bluuebunny/crossref_metadata_2025 huggingface dataset:
Study of Regression Algorithms and Influent Factors between Intelligent Compaction Measurement Values and In-Situ Measurement Values
Authors: Pang Jinsong , Yang Jingli , Zhu Bin , Qian Jinsong
Published: May 2023

Intelligent compaction (IC) technology have been used for quality control and quality assurance (QC/QA) in subgrade construction. The effective regression correlations between Intelligent Compaction Measurement Values (ICMV) and In-situ Measurement Values (ISMV, including compaction degree and subgrade modulus ELWD) are the essential prerequisite of using IC technology for QC/QA. This paper presents the results from an experimental research study that was conducted from a practical subgrade project of China to explore the regression relationships between ICMV and ISMV. Three types of ICMV, including CMV, CCV and Evib, were collected along with the corresponding positions of the rollers. Two types of ISMV, containing compaction degree and ELWD, were measured by ring sampler method and light weight deflectometer (LWD) at specified test points, respectively. Based on these data, the influences of roller parameters and subgrade properties on the regression relationships of ICMV and ISMV were investigated. In addition, linear regression and 5 nonlinear regression algorithms were compared. The results suggest that ICMV reflect the stiffness of subgrade more than reflecting the density. In the regression of ICMV and ISMV, subgrade properties are more important than roller parameters while both of them should not be neglected. The influences of underlying stiffness and roller amplitude are linear while that of roller speed and moisture content are nonlinear. Nonlinear algorithms, especially the random forest, have the better performance compared to linear algorithm. Moreover, the combination of random forest and linear algorithm can further improve the accuracy of ISMV prediction.
Experimental Study on Mechanical Properties and Deterioration Mechanism of Red Sandstone from the Panjiatuo Landslide under Action of Acidic Drying−Wetting Cycles
Authors: Zhang Ganping , Wang Lunan , Liu Zhenning , Wu Nan
Published: May 2023

Due to frequent water level fluctuations and complex hydrochemical environments, rock slopes in reservoir areas progressively deteriorate and become unstable. This study investigated the coupling effect of drying−wetting cycles and acidic solutions on the physical and mechanical properties, strain field evolution, failure mode, and micro-mechanism of red sandstone using a series of laboratory experiments (wave velocity tests, uniaxial compression tests, the digital image correlation method, scanning electron microscopy, and X-ray diffraction). The results showed that with increasing drying−wetting cycles, the mass, P-wave velocity, elastic modulus, and uniaxial compressive strength decreased monotonically, while the water absorption and apparent strain in the strain localization band increased. Moreover, the failure mode transitioned gradually from tensile failure to shear failure or tensile-shear composite failure. The decrease in the solution pH values aggravated the changes in the physical and mechanical parameters and contributed to an increase in the secondary cracks and the occurrence of shear behavior. In addition, the coupling effect of drying−wetting cycles and acidic solutions accelerated the worsening of the microstructure and the dissolution of minerals, resulting in a loose structure with well-developed pores and fissures. These changes provide a favorable explanation for the mechanical property deterioration of red sandstone subjected to acidic drying−wetting cycles.
DKFD: Optimizing Common Pediatric Dermatoses Detection with Novel Loss Function and Post-Processing
Authors: Fan Dandan , Li Hui , Chen Mei , Liang Qingqing , Xu Huarong
Published: May 2023

Using appropriate classification and recognition technology can help physicians make clinical diagnoses and decisions more effectively as a result of the ongoing development of artificial intelligence technology in the medical field. There are currently a number of issues with the detection of common pediatric dermatoses, including the challenge of image collection, the low resolution of some collected images, the intra-class variability and inter-class similarity of disease symptoms, and the mixing of disease symptom detection results. To resolve these problems, we first introduced the Random Online Data Augmentation and Selective Image Super-Resolution Reconstruction (RDA-SSR) method, which successfully avoids overfitting in training, to address the issue of the small dataset and low resolution of collected images, increase the number of images, and improve the image quality. Second, for the issue of an imbalance between difficult and simple samples, which is brought on by the variation within and between classes of disease signs during distinct disease phases. By increasing the loss contribution of hard samples for classification on the basis of the cross-entropy, we propose the DK_Loss loss function for two-stage object detection, allowing the model to concentrate more on the learning of hard samples. Third, in order to reduce redundancy and improve detection precision, we propose the Fliter_nms post-processing method for the intermingling of detection results based on the NMS algorithm. We created the CPD-10 image dataset for common pediatric dermatoses and used the Faster R-CNN network training findings as a benchmark. The experimental results show that the RDA-SSR technique, while needing a similar collection of parameters, can improve mAP by more than 4%. Furthermore, experiments were conducted over the CPD-10 dataset and PASCAL VOC2007 dataset to evaluate the effectiveness of DK_Loss over the two-stage object detection algorithm, and the results of cross-entropy loss-function-based training are used as baselines. The findings demonstrated that, with DK_Loss taken into account, its mAP is 1–2% above the baseline. Furthermore, the experiments confirmed that the Fliter_nms post-processing method can also improve model precision.
A Method of Sentiment Analysis and Visualized Interaction Based on Ernie-Tiny and BiGRU
Authors: Xiu Yiqi , Liu Xinlei , Qiu Jingjing , Qu Tangjun , Liu Juan , Bian Yulong
Published: May 2023

Sentiment analysis of subjective texts in social media is beneficial to help people adjust and intervene in a negative mental state in time, which is significant to mental health care. At present, limited by the accuracy of word segmentation, sentiment analysis of subjective text has difficulties in dealing with context, sentence patterns, and word co-occurrence. This paper aims to propose an efficient method of semantic feature representation and sentiment analysis, thereby providing a basis for sentiment visualization and interactive applications. Based on Ernie-Tiny and BiGRU, this paper proposes a sentiment analysis model ET_s_BG+p to solve problems in analyzing Chinese subjective texts’ complex semantics, diverse sentence patterns, and shortness. The model inputs the semantic features obtained via Ernie-Tiny into BiGRU and then splices the output with the sentence vectors of Ernie-Tiny to form final text features and perform sentiment classification. Experiments are performed on a dataset integrating text comments from Weibo, takeaway, and e-commerce platforms. The results show that the model proposed in this paper performs best in most of the evaluation indicators compared with baseline models such as CNN, BiLSTM, and GRU. The experiments show that the accuracy of the model on the dataset built in this research is 84.30%, the precision is 83.95%, the recall rate is 88.35%, and the F1 value is 85.98%. At the same time, based on ET_s_BG+p, this paper develops a prototype visual display platform that integrates functions such as text input, sentiment analysis, and agent interaction, which can provide support for daily emotion monitoring and adjustment.
Bone Mineral Density through DEXA and CBCT: A Systematic Review with Meta-Analysis
Authors: Francisco Inês , Nunes Catarina , Pereira Flávia , Travassos Raquel , Ribeiro Madalena Prata , Marques Filipa , McEvoy Mariana , Santos Mariana , Oliveira Catarina , Marto Carlos Miguel , Caramelo Francisco , Paula Anabela Baptista , Vale Francisco
Published: May 2023

Dual-energy X-ray absorptiometry is used to determine bone density in several pathologies, namely osteoporosis and fracture risk in post-menopausal women. The aim of this study was to identify, appraise and synthesize all available evidence about the correlation between Dual Energy X-ray Absorptiometry (DEXA) and Cone Beam Computed Tomography (CBCT) techniques through a systematic review. A systematic literature search was conducted in the following databases: PubMed via MEDLINE, Cochrane Library, EMBASE and Web of Science Core Collection, along with several sources of grey literature. The Cochrane Risk of Bias Tools were used to perform the qualitative assessment of the selected studies. A total of 913 articles were initially scrutinized and 11 were included for qualitative analysis, of which 3 were included in a meta-analysis. Most of the included studies revealed a low risk of bias (7 out of 11). A strong correlation (min r = 0.46 max r = 0.62) between DEXA and CBCT values were found. Thus, opportunistic CBCT scans may be used to assess the bone mineral density and fracture risk, improving the ability to track disease progression and providing better care.
Analysis of 13 Banned Colorants in Cosmetics via Liquid Chromatographic and Mass Spectrometric Techniques
Authors: Han Kyoung-Moon , Kim You Kyung , Seo Sowoon , Kim Jun Hyoung , Lee Ji Hyun , Kim Hyung Il , Cho Sooyeul
Published: May 2023

Even though synthetic colorants can cause side effects such as allergies and pigmentation, they have not been sufficiently researched. Herein, high-performance liquid chromatography, liquid chromatography-tandem mass spectrometry, and liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS) were used to detect 13 banned synthetic colorants in cosmetics and characterize their fragmentation. The developed HPLC method was validated following the International Conference on Harmonisation guidelines (specificity, limit of detection, limit of quantification, recovery, linearity, accuracy, and precision) and applied to 120 distributed cosmetic products, one of which was found to contain three illegal synthetic colorants, namely Basic Blue 26 (0.33 mg/g), Basic Red 2 (0.53 mg/g), and Basic Yellow 28 (31.50 mg/g). Additionally, based on their fragment ions obtained using LC-Q-TOF-MS, the fragmentation pattern of synthetic colorants was predicted. Thus, our work paves the way for the reliable detection of illegal synthetic colorants and may help to prevent the distribution of cosmetics containing the same.
Development of a New Eye Movement Measurement Device Using Eye-Tracking Analysis Technology
Authors: Tatara Shunya , Toda Haruo , Maeda Fumiatsu , Handa Tomoya
Published: May 2023

Smooth pursuit eye movements and saccadic eye movements are vital for precise vision. Therefore, tests for eye movement are important for assessing nervous or muscular diseases. However, objective measurements are not frequently performed due to the need for a polygraph system, electrodes, amplifier, and personal computer for data analysis. To address this, we developed an all-in-one eye-movement-measuring device that simultaneously presents visual stimuli, records eye positions, and examines its feasibility for evaluating eye movements. This device generates stimulus that induces eye movements and records those movements continuously. The horizontal or vertical eye movements of 16 participants were measured at various visual target speeds of 20–100 deg/s. The maximum cross-correlation coefficient (rho max) between the eye and visual target positions was used as an index of eye movement accuracy. A repeated-measures multi-way analysis of variance was performed, with the main effect being that rho max significantly decreased as the visual target speed increased. The average (±standard deviation) rho max values across all velocities were 0.995 ± 0.008 and 0.967 ± 0.062 in the horizontal and vertical directions, respectively, and were significantly higher for horizontal eye movements than for vertical eye movements. Moreover, rho max and saccadic frequency were significantly correlated for the slowest and fastest visual target motions. These suggest that our device enables accurate measurements of eye movements. We believe our new measurement device can be applied clinically for easily and objectively evaluating eye movements.
A Cosine-Similarity-Based Deconvolution Method for Analyzing Data-Independent Acquisition Mass Spectrometry Data
Authors: Zhang Xiang , Wu Ruitao , Qu Zhijian
Published: May 2023

Although data-independent acquisition (DIA) has the ability to identify and quantify all peptides in a sample, highly complex mixed mass spectra present difficulties for accurate peptide and protein identification. Additionally, the correspondence between the precursor and its fragments is broken, making it challenging to perform peptide identification directly using conventional DDA search engines. In this paper, we propose a cosine-similarity-based deconvolution method: CorrDIA. This is achieved by reconstructing the correspondence between precursor and fragment ions based on the consistency of extracted ion chromatograms (XICs). A deisotope peak cluster operation is added and centered on the MS/MS spectrum to improve the accuracy of spectrum interpretation and increase the number of identified peptides. The resulting MS/MS spectra can be identified using any data-dependent acquisition (DDA) sequencing software. The experimental results demonstrate that the number of peptide results increased by 12 percent and 21 percent respectively, and the repetition rate decreased by 12 percent. This reduces mass spectra complexity and difficulties in mass spectra analysis without the need for any mass spectra libraries.
Bacteria Filtration Efficiency for Different Types of Protective Face Masks
Authors: Linšak Željko , Ražov Lucija , Furlan Nikolina , Begić Gabrijela , Pavičić Žeželj Sandra , Crvelin Goran , Broznić Dalibor , Tomić Linšak Dijana
Published: May 2023

Emerging infectious diseases that we are witnessing in the modern age are among the leading public health concerns. They most often occur in the form of epidemics or pandemics, and they have not been sufficiently researched. Owing to the current coronavirus disease 2019 (COVID-19) pandemic, the World Health Organization has published various recommendations to prevent the spread of this communicable disease, including a recommendation to wear protective facial masks. Therefore, this study aimed to determine the filtration effectiveness of bacteria, yeasts, and molds on three different commonly and commercially available masks used in children’s educational institutions. In addition, the bacterial content of indoor air bioaerosols was identified. The genera Staphylococcus and Micrococcus were dominant in all samples, whereas bacteria of the genera Bacillus, Acinetobacter, and Corynebacterium were identified at a significantly smaller number. Bacterial, yeast, and mold filtering effectiveness increased from the single-layer cloth mask, which proved to be the least effective, to the surgical mask, to the filtering facepiece type 2 (FFP2) mask. Furthermore, surveys are needed to study the effectiveness of protective measures.
Pharmaceuticals in Coastal Waters: An UHPLC-TOF-MS Multi-Residue Approach
Authors: Leston Sara , Freitas Andreia , Rosa João , Vila Pouca Ana Sofia , Barbosa Jorge , Reis-Santos Patrick , Fonseca Vanessa F. , Pardal Miguel A. , Ramos Fernando
Published: May 2023

Anthropogenic chemical contamination represents a key stressor of natural environments with pharmaceuticals comprising a particular group of emerging pollutants with the potential to induce biological responses in non-target organisms. Therefore, an analytical method based on ultra-high-performance liquid chromatography coupled to time-of-flight tandem mass spectrometry (UHPLC-TOF-MS) was developed for estuarine and seawaters, targeting 63 globally used pharmaceuticals (including amoxicillin, ciprofloxacin, sulfamethoxazole, trimethoprim and venlafaxine included in the Surface Water Watch List) from 8 therapeutic groups: antibiotics, analgesic, NSAIDs, antidepressants, β-blockers, lipid regulators, anticonvulsants and antihypertensive drugs. The method presents high selectivity and sensitivity, with the limits of detection ranging from 0.01 to 8.92 ng/L and the limits of quantification from 0.02 to 29.73 ng/L. Considering precision, the highest value was achieved for amoxicillin (20.9%) and the lower for ofloxacin (2.6%), while recoveries ranged from 80.6 to 112.6%. Overall, the quantification method was highly efficient for multi-residues quantification in such complex environmental samples.
A Comparison of Signal Analysis Techniques for the Diagnostics of the IMS Rolling Element Bearing Dataset
Authors: Sacerdoti Diletta , Strozzi Matteo , Secchi Cristian
Published: May 2023

In this paper, a comparison of signal analysis techniques for the diagnostics of rolling element bearings is carried out. Specifically, the comparison is performed in terms of fault detection, diagnosis and prognosis techniques with regards to the first rolling element bearing dataset released by NASA IMS Center in 2014. As for fault detection, it is obtained that RMS value, Kurtosis and Detectivity, as statistical parameters, are able to properly detect the arising of the fault on the defective bearings. Then, several signal processing techniques, such as deterministic/random signal separation, time-frequency and cyclostationary analyses are applied to perform fault diagnosis. Among these techniques, it is found that the combination of Cepstrum Pre-Whitening and Squared Envelope Spectrum, and Improved Envelope Spectrum, allow the faults to be correctly identified on specific bearing components. Finally, the Correlation, Monotonicity and Robustness of the previous statistical parameters are computed to identify the most accurate tools for bearing fault prognosis.
Identification of Grape Diseases Based on Improved YOLOXS
Authors: Wang Chaoxue , Wang Yuanzhao , Ma Gang , Bian Genqing , Ma Chunsen
Published: May 2023

Here we proposed a grape disease identification model based on improved YOLOXS (GFCD-YOLOXS) to achieve real-time detection of grape diseases in field conditions. We build a dataset of 11,056 grape disease images in 15 categories, based on 2566 original grape disease images provided by the State Key Laboratory of Plant Pest Biology data center after pre-processing. To improve the YOLOXS algorithm, first, the FOCUS module was added to the backbone network to reduce the lack of information related to grape diseases in the convolution process so that the different depth features in the backbone network are fused. Then, the CBAM (Convolutional Block Attention Module) was introduced at the prediction end to make the model focus on the key features of grape diseases and mitigate the influence of the natural environment. Finally, the double residual edge was introduced at the prediction end to prevent degradation in the deep network and to make full use of the non-key features. Compared with the experimental results of relevant authoritative literature, GFCD-YOLOXS had the highest identification accuracy of 99.10%, indicating the superiority of the algorithm in this paper.
Password Cracking with Brute Force Algorithm and Dictionary Attack Using Parallel Programming
Authors: Alkhwaja Ibrahim , Albugami Mohammed , Alkhwaja Ali , Alghamdi Mohammed , Abahussain Hussam , Alfawaz Faisal , Almurayh Abdullah , Min-Allah Nasro
Published: May 2023

Studying password-cracking techniques is essential in the information security discipline as it highlights the vulnerability of weak passwords and the need for stronger security measures to protect sensitive information. While both methods aim to uncover passwords, both approach the task in different ways. A brute force algorithm generates all possible combinations of characters in a specified range and length, while the dictionary attack checks against a predefined word list. This study compares the efficiency of these methods using parallel versions of Python, C++, and Hashcat. The results show that the NVIDIA GeForce GTX 1050 Ti with CUDA is significantly faster than the Intel(R) HD Graphics 630 GPU for cracking passwords, with a speedup of 11.5× and 10.4× for passwords with and without special characters, respectively. Special characters increase password-cracking time, making the process more challenging. The results of our implementation indicate that parallel processing greatly improves the speed of password-cracking techniques. The brute force algorithm achieved a speedup of 1.9× with six cores, while the dictionary attack showed a speedup of 4.4× with eight-core static scheduling. Studying password-cracking techniques highlights the need for stronger security measures to protect sensitive information and the vulnerability of weak passwords.
Has the Toxicity of Therapeutic Deep Eutectic Systems Been Assessed?
Authors: García Cristina B. , Concha Julia , Culleré Laura , Lomba Laura , Sangüesa Estela , Ribate Mª Pilar
Published: May 2023

Therapeutic Deep Eutectic Systems (THEDESs) are a mixture of components, including an active pharmaceutical ingredient, that have recently emerged because of their interesting properties for drug therapies. In general, they have been recognized to increase the solubility and permeability of some drugs, and consequently, their bioavailability. Moreover, they have also been used for novel formulations of pharmaceuticals. Despite the potential benefits of THEDESs, concerns about their safety and toxicity remain. In this review, we summarize previous studies that have investigated the toxicity of THEDESs. These studies evaluate the toxicity of THEDESs using various methods, including cell cultures, animal models, and human trials. The results of previous findings suggest that THEDESs are generally well-tolerated and have low toxicity. However, further research is needed to fully understand the long-term effects of these systems on human health and to identify any potential adverse effects.
Void Detection inside Duct of Prestressed Concrete Bridges Based on Deep Support Vector Data Description
Authors: Oh Byoung-Doo , Choi Hyung , Chin Won-Jong , Park Chan-Young , Kim Yu-Seop
Published: May 2023

The tendon that is inserted into the duct is a crucial component of prestressed concrete (PSC) bridges and, when exposed to air, can quickly corrode, and cause structural collapse. It can interpret the signal measured by non-destructive testing (NDT) to determine the condition (normal or void) inside the duct. However, it requires the use of expensive NDT equipment such as ultrasonic waves or the hiring of experts. In this paper, we proposed an impact–echo (IE) method based on deep support vector data description (Deep SVDD) for economical void detection inside a duct. Because the pattern of IE changes for various reasons such as difference of specimen or bridge, supervised learning is not suitable. Deep SVDD is classified as normal and defective, which is a broad distribution as a hypersphere that encloses a multi-dimensional feature space for normal data represented by an autoencoder. Here, an autoencoder was developed based on the ELMo (embeddings from language model)-like structure to obtain an effective representation for IE. In the experiment, we evaluated the performance of the IE data measured in different specimens. Thus, our proposed model showed an accuracy of about 77.84% which is an improvement of up to about 47% compared to the supervised learning approach.
A Review of Plant Disease Detection Systems for Farming Applications
Authors: Ngongoma Mbulelo S. P. , Kabeya Musasa , Moloi Katleho
Published: May 2023

The globe and more particularly the economically developed regions of the world are currently in the era of the Fourth Industrial Revolution (4IR). Conversely, the economically developing regions in the world (and more particularly the African continent) have not yet even fully passed through the Third Industrial Revolution (3IR) wave, and Africa’s economy is still heavily dependent on the agricultural field. On the other hand, the state of global food insecurity is worsening on an annual basis thanks to the exponential growth in the global human population, which continuously heightens the food demand in both quantity and quality. This justifies the significance of the focus on digitizing agricultural practices to improve the farm yield to meet the steep food demand and stabilize the economies of the African continent and countries such as India that are dependent on the agricultural sector to some extent. Technological advances in precision agriculture are already improving farm yields, although several opportunities for further improvement still exist. This study evaluated plant disease detection models (in particular, those over the past two decades) while aiming to gauge the status of the research in this area and identify the opportunities for further research. This study realized that little literature has discussed the real-time monitoring of the onset signs of diseases before they spread throughout the whole plant. There was also substantially less focus on real-time mitigation measures such as actuation operations, spraying pesticides, spraying fertilizers, etc., once a disease was identified. Very little research has focused on the combination of monitoring and phenotyping functions into one model capable of multiple tasks. Hence, this study highlighted a few opportunities for further focus.
Adaptive PI + VPI Harmonic Current Compensation Strategy under Weak Grid Conditions
Authors: Zhou Lili , Han Wei , Qi Jia , Zhou Zhen
Published: May 2023

With the increase of the penetration rate of renewable energy power generation in the power system, the power grid gradually tends to be weak. Under the scenario of nonlinear load connecting to weak power grid, the grid-side voltage will produce unbalance, distortion and frequency deviation due to the influence of large internal impedance, insufficient inertia, three-phase current unbalance and harmonics of weak power grid. The operation of active power filters (APF) under above conditions can lead to significant degradation in harmonic compensation performance. An adaptive proportional integral (PI) + vector PI (VPI) harmonic compensation strategy for a three-phase APF is proposed for use in complex conditions of weak grid. The strategy consists of an adaptive notch filter based synchronous phase-locked loop (ANF-PLL) and an adaptive PI + VPI current control method. In this strategy, a series of adaptive lattice notch filters are introduced to improve the accuracy of grid phase and frequency estimation under the condition of voltage unbalance, distortion and a large range of frequency deviation. Then the phase and frequency information are used in the Park transformation of harmonic detection and current compensation control and the update of PI + VPI current control law parameters. A VPI current tracking controller with adaptive resonant frequency is constructed, which can improve the gain of the resonant frequency point and ensure that the APF can maintain the best compensation performance under the above weak grid conditions. Finally, the simulation and experimental results indicate that the ANF-PLL shows a better phase and frequency estimation performance under complex conditions of weak grid than the conventional and notch filter based methods, and the harmonic compensation strategy presented in this paper achieves a significant performance improvement under complex conditions of weak grid compared with Fixed VPI/SRF-PLL strategy and adaptive VPI/NF-PLL strategy.
User Opinion Prediction for Arabic Hotel Reviews Using Lexicons and Artificial Intelligence Techniques
Authors: Al-Mutawa Rihab Fahd , Al-Aama Arwa Yousef
Published: May 2023

Opinion mining refers to the process that helps to identify and to classify users’ emotions and opinions from any source, such as an online review. Thus, opinion mining provides organizations with an insight into their reputation based on previous customers’ opinions regarding their services or products. Automating opinion mining in different languages is still an important topic of interest for scientists, including those using the Arabic language, especially since potential customers mostly do not rate their opinion explicitly. This study proposes an ensemble-based deep learning approach using fastText embeddings and the proposed Arabic emoji and emoticon opinion lexicon to predict user opinion. For testing purposes, the study uses the publicly available Arabic HARD dataset, which includes hotel reviews associated with ratings, starting from one to five. Then, by employing multiple Arabic resources, it experiments with different generated features from the HARD dataset by combining shallow learning with the proposed approach. To the best of our knowledge, this study is the first to create a lexicon that considers emojis and emoticons for its user opinion prediction. Therefore, it is mainly a helpful contribution to the literature related to opinion mining and emojis and emoticons lexicons. Compared to other studies found in the literature related to the five-star rating prediction using the HARD dataset, the accuracy of the prediction using the proposed approach reached an increase of 3.21% using the balanced HARD dataset and an increase of 2.17% using the unbalanced HARD dataset. The proposed work can support a new direction for automating the unrated Arabic opinions in social media, based on five rating levels, to provide potential stakeholders with a precise idea about a service or product quality, instead of spending much time reading other opinions to learn that information.
The Role of Industry 4.0 and Circular Economy for Sustainable Operations: The Case of Bike Industry
Authors: Shen Chiu-Yen , Huang Yung-Fu , Weng Ming-Wei , Lai I-Sung , Huang Hung-Fu
Published: May 2023

In this paper, sustainable design seeks to reduce negative impacts on the environment, and the health and comfort of building occupants, thereby improving financial performance. The basic objectives of sustainability are to reduce consumption of non-renewable resources, minimize waste, and create healthy, productive environments. A sustainable alternative to this production system is Industry 4.0 (I4.0) and circular economy (CE). The contribution of this paper is integrating sustainable production and design decisions of a supply chain in the adoption of I4.0 aimed at cost minimization, in which the decision variables include the production rate of engineered-to-order (ETO) components, design time of general components, and time period of advertising and sales promotions. The validation of the implementation of CE and its production and sale strategies are demonstrated through I4.0. The results presented in this paper may have significant practical value, notably with respect to manufacturers in the bike industry.
Investigation of the Mechanical Properties of Spur Involute Gearing by Infrared Thermography
Authors: Sapieta Milan , Dekýš Vladimír , Kaco Michal , Pástor Miroslav , Sapietová Alžbeta , Drvárová Barbora
Published: May 2023

The work aims at validating a methodology for 3D printing of gears with involute gearing and evaluating their mechanical properties using infrared camera. A general methodology for the setup of 3D printing of gears made of polymeric materials has been developed, which can be used in technical practice in order to replace parts produced by conventional methods. An experiment was prepared determination of the distribution of the 1st invariant of the stress tensor and phase shift using a modal exciter and an IR camera. The values of the 1st invariant of the stress invariant were found. For these measurements, the lock-in thermography method was used, using a modal exciter we force loaded a gear in which the response to the load was registered. The aim was to obtain the distribution of the strain or stress field on the loaded tooth. The experimental method used also belongs to the field of non-destructive testing (NDT), and with suitable experimental parameters we can also obtain information from the layers below the surface, as demonstrated in the phase images. The practical benefit is to provide a competitive advantage to companies that will exploit the properties of polymeric materials by knowing the mechanical properties of these materials.
The Effects of Drought in the Huaibei Plain of China Due to Climate Change
Authors: Badji Ousmane , Zhu Yonghua , Lü Haishen , Guédé Kanon Guédet , Chen Tingxing , Oumarou Abdoulaye , Yao Kouassi Bienvenue Mikael Onan , Brice Sika
Published: May 2023

Damage from climate change is widespread throughout the world. This change has brought about calamities, the most prevalent of which is the emergence of numerous droughts which are increasingly threatening human lives. In this paper, we studied the spatial and temporal variations of drought under the effect of climate change in the Huaibei Plain, which is a very important agricultural zone in China. Drought has attracted increasing attention in research due to its heavy impact on agriculture, the environment, livelihood, and food security. The SPEI (Standardized Precipitation Evapotranspiration Index) has been used in this study to express and identify drought events in the Huaibei Plain due to climate change. A general circulation model (GCM), HadGEM2-AO, which was the most appropriate for the study area’s precipitation simulation, and three Representative Concentration Pathways (RCP), RCP 2.6, RCP 4.5, and RCP 8.5, were used to analyze and compare the drought effect for the baseline (1985–2017) and the future climate scenarios (2025–2090). At 3 and 6 months, the SPEI successfully detects agricultural drought in temporal and spatial variation. However, according to the analysis, more severe agricultural drought events are foreseen in the future than in the baseline because of climate change. SPEI performed better than SPI in detecting drought in the baseline and simulated data due to increased evapotranspiration. Between the SPEI-3 and SPEI-6, the Pearson coefficient correlation reveals a positive association. The Mann-Kendall test was used to cover the two studied periods in order to establish the drought trend. Both decreasing and increasing trends, in different timescales, were detected by Sen’s Slope in the baseline and future periods with all RCPs.
Physicochemical Assessment of the Road Vehicle Traffic Pollution Impact on the Urban Environment
Authors: Rusca Marcel , Rusu Tiberiu , Avram Simona Elena , Prodan Doina , Paltinean Gertrud Alexandra , Filip Miuta Rafila , Ciotlaus Irina , Pascuta Petru , Rusu Tudor Andrei , Petean Ioan
Published: May 2023

Vehicle traffic pollution requires complex physicochemical analysis besides emission level measuring. The current study is focused on two campaigns of emissions measurements held in May and September 2019 in Alba Iulia City, Romania. There was found a significant excess of PM2.5 for all measuring points and PM10 for the most circulated points during May, along with significant VOC and CO2 emissions. September measurements reveal threshold excess for all PM along with increased values for VOC and CO2 emissions. These are the consequences of the complex environmental interaction of the traffic. Street dust and air-suspended particle samples were collected and analyzed to evidence the PM2.5 and PM10 sources. Physicochemical investigation reveals highly mineralized particulate matter: PM2.5 fractions within air-suspended particle samples predominantly contain Muscovite, Kaolinite, and traces of Quartz and Calcite, while PM10 fractions within air-suspended particle samples predominantly contain Quartz and Calcite. These mineral fractions originate in street dust and are suspended in the atmosphere due to the vehicles’ circulation. A significant amount of soot was found as small micro-sized clusters in PM2.5 and fine micro-spots attached over PM10 particles, as observed by Mineralogical Optical Microscopy (MOM) and Fourier Transformed Infrared Spectroscopy (FTIR). GC-MS analysis found over 53 volatile compounds on the investigated floating particles that are related to the combustion gases, such as saturated alkanes, cycloalkanes, esters, and aromatic hydrocarbons. It proves a VOC contamination of the measured particulate matters that make them more hazardous for the health. Viable strategies for vehicle traffic-related pollutants mitigation would be reducing the street dust occurrence and usage of modern catalyst filters of the combustion gas exhausting system.
Stabilizing Frequency of a Diode Laser to a Reference Transition of Molecular Iodine through Modulation Transfer Spectroscopy
Authors: Sharma Lakhi , Roy Atish , Panja Subhasis , De Subhadeep
Published: May 2023

We report the frequency stabilization of an external cavity diode laser (ECDL) to a reference molecular iodine (I2) transition at 13,531.18 cm−1 (739.03382 nm). Using the Modulation Transfer Spectroscopy (MTS) method for the highly sensitive detection of weak absorption signals, the Doppler-free absorption peaks of I2 corresponding to the hot band transition R(78) (1–11) are resolved. The ECDL’s frequency is stabilized with respect to one of the lines lying within the reference absorption band. For this, the iodine vapor cell is heated to 450 °C and the corresponding circularly polarized pump and probe beam powers are maintained at 10 mW and 1 mW, respectively, to avoid power broadening. The short (100 ms) and long-term (50 h) linewidths of the frequency stabilized laser are measured to be 0.75(3) MHz and 0.5(2) MHz, respectively, whereas the natural linewidth of the specific I2-transitions lie within a range of tens of MHz.
Hearing Rehabilitation in Vestibular Schwannoma
Authors: Mankekar Gauri , Holmes Sean
Published: May 2023

The most common complaint among patients with vestibular schwannoma (VS) is hearing loss. This significantly affects the quality of life before, during, and after treatment for patients with VS. Untreated hearing loss in VS patients may even lead to depression and feelings of social isolation. A variety of devices are available for hearing rehabilitation for patients with vestibular schwannoma. These include contralateral routing of hearing signals (CROSs), bone-anchored hearing devices, auditory brainstem implants (ABI), and cochlear implants. In the United States, ABI is approved for patients 12 years of age and older with neurofibromatosis type 2. In the past few years, cochlear implantation has been offered simultaneously or sequentially with tumor resection or irradiation, or even to patients whose VS have been monitored with serial imaging. However, determining the functional integrity of the auditory nerve in patients with vestibular schwannoma is a challenge. This review article consists of (1) the pathophysiology of vestibular schwannoma (VS), (2) hearing loss in VS, (3) treatment of VS and associated hearing loss, (4) options for auditory rehabilitation in patients with VS with their individual benefits and limitations, and (5) challenges in hearing rehabilitation in this cohort of patients to determine auditory nerve functionality. (6) Future directions.
Abundant Solitary Wave Solutions for the Boiti–Leon–Manna–Pempinelli Equation with M-Truncated Derivative
Authors: Al-Askar Farah M. , Cesarano Clemente , Mohammed Wael W.
Published: May 2023

In this work, we consider the Boiti–Leon–Manna–Pempinelli equation with the M-truncated derivative (BLMPE-MTD). Our aim here is to obtain trigonometric, rational and hyperbolic solutions of BLMPE-MTD by employing two diverse methods, namely, He’s semi-inverse method and the extended tanh function method. In addition, we generalize some previous results. As the Boiti–Leon–Manna–Pempinelli equation is a model for an incompressible fluid, the solutions obtained may be utilized to represent a wide variety of fascinating physical phenomena. We construct a large number of 2D and 3D figures to demonstrate the impact of the M-truncated derivative on the exact solution of the BLMPE-MTD.
Selection of a Forklift for a Cargo Company with Fuzzy BWM and Fuzzy MCRAT Methods
Authors: Ulutaş Alptekin , Topal Ayse , Karabasevic Darjan , Balo Figen
Published: May 2023

Material handling is a cost-intensive operation for businesses. There are several alternative types of equipment for material handling, therefore it is important to select the best one among them to decrease the cost. As there are several different alternatives and criteria which are used to assess these alternatives, multi-criteria decision making (MCDM) techniques are useful to determine the optimal material handling equipment (MHE) for businesses. In this study, fuzzy BWM for determining weights of criteria and the fuzzy Multiple Criteria Ranking by Alternative Trace (MCRAT) method have been used for ranking forklift alternatives. This study’s significance in the literature will be the creation of a novel fuzzy MCDM technique with the application of fuzzy MCRAT. Furthermore, there are relatively few studies employing the MCRAT approach in the literature; therefore, this study will provide additional data and outcomes from this method to the literature. The findings present that the forklift with the code FLT-3 performed the best, whereas the forklift with the code FLT-2 had the worst performance, according to the fuzzy MCRAT technique. According to the comparison analysis, the fuzzy MCRAT produced the same results as the fuzzy ARAS and had a few subtle differences to fuzzy MARCOS.
High-Energy and High-Power Primary Li-CFx Batteries Enabled by the Combined Effects of the Binder and the Electrolyte
Authors: Huo Haobin , Radhakrishnan Sivaviswa , Shaw Leon L. , Németh Károly
Published: May 2023

Several effective methods have been developed recently to demonstrate simultaneous high energy and high power density in Lithium - carbon fluoride (Li-CFx) batteries. These methods can achieve as high as a 1000 Wh/kg energy density at a 60–70 kW/kg power density (40–50 C rate) in coin cells and a 750 Wh/kg energy density at a 12.5 kW/kg power density (20 C rate) in pouch cells. This performance is made possible by an ingenious nano-architecture design, controlled porosity, boron doping, and electrolyte additives. In the present study, we show that a similarly great performance, a 931 Wh/kg energy density at a 59 kW/kg power density, can be achieved by using a polyacrylonitrile binder and a LiBF4 electrolyte in Li-graphite fluoride coin cells. We also demonstrate that the observed effect is the result of the right combination of the binder and the electrolyte. We propose that the mechanistic origin of the observed phenomena is an electro-catalytic effect of the polyacrylonitrile binder. While our proposed method has a competitive performance, it also offers a simple implementation and a scalable production of high-energy and high-power primary Li-CFx cells.
SQL and NoSQL Database Software Architecture Performance Analysis and Assessments—A Systematic Literature Review
Authors: Khan Wisal , Kumar Teerath , Zhang Cheng , Raj Kislay , Roy Arunabha M. , Luo Bin
Published: May 2023

The competent software architecture plays a crucial role in the difficult task of big data processing for SQL and NoSQL databases. SQL databases were created to organize data and allow for horizontal expansion. NoSQL databases, on the other hand, support horizontal scalability and can efficiently process large amounts of unstructured data. Organizational needs determine which paradigm is appropriate, yet selecting the best option is not always easy. Differences in database design are what set SQL and NoSQL databases apart. Each NoSQL database type also consistently employs a mixed-model approach. Therefore, it is challenging for cloud users to transfer their data among different cloud storage services (CSPs). There are several different paradigms being monitored by the various cloud platforms (IaaS, PaaS, SaaS, and DBaaS). The purpose of this SLR is to examine the articles that address cloud data portability and interoperability, as well as the software architectures of SQL and NoSQL databases. Numerous studies comparing the capabilities of SQL and NoSQL of databases, particularly Oracle RDBMS and NoSQL Document Database (MongoDB), in terms of scale, performance, availability, consistency, and sharding, were presented as part of the state of the art. Research indicates that NoSQL databases, with their specifically tailored structures, may be the best option for big data analytics, while SQL databases are best suited for online transaction processing (OLTP) purposes.
Optimization Design and Performance Analysis of a Bionic Knee Joint Based on the Geared Five-Bar Mechanism
Authors: Wang Zhuo , Ge Wenjie , Zhang Yonghong , Liu Bo , Liu Bin , Jin Shikai , Li Yuzhu
Published: May 2023

Animal joint motion is a combination of rotation and translational motion, which brings high stability, high energy utilization, and other advantages. At present, the hinge joint is widely used in the legged robot. The simple motion characteristic of the hinge joint rotating around the fixed axis limits the improvement of the robot’s motion performance. In this paper, by imitating the knee joint of a kangaroo, we propose a new bionic geared five-bar knee joint mechanism to improve the energy utilization rate of the legged robot and reduce the required driving power. Firstly, based on image processing technology, the trajectory curve of the instantaneous center of rotation (ICR) of the kangaroo knee joint was quickly obtained. Then, the bionic knee joint was designed by the single-degree-of-freedom geared five-bar mechanism and the parameters for each part of the mechanism were optimized. Finally, based on the inverted pendulum model and the Newton–Euler recursive method, the dynamics model of the single leg of the robot in the landing stage was established, and the influence of the designed bionic knee joint and hinge joint on the robot’s motion performance was compared and analyzed. The proposed bionic geared five-bar knee joint mechanism can more closely track the given trajectory of the total center of mass motion, has abundant motion characteristics, and can effectively reduce the power demand and energy consumption of the robot knee actuators under the high-speed running and jumping gait.
Different Strategies Affect Enzyme Packaging into Bacterial Outer Membrane Vesicles
Authors: Dean Scott N. , Thakur Meghna , Spangler Joseph R. , Smith Aaron D. , Garin Sean P. , Walper Scott A. , Ellis Gregory A.
Published: May 2023

All Gram-negative bacteria are believed to produce outer membrane vesicles (OMVs), proteoliposomes shed from the outermost membrane. We previously separately engineered E. coli to produce and package two organophosphate (OP) hydrolyzing enzymes, phosphotriesterase (PTE) and diisopropylfluorophosphatase (DFPase), into secreted OMVs. From this work, we realized a need to thoroughly compare multiple packaging strategies to elicit design rules for this process, focused on (1) membrane anchors or periplasm-directing proteins (herein “anchors/directors”) and (2) the linkers connecting these to the cargo enzyme; both may affect enzyme cargo activity. Herein, we assessed six anchors/directors to load PTE and DFPase into OMVs: four membrane anchors, namely, lipopeptide Lpp’, SlyB, SLP, and OmpA, and two periplasm-directing proteins, namely, maltose-binding protein (MBP) and BtuF. To test the effect of linker length and rigidity, four different linkers were compared using the anchor Lpp’. Our results showed that PTE and DFPase were packaged with most anchors/directors to different degrees. For the Lpp’ anchor, increased packaging and activity corresponded to increased linker length. Our findings demonstrate that the selection of anchors/directors and linkers can greatly influence the packaging and bioactivity of enzymes loaded into OMVs, and these findings have the potential to be utilized for packaging other enzymes into OMVs.