bluuebunny/crossref_metadata_2025 huggingface dataset:
A Comparison of Copromicroscopic and Molecular Methods for the Diagnosis of Cat Aelurostrongylosis
Authors: Morelli Simone , Traversa Donato , Diakou Anastasia , Colombo Mariasole , Russi Ilaria , Mestek Anton , Chandrashekar Ramaswamy , Beall Melissa , Paoletti Barbara , Iorio Raffaella , Tsokana Athina , De Cristofaro Domitilla , Barlaam Alessandra , Simonato Giulia , Di Cesare Angela
Published: April 2022

The gold standard method for the diagnosis of cat aelurostrongylosis is the detection of Aelurostrongylus abstrusus first stage larvae with the Baermann’s examination. Nevertheless, molecular assays have shown higher diagnostic performances compared to copromicroscopy. This study evaluated the usefulness of an A. abstrusus species-specific PCR on different biological samples collected in clinical settings from 100 privately-owned cats in Italy (n. 60) and Greece (n. 40). A fecal sample was collected from each animal and a pharyngeal swab was also obtained for cats from Italy. All stool samples were subjected to flotation and Baermann’s test. The cats were categorized in three groups based on the results of copromicroscopy, i.e., Group A (n. 50 cats with A. abstrusus infection regardless of positivity for other helminths), Group B (n. 25 cats negative for A. abstrusus but positive for at least one of any other helminth), Group C (n. 25 cats negative for any helminth). DNA was extracted from individual aliquots of feces, flotation supernatant, Baermann’s sediment and the pharyngeal swab and then subjected to a PCR specific for A. abstrusus. At least one fecal aliquot or the pharyngeal swab scored positive by the A. abstrusus-specific PCR for 48/50 (96%) cats enrolled in Group A; in particular, 38/50 (76%), 35/50 (70%), 41/50 (82%) and 21/25 (84%) DNA extracts from feces, flotation supernatant, Baermann’s sediment and pharyngeal swabs were positive by PCR. These results confirm that molecular tools are highly sensitive and specific and indicate that pharyngeal swabs are the most suitable sample for molecular analysis in clinical settings.
Creeping Wood Sorrel and Chromium Picolinate Effect on the Nutritional Composition and Lipid Oxidative Stability of Broiler Meat
Authors: Saracila Mihaela , Untea Arabela Elena , Panaite Tatiana Dumitra , Varzaru Iulia , Oancea Alexandra , Turcu Raluca Paula , Vlaicu Petru Alexandru
Published: April 2022

The study investigates the efficacy of Cr in broilers, aiming to evaluate the effects of Chromium picolinate (CrPic) in association with creeping wood sorrel powder (CWS) on the proximate composition, fatty acids profile, bioactive nutrients and lipid oxidative stability of broiler meat. A total of 120 Cobb 500 chickens were assigned into three treatments: a control diet (C) and two test diets, including 200 µg/kg diet CrPic (E1), and 200 µg/kg diet CrPic +10 g CWS/kg diet (E2). Dietary supplementation with Cr + CWS significantly improved the concentration of n − 3 polyunsaturated fatty acids (PUFAs), while its n − 6/n − 3 ratio decreased in comparison to the group receiving Cr and the conventional diet. The concentration of docosahexaenoic acid (DHA) significantly increased in the breast meat collected from the E2 group than that from the C group. Dietary administration of Cr and CWS improved lutein and zeaxanthin content, decreased Fe and Zn levels of the breast, and increased Zn deposition in the thigh samples. Malondialdehyde (MDA) concentration decreased more in the thigh meat of the supplemental groups (E1, E2) than in that from the C group. In conclusion, the current study suggests that Cr together with CWS can be a viable option as antioxidant sources for broiler diets, promoting the nutritional quality of meat.
Effect of Dietary Phenolic Compounds on Incidence of Cardiovascular Disease in the SUN Project; 10 Years of Follow-Up
Authors: Vázquez-Ruiz Zenaida , Toledo Estefanía , Vitelli-Storelli Facundo , Goni Leticia , de la O Víctor , Bes-Rastrollo Maira , Martínez-González Miguel Ángel
Published: April 2022

The health benefits of plant-based diets have been reported. Plant-based diets found in Spain and other Mediterranean countries differ from typical diets in other countries. In the Mediterranean diet, a high intake of phenolic compounds through olives, olive oil, and red wine may play an important role in cardiovascular prevention. Prospective studies carried out in Mediterranean countries may provide interesting insights. A relatively young Mediterranean cohort of 16,147 Spanish participants free of cardiovascular disease (CVD) was followed (61% women, mean (SD) age 37(12) years at baseline) for a median of 12.2 years. Dietary intake was repeatedly assessed using a 136-item validated food frequency questionnaire, and (poly)phenol intake was obtained using the Phenol-Explorer database. Participants were classified as incident cases of CVD if a medical diagnosis of myocardial infarction, stroke, or cardiovascular death was medically confirmed. Time-dependent Cox regression models were used to assess the relationship between (poly)phenol intake and the incidence of major CVD. A suboptimal intake of phenolic compounds was independently associated with a higher risk of CVD, multivariable-adjusted hazard ratio for the lowest versus top 4 quintiles: 1.85 (95% CI: 1.09–3.16). A moderate-to-high dietary intake of phenolic compounds, especially flavonoids, is likely to reduce CVD incidence in the context of a Mediterranean dietary pattern.
A Transition of Ignition Kernel Delay Time at the Early Stages of Lean Premixed n-Butane/Air Turbulent Spherical Flame Propagation
Authors: Nguyen Minh Tien , Shy Shenqyang (Steven)
Published: April 2022

This paper explores the effects of root-mean-square turbulence fluctuation velocity (u′) and ignition energy (Eig) on an ignition kernel delay time (τdelay) of lean premixed n-butane/air spherical flames with an effective Lewis number Le ≈ 2.1 >> 1. Experiments are conducted in a dual-chamber, fan-stirred cruciform burner capable of generating near-isotropic turbulence with negligible mean velocities using a pair of cantilevered electrodes with sharp ends at a fixed spark gap of 2 mm. τdelay is determined at a critical flame radius with a minimum flame speed during the early stages of laminar and turbulent flame propagation. Laminar and turbulent minimum ignition energies (MIEL and MIET) are measured at 50% ignitability, where MIEL = 3.4 mJ and the increasing slopes of MIET with u′ change from gradual to drastic when u′ > 0.92 m/s (MIE transition). In quiescence, a transition of τdelay is observed, where the decrement of τdelay becomes rapid (modest) when Eig is less (greater) than MIEL. For turbulent cases, when applying Eig ≈ MIET, the reverse trend of MIE transition is found for τdelay versus u′ results with the same critical u′ ≈ 0.92 m/s. These results indicated that the increasing u′ could reduce τdelay on the one hand, but require higher Eig (or MIET) on the other hand. Moreover, the rising of Eig in a specific range, where Eig ≤ MIE, could shorten τdelay, but less contribution as Eig > MIE. These results may play an important role to achieve optimal combustion phases and design an effective ignition system on spark ignition engines operated under lean-burn turbulent conditions.
Using Singular Value Decomposition and Chaotic Maps for Selective Encryption of Video Feeds in Smart Traffic Management
Authors: Benrhouma Oussama , Alkhodre Ahmad B. , AlZahrani Ali , Namoun Abdallah , Bhat Wasim A.
Published: April 2022

Traffic management in a smart city mainly relies on video feeds from various sources such as street cameras, car dash cams, traffic signal cameras, and so on. Ensuring the confidentiality of these video feeds during transmission is necessary. However, due to these devices’ poor processing power and memory capacity, the applicability of traditional encryption algorithms is not feasible. Therefore, a selective encryption system based on singular value decomposition (SVD) and chaotic maps is presented in this study. The proposed cryptosystem can be used in smart traffic management. We apply SVD to identify the most significant parts of each frame of the video feed for encryption. Chaotic systems were deployed to achieve high diffusion and confusion properties in the resulted cipher. Our results suggest that the computational overhead is significantly less than that of the traditional approaches with no compromise on the strength of the encryption.
Assessment of an NDL-PCBs Sequestration Strategy in Soil Using Contrasted Carbonaceous Materials through In Vitro and Cucurbita pepo Assays
Authors: Piutti Severine , El Wanny Nadine , Laflotte Alexandre , Baroudi Moomen , Caria Giovanni , Perronnet Karen , Jurjanz Stefan , Slezack Sophie , Feidt Cyril , Delannoy Matthieu
Published: April 2022

The present study aims to assess the respective efficiency of Biochars (BCs) and activated carbons (ACs) to limit PCB 101, 138, 153 and 180 transfer to plants. A set of 6 high carbon materials comprising 3 BCs and 3 ACs was tested and used to amend a soil at 2% rate. Then, the two most efficient carbonaceous materials were used as an amendment of an historically contaminated soil sampled in the St Cyprien vicinity (Loire, France). An environmental availability assessment was performed using the ISO/DIS 16751 Part A assay (n = 3). For the in vivo part, Cucurbita pepo were grown for 12 weeks. Significant decreases of transfer were found for both assays notably for powdered ACs (up to 98%). By contrast, significantly lower levels of transfer reduction were observed when BCs amendments were performed, ranging from 27 to 80% for environmental availability assessment and 0 to 36% for C. pepo. Reduction factors above 90% for the 2 selected materials were found from amended historically contaminated soils. Present results led to consider such a sequestering strategy as valuable to ensure plant production on non-dioxin-like polychlorobiphenyls (NDL-PCBs) contaminated soils.
BenSignNet: Bengali Sign Language Alphabet Recognition Using Concatenated Segmentation and Convolutional Neural Network
Authors: Miah Abu Saleh Musa , Shin Jungpil , Hasan Md Al Mehedi , Rahim Md Abdur
Published: April 2022

Sign language recognition is one of the most challenging applications in machine learning and human-computer interaction. Many researchers have developed classification models for different sign languages such as English, Arabic, Japanese, and Bengali; however, no significant research has been done on the general-shape performance for different datasets. Most research work has achieved satisfactory performance with a small dataset. These models may fail to replicate the same performance for evaluating different and larger datasets. In this context, this paper proposes a novel method for recognizing Bengali sign language (BSL) alphabets to overcome the issue of generalization. The proposed method has been evaluated with three benchmark datasets such as ‘38 BdSL’, ‘KU-BdSL’, and ‘Ishara-Lipi’. Here, three steps are followed to achieve the goal: segmentation, augmentation, and Convolutional neural network (CNN) based classification. Firstly, a concatenated segmentation approach with YCbCr, HSV and watershed algorithm was designed to accurately identify gesture signs. Secondly, seven image augmentation techniques are selected to increase the training data size without changing the semantic meaning. Finally, the CNN-based model called BenSignNet was applied to extract the features and classify purposes. The performance accuracy of the model achieved 94.00%, 99.60%, and 99.60% for the BdSL Alphabet, KU-BdSL, and Ishara-Lipi datasets, respectively. Experimental findings confirmed that our proposed method achieved a higher recognition rate than the conventional ones and accomplished a generalization property in all datasets for the BSL domain.
Improved FULMS Algorithm for Multi-Modal Active Control of Compressor Vibration and Noise Reduction
Authors: Wu Xiaowen , Li Chaopeng , Huang Yizhe , Yang Mingquan , Huang Qibai
Published: April 2022

Active control is currently a hot-button issue in the research of reducing vibration and noise created by rolling piston compressors. Active control can effectively suppress the modal vibration of the structure and reduce the modal resonance acoustic radiation. This paper, which focuses on the active control of the compressor shell’s multiple modes with the control of acoustic radiation power being the research objective, studies the relationship between vibration modes and acoustic radiation modes of the compressor shell and the primary sources of noise. An improved Filtered-U least mean square (FULMS) algorithm for compressor vibration and noise control, which is based on the Nesterov accelerated adaptive moment estimation (NADAM) optimization algorithm, is proposed to determine the multi-order modes to be controlled from the perspective of sound energy, and a particle swarm algorithm is used to determine the location and number of secondary sources. The active control model of the compressor shell was established by using the joint simulation platform, and the performance of the improved algorithm was verified and analyzed by the simulation test process. The results show that compared with the traditional FULMS algorithm, the improved FULMS algorithm has better active vibration control effect, higher convergence speed and can effectively suppress structural mode vibration in a short period time.
Effect of Gear Design Parameters on Stress Histories Induced by Different Tooth Bending Fatigue Tests: A Numerical-Statistical Investigation
Authors: Concli Franco , Maccioni Lorenzo , Fraccaroli Lorenzo , Cappellini Cristian
Published: April 2022

The characterization of new materials for enabling gear design is definitely a fundamental objective in the gear industry and research. Single Tooth Bending Fatigue (STBF) tests can be performed to speed up this process. However, it is well known that STBF tests tend to overestimate material strength compared to tests performed directly on meshing gears (MG) which, in turn, require an excessively long test time. Therefore, it is common practice to use a constant correction factor fkorr of 0.9 to translate STBF results for designing actual MG (e.g., via ISO 6336). Recent works involving a combination of Finite Element Models (FEM) and multiaxial (non-proportional) fatigue criteria based on the critical plane concept have highlighted that the assumption of considering fkorr as a constant independent of the gear design parameters leads to inaccurate results. However, in previous studies, no correlation between fkorr and gear design parameters has emerged. In the present paper, the influence of the normal pressure angle (αn), the profile shift coefficient (x*), and the normal module (mn) on fkorr was investigated by analyzing FEM simulations with the Findley fatigue criterion. 27 gear geometries were studied by varying the above 3 parameters in 3 levels (full factorial DOE). These geometries were simulated in both MG and STBF configurations. The results of the 54 FEM simulations were analyzed by applying the Findley fatigue criterion and the corresponding fkorr were calculated. The correlation between fkorr and αn, x* and mn was investigated using the Analysis of Variance (ANOVA) technique. The results show that the only gear design parameter influencing fkorr is x* hence, a regression model for fkorr including x* has been developed. This latter has been then adopted for calculating and comparing fkorr values from other combination of the parameters found in literature, giving good correspondence.
Design Approaches of an Exoskeleton for Human Neuromotor Rehabilitation
Authors: Copilusi Cristian , Dumitru Sorin , Geonea Ionut , Ciurezu Leonard Gherghe , Dumitru Nicolae
Published: April 2022

This paper addresses a design for an exoskeleton used for human locomotion purposes in cases of people with neuromotor disorders. The reason for starting this research was given by the development of some intelligent systems for walking recovery involved in a new therapy called stationary walking therapy. This therapy type will be used in this research case, through a robotic system specially designed for functional walking recovery. Thus, the designed robotic system structure will have a patient lifting/positioning mechanism, a special exoskeleton equipped with sensors and actuators, a treadmill for walking, and a command and control unit. The exoskeleton’s lower limbs will have six orthotic devices. Thus, the exoskeleton’s lower limbs’ motions and orthoses angle variations will be generated by healthy human subjects on the treadmill with the possibility of memorizing these specific motions for obtaining one complete gait cycle. After this, the memorized motions will be performed to a patient with neuromotor disorders for walking recovery programs. The design core is focused on two planar-parallel mechanisms implemented at the knee and ankle joints of each leg’s exoskeleton. Thus, numerical simulations for the design process were carried out to validate the engineering feasibility of the proposed leg exoskeleton.
Software-as-a-Service Security Challenges and Best Practices: A Multivocal Literature Review
Authors: Humayun Mamoona , Niazi Mahmood , Almufareh Maram Fahhad , Jhanjhi N. Z. , Mahmood Sajjad , Alshayeb Mohammad
Published: April 2022

Cloud computing (CC) is the delivery of computing services on demand and is charged using a “pay per you use” policy. Of the multiple services offered by CC, SaaS is the most popular and widely adapted service platform and is used by billions of organizations due to its wide range of benefits. However, security is a key challenge and obstacle in cloud adoption and therefore needs to be addressed. Researchers and practitioners (R&P) have discussed various security challenges for SaaS along with possible solutions. However, no research study exists that systematically accumulates and analyzes the security challenges and solutions. To fill this gap and provide the state-of-the-art (SOTA) picture of SaaS security, this study provides a comprehensive multivocal literature review (MVLR), including SaaS security issues/challenges and best practices for mitigating these security issues. We identified SaaS security issues/challenges and best practices from the formal literature (FL) as well as the grey literature (GL) to evaluate whether R&P is on the same page or if controversies exist. A total of 93 primary studies were identified, of which 58 are from the FL and 35 belong to the GL. The studies are from the last ten years, from 2010 to 2021. The selected studies were evaluated and analyzed to identify the key security issues faced by SaaS computing and to be aware of the best practices suggested by R&P to improve SaaS security. This MVLR will assist SaaS users to identify the many areas in which additional research and development in SaaS security is required. According to our study findings, data breaches/leakage, identity and access management, governance and regulatory compliance/SLA compliance, and malicious insiders are the key security challenges with the maximum frequency of occurrence in both FL and GL. On the other hand, R&P agree that up-to-date security controls/standards, the use of strong encryption techniques, regulatory compliance/SLA compliance, and multifactor authentication are the most important solutions.
Efficient Enhancement of Second Harmonic Generation via Noninvasive Modulation
Authors: Wu Liqing , Fan Weiru , Chen Ziyang , Pu Jixiong
Published: April 2022

Second harmonic generation has been widely applied in various fields. High second harmonic intensity can facilitate optical imaging, signal sensing, and detection. Thus, enhancing the intensity of the second harmonic is a significant work. However, changing the external character of crystal or increasing the pump light intensity to improve the intensity of the second harmonic is not always advisable in some applications, such as bioimaging, biopsies, etc. Here, we implemented a noninvasive method that constructs a specific spatial distribution field via a scattering medium to realize a high enhancement of second harmonic intensity. We studied that different scattering mediums exerted the influence on the optimal enhancement effect of second harmonic. It was found that choosing an appropriate scattering medium can greatly enhance the intensity of the second harmonic. The results can offer a helpful value for second harmonic applications such as bioimaging, sensing, and optical frequency conversion.
Aerodynamic Shape Optimization of an Arc-Plate-Shaped Bluff Body via Surrogate Modeling for Wind Energy Harvesting
Authors: Shi Tianyi , Hu Gang , Zou Lianghao
Published: April 2022

Galloping-based piezoelectric wind energy harvesters (WEHs) are being used to supply renewable electricity for self-powered devices. This paper investigates the performance of a galloping-based piezoelectric WEH, with different arc-plate-shaped bluff bodies to improve harvesting efficiency. The Latin hypercube sampling method was employed to design the experiment. After conducting a series of wind tunnel tests, a Kriging surrogate model was then established, with high accuracy. The results show that the wind energy harvester with an arc angle 0.40π and tail length 1.26D generated the maximum power. The output power of the proposed WEH was doubled by optimizing the aerodynamic shape of the bluff body. The reasons for the improvement are discussed in detail. The force measurement results indicated that a large value of the transverse force coefficient means a large galloping response of the WEH. The aerodynamic optimization of this study can be applied to improve the performance of galloping-based wind energy harvesters.
Concept for Generating Energy Demand in Electric Vehicles with a Model Based Approach
Authors: Nguyen Tuyen , Kriesten Reiner , Chrenko Daniela
Published: April 2022

Hybrid energy storage systems (HESS) for electric vehicles, which consist of lithium-ion batteries and supercapacitors, have become an increasing focus of research and development in recent years. The combination of the two combines the advantages of each storage technology (high energy density in batteries and high power density in supercapacitors) in one system. To effectively manage the energy flow between these two different storage technologies, an intelligent energy management system (EMS) is required. In the development of the EMS, it is usual to run preliminary checks in a simulation environment that is as close to reality as feasible already during the development process. For this purpose, this paper presents a concept for the creation of a simulation environment consisting of realistic routes and a holistic vehicle model. The realistic route data are generated by a route-generating algorithm, which accesses different map services via application programming interfaces (API) and retrieves real route data to generate a simulated route. By integrating further online services (e.g., OpenWeather API), the routes are further specified with, for example, real weather data, traffic data, speed limits and altitude data. For the complete vehicle model, components including the suspension, chassis and auxiliary consumers are simulated as blackbox models. The components that can be accessed during the simulation are simulated as white box models. These are the battery, the supercapacitor, the DC/DC converter and the electric motor. This allows the EMS to control and regulate the HESS in real time during the simulation. To validate the simulation environment presented here, a real BMW i3 was driven on a real route, and its energy demand was measured. The same route was simulated in the simulation environment with environmental conditions that were as realistic as feasible (traffic volume, traffic facilities, weather) and the vehicle model of the BMW i3. The resulting energy demand from the simulation was recorded. The results show that the simulated energy consumption value differs by only 1.92% from the real measured value. This demonstrates the accuracy of the simulation environment presented here.
Optical Response of Expired EBT3 Film for Absorbed Dose Measurement in X-ray and Electron Beam Range
Authors: Musa Maisarah , Abu Mhanna Hamad Yahia , Omar Ahmad Fairuz , Radzi Yasmin Md , Akhdar Hanan Fawaz , Ishak Nor Hafizah , Al Ewaidat Haytham
Published: April 2022

The purpose of this study was to investigate the optical response of an expired External Beam Therapy (EBT3) film, which expired in 2018, using X-rays and electron beam doses. The film’s optical responses were evaluated for its usability in measuring different radiation sources, energy, and absorbed doses ranging up to 5 Gy. Pieces of the expired EBT3 film were irradiated with 90 kVp, 6 MV X-ray photons, and 6 MeV electron beam. The analysis was performed using the Jaz visible spectrometer and EPSON Perfection V370 Photo scanner to obtain the absorbance and the net relative optical density (ROD) of the film samples respectively. The results showed that spectroscopic measurements of the exposed expired EBT3 films under these radiation sources were able to produce primary secondary peaks at λ = 633.52 nm and λ = 582.3 nm respectively. The best wavelength subsets that presented the best MLR regression fitting for all experiments were 541.48 nm, 561.11 nm, and 600.28 nm. While, for the 6 MV photon and the 6 MeV electron beam they were 600.28 nm, 650.79 nm and 654.10 nm. In case of the irradiation with the 6 MV photon and the 6 MeV electron beam, expired EBT3 film showed no significant differences, which made it suitable for dosimetry in various sources of radiation. The individual calibration of radiation dose produces very high measurement accuracy with coefficient of determination, R2 above 0.99 and root mean square of error, RMSE of 0.038 Gy, 0.113 Gy, and 0.115 Gy for films irradiated with 90 kVp X-rays, 6 MV photon beam, and 6 MeV electron beam respectively. Hence, from the results, the expired EBT3 film used in this study showed promising usability of expired EBT3 films beyond their prescribed expiry dates.
Experimental Research on the Effects of Suction Ports on Twin Screw Expander Performance
Authors: He Yongning , Wu Huihong , Zhang Yeqiang , Jin Tingxiang , Xing Ziwen
Published: April 2022

An organic Rankine cycle (ORC) system is an efficient technology for generating power from low-grade thermal sources. Twin screw expanders are widely used in ORC systems. Pressure loss caused by a suction port influences the suction process and the system performance. In this paper, the effects of suction ports on twin screw expander performance are experimentally investigated. The pressure loss value of R245fa is measured under different working conditions, and its effects on the suction coefficient are discussed. Results show that a lower rotation speed results in a lower pressure loss value and a higher suction coefficient under certain working conditions. Increasing the suction pressure leads to a higher pressure loss value but a lower pressure loss ratio. Discharge pressure has little effect on the suction process.
Study on Circular Economy Implementation Propensity of Construction Companies in Context of Prevailing Management Styles
Authors: Górecki Jarosław , Núñez-Cacho Pedro , Rutkowska Milena
Published: April 2022

The construction sector significantly impacts the environment. Buildings and non-building structures require natural resources and technical nutrients to be constructed and maintained. One of the most important challenges is the mitigation of their usage for construction projects. In the context of insufficient knowledge about the most effective leadership patterns for sustainable construction projects, one may wonder if there is one dominant style of management represented by construction companies. In turn, the challenges faced by these organizations can be related to how to effectively implement the circular economy (CE) concept, and thus reduce the negative externalities of the construction industry. Transition to sustainable construction requires the involvement of change leaders. In this article, based on a literature review and questionnaire, it was revealed that it is extremely difficult to distinguish one prevailing leadership style in construction companies. Besides, a path to CE maturity has been shown as a continual pursuit. The consistency enables effective promotion of the concept of CE in the construction company. The research allowed the identification of three explicit phases, disharmony, euphoria, and harmony, in becoming the CE-matured construction enterprise.
Obfuscation Algorithm for Privacy-Preserving Deep Learning-Based Medical Image Analysis
Authors: Popescu Andreea Bianca , Taca Ioana Antonia , Vizitiu Anamaria , Nita Cosmin Ioan , Suciu Constantin , Itu Lucian Mihai , Scafa-Udriste Alexandru
Published: April 2022

Deep learning (DL)-based algorithms have demonstrated remarkable results in potentially improving the performance and the efficiency of healthcare applications. Since the data typically needs to leave the healthcare facility for performing model training and inference, e.g., in a cloud based solution, privacy concerns have been raised. As a result, the demand for privacy-preserving techniques that enable DL model training and inference on secured data has significantly grown. We propose an image obfuscation algorithm that combines a variational autoencoder (VAE) with random non-bijective pixel intensity mapping to protect the content of medical images, which are subsequently employed in the development of DL-based solutions. A binary classifier is trained on secured coronary angiographic frames to evaluate the utility of obfuscated images in the context of model training. Two possible attack configurations are considered to assess the security level against artificial intelligence (AI)-based reconstruction attempts. Similarity metrics are employed to quantify the security against human perception (structural similarity index measure and peak signal-to-noise-ratio). Furthermore, expert readers performed a visual assessment to determine to what extent the reconstructed images are protected against human perception. The proposed algorithm successfully enables DL model training on obfuscated images with no significant computational overhead while ensuring protection against human eye perception and AI-based reconstruction attacks. Regardless of the threat actor’s prior knowledge of the target content, the coronary vessels cannot be entirely recovered through an AI-based attack. Although a drop in accuracy can be observed when the classifier is trained on obfuscated images, the performance is deemed satisfactory in the context of a privacy–accuracy trade-off.
Risk Assessment in Supplier Selection for Intelligent Manufacturing Systems Based on PLS-SEM
Authors: Shi Li , Huang Ke , Liu Yuan , Ge Fangzhen , Liu Sheng
Published: April 2022

With the in-depth reform of intelligent manufacturing, selecting high-quality intelligent manufacturing system solution suppliers has become a key force to promote the intelligent transformation of manufacturing enterprises. However, manufacturing enterprises have hidden risks in the selection process of many intelligent manufacturing system solution suppliers, so it is urgent to carry out the research on the risk evaluation of intelligent manufacturing system solution suppliers. Based on the current situation in China’s intelligent manufacturing industry, this paper constructs the evaluation index system of intelligent manufacturing system solution suppliers, uses the PLS-SEM method to establish the risk evaluation model of intelligent manufacturing system solution suppliers, collects data through a questionnaire survey, uses a PLS algorithm to fit the index and test the model, and uses power BI software to visualize the risky impact. The conclusions are as follows: (1) The primary indicators have hidden risks for the system solution suppliers. (2) The higher the achievement of secondary indicators, the lower the implied risk, and the more conducive to the intelligent upgrading of manufacturing enterprises. According to the visualization results, management suggestions are given to provide useful reference for manufacturing enterprises to select high-quality intelligent manufacturing system solution suppliers and promote the transformation and upgrading of manufacturing enterprises, from digitization and networking to intelligent stage.
Method for In-Operando Contamination of Lithium Ion Batteries for Prediction of Impurity-Induced Non-Obvious Cell Damage
Authors: Höschele Patrick , Heindl Simon Franz , Schneider Bernd , Sinz Wolfgang , Ellersdorfer Christian
Published: April 2022

The safety of lithium-ion batteries within electrified vehicles plays an important role. Hazards can arise from contaminated batteries resulting from non-obvious damages or insufficient production processes. A systematic examination requires experimental methods to provoke a defined contamination. Two prerequisites were required: First, the extent and type of contamination should be determinable to exclude randomness. Second, specimens should work properly before the contamination, enabling realistic behavior. In this study, two experimental methods were developed to allow for the first time a controlled and reproducible application of water or oxygen into 11 single-layer full cells (Li4Ti5O12/LiCoO2) used as specimens during electrical cycling. Electrochemical impedance spectroscopy was used to continuously monitor the specimens and to fit the parameters of an equivalent circuit model (ECM). For the first time, these parameters were used to calibrate a machine-learning algorithm which was able to predict the contamination state. A decision tree was calibrated with the ECM parameters of eight specimens (training data) and was validated by predicting the contamination state of the three remaining specimens (test data). The prediction quality proved the usability of classification algorithms to monitor for contaminations or non-obvious battery damage after manufacturing and during use. It can be an integral part of battery management systems that increases vehicle safety.
Acute Effect of Electromyostimulation Superimposed on Running on Maximal Velocity, Metabolism, and Perceived Exertion
Authors: Stephan Holger , Hagedorn Thorsten , Wehmeier Udo Frank , Tomschi Fabian , Hilberg Thomas
Published: April 2022

Electromyostimulation has been shown to intensify exercise when superimposed on cycling. However, little is known about the application during running, which might help to prevent injuries linked to high running volumes, as intensification of running allows for a reduction in training volume. Therefore, the purpose of the study was to examine the effects of electromyostimulation superimposed on running. Men who were no younger than 18 and no older than 35 were eligible for inclusion in the study. Exclusion criteria were previous experience with electromyostimulation training, the presence of a contraindication according to the manufacturer, or a contraindication to physical activity. A sample of 22 healthy males with an ordinary performance capability accomplished three similar cardiopulmonary treadmill tests until exhaustion in a crossover study design that included lactate measurements and interrogations of perceived exertion. The first test was conducted without electromyostimulation and was followed in a randomized order by the second and the third test condition with 30 or 85 Hz stimulation, respectively, of the lower body. Superimposed electromyostimulation significantly reduced the maximal achieved velocity (control 15.6 ± 1.1 vs. 30 Hz 15.1 ± 1.2, p = 0.002; vs. 85 Hz 14.9 ± 1.1 km/h, p < 0.001), increased the perceived exertion at 10, 12 and 14 km/h (85 Hz + 0.7, p = 0.036; +0.9, p = 0.007; +1.3, p < 0.001; 30 Hz + 0.7, p = 0.025; +1.0, p = 0.002; +1.2, p < 0.001), and induced a significantly higher oxygen uptake at 8 km/h (85 Hz + 1.1, p = 0.006; 30 Hz + 0.9 mL·min−1·kg−1, p = 0.042), 10 km/h (30 Hz + 0.9 mL·min−1·kg−1, p = 0.032), and 14 km/h (85 Hz + 1.0 mL·min−1·kg−1, p = 0.011). Both electromyostimulation conditions significantly limited the maximal lactate level (30 Hz p = 0.046; 85 Hz p < 0.001) and 85 Hz also the recovery lactate level (p < 0.001). Superimposed electromyostimulation is feasible and intensifies running. Coaches and athletes could benefit from the increased training stimulus by reducing running velocity or volume, by combining endurance and strength training, and also by inducing better adaptations while maintaining the same velocity or volume. Therefore, electromyostimulation superimposed on running could be an interesting training tool for runners.
Comment on Chen et al. Dual Blockade of Lactate/GPR81 and PD-1/PD-L1 Pathways Enhances the Anti-Tumor Effects of Metformin. Biomolecules 2021, 11, 1373
Authors: Stransky Nicolai , Huber Stephan M.
Published: April 2022

In the study of Chen et al. [...]
RT-QuIC and Related Assays for Detecting and Quantifying Prion-like Pathological Seeds of α-Synuclein
Authors: Srivastava Ankit , Alam Parvez , Caughey Byron
Published: April 2022

Various disease-associated forms or strains of α-synuclein (αSynD) can spread and accumulate in a prion-like fashion during synucleinopathies such as Parkinson’s disease (PD), Lewy body dementia (DLB), and multiple system atrophy (MSA). This capacity for self-propagation has enabled the development of seed amplification assays (SAAs) that can detect αSynD in clinical samples. Notably, α-synuclein real-time quaking-induced conversion (RT-QuIC) and protein misfolding cyclic amplification (PMCA) assays have evolved as ultrasensitive, specific, and relatively practical methods for detecting αSynD in a variety of biospecimens including brain tissue, CSF, skin, and olfactory mucosa from synucleinopathy patients. However, αSyn SAAs still lack concordance in detecting MSA and familial forms of PD/DLB, and the assay parameters show poor correlations with various clinical measures. End-point dilution analysis in αSyn RT-QuIC assays allows for the quantitation of relative amounts of αSynD seeding activity that may correlate moderately with clinical measures and levels of other biomarkers. Herein, we review recent advancements in α-synuclein SAAs for detecting αSynD and describe in detail the modified Spearman–Karber quantification algorithm used with end-point dilutions.
IntroSpect: Motif-Guided Immunopeptidome Database Building Tool to Improve the Sensitivity of HLA I Binding Peptide Identification by Mass Spectrometry
Authors: Zhang Le , Liu Geng , Hou Guixue , Xiang Haitao , Zhang Xi , Huang Ying , Zhang Xiuqing , Li Bo , Lee Leo J.
Published: April 2022

Although database search tools originally developed for shotgun proteome have been widely used in immunopeptidomic mass spectrometry identifications, they have been reported to achieve undesirably low sensitivities or high false positive rates as a result of the hugely inflated search space caused by the lack of specific enzymic digestions in immunopeptidome. To overcome such a problem, we developed a motif-guided immunopeptidome database building tool named IntroSpect, which is designed to first learn the peptide motifs from high confidence hits in the initial search, and then build a targeted database for refined search. Evaluated on 18 representative HLA class I datasets, IntroSpect can improve the sensitivity by an average of 76%, compared to conventional searches with unspecific digestions, while maintaining a very high level of accuracy (~96%), as confirmed by synthetic validation experiments. A distinct advantage of IntroSpect is that it does not depend on any external HLA data, so that it performs equally well on both well-studied and poorly-studied HLA types, unlike the previously developed method SpectMHC. We have also designed IntroSpect to keep a global FDR that can be conveniently controlled, similar to a conventional database search. Finally, we demonstrate the practical value of IntroSpect by discovering neoepitopes from MS data directly, an important application in cancer immunotherapies. IntroSpect is freely available to download and use.
Liver-Targeted Nanoparticles Facilitate the Bioavailability and Anti-HBV Efficacy of Baicalin In Vitro and In Vivo
Authors: Xu Weiming , Niu Yijun , Ai Xin , Xia Chengjie , Geng Ping , Zhu Haiyan , Zhou Wei , Huang Hai , Shi Xunlong
Published: April 2022

The anti-hepatitis B virus (HBV) efficacy of baicalin (BA) is mediated by HBV-related hepatocyte nuclear factors (HNFs). However, this efficacy is severely limited by the low bioavailability of BA. Therefore, a novel liver-targeted BA liposome was constructed to promote the bioavailability and antiviral ability of BA. The results showed that apolipoprotein A1 (ApoA1)–modified liposomes (BAA1) significantly enhanced BA’s cellular uptake and specific distribution in the liver. Furthermore, the substantial inhibitory effects of BAA1 on HBsAg, HBeAg, HBV RNA, and HBV DNA were assessed in HB-infected cells and mice. Western blotting, co-immunoprecipitation, and transcriptomics analysis further revealed that the enhanced anti-HBV efficacy of BAA1 was attributed to the interaction between hepatocyte nuclear factors (HNFs) and estrogen receptors (ERs). Based on the findings, we propose that the ApoA1-modified liposomes aid BA in inhibiting HBV transcription and replication by augmenting its bioavailability and the HNFs–ERs axis.
Photonic Biosensors: Detection, Analysis and Medical Diagnostics
Authors: Conteduca Donato
Published: April 2022

The necessity of personalised diagnoses and ad hoc treatments for individual patients is driving the outbreak of personalised nanomedicine in research and in clinical studies in the healthcare field [...]
Based on Unmodified Aptamer-Gold Nanoparticles Colorimetric Detection of Dexamethasone in Food
Authors: Qin Yadi , Bubiajiaer Hayilati , Yao Jun , Zhang Minwei
Published: April 2022

Residue and illegal addition of Dexamethasone (DEX) in food has received widespread attention over the past few decades. Long-term intake of DEX will have a strong endocrine-disrupting effect, and there is an urgent need to develop highly sensitive and rapid on-site detection methods. In this work, a colorimetric sensor based on an unmodified aptamer and gold nanoparticles (Au NPs) was designed to detect DEX in milk and glucosamine. Under optimized conditions, the absorbance ratio of Au NPs increased linearly with DEX concentration over the range of 10–350 nmol/mL (r2 = 0.997), with a limit of detection (LOD) of 0.5 nmol/mL, and the recoveries ranged from 93.6 to 117%. To explore the interaction mechanism between aptamer and DEX, molecular docking and molecular dynamics simulations were applied to probe intermolecular interactions and structures of the complex. The establishment of aptamer-based sensors effectively avoids the antibody screening response, with a cost-efficient, excellent selective and great potential in DEX determination.
Fiber-Enhanced Stimulated Raman Scattering and Sensitive Detection of Dilute Solutions
Authors: Guo Li , Huang Jing , Chen Yaxin , Zhang Bohan , Ji Minbiao
Published: April 2022

Stimulated Raman scattering (SRS) is known to gain coherent amplification of molecular vibrations that allow for rapid and label-free chemical imaging in the microscopy setting. However, the tightly focused laser spot has limited the detection sensitivity, partly due to the tiny interaction volume. Here, we report the use of metal-lined hollow-core fiber (MLHCF) to improve the sensitivity of SRS in sensing dilute solutions by extending the light–matter interaction volume through the fiber waveguide. With a focusing lens (100 mm FL) and 320 μm diameter fiber, we demonstrated an optimum enhancement factor of ~20 at a fiber length of 8.3 cm. More importantly, the MLHCF exhibited a significantly suppressed cross-phase modulation (XPM) background, enabling the detection of ~0.7 mM DMSO in water. Furthermore, the relationship between fiber length and SRS signal could be well explained theoretically. The fiber-enhanced SRS (FE-SRS) method may be further optimized and bears potential in the sensitive detection of molecules in the solution and gas phases.
Immobilization and Characterization of L-Asparaginase over Carbon Xerogels
Authors: Barros Rita A. M. , Cristóvão Raquel O. , Carabineiro Sónia A. C. , Neves Márcia C. , Freire Mara G. , Faria Joaquim L. , Santos-Ebinuma Valéria C. , Tavares Ana P. M. , Silva Cláudia G.
Published: April 2022

L-asparaginase (ASNase) is an aminohydrolase currently used in the pharmaceutical and food industries. Enzyme immobilization is an exciting option for both applications, allowing for a more straightforward recovery and increased stability. High surface area and customizable porosity make carbon xerogels (CXs) promising materials for ASNase immobilization. This work describes the influence of contact time, pH, and ASNase concentration on the immobilization yield (IY) and relative recovered activity (RRA) using the Central Composite Design methodology. The most promising results were obtained using CX with an average pore size of 4 nm (CX-4), reaching IY and RRA of 100%. At the optimal conditions (contact time 49 min, pH 6.73, and [ASNase] 0.26 mg·mL−1), the ASNase-CXs biocomposite was characterized and evaluated in terms of kinetic properties and operational, thermal, and pH stabilities. The immobilized ASNase onto CX-4 retained 71% of its original activity after six continuous reaction cycles, showed good thermal stability at 37 °C (RRA of 91% after 90 min), and was able to adapt to both acidic and alkaline environments. Finally, the results indicated a 3.9-fold increase in the immobilized ASNase affinity for the substrate, confirming the potential of CXs as a support for ASNase and as a cost-effective tool for subsequent use in the therapeutic and food sectors.
Young Adults with a Parent with Dementia Show Early Abnormalities in Brain Activity and Brain Volume in the Hippocampus: A Matched Case-Control Study
Authors: McDonough Ian M. , Mayhugh Christopher , Moore Mary Katherine , Brasfield Mikenzi B. , Letang Sarah K. , Madan Christopher R. , Allen Rebecca S.
Published: April 2022

Having a parent with Alzheimer’s disease (AD) and related dementias confers a risk for developing these types of neurocognitive disorders in old age, but the mechanisms underlying this risk are understudied. Although the hippocampus is often one of the earliest brain regions to undergo change in the AD process, we do not know how early in the lifespan such changes might occur or whether they differ early in the lifespan as a function of family history of AD. Using a rare sample, young adults with a parent with late-onset dementia, we investigated whether brain abnormalities could already be detected compared with a matched sample. Moreover, we employed simple yet novel techniques to characterize resting brain activity (mean and standard deviation) and brain volume in the hippocampus. Young adults with a parent with dementia showed greater resting mean activity and smaller volumes in the left hippocampus compared to young adults without a parent with dementia. Having a parent with AD or a related dementia was associated with early aberrations in brain function and structure. This early hippocampal dysfunction may be due to aberrant neural firing, which may increase the risk for a diagnosis of dementia in old age.