bluuebunny/crossref_metadata_2025 huggingface dataset:
The impact of COVID-19 lockdown on maternal and neonatal outcomes of uninfected woman in late pregnancy: A multicenter study in China
Authors: Lin Ting-ting , Chen Yang , Wang Hong-lin , Li Chao , Zhang Ting , Fan Li-chun , Huang He-feng , Wu Yan-ting , Wen Yang
Published: September 2022

Background
COVID-19 pandemic has had direct and indirect impacts on health-care system and maternal and neonatal health, but no multicenter evidence from China of this effects has been undertaken. The purpose of this study was to investigate the impacts of COVID-19 lockdown on maternal and fetal outcomes in China.
Methods
This retrospective cohort study included 3540 women in their late pregnancy without COVID-19 who received perinatal healthcare in three hospitals in Wuhan, Shanghai and Haikou during COVID-19 lockdown period in 2020 or the non-lockdown period in 2019. Propensity-score matching was used to compare preterm birth (< 37 weeks) and its classification, very preterm birth (< 34 weeks), caesarean section and its indications, the length of hospital stay, birth weight and other pregnancy outcomes between two groups.
Results
Preterm births before 37 weeks’ gestation (5.4% vs. 5.3%, P = 0.83) and very preterm birth (0.7% vs. 0.8%, P = 0.58) were not significantly changed overall. But medical-induced preterm birth before 37 weeks’ gestation in Wuhan was decreased (0.8% vs. 1.7%, P = 0.04). The cesarean section for maternal factors was decreased (21.4% vs. 24.3%, P = 0.003). The length of maternal (4.2d vs 4.5d, P < 0.001) and neonatal (3.4d vs 3.7d, P < 0.001) hospital stay was shortened. No overall significant effects were identified for other outcomes included in the quantitative analysis: maternal gestational diabetes; pregnancy-induced hypertension; preterm birth with premature rupture of membranes; low birthweight (< 2500 g); neonatal intensive care unit admission; or abnormal Apgar score.
Conclusions
This study demonstrated that there was protective impact of the COVID-19 lockdown on maternal and neonatal outcomes among women in their late pregnancy in China.
Exploring the possible mechanism involved in the anti-nociceptive effect of β-sitosterol: Modulation of oxidative stress, nitric oxide and IL-6
Authors: Kaur Kiranjot , Singh Lovedeep , Kaur Anudeep , Bhatti Rajbir
Published: September 2022

β-sitosterol is a phytosterol, documented to possess various activities including inflammation, diabetes, Alzheimer's disease etc. The current investigation was designed to explore the analgesic potential of β-sitosterol and the possible molecular mechanism involved in the observed effect. β-sitosterol was administered at varying doses of 10, 20, and 40 mg/kg before subjecting the mice to acetic acid and formalin challenges. The number of writhings in acetic acid and the number of flinchings and foot tappings were quantified in the formalin test. For mechanistic studies, substance P (COX-2 stimulator) and L-NAME (NOS inhibitor) and L-arginine (NO precursor) were administered before β-sitosterol treatment. β-sitosterol (10, 20, 40 mg/kg) treatment significantly reduced acetic acid-induced writhings and ameliorated the formalin-induced inflammatory phase dose-dependently. Whereas, 40 mg/kg dose of β-sitosterol abrogated formalin-induced neurogenic phase. Substance-P abrogated the effect of β-sitosterol in both neurogenic and inflammatory phases. Whereas, L-arginine only abrogated the inflammatory phase. In biochemical analysis, β-sitosterol treatment reduced the level of IL-6, TBARS and increased the GSH level. Furthermore, L-arginine and substance-P abrogated the GSH increasing and TBARS lowering effect of β-sitosterol (40 mg/kg). Overall, the current study delineated that β-sitosterol might induce anti-nociceptive effect via inhibiting the IL-6, oxidative stress, cyclo-oxygenase and nitric oxide.
Clinical symptoms and radiologic features of airway abnormalities assessed by impulse oscillometry in patients with chronic obstructive pulmonary disease
Authors: Lu Lifei , peng Jieqi , Wu Fan , Yang Huajing , Zheng Youlan , Deng Zhishan , Zhao Ningning , Dai Cuiqiong , Xiao Shan , Wen Xiang , Xu Jianwu , Wu Xiaohui , Zhou Kunning , Ran Pixin , Zhou Yumin
Published: September 2022

Background: Airway abnormalities assessed by impulse oscillometry (IOS) were common in patients with chronic obstructive pulmonary disease (COPD). However, most studies only used difference from R5 to R20 (R5-R20) > 0.7kPa/L/s to diagnose airway abnormalities, which may ignore the value of other IOS indicators in the diagnosis of airway abnormalities. Our study aimed to comprehensively assess clinical symptoms and radiologic features of airway abnormalities in COPD patients in China.
Methods: We enrolled 805 COPD patients from a part of ECOPD cohort, they underwent questionnaires, symptom scores, lung function, IOS and HRCT. The criteria of airway abnormalities were based on standardized IOS reference values. Logistic regression was used to analyze risk factors of airway abnormalities. The associations between acute exacerbation of COPD (AECOPD) in the previous year and airway abnormalities were assessed by Poisson regression. Logistic regression was used to assess the associations between CT imaging and airway abnormalities.
Results: The proportion of airway abnormalities evaluated by other indicators increased gradually with COPD severity except for R20. Multivariate logistic analysis showed dyspnea, low FEV1% predicted and airway obstruction were associated with risk of airway abnormalities. Compared with normal airway group, airway abnormalities group had more clinical symptoms (wheeze and dyspnea) and higher mMRC and CAT scores. Airway abnormalities assessed by X5 and AX had more emphysema, gas trapping and higher risk of AECOPD in the previous year.
Conclusions: Reactance (X5, AX) assessment of airway abnormalities had more clinical symptoms, emphysema, gas trapping and higher risk of AECOPD in the previous year.
Spatial Proximity of Tumor Infiltrating Immune Cells Uncovers a Novel Insight in Pulmonary Lymphoepithelial Carcinoma
Authors: Hsu Wei-Hsun , Hsu Chia-Chi , Hsieh Min-Shu , Tai Pei-Chen , Huang Derek De-Rui , Lee Jih-Hsiang , Lin Chia-Chi , Chang Yih-Leong , Yang James Chih-Hsin
Published: September 2022

Pulmonary lymphoepithelial carcinoma (LEC) is a rare type of lung cancer. Though the clinical outcomes of patients with LEC are better than those for patients with other types of lung cancer, tumors frequently recur. Evidence has indicated that the immune microenvironment factors may predict outcome of cancer therapy; however, the composition of immune microenvironment in LEC remains largely unknown. We investigated the association between the immune microenvironment of LEC by using multiplex immunohistochemical staining. The densities of each tumor-infiltrating immune cell type and the amount of infiltrating immune cells spatially proximal to the closet tumor cell were analyzed. Although there was no significant correlation between the clinical outcome of LEC and the density of each tumor-infiltrating immune cell type, we found that the amount of CD4 + T lymphocyte proximal to tumor positively trended to longer disease-free survival in LEC. Additionally, the PD-L1 tumor proportion score was highly correlated with the amount of CD8 + T lymphocyte proximal to tumor, suggesting that immunotherapy might be beneficial for LEC patients. The spatial proximity of tumor-infiltrating immune cell measurement is useful for investigating the tumor-immune cells interaction. The spatial proximity of tumor-infiltrating CD4 + T lymphocytes might serve as a good prognostic factor for LEC.
Solution Printable Multifunctional Polymer-Based Composites for Smart Electromagnetic Interference Shielding with Tunable Frequency and On-Off Selectivities
Authors: Seol Mina , Hwang Uiseok , Kim Junyoung , Eom Deokjoon , Park In-Kyung , Kim Hyoungsub , Suhr Jonghwan , Nam Jae-Do
Published: September 2022

The advances in modern intelligent electronic systems have a pressing need for smart electromagnetic interference (EMI) shielding capabilities in a frequency-selective manner to choose which electromagnetic waves in a certain range to be blocked. Herein, we present multilayered EMI shielding composites that can provide selective on-off characteristics for specific frequency ranges across a broad spectrum. The composites are composed of outermost dielectric layers and conductive interlayers fabricated via solution-printing, wherein hexagonal boron nitride (BN) and silver-coated BN particles are embedded, respectively. The EMI shielding frequency range and on-off selectivity are controllable by varying the configuration of the composite structure in terms of the BN content and the number of composite layers, providing different interstitial spaces between the fillers and interfacial dielectric properties. Furthermore, the optimal combination of these layers permits excellent combinatorial properties of EMI shielding (32–62 dB), thermal conductivity (7.61 W/m·K), and electrical insulation (4.03 kV/mm) in the through-plane direction. The developed composites and their synthetic pathways have enormous potential for tailored material design and flexible system integration in next-generation EMI shielding technologies.
Efficient anti-tumor immunotherapy using tumor epitope-coated biodegradable nanoparticles combined with polyinosinic-polycytidylic acid and an anti-PD1 monoclonal antibody
Authors: Kim Sang-Hyun , Park Ji-Hyun , Lee Sun-Jae , Lee Hee-Sung , Jung Jae-Kyung , Lee Young-Ran , Cho Hyun-Il , Kim Jeong-Ki , Kim Kyungjae , Park Chan-Su , Lee Chong-Kil
Published: September 2022

BackgroundVaccination with tumor peptide epitopes associated with major histocompatibility complex class I molecules is an attractive approach directed at inducing tumor-specific cytotoxic T lymphocytes (CTLs). However, challenges remain in improving the therapeutic efficacy of peptide epitope vaccines, including the low immunogenicity of peptide epitopes and insufficient stimulation of innate immune componentsin vivo. To overcome this, we aimed to develop and test an innovative strategy that elicits potent CTL responses against tumor epitopes. The essential feature of this strategy is vaccination using tumor epitope-loaded nanoparticles (NPs) in combination with polyinosinic-polycytidylic acid (poly-IC) and anti-PD1 monoclonal antibody (mAb).MethodsCarboxylated NPs were prepared using poly(lactic-co-glycolic acid) and poly(ethylene/maleic anhydride), covalently conjugated with anti-H-2KbmAbs, and then attached to H-2Kb molecules isolated from the tumor mass (H-2b). Native peptides associated with the H-2Kbmolecules of H-2Kb-attached NPs were exchanged with tumor peptide epitopes. The tumor-specific CTL-inducing and anti-tumor activities of the tumor epitope-loaded NPs were examined in mice bearing EG7-OVA thymoma or B16-F10 melanoma. In addition, the anti-tumor therapeutic efficacy of the NPs was examined in combination with poly-IC, anti-PD1 mAb, or both.ResultsTumor peptide epitope-loaded NPs efficiently induced tumor-specific CTLs when used to immunize tumor-bearing mice as well as normal mice. This activity of the NPs significantly was increased when co-administered with poly-IC. Accordingly, the NPs exerted significant anti-tumor effects in mice implanted with EG7-OVA thymoma or B16-F10 melanoma, and the anti-tumor activity of the NPs was significantly increased when applied in combination with poly-IC. The most potent anti-tumor activity was observed when the NPs were co-administered with both poly-IC and anti-PD1 mAb.ConclusionsImmunization with tumor epitope-loaded NPs in combination with poly-IC and anti-PD1 mAb in tumor-bearing mice can be a powerful means to induce tumor-specific CTLs with therapeutic anti-tumor activity.
The Effect of dialysis rate on continuous renal replacement therapy for neonatal hyperammonemia
Authors: Chu Xiaoyun , Sun Yifan , Hong Wenchao , Gong Xiaohui , Cai Cheng
Published: September 2022

Background
CRRT has attracted more and more attention in the treatment of acute neonatal hyperammonemia.
Methods
We retrospectively analyzed the clinical data of hyperammonemic neonates treated with CRRT in the neonatal intensive care unit (NICU) of Shanghai Children's Hospital from August 2016 to September 2021, and further explored the relationship between the rate of decrease of blood ammonia and dialysis rate.
Results
A total of 6 cases of neonatal hyperammonemia were included, their primary diseases were 3 cases of ornithine transcarbamyltransferase deficiency (OTCD), 1 case of carbamoyl phosphate synthetase 1 deficiency (CPS1D), 1 case of methylmalonic acidemia (MMA) with homocysteinemia (combined MMA) and 1 case of transient hyperammonemia. All infants developed impaired consciousness, convulsions and severe hyperammonemia, so CRRT was superimposed on diet control and medication, and the mode of continuous venovenous hemodiafiltration (CVVHDF) was used in all cases. The gestational age at birth was (37.98 ± 1.12) weeks, the age at onset was (1.91 ± 0.91) d, and the weight at CRRT was (3157.50 ± 605.95) g. The dialysis rate was (880–3937) ml/h/1.73m2, the decrease rate of blood ammonia was (15.79–33.33) µmol/h, and the duration of CRRT diversion was 44–110 h. The decrease rate of blood ammonia increased with the increase in dialysis rate, without an increase in the incidence of serious complications.
Conclusions
CRRT can alleviate the metabolic crisis of hyperammonemic neonates, and increasing the dialysis rate of CRRT can safely and more effectively reduce blood ammonia levels in critically hyperammonemic neonates.
Amide proton transfer MRI differentiates between progressive multifocal leukoencephalopathy and malignant brain tumors: a pilot study
Authors: Koike Hirofumi , Morikawa Minoru , Ishimaru Hideki , Ideguchi Reiko , Uetani Masataka , Hiu Takeshi , Matsuo Takayuki , Miyoshi Mitsuharu
Published: September 2022

Background
Progressive multifocal leukoencephalopathy (PML) is a demyelinating disease of the central nerve system caused by the John Cunningham virus. On MRI, PML may sometimes appear similar to primary central nervous system lymphoma (PCNSL) and glioblastoma multiforme (GBM). The purpose of this pilot study was to evaluate the potential of amide proton transfer (APT) imaging for differentiating PML from PCNSL and GBM.
Methods
Patients with PML (n = 3; two men; mean age 52.0 ± 7.0 years), PCNSL (n = 7; four women; mean age 74.4 ± 5.8 years), or GBM (n = 11; 6 men; mean age 65.0 ± 15.2 years) who underwent APT-CEST MRI between January 2021 and July 2022 were retrospectively evaluated. Magnetization transfer ratio (MTR) values were measured on APT imaging using a region of interest within the lesion. Receiver operating characteristics curve analysis was used to determine diagnostic cutoffs for MTR.
Results
The mean MTR values were 0.005 ± 0.006 in the PML group, 0.025 ± 0.005 in the PCNLS group, and 0.025 ± 0.009 in the GBM group. There were significant differences in MTR between PML and PCNSL (P = 0.050), and between PML and GBM (P = 0.039). For differentiating PML from PCNSL, an MTR threshold of 0.0165 gave diagnostic sensitivity, specificity, positive predictive value, and negative predictive value of 100% (all). For differentiating PML from GBM, an MTR threshold of 0.015 gave diagnostic sensitivity, specificity, positive predictive value, and negative predictive value of 90.9%, 100%, 100%, and 97.6%, respectively.
Conclusion
MTR values obtained from APT imaging allowed patients with PML to be clearly discriminated from patients with PCNSL or GBM.
LFD-CNN: Levy Flight Distribution based Convolutional Neural Network for an Adaptive Learning Style Prediction in E-learning Environment
Authors: Alshmrany Sami
Published: September 2022

One of the essential factors in any learning environment is a learning style that deals with individual learning. With different learning styles, each learner has different ways of understanding, retaining, processing, and perceiving new knowledge. Automatic student learning style determination has become an important ability of the e-learning system. For learning events, the evolution of e-learning platforms provides students with higher opportunities online. In this article, we proposed a Convolutional Neural Network-based Levy Flight Distribution (CNN-LFD) algorithm for learning style prediction. An adaptive e-learning system is broken up into an automatic learning style prediction and classification based on the number of learning styles incorporated. Initially, the learner's login the ID, and the data are stored in the database. The features such as questionnaire score, login credentials (session ID, learner ID, and course ID), and login time (location, session ID) are extracted. After that, the CNN-LFD algorithm predicts the learners learning styles namely Active/reflective, Sensing/intuitive, visual/verbal, sequential/global based on the extracted features. The dataset details are obtained from Massive Open Online Course (MOOC) and the proposed model is implemented in JAVA software. The experimental results demonstrate higher classification accuracy during learning style prediction.
Intentional and actional components of engaged participation in public health research studies: qualitative synthesis of a recruitment and retention process into the theory-informed INTACT-RS framework
Authors: Lander Jonas , Heiberger Andrea , von Sommoggy Julia , Schulz Anja Alexandra , Dresch Carolin , Hala Altawil , Schmitt Gwendolyn , Wirtz Markus Antonius
Published: September 2022

Background
Ensuring motivated and successful study participation is a key challenge in the design and conduct of health research studies. Previously, recruitment barriers and facilitators have been identified mainly from experience, and rarely based on theoretical approaches. We developed a framework of intentional and actional components of engaged participation in public health research studies (INTACT-RS) based on psychological behavioral models. We aimed a) to identify precise indicators for each component of the framework and b) to better understand which components and decision processes are essential to interested and committed participation by study participants.
Methods
Within a multicenter research network, we applied various approaches to recruit parents of newborns, pediatricians, and midwives. All recruitment processes were documented from the perspective of both participants and researchers. We used different qualitative and quantitative data material, which we applied in a multistage process according to the basic principles of qualitative content analysis.
Results
INTACT-RS encompasses pre-intentional, intentional and actional phases with a total of n = 15 components covering all aspects of an individual’s involvement with a research study. During intention formation, an understanding of efforts and benefits, why participation is valuable beyond contributing to research, and how others perceive the study, were particularly important to (potential) participants. Subsequently (intentional phase), participants consider how and when participation is compatible with their own resources, ability and availability, and hence seek for close communication with, and flexibility and support from the research team. During and after (initial) participation (actional phase), participants’ assessment of whether expectations and interests have been met impact crucial further steps, especially the willingness to continue and to recommend participation to others. A strong topic-wise and or supportive participation interest as well as active, continuous exchange with the researchers appeared to be central determinants of study completion and data validity.
Conclusions
A theoretical framework is now available to plan and conduct recruitment of different target groups, which accounts for essential motivational and volitional decision-making processes. Based on empirically specified constructs, possible barriers can be addressed even before the initial recruitment process. Therefore, recommendations for scientific practice have been formulated.
Diuretic resistance in acute decompensated HFpEF vs. HFrEF
Authors: Sharma Akash , Patel Rahul , Prasad Anand , Bansal Shweta
Published: September 2022

Background: Diuretic resistance (DR) is a common cause of inadequate decongestion in patients hospitalized with acute decompensated heart failure (ADHF). DR has not been characterized in patients with HF with preserved ejection fraction (HFpEF).
Methods: In a post-hoc analysis of a pilot study evaluating the role of high-dose spironolactone in ADHF patients with DR, we analyzed the prevalence and potential pathophysiologic factors of DR in HFpEF (n=20) and compared those with HF with reduced EF (HFrEF) (n=27). DR was defined as weight loss<1lb/day despite intravenous furosemide>160mg/day (at least one dose of 80mg/day).
Results: DR was observed in 10 (50%) of HFpEF participants as compared to 10 (37%) of HFrEF participants (p=ns). DR-HFpEF participants were older and had lower kidney function compared to DR-HFrEF. There was no difference in clinical presentation and lab parameters. Moreover, urine sodium/potassium ratio, plasma renin activity, plasma aldosterone and epinephrine levels were lower in DR-HFpEF as compared to DR-HFrEF, though still higher than diuretic responsive-HFpEF patients. Weight loss in response to high-dose spironolactone was similar in DR-HFpEF and HFrEF.
Conclusion: We demonstrate that DR is more prevalent in HFpEF compared to HFrEF patients. Despite similar clinical features of congestion and response to high-dose spironolactone, a state of reduced neurohormonal activation points that additional factors might be contributing to DR in HFpEF versus HFrEF patients.
A novel multi-pass machining accuracy prediction method for thin-walled parts
Authors: Huang Qiang , Wang Sibao , Wang Shilong , Zhao Zengya , Wang Zehua , Tang Binrui
Published: September 2022

Thin-Walled Parts (TWP) are widely used in aerospace, whose service performance is significantly affected by the machining accuracy. Considering the poor stiffness of TWP, multi-pass machining is used to machine TWP for better surface accuracy. However, it is difficult to accurately predict the final machining accuracy due to the surface topography error’s propagation and accumulation in multi-pass machining. Therefore, this paper proposes a multi-pass machining accuracy prediction method for TWP based on dynamic factors (cutting force and stiffness). Firstly, a flexible cutting force prediction model, which considers the axial errors determined by the initial surface topography and part deflection, is proposed. Secondly, a Position-Pass-Dependent Stiffness (PPDS) model is established considering position-dependent of stiffness and multi-pass machining material removal. Finally, combining the two models above, a multi-pass machining accuracy prediction method based on Genetic Algorithm - Back Propagation (GA-BP) neural network is proposed. The experiments under various conditions have been carried out to validate the proposed method. The machining accuracy (flatness as an example) is as high as 90.8% using the method in this paper, while it is only 73.9% when the accumulative error is neglected. The proposed method can significantly improve the performance of machining accuracy prediction by analyzing the error propagation mechanism and the effect of dynamic factors between multi-pass machining. Furthermore, this also provides a theoretical basis for process parameters optimization and machining accuracy improvement in TWP machining.
Small-Area Estimation and Analysis of HIV/AIDS Indicators for Precise Geographical Targeting of Health Interventions in Nigeria. A Spatial Microsimulation Approach
Authors: ABUBAKAR Eleojo Oluwaseun , CUNNINGHAM Niall
Published: September 2022

Background: Precise geographical targeting is well recognised as an indispensable intervention strategy for achieving many Sustainable Development Goals (SDGs). This is more cogent for health-related goals such as the reduction of the HIV/AIDS pandemic, which exhibits substantial spatial heterogeneity at various spatial scales (including at microscale levels). Despite the dire data limitations in Low and Middle Income Countries (LMICs), it is essential to produce fine-scale estimates of health-related indicators such as HIV/AIDS. Existing small-area estimates (SAEs) incorporate limited synthesis of the spatial and socio-behavioural aspects of the HIV/AIDS pandemic and/or are not adequately grounded in international indicator frameworks for sustainable development initiatives. They are, therefore, of limited policy-relevance, not least because of their inability to provide necessary fine-scale socio-spatial disaggregation of relevant indicators.
Methods: The current study attempts to overcome these challenges through innovative utilisation of gridded demographic datasets for SAEs as well as the mapping of standard HIV/AIDS indicators in LMICs using spatial microsimulation (SMS).
Results: The result is a spatially enriched synthetic individual-level population of the study area as well as microscale estimates of four standard HIV/AIDS and sexual behaviour indicators. The analysis of these indicators follows similar studies with the added advantage of mapping fine-grained spatial patterns to facilitate precise geographical targeting of relevant interventions. In doing so, the need to explicate socio-spatial variations through proper socioeconomic disaggregation of data is reiterated.
Conclusions: In addition to creating SAEs of standard health-related indicators from disparate multivariate data, the outputs make it possible to establish more robust links (even at individual levels) with other mesoscale models, thereby enabling spatial analytics to be more responsive to evidence-based policymaking in LMICs. It is hoped that international organisations concerned with producing SDG-related indicators for LMICs move towards SAEs of such metrics using methods like SMS.
Design, Implementation, and Evaluation of a Communication Skills Course for Clinical Faculty Members
Authors: Hayat Ali Asghar , Abdi Masumeh , Keshavarzi Mohammad Hasan , Rezaei Habibolah
Published: September 2022

Background:Due to the importance and necessity of communication skills for clinical faculty members and the lack of assessment of this skill in faculty members of Yasuj University of Medical Sciences, this study was carried out under the title of design, implementation, and evaluation of the communication skills course for clinical faculty members.
Methods: This semi-experimental study was conducted in 2021 at Yasuj University of Medical Sciences. The study population was clinical faculty members, students, and nurses of Yasuj University of Medical Sciences. A researcher-made questionnaire was used to assess the clinical communication skills of faculty members. Areas where faculty members needed training were identified and, according to those needs, an educational webinar was held for faculty members. The clinical communication skills of the faculty members were evaluated again, as well as their satisfaction with the course.
Results: The clinical communication skills of the faculty members were higher than 4.2 on most items. In most items, the score increased after the course, but none of these increases were significant. The total satisfaction of the faculty members from the course was 3.98, with a standard deviation of 0.18.
Conclusions:The level of clinical communication skills of the faculty members of Yasuj University of Medical Sciences is appropriate and this skill was improved after the training course. Due to the low score of the faculty members in the feedback to the patient, it is suggested that a training course on appropriate feedback and its principles be held for the faculty members.
The application of chemometrics in metals source of identification in Brunei Bay surface sediment
Authors: Chuan Ong Meng , Chuen Yong Jaw , Shaari Hasrizal , Bidai Joseph , Shazili Noor Azhar Mohamed , Pradit Siriporn , Ghazali Adiana
Published: September 2022

Brunei Bay is a unique ecosystem which offer a vast diversity of biology. The current study was carried out to trace the source of metals in the surface sediment of Brunei Bay as a control check on the bay’s ecosystem. The study has analyzed the secondary data using chemometrics analysis to verify and better understand the factors that influence metals distribution in Brunei Bay sediment. Samples were collected several times during 2013 to 2014 using ponar grab at 16 stations within the bay. Samples were then dried, pre-treated, digested and analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) in the laboratory. Overall, the mean concentration of metal changed during different sampling periods as the changes was presumed affected by seasonal changes. Furthermore, Al, Zn, Cd, Fe, sediment pH and clay fraction were significantly affected temporally. In identifying the source of metals in Brunei Bay’s sediment, the Pearson correlation has classified natural input of metals and proved that total organic carbon was derived by anthropogenic sources. Moreover, the principal component analysis has simplified the natural input is dominantly affecting the distribution of metals in the bay’s sediment. However, the utilization of marine resources is slightly affecting the bay’s ecosystem which may deteriorate the ecosystem health soon.
Evaluation of the potential of miR-21 as a diagnostic marker for oocyte maturity and embryo quality in women undergoing ICSI
Authors: Jenabi Maryam , Khodarahmi Parvin , Tafvizi Farzaneh , Bostanabad Saeed Zaker
Published: September 2022

MicroRNAs are small molecules that play a crucial role in regulating a woman's reproductive system. The present study evaluates the expression of miR-21 in the serum, follicular fluid (FF), and cumulus cells (CCs) and their association with oocyte maturity and embryo quality in women undergoing intracytoplasmic sperm injection (ICSI). Women subjects were divided into the case (female factor infertility) and control groups (male factor fertility). The level of miR-21 was measured using Real-Time PCR. The level of miR-21 was significantly lower in the CCs, FF, and serum in the case compared to the control group. MiR-21 abundance was higher in FF and CCs samples than in serum. Furthermore, there was a significant increase in CCs to FF in the case group. A significant decrease in oocyte count, MII oocytes, and percentage of mature oocytes were observed in the case group. The expression of miR-21 in FF and CCs was positively related to oocyte maturation, but no correlation with embryo development was observed. This study found that miR-21 is expressed less in women with female factor infertility, and human oocytes' development is crucially affected by the expression of miR-21. Therefore, miR-21 could provide new helpful biomarkers of oocyte maturity.
The Berlin Bimanual Test for Tetraplegia (BeBiTT) to assess the impact of assistive hand exoskeletons on bimanual task performance
Authors: Angerhöfer Cornelius , Vermehren Mareike , Colucci Annalisa , Nann Marius , Koßmehl Peter , Niedeggen Andreas , Kim Won-Seok , Chang Won Kee , Paik Nam-Jong , Hömberg Volker , Soekadar Surjo R.
Published: September 2022

Background:Assistive hand exoskeletons are promising tools to restore hand function after cervical spinal cord injury (SCI) but assessing their specific impact on bimanual hand and arm function is limited due to lack of reliable and valid clinical tests. Here, we introduce the Berlin Bimanual Test for Tetraplegia (BeBiTT) and demonstrate its sensitivity to brain/neural hand exoskeleton(B/NHE)-related improvements in bimanual task performance.Methods:Fourteen study participants with subacute cervical SCI performed the BeBiTT unassisted (baseline). Thereafter, participants repeated the BeBiTT while wearing a B/NHE (intervention). Online control of the B/NHE was established via a hybrid sensorimotor rhythm-based brain-computer interface (BCI) translating electroencephalographic (EEG) and electrooculographic (EOG) signals into open/close commands. For reliability assessment, BeBiTT scores were obtained by four independent observers. Besides internal consistency analysis, construct validity was assessed by correlating baseline BeBiTT scores with the Spinal Cord Independence Measure III (SCIM III) and Quadriplegia Index of Function (QIF). Sensitivity to differences in bimanual task performance was assessed with a bootstrapped pairedt-test.Results:The BeBiTT showed excellent interrater reliability (intraclass correlation coefficients > 0.9) and internal consistency (α = 0.91). Validity of the BeBiTT was evidenced by strong correlations between BeBiTT scores and SCIM III as well as QIF. Wearing a B/NHE (intervention) improved the BeBiTT score significantly (p< 0.05) with high effect size (d=1.063), documenting high sensitivity to intervention-related differences in bimanual task performance.Conclusion:The BeBiTT is a reliable and valid test for evaluating bimanual task performance in persons with tetraplegia, suitable to assess the impact of assistive hand exoskeletons on bimanual function.
The constant solution method for solving large scale differential Sylvester matrix equations with time invariant coefficients
Authors: Bouhamidi Abderrahman , Elbouyahyaoui Lakhdar , Heyouni Mohammed
Published: September 2022

This paper is mainly focused on the solution of Sylvester matrix differential equations with time independent coefficients. We propose a new approach based on the construction of a particular constant solution which allows to construct an approximate solution of the differential equation from that of the corresponding algebraic equation. Moreover, when the matrix coefficients of the differential equation are large, we combine the constant solution approach with Krylov subspace methods for obtaining an approximate solution of the Sylvester algebraic equation, and thus form an approximate solution of the large-scale Sylvester matrix differential equation. We establish some theoretical results including error estimates and convergence as well as relations between the residuals of the differential and its corresponding algebraic Sylvester matrix equation. We also give explicit benchmark formulas for the solution of the differential equation.To illustrate the efficiency of the proposed approach, we perform numerous numerical tests and make various comparisons with other methods for solving Sylvester matrix differential equations.
Robust Local Bootstrap for WeaklyStationary Time Series in the Presence ofAdditive Outliers
Authors: Solci Carlo Correa , Reisen Valderio Anselmo , Rodrigues Paulo Canas
Published: September 2022

The aim of this paper is to propose a generalization of the local bootstrap for periodogram statistics to the case when weakly stationary time series are contaminated by additive outliers. In order to achieve robustness, we suggest to replace the classical version of the periodogram with the M-periodogram in the local bootstrap procedure. The robust bootstrap periodogram is implemented in the Whittle estimator to obtain confidence intervals for the parameters of a time series model. A finite sample size investigation was conducted to compare the performance of the classical local bootstrap with the one proposed in this paper, to estimate 95% confidence intervals for the parameters of autoregressive and of seasonal autoregressive time series. The results have shown that the robust estimator is resistant to additive outlier contamination and produces confidence intervals with coverage percentage closer to 95\% and with lower amplitudes than the ones obtained with the classical estimator, even for small percentages and magnitudes of outliers. It was also empirically demonstrated that when the expected number of outliers is kept constant, the coverage percentages of the confidence intervals of the robust estimators tend to 95\% as the sample size increases. An application to the daily mean concentration of the particulate matter with diameter smaller than \SI{10}{\micro\meter} (PM$_{10}$) was considered to illustrate the methodologies in a real data context. All the results presented here give strong motivation to use the proposed robust methodology in practical situations in which weakly stationary time series are contaminated by additive outliers.
Extraction of terrain ridge lines and valley lines based on agglomeration analysis of terrain points: a cluster analysis method
Authors: Cheng Zhang , Wanfeng Dou , Yuan Pang
Published: September 2022

Terrain feature extraction is one of the critical issues in geographic information science. As important terrain feature lines, ridge lines and valley lines, play an important role in hydrological analysis, terrain reconstruction and automatic integration of contour lines. But, the extraction of terrain feature lines is complicated and time-consuming task. In this paper, a terrain feature line extraction method is proposed based on clustering technique. The terrain feature points are automatically extracted according to the agglomeration of terrain points, and the similar points are automatically identified according to the DBSCAN clustering algorithm. The points with high similarity are clustered along the direction of ridge or valley, and the whole terrain will be clustered into multiple sub-regions. The nearest sub-regions are found by calculating the minimum distance between these sub-regions, and the adjacent sub-regions are connected orderly by their center line to obtain terrain feature lines. Compared with other methods, the cluster analysis method in this paper has simple process and high efficiency.
Fat-free mass estimation in male high-level futsal players: development and validation of a new bioelectrical impedance-based predictive equation
Authors: Matias Catarina , Campa Francesco , Cavaca Margarida , Paoli Antonio , Teixeira Filipe
Published: September 2022

Objectives: the present study aimed to develop and
cross-validate a futsal-specific bioelectrical equation for
estimating fat-free mass (FFM) in male players. Methods: a total of
66 futsal players (age 23.3 ± 5.4 years) from the Major Portuguese
Futsal League “LIGA PLACARD” and from the 2nd and 3rd National
Futsal Leagues were included in this cross-sectional, observational
study. The participants underwent a foot-to-hand bioelectrical
impedance analysis (BIA) at 50 kHz and completed a dual-energy
X-ray absorptiometry (DXA) scan for reference body composition
data. The sport-specific model was developed by stepwise multiple
regression using bioelectrical raw parameters [resistance (R) and
reactance (Xc)] as independent variables. Cross-validation was
performed using the PRESS approach, least squares regression,
concordance correlation coefficient (CCC) and Bland-Altman
analyses. Results: a BIA-based model was developed for FFM [FFM
(kg) = -8.865 + 0.437 * Body Mass (kg) + 0.186 * Xc + 0.415 *
stature (cm)2/R (R2 = 0.89, standard error of estimation = 2.38
kg)]. Cross validation revealed a substantial strength of agreement
(CCC = 0.953), an r2 of 0.88 with a standard error of estimation
equal to 2.31 kg, no mean bias (0.04 kg, p>0.05), low limits of
agreement (ranged from -4.5 to 4.6 kg), and no trend (r = -0.170, p
= 0.172). Conclusions: the present equation is the first to allow
for a valid, accurate, and sport-specific assessment of FFM in male
futsal players.
The first record of Ozius tuberculosus H. Milne Edwards (Crustacea: Decapoda: Brachyura) from the East Coast of Indian subcontinent
Authors: Banerjee Somesh , Ramakrishnan Sreeraj Chemmencheri
Published: September 2022

The diversity of marine brachyuran crabs along India's east coast has been investigated extensively. This study deals with the widespread distribution of Ozius tuberculosus H. Milne Edwards' 1834 species in India's eastern coast from Visakhapatnam. The distribution of this species, which is found in Maharashtra, Karnataka, Kerala, the Lakshadweep Islands, and the Andaman & Nicobar Islands, was previously mainly known from the west coast of India. Along with details regarding the geographic range of this species in India, a taxonomic description is also given. Besides its taxonomic value, it has very little economic value since it is non-edible.
Splenic irradiation combined with plasmapheresis and rituximab: a new option reducing donor specific antibody in haplo-identical hematopoietic stem cell transplantation
Authors: Wu Xiaojin , Zhou Shiyuan , Ma Xiao , Ma Chao , Qian Zhu , Zhao Qi , Li Ling , Li Shijia , Tang Zaixiang , He Jun , Wu Depei , Qin Songbing
Published: September 2022

The development of donor-specific antibodies (DSAs) against human leukocyte antigens (HLA) is a major problem during haplo-identical hematopoietic stem cell transplantation (haplo-HSCT). There is currently no recommended treatment option to remove DSAs. Thus, we conducted a prospective, single-arm study where we combined low-dose splenic irradiation with plasmapheresis and rituximab as a new treatment protocol to reduce DSAs before haplo-HSCT. Nineteen patients were enrolled in this prospective study and matched controls treated with the same protocol, but without splenic irradiation, were simultaneously collected from DSA patients. The aim of this study is to explore the safety and efficacy of our outlined treatment protocol made up of splenic irradiation, plasmapheresis, and rituximab. We found that DSA levels decreased significantly after transplantation in both groups, however they decreased more greatly in patients treated additionally with splenic irradiation than those in control group. De novo DSAs were not detected after transplantation in the splenic irradiation group but detected in 5 patients from the control group. At follow-up, we found that patients in splenic irradiation group achieved superior overall survival (OS) and progress free survival (PFS) compared to those in control group. We concluded that adding low-dose splenic irradiation to routine protocol is feasible. chictr.org.cn: ChiCTR2100051456. Registered 24 September 2021. Retrospectively registered.
Designing Energy Efficiency for Traditional Data Center
Authors: Bhattacharya Tathagata , Mao Jianzhou , Bhattacharya Sutanu , Cao Ting , Peng Xiaopu , Rahgouy Mostafa , Qin Xiao
Published: September 2022

Power Management Strategies and the impact of carbon dioxide emissions from data centers across the globe have drawn significant attention worldwide. The rapid growth of energy consumed in data centers has led to 1) huge costs 2) depletion of non-renewable resources such as coal and petroleum, and 3) emission of greenhouse gases like CO2 in the atmosphere. These greenhouse gas significantly contributes to the climate change of the earth. To tackle this challenge, our research deals with modeling the energy resources of data centers, thereby offering insights to reduce the global carbon footprint and energy cost. In our model, we prioritize green energy consumption by eliminating brown energy resources. In this process, we devise an algorithm that can determine the amount of CO2 emission in the atmosphere per hour by different energy resources. We create an energy model for data centers by incorporating the support vector regression algorithm. Our model is adroit at projecting energy consumed in data centers powered by green energy. Our experimental results confirm that our model consistently delivers high prediction accuracy in terms of energy usage in data centers. The model is expected to facilitate data analytic venues to optimize energy efficiency and sustaininability for the development of future data centers.
TFPA: A traceable federated privacy aggregation protocol
Authors: Li Xingyu , Long Yucheng , Hu Li
Published: September 2022

Federated learning is gaining significant interests as it enables model training over a large volume of data that is distributedly stored over many users. However, Malicious or dishonest aggregator still possible to infer sensitive information and even restore private data from local model updates even destroy the process of training. To solve the problem, researchers have proposed many excellent methods based on privacy protection technologies, such as secure multiparty computation (MPC), homomorphic encryption (HE), and differential privacy. But these methods don't only ignore users' address and identity privacy, but also include nothing about a feasible scheme to trace malicious users and malicious gradients.
In this papper, we propose a decentralized Byzantine-fault-tolerant federated learning protocol based on traceable ring signature and undirectional proxy re-encryption, named RFL, which consists of an one-time dynamic proxy protocol, an robust aggregation protocol and an gradient calibration protocol. In our protocol, all users owns a aggregator, a proxy and a trainer while there is no central server. These users can achieve anonymous sharing of local gradients, robust aggregation of global gradients, and tracing of malicious gradients through the protocol. We design, implement, and evaluate a practical system to jointly learn an accurate model under semi-honest and malicious adversary security, respectively. The experiments show our protocols achieve the best overall performance as well.
A hybrid neural network and data sampling solver for forward and backward modified diffusion equations
Authors: Mou Xuankang , Fang Qian , Li Shiben
Published: September 2022

We developed a hybrid solver based on physics-informed neural networks and a mixture of grid and Latin hypercube sampling to solve forward and backward modified diffusion equations. We optimized the parameters in the neural networks by considering the squeeze boundary condition and the parameter in the mixed data sampling by adjusting the mixture coefficient. Then,we used a given modified diffusion equation as an example to demonstrate the efficiency of the hybrid solver for forward and backward problems. The neural network results were compared with the numerical solutions, and good agreement with high precision was observed. This hybrid neural network solver can be generalized to other partial differential equations.
Preliminary study regarding the optimisation of the accelerated ageing of sugar cane spirit by applying ultrasound-assisted extraction and white oak chips (Quercus Alba)
Authors: Abreu-Naranjo Reinier , Estela Guardado Yordi , Radice Matteo , Scalvenzi Laura , Martínez Amaury Pérez
Published: September 2022

The ageing of alcoholic beverages is a common practice in order to increase their quality due to the release of wood extractable compounds from the barrels used. However, this process is slow and can take several years. This research focussed on optimising the use of Quercus alba chips and ultrasound in the accelerated ageing process of sugar cane spirit using the response surface methodology. The effect of temperature and ultrasound was analysed using a two-level factorial design type 22. Subsequently, the accelerated ageing process was optimised using response surface methodology. Temperature and time of exposure to ultrasound energy were the selected independent variables. As a response variable, the total polyphenol index (TPI) was selected. In addition, the CIELab method was used to determine the colour characteristics (L*, a*, b*) of the aged samples. Roasting had a negative effect on the TPI, while the oak chips that were untoasted and treated with ultrasound obtained the highest TPI yield (80.5–81.5 mg GAEeq/L). The TPI values obtained through the use of the accelerated ageing method suggest that it is more efficient than the traditional ageing process, as it leads to a decrease in the maturation period of sugar cane spirit. Regarding the colour properties, a higher intensity of colour was found in the samples where the accelerated ageing method was applied. The temperature and sonication time of 48.9°C and 18.8 min were the optimal parameters to obtain a TPI value (85 GAEeq./L) comparable to the Brandy Solera Reserve (12–18 months for the traditional method) for sugar cane spirit using the accelerated method. The findings of this research can contribute towards the development of new ageing processes of distillates, mainly in terms of decreasing ageing times.