bluuebunny/crossref_metadata_2025 huggingface dataset:
Carbapenem Combinations for Infections Caused by Carbapenemase-Producing Pseudomonas aeruginosa: Experimental In Vitro and In Vivo Analysis
Authors: Herrera-Espejo Soraya , Del Barrio-Tofiño Ester , Cebrero-Cangueiro Tania , López-Causapé Carla , Álvarez-Marín Rocío , Cisneros José Miguel , Pachón Jerónimo , Oliver Antonio , Pachón-Ibáñez María Eugenia
Published: September 2022

In the context of difficult-to-treat carbapenem-resistant Pseudomonas aeruginosa infections, we evaluated imipenem, meropenem, and doripenem combinations against eleven carbapenemase-producing P. aeruginosa isolates. According to the widespread global distribution of high-risk clones and carbapenemases, four representative isolates were selected: ST175 (OXA-2/VIM-20), ST175 (VIM-2), ST235 (GES-5), and ST111 (IMP-33), for efficacy studies using a sepsis murine model. Minimum inhibitory concentration (mg/L) ranges were 64–256 for imipenem and 16–128 for meropenem and doripenem. In vitro, imipenem plus meropenem was synergistic against 72% of isolates and doripenem plus meropenem or imipenem against 55% and 45%, respectively. All combinations were synergistic against the ST175, ST235, and ST155 clones. In vivo, meropenem diminished the spleen and blood bacterial concentrations of four and three isolates, respectively, with better efficacy than imipenem or doripenem. The combinations did not show efficacy compared with the more active monotherapies, except for imipenem plus meropenem, which reduced the ST235 bacterial spleen concentration. Mortality decreased with imipenem plus meropenem or doripenem for the ST175 isolate. Results suggest that carbapenem combinations are not an alternative for severe infections by carbapenemase-producing P. aeruginosa. Meropenem monotherapy showed in vivo efficacy despite its high MIC, probably because its dosage allowed a sufficient antimicrobial exposure at the infection sites.
Resistance of Streptococcus suis Isolates from the Czech Republic during 2018–2022
Authors: Nedbalcova Katerina , Kucharovicova Ivana , Zouharova Monika , Matiaskova Katarina , Kralova Natalie , Brychta Marek , Simek Bronislav , Pecha Tomas , Plodkova Hana , Matiasovic Jan
Published: September 2022

A determination of susceptibility/resistance to antimicrobials via serotype was carried out in 506 field isolates of Streptococcus suis, originating from pig farms in the Czech Republic in the period 2018–2022. A very high level of susceptibility of S. suis isolates was found to amoxicillin, in combination with clavulanic acid and sulfamethoxazole potentiated with trimethoprim. None of the tested isolates were resistant to these antimicrobial substances. Only two isolates were found to be intermediately resistant to enrofloxacin in 2020. With regard to ceftiofur, one isolate was intermediately resistant in 2020 and 2022, and two isolates were intermediately resistant in 2018 and 2021. A low level of resistance was detected to ampicillin (0.6% in 2021) and to florfenicol (1.15% in 2019; 1.3% in 2022). With regard to penicillin, a medium level of resistance was detected in 2018 (10.6%), but a low level of resistance was found in the following years (7.0% in 2019; 3.1% in 2020; 3.3% in 2021; 3.9% in 2022). On the contrary, a high or very high level of resistance was found to tetracycline (66.0% in 2018; 65.1% in 2019; 44.35% in 2020; 46.4% in 2021; 54.0% in 2022). Using molecular and serological methods, serotype 7 (16.4%) was determined to be predominant among S. suis isolates, followed by serotypes 1/2, 2, 9, 4, 3, 1, 29, 16, and 31 (10.7%; 8.5%; 5.7%; 5.5%; 4.5%; 4.3%; 3.6%; 3.4%; 3.4%, respectively). Other serotypes were identified among the investigated strains either rarely (up to 10 cases) or not at all. A relatively high percentage of isolates were detected as non-typeable (79 isolates; 15.6%). Dependence of resistance upon serotype assignment could not be proven in all but serotype 31, wherein all isolates (n = 17) were resistant or intermediately resistant to clindamycin, tilmycosin, tulathromycin, and tetracycline. The resistance to clindamycin and tetracycline may be related to the high consumption of these antibiotics on pig farms at present or in previous years. Macrolides (tilmicosin and tulathromycin) and tiamulin are not suitable for the treatment of streptococcal infections, but are used on pig farms to treat respiratory infections caused by gram-negative bacteria, so they were included in the study.
Silver Nanoparticle-Based Combinations with Antimicrobial Agents against Antimicrobial-Resistant Clinical Isolates
Authors: Alotaibi Areej M. , Alsaleh Nasser B. , Aljasham Alanoud T. , Tawfik Essam A. , Almutairi Mohammed M. , Assiri Mohammed A. , Alkholief Musaed , Almutairi Mashal M.
Published: September 2022

The increasing prevalence of antimicrobial-resistant (AMR) bacteria along with the limited development of antimicrobials warrant investigating novel antimicrobial modalities. Emerging inorganic engineered nanomaterials (ENMs), most notably silver nanoparticles (AgNPs), have demonstrated superior antimicrobial properties. However, AgNPs, particularly those of small size, could exert overt toxicity to mammalian cells. This study investigated whether combining AgNPs and conventional antimicrobials would produce a synergistic response and determined the optimal and safe minimum inhibitory concentration (MIC) range against several wild-type Gram-positive and -negative strains and three different clinical isolates of AMR Klebsiella pneumoniae. Furthermore, the cytotoxicity of the synergistic combinations was assessed in a human hepatocyte model. The results showed that the AgNPs (15–25 nm) were effective against Gram-negative bacteria (MIC of 16–128 µg/mL) but not Gram-positive strains (MIC of 256 µg/mL). Both wild-type and AMR K. pneumoniae had similar MIC values following exposure to AgNPs. Importantly, co-exposure to combinations of AgNPs and antimicrobial agents, including kanamycin, colistin, rifampicin, and vancomycin, displayed synergy against both wild-type and AMR K. pneumoniae isolates (except for vancomycin against AMR strain I). Notably, the tested combinations demonstrated no to minimal toxicity against hepatocytes. Altogether, this study indicates the potential of combining AgNPs with conventional antimicrobials to overcome AMR bacteria.
An Oleocanthal-Enriched EVO Oil Extract Induces the ROS Production in Gastric Cancer Cells and Potentiates the Effect of Chemotherapy
Authors: Peri Sara , Ruzzolini Jessica , Urciuoli Silvia , Versienti Giampaolo , Biagioni Alessio , Andreucci Elena , Peppicelli Silvia , Bianchini Francesca , Bottari Andrea , Calorini Lido , Nediani Chiara , Magnelli Lucia , Papucci Laura
Published: September 2022

Oleocanthal, a minor polar compound in extra-virgin olive (EVO) oil, contains anticancer properties, which should be encouraged in its use in oncology. Gastric Cancer (GC), a very aggressive human cancer, is often diagnosed at advanced stages, when surgery is substituted or supported by chemotherapy (CT). However, CT frequently fails due to the patient’s resistance to the treatment. Thus, the aim of this study is to verify whether an OC-enriched EVO oil extract fraction (OCF) may be useful in order to overcome a resistance to GC. We evaluated the OCF effects on an AGS gastric adenocarcinoma cell line wild type (AGS wt) and on its subpopulations resistant to 5-fluorouracil (5FUr), Paclitaxel (TAXr) or cisplatin (CISr). We found that a 60 µM dose of the OCF acts on the AGS wt, 5FUr and TAXr, leading to the cell cycle inhibition and to a ROS production, but not on CISr cells. Resistance of CISr to the OCF seems to be due to higher levels of antioxidant-enzymes that can counteract the OCF-induced ROS production. Moreover, using the OCF plus 5-fluorouracil, Paclitaxel or cisplatin, we found a potentiating effect compared with a mono-treatment in all resistant GC cells, including CISr. In conclusion, the use of the OCF in the management of GC has shown very interesting advantages, opening-up the possibility to evaluate the efficacy of the OCF in vivo, as a valid adjuvant in the treatment of resistant GC.
Identification and Antioxidant Capacity of Free and Bound Phenolics in Six Varieties of Mulberry Seeds Using UPLC-ESI-QTOF-MS/MS
Authors: Gao Huaqi , Guo Meimei , Wang Liqin , Sun Cui , Huang Lingxia
Published: September 2022

Mulberry seeds are a byproduct of juice processing and may be an important resource for its abundant compounds. In this study, we analyzed the qualitative composition of free and bound phenolics from six varieties of mulberry seeds using UPLC-ESI-QTOF-MS/MS. Free phenolics (FPs) and bound phenolics (BPs) were measured using the Folin–Ciocalteu method; antioxidant capacity was determined by measuring 2,2-diphenyl-1-picrylhydrazyl radical-scavenging activity, using the ferric reducing antioxidant power assay. A total of 28 free and 11 bound phenolics were extracted and identified, wherein five free phenolics were found in mulberry matrices for the first time. The six varieties of mulberry seeds exhibited higher content of FPs than BPs, and there was a correlation between the phenolic content and antioxidant capacity. Consequently, three varieties were selected for their high phenolic content and antioxidant capacity. This study might offer a theoretical basis for the utilization of mulberry seed.
Dimethyl Fumarate (DMF) Alleviated Post-Operative (PO) Pain through the N-Methyl-d-Aspartate (NMDA) Receptors
Authors: Casili Giovanna , Lanza Marika , Filippone Alessia , Cucinotta Laura , Paterniti Irene , Repici Alberto , Capra Anna Paola , Cuzzocrea Salvatore , Esposito Emanuela , Campolo Michela
Published: September 2022

The management of post-operative (PO) pain has generally been shown to be inadequate; therefore, acquiring a novel understanding of PO pain mechanisms would increase the therapeutic options available. There is accumulating evidence to implicate N-methyl-d-aspartate (NMDA) receptors in the induction and maintenance of central sensitization during pain states by reinforcing glutamate sensory transmission. It is known that DMF protects from oxidative glutamate toxicity. Therefore, NMDA receptor antagonists have been implicated in peri-operative pain management. Recent advances demonstrated that dimethyl fumarate (DMF), a non-opioid and orally bioavailable drug, is able to resolve neuroinflammation through mechanisms that drive nociceptive hypersensitivity. Therefore, in this study, we evaluated the role of DMF on pain and neuroinflammation in a mouse model of PO pain. An incision of the hind paw was performed, and DMF at two different doses (30 and 100 mg/kg) was administered by oral gavage for five consecutive days. Mechanical allodynia, thermal hyperalgesia and locomotor dysfunction were evaluated daily for five days after surgery. Mice were sacrificed at day 7 following PO pain induction, and hind paw and lumbar spinal cord samples were collected for histological and molecular studies. DMF administration significantly reduced hyperalgesia and allodynia, alleviating motor disfunction. Treatment with DMF significantly reduced histological damage, counteracted mast cell activation and reduced the nuclear factor kappa-light-chain-enhancer of the activated B cell (NF-κB) inflammatory pathway, in addition to downregulating tumor necrosis factor-α (TNF-α), Interleukin-1β (Il-1β) and Il-4 expression. Interestingly, DMF treatment lowered the activation of NMDA receptor subtypes (NR2B and NR1) and the NMDA-receptor-interacting PDZ proteins, including PSD93 and PSD95. Furthermore, DMF interfered with calcium ion release, modulating nociception. Thus, DMF administration modulated PO pain, managing NMDA signaling pathways. The results suggest that DMF positively modulated persistent nociception related to PO pain, through predominantly NMDA-receptor-operated calcium channels.
Enhanced Arabic Sentiment Analysis Using a Novel Stacking Ensemble of Hybrid and Deep Learning Models
Authors: Saleh Hager , Mostafa Sherif , Gabralla Lubna Abdelkareim , O. Aseeri Ahmad , El-Sappagh Shaker
Published: September 2022

Sentiment analysis (SA) is a machine learning application that drives people’s opinions from text using natural language processing (NLP) techniques. Implementing Arabic SA is challenging for many reasons, including equivocation, numerous dialects, lack of resources, morphological diversity, lack of contextual information, and hiding of sentiment terms in the implicit text. Deep learning models such as convolutional neural networks (CNN) and long short-term memory (LSTM) have significantly improved in the Arabic SA domain. Hybrid models based on CNN combined with long short-term memory (LSTM) or gated recurrent unit (GRU) have further improved the performance of single DL models. In addition, the ensemble of deep learning models, especially stacking ensembles, is expected to increase the robustness and accuracy of the previous DL models. In this paper, we proposed a stacking ensemble model that combined the prediction power of CNN and hybrid deep learning models to predict Arabic sentiment accurately. The stacking ensemble algorithm has two main phases. Three DL models were optimized in the first phase, including deep CNN, hybrid CNN-LSTM, and hybrid CNN-GRU. In the second phase, these three separate pre-trained models’ outputs were integrated with a support vector machine (SVM) meta-learner. To extract features for DL models, the continuous bag of words (CBOW) and the skip-gram models with 300 dimensions of the word embedding were used. Arabic health services datasets (Main-AHS and Sub-AHS) and the Arabic sentiment tweets dataset were used to train and test the models (ASTD). A number of well-known deep learning models, including DeepCNN, hybrid CNN-LSTM, hybrid CNN-GRU, and conventional ML algorithms, have been used to compare the performance of the proposed ensemble model. We discovered that the proposed deep stacking model achieved the best performance compared to the previous models. Based on the CBOW word embedding, the proposed model achieved the highest accuracy of 92.12%, 95.81%, and 81.4% for Main-AHS, Sub-AHS, and ASTD datasets, respectively.
Continual Learning for Table Detection in Document Images
Authors: Minouei Mohammad , Hashmi Khurram Azeem , Soheili Mohammad Reza , Afzal Muhammad Zeshan , Stricker Didier
Published: September 2022

The growing amount of data demands methods that can gradually learn from new samples. However, it is not trivial to continually train a network. Retraining a network with new data usually results in a phenomenon called “catastrophic forgetting”. In a nutshell, the performance of the model on the previous data drops by learning from the new instances. This paper explores this issue in the table detection problem. While there are multiple datasets and sophisticated methods for table detection, the utilization of continual learning techniques in this domain has not been studied. We employed an effective technique called experience replay and performed extensive experiments on several datasets to investigate the effects of catastrophic forgetting. The results show that our proposed approach mitigates the performance drop by 15 percent. To the best of our knowledge, this is the first time that continual learning techniques have been adopted for table detection, and we hope this stands as a baseline for future research.
MSSI-Based Dispersion-Managed Link Configured by Randomly-Distributed RDPS Only in Former Half Section
Authors: Chung Jae-Pil , Lee Seong-Real
Published: September 2022

The weakness of the dispersion-managed link, which is combined with optical phase conjugation to compensate for optical signal distortion caused by chromatic dispersion and the nonlinear Kerr effect of the standard single mode fiber is, its limited structural flexibility. We propose a dispersion map that can simultaneously compensate for the distorted wavelength division multiplexed signal while increasing the configurational flexibility. Each residual dispersion per span (RDPS) in the former half of the proposed link is randomly determined, and in the latter half, the arrangement order of RDPS is the same as or inverted in the former half. We confirm that the dispersion maps in which the RDPS distribution pattern in the latter half is opposite to the arrangement order in the former half are more effective in compensation, and the compensation effect is better than in the dispersion map of the conventional scheme. The notable result of this study is that the flexibility can be increased by randomly arranging RDPS in the former half, and compensation improvement can be achieved by inversing the order of RDPS arrangement of the former half in the latter half, which makes the dispersion profile of each half link roughly symmetric with respect to the midway optical phase conjugator.
Home-Based Activities for Children with Speech Sound Disorders: Requirements for a Tangible User Interface for Internet of Things Artefacts
Authors: Santos Joaquim , Vairinhos Mário , Rodriguez Jonathan , Jesus Luis M. T.
Published: September 2022

This paper presents the state of the art regarding the use of tangible user interfaces for internet of artefacts (IoA) targeting health applications, with a focus on speech and language therapy and related areas, targeting home-based interventions, including data security and privacy issues. Results from a systematic literature review, focus group, and a nationwide questionnaire have been used to determine the system requirements for an artefact prototype to be developed. The aim of this study was to understand what is the usual practice of clinicians and to contribute to a better intervention or post-intervention approach for children with Speech Sound Disorders (SSD). The literature review revealed that some studies proposed technological solutions while others used a social approach and/or gamified activities. We could conclude that more research is needed and that a unified method or framework to address SSD intervention or post-intervention tools is lacking. Clinicians need more and better tools to be able to quantify and qualitatively assess the activities developed at home.
Efficient Design of Thermoelastic Structures Using a Krylov Subspace Preconditioner and Parallel Sensitivity Computation
Authors: Fu Yu , Li Li , Hu Yujin
Published: September 2022

The repeated updating of parametric designs is computationally challenging, especially for large-scale multi-physics models. This work is focused on proposing an efficient modal modification method for gradient-based topology optimization of thermoelastic structures, which is essential when dealing with their complex eigenproblems and global sensitivity analysis for a huge number of design parameters. The degrees of freedom of the governing equation of thermoelastic structures is very huge when its parametric partial differential equation is discretized using the numerical technique. A Krylov subspace preconditioner is constructed based on the Neumann series expansion series so that the thermoelastic eigenproblem can be solved in an efficient low-dimension solver, rather than its original high-fidelity solver. In the construction of Krylov reduced-basis vectors, the computational cost of the systemic matrix inverse becomes a critical issue, which is solved efficiently by means of constructing a diagonal systemic matrix with the lumped mass and heat generation submatrices. Then, the reduced-basis preconditioner can provide an efficient optimal solver for both the thermoelastic eigenproblem and its eigen sensitivity. Furthermore, a master-slave pattern parallel method is developed to reduce the computational time of computing the global sensitivity numbers, and therefore, the global sensitivity problem can be efficiently discretized into element-scale problems in a parallel way. The sensitivity numbers can thus be solved at the element scale and aggregated to the global sensitivity number. Finally, two case studies of the iterative topology optimization process, in which the proposed modal modification method and the traditional method are implemented, are used to illustrate the effectiveness of the proposed method. Numerical examples show that the proposed method can reduce the computational cost remarkably with acceptable accuracy.
Effectiveness of Decision Support to Treat Complex Regional Pain Syndrome
Authors: Ryskalin Larisa , Ghelarducci Giulia , Marinelli Chiara , Morucci Gabriele , Soldani Paola , Bertozzi Nicolò , Annoscia Paolo , Poggetti Andrea , Gesi Marco
Published: September 2022

Background: Complex regional pain syndrome (CRPS) type 1 is a rare but disabling pain condition, usually involving distal extremities such as the wrist, hand, ankle, and foot due to either direct or indirect traumas. CRPS type 1 is characterized by a complex set of symptoms where no correlation can be identified between the severity of the initial injury and the ensuing painful syndrome. Over the years, numerous treatment strategies have been proposed for CRPS management, but therapies remain controversial. At present, no successful therapeutic intervention exists for this condition. The aim of the present study was to propose and assess the effectiveness of a rehabilitative treatment algorithm for CRPS, which is actually in use at our institution. Methods: We retrospectively reviewed all the patients that underwent physical rehabilitative treatment algorithm for hand CRPS between 2011 and 2017 at our Institution. Results: All the parameters taken into consideration, namely the Purdue Pegboard Test (PPT), Disability of the Arm, Shoulder and Hand (DASH), Visual Analog Scale (VAS), as well hand edema, were significantly improved at the end of the rehabilitation protocol. Conclusions: The results obtained in the present study demonstrated that our rehabilitation protocol was able to achieve substantial improvement in pain and quality of life scores. Thus, an early and skillful rehabilitation intervention is of paramount importance for CPRS type 1 management to achieve a stable and optimal functional recovery while preventing the onset of deformities.
Secure Smart Communication Efficiency in Federated Learning: Achievements and Challenges
Authors: Pouriyeh Seyedamin , Shahid Osama , Parizi Reza M. , Sheng Quan Z. , Srivastava Gautam , Zhao Liang , Nasajpour Mohammad
Published: September 2022

Federated learning (FL) is known to perform machine learning tasks in a distributed manner. Over the years, this has become an emerging technology, especially with various data protection and privacy policies being imposed. FL allows for performing machine learning tasks while adhering to these challenges. As with the emergence of any new technology, there will be challenges and benefits. A challenge that exists in FL is the communication costs: as FL takes place in a distributed environment where devices connected over the network have to constantly share their updates, this can create a communication bottleneck. This paper presents the state-of-the-art of the conducted works on communication constraints of FL while maintaining the secure and smart properties that federated learning is known for. Overall, current challenges and possible methods for enhancing the FL models’ efficiency with a perspective on communication are discussed. This paper aims to bridge the gap in all conducted review papers by solely focusing on communication aspects in FL environments.
Genesis and Significance of Late Cretaceous Granitic Magmatism in Xianghualing Tin–Polymetallic Orefield, Nanling Region, South China
Authors: Zhang Zhihui , Hu Bojie , Zhang Da , He Xiaolong , Zou Jianlin , Tian Xufeng , Yi Yuanshun
Published: September 2022

Typical stratiform-like cassiterite–sulfide orebodies formed at 160–150 Ma cut by a steep hydrothermal vein-type orebody were discovered in the Xianghualing tin–polymetallic orefield, which implied a new phase of magmatism and mineralization later than the Late Jurassic stage. Hence, a systematic study of the characteristics and genesis of the concealed Laohuya granite, including U–Pb age, trace elements, Lu–Hf isotopes of zircons, and whole-rock major- and trace-elements, is examined in this paper. The zircon U–Pb dating yielded a Concordia age of 87.75 ± 1 Ma, confirming the existence of Late Cretaceous magmatism in the Xianghualing tin–polymetallic orefield. The Laohuya granite is classified as syenogranite and belongs to the peraluminous, high K calc-alkaline series. It is a highly evolved A2-type granite with εHf(t) values ranging from −14.97 to −7.59 and two-stage model ages (TDM2) ranging from 2939 to 2280 Ma. Combining chronology, petrochemistry, isotopic geochemistry, and previous tectonic studies, we believe that the Laohuya granite originated from the partial melting of a reworked ancient crust composed of TTGs, and its weathered sediments formed in subduction or collision zones at 2.5 Ga, controlled by the reactivation of the Chenzhou–Linwu deep fault in the extensional setting of South China during the Late Cretaceous.
Inversion and Analysis of the Initial Ground Stress Field of the Deep-Buried Tunnel Area
Authors: Yu Rongsen , Tan Zhongsheng , Gao Junpeng , Wang Xiuying , Zhao Jinpeng
Published: September 2022

The detailed analysis of the initial ground stress distribution law is an important work for the safety of tunnel construction and operation. Especially, the high ground stress phenomenon in the deep-buried tunnel area is common, which has a great impact on the tunnel construction. Based on the on-site measured ground stress data, the analysis of the initial ground stress field by numerical simulation and multiple linear regression is mainly described in this study. Following the comparison and selection of three coefficient estimation methods for the regression equation, the best regression method is selected for inversion and verification. The distribution characteristic of the initial ground stress at different buried depths of the tunnel line is obtained. The inversion results of the initial ground stress in a tunnel area, in China, show that the lateral pressure coefficient gradually decreases with the buried depth increasing, while the overall lateral pressure coefficient is in the range of 1.0–2.0, showing a more significant horizontal tectonic. At the area where the tunnel passes through the fault, a small amount of horizontal tectonic stress is released. The ratio of horizontal principal stress to vertical principal stress is smaller than that on both sides, which is different from the distribution characteristic of lateral pressure coefficient without the impact of fault. It shows that faults have a great influence on ground stress. The lateral pressure coefficient in the area near the fault must be determined according to the on-site measured results.
A Double-Side Feedback Pulse Train Control for the Output Voltage Regulation of Two-Stage Wireless Power Transfer System
Authors: Lei Juan , Junaid Muhammad , Yu Dongsheng , Hua Zhuo , Yu Samson
Published: September 2022

Pulse Train (PT) control is a nonlinear voltage regulation method with favorable characteristics of quick response time and simple structure. In this paper, a PT-based feedback control strategy is proposed for stabilizing the output voltage of two-stage wireless power transfer (WPT) systems. Low-frequency voltage oscillations can be observed in PT controlled front-stage power converters, which significantly degrades the output power quality of the WPT system. To solve this problem, by using feedback variables sampled from both output sides of a power converter and WPT, a capacitor current and output voltage feedback PT (CC&OV-PT) controlled two-stage WPT system is further devised in this paper. A discrete time model of the two-stage WPT system is established, and the performance of low-frequency voltage oscillations suppression for the double-side feedback CC&OV-PT controlled WPT system is analyzed. Simulation and experimental verification have been conducted, both of which show that the CC&OV-PT controlled WPT system achieves fast response with effective low-frequency oscillation suppression.
Special Issue on Metal Additive Manufacturing and Its Applications: From the Material to Components Service Life
Authors: Treutler Kai , Wesling Volker
Published: September 2022

These days, additive manufacturing processes have a large representation in current research and in the field of industrial applications [...]
A Study on the Calibrated Confidence of Text Classification Using a Variational Bayes
Authors: Lee Juhyun , Park Sangsung
Published: September 2022

Recently, predictions based on big data have become more successful. In fact, research using images or text can make a long-imagined future come true. However, the data often contain a lot of noise, or the model does not account for the data, which increases uncertainty. Moreover, the gap between accuracy and likelihood is widening in modern predictive models. This gap may increase the uncertainty of predictions. In particular, applications such as self-driving cars and healthcare have problems that can be directly threatened by these uncertainties. Previous studies have proposed methods for reducing uncertainty in applications using images or signals. However, although studies that use natural language processing are being actively conducted, there remains insufficient discussion about uncertainty in text classification. Therefore, we propose a method that uses Variational Bayes to reduce the difference between accuracy and likelihood in text classification. This paper conducts an experiment using patent data in the field of technology management to confirm the proposed method’s practical applicability. As a result of the experiment, the calibrated confidence in the model was very small, from a minimum of 0.02 to a maximum of 0.04. Furthermore, through statistical tests, we proved that the proposed method within the significance level of 0.05 was more effective at calibrating the confidence than before.
Simulation of Intellectual Property Management on Evolution Driving of Regional Economic Growth
Authors: Yang Xiran , Qi Yong
Published: September 2022

The input, application, and transformation of intellectual property can significantly promote the economic development of a region, but the path and operation mechanism of intellectual property management on regional economic growth are not very clear. System dynamics theory was used to analyze the driving force and resistance of intellectual property management from macro to micro. With the help of system dynamics theory, equations were constructed to simulate the process path and force from intellectual property management to regional economic growth, and sensitivity analysis was used to find sensitive influencing factors in the system. The following conclusions were drawn: (1) intellectual property affects regional economic growth from the macro level, such as intellectual property investment, policies, and the construction of rules and regulations; (2) enterprises, whether in the industry, universities and research institutes, or in this system, are the main body to create innovative benefits and ultimately promote regional economic growth; (3) the continuous investment of intellectual property resources and the driving force of enterprise innovation are all sensitive factors of this system. The government should give full play to its functions and strengthen the management of intellectual property in order to enable the regional economy to obtain high quality development. Through the study of the cooperation between the subjects in the process of intellectual property management activities, the integration and allocation process of factors and resources has been researched, and revealing the action process and dynamic change process of technological innovation activities on economic growth also have been revealed.
Propagation Characteristics of Fractures Induced by Supercritical Carbon Dioxide Jet in Hard and Soft Layered Rocks
Authors: Liu Feng , Hu Yi , Liu Jiawei
Published: September 2022

The initiation and propagation behavior of fractures induced by supercritical carbon dioxide (SC-CO2) jet fracturing is significant to evaluate stimulated reservoir volume (SRV). However, the propagation characteristics of fractures induced by SC-CO2 jet in layered rocks with layers having different mechanical properties have not yet been studied. In this study, four groups of artificial sandstones were used to conduct SC-CO2 jet fracturing experiments and investigate the fracture initiation and propagation behavior in hard and soft layered rocks. A strain collection device was employed to monitor the strain changes of the specimens during the experiments, and after the experiments, a three-dimensional scanner was used to obtain the morphologies of the main fractures. Experimental results showed that the SC-CO2 jet fracturing can be divided into the pressurization of the perforation pressure stage and fracture propagation stage, and the fractures initiation and propagation is intermittent. Three types of main fractures have been found—longitudinal fracture, transverse fracture and oblique fracture—and the formation mechanism of the main fractures has been elaborated. The rock strength can affect the number and complexity of fractures created and the fracturing rate, and the Young’s modulus of rock has an effect on fracture propagation length. The fractures mainly develop near the perforation and are difficult to propagate to another layer with different mechanical properties. The result in our study is conducive to the application of SC-CO2 jet fracturing technology in the field.
Kinematic Analysis for Repetitive Peripheral Magnetic Stimulation of the Intrinsic Muscles of the Hand
Authors: Fujimura Kenta , Kagaya Hitoshi , Tanikawa Hiroki
Published: September 2022

The intrinsic muscles of the hand are responsible for finger flexion and extension. The purpose of this study was to investigate the usefulness of stimulating the intrinsic muscles of the hand using repetitive peripheral magnetic stimulation (rPMS). We evaluated angular changes in the finger joints by studying active motion and rPMS. Ten healthy adults were instructed to perform the following tests in random order: (1) maximum active metacarpophalangeal joint flexion; (2) maximum active metacarpophalangeal joint abduction; and (3) repetitive peripheral magnetic stimulation for 2 s at maximum stimulation intensity. A three-dimensional motion analysis system was used to measure angular changes. Pain during stimulation was graded on a numerical rating scale (NRS). The maximum flexion and abduction of the metacarpophalangeal joint were not significantly different between active motion and rPMS. The proximal interphalangeal joint (p = 0.009) and distal interphalangeal joint (p = 0.005) were significantly extended by rPMS. The median NRS score for pain during rPMS was 2. rPMS can produce the same extent of metacarpophalangeal joint flexion and abduction as active movement with less pain. This technique can effectively stimulate the intrinsic muscles of the hand and may be used as a treatment for various diseases that cause immobility of the metacarpophalangeal joints.
Calculating Bias-Free Volumetric Fracture Counts (VFCs) in Underground Works and Their Use in Estimating Rock Mass Strength and Deformability Parameters
Authors: Schlotfeldt Paul , Nikl Jacob , Sutton Jonathon
Published: September 2022

This paper initially provides a practical example on how to estimate a bias-free volumetric fracture count (VFC—fractures/m3) in a tunnel and incorporate it into a new and unified volumetric-based Geological Strength Index (V-GSI) chart. The quantified V-GSI chart and the methods shown in the practical example were used extensively as tools to assess rock mass conditions and assist in support determinations on the WestConnex M8 Motorway tunnel project in Sydney, Australia. The reliability of the strength and deformability estimates obtained using the V-GSI ratings while tunneling within the Hawkesbury Sandstone is demonstrated here by providing an example of deformation results obtained through 3-D finite element analysis in a single location in the tunnel. The modelling results are compared to measure convergence in the tunnel in this location, which demonstrated good correlation between predicted and observed deformation. This provides validation that the V-GSI chart and associated Hoek–Brown strength and deformability equations can be used with some confidence to determine potential deformation in underground works.
Solid-State Rotary Friction-Welded Tungsten and Mild Steel Joints
Authors: Skowrońska Beata , Bober Mariusz , Kołodziejczak Paweł , Baranowski Michał , Kozłowski Mirosław , Chmielewski Tomasz
Published: September 2022

This paper is a study of the microstructure and other selected properties of solid-state, high-speed, rotary friction-welded tungsten and mild steel (S355) joints. Due to the high affinity of tungsten for oxygen, the welding process was carried out in a chamber with an argon protective atmosphere. Joints of suitable quality were obtained without any macroscopic defects and discontinuities. Scanning electron microscopy (SEM) was used to investigate the phase transformations taking place during the friction welding process. Chemical compositions in the interfaces of the welded joints were determined by using energy dispersive spectroscopy (EDS). The microstructure of friction welds consisted of a few zones, fine equiaxed grains (formed due to dynamic recrystallization) and ultrafine grains in the region on the steel side. A plastic deformation in the direction of the flash was visible mainly on the steel side. EDS-SEM scan line analyses across the interface did not confirm the diffusion of tungsten to iron. The nature of the friction welding dissimilar joint is non-equilibrium based on deep plastic deformation without visible diffusive processes in the interface zone. The absence of intermetallic phases was found in the weld interface during SEM observations. Mechanical properties of the friction-welded joint were defined using the Vickers hardness test and the instrumented indentation test (IIT). The results are presented in the form of a distribution in the longitudinal plane of the welded joint. The fracture during strength tests occurred mainly through the cleavage planes at the interface of the tungsten grain close to the friction surface.
A Novel Hybrid Method for Short-Term Wind Speed Prediction Based on Wind Probability Distribution Function and Machine Learning Models
Authors: Dhakal Rabin , Sedai Ashish , Pol Suhas , Parameswaran Siva , Nejat Ali , Moussa Hanna
Published: September 2022

The need to deliver accurate predictions of renewable energy generation has long been recognized by stakeholders in the field and has propelled recent improvements in more precise wind speed prediction (WSP) methods. Models such as Weibull-probability-density-based WSP (WEB), Rayleigh-probability-density-based WSP (RYM), autoregressive integrated moving average (ARIMA), Kalman filter and support vector machines (SVR), artificial neural network (ANN), and hybrid models have been used for accurate prediction of wind speed with various forecast horizons. This study intends to incorporate all these methods to achieve a higher WSP accuracy as, thus far, hybrid wind speed predictions are mainly made by using multivariate time series data. To do so, an error correction algorithm for the probability-density-based wind speed prediction model is introduced. Moreover, a comparative analysis of the performance of each method for accurately predicting wind speed for each time step of short-term forecast horizons is performed. All the models studied are used to form the prediction model by optimizing the weight function for each time step of a forecast horizon for each model that contributed to forming the proposed hybrid prediction model. The National Oceanic and Atmospheric Administration (NOAA) and System Advisory Module (SAM) databases were used to demonstrate the accuracy of the proposed models and conduct a comparative analysis. The results of the study show the significant improvement on the performance of wind speed prediction models through the development of a proposed hybrid prediction model.
Occlusal Plane Changes after Maxillary Molar Distalization Using Temporary Skeletal Anchorages Devices: A Narrative Review and Preliminary Study
Authors: Park Jung Jin , Kim Kyung-A , Park Hai-Ji , Kang Yoon-Goo
Published: September 2022

Background: We conducted a narrative review of studies analyzing the occlusal and mandibular plane angles after maxillary molar distalization using temporary skeletal anchorage devices (TADs). An original preliminary investigation was conducted on the occlusal and mandibular plane angle changes according to the design of TAD-supported distalization. Methods: We included 51 participants stratified into three groups (buccal TAD, lingual arch TAD, and pendulum TAD) who underwent lateral cephalography before and after treatment. The paired t-test and ANOVA were used to analyze the significant differences among the groups. Results: The pterygoid vertical to maxillary second molar (p < 0.01) significantly differed before and after treatment within each group (group 1, 1.29 ± 1.73 mm; group 2, 2.01 ± 1.46 mm; group 3, 1.12 ± 1.43 mm). The angle between the Frankfort horizontal and anatomical occlusal plane increased by 1.96 ± 2.88° (p < 0.05) and 2.51 ± 2.57° (p < 0.01) in groups 2 and 3, respectively. Conclusions: The measured variables did not significantly differ among the three groups. The Frankfort-mandibular plane angle and functional occlusal plane did not change after maxillary molar distalization. The anatomical occlusal plane is influenced by the anterior teeth and may be unrelated to maxillary molar distalization. Further studies are required to verify the exact relationship between maxillary molar distalization and occlusal plane angle.
Tyrosine, Phenylalanine, and Tryptophan Undergo Self-Aggregation in Similar and Different Manners
Authors: Uyaver Sahin
Published: September 2022

Phenylalanine, tyrosine, and tryptophan are aromatic amino acids, and they are of high interest in both health science and biotechnology. These amino acids form organized structures, like fibrils and nanotubes. Although these amino acids belong to the same family, they still differ from each other with respect to polarity, hydrophobicity as well as internal structures. In this work, we performed extensive molecular dynamics simulations to investigate the dynamics of the self-aggregations of these amino acids and studied the details of the formed structures. The amino acid monomers placed in water were simulated at a constant temperature. It has been observed that they compose nanostructures with similarities and differences.
Battery Lifespan of an Implantable Middle Ear Device
Authors: Bruschini Luca , Forli Francesca , Fiacchini Giacomo , Canelli Rachele , Berrettini Stefano , Lazzerini Francesco
Published: September 2022

Background: The Carina system (Cochlear Ltd., Sydney, Australia) is a totally implantable device providing acoustic amplification in adult patients with moderate-to-severe sensorineural or mixed hearing loss. One of the main concerns about such a totally implantable device has been represented by the subcutaneous battery lifespan. The aim of this article is to report the analysis of battery performances in a series of Carina-implanted patients after a long follow up. Methods: In this retrospective study, the technical data of a series of patients implanted with the Carina middle ear implant in our clinic have been analysed, extracting the data from the log of telemetric measures. Results: The mean lifespan cutback was 0.43 h/years (from 0 to 0.71 h/year), with a strong negative significant correlation between the follow-up period and the percentage of battery residual lifespan. Conclusion: The lifespan of the Carina’s battery seems consistent with the manufacturer statement of a pluri-decennial lifespan, avoiding the need of an early surgical substitution and providing a full day of use of the system even after up to 12 years from the implantation.
Selection of Appropriate Symbolic Regression Models Using Statistical and Dynamic System Criteria: Example of Waste Gasification
Authors: Praks Pavel , Lampart Marek , Praksová Renáta , Brkić Dejan , Kozubek Tomáš , Najser Jan
Published: September 2022

In this paper, we analyze the interpretable models from real gasification datasets of the project “Centre for Energy and Environmental Technologies” (CEET) discovered by symbolic regression. To evaluate CEET models based on input data, two different statistical metrics to quantify their accuracy are usually used: Mean Square Error (MSE) and the Pearson Correlation Coefficient (PCC). However, if the testing points and the points used to construct the models are not chosen randomly from the continuum of the input variable, but instead from the limited number of discrete input points, the behavior of the model between such points very possibly will not fit well the physical essence of the modelled phenomenon. For example, the developed model can have unexpected oscillatory tendencies between the used points, while the usually used statistical metrics cannot detect these anomalies. However, using dynamic system criteria in addition to statistical metrics, such suspicious models that do fit well-expected behavior can be automatically detected and abandoned. This communication will show the universal method based on dynamic system criteria which can detect suitable models among all those which have good properties following statistical metrics. The dynamic system criteria measure the complexity of the candidate models using approximate and sample entropy. The examples are given for waste gasification where the output data (percentage of each particular gas in the produced mixture) is given only for six values of the input data (temperature in the chamber in which the process takes place). In such cases instead, to produce expected simple spline-like curves, artificial intelligence tools can produce inappropriate oscillatory curves with sharp picks due to the known tendency of symbolic regression to produce overfitted and relatively more complex models if the nature of the physical model is simple.
Drug Efflux Pump Inhibitors: A Promising Approach to Counter Multidrug Resistance in Gram-Negative Pathogens by Targeting AcrB Protein from AcrAB-TolC Multidrug Efflux Pump from Escherichia coli
Authors: Alenazy Rawaf
Published: September 2022

Infections caused by multidrug resistance (MDR) of Gram-negative bacteria have become one of the most severe public health problems worldwide. The main mechanism that confers MDR to bacteria is drug efflux pumps, as they expel a wide range of compounds, especially antibiotics. Among the different types of drug efflux pumps, the resistance nodulation division (RND) superfamily confers MDR to various Gram-negative bacteria species. The AcrAB-TolC multidrug efflux pump, from E. coli, a member of RND, is the best-characterized example and an excellent model for understanding MDR because of an abundance of functional and structural data. Small molecule inhibitors that target the AcrAB-TolC drug efflux pump represent a new solution to reversing MDR in Gram-negative bacteria and restoring the efficacy of various used drugs that are clinically relevant to these pathogens, especially in the high shortage of drugs for multidrug-resistant Gram-negative bacteria. This review will investigate solutions of MDR in Gram-negative bacteria by studying the inhibition of the AcrAB-TolC multidrug efflux pump.
Galectins: Their Network and Roles in Infection/Immunity/Tumor Growth Control 2021
Authors: Hattori Toshio
Published: September 2022

Galectins constitute a protein family of soluble and non-glycosylated animal lectins that show a β-galactoside-binding activity via a conserved sequence of approximately 130–140 amino acids located in the carbohydrate recognition domain (CRD) [...]