bluuebunny/crossref_metadata_2025 huggingface dataset:
Semi-supervised learning to automate tumor bud detection in cytokeratin-stained whole-slide images of colorectal cancer
Authors: Bokhorst John-Melle , Nagtegaal Iris D. , Zlobec Inti , Dawson Heather , Sheahan Kieran , Simmer Femke , Kirsch Richard , Vieth Michael , Lugli Alessandro , Laak Jeroen , Ciompi Francesco
Published: October 2022

Tumor budding is a histopathological biomarker associated with metastases and adverse survival outcome in colorectal carcinoma (CRC) patients. It is characterized by the presence of single tumor cells or small clusters of cells within the tumor or at the tumor-invasion front. In order to obtain a tumor budding score for a patient, the region with the highest tumor bud density must first be visually identified by a pathologist, after which buds will be counted in the chosen hotspot field. Automation of this process will expectedly increase efficiency and reproducibility. Here we present a deep learning convolutional neural network model that automates the above procedure. For model training we used a semi-supervised learning method, to maximize detection performance despite the limited amount of labeled training data. The model was tested on an independent dataset in which human and machine selected hotspots were mapped in relation to each other and manual and machine detected tumor bud numbers in the manually selected fields were compared. We report the results of the proposed method in comparison with visual assessment by pathologists. We show that automated tumor bud count achieves a prognostic value comparable with visual estimation, while based on an objective and reproducible quantification. We also explore novel metrics to quantify buds such as density and dispersion and report their prognostic value. We have made the model available for research use on https://grand-challenge.org/algorithms/colon-budding-in-ihc/.
A novel FOPID2FF2 controller optimized by a new Opposition based learning (OBL)-Black Widow Optimization (BWO) algorithm: application to CSTR
Authors: v ANUSHA RANI , D Prabhakaran , M Thirumarimurugan
Published: October 2022

In this study a novel controller FOPID2FF2 which is a FOPID controller with two fractional order filter in the two fractional order derivatives was proposed to improve the performance of the Continuous Stirred Tank Reactor (CSTR) system. The proposed controller has nine independent tunable parameters which are optimized by a new metaheuristic algorithm opposition based learning (OBL)-Black widow optimization (BWO). The OBL-BWO chooses its initial population using the opposition based learning (OBL). The OBL helps in improving the exploration capability of the algorithm, avoids the stagnation in local optima, and improves the quality of the initial population for the BWO. The proposed OBL-BWO was tested on standard benchmark functions using the statistical performance and the non-parametric analysis such as Wilcoxon signed rank test, convergence performance was carried out and compared to other state-of-art algorithms. To verify the superiority of the FOPID2FF2 controller optimized using OBL-BWO; FOPID without any filter, FOPID with a integer order filter (FOPIDF), FOPID with one fractional order filter (FOPIDFF) optimized using the same was proposed. The performance of the controller was analysed using the time domain response, frequency domain response and robustnesscriterion. From the statistical analysis the new OBL-BWO was better compared to the state of art algorithms and was used to optimize the FOPID2FF2 controller. From the performance analysis of the mentioned controllers it was identified that the OBL-BWO optimized FOPID2FF2 controller outperforms the other controllers.
An Advanced in Silico Model to Optimize the Pharmacokinetic Studies ON25 Mg2+ – Releasing Porphyrin – Fullerene Nanoparticles in Brain Ischemic Disorders
Authors: Fursov Valentin V. , Namestnikova Daria D. , Kuznetsov Dmitriy A.
Published: October 2022

The In Silico study on neuropharmacokinetiks of some novel porphyrin-fullerene based 25Mg2+ - nanocarriers was performed with an aim to optimize the preclinical research path required for both prevention and correction of the brain ischemic stroke related metabolic disorders such us ATP deplete and its direct consequences. Thus, the local brain tissue hypoxia scenario are in a focus of this novel analytical approach suitable for prediction of some parameters of the 25Mg – magnetic isotope effect promoted antihypoxic activities as long as they relates upon delivery, distribution and intralization of the low toxic/amphiphilic Mg2+ – releasing nanoparticles of PMC16 type. This is the first report ever on mathematical model applied to predict and to prove a mere phenomenon of the “cellular pump” keeping the constant traffic of PMC16 particles towards a brain hypoxia area even when/if lowest concentration of pharmacophore were the case. For experimental verifications of the In Silico platform proposed, a combination of (a) the rat brain occlusion – promoted ischemic stroke model and (b) the capillary zone electrophoretic (CZE) quantification of PMC16-RX nanoparticles in cytosol fractions isolated from intact / penumbra / stroke brain areas, has been employed.
A novel inflammatory indicator in extensive ulcerative colitis; Endocan?
Authors: Albayrak Bulent , Sebin Engin
Published: October 2022

Background and study aim

Ulcerative colitis (UC) is an inflammatory bowel disease characterized by mucosal inflammation that starts from the rectum (distal) and extends proximally, involving the entire colon (pancolitis). In this study, we aimed to evaluate the usability of endocan level in determining the extent and severity of disease in patients with ulcerative colitis and to determine whether it can be a candidate marker for noninvasive evaluation and monitoring since there is not enough data in the literature.

Materials and Methods

Sixty-five people were included in the study, including thirty-five with ulcerative colitis and thirty in the control group. patients with newly diagnosed ulcerative colitis clinically, endoscopically, and histopathologically, without any treatment, and with normal liver and kidney tests were included in the study. Endoscopic scoring of all patients was performed according to the mayo endoscopic scoring (MES) system. Blood samples for CRP (C-reactive protein) and endocan were taken from the patients simultaneously.

Results

There was a significant statistical difference between all patients with ulcerative colitis and the control group in both endocan level and CRP level (p < 0.001). There was a statistically significant difference between endocan levels and CRP levels between the left-distal group and pancolitis (diffuse colitis) patients, but there was no statistical difference between age and MES.

Conclusion

Serum endocan level can be a useful test in determining the extent and severity of ulcerative colitis, making hospitalization decisions, and planning treatment. Stool markers may not always be available due to patient compliance.
Unsteady Incidence and the Correction of Pneumatic Probe Measurements
Authors: Coull John , Ng Henry , Dickens Tony , Serna José
Published: October 2022

Pneumatic probes such as five-hole probes (5HP) have many advantages and can measure flow angles, total and static pressure, velocity and Mach number. In most applications, pressure transducers are connected to the probe head by lengths of tubes, allowing a simple, miniaturised, low-cost probe construction. Such “steady” probes therefore measure a “pneumatically-averaged” flow field, which is of sufficient accuracy for many purposes. However, this paper demonstrates that when the probe incidence angle fluctuates, pneumatic averaging causes errors in the indicated total and static pressure. The aim of this paper is to understand these pneumatic averaging errors and to demonstrate practical means to post-correct data. A quasi-steady model provides an analytical framework to explain the effect of unsteady flow on 5HPs. Total and static pressure coefficients have a largely symmetric response to positive and negative incidence, causing a bias error in the pneumatic average. The steady calibration cannot account for these effects, leading to erroneous measurements. These errors are demonstrated by comparing 5HP and Kiel-shrouded pitot traverses in the shedding wake of a D-shaped body. The 5HP overestimates total pressure loss and drag coefficients by up to 44% and 60% respectively. Similar pneumatic-averaging errors will have affected a substantial body of data in the literature. A post-correction method is demonstrated that can be applied to historical data. Estimates of unsteady flow angles are obtained from a low-cost unsteady computation. The quasi-steady model accurately corrects the 5HP data, reducing errors by an order of magnitude. Similar corrections are obtained using simple correlations based on the root-mean-squared angle fluctuation.
Synthesis of graphene oxide for boron removal: equilibrium, kinetic and thermodynamic studies
Authors: Onen Mehmet Fatih , Aydin Nalan Erdol , Eksik Osman , Demircivi Pelin , Saygili Gulhayat Nasun
Published: October 2022

Graphene oxide is one of the promising carbonous materials, which has such a great application in industry. Modified Hummers method was applied to synthesize graphene oxide. Characterization technics showed that pure graphene oxide was successfully obtained. Its adsorptive properties were investigated by boron adsorption. The results were demonstrated that boron adsorption on graphene oxide was a pH dependent process and maximum adsorption was achieved at pH 6 (0.98 mg g− 1). Langmuir adsorption capacity was calculated as 3.92 mg g− 1. The kinetic data brought to light that pseudo-second-order kinetic model was well described the experimental data.
Biological 12-hour rhythm facilitates re-entrainment from circadian desynchrony and promotes psychological resilience during long-duration spaceflight
Authors: Otsuka Kuniaki , Cornelissen Germaine , Furukawa Satoshi , Kubo Yutaka , Shibata Koichi , Mizuno Koh , Aiba Tatsuya , Ohshima Hiroshi , Mukai Chiaki
Published: October 2022

Heart rate variability (HRV) reflects brain’s ‘vertical integration’ in association with functions of the default mode network (DMN) and salience network (SN). We investigate the role of 12-h components in HRV endpoints in facilitating adaptation to the space environment. Ambulatory 24-h electrocardiograms were obtained from 20 healthy astronauts (47.2 ± 5.9 years) before launch, twice in space (ISS01 on days 21.7 ± 2.9 and ISS02 on days 159.2 ± 46.1), and after return to Earth. Astronauts were classified depending on whether the 12-h amplitude of the TF-component of HRV during ISS01 versus pre-flight increased (Group I, N = 11) or not (Group II, N = 9). In Group I, the circadian acrophases of TF- and ULF-components were delayed during ISS01 versus pre-launch, whereas in Group II, the circadian acrophase of the MF1-band advanced. Lower HRV spectral power indicated psychological resilience during both ISS01 and ISS02 in association with the brain’s DMN and SN. Since adverse consequences of circadian desynchrony may be more pronounced due to phase advances than to phase delays, the differential behavior of the 12-h component between Groups I and II suggests its amenability to manipulation in interventions aimed at improving space adaptation.
Sustaining the quality of Hypertension Control Initiative: Study of primary health intervention in Kerala
Authors: R Anju , Kannan Srinivasan
Published: October 2022

Background
Non-communicable diseases programmes need to use social science for improving the quality and safety during implementation. Emphasising only the epidemiological parameters undermine the quality of healthcare provision. Implementation research at the health care delivery level of the India Hypertension Control Initiative was studied and the strategies and best practices were documented.
Methods
Cross sectional survey conducted among 295 Healthcare Providers from different strata in 42 public health institutions of Thrissur district, Kerala. Using Donabedian quality of care model, structure and process indicators were studied. The personnel include, medical officers, nursing officers, dieticians, pharmacists, junior health staffs, and field level works at different levels of primary care were observed.
Results
There were inadequacies in human and material resources. Lack of recommended skills, inadequacy in training (66%) were directly associated with the quality of services delivered. Opportunistic screening (26%), defaulter retrieval (55%), and organized referral system were inadequate. Task sharing and monitoring were followed in all the institutions. While better patient care was widely recognized as strength, interrupted drug supply was a limitation. The initiative added more workload for the health workers.
Conclusion
The assessment made based on the structural and process indicators, there found to be newer process features added to the system without increasing structural factors such as manpower hindered the quality of services provided. The inherent inadequacies in health system further deteriorated the quality.
Collective behavior of soft self-propelled disks with rotational inertia
Authors: De Karmakar Soumen , Chugh Anshika , Ganesh Rajaraman
Published: October 2022

We investigate collective properties of a large system of soft self-propelled inertial disks with active Langevin dynamics simulation in two dimensions. Rotational inertia of the disks is found to favor motility induced phase separation (MIPS), due to increased effective persistence of the disks. The MIPS phase diagram in the parameter space of rotational inertia and disk softness is reported over a range of values of translation inertia and self-propulsion strength of the disks. Our analytical prediction of the phase boundary between the homogeneous (no-MIPS) and MIPS state in the limit of small and large rotational inertia is found to agree with the numerical data over a large range of translational inertia. Shape of the high density MIPSphase is found to change from circular to rectangular one as the system moves away from the phase boundary. Structural and dynamical properties of the system, measured by several physical quantities, are found to be invariant in the central region of the high density MIPS phase, whereas they are found to vary gradually near the peripheral region of the high density phase.Importantly, the width of the peripheral region near the phase boundary is much larger compared to the narrow peripheral region far away from the phase boundary. Rich dynamics of the disks inside the high density MIPS phase is addressed. Spatial correlation of velocity of the disks is found to increase with rotational inertia and disk hardness. However, temporal correlation of the disks’ velocity is found to be a function of rotational inertia, while it is independent of disk softness.
A physical analysis of summertime North American heatwaves
Authors: Yu Bin , Lin Hai , Mo Ruping , Li Guilong
Published: October 2022

This study examines the dominant heatwave variability over North America (NA), extracted from an empirical orthogonal function (EOF) analysis of summertime monthly warm extreme index anomalies over 1959–2021. The principal mode features a dipole structure with a large area of anomaly over northwestern NA and an anomaly of opposite sign over the southern U.S. The corresponding principal component is associated with a large-scale atmospheric wave train extending from the North Pacific to North America (NP-NA) and a northeastward injection of moisture from the subtropical western Pacific towards western NA, which are key factors in supporting the NA heatwave variability. The NP-NA wave train can be systematically reinforced and supported by synoptic-scale eddies, and may also be forced by an anomalous convection over the tropical-subtropical western Pacific. Surface radiation heating directly contributes to surface temperature anomalies and is dominated by anomalous downwelling shortwave and longwave radiations. In association with a positive phase of the heatwave variability, the NP-NA wave train brings an anticyclonic anomaly over northern NA, leading to anomalous descent, reduced total cloud cover and below-normal precipitation over northern NA. Over northwestern NA, the anomalous subsidence causes air to warm through compression. Reduced cloud cover results in increased downward shortwave radiation that is a key contributor to surface radiation heating. In addition, increase in vertically integrated water vapour through the moisture injection from the North Pacific collocates with tropospheric warming. The atmosphere has more water vapor holding capability and acts as a greenhouse gas to absorb longwave radiation, leading to increased downward longwave radiation that is the second major contributor to surface radiation heating. Processes with circulation and surface radiation anomalies of opposite signs will likewise lead to the negative heatwave variability.
Correlations between proBDNF/p75NTR and inflammatory markers in patients with major depression
Authors: Yang Chun-Rui , Liang Rui , Meng Fan-Jie , Zhou Fiona , Zhang Xiao-Yang , Ning Li , Liu Yuan , Wang Zhi-Qiang , Liu Shuang , Zhou Xin-Fu
Published: October 2022

Major depressive disorder (MDD) is a serious mental disorder with unclear pathogenesis. ProBDNF is a precursor protein of brain derived neurotrophic factor (BDNF) expressed in the central nervous system and peripheral tissues. Previous studies showed that blood proBDNF levels in MDD were increased. However, the relationship between proBDNF/p75NTR and inflammatory cytokines in peripheral blood of MDD is unknown. The current study examined the expression of proBDNF and inflammatory markers in patients with major depression. Peripheral blood mononuclear cells (PBMCs) and serum were obtained from depressive patients (n = 32) and normal donors (n = 20). We examined the mRNA and protein expression of proBDNF/p75NTR/sortilin signaling pathway, as well as tumor necrosis factor α (TNF-α), interleukin-1β (IL-1β), interleukin-6 (IL-6), interleukin-10 (IL-10) in human PBMCs. The Enzyme-Linked Immunosorbent Assay (ELISA) levels of these factors in the sera were also examined. Furthermore, the correlations between each factor and severity of major depression were tested. Of biomarkers studies, we found that proBDNF, p75NTR and sortilin production were significantly increased in PBMCs from MDD patients compared with that from the normal donors. The upregulation of p75NTR in PBMCs was most obvious as determined by qPRC and Western blots. Interestingly, the expression of proBDNF/p75NTR/sortilin signaling pathway in PBMC could be reversed after therapeutic management. Inflammatory cytokines in PBMC from MDD patients were also increased. Consistently, ELISA showed that the levels of p75NTR, sortilin, IL-1β and IL-10 in the serum of major depression were also increased compared with normal donors, and positively correlated with the major depression scores. The levels of IL-1β and IL-10 were also positively correlated with the major depression scores. Intriguingly, the levels of sortilin was positively correlated with IL-1β. Further flow cytometry studies showed that the number of proBDNF and p75NTR positive CD4+, CD8+ T cells and CD19+ B cells from MDD patients was increased and subsequently reversed after therapeutic management. The findings suggest that the upregulation of proBDNF/p75NTR/sortilin signaling pathway may relate to inflammatory markers in patients with major depression. Our data also suggest that proBDNF/p75NTR/sortilin signaling pathway may serve as biomarkers for MDD.
Genetic manifestations and phenotype spectrum of feeding difficulty of unknown etiology: a hospital-based cohort study
Authors: Han Mingyu , Shi Wei , Yuan Tianming , Wu Dingwen , Sun Yi , Wang Weiyan , Zhan Canyang , Hu Lingling
Published: October 2022

Background
Feeding difficulties of unknown etiology are often combined with multiple system disorders caused by rare genetic diseases that are difficult to diagnose only based on clinical manifestations. In this study, we aimed to investigate the genetic causes of feeding difficulty of unknown etiology.
Methods
Patients during 2018-10 to 2022-5 diagnosed with feeding difficulty at our institution were enrolled in this cohort study. WES was performed for patients included with feeding difficulty of unknown etiology. Clinical phenotype and genetic results of those infants were analyzed.
Results
Of a total of 28 infants included in this study, 12(42.9%) cases were complicated with multiple malformations. 25(89.3%) patients had positive findings in WES, 14(50%) patients were genetically diagnosed and 8(28.6%) patients were suspected diagnosed.
Conclusions
Feeding difficulty might be part of the phenotype spectrum of rare genetic diseases. We recommend WES for patients with feeding difficulty of unknown etiology.
2060: Civilization, Energy, and Progression of Mankind on the Kardashev Scale
Authors: Zhang Antong , Yang Jiani , Luo Yangcheng , Fan Siteng
Published: October 2022

Energy has been propelling the development of human civilization for millennia. Humanity presently stands at Type 0.7276 on the Kardashev Scale, which was proposed to quantify the relationship between energy consumption and the development of civilizations. Projecting the future energy consumption and estimating the change of its composition are critical in the context of civilization development. Here machine learning models, random forest (RF) and autoregressive integrated moving average (ARIMA), are used to simulate and predict energy consumption on a global scale and project the position of humanity on the Kardashev Scale in 2060. The result suggests that global energy consumption is expected to reach 928-940 EJ in 2060, and our civilization is expected to achieve Type 0.7474 on the Kardashev Scale. Additionally, the potential energy segmentation changes before 2060 and present the influence of the advent of nuclear fusion in this context are discussed.
Treatment Persistence in Patients with Schizophrenia Treated with Lurasidone in Italian Clinical Practice
Authors: Fagiolini Andrea , Olivola Miriam , Lavatelli Lisa , Bellomo Antonello , Lobaccaro Caterina , Falsetto Nathalie , Micillo Marco , Cuomo Alessandro
Published: October 2022

Background and rationale
Treatment persistence combines clinician and patient judgment of efficacy, tolerability and safety into a comprehensive measure of effectiveness. Studies have reported poor treatment persistence to antipsychotic medications in patients with schizophrenia. This study evaluated treatment persistence to lurasidone (LUR) in patients with schizophrenia in a real-world Italian setting.
Methods
This was a retrospective observational study of patients with schizophrenia who started treatment with LUR ≥6 months before inclusion. Following informed consent, data were collected starting from the index date (start of LUR treatment) at all visits occurring as per clinical practice. The primary endpoint was treatment persistence during the first 6 months, defined as the time between index date and all-cause discontinuation. Patients treated with LUR ˃180 days were considered persistent. As secondary endpoint, treatment persistence was evaluated for a period of ≥18 months.
Results
Forty-five patients were enrolled and 41 (91.11%) completed the study. Forty-one patients (91.11%) were included in the eligible population as they initiated LUR treatment ≥6 months before data collection.
Patients were 43.0±15.89 years old and 61% were female. Twenty-two patients (53.66%) started LUR treatment in a hospital setting and 19 (46.34%) in an outpatient setting. Based on Clinical Global Impression – Severity scale (CGI-S) at LUR initiation, 12 patients (29.27%) were severely ill, 17.07% markedly ill, 19.51% moderately ill, 2.44% mildly ill and 4.88% borderline mentally ill.
Thirty-two patients (78.05%) were treatment persistent for ≥180 days. Among the 19 patients observed for ≥18 months, 11 (57.89%) were persistent for ≥18 months. Among the 22 study patients observed for ˂18 months, 12 (54.5%) were persistent. An improvement in schizophrenia severity according to CGI-S was observed at inclusion (following LUR therapy) compared to the index date. Six patients (14.63%) experienced at least one adverse drug reaction: akathisia (7.32%), extrapyramidal disorder (4.88%), hyperprolactinemia (2.44%), restlessness (2.44%), and galactorrhea (2.44%). None were serious.
Conclusions
Persistence to LUR in patients with schizophrenia was relatively high: 78% and 58% of patients were still on LUR after 6 and 18 months of treatment respectively. This may reflect LUR’s relatively favorable balance between efficacy and tolerability, as well as favorable patient satisfaction and acceptance.
Antibiotic use in township hospitals during the COVID-19 pandemic in Shandong, China
Authors: Wang Ting , Shen Liyan , Yin Jia , Zhou Liansheng , Sun Qiang
Published: October 2022

Background
The overuse of antibiotics in primary healthcare settings (PHSs) has caused a serious public health problem in China. The Coronavirus Disease-19 (COVID-19) pandemic outbreak has brought about dramatic changes in the supply of and demand for medical services in PHSs, possibly resulting in unprecedented changes in antibiotic use.
Objective
This study aims to assess the immediate and long-term impacts of the COVID-19 pandemic on the changes in antibiotic consumption in PHSs.
Method
From January 2019 to December 2021, the data on antibiotic consumption were collected from selected township hospitals in Shandong, China. Antibiotic consumption was quantified by using the defined daily doses (DDDs) and the WHO Access, Watch, Reserve category. A Segmented regression model was established to analyze the immediate and long-term impacts of the COVID-19 pandemic on antibiotic use by using the interrupted time series analysis.
Results
The total antibiotic consumption on all PHSs decreased from 170.36 (DDDs in ten thousand) in 2019 to 128.86 (DDDs in ten thousand) in 2020/2021 with a 24.36% reduction under the COVID-19 pandemic. Over the entire study period, the use of penicillins (J01C) and cephalosporins (J01D) accounted for more than 50% of total antibiotic consumption. The average annual consumption of Watch category antibiotics in 2020/2021 down by 37.74% compared to that in 2019. According to the interrupted time series analysis, the total antibiotic consumption decreased significantly immediately after the COVID-19 pandemic outbreak (coef. =-2.712, p = 0.045) and then increased significantly month-over-month in the long-term (coef. =0.205, p = 0.005). Additionally, the consumption of Access category antibiotics increased significantly in PHSs in the log-term (coef. =0.136, p = 0.018), while the consumption of Watch category antibiotics declined sharply immediately (coef. =-1.222, p < 0.001) after the pandemic but increased slightly over the long-term (coef. =0.073, p = 0.001).
Conclusion
The extensive use of penicillin and cephalosporins should be of great concern. After the outbreak of COVID-19 pandemic, the total antibiotic consumption decreased generally and the use pattern was improved to some extent in the PHSs in Shandong, China. This provides an opportunity to improve the abuse of antibiotic in PHSs in China.
The prognostic value of gene alterations in colon cancer patients: An analysis of the cBioPortal database
Authors: Alqrache Abdulraof , Hull Jonathon
Published: October 2022

Background: Colorectal cancer is the third most common cancer worldwide, with colon cancer representing 66.7% of cases. Treatment consists of surgical resection and chemotherapy; however, this is less effective at the later stages of the disease. Gene targeted therapies represent a promising treatment option and, where available, show a significant improvement in overall patient survival. The present study investigated the genetic alteration occurring in colon cancer and used this to produce a predictive model for patient overall survival.
Methods: The data was obtained from the cBioPortal database (cbioportal.org) and was used to analyse genetic alteration in 1272 colon cancer patients. Kaplan-Meyer analysis was used to evaluate the effect of specific gene alteration and patient information on overall survival.
Results: Genetic alteration to either APC, PTPRT, SRC, and TP53 were associated with improved patient overall survival compared to wild-type. Conversely, alteration to BRAF, CSMD1, FBXW7, MACROD2, RBFOX1, SYNE1, TTN, and WWOX were associated with worse overall survival. Patient data indicated that BMI, sex, TMB, and stage at diagnosis had no significant effect in this population, whilst an age greater than 60 years and right sided cancer was associated with a worse overall survival irrespective of genetic alteration. These factors were used to produce a predictive model for colon cancer overall survival.
Conclusions: This study provides a partially predictive model for clinical research to estimate overall survival in colon cancer patients. Understanding the precise clinical significance of tumour genetics will result in a more tailored approach to the treatment of the disease.
Phytoalexin deficient 4 is associated with the lesion mimic trait in watermelon clalm mutant
Authors: Zhu Lili , Shi Jiale , Yang Congji , Liu Xueyan , Dong Wei
Published: October 2022

In watermelon (Citrullus lanatus), lesion mimic is a rare, valuable trait that can be used by breeders for selection at early growth stages. In this study, we tested a seven-generation family to determine the inheritance and genetic basis of this trait. As revealed by analysis of the lesion mimic mutant clalm, this trait is controlled by a single dominant gene. Whole genome resequencing–bulked segregant analysis demonstrated that this gene is located on chromosome 4 from 3,760,000 bp to 7,440,000 bp, a region corresponding to a physical distance of 3.68 Mb encompassing approximately 72 annotated genes. There are 6 genes with non synonymous mutation SNP sites. The predicted target gene, ClCG04G001930, encodes a Phytoalexin deficient 4 (PAD4), a protein that plays an important regulatory role in leaf senescence in many plant species. According to quantitative real-time PCR analysis, the expression level of ClCG04G001930 was significantly higher in the clalm mutant than in normal watermelon. Twelve-five SNPs were identified in the ClCG04G001930 gene of F2 individuals of the clalm mutant. The leaf SA content of clalm mutant was higher than that of normal leaf. Our results suggest that ClPAD4 might be the candidate gene responsible for lesion mimic in the clalm mutant. Our findings may serve as a foundation for elucidating the mechanism underlying the molecular metabolism of programmed cell death and should be useful for marker-assisted selection breeding in watermelon.
PreCLN: Pretrained-based Contrastive Learning Network for Vehicle Trajectory Prediction
Authors: Yan Bingqi , Zhao Geng , Song Lexue , Yu Yanwei , Dong Junyu
Published: October 2022

Trajectory prediction of vehicles is of great importance to various smart city applications ranging from transportation scheduling, vehicle navigation, to location-based advertisements. Existing methods all focus on modeling spatiotemporal relations with explicit contextual semantics from labeled trajectory data, and rarely consider the effective use of large amounts of available unlabeled trajectory data with the assistance of contrastive learning and pre-training techniques. To this end, we develop a novel Pretrained-based Contrastive Learning Network (PreCLN) for vehicle trajectory prediction. Specifically, we propose a dual-view trajectory contrastive learning framework to achieve self-supervised pre-training. A Transformer-based trajectory encoder is designed to effectively capture the long-term spatiotemporal dependencies in trajectories to embed input trajectories into fixed-length representation vectors. Moreover, three auxiliary pre-training tasks, i.e, trajectory imputation, trajectory destination prediction, and trajectory-user linking, are used to assist the training of PreCLN with the dual-view trajectory contrastive learning framework. After pre-training, the result trajectory encoder is used to generate trajectory representations for future trajectory prediction. Extensive experiments on two real-world large-scale trajectory datasets demonstrate the significant superiority of PreCLN against state-of-the-art trajectory prediction baselines in terms of all evaluation metrics.
Overview of Digital Agriculture Technologies in Indonesia: Policies, Implementation, and Covid-19 Relation
Authors: Mangurai Silvia Uthari Nuzaverra Mayang , Octaviani Eti Artiningsih , Anidah Anidah , Solikhin Achmad , Darmawan Refianto Damai , Wulandari Lora Septrianda , Kurniawan Tegar
Published: October 2022

This study was purposed to overview on general application of Indonesia’s digital agriculture technology policies, implementation, and its relation to the Covid-19 pandemic. This study was undertaken through a systematic evidence evaluation complemented with an interactive map and thematic map of digital agriculture application. This study reported that the Government of Indonesia (GoI) has issued national initiatives and policies that support the implementation of digital techologies in food and agriculture sectors. However, a very limited number of both initiatives and policy has mainstreamed the Covid-19 pandemic. An interactive map of digital agriculture companies can be found at this link:https://agriculture40companies.gis.co.id/, and most of the companies are in form of farmers advisory, mechanization platforms, digital marketplace, e-commerce, traceability, food delivery, and peer-to-peer lending. These applications are mostly concentrated in Java island, and and have benefited digital technologies, such as IoT, blockchain, artifical intelligence, smart phone or android, mobile apps, GPS/GIS, and drone. Start-up companies have applied strategic measures to cope with the pandemic implications and some activities of the companies are suspended.
Optimized Feature Extraction and Cross-Lingual Text Reuse Detection using Ensemble Machine Learning Models
Authors: Maqbool Muhammad Sajid , Hanif Israr , Iqbal Sajid , Basit Abdul , Shabbir Aiman
Published: October 2022

With the availability of digital data in different languages, cross-lingual plagiarism (CLP) detection has gained more importance. CLP is difficult to detect because suspicious and source texts can be written in different languages and processing of digitized text in different languages presents varying types of challenges. In this work, we propose a cross-lingual plagiarism detection method using machine learning algorithms. In this work, we have created an ensemble of machine learning algorithms and to evaluate the designed methodology, a corpus focusing Urdu-English language pair titled CLPD-UE-19 (Israr Haneef et al. 2019) is used. The corpus is a collection of 2398 documents where the source text is written in Urdu language and the suspicious text is presented in the English language. Using NLP methods, optimal features are extracted and fed to designed ensemble method for document classification. A number of aggregating techniques are employed which include majority voting, stacking, averaging, boosting, and bagging. Among these models, the stacking has performed the best achieving accuracy of 96 percent.
Covid-19 Vaccine Recommendation Opinions of Nursing/midwifery Students to Women of Reproductive Age
Authors: VAYISOGLU SUMBULE KOKSOY , BESEN MELTEM AYDIN , ONCU EMİNE
Published: October 2022

Nursing and midwifery students are an important resource in increasing COVID-19 vaccine acceptance among women of reproductive age. In this study, it was aimed to determine the thoughts of midwifery and nursing senior students to recommend COVID-19 vaccine to women of reproductive age and related factors. The data of the cross-sectional study were collected from 504 midwifery and nursing senior students across Türkiye between March 15th - April 30th, 2022, using the "Individual Identification Form", "Vaccine Opinion Form" and "Scale of Attitudes towards COVID-19 Vaccine" in the online environment with snowball sampling method. Data were evaluated with t test, chi-square analysis, correlation analysis, ANOVA, logistic regression, and decision tree analysis. Of the students, 84.3% were women, 50.2% were in the nursing department, and 97.6% had at least two doses of COVID-19 vaccine. While 44.4% of the students stated that they would not recommend vaccination to any of the women that pregnant, breastfeeding and planning to pregnancy, 22.6% reported that they could recommend the COVID-19 vaccine to all three groups. Students who thought they could be counselled on vaccines and had received a previous flu shot were more likely to recommend a COVID-19 vaccine, while students who did not find vaccines safe and believed they could be harmful and did not receive adequate training on vaccines were less likely to recommend vaccines. Counselling self-efficacy of students was affected by education and up-to-date information. It is recommended to develop knowledge and counselling skills so that nursing and midwifery students can recommend COVID-19 vaccine to women of reproductive age.
Mental wellbeing and Health-Risk behaviors of University students in Brunei: A cross-sectional study during COVID-19
Authors: Rahman Hanif Abdul , Julaini Nurul Nazurah , Zaim Siti Nurzaimah Nazhirah , Masri Nurfatin Amalina , Abdul-Mumin Khadizah H.
Published: October 2022

Introduction: The coronavirus disease 2019 (COVID-19) has detrimental effects on mental wellbeing and has altered health behaviors of university students. However, little is known about the impact on university students in South-East Asia, particularly in Brunei.
Aim: To estimate the prevalence and factors related to poor mental wellbeing and engaging in health-risk behaviors among university students in Brunei during the COVID-19 pandemic.
Methods: A cross-sectional online survey of students in all public universities. Warwick-Edinburgh Mental Well-being Scale, Global Physical Activity Questionnaire, and WHO STEPs questionnaires were used to measure mental wellbeing, physical activity, and health behaviors, respectively. Logistic regressions were applied.
Results: 1020 university students participated in this study (57% response rate). Prevalence of poor mental wellbeing and physical inactivity were 30% and 42.8%, respectively. Excessive snacking (89.7%), sugar intake (81.7%), and salt intake (53.8%) were the most prevalent health-risk behaviors. Body mass index and participate in sports activities were the most common factors related to mental wellbeing and health-risk behaviors.
Conclusions: Participating in certain sports activities appear to have protective effects against study outcomes. However, high prevalence of physical inactivity and unhealthy diet among university students is a concern as it could be indicative of future non-communicable disease trend.
Development and validation of machine learning based models for predicting distant metastasis in colorectal cancer: a population-level study
Authors: Li Shuofeng , Yu Guanhua , Wei Ran , Wang Xishan , Jiang Zheng
Published: October 2022

Background
Distant metastasis (DM) is an important prognostic factor and determines the following treatments in patients with colorectal cancer (CRC). The purpose of this study was to construct prediction models for DM in patients with CRC based on machine learning.
Methods
CRC patients between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were identified. Prediction models for DM were developed by applying four machine-learning methods including eXtreme Gradient Boost (XGB), decision tree (DT), random forest (RF), and support vector machine (SVM). The performance of models was quantitatively assessed by receiver operating characteristics (ROC) curve, calibration curve and decision curve analysis (DCA) curve. The SHapley Additive exPlanation (SHAP) method was used for visualization analysis to better explain the results of the machine learning models.
Results
A total of 51788 patients were identified in the SEER database. ROC curves exhibited excellent accuracy of machine learning models. Calibration curves for the probability of DM showed good agreement between model prediction and actual observation in both the training and validation cohorts. The DCA demonstrated that each machine learning model can provide net benefits with treat-none and treat-all strategies. In the SHAP summary plot of the RF and XGB models, carcinoembryonic antigen (CEA), N stage, T stage and tumor deposits were identified as the most important risk factors for DM.
Conclusion
The XGB and RF were ideal machine learning models and showed that CEA, N stage, T stage and tumor deposits were the most important DM-related risk factors.
Pyrometallurgy and Electrometallurgy of Rare Earths – Part B: Cell design, construction, rate processes, and unit operation
Authors: Rafique Muhammad Musaddique Ali , Rafique Muhammad Musaddique Ali
Published: October 2022

Production of rare earths by metallothermic reduction and its variants is presented in an earlier study and its analysis is performed indicating major type and sequence of reactions. Diagrams required and procedures to establish them are also described. Their role and importance are also described. A comparison is also made to identify parameters of importance. This study is continuation of a previous study in which cell design to extract metals is described. Parameters to design and construct cell (metallothermic and electrothermic) are determined and used. Rate processes (heat transfer, mass transfer, charge transfer and simultaneous processes) occurring inside a cell, its operation for a specific reaction and sequence for a specific metal (Nd) are described. Outline of calculations outlining cell efficiency, output and yield are enumerated for individual (Nd, Ce, Dy) metal. Optimization and method to achieve is described. Procedures to control and production is also described. Here preliminary graphs are presented.
Irreversibility optimization on chemically reactive in MHD of radiated Powell-Eyring nanofluid flow with Arrhenius activation energy through Peristaltic micro vessel containing Planktonic microorganisms
Authors: Hussein Sameh A. , Arafa Anas A. M. , Almalki Nawal , AL-Essa Lulwah , Elshekhipy Abdelhafeez , Almuaddi Saad , Ghrib Taher , AL-Saleem Nouf , Ibrahim Nehad
Published: October 2022

The amount of energy lost during any irreversible process is called entropy. The focus of this paper is on how to reduce this energy loss in order to improve the capacity of our system, especially in the presence of planktonic microorganisms. To understand the flow physics associated with bolus formation and the impact of reverberation on the micro vessel, a 3D computational fluid dynamic analysis is performed. The effects of binary chemical interaction with nonlinear mixed convection and Arrhenius activation energy are considered in the present analysis. The complexity of the system was achieved through a numerical approach based on the concepts of small Reynolds number and large wavelength. The resulting nonlinear coupled differential equation system is solved numerically using the built-in command in MATHEMATICA (ParametricNDSolve). Some of the investigation's findings are the entropy profile has been improved for incremental values of Hartmann number and Brinkmann number whereas the axial velocity shows a downward trend for the highest values of the Hartmann number and the material parameter "A". The improvement in the flow, heat, and mass transmission properties of hypoxic tumor regions, will provide developing in drug carrier uses in hypoxic carcinoma regions.
Well-posedness and exponential stability of a coupled fluid-thermoelastic plate interaction model with second sound
Authors: Jiang Jian , Liu Wenjun
Published: October 2022

In this paper, we investigate a coupled system modeled by fluid and thermoelastic plate while the heat effects are modeled by the Cattaneo' law giving rise to a ``second sound" effect. By using the semigroup method, we prove the well-posedness of the system. Then, we construct the second order energy to control the term ∥∇θ∥L2(Г0) so as to establish the exponential decay of the solutions by using the modified multipliers method.
2010 Mathematics Subject Classification: 35Q30, 74F05, 74F10.
Deciphering the broadband absorption of eumelanin in solution
Authors: Izgorodina Ekaterina I , Singh Abhishek , Mason Thomas G , Freeman Benny D
Published: October 2022

Melanin, a bio-polymer responsible for visible pigmentation in the human body, works as a protective layer in our skin by absorbing UV radiation and efficiently dissipating it into heat, preventing DNA damage. The primary structure of eumelanin, one of the two main forms of melanin, is presumed to be a co-polymer of 5,6-dihydroxyindole (DHI) and 5,6-dihydroxyindole-2-carboxylic acid (DHICA) monomers, with DHI being the major component. The solution phase investigation into the origin of broadband monotonic absorption spectrum of melanin has been realized through the polymerization of dopamine and L-DOPA, the molecular precursors of DHI and DHICA, respectively, in an ionic liquid (IL). The evolution of the electronic absorption spectrum of polymerized L-DOPA did not mimic the electronic spectrum of eumelanin, which was attributed to their inability to form stable redox states, as elucidated via structural characterization. In contrast, polymerized DA (pDA) mimics the eumelanin absorption spectrum, and the structural characterization of the polymerization process performed with 1H and 13C NMR and DOSY spectroscopy allowed us to identify chromophores responsible for the absorption profile of pDA. Furthermore, the identified chromophores were subjected to quantum chemical calculations, and the predicted absorption spectra not only supported their presence in the experimental UV-Vis spectra but also allowed us to identify their gradual evolution during polymerisation. The knowledge of the chromophores responsible for the optical properties of melanin will undoubtedly result in their increased application in functional materials.