bluuebunny/crossref_metadata_2025 huggingface dataset:
Knowledge Creation for Digital Innovation in Malaysia: Practitioners’ Standpoint
Authors: Tung Soon Seng , Dorasamy Magiswary , Ab Razak Ruzanna
Published: September 2022

Background: Malaysia established the National Industry 4.0 strategy (NI4.0) in 2018 to aid the country’s industries in adopting modern technologies to increase productivity and competitiveness. The purpose of NI4.0 is to increase enterprises’ intelligence capabilities as smart manufacturers in the Association of Southeast Asian Nations (ASEAN), who employ data and information across the whole enactment process. As a result, high-technology adoption in NI4.0 is expected to improve knowledge creation (KC) in the Information Technology (IT) business. Recent NI4.0 breakthroughs have permitted new types of borderless projects, thereby, increasing the complexity and unpredictability of IT projects while simultaneously providing a multitude of new knowledge. However, the understanding of contemporary practice difficulties in IT projects and the knowledge creation phenomena is limited. Method: This study is exploratory in nature with a generic qualitative research method. Ten selected key IT project managers were interviewed to understand the current challenges confronting IT projects in Malaysia to build practice-oriented problem statements and to provide relevance leading to a research framework for knowledge creation impacting digital innovation. Interview data were systematically analysed using the NVivo software tool. Results: Practitioners’ reflected that a transactive memory system, IT support and T-shaped skills are current challenges in Malaysian IT projects. This is consistent with the literature. Conclusions: This practice review benefits Malaysia’s public and commercial sectors by confirming that the literature is coherent with practice by providing insights that may warrant further research in this field.
Understanding Social Spaces in Tourist Villages through Space Syntax Analysis: Cases of Villages in Huizhou, China
Authors: Ding Jie , Gao Zhengdong , Ma Shanshan
Published: September 2022

The development of tourism in historical villages has a certain impact on the native environment, which leads to visitors occupying community public spaces relatively frequently. The design of rural public spaces, especially in relation to the street network’s spatial configuration, significantly affects how villagers interact with one another. This research investigated the influence of street network space on the regional social interaction preferences of rural community populations by applying space syntax theory. Three typical villages in southern Anhui, China, were the subject of an observation analysis of social behaviors and pedestrian volumes on street networks. Using a segment model, it was possible to determine seven spatial configuration attributes of streets, including depth to the village entrance (DtoE), connectivity, curvature, the normalized angle choice (NACH) and integration (NAIN) with two radii. A considerable joint effect of street spatial type and spatial layout attributes on the regional social interaction preferences of rural community populations was found by MANOVA and stepwise regression analysis. The sampled community tends to engage in social activities in branch streets, and the pedestrian volume contained 67.1% of all the observed people in the street networks. Streets’ spatial attributes with lower NACH or NAIN levels (less usability or accessibility) and higher DtoE or curvature levels (more privacy or deformation) have greater influences on community pedestrian volumes. Regarding street type, the in-between space was found to have the most significant effect on the pedestrian volume of the branch streets, which are the preferred zones of community populations in the context of social activities.
Elements of Divergence in Urbanization between Central and Eastern Europe (CEE) and the Core of the Continent
Authors: Faragó Péter , Gálos Krisztina , Fekete Dávid
Published: September 2022

There is an ongoing debate regarding whether the EU-10 converges at the core of Europe or not. Although the evidence supports both perspectives, the gap in urbanization is undeniable. In this explorative study, two economic processes contributing to this disparity—foreign direct investment and migration—were analyzed and contextualized with respect to urbanization using grounded theory. It was concluded that there is slight convergence in the frontier, usually in urbanized areas of Central and Eastern Europe (CEE), but not in the rural areas; additionally, the rural–urban dichotomy within the CEE countries is deepening due to the self-enhancing nature of the analyzed processes.
Increasing Sustainability Literacy for Environmental Design Students: A Transdisciplinary Learning Practice
Authors: Ma Jianqing , Jin Huixia
Published: September 2022

Nowadays, the urban water system is facing many challenges which affect the sustainable development of society. This requires higher education institutions to develop people with a diversity of knowledge and complex problem-solving capacities. This paper presents a practical case of transdisciplinary learning for junior students of environmental design at NingboTech University (Ningbo, China). The course “Environmental Engineering and Technology” ran from 1 March to 24 April 2022. A total of 25 students were instructed in the theories of urban water environmental engineering and then worked in groups to complete a design project for a river ecological restoration. The outcomes were analyzed from the perspective of combining engineering and landscape design. At the end of the course, students volunteered to take an online questionnaire about course evaluation. Students responded highly positively to the course, achieved growth in sustainability literacy, and developed skills in transdisciplinary learning. It also confirms the importance of outdoor education and project-based teaching. Additionally, the lowering of the requirement for mathematical skills through the internet tools usage and the formation of multidisciplinary teams are expected to improve future teaching outcomes. These results provide new insights for educators into the integration of the disciplines between design and engineering.
Two Decades of Life Cycle Sustainability Assessment of Solid Oxide Fuel Cells (SOFCs): A Review
Authors: Salim Khaled M. A. , Maelah Ruhanita , Hishamuddin Hawa , Amir Amizawati Mohd , Ab Rahman Mohd Nizam
Published: September 2022

The aim of this study is to draw a comprehensive image of the relationship between life cycle sustainability assessment (LCSA) impact using the three dimensions, namely life cycle costing (LCC), life cycle assessment (LCA), and social life cycle (SLC), and solid oxide fuel cells (SOFCs). By systematically reviewing and analyzing 43 articles from 17 different peer-reviewed journals between 1998 and 2021, the analysis shows that SOFC-related applications may substantially contribute to a cleaner energy sector in the future via high-level temperature power generation. The result indicated that SOFCs have better implications for environmental performance, as well as being the least cost-effective option for commercially competitive purposes. The review revealed several gaps in the literature; several studies assessed LCA using particular or very few indicators, and the few indicators may not sufficiently assess the environmental impact of SOFCs. Further, limited studies shed the light on the association between SLC and SOFCs. Future LCSA studies ought to adopt dynamic criteria, especially environmental impact analysis considering social and economic factors, to enable a feasible comparison of results. Future studies should also target various industrial sectors in developing countries.
Aggregation Operators Based on Algebraic t-Norm and t-Conorm for Complex Linguistic Fuzzy Sets and Their Applications in Strategic Decision Making
Authors: Mahmood Tahir , Ali Zeeshan , Albaity Majed
Published: September 2022

Aggregation operators perform a valuable and significant role in various decision-making processes. Averaging and geometric aggregation operators are both used for capturing the interrelationships of the aggregated preferences, even if the preferences are independent. The purpose of this paper is to analyze the theory of complex linguistic fuzzy (CLF) sets and their important laws, such as algebraic laws, score values, and accuracy values, and to describe the relationship between the score and accuracy values with the help of their properties. Additionally, based on the proposed CLF information, we introduce the theory of CLF weighted averaging (CLFWA), CLF ordered weighted averaging (CLFOWA), CLF hybrid averaging (CLFHA), CLF weighted geometric (CLFWG), CLF ordered weighted geometric (CLFOWG), and CLF hybrid geometric (CLFHG) operators. The fundamental properties and some valuable results of these operators are evaluated, and their particular cases are described. Based on the presented operators, a technique for evaluating the “multi-attribute decision-making” (MADM) problems in the consideration of CLF sets is derived. The superiority of the derived technique is illustrated via a practical example, a set of experiments, and significant and qualitative comparisons. The illustration results indicate that the derived technique can be feasible and superior in evaluating CLF information. Further, it can be used for determining the interrelationships of attributes and the criteria of experts. Moreover, it is valuable and capable of evaluating the MADM problems using CLF numbers.
Flight Conflict Detection Algorithm Based on Relevance Vector Machine
Authors: Wang Senlin , Nie Dangmin
Published: September 2022

In response to the problems of slow running speed and high error rates of traditional flight conflict detection algorithms, in this paper, we propose a conflict detection algorithm based on the use of a relevance vector machine. A set of symmetrical historical flight data was used as the training set of the model, and we used the SMOTE resampling method to optimize the training set. We obtained relatively symmetrical training data and trained it with the relevance vector machine, improving the kernels through an intelligent algorithm. We tested this method with new symmetrical flight data. The improved algorithm greatly improved the running speed and was able to effectively reduce the missed alarm rate of in-flight conflict detection symmetrically, thus effectively ensuring flight safety.
Why Sports Should Embrace Bilateral Asymmetry: A Narrative Review
Authors: Afonso José , Peña Javier , Sá Mário , Virgile Adam , García-de-Alcaraz Antonio , Bishop Chris
Published: September 2022

(1) Background: Asymmetry is ubiquitous in nature and humans have well-established bilateral asymmetries in their structures and functions. However, there are (mostly unsubstantiated) claims that bilateral asymmetries may impair sports performance or increase injury risk. (2) Objective: To critically review the evidence of the occurrence and effects of asymmetry and sports performance. (3) Development: Asymmetry is prevalent across several sports regardless of age, gender, or competitive level, and can be verified even in apparently symmetric actions (e.g., running and rowing). Assessments of bilateral asymmetries are highly task-, metric-, individual-, and sport-specific; fluctuate significantly in time (in magnitude and, more importantly, in direction); and tend to be poorly correlated among themselves, as well as with general performance measures. Assessments of sports-specific performance is mostly lacking. Most studies assessing bilateral asymmetries do not actually assess the occurrence of injuries. While injuries tend to accentuate bilateral asymmetries, there is no evidence that pre-existing asymmetries increase injury risk. While training programs reduce certain bilateral asymmetries, there is no evidence that such reductions result in increased sport-specific performance or reduced injury risk. (4) Conclusions: Bilateral asymmetries are prevalent in sports, do not seem to impair performance, and there is no evidence that suggests that they increase injury risk.
Step Length Asymmetry Predicts Rehabilitation Length in Subacute Post Stroke Patients
Authors: Schwartz Isabella , Ofran Yonah , Karniel Naama , Seyres Martin , Portnoy Sigal
Published: September 2022

Background: During the rehabilitation of individuals post stroke, evaluations are performed in order to discern the patient’s prognosis and optimize the treatment plan. However, these tests do not focus on gait symmetry, which might be a predictor for rehabilitation outcomes. We aimed to correlate gait symmetry measures of subacute post stroke patients with rehabilitation outcome and find the symmetry measure that best predicts the variability of the rehabilitation duration. A secondary aim was to compare these measures between patients with right and left brain lesions. Methods: We recruited 30 subacute post stroke patients (14 with right side lesion). We collected the following measures: National Institutes of Health Stroke Scale (NIHSS), Functional Independence Measure (FIM), the 10 m walk test (10MWT), Functional Ambulation Categories (FAC), spatial-temporal gait measures, and gait symmetry and variability. Results: We found moderate correlations between the step length symmetry and the length of rehabilitation, NIHSS, FIM, FAC and 10MWT. The symmetry index of the step length predicted the length of the rehabilitation period as it explained 32.1% of its variance (p = 0.001). Discussion: We conclude that a simple test of the step length symmetry might be informative in predicting rehabilitation length in subacute post stroke patients.
Machine Vision Approach for Diagnosing Tuberculosis (TB) Based on Computerized Tomography (CT) Scan Images
Authors: Haq Inayatul , Mazhar Tehseen , Nasir Qandeel , Razzaq Saqib , Mohsan Syed Agha Hassnain , Alsharif Mohammed H. , Alkahtani Hend Khalid , Aljarbouh Ayman , Mostafa Samih M.
Published: September 2022

Tuberculosis is curable, still the world’s second inflectional murderous disease, and ranked 13th (in 2020) by the World Health Organization on the list of leading death causes. One of the reasons for its fatality is the unavailability of modern technology and human experts for early detection. This study represents a precise and reliable machine vision-based approach for Tuberculosis detection in the lung through Symmetry CT scan images. TB spreads irregularly, which means it might not affect both lungs equally, and it might affect only some part of the lung. That’s why regions of interest (ROI’s) from TB infected and normal CT scan images of lungs were selected after pre-processing i.e., selection/cropping, grayscale image conversion, and filtration, Statistical texture features were extracted, and 30 optimized features using F (Fisher) + PA (probability of error + average correlation) + MI (mutual information) were selected for final optimization and only 6 most optimized features were selected. Several supervised learning classifiers were used to classify between normal and infected TB images. Artificial Neural Network (ANN: n class) based classifier Multi-Layer Perceptron (MLP) showed comparatively better and probably best accuracy of 99% with execution time of less than a second, followed by Random Forest 98.83%, J48 98.67%, Log it Boost 98%, AdaBoostM1 97.16% and Bayes Net 96.83%.
Stochastic Analysis of Train Running Safety on Bridge with Earthquake-Induced Irregularity under Aftershock
Authors: Tan Jincheng , Xiang Ping , Zhao Han , Yu Jian , Ye Bailong , Yang Delei
Published: September 2022

As a type of urban life project in China, bridges need a certain capacity of trains running safely after an earthquake to ensure and guarantee transportation on railway lines, post-disaster reconstruction and relief work. Since aftershocks may occur after the main shock, the earthquake-induced irregularity and aftershock intensity are fully considered, based on the running safety index in the seismic design of bridges. However, there is a lack of research on the running safety of trains after an earthquake; it is mainly judged on experience, and lacks theoretical basis. In this paper, the established finite element model of a train bridge interaction system with symmetry was considered. The point estimation method (PEM) combined with moment expansion approximation (MEA) is used for random calculation of the Housner Intensity (HI). Furthermore, running safety indexes were analyzed and the running safety performance of a simply supported bridge with symmetry was assessed under a post-earthquake condition. Then the limit value, to ensure the traffic safety performance after an earthquake, is calculated based on stochastic analysis. The HI can be calculated with full consideration of the randomness of aftershock intensity and structural parameters. On this basis, a calculation method of the HI that considers the randomness of aftershock intensity is proposed. This study can be helpful for the performance-based design of symmetric railway structures under post-earthquake conditions.
On Diophantine Equations Related to Narayana’s Cows Sequence and Double Factorials or Repdigits
Authors: Ji Yanjiao , Yang Peng , Cai Tianxin
Published: September 2022

In this paper, we determine all the Narayana’s cows numbers that are factorials or double factorials. We also show that 88 is the only repdigit (i.e., a class of numbers that has reflectional symmetry across a vertical axis) that can be written as the product of consecutive Narayana’s cows numbers.
Molecular Interaction and Magnetic Dipole Effects on Fully Developed Nanofluid Flowing via a Vertical Duct Applying Finite Volume Methodology
Authors: Ali Kashif , Ahmad Shabbir , Ahmad Sohail , Jamshed Wasim , Hussain Syed M. , Tag El Din El Sayed M.
Published: September 2022

Interpreting the complex interaction of nanostructured fluid flow with a dipole in a duct, with peripherally uniform temperature distribution, is the main focus of the current work. This paper also sheds light on the changes in the Nusselt number, temperature profiles, and velocity distributions for the fully developed nanofluid flow in a vertical rectangular duct due to a dipole placed near a corner of the duct. A finite volume approach has been incorporated for the numerical study of the problem. It is interesting to note the unusually lower values of the Nusselt number for the higher values of the ratio Gr/Re. Due to the nanostructure in the fluid, an enhancement in the Nusselt number has been noted, which is strongly supported by the magnetic field caused by the dipole. However, as the duct shape is transformed from rectangular to square, the Nusselt number is reduced remarkably. Further, as the dipole is brought nearer to the duct corner, the Nusselt number increases significantly. On the other hand, the flow reversal in the middle of the duct has been noted at higher values of the ratio Gr/Re. The dipole is noted to have a low impact on the reversal flow as well as on the temperature distribution.
Property (Bv) and Tensor Product
Authors: Aponte Elvis , Vasanthakumar Ponraj , Jayanthi Narayanapillai
Published: September 2022

In this article, a-Browder’s classical theorem is considered through the property (Bv), and we show that if two operators are norm equivalent, then property (Bv) holds for one if and only if it holds for the other. The necessary conditions for the difference of the spectrum and essential approximate point spectrum of the tensor product of two operators coincide with the product of differences between the spectrum and the essential approximate point spectrum of its two factors are investigated. We also discuss the necessary conditions for the tensor product of two operators to verify the property (Bv) and simultaneously give the equivalence between their various spectra with their Browder spectrum, likewise with the Drazin spectrum.
𝒩-Structures Applied to Commutative Ideals of BCI-Algebras
Authors: Muhiuddin Ghulam , Elnair Mohamed E. , Al-Kadi Deena
Published: September 2022

The study of symmetry is one of the most important and beautiful themes uniting various areas of contemporary arithmetic. Algebraic structures are useful structures in pure mathematics for learning a geometrical object’s symmetries. In order to provide a mathematical tool for dealing with negative information, a negative-valued function came into existence along with N-structures. In the present analysis, the notion of N-structures is applied to the ideals, especially the commutative ideals of BCI-algebras. Firstly, several properties of N-subalgebras and N-ideals in BCI-algebras are investigated. Furthermore, the notion of a commutative N-ideal is defined, and related properties are investigated. In addition, useful characterizations of commutative N-ideals are established. A condition for a closed N-ideal to be a commutative N-ideal is provided. Finally, it is proved that in a commutative BCI-algebra, every closed N-ideal is a commutative N-ideal.
Vortex Flows with Particles and Droplets (A Review)
Authors: Varaksin Aleksey Yu. , Ryzhkov Sergei V.
Published: September 2022

Single-phase vortices are a classic example of objects characterized by symmetry in the distribution of all main parameters. The presence of inertial particles (or droplets) in such objects, even with their initial uniform distribution in space, leads to symmetry breaking due to the inverse effect of the dispersed phase on the characteristics of carrier vortices. A review of calculation-theoretical and experimental works devoted to the study of the motion of particles (or droplets) in various concentrated vortex structures, as well as their inverse effect on vortex characteristics, is conducted. The main characteristics (inertia, concentration) as well as dimensionless parameters (Reynolds, Stokes, Froude, Tachikawa numbers) determining the interaction between the dispersed phase and vortices are described. The results of available studies are analyzed in order to establish the peculiarities of particle (or droplet) behavior and stability of different vortex structures, including natural ones. The works analyzed in the review cover a wide range of inertia of the dispersed phase (Stkf = 0.002 − 14.7) and vortex intensities (ReΓ = 200 − 5000).
Deep Learning Method on Deformation Prediction for Large-Section Tunnels
Authors: Xu Wei , Cheng Ming , Xu Xiangyang , Chen Cheng , Liu Wei
Published: September 2022

With the continuous development of engineering construction in China, more and more large-section highway tunnels have emerged. Different geological engineering environments determine the diversity of construction plans. The determination of construction plans and the prediction of tunnel deformations have always been the key points of engineering construction. In this paper, we use numerical simulations to determine specific construction parameters in the context of actual highway tunnel projects, and then use deep learning methods to predict deformation during tunnel construction, thus providing guidance for construction. We have found that: (i) Different excavation sequences and excavation depths have different effects on the surrounding rock deformation around the tunnel. The optimal excavation sequence through numerical simulation in this study is symmetrical excavation, and the excavation depth is 2 m. (ii) Numerical simulation based on Long Short-Term Memory (LSTM) algorithm is used to predict the tunnel deformation. It is found that the prediction results of the LSTM algorithm are more consistent with the actual monitoring data. (iii) Multi-step prediction is more important for engineering guidance, and three-step prediction can be considered during the process of engineering construction. Therefore, the machine learning algorithm provides a new method for engineering prediction.
Influence of Centrifugal Buoyancy in Thermal Convection within a Rotating Spherical Shell
Authors: Satake Hidemoto , Tagawa Toshio
Published: September 2022

The dynamo action, which is of importance in the study of the geomagnetism mechanism, is considered to be caused by the convection structure formed inside a rotating spherical shell. This convection structure elongated in the rotation axis is generated by the action of both heat and rotation on the fluid inside a spherical shell. In this study, we analyzed thermal convection in such a rotating spherical shell and attempted to understand the phenomenon of this convective structure. It is known that each value of the Prandtl number, the Ekman number and the Rayleigh number and their balance are important for the generation of such convective structure. We fixed these three parameters and considered the effect of centrifugal buoyancy as the Froude number additionally. To investigate how the effects of centrifugal buoyancy affect the convective structure, we carried out both three-dimensional numerical simulations and linear stability analyses. In particular, we focused on the transition from axisymmetric flow to non-axisymmetric flow having wavenumbers in the toroidal direction and investigated both growth rate and phase velocity of the disturbance. It was found that axisymmetric flow tends to be maintained as the effect of centrifugal buoyancy increases.
Analysis and Design of Enhanced Distributed Fountain Codes in Multiple Access Networks with Cooperative Relay
Authors: Shao Hanqin , Zhu Hongbo , Bao Junwei
Published: September 2022

Distributed fountain coding plays an important role in rateless code research. The reliability and effectiveness of these coding schemes are increasingly challenged with the growing applications. In this paper, a novel multiple-access network with cooperative relay is presented, and a novel enhanced distributed fountain coding scheme for this network is proposed. The overall degree distributions are derived, and the asymptotic decoding performance is analyzed theoretically by employing the And-Or tree method. On this basis, a design method using joint iterative optimization algorithms is proposed to optimize the degree distributions of the sources and relays. Simulation results show that the proposed enhanced distributed fountain codes outperform the existing generalized distributed fountain codes (GDFC) and have a good performance on both lossless and lossy channels. It reveals that the proposed codes can provide unequal error protection (UEP) property for different sources by introducing the extra cooperative relay. The performance improvement is not restricted to the sources connected to the cooperative relay but applies to all sources. With the additional relay, the proposed codes are able to overcome the effects of bad channel conditions caused by terrain, obstacles, and so on, to avoid communication interruptions and improve the reliability of the network.
Comprehensive Review of Solid State Transformers in the Distribution System: From High Voltage Power Components to the Field Application
Authors: Rehman Abdur , Imran-Daud Malik , Haider Syed Kamran , Rehman Ateeq Ur , Shafiq Muhammad , Eldin Elsayed Tag
Published: September 2022

This paper presents a systematical and progressive appraisal of the technology since the inception of AC-AC conversion, which is seen to be an indispensable and vital for the advancement of the Solid State Transformer (SST) in a distribution system. Special attention is given to the concepts/topologies and architecture of the SST, the DC-DC conversion devices in the isolation facet, the inversion gadget in the bridge arrangement and their integration in the development of an economically viable and efficient SST design. For the purpose of this article, a number of research papers, research proposals and research dissertations/studies have been accessed that mostly cover work related to this device and brief discussions about several aspects. The various sections of this article are correspondingly devoted to the review of SST design and its various configurations, the significant stages of the DC-DC converter from a transformer-specific perspective and lastly the high-frequency inverter. In critical appraisal, the SST in a three-stage perspective, the dual half-bridge converter and high-frequency half-bridge inverter are the most viable and promising means, offering tremendous advantages over other configurations with emphasis on economy, high flexibility and control performance; thereby weighed as the most workable, practical and realistic solutions. The foremost potential application of this expedient includes a vital component of the power grid.
An Efficient Algorithm for Mining Stable Periodic High-Utility Sequential Patterns
Authors: Xie Shiyong , Zhao Long
Published: September 2022

Periodic high-utility sequential pattern mining (PHUSPM) is used to extract periodically occurring high-utility sequential patterns (HUSPs) from a quantitative sequence database according to a user-specified minimum utility threshold (minutil). A sequential pattern’s periodicity is determined by measuring when the frequency of its periods (the time between two consecutive happenings of the sequential pattern) exceed a user-specified maximum periodicity threshold (maxPer). However, due to the strict judgment threshold, the traditional PHUSPM method has the problem that some useful sequential patterns are discarded and the periodic values of some sequential patterns fluctuate greatly (i.e., are unstable). In frequent itemset mining (FIM), some researchers put forward some strategies to solve these problems. Because of the symmetry of frequent itemset pattern (FIPs), these strategies cannot be directly applied to PHUSPM. In order to address these issues, this work proposes the stable periodic high-utility sequential pattern mining (SPHUSPM) algorithm. The contributions made by this paper are as follows. First, we introduce the concept of stability to overcome the abovementioned problems, mine sequential patterns with stable periodic behavior, and propose the concept of stable periodic high-utility sequential patterns (SPHUSPs) for the first time. Secondly, we design a new data structure named the PUL-list to record the periodic information of sequential patterns, thereby improving the mining efficiency. Thirdly, we propose the maximum lability pruning strategy in sequential pattern (MLPS), which can prune a large number of unstable sequential patterns in advance. To assess the algorithm’s effectiveness, we perform many experiments. It turns out that the algorithm can not only mine patterns that are ignored by traditional algorithms, but also ensure that the discovered patterns have stable periodic behavior. In addition, after using the MLPS pruning strategy, the algorithm can prune 46.5% of candidates in advance on average in six datasets. Pruning a large number of candidates in advance not only speeds up the mining process, but also greatly reduces memory usage.
SALMA: A Novel Middlebox Infrastructure System Based on Integrated Subnets
Authors: AlGhadhban Amer , Showail Ahmad
Published: September 2022

Middleboxes are critical components in today’s networks. Due to the variety of network/security policies and the limitations of routing protocols, middleboxes are installed in multiple physical locations to face high traffic with few considerations for efficiency. Reducing the number of deployed middleboxes would reduce capital and operation costs. Moreover, some flows prefer to bypass one or more in-path middlebox where they provide useless services, such as payload compression for multimedia streams. These challenges can be partially tackled by network function virtualization (NFV) schemes with the costs of performance reduction and replacement expenses. Given the rapid growth and the wide adoption of software-defined networking solutions and the recent advances in managing middleboxes’ configuration, the consolidation of middleboxes is becoming easier than before. We designed and evaluated SALMA, a new pre-NFV practical solution that systematically recreates the infrastructure of middleboxes by proposing the Integrated Middleboxes Subnets scheme. In this work, we attempted to reduce the number of installed middleboxes by implementing horizontal integration of middleboxes’ functions, such as every pair of middleboxes being integrated into a dedicated hardware box. We support the motivation for creating SALMA with a practical survey of in-production middleboxes from 30 enterprises. Our solution addresses key challenges of middleboxes, including cost, utilization, flexibility, and load balancing. SALMA’s performance has been evaluated experimentally as well.
How Should I Teach from This Month Onward? A State-Space Model That Helps Drive Whole Classes to Achieve End-of-Year National Standardized Test Learning Targets
Authors: Ulloa Obed , Araya Roberto
Published: September 2022

Every month, teachers face the dilemma of what exercises their students should practice, and what their consequences are regarding long-term learning. Since teachers prefer to pose their own exercises, this generates a large number of questions, each one attempted by a small number of students. Thus, we could not use models based on big data, such as deep learning. Instead, we developed a simple-to-understand state-space model that predicts end-of-year national test scores. We used 2386 online fourth-grade mathematics questions designed by teachers, each attempted by some of the 500 students in 24 low socioeconomic schools. We found that the state-space model predictions improved month by month and that in most months, it outperformed linear regression models. Moreover, the state-space estimator provides for each month a direct mechanism to simulate different practice strategies and compute their impact on the end-of-year standardized national test. We built iso-impact curves based on two critical variables: the number of questions solved correctly in the first attempt and the total number of exercises attempted. This allows the teacher to visualize the trade-off between asking students to perform exercises more carefully or perform more exercises. To the best of our knowledge, this model is the first of its kind in education. It is a novel tool that supports teachers drive whole classes to achieve long-term learning targets.
TDP-43 CSF Concentrations Increase Exponentially with Age in Metropolitan Mexico City Young Urbanites Highly Exposed to PM2.5 and Ultrafine Particles and Historically Showing Alzheimer and Parkinson’s Hallmarks. Brain TDP-43 Pathology in MMC Residents Is Associated with High Cisternal CSF TDP-43 Concentrations
Authors: Calderón-Garcidueñas Lilian , Stommel Elijah W. , Lachmann Ingolf , Waniek Katharina , Chao Chih-Kai , González-Maciel Angélica , García-Rojas Edgar , Torres-Jardón Ricardo , Delgado-Chávez Ricardo , Mukherjee Partha S.
Published: September 2022

Environmental exposures to fine particulate matter (PM2.5) and ultrafine particle matter (UFPM) are associated with overlapping Alzheimer’s, Parkinson’s and TAR DNA-binding protein 43 (TDP-43) hallmark protein pathologies in young Metropolitan Mexico City (MMC) urbanites. We measured CSF concentrations of TDP-43 in 194 urban residents, including 92 MMC children aged 10.2 ± 4.7 y exposed to PM2.5 levels above the USEPA annual standard and to high UFPM and 26 low pollution controls (11.5 ± 4.4 y); 43 MMC adults (42.3 ± 15.9 y) and 14 low pollution adult controls (33.1 ± 12.0 y); and 19 amyotrophic lateral sclerosis (ALS) patients (52.4 ± 14.1 y). TDP-43 neuropathology and cisternal CSF data from 20 subjects—15 MMC (41.1 ± 18.9 y) and 5 low pollution controls (46 ± 16.01 y)—were included. CSF TDP-43 exponentially increased with age (p < 0.0001) and it was higher for MMC residents. TDP-43 cisternal CSF levels of 572 ± 208 pg/mL in 6/15 MMC autopsy cases forecasted TDP-43 in the olfactory bulb, medulla and pons, reticular formation and motor nuclei neurons. A 16 y old with TDP-43 cisternal levels of 1030 pg/mL exhibited TDP-43 pathology and all 15 MMC autopsy cases exhibited AD and PD hallmarks. Overlapping TDP-43, AD and PD pathologies start in childhood in urbanites with high exposures to PM2.5 and UFPM. Early, sustained exposures to PM air pollution represent a high risk for developing brains and MMC UFPM emissions sources ought to be clearly identified, regulated, monitored and controlled. Prevention of deadly neurologic diseases associated with air pollution ought to be a public health priority and preventive medicine is key.
Detecting Aquatic Pollution Using Histological Investigations of the Gills, Liver, Kidney, and Muscles of Oreochromis niloticus
Authors: Shahid Sana , Sultana Tayyaba , Sultana Salma , Hussain Bilal , Al-Ghanim Khalid Abdullah , Al-Bashir Fahad , Riaz Mian Nadeem , Mahboob Shahid
Published: September 2022

The present study aimed to determine the degree of changes in the histological architecture of the liver, gills, kidneys, and muscles of fish Oreochromis niloticus collected from different polluted river sites. Fish samples collected from the Faisalabad Fish Hatchery and upstream of Chakbandi drain acted as a control. Necrosis, hemorrhage, and epithelial hyperplasia were observed in the gills of fish inhabiting the river downstream of the Chakbandi drain entrance. Liver tissues were found to be affected by vacuolated cytoplasm, bile duct proliferation, melanomacrophages, and necrosis. In kidney tissues, shrinkage of the renal cortex, necrosis, and destructive renal tubules were observed. Histopathology of muscles indicates the presence of hypertrophy and swollen myofibers. In contrast, upstream specimens of fish exhibited mild tissue alterations. Histopathology of gills tissue showed vacuolization. Liver tissues indicated the presence of hypertrophy and more frequent Kupffer cells than usual. The vacuolation was also observed in kidney tissues. Muscle tissues expressed splitting of muscle fibres and degeneration in muscle bundles. However, sections of tissues collected from farmed fish have normal morphology and no anomalies. The histopathological assessment indicated various cellular, biochemical, and histological changes in response to the contamination in the vicinity of the fish.
Evaluation of Metabolism of a Defined Pesticide Mixture through Multiple In Vitro Liver Models
Authors: Valdiviezo Alan , Kato Yuki , Baker Erin S. , Chiu Weihsueh A. , Rusyn Ivan
Published: September 2022

The evaluation of exposure to multiple contaminants in a mixture presents a number of challenges. For example, the characterization of chemical metabolism in a mixture setting remains a research area with critical knowledge gaps. Studies of chemical metabolism typically utilize suspension cultures of primary human hepatocytes; however, this model is not suitable for studies of more extended exposures and donor-to-donor variability in a metabolic capacity is unavoidable. To address this issue, we utilized several in vitro models based on human-induced pluripotent stem cell (iPSC)-derived hepatocytes (iHep) to characterize the metabolism of an equimolar (1 or 5 µM) mixture of 20 pesticides. We used iHep suspensions and 2D sandwich cultures, and a microphysiological system OrganoPlate® 2-lane 96 (MimetasTM) that also included endothelial cells and THP-1 cell-derived macrophages. When cell culture media were evaluated using gas and liquid chromatography coupled to tandem mass spectrometry methods, we found that the parent molecule concentrations diminished, consistent with metabolic activity. This effect was most pronounced in iHep suspensions with a 1 µM mixture, and was lowest in OrganoPlate® 2-lane 96 for both mixtures. Additionally, we used ion mobility spectrometry–mass spectrometry (IMS-MS) to screen for metabolite formation in these cultures. These analyses revealed the presence of five primary metabolites that allowed for a more comprehensive evaluation of chemical metabolism in vitro. These findings suggest that iHep-based suspension assays maintain higher metabolic activity compared to 2D sandwich and OrganoPlate® 2-lane 96 model. Moreover, this study illustrates that IMS-MS can characterize in vitro metabolite formation following exposure to mixtures of environmental contaminants.
A Nanobody-Based Immunoassay for Detection of Ustilaginoidins in Rice Samples
Authors: Wang Weixuan , Gu Gan , Yin Ruya , Fu Jiajin , Jing Mingpeng , Shen Zhen , Lai Daowan , Wang Baomin , Zhou Ligang
Published: September 2022

Ustilaginoidins are a class of bis-naphtho-γ-pyrone mycotoxins produced by the pathogen Villosiclava virens of rice false smut, which has recently become one of the most devastating diseases in rice-growing regions worldwide. In this research, the nanobody phage display library was established after an alpaca was immunized with the hemiustilaginoidin F-hapten coupled with bovine serum albumin (BSA). Heterologous antigen selection and combing trypsin with competition alternant elution methods were performed for nanobody screening. Two nanobodies, namely, Nb-B15 and Nb–C21, were selected for the establishment of indirect competitive enzyme-linked immunosorbent assays (ic-ELISAs). For Nb–B15 and Nb-C21, their IC50 values were 11.86 μg/mL and 11.22 μg/mL, and the detection ranges were at 3.41–19.98 μg/mL and 1.17–32.13 μg/mL, respectively. Two nanobodies had a broad spectrum to quantify the contents of total ustilaginoidins in rice samples according to cross-reactivity. The recognition mechanisms of Nb-B15 and Nb-C21 against ustilaginoidin A were elucidated by molecular modeling and docking. The key amino acid sites for the binding of Nb–B15 or Nb–C21 to ustilaginoidin A were mainly located in the FR1 and CDR1 regions. As Nb-B15 was superior to Nb–C21 in the aspects of protein expression, ELISA titer, and tolerance to organic solvents, it was selected for application in the detection of actual contaminated rice samples. The total ustilaginoidin contents of rice samples were analyzed by Nb–B15-based ic–ELISA and HPLC-DAD, between which the results were found to be consistent. The developed immunoassay based on the nanobody from the alpaca can be employed as a rapid and effective method for detection of total utilaginoidins in contaminated rice samples.
Therapeutic Effect of Bee Venom and Melittin on Skin Infection Caused by Streptococcus pyogenes
Authors: Bae Seongjae , Gu Hyemin , Gwon Mi-Gyeong , An Hyun-Jin , Han Sang-Mi , Lee Sun-Jae , Leem Jaechan , Park Kwan-Kyu
Published: September 2022

Streptococcus pyogenes (S. pyogenes) bacteria cause almost all primary skin infections in humans. Bee venom (BV) and melittin (Mel) have multiple effects, including antibacterial and anti-inflammatory activities. This study aims to demonstrate their effects on bacterial mouse skin infection using S. pyogenes. The dorsal skin was tape-stripped, then S. pyogenes was topically applied. BV or Mel were topically applied to the lesion. The tissues were stained with hematoxylin and eosin, while immunohistochemical staining was performed with anti-neutrophil. S. pyogenes-infected skin revealed increased epidermal and dermal layers, but it was reduced in the BV and Mel groups. Finding increased neutrophils in the mice infected with S. pyogenes, but the BV and Mel mice showed decreased expression. These results suggest that BV and Mel treatments could reduce the inflammatory reactions and help improve lesions induced by S. pyogenes skin infection. This study provides additional assessment of the potential therapeutic effects of BV and Mel in managing skin infection caused by S. pyogenes, further suggesting that it could be a candidate for developing novel treatment alternative for streptococcal skin infections.
Effects of Compound Mycotoxin Detoxifier on Alleviating Aflatoxin B1-Induced Inflammatory Responses in Intestine, Liver and Kidney of Broilers
Authors: Guo Hongwei , Wang Ping , Liu Chaoqi , Zhou Ting , Chang Juan , Yin Qingqiang , Wang Lijun , Jin Sanjun , Zhu Qun , Lu Fushan
Published: September 2022

In order to alleviate the toxic effects of aflatoxins B1 (AFB1) on inflammatory responses in the intestine, liver, and kidney of broilers, the aflatoxin B1-degrading enzyme, montmorillonite, and compound probiotics were selected and combined to make a triple-action compound mycotoxin detoxifier (CMD). The feeding experiment was divided into two stages. In the early feeding stage (1–21 day), a total of 200 one-day-old Ross broilers were randomly divided into four groups; in the later feeding stage (22–42 day), 160 broilers aged at 22 days were assigned to four groups: Group A: basal diet (4.31 μg/kg AFB1); Group B: basal diet with 40 μg/kg AFB1; Group C: Group A plus 1.5 g/kg CMD; Group D: Group B plus 1.5 g/kg CMD. After the feeding experiment, the intestine, liver, and kidney tissues of the broilers were selected to investigate the molecular mechanism for CMD to alleviate the tissue damages. Analyses of mRNA abundances and western blotting (WB) of inflammatory factors, as well as immunohistochemical (IHC) staining of intestine, liver, and kidney tissues showed that AFB1 aggravated the inflammatory responses through NF-κB and TN-α signaling pathways via TLR pattern receptors, while the addition of CMD significantly inhibited the inflammatory responses. Phylogenetic investigation showed that AFB1 significantly increased interleukin-1 receptor-associated kinase (IRAK-1) and mitogen-activated protein kinase (MAPK) activities (p < 0.05), which were restored to normal levels by CMD addition, indicating that CMD could alleviate cell inflammatory damages induced by AFB1.
Influence of Season and Food Type on Bacterial and Entero-Toxigenic Prevalence of Staphylococcus aureus
Authors: Bianchi Daniela Manila , Maurella Cristiana , Lenzi Christian , Fornasiero Massimo , Barbaro Antonio , Decastelli Lucia
Published: September 2022

Staphylococcus (S.) aureus is a coagulase-positive pathogen of interest for human health and food safety in particular. It can survive in a wide environmental temperature range (7–48 °C, optimum 37 °C). Its enterotoxins are thermostable, which increases the risk of potential contamination in a variety of food products. Here we investigated the influence of seasonality and food type on bacterial count and presence of S. aureus enterotoxins. To do this, we analyzed 3604 food samples collected over a 5-year period (2016–2020). Ordinal logistic regression showed an influence of both seasonality and food type on the bacterial count. Regarding bacterial counts, winter was found to be the season with the highest risk, while with regards to enterotoxin production, the highest risk was found in autumn, specifically in October. The risk of contamination with S. aureus was greatest for dairy products. Our findings may inform food epidemiologists about foodborne illness prevention and risk to human health.