bluuebunny/crossref_metadata_2025 huggingface dataset:
Pathological oligodendrocyte precursor cells revealed in human schizophrenic brains and trigger schizophrenia-like behaviors and synaptic defects in genetic animal model
Authors: Niu Jian-Qin , Yu Guangdan , Su Yixun , Guo Chen , Yi Chenju , Yu Bin , Chen Hui , Cui Yihui , Wang Xiaorui , Wang Yuxin , Chen Xiaoying , Wang Shouyu , Wang Qi , Chen Xianjun , Hu Xuelian , Mei Feng , Verkhratsky Alexej , Xiao Lan
Published: March 2022

Although the link of white matter to pathophysiology of schizophrenia is documented, loss of myelin is not detected in patients at the early stages of the disease, suggesting that pathological evolution of schizophrenia may occur before significant myelin loss. Disrupted-in-schizophrenia-1 (DISC1) protein is highly expressed in oligodendrocyte precursor cells (OPCs) and regulates their maturation. Recently, DISC1-Δ3, a major DISC1 variant that lacks exon 3, has been identified in schizophrenia patients, although its pathological significance remains unknown. In this study, we detected in schizophrenia patients a previously unidentified pathological phenotype of OPCs exhibiting excessive branching. We replicated this phenotype by generating a mouse strain expressing DISC1-Δ3 gene in OPCs. We further demonstrated that pathological OPCs, rather than myelin defects, drive the onset of schizophrenic phenotype by hyperactivating OPCs’ Wnt/β-catenin pathway, which consequently upregulates Wnt Inhibitory Factor 1 (Wif1) leading to the aberrant synaptic formation and neuronal activity. Suppressing Wif1 in OPCs rescues synaptic loss and behavioral disorders in DISC1-Δ3 mice. Our findings reveal the pathogenetic role of OPC-specific DISC1-Δ3 variant in the onset of schizophrenia and highlight the therapeutic potential of Wif1 as an alternative target for the treatment of this disease.
Combined wind profile characteristics based on wind parameters joint probability model in a mountainous gorge
Authors: Zhang Mingjin , Zhang Jinxiang , Jiang Fanying , Wu Lianhuo , Qin Jingxi , Li Yongle
Published: March 2022

Long-span bridges in mountainous areas are greatly disturbed by wind, and the wind field in the mountain gorge bridge site is extremely complex. Therefore, it is of great engineering significance to accurately evaluate the wind field characteristics of this kind of terrain. In this paper, to enhance understanding of this kind of wind field, the wind field in a mountainous gorge is measured for a long time using wind radar, and the mean wind parameters is statistically analyzed. The results show that the mean wind parameters vary greatly under different wind directions, and the wind speed profile does not meet the power-law model. Therefore, a mixed model suitable for the wind speed profile in a mountainous gorge is proposed. Additionally, GEV distribution and Logistic distribution are found to be suitable for describing the distribution characteristics of wind speed and angle of attack, respectively. In addition, considering the correlation between wind parameters, this paper also constructs the joint probability model of wind speed and angle of attack at different heights by the Copula function. Thus, a combined wind parameters profile model is developed under different exceedance probabilities based on the inverse first-order reliability method (IFORM). This study can provide a reference for the construction of the joint probability model of wind parameters.
The Role of Assistant Psychologists within Inpatient Units: A Clinical Audit
Authors: Wilkinson Jade , Chin Rachel
Published: March 2022

Objectives: Current guidelines for the employment of Assistant Psychologists (APs) and Honorary APs (HAPs) are unclear and lack contextual considerations. This leaves standards open to interpretation, and thus places psychology graduates in a vulnerable position risking exploitation. In anticipation of the release of new guidelines, this audit aimed to evaluate the role of the APs within inpatient units against the current standards. Methods: All APs within a specialist mental health rehabilitation service in the North-West of England (n = 5) were invited, and agreed, to participate in the audit.Findings: All standards were found to be unmet, with only a proportion of APs receiving the support stipulated and working within the parameters of their pay band. Conclusion: This audit highlighted the need for context-specific considerations in the new guidance and recommendations to ensure appropriate support is in place. A re-audit is suggested upon publication of new standards and the national implications of this audit are discussed.
X-linked recessive ichthyosis in 8 Tunisian patients: awareness of misdiagnosis due to the technical trap of the STS pseudogene
Authors: CHOUK Hamza , SAAD Sarra , DIMASSI Sarra , FETOUI Nadia GHARIANI , BENNOUR Ayda , GAMMOUDI Rima , ELMABROUK Haifa , SAAD Ali , DENGUEZLI Mohamed , H’MIDA Dorra
Published: March 2022

Introduction: X-linked recessive ichthyosis (XLI) is a genodermatosis, caused by a deficiency of the steroid sulphatase enzyme encoded by the STS gene (OMIM # 300747). Adopted XLI molecular diagnosis approaches differ from one laboratory to another depending on available technical facilities. Our work aims to figure out a sound diagnostic strategy for XLI.Patients and Methods: We collected 8 patients with XLI, all males, from 3 unrelated Tunisian families from central Tunisia. Genetic diagnosis was conducted through a large panel of genetic techniques including: Sanger Sequencing, haplotype analysis of STR markers, MLPA analysis, FISH and array CGH.Results: Direct Sanger sequencing of the STS gene showed the same deletion of 13 base pairs within the exon 4 in all patients resulting in a premature stop codon. However, all patients’ mothers were not carriers of this variant and no common haplotype flanking STS gene was shared between affected patients. Sequence alignment with reference human genome revealed an unprocessed pseudogene of the STS gene located on the Y chromosome, on which the 13 bp deletion was actually located. STS MLPA analysis identified a deletion of the entire STS gene on X chromosome for all affected patients. This deletion was confirmed by FISH and delineated by array CGH.Conclusion: All our patients shared a deletion of the entire STS gene revealed by MLPA, confirmed by FISH and delineated by array CGH. Geneticists must be aware of the presence of pseudogenes that can lead to XLI misdiagnosis.
Using the esophageal cancer stem cells (CSCs) for better understanding the tumor metastasis and metastasis-associated genes
Authors: Kokabi Fariba , Khosravi Ayyoob , Jazi Marie Saghaeian , Asadi Jahanbakhsh
Published: March 2022

Background: Understanding the metastasis and host–tumor cell interactions is needed for effective targeted therapy of metastasis. The aim of this study was to develop mouse model to mimic the late steps of the metastasis process using tail-vein injection of esophageal CSCs. Also, the expression of human metastasis-associated genes (SLUG, E-cad, and CTHRC1) were evaluated in primary tumors. Material and Methods: The sphere formation assay was used to enrich CSCs from YM-1 cell line. For analysis of tumorigenicity, Adherent cells and enriched CSCs were injected into the nude mice. The expression of SLUG, E-cad, and CTHRC1 genes was examined by Real-Time qRT-PCR and immunohistochemistry (IHC) methods. Also, these cancer cells were injected into the tail vein of nude mice to investigate the metastatic potential of enriched CSCs and their adherent YM-1 cells. To verify metastasis, IHC staining for human p63 and p40 proteins were performed. Results: Our findings showed the up-regulation of SLUG and down-regulation of E-cad in the esophageal CSC-derived tumors (ECSCTs) compared to adherent cells-derived tumors. There was no statistically significant difference between CTHRC1 gene expressions in both groups of tumors. IHC staining confirmed the higher expression of SLUG protein in ECSCTs compared to adherent cell-derived tumors. Enriched CSCs were able to metastasize to the lungs and livers, but, metastasis of adherent cells wasn't observed. Conclusion: Our study suggests esophageal CSCs can migrate and metastasize to the lung and liver and this mouse model can provide a useful and relevant model for studying the metastasis in human esophageal cancer. Also, our findings showed the up-regulation of SLUG in the ECSCTs compared to esophageal adherent cells-derived tumors.
Bacillus thuringiensis pesticidal toxins: A global analysis based on scientometric study (1980 – 2021)
Authors: Karim Abdul Aziz , Idris Abeer Babiker , YILMAZ Semih
Published: March 2022

Background: Several studies have been conducted on Bacillus thuringiensis (Bt) pesticidal toxins due to their successful environmentally friendly biopesticide activity against various insect pest orders, protozoa, mites, and nematodes. However, no existing study has systematically examined the trends and evolution of research on Bt pesticidal toxins from a scientometric perspective. This study aimed to analyze the trends and hotspots of global research in this field.Methodology: 5757 publications on Bt pesticidal toxins were extracted from the Web of Science Core Collection (WoS) from 1980 to 2021. Statistical and scientometric analyses were performed using Excel, CiteSpace and VOSviewer visualisation tools to evaluate the contributions of different countries, institutions, highly influential references, and most used keywords.Results: Out of the 5757 publications, the USA contributed the most, with 1562 publications, 72,754 citations, and 46.58 average citations per paper (ACPP); however, Belgium had the highest (106.43) ACPP among the top 20 contributing countries. The Chinese Academy of Agricultural Sciences is the leading institution with 298 publications and 21.20 ACPP. The Pasteur Institute is ranked first (90.04) in terms of ACPP. Keywords analyses revealed that recent studies are inclined towards the evolution of insect resistance against Bt toxins.Conclusion: In future, studies related to the development of resistance mechanisms by insects against Bt pesticidal toxins and ways to overcome them will likely receive more attention.
Keystone Genes from Extracellular DNA Facilitate Microbial Adaptation in Organochlorine Pesticide-Contaminated Soil
Authors: Zhang Zhongyun , Shi Yu , Adams Jonathan M. , Shu Wensheng , Ye Mao , Yu Pingfeng , Jiang Xin
Published: March 2022

Background: Keystone genes exert great influence on maintaining microbiome stability and functional recovery irrespective of their environmental abundance. Elucidating the effects of environmental stresses on their variation is vital for identifying the recovery potential of ecosystems and regulating microbial adaptation within. Extracellular and intracellular gene transfer under pesticide-induced selection is convenient for studying keystone genes shifts and their role in ecosystem recovery potential. Results: Metagenomic analysis revealed that increased stress induced by organochlorine pesticides (OCPs) decreased soil bacterial diversity, and enriched abundance of functional genes associated with metabolism and gene transfer potential, both in extracellular and intracellular DNA. Increased OCP concentrations also significantly enhanced intercellular gene associations, which facilitated the abundance of keystone genes associated with metabolic functions by a factor of 2.14 times. Keystone genes devoted their niche specificity in microbiome co-occurrence networks, enhancing microbial survival under OCP stress where they had been taken up and incorporated by intercellular transfer. This was verified by culturing on media containing OCP (e.g., p-nitrochlorobenzene). Furthermore, in a 100-day field observation of ten different OCP-contaminated sites, China, keystone genes genes ssuD, livH, yfcG, coxA and gst, showed significant variations in abundance in response to the recovery of OCP-induced ecosystems and their intercellular transfer was promoted by 0~1.50 orders of magnitude. Conclusion: Under OCP-induced stress, the microbial community composition, community structure and certain transferable keystone genes all participate in the adaptive response to the environmental stresses. The observed gene transfers within the extracellular and intracellular DNA fractions emphasize the pivotal influence of keystone genes in maintaining ecosystem stability and resilience.
Nonlinear ultrasonic inspection of the effect of contaminants on material properties of epoxy-adhesive
Authors: Pyun Do-Kyung , Koester Lucas W. , Barnard Daniel J. , Bond Leonard J.
Published: March 2022

Adhesive joints have been an effective alternative to conventional mechanical fasteners for joining materials in the aerospace and automotive industries. Although adhesive joints have various advantages, including uniform stress distribution, lower weight, improved corrosion tolerance, and design flexibility, there can be various defects in adhesive joints, which have limited wider application. This paper investigates the effect of a contaminant on the chemical and mechanical properties of the epoxy-adhesive and seeks to determine if a SHG method can reliably detect and characterize the degree of contamination in the epoxy-adhesive. A contract based ultrasonic through-transmission method was used to measure nonlinearity and then the nonlinearity parameter was calculated using the measured fundamental and second harmonic frequency components in the signals. It was found that there is higher sensitivity to contaminant concentration, up to 1.5%, of the nonlinearity parameter than that for the sound velocity. These data were also found to correlate with changes in the mechanical hardness, which was measured by the Rockwell hardness testing, with different four levels of contamination. Differential scanning calorimetry (DSC) and the thermogravimetric analysis (TGA) were also conducted to assess the effect of the contaminant on thermal properties of the epoxy-adhesive. The DSC and TGA techniques were used to evaluate the curing reaction and the thermal stability of the epoxy-adhesive respectively.
Predict lncRNA-disease associations based on graphlet interaction
Authors: Li Nian , Guan Nana , Qu Jia
Published: March 2022

The study of the lncRNA-diseases association is a prevalent project. Researchers have developed many effective computational models to assist experimental research. In this paper, we proposed a computational model (GILDA) to predict the potential lncRNA-disease associations based on graphlet interaction. This model established lncRNA similarity graph and disease similarity graph. Based on the graphlet interaction, we calculated the numbers of graphlet interaction isomers in the similarity graphs respectively, which were then taken as features to train the model, and obtained the predicted lncRNA-disease association scores. Compared with the previous calculation models, GILDA fully considers the direct and indirect relationship between two nodes through the graphlet interaction. The AUC value of GILDA in global LOOCV is 0.8844, in local LOOCV is 0.8468, and in fivefold cross-validation is \(0.8742\pm 0.0057\). At the same time, we made case studies of hepatecellular carcinoma, renal cancer and adenocarcinoma. The results proved that among the first 10 lncRNAs predicted for the three diseases, the prediction accuracy was 100%, 100% and 80%, respectively.
Theoretical proposal of a revolutionary water-splitting photocatalyst: The monolayer of boron phosphide
Authors: Suzuki Tatsuo
Published: March 2022

Recently, hydrogen generation by water-splitting photocatalysts is attracting attention as a sustainable and clean energy resource. Photocatalytic hydrogen-generation systems are much simpler, cheaper, and easier to scale up than the coupled systems of electrolysis and solar cells, wind-power generation, etc. However, photocatalytic hydrogen generation is currently inefficient. This paper proposes the monolayer of boron phosphide as a stable highly-efficient water-splitting photocatalyst by high-precision density-functional theory calculations using a HSE06 functional with a solvent effect. The monolayer of boron phosphide has a direct allowed energy gap of about 1.4 eV, and functions as a one-step excitation photocatalyst. It absorbs sunlight with wavelengths below about 890 nm (ultraviolet, visible, and near-infrared light) and produces both hydrogen gas and oxygen gas from water at a suitable pH condition. By calculating the overpotentials of hydrogen and oxygen evolution reactions, its photocatalytic effectiveness was confirmed. The monolayers of boron phosphide will realize green hydrogen revolution.
Serum C reactive protein predicts humoral response after BNT162b2 booster administration
Authors: Salvagno Gian Luca , Henry Brandon M. , Pighi Laura , De Nitto Simone , Lippi Giuseppe
Published: March 2022

Background: We explored here the impact that baseline inflammation on post-vaccine anti-SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) antibodies response after BNT162b2 vaccine booster administration.Materials and Methods: The population consisted of 78 healthcare workers of Pederzoli Hospital in Peschiera del Garda (Italy), who received a booster dose of BNT162b2 vaccine 8 months after completing homologous primary vaccination cycle. Serum levels of anti-SARS-CoV-2 spike trimeric IgG were measured pre- and post-booster, whilst serum C reactive protein (CRP) was measured on pre-booster samples.Results: BNT162b2 vaccine booster increased anti-SARS-CoV-2 spike trimeric IgG by nearly 40-fold (median increase, 38-fold; IQR, 20-78 folds). A highly significant correlation was found between pre-booster serum CRP concentration and post-booster anti-SARS-COV-2 spike trimeric RBD IgG antibodies variation (r= 0.36; 95%CI, 0.15-0.54; p=0.001). The median post-booster increase of anti-SARS-COV-2 spike trimeric RBD IgG antibodies was significantly higher in patients with serum CRP >3 mg/L compared to those with serum CRP <3 mg/L (54 vs. 37 folds; p=0.025).Conclusions: Evidence emerged from this study suggest that baseline CRP values could be used as valuable information for personalizing COVID-19 vaccines booster administration.
Comparison of estimated late toxicities between IMPT and IMRT based on multivariable NTCP models for high-risk prostate cancers treated with pelvic nodal radiation
Authors: Chilukuri Srinivas , Sundar Sham , Patro Kartikeswar , Sawant Mayur , Sivaraman Rangasamy , Arjunan Manikandan , Panda Pankaj Kumar , Sharma Dayananda S , Jalali Rakesh
Published: March 2022

PurposeTo compare the late gastrointestinal (GI) and genitourinary toxicities (GU) estimated using multivariable NTCP models, between pencil beam scanning proton bream therapy (PBT) and helical tomotherapy (HT) in patients of high-risk prostate cancers requiring pelvic nodal irradiation (PNI) using moderately hypo-fractionated regimen.Materials and MethodsTwelve consecutive patients treated with PBT at our centre were replanned with HT using the same planning goals. Six late GI and GU toxicity domains (stool frequency, rectal bleeding, fecal incontinence, dysuria, urinary incontinence and hematuria) were estimated based on the published multivariable NTCP models. ΔNTCP (difference in absolute NTCP between HT and PBT plans) for each of the toxicity domains was calculated. One-Sample Kolmogorov-Smirnov test was used to analyze distribution of data and either a Paired T-test or a Wilcoxon matched-pair signed rank test was used to test statistical significance. ResultsPBT and HT plans achieved adequate target coverage. PBT plans led to significantly better sparing of bladder, rectum and bowel bag especially in the intermediate range of 15-40Gy; whereas doses to penile bulb and femoral heads were higher with PBT plans. The average ΔNTCP for grade(G)2-rectal bleeding, fecal incontinence, stool frequency, dysuria, urinary incontinence and G1-hematuria were 12.17%, 1.67%, 2%, 5.83%, 2.42% and 3.91% respectively favoring PBT plans. The average cumulative ΔNTCP for GI and GU toxicities (ΣΔNTCP) was 16.58% and 11.41% respectively favoring PBT. Using a model-based selection threshold of any G2 ΔNTCP >10%, 67% (8 patients) would be eligible for PBT.ConclusionPBT plans led to superior OAR sparing compared to HT which translated to lower NTCP for late moderate GI and GU toxicities in patients of prostate cancer treated with PNI. For two-thirds of our patients, the difference in estimated absolute NTCP values between PBT and HT, crossed the accepted threshold for minimal clinically important difference.
Big Data for Specific Emotion Detection Model: Any Position and Representative Emotion Hashtag Approach
Authors: Sanghyub John Lee , Lim JongYoon , Paas Leo , Ahn Ho Seok
Published: March 2022

Background/ introduction: We propose the large emotion-labelled dataset consisted of tweets labelling representative emotions hashtags posted over 12 years to train a specific emotion detection model. The dataset is available at https://github.com/ EmotionDetection/6H-AP_emotion_labelled_tweets. Prediction of human emotion has been and remains a major challenge in many research fields such as psychology, neuroscience, and computer science. Tweets are considered as a suitable source for collecting big data using emotion hashtags as reliable emotion annotations. However, little is known about data collection criteria on how to apply emotion hashtags (i.e., type and position of emotion hashtags). Methods: To elucidate unclear criteria, this paper collected over five million tweets that were divided into six datasets. Five traditional ML algorithms trained on six different datasets were evaluated on both internal test sets (30 analyses) of six datasets and external test set (30 analyses). Results: We propose the emotion labelled dataset ( n =1,478,116; any position of representative emotions hashtags) that achieved the highest F1 score. Furthermore, this paper compared the model trained on the proposed dataset with the model trained on a small dataset. We find that this large dataset further improved the model performance in deep learning (18 analyses) than in traditional ML algorithms (30 analyses). Conclusions: Finally, we share the proposed dataset with other researchers to contribute to future specific emotion detection model studies, provide reliable baseline results for this data set.
Gardens of Tolerance: Ukrainian Women Artists Reflect the War in the Donbas
Authors: Martynyuk Olena
Published: March 2022

With ongoing war in the Donbas, war narratives and war images saturate public media in Ukraine, the discourse contaminated by ideological remnants of the Soviet World War II cult and by fake news. Art that deals with war wounds can subvert the familiar visual language of war propaganda, where the suffering of victims is a mere pretext for touting the inevitable triumph of the heroes. Currently in Ukraine, the most prolific art in this regard is produced by women-artists who address the trauma of war through painting and installations that offer highly personalized accounts. Often touching upon extreme circumstances, their art is about tolerance, both in terms of endurance and of the mutual understanding necessary for cohabitation. Alevtyna (Alevtina) Kakhidze’s ongoing performance creates an opportunity to comprehend the war in the Donbas from multiple perspectives, including that of a gardener. She associates the tending of plants with her mother who died on occupied territory, refusing to leave her garden. Mariia (Maria) Kulikovs'ka’s sculptures serve as shooting targets for separatists in the occupied centre of contemporary art in Donetsk. Vlada Ralko’s paintings of tortured bodies become a metaphor for scars garnered by a war that remains close to home. Paintings and sculptures by Maryna Skuharieva (Skugareva) and Anna Zviahintseva (Zvyagintseva) address the ruin of representation inflicted by war, and the conceptual performance by Liia (Lia) Dostlieva and Andrii Dostliev contemplates the healing process of war wounds. Neither making spectacle from the “pain of others” nor deeming it unrepresentable, this art seeks emphatic alternatives to traditional war narratives.
Development of empirical mode decomposition based neural network for power quality disturbances classification
Authors: Rofii Faqih , Naba Agus , Dharmawan Hari Arief , Hunaini Fachrudin
Published: March 2022

The complexity of the electric power network causes a lot of distortion, such as a decrease in power quality (PQ) in the form of voltage variations, harmonics, and frequency fluctuations. Monitoring the distortion source is important to ensure the availability of clean and quality electric power. Therefore, this study aims to classify power quality using a neural network with empirical mode decomposition-based feature extraction. The proposed method consists of 2 main steps, namely feature extraction, and classification. Empirical Mode Decomposition (EMD) was also applied to categorize the PQ disturbances into several intrinsic mode functions (IMF) components, which were extracted using statistical parameters and the Hilbert transformation. The statistical parameters consist of mean, root mean squared, range, standard deviation, kurtosis, crest factor, energy, and skewness, while the Hilbert transformation consists of instantaneous frequency and amplitude. The feature extraction results from both parameters were combined into a set of PQ disturbances and classified using Multi-Layer Feedforward Neural Networks (MLFNN). Training and testing were carried out on 3 feature datasets, namely statistical parameters, Hilbert transforms, and a combination of both as inputs from 3 different MLFNN architectures. The best results were obtained from the combined feature input on the network architecture with 2 layers of ten neurons, by 98.4 %, 97.75, and 97.4 % for precision, recall, and overall accuracy, respectively. The implemented method is used to classify PQ signals reliably for pure sinusoids, harmonics with sag and swell, as well as flicker with 100 % precision
Developing an algorithm for monitoring gas generators of hydrogen storage and supply systems
Authors: Abramov Yuriy , Basmanov Oleksii , Krivtsova Valentina , Mikhayluk Andrey , Mikhayluk Oleksandra
Published: March 2022

In relation to the main element of the hydrogen storage and supply system based on the hydro-reacting composition – the gas generator – an algorithm for its control has been developed. The development of such an algorithm is carried out in three stages. At the first stage, the problem of formalizing the hydrogen generation process is solved. Formalization of this process is carried out using the transfer function of the gas generator. The use of the criterion for the minimum error of the mismatch of the given amplitude-frequency characteristics of the gas generator allows to represent its transfer function in the form of a transfer function of the inertial link. At the second stage, the problem of determining the conditions for the occurrence of self-oscillations in the pressure stabilization subsystem is solved. A prerequisite for the emergence of a self-oscillating mode of operation of the hydrogen storage and supply system is the presence of a relay static characteristic of the pressure sensor. For the characteristic parameters of such a system, the ranges of values of the parameters of self-oscillations, frequencies and amplitudes, are determined. For these parameters, analytical expressions are obtained, which include the main parameters of the pressure stabilization subsystem in the hydrogen storage and supply system.

At the third stage, the problem of forming a gas generator control algorithm is solved. As a test action in the implementation of the control algorithm, self-oscillations in the pressure stabilization subsystem are used. The control algorithm for the gas generator of the hydrogen storage and supply system includes determining the parameters of self-oscillations and comparing their values with the values obtained a priori.

A typical diagram of a hydrogen storage and supply system is presented, in which the developed gas generator control algorithm is implemented
Implementation of the dynamic balancing approach of a rotating composite hollow shaft
Authors: Al-Falahat Ala’a M.
Published: March 2022

Balancing is essential in rotating machinery, which is widely employed in many technical sectors, particularly in high-speed rotor-bearing systems. The mass balancing method of the hollow shaft manufactured of composite materials is investigated in this study over the whole speed range of the rotor. The main goal of the balancing technique is to generate a smooth-running machine by removing the commonality imbalance mass through the use of compensating mass unbalance. As a result, MATLAB code is created to produce a functioning mathematical model of the rotor-bearing system. The unbalanced rotor-bearing system finite element model is proposed to set the balancing mass of the composite hollow shaft at a selected speed rotor that allows minimizing the vibration response amplitude of the rotor as much as possible with minimal impact on the rest of the imbalance response within the speed range of the interest. As a consequence, this study validates the process for distributing imbalance in modelling balancing to balance the flexible hollow shaft with an unbalanced mass throughout the complete speed range of the shaft. The balance of the hollow shaft at the critical speed was observed in this approach, and the vibration amplitude was determined by adding extra mass at a specific angle
Analysis of semi-Markov systems with fuzzy initial data
Authors: Raskin Lev , Sira Oksana , Sukhomlyn Larysa , Korsun Roman
Published: March 2022

In real operating conditions of complex systems, random changes in their possible states occur in the course of their operation. The traditional approach to describing such systems uses Markov models. However, the real non-deterministic mechanism that controls the duration of the system's stay in each of its possible states predetermines the insufficient adequacy of the models obtained in this case. This circumstance makes it expedient to consider models that are more general than Markov ones. In addition, when choosing such models, one should take into account the fundamental often manifested feature of the statistical material actually used in the processing of an array of observations, their small sample. All this, taken together, makes it relevant to study the possibility of developing less demanding, tolerant models of the behavior of complex systems. A method for the analysis of systems described under conditions of initial data uncertainty by semi-Markov models is proposed. The main approaches to the description of this uncertainty are considered: probabilistic, fuzzy, and bi-fuzzy. A procedure has been developed for determining the membership functions of fuzzy numbers based on the results of real data processing. Next, the following tasks are solved sequentially. First, the vector of stationary state probabilities of the Markov chain embedded in the semi-Markov process is found. Then, a set of expected values for the duration of the system's stay in each state before leaving it is determined, after which the required probability distribution of the system states is calculated. The proposed method has been developed to solve the problem in the case when the parameters of the membership functions of fuzzy initial data cannot be clearly estimated under conditions of a small sample
Enhancement efficiency of Michell-Banki turbine using NACA 6512 modified blade profile via CFD
Authors: Galvis-Holguin Steven , Rio Jorge Sierra-Del , Hincapié-Zuluaga D.
Published: March 2022

The small hydroelectric power plants (SHPP) are implemented in non-interconnected zones (NIZ) of developing countries. In which, the provision of electrical energy from the national interconnected system is not economically feasible. Therefore, in the literature, hydroelectric generation technologies have been implemented taking advantage of the energy available in the rivers. One of these technologies is the Michell-Banki type cross-flow turbines (MBT), which, despite having lower efficiencies than turbines such as Pelton and Francis, maintain their efficiency although fluctuations in site conditions. For this reason, different studies have been made to increase the efficiency of the MBT by making geometric modifications to both the nozzle and the rotor.

The purpose of this study is to determine numerically the effect of the geometry of the blades that form the runner on the efficiency of Michell-Banki Turbine (MBT). For this, two (2) geometries were studied corresponding to a circular sector of a standard tubular profile and an airfoil NACA 6512 modified in curvature profile and chord length, according to the profile of the standard tubular blade. For this study, transient simulations for multiphase water-air flow were implemented using a k-ε turbulence model in the Ansys 2020R1® CFX software. The two (2) turbine models were configured to the same hydraulic conditions of head and volumetric flow corresponding to 0.5 m and 16.27 L/s, respectively. Variations in rotational speed were configured between 100 and 200 RPM with 20 RPM steps. It was found that using the modified 6512 hydrodynamic profile, at 140 RPM increased efficiency by 6 %, compared to the conventional tubular type blade geometry
Gravitational wave induced baryon acoustic oscillations
Authors: Döring Christian , Centelles Chuliá Salvador , Lindner Manfred , Schaefer Bjoern Malte , Bartelmann Matthias
Published: March 2022

We study the impact of gravitational waves originating from a first
order phase transition on structure formation. To do so, we perform a
second order perturbation analysis in the 1+31+3
covariant framework and derive a wave equation in which second order,
adiabatic density perturbations of the photon-baryon fluid are sourced
by the gravitational wave energy density during radiation domination and
on sub-horizon scales. The scale on which such waves affect the energy
density perturbation spectrum is found to be proportional to the horizon
size at the time of the phase transition times its inverse duration.
Consequently, structure of the size of galaxies and bigger can only be
affected in this way by relatively late phase transitions at
\ge 10^{6}\,\text{s}≥106s.
Using cosmic variance as a bound we derive limits on the strength
\alphaα
and the relative duration (\beta/H_*)^{-1}(β/H*)−1
of phase transitions as functions of the time of their occurrence which
results in a new exclusion region for the energy density in
gravitational waves today. We find that the cosmic variance bound
forbids only relative long lasting phase transitions,
e.g. \beta/H_*\lesssim 6.8β/H*≲6.8
for t_*\approx 5\times10^{11}\,\text{s}t*≈5×1011s,
which exhibit a substantial amount of supercooling
\alpha>20α>20
to affect the matter power spectrum.
Macroeconomic policy and profit rate of a company: A dynamic panel estimation and comparative analysis from Indonesia
Authors: Ismanto Hadi , Pebruary Silviana , Nur Maulidiyah Dewi
Published: March 2022

Macroeconomic policy (fiscal and monetary) dynamics are interesting to analyze, especially considering corporate performance. This paper aims to determine the effect of macroeconomic policy on the company’s profit rate. Effectiveness of tax revenue (ETAX), realization of tax revenue (RTAX), Bank of Indonesian rate (BIRT), investment growth (INVG), realization of investments (RINV), infrastructure fund allocation rate (INFR), and realization of infrastructure funds (RINF) are macroeconomic policy variables. This study uses a sample of 256 companies listed on the Indonesia Stock Exchange (IDX) in 2005–2019. This paper employs such methods as GMM, using Wald-test and Sargan’s test. GMM estimator result shows that the instrument of infrastructure fund realization policy (RINF), investment growth (INVG), and investment realization (RINV) affect the company’s profit rate (PROF). Therefore, companies need to pay attention to the government development plans, investment growth, and investment realization, which can improve company performance. The result, government’s development for the 2005–2009 and 2015–2019 periods shows a significant difference in companies’ ability to generate profits.
AcknowledgmentsWe would like to thank the Department of Management, Faculty of Economics and Business, Universitas Islam Nahdlatul Ulama Jepara (Unisnu), and the Institute of Research and Community Services (LPPM) Unisnu Jepara Indonesia, which has supported this study.
Priorización de áreas para la conservación de aves en el occidente de la Faja Volcánica Transmexicana
Authors: Galindo-Cruz Alejandra , Rosas-Espinoza Verónica Carolina , Vásquez-Bolaños Miguel , Sahagún-Sánchez Francisco Javier
Published: March 2022

Para asegurar el mantenimiento de las poblaciones de vida silvestre y sus ecosistemas en México, es necesaria la identificación de regiones clave que resulten prioritarias y representativas para la mayor cantidad de ecosistemas y especies. En el presente estudio se identificaron sitios importantes para llevar a cabo acciones de conservación para las aves en el extremo occidental de la Faja Volcánica Transmexicana. Para tal efecto, se modeló la distribución de especies de aves prioritarias y se determinó la conectividad de las coberturas vegetales donde potencialmente se distribuyen las especies. Los resultados indican tres áreas óptimas, con distintas características ecológicas, determinadas por su nivel de conectividad y número de especies representadas como sitios relevantes de conservación para las aves prioritarias. Se destacan los sitios con coberturas de bosques templados y selvas, en la zona norte y centro sur de la zona de estudio. La información generada será útil para complementar la Red de Áreas Naturales Protegidas que favorezca la conservación de las aves prioritarias y los ecosistemas donde habitan en la zona de estudio.
Experimental investigation of automotive component in hybrid fibre reinforced thermoplastic design
Authors: Maier Andreas , Kroll Lothar
Published: March 2022

A tailored use of continuous fibre reinforced plastics enables application in high volume car body structures. The combination of pultruded, load carrying, unidirectional, continuous fibre reinforced thermoplastic (FRTP) profiles and injection moulds, named “skeleton design”, is a promising approach to meet structural requirements and economical needs. This design offers the advantages of FRTP such as short cycle times of approx. 75 s and functional integration via injection moulding. A pre-serial BMW iX geometry of a windshield panel is used to analyse the impact of different fibre configurations in the profiles on the mechanical properties of the part. Therefore, different pultruded profiles with a cross-section of 10 mm x 10 mm made of polyamide 6 (PA6) with carbon fibres (CF) and glass fibres (GF) as well as a CF/GF hybrid were used. Furthermore, an optimized part using different materials within one part was investigated. Therefore, quasi-static and dynamic compression tests were performed on part level. It could be shown that the optimized parts meet mechanical requirements while decreasing material costs significantly.
The Role of Influential Actors in Fostering the Polarized COVID-19 Vaccine Discourse on Twitter: Mixed Methods of Machine Learning and Inductive Coding
Authors: Hagen Loni , Fox Ashley , O'Leary Heather , Dyson DeAndre , Walker Kimberly , Lengacher Cecile A , Hernandez Raquel
Published: March 2022

Background

Since COVID-19 vaccines became broadly available to the adult population, sharp divergences in uptake have emerged along partisan lines. Researchers have indicated a polarized social media presence contributing to the spread of mis- or disinformation as being responsible for these growing partisan gaps in uptake.

Objective

The major aim of this study was to investigate the role of influential actors in the context of the community structures and discourse related to COVID-19 vaccine conversations on Twitter that emerged prior to the vaccine rollout to the general population and discuss implications for vaccine promotion and policy.

Methods

We collected tweets on COVID-19 between July 1, 2020, and July 31, 2020, a time when attitudes toward the vaccines were forming but before the vaccines were widely available to the public. Using network analysis, we identified different naturally emerging Twitter communities based on their internal information sharing. A PageRank algorithm was used to quantitively measure the level of “influentialness” of Twitter accounts and identifying the “influencers,” followed by coding them into different actor categories. Inductive coding was conducted to describe discourses shared in each of the 7 communities.

Results

Twitter vaccine conversations were highly polarized, with different actors occupying separate “clusters.” The antivaccine cluster was the most densely connected group. Among the 100 most influential actors, medical experts were outnumbered both by partisan actors and by activist vaccine skeptics or conspiracy theorists. Scientists and medical actors were largely absent from the conservative network, and antivaccine sentiment was especially salient among actors on the political right. Conversations related to COVID-19 vaccines were highly polarized along partisan lines, with “trust” in vaccines being manipulated to the political advantage of partisan actors.

Conclusions

These findings are informative for designing improved vaccine information communication strategies to be delivered on social media especially by incorporating influential actors. Although polarization and echo chamber effect are not new in political conversations in social media, it was concerning to observe these in health conversations on COVID-19 vaccines during the vaccine development process.
Shared Access to Patient Portals for Older Adults: Implications for Privacy and Digital Health Equity
Authors: Wolff Jennifer L , Dukhanin Vadim , Burgdorf Julia G , DesRoches Catherine M
Published: March 2022

Growing reliance on the patient portal as a mainstream modality in health system interactions necessitates prioritizing digital health equity through systems-level strategies that acknowledge and support all persons. Older adults with physical, cognitive, sensory, and socioeconomic vulnerabilities often rely on the involvement of family and friends in managing their health, but the role of these care partners in health information technology is largely undefined and poorly understood. This viewpoint article discusses challenges and opportunities of systematic engagement of care partners through shared access to the patient portal that have been amplified in the context of the COVID-19 outbreak and recent implementation of federal information blocking rules to promote information transparency alongside broader shifts toward care delivery innovation and population aging. We describe implementation considerations and the promise of granular, role-based privacy controls in addressing the nuanced and dynamic nature of individual information sharing preferences and fostering person- and family-centered care delivery.
Implementation Outcomes Assessment of a Digital Clinical Support Tool for Intrapartum Care in Rural Kenya: Observational Analysis
Authors: Dinh Nhi , Agarwal Smisha , Avery Lisa , Ponnappan Priya , Chelangat Judith , Amendola Paul , Labrique Alain , Bartlett Linda
Published: March 2022

Background

iDeliver, a digital clinical support system for maternal and neonatal care, was developed to support quality of care improvements in Kenya.

Objective

Taking an implementation research approach, we evaluated the adoption and fidelity of iDeliver over time and assessed the feasibility of its use to provide routine Ministry of Health (MOH) reports.

Methods

We analyzed routinely collected data from iDeliver, which was implemented at the Transmara West Sub-County Hospital from December 2018 to September 2020. To evaluate its adoption, we assessed the proportion of actual facility deliveries that was recorded in iDeliver over time. We evaluated the fidelity of iDeliver use by studying the completeness of data entry by care providers during each stage of the labor and delivery workflow and whether the use reflected iDeliver’s envisioned function. We also examined the data completeness of the maternal and neonatal indicators prioritized by the Kenya MOH.

Results

A total of 1164 deliveries were registered in iDeliver, capturing 45.31% (1164/2569) of the facility’s deliveries over 22 months. This uptake of registration improved significantly over time by 6.7% (SE 2.1) on average in each quarter-year (P=.005), from 9.6% (15/157) in the fourth quarter of 2018 to 64% (235/367) in the third quarter of 2020. Across iDeliver’s workflow, the overall completion rate of all variables improved significantly by 2.9% (SE 0.4) on average in each quarter-year (P<.001), from 22.25% (257/1155) in the fourth quarter of 2018 to 49.21% (8905/18,095) in the third quarter of 2020. Data completion was highest for the discharge-labor summary stage (16,796/23,280, 72.15%) and lowest for the labor signs stage (848/5820, 14.57%). The completion rate of the key MOH indicators also improved significantly by 4.6% (SE 0.5) on average in each quarter-year (P<.001), from 27.1% (69/255) in the fourth quarter of 2018 to 83.75% (3346/3995) in the third quarter of 2020.

Conclusions

iDeliver’s adoption and data completeness improved significantly over time. The assessment of iDeliver’ use fidelity suggested that some features were more easily used because providers had time to enter data; however, there was low use during active childbirth, which is when providers are necessarily engaged with the woman and newborn. These insights on the adoption and fidelity of iDeliver use prompted the team to adapt the application to reflect the users’ culture of use and further improve the implementation of iDeliver.