bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reactive Enteric Glial Cells Participate in Paralytic Ileus by Damaging Nitrergic Neurons During Endotoxemia
Authors: Li Na , Xu Jing , Gao Hui , Zhang Yuxin , Li Yansong , Chang Haiqing , Tan Shuwen , Li Shuang , Wang Qiang 
Published: November 2021

Abstract
BackgroundParalytic ileus is common in patients with septic shock, which may cause high morbidity and mortality. Enteric neurons and enteric glial cells (EGCs) participate in the regulation of intestinal motility, but little is known about their role. We aimed to prove whether reactive EGCs have harmful effects on enteric neurons during endotoxemia and lead to intestinal motility disorder in mice. MethodsIn this study, lipopolysaccharide (LPS) was used to induce endotoxemia in mice, and intraperitoneal injections of fluorocitrate (FC) twice per day (9 AM and 6 PM) for 7 days before LPS injections to prevent the activation of EGCs. The effects of reactive EGCs on intestinal motility were analyzed by motility assays in vivo and colonic migrating motor complexes (CMMCs) in vitro. The changes of enteric neurons were evaluated by immunofluorescent staining HuCD, nNOS, CHAT, and TUNEL.ResultsThe expression of glial fibrillary acidic protein (GFAP) was significantly upregulated in LPS-injected animals, indicating EGCs were transformed into a reactive state. The administration of FC could significantly prevent it. Meanwhile, inhibition of reactive EGCs can improve intestinal motility and peristaltic reflex. The density of the general neuronal population (HuC/D-immunoreactive) in the colonic myenteric plexus was significantly increased after suppressing reactive EGCs. The population of nNOS neurons was increased significantly, but there was no significant difference in the number of ChAT neurons. Furthermore, the apoptotic rate of enteric neurons significantly increased, when incubated with the conditional medium of reactive EGCs in vitro. At the same time, the dendritic complexity and the number of primary neuritis neurons were significantly reduced.ConclusionReactive enteric glial cells participated in paralytic ileus by damaging nitrergic neurons during endotoxemia. It may provide a novel therapeutic strategy for intestinal motility disorders during endotoxemia or sepsis.
Chlorhexidine Versus Organoselenium for Inhibition of S.Mutans Biofilm, an Invitro Study
Authors: Seguya Abdul , Mowafy Mohamed , Gaballah Ahmed , Zaher Abbas 
Published: November 2021

Abstract
Background: White Spot Lesions are a common misharp during fixed orthodontic appliance therapy which creates the need for non-compliance based prevention methods. S.mutans is considered the main etiologic factor for caries. This was an in vitro study to compare between the efficacy of chlorohexidine diaceteate varnish, and an organoselenium sealant, to prevent S.mutans biofilm formation on human teeth. Methods: Fourty five premolars extracted for orthodontic purposes were randomly divided into 3 groups of 15 teeth each. One control group and two test groups, chlorohexidine diaceteate varnish and an organoselenium sealant. The teeth were autoclaved before S. mutans biofilm was induced on to each in their respective groups. The reading T1 was taken for each tooth to assess the number of S.mutans attached in order to compare for differences in surface area among the 3 groups. The respective test materials were applied onto the teeth and biofilm induced onto them in their respective groups. The reading T2 was taken for the 2 test groups .The 3 groups were then subjected to aging for a period equivalent to 5 months before the biofilm was induced to take the reading T3 for the number of S.mutans. We used vortexing of the teeth to disrupt the biofilm at time points T1, T2 and T3. S. mutans count was then done using PCR.Results: There were significantly lower S. mutans counts in the control group as compared to the chlorhexidine diacetate group at T3.There were no other statistically significant differences found.Conclusion. Both organoselenium and Chlorhexidine diacetate do not inhibit S.mutans biofilm attachment onto the teeth.
Resilience of Resprouting Temperate Forests is Diminished by Coupled Severe Drought and Fire
Authors: Bendall Eli Ryan , Bedward Michael , Boer Matthias , Clarke Hamish , Collins Luke , Leigh Andrea , Bradstock Ross A. 
Published: November 2021

Abstract
Elevated tree mortality and reduced recruitment of new trees linked to drought and fires has been reported across a range of forests over the last few decades. Forests that resprout new foliage epicormically from buds beneath the bark are considered highly resilient to disturbance, but are potentially at risk of elevated mortality, demographic shifts and changes to species composition due to synergistic effects of drought and fire. Despite this, the effects of drought-fire interactions on such forests remain largely unknown. We assessed the effects of drought severity and fire frequency on juvenile mortality, post-fire seedling recruitment and replacement of juvenile trees (balance of recruitment minus mortality) following fire. We compared dry ridgetop and wet gully assemblages across a temperate forest in southern Australia. Both forest types experienced higher rates of fire-induced juvenile mortality in areas that had experienced severe drought compared to moderate drought, though mortality rates were generally low across all drought and fire combinations. This result indicated that topographic position (i.e. wet gullies) did little to moderate juvenile mortality when exposed to severe drought plus fire. In wet forest, severe drought also reduced recruitment and replacement of dead juveniles by post-fire seedlings compared to moderate drought. In dry forest net-negative replacement increased with the severity of drought. Across both forest types, the total pool of juveniles was reduced under severe drought. Future increases in the frequency of coupled severe drought and fire will likely increase the susceptibility of resilient temperate forests to major changes in structure and function.
Poka Yoke Meets Deep Learning: a Proof of Concept for an Assembly Line Application
Authors: Martinelli Matteo , Gamberini Rita , Lippi Marco 
Published: November 2021

Abstract
In this paper we present the re-engineering process of an assembly line that features speed reducers and multipliers for agricultural applications. The product operates as an interface between an input torque, typically supplied by an agricultural vehicle, and an output torque, generally moving specific equipment placed on a trolley equipped with a tow hook. The "as-is'' (initial version) line was highly inefficient due to several critical issues, including the high age of the machines, a non-optimal arrangement of them in the shop floor, and the absence of controls and process standards. These critical issues were analysed with the tools offered by Lean Manufacturing, which made it possible to identify irregularities and operations that require effort (Mura), overload (Muri), and waste (Muda). The definition of the "to-be'' (new version) assembly line included actions to update the department layout, to modify the assembly process and to design the line feeding system in compliance with the well-known concepts of Golden Zone and Strike Zone. The whole process addressed, in particular, the problem of the incorrect assembly of the oil seals. The registered error was mainly caused by the difficulty in visually identifying the correct side of the assembled oil seal, and by the mental fatigue of operators at the end of the shift. The solution studied in this paper resulted in a Poka-Yoke solution, which, leveraging the modern technologies and methods of deep learning and computer vision, monitors the process flow of the operators through a camera, preventing its completion in the event of an assembly error.
Economic Impact of COVID-19 on the Vulnerable Population of Bangladesh
Authors: Mahmud Sakib , Zubayer Sayed Arafat , Eshtiak Ahmed , Ahmed Ibrahim , Nasim Mahmudul Hossain 
Published: November 2021

Abstract
This study aims to find out the Economic condition of the vulnerable population of Bangladesh in the COVID-19 situation. This study uses the primary data of 203 respondents who were collected from all around Bangladesh using convenience and purposive sampling during the first wave of the COVID-19 pandemic. In this study, a comparison of expected income in the COVID-19 situation is made with the pre-COVID-19 situation using Welch two-sample t-test, and the possible impact on Expenditure and Savings is discovered using OLS estimation. Descriptive analysis is also included considering the key economic variable of the respondents. This study finds a significant drop in income due to the COVID-19 pandemic and infers that it will cause both drop-in expenditure and monthly savings. Moreover, this study gives an overall idea of the situation of vulnerable people in the COVID-19 situation. This paper intends to help the stakeholders and policymakers to understand the situation of the vulnerable population of Bangladesh during the COVID-19 pandemic.
The K Nearest Neighbor Algorithm for Imputation of Missing Longitudinal Prenatal Alcohol Data
Authors: Sania Ayesha , Pini Nicolo , Nelson Morgan , Myers Michael , Shuffrey Lauren , Lucchini Maristella , Elliott Amy J. , Odendaal Hein J. , Fifer William 
Published: November 2021

Abstract
Background — Missing data are a source of bias in epidemiologic studies. This is problematic in alcohol research where data missingness is linked to drinking behavior. Methods — The Safe Passage study was a prospective investigation of prenatal drinking and fetal/infant outcomes (n=11,083). Daily alcohol consumption for last reported drinking day and 30 days prior was recorded using Timeline Followback method. Of 3.2 million person-days, data were missing for 0.36 million. We imputed missing data using a machine learning algorithm; “K Nearest Neighbor” (K-NN). K-NN imputes missing values for a participant using data of participants closest to it. Imputed values were weighted for the distances from nearest neighbors and matched for day of week. Validation was done on randomly deleted data for 5-15 consecutive days. Results — Data from 5 nearest neighbors and segments of 55 days provided imputed values with least imputation error. After deleting data segments from with no missing days first trimester, there was no difference between actual and predicted values for 64% of deleted segments. For 31% of the segments, imputed data were within +/-1 drink/day of the actual. Conclusions — K-NN can be used to impute missing data in longitudinal studies of alcohol use during pregnancy with high accuracy.
On the order of the non-primes of type 6n+5 and 6n+1
Authors: Wolmersdorfer Christoph 
Published: November 2021

Abstract
The fundamental importance of prime numbers for mathematics is that all other natural numbers can be represented as a unique product of prime numbers[1]. For centuries, mathematicians have been trying to find an order in the occurrence of prime numbers. Since Riemann´s paper on the number of primes under a given size, the distribution of the primes is assumed to be random[2]. Here, I show that prime numbers are not randomly distributed. Their positions are determined by the order of occurrence of the nonprimes of types 6n+5 and 6n+1. By using parametric sine functions, I will show here that all assumptions known today regarding the distribution of prime numbers larger than 3 are wrong. In particular, this refutes Riemann´s hypothesis of random distribution of prime numbers. Furthermore, I will show an exact primality test based on these parametric sine functions, which only uses one parameter.
Image Quality of Abdominal Ultrasonography After Esophagogastroduodenoscopy is Preserved by Using Carbon Dioxide Insufflation
Authors: Suda Tsuyoshi , Shirota Yukihiro , Takimoto Hiroaki , Tsukada Yasunori , Takishita Kensaku , Nadamura Takahiro , Miyazawa Masaki , Hodo Yuji , Wakabayashi Tokio 
Published: November 2021

Abstract
Because bowel gas deteriorates the image quality of abdominal ultrasonography (AUS), it is common to perform AUS prior to esophagogastroduodenoscopy (EGD). This one-way order limits the availability of examination appointments. To evaluate whether EGD using insufflation of carbon dioxide (CO2), which is rapidly absorbed by the gastrointestinal mucosa, preserves the image quality of AUS performed subsequently, we designed a non-inferiority test in which each subject underwent AUS, EGD with CO2 insufflation, and a second AUS. All saved AUS moving images were randomized and evaluated using a four-point Likert scale that divides the depiction rate by 25%. Sample size was calculated to be 26 and 30 subjects were enrolled. The mean and 95% confidence interval (CI) of the image quality score at pre- and post-EGD AUS were 3.54 [3.48–3.60] and 3.46 [3.39–3.52], respectively. The difference in the means was 0.08, corresponding to a 2% depiction rate. The effect size was 0.172. The image quality of post-EGD AUS was not inferior, as demonstrated by the 97.5% CI of the difference, which did not cross the non-inferiority margin of –0.40 corresponding to depiction rate of –10%. Because EGD using CO2 insufflation does not appreciably deteriorate the image quality of AUS performed subsequently, it is permissible to perform EGD prior to AUS.
Relationship Between Summer Extreme Precipitation Anomaly in Central Asia and Surface Sensible Heat Variation on the Central-Eastern Tibetan Plateau
Authors: wang hui , Zhang Jie , Chen Lian , Li Dongliang 
Published: November 2021

Abstract
In the context of global warming, the frequency and intensity of extreme weather and climate events have increased, especially in Central Asia (CA). In this study, we investigate the characteristics of Summer Extreme Precipitation (SEP) in CA and its relationship with the Surface Sensible Heat (SSH) variation over the Central-Eastern Tibetan Plateau (CETP). Our results suggest that the distribution of SEP in CA is extremely uneven, and the SEP threshold ranges from 2 to 32 mm, 80% of them are concentrated in the range of 4–10mm. Both the total amount of SEP and the number of SEP days show significant increasing trends, with the climatic tendencies of 4.4 mm/decade and 0.4 day/decade, respectively. The SSH anomalies over the CETP can affect the SEP and the summer drought in CA by regulating the strength of the SAH and the subtropical jet over CA. The strong SSH anomalies over the CETP in late spring (April-May) can lead to the anomalously strong SAH in summer, anomalously weak subtropical westerly jet over CA and anomalously strong subtropical high over north Africa and the Arabian Peninsula. In addition, the Ural ridge strengthens, the CA trough weakens, and the northern CA is controlled by an abnormal warm high-pressure ridge with less anomalous water vapor convergence. Therefore, the SEP in northern CA will be abnormally less and the summer drought intensifies. Whereas, when the SSH over the CETP is anomalously weak in late spring, the key circulation characteristics are quite the opposite, at the same time, the anomalous water vapor from the Arctic, North Atlantic and western Pacific converges in northern CA and northern Xinjiang, China, which are conducive to the generation of widespread extreme precipitation and alleviates the summer drought in these regions.
Uncertainty Analysis of WDN Pipes Repair and Replacement Optimal Instruction Using EPANET Simulation Model and Fuzzy Cut Approach Combination
Authors: Jafari Seyed Mehran , Zahiri Abdol Reza , Hadad Omid Bozorg , Tabari Mahmoud Mohammad Rezapour 
Published: November 2021

Abstract
Optimization of the initial design or pipes repair and replacement instructions of water distribution network during operation period is based on the crisp values of the input variables. Some input variables such as node demand, pipe roughness coefficient and reservoir water level have the uncertain nature. Changing the input parameters values during operation period, due to uncertainty, changes the water distribution network behavior and performance compared to the crisp input parameters values. Recognition and analyzing these behaviors are very important to make the right decision to deal with their consequences and reduce the water distribution network problems, during operation period. In this research, the water distribution network nodes pressure uncertainty due to the pipe's roughness coefficient and the nodes demand uncertainty as input parameters, is analyzed after the implementation of the optimal pipes repair and replacement instruction. For the purpose, a combination of simulation model (EPANET) and fuzzy α-cut approach is used. Fuzzy membership functions of the input and output variables are selected as triangular type and the membership functions values, after normalization, were in the range of zero and one. The extreme values combinations of two uncertain input variables, at each uncertainty level, in the form of four scenarios, were considered as the input fuzzy set of the simulation model. Between the research scenarios, the second scenario, which is the combination of the minimum pipe roughness coefficient and the maximum demand, is known as the critical scenario. The research results show that in the critical scenario, at the highest uncertainty level, the water distribution network reliability index is very low and about 30 to 40% due to lack of required pressure of the most nodes. At the uncertainty lower levels, the reliability index rises above 75%, which is relatively acceptable. In the first and fourth scenarios, the network reliability index is always more than 72%. In the third scenario, the network reliability index, at all uncertainty levels, is always more than 90%.
After Strict Comparison, the Conclusion of the Double-Slit Test Conflicts with the Mathematical Model
Authors: Ruhuai Xia 
Published: November 2021

Abstract
Light waves, which have almost no physical properties, are an abstract mathematical concept rather than an objective description. Confused by a set of dark and bright stripes and a sketchy schematic with little relation to the actual result, the double-slit phenomenon was misjudged as being caused by interfering light waves, but this plausible principle implies disastrous flaws. For example, (1) immediately after light passes through the double-slit device, the pattern is generated early or before interference. By changing the device-screen distance, the pattern only scales synchronously without being reconstructed by interference. The pattern with more interference points is darker, but it should be brighter. (2) Light waves can not only be subdivided into many parts but also greatly proliferate. (3) Light waves with missing leading edges outside the screen can still induce much interference. (4) Reflected light waves do not interfere. (5) The effect of polarization direction on interference should not be ignored. (6) Compared with the mathematical model, the location where the dark stripe should appear is actually the brightest spot. The formation principle of multiple regular dark stripes cannot be found. (7) To reflect the quantum property in the interference process, unless all conditions are simultaneously met, interference will not be triggered, and therefore, the principle of interference will be rejected. (8) A light source cannot be produced in a slit that may be in vacuum. (9) In the causality test, to verify the effect of collapse, the photons that have collapsed into particles should be tested again with a double-slit test. (10) The phenomenon of "observed tampering results" is obtained by observation. Has it been tampered with by observation? (11) If light is a wave, then matter and antimatter are conjoined. In conclusion, Newton's particle model is wrong, as is light wave theory.
Usefulness of Grayscale Values of Hypoechoic Lesions Matched with Target Lesions Observed on Magnetic Resonance Imaging for the Prediction of Clinically Significant Prostate Cancer
Authors: Kim Dong Gyun , Yoo Jeong Woo , Koo Kyo Chul , Chung Byung Ha , Lee Kwang Suk 
Published: November 2021

Abstract
Background: To analyze grayscale values for hypoechoic lesions matched with target lesions evaluated using prebiopsy magnetic resonance imaging (MRI) according to the Prostate Imaging-Reporting and Data System (PI-RADS).Methods: We collected data on 420 target lesions in patients who underwent MRI/transrectal ultrasound fusion-targeted biopsies between January 2017 and September 2020. Images of hypoechoic lesions that matched the target lesions on MRI were stored in a picture archiving and communication system, and their grayscale values were estimated using the red/green/blue scoring method through an embedded function. We analyzed imaging data using grayscale values.Results: Of the 420 lesions, 261 (62.1%) were prostate cancer lesions. There was no difference in the median grayscale values between benign and prostate cancer lesions. However, grayscale ranges (41.8–98.5 and 42.6–91.8) were significant predictors of prostate cancer and clinically significant prostate cancer (csPC) in multivariable logistic regression analyses. Area under the curve for detecting csPC using grayscale values along with conventional variables (age, prostate-specific antigen levels, prostate volume, previous prostate biopsy results, and PI-RADS scores) was 0.839, which was significantly higher than that for detecting csPC using only conventional variables (0.828; p=0.036). Subgroup analysis revealed a significant difference for PI-RADS 3 lesions between grayscale values for benign and cancerous lesions (74.5 vs. 58.8, p=0.008). Grayscale values were the only significant predictive factor (odds ratio=4.46, p=0.005) for csPC.Conclusions: Distribution of grayscale values according to PI-RAD 3 scores was useful, and the grayscale range (42.6–91.8) was an important factor for csPC diagnosis.
Evaluating The Performance of Several Data Preprocessing Methods Based On GRU in Forecasting Monthly Runoff Time Series
Authors: Wang Wenchuan , Du Yu-jin , Chau Kwok-wing , Cheng Chun-Tian , Xu Dong-mei , Zhuang Wen-Tao 
Published: November 2021

Abstract
The optimal planning and management of modern water resources depends highly on reliable and accurate runoff forecasting. Data preprocessing technology can provide new possibilities for improving the accuracy of runoff forecasting, when basic physical relationships cannot be captured using a single prediction model. Yet, few researches evaluated the performances of various data preprocessing technology in predicting monthly runoff time series so far. In order to fill this research gap, this paper investigates the potential of five data preprocessing techniques based on gated recurrent unit network (GRU) model in monthly runoff prediction, namely variational mode decomposition (VMD), wavelet packet decomposition (WPD), complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), extreme-point symmetric mode decomposition (ESMD), and singular spectrum analysis (SSA). In this study, the original monthly runoff data is first decomposed into a set of subcomponents using five data preprocessing methods; second, each component is predicted by developing an appropriate GRU model; finally, the forecasting results of different two-stage hybrid models are obtained by aggregating of forecast results of the corresponding subcomponents. Four performance metrics are employed as the evaluation benchmarks. The experimental results from two hydropower stations in China show that five data preprocessing techniques can attain satisfying prediction results, while VMD and WPD methods can yield better performance than CEEMDAN, ESMD and SSA in both training and testing periods in terms of four indexes. Indeed, it is significantly important to carefully determine an appropriate data preprocessing method according to the actual characteristics of the study area.