , Rahmim Arman
Published: May 2023

Background: Although handcrafted radiomics features (RF) are commonly extracted via radiomics software, employing deep features (DF) extracted from deep learning (DL) algorithms merits significant investigation. Moreover, a “tensor’’ radiomics paradigm where various flavours of a given feature are generated and explored can provide added value. We aimed to employ conventional and tensor DFs, and compare their outcome prediction performance to conventional and tensor RFs. Methods: 408 patients with head and neck cancer were selected from TCIA. PET images were first registered to CT, enhanced, normalized, and cropped. We employed 15 image-level fusion techniques (e.g., dual tree complex wavelet transform (DTCWT)) to combine PET and CT images. Subsequently, 215 RFs were extracted from each tumor in 17 images (or flavours) including CT only, PET only, and 15 fused PET-CT images through the standardized-SERA radiomics software. Furthermore, a 3 dimensional autoencoder was used to extract DFs. To predict the binary progression-free-survival-outcome, first, an end-to-end CNN algorithm was employed. Subsequently, we applied conventional and tensor DFs vs. RFs as extracted from each image to three sole classifiers, namely multilayer perceptron (MLP), random-forest, and logistic regression (LR), linked with dimension reduction algorithms. Results: DTCWT fusion linked with CNN resulted in accuracies of 75.6 ± 7.0% and 63.4 ± 6.7% in five-fold cross-validation and external-nested-testing, respectively. For the tensor RF-framework, polynomial transform algorithms + analysis of variance feature selector (ANOVA) + LR enabled 76.67 ± 3.3% and 70.6 ± 6.7% in the mentioned tests. For the tensor DF framework, PCA + ANOVA + MLP arrived at 87.0 ± 3.5% and 85.3 ± 5.2% in both tests. Conclusions: This study showed that tensor DF combined with proper machine learning approaches enhanced survival prediction performance compared to conventional DF, tensor and conventional RF, and end-to-end CNN frameworks.
Is There Still a Role for Invasive Assessment of Aortic Gradient?
Authors: Angellotti Domenico , Immobile Molaro Maddalena , Simonetti Fiorenzo , Ilardi Federica , Castiello Domenico Simone , Mariani Andrea , Manzo Rachele , Avvedimento Marisa , Leone Attilio , Nappa Dalila , Piccolo Raffaele , Losi Maria Angela , Franzone Anna , Esposito Giovanni
Published: May 2023

Advances in technology and imaging have expanded the range of tools for diagnosing aortic stenosis (AS). The accurate assessment of aortic valve area and mean pressure gradient is crucial to determine which patients are appropriate candidates for aortic valve replacement. Nowadays, these values can be obtained noninvasively or invasively, with similar results. Contrariwise, in the past, cardiac catheterization played a major role in the evaluation of AS severity. In this review, we will discuss the historical role of the invasive assessment of AS. Moreover, we will specifically focus on tips and tricks for properly performing cardiac catheterization in patients with AS. We will also elucidate the role of invasive methods in current clinical practice and their additional value to the information provided through non-invasive techniques.
Teachers’ Perceptions and Appropriation of EFL Educational Reforms: Insights from Generalist Teachers Teaching English in Mexican Rural Schools
Authors: Hernández Hernández Miguel , Izquierdo Jesús
Published: May 2023

Educational reforms and educational policy changes have favored the learning of English as a foreign language (EFL) in public education. Empirical research has examined how EFL specialist teachers in urban public schools perceive these changes or the extent to which they adopt a new curriculum. Nonetheless, the new EFL policies have also had an impact on rural schools where generalist teachers are forced to teach English along with other areas of the curriculum. In this context, little research has explored teachers’ perceptions and appropriation of ongoing curricular changes. The present study explored this issue among generalist rural secondary school teachers in the southeast of Mexico. To this end, an explanatory sequential mixed method was adopted with a sample of 216 generalist teachers. During the quantitative phase, the participants completed two Likert scale questionnaires. Then, a semi-structured interview was conducted with a sub-sample of participants who obtained high (n = 7) or low (n = 7) results in the perceptions and appropriation questionnaires. The statistical analyses showed a weak but positive correlation between perceptions and appropriation. The qualitative data provide some insights that explain the weakness of the correlation.
Energy-Based MRI Semantic Augmented Segmentation for Unpaired CT Images
Authors: Cai Shengliang , Shen Chuyun , Wang Xiangfeng
Published: May 2023

The multimodal segmentation of medical images is essential for clinical applications as it allows medical professionals to detect anomalies, monitor treatment effectiveness, and make informed therapeutic decisions. However, existing segmentation methods depend on paired images of modalities, which may not always be available in practical scenarios, thereby limiting their applicability. To address this challenge, current approaches aim to align modalities or generate missing modality images without a ground truth, which can introduce irrelevant texture details. In this paper, we propose the energy-basedsemantic augmented segmentation (ESAS) model, which employs the energy of latent semantic features from a supporting modality to enhance the segmentation performance on unpaired query modality data. The proposed ESAS model is a lightweight and efficient framework suitable for most unpaired multimodal image-learning tasks. We demonstrate the effectiveness of our ESAS model on the MM-WHS 2017 challenge dataset, where it significantly improved Dice accuracy for cardiac segmentation on CT volumes. Our results highlight the potential of the proposed ESAS model to enhance patient outcomes in clinical settings by providing a promising approach for unpaired multimodal medical image segmentation tasks.
Booth Encoded Bit-Serial Multiply-Accumulate Units with Improved Area and Energy Efficiencies
Authors: Cheng Xiaoshu , Wang Yiwen , Liu Jiazhi , Ding Weiran , Lou Hongfei , Li Ping
Published: May 2023

Bit-serial multiply-accumulate units (MACs) play a crucial role in various hardware accelerator applications, including deep learning, image processing, and signal processing. Despite the advantages of bit-serial MACs, such as a small footprint, full hardware utilization, and high frequency, their serial nature can lead to high latency and potentially compromised performance. This study investigates the potential of bit-serial solutions by applying Booth encoding to bit-serial multipliers within MACs to enhance area and power efficiencies. We present two types of bit-serial MACs based on radix-2 and radix-4 Booth encoding multipliers, respectively. Their performance is assessed through simulations and synthesis results, demonstrating the benefits of the proposed approach. The radix-4 Booth bit-serial MAC improves power and area efficiencies compared to the original bit-serial MAC. Operating at TSMC 90 nm and 150 MHz, our design exhibits a remarkable 96.39% reduction in area-power-product (APP). Moreover, the prototype verification on a Xilinx Kintex-7 FPGA proved successful. The proposed solution offers significant advantages in energy efficiency, area reduction, and APP, making it a promising candidate for next-generation hardware accelerators in offline inference, low-power devices, and other applications.
Driver Stress Detection from Physiological Signals by Virtual Reality Simulator
Authors: Mateos-García Nuria , Gil-González Ana-Belén , Luis-Reboredo Ana , Pérez-Lancho Belén
Published: May 2023

One of the many areas in which artificial intelligence (AI) techniques are used is the development of systems for the recognition of vital emotions to control human health and safety. This study used biometric sensors in a multimodal approach to capture signals in the recognition of stressful situations. The great advances in technology have allowed the development of portable devices capable of monitoring different physiological measures in an inexpensive, non-invasive, and efficient manner. Virtual reality (VR) has evolved to achieve a realistic immersive experience in different contexts. The combination of AI, signal acquisition devices, and VR makes it possible to generate useful knowledge even in challenging situations in daily life, such as when driving. The main goal of this work is to combine the use of sensors and the possibilities offered by VR for the creation of a system for recognizing stress during different driving situations in a vehicle. We investigated the feasibility of detecting stress in individuals using physiological signals collected using a photoplethysmography (PPG) sensor incorporated into a commonly used wristwatch. We developed an immersive environment based on VR to simulate experimental situations and collect information on the user’s reactions through the detection of physiological signals. Data collected through sensors in the VR simulations are taken as input to several models previously trained by machine learning (ML) algorithms to obtain a system that performs driver stress detection and high-precision classification in real time.
A Wirelessly-Powered Body-Coupled Data Transmission with Multi-Stage and Multi-Source Rectifier
Authors: Kim Byeongseol , Bae Joonsung
Published: May 2023

This paper demonstrates body-coupled (BC) data transmission and multi-source power delivery systems for neural interface applications. The implanted data transmitter and power receiver utilize an electrode interface rather than an antenna or coil interface for battery-free wireless transmission, enabling the external data receiver and power transmitter with patch electrodes to be placed away from the implant without requiring precise alignment, which is a critical issue in the conventional communication modalities of inductive coupling. Significantly, the implanted power receiver produces the supply voltage using ambient body-coupled 50/60 Hz signals from the Mains, on top of the 40.68 MHz wireless power source from the external power transmitter, to increase the recovered power level and the voltage conversion efficiency (VCE). The body-coupled wireless systems for implanted and external devices are implemented with integrated circuits (ICs) fabricated in a 180 nm CMOS process. When 650 mVpp AC voltage is applied to the implanted device, the power receiver recovers up to 780 μW with ambient (60 Hz signals) BC energy harvesting, achieving 93% VCE, while 600 μW is recovered without ambient (60 Hz signals) signal. The recovered power supplies the regulated voltage to the direct-digital signaling transceiver, which consumes 460 μW with an uplink data rate of 10 Mbps and a downlink data rate of 200 kbps, corresponding to an energy efficiency of 46 pJ/b.
Multimodal Natural Language Explanation Generation for Visual Question Answering Based on Multiple Reference Data
Authors: Zhu He , Togo Ren , Ogawa Takahiro , Haseyama Miki
Published: May 2023

As deep learning research continues to advance, interpretability is becoming as important as model performance. Conducting interpretability studies to understand the decision-making processes of deep learning models can improve performance and provide valuable insights for humans. The interpretability of visual question answering (VQA), a crucial task for human–computer interaction, has garnered the attention of researchers due to its wide range of applications. The generation of natural language explanations for VQA that humans can better understand has gradually supplanted heatmap representations as the mainstream focus in the field. Humans typically answer questions by first identifying the primary objects in an image and then referring to various information sources, both within and beyond the image, including prior knowledge. However, previous studies have only considered input images, resulting in insufficient information that can lead to incorrect answers and implausible explanations. To address this issue, we introduce multiple references in addition to the input image. Specifically, we propose a multimodal model that generates natural language explanations for VQA. We introduce outside knowledge using the input image and question and incorporate object information into the model through an object detection module. By increasing the information available during the model generation process, we significantly improve VQA accuracy and the reliability of the generated explanations. Moreover, we employ a simple and effective feature fusion joint vector to combine information from multiple modalities while maximizing information preservation. Qualitative and quantitative evaluation experiments demonstrate that the proposed method can generate more reliable explanations than state-of-the-art methods while maintaining answering accuracy.
Underdetermined Blind Source Separation Method Based on a Two-Stage Single-Source Point Screening
Authors: Zhu Zhanyu , Chen Xingjie , Lv Zhaomin
Published: May 2023

Underdetermined blind source separation is a signal processing technique that is more suitable for practical applications and aims to separate the source signals from the mixed signals. The mixing matrix estimation is a major step in the underdetermined blind source separation. Since the current methods for estimating the mixing matrix have the disadvantages of insufficient accuracy or weak noise immunity, a two-stage single-source point screening that combines the cosine angle algorithm and the L1-norm optimization algorithm is proposed. During the first stage, the first-stage single-source points are extracted from the original mixed signals using the cosine angle algorithm. During the second stage, based on the L1-norm optimization algorithm, the reference single-source points are extracted from the original mixed signals. The reference single-source points are then clustered to obtain the clustering center, which is defined as the reference center. In combination with the reference center, the deviation and interference points in the first-stage single-source points are eliminated by the cosine distance. The remaining signal points are considered as the second-stage single-source points, which are clustered to obtain the mixing matrix estimation. Experiments on simulated and speech signals show that the proposed method can obtain more accurate and robust mixing matrix estimation, leading to better separation of the source signals.
Mail Man Ferry: A Novel Routing Protocol in Intermittently Connected Networks
Authors: Altamimi Ahmed B.
Published: May 2023

As an important area for mobile wireless networks, Intermittently Connected Networks (ICNs) have received increasing attention in practice and research in recent years. The main goals of the ICN routing protocol are to maximize the delivery probability and to minimize the delivery delay. These challenges have been investigated in previously proposed protocols with an assumption of fully cooperating nodes. Node cooperation directly impacts ICN performance in terms of delivery probability and delay. However, node cooperation is not guaranteed because a cooperating node consumes its buffer size and energy, thereby highlighting the challenges of memory, computation, and energy efficiencies. This paper addresses the challenge of ensuring node cooperation by proposing a novel routing protocol called Mail Man Ferry (MMF). The new protocol includes a node credit mechanism that ensures the cooperation of the network nodes. Extensive simulations were executed to evaluate the proposed protocol. Varying values of node cooperation in ICNs were employed in the simulation tests. The evaluation shows exciting results in which Mail Man Ferry outperforms previously proposed ICN protocols.
“To Show in a Frozen Moment”: Camp Models and Dioramas as Forms of Holocaust Representation and Memory
Authors: Wraight Jamie Lee
Published: May 2023

This article seeks to investigate the design and creation of several models and dioramas of Holocaust death camps as spatial and historical representations of Holocaust memory. It broadly discusses their use as pedagogical tools, forms of art, testimonial expression and memorialization. It also addresses questions concerning the intention of their designers and creators, as well as the ethical considerations of recreating these spaces.