bluuebunny/crossref_metadata_2025 huggingface dataset:
Analytical parameters to check association between load carriage system and bag packs-influenced musculoskeletal complications among school going students: a scoping review
Authors: Guleria Mahima , Sharma Shashi Prakash , Kumar Amit
Published: October 2023

[Purpose] This study aimed to investigate the correlation between load-carriage systems and backpacks on musculoskeletal complications among school-going students. Additionally, the purpose was to identify research gaps and provide recommendations for future research.[Methods] To conduct this study, we conducted a thorough search of five databases for literature published between January 2010 and December 2022. Our focus was on original published articles that reported musculoskeletal complications using analytical parameters or outcome measures among school-going students. Two reviewers independently extracted data for eligibility. The studies selected for the analysis focused on musculoskeletal complications and the outcome measures to report these complications.[Results] A total of 3541 titles were screened; of which, 18 observational studies were included. The musculoskeletal complications identified in these studies included lower back, shoulder, and neck pain and disturbed posture. Overall, the quality of the reporting in these studies was deemed satisfactory.[Conclusion] Our analysis revealed that pain and postural abnormalities were the most frequently reported complications. Hence, we recommend that future studies incorporate multiple evaluations rather than concentrating on a single symptom.
Effects of environmental variability on population dynamics of golden carpet shell clam (Polititapes aureus)
Authors: Parada José Manuel , Molares José
Published: October 2023

The population dynamics of the golden carpet shell clam Polititapes aureus (Gmelin, 1791) were studied over the course of six years in the ria of Arousa (Galicia, NW Spain). Density reached a value of 62.29 individuals m−2 and biomass was 76.30 g m−2. Recruitment was related to water temperature, to food availability measured as fluorescence and to density-dependent phenomena starting at 39 individuals m−2. The condition factor and mortality showed a clear annual periodicity, while growth rate G30 was biannual. Growth was fitted to a seasonal von Bertalanffy function, with L∞ = 43.6 mm; K = 0.360 y−1; C = 0.65 and ts = 1.21, with a confidence interval determined by bootstrapping. The instantaneous mortality rate for individuals aged 1 and 2 years was 0.94 in spring-summer and 0.14 in autumn-winter. The fishing mortality rate had little effect on the population. A model was built to explain the natural mortality rate as function of temperature, salinity, fluorescence, and the condition factor. The results allow the application of fishery management tools based on their population dynamics and to measure their effectiveness considering the environmental variability. They also show the vulnerability of these stocks to changes resulting from climate change.
On Weakly Tripotent and Locally Invo-Regular Rings
Authors: Pandey S K
Published: October 2023

In this article some important observations have been reported on recent works related to weakly tripotent rings and locally invo-regular rings. Our findings give additional results as well as correct some recent results on weakly tripotent rings and locally invo-regular rings appeared in Rendiconti Sem. Mat. Univ. Pol. Torino (2021) and Azerbaijan Journal of Mathematics (2021) respectively. In addition we exhibit that if the Jacobson radical J(A) of a ring is strongly involution t-clean then the characteristic of J(A) need not be four. This finding improves an important result appeared in Eur. J. Pure Appl. Math (2022).
Joint Probability Densities as Symmetric Covariant Tensor Densities on Riemannian Manifold
Authors: Amiri Manouchehr
Published: October 2023

This paper presents the tensor properties of joint probability densities on a Riemannian manifold. Initially we develop a binary data matrix to record variables' values of a large number of particles confining in a closed system at a certain time in order to retrieve the joint probability densities of related variables. By introducing the particle oriented coordinate and generalized inner product as a multi-linear operation on the basis of this coordinate, we extract the set of joint probabilities and prove them to meet covariant tensor properties on a general Riemannian space of variables. Based on the Taylor expansion of scalar field in Riemannian manifolds, it has been shown that the symmetrized iterative covariant derivatives of cumulative probability function defined on Riemannian manifold also gives the set of related joint probability densities equivalent to the aforementioned multi-linear method. We show these covariant tensors reduce to classical ordinary partial derivatives in ordinary Euclidean space with Cartesian coordinates and gives the formal definition of joint probabilities by partial derivatives of cumulative distribution function. The equivalence between symmetrized covariant derivative and generalized inner product has been concluded. Some examples of well-known physical tensors clarify that many deterministic physical variables are presented as tensor densities with an interpretation similar to probability densities.
Network Inference from Cancer and Epithelial Cell Co-Culture Reveal Microenvironmental Configurations That Drives Population Dynamics
Authors: Queiroga Alexandre , Morais Mauro , Stransky Beatriz
Published: October 2023

Cellular Automata and Boolean Networks are generalizations of one another because algorithms to compute the preimage of cellular automata reveal the underlying network, i.e., the global dynamics in terms of the basins of attraction. Therefore, we hypothesize we can reveal the local dynamics of cellular automata from the basin of attraction of an inferred boolean network. Our motivation was the observation that human keratinocytes and melanoma can stick together to form clusters after eight days in co-culture. This cluster formation would be the attractor of population dynamics, and cell seeding would be the initial condition of the basin of attraction. Hence, we propose a method to estimate the rules of cellular automata, which consist of comparing the density states within each state transition and reaching a consensus among state transitions belonging to a basin of attraction. Therefore, we aim: (1) to infer a boolean network from the \emph{in vitro} co-culture growth curve; (2) to estimate the rules of cellular automata; and (3) to implement a cellular automata for spatial dynamics simulations. The binarization of the growth curve shows high population density after four days; the estimated cellular automata rules were compatible with cell proliferation and migration in agreement with experimental observations. Spatial dynamics shows that: (1) keratinocytes exhibit higher density in neighborhoods where melanoma is present; (2) the chance of keratinocyte migration increases until the fourth day, but the probability of survival increases; and (3) space is freed for cells with maximum proliferation capacity through proliferation compensated by death. Our approach suggests that the attractor state of cell co-culture would be induced by an increase in keratinocyte migration and survival, as well as the balance of proliferation and death concerning melanoma. Our approach has the potential to offer valuable clues about microenvironmental interactions or configurations that drive population dynamics.
Numerical and Experimental Investigations in Particle Dampers Attached to a Pipeline Structure
Authors: Ma Rui , Shi Fuqiang , Juan Mingxin , Wang Jiao , Jin Jie , Yu Tao
Published: October 2023

The base excitation of mechanical equipment can result in pipeline system vibration which seriously affects the safe operation of the equipment. Particle damping technology is based on the particle collision dissipation principle to realize the structural vibration energy dissipation. This paper introduces the particle damping method into the vibration control of pipeline system. A particle damper has been designed for the structural characteristics of the pipeline. The influence of the material and structure of the pipeline particle damper, the external excitation and other parameters on the energy dissipation characteristics of particle damping are revealed. The energy dissipation mechanism of the pipeline particle collision damper under various parameter is analyzed. A pipeline vibration reduction test system with particle damping has been established. The effects of different excitation conditions, damper materials and number of unit structures of particle damper on the vibration damping effect of pipeline systems are investigated comparatively. The influence of damper parameters on the vibration suppression of pipeline system is obtained. The research in this paper can provide technical references for vibration suppression of pipeline systems.
Fusing Sequence and Structural Knowledge by Heterogeneous Models to Accurately and Interpretively Predict Drug-Target Affinity
Authors: Zeng Xin , Zhong Kai-Yang , Jiang Bei , Li Yi
Published: October 2023

Drug-target affinity (DTA) prediction is crucial for understanding molecular interactions and aiding drug discovery and development. While various computational methods have been proposed for DTA prediction, their predictive accuracy remains limited, failing to delve into the structural nuances of interactions. With increasingly accurate and accessible structure prediction of targets, we developed a novel deep learning model, named S2DTA, to accurately predict DTA by fusing sequence and structural knowledge of drugs, targets, and pockets using heterogeneous models based on graph and semantic networks. Experimental findings underscored that complex feature representations imparted negligible enhancements to the model’s performance. However, the integration of heterogeneous models demonstrably bolstered predictive accuracy. In comparison to three state-of-the-art methodologies, the supremacy of S2DTA became strikingly apparent. It showcased a noteworthy 25.2% reduction in Mean Absolute Error (MAE) and an impressive 20.1% decrease in Root Mean Square Error (RMSE). Furthermore, S2DTA exhibited substantial advancements in other pivotal metrics, including Pearson Correlation Coefficient (PCC), Spearman, Concordance Index (CI), and R2. These metrics experienced remarkable increments of at least 19.6%, 17.5%, 8.1%, and a remarkable 49.4%, respectively. Finally, we conducted interpretability analysis on the effectiveness of S2DTA by bidirectional self-attention mechanism, fully proving that S2DTA is a valuable and accurate tool for predicting DTA. For further exploration, the source data and code repository can be accessed at https://github.com/dldxzx/S2DTA.
From Fresh to Salt Waters: First Data about the Invasiveness of the Red Swamp Crayfish Procambarus clarkii (Girard, 1852) in Mediterranean Marine Waters
Authors: Nota Alessandro , Santovito Alfredo , Gattelli Raffaele , Tiralongo Francesco
Published: October 2023

Background: The red swamp crayfish Procambarus clarkii (Girard, 1852), native to the United States and northern Mexico, has been introduced in many countries worldwide. The species has a remarkable invasiveness, due to its high reproductive rate and to its ability to tolerate broad ranges of water parameters like salinity. Nevertheless, no consistent observations of P. clarkii have been reported in the marine environment until now. Methods: Through the observations of a personal acquaintance and of two volunteers who published photos of the species on Facebook marine biology and fishing groups, we collected data showing the presence of the crayfish within marine ecosystems. Results: P. clarkii has been spotted in three different localities, in two of which observations are recurrent. The species can live miles from the nearest freshwater stream, and can colonise the depths up to 20 meters. Conclusions: The multiple observations of P. clarkii collected in our study uncover a persistent presence of the species within some marine areas, rather than its mere sporadic occurrence. As resistance to increasing salinities is influenced by multiple genes, genetic admixture between genetically-differentiated individuals coming from distinct geographical origins could have brought together different salinity-resistance genes, leading to the formation of these resilient phenotypes.
Research on Time-Varying Meshing Stiffness of Marine Bevoloid Gear System
Authors: Wen Jianmin , Yao Haoyu , Yan Qian , You Bindi
Published: October 2023

As a new type of gear, bevoloid gears have the advantages of compensating axial error, smooth transmission, and eliminating turning error, and they are widely used in applications requiring high transmission accuracy and stability. However, research on calculating the time-varying mesh stiffness of bevoloid gears is still limited, and there is an urgent need to propose a method that can calculate the stiffness of bevoloid gears quickly and accurately. This paper first establishes the bevoloid gear tooth profile expressions, then assumes a pair of bevoloid gears meshing with the same rack and derives the contact line equations of parallel axis bevoloid gear pairs, and analyze the contact process of bevoloid gears. We propose an analytical algorithm that uses the slicing method to calculate the stiffness of helical gears, straight bevoloid gears, and helical bevoloid gears, change the parameters of helical bevoloid gears respectively, and analyze the influence of different parameters on stiffness. Finally, the finite element method is used to verify the analytical method, and the correctness of the analytical calculation results is verified, and the errors are analyzed.
Enhancing the Classification of Biosynthetic Gene Clusters through Comprehensive NLP-Based Approach
Authors: Mishra Dwijesh Chandra , Madival Sharanbasappa D , Sharma Anu , Budhlakoti Neeraj , Chaturvedi Krishna Kumar , Angadi Ulavappa Basavanneppa , Farooqi Mohammad Samir , Srivastava Sudhir , Basavaraja Pavana , Arora Alka , Jha Girish Kumar , Rai Shesh
Published: October 2023

Biosynthetic gene clusters are specific genomic regions in microorganisms, like bacteria and fungi, responsible for producing bioactive compounds. Identifying these clusters is complex due to their diverse nature. This research presents a comprehensive approach to effective BGC identification. The study focuses on five classes of Natural Products: PKS , NRPS, RiPP, Terpenes, and Hybrid PKS-NRPS. Data was gathered from the MiBIG database in GBK format. Protein sequences from each file were extracted, and sequences under the same BGC ID were combined. Physicochemical properties were calculated, and sequence embeddings were generated using NLP techniques like CountVec, TFIDF, and Word2Vec specific to each NP class. An integrated feature matrix was created by merging physicochemical properties and generated embeddings. This matrix was used for training and testing of nine ML models such SVM, RF and many more. The study explored data balancing techniques with and without SMOTE and employed Grid Search for parameter optimization. This led to six datasets and 54 models. The LR model, using TFIDF with SMOTE, emerged as the most effective, achieving an accuracy of 0.96, AUC of 0.9912, and other strong metrics. This method enhances BGC identification for drug development, offering a broader understanding of their applications in medicine and biotechnology.
Donor Causes of Death and Sex and Their Relationship to AMR and CAV in Heart Transplant Recipients
Authors: Hammond Margo Elizabeth , Zollinger Charles , Vidic Andrija , Snow Gregory , Stehlik Josef , Alharethi Rami , Kfoury Abdallah G , Drakos Stavros , Hammond M Elizabeth Hale
Published: October 2023

Background
Recent studies indicate that donor innate immune responses participate in initiating and accelerating innate responses and allorecognition in the recipient. These immune responses negatively affect recipient outcomes and predispose recipients to allograft coronary artery vasculopathy (CAV). We hypothesized that donor cause of death (COD) associated with higher levels of innate immune response would predispose recipients to more adverse outcomes post-transplant, including CAV.
Methods
We performed a single-institution retrospective analysis comparing donor characteristics and COD to recipient adverse cardiovascular outcomes. We analyzed the medical records of local adult donors (age 18-64) in a database of donors where adequate data was available. We linked donor characteristics and COD to recipient adverse cardiac outcomes after transplant, including cardiovascular (CV) death and incidence of significant antibody-mediated rejection (pAMR) after transplant (>2 episodes of pAMR within 90 days post-transplant). The data were analyzed using logistic regression, log-rank test of differences, and Tukey Contrast.
Results
Donor advanced age, female sex, and CODs of motor vehicle accident and intracranial hemorrhage were significantly associated with a higher incidence of recipient CV death and early pAMR compared to other donor characteristics and CODs.
Conclusions
In this single institution study, we found that recipients with hearts from donors over 40 years, donors who were female, or donors who died with a COD of motor vehicle accidents or intracranial hemorrhage had a higher frequency of CV related deaths and early pAMR. Donor monitoring and potential treatment of innate immune activation may decrease subsequent recipient innate responses and allorecognition stimulated by donor derived inflammatory signaling which lead to adverse outcomes.
Water Governance in the Cambodian Mekong Delta: The Nexus of Farmer Water User Community (FWUC), Community Fisheries (CFis), and Community Fish Refuges (CFRs) in the Context of Climate Change
Authors: Sithirith Mak , Sok Sao , De Silva Sanjiv , Heng Kong , Chay Kongkroy , Tim Thavrin , Hy Sarun
Published: October 2023

Cambodia faces the challenge of managing excess water during the wet season and insufficient water during the dry season. This harms human life and endangers aquatic and natural resources, agricultural practices, and food security. In order to ensure the well-being of both people and food security, water governance is crucial. However, Cambodia's water governance is hindered by various obstacles, including sectoral and centralized influences, top-down and large-scale strategies, a lack of coordination among relevant agencies, and limited involvement of local communities. This study delves into water governance across different sectors, from centralized to community-based natural resources management to tackle these challenges. Through analyzing literature and case studies of farmer water user communities (FWUC), community fisheries (CFis), and community fish refuges (CFRs) in three Mekong Delta provinces in Cambodia, the study concludes that although water governance has improved, it has resulted in a decline in fishery resources from rivers and water bodies and an increase in water conflicts among farmers and sectors in the face of climate change. To enhance water governance in Cambodia, it is critical to integrate it at the district level. This will promote sustainable water use and management across the country and pave the way for a brighter future.
Could the Combination of eGFR and mGPS Facilitate the Differential Diagnosis of Age-Related Renal Decline from Diseases? A Large Study on the Population of Western Sicily
Authors: Carella Miriam , Porreca Annamaria , Piazza Cinzia , Gervasi Francesco , Magro Daniele , Venezia Marika , Lo verso Raffaella , Vitale Giuseppe , Agnello Anna giusy , Aronica Tommaso , Balistreri Carmela Rita
Published: October 2023

Assessment of renal function is critical to diagnose and manage renal age-related decline, disease (KD), and failure, which are prevalent in the elderly population. Glomerular filtration rate (GFR) is widely used as an indicator of kidney function, but its direct measurement is challenging, as are its age and gender caveats. This makes difficult the differential diagnosis, between age-related physiological decline and KD and/or failure. Currently, the inflammation-based modified Glasgow prognostic score (mGPS) is emerging as promising biomarker of several inflammatory acute/chronic diseases. In this study, the large variability of eGFR with age and gender was evaluated, as the association of eGFR values with mGPS levels. A population of 57449 adult participants (age ≥18 years) was enrolled. Appropriate circulating biomarkers were measured to detect eGFR and mGPS values. The data obtained demonstrated a significant decrease of eGFR in men vs. women across the four selected age classes (18-40, 40-60, 60-80, 80-100 years), eGFR classes were significantly associated with mGPS (p<0.001), as age-classes and gender with mGPS categories. Accordingly, the percentage of people having a mGPS score= 2 significantly increased across the eGFR classes: with a 11% in the G1/eGFR class to achieve the 44% in G5/eGFR. Thus, the combination of mGPS with eGFR could represent the best benchmark risk model for differentiating age-related renal decline from a very KD, and for a better identification of different degrees of KD severity.
A Three-Dimensional Time-Dependent Model of the Degradation Caused by Chromium Poisoning in a Solid Oxide Fuel Cell Stack
Authors: Yu Shangzhe , Schäfer Dominik , Zhang Shidong , Peters Roland , Kunz Felix , Eichel Rüdiger-A.
Published: October 2023

Chromium poisoning strongly influences the performance of solid oxide fuel cell (SOFC) stacks. A three-dimensional, time-dependent, computational fluid dynamics model of a single channel of a F10 SOFC stack in Forschungszentrum Jülich GmbH is developed to investigate chromium poisoning for different stack designs, temperatures and absolute air humidities. The model takes into account both chemical and electrochemical mechanisms of chromium poisoning and is able to predict the spatial distribution of SrCrO4 and Cr2O3. The voltage degradation over 100 kh can be simulated quantitatively. According to the simulation results, chromium poisoning is almost eliminated by the application of the protective coating fabricated by the atmospheric plasma-spraying (APS) technology. Besides, with the help of the APS protective coating, operating a SOFC stack with less dehumidified air at 650 oC is possible according to the simulation.
A Comprehensive Review on Therapeutic Potential of Nanobodies
Authors: Haddad Fatma , Dokmak Ghadeer , Kanwal Shahla , Karaman Rafik
Published: October 2023

Recently, nanobodies have taken center stage in research on drug discovery and development. Several therapeutic possibilities using nanobodies are presently undergoing clinical trials and waiting for FDA approval. The goal of this study was to emphasize the potential of nanobodies as therapeutic agents by concentrating on the most recent published studies that examined their properties, manufacturing, and possible applications. This article demonstrates that the unique properties of nanobodies in comparison to conventional antibodies, which are based on their small size and offer a number of benefits, make them seem to have a promising future. These advantages include the ability to access complex or hidden target sites that may be elusive to their larger antibody counterparts, and increased resilience against extreme conditions like tempera-ture changes and pH variations. As a result, nanobodies seem to have a bright future as adaptable tools for imaging in cancer and non-malignant diseases, as well as for in vitro and in vivo diagnostic and therapeutic potential for a variety of conditions, including oncology, infectious, metabolic, neurological, and other conditions like ophthalmologic, immune-mediated, and genetic disorders. More research is required to determine their effectiveness and safety in clinical applications. The current analysis offers a thorough overview of the therapeutic uses for nanobody products that are either on the market or undergoing clinical trials.
A Spectral Polak-Ribi{\'e}re-Polyak Conjugate Gradient Method on Quantum Derivative for Unconstrained Optimization Problems
Authors: Lai Kin Keung , Mishra Shashi Kant , Ram Bhagwat , Sharma Ravina
Published: October 2023

Quantum computing is an emerging field that have given a significant impact on optimization. Among the diverse quantum algorithm, the quantum gradient descent has become a prominent technique for solving unconstrained optimization problems. In this paper, we propose a quantum-spectral Polak-Ribi{\'e}re-Polyak (PRP) conjugate gradient approach. The technique is considered as a generalization of the spectral PRP method which employs a $q$-gradient that approximate the classical gradient with quadratically better dependence on the quantum variable $q$. Additionally, the proposed method reduces to the classical variant as quantum variable $q$ gets closer to $1$. The quantum search direction always satisfies the sufficient descent condition and does not depend on any line search. This approach is globally convergent with the standard Wolfe line search without any convexity assumption. Numerical experiments are conducted and compared with the existing approach to demonstrate the improvement of the proposed strategy.
In Silico and In Vitro Study towards the Rational Design of 4,4′-Disarylbisthiazoles as a Selective α-Synucleinopathy Biomarker
Authors: Uzuegbunam Bright , Li Junhao , Paslawski Wojciech , Weber Wolfgang , Svenningsson Per , Ågren Hans , B Hooshyar Yousefi
Published: October 2023

The α-synucleinopathies are a group of neurodegenerative diseases characterized by the deposition of α-synuclein aggregates (α-syn) in the brain. Currently, there is no suitable tracer to enable a definitive early diagnosis of these diseases. We reported candidates based on 4,4'-disarylbisthiazole (DABTA) scaffold with a high affinity towards α-syn and excellent selectivity over Aβ and tau fibrils. Based on prior in silico studies a focused library of 23 halide-containing and O-methylated DABTAs was prepared. The DABTAs were synthesized via a modified two-step Hantzsch thiazole synthesis, characterized, and used in competitive binding assays against [3H]PiB, and [3H]DCVJ. The DABTAs gave an overall chemical yield of 15 – 71%, with a calculated lipophilicity of 2.5 – 5.7. The ligands demonstrated an excellent affinity to α-syn with both [3H]PiB and [3H]DCVJ: Ki 0.1 – 4.9 nM and up to 20 – 3900-fold selectivity over Aβ and tau fibrils. It could be concluded that in-silico simulation is useful for the rational design of a new generation of DABTAs. Further investigation of the leads in the next step is encouraged: radiolabeling of the ligands with radioisotopes such as fluorine-18 or carbon-11 for in vivo, ex vivo and translational research and for further in vitro experiments on human-derived protein aggregates.
Experimental study on Microstructural Characterization of Retardation Capacity of Microbial Inhibitors to Lignite Spontaneous Combustion
Authors: Wang Yanming , Liu Ruijie , Chen Xiaoyu , Zou Xiangyu , Li Dingrui , Wang Shasha
Published: October 2023

The spontaneous combustion of coal in goaf is the main cause of mine fire at present. Lignite has become a major hidden danger in mine production safety because of its easy oxidation. In this paper, an innovative strategy was proposed to inhibit the spontaneous combustion of lignite by using the principle of microbial-induced calcium deposition. Based on the optimized culture method, a novel composite inhibitor of Bacillus pasteurelli was prepared. SEM, pore size analysis and FT-IR experiments were carried out simultaneously, and the oxidation properties of lignite before and after inhibition were quantitatively characterized from the perspective of microstructure, and the flame retardant properties of microbial and chemical retardants on coal samples were compared. The results show that a large number of deposited calcium carbonate particles are obviously attached to the surface of lignite after microbial inhibition treatment, which plays a physical oxygen insulation role. At the same time, the total pore volume and specific surface area of the coal sample decreased by 68.49% and 74.01%, respectively, indicating that microbial inhibitors can effectively plug the primary pores of lignite. Based on the peak measurement of 400-4000cm-1 infrared spectrum of coal samples, it is found that the contents of active groups including hydroxyl, carboxyl and methyl/methylene in lignite molecules after microbial inhibition are lower than those in raw coal, especially the methyl/methylene content involved in the initial oxidation reaction decreased by 96.5% compared with the baseline content in raw coal. The results show that the oxidation and self-heating capacity of lignite after microbial inhibition is effectively restrained in the initial spontaneous combustion. The research results of this paper can provide effective solutions for the prevention and control of coal spontaneous combustion risk in mined-out area.
Multi-Omics Mining of LNC-RNAs With Biological and Clinical Relevance in Cancer
Authors: Salido-Guadarrama Ivan , Romero-Cordoba Sandra L. , Rueda-Zarazua Bertha
Published: October 2023

In this review, we will cover a general overview of the current panorama on lncRNAs with an actual or potential role as biological markers in cancer. We will discuss examples of multi-omics approaches that integrates information on somatic aberrations, gene expression and epigenomics, with the scope of providing a more comprehensive view of the functional impact of lncRNA profiles and how these paradigm can be exploited for the discovery and selection of lncRNAs with a functional role and their use as variables informing on progression and prognostic and help guiding the selection of therapeutic strategies for cancers. Finally, we propose a perspective for future evolution of the study of lncRNAs and the discovery of their functional and harnessing their potential to assist in clinical management of malignancies.
Effect of Comprehensive and Integrative Medical Service on Patients with Degenerative Lumbar Spinal Stenosis: A Randomized Control Clinical Trial
Authors: Ko Sang-Bong , Kwak Sang Gyu
Published: October 2023

Background: Two types of medicinal systems are available in Korea: Western and oriental. These exist as separate services that independently provide medical care to patients. We determined the utility and benefits of compressive and integrated medical services (CIMS) comprising 12 sessions of acupuncture and healing programs over 6 weeks. Methods: In this two-group parallel single-center randomized controlled assessor-blinded trial, 24 participants were assigned to either the experimental (conventional medical treatment plus CIMS, n = 12) or control (conventional medical treatment, n = 13) group. Spinal nerve root block was performed on the compressed spinal nerve root (identified using magnetic resonance imaging) when no improvement was observed after the initial treatment. The experimental group received 12 cycles of acupuncture and manual therapy for 6 weeks; the control group received conventional medical treatment alone. Results: The average age of participants in the experimental and control groups was 70.73 ± 5.95 and 67.33 ± 8.89 years, respectively. There were no significant differences between the groups in terms of age, body mass index, Leeds Assessment of Neuropathic Symptoms and Signs, sex, and current medical history. We found high compliance for both programs (acupuncture and healing). On exclusion of between-group effects, the visual analog scale (VAS) score improved significantly over time (p = 0.045). Further, comparison of the groups after excluding the effects of visits revealed significantly lower VAS scores in the experimental group than in the control group (p = 0.000). Conclusions: Patients with degenerative lumbar spinal stenosis who mainly complain of radiating pain in the lower leg may benefit from CIMS after spinal nerve root block for ≤3 months after treatment. Our study findings suggest that this treatment improves spinal function and Oswestry Disability Index score. However, CIMS did not improve QoL.
Exploring an Interdisciplinary Curriculum in Product and Media Design Education: Knowledge Innovation and Competency Development
Authors: Kao Yi-Fang , Chen Hung-Cheng , Lo Jung-Hua
Published: October 2023

This study explores the implementation of an interdisciplinary curriculum in product and media design education and its impact on knowledge innovation and competency development. The curriculum is based on scaffolding theory, incorporating design proposals, workshops, digital design, marketing tests, and marketing activities guided by teachers and mentors from a branded ceramic workshop. The research findings demonstrate that the interdisciplinary curriculum facilitates knowledge innovation and fosters the development of students' professional skills, creativity, and problem-solving skills. The study also highlights the importance of stable scaffolding, including artefact, peer, and teacher support, which significantly contributes to cultivating transformational competencies, as outlined in the 2030 OECD Learning Compass. Additionally, the collaboration with Shanshing Four Seasons Celadon Studio on a patented ceramic product, "Funny Monkey," is a tangible example of the journey towards a triple-helix knowledge economy. This research underscores the importance of interdisciplinary curricula in promoting knowledge innovation and integrating transformational competencies in education. Scaffolding theory provides practical guidance for student learning and teaching strategies, presenting a sustainable roadmap for developing interdisciplinary curricula and offering a concrete and transferable pedagogical prototype for educational innovation.
Artificial Intelligence to Solve Production Scheduling Problems in Real Industrial Settings: Systematic Literature Review
Authors: Del Gallo Mateo , Ciarapica Filippo Emanuele , Mazzuto Giovanni , Bevilacqua Maurizio
Published: October 2023

This systematic literature review explores the burgeoning use of Artificial Intelligence (AI) in manufacturing systems, in line with the principles of Industry 4.0 and the growth of smart factories. In this landscape, AI is crucial in addressing the complexity and dynamism of contemporary manufacturing processes, including machine breakdowns, fluctuating orders and unpredictable job arrivals. This systematic literature review, conducted using the Scopus database and bibliometric tools, pursues two primary objectives. First, it identifies the prevailing trends in solving scheduling problems with AI and identifies the most commonly used AI techniques in the literature. Secondly, it analyses how authors have successfully employed AI to address production scheduling challenges in real-world industrial settings and assesses the benefits obtained by companies. The dynamic nature of manufacturing systems requires adaptive scheduling paradigms. AI, including Particle Swarm Optimization, Neural Networks, and Reinforcement Learning, is applied to optimize production processes, predict machine failures, and achieve substantial benefits. In real-world applications, these AI-driven solutions have led to reduced production costs, enhanced energy efficiency, and more efficient scheduling processes. AI is increasingly recognized as an essential tool in addressing the evolving challenges of modern manufacturing environments.
Dual-Pyramid Wide Residual Network for Semantic Segmentation on Cross-Style Datasets
Authors: Huang Yin-Fu , Shen Guan-Ting
Published: October 2023

Image segmentation is the process of partitioning an image into multiple segments where the goal is to simplify the representation of the image and make the image more meaningful and easier to analyze. In particular, semantic segmentation is an approach of detecting the classes of objects, based on each pixel. In the past, most semantic segmentation models were for only one single style, such as urban street views, medical images, or even Manga. In this paper, we proposed a semantic segmentation model called Dual-Pyramid Wide Residual Network (DPWRN) to solve the segmentation for cross-style datasets, which is suitable for diverse segmentation applications. The DPWRN integrated the Pyramid of Kernel paralleled with Dilation (PKD) and Multi-Feature Fusion (MFF) to improve the accuracy of segmentation. To evaluate the generalization of the DPWRN and its superiority over most state-of-the-art models, three datasets with completely different styles are tested in the experiments. Finally, the DPWRN verified its generalization and also showed its superiority over most state-of-the-art models.
Energy Storage in Power to Heat or Cold Applications – an Analysis of Electrical versus Thermal Energy Storage
Authors: Mehling Harald
Published: October 2023

The transition of the energy system to renewable sources means the cheap energy storage in fossil fuels must be replaced by other options. A large part of the demand for useful energy is heat and cold, often produced from electric energy by a resistance heater, compression heat pump or cooler. The question is then to store the initial electric energy by electric energy storage (EES) or the useful energy by thermal energy storage (TES). In a desktop study both options were compared, by the choice made in existing applications, and also generally analyzing current technology data. For the latter, cost, round-trip efficiencies, life cycles and life time of EES, specifically for batteries, and of TES, specifically for hot and cold water, ice and other PCM were collected. Applications studied are heating and cooling in buildings and in industry. Application-typical conversion efficiencies were also collected and taken into account. The results show that in many existing installations TES, incl. by PCM, is already preferred, and that TES is advantageous in most investigated applications economically, in addition to technical advantages. Thus, TES has a large potential in the transition of the energy system to stabilize the electricity grid by demand side management.
Biologicalization of Smart Manufacturing using DNA-Based Computing
Authors: Ura Sharifu , Zaman Lubna
Published: October 2023

This article provides a general overview of the bio-inspired computing method called DNA-Based Computing (DBC), including its theory and applications. The main theme of DBC is the central dogma of molecular biology (once information of DNA/RNA has got into a protein, it can’t get out again), i.e., DNA to RNA (sequences of four types of nucleotides) and DNA/RNA to protein (sequence of twenty types of amino acids) are allowed, not the reverse ones. Thus, DBC transfers few-element information (DNA/RAN-like) to many-element information (protein-like), solving a given cognitive problem. DBC can take many forms; this article elucidates two main forms, denoted as DBC-1 and DBC-2. Using arbitrary numerical examples, it is shown that DBC-1 can solve the following cognitive problems: “similarity indexing between seemingly different but inherently identical objects” and “recognizing regions of an image separated by a complex boundary.” DBC-2 can solve the following cognitive problem: “pattern recognition when the relevant information is insufficient.” Smart manufacturing-based systems (digital twins and big data analytics) must solve the abovementioned problems to make the manufacturing enablers (machine tools and monitoring systems) more self-reliant and autonomous. Consequently, DBC can improve the cognitive problem-solving ability of smart manufacturing-relevant systems and, thereby, can enhance its biologicalization.
Engineering a Novel Modular Adenoviral mRNA Delivery Platform Based on Tag/Catcher Bioconjugation
Authors: Geng Kexin , Rice-Boucher Paul J. , Kashentseva Elena A. , Dmitriev Igor P. , Lu Zhihong , Goedegebuure S. Peter , Gillanders William E. , Curiel David T.
Published: October 2023

mRNA vaccines have attracted widespread research attention with clear advantages in terms of molecular flexibility, rapid development, and potential for personalization. However, current mRNA vaccine platforms have not been optimized for induction of CD4/CD8 T cell responses. In addition, mucosal administration of mRNA based on lipid nanoparticle technology faces challenges in clinical translation. In contrast, adenovirus-based vaccines induce strong T-cell responses and have been approved for intranasal delivery. To leverage the inherent strengths of both the mRNA and adenovirus platforms, we developed a novel modular adenoviral mRNA delivery platform based on Tag/Catcher bioconjugation. Specifically, we engineered adenoviral vectors integrating Tag/Catcher proteins at specific locales on the Ad capsid proteins, allowing us to anchor mRNA to the surface of engineered Ad viruses. In proof-of-concept studies, the Ad-mRNA platform successfully mediated mRNA delivery and could be optimized via the highly flexible modular design of both the Ad-mRNA and protein bioconjugation systems.
Shock-Induced Degradation of Guanosine and Uridine Promoted by Nickel and Carbonate: Potential Applications
Authors: Maia Gustavo P. , Da Silva José Armando Luisa , André Vânia , Galvão Adelino M.
Published: October 2023

Experimental studies of degradation of two ribonucleosides (guanosine and uridine) were carried out by making use of mechanochemistry. Mechanochemical experiments reveal the decomposition of guanosine and uridine promoted by nickel(II) and carbonate ions into guanine and uracil, respectively which were identified by HPLC and 1H NMR spectroscopy (this applied only to uracil). Additionally, DFT methodologies were used to probe the energetic viability of several degradation pathways, including in the presence of the same ions. Three mechanisms were analysed via ribose ring-opening: dry, single molecule water- and metal-assisted, which confirmed the mechanochemical degradation of ribonucleosides, with nucleobase preservation. These results can be applied to interpret the organic content of terrestrial and extra-terrestrial samples after mechanochemical treatment.
Comparison between the Jaeger Oxycon Pro and the COSMED Quark RMR Metabolic Carts for Cardiopulmonary Exercise Testing in the Context of an Aerosol-Borne Infectious Disease
Authors: Muñoz-Muñoz Miguel , Leal-Martín Javier , Baltasar-Fernandez Ivan , Alcazar Julian , Alegre Luis M. , Losa-Reyna José , Ara Ignacio
Published: October 2023

Several factors, such as internal algorithm, sensor technology, use of antibacterial filters or obsolescence, might explain the differences among computerised metabolic carts when measuring gas exchange parameters during cardiopulmonary exercise tests (CPET). Thus, the main aim of this study was to compare the Jaeger Oxycon Pro and the Quark RMR during CPET in the context of an aerosol-borne infectious disease. Forty-two participants (19-54 years old) performed two non-consecutive maximal graded exercise tests on a cycle-ergometer on two counterbalance and different days using the Oxycon Pro, with and antibacterial filter, and the Quark RMR in a randomized order. Differences between devices were tested using a generalized linear model adjusted by Bonferroni, and correlation and agreement was assessed using Pearson’s correlation coefficient (R), intraclass coefficient correlation (ICC), Lin’s concordance correlation coefficient (CCC) and Bland-Altman plots. No significant differences were found between devices in any of metabolic or ventilatory parameters for cardiorespiratory fitness assessment (VO2max: 3131.3±882.1 vs. 3189.8±894.8, p=0.071, VCO2max: 3436.3±936.0 vs. 3550.3±1043.2, p=0.071, for Quark RMR and Oxycon Pro, respectively). However, Bland-Altman plots showed a trivial tendency towards Oxycon Pro overestimation relative to Quark RMR as air flow volume increases. Both devices showed strong correlation and high level of agreement during maximal and submaximal exercise intensities (Pearson’s R: 0.974 & 0.977; ICC: 0.985 & 0.987; Lin’s CCC: 0.971 & 0.974, for VO2 and VCO2, respectively). Therefore, providing consistency to CPET data comparison between both devices, and insight into whether the use of these metabolic carts could be interchangeable or combined when a single device cannot be used for CPET assessment.
Physicochemical and Oscillatory Properties, Microstructure, and Survival of Bifidobacterum longum subsp. longum TISTR 2195 of Yogurt Ice Cream with different Fat Contents and Prebiotics
Authors: Toommuangpak Watcharaporn , Thaiudom Siwatt
Published: October 2023

Yogurt ice cream (YIC) containing Bifidobacterum longum subsp. longum TISTR 2195 (B. longum) with different fat contents (2 and 10% fat) and prebiotics (galacto-oligosaccharide, GOS and fructo-oligosaccharide, FOS) was investigated for its physicochemical properties, microstructure, and survival of B. longum during storage time and in a simulated gastrointestinal tract. Fat contents affected pH, fat particle size, hardness, melting rate, and solid-like characteristic of ice cream while FOS seemed to enhance the hardness and elasticity of YIC better than GOS due to less solubility and denser microstructure which exhibited more solid-like properties than YIC containing GOS. The interaction effect of fat content at 10% fat and FOS in YIC seemed to promote more sensorial acceptance than the ice cream containing 2% fat and GOS. The fat content, concentration of prebiotics, and type of prebiotics were attributed to the survival of B. longum in YIC. Moreover, the survival number of B. longum in YIC during storage for 180 days and in the simulated gastrointestinal tract was still in 106 CFU g-1, which is considered to benefit human health. Finally, probiotic YIC in this study could be used as a guide for functional ice cream manufacture future.
Mechanical Properties Comparison of Geo Polymer Brick Dried by Electrical and Passive Solar Devices With Phase Change Material (Paraffin Wax)
Authors: Jeevan Ashok Kumar , Sattanathan Muthuvel , Issac Selvaraj Rajay Vedaraj , Ramoni Monsuru , Shanmugam Ragavanantham , Ranjitharamasamy Sudhakara Pandian
Published: October 2023

In Geo Polymer bricks (GPB), fly ash content which is a waste from power plants is converted into bricks by chemical treatment. GPB can be dried by using appropriate curing methods. Conven-tionally electric oven curing is one of the prominent methods. Using solar dryer instead of elec-trical oven gives added advantage of saving high grade electrical energy. So in this work solar dryer with PCM (Phase Change materials) Paraffin Wax and without PCM is used for curing ap-plication. GPB are gaining added advantage when compared to conventional bricks like cement and sand bricks in terms of strength. GPB has been taken as specimen for comparing the com-pressive, tensile split strength and flexural strength by electrical energy based curing and solar energy based curing. It is experimentally observed that solar energy based curing with PCM and without PCM exhibits higher compressive strength, higher tensile split strength and flexural strength when compared to electrical energy based curing. Solar curing with PCM shows higher compressive strength, higher tensile split strength and flexural strength when compared to Solar curing without PCM. Open solar curing is a traditional technique but nowadays aggressive cli-matic conditions can lead to severe damage of Geo polymers. The novelty of this work is to suggest to study the effect of PCM like paraffin wax in solar drying on curing time, mechanical properties of GPB.