bluuebunny/crossref_metadata_2025 huggingface dataset:
Efficacy and tolerability of full spectrum hemp oil in dogs living with pain in common household settings
Authors: Panda Chinmayee , Rathinasabapathy Thirumurugan , Metzger Brandon , Dodson Sheila , Hanson Dirk , Griffiths Jody , Komarnytsky Slavko
Published: July 2024

Lameness and restricted mobility are a significant concern in companion animals experiencing chronic pain, inflammation, or age-related pathologies. The growing awareness of health risks and side effects associated with the long-term use of prescription analgesics requires different management strategies to address these issues. In this study, we conducted a crossover evaluation of the effect of full spectrum hemp oil dosed orally at 2 mg/kg BID phytocannabinoids for 8 weeks in dogs (n = 37) living with pain in common household settings. Owner-reported canine pain, home activity, accelerometer-based activity, walkway-based gait, and tolerability were assessed at each phase of the study. Secondary endpoints included changes in blood biochemistry, liver enzymes, inflammatory biomarkers, and plasma metabolites. The intervention was positively associated with a decrease in pain scores (−46.2%, p = 0.0016), increased ability to walk up and down the stairs (10.6–14.7%, p < 0.05), and improved daily activity (25.9%, p = 0.0038). Decreases in plasma levels of proinflammatory cytokines TNF-α, IL-6, and IL-8 were also observed. Taken together, these findings suggest that the benefits of nutritional supplementation with hemp oil could include control of pain, greater mobility, and an overall improvement in the animal wellbeing.
Growth factor and cytokine characterization of canine platelet lysate with variable leukocyte concentration, plasma content, and heat-sensitive proteins
Authors: Lunardon Thainá , Sumner Scarlett M. , Mollabashi Melikasadat , Darzenta Nikolia , Davis Emily , Naskou Maria C.
Published: July 2024

Background

Platelet lysate is an acellular platelet product containing factors released from secretory granules, including cytokines and growth factors. This study aimed to evaluate different centrifugation methods used to prepare canine platelet lysate with variable content of leukocytes, plasma, and heat-sensitive proteins.

Methods

Whole blood was collected from six dogs and two double-spin preparation methods were used to generate the platelet-rich plasma with reduced (PRP) and high (L-PRP) concentration of leukocytes. A portion of both methods underwent plasma depletion via centrifugation and platelet lysate was generated via freeze–thaw cycles. A portion of the generated platelet lysate underwent complement inactivation via heat treatment. Growth factors (TGF-β1, VEGF, TNF-α, PDGF-BB, HGF) were quantified in all different platelet lysate preparations using ELISAs.

Results

Both platelet-rich plasma preparations had a 6.7-fold increase in platelet concentration. White blood cell (WBC) concentration compared to whole blood increased 1.2-fold times in PRP and 1.9-fold times in L-PRP. Negligible concentrations of platelets, WBC, and hematocrit were identified in all lysate groups. Statistically significant differences were identified for PDGF, VEGF, and TNF-α, and not for TGF-β or HGF. No growth factor differences were noted between centrifugation methods. PDGF was significantly higher in platelet lysate that was plasma depleted. VEGF was significantly higher in heat-treated lysate groups. TNF-α concentrations were overall very low, though were noted to significantly increase following plasma depletion.

Conclusion

These results support that growth factors and cytokine release can be affected by the platelet lysate preparation and processing.
ENGINE—An EHS Project for Future Guidelines
Authors: Stabilini Cesare , Antoniou Stavros , Berrevoet Frederik , Boermeester Marja , Bracale Umberto , de Beaux Andrew , East Barbora , Gök Hakan , Lopez Cano Manuel , Muysoms Filip , Capoccia Giovannini Sara , Simons Maarten
Published: July 2024

Clinical guidelines are evidence-based recommendations developed by healthcare organizations or expert panels to assist healthcare providers and patients in making appropriate and reliable decisions regarding specific health conditions, aiming to enhance the quality of healthcare by promoting best practices, reducing variations in care, and at the same time, allowing tailored clinical decision-making. European Hernia Society (EHS) guidelines aim to provide surgeons a reliable set of answers to their pertinent clinical questions and a tool to base their activity as experts in the management of abdominal wall defects. The traditional approach to guideline production is based on gathering key opinion leader in a particular field, to address a number of key questions, appraising papers, presenting evidence and produce final recommendations based on the literature and consensus. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) method offers a transparent and structured process for developing and presenting evidence summaries and for carrying out the steps involved in developing recommendations. Its main strength lies in guiding complex judgments that balance the need for simplicity with the requirement for complete and transparent consideration of all important issues. EHS guidelines are of overall good quality but the application of GRADE method, began with EHS guidelines on open abdomen, and the increasing adherence to the process, has greatly improved the reliability of our guidelines. Currently, the need to application of this methodology and the creation of stable and dedicated group of researchers interested in following GRADE in the production of guidelines has been outlined in the literature. Considering that the production of clinical guidelines is a complex process, this paper aim to highlights the primary features of guideline production, GRADE methodology, the challenges associated with their adoption in the field of hernia surgery and the project of the EHS to establish a stable guidelines committee to provide technical and methodological support in update of previously published guideline or the creation of new ones.
Messy Broadcasting in Grid
Authors: Adibi Aria , Harutyunyan Hovhannes A.
Published: July 2024

In classical broadcast models, information is disseminated in synchronous rounds under the constant communication time model, wherein a node may only inform one of its neighbors in each time-unit—also known as the processor-bound model. These models assume either a coordinating leader or that each node has a set of coordinated actions optimized for each originator, which may require nodes to have sufficient storage, processing power, and the ability to determine the originator. This assumption is not always ideal, and a broadcast model based on the node’s local knowledge can sometimes be more effective. Messy models address these issues by eliminating the need for a leader, knowledge of the starting time, and the identity of the originator, relying solely on local knowledge available to each node. This paper investigates the messy broadcast time and optimal scheme in a grid graph, a structure widely used in computer networking systems, particularly in parallel computing, due to its robustness, scalability, fault tolerance, and simplicity. The focus is on scenarios where the originator is located at one of the corner vertices, aiming to understand the efficiency and performance of messy models in such grid structures.
Reduction in Nitrogen Fertilization Rate for Spring Wheat Due to Carbon Mineralization-Induced Nitrogen Mineralization
Authors: Sainju Upendra M.
Published: July 2024

Using predicted potential N mineralization (PNM) from its relationship with CO2 flush at 1 d incubation (CF) of soil samples in recommended N rates can reduce N fertilization rates for crops. This study used predicted PNM at the 0–15 cm depth to reduce N fertilization rates and examined spring wheat (Triticum aestivum L.) yields at two sites (Froid and Sidney) in Montana, USA. Cropping sequences at Froid were fall and spring till continuous spring wheat (FSTCW), no-till continuous spring wheat (NTCW1), no-till spring wheat–pea (Pisum sativum L.) (NTWP1), and spring till spring wheat–fallow (STWF). At Sidney, cropping sequences were conventional till spring wheat–fallow (CTWF), no-till spring wheat–fallow (NTWF), no-till continuous spring wheat (NTCW2), and no-till spring wheat–pea (NTWP2). Soil samples collected to a depth of 15 cm in September 2021 at both sites were analyzed for CF, PNM, and NO3-N contents, from which the reduction in N fertilization rate (RNFA) and the amount of N fertilizer applied (ANFA) to 2022 spring wheat were determined. In April 2022, spring wheat was grown with or without predicted PNM and annualized crop yields were compared. The CF and PNM were 114–137% greater for NTWP1 than STWF at Froid and 26–80% greater for NTCW2 than CTWF and NTWF at Sidney. The reduction in N fertilization rate was 26–102% greater for NTWP1 at Froid and 8–10% greater for NTCW2 and NTWF than other cropping sequences at Sidney. Annualized crop yield was 26–60% lower for crop–fallow than continuous cropping, but was not significantly different between with or without PNM at both sites. Using PNM can significantly reduce N fertilization rates for crops while sustaining dryland yields.
Sensitivity Analysis of Performance Indices of Surge-Flow Irrigation with System Variables Using the SIRMOD Model
Authors: Romay Catalina , Ezquerra-Canalejo Alejandra , Botta Guido Fernando
Published: July 2024

A current challenge of irrigationengineering is to modernize surface irrigation. For example, surge flow irrigation has the potential to increase the efficiency of applying irrigationwater. The objective of this study was to perform a sensitivity analysis using the performance indices: Application Efficiency (AE), Storage Efficiency (SE), Distribution Efficiency (DE), Deep Percolation (DP), and Runoff (RO), and to investigate their relationship with the main system variables: length (L), unit flow rate (Qo), surge cycles and surge time, using the SIRMOD model. The SIRMOD model simulates the hydraulics of surface irrigation at the field level. The model with the best fit of AE, DE, DP, and RO as a function of L, Qo, or surge cycles and surge time was a quadratic polynomial function with an R2 > 0.70. The model reflects the goodness of fit to the variable that is intended to be explained. The AE is an increasing function of L and a decreasing function of Qo, while DE and RO are decreasing functions of L and are increasing functions of Qo. The number of surges has an impact on the stream size of each surge and on the volume of water stored, but not on the performance indices. It was demonstrated that the SIRMOD model provided the ability to adjust the system parameters and design variables, giving answersto any surge flow configuration. The potential application efficiency (AEpot) (>80%) can be achieved by establishing, e.g., an optimal flow rate (Qopt), with a schedule for the cycle number and surge time, according to soil characteristics.
Simultaneous Biofortification: Interaction between Zinc and Selenium Regarding Their Accumulation in Wheat
Authors: Kong Lingxuan , Tao Yanjin , Xu Yang , Zhou Xuan , Fu Guohai , Zhao Lijie , Wang Qi , Li Huafen , Wan Yanan
Published: July 2024

Wheat (Triticum aestivum L.) is a staple food worldwide, and agronomic biofortification with selenium (Se) and zinc (Zn) is a simple and effective way to increase nutrient intake. This study aimed to evaluate the combined effects of Zn and Se on the biofortification of wheat grain. Zinc sulfate (ZnSO4·H2O, 1.74, 2.61 and 3.48 kg Zn hm−2) and sodium selenite (Na2SeO3, 15 and 30 g Se hm−2) were sprayed individually or simultaneously at key stages of wheat growth (the jointing, booting, and filling stage) under field conditions. On the basis of soil Zn application, the foliar application of Zn or Se alone greatly increased grain Zn by 12.07–71.88% (up to 41.66–64.30 mg kg−1), and grain Se content by 131.81–527.21% (up to 0.21–0.50 mg kg−1), while the soil application of Zn had little effect on grain Zn. Compared with the foliar application of Zn or Se alone, the co-application of Se increased the grain Zn content by 1.74–16.15%, while the co-application of Zn significantly reduced grain Se content by 25.43–86.34% and the effect was more pronounced with an increase in Zn dosage. Moreover, positive correlations were found between Zn and copper (Cu) in grains, and wheat grains could provide adequate dietary intakes of manganese (Mn), Cu, and molybdenum (Mo) for humans. In summary, the soil application of 11 kg Zn hm−2 combined with the foliar application of 2.61 kg Zn hm−2 and 30 g Se·hm−2 is a feasible Zn-Se co-enrichment strategy, which would provide the recommended nutrient intake (RNI) of 113.63–124.72% (female) and 68.18–74.84% (male) of Zn and 81.30–95.85% of Se.
Transcriptome-Wide Genetic Variations in the Legume Genus Leucaena for Fingerprinting and Breeding
Authors: Han Yong , Abair Alexander , van der Zanden Julian , Nageswara-Rao Madhugiri , Vasan Saipriyaa Purushotham , Bhoite Roopali , Castello Marieclaire , Bailey Donovan , Revell Clinton , Li Chengdao , Real Daniel
Published: July 2024

Leucaena is a versatile legume shrub/tree used as tropical livestock forage and in timber industries, but it is considered a high environmental weed risk due to its prolific seed production and broad environmental adaptation. Interspecific crossings between Leucaena species have been used to create non-flowering or sterile triploids that can display reduced weediness and other desirable traits for broad use in forest and agricultural settings. However, assessing the success of the hybridisation process before evaluating the sterility of putative hybrids in the target environment is advisable. Here, RNA sequencing was used to develop breeding markers for hybrid parental identification in Leucaena. RNA-seq was carried out on 20 diploid and one tetraploid Leucaena taxa, and transcriptome-wide unique genetic variants were identified relative to a L. trichandra draft genome. Over 16 million single-nucleotide polymorphisms (SNPs) and 0.8 million insertions and deletions (indels) were mapped. These sequence variations can differentiate all species of Leucaena from one another, and a core set of about 75,000 variants can be genetically mapped and transformed into genotyping arrays/chips for the conduction of population genetics, diversity assessment, and genome-wide association studies in Leucaena. For genetic fingerprinting, more than 1500 variants with even allele frequencies (0.4–0.6) among all species were filtered out for marker development and testing in planta. Notably, SNPs were preferable for future testing as they were more accurate and displayed higher transferability within the genus than indels. Hybridity testing of ca. 3300 putative progenies using SNP markers was also more reliable and highly consistent with the field observations. The developed markers pave the way for rapid, accurate, and cost-effective diversity assessments, variety identification and breeding selection in Leucaena.
What Place Is There for Long-Acting Antibiotics in the Management of Gram-Positive Infections? A Qualitative Cross-Sectional Study
Authors: Dinh Aurélien , Béraud Guillaume , Courjon Johan , Le Goff Yann , Ettahar Nicolas Kader , Grégoire Matthieu , Senneville Eric
Published: July 2024

Objectives. To identify the current practices with long half-life lipoglycopeptides (LGPs) and potential use/position of oritavancin. Results. Despite their indication being limited to skin and soft tissue infections (SSTIs), long half-life lipoglycopeptides are mainly used off-label to treat bone and joint infections (BJIs) and infective endocarditis. Oritavancin and dalbavancin are both semisynthetic lipoglycopeptide antibiotics with activity against Gram-positive organisms. The game-changing property of these two antibiotics is their one-time dosing. Due to its shorter half-life, oritavancin might have an advantage over dalbavancin for a treatment duration of less than 2 weeks, as it could be used both in prolonged treatments of complicated patients in BJIs or administered as a single-dose treatment for Gram-positive cocci infections usually treated by a 5- to 10-day antibiotic course. These infections include urinary tract infections, bacteremias, catheter-related infections, etc. In addition to the possibility of being used as an end-of-treatment injection, oritavancin could be used as an empiric therapy treatment in the postoperative period in the context of device-associated especially prosthetic joint infections to allow for the early discharge of the patient. Methods. A qualitative survey was conducted in March 2022 including sixteen infectiologists, one internist, five hospital pharmacists, and one pharmacologist. Conclusion. Long half-life lipoglycopeptides contribute to changing the paradigm in the management of acute bacterial infections, as infectiologists now consider a range of indications and patient profiles for one single drug. Oritavancin strengthens the therapeutic arsenal in numerous infections from BJIs to urinary tract infections and could help to manage specific clinical situations, on top of providing potential benefits for the hospital’s budget.
Patterns of Antibiotic Prescription in Endodontic Therapy in the Republic of Croatia
Authors: Sović Josipa , Šegović Sanja , Pavelić Božidar , Bago Ivona , Šutej Ivana , Tomašić Ivan
Published: July 2024

In response to the global trend of decreasing antibiotic usage, this study aimed to evaluate the nature and frequency of antibiotic prescriptions in conjunction with endodontic therapy in Croatia and to assess the attitudes of Croatian dental practitioners towards the endodontic treatment of patients susceptible to bacterial endocarditis. A survey questionnaire was sent to all dental practitioners in Croatia, achieving a response rate of 27%. The most frequently prescribed antibiotic was penicillin with clavulanic acid (63.4%), while standalone penicillin was less prevalent (18.6%). For patients exhibiting penicillin allergies, 90% of respondents indicated clindamycin as their preferred alternative. Antibiotics were mostly prescribed for localized acute apical abscesses without fever, followed by prophylaxis for infectious endocarditis and cellulitis. Only 1.3% of the respondents reported frequent antibiotic prescriptions without accompanying local treatment. While a substantial proportion of surveyed practitioners professed familiarity with the latest guidelines for antibiotic prophylaxis, their choice of antibiotics did not consistently reflect this claim. Most respondents conducted endodontic procedures on patients at risk of bacterial endocarditis. The findings highlight a need for targeted continuing education for dental practitioners in the Republic of Croatia, ensuring their practices align with current guidelines and global trends in antibiotic prescription.
Impact of a Bundle of Interventions on Quality-of-Care Indicators for Staphylococcus aureus Bacteraemia: A Single-Centre, Quasi-Experimental, Before–After Study
Authors: Casalini Giacomo , Pagani Cristina , Giacomelli Andrea , Galimberti Laura , Milazzo Laura , Coen Massimo , Reato Serena , Caloni Beatrice , Caronni Stefania , Pagano Simone , Lazzarin Samuel , Ridolfo Anna Lisa , Rimoldi Sara Giordana , Gori Andrea , Antinori Spinello
Published: July 2024

Staphylococcus aureus bacteraemia (SAB) is a life-threatening bloodstream infection. Improved adherence to quality-of-care indicators (QCIs) can significantly enhance patient outcomes. This quasi-experimental study evaluated the impact of a bundle of interventions on QCI adherence in adult patients with SAB. Additionally, a molecular rapid diagnostic test (mRDT) for S. aureus and methicillin resistance was introduced during weekdays. We compared pre-intervention (January–December 2022) and post-intervention (May 2023–April 2024) data on QCI adherence and time to appropriate treatment. A total of 56 and 40 SAB episodes were included in the pre- and post-intervention periods, respectively. Full QCI adherence significantly increased from 28.6% to 67.5% in the post-intervention period (p < 0.001). The mRDT diagnosed SAB in eight cases (26.6%), but the time to achieve appropriate target therapy did not improve in the post-intervention period (54 h (IQR 30–74) vs. 72 h (IQR 51–83), p = 0.131). The thirty-day mortality rate was comparable between the two periods (17.9% vs. 12.5%, p = 0.476). This study demonstrates that a bundle of interventions can substantially improve adherence to SAB management QCIs.
Targeting Metabolic–Redox Nexus to Regulate Drug Resistance: From Mechanism to Tumor Therapy
Authors: Wang Yuke , He Jingqiu , Lian Shan , Zeng Yan , He Sheng , Xu Jue , Luo Li , Yang Wenyong , Jiang Jingwen
Published: July 2024

Drug resistance is currently one of the biggest challenges in cancer treatment. With the deepening understanding of drug resistance, various mechanisms have been revealed, including metabolic reprogramming and alterations of redox balance. Notably, metabolic reprogramming mediates the survival of tumor cells in harsh environments, thereby promoting the development of drug resistance. In addition, the changes during metabolic pattern shift trigger reactive oxygen species (ROS) production, which in turn regulates cellular metabolism, DNA repair, cell death, and drug metabolism in direct or indirect ways to influence the sensitivity of tumors to therapies. Therefore, the intersection of metabolism and ROS profoundly affects tumor drug resistance, and clarifying the entangled mechanisms may be beneficial for developing drugs and treatment methods to thwart drug resistance. In this review, we will summarize the regulatory mechanism of redox and metabolism on tumor drug resistance and highlight recent therapeutic strategies targeting metabolic–redox circuits, including dietary interventions, novel chemosynthetic drugs, drug combination regimens, and novel drug delivery systems.
Canagliflozin Inhibits Palmitic Acid-Induced Vascular Cell Aging In Vitro through ROS/ERK and Ferroptosis Pathways
Authors: Wan Fang , He Xin , Xie Weidong
Published: July 2024

Vascular aging is one of the reasons for the high incidence of cardiovascular diseases nowadays, as vascular cells age due to various internal and external factors. Among them, high fat is an important inducer. Canagliflozin (CAN) is one of the SGLT2 inhibitors that has been shown to have cardiovascular protective effects in addition to lowering blood sugar, but the specific mechanism is not clear. This study first established a vascular aging model using palmitic acid (PA), then tested the effect of CAN on PA-induced vascular aging, and finally examined the mechanism of CAN’s anti-vascular aging via ROS/ERK and ferroptosis pathways. We found that CAN alleviates PA-induced vascular cell aging by inhibiting the activation of ROS/ERK and ferroptosis signaling pathways. This study reveals new mechanisms of lipid-induced vascular aging and CAN inhibition of vascular aging from the perspectives of ROS/ERK and ferroptosis pathways, which is expected to provide new ideas for the development of related drugs in the future.
Sleep Deprivation Triggers Mitochondrial DNA Release in Microglia to Induce Neural Inflammation: Preventative Effect of Hydroxytyrosol Butyrate
Authors: Hu Yachong , Wang Yongyao , Wang Yifang , Zhang Yuxia , Wang Zhen , Xu Xiaohong , Zhang Tinghua , Zhang Tiantian , Zhang Shuangxi , Hu Ranrui , Shi Le , Wang Xudong , Li Jin , Shen Hui , Liu Jiankang , Noda Mami , Peng Yunhua , Long Jiangang
Published: July 2024

Sleep deprivation (SD) triggers mitochondrial dysfunction and neural inflammation, leading to cognitive impairment and mental issues. However, the mechanism involving mitochondrial dysfunction and neural inflammation still remains unclear. Here, we report that SD rats exhibited multiple behavioral disorders, brain oxidative stress, and robust brain mitochondrial DNA (mtDNA) oxidation. In particular, SD activated microglia and microglial mtDNA efflux to the cytosol and provoked brain pro-inflammatory cytokines. We observed that the mtDNA efflux and pro-inflammatory cytokines significantly reduced with the suppression of the mtDNA oxidation. With the treatment of a novel mitochondrial nutrient, hydroxytyrosol butyrate (HTHB), the SD-induced behavioral disorders were significantly ameliorated while mtDNA oxidation, mtDNA release, and NF-κB activation were remarkably alleviated in both the rat brain and the N9 microglial cell line. Together, these results indicate that microglial mtDNA oxidation and the resultant release induced by SD mediate neural inflammation and HTHB prevents mtDNA oxidation and efflux, providing a potential treatment for SD-induced mental issues.
RETRACTED: Mohan et al. Laser Welding of UNS S33207 Hyper-Duplex Stainless Steel to 6061 Aluminum Alloy Using High Entropy Alloy as a Filler Material. Appl. Sci. 2022, 12, 2849
Authors: Mohan Dhanesh G. , Tomków Jacek , Karganroudi Sasan Sattarpanah
Published: July 2024

The Applied Sciences Editorial Office retracts the article, “Laser Welding of UNS S33207 Hyper-Duplex Stainless Steel to 6061 Aluminum Alloy Using High Entropy Alloy as a Filler Material” [...]
Unmanned Aerial Vehicle Landing on Rugged Terrain by On-Board LIDAR–Camera Positioning System
Authors: Zou Cheng , Sun Yezhen , Kong Linghua
Published: July 2024

Safely landing unmanned aerial vehicles (UAVs) in unknown environments that are denied by GPS is challenging but crucial. In most cases, traditional landing methods are not suitable, especially under complex terrain conditions with insufficient map information. This report proposes an innovative multi-stage UAV landing framework involving (i) point cloud and image fusion positioning, (ii) terrain analysis, and (iii) neural network semantic recognition to optimize landing site selection. In the first step, 3D point cloud and image data are fused to attain a comprehensive perception of the environment. In the second step, an energy cost function considering texture and flatness is employed to identify potential landing sites based on energy scores. To navigate the complexities of classification for precise landings, the results are stratified by the difficulty of various UAV landing scenarios. In the third step, a network model is applied to analyze UAV landing site options by integrating the ResNet50 network with a convolutional block attention module. Experimental results indicate a reduction in computational load and improved landing site identification accuracy. The developed framework fuses multi-modal data to enhance the safety and feasibility of UAV landings in complex environments.
Metrics for Evaluating Synthetic Time-Series Data of Battery
Authors: Seol Sujin , Yoon Jaewoo , Lee Jungeun , Kim Byeongwoo
Published: July 2024

The advancements in artificial intelligence have encouraged the application of deep learning in various fields. However, the accuracy of deep learning algorithms is influenced by the quality of the dataset used. Therefore, a high-quality dataset is critical for deep learning. Data augmentation algorithms can generate large, high-quality datasets. The dataset quality is mainly assessed through qualitative and quantitative evaluations. However, conventional qualitative evaluation methods lack the objective and quantitative parameters necessary for battery synthetic datasets. Therefore, this study proposes the application of the rate of change in linear regression correlation coefficients, Dunn index, and silhouette coefficient as clustering indices for quantitatively evaluating the quality of synthetic time-series datasets of batteries. To verify the reliability of the proposed method, we first applied the TimeGAN algorithm to an open-source battery dataset, generated a synthetic battery dataset, and then compared its similarity to the original dataset using the proposed evaluation method. The silhouette coefficient was confirmed as the most reliable index. Furthermore, the similarity of datasets increased as the silhouette index decreased from 0.1053 to 0.0073 based on the number of learning iterations. The results demonstrate that the insufficient quality of datasets used for deep learning can be overcome and supplemented. Furthermore, data similarity can be efficiently evaluated regardless of the learning environment. In conclusion, we present a new synthetic time-series dataset evaluation method that is more reliable than the conventional representative evaluation method (the training loss rate).
Accuracy and Precision of Three-Dimensionally Printed Orthognathic Surgical Splints
Authors: Kim Na Y. , Donaldson Christopher D. , Wertheim David , Naini Farhad B.
Published: July 2024

The adoption of three-dimensional (3D) imaging technologies in orthognathic surgery led to the development of virtual surgical planning and printing of patient-specific orthognathic surgical splints (OSSs). The accuracy and precision of 3D printed OSSs are considered important; however, there is limited data in the literature regarding whether the type of resin materials may influence these measures. A virtual OSS was created using a set of typodont models and printed in Biomed Clear, Dental LT V2, and Surgical Guide resins (Formlabs, Somerville, MA, USA), using a stereolithography printer. The upper intercanine width, intermolar width, and arch length were analysed. Differences between the reference dimensions of the virtual splint and the corresponding mean measurements of the 3D-printed splints were mostly considered clinically acceptable. The greatest variation was observed in the arch length for all 3 materials, which relates to the Z-axis of the printer; only 33.3–66.7% of OSSs were within the tolerance limit of ±0.1 mm quoted by the manufacturer. The Surgical Guide group demonstrated the highest degree of accuracy and precision overall. Further research would help to assess the 3D accuracy and precision, explore the variation found between different resin materials used, and confirm the findings of this research.
Enhancing DDBMS Performance through RFO-SVM Optimized Data Fragmentation: A Strategic Approach to Machine Learning Enhanced Systems
Authors: Danach Kassem , Khalaf Abdullah Hussein , Rammal Abbas , Harb Hassan
Published: July 2024

Effective data fragmentation is essential in enhancing the performance of distributed database management systems (DDBMS) by strategically dividing extensive databases into smaller fragments distributed across multiple nodes. This study emphasizes horizontal fragmentation and introduces an advanced machine learning algorithm, Red Fox Optimization-based Support Vector Machine (RFO-SVM), designed for optimizing the data fragmentation process. The input database undergoes meticulous pre-processing to address missing data concerns, followed by analysis through RFO-SVM. This algorithm efficiently classifies features and target labels based on class labels. The RFO algorithm optimizes critical SVM parameters, including the kernel, kernel parameter, and boundary parameter, leveraging the accuracy metric. The resulting classified data serves as fragments for the fragmentation process. To ensure precision in fragmentation, a Genetic Algorithm (GA) allocates these fragments to diverse nodes within the DDBMS, optimizing the total allocation cost as the fitness function. The proposed model, implemented in Python, significantly contributes to the efficient fragmentation and allocation of databases in distributed systems, thereby enhancing overall performance and scalability.
Statistical Analysis of Tonal Acquisition in Disyllabic Words among Polish Learners of Mandarin: A Comparative Study
Authors: Chu Man-Ni , Chang Carson , Lin Hui-Wen
Published: July 2024

In this study, we utilized a mixture random effects model and pairwise comparisons to conduct our analysis. Furthermore, we employed visualization techniques, specifically line plots in Python, to illustrate the tonal variations in disyllabic words among Polish learners of Mandarin. Our findings indicate that Polish learners experience more difficulty with the tonal contours of Tone 1 (T1) and Tone 2 (T2) compared to Taiwanese Mandarin (TM) natives, particularly due to the lower pitch range required. We provide potential pedagogical recommendations based on these results. We suggest that integrating training on T1 and T2 accompanied with Tone 3 (T3) and Tone 4 (T4), because of their lower endpoint tones, may offer a more effective learning strategy for these learners.
Enhanced Energy, Conversion Efficiency and Collimation of Protons Driven by High-Contrast and Ultrashort Laser Pulses
Authors: Yao Weipeng , Lelièvre Ronan , Waltenspiel Tessa , Cohen Itamar , Allaoua Amokrane , Antici Patrizio , Beck Arie , Cohen Erez , Davoine Xavier , d’Humières Emmanuel , Ducasse Quentin , Filippov Evgeny , Gautier Cort , Gremillet Laurent , Koseoglou Pavlos , Michaeli David , Papadopoulos Dimitrios , Pikuz Sergey , Pomerantz Ishay , Trompier Francois , Yuan Yuran , Mathieu Francois , Fuchs Julien
Published: July 2024

Progress in laser-driven proton acceleration requires increasing the proton maximum energy and laser-to-proton conversion efficiency while reducing the divergence of the proton beam. However, achieving all these qualities simultaneously has proven challenging experimentally, with the increase in beam energy often coming at the cost of beam quality. Numerical simulations suggest that coupling multi-PW laser pulses with ultrathin foils could offer a route for such simultaneous improvement. Yet, experimental investigations have been limited by the scarcity of such lasers and the need for very stringent temporal contrast conditions to prevent premature target expansion before the pulse maximum. Here, combining the newly commissioned Apollon laser facility that delivers high-power ultrashort (∼24fs) pulses with a double plasma mirror scheme to enhance its temporal contrast, we demonstrate the generation of up to 35 MeV protons with only 5 J of laser energy. This approach also achieves improved laser-to-proton energy conversion efficiency, reduced beam divergence, and optimized spatial beam profile. Therefore, despite the laser energy losses induced by the plasma mirror, the proton beams produced by this method are enhanced on all accounts compared to those obtained under standard conditions. Particle-in-cell simulations reveal that this improvement mainly results from a better space–time synchronization of the maximum of the accelerating charge-separation field with the proton bunch.
Integrating Spatio-Temporal Graph Convolutional Networks with Convolutional Neural Networks for Predicting Short-Term Traffic Speed in Urban Road Networks
Authors: Jeon Seung Bae , Jeong Myeong-Hun
Published: July 2024

The rapid expansion of large urban areas underscores the critical importance of road infrastructure. An accurate understanding of traffic flow on road networks is essential for enhancing civil services and reducing fuel consumption. However, traffic flow is influenced by a complex array of factors and perpetually changing conditions, making comprehensive prediction of road network behavior challenging. Recent research has leveraged deep learning techniques to identify and forecast traffic flow and road network conditions, enhancing prediction accuracy by extracting key features from diverse factors. In this study, we performed short-term traffic speed predictions for road networks using data from Mobileye sensors mounted on taxis in Daegu City, Republic of Korea. These sensors capture the road network flow environment and the driver’s intentions. Utilizing these data, we integrated convolutional neural networks (CNNs) with spatio-temporal graph convolutional networks (STGCNs). Our experimental results demonstrated that the combined STGCN and CNN model outperformed the standalone STGCN and CNN models. The findings of this study contribute to the advancement of short-term traffic speed prediction models, thereby improving road network flow management.
Development of a Finishing Process for Imbuing Flame Retardancy into Materials Using Biohybrid Anchor Peptides
Authors: Heesemann Rahel , Sanders Matthias , Paul Roshan , Bettermann Isa , Gries Thomas , Feng Lilin , Schwaneberg Ulrich , Hummelsheim Claus , Danielsiek Dominic
Published: July 2024

Flame retardants are commonly used to reduce fire risk in various products and environments, including textiles. While many of these additives contain harmful substances, efforts are underway to reduce their usage. Current research aims to minimize flame-retardant quantities and enhance durability against external factors. This involves utilizing anchor peptides or material-binding peptides (MBPs), which are versatile molecules that bind strongly to surfaces like textiles. MBPs can be equipped with functional molecules, e.g., flame-retardant additives, by chemical or enzymatic bioconjugation. In this research, biohybrid flame retardants and an adapted finishing process are developed. Specifically, biobased adhesion promoters, the so-called MBPs, are used to finish textiles with flame-retardant additives. To date, there is no finishing process for treating textiles with MBPs and so a laboratory-scale finishing process based on foulard was developed. Necessary parameters, such as the take-off speed or the contact pressure of the squeezing rollers, are determined experimentally. In order to develop an adapted finishing process, various trials are designed and carried out. Part of the trials is the testing and comparison of different textiles (e.g., glass woven fabrics and aramid woven fabrics) under different conditions (e.g., different ratios of MBPs and flame retardants). The finished textiles are then analysed and validated regarding their flammability and the amount of adhered flame retardants.
Review on Applied Applications of Microbiome on Human Lives
Authors: Kamble Nitin S. , Bera Surojit , Bhedase Sanjivani A. , Gaur Vinita , Chowdhury Debabrata
Published: July 2024

It is imperative to say that we are immersed in a sea of microorganisms due to their ubiquitous presence on the planet, from soil to water and air. Human bodies harbor a vast array of microorganisms from both the inside and out called the human microbiome. It is composed of single-celled organisms, including archaea, fungi, viruses, and bacteria, including bacteriophages, where bacteria are the biggest players, and this is collectively referred to as the human microbiome. These organisms have a symbiotic relationship with humans and impact human physiology where they colonize various sites on and in the human body, adapting to specific features of each niche. However, dysbiosis, or the deviation from normal microbial composition, is associated with adverse health effects, disrupted ecosystems, and eco-imbalance in nature. In this review, we delve into the comprehensive oversight of bacteria, their cosmopolitan presence, and their additional applications affecting human lives.
Surface Reduction of Li2CO3 on LLZTO Solid-State Electrolyte via Scalable Open-Air Plasma Treatment
Authors: Sahal Mohammed , Guo Jinzhao , Chan Candace K. , Rolston Nicholas
Published: July 2024

We report on the use of an atmospheric pressure, open-air plasma treatment to remove Li2CO3 species from the surface of garnet-type tantalum-doped lithium lanthanum zirconium oxide (Li6.4La3Zr1.4Ta0.6O12, LLZTO) solid-state electrolyte pellets. The Li2CO3 layer, which we show forms on the surface of garnets within 3 min of exposure to ambient moisture and CO2, increases the interface (surface) resistance of LLZTO. The plasma treatment is carried out entirely in ambient and is enabled by use of a custom-built metal shroud that is placed around the plasma nozzle to prevent moisture and CO2 from reacting with the sample. After the plasma treatment, N2 compressed gas is flowed through the shroud to cool the sample and prevent atmospheric species from reacting with the LLZTO. We demonstrate that this approach is effective for removing the Li2CO3 from the surface of LLZTO. The surface chemistry is characterized with X-ray photoelectron spectroscopy to evaluate the effect of process parameters (plasma exposure time and shroud gas chemistry) on removal of the surface species. We also show that the open-air plasma treatment can significantly reduce the interface resistance. This platform demonstrates a path towards open-air processed solid-state batteries.
Trends and Challenges towards Effective Data-Driven Decision Making in UK Small and Medium-Sized Enterprises: Case Studies and Lessons Learnt from the Analysis of 85 Small and Medium-Sized Enterprises
Authors: Tawil Abdel-Rahman H. , Mohamed Muhidin , Schmoor Xavier , Vlachos Konstantinos , Haidar Diana
Published: July 2024

The adoption of data science brings vast benefits to Small and Medium-sized Enterprises (SMEs) including business productivity, economic growth, innovation and job creation. Data science can support SMEs to optimise production processes, anticipate customers’ needs, predict machinery failures and deliver efficient smart services. Businesses can also harness the power of artificial intelligence (AI) and big data, and the smart use of digital technologies to enhance productivity and performance, paving the way for innovation. However, integrating data science decisions into an SME requires both skills and IT investments. In most cases, such expenses are beyond the means of SMEs due to their limited resources and restricted access to financing. This paper presents trends and challenges towards effective data-driven decision making for organisations based on a 3-year long study which covered more than 85 UK SMEs, mostly from the West Midlands region of England. In particular, this study attempts to find answers to several key research questions around data science and AI adoption among UK SMEs, and the advantages of digitalisation and data-driven decision making, as well as the challenges hindering their effective utilisation of these technologies. We also present two case studies that demonstrate the potential of digitisation and data science, and use these as examples to unveil challenges and showcase the wealth of currently available opportunities for SMEs.
Adaptive Filtering with Fitted Noise Estimate (AFFiNE): Blink Artifact Correction in Simulated and Real P300 Data
Authors: Alexander Kevin E. , Estepp Justin R. , Elbasiouny Sherif M.
Published: July 2024

(1) Background: The electroencephalogram (EEG) is frequently corrupted by ocular artifacts such as saccades and blinks. Methods for correcting these artifacts include independent component analysis (ICA) and recursive-least-squares (RLS) adaptive filtering (-AF). Here, we introduce a new method, AFFiNE, that applies Bayesian adaptive regression spline (BARS) fitting to the adaptive filter’s reference noise input to address the known limitations of both ICA and RLS-AF, and then compare the performance of all three methods. (2) Methods: Artifact-corrected P300 morphologies, topographies, and measurements were compared between the three methods, and to known truth conditions, where possible, using real and simulated blink-corrupted event-related potential (ERP) datasets. (3) Results: In both simulated and real datasets, AFFiNE was successful at removing the blink artifact while preserving the underlying P300 signal in all situations where RLS-AF failed. Compared to ICA, AFFiNE resulted in either a practically or an observably comparable error. (4) Conclusions: AFFiNE is an ocular artifact correction technique that is implementable in online analyses; it can adapt to being non-stationarity and is independent of channel density and recording duration. AFFiNE can be utilized for the removal of blink artifacts in situations where ICA may not be practically or theoretically useful.
Mathematical Modeling of Vedolizumab Treatment’s Effect on Microbiota and Intestinal Permeability in Inflammatory Bowel Disease Patients
Authors: D’Ambrosio Antonio , Altomare Annamaria , Boscarino Tamara , Gori Manuele , Balestrieri Paola , Putignani Lorenza , Del Chierico Federica , Carotti Simone , Cicala Michele , Guarino Michele Pier Luca , Piemonte Vincenzo
Published: July 2024

Growing evidence suggests that impaired gut permeability and gut microbiota alterations are involved in the pathogenesis of Inflammatory Bowel Diseases (IBDs), which include Ulcerative Colitis (UC) and Crohn’s Disease (CD). Vedolizumab is an anti-α4β7 antibody approved for IBD treatment, used as the first treatment or second-line therapy when the first line results in inadequate effectiveness. The aim of this study is to develop a mathematical model capable of describing the pathophysiological mechanisms of Vedolizumab treatment in IBD patients. In particular, the relationship between drug concentration in the blood, colonic mucosal permeability and fecal microbiota composition was investigated and modeled to detect and predict trends in order to support and tailor Vedolizumab therapies. To pursue this aim, clinical data from a pilot study on a cluster of 11 IBD patients were analyzed. Enrolled patients underwent colonoscopy in three phases (before (t0), after 24 weeks of (t1) and after 52 weeks of (t2 ) Vedolizumab treatment) to collect mucosal biopsies for transepithelial electrical resistance (TEER) evaluation (permeability to ions), intestinal permeability measurement and histological analysis. Moreover, fecal samples were collected for the intestinal microbiota analysis at the three time points. The collected data were compared to those of 11 healthy subjects at t0, who underwent colonoscopy for screening surveillance, and used to implement a three-compartmental mathematical model (comprising central blood, peripheral blood and the intestine). The latter extends previous evidence from the literature, based on the regression of experimental data, to link drug concentration in the peripheral blood compartment with Roseburia abundance and intestinal permeability. The clinical data showed that Vedolizumab treatment leads to an increase in TEER and a reduction in intestinal permeability to a paracellular probe, improving tissue inflammation status. Microbiota analysis showed increasing values of Roseburia, albeit not statistically significant. This trend was adequately reproduced by the mathematical model, which offers a useful tool to describe the pathophysiological effects of Vedolizumab therapy on colonic mucosal permeability and fecal microbiota composition. The model’s satisfactory predictive capabilities and simplicity shed light on the relationship between the drug, the microbiota and permeability and allow for its straightforward extension to diverse therapeutic conditions.
The Effect of Sample Handling on Rabies-Neutralizing Antibody Stability
Authors: Pralle Samantha J. , Gatrell Stephanie K. , Keating Cassidy C. , Moore Susan M.
Published: July 2024

The measurement of rabies-neutralizing antibody is important for monitoring the response to rabies vaccination. For all the purposes of measurement, such as routine monitoring of vaccine response in humans and animals, serosurveys, and biologics qualification, accurate and precise results are necessary. The risks associated with sample handling variation, which may impact the test results, can be overlooked within a laboratory. To determine the robustness of rabies-neutralizing antibodies in human and animal serum, samples were treated to mimic various possible deviations in the sample handling protocols. Potential deviations were designed to investigate common client inquiries and possible sample conditions experienced during shipping, storage, and laboratory processes. The treatments included the duration that sera were kept at a temperature greater than that of a refrigerator (room temperature, zero hours to two weeks), the number and duration of heat inactivation treatments (i.e., heat inactivation directly from freezer storage, etc.), the number of freeze–thaw cycles (zero, four, or six cycles), and the storage duration of sample dilutions in chamber slides before the addition of virus (zero hours to overnight). The results provided evidence for the robustness of rabies antibodies and the antibodies’ neutralizing function in uncontaminated, clear human and animal serum. In addition, prolonged heat exposure was identified as exerting the greatest impact on the measurement of rabies antibodies.