bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence and cost of sickle cell disease in France: real-world analysis using data from the Echantillon Généraliste des Bénéficiaires
Authors: Beillat Maud , Durand-Zaleski Isabelle , Pirenne France , Bénard Stève , Chillotti Louis , Galacteros Frédéric
Published: September 2023

Sickle cell disease (SCD) is a genetic disorder of the hemoglobin resulting in chronic anemia, hemolysis, and vaso-occlusions. Its treatment mostly relies on hydroxycarbamide, transfusions, and stem cell transplantation. This study aimed at describing the epidemiology and management of SCD in adolescent and adult patients in France. This was a retrospective study performed among SCD patients aged ≥12 years between 2016 and 2018 and controls. SCD patients were matched on a 1:3 ratio with a group of individuals with no diagnosis of SCD, referred as control group. The matching of SCD patients and controls was a direct matching based on age, sex, CMU-c status (which corresponds to free-of-charge complementary coverage for people with low resources) and geographical region of residence. SCD patients and their matched controls were followed-up for the same amount of time by adjusting controls’ follow-up period to that of the associated patients. This study used claims data from the French representative 1/97th sample of health data system. The main outcomes were the patients’ characteristics and treatments received, healthcare consumptions and related costs among SCD cases and controls. Between 2016 and 2018, 151 patients with ≥6 months of follow-up were identified out of the total population of 732,164 individuals. SCD prevalence extrapolated to the entire population [95% CI] was 19,502 [19,230, 19,778] in 2018. The median (Q1–Q3) age at inclusion date was 37.0 (25.0–48.0) years, with 69.5% of patients being female. The mean (SD) reimbursed cost over follow-up was €24,310 (89,167), mostly represented by hospitalization costs accounting for €21,156 (86,402). A switch in SCD management was observed with age, as younger patients presented more frequent hospitalizations and acute procedures, while older ones had more frequent medical visits and paramedical care. Mean (SD) annual costs were €25,680 (91,843) and vs. €3,227 (23,372) for patients and controls, respectively (p < 0.001), representing an extra cost of almost €150 million over the entire SCD population. This study highlighted the important costs related to SCD and the related medical need with treatment alternatives, which could be filled by the emergence of new therapies.
Adaptation and psychometric study of the scale for the measurement of fear and anxiety of COVID-19 disease in pregnant women (AMICO_Pregnant)
Authors: Muñoz-Vela Francisco Javier , Rodríguez-Díaz Luciano , Fernández-Carrasco Francisco Javier , Allande-Cussó Regina , Vázquez-Lara Juana Maria , Fagundo-Rivera Javier , Gómez-Salgado Juan
Published: September 2023

Objective

The aim of this research was to adapt and explore the psychometric properties of a specific scale to assess the levels of fear and anxiety of COVID-19 disease in pregnant women.

Methods

An adaptation phase, by a panel of experts, and a psychometric descriptive cross-sectional study were carried out on the final version of the 16-item, self-administered AMICO_Pregnant scale. Univariate and bivariate analyses were carried out, followed by exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The consistency of the scale was assessed using the Omega coefficient and Cronbach’s Alpha.

Results

With a sample of 1,013 pregnant women living in Spain and over 18 years of age, the mean age was 33 years. The scale showed a bifactor structure (anxiety and fear) that was confirmed with good fit parameters. Reliability was assessed in terms of internal consistency by calculating Cronbach’s Alpha coefficient (0.95) and McDonald’s Omega coefficient (0.94) as indicators of robustness of the scale’s reliability.

Conclusion

The AMICO_Pregnant scale of 16 items with scores ranging from 1 to 10 is a valid and reliable tool to assess levels of anxiety and fear of COVID_19 in Spanish pregnant women. Pregnant women have shown moderate levels of anxiety and fear regarding the COVID_19 disease in the final phase of the pandemic.
Introducing the keyconcept approach to the analysis of language: the case of regulation in COVID-19 diaries
Authors: Robinson Justyna A. , Sandow Rhys J. , Piazza Roberta
Published: September 2023

Using the Mass Observation corpus of 12th of May Diaries, we investigate concepts that are characteristic of the first coronavirus lockdown in the UK. More specifically, we extract and analyse concepts which are distinctive of the discourses produced in May 2020 in relation to concepts used in the 10 previous years, 2010–2019. In the current paper we focus on the concept of regulation, which we identify through a novel approach to querying semantic content in large datasets. Typically, linguists look at keywords to understand differences between two datasets. We demonstrate that taking the perspective of a keyconcept rather than the keyword in linguistic analysis is a beneficial way of identifying trends in broader patterns of thoughts and behaviours which reflect lived-experiences that are particularly prominent of a given dataset, which, in this current paper, is the COVID-19 era dataset. In order to contextualise the keyconcept analysis, we investigate the discourses surrounding the concept of regulation. We find that diarists communicate collective experience of limited individual agency, surrounded by feelings of fear and gratitude. Diarists' reporting on events is often fragmented, focused on new information, and firmly placed in a temporal frame.
Sustainable collaboration on complex problems: a “who” not a “what” challenge
Authors: Gibson Josie
Published: September 2023

Despite decades of collective efforts and millions of dollars of cross-sector investment, collaborations created to address wicked problems—complex issues that span industries and sectors whose root causes are unclear—have had mixed success. The wicked problems terrain is tribal and competitive. It is contested by proponents of competing collective change and innovation tools and methodologies, advocates of different leadership approaches and, in recent years, big business champions who claim private enterprise is the most effective driver of solutions. This perspective article argues that while all these elements deserve attention, the primary focus of many collaborations reflects a Western scientific bias toward “what” and “how” questions—governance, processes, activities, metrics and outcomes—at the expense of the “who” component: the human relationships, or relational infrastructure, required to build and sustain effective collective efforts. This is crucial given the grueling realities of complex multi-year initiatives. This article explores the tension between this bias and the need to develop robust relational networks through skilful collective leadership, as reflected in numerous First Nations knowledge practices. We discuss leadership as a both an individual and a collective capability and highlight the need for better understanding of its significant role in anchoring, shaping and guiding effective system-based efforts that achieve positive impact.
River reach-level machine learning estimation of nutrient concentrations in Great Britain
Authors: Tso Chak-Hau Michael , Magee Eugene , Huxley David , Eastman Michael , Fry Matthew
Published: September 2023

Nitrogen (N) and phosphorus (P) are essential nutrients necessary for plant growth and support life in aquatic ecosystems. However, excessive N and P can lead to algal blooms that deplete oxygen and lead to fish death and the release of toxins that are harmful to humans. Estimates of N and P levels in rivers are typically calculated at station or grid (>1 km) scale; therefore, it is difficult to visualise the evolution of water quality as water travels downstream. Using a high-resolution reach-scale river network and associating each reach with land cover fractions and catchment descriptors, we trained random forest models on aggregated data (2010–2020) from the Environmental Agency Open Water Quality Data Archive for 2,343 stations to predict long-term nitrate and orthophosphate concentrations at each river reach in Great Britain (GB). We separated the model training and predictions for different seasons to investigate the potential difference in feature importance. Our model predicted concentrations with an average testing coefficient of determination (R2) of 0.71 for nitrate and 0.58 for orthophosphate using 5-fold cross-validation. Our model showed slightly better performance for higher Strahler stream orders, highlighting the challenges of making predictions in small streams. Our results revealed that arable and horticultural land use is the strongest and most reliable predictor for nitrate, while floodplain extents and standard percentage runoff are stronger predictors for orthophosphate. Nationally, higher orthophosphate concentrations were observed in urbanised areas. This study shows how combining a river network model with machine learning can easily provide a river network understanding of the spatial distribution of water quality levels.
Fermentation quality, aerobic stability, and microbiome structure and function of Caragana korshinskii silage inoculated with/without Lactobacillus rhamnosus or Lactobacillus buchneri
Authors: Wu Baiyila , Ai Juanjuan , Li Tiyu , Qin Weize , Hu Zongfu , Siqin Tuya , Wu Tiemei , Wang Chao , Niu Huaxin
Published: September 2023

Caragana korshinskii is a forage shrub species with high-protein content that has been extensively used to alleviate feed shortages for ruminants in northern China. Herein, we investigated the effects of Lactobacillus rhamnosus and Lactobacillus buchneri on the fermentation quality, aerobic stability, and microbiome composition and the predicted functional characteristics of C. korshinskii silage. C. korshinskii silages were inoculated with and without L. rhamnosus or L. buchneri. After 14 and 56 days of ensiling, the aerobic stability was determined. The results revealed that after 14 and 56 days of ensiling, L. rhamnosus- and L. buchneri-inoculated silage exhibited increased acetic acid and lactic acid contents, whereas the pH and 2,3-butanediol and butyric acid contents were decreased compared with those of the control silage. The control silages that were opened at 14 and 56 d, deteriorated during the aerobic stability test, whereas silages inoculated with L. rhamnosus and L. buchneri did not exhibit any aerobic deterioration. The control silage showed an increased Clostridium and Bacillus abundance, whereas Lactobacillus abundance decreased compared with L. rhamnosus- and L. buchneri-inoculated silages, following the 7 days of aerobic exposure. The fermentation parameters were associated with microbial communities, including Lactobacillus, Pedicoccus, Weissella, Clostridium, and Bacillus. Carbohydrate and amino acid metabolisms in the control silage decreased after 7 days of aerobic exposure compared with lactic acid bacteria-inoculated silages. To conclude, next-generation sequencing combined with 16S ribosomal RNA gene-predicted functional analyses might provide new information about the silage quality during fermentation and the aerobic stability.
Understanding tumor localization in multiparametric MRI of the prostate—effectiveness of 3D printed models
Authors: Haack Maximilian , Reisen Katja , Ghazy Ahmed , Stroh Kristina , Frey Lisa , Sparwasser Peter , Duwe Gregor , Mager Rene , Haferkamp Axel , Borgmann Hendrik
Published: September 2023

Introduction

Understanding tumor localization in multiparametric MRI (mpMRI) of the prostate is challenging for urologists but of great importance in mpMRI-fused prostate biopsy or radical prostatectomy. The aim was to evaluate the effectiveness of 3D printed models of the prostate to help urologists to locate tumors.

Methods and Participants

20 urologists from University Medical Center Mainz (Germany) were asked to plot the location of a cancer suspicious lesion (PI-RADS ≥ 4) on a total of 30 mpMRI on a prostate sector diagram. The following 3 groups (as matched triplets) were divided into: mpMRI only, mpMRI with radiological report and mpMRI with 3D printed model (scaled 1:1). Statistical analysis was performed using one-way and two-way ANOVA (with bonferroni post-test).

Results

Overall, localization of the suspicious lesion was superior with the radiological report (median of max. 10 [IQR]: MRI 2 [IQR 1;5], MRI + report: 8 [6.3;9], MRI + 3D model 3 [1.3;5.8]; p < 0.001). Residents with <1 year of experience had a significantly higher detection rate using a 3D printed model [5 (5;5.8)] compared to mpMRI alone [1.5 (1;3.5)] (p < 0.05). Regarding the estimation of index lesion extension, the 3D model showed a significant benefit (mean percentage difference [95% CI]: MRI alone 234% [17.1;451.5], MRI + report 114% [78.5;149.6], MRI + 3D model 17% [−7.4;41.3] (p < 0.01).

Conclusion

Urologists still need the written radiological report for a sufficient understanding of tumor localization. The effectiveness of the 3D printed model regarding tumor localization is particularly evident in young residents (<1 year) and leads to a better overall assessment of the tumor extension.
The ToxCast pipeline: updates to curve-fitting approaches and database structure
Authors: Feshuk M. , Kolaczkowski L. , Dunham K. , Davidson-Fritz S. E. , Carstens K. E. , Brown J. , Judson R. S. , Paul Friedman K.
Published: September 2023

Introduction: The US Environmental Protection Agency Toxicity Forecaster (ToxCast) program makes in vitro medium- and high-throughput screening assay data publicly available for prioritization and hazard characterization of thousands of chemicals. The assays employ a variety of technologies to evaluate the effects of chemical exposure on diverse biological targets, from distinct proteins to more complex cellular processes like mitochondrial toxicity, nuclear receptor signaling, immune responses, and developmental toxicity. The ToxCast data pipeline (tcpl) is an open-source R package that stores, manages, curve-fits, and visualizes ToxCast data and populates the linked MySQL Database, invitrodb.

Methods: Herein we describe major updates to tcpl and invitrodb to accommodate a new curve-fitting approach. The original tcpl curve-fitting models (constant, Hill, and gain-loss models) have been expanded to include Polynomial 1 (Linear), Polynomial 2 (Quadratic), Power, Exponential 2, Exponential 3, Exponential 4, and Exponential 5 based on BMDExpress and encoded by the R package dependency, tcplfit2. Inclusion of these models impacted invitrodb (beta version v4.0) and tcpl v3 in several ways: (1) long-format storage of generic modeling parameters to permit additional curve-fitting models; (2) updated logic for winning model selection; (3) continuous hit calling logic; and (4) removal of redundant endpoints as a result of bidirectional fitting.

Results and discussion: Overall, the hit call and potency estimates were largely consistent between invitrodb v3.5 and 4.0. Tcpl and invitrodb provide a standard for consistent and reproducible curve-fitting and data management for diverse, targeted in vitro assay data with readily available documentation, thus enabling sharing and use of these data in myriad toxicology applications. The software and database updates described herein promote comparability across multiple tiers of data within the US Environmental Protection Agency CompTox Blueprint.
Conservation agriculture has no significant impact on sheep digestive parasitism
Authors: ElHamdi Sihem , Sassi Limam , Rekik Mourad , Dhehibi Mokhtar , Cheikh M'hamed Hatem , Gharbi Mohamed
Published: September 2023

Conservation agriculture (CONS A) is a sustainable agriculture system based on crop rotation with no tillage. It has various environmental advantages compared to conventional agriculture (CONV A): decreased water evaporation, erosion, and CO2 emissions. In this first study of its kind, we aim to evaluate the impact of this type of agriculture on sheep gastrointestinal parasites. Two lamb groups aged between 5 and 10 months were randomly included to graze separately on CONS A and CONV A pastures. Each group was composed of two batches of three lambs, and these were followed up for two rearing months. Liveweight, hematological parameter variation, and digestive parasites were studied. At the end of the study period, lambs were slaughtered the carcass yield was determined, and a helminthological autopsy was performed on the digestive tracts of the animals to estimate different parasitological indicators. There was no difference between lambs reared on CONS A and those reared on CONV A for all parasite indicators (infestation intensity, abundance, and prevalence). The same trend was also obtained for hematological parameters, liveweight evolution, and carcass yield. These results prove that there is no impact of CONS A on the sheep's digestive parasitism. Further studies are needed to support these findings on larger animal samples and to investigate the impact of conservation agriculture on other parasite species. Similar studies could also be conducted on ruminant species.
Cross-protection of commercial vaccines against Chilean swine influenza A virus using the guinea pig model as a surrogate
Authors: Tapia Rodrigo , Mena Juan , García Victoria , Culhane Marie , Medina Rafael A. , Neira Victor
Published: September 2023

Influenza A virus poses a significant threat to public health and the swine industry. Vaccination is the primary measure for controlling the disease, but the effectiveness of vaccines can vary depending on the antigenic match between vaccine strains and circulating strains. In Chile, H1N1pdm09 and other lineages H1N2 and H3N2 have been detected in pigs, which are genetically distinct from the strains included in commercial vaccines. This study aimed to evaluate the cross-protection by commercial vaccines against strains circulating in Chile using the guinea pig model. For this study, four circulating strains [A/swine/Chile/H1A-7/2014(H1N2), A/swine/Chile/H1B-2/2014(H1N2), A/swine/Chile/H1P-12/2015(H1N1), and A/swine/Chile/H3-2/2015(H3N2)] were selected. Guinea pigs were divided into vaccinated and control groups. The vaccinated animals received either a multivalent antigenically heterologous or monovalent homologous vaccine, while the control animals remained unvaccinated. Following vaccination, all animals were intranasally challenged, and nasal wash samples were collected at different time points post-infection. The results showed that the homologous monovalent vaccine-induced hemagglutinin-specific antibodies against the Chilean pandemic H1N1pdm09 strain. However, the commercial heterologous multivalent vaccine failed to induce hemagglutinin-specific antibody titers against the H1N2 and H3N2 challenge strains. Furthermore, the homologous monovalent vaccine significantly reduced the duration of viral shedding and viral titers specifically against the Chilean pandemic H1N1pdm09 strain and heterologous multivalent vaccine only partial. These findings highlight the importance of regularly updating vaccine strains to match the circulating field strains for effective control of swine influenza. Further research is needed to develop vaccines that confer broader protection against diverse strains of swine influenza A virus.
Comparison of visual assessments of anisocytosis in canine blood smears and analyzer-calculated red blood cell distribution width
Authors: Jensen Asger L. , Krogh Anne K. H. , Nielsen Lise N.
Published: September 2023

Red blood cell distribution width (RDW) and visual assessments of anisocytosis assess variability in erythrocyte size. Veterinary studies on the correlation between the two methods and on observer agreement are scarce. The objectives were to assess the correlation of the grading of anisocytosis by means of conventional microscopy of canine blood smears to RDW, and to assess intra- and inter-observer variation in assessing the degree of anisocytosis. The study included 100 canine blood samples on which blood smear examination and RDW measurement were performed. RDW was measured on the Advia 2120i analyzer. The degree of anisocytosis was based on a human grading scheme assessing the ratio between the size of the representative largest red blood cell and that of the representative smallest red blood cell (1+ if <2x, 2+ if 2–3x, 3+ if 3–4x, and 4+ if >4x). Three observers participated and assessed the blood smears by conventional microscopy twice, 3 weeks apart by each observer. The correlation was assessed for each observer on each occasion using Kendahl-tau-b analysis. Intra-observer agreement was assessed using quadratically weighted kappa. Inter-observer agreement was assessed using free-marginal multi-rater kappa. Anisocytosis graded on blood smears correlated significantly with RDW values as assessed by Kendahl-tau-b ranging between 0.37 and 0.51 (p < 0.0001). Intra-observer agreement ranged from weak to moderate with resulting kappa-coefficients being 0.58, 0.68, and 0.75, respectively. Inter-observer agreement was weak (Kappa-values 0.44). The weak to moderate observer agreement in the visual assessment of anisocytosis indicates that the more precise and more repeatable RDW measurement should be used for clinical decision-making.
Magnetic Resonance Roadmap in Detecting and Staging Endometriosis: Usual and Unusual Localizations
Authors: Piccolo Claudia Lucia , Cea Laura , Sbarra Martina , De Nicola Anna Maria , De Cicco Nardone Carlo , Faiella Eliodoro , Grasso Rosario Francesco , Beomonte Zobel Bruno
Published: September 2023

Endometriosis is a chronic condition characterized by the presence of abnormal endometrial tissue outside the uterus. These misplaced cells are responsible for inflammation, symptoms, scar tissue and adhesions. Endometriosis manifests mainly in three patterns: superficial peritoneal lesions (SUP), ovarian endometriomas (OMA) and deep infiltrating endometriosis (DIE). It also exhibits atypical and extremely rare localization. The updated 2022 guidelines of the ESHRE recommend using both ultrasound and magnetic resonance imaging (MRI) as first-line diagnostic tests. Currently, MRI provides a more complete view of the pelvis anatomy. The aim of our review is to provide radiologists with a “map” that can help them in reporting pelvic MRI scans in patients with endometriosis. We will illustrate the usual and unusual localizations of endometriosis (categorized into compartments) using post-operative imaging, and we will focus on the role of MRI, the main sequences and the use of contrast agents.
HHV-6 in Cerebrospinal Fluid in Immunocompetent Children
Authors: Nikolskiy Mikhail A. , Lioznov Dmitriy A. , Gorelik Evgeniy U. , Vishnevskaya Tatyana V.
Published: September 2023

Background: Human herpes virus-6 (HHV-6) is a ubiquitous virus known as an etiological agent of exanthem subitum. HHV-6-encephalitis in immunocompetent children is a rare complication of the primary infection. There are a lack of data on the prevalence of HHV-6-encephalitis in Russia. The aim of our study was to analyze the prevalence of HHV-6 DNA in the cerebrospinal fluid (CSF) of immunocompetent children with suspected acute meningoencephalitis. Materials and Methods: A total of 712 CSF samples were tested using qualitative PCR over 12 years at N.F. Filatov Children’s City Clinical Hospital No.5, Saint-Petersburg, Russia. Results: HHV-6 DNA was detected in 20 (2.8%) of the samples. Retrospectively, we analyzed the medical records of 15 cases. There were seven boys and eight girls from 1 month to 7 years old; the mean age was 22.3 ± 5.6 months. Most HHV-6 DNA-positive cases were due to the primary form of HHV-6 infection. There were, in total, four cases of HHV-6-meningoencephalitis. All the children had a complete recovery, without neurological deficits or death. Conclusions: HHV-6 encephalitis is a very rare disease in immunocompetent children (four cases among 712 samples over 12 years). Additional studies are needed to develop accurate diagnostic criteria and therapeutic approaches.
The Good Clinical Outcome for Patients with Acute Ischemic Stroke Treated with Mechanical Thrombectomy—Does Time Still Matter?
Authors: Sila Dalibor , Marinovic Marko , Vojtková Mária , Kirsch Philipp , Rath Stefan , Charvát František
Published: September 2023

The primary target was an investigation of the factors predicting a good clinical outcome of patients with acute ischemic stroke after treatment with mechanical thrombectomy. Additionally, we compared the treatment results in known and unknown symptom onset time groups. We retrospectively analyzed the data from 2012 to 2020 and divided 240 patients into the known and unknown symptom onset time groups. We looked for the variables predicting a good clinical outcome (NIHSS 0–4 at discharge) in both groups. In both groups, there was no statistically significant difference in good clinical outcomes (43% in the known symptom onset time group vs. 33.3% in the unknown symptom onset time group, p = 0.203). Factors predicting a good clinical outcome in both groups were lower NIHSS scores at admission, the presentation of pial arterial collaterals on admission CT angiography, and bridging intravenous thrombolysis. In the known symptom onset time group, lower age was also a factor predicting good outcome. Our clinical results of treatment by using mechanical thrombectomy were comparable in the known and unknown symptom onset time groups.
Pediatric-Inspired Regimens in the Treatment of Acute Lymphoblastic Leukemia in Adolescents and Young Adults: A Systematic Review
Authors: Zeckanovic Aida , Fuchs Philipp , Heesen Philip , Bodmer Nicole , Otth Maria , Scheinemann Katrin
Published: September 2023

Adolescents and young adults (AYA) with acute lymphoblastic leukemia (ALL) have significantly worse outcomes than their younger counterparts. Current treatment guidelines rely mostly on non-randomized retrospective studies. We performed a systematic review of studies published within the last 15 years comparing pediatric-inspired regimens (PIR) versus adult-type regimens or performing an age-stratified analysis of outcomes in the AYA population. Due to the heterogeneity of data, a meta-analysis was not possible. However, the gathered data show a trend toward improvement in outcomes and an acceptable toxicity profile in patients treated with PIRs compared to conventional adult-type regimens. There is still room for further improvement, as older patients within the AYA population tend to perform poorly with PIR or conventional adult-type chemotherapy. Further randomized studies are needed to develop an optimal treatment strategy for AYA with ALL.
Research on Key Technology of Ship Re-Identification Based on the USV-UAV Collaboration
Authors: Dou Wenhao , Zhu Leiming , Wang Yang , Wang Shubo
Published: September 2023

Distinguishing ship identities is critical in ensuring the safety and supervision of the marine agriculture and transportation industry. In this paper, we present a comprehensive investigation and validation of the progression of ship re-identification technology within a cooperative framework predominantly governed by UAVs. Our research revolves around the creation of a ship ReID dataset, the creation of a ship ReID dataset, the development of a feature extraction network, ranking optimization, and the establishment of a ship identity re-identification system built upon the collaboration of unmanned surface vehicles (USVs) and unmanned aerial vehicles (UAVs). We introduce a ship ReID dataset named VesselID-700, comprising 56,069 images covering seven classes of typical ships. We also simulated the multi-angle acquisition state of UAVs to categorize the ship orientations within this dataset. To address the challenge of distinguishing between ships with small inter-class differences and large intra-class variations, we propose a fine-grained feature extraction network called FGFN. FGFN enhances the ResNet architecture with a self-attentive mechanism and generalized mean pooling. We also introduce a multi-task loss function that combines classification and triplet loss, incorporating hard sample mining. Ablation experiments on the VesselID-700 dataset demonstrate that the FGFN network achieves outstanding performance, with a Rank-1 accuracy of 89.78% and mAP of 65.72% at a state-of-the-art level. Generalization experiments on pedestrian and vehicle ReID datasets reveal that FGFN excels in recognizing other rigid body targets and diverse viewpoints. Furthermore, to further enhance the advantages of UAV-USV synergy in ship ReID performance, we propose a ranking optimization method based on the homologous fusion of multi-angle UAVs and heterologous fusion of USV-UAV collaborative architecture. This optimization leads to a significant 3% improvement in Rank-1 performance, accompanied by a 73% reduction in retrieval time cost.
Learning Template-Constraint Real-Time Siamese Tracker for Drone AI Devices via Concatenation
Authors: Wu Zhewei , Liu Qihe , Zhou Shijie , Qiu Shilin , Zhang Zhun , Zeng Yi
Published: September 2023

Significant progress has been made in object tracking tasks thanks to the application of deep learning. However, current deep neural network-based object tracking methods often rely on stacking sub-modules and introducing complex structures to improve tracking accuracy. Unfortunately, these approaches are inefficient and limit the feasibility of deploying efficient trackers on drone AI devices. To address these challenges, this paper introduces ConcatTrk, a high-speed object tracking method designed specifically for drone AI devices. ConcatTrk utilizes a lightweight network architecture, enabling real-time tracking on edge devices. Specifically, the proposed method primarily uses the concatenation operation to construct its core tracking steps, including multi-scale feature fusion, intra-frame feature matching, and dynamic template updating, which aim to reduce the computational overhead of the tracker. To ensure tracking performance in UAV tracking scenarios, ConcatTrk implements a learnable feature matching operator along with a simple and efficient template constraint branch, which enables accurate tracking by discriminatively matching features and incorporating periodic template updates. Results of comprehensive experiments on popular benchmarks, including UAV123, OTB100, and LaSOT, show that ConcatTrk has achieved promising accuracy and attained a tracking speed of 41 FPS on an edge AI device, Nvidia AGX Xavier. ConcatTrk runs 8× faster than the SOTA tracker TransT while using 4.9× fewer FLOPs. Real-world tests on the drone platform have strongly validated its practicability, including real-time tracking speed, reliable accuracy, and low power consumption.
A Novel Joint Channel Estimation and Symbol Detection Receiver for Orthogonal Time Frequency Space in Vehicular Networks
Authors: Zhang Xiaoqi , Wen Haifeng , Yan Ziyu , Yuan Weijie , Wu Jun , Li Zhongjie
Published: September 2023

A vehicular network embodies a specialized variant of wireless network systems, characterized by its capability to facilitate inter-vehicular communication and connectivity with the encompassing infrastructure. With the rapid development of wireless communication technology, high-speed and reliable communication has become increasingly important in vehicular networks. It has been demonstrated that orthogonal time frequency space (OTFS) modulation proves effective in addressing the challenges posed by high-mobility environments, as it transforms the time-varying channels into the delay-Doppler domain. Motivated by this, in this paper, we focus on the theme of integrated sensing and communication (ISAC)-assisted OTFS receiver design, which aims to perform sensing channel estimation and communication symbol detection. Specifically, the estimation of the sensing channel is accomplished through the utilization of a deep residual denoising network (DRDN), while the communication symbol detection is performed by orthogonal approximate message passing (OAMP) processing. The numerical results demonstrate that the proposed ISAC system exhibits superior performance and robustness compared to traditional methods, with a lower complexity as well. The proposed system has great potential for future applications in wireless communication systems, especially in challenging scenarios with high mobility and interference.
A New Truncated Lindley-Generated Family of Distributions: Properties, Regression Analysis, and Applications
Authors: Hussein Mohamed , Rodrigues Gabriela M. , Ortega Edwin M. M. , Vila Roberto , Elsayed Howaida
Published: September 2023

We present the truncated Lindley-G (TLG) model, a novel class of probability distributions with an additional shape parameter, by composing a unit distribution called the truncated Lindley distribution with a parent distribution function G(x). The proposed model’s characteristics including critical points, moments, generating function, quantile function, mean deviations, and entropy are discussed. Also, we introduce a regression model based on the truncated Lindley–Weibull distribution considering two systematic components. The model parameters are estimated using the maximum likelihood method. In order to investigate the behavior of the estimators, some simulations are run for various parameter settings, censoring percentages, and sample sizes. Four real datasets are used to demonstrate the new model’s potential.
Effects of Nonextensive Electrons on Dust–Ion Acoustic Waves in a Collisional Dusty Plasma with Negative Ions
Authors: Liu Zhipeng
Published: September 2023

The effects of nonextensive electrons on nonlinear ion acoustic waves in dusty negative ion plasmas with ion–dust collisions are investigated. Analytical results show that both solitary and shock waves are supported in this system. The wave propagation is governed by a Korteweg–de Vries Burgers-type equation. The coefficients of this equation are modified by the nonextensive parameter q. Numerical calculations indicate that the amplitude of solitary wave and oscillatory shock can be obviously modified by the nonextensive electrons, but the monotonic shock is little affected.
Suitability Analysis Using GIS-Based Analytic Hierarchy Process (AHP) for Solar Power Exploration
Authors: Gacu Jerome G. , Garcia Junrey D. , Fetalvero Eddie G. , Catajay-Mani Merian P. , Monjardin Cris Edward F.
Published: September 2023

Sibuyan Island is experiencing a significant increase in electricity demand due to population growth, urbanization, and industrial development. The island plans to use solar energy, recognizing its abundance and renewable nature; thus, this study was conducted to visualize the spatial distribution of solar exploration suitability using a geographic information system (GIS). Various criteria, including climatology, location, geography, meteorology, and disaster susceptibility, were considered in the assessment. Parameters affected by government policies, such as protected areas, proximity to rivers, roads and faults, ancestral domains, and proclaimed watersheds, were also considered. Parameters were weighted, and suitability levels were highlighted using AHP. The study revealed that about 5.88% (2674.06 km2) of the island was categorized as highly suitable for a solar farm, 34.99% (15,908.21 km2) as suitable, 2.49% (1129.95 km2) as moderately suitable, and the majority, 56.64% (25,754.47 km2), was considered not suitable for solar projects. A solar power suitability map was developed as a reference for local governments and residents in establishing solar PV systems in their respective sites, thus maximizing the full potential of their land. The study also directs future solar power exploration studies in Sibuyan Island, supporting ongoing efforts to maximize solar energy utilization.
Applications of Machine Learning in Subsurface Reservoir Simulation—A Review—Part II
Authors: Samnioti Anna , Gaganis Vassilis
Published: September 2023

In recent years, Machine Learning (ML) has become a buzzword in the petroleum industry, with numerous applications which guide engineers in better decision making. The most powerful tool that most production development decisions rely on is reservoir simulation with applications in multiple modeling procedures, such as individual simulation runs, history matching and production forecast and optimization. However, all of these applications lead to considerable computational time and computer resource-associated costs, rendering reservoir simulators as not fast and robust enough, and thus introducing the need for more time-efficient and intelligent tools, such as ML models which are able to adapt and provide fast and competent results that mimic the simulator’s performance within an acceptable error margin. In a recent paper, the developed ML applications in a subsurface reservoir simulation were reviewed, focusing on improving the speed and accuracy of individual reservoir simulation runs and history matching. This paper consists of the second part of that study, offering a detailed review of ML-based Production Forecast Optimization (PFO). This review can assist engineers as a complete source for applied ML techniques in reservoir simulation since, with the generation of large-scale data in everyday activities, ML is becoming a necessity for future and more efficient applications.
Intrinsic Photoconductivity Spectral Dependence as a Tool for Prediction of Open-Circuit Voltage in Organic Solar Cells
Authors: Grzibovskis Raitis , Polaks Andis , Vembris Aivars
Published: September 2023

Organic materials are known for their variety of molecules. Methods to predict the parameters of organic photovoltaic (OPV) cells are required to avoid the time- and resource-consuming processes of manufacturing and testing OPVs. Usually, the open-circuit voltage (Uoc) is estimated as the difference between the ionization energy level of the electron donor molecule (Id) and the electron affinity level of the electron acceptor molecule (EAa). Various measurement methods are used to determine the energy level values of pure materials, which, when combined with energy level shifts due to the donor:acceptor interactions, make these estimations less precise. In this work, photoconductivity measurements were applied to the donor:acceptor films. Near threshold energy, the electron can be directly transferred from the donor to the acceptor molecule. The obtained charge transfer energy (ECT) shows the difference between Id and EAa in the film. This difference was compared to the Uoc value of an OPV made of the same donor:acceptor combination. We show that this approach provides less scattered results and a higher correlation coefficient compared to the Uoc estimation using energy level values.
Comparing Enhanced Models for Evaluating the Economic Impact of Airports
Authors: de Quadra Magalhães Ivaciane , Correia Anderson Ribeiro , da Silva Pinto Bandeira Michelle Carvalho Galvão , Zackiewicz Mauro , Tozi Luiz Antonio
Published: September 2023

Evaluating the economic impact of airports is crucial for understanding the benefits they bring to a region. However, when an area has more than one airport, it becomes essential to analyze each airport’s contribution to the local economy to make informed investment and policy decisions. Thus, studying economic models that can distinguish each airport’s impact on the region’s economy becomes essential. In this context, this paper aims to compare three different approaches to determine the economic contributions of airports in a given region and identify their social and economic benefits. The International Civil Aviation Organization recommends using input–output analysis in this context. The study considered three weight factors for the input–output basic model: circular buffer, displacement time, and Huff’s gravitational model. The analysis was performed using the three largest airports in São Paulo state, Brazil, due to their proximity and influence on the surrounding areas. The models were compared based on their efficiency and accuracy in reflecting the reality of the case study context. The study identified the most suitable model for establishing correlations between investments made in airport infrastructure and the generation of gross domestic product, employment, and added value. This study fills a gap in the existing literature by proposing improvements to the methods for evaluating airports’ economic and social benefits. In recent times, airport investors, both in the government and private sectors, have become increasingly demanding in their need for accurate analyses before making investments. Therefore, the results of this paper will provide valuable insights into the benefits of investing in airport infrastructure and help policymakers and investors make informed decisions.
Genome-Wide Identification of TCP Gene Family in Dendrobium and Their Expression Patterns in Dendrobium chrysotoxum
Authors: Huang Ye , Zhao Xuewei , Zheng Qinyao , He Xin , Zhang Meng-Meng , Ke Shijie , Li Yuanyuan , Zhang Cuili , Ahmad Sagheer , Lan Siren , Liu Zhong-Jian
Published: September 2023

The TCP gene family are plant-specific transcription factors that play important roles in plant growth and development. Dendrobium chrysotoxum, D. nobile, and D. huoshanense are orchids with a high ornamental value, but few studies have investigated the specific functions of TCPs in Dendrobium flower development. In this study, we used these three Dendrobium species to analyze TCPs, examining their physicochemical properties, phylogenetic relationships, gene structures, and expression profiles. A total of 50 TCPs were identified across three Dendrobium species; they were divided into two clades—Class-I (PCF subfamily) and Class-II (CIN and CYC/TB1 subfamilies)—based on their phylogenetic relationships. Our sequence logo analysis showed that almost all Dendrobium TCPs contain a conserved TCP domain, as well as the existence of fewer exons, and the cis-regulatory elements of the TCPs were mostly related to light response. In addition, our transcriptomic data and qRT-PCR results showed that DchTCP2 and DchTCP13 had a significant impact on lateral organs. Moreover, changes in the expression level of DchTCP4 suggested its important role in the phenotypic variation of floral organs. Therefore, this study provides a significant reference for the further exploration of TCP gene functions in the regulation of different floral organs in Dendrobium orchids.
A Benchmark Study of Protein–Fragment Complex Structure Calculations with NMR2
Authors: Torres Felix , Stadler Gabriela , Kwiatkowski Witek , Orts Julien
Published: September 2023

Protein–fragment complex structures are particularly sought after in medicinal chemistry to rationally design lead molecules. These structures are usually derived using X-ray crystallography, but the failure rate is non-neglectable. NMR is a possible alternative for the calculation of weakly interacting complexes. Nevertheless, the time-consuming protein signal assignment step remains a barrier to its routine application. NMR Molecular Replacement (NMR2) is a versatile and rapid method that enables the elucidation of a protein–ligand complex structure. It has been successfully applied to peptides, drug-like molecules, and more recently to fragments. Due to the small size of the fragments, ca < 300 Da, solving the structures of the protein–fragment complexes is particularly challenging. Here, we present the expected performances of NMR2 when applied to protein–fragment complexes. The NMR2 approach has been benchmarked with the SERAPhic fragment library to identify the technical challenges in protein–fragment NMR structure calculation. A straightforward strategy is proposed to increase the method’s success rate further. The presented work confirms that NMR2 is an alternative method to X-ray crystallography for solving protein–fragment complex structures.
Cold Exposure Regulates Hepatic Glycogen and Lipid Metabolism in Newborn Goats
Authors: Su Duo , Zhou Tianhui , Wang Yan , Wang Linjie
Published: September 2023

Cold exposure influences liver metabolism, thereby affecting energy homeostasis. However, the gene regulatory network of the liver after cold exposure remains poorly understood. In this study, we found that 24 h cold exposure (COLD, 6 °C) increased plasma glucose (GLU) levels, while reducing plasma non-esterified fatty acid (NEFA) and triglyceride (TG) levels compared to the room temperature (RT, 25 °C) group. Cold exposure increased hepatic glycogen content and decreased hepatic lipid content in the livers of newborn goats. We conducted RNA-seq analysis on the livers of newborn goats in both the RT and cold exposure groups. A total of 1600 genes were identified as differentially expressed genes (DEGs), of which 555 genes were up-regulated and 1045 genes were down-regulated in the cold exposure group compared with the RT group. Cold exposure increased the expression of genes involved in glycolysis, glycogen synthesis, and fatty acid degradation pathways. These results can provide a reference for hepatic lipid and glycogen metabolism in newborn goats after cold exposure.
Identification of Antibody-Mediated Hydrolysis Sites of Oligopeptides Corresponding to the SARS-CoV-2 S-Protein by MALDI-TOF Mass Spectrometry
Authors: Timofeeva Anna M. , Sedykh Sergey E. , Dmitrenok Pavel S. , Nevinsky Georgy A.
Published: September 2023

Antibodies recognizing RBD and the S-protein have been previously demonstrated to be formed in humans after SARS-CoV-2 infection and vaccination with the Sputnik V adenovirus vaccine. These antibodies were found to be active when hydrolyzing FITC-labeled oligopeptides corresponding to linear epitopes of the S-protein. The thin-layer chromatography method allows the relative accumulation of the reaction product to be estimated but cannot identify hydrolysis sites. This study used the MALDI-TOF MS method to establish oligopeptide hydrolysis sites. Using the MALDI-TOF MS method in combination with the analysis of known hydrolysis sites characteristic of canonical proteases allowed us to establish the unique hydrolysis sites inherent only to catalytically active antibodies. We have discovered two 12-mer oligopeptides to have six hydrolysis sites equally distributed throughout the oligopeptide. The other three oligopeptides were found to have two to three closely spaced hydrolysis sites. In contrast to trypsin and chymotrypsin proteases, the catalytically active antibodies of COVID-19 patients have their peptide bond hydrolyzed mainly after proline, threonine, glycine, or serine residues. Here, we propose a new high-throughput experimental method for analyzing the proteolytic activity of natural antibodies produced in viral pathology.