bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating pre-tertiary students’ mistakes in solving algebraic word problems: Insights from Asutifi North District, Ghana
Authors: Korkor Sarah , Bonyah Ebenezer
Published: October 2024

Algebra word problems inculcate in learners the skills and ability to think critically and look for answers to problems in society and the world. Using an explanatory sequential mixed design, the study investigated the errors made by pre-tertiary students in algebraic word problems in a selected school in the Asutifi North District of the Ahafo Region of Ghana. Whereas the Newman Error Analysis Model was used to find the types of errors students make when translating and solving algebraic word problems, protocols from topics relating to the study were carefully selected and used as interview guides alongside inspiration from the Newman Error Analysis Model. Quota and simple random sampling techniques were used to select ninety-eight (98) respondents. The Algebraic Word Problem Achievement Test (AWPAT) was given to the ninety-eight students who had studied several topics on word problems, followed by a structured interview to elicit more information from the respondents. The scores gained from the marked test items illustrated that students made more transformation errors, which happened indirectly from a lack of understanding of the concept. A careful analysis of the written responses of the five (5) students interviewed also revealed that, lack of comprehension directly translated into students’ inability to transform algebraic word problems into mathematics equations. In the same vein, the study showed that the main cause of students’ failure to translate and solve algebraic word problems was students’ lack of understanding of the concept of “word problem” among others. The study recommends that students be motivated by encouragement and praise to arouse their interest in translating and solving algebraic word problems.
Metal-organic framework (MOF) integrated Ti3C2 MXene composites for CO2 reduction and hydrogen production applications: a review on recent advances and future perspectives
Authors: Tahir Beenish , Alraeesi Abdulrahman , Tahir Muhammad
Published: October 2024

Titanium carbide (Ti3C2) MXenes due to their structural and optical characteristics rapidly emerged as the preferred material, particularly in catalysis and energy applications. On the other hand, because of its enormous surface/volume ratio and porosity, Metal-organic Frameworks (MOFs) show promise in several areas, including catalysis, delivery, and storage. The potential to increase the applicability of these magic compounds might be achieved by taking advantage of the inherent flexibility in design and synthesis, and optical characteristics of MXenes. Thus, coupling MOF with Ti3C2 MXenes to construct hybrid composites is considered promising in a variety of applications, including energy conversion and storage. This paper presents a systematic discussion of current developments in Ti3C2 MXenes/MOF composites for photocatalytic reduction of CO2, and production of hydrogen through water splitting. Initially, the overview and characteristics of MXenes and MOFs are independently discussed and then a detailed investigation of efficiency enhancement is examined. Different strategies such as engineering aspects, construction of binary and ternary composites and their efficiency enhancement mechanism are deliberated. Finally, different strategies to explore further in various other applications are suggested. Although Ti3C2 MXenes/MOF composites have not yet been thoroughly investigated, they are potential photocatalysts for the production of solar fuel and ought to be looked into further for a range of applications.
Gut microbiota dysbiosis in ankylosing spondylitis: a systematic review and meta-analysis
Authors: Su Qin-Yi , Zhang Yan , Qiao Dan , Song Xia , Shi Yang , Wang Zhe , Wang Chen-Yan , Zhang Sheng-Xiao
Published: October 2024

Background

Ankylosing spondylitis (AS) is a connective tissue disease that primarily affects spinal joints, peripheral joints, and paravertebral soft tissues, leading to joint stiffness and spinal deformity. Growing evidence has implicated gut microbiota in the regulation of AS, though the underlying mechanisms remain poorly understood.

Methods

We conducted a comprehensive search of PubMed, Embase, Web of Science, the Cochrane Library, MEDLINE, Wanfang Data, China Science and Technology Journal Database (VIP), and China National Knowledge Internet (CNKI) databases from the time the databases were created until 30 July 2023. To evaluate changes in α-diversity and the abundance of certain microbiota families in AS, standardized mean difference (SMD) and 95% confidence interval (CI) calculations were made. Meta-analyses were performed using STATA 12.0 and the quality of the literature was assessed by following systematic review guidelines.

Results

This systematic review and meta-analysis included 47 studies, providing insights into the gut microbiota composition in patients with AS compared to healthy controls (HCs). Our findings indicate a significant reduction in gut microbial diversity in patients with AS, as evidenced by a decrease in both richness and evenness. Specifically, the Shannon index showed a moderate decrease (SMD = -0.27, 95% CI: -0.49, -0.04; P < 0.001), suggesting a less diverse microbial ecosystem in patients with AS. The Chao1 index further confirmed this trend, with a larger effect size (SMD = -0.44, 95% CI: -0.80, -0.07; P < 0.001), indicating a lower species richness. The Simpson index also reflected a significant reduction in evenness (SMD = -0.30, 95% CI: -0.53, -0.06; P < 0.001). Additionally, patients with AS who received anti-rheumatic combination treatment exhibited a more pronounced reduction in α-diversity compared to untreated patients, highlighting the potential impact of this treatment on gut microbiota balance. In terms of specific microbial families, we observed a significant decrease in the abundance of Bifidobacterium (SMD = -0.42, 95% CI: -2.37, 1.52; P < 0.001), which is known for its beneficial effects on gut health. Conversely, an increase in the abundance of Bacteroidetes was noted (SMD = 0.42, 95% CI: -0.93, 1.76; P < 0.001), suggesting a possible shift in the gut microbiota composition that may be associated with AS pathophysiology.

Conclusion

Our analysis revealed changes in α-diversity and the relative abundance of specific bacteria in AS. This suggests that targeting the gut microbiota could provide new therapeutic opportunities for treating AS.

Systematic review registration

https://www.crd.york.ac.uk./PROSPERO/, identifier CRD42023450028.
Effects of ocean acidification on the interaction between calcifying oysters (Ostrea chilensis) and bioeroding sponges (Cliona sp.)
Authors: Böök Imke M. , Krieger Erik C. , Phillips Nicole E. , Michael Keith P. , Bell James J. , Dillon Wayne D. N. , Cornwall Christopher E.
Published: October 2024

Ocean acidification can negatively affect a broad range of physiological processes in marine shelled molluscs. Marine bioeroding organisms could, in contrast, benefit from ocean acidification due to reduced energetic costs of bioerosion. Ocean acidification could thus exacerbate negative effects (e.g. reduced growth) of ocean acidification and shell borers on oysters. The aim of this study was to assess the impact of ocean acidification on the oyster Ostrea chilensis, the boring sponge Cliona sp., and their host-parasite relationship. We exposed three sets of organisms 1) O. chilensis, 2) Cliona sp., and 3) O. chilensis infested with Cliona sp. to pHT 8.03, 7.83, and 7.63. Reduced pH had no significant effect on calcification, respiration and clearance rate of uninfested O. chilensis. Low pH significantly reduced calcification leading to net dissolution of oyster shells at pHT 7.63 in sponge infested oysters. Net dissolution was likely caused by increased bioerosion by Cliona sp. at pHT 7.63. Additionally, declining pH and sponge infestation had a significant negative antagonistic effect (less negative than predicted additively) on clearance rate. This interaction suggests that sponge infested oysters increase clearance rates to cope with higher energy demand of increased shell repair resulting from higher boring activity of Cliona sp. at low seawater pH. O. chilensis body condition was unaffected by sponge infestation, pH, and the interaction of the two. The reduction in calcification rate suggests sponge infestation and ocean acidification together would exacerbate direct (reduced growth) and indirect (e.g., increased predation) negative effects on oyster health and survival. Our results indicate that ocean acidification by the end of the century could have severe consequences for marine molluscs with boring organisms.
L-shaped association of thiamine intake and risk for peripheral artery disease in US adults: a cross-sectional study
Authors: Dong Zhiyong , Wang Qingyun
Published: October 2024

Background

The relationship between thiamine intake and risk for peripheral artery disease (PAD) is unknown. We aimed to clarify the role of thiamine intake on risk for PAD and the implications of this relationship. The secondary objective of this study is to explore the potential non-linear dose–response relationship between exposure to thiamine intake and outcome risk for PAD.

Methods

We conducted a cross-sectional study involving 6,112 participants with US adults from the National Health and Nutrition Examination Survey (1999–2004). Logistic regression and restricted cubic spline were utilized to substantiate the research objectives.

Results

The overall prevalence of risk for PAD was 7.9, 51% in males and 49% in females. After multivariable adjustment, lower thiamine intake was significantly and nonlinearly associated with higher risks of PAD among participants. Furthermore, we discovered L-shaped associations (p = 0.082) between thiamine intake and the risk of PAD, with an inflection point at 0.66 mg/day. Accordingly, in the threshold effect analysis, there was an inverse association between dietary thiamine intake and the risk in participants with dietary thiamine intake <0.65 mg/day. Compared to participants with thiamine intake below the inflection points, those with higher levels had a 31% lower risk for PAD (OR, 0.69; 95% CI: 0.51, 0.95). Further subgroup analysis showed no significant interactions between the subgroups (all p values for interaction were > 0.05).

Conclusion

A non-linear association was revealed, showing that low and high levels of thiamine intake were associated with an increased the risk of peripheral artery disease in American adults. The inflection point at 0.66 mg/day and lower risk of PAD at 0.65–1.13mg/day of dietary thiamine intake may represent intervention targets for lowering the risk of PAD. The findings of this study require further validation and confirmation.
Predicting monotherapy resistance risk in patients with low-risk gestational trophoblastic neoplasia: integration of the systemic immune−inflammation index and the prognostic nutritional index
Authors: Lin Tianfu , Wu Caijin , Peng Meilian , Chen Lihua , Lin Wenyu , Zheng Meijin , Wu Qibin , Sun Pengming
Published: October 2024

Purpose

Currently, there are no reliable indicators for the early identification of patients with low-risk gestational trophoblastic neoplasia (GTN) who develop resistance to monotherapy. This study aimed to evaluate the effectiveness of combining the Systemic Immune-Inflammation Index (SII) and Prognostic Nutritional Index (PNI) in detecting early resistance to monotherapy in patients with low-risk GTN.

Methods

This retrospective study included 91 patients with low-risk GTN who received initial monotherapy at Fujian Maternal and Child Health Hospital between 2013 and 2021. The SII and PNI before chemotherapy were calculated from prechemotherapy peripheral blood samples, with cut-off values determined by receiver operating characteristic (ROC) curves. The SII-PNI score ranged from 0 to 2 points and was categorized as follows: a score of 2 points indicated a high SII (≥467.02) and a low PNI (≤51.35); a score of 1 point indicated either a high SII or a low PNI; and a score of 0 points indicated neither a high SII nor a low PNI.

Results

Ninety-one patients with low-risk GTN underwent monotherapy, 19 of whom developed resistance, whereas the remaining 72 did not. The SII was significantly greater in chemotherapy-resistant patients than in non-resistant patients (P=0.04), whereas the PNI was markedly lower in chemotherapy-resistant patients (P=0.002). Univariate analysis revealed that cut-off values of 467.02 for the SII (P=0.04) and 51.35 for the PNI (P=0.024) were associated with chemotherapy resistance in patients with low-risk GTN. As the SII-PNI score increased, the proportion of chemotherapy-resistant patients increased (P<0.001), and the time for human chorionic gonadotropin (hCG) normalization correspondingly increased (P<0.001). Multivariate logistic regression analysis indicated that a high SII-PNI score is an independent risk factor for chemotherapy resistance in patients with low-risk GTN (P=0.001).

Conclusion

A high SII and low PNI are linked to chemotherapy resistance in patients with low-risk GTN. The pretreatment SII-PNI score is a key indicator for predicting the sensitivity of patients with low-risk GTN to single-agent chemotherapy, aiding in the early identification of individuals at high risk of resistance.
Risk factors for early readmission to hospital in patients with malignancy-related ascites: a retrospective cohort study
Authors: Tian Zhenhua , Huang Zhilong , Guo Yaqi , Zhao Xiaolin , Liu Luna , Yu Chunxiao , Guan Qingbo
Published: October 2024

Introduction

Malignancy-related ascites (MRA) is a common serious complication of many advanced malignant tumors with high morbidity and mortality. The high hospital expenditures induced by unplanned readmission in patients with MRA have become an urgent issue to the public. We aimed to overall assess the unplanned early readmission rate of patients with MRA and explore the potential risk factors for such readmission.

Methods

A retrospective cohort study based on 2018 Nationwide Readmissions Database was performed and patients with MRA were recruited into the analysis. The primary outcome was unplanned 30-day readmission rate and inpatient outcomes. The multivariate logistic regression analysis was performed to evaluate the potential risk factors for such early readmission.

Results

Data obtained from 32,457 patients with MRA were analyzed, and of these 7,799 individuals (24.03%) were unplanned readmitted within 30-day follow-up. The mortality rate in the readmitted population was 15.15%. Patients at younger age were at a higher risk of readmission. The morbidities including hypertension (OR=1.117, 95%CI: 1.054-1.184), hyperlipemia (OR=1.075, 95%CI: 1.009-1.146) and diabetes (OR=1.118, 95%CI: 1.053-1.188), gastrointestinal malignancies and peritoneal procedure significantly increased the risk of 30-day readmission in patients with MRA.

Discussion

More than one in five patients with MRA was unplanned readmitted within 30-day follow-up. The above risk factors should be timely intervened and the corresponding medical care should be strengthened in patients with MRA to lessen the unplanned readmission and improve the readmission outcomes.
Vitamin D receptor is associated with prognostic characteristics of breast cancer after neoadjuvant chemotherapy—an observational study
Authors: Streb Joanna , Łazarczyk Agnieszka , Hałubiec Przemysław , Streb-Smoleń Anna , Ciuruś Julita , Ulatowska-Białas Magdalena , Trzeszcz Martyna , Konopka Kamil , Hodorowicz-Zaniewska Diana , Szpor Joanna
Published: October 2024

Background

Breast cancer (BC) is the most commonly diagnosed malignant tumor in women. The disease and its subsequent treatment pose a serious burden on the quality of life of patients. Neoadjuvant chemotherapy (NAC) has become one of the crucial strategies for the management of BC. Since the identification of the vitamin D receptor (VDR) in mammary tissues, extensive mechanistic research has been conducted on its function. The expression of VDR in BC cells and the tumor microenvironment could be a new prognostic factor for BC after NAC.

Patients and Methods

This observational, single-center study compared data from clinical and histopathological records of 111 female subjects with the expression of VDR in different cellular and tissue components of breast specimens obtained from surgery after NAC. VDR expression was evaluated using an immunoreactive score assigned after immunohistochemistry. Intergroup comparisons and logistic regression were used to identify associations between VDR expression and clinicopathological features of BC.

Results

We found that the expression of VDR is associated with various clinical features (i.e., age, menopausal status, and NAC cycle number) and characteristics of prognostic significance, such as residual cancer burden class. Logistic regression analysis revealed that the expression of VDR in the nuclei and cytoplasm of surrounding normal mammary cells predicted vascular invasion and lymph node involvement.

Conclusions

The expression of VDR in tumor cells and their microenvironment is related to the clinicopathological characteristics of BC after NAC.
Exploring the role of regional capacity in human resource development in Indonesia
Authors: Burhanuddin Burhanuddin , Syufri Syufri , Asriani Asriani , Hartawan Hartawan , Saputra Aco N.
Published: October 2024

The role of local government in regional development planning is an essential topic in the context of sustainable local development. This study aimed to analyze the role of local governments in regional development planning and their impact on the effectiveness and sustainability of development at the local level. The research method used is a qualitative approach with data collection techniques through in-depth interviews, participatory observation, and document analysis related to regional development policies and regulations. This research was conducted in several districts/cities in certain regions, considering diverse geographical, social, and economic contexts. The results showed that the role of local governments in regional development planning is vital in coordinating various interests, resources, and related actors. Local governments act as regulators, facilitators, and implementers in determining the direction, policies, and allocation of development resources. In addition, community and private-sector involvement is also recognized as an integral part of democratic and inclusive planning processes. The impact of the role of local governments in regional development planning can be seen in increasing the effectiveness of development programs, increasing community participation, reducing regional disparities, and improving the community’s quality of life. Nevertheless, challenges such as corruption, lack of interagency coordination, and political uncertainty remain obstacles that must be overcome. This study concludes that the role of local governments in regional development planning is a critical factor in achieving sustainable regional development. Therefore, measures are needed to strengthen institutional capacity, increase transparency, and strengthen public participation to ensure sustainable and inclusive development planning at the local level.
Interventions on informal healthcare providers to improve the delivery of healthcare services in low-and middle-income countries: a systematic review
Authors: Das Saibal , Khare Shweta , Eriksen Jaran , Diwan Vishal , Stålsby Lundborg Cecilia , Skender Kristina
Published: October 2024

Objective

Informal healthcare providers (IHCPs) play a big role in health systems in low-and middle-income countries (LMICs) and are often the first point of contact for healthcare in rural and underserved areas where formal healthcare infrastructure is insufficient or absent. This study was performed to systematically review the literature on interventions targeting IHCPs in improving the delivery of healthcare services in LMICs.

Methods

PubMed, Embase, and Cochrane CENTRAL databases were searched for studies that assessed any type of intervention among IHCPs to improve the delivery of healthcare services in any LMIC. Outcomes included changes in knowledge, attitude, and reported practice of appropriate case diagnosis and management; improved referral services; effective contraceptive use; and medication appropriateness (PROSPERO ID: CRD42024521739).

Results

A total of 7,255 studies were screened and 38 were included. Most of the studies were conducted in Africa and Asia. The IHCPs who were trained included medicine sellers, community health workers/traditional healers, and traditional birth attendants. The main intervention used was educational programs in the form of training. The other interventions were health services, policy and guidelines, and community-based interventions. Most of the interventions were multi-faceted. The disease/service areas targeted were mainly maternal and child health, sexually transmitted diseases, common infectious diseases, medicine use/dispensing practices, and contraception. The outcomes that showed improvements were knowledge, attitude, and reported practice; diagnosis and case management; improved referral services; contraceptive uses; and medication appropriateness. Around one-fourth of the studies reported negative results. The certainty of evidence generated (GRADE criteria) was very low.

Conclusion

Some multifaceted interventions coupled with training showed improvements in the delivery of healthcare services by IHCPs. However, the improvements were inconsistent. Hence, it is unclear to identify any context-specific optimum intervention to improve the delivery of healthcare services by IHCPs.
Application of HPLC Coupled with a Charged Aerosol Detector to the Evaluation of Fructose, Glucose, Sucrose, and Inositol Levels in Fruit Juices, Energy Drinks, Sports Drinks, and Soft Drinks
Authors: Grembecka Małgorzata , Lebiedzińska Anna , Szefer Piotr
Published: October 2024

The study aimed to estimate the levels of fructose, glucose, sucrose, and inositol levels in sweetened beverages with a newly developed method using HPLC coupled with a charged aerosol detector (CAD). In total, 85 commercially available non-alcoholic beverages, including 18 energy drinks, 8 sports drinks, 15 soft drinks, 14 fruit drinks, 7 fruit nectars, and 22 fruit juices were analyzed by HPLC-CAD. The method was validated, and it was characterized by a wide concentration range (1–150 µg/mL), sensitivity, and good accuracy (94.9–103%). The results showed significant variation in fructose, glucose, and sucrose concentrations in energy drinks, sports drinks, soft drinks, fruit drinks, fruit nectars, and juice. The highest total sugar contents (fructose, glucose, sucrose, and inositol) were found in energy drinks (14.2 g/100 mL), followed by fruit nectars (13.7 g/100 mL) and soft drinks (12.7 g/100 mL). Statistical analysis (Spearman correlation test, Kruskal–Wallis test) of the data showed significant relationships between particular sugars in the analyzed products.
Design and Demonstration of Hingeless Pneumatic Actuators Inspired by Plants
Authors: Zeng Xiangli , Wang Yingzhe , Morishima Keisuke
Published: October 2024

Soft robots have often been proposed for medical applications, creating human-friendly machines, and dedicated subject operation, and the pneumatic actuator is a representative example of such a robot. Plants, with their hingeless architecture, can take advantage of morphology to achieve a predetermined deformation. To improve the modes of motion, two pneumatic actuators that mimic the principles of the plants (the birds-of-paradise plant and the waterwheel plant) were designed, simulated, and tested using physical models in this study. The most common deformation pattern of the pneumatic actuator, bending deformation, was utilized and hingeless structures based on the plants were fabricated for a more complex motion of the lobes. Here, an ABP (actuator inspired by the birds-of-paradise plant) could bend its midrib downward to open the lobes, but an AWP (actuator inspired by the waterwheel plant) could bend its midrib upward to open the two lobes. In both the computational and physical models, the associated movements of the midrib and lobes could be observed and measured. As it lacks multiple parts that have to be assembled using joints, the actuator would be simpler to fabricate, have a variety of deformation modes, and be applicable in more fields.
Use of Vegetable Waste for New Ecological Methods in Wool Fibre Treatments
Authors: Gavrilaș Simona , Dochia Mihaela , Sărsan Andreea-Raluca , Chereji Bianca-Denisa , Munteanu Florentina-Daniela
Published: October 2024

In this current research, various amino acids (lysine, betaine, and cysteine) and peptides (oxidised or reduced glutathione) were considered as potential environmentally friendly alternatives to wool bleaching. A greener methodology was also applied to dyeing. Different agro-wastes (red cabbage, peppercorns, and red and yellow onion peels) served as raw pigment materials. The process’s efficiency was characterised by the whiteness degree, colour strength, and fastness to accelerated washing and perspiration. A higher whiteness index value was observed in the cysteine-based formulations. The onion peel exhibited significant tinctorial properties due to the presence of some natural mordants. All the proposed treatments were designed with a primary focus on environmental sustainability. These treatments offer a sustainable and environmentally friendly alternative to traditional bleaching and dyeing methods for wool. They reduce costs and energy consumption while creating added value by valorising waste.
Spa Therapy Efficacy in Mental Health and Sleep Quality Disorders in Patients with a History of COVID-19: A Comparative Study
Authors: Costantino Maria , Giudice Valentina , Marongiu Francesco , Marongiu Mariagrazia Bathilde , Filippelli Amelia , Kunhardt Horst
Published: October 2024

The COVID-19 pandemic has left behind mental health issues like anxiety, depression, and sleep disorders among survivors. This study assessed the efficacy of spa therapy in enhancing psychological well-being and sleep quality in individuals with chronic arthro-rheumatic, respiratory, and otorhinolaryngological diseases, including COVID-19 recoverees. Our prospective observational study included 144 Caucasian subjects from three Italian spas who underwent a 2-week spa therapy cycle, involving balneotherapy and/or inhalation treatments. Symptoms were assessed with the Visual Analogue Scale (VAS), psychological well-being with Depression Anxiety Stress Scales-21 items (DASS-21), and sleep quality with the Insomnia Severity Index (ISI). Significant reductions in VAS scores for arthro-rheumatic, respiratory, and otorhinolaryngological symptoms were observed after spa therapy, as well as for DASS-21 and ISI scores for sleep quality, transitioning to less severe insomnia categories. Females had more pronounced improvements in DASS-21 scores and sleep quality. Subjects with and without prior SARS-CoV-2 infection experienced significant reductions in anxiety, depression, and stress, with more pronounced improvements in those without prior infection. COVID-19 survivors also showed significant ISI score improvements. Spa therapy is a promising complementary treatment for improving mental health and sleep quality in chronic disease patients, including COVID-19 survivors.
Chestnut Burr Segmentation for Yield Estimation Using UAV-Based Imagery and Deep Learning
Authors: Carneiro Gabriel A. , Santos Joaquim , Sousa Joaquim J. , Cunha António , Pádua Luís
Published: October 2024

Precision agriculture (PA) has advanced agricultural practices, offering new opportunities for crop management and yield optimization. The use of unmanned aerial vehicles (UAVs) in PA enables high-resolution data acquisition, which has been adopted across different agricultural sectors. However, its application for decision support in chestnut plantations remains under-represented. This study presents the initial development of a methodology for segmenting chestnut burrs from UAV-based imagery to estimate its productivity in point cloud data. Deep learning (DL) architectures, including U-Net, LinkNet, and PSPNet, were employed for chestnut burr segmentation in UAV images captured at a 30 m flight height, with YOLOv8m trained for comparison. Two datasets were used for training and to evaluate the models: one newly introduced in this study and an existing dataset. U-Net demonstrated the best performance, achieving an F1-score of 0.56 and a counting accuracy of 0.71 on the proposed dataset, using a combination of both datasets during training. The primary challenge encountered was that burrs often tend to grow in clusters, leading to unified regions in segmentation, making object detection potentially more suitable for counting. Nevertheless, the results show that DL architectures can generate masks for point cloud segmentation, supporting precise chestnut tree production estimation in future studies.
A Two-Stage Target Search and Tracking Method for UAV Based on Deep Reinforcement Learning
Authors: Liu Mei , Wei Jingbo , Liu Kun
Published: October 2024

To deal with the complexities of decision-making for unmanned aerial vehicles (UAVs) in denial environments, this paper applies deep reinforcement learning algorithms to search and rescue (SAR) tasks. It proposes a two-stage target search and tracking method for UAVs based on deep reinforcement learning, which divides SAR tasks into search and tracking stages, and the controllers for each stage are trained based on the proposed deep deterministic policy gradient with three critic networks (DDPG-3C) algorithm. Simulation experiments are carried out to evaluate the performance of each stage in a two-dimensional rectangular SAR scenario, including search, tracking, and the integrated whole stage. The experimental results show that the proposed DDPG-3C model can effectively alleviate the overestimation problem, and hence results in a faster convergence and improved performance during both the search and tracking stages. Additionally, the two-stage target search and tracking method outperforms the traditional single-stage approach, leading to a more efficient and effective decision-making ability in SAR tasks.
Application of End-to-End Perception Framework Based on Boosted DETR in UAV Inspection of Overhead Transmission Lines
Authors: Wang Jinyu , Jin Lijun , Li Yingna , Cao Pei
Published: October 2024

As crucial predecessor tasks for fault detection and transmission line inspection, insulators, anti-vibration hammers, and arc sag detection are critical jobs. Due to the complexity of the high-voltage transmission line environment and other factors, target detection work on transmission lines remains challenging. A method for high-voltage transmission line inspection based on DETR (TLI-DETR) is proposed to detect insulators, anti-vibration hammers, and arc sag. This model achieves a better balance in terms of speed and accuracy than previous methods. Due to environmental interference such as mountainous forests, rivers, and lakes, this paper uses the Improved Multi-Scale Retinex with Color Restoration (IMSRCR) algorithm to make edge extraction more robust with less noise interference. Based on the TLI-DETR’s feature extraction network, we introduce the edge and semantic information by Momentum Comparison (MoCo) to boost the model’s feature extraction ability for small targets. The different shooting angles and distances of drones result in the target images taking up small proportions and impeding each other. Consequently, the statistical profiling of the area and aspect ratio of transmission line targets captured by UAV generate target query vectors with prior information to enable the model to adapt to the detection needs of transmission line targets more accurately and effectively improve the detection accuracy of small targets. The experimental results show that this method has excellent performance in high-voltage transmission line detection, achieving up to 91.65% accuracy and a 55FPS detection speed, which provides a technical basis for the online detection of transmission line targets.
Missed Insights for Earlier Management of Parkinson’s Disease and the Value of Dopamine Transporter (DAT) Scans
Authors: Hafeez Mohib , Eoff Elizabeth , Wei Jeanne , Azhar Gohar
Published: October 2024

Background/Objectives: This retrospective study focused on the role of Dopamine Transporter (DAT) scans in diagnosing Parkinson’s Disease (PD) in older adults with cognitive impairment (CI). Methods: We retrospectively analyzed brain imaging of 6483 individuals aged 60 and above with CI. Among these, 297 underwent a DAT scan, with 189 testing positive and 89 starting dopamine therapy. In contrast, 173 patients exhibited PD-associated structural changes on CT or MRI without receiving DAT scans or treatment. Results: Of these patients, 50 (29%) experienced falls. This points towards a potential missed diagnosis of PD, which can respond to therapy in the early stages. Conclusions: Our results suggest that providers may overlook subtle signs of parkinsonism in patients with CI, resulting in symptoms worsening and treatment delay. Since CI is often first brought to the attention of PCPs, our findings call for an increased effort to inform PCPs of the role of DAT scans in aiding the diagnosis of dopamine deficiency states. By understanding PD-related structural changes seen on brain imaging and using a DAT scan to confirm dopamine deficiency, treatment for PD or related states might be started earlier or a timely referral made to a specialist, reducing patient disability and improving their quality of life.
A Machine Learning Approach for Mechanical Component Design Based on Topology Optimization Considering the Restrictions of Additive Manufacturing
Authors: Ullah Abid , Asami Karim , Holtz Lukas , Röver Tim , Azher Kashif , Bartsch Katharina , Emmelmann Claus
Published: October 2024

Additive manufacturing (AM) and topology optimization (TO) emerge as vital processes in modern industries, with broad adoption driven by reduced expenses and the desire for lightweight and complex designs. However, iterative topology optimization can be inefficient and time-consuming for individual products with a large set of parameters. To address this shortcoming, machine learning (ML), primarily neural networks, is considered a viable tool to enhance topology optimization and streamline AM processes. In this work, a machine learning (ML) model that generates a parameterized optimized topology is presented, capable of eliminating the conventional iterative steps of TO, which shortens the development cycle and decreases overall development costs. The ML algorithm used, a conditional generative adversarial network (cGAN) known as Pix2Pix-GAN, is adopted to train using a variety of training data pairs consisting of color-coded images and is applied to an example of cantilever optimization, significantly enhancing model accuracy and operational efficiency. The analysis of training data numbers in relation to the model’s accuracy shows that as data volume increases, the accuracy of the model improves. Various ML models are developed and validated in this study; however, some artefacts are still present in the generated designs. Structures that are free from these artefacts achieve 91% reliability successfully. On the other hand, the images generated with artefacts may still serve as suitable design templates with minimal adjustments. Furthermore, this research also assesses compliance with two manufacturing constraints: the limitations on build space and passive elements (voids). Incorporating manufacturing constraints into model design ensures that the generated designs are not only optimized for performance but also feasible for production. By adhering to these constraints, the models can deliver superior performance in future use while maintaining practicality in real-world applications.
Analysis of Dynamic Changes in Sea Ice Concentration in Northeast Passage during Navigation Period
Authors: He Yawen , Liu Yanhua , Feng Duxian , Li Yongheng , Jin Feng , Deng Jinxiu
Published: October 2024

With global warming and the gradual melting of Arctic sea ice, the navigation duration of the Northeast Passage (NEP) is gradually increasing. The dynamic changes in sea ice concentration (SIC) during navigation time are a critical factor affecting the navigation of the passage. This study uses multiple linear regression and random forest to analyze the navigation windows of the NEP from 1979 to 2022 and examines the critical factors affecting the dynamic changes in the SIC. The results suggest that there are 25 years of navigable windows from 1979 to 2022. The average start date of navigable windows is approximately between late July and early August, while the end date is approximately early and mid-October, with considerable variation in the duration of navigable windows. The explanatory power of RF is significantly better than MLR, while LMG is better at identifying extreme events, and RF is more suitable for assessing the combined effects of all variables on the sea ice concentration. This study also found that the 2 m temperature is the main influencing factor, and the sea ice movement, sea level pressure and 10 m wind speed also play a role in a specific period. By integrating traditional statistical methods with machine learning techniques, this study reveals the dynamic changes of the SIC during the navigation period of the NEP and identifies its driving factors. This provides a scientific reference for the development and utilization of the Arctic Passage.
Improving Hybrid Regularized Diffusion Processes with the Triple-Cosine Smoothness Constraint for Re-Ranking
Authors: Du Miao , Cai Jianfeng
Published: October 2024

In the last few decades, diffusion processes have been widely used to solve visual re-ranking problems. The key point of these approaches is that, by diffusing the baseline similarities in the context of other samples, more reliable similarities or dissimilarities can be learned. This was later found to be achieved by solving the optimization problem underlying the framework of the regularized diffusion process. In this paper, the proposed model differs from previous approaches in two aspects. Firstly, by taking the high-order information of the graph into account, a novel smoothness constraint, named the triple-cosine smoothness constraint, is proposed. The triple-cosine smoothness constraint is generated using the cosine of the angle between the vectors in the coordinate system, which is created based on a group of three elements: the queries treated as a whole and two other data points. A hybrid fitting constraint is also introduced into the proposed model. It consists of two types of predefined values, which are, respectively, used to construct two types of terms: the squared L2 norm and the L1 norm. Both the closed-form solution and the iterative solution of the proposed model are provided. Secondly, in the proposed model, the learned contextual dissimilarities can be used to describe “one-to-many” relationships, making it applicable to problems with multiple queries, which cannot be solved by previous methods that only handle “one-to-one” relationships. By taking advantage of these “one-to-many” contextual dissimilarities, an iterative re-ranking process based on the proposed model is further provided. Finally, the proposed algorithms are validated on various databases, and comprehensive experiments demonstrate that retrieval results can be effectively improved using our methods.
Multi-Omics Analysis Unravels the Impact of Stool Sample Logistics on Metabolites and Microbial Composition
Authors: Krause Jannike L. , Engelmann Beatrice , Lallinger David J. D. , Rolle-Kampczyk Ulrike , von Bergen Martin , Chang Hyun-Dong
Published: October 2024

Human health and the human microbiome are inevitably intertwined, increasing their relevance in clinical research. However, the collection, transportation and storage of faecal samples may introduce bias due to methodological differences, especially since postal shipping is a common practise in large-scale clinical cohort studies. Using four different Omics layer, we determined the structural (16S rRNA sequencing, cytometric microbiota profiling) and functional integrity (SCFAs, global metabolome) of the microbiota in relation to different easy-to-handle conditions. These conditions were storage at −20 °C, −20 °C as glycerol stock, 4 °C and room temperature with and without oxygen exposure for a maximum of one week. Storage time affected the microbiota on all Omics levels. However, the magnitude was donor-dependent, highlighting the need for purpose-optimized sample collection in clinical multi-donor studies. The effects of oxygen exposure were negligible for all analyses. At ambient temperature, SCFA and compositional profiles were stable for 24 h and 48 h, respectively, while at 4 °C, SCFA profiles were maintained for 48 h. The global metabolome was highly susceptible, already changing at 24 h in non-frozen conditions. Thus, faecal microbiota was best preserved on all levels when transported as a native sample frozen within 24 h, leading to the least biased outcomes in the analysis. We conclude that the immediate freezing of native stool samples for transportation to the lab is best suited for planned multi-Omics analyses that include metabolomics to extend standard sequencing approaches.
Novel Agrobacterium fabrum str. 1D1416 for Citrus Transformation
Authors: Alabed Diaa , Tibebu Redeat , Ariyaratne Menaka , Shao Min , Milner Matthew J. , Thomson James G.
Published: October 2024

Citrus is one of the world’s most important and widely produced fruit crops, with over a 100 million metric tons harvested from nearly 10 million hectares in 2023. Challenges in crop maintenance, production, and fruit quality necessitate developing new traits through Agrobacterium-mediated genetic transformation. While a few Agrobacterium strains (EHA105, GV3101, LBA4404) are known to transform citrus, many wild strains remain untested. We screened forty-one wild-type Agrobacterium strains isolated from various woody species and identified five capable of DNA transfer into citrus cells. Strain 1D1416 demonstrated the highest transient transformation frequency in Carrizo epicotyl explants (88%), outperforming the control EHA105 (84%) with comparable shoot regeneration rates (32% and 42%, respectively). Notably, 1D1416 exhibited no overgrowth and had the lowest necrosis and mortality rates in transformed tissues. It efficiently transferred the DsRed gene and induced galls in mature tissues of Mexican lime (70%), lemon (48%), Washington navel orange (25%), and clementine (6%). Genome sequencing of 1D1416 allowed for the disarming of the native T-DNA and addition of GAANTRY technology. This novel strain, combined with an optimized transformation procedure, make it a valuable tool for advancing citrus transformation.
It Takes Two to Make a Thing Go Right: Epistasis, Two-Component Response Systems, and Bacterial Adaptation
Authors: Sanders Brittany R. , Thomas Lauren S. , Lewis Naya M. , Ferguson Zaria A. , Graves Joseph L. , Thomas Misty D.
Published: October 2024

Understanding the interplay between genotype and fitness is a core question in evolutionary biology. Here, we address this challenge in the context of microbial adaptation to environmental stressors. This study explores the role of epistasis in bacterial adaptation by examining genetic and phenotypic changes in silver-adapted Escherichia coli populations, focusing on the role of beneficial mutations in two-component response systems (TCRS). To do this, we measured 24-hour growth assays and conducted whole-genome DNA and RNA sequencing on E. coli mutants that confer resistance to ionic silver. We showed recently that the R15L cusS mutation is central to silver resistance, primarily through upregulation of the cus efflux system. However, here we show that this mutation’s effectiveness is significantly enhanced by epistatic interactions with additional mutations in regulatory genes such as ompR, rho, and fur. These interactions reconfigure global stress response networks, resulting in robust and varied resistance strategies across different populations. This study underscores the critical role of epistasis in bacterial adaptation, illustrating how interactions between multiple mutations and how genetic backgrounds shape the resistance phenotypes of E. coli populations. This work also allowed for refinement of our model describing the role TCRS genes play in bacterial adaptation by now emphasizing that adaptation to environmental stressors is a complex, context-dependent process, driven by the dynamic interplay between genetic and environmental factors. These findings have broader implications for understanding microbial evolution and developing strategies to combat antimicrobial resistance.
Imaging Recommendations for Diagnosis, Staging, and Management of Primary Central Nervous System Neoplasms in Adults
Authors: Bhattacharya Kajari , Mahajan Abhishek
Published: October 2024

Central nervous system (CNS) neoplasms are a vast and diverse group of tumors in adults with variable prognoses depending on histology and increasingly understood molecular features. There has been a major paradigm shift in the approach towards these neoplasms ever since the implications of these molecular features have been recognized. Gliomas are the major group of primary CNS neoplasms in adults, and glioblastomas are a significant cause of morbidity and mortality, especially in older patients. Apart from gliomas, meningiomas and pituitary tumors are other major groups. This review aims to elucidate the role of imaging in the screening, diagnosis, management, and follow-up of major primary CNS neoplasms, with an elaborate discussion on the role of artificial intelligence and advanced imaging techniques and future directions likely to play a pivotal role in this ever-evolving subspecialty of oncology.
Determination of Submerged Breakwater Efficiency Using Computational Fluid Dynamics
Authors: Rudan Smiljko , Sviličić Šimun
Published: October 2024

Wind-induced waves can lead to the partial or complete wash-over of beaches, causing erosion that impacts both the landscape and tourist infrastructure. In some regions of the world, e.g., Croatia, this process, which usually occurs during a harsh winter, has a major impact on the environment and the economy, and preventing or reducing this process is highly desirable. One of the simplest methods to reduce or prevent beach erosion is the use of innovative underwater structures designed to decrease wave energy by reducing wave height. In this study, submerged breakwaters are numerically investigated using various topologies, positions, and angles relative to the free surface. Not only is the optimal topology determined, but the most efficient arrangement of multiple breakwaters is also determined. The advantage of newly developed submerged breakwaters over traditional ones (rock-fixed piers) is that they do not require complex construction, massive foundations, or high investment costs. Instead, they comprise simple floating bodies connected to the seabed by mooring lines. This design makes them not only cheap, adaptable, and easy to install but also environmentally friendly, as they have little impact on the seabed and the environment. To evaluate wave damping effectiveness, the incompressible computational fluid dynamics (ICFD) method is used, which enables the use of a turbulence model and the possibility of accurate wave modelling.