bluuebunny/crossref_metadata_2025 huggingface dataset:
An innovative tool to assess the functional resilience of a school system: learning from the COVID-19 pandemic
Authors: Kaim Arielle , Siman-Tov Maya , Adini Bruria , Lev-ari Shahar
Published: November 2023

Introduction

Preparing the school system for a future crisis requires the ability to examine the effectiveness of schools’ functioning during distant learning and their level of preparedness for future crises. Functional resilience (FR) is defined as the ability to maintain vital operational continuity in the face of disturbance. The study objectives included to develop a FR index of schools and to evaluate and validate it.

Methods

To enable examination of the study objectives, the study design included tool development, followed by a validation process among 20 content experts. Concurrently, an eDelphi process for building an inclusive index, based on various components of resilience was conducted. The final study tool consists of four tailored questionnaires to examine perceptions of key stakeholders, i.e.- teachers, principals, parents, and highschool students regarding communication, psychosocial aspects, perceived stress, infrastructure, resources, pedagogic support, digital literacy, and perceived FR. Using an internet panel, the tool was disseminated cross-sectionally among the four groups of stakeholders.

Results

The results showed high reliability of most of the scales developed. Furthermore, a high consensus level was reached on the relative importance of each component/ stakeholder to the schools FR. The findings further suggest that there were no significant differences in the composite FR score based on characteristics such as school type/ size/geographic location. However, the findings revealed interesting variations among stakeholders, with findings suggesting greater vulnerability among some.

Discussion

To increase resilience and preparedness for future adversities that school systems may face, it is recommended to periodically incorporate an assessment based on a structured tool.
Depression and perceived stress among perinatal women living with HIV in Nigeria
Authors: Akinsolu Folahanmi T. , Abodunrin Olunike R. , Lawale Abisola A. , Bankole Samuel A. , Adegbite Zaniab O. , Adewole Ifeoluwa E. , Olagunju Mobolaji T. , Ola Oluwabukola M. , Dabar Anita M. , Sanni-Adeniyi Rukayat A. , Gambari Aisha O. , Njuguna Diana Wangeshi , Salako Abideen O. , Ezechi Oliver C.
Published: November 2023

Background

Pregnancy and postpartum periods are crucial stages for women’s mental health, and women living with HIV are particularly susceptible to depression and psychological stress due to various factors. This study investigated the prevalence and associated factors of depression and perceived stress among women living with HIV during their perinatal period in Ibadan, Nigeria.

Methods

A cross-sectional survey was conducted in three HIV treatment centers in Ibadan, Nigeria, among women living with HIV between the ages of 19 and 49 who were either pregnant or had given birth within the last 2 years. The study was conducted from September 2022 to December 2022. An interviewer-administered questionnaire was used to collect the data from the participants. Ethical approval and informed consent were obtained, and data were analyzed using the Statistical Package for Social Science version 26.

Results

The study included 402 participants, of whom 69.0 and 78.0% reported symptoms of depression and perceived stress, respectively. However, 15.2% of the participants have comorbid depression and stress. Positive partner status was significantly associated with lower perceived depression, while gestational age between 29 and 40 weeks was significantly associated with lower perceived stress. The co-occurrence of depression and perceived stress was associated with partner status, income level, family support, gestational age, and years on antiretroviral therapy.

Conclusion

The high prevalence of depression, perceived stress, and their co-occurrence among women living with HIV during the perinatal period call for incorporating mental health care into routine maternal healthcare for all women, particularly those living with HIV. This finding emphasizes the need for public health efforts to prioritize perinatal mental health and improve access to care and support for women and their partners.
Epidemiology and grade 2 disability of leprosy among migrant and resident patients in Guangdong: an unignorable continued transmission of leprosy
Authors: Chen Lei , Zheng Daocheng , Li Ming , Zeng Meiling , Yang Bin , Wang Xiaohua
Published: November 2023

Introduction

Leprosy remains a major public health concern worldwide and one of the leading causes of disability. New cases of leprosy with grade 2 disability (G2D) often reflect delayed detection due to the limited capacity of the health system to recognize leprosy early. This study aimed to describe the epidemiology and G2D of leprosy among migrant and resident patients with leprosy in Guangdong province, China.

Methods

Data on newly diagnosed cases of leprosy were collected from the leprosy management information system in China. Descriptive statistical analysis was used to describe the status of G2D. Joinpoint regression model and logistic regression were performed to analyze the temporal trends and influencing factors for G2D.

Results

The G2D rate among migrant, resident, and total patients with leprosy was 17.5%, 18.7%, and 18.4%, respectively. The total G2D rate increased significantly from 18.0% in 2001 to 25.7% in 2021 (average annual per cent change: 2.5%). Multivariate analysis revealed that factors that negatively influence G2D between migrant and resident patients included delayed discovery time (migrants: OR = 2.57; residents: OR = 4.99) and nerve damage when diagnosed (migrants: OR = 9.40; residents: OR = 21.28).

Discussion

Our findings indicate that the targeted intervention measures implemented by our health system are urgently needed to improve the current situation, such as programs to promote early detection, strengthen awareness and skills of healthcare workers, and rehabilitation for disabled patients to improve their quality of life.
An algorithm for computing Schubert varieties of best fit with applications
Authors: Karimov Karim , Kirby Michael , Peterson Chris
Published: November 2023

We propose the geometric framework of the Schubert variety as a tool for representing a collection of subspaces of a fixed vector space. Specifically, given a collection of l-dimensional subspaces V1, …, Vr of ℝn, represented as the column spaces of matrices X1, …, Xr, we seek to determine a representative matrix K∈ℝn×k such that each subspace Vi intersects (or comes close to intersecting) the span of the columns of K in at least c dimensions. We formulate a non-convex optimization problem to determine such a K along with associated sets of vectors {ai} and {bi} used to express linear combinations of the columns of the Xi that are close to linear combinations of the columns of K. Further, we present a mechanism for integrating this representation into an artificial neural network architecture as a computational unit (which we refer to as an abstract node). The representative matrix K can be learned in situ, or sequentially, as part of a learning problem. Additionally, the matrix K can be employed as a change of coordinates in the learning problem. The set of all l-dimensional subspaces of ℝn that intersects the span of the columns of K in at least c dimensions is an example of a Schubert subvariety of the Grassmannian GR(l, n). When it is not possible to find a Schubert variety passing through a collection of points on GR(l, n), the goal of the non-convex optimization problem is to find the Schubert variety of best fit, i.e., the Schubert variety that comes as close as possible to the points. This may be viewed as an analog of finding a subspace of best fit to data in a vector space. The approach we take is well-suited to the modeling of collections of sets of data either as a stand-alone Schubert variety of best fit (SVBF), or in the processing workflow of a deep neural network. We present applications to some classification problems on sets of data to illustrate the behavior of the method.
Prediction of progression from mild cognitive impairment to Alzheimer's disease with longitudinal and multimodal data
Authors: Ding Huitong , Wang Biqi , Hamel Alexander P. , Melkonyan Mark , Ang Ting F. A. , Au Rhoda , Lin Honghuang
Published: November 2023

Introduction

Accurate prediction of the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) within a certain time frame is crucial for appropriate therapeutic interventions. However, it is challenging to capture the dynamic changes in cognitive and functional abilities over time, resulting in limited predictive performance. Our study aimed to investigate whether incorporating longitudinal multimodal data with advanced analytical methods could improve the capability to predict the risk of progressing to AD.

Methods

This study included participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI), a large-scale multi-center longitudinal study. Three data modalities, including demographic variables, neuropsychological tests, and neuroimaging measures were considered. A Long Short-Term Memory (LSTM) model using data collected at five-time points (baseline, 6, 12, 18, and 24-month) was developed to predict the risk of progression from MCI to AD within 2 years from the index exam (the exam at 24-month). In contrast, a random forest model was developed to predict the risk of progression just based on the data collected at the index exam.

Results

The study included 347 participants with MCI at 24-month (age: mean 75, SD 7 years; 39.8% women) from ADNI, of whom 77 converted to AD over a 2-year follow-up period. The longitudinal LSTM model showed superior prediction performance of MCI-to-AD progression (AUC 0.93 ± 0.06) compared to the random forest model (AUC 0.90 ± 0.09). A similar pattern was also observed across different age groups.

Discussion

Our study suggests that the incorporation of longitudinal data can provide better predictive performance for 2-year MCI-to-AD progression risk than relying solely on cross-sectional data. Therefore, repeated or multiple times routine health surveillance of MCI patients are essential in the early detection and intervention of AD.
Mass spectrometry-based proteomics for advancing solid organ transplantation research
Authors: Huang Che-Fan , Su Pei , Fisher Troy D. , Levitsky Josh , Kelleher Neil L. , Forte Eleonora
Published: November 2023

Scarcity of high-quality organs, suboptimal organ quality assessment, unsatisfactory pre-implantation procedures, and poor long-term organ and patient survival are the main challenges currently faced by the solid organ transplant (SOT) field. New biomarkers for assessing graft quality pre-implantation, detecting, and predicting graft injury, rejection, dysfunction, and survival are critical to provide clinicians with invaluable prediction tools and guidance for personalized patients' treatment. Additionally, new therapeutic targets are also needed to reduce injury and rejection and improve transplant outcomes. Proteins, which underlie phenotypes, are ideal candidate biomarkers of health and disease statuses and therapeutic targets. A protein can exist in different molecular forms, called proteoforms. As the function of a protein depends on its exact composition, proteoforms can offer a more accurate basis for connection to complex phenotypes than protein from which they derive. Mass spectrometry-based proteomics has been largely used in SOT research for identification of candidate biomarkers and therapeutic intervention targets by so-called “bottom-up” proteomics (BUP). However, such BUP approaches analyze small peptides in lieu of intact proteins and provide incomplete information on the exact molecular composition of the proteins of interest. In contrast, “Top-down” proteomics (TDP), which analyze intact proteins retaining proteoform-level information, have been only recently adopted in transplantation studies and already led to the identification of promising proteoforms as biomarkers for organ rejection and dysfunction. We anticipate that the use of top-down strategies in combination with new technological advancements in single-cell and spatial proteomics could drive future breakthroughs in biomarker and therapeutic target discovery in SOT.
Technological potential of native lactic acid bacteria isolated from Swiss-type artisanal cheese (Ancash, Peru) for their application in food
Authors: Valdiviezo-Marcelo Jaime , Arana-Torres Nancy Maribel , Vega-Portalatino Edwin Jorge , Ruiz-Flores Luis Alberto , Tamariz-Angeles Carmen , Olivera-Gonzales Percy , Rosales-Cuentas Miriam Marleni , Espinoza-Espinoza Luis Alfredo
Published: November 2023

Swiss-type artisanal cheese is highly appreciated sensorially, its flavor is often associated with the lactic acid bacteria involved in its production, which in many cases are indigenous. Three artisanal Swiss-type cheeses of greatest preference in the market of Huaraz (Ancash) were selected. The main LAB were isolated and identified and their safety properties and technological potential for their application in new cheeses were verified in vitro and evaluated by consumers. Eleven strains were confirmed as LAB by Gram-positive and catalase-negative biochemical tests; according to 16S rDNA, seven strains belonged to Lacticaseibacillus paracasei (KQ3, EQ1, CQ1, YQ1, LQ2, GQ2 and TQ1), three strains to Lentilactobacillus parabuchneri (BQ2, OQ2 and RQ3), and one to Lactiplantibacillus sp. (QQ3). In safety assays, LAB did not exhibit gelatinase or hemolytic activities. In addition, L. paracasei KQ3, GQ2 and L. parabuchneri BQ2 effectively inhibited pathogens such as S. aureus, E. coli and L. monocytogenes. Antibiotic susceptibility was variable among strains. L. paracasei CQ1, EQ1, KQ3, TQ1 and Lactiplantibacillus sp. QQ3 showed high milk acidification capacity (0.16-1.44%) and reduced pH from 6.6 to 3.5 after 72 h of incubation. L. paracasei CQ1, Lactiplantibacillus sp. QQ3 and L. paracasei KQ3 showed the highest casein degradation zones (20.8-11.5 mm). All strains showed lipolytic activity, with Lactiplantibacillus sp. QQ3, L. paracasei CQ1 and L. parabuchneri BQ2 standing out with halos of 30.8-36.3 mm. Lactiplantibacillus sp. QQ3 and L. paracasei TQ1 showed ability to produce diacetyl. The best strains were tested in cheese production where L. paracasei CQ1 showed the best sensory qualities. Finally, the native BAL strains showed a high potential for the production of natural, safe and sensorially acceptable dairy products.
A pharmacokinetic study on red ginseng with furosemide in equine
Authors: Kwak Young Beom , Lee Eunkyu , Choi Hyunjoo , Park Taemook , Kim Ahram , Kim Jungon , Yoon Jungho , Yoo Hye Hyun
Published: November 2023

Red ginseng (RG) is a popular ingredient in traditional Korean medicine that has various health benefits. It is commonly taken orally as a dietary supplement; however, its potential interactions with concomitantly administered drugs are unclear. In this study, we examined the pharmacokinetic interaction between furosemide and RG in equine plasma. Liquid chromatography with tandem mass spectrometry analysis was performed to evaluate ginsenosides in the plasma of horses after feeding them RG and furosemide and validate the results. A single bolus of furosemide (0.5 mg/kg) was administered intravenously to female horses that had consumed RG (600 mg/kg/day) every morning for 3 weeks (experimental group), and blood samples were collected from 0 to 24 h, analyzed, and compared with those from female horses that did not consume RG (control group). Four (20s)-protopanaxadiol ginsenosides (Rb1, Rb2, Rc, and Rd) were detected in the plasma. Rb1 and Rc individually showed a high concentration distribution in the plasma. The Cmax, AUC0−t, and AUC0−∞ of furosemide was significantly increased in the experimental group (p < 0.05), while the CL, Vz, and Vss was decreased (p < 0.05, p < 0.01). These changes indicate the potential for pharmacokinetic interactions between furosemide and RG.
Plasma Actuators for Cycloidal Rotor Thrust Vectoring Enhancement in Airships
Authors: Benmoussa Amine , Rodrigues Frederico F. , Páscoa José C.
Published: November 2023

Airships are a method of transportation with reduced fuel consumption and great potential for different applications. However, these aerial vehicles still present considerable control and maneuverability problems. To overcome these issues, in the current work, we propose the use of plasma-enhanced cycloidal rotor thrusters to increase the controllability and maneuverability of airships. Numerical simulations are carried out to demonstrate the potential of plasma actuators to enhance the efficiency and thrust vectoring capabilities of cycloidal rotors. The fluid dynamics of the flow effects created via the operation of the cycloidal rotor is analyzed with and without plasma actuation. In addition, smart combined plasma actuation is proposed to further optimize the plasma-coupled cycloidal rotor device. The results demonstrated that by using this novel approach, the lift coefficient was increased by about 27%. To summarize, the obtained results for a rotational speed of 100 rpm are compared with results for 200 rpm, and it is demonstrated that for lower rotational speeds, the plasma effect is increased and more significant. This allows us to conclude that airships are an ideal application for plasma-enhanced cycloidal rotors, because since the lift is mostly generated via aerostatic principles, the plasma-enhanced thruster can be operated at lower rotational speeds and effectively increase the controllability and maneuverability of the aerial vehicle.
Suction Control of a Boundary Layer Ingestion Inlet
Authors: Liu Lei , Li Guozhan , Wang Ban , Wu Shaofeng
Published: November 2023

This study presents a numerical investigation of suction control in an aggressive S-shaped air intake with large boundary ingestion. The results show that the variation of suction control parameters such as suction location, suction pipe diameter, and suction angle all have an impact on the effectiveness of the flow control. In general, further upstream suction, such as near the throat, is favorable for the decrease of the second flow intensity and the area of the low-energy fluid region at the exit of the S-shaped inlet. However, it is bad for the total pressure recovery and the circumferential total pressure uniform distribution. From the perspective of the uniformity of the total pressure distribution at the air intake exit, there is an optimal location for suction between the throat and the separation start point. A bigger suction pipe diameter brings better effects as the suction location and suction angle keep constant, due to more low-energy fluid being sucked out. But this doesn’t mean the largest mass flow suction results in the biggest improvement. Overall, sucking at the 1st bend, with suction angle and suction pipe diameter equaling 15 degrees and 12 mm, respectively, is the optimal suction scheme here. Since the change rule of the cross-section area along the centerline has not changed during suction control, the second flow and complex surface streamline at the air intake exit cannot be eliminated, though they can be decreased a lot with reasonable suction control. Similarly, owing to large boundary ingestion, the remarkable low-energy fluid region always exists despite the significant reduction of the separation and second flow, which is very different from the results of this kind of micro-suction executed in the non-BLI S-duct. To pursue a higher improvement, suction combined with vortex generator vanes has been further studied. Corresponding results analysis shows that the hybrid flow control method has great potential and should be investigated in detail in the future.
Profitability, Productivity, and Technical Efficiency of Cretan Olive Groves across Alternative Ecological Farm Types
Authors: Sintori Alexandra , Konstantidelli Vasilia , Gouta Penelope , Tzouramani Irene
Published: November 2023

Olive groves are an important element of the Mediterranean landscape and heritage and contribute significantly to the area’s rural economies. The primary interest of researchers and policymakers lies in the economic performance of this activity, especially in light of the resource limitations imposed by climate change. Profitability and productivity analyses, as well as technical efficiency methodologies, have been applied to evaluate the economic sustainability of olive cultivation and have often identified shortcomings in farms’ management and structure. In our study, we use profitability and productivity indicators, as well as data envelopment analysis, to estimate the economic performance of Cretan olive groves and a second-stage regression analysis to determine factors that affect efficiency scores. One novelty of this study is that the results are presented across alternative ecological approaches, i.e., organic, conservation, low-input, and standard farms. Our findings indicate that organic farms perform better in the examined economic indicators. On the other hand, standard farms demonstrate a low labour productivity, while conservation and low-input farms exhibit an inefficient use of capital. Scale inefficiencies indicate that certain farm types should also increase in size to be more competitive. Finally, our analysis suggests that training, market orientation, and a commitment to farming positively affect the efficiency of olive groves.
Soil Water and Salt Transport in Severe Saline–Alkali Soil after Ditching under Subsurface Pipe Drainage Conditions
Authors: Tian Feng , Shi Haibin , Miao Qingfeng , Li Ruiping , Duan Jie , Dou Xu , Feng Weiying
Published: November 2023

The subsurface pipe drainage project is essential in farmland drainage operations and is globally recognized as an effective saline–alkali land improvement measure owing to its efficient drainage capacity and low land occupation rate. This study aimed to establish enhanced methods for improving saline–alkali land by combining ditching with subsurface pipe drainage. The ditching was conducted at a depth of 60 cm based on the existing subsurface pipe arrangement. The calibrated DRAINMOD-S model was employed to simulate the test area with different ditching depths and subsurface pipe arrangement parameters. Furthermore, the law of soil water and salt transport in the subsurface pipe drainage system at different ditching depths was investigated. After ditching, the total unit drainage volume of leaching increased by an average of 14.65% over two years and the water storage of different soil layers in the different plots decreased by 1.37–1.48 mm on average. Ditching demonstrated a superior salt-leaching effect in areas with subsurface pipe layouts. The soil desalination rate of different soil layers increased by 6.40–13.40% on average, with a more significant impact on the surface soil desalination rate. The effect of the increased desalination rate was more apparent as the ditching depth increased. However, as the buried depth of the subsurface pipe increased, the relationship between the ditching depth and soil desalination rate became insignificant. Ditching improved the salt-leaching effect of subsurface pipe drainage projects, which can effectively reduce the cost of subsurface pipe burial, consequently promoting subsurface pipe use.
Monitoring Indicators for Comprehensive Growth of Summer Maize Based on UAV Remote Sensing
Authors: Ma Hao , Li Xue , Ji Jiangtao , Cui Hongwei , Shi Yi , Li Nana , Yang Ce
Published: November 2023

Maize is one of the important grain crops grown globally, and growth will directly affect its yield and quality, so it is important to monitor maize growth efficiently and non-destructively. To facilitate the use of unmanned aerial vehicles (UAVs) for maize growth monitoring, comprehensive growth indicators for maize monitoring based on multispectral remote sensing imagery were established. First of all, multispectral image data of summer maize canopy were collected at the jointing stage, and meanwhile, leaf area index (LAI), relative chlorophyll content (SPAD), and plant height (VH) were measured. Then, the comprehensive growth monitoring indicators CGMICV and CGMICR for summer maize were constructed by the coefficient of variation method and the CRITIC weighting method. After that, the CGMICV and CGMICR prediction models were established by the partial least-squares (PLSR) and sparrow search optimization kernel extremum learning machine (SSA-KELM) using eight typical vegetation indices selected. Finally, a comparative analysis was performed using ground-truthing data, and the results show: (1) For CGMICV, the R2 and RMSE of the model built by SSA-KELM are 0.865 and 0.040, respectively. Compared to the model built by PLSR, R2 increased by 4.5%, while RMSE decreased by 0.3%. For CGMICR, the R2 and RMSE of the model built by SSA-KELM are 0.885 and 0.056, respectively. Compared to the other model, R2 increased by 4.6%, and RMSE decreased by 2.8%. (2) Compared to the models by single indicator, among the models constructed based on PLSR, the CGMICR model had the highest R2. In the models constructed based on SSA-KELM, the R2 of models by the CGMICR and CGMICV were larger than that of the models by SPAD (R2 = 0.837), while smaller than that of the models by LAI (R2 = 0.906) and models by VH (R2 = 0.902). In summary, the comprehensive growth monitoring indicators prediction model established in this paper is effective and can provide technical support for maize growth monitoring.
Hemosiderin-Laden Macrophages in Canine Mammary Carcinomas
Authors: Giambrone Giada , Vullo Cecilia , Puleio Roberto , Rifici Claudia , Di Giorgio Stefania , Sfacteria Alessandra
Published: November 2023

Macrophages are among the main actors in cancer immunoediting, with several functions, including recycling iron and packaging it in hemosiderin. Even though TAMs are widely studied in breast cancer and canine mammary tumors, hemosiderin-laden macrophages (HLMs) have not received as much attention. Considering the growing interest in iron metabolism in cancer, this study aims to evaluate the presence of HLMs in canine mammary tumors. Fifty cases of canine mammary carcinomas presenting aggregates of pigmented macrophages were chosen. Prussian blue and Meguro staining were performed to assess the presence of iron. Immunohistochemistry was carried out to try to identify macrophagic phenotypes and hypothesize their role. Evaluation of the H&E sections showed that pigmented macrophages were variously localized in peritumoral and stromal areas. These pigmented cells were variably stained with Prussian blue and reacted strongly with DAB in the Meguro staining method, thus confirming the presence of iron within them. In their immunohistochemistry, the HLMs were negative for the MAC387 but positive for CD 204 and VEGF. Considering their positivity for CD 204, HLMs could be M2 macrophages that supply iron to both the neoplastic cells and the tumor inflammatory microenvironment, promoting angiogenesis and protecting cancer cells from hypoxia.
Valorization of Defatted Cherry Seed Residues from Liquor Processing by Matrix Solid-Phase Dispersion Extraction: A Sustainable Strategy for Production of Phenolic-Rich Extracts with Antioxidant Potential
Authors: Rodríguez-Blázquez Sandra , Fernández-Ávila Lorena , Gómez-Mejía Esther , Rosales-Conrado Noelia , León-González María Eugenia , Miranda Rubén
Published: November 2023

The integrated valorization of food chain waste is one of the most promising alternatives in the transition to a sustainable bioeconomy. Thus, an efficient solid-phase matrix dispersion extraction method, using experimental factorial design and response surface methodology, has been developed and optimized for the recovery of polyphenols from defatted cherry seeds obtained after cherry liquor manufacture and subsequent fatty acid extraction, evaluating the effect of each processing step on the composition and phenolic content of sweet cherry residues. The phenolic extracts before fermentation showed the highest content of total polyphenols (TPC) and flavonoids (TFC) (3 ± 1 mg QE·g−1 and 1.37 ± 0.08 mg GAE·g−1, respectively), while the highest antioxidant capacity was obtained in the defatted seed extracts after both fermentation and distillation. In addition, high-performance liquid chromatography coupled to a quadrupole time-of-flight mass spectrometer (HPLC-ESI-QTOF-MS) was used to determine the phenolic profile. Dihydroxybenzoic acid, neochlorogenic acid, caffeic acid, and quercetin were the main phenolics found, showing differences in concentration between the stages of liquor production. The results underline the prospective of cherry by-products for obtaining phenol-rich bioactive extracts for possible use in different industrial sectors, offering a feasible solution for the cascade valorization of cherry agri-food waste.
A Unified Vendor-Agnostic Solution for Big Data Stream Processing in a Multi-Cloud Environment
Authors: Vergilio Thalita , Kor Ah-Lian , Mullier Duncan
Published: November 2023

The field of cloud computing has witnessed tremendous progress, with commercial cloud providers offering powerful distributed infrastructures to small and medium enterprises (SMEs) through their revolutionary pay-as-you-go model. Simultaneously, the rise of containers has empowered virtualisation, providing orchestration technologies for the deployment and management of large-scale distributed systems across different geolocations and providers. Big data is another research area which has developed at an extraordinary pace as industries endeavour to discover innovative and effective ways of processing large volumes of structured, semi-structured, and unstructured data. This research aims to integrate the latest advances within the fields of cloud computing, virtualisation, and big data for a systematic approach to stream processing. The novel contributions of this research are: (1) MC-BDP, a reference architecture for big data stream processing in a containerised, multi-cloud environment; (2) a case study conducted with the Estates and Sustainability departments at Leeds Beckett University to evaluate an MC-BDP prototype within the context of energy efficiency for smart buildings. The study found that MC-BDP is scalable and fault-tolerant across cloud environments, key attributes for SMEs managing resources under budgetary constraints. Additionally, our experiments on technology agnosticism and container co-location provide new insights into resource utilisation, cost implications, and optimal deployment strategies in cloud-based big data streaming, offering valuable guidelines for practitioners in the field.
Multi-Resolution and Semantic-Aware Bidirectional Adapter for Multi-Scale Object Detection
Authors: Li Zekun , Pan Jin , He Peidong , Zhang Ziqi , Zhao Chunlu , Li Bing
Published: November 2023

Scale variation presents a significant challenge in object detection. To address this, multi-level feature fusion techniques have been proposed, exemplified by methods such as the feature pyramid network (FPN) and its extensions. Nonetheless, the input features provided to these methods and the interaction among features across different levels are limited and inflexible. In order to fully leverage the features of multi-scale objects and amplify feature interaction and representation, we introduce a novel and efficient framework known as a multi-resolution and semantic-aware bidirectional adapter (MSBA). Specifically, MSBA comprises three successive components: multi-resolution cascaded fusion (MCF), a semantic-aware refinement transformer (SRT), and bidirectional fine-grained interaction (BFI). MCF adaptively extracts multi-level features to enable cascaded fusion. Subsequently, SRT enriches the long-range semantic information within high-level features. Following this, BFI facilitates ample fine-grained interaction via bidirectional guidance. Benefiting from the coarse-to-fine process, we can acquire robust multi-scale representations for a variety of objects. Each component can be individually integrated into different backbone architectures. Experimental results substantiate the superiority of our approach and validate the efficacy of each proposed module.
A Novel Intelligent Anti-Jamming Algorithm Based on Deep Reinforcement Learning Assisted by Meta-Learning for Wireless Communication Systems
Authors: Chen Qingchuan , Niu Yingtao , Wan Boyu , Xiang Peng
Published: November 2023

In the field of intelligent anti-jamming, deep reinforcement learning algorithms are regarded as key technical means. However, the learning process of deep reinforcement learning algorithms requires a stable learning environment to ensure its effectiveness. Moreover, the inherent limitations of deep reinforcement learning algorithms mean that they can only demonstrate excellent learning capabilities on specific tasks with constant parameters. When parameters change, they can only resample and relearn to converge. In a changing jamming environment, its stability and convergence speed may be challenged, thereby affecting its robustness and generalization capabilities. Aiming at the naive yet unique similarity characteristics of the communication anti-jamming problem, this paper designs a new Meta-PPO deep reinforcement learning algorithm that combines Proximal Policy Optimization (PPO) and MAML meta-learning ideas. The proposed algorithm engrafts the principle of meta-learning used in the Model Agnostic Meta-Learning (MAML) model onto the Proximal Policy Optimization (PPO)-based schemes, enabling the communication systems to harness its prior learned experiences acquired from previous anti-jamming tasks to facilitate and speed up its optimal decision-making process when faced with incoming jamming attacks with similar features. The proposed algorithm is verified through computer simulation analyses and the results show that the proposed novel Meta-PPO algorithm can outperform traditional DQN- and PPO-based algorithms in terms of better robustness and generalization abilities, which can be used to enhance the anti-jamming capabilities of wireless communication systems.
Numerical Study on the Application of Near-Infrared Temperature Distribution Measurement of HIFU
Authors: Zhao Peng , Guo Xiaoan , Liu Wenjing , Shi Wanting , Wang Yuebing
Published: November 2023

Accurate temperature distribution measurement during high-intensity focused ultrasound (HIFU) treatment is crucial for avoiding damage to sensitive tissues and organ systems. To surpass the constraints of conventional thermocouple temperature measurement approaches, near-infrared temperature measurement, as a non-invasive imaging method, is proposed. Using infrared glass as a temperature observation window allows for studying the temperature distribution on the surface of biological tissues under ultrasound exposure. The temperature rise in the tissues near the infrared glass under ultrasound exposure was investigated through numerical simulations. Moreover, the effects of the shear waves and thermal viscosity induced by the infrared glass were also analyzed. The results indicate that the shear wave in the glass weakens the intensity of the ultrasound pressure in the focal region while enhancing the efficiency of the acoustic thermal conversion. Thermal viscosity increases the acoustic pressure and temperature in the focal zone. Furthermore, oblique incidence facilitates the transformation of the acoustic thermal effect, caused by shear waves and thermal viscosity, resulting in an expanded temperature rise range on the tissue surface. The non-linear effects in the ultrasound field further enhance the acoustic thermal effect. Significant errors occur in the near-infrared method when utilizing infrared glass for temperature measurement, with the shear waves exerting the most substantial impact on the temperature distribution. These research findings carry substantial implications for optimizing treatment plans, enhancing treatment safety and efficacy, and offering potential application value for temperature control in HIFU treatment.
Evaluation of Filtration Efficiency of Various Filter Media in Addressing Wildfire Smoke in Indoor Environments: Importance of Particle Size and Composition
Authors: Shirman Tanya , Shirman Elijah , Liu Sissi
Published: November 2023

Sub-micron particles are ubiquitous in the indoor environment, especially during wildfire smoke episodes, and have a higher impact on human health than larger particles. Conventional fibrous air filters installed in heating, ventilation, and air conditioning (HVAC) systems play an important role in controlling indoor air quality by removing various air pollutants, including particulate matter (PM). However, it is evident that the removal efficiency of wildfire smoke PM and its effect on filter performance is significantly under-studied. This study delves into the size-specific removal efficiency of pine needle smoke, a representative of wildfire smoke and emissions. We test an array of filter media with minimum efficiency reporting values (MERV) spanning 11–15. Both size-resolved particle number concentrations and mass concentrations were measured using an Optical Particle Sizer (OPS, TSI, Inc.) and a Scanning Mobility Particle Sizer (SMPS, TSI, Inc.). Furthermore, we characterize the filter media morphology and smoke particles deposited on filter fibers using Scanning Electron Microscopy (SEM) to gain insights into the interaction dynamics of these particles. Our findings add to the comprehension of the relationship between MERV designations and smoke removal efficiency. Such insight can inform standards and guidelines and equip decision-makers with the knowledge needed to initiate measures for mitigating the impact of air pollution, specifically on the indoor environment.
Drift Velocity with Elastic Scattering
Authors: Morin Rachel M. , Mecholsky Nicholas A.
Published: November 2023

The drift velocity of a particle under a driving force has its roots in the theory of electrical conduction. Although it has been studied for over 100 years, it still yields surprises. At the heart of a particle’s drift velocity is an interplay of classical, quantum, and statistical mechanics. Irreversibility and energy loss have been assumed as essential features of drift velocities and very little effort has been made to isolate the aspects of particle transport that are due to elastic mechanisms alone. In this paper, we remove energy loss and quantum mechanics to investigate the classical and statistical factors that can produce a drift velocity using only elastic scattering. A Monte Carlo simulation is used to model a particle in a uniform force field, subject to randomly placed scatterers. Time-, space-, and energy-dependent scattering models, with varied ranges of scattering angles, are investigated. A constant drift velocity is achieved with the time scattering model, which has a constant average time between scattering events. A decreasing drift velocity is observed for space and energy-dependent models. The arrival of a constant drift velocity has to do with a balance of momentum gained between collisions and momentum lost after a collision.
State-of-Health Estimation of Lithium-Ion Battery Based on Constant Voltage Charging Duration
Authors: Chen Jinyu , Chen Dawei , Han Xiaolan , Li Zhicheng , Zhang Weijun , Lai Chun Sing
Published: November 2023

It is imperative to determine the State of Health (SOH) of lithium-ion batteries precisely to guarantee the secure functioning of energy storage systems including those in electric vehicles. Nevertheless, predicting the SOH of lithium-ion batteries by analyzing full charge–discharge patterns in everyday situations can be a daunting task. Moreover, to conduct this by analyzing relaxation phase traits necessitates a more extended idle waiting period. In order to confront these challenges, this study offers a SOH prediction method based on the features observed during the constant voltage charging stage, delving into the rich information about battery health contained in the duration of constant voltage charging. Innovatively, this study suggests using statistics of the time of constant voltage (CV) charging as health features for the SOH estimation model. Specifically, new features, including the duration of constant voltage charging, the Shannon entropy of the time of the CV charging sequence, and the Shannon entropy of the duration increment sequence, are extracted from the CV charging phase data. A battery’s State-of-Health estimation is then performed via an elastic net regression model. The experimentally derived results validate the efficacy of the approach as it attains an average mean absolute error (MAE) of only 0.64%, a maximum root mean square error (RMSE) of 0.81%, and an average coefficient of determination (R2) of 0.98. The above statement serves as proof that the suggested technique presents a substantial level of precision and feasibility for the estimation of SOH.
Optimal Laboratory Cultivation Conditions of Limnospira maxima for Large-Scale Production
Authors: Pineda-Rodríguez Yirlis Yadeth , Herazo-Cárdenas Diana Sofia , Vallejo-Isaza Adriana , Pompelli Marcelo F. , Jarma-Orozco Alfredo , Jaraba-Navas Juan de Dios , Cordero-Ocampo Jhony David , González-Berrio Marianella , Arrieta Daniela Vegliante , Pico-González Ana , Ariza-González Anthony , Aviña-Padilla Katia , Rodríguez-Páez Luis Alfonso
Published: November 2023

Cultivating Limnospira maxima, renowned for its abundant proteins and valuable pigments, faces substantial challenges rooted in the limited understanding of its optimal growth parameters, associated high costs, and constraints in the procurement of traditional nitrogen sources, particularly NaNO3. To overcome these challenges, we conducted a comprehensive 4 × 3 factorial design study. Factors considered included white, red, blue, and yellow light spectra, along with nitrogen sources NaNO3 and KNO3, as well as a nitrogen-free control, for large-scale implementation. Optimal growth, measured by Optical Density, occurred with white and yellow light combined with KNO3 as the nitrogen source. These conditions also increased dry weight and Chl-a content. Cultures with nitrogen deprivation exhibited high values for these variables, attributed to carbon accumulation in response to nitrogen scarcity. Phycocyanin, a crucial pigment for nutrition and industry, reached its highest levels in cultures exposed to white light and supplemented with KNO3, with an impressive content of 384.11 g kg−1 of dry weight. These results highlight the efficacy and cost-efficiency of using a combination of white light and KNO3 for large-scale L. maxima cultivation. This strategy offers promising opportunities to address global food security challenges and enhance the production of industrially relevant pigments.
The Role of the Intestinal Microbiome in Multiple Sclerosis—Lessons to Be Learned from Hippocrates
Authors: El-Sayed Mohamed Mahmoud , Mohak Sidhesh , Gala Dhir , Fabian Reka , Peterfi Zoltan , Fabian Zsolt
Published: November 2023

Based on recent advances in research of chronic inflammatory conditions, there is a growing body of evidence that suggests a close correlation between the microbiota of the gastrointestinal tract and the physiologic activity of the immune system. This raises the idea that disturbances of the GI ecosystem contribute to the unfolding of chronic diseases including neurodegenerative pathologies. Here, we overview our current understanding on the putative interaction between the gut microbiota and the immune system from the aspect of multiple sclerosis, one of the autoimmune conditions accompanied by severe chronic neuroinflammation that affects millions of people worldwide.
The Roles of WNT Signaling Pathways in Skin Development and Mechanical-Stretch-Induced Skin Regeneration
Authors: Bai Ruoxue , Guo Yaotao , Liu Wei , Song Yajuan , Yu Zhou , Ma Xianjie
Published: November 2023

The WNT signaling pathway plays a critical role in a variety of biological processes, including development, adult tissue homeostasis maintenance, and stem cell regulation. Variations in skin conditions can influence the expression of the WNT signaling pathway. In light of the above, a deeper understanding of the specific mechanisms of the WNT signaling pathway in different physiological and pathological states of the skin holds the potential to significantly advance clinical treatments of skin-related diseases. In this review, we present a comprehensive analysis of the molecular and cellular mechanisms of the WNT signaling pathway in skin development, wound healing, and mechanical stretching. Our review sheds new light on the crucial role of the WNT signaling pathway in the regulation of skin physiology and pathology.
How the Intrinsically Disordered N-Terminus of Cancer/Testis Antigen MAGEA10 Is Responsible for Its Expression, Nuclear Localisation and Aberrant Migration
Authors: Samel Anneli , Väärtnõu Fred , Verk Lisbeth , Kurg Kristiina , Mutso Margit , Kurg Reet
Published: November 2023

Melanoma-associated antigen A (MAGEA) subfamily proteins are normally expressed in testis and/or placenta. However, aberrant expression is detected in the tumour cells of multiple types of human cancer. MAGEA expression is mainly observed in cancers that have acquired malignant phenotypes, invasiveness and metastasis, and the expression of MAGEA family proteins has been linked to poor prognosis in cancer patients. All MAGE proteins share the common MAGE homology domain (MHD) which encompasses up to 70% of the protein; however, the areas flanking the MHD region vary between family members and are poorly conserved. To investigate the molecular basis of MAGEA10 expression and anomalous mobility in gel, deletion and point-mutation, analyses of the MAGEA10 protein were performed. Our data show that the intrinsically disordered N-terminal domain and, specifically, the first seven amino acids containing a unique linear motif, PRAPKR, are responsible for its expression, aberrant migration in SDS-PAGE and nuclear localisation. The aberrant migration in gel and nuclear localisation are not related to each other. Hiding the N-terminus with an epitope tag strongly affected its mobility in gel and expression in cells. Our results suggest that the intrinsically disordered domains flanking the MHD determine the unique properties of individual MAGEA proteins.
Roles of Human Endogenous Retroviruses and Endogenous Virus-Like Elements in Cancer Development and Innate Immunity
Authors: Katoh Hirokazu , Honda Tomoyuki
Published: November 2023

Human endogenous retroviruses (HERVs) are remnants of ancient retroviral infections in the host genome. Although mutations and silencing mechanisms impair their original role in viral replication, HERVs are believed to play roles in various biological processes. Long interspersed nuclear elements (LINEs) are non-LTR retrotransposons that have a lifecycle resembling that of retroviruses. Although LINE expression is typically silenced in somatic cells, it also contributes to various biological processes. The aberrant expression of HERVs and LINEs is closely associated with the development of cancer and/or immunological diseases, suggesting that they are integrated into various pathways related to the diseases. HERVs/LINEs control gene expression depending on the context as promoter/enhancer elements. Some RNAs and proteins derived from HERVs/LINEs have oncogenic potential, whereas others stimulate innate immunity. Non-retroviral endogenous viral elements (nrEVEs) are a novel type of virus-like element in the genome. nrEVEs may also be involved in host immunity. This article provides a current understanding of how these elements impact cellular physiology in cancer development and innate immunity, and provides perspectives for future studies.