bluuebunny/crossref_metadata_2025 huggingface dataset:
Neuroinflammation and the immune system in hypoxic ischaemic brain injury pathophysiology after cardiac arrest
Authors: Sekhon Mypinder S. , Stukas Sophie , Hirsch‐Reinshagen Veronica , Thiara Sonny , Schoenthal Tison , Tymko Michael , McNagny Kelly M. , Wellington Cheryl , Hoiland Ryan
Published: August 2023

Hypoxic ischaemic brain injury after resuscitation from cardiac arrest is associated with dismal clinical outcomes. To date, most clinical interventions have been geared towards the restoration of cerebral oxygen delivery after resuscitation; however, outcomes in clinical trials are disappointing. Therefore, alternative disease mechanism(s) are likely to be at play, of which the response of the innate immune system to sterile injured tissue in vivo after reperfusion has garnered significant interest. The innate immune system is composed of three pillars: (i) cytokines and signalling molecules; (ii) leucocyte migration and activation; and (iii) the complement cascade. In animal models of hypoxic ischaemic brain injury, pro‐inflammatory cytokines are central to propagation of the response of the innate immune system to cerebral ischaemia–reperfusion. In particular, interleukin‐1 beta and downstream signalling can result in direct neural injury that culminates in cell death, termed pyroptosis. Leucocyte chemotaxis and activation are central to the in vivo response to cerebral ischaemia–reperfusion. Both parenchymal microglial activation and possible infiltration of peripherally circulating monocytes might account for exacerbation of an immunopathological response in humans. Finally, activation of the complement cascade intersects with multiple aspects of the innate immune response by facilitating leucocyte activation, further cytokine release and endothelial activation. To date, large studies of immunomodulatory therapies have not been conducted; however, lessons learned from historical studies using therapeutic hypothermia in humans suggest that quelling an immunopathological response might be efficacious. Future work should delineate the precise pathways involved in vivo in humans to target specific signalling molecules.

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The Momentum Battle in an Upper Airway During High Flow Nasal Cannula Oxygen Therapy
Authors: Kacinski Robert , Strasser Wayne , Leonard Scott
Published: August 2023

Two types of high flow nasal cannula (HFNC) oxygen therapy were tested using computational models of the human upper airway to investigate cannula geometry's effect on CO2 flush. Models were run with a generic HFNC geometry, two High Velocity Nasal Insufflation (HVNI) cannula geometries, and without any cannula, each for open and closed mouth patient scenarios. For the open mouth scenario, models included either an inflamed left nasal passageway or a healthy (uninflamed) left nasal passageway. With a healthy left nasal passageway and open mouth, the CO2 remaining in the airway at end-exhale was 1.88 mg and 1.84 mg for the HVNI cannulas, 2.56 mg for HFNC, and 10.0 mg for the model with no cannula. With an inflamed left nasal passageway and open mouth, the CO2 remaining was 1.97 mg, 1.95 mg, 4.24 mg, and 10.5 mg for the same sequence of therapy types. For the closed mouth models, the distinction between therapy types was negligible. It was found that the higher momentum from the HVNI cannulas created a higher resistance against the infiltration of exhaled CO2 into the upper airway. The HVNI cannulas also began flushing the airway (reducing total CO2 mass) earlier in the exhalation cycle than both the HFNC and no-cannula models. The higher resistance to expiratory flow entering the upper airway and earlier transition to flush led to HVNI therapy having the lowest values of CO2 remaining in the airway.
A Comparative Study of LSTM and Temporal Convolutional Network Models for Semisubmersible Platform Wave Runup Prediction
Authors: Li Yan , Xiao Longfei , Wei Handi , Li Deyu , Li Xu
Published: August 2023

Wave runup prediction is necessary for offshore structure designs and early warnings. Data-driven methods based on machine learning have inspired reduced-order solutions for wave–structure interaction problems. This study provides the quantification of deep learning algorithms’ potential for wave runup prediction. Two prominent deep learning models were utilized to predict the wave runups along the fore column of semisubmersible under head seas. The long short-term memory (LSTM) and the temporal convolutional networks (TCNs) were comprehensively compared based on the datasets from a model test carried out in the deep ocean basin. The LSTM and TCN model structures were optimized to compare prediction accuracy and computational complexity reasonably. The results reveal that (1) both developed TCN and LSTM models had a satisfied prediction accuracy of over 90%. Their predictions were extended to 10 s into the future with accuracies over 80% and 45%, respectively. (2) With the noise-extended datasets, the LSTM model was robust to noises, while the TCN model showed better prediction performance on the extreme wave runup events. (3) The incident wave and dominant rotation provided the major information for wave runup prediction. TCN and LSTM models’ prediction accuracies were 91.5% and 89.3% based on the simplified input tensors composed of incident wave and pitch. The comparison showed the great potential of the TCN model to predict the nonlinear wave runup with less time and memory costs. The input tensors’ design and optimization based on physical understanding also play a significant role in the prediction performance.
Assessment of Aerobic Fitness Following Anterior Cruciate Ligament Rupture and Reconstruction
Authors: Cordingley Dean M. , McRae Sheila M.B. , Stranges Greg , MacDonald Peter B.
Published: August 2023

Following anterior cruciate ligament rupture, physical activity may be limited due to restrictions placed on the patient while awaiting reconstruction (anterior cruciate ligament reconstruction [ACLr]). The purpose of the study was to evaluate aerobic fitness in individuals undergoing ACLr at the time of medical clearance following injury, 6-month post-ACLr, and 12-month post-ACLr. Seventeen individuals participated in the research study to completion (females, n = 6, age = 23.3 ± 5.5 years; males, n = 11, age = 23.2 ± 4.7 years). There were no changes in aerobic fitness from baseline to 12-month postoperative, but due to the length of time between injury and baseline assessments, it is unknown if aerobic deconditioning occurred before the patient was assessed preoperatively.
The Effects of Stroboscopic Training in Athletes With Chronic Ankle Instability
Authors: Uzlaşır Serkan , Harput Gülcan , Dağ Osman , Tunay Volga B.
Published: August 2023

This study aimed to determine the effects of a 6-week stroboscopic balance training program on balance scores in athletes with chronic ankle instability. Balance was evaluated before and after the 6-week balance training program. After the program, there were no differences between the strobe and nonstrobe groups in static balance. In terms of dynamic balance, the strobe group showed a significant increase in limits of stability between pretest and posttest and terms of dynamic balance, the strobe group showed a significant increase in limits of stability between pretest and posttest and had significantly greater limits of stability than the nonstrobe group at posttest. Stroboscopic balance training may be useful in improving dynamic balance in athletes with chronic ankle instability.
The Relationship Between Isometric Hip Strength and Incidence of Noncontact Anterior Cruciate Ligament Injuries in Female Athletes: A Critically Appraised Topic
Authors: Lee Cayla A. , Jacobs Jessica L. , Volberding Jennifer L.
Published: August 2023

Clinical Scenario: Noncontact anterior cruciate ligament (ACL) injuries are prevalent among athletes in multiplanar sports, especially females. Hip strength may contribute to the incidence of these injuries due to dynamic movement patterns at the knee. Clinical Question: Does hip strength impact the incidence of noncontact ACL injuries in female athletes? Summary of Key Findings: A literature search was conducted on the relationship between hip strength and noncontact ACLs. Three prospective studies measuring isometric hip strength and recording the number of noncontact ACL injuries that occurred within a time period were included. One study demonstrated lower isometric hip adductor-to-abductor ratio was associated with noncontact ACL injuries. Two studies demonstrated those with noncontact ACL injuries had greater isometric hip abduction strength. Clinical Bottom Line: Evidence suggests that greater isometric hip strength and low hip adductor-to-abductor strength ratio may be a risk factor that is associated with noncontact ACL injuries in females. Future research should investigate the impact of hip strength on the incidence of noncontact ACL injuries, across all genders. Strength of Recommendation: Based on the Center of Evidence-Based Medicine, these studies provide Level 3 evidence that hip strength is associated with the risk of noncontact ACL injuries in females.
Dissemination of the
Acinetobacter baumannii
isolates belonging to global clone 2 containing AbGRI resistance islands in a referral hospital
Authors: Naderi Ghazal , Asadian Mahla , Seifi Arash , Ghourchian Sedigheh , Talebi Malihe , Rahbar Mohammad , Abdollahi Alireza , Douraghi Masoumeh
Published: August 2023

Acinetobacter baumannii
strains belonging to global clone 2 (GC2) contain resistance islands (AbGRIs), which are composed of genes conferring resistance to older and newer antibiotics. Here, to locate these genes in AbGRIs, the GC2 strains from Tehran, Iran were examined. Among the 170
A
.
baumannii
, 90 isolates were identified as GC2. Of the genes that confer resistance to older antibiotics,
tetA(B
),
tetR(B)
(tetracyclines),
strA
, and
strB
(aminoglycosides) were located in AbGRI1 of 65 GC2 isolates (72.2%). Of the other aminoglycosides, the
aphA1b
was located in AbGRI2-12b (63.6%), AbGRI2-12a (21.2%), or AbGRI2-1 (15.1%). The
aacC1
and
aadA1
genes were co-located within AbGRI2-1 (5.5%). The
armA
was located in AbGRI3-4 (77.7%) and AbGRI3
ABI221
(22.2%). Of sulfonamides, the
sul1
was located within AbGRI2-1 (5.5%). Of beta-lactams, the

bla
TEM

was located in AbGRI2-12b (42%), AbGRI2-12a (14%), AbGRI2-1 (10%), or AbGRI2
ABI257
(34%). The
oxa23
gene conferring resistance to newer antibiotics (carbapenems) was located in AbaR4 (81.1%); of them, the AbaR4 was located within AbGRI1 in 45.2% of the isolates. This study showed that the GC2 isolates, which contained at least one AbGRI, disseminate in the hospital. Hence, it is likely that the AbGRIs play a significant role in conferring resistance to older and newer antibiotics in GC2 isolates from Iran.

IMPORTANCE

The majority of
Acinetobacter baumannii
isolates that are resistant to multiple antibiotics belong to one of the two major global clones, namely global clone 1 (GC1) and global clone 2 (GC2). The resistance islands, which contain variable assortments of transposons, integrons, and specific resistance genes, have been characterized in the genome of these GCs. In GC2
A. baumannii,
the chromosomally located
A. baumannii
genomic resistance islands (AbGRIs) carry the genes conferring resistance to older and newer antibiotics. In this context, we tested whether GC2 isolates collected from a referral hospital carry the AbGRIs containing these genes. This study provided evidence for the circulation of the GC2
A. baumannii
strains harboring AbGRI resistance islands between different wards of a referral hospital.
Sustainability of performance improvements after 26 Kaizen events in a large academic hospital system: a mixed methods study
Authors: Haapatalo Erik , Reponen Elina , Torkki Paulus
Published: August 2023

Introduction

Implementing Kaizen can improve productivity in healthcare but maintaining long-term results has proven challenging. This study aimed to assess improved performance achieved and sustained by Kaizen events and find explanatory factors for the persistence or decline of long-term results.

Methods

Kaizen events were conducted in 26 specialised healthcare units in a large academic hospital system in southern Finland. Primary data for mixed methods analysis was collected from each unit with 21 semi-structured interviews, Kaizen report files and performance metrics.

Results

Fifteen explanatory factors were found in this study. Work culture and motivation for continuous improvement stood out as the most important explanatory factor for the persistence of long-term results—lack of time for improvement activities and high workload for the decline. Success in preparation and follow-up was associated with sustained long-term results. Thirteen units achieved long-term results, three units could not sustain the performance improvements and five units struggled to make any improvements.

Conclusions

This study explains the long-term sustainability of performance improvements, bringing new insights to Kaizen research. Our findings can guide organising successful Kaizen events. The events can be worth organising even though long-term performance improvements are not guaranteed. Units with supportive working culture and motivation for the Kaizen event will likely succeed. A unit should aim to create a supportive foundation for Kaizen before organising a Kaizen event. Units that lack the foundation can be identified, trained and guided to increase their chances of success. Pitfalls like high workload and insufficient follow-up should be proactively identified and appropriately managed by allocating the required time and resources for the development work.
Stress and safety of maternal and newborn healthcare workers early in the COVID-19 pandemic: a repeat cross-sectional analysis from a global online survey from March 2020 to March 2021
Authors: Ezema Ashley , Caputo Matthew , Semaan Aline , Benova Lenka , Liang Shu-ting , Hirschhorn Lisa R
Published: August 2023

Objectives

This study aims to characterise the physical and psychological well-being of maternal and newborn healthcare workers (MNHCWs) during the COVID-19 pandemic.

Design

Observational repeated cross-sectional study.

Setting

An online questionnaire was distributed to MNHCWs around the globe in three separate rounds from March 2020 to March 2021.

Participants

Total samples of N=1357 (round 1) and N=420 (round 3) primarily consisted of doctors, midwives and nurses in maternal and newborn specialties. Samples represented all WHO regions, with 33% (round 1) and 42% (round 3) from low- or middle-income countries (LMICs).

Primary and secondary outcome measures

Responses from rounds 1 (March–June 2020) and 3 (December 2020–March 2021) were analysed to measure self-reported levels of relative stress and workplace protection from COVID-19, while associated factors were determined through multivariable ordinal logistic regression.

Results

In round 1, 90% of MNHCWs reported increased stress levels and 45% reported insufficient personal protective equipment (PPE) access. Nurses and physicians were less likely to report increased stress than midwives at the pandemic onset. Factors associated with increased stress included being female, being from an LMIC and insufficient PPE. In round 3, 75% reported similar or increased stress while 10% reported insufficient PPE. In both rounds, over 50% of MNHCWs felt relatively or completely unprotected from COVID-19 in the workplace. Those from LMICs were more likely to report feeling unprotected, while receiving organisational information that valued safety was associated with better feelings of protection in the workplace.

Conclusions

Among our international sample of MNHCWs, we observed high rates of self-reported stress increase at the start of the pandemic with persistence or increase up to a year later. High rates of feeling unprotected persisted even as PPE became more available. These results may inform interventions needed to support and protect MNHCWs during this and future pandemics.
Maternal and neonatal antibody levels on pertussis vaccination in pregnant women on immune-modulating therapy for rheumatic disease
Authors: Ghalandari Nafise , Immink Maarten M , Röder Esther , Bruijning-Verhagen Patricia C J , Smeele Hieronymus , Crijns Hubertina , van der Maas Nicoline A T , Bekker Mireille N , Sanders Elisabeth A M , Dolhain Radboud J E M
Published: August 2023

Objectives

While protection against pertussis following maternal tetanus-diphtheria-and-acellular-pertussis (Tdap) vaccination was demonstrated in healthy term-born infants, no evidence is available on Tdap vaccination in combination with immune-modulating therapy during pregnancy. In this pilot study, we explored whether treatment with tumour necrosis factor alpha inhibitors (TNFis) in pregnant patients with rheumatic disease interferes with Tdap vaccine responses and affects maternal anti-pertussis IgG antibody levels in newborns.

Methods

Patients were included by a rheumatologist during pregnancy in case they received maternal Tdap vaccination in the late-second or early-third trimester of pregnancy. Blood samples were obtained from mothers during the first pregnancy trimester, 3 months after delivery and from the umbilical cord. IgG antibody levels against Tdap-included antigens were measured using a bead-based multiplex immunoassay. Findings on patients exposed to TNFis were compared with those from TNFi-unexposed patients and with data from a historical comparator study among healthy Tdap vaccinated mother–infant pairs (n=53).

Results

66 patients (46 exposed and 20 unexposed to TNFIs) were enrolled. No major differences in IgG antibody levels were observed between TNFi-exposed and unexposed mothers before maternal Tdap vaccination and 3 months after delivery. In cord sera, however, antibody levels against pertussis toxin were significantly lower after TNFi-treatment (35.94 IU/mL, 95% CI 20.68 to 62.45) compared with no TNFi-treatment of mothers with rheumatic disease (94.61 IU/mL, 95% CI 48.89 to 183.07) and lower compared with a cohort of healthy mothers (125.12 IU/mL, 95% CI 90.75 to 172.50). We observed similar differences for filamentous haemagglutinin, pertactin, tetanus toxoid and diphtheria toxoid.

Conclusion

These preliminary data indicate no major differences in IgG antibody levels on maternal Tdap vaccination in pregnant women with or without immune-modulating treatment, although our findings suggest that TNFis during pregnancy induce lower maternal anti-pertussis-specific protective antibody levels in newborns.
Palliative care delivery in India during COVID-19 pandemic: role of faith-based hospitals – a qualitative study
Authors: Sundararaj Jenifer Jeba , Singh Ashita , Priscilla Ruby Angeline , John Priya , Duomai Savita , Munday Daniel , Powys Ruth , Boyd Kirsty J , Grant Liz , Murray Scott A
Published: August 2023

Objectives

The COVID-19 pandemic challenged palliative care (PC) services globally. We studied the ways healthcare professionals (HCPs) working in faith-based hospitals (FBHs) experienced and adapted care through the pandemic, and how this impacted patients with PC needs.

Methods

In-depth interviews were conducted with HCPs from FBHs serving rural and urban population across India. Thematic analysis was conducted.

Results

A total of 10 in-depth interviews were conducted during the COVID-19 pandemic, first wave (4), second wave (4) and between them (2). HCPs described fear and stigma in the community early in the pandemic. Migrant workers struggled, many local health services closed and cancer care was severely affected. Access and availability of healthcare services was better during the second wave. During both waves, FBHs provided care for non-COVID patients, earning community appreciation. For HCPs, the first wave entailed preparation and training; the second wave was frightening with scarcity of hospital beds, oxygen and many deaths. Eight of the 10 FBHs provided COVID-19 care. PC teams adapted services providing teleconsultations, triaging home visits, delivering medications, food at home, doing online teaching for adolescents, raising funds. Strengths of FBHs were dedicated teamwork, staff care, quick response and adaptations to community needs, building on established community relationship.

Conclusion

FBHs remained open and continued providing consistent, good quality, person-centred care during the pandemic. Challenges were overcome innovatively using novel approaches, often achieving good outcomes despite limited resources. By defining and redefining quality using a PC lens, FBHs strengthened patient care services.
Multi-View Graph Contrastive Learning via Adaptive Channel Optimization for Depression Detection in EEG Signals
Authors: Zhang Shuangyong , Wang Hong , Zheng Zixi , Liu Tianyu , Li Weixin , Zhang Zishan , Sun Yanshen
Published: August 2023

Automated detection of depression using Electroencephalogram (EEG) signals has become a promising application in advanced bioinformatics technology. Although current methods have achieved high detection performance, several challenges still need to be addressed: (1) Previous studies do not consider data redundancy when modeling multi-channel EEG signals, resulting in some unrecognized noise channels remaining. (2) Most works focus on the functional connection of EEG signals, ignoring their spatial proximity. The spatial topological structure of EEG signals has not been fully utilized to capture more fine-grained features. (3) Prior depression detection models fail to provide interpretability. To address these challenges, this paper proposes a new model, Multi-view Graph Contrastive Learning via Adaptive Channel Optimization (MGCL-ACO) for depression detection in EEG signals. Specifically, the proposed model first selects the critical channels by maximizing the mutual information between tracks and labels of EEG signals to eliminate data redundancy. Then, the MGCL-ACO model builds two similarity metric views based on functional connectivity and spatial proximity. MGCL-ACO constructs the feature extraction module by graph convolutions and contrastive learning to capture more fine-grained features of different perspectives. Finally, our model provides interpretability by visualizing a brain map related to the significance scores of the selected channels. Extensive experiments have been performed on public datasets, and the results show that our proposed model outperforms the most advanced baselines. Our proposed model not only provides a promising approach for automated depression detection using optimal EEG signals but also has the potential to improve the accuracy and interpretability of depression diagnosis in clinical practice.
Advancing high-speed flow simulations: SAUSM – an innovative hybrid numerical scheme for shock stability and accuracy
Authors: Mohammadi Adnan , Djavareshkian Mohammad Hassan
Published: August 2023

This paper introduces a novel hybrid numerical method, SAUSM, designed for accurate and robust simulation of compressible flows governed by the Euler equations. While the AUSM[Formula: see text] scheme provides proper resolution of smooth flow features, it is susceptible to anomalies, particularly the carbuncle phenomenon near strong shock discontinuities. Conversely, the AUFS scheme offers inherent stability in capturing shocks; however, it lacks the accuracy of AUSM[Formula: see text] in smooth regions. The proposed SAUSM method combines AUSM[Formula: see text] and AUFS through an adaptive weighting function, facilitating a seamless transition between the schemes. This approach preserves the accuracy of AUSM[Formula: see text] in smooth regions while ensuring robust shock-capturing capabilities near discontinuities. The effectiveness of the SAUSM method is rigorously demonstrated through a comprehensive suite of progressively complex test cases. Numerical experiments demonstrate SAUSM’s proficiency in resolving intense shock patterns and discontinuities without introducing anomalies. In the selected test cases, SAUSM agrees with reference solutions and effectively mitigates anomalies observed in AUSM[Formula: see text], including kinked Mach stems. In the challenging test case involving hypersonic blunt body flow over a cylinder, SAUSM adapts dissipation effectively by utilizing its adaptive weighting function to generate smooth pressure distributions, thereby eliminating the carbuncle instability linked to AUSM[Formula: see text] when applied to a high aspect ratio grid. The consistent formulation of flux splitting and the adaptive weighting in SAUSM prevent excessive dissipation away from discontinuities, thus preserving accuracy comparable to that of exact Riemann solvers. Consequently, SAUSM emerges as a promising and innovative approach to accurately and robustly simulate a wide range of compressible Euler flows. The comprehensive results obtained from the validation tests firmly establish SAUSM as a highly effective general-purpose technique for computational fluid dynamics in academic research.
Study on elastic deformation and thermodynamic properties of metals Mg, Zn, Dy, Er and Gd with HCP structure by statistical moment method: Dependences on temperature and pressure
Authors: Quang Hoc Nguyen , Minh Hang Phan , Thi Mai Linh Nguyen , Ngoc Huyen Dao , Trung Thanh Pham , Thi Sao Mai Nguyen , Chi Cong Vu , Thi Mai Van Nguyen
Published: August 2023

This paper presents the elastic deformation and thermodynamic theory for crystals with HCP structure on the basis of the statistical moment method (SMM) together with numerical results and discussions for metals Mg, Zn, Dy, Er and Gd. Some numerical results are compared with experiments and other calculations.
Aerial Gaze Target Recognition Based on Head and Eye Movements
Authors: Wang Yawen , Wang Changyuan , Xue Pengxiang , Zhang Yu , Jiang Guangyi , Yao Yining
Published: August 2023

Aerial gaze target recognition is an important step in aerial eye control interaction. In order to achieve accurate aerial gaze target recognition, the VT4LM recognition algorithm was constructed in this paper. By this algorithm, the facial images containing the eyes of the flight operators were first inputted into Vision Transformer (ViT) to extract the local features, and the head posture of the flight operators was inputted into four LSTMs to extract the global features. Then, the local and global features of the flight operators were inputted into three fully connected layers, two dropout layers and one softmax classifier. Finally, the recognition result of aerial gaze target was obtained. In this paper the effectiveness of the VT4LM recognition algorithm was verified through the identification of four aerial line-of-sight gaze targets named Head-up display, Accelerator push rod, Control lever and Rudder by four flight operators during simulated flight. The experimental results showed that the accuracy of the VT4LM algorithm for aerial gaze target recognition reached 89.29% and the Cross Entropy Loss was 1.45. Compared to the other three recognition methods, the VT4LM algorithm had the highest recognition accuracy and minimum loss. When using the VT4LM algorithm to detect four simulated flight operators staring at four aerial gaze targets, the recognition accuracy was all higher than 85.00%. It could be seen that the VT4LM algorithm had a good performance in aerial gaze target recognition.
Unifying Behavioral and Feature Modeling for Testing of Software Product Lines
Authors: Belli Fevzi , Tuglular Tugkan , Ufuktepe Ekincan
Published: August 2023

Existing software product line (SPL) engineering testing approaches generally provide positive testing that validates the SPL’s functionality. Negative testing is commonly neglected. This research aims to unify behavioral and feature models of an SPL, enable testing before and after variability binding for domain-centric and product-centric testing, and combine positive and negative testing for a holistic testing view. This study suggests behavioral modeling with event sequence graphs (ESGs). This heterogeneous modeling strategy supports bottom-up domain testing and top-down product testing with the feature model. This new feature-oriented ESG test creation method generates shorter test sequences than the original ESG optimum test sequences. Statechart and original ESG test-generating methods are compared. Positive testing findings are similar. The Statechart technique generated 12 test cases with 59 events, whereas the ESG technique created six test cases with 60 events. The ESG technique generated 205 negative test cases with 858 events with the Test Suite Designer tool. However, the Conformiq Designer tool for the Statechart technique does not have a negative test case generation capability. It is shown that the proposed ESG-based holistic approach confirms not only the desirable (positive) properties but also the undesirable (negative) ones. As an additional research, the traditional ESG test-generating approach is compared to the new feature-oriented method on six SPLs of different sizes and features. Our case study results show that the traditional ESG test generation approach demonstrated higher positive test generation scores compare to the proposed feature-oriented test generation approach. However, our proposed feature-oriented test generation approach is capable of generating shorter test sequences, which could be beneficial for reducing the execution time of test cases compared to traditional ESG approach. Finally, our case study has also shown that regardless of the test generation approach, there has been found no significant difference between the Bottom-up and Top-down test strategies with respect to their positive test generation scores.
Formalization and Verification of Enhanced Group Communication CoAP
Authors: Chen Sini , Li Ran , Zhu Huibiao
Published: August 2023

With the flourish of the Internet of Things (IoT), the group communication Constrained Application Protocol (CoAP) emerged at the historic moment, enabling homogeneous devices with constrained computing ability to communicate with ease. CoAP is widely used in transportation, health care and many other aspects. Hence, it is prominent to propose a flexible and efficient architecture for usage in such scenarios and study the data security and consistency of the architecture from the perspective of formal methods. In this paper, we extend the group communication CoAP model to the enhanced group communication CoAP by the introduction of smart gateways and binding to new security suites. We make further improvements to increase the scalability and flexibility of the architecture, making it more applicable in a healthcare scenario or smart home scenario. And we adopt process algebra Communicating Sequential Processes (CSP) with real-time extension to model the enhanced group communication CoAP. We use model checker PAT to verify eight properties of our model on an abstract level, including four basic properties and four security properties. We also conduct a simulation on the local machine for validation of the above properties on a more detailed level. Despite some simplifications of physical properties, both results of the verification and simulation show that the proposed architecture can satisfy those requirements and demonstrate a good possibility of being securely put into service.
Gravity-induced entanglement as a probe of spacetime curvature
Authors: Brahma Suddhasattwa , Seenivasan Abhinove Nagarajan
Published: August 2023

It is now widely believed that if the gravitational field is (perturbatively) quantum, it would entangle two massive objects (in spatial superpositions) which were otherwise unentangled to begin with. Recently, actual table-top experiments have been proposed to test this idea in what would be the first detection of perturbative quantum gravity. In this essay, we devise a thought experiment to prove that such gravity-induced entanglement depends on the spacetime curvature and can, in principle, act as an alternate signature of the expanding background. This will open up new and complementary directions to search for such entanglement in curved spacetime and reveal fresh perspectives on it.
New class of Gibbs measures for two-state hard-core model on a Cayley tree
Authors: Khakimov R. M. , Makhammadaliev M. T. , Haydarov F. H.
Published: August 2023

In this paper, we consider a Hard-Core (HC) model with two spin values on Cayley trees. The conception of alternative Gibbs measure is introduced and translational invariance conditions for alternative Gibbs measures are found. Also, we show that the existence of alternative Gibbs measures which are not translation-invariant. In addition, we study free energy of the model.
Dynamic Behavior and Parameter Characteristics of Buried Pipeline in Airports
Authors: Huang Chongwei , Li Weixiao , Sun Yu
Published: August 2023

Buried pipeline, as one of the crucial facilities of airport ground engineering, has been extensively utilized for the transportation of petroleum, natural gas, industrial wastewater, and more. However, there are significant gaps in the research on the dynamic response of buried pipelines in airports under the action of dynamic traffic loads, which severely hampers the design and engineering quality of oil transmission pipelines. This study builds a three-dimensional finite element model to simulate the action of vehicles on the pipe–soil structure with actual loads. Moreover, the current research establishes a dynamic analysis model of pipe–soil interaction to analyze the material damping and load parameters. Using the structural dynamic response equation and Rayleigh damping calculation theory, this study investigates the change law of pipe dynamic stress and influencing factors and presents the recommended values of the parameters related to the pipe–soil interaction. Results are as follows. A damping ratio of 0.05 can enhance the time lag of the dynamic response of the structure and weaken the response peak. For the Rayleigh damping parameters, the viscous damping coefficient [Formula: see text] has almost no effect on the dynamic response of the pipe–soil structure, so it can be disregarded in the calculation. With the increase of the axial weight of the traffic load above the pavement structure, the peak value of each dynamic response quantity of the pipe–soil structure and load magnitude. The suggested value of the dynamic load coefficient of the pipe–soil structure is 1.5. Lastly, the earth pressure and dynamic load coefficients are suggested to take values for different load and axle type cases.
Weakly-Einstein conditions over four-dimensional homogenous pseudo-Riemannian manifolds
Authors: Atashpeykar Parvane , Haji-Badali Ali , Zaeim Amirhesam
Published: August 2023

A curvature identity is studied through homogenous pseudo-Riemannian four-manifolds with nontrivial isotropy. Then, special classes of the considered spaces i.e. weakly-Einstein examples are completely classified.
f(T) theory solutions for traversable wormhole existence and neutron stars mass limits problems
Authors: Aïnamon C. , Ganiou M. G. , Tefo R. C. , Houndjo M. J. S.
Published: August 2023

In this paper, some Schwarzschild-like solutions in the framework of [Formula: see text] theory where [Formula: see text] means the scalar tensor are reconstructed and analyzed in the context of some open problems like traversable wormholes and neutron starts mass limits. Like some authors, we search for the potentiality of the presence of traversable wormholes in the outer/inner regions halo of galaxies particularly the Milky Way galaxy by considering diagonal tetrads which support the Morris–Thorne metric. In such description where attention is attached to the energy density of dark matter present in the halo of spiral galaxies, a new dark matter density emerges in this work. The reconstructed density profile reveals the existence of traversable wormholes not only in the inner of the Milky Way galaxy but also in the both outer and inner of another galaxy smaller than the Milky Way galaxy. The use of Einasto density profile in this work makes it predict traversable wormholes in both outer and inner of the Milky Way galaxy. In the second part of this work, the non-diagonal tetrads describing the Schwarzschild metric are considered to solve the [Formula: see text] motion equations, where solutions describing neutron stars are provided. Several numerical analyses based on neutron stars mass are done and the obtained results give the best fit with observational data in the framework of neutron stars mass limit.
Compound learning adaptive neural network optimal backstepping control of uncertain fractional-order predator–prey systems
Authors: Liu Heng , Zhong Mei , Cao Jinde , Huang Chengdai
Published: August 2023

Reinforcement learning as an effective strategy is widely utilized in optimal control. However, when updating critic–actor weight vectors based on the square of Bellman residual, it often leads to substantial computational complexity. This paper formulates a compound learning optimal backstepping control programme that can efficaciously reduce the computational burden for fractional-order predator–prey systems (FOPPS) with uncertainties. To economize resource, a reinforcement learning technology is adopted to realize the optimal control in view of neural networks under identifier–critic–actor structure. To address the computational complexity issue raised above, a simple positive definite function is proposed to update critic–actor weight vectors. Fractional-order filters are utilized to estimate virtual signals and their fractional-order derivatives for tackling the “explosion of complexity” problem existing in the conventional backstepping technology. Simultaneously, to enhance the approximation accuracy of uncertainties in FOPPS, a compound learning updating law is built by using tracking error and prediction error. In accordance with the stability analysis, the formulated scheme ensures that the output of FOPPS can track the reference signal with the expected accuracy and all signals are bounded. Eventually, a numerical simulation is presented to validate the effectiveness of the proposed control strategy.
DT-k-group structures on digital objects and an answer to an open problem
Authors: Han Sang-Eon
Published: August 2023

The paper examines various properties of [Formula: see text]-[Formula: see text]-subgroup structures and addresses an open problem on the existence of topological group structures on the [Formula: see text]-dimensional Khalimsky ([Formula: see text]-, for brevity) topological space and Marcus–Wyse ([Formula: see text]-, for short) topological plane. In particular, we obtain many types of totally [Formula: see text]-disconnected or [Formula: see text]-connected subgroups of a [Formula: see text]-connected [Formula: see text]-[Formula: see text]-group. Besides, we prove that each of the [Formula: see text]-dimensional [Formula: see text]-topological space and the [Formula: see text]-topological plane cannot be a typical topological group. Unlike an existence of a [Formula: see text]-[Formula: see text]-group structure of [Formula: see text] (see Proposition 4.7), we prove that neither of [Formula: see text] and [Formula: see text] is a topological group, where [Formula: see text] (respectively, [Formula: see text]) is a simple closed [Formula: see text]- (respectively, [Formula: see text]-) topological curve with [Formula: see text] elements in [Formula: see text] (respectively, [Formula: see text]) and the operation “∗” is a special kind of binary operation for establishing a group structure of each of [Formula: see text] and [Formula: see text]. Finally, given a [Formula: see text]-[Formula: see text]-group structure of [Formula: see text], we find several types of [Formula: see text]-[Formula: see text]-subgroup structures of it (see Theorem 5.7).
Exploring Composite Indexes for Domain Adaptation in Neural Machine Translation
Authors: Minh Nhan Vo , Minh Khue Nguyen Tran , Nguyen Long H. B. , Dinh Dien
Published: August 2023

Domain adaptation in neural machine translation (NMT) tasks often involves working with datasets that have a different distribution from the training data. In such scenarios, k-nearest-neighbor machine translation (kNN-MT) has been shown to be effective in retrieving relevant information from large datastores. However, the high-dimensional context vectors of large neural machine translation model result in high computational costs for distance computation and storage. To address this issue, index optimization techniques have been proposed, including the use of inverted file index (IVF) and product vector quantization (PQ), called IVFPQ. In this paper, we explore the recent index techniques for efficient machine translation domain adaptation and combine multiple index structures to improve the efficiency of nearest-neighbor search in domain adaptation datasets for machine translation task. Specifically, we evaluate the effectiveness when combining optimized product quantization (OPQ) and hierarchical navigable small-world (HNSW) indexing with IVFPQ. Our study aims to provide insights into the most suitable composite index methods for efficient nearest-neighbor search in domain adaptation datasets, with a focus on improving both accuracy and speed.
Breaking Barriers: The Path to Empowering Women Entrepreneurs in Saudi Arabia
Authors: Al-Mamary Yaser Hasan , Abubakar Aliyu Alhaji
Published: August 2023

Due to the important contribution of women to economic development, we propose to investigate the factors that affect women entrepreneurs’ success in Saudi Arabia. 271 women in Saudi Arabia participated in the study. A conceptual model is developed, while PLS-SEM software is used for analysis. The findings show a positive association between women’s empowerment as successful entrepreneurs and certain dimensions of entrepreneurial orientation, including economic factors, autonomy, innovativeness, and proactiveness. These findings shed light on the factors that influence women’s ability to become successful entrepreneurs and identify the dimensions and external factors in the entrepreneurial orientation model that are the best predictors of women’s success. This paper contributes to new knowledge on the conditions of women’s entrepreneurship by developing and validating an analytic model for promoting women’s entrepreneurship Saudi Arabia. From a policy perspective, the model can inform the design of training programs to support women’s entrepreneurship in the country. The study has practical implications and suggests future directions for research in this field[Formula: see text]
A Review of Abstraction Methods Toward Verifying Neural Networks
Authors: Boudardara Fateh , Boussif Abderraouf , Meyer Pierre-Jean , Ghazel Mohamed
Published: August 2023

Neural networks as a machine learning technique are increasingly deployed in various domains. Despite their performance and their continuous improvement, the deployment of neural networks in safety-critical systems, in particular for autonomous mobility, remains restricted. This is mainly due to the lack of (formal) specifications and verification methods and tools that allow for having sufficient confidence in the behavior of the neural-network-based functions. Recent years have seen neural network verification getting more attention; many verification methods were proposed, yet the practical applicability of these methods to real-world neural network models remains limited. The main challenge of neural network verification methods is related to the computational complexity and the large size of neural networks pertaining to complex functions. As a consequence, applying abstraction methods for neural network verification purposes is seen as a promising mean to cope with such issues. The aim of abstraction is to build an
abstract
model by
omitting
some irrelevant details or some details that are not highly impacting w.r.t some considered features. Thus, the verification process is made faster and easier while preserving, to some extent, the relevant behavior regarding the properties to be examined on the original model. In this article, we review both the abstraction techniques for activation functions and model size reduction approaches, with a particular focus on the latter. The review primarily discusses the application of abstraction techniques on feed-forward neural networks and explores the potential for applying abstraction to other types of neural networks. Throughout the article, we present the main idea of each approach and then discuss its respective advantages and limitations in detail. Finally, we provide some insights and guidelines to improve the discussed methods.
Gene Expression Programming for Quantum Computing
Authors: Alvarez Gonzalo , Bennink Ryan , Irle Stephan , Jakowski Jacek
Published: August 2023

We introduce
QuantumGEP
, a scientific computer program that uses gene expression programming (GEP) to find a quantum circuit that either (1) maps a given set of input states to a given set of output states or (2) transforms a fixed initial state to minimize a given physical quantity of the output state.
QuantumGEP
is a driver program that uses
evendim
, a generic computational engine for GEP, both of which are free and open source. We apply
QuantumGEP
as a powerful solver for MaxCut in graphs and for condensed matter quantum many-body Hamiltonians.
Successful Elective Thoracoscopic Resection of Complicate Extralobar Bronchopulmonary Sequestration after Intrafoetal Vascular Laser Ablation: The Paediatric Surgeon’s Point of View
Authors: Fusi Giulia , Sartor Agnès , Groussolles Marion , Joseph Solene , Vial Julie , Roditis Lea , Vayssière Christophe , Abbo Olivier
Published: August 2023

Few reports of laser coagulation for foetal bronchopulmonary sequestration (BPS), a rare congenital malformation characterised by the absence of tracheobronchial connection and the presence of a systemic feeding artery, have been published. Additionally, very few of them focus also on the postnatal management, with results limited and controversial. Postnatal treatment of residual malformation remains debated, hence the need to share our experience of a combined pre- and postnatal approach to complicated extra-lobar BPS. We report the case of a female foetus with the diagnosis of a pulmonary lesion. Due to mediastinal shift, unilateral compressive hydrothorax, ascites, and hydrops, a foetal treatment with ultrasound-guided laser coagulation of the anomalous vessel was performed. At birth, due to the persistence of the malformation, an elective delayed thoracoscopical surgery was performed. Prenatal laser ablation for complicated BPS is a life-saving procedure not always resulting in lesion disappearance. Thoracoscopical surgical exploration in case of persistent lesions at birth offers the possibility of a minimally invasive sequestrectomy feasible and safe.
Analysis of Option Butterfly Portfolio Models Based on Nonparametric Estimation Deep Learning Method
Authors: Ge Xiangyu , Zhu Xia , Bi Gang , Zheng Hao , Li Qing
Published: August 2023

The option butterfly portfolio is the commonly option arbitrage strategy. In reality, because the distribution of the option state price density (SPD) function is not normal and unknown, so the nonparametric deep learning methods to estimate option butterfly portfolio returns are proposed. This paper constructs the single-index nonparametric option pricing model which contains multiple influencing factors and presents the nonparametric estimation form for option butterfly portfolio returns. The empirical analysis shows that the SPD function estimated by using single-index nonparametric option model can effectively calculate the option butterfly portfolio returns with the minimum option strike price interval and provide an effective reference tool for risk-averse investors with limited risk preferences.