bluuebunny/crossref_metadata_2025 huggingface dataset:
Housing affordability, market interventions, and policy platforms in the 2022 Ontario provincial election
Authors: Dantzler Prentiss A. ,   Urban Policy Collective
Published: October 2022

Since the Great Recession, many cities around the world have undergone extreme demographic changes as people and capital resettle into urban areas. This has resulted in issues of gentrification and displacement forcing many governments to address growing concerns of housing insecurity. Housing policy is a function of political ideologies and social conditions drawing from market‐based housing supply (MBHS) solutions or demand‐side interventions (DSI) to alleviate housing cost burdens. Yet, debates on their effectiveness have often undermined their ability to grow to scale leaving many households in precarious housing situations. This paper focuses on the 2022 Ontario provincial election to uncover how Canadian political parties frame housing insecurity and their policy platforms. This paper finds all political parties promote the MBHS framework, yet various degrees of the DSI framework. Embedded within this variation are questions of federalism with responsibility shifting between provincial and municipal governments. The findings reveal while different forms of neoliberal ideology inform the policy platforms of political parties, federalism plays a significant role in framing the level and scale of government involvement.
RESPONSE TO THE COMPATIBILITY OF EVOLUTION AND DESIGN
Authors: Sollereder Bethany N.
Published: October 2022

The first half of this article offers two possibilities of how the argument Kojonen makes might be vulnerable to other new developments in evolutionary science and psychology—potential broadsides that might threaten to sink the salvaged ship of design once again. Work on the development of life suggests that life is a simplification of surrounding environmental information, and therefore life does not generate new information. Second, the psychology of pareidolia suggests we find design as a bias of our information processing, rather than observing something that exists. The second half of the article offers a critique of how the metaphors we use to describe God and the world shape our approaches to solving theological and philosophical questions (particularly theodicy). I offer some organic metaphors in place of the usual mechanistic metaphors to think about how the design argument could be reformulated.
Antibacterial Effectiveness of Chitosan Solution on Streptococcus Mutans
Authors: Wahjuningrum Dian Agustin , Setyabudi Setyabudi , Hadinata Daniel , Amalia Ilona Talitha , Ro’ifa Rizki Annisa , Juniarti Devi Eka
Published: October 2022

Dental caries is a localized destruction on teeth by organic acid produced by carbohydrate fermentation of cariogenic bacteria. Streptococcus mutans is a Gram-positive bacterium, a facultative anaerobe species often found in human oral cavity and is a significant contributor to dental caries. Chitosan is the collective name of a group of partially or fully deacetylated chitin. Because of its unique biological properties, including biodegradability and nontoxicity, a lot of applications have been found for chitosan, on its own or combined with other polymers. Chitosan has a wide spectrum of activity and high killing rate against Gram positive and Gram-negative bacteria, while having low toxicity against mammal cell. In this research a Kirby-Bauer test is done on Streptococcus mutans using 1%, 1.5%, and 2% chitosan solution as treatment group and aquades as control group. Average of each group is calculated and significancy is determined using statistical calculation. The resulting data is analyzed using Kruskal-Wallis and Post-hoc Tukey HSD and is shown there to be a significant difference between each treatment groups. The biggest zone of inhibition is seen on the 2% chitosan solution group. 2% chitosan solution has higher antibacterial effectiveness on Streptococcus mutans than 1% and 1.5% chitosan solution.
Solutions to the Diophantine Equation x²+16⋅7ᵇ=y²ʳ
Authors: Yow Kai Siong , Sapar Siti Hasana , Low Cheng Yaw
Published: October 2022

We present a method of determining integral solutions to the equation x^2 + 16.7^b = y^2r, where x,y,b,r \in Z^+. We observe that the results can be classified into several categories. Under each category, a general formula is obtained by using the method of geometric progression. We then provide the bound for the number of non-negative integral solutions associated with each b. Lastly, the general formula for each of the categories is obtained and presented to determine respective values of x and y^r. We also highlight two special cases where different formulae are needed to represent their integral solutions.
Water Footprint of Rice Production in Malaysia: A Review of Evapotranspiration and Factors of Climate Change for Rice and Food Security in Malaysia
Authors: Mohamed Rusli Nurfarhain , Zainon Noor Zainura , Mat Taib Shazwin , Mohammad Sabli Noor Salehan
Published: October 2022

Rice is a special crop that requires a thin layer of water to produce, and is produced differently from other crops. The rice sectors in Malaysia continue to be developed in a proactive and progressive manner. Due to its growth process, rice has a different water footprint (WF) compared to other crops. This study improved the calculation of the blue and green WF of rice production and examined the variations of these footprints under the primary granary area of Malaysia. The effects of climate change will, however, make it more difficult to achieve food security and increase rice yields in the future. Therefore, this paper aims to discuss climate change impacts on rice production and food security in Malaysia. Many countries worldwide are becoming increasingly vulnerable to natural disasters due to climate change. Many climate models predict a decline in agricultural productivity due to excessive heat in tropical and subtropical regions, especially in Southeast Asia. Malaysia is no exception. Therefore, the present study examined the impact of climate change on rice yields in Muda Granary, Malaysia. Utilizing literature reviews, we assessed the value of evapotranspiration (ET) in order to calculate the green WF for the area. Climate variables (such as ET), yield, and variance of impact during the main season and off-season were the primary objectives of the study. Precipitation did not show a statistically significant difference between the main and off-seasons from 2011-2015. During the main crop season, the maximum ET was negatively associated with yield, but the minimum ET showed a positive association. In the off-season, green WF levels were higher than those in the main season. These findings indicate that climate change poses a serious threat to rice production, which will in turn affect food security as they are highly interconnected. Thus, it is high time for Malaysia to revamp its paddy and rice intervention strategies by giving due attention to enhancing the adaptive capacity of rice farmers to cope with climate change.
Characterization of Basin of Attraction for An Attractor in A Discrete Prey-Predator Sea Turtle-Human Interaction Model using Stability Index Approach
Authors: Mohd Lutfi Mohd Tirmizi , Mohd Roslan Ummu Atiqah , Ghane Fatemeh Helen , Embong Ahmad Fadillah
Published: October 2022

Drastic declines of the number of sea turtles have become a global issue since decades ago. This is due to overexploitation through human activities in various ways, such as poaching and trapping in the fishing nets, consuming their eggs and meat, other than being threatened by pollution, habitat destruction and many more. Therefore, it is our interest to investigate this issue through mathematical modelling. For that purpose, a discrete model of interaction between sea turtles and humans is proposed in this paper. The objective of this paper is to determine sustainability of sea turtle population in the future. In order to achieve this, an approach called the stability index, has been implemented on the basin of attraction of an attractor in the model proposed for different values of consumption rate  The results show that the stability indices vary from  down to positive values as  increases. Biologically,  index means that the sea turtles will survive, while positive index means that riddled basin has occurred in which it is predicted that the sea turtles might extinct or not depending on the initial population existing in a habitat.  Moreover, the time series have also been plotted for different values of  The patterns show that for a low  the sea turtles will survive in the next 10 years while when  is high, the sea turtle will extinct in less than two years. Thus, the results of this model could significantly be used to urge humans to stop exploiting these unique creatures and start appreciating their existence in the ecosystem.
Experimental Investigation into Liquid and Solid Separation by an Industrial Mesh-Vane-Type Separator on Natural Gas at 4–5 MPa, Different Liquid Loadings and Gas Flows
Authors: Botros K.K. , Chan N. , Geerligs J. , Leong K. , Hickey B. , Gong I.
Published: October 2022

Inline vertical separators are commonly employed in natural gas transmission facilities (e.g., receipt stations) to filter liquid contaminants such as compressor oil, glycol, and free water from the gas stream. Manufacturers of these separators have claimed liquid removal efficiencies of 98–99% for droplet sizes ≥ 8 μm. However, these contaminants have been found invariably in piping systems downstream of these separators, suggesting inadequate separator performance. Currently, there is a lack of ability to verify manufacturer claims due to difficulties in quantifying liquid contaminants and droplet characteristics. The potential consequences of having such contaminants include lower gas quality, impaired gas metering accuracy, corrosion and damage to equipment/instrumentation, and adverse impacts on industrial and residential end users. This paper presents performance testing of a mesh-vane-type vertical separator conducted on high pressure, pipeline quality, natural gas in the range of 4–5 MPa and flow velocity in the range of 1.3–13 m/s in the DN150 separator inlet (hence turndown ratio of 10:1). Four different spray nozzles were used to inject and atomize industrial compressor oil with a liquid-to-gas mass loading ratio of 0.06–1.8%. Test results revealed that the average bulk efficiency separation performance for this separator is approximately 90.34%. This was found to be independent of the liquid-to-gas mass loading ratio. The effective Souders–Brown K-factor was found to be 0.15 m/s. This is below literature published data in the range of 0.27–0.3 m/s for horizontal flow, vane-pack-type separators. Liquid separation tests were also conducted following the injection of solid glass beads. Liquid separation efficiency decreased by approximately 9%, following the injection of 7 kg of industrial glass beads over a period of approximately 4 h. This was attributed to accumulation of solids in the vane pack.
A Data-Driven Proxy Modeling Approach Adapted to Well Placement Optimization Problem
Authors: Amiri Kolajoobi Rasool , Emami Niri Mohammad , Amini Shahram , Haghshenas Yousof
Published: October 2022

Well placement optimization (WPO) plays an essential role in field management and economy. However, it entails massive computational time and demand since hundreds, even thousands, simulation runs are needed. Different types of proxy models have been utilized to address this issue. Among different proxy models, data-driven proxies are preferred as they can determine the combined effect of several parameters without suffering from the type and the number of modeling parameters. This article aims to develop a data-driven proxy model in an artificial intelligence framework adapted to the WPO problem. This proxy estimates and compares the oil recovery for different well configurations. Our contribution is building a dynamic proxy by training a sequence of static proxies in a time-dependent manner to make more benefit from the modeling capability of artificial neural networks (ANNs). The workflow comprises preparing a learning database using experimental design techniques, finding the significant parameters by searching the parameter space, training and validating a series of ANNs to obtain the desired field response, and conducting a blind test to ensure the model performance and generality. This proxy is then coupled with the genetic algorithm to find an optimal well configuration in a test case. Verifying the results obtained by our proxy with those of a commercial simulator shows that the objectives of constructing this proxy for WPO are successfully achieved.
Resource-efficient high-dimensional subspace teleportation with a quantum autoencoder
Authors: Zhang Hui , Wan Lingxiao , Haug Tobias , Mok Wai-Keong , Paesani Stefano , Shi Yuzhi , Cai Hong , Chin Lip Ket , Karim Muhammad Faeyz , Xiao Limin , Luo Xianshu , Gao Feng , Dong Bin , Assad Syed , Kim M. S. , Laing Anthony , Kwek Leong Chuan , Liu Ai Qun
Published: October 2022

Quantum autoencoders serve as efficient means for quantum data compression. Here, we propose and demonstrate their use to reduce resource costs for quantum teleportation of subspaces in high-dimensional systems. We use a quantum autoencoder in a compress-teleport-decompress manner and report the first demonstration with qutrits using an integrated photonic platform for future scalability. The key strategy is to compress the dimensionality of input states by erasing redundant information and recover the initial states after chip-to-chip teleportation. Unsupervised machine learning is applied to train the on-chip autoencoder, enabling the compression and teleportation of any state from a high-dimensional subspace. Unknown states are decompressed at a high fidelity (~0.971), obtaining a total teleportation fidelity of ~0.894. Subspace encodings hold great potential as they support enhanced noise robustness and increased coherence. Laying the groundwork for machine learning techniques in quantum systems, our scheme opens previously unidentified paths toward high-dimensional quantum computing and networking.
EBVerified TCRs and multiple sclerosis
Authors: Sefik Esen , O’Connor Kevin C.
Published: October 2022

Patients with multiple sclerosis display broad EBV-specific TCR repertoires driven by an enduring anti-EBV immune response.
Screening of Medicinal Compounds in Blood by Atmospheric Pressure Laser Plasma Ionization Mass Spectrometry
Authors: Kravets K. Yu. , Timakova S. I. , Grechnikov A. A. , Borodkov A. S. , Laptinskaya P. K. , Kuzmin V. S. , Simanovsky Ya. O.
Published: October 2022

We proposed a procedure for screening drug compounds by high-resolution mass spectrometry with atmospheric pressure laser plasma ionization (APLPI). The analytical performance of the method was studied on examples of five medicinal compounds: Lidocaine, Bendazole, Papaverine, Chloropyramine, and Carbamazepine. Calibration dependences were obtained in the analysis of model solutions and blood samples; sensitivity coefficients were determined. The relative standard deviation of the results is in the range 20–27%. The APLPI technique can detect promptly and reliably the studied medicinal compounds at concentrations 0.5–6 ng/mL in a sample. The sensitivity of APLPI exceeds that of atmospheric pressure electrospray ionization by 4–16 times.
Increasing bioactive compound levels in Agastache rugosa by hydrogen peroxide soaking in a hydroponic culture system
Authors: Lam Vu Phong , Anh Vu Ky , Loi Dao Nhan , Park Jong Seok
Published: October 2022

Hydrogen peroxide (H2O2) is a reactive oxygen species that can damage a variety of cellular structures. Recent studies have shown that H2O2 can mediate multiple physiological and biochemical processes by acting as a signaling molecule. This study was performed to explore the optimum H2O2 treatments for increasing the bioactive compounds in Agastache rugosa Fisch. & C.A. May plants with roots temporarily immersed in H2O2 concentrations of 0 (control), 4, 8, 16, 32, 64, and 128 mmol L−1 in a hydroponic culture system. All cultivated plants were subjected to root soaking with diniconazole (120 µmol L−1) at 7 days after transplanting to restrict plant height. H2O2 concentrations of 4, 16, and 64 mmol L−1 significantly reduced root length compared with no H2O2 treatment. Root fresh weight was significantly lower in response to exposure to 128 mmol L−1 H2O2 compared with control plants. Although shoot and root dry weights were lower in plants exposed to 128 mmol L−1 H2O2 compared with control plants, no significant differences were detected among treatments. Soaking roots in 16 mmol L−1 H2O2 induced the highest rosmarinic acid (RA) content, and 16, 32, and 64 mmol L−1 H2O2 significantly increased tilianin content in the whole plant compared with the control. The highest acacetin content was detected under 32 mmol L−1 H2O2. In addition, root extract of A. rugosa had the highest RA concentration, and the tilianin concentration was the highest in flowers. Collectively, these results show that soaking roots in 16 and 32 mmol L−1 H2O2 at 3.5 weeks after transplanting promotes secondary metabolites of hydroponically grown A. rugosa.
Design and Development of Microbial Fuel Cells Based Low Power Energy Harvesting Mechanism for Ecological Monitoring and Farming of Agricultural Applications
Authors: Suganya P , Divya Navamani J , Lavanya A , Mrinal Rishabh
Published: October 2022

Energy harvesting from the microbial fuel cells have a significant attention in the recent days, due to their cost efficiency, simple designing structure and self-powered system. Also, the emergence of internet of things plays a vital role in many real time application scenarios like agricultural purposes and activities. But, the incorporation of these techniques is one of challenging and interesting tasks in the research field. In the conventional works, the internet of things has been utilized as a cloud storage domain for activating the sensors used for environmental monitoring and controlling purposes. The main intention of this paper is to design a robust and cost-effective sludge water based microbial fuel cells, and utilize it for an internet of things incorporated ecological monitoring and farming applications by activating the smart sensors. It discusses about the various electrode combination with several mixture of substrate to study about the optimum performance of microbial fuel cells. To ease the comparative study, Thing Speak platform is used along with the necessary sensors for continuous monitoring. In addition to that, the efficiency of single and dual chamber microbial fuel cell is analyzed based on the set of parameters such as cost, size, and construction. In this work, the microbial fuel cell-based energy harvesting scheme is also developed with switched capacitance-based metal oxide semiconductor field effect transistor and relay-based charge pump circuit which can be incorporated to the internet of things based agriculture applications. Here, the cost analysis of microbial fuel cell with and without DC–DC converter have been compared for selecting the most suitable one for the application system. Moreover, the digital temperature and humidity sensor can be utilized with the proposed microbial fuel cell system for gathering the inputs of the ecological system, which acts as an interface of the microbial fuel cell and cloud systems. During experimentation, the results of both the energy harvesting schemes are evaluated and compared by using various performance indicators.
New FTFN-Based Tunable Memristor Emulator Circuit and its Mutation to Meminductor and Memcapacitor Emulators
Authors: Bhardwaj Kapil , Narayana Ravuri , Srivastava Mayank
Published: October 2022

For the first time, a new memristor emulator structure using a single four-terminal floating nullor (FTFN) and a transconductance stage has been presented with tunable circuit configuration. Along with that the circuit requires only a single grounded capacitance and two external MOS transistors to realize both incremental and decremental types of memductance functions. The use of the FTFN block has been demonstrated for the first time to build such a compact memristor emulator, which fully utilizes the employed circuit resources. The wide-band operating frequency range (1 kHz–3 MHz) is another attractive feature of the proposed emulator. Moreover, the mutation of the proposed memristor emulator into meminductor and memcapacitor emulators is also presented by the mutators based on FTFN. All the presented circuits have been tested by performing simulations using PSPICE with 0.18-[Formula: see text]m CMOS technology. The generated simulation results clearly show the ideal nonvolatile nature of the realized memristor, which has also been utilized in an op-amp-based circuit designed to exhibit associative learning phenomena. The proposed FTFN-based memristor has been implemented using commercially available ICs, LM13700, and AD844, and the generated PHL plot is discussed.
Fluid–structure interaction modeling with nonmatching interface discretizations for compressible flow problems: Computational framework and validation study
Authors: Rajanna Manoj R. , Johnson Emily L. , Liu Ning , Korobenko Artem , Bazilevs Yuri , Hsu Ming-Chen
Published: October 2022

This work presents a strongly-coupled fluid–structure interaction (FSI) formulation for compressible flows that is developed based on an augmented Lagrangian approach. The method is suitable for handling problems that involve nonmatching fluid–structure interface discretizations. In this work, the fluid is modeled using a stabilized finite element method for the Navier–Stokes equations of compressible flows and is coupled to the structure, which is formulated using isogeometric Kirchhoff–Love shells. The strongly-coupled system is solved using a block-iterative approach. The proposed method is validated using two compressible flow benchmark problems to assess the accuracy of the developed formulation.
HYBRID ALGORITHM FOR THE CLASSIFICATION OF FRACTAL DESIGNS AND IMAGES
Authors: YU ZHENHUA , SOHAIL AYESHA , JAMIL MARYAM , BEG O. A. , TAVARES JOÃO MANUEL R. S.
Published: October 2022

The fractal patterns are recursive patterns and are self-similar in nature. The fractal geometry provides better understanding of natural patterns as compared to the Euclidean geometry. The fractal designs have been used extensively in the fields of applied sciences due to the systematic methods used for their generation. These methods provide benchmarks to analyze the roughness, narrow/broad vision of the objects. In the fields of architecture and design, computational methods for fractal generation can prove to be more reliable tools. The fractal patterns can be simulated and the architecture can be modeled, with several options, before implementing it practically. During this research, this strategy is opted to design novel fractal tile designs. Several designs are selected from a series of simulations, based on the final visionary evaluation, according to the requirement of the walls of different zones in modern buildings. Four fractal patterns are simulated with several orientations and final designs are documented with corresponding geometrical evaluation.
Sustainable Supplier Evaluation in an Automotive Company Using Fuzzy Multi-Criteria Decision-Making Methods
Authors: Şişman Tuğçe , Kiriş Sinem Büyüksaatçi , Yilmaz Dilek
Published: October 2022

Sustainable supplier management literature is mainly on sustainable supplier selection but sustainable supplier performance monitoring & evaluation studies are scarce. Furthermore, the studies do not differentiate the sustainability evaluation criteria between the supplier selection and monitoring & evaluation stages. To bridge this gap, this study aimed to monitor & evaluate sustainability performance of the suppliers of a focal manufacturing company in automotive sector with the TBL approach. Toward that end, we questioned and tried to identify first the sustainable supplier selection and monitoring & evaluation differentiating criteria, and then, how we can rank and rate the sustainable suppliers for developmental purposes in the monitoring & evaluation phase. 21 criteria were determined for sustainable supplier performance in monitoring & evaluation by a detailed literature review and taking the opinions of the focal company. Then, decision makers assessed sustainability dimensions and determined criteria related to these dimensions. The weights of dimensions and criteria were calculated by Interval-Valued Intuitionistic Fuzzy AHP method. Then, sustainability performances of selected suppliers from the focal company’s portfolio were ranked by using Fuzzy EDAS, Fuzzy CODAS and Fuzzy MOORA methods. The results show that sustainable supplier monitoring & evaluation criteria involve a mix of external criteria (rules and regulations) and internal criteria (suppliers’ values). This finding helps us understand how we can have a more relaxed criteria set involving basic external criteria while selecting suppliers to have access to a more innovative and diverse supplier space and then have more challenging internal and external criteria to monitor & evaluate those suppliers toward true sustainability.
Modified Hawking temperatures of black holes in Lorentz violation theory
Authors: Christina S. , Singh T. Ibungochouba , Meitei I. Ablu
Published: October 2022

In this paper, the tunneling of scalar particles near the event horizons of Riemann space time, BTZ black hole and Schwarzschild–de Sitter black hole are investigated by applying Hamilton–Jacobi equation with Lorentz violation theory in curved space time. The modified Hamilton–Jacobi equation is derived from Klein–Gordon equation of scalar particles induced by Lorentz violation theory in curved space time. The Hawking temperatures of Riemann space time and the BTZ black hole are modified due to the effect of Lorentz violation theory. Moreover, the Bekenstein–Hawking entropy near the event horizon of Schwarzschild–de Sitter black hole is also modified due to Lorentz violation theory. It is observed that the modified values of Hawking temperatures and change in Bekenstein–Hawking entropy depend upon the ether-like vectors [Formula: see text].
Prosodic Prominence Across Languages
Authors: Ladd D. Robert , Arvaniti Amalia
Published: October 2022

Current empirical work on prosodic prominence is based on theoretical developments in the mid-twentieth century, in which a generalized notion of stress (in word pairs like English insight/incite and in sentence pairs like THEY left/they LEFT) was replaced by a distinction between an abstract notion of word stress and a concrete notion of phrasal accent or prominence that applies to specific words in an utterance. Much research since then has focused on phonetic and other cues that signal such prominence. Early findings emphasized the role of intonational pitch movements; more recent research demonstrates the importance of other phonetic cues, categorical differences between pitch movement types, and nonphonetic factors like word frequency. However, the definition of prominence itself remains informal and depends on intuitions that are well motivated primarily in European languages. Recent findings point to important differences between languages. These might be accommodated in a more comprehensive theory of word and sentence stress that treats both as manifestations of a hierarchical prosodic structure of the sort assumed in metrical phonology, while at the same time allowing for significant differences of prosodic typology.
Orchestration of Collective Migration and Metastasis by Tumor Cell Clusters
Authors: Yamamoto Ami , Doak Andrea E. , Cheung Kevin J.
Published: October 2022

Metastatic dissemination has lethal consequences for cancer patients. Accruing evidence supports the hypothesis that tumor cells can migrate and metastasize as clusters of cells while maintaining contacts with one another. Collective metastasis enables tumor cells to colonize secondary sites more efficiently, resist cell death, and evade the immune system. On the other hand, tumor cell clusters face unique challenges for dissemination particularly during systemic dissemination. Here, we review recent progress toward understanding how tumor cell clusters overcome these disadvantages as well as mechanisms they utilize to gain advantages throughout the metastatic process. We consider useful models for studying collective metastasis and reflect on how the study of collective metastasis suggests new opportunities for eradicating and preventing metastatic disease.
Procalcitonin and High APACHE (Acute Physiological and Chronic Health Evaluation) Level Are Associated with the Course of Acute Kidney Injury in Patients with SARS-CoV-2
Authors: Andrade Sierra Jorge , Delgado Astorga Claudia , Nava Vargas Miriam Gabriela , Rojas Campos Enrique , Arrelano Arteaga Kevin Javier , Hernández Morales Karla , Andrade Castellanos Carlos A. , Andrade-Ortega Antonio de Jesús , González Correa Luis Gerardo
Published: October 2022

Background. Acute kidney injury (AKI) is associated with poor outcomes in patients infected with SARS-CoV-2. Sepsis, direct injury to kidney cells by the virus, and severe systemic inflammation are mechanisms implicated in its development. We investigated the association between inflammatory markers (C-reactive protein, procalcitonin, D-dimer, lactate dehydrogenase, and ferritin) in patients infected with SARS-CoV-2 and the development of AKI. Methods. A prospective cohort study performed at the Civil Hospital (Dr. Juan I. Menchaca) Guadalajara, Mexico, included patients aged >18 years with a diagnosis of SARS-CoV-2 pneumonia confirmed by RT-PCR and who did or did not present with AKI (KDIGO) while hospitalized. Biomarkers of inflammation were recorded, and kidney function was estimated using the CKD-EPI formula. Results. 291 patients were included (68% males; average age, 57 years). The incidence of AKI was 40.5% (118 patients); 21% developed stage 1 AKI, 6% developed stage 2 AKI, and 14% developed stage 3 AKI. The development of AKI was associated with higher phosphate (

p
=
0.002

) (RR 1.39, CI 95% 1.13–1.72), high procalcitonin levels at hospital admission (

p
=
0.005

) (RR 2.09, CI 95% 1.26–3.50), and high APACHE scores (

p
=
0.011

) (RR 2.0, CI 95% 1.17–3.40). The survival analysis free of AKI according to procalcitonin levels and APACHE scores demonstrated a lower survival in patients with procalcitonin >0.5 ng/ml (

p
=
0.001

) and APACHE >15 points (

p
=
0.004

). Conclusions. Phosphate, high procalcitonin levels, and APACHE levels >15 were predictors of AKI development in patients hospitalized with COVID-19.
Molecular Assessment of Domain I of Apical Membrane Antigen I Gene in Plasmodium falciparum: Implications in Plasmodium Invasion, Taxonomy, Vaccine Development, and Drug Discovery
Authors: Achungu Che Roland , Anong Damian Nota , Shey Robert Adamu , Tabe Cevie Jesenta
Published: October 2022

Given its global morbidity and mortality rates, malaria continues to be a major public health concern. Despite significant progress in the fight against malaria, efforts to control and eradicate the disease globally are in jeopardy due to lack of a universal vaccine. The conserved short peptide sequences found in Domain I of Plasmodium falciparum apical membrane antigen 1 (PfAMA1), which are exposed on the parasite cell surface and in charge of Plasmodium falciparum invasion of host cells, make PfAMA1 a promising vaccine candidate antigen. The precise amino acids that make up these conserved short peptides are still unknown, and it is still difficult to pinpoint the molecular processes by which PfAMA1 interacts with the human host cell during invasion. The creation of a universal malaria vaccine based on the AMA1 antigen is challenging due to these knowledge limitations. This study used genome mining techniques to look for these particular short peptides in PfAMA1. Thirty individuals with Plasmodium falciparum malaria had blood samples taken using Whatman’s filter papers. DNA from the parasite was taken out using the Chelex technique. Domain I of the Plasmodium falciparum AMA1 gene was amplified using nested polymerase chain reactions, and the amplified products were removed, purified, and sequenced. The DNA sequence generated was converted into the matching amino acid sequence using bioinformatic techniques. These amino acid sequences were utilized to search for antigenic epitopes, therapeutic targets, and conserved short peptides in Domain I of PfAMA1. The results of this investigation shed important light on the molecular mechanisms behind Plasmodium invasion of host cells, a potential PfAMA1 vaccine antigen sequence, and prospective malaria treatment options in the future. Our work offers fresh information on malaria medication and vaccine research that has not been previously discussed.
Load Balancing Algorithms for Hadoop Cluster in Unbalanced Environment
Authors: Fu Weiyu , Wang Lixia
Published: October 2022

Considering that in the process of job scheduling, the cluster load should be prebalanced rather than remedied when the load is seriously unbalanced; therefore, in this paper, the task scheduling flow of the Hadoop cluster is analyzed deeply. On the Hadoop platform, a self-dividing algorithm is proposed for load balancing. An intelligent optimization algorithm is used to solve load balance. A dynamic feedback load balancing scheduling method is proposed from the point of view of task scheduling. In order to solve the shortcoming of the fair scheduling algorithm, this paper proposes two ways to improve the resource utilization and overall performance of Hadoop. When the mapping task is completed and the tasks to be reduced are assigned, the task assignment is based on the performance of the nodes to be reduced. It gives full play to the advantages of the ant colony algorithm and the hive colony algorithm so that the fusion algorithm can better deal with load balance. Then, three existing scheduling algorithms are introduced in detail: single queue scheduling, capacity scheduling, and fair scheduling. On this basis, an improved task scheduling strategy based on genetic algorithm is proposed to allocate and execute application tasks to reduce task completion time. The experiment verifies the effectiveness of the algorithm. The LBNP algorithm greatly improves the efficiency of reducing task execution and job execution. The delay capacity scheduling algorithm can ensure that most tasks can achieve localization scheduling, improve resource utilization, improve load balance, and speed up job completion time.
Discrete Analogues of the Erdélyi Type Integrals for Hypergeometric Functions
Authors: Vyas Yashoverdhan , Bhatnagar Anand V. , Fatawat Kalpana , Suthar D. L. , Purohit S. D.
Published: October 2022

Gasper followed the fractional calculus proof of an Erdélyi integral to derive its discrete analogue in the form of a hypergeometric expansion. To give an alternative proof, we derive it by following a procedure analogous to a triple series manipulation‐based proof of the Erdélyi integral, due to “Joshi and Vyas”. Motivated from this alternative way of proof, we establish the discrete analogues corresponding to many of the Erdélyi type integrals due to “Joshi and Vyas” and “Luo and Raina” in the form of new hypergeometric expansion formulas. Moreover, the applications of investigated discrete analogues in deriving some expansion formulas involving orthogonal polynomials of the Askey‐scheme and a new generalization of Whipple’s transformation for a balanced 4F3 in the form of an  m + 4Fm + 3 transformation, are also discussed.
A Novel Affective Analysis System Modeling Method Integrating Affective Cognitive Model and Bi-LSTM Neural Network
Authors: Yang Zhuqing , Zhou Liya , Jing Zhengjun
Published: October 2022

The severity of mental health issues among college students has increased over the past few years, having a significant negative impact on not only their academic performance but also on their families and even society as a whole. Therefore, one of the pressing issues facing college administrators right now is finding a method that is both scientific and useful for determining the mental health of college students. In pace with the advancement of Internet technology, the Internet has become an important communication channel for contemporary college students. As one of the main forces in the huge Internet population, college students are at the stage of growing knowledge and being most enthusiastic about new things, and they like to express their opinions and views on study life and social issues and are brave to express their emotions. These subjective text data often contain some affective tendencies and psychological characteristics of college students, and it is beneficial to dig out their affective tendencies to further understand what they think and expect and to grasp their mental health as early as possible. In order to address the issue of assessing the mental health of college students, this study makes an effort to use public opinion data from the university network and suggests a college student sentiment analysis model based on the OCC affective cognitive model and Bi-LSTM neural network. In order to label three different types of positive, negative, and neutral sentiment on the microblog text of college network public opinion, we first design a sentiment rule system based on the OCC affective cognition elicitation mechanism. In order to effectively and automatically identify the sentiment state of college students in the network public opinion, this study uses a Bi-LSTM neural network to classify the preprocessed college network public opinion data. Finally, this study performs comparison experiments to confirm the validity of the Bi-LSTM neural network sentiment recognition algorithm and the accuracy of the OCC sentiment rule labeling system. The findings show that the college student sentiment recognition effect of the model is significantly enhanced when the OCC sentiment rule system is used to label the college network public opinion data set as opposed to the naturally labeled data set. In contrast to SVM and other classification models like CNN and LSTM, the Bi-LSTM neural network-based classification model achieves more satisfactory classification results in the recognition of college opinion sentiment.
Experimental Study on Mechanism of Graphene Oxide-Modified Coral Sand Cement Mortar to Resist Sulfate Erosion
Authors: Chen Bin , Zhang Jianlin , Zhao Yanlin , Lu Yiwei
Published: October 2022

Coral sand particles with low strength and rich pores affect the mechanical properties and durability of their cement-based materials. This paper investigates the mechanical properties and internal pore evolution of graphene oxide-modified coral sand cement mortar under sulfate erosion environment, aiming to better understand the effect of graphene oxide on the mechanical properties of coral sand cement mortar under an erosion environment, especially in wet and dry cycles. Mechanical properties of coral sand cement mortar were tested with different amounts of graphene oxide and different erosion cycles to understand the relationship between the change of flexural and compressive strength and the content and erosion cycle. The microscopic parameters of hydration products and internal dissolution pores were analyzed by XRD and SEM. The results showed that the degree of erosion performance improvement is related to the content of GO, and the two are positively correlated at first and then negatively correlated. At 0.03 wt% content, the retardation effect is the best. There were more orderly pore arrangement with less morphological complexity, when the dissolution amount of Ca(OH)2, porosity, total pore area, pore number, probability entropy, average form factor, and fractal dimension decreased. Coral sand cement mortar increases resistance to sulfate attack, which graphene oxide inhibits the formation of new dissolution pores and the expansion of original pores.
An Overview of the Application of Harmony Search for Chemical Engineering Optimization
Authors: Fonseca-Pérez R. M. , Del-Mazo-Alvarado O. , Meza-de-Luna A. , Bonilla-Petriciolet A. , Geem Z. W.
Published: October 2022

Harmony search algorithm and its variants have been used in several applications in medicine, telecommunications, computer science, and engineering. This article reviews the global and multi-objective optimization for chemical engineering using harmony search. The main features of the HS method and several of its popular variants and hybrid versions including their relevant algorithm characteristics are described and discussed. A variety of global and multi-objective optimization problems from chemical engineering and their resolution using HS-based methods are also included. These problems involve thermodynamic calculations (phase stability analysis, phase equilibrium calculations, parameter estimation, and azeotrope calculation), heat exchanger design, distillation simulation, life cycle analysis, and water distribution systems, among others. Remarks on future developments of HS and its related algorithms for global and multi-objective optimization in chemical engineering are also provided in this review. HS is a reliable and promising stochastic optimizer to resolve challenging global and multi-objective optimization problems for process systems engineering.
Functional Localization of Adult-Onset Idiopathic Nesidioblastosis
Authors: Hercus Jess C. , Pasha Pouneh , Al Lawati Sadiq , Kim Peter , Mattman Andre , Webber Douglas , Thompson David M.
Published: October 2022

Nesidioblastosis is a rare pancreatic disorder involving enlarged beta cells throughout the pancreas, causing elevated insulin production. We present the case of a 53-year-old woman with the initial symptom of fasting hypoglycemia. No pancreatic lesions were indicated on computed tomography and magnetic resonance imaging scans, and an octreotide scan was negative for insulinoma. Selective arterial calcium stimulation (SACST) showed increased insulin production from the stimulation of 3 out of 5 arteries. The SACST results suggested a diagnosis of nesidioblastosis, which was confirmed by histopathology after a subtotal distal pancreatectomy. The patient has normal glucose tolerance after surgery with no further problems of hypoglycemia, indicating that this is a rare case of nesidioblastosis extending only partially through the pancreas.
Vehicle Driving Risk Prediction Model by Reverse Artificial Intelligence Neural Network
Authors: Ding Huizhe , Raja Ghazilla Raja Ariffin , Kuldip Singh Ramesh Singh , Wei Lina
Published: October 2022

The popularity of private cars has brought great convenience to citizens’ travel. However, the number of private cars in society is increasing yearly, and the traffic pressure on the road is also increasing. The number of traffic accidents is increasing yearly, and the vast majority are caused by small private cars. Therefore, it is necessary to improve the traffic safety awareness of drivers and help car manufacturers to design traffic risk prediction systems. The Backpropagation neural network (BPNN) algorithm is used as the technical basis, combined with the MATLAB operation program, to simulate the driving process of the car. Dynamic predictive models are built to predict and analyze vehicle safety risks. Multiple experiments found that: (1) in various simulations, the simulation driving process of MATLAB is more in line with the actual car driving process; (2) the error between BPNN and the actual driving prediction is within 0.4, which can meet the actual needs. Predictive models are optimized to deploy and predict in various traffic situations. The model can effectively prompt risk accidents, reduce the probability of traffic accidents, provide a certain degree of protection for the lives of drivers and passengers, and significantly improve the safety of traffic roads.
In Vivo Antimalarial Activity of the Leaf Extract of Osyris quadripartita Salzm. ex Decne and Its Major Compound (–) Catechin
Authors: Kemal Teyiba , Feyisa Kebede , Bisrat Daniel , Asres Kaleab
Published: October 2022

Background. The leaves of Osyris quadripartita Salzm. ex Decne, endemic to Ethiopia, are traditionally used for the treatment of malaria. Previous phytochemical investigations of Osyris species showed the presence of flavonoids, anthracene derivatives, and sesquiterpene lactones as the main constituents. The aim of the present study was to investigate the antimalarial activity of the leaf extract of O. quadripartita and its isolated constituent against mice infected with Plasmodium berghei. Methods. Isolation of a compound was carried out on silica gel column chromatography of the extract eluting with gradient mixtures of CHCl3/MeOH. Structural elucidation of the isolated compound was achieved by ESI-MS and 1D-and 2D-NMR spectral data. Peter’s 4-day suppressive test method was used to determine the antimalarial activity of the test substances. Level of parasitemia, survival time, and body weight change were used to determine the antimalarial activity of the test substances. Results. (–) Catechin was isolated and characterized from the hydroalcoholic extract of O. quadripartita. At a concentration of 400 mg/kg, both the extract and (–) catechin exhibited antimalarial activity with the highest chemosuppression values of 70.61% and 64.26%, respectively. Conclusion. These findings indicate that O. quadripartita is endowed with genuine antimalarial activity attributed in part, to its (–) catechin content. Hence, the present study may validate the traditional use of the plant for the treatment of malaria.
Long-Term Zidovudine Therapy and Whether It is a Trigger of Vitamin B12 Deficiency: A Case Study of Megaloblastic Anemia at the University of Zambia Teaching Hospital
Authors: Kaweme Natasha Mupeta , Butress Sahar Mounir Nagib , Mantina Hamakwa Muluti
Published: October 2022

Macrocytic anemia is frequently observed in adult HIV-infected patients treated with nucleoside reverse transcriptase inhibitors and with vitamin B12 and folate deficiency. In this case report, we discuss a 52-year-old nonvegetarian male on long-term antiretroviral therapy for 5 years, presenting with severe macrocytic anemia (hemoglobin, 3.7 g/dL; mean corpuscular volume, 119.6 fL) and leukopenia (2.71

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109/L), who was diagnosed with megaloblastic anemia caused by vitamin B12 deficiency following laboratory investigations. Parenteral vitamin B12 replacement therapy was initiated, with an early response observed. Notwithstanding, the treatment response was not sustained as the patient later presented with refractory anemia and persistence of macrocytosis. Discontinuation of zidovudine with concurrent vitamin B12 administration promptly improved the patient’s clinical deficiency symptoms. At the end of 3 months, the patient had a complete hematological recovery. The deficiency of vitamin B12 disrupts DNA synthesis inhibiting effective hematopoiesis in all cell lines, particularly erythroid precursors and further promotes reversible bone marrow failure. Long-term ART therapy with zidovudine causes cytotoxicity in myeloid and erythroid precursors and induces bone marrow suppression. Whether long-term zidovudine consumption induced lower levels of vitamin B12 and subsequent megaloblastic anemia requires in-depth research and exploration.