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Mobile learning (m-learning) is a crucial educational technology for teacher education due to its significant benefits and the development of mobile technology. This study's objective is to conduct a systematic review and present a recent synthesis of the m-learning literature from 2018 to 2023 in teacher education relating to subject publication year, geographic distribution, matter domains, mobile devices and technologies used, research methodologies used to examine the implementation of m-learning, results for pre-service teachers, as well as benefits and challenges of m-learning adoption. The study used the systematic review methodology and PRISMA guidelines. A list of 27 studies was included from several relevant studies in four, Google Scholar, Mendeley, ScienceDirect, and Scopus, databases using inclusion and exclusion criteria to evaluate the full text after screening the titles and abstracts. The results of this study show that m-learning has garnered interest in numerous nations worldwide, applied in different subject matter domains with the use of various mobile devices and technologies. More significantly, the findings show that using mobile learning to learn positively impacts how pre-service teachers develop their knowledge, skills, and attitudes. Additionally, adopting this learning style recently in teacher education has certain advantages and challenges, requiring lecturers, pre-service teachers, and institutions to have the necessary equipment for knowledge, skills and facilities to achieve efficiency. Consequently, the results of this study can be used as a guide for research on m-learning in the future and contribute to the body of knowledge about this pedagogical strategy for teacher training.

Abstract The development of soft computing methods has had a significant influence on the subject of autonomous intelligent agriculture. This paper offers a system for autonomous greenhouse navigation that employs a fuzzy control algorithm and a deep learning-based disease classification model for tomato plants, identifying illnesses using photos of tomato leaves. The primary novelty in this study is the introduction of an upgraded Deep Convolutional Generative Adversarial Network (DCGAN) that creates augmented pictures of disease tomato leaves from original genuine samples, considerably enhancing the training dataset. To find the optimum training model, four deep learning networks (VGG19, Inception-v3, DenseNet-201, and ResNet-152) were carefully compared on a dataset of nine tomato leaf disease classes. These models have validation accuracy of 92.32%, 90.83%, 96.61%, and 97.07%, respectively, when using the original PlantVillage dataset. The system then uses an enhanced dataset with ResNet-152 network design to achieve a high accuracy of 99.69%, as compared to the original dataset with ResNet-152’s accuracy of 97.07%. This improvement indicates the use of the proposed DCGAN in improving the performance of the deep learning model for greenhouse plant monitoring and disease detection. Furthermore, the proposed approach may have a broader use in various agricultural scenarios, potentially altering the field of autonomous intelligent agriculture.

The article gives an in-depth understanding of the commitment to corporate social responsibility (CSR) on labour under the new generation of free trade agreements (FTAs) of the European Union (EU), and especially, the EU – Vietnam Free Trade Agreement (EVFTA). Following that, via the EU’s foreign and trade policies, this research clarifies the history as well as the evolution of the CSR commitments in the EU’s new generation FTAs. On that basis, this article also delves into the nature of CSR commitments related to labour in the EVFTA. Last but not least, the article reviews the current legislation of the EU and its member states as partners and suggests different policy implications that Vietnam and other developing nations might adopt to execute their CSR commitments in the context of global sustainable development.

Abstract Pangenome inference is an indispensable step in bacterial genomics, yet its scalability poses a challenge due to the rapid growth of genomic collections. This paper presents PanTA, a software package designed for constructing pangenomes of large bacterial datasets, showing unprecedented efficiency levels multiple times higher than existing tools. PanTA introduces a novel mechanism to construct the pangenome progressively without rebuilding the accumulated collection from scratch. The progressive mode is shown to consume orders of magnitude less computational resources than existing solutions in managing growing datasets. The software is open source and is publicly available at https://github.com/amromics/panta and at 10.6084/m9.figshare.23724705 .

This paper presents a study on behavior of vertical stress profiles in head-enlarged (PF) and conventional CDM columns obtained from field static load test (SLT) and numerical analyses. Results from the numerical SLT on PF and CDM columns installed in ideally elastoplastic soil show that, due to the configuration of the column head, plastic failure points happen around the CDM column at lower load levels than that for the case of the PF column, and the load on PF column is showed to transfer to the soil more pronouncedly than that on the CDM column. The stress distribution and load – settlement curves obtained from the numerical analyses on the instrumented PF columns in general agree well with that obtained from the field tests. The induced stress profiles obtained from both numerical analyses and measured data show that there exists a major peak point of concentrated stress at the bottom of the cone section. This concentrated stress point may make the columns severely cracked and failed and this must be well aware in the design of bearing capacity of the PF columns.

In this study, a nanostructured NdFeO3 material was synthesized via a simple process of the hydrolysis of Nd (III) and Fe (III) cations in hot water with 5% NaOH as a precipitating agent. According to the results of the thermal behaviors of each hydroxide, either containing Fe (III) or Nd (III), the perovskite type of neodymium orthoferrite NdFeO3 was simply synthesized by annealing a mixture of Fe (III) and Nd (III) hydroxides at 750 °C. The nanostructured NdFeO3 was obtained in spherical granules with diameters of around 30 nm. The magnetic properties of the material were a coercive force (Hc) of 136.76 Oe, a remanent magnetization (Mr) of 0.68 emu·g−1, and a saturation magnetization (Ms) of 0.79 emu·g−1.

Background Subtraction (BgS) is a widely researched technique to develop online Change Detection algorithms for static video cameras. Many BgS methods have employed the unsupervised, adaptive approach of Gaussian Mixture Model (GMM) to produce decent backgrounds, but they lack proper consideration of scene semantics to produce better foregrounds. On the other hand, with considerable computational expenses, BgS with Deep Neural Networks (DNN) is able to produce accurate background and foreground segments. In our research, we blend both approaches for the best. First, we formulated a network called Convolutional Density Approximation (CDA) for direct density estimation of background models. Then, we propose a self-supervised training strategy for CDA to adaptively capture high-frequency color distributions for the corresponding backgrounds. Finally, we show that background models can indeed assist foreground extraction by an efficient Neural Motion Subtraction (NeMos) network. Our experiments verify competitive results in the balance between effectiveness and efficiency.

The escalating challenge of antibiotic resistance has driven the innovation of new antibacterial and antifouling materials. Recent developments focus on nature-inspired topographical engineering and nanostructured surfaces to combat resistant bacteria. This review discusses these advances, emphasizing the potential of nanoantibiotics and biopolymers. Nanoantibiotics revitalize drug effectiveness by encapsulating them in nanoparticles, presenting a new strategy to fight pathogens. Biopolymers, eco-friendly and biodegradable, emerge as a sustainable alternative, with applications in food safety and beyond. The exploration of these materials signifies a leap in design, fabrication, and the possibility of cost-effective, large-scale production, highlighting a promising avenue for commercial applications to tackle antibiotic resistance and biofouling effectively.

In this paper, a novel composite right-/left-handed (CRLH) leaky-wave antenna with a simple structure, low cost, high gain, and wide beam-scanning range performance for the millimeter wave (mmWave) band. The proposed antenna comprises a series-fed array of asymmetrically slotted elliptical CRLH unit cells loaded with a short-circuit stub. By optimizing the length of the stub, the condition of the CRLH structure is balanced to enable beam scanning from the backward to the forward direction within the mmWave band. The proposed antenna exhibits a wide beam-scanning angle of 112° (−60° to 52°), coupled with high gain and radiation efficiency at the designated band. Furthermore, it is fabricated on a traditional microwave substrate, Rogers RT/duroid 5880, thus offering a cost-effective approach to streamlining the manufacturing process. The measurement results confirmed a peak realized gain of 16.8 dBi. The excellent performance achieved using a low-cost design makes the proposed antenna attractive for 5G mmWave applications.

Abstract Background Genomic selection (GS) is an efficient breeding strategy to improve quantitative traits. It is necessary to calculate genomic estimated breeding values (GEBVs) for GS. This study investigated the prediction accuracy of GEBVs for five fruit traits including fruit weight, fruit width, fruit height, pericarp thickness, and Brix. Two tomato germplasm collections (TGC1 and TGC2) were used as training populations, consisting of 162 and 191 accessions, respectively. Results Large phenotypic variations for the fruit traits were found in these collections and the 51K Axiom™ SNP array generated confident 31,142 SNPs. Prediction accuracy was evaluated using different cross-validation methods, GS models, and marker sets in three training populations (TGC1, TGC2, and combined). For cross-validation, LOOCV was effective as k-fold across traits and training populations. The parametric (RR-BLUP, Bayes A, and Bayesian LASSO) and non-parametric (RKHS, SVM, and random forest) models showed different prediction accuracies (0.594–0.870) between traits and training populations. Of these, random forest was the best model for fruit weight (0.780–0.835), fruit width (0.791–0.865), and pericarp thickness (0.643–0.866). The effect of marker density was trait-dependent and reached a plateau for each trait with 768−12,288 SNPs. Two additional sets of 192 and 96 SNPs from GWAS revealed higher prediction accuracies for the fruit traits compared to the 31,142 SNPs and eight subsets. Conclusion Our study explored several factors to increase the prediction accuracy of GEBVs for fruit traits in tomato. The results can facilitate development of advanced GS strategies with cost-effective marker sets for improving fruit traits as well as other traits. Consequently, GS will be successfully applied to accelerate the tomato breeding process for developing elite cultivars.

Abstract The glutaminase enzymes GAC and GLS2 catalyze the hydrolysis of glutamine to glutamate, satisfying the ‘glutamine addiction’ of cancer cells. They are the targets of anti-cancer drugs; however, their mechanisms of activation and catalytic activity have been unclear. Here we demonstrate that the ability of GAC and GLS2 to form filaments is directly coupled to their catalytic activity and present their cryo-EM structures which provide a view of the conformational states essential for catalysis. Filament formation guides an ‘activation loop’ to assume a specific conformation that works together with a ‘lid’ to close over the active site and position glutamine for nucleophilic attack by an essential serine. Our findings highlight how ankyrin repeats on GLS2 regulate enzymatic activity, while allosteric activators stabilize, and clinically relevant inhibitors block, filament formation that enables glutaminases to catalyze glutaminolysis and support cancer progression.

The title compound, C27H20N4O3S, crystallizes in the monoclinic system, space group P21/n, with Z = 4. The global shape of the molecule is determined by the orientation of the substituents on the central 4H-1,2,4-triazole ring. The nitrophenyl ring, phenyl ring, and naphthalene ring system are oriented at dihedral angles of 82.95 (17), 77.14 (18) and 89.46 (15)°, respectively, with respect to the triazole ring. The crystal packing features chain formation in the b-axis direction by S...O interactions. A Hirshfeld surface analysis indicates that the highest contributions to surface contacts arise from contacts in which H atoms are involved.

AbstractCareer guidance, which strongly influences the world labor market and social structure, is studied in many countries on different levels. This study aims to explore the number, growth trajectories, and geographic distribution of studies on Career guidance in general schools and identify prominent influential authors, sources, publications, and new research issues. Bibliometric analysis is employed to analyze all 382 publications on the topic of Career guidance in general schools in the Scopus database. The data shows that the volume of scientific publications in this field remained steady from 1964 to 2010, while the period from 2010 to 2022 experienced a significant increase. There is a total of 2412 authors participating in research on this topic, from 1609 institutions, in 98 different countries and regions. Besides the studies of American, Italian, and Russian scholars, researchers in the Netherlands, the United Kingdom, and Australia also play a notable role in this topic. The most cited and notable journal on this topic is the British Journal of Guidance and Counseling. Recently, the most prevalent research topics include influencing general school students to prepare for their career readiness, and the opportunity to create social justice in understanding and deciding on career options.

The aerodynamic drag reduction of ground vehicles is crucial for meeting the increasingly strict emission standards. In this context, a potential approach to achieve this objective is to use active flow control techniques. Many active flow control techniques have been applied for ground vehicles, and the unsteady jet device has been proven to have better control energy efficiency than some other flow actuators. Therefore, this study focuses on applying this unsteady jet technique to a realistic truck model. The main parameters of the control flow device, including jet amplitude, jet angle, and control frequency were optimized to reduce the aerodynamic drag of the truck model and achieve the maximum control energy efficiency. Numerical studies were performed based on the CFD method with the k-ω SST turbulence model. A 25-level optimal Latin Hypercube design experimental study was conducted. The optimization method based on the Kriging response surface model and genetic algorithm was chosen to determine the optimal solution. The results show that the maximum energy efficiency is 9.174 % using the unsteady jet devices with the optimal parameters on the small-scale truck model.

Hydrotalcite-Ag nanoparticles (HT-Ag NPs) have garnered significant attention in research due to their remarkable antibacterial activity and excellent photocatalytic properties. Consequently, they have been utilized in various fields, such as pharmaceuticals, medicine, electronics, and environmental treatment. However, the synthesis of HT-Ag nanoparticles often involves the use of NaBH4, a chemical reducing agent, to reduce Ag (I) ions and form Ag NPs on HT. Nevertheless, the residue of chemical reducing agents can lead to environmental pollution as above mentioned. The approach of utilizing plant extracts for the synthesis of Ag NPs decorated on HT has captivated many scientists due to its eco-friendly and environmentally sustainable process. Additionally, the plant extract plays a crucial role in stabilizing Ag NPs within HT-Ag structures. This paper presents a green synthesis of hydrotalcite-silver (HT-Ag) nanosheets using an AgNO3 salt solution as a precursor and areca (Areca catechu L.) nut extract as a reducing agent. The HT nanosheets, synthesized by a co-precipitation method combined with a hydrothermal method, exhibited an ordered lamellar layer structure. The areca seed extract in 99.5 % ethanol solvent acts as a reducing agent to convert Ag(I) ions into silver nanoparticles (Ag NPs). The presence of Ag NPs on the surface of HT nanosheets was confirmed using UV–Vis spectroscopy, XRD, AAS, HR-TEM, and SEM methods. The results indicated that Ag NPs are spherical in shape and uniformly dispersed on the surface of HT. The particle size of Ag NPs ranged from 15 nm to 40 nm. The yield of the Ag NPs synthesis process on HT ranged from 60.79 % to 85.89 %, depending on the concentration of AgNO3 salt solution. The antibacterial properties, including their effectiveness against E. coli and S. aureus, were tested using the agar well diffusion method to determine the zone of inhibition. The minimum inhibitory concentration (MIC) value of HT-Ag nanosheets has also been evaluated. Specifically, the study focused on evaluating the antibacterial activity of HT-Ag nanosheets using a marine Gram-negative bacterium, P. stutzeri B27, to explore their potential applications in materials designed for use in marine environments. Furthermore, the durability of HT-Ag nanosheets was assessed. The obtained results demonstrated that the Ag NPs decorated on HT exhibited excellent antibacterial activity against E. coli, S. aureus, and P. stutzeri B27, making them suitable for applications as antibacterial and enhancing additives for polymer systems, particularly in materials used in marine environments.

Relevance. In the face of current climate change trends, coastal erosion occurs more frequently in coastal lands. This problem not only causes damage to houses and works, but also affects the lives of coastal people. Quang Nam has a coastline of 125 km, which is an area that has been seriously eroded under the impact of hydrodynamic factors, along with extreme weather phenomena, affecting people's lives, and degrade the local economy. Aim. This article presents research on shoreline changes in Quang Nam region using the method of integrating remote sensing and GIS to create a change map. From there, identify erosion and deposition areas to help management agencies pay attention to the protection and development orientation of Quang Nam province in the context of climate change. Methods. Shoreline extraction method in combination with GIS to calculate the coastline change and combines with storm statistics to assess the shoreline change. Results. In the whole study area, erosion is dominant over deposition. Erosion is concentrated mainly in An Bang, North Cua Dai, Duy Hai and Tam Tien areas, ranging from 3.9–9.2 m/year. Deposition is concentrated mainly in the areas south of Cua Dai and Tam Hoa (near the mouth of Truong Giang river). In addition, the analysis results of shoreline changes in Quang Nam area, when combined with storm data affecting this area, also show a positive correlation. Research results can contribute useful information to local authorities to have solutions for planning and managing coastal areas.

Abstract Extracellular vesicles (EVs) are emerging as a promising drug delivery vehicle as they are biocompatible and capable of targeted delivery. However, clinical translation of EVs remains challenging due to the lack of standardized and scalable manufacturing protocols to consistently isolate small EVs (sEVs) with both high yield and high purity. The heterogenous nature of sEVs leading to unknown composition of biocargos causes further pushback due to safety concerns. In order to address these issues, we developed a robust quality‐controlled multi‐stage process to produce and isolate sEVs from human embryonic kidney HEK293F cells. We then compared different 2‐step and 3‐step workflows for eliminating protein impurities and cell‐free nucleic acids to meet acceptable limits of regulatory authorities. Our results showed that sEV production was maximized when HEK293F cells were grown at high‐density stationary phase in semi‐continuous culture. The novel 3‐step workflow combining tangential flow filtration, sucrose‐cushion ultracentrifugation and bind‐elute size‐exclusion chromatography outperformed other methods in sEV purity while still preserved high yield and particle integrity. The purified HEK293F‐derived sEVs were thoroughly characterized for identity including sub‐population analysis, content profiling including proteomics and miRNA sequencing, and demonstrated excellent preclinical safety profile in both in‐vitro and in‐vivo testing. Our rigorous enrichment workflow and comprehensive characterization will help advance the development of EVs, particularly HEK293F‐derived sEVs, to be safe and reliable drug carriers for therapeutic applications.

In this paper, we evaluate short packet communication (SPC) for a cooperative system where one relay assists data transmission between one multi-antenna source and one single antenna destination with the presence of co-channel interference at the relay. Two transmission schemes, i.e., transmit antenna selection (TAS) scheme and beamforming scheme (BF), are considered. Based on metric of SPC, we derive the average block error rate (BLER) for the system in asymptotic and closed-form expressions for both schemes. In addition, a solution of optimal power allocation (OPA) to maximize end-to-end effective system throughput is proposed. Effects of parameters such as total transmit power, number of the source’s antennas, number of co-channel interference, and packet length on the performance of the system are evaluated. Finally, the results reveal that the performance of the OPA scheme outperforms that of the benchmark scheme, i.e., equal power allocation solution, in terms of BLER and the effective throughput for both the TAS and BF schemes. Moreover, the performance of the system reaches to saturation value with more antennas at the source. The findings indicate that the TAS and BF schemes have the same performance in terms of both the BLER and the effective throughput.

Background: Digital transformation refers to applying digital technology in various fields of society. In the last 5 years, digital transformation has spread to most areas of social life, including education. However, research on digital transformation in education is still fragmented.Objectives: The aim of the study was to present a comprehensive review of studies on digital transformation in education using bibliometric analysis.Methods: We searched the Scopus database from inception to 1 January 2023 using the search terms ‘digital transformation’ AND ‘education’ within abstracts, keywords, or titles of journal articles or conference papers written in English. The retrieved articles were analysed using VOSviewer and Biblioshiny tools.Results: A total of 1329 relevant studies were retrieved. Although the first paper in this field was published in 1999, the number of publications has increased rapidly only in the past 4 years. The most influential countries in this field are the developed countries (Russian Federation, Germany, and the United States), but scholars from the developing countries (Indonesia and Thailand) are among the most productive. Papers on digital transformation are frequently published in journals with lower rankings within the Scopus database. Using VOSviewer for keyword co-occurrence analysis, we classified the research topics related to digital transformation in educa-tion into four main groups: digital transformation in higher education under the impact of the coronavirus disease pandemic 2019 pandemic, applying the technolo-gies of the Fourth Industrial Revolution to education, digitization and digital compe-tence in education in the context of digital transformation, and learning forms using technology (for example, e-learning, m-learning, and blended learning) in higher-education institutions.Conclusions: Four research trends related to digital transformation in education were identified. These trends may also change as digital transformation continues to develop.

AbstractIn this study, twenty-five yeast strains were isolated from soil samples collected in the gold mining ore in Gia Lai, Vietnam. Among them, one isolate named GL1T could highly tolerate Cu2+ up to 10 mM, and the isolates could also grow in a wide range of pH (3–7), and temperature (10–40 °C). Dried biomass of GL1 was able to remove Cu2+ effectively up to 90.49% with a maximal biosorption capacity of 18.1 mg/g at pH 6, temperature 30 °C, and incubation time 60 min. Sequence analysis of rDNA indicated this strain was closely related to Rhodotorula mucilaginosa but with 1.53 and 3.46% nucleotide differences in the D1/D2 domain of the 28S rRNA gene and the ITS1-5.8S rRNA gene-ITS2 region sequence, respectively. Based on phylogenetic tree analysis and the biochemical characteristics, the strain appears to be a novel Rhodotorula species, and the name Rhodotorula aurum sp. nov. is proposed. This study provides us with more information about heavy metal-tolerant yeasts and it may produce a new tool for environmental control and metal recovery operations.

Chronic wounds often result in multiple infections with various kinds of bacteria and uncontrolled wound exudate, resulting in several healthcare issues. Advanced medicated nanofibres prepared by electrospinning have gained much attention for their topical application on infected chronic wounds. The objective of this work is to enhance the critical variables of ciprofloxacin-loaded polycaprolactone-silk sericin (PCL/SS-PVA-CIP) nanofibre production via the process of electrospinning. To examine the antibacterial effectiveness of PCL/SS-PVA-CIP nanocomposites, the material was tested against P. aeruginosa and S. aureus. The combination of PCL/SS-PVA-CIP exhibited potent inhibitory properties, with the most effective concentrations of ciprofloxacin (CIP) being 3 μg/g and 7.0 μg/g for each bacterium, respectively. The biocompatibility was evaluated by conducting cell reduction and proliferation studies using the human epidermal keratinocyte (HaCaT) cells and human gingival fibroblasts (HGFs) in vitro cell lines. The PCL/SS-PVA-CIP showed good cell compatibility with HaCaT and HGF cells, with effective proliferation even at antibiotic doses of up to 7.0 μg/g. The drug release effectiveness of the nanocomposites was assessed at various concentrations of CIP, resulting in a maximum cumulative release of 76.5% and 74.4% after 72 h for CIP concentrations of 3 μg/g and 7 μg/g, respectively. In summary, our study emphasizes the possibility of combining silk sericin (SS) and polycaprolactone (PCL) loading with CIP nanocomposite for wound management.

SARS-CoV-2 transmission is largely driven by heterogeneous dynamics at a local scale, leaving local health departments to design interventions with limited information. We analyzed SARS-CoV-2 genomes sampled between February 2020 and March 2022 jointly with epidemiological and cell phone mobility data to investigate fine scale spatiotemporal SARS-CoV-2 transmission dynamics in King County, Washington, a diverse, metropolitan US county. We applied an approximate structured coalescent approach to model transmission within and between North King County and South King County alongside the rate of outside introductions into the county. Our phylodynamic analyses reveal that following stay-at-home orders, the epidemic trajectories of North and South King County began to diverge. We find that South King County consistently had more reported and estimated cases, COVID-19 hospitalizations, and longer persistence of local viral transmission when compared to North King County, where viral importations from outside drove a larger proportion of new cases. Using mobility and demographic data, we also find that South King County experienced a more modest and less sustained reduction in mobility following stay-at-home orders than North King County, while also bearing more socioeconomic inequities that might contribute to a disproportionate burden of SARS-CoV-2 transmission. Overall, our findings suggest a role for local-scale phylodynamics in understanding the heterogeneous transmission landscape.

Relevance. Achieving the greatest rate of penetration is the aim of every drilling engineer because it is one of the most significant factors influencing drilling costs. However, a variety of drilling conditions could have an impact on rate of penetration, complicating its forecast. Aim. To suggest a novel strategy to accurately predict rate of penetration and optimize drilling parameters. Objects. Real-time drilling data of a few wells in the Ca Tam oil field, Vietnam, with more than 900 datasets including significant parameters like rotary speed, weight on bit, standpipe pressure, flow rate, weight of mud, torque. Methods. Various methods using Artificial Neural Network was proposed to estimate rate of penetration. Results. The number of neurons in a hidden layer was varied then the results of different Artificial Neural Network models were compared in order to obtain the optimal model. The final Artificial Neural Network model shows high exactness when contrasted with actual rate of penetration, in this manner, it tends to be suggested as a successful and reasonable approach to predict the rate of penetration of different wells in the Ca Tam oil field. Based on the proposed Artificial Neural Network model, the optimal weight on bit was determined for the drilling interval from 1800 to 2300 m of oil wells in the research region.

Background: Biomarker testing has gradually become standard of care in precision oncology to help physicians select optimal treatment for patients. Compared to single-gene or small gene panel testing, comprehensive genomic profiling (CGP) has emerged as a more time- and tissue-efficient method. This study demonstrated in-depth analytical validation of K-4CARE, a CGP assay that integrates circulating tumor DNA (ctDNA) tracking for residual cancer surveillance.Methods: The assay utilized a panel of 473 cancer-relevant genes with a total length of 1.7 Mb. Reference standards were used to evaluate limit of detection (LOD), concordance, sensitivity, specificity and precision of the assay to detect single nucleotide variants (SNVs), small insertion/deletions (Indels), gene amplification and fusion, microsatellite instability (MSI) and tumor mutational burden (TMB). The assay was then benchmarked against orthogonal methods using 155 clinical samples from 10 cancer types. In selected cancers, top tumor-derived somatic mutations, as ranked by our proprietary algorithm, were used to detect ctDNA in the plasma.Results: For detection of somatic SNVs and Indels, gene fusion and amplification, the assay had sensitivity of >99%, 94% and >99% respectively, and specificity of >99%. Detection of germline variants also achieved sensitivity and specificity of >99%. For TMB measurement, the correlation coefficient between whole-exome sequencing and our targeted panel was 97%. MSI analysis when benchmarked against polymerase chain reaction method showed sensitivity of 94% and specificity of >99%. The concordance between our assay and the TruSight Oncology 500 assay for detection of somatic variants, TMB and MSI measurement was 100%, 89%, and 98% respectively. When CGP-informed mutations were used to personalize ctDNA tracking, the detection rate of ctDNA in liquid biopsy was 79%, and clinical utility in cancer surveillance was demonstrated in 2 case studies.Conclusion: K-4CARE™ assay provides comprehensive and reliable genomic information that fulfills all guideline-based biomarker testing for both targeted therapy and immunotherapy. Integration of ctDNA tracking helps clinicians to further monitor treatment response and ultimately provide well-rounded care to cancer patients.

Service innovation has been seen as a significant source of competitive advantage between the market and the business since its inception over two decades ago. Due to the growing interest in service innovation, this study delves deeper into the service innovation phenomenon to understand how service innovation has emerged and provides a comprehensive view of the phenomenon development of service innovation. A review of a systematic investigation of the evolution of “service innovation” in various sectors by conducting a comprehensive analysis (qualitative and quantitative) using 850 publications from the Web of Science was published during the 1996 - 2022 period. The quantitative method used was bibliometrics analysis (citation and co-citation) by VOS-viewer software. The results show that five clusters are distinguishable. Each cluster shows different characteristics of the service innovation sector, including innovation in market-oriented service companies, new service development, service innovation process, adding service value in manufacturing enterprises, and co-creator of value in services. Specifically, we analyse which research flows are relevant to service innovation and compare these themes over time. In-depth analysis and discussion of the five themes have helped to uncover two more sub-themes, service innovation and service innovation in brand engagement that scholars have been interested in and have developed. This paper supports the assertion that service innovation has an interdisciplinary theoretical foundation and that the structure of the service innovation research platform has changed significantly over time.

Cell-free Massive multiple-input multiple-output can offer many degrees of freedom for the high data rate and coverage probability. This network topology is one of the cutting-edge technologies potentially applied for next-generation wireless communications. In the canonical structure, however, each access point needs to accurately estimate the channel state information for the signal detection in the uplink and the precoding design in the downlink. Due to the finite lengths of coherence intervals, pilot contamination is one of the bottlenecks, reducing the data throughput of each user. We propose an efficient pilot assignment scheme called location-based pilot assignment (LPA) to overcome this limitation. It takes full advantage of the number of orthogonal pilot signals into account. The proposed algorithm divides the coverage area into smaller areas based on the number of users, where each area uses a subset of the pilot signals. Numerical results show that the proposed pilot assignment, LPA, offers good spectral efficiency to every users in the network with a tolerable computational complexity.

Abstract Flagellin, the TLR5 agonist, shows potent adjuvant activities in diverse vaccines and immunotherapies. Vibrio vulnificus flagellin B expressed in eukaryotic cells (eFlaB) could not stimulate TLR5 signaling. Enzymatic deglycosylation restored eFlaB’s TLR5 stimulating functionality, suggesting that glycosylation interferes with eFlaB binding to TLR5. Site-directed mutagenesis of N-glycosylation residues restored TLR5 stimulation and adjuvanticity. Collectively, deglycosylated eFlaB may provide a built-in adjuvant platform for eukaryotic-expressed antigens and nucleic acid vaccines.

Tourism has emerged as one of the foremost industries experiencing rapid growth. Over the past few decades, the sector has witnessed continuous development in Indonesia, evident from the increasing number of foreign tourist arrivals. The rapid growth of tourism in various regions has undeniably yielded positive impacts on both investment and the overall economy. However, it has also given rise to a multitude of challenges that need to be addressed. One of the challenges pertains to the issue of land ownership, specifically concerning the acquisition of residents' lands surrounding tourist destinations by foreign individuals, which is strictly prohibited under Indonesian law. Therefore, a comparative analysis between Indonesia and Malaysia is needed to identify regulation problems to potentially increase cases of legal smuggling of foreign land ownership transfers. This study explains the practice of land ownership by foreigners in the Pesisir Barat District of Lampung, along with the associated problems analyzed through a socio-legal approach. The results show that tourism undeniably benefits the economic sector, and resulted in legal infringements concerning land ownership, leading to the marginalization and displacement of local communities. This study adopts a comparative law method, elucidating the respective provisions of both Indonesia and Malaysia, supplemented by a normative juridical approach to examine legal principles, regulations, and systematics through the examination of relevant library materials. Consequently, it is essential to enhance the regulations surrounding the transfer of land to foreigners, including Foreign Citizens and Foreign Legal Entities with representatives in Indonesia, emulating the stringent land tenure restrictions imposed by Malaysia on foreign nationals.