bluuebunny/crossref_metadata_2025 huggingface dataset:
Bayesian Multi-level Mixed-effects Model for Influenza Dynamics
Authors: Huang Hanwen
Published: October 2022

Influenza A viruses (IAV) are the only influenza viruses known to cause flu pandemics. Understanding the evolution of different sub-types of IAV on their natural hosts is important for preventing and controlling the virus. We propose a mechanism-based Bayesian multi-level mixed-effects model for characterising influenza viral dynamics, described by a set of ordinary differential equations (ODE). Both strain-specific and subject-specific random effects are included for the ODE parameters. Our models can characterise the common features in the population while taking into account the variations among individuals. The random effects selection is conducted at strain level through re-parameterising the covariance parameters of the corresponding random effect distribution. Our method does not need to solve ODE directly. We demonstrate that the posterior computation can proceed via a simple and efficient Markov chain Monte Carlo algorithm. The methods are illustrated using simulated data and a real data from a study relating virus load estimates from influenza infections in ducks.
Los bordes de la ley: la escena judicial y la violencia de género en el cine argentino
Authors: Forcinito Ana
Published: October 2022

En este ensayo analizo cuatro instancias en la representación del escenario jurídico-legal en relación con la violencia de género (en especial la violación sexual y el femicidio) dentro el cine argentino desde los noventa. A pesar de que en todos los casos hay un cuestionamiento de la justicia (y una puesta en escena de lo injusto), en todas las películas que analizaré se plantean diferentes dilemas legales o jurídicos. Ya sea en forma de denuncia de un crimen que conmocionó a toda la sociedad argentina (El caso María Soledad), o de un cuestionamiento de la justicia en plena época de impunidad y neoliberalismo y una simultánea invisibilización del género y de las mujeres (Cenizas del paraíso), o de un cuestionamiento de la justicia y los resabios del Estado terrorista, pero ahora anclado en la pregunta sobre un femicidio (El secreto de sus ojos), o una discusión teórica sobre la justicia que hace uso del cadáver de una joven mujer como telón de fondo y como excusa para discutir el poder masculino del derecho (Tesis sobre un homicidio). Los films que voy a analizar delinean la ley y, sobre todo, sus bordes, es decir, lo que no queda representado en el escenario legal o jurídico, pero que es muchas veces determinante de decisiones judiciales que atentan contra la justicia y contra los derechos de las mujeres.
Numerical Modeling of Moored Floating Platforms for Wave Energy Converters Using DualSPHysics
Authors: Tagliafierro Bonaventura , Martínez-Estévez Iván , Crego-Loureiro César , Domínguez José M. , Crespo Alejandro J. C. , Coe Ryan G. , Bacelli Giorgio , Gómez-Gesteira Moncho , Viccione Giacomo
Published: October 2022

The DualSPHysics open-source code establishes a comprehensive and efficient framework for simulating coastal and ocean engineering structures, which has been proven to be particularly reliable in wave energy converter (WEC) simulation. In this research, the experimental data of the floating oscillating surge wave energy converter (FOSWEC), is used for validation purposes. The FOSWEC2 device developed by SANDIA National Laboratories (US) is quite complex as it has several floating parts, anchor legs and a power take-off system (PTO) connected to the pitching motion of two flaps. Kinetic energy is in fact converted from the relative rotation between the flaps and a movable frame of the platform, setting a significant challenge for the validation of the FOSWEC with time-domain integrated methods. This work proposes a first validation campaign carried out using regular waves, and considering different parameters for the definition of the PTO system. The numerical model prediction for the platform motion (surge and pitch) and the relative flap pitch angle (bow and aft) shows that the model is able to deal with multi-body dynamics interacting with wave-induced forces.
Numerical Investigation on Scale Effect of 5415M Maneuverability
Authors: Zhang Donglei , Wang Qing , Dong Kai , Wang Xianzhou
Published: October 2022

A numerical investigation about the effect of ship model scale on turning maneuver has been presented in this study. A preliminary US Navy surface combatant, David Taylor Model Basin (DTMB) 5415M, is chosen as the object of study. An in-house computational fluid dynamics (CFD) solver is used for the numerical simulation. Structured grid has been divided for the model and the use of overset grid technology allows the deflection of the rudders when the surface combatant undergoes 6 degrees of freedom motions. Numerical modelling errors for the simulation of steady turning at 35-degree deflection of DTMB 5415M rudder at Fr = 0.41 in calm water have been estimated. The grid convergence studies have been conducted for the uncertainty analysis and the numerical results have been compared with the existed experimental data, which showed a good agreement. Three different scales (1:5, 1:15, 1:35.48) have been selected for the investigation to study the scale effects on ship turning maneuvers. Ship motions, hydrodynamic forces and moments for all the scales have been compared for the purpose of analyzing the scale effects on ship maneuverability. The results show that larger scale has smaller tactical diameter and smaller roll angle. The results of intermediate scale are less than 5% compared with the smallest scale, and the difference between the largest scale and the smallest scale is more than 10%, especially the roll angle reaches 50%. The scales have different influence on forces coefficient and moment coefficient of different directions.
Platform Motion Forecast of Hywind Floating Offshore Wind Turbine Based on SADA Method and Full-Scale Measurement Data
Authors: Chen Peng , Hu Zhiqiang
Published: October 2022

The dynamic responses analysis of floating offshore wind turbines (FOWTs) is very complex, which involves very strong nonlinear and coupling effects. This has also led to the current engineering application of FOWTs still facing critical gaps, especially in innovative design and dynamic performances prediction. Both academia and the wind industry are constantly exploring breakthroughs in terms of design and maintenance for FOWTs. The purpose of this paper is to apply a novel method, named SADA, which combines AI technology with numerical analysis methods, on full-scale measured data to optimize the platform motion prediction of the Hywind FOWT. The full-scale data used in this paper was collected by one of Hywind FOWTs in Scotland. The results show that the AI-trained numerical model can predict the motions of Hywind supporting floater with higher accuracy. The tension of the fairlead has undergone a huge change although the deformation of the blades and the tower has been reduced. In addition, compared with the deformation of the tower and the blades, the changes in the mooring system are the most significant. In summary, the SADA method can bring an innovative vision for FOWTs’ full-scale measurement technology in the future.
Dynamic Response Analysis of a Novel Semi-Submersible Floating Offshore Wind Turbine Based on Different Mooring System Designs
Authors: Zhao Zhixin , Wang Wenhua , Shi Wei , Li Xin , Wang Bin
Published: October 2022

A conceptual semi-submersible platform at the water depth of 100 m is proposed to support the Technical University of Denmark (DTU) 10 MW wind turbine and four types of mooring systems are designed to constrain the motions of this newly designed semi-submersible platform. The fully coupled time domain simulation is conducted using aero-hydro-servo-elastic OpenFAST code and the dynamic responses of the floating wind turbine concept are studied based on different mooring system designs. This innovative concept meets reasonable natural period requirements and achieves great stability under design environmental conditions. Furthermore, the difference of the four types of mooring systems on the motion responses and structural dynamics of the 10 MW semi-submersible floating offshore wind turbine (FOWT) is investigated and compared, and the optimal mooring system design is suggested.
Data Fusion for Jack-Up Wind Load Prediction
Authors: Xing Xiuqing , Dao My Ha , Zhang Baili , Lou Jing , Tan Wei Siang , Cui Yongdong , Khoo Boo Cheong
Published: October 2022

In this study, wind load on a typical jack-up is calculated through CFD simulation and measured through wind tunnel tests for operational condition (OC) and extreme condition (EC). The Reduced Order Method (ROM) model is built up based on high fidelity CFD simulation results. Two data assimilation models, ROM-based Gappy POD and Extended Kalman Filter (EKF) model, are developed to fuse the measured data from wind tunnel tests with the numerical results for jack-up wind load predictions. The outcomes show that both the EKF and gappy POD are able to predict the wind loads on the jack-up platform under OC and EC with satisfying accuracy, even with only 21 measurement data. The findings of this study provide an option for fusing the numerical simulation results with wind-tunnel measurements or operational data for accurately predicting the wind load on marine vessels and offshore platforms.
The one-up one-down adaptive (staircase) procedure in speech-in-noise testing: Standard error of measurement and fluctuations in the track
Authors: Smits Cas , Festen Joost M. , Swanepoel De Wet , Moore David R. , Dillon Harvey
Published: October 2022

The one-up one-down adaptive (staircase or up-down) procedure is often used to estimate the speech recognition threshold (SRT) in speech-in-noise testing. This article provides a brief historical overview of the one-up one-down procedure in psychophysics, discussing the groundbreaking early work that is still relevant to clinical audiology and scientific research. Next, this article focuses on two aspects of the one-up one-down adaptive procedure: first, the standard error of measurement (SEM) and, second, the fluctuations in the track [i.e., the standard deviation of the signal-to-noise ratios of the stimuli within the track (SDtrack)]. Simulations of ideal and non-ideal listeners and experimental data are used to determine and evaluate different relationships between the parameters slope of the speech recognition function, SRT, SEM, and SDtrack. Hearing loss and non-ideal behavior (inattentiveness, fatigue, and giving up when the task becomes too difficult) slightly increase the average value of SDtrack. SDtrack, however, poorly discriminates between reliable and unreliable SRT estimates.
The Percentage of Mature Height as a Morphometric Index of Somatic Growth: A Formal Scrutiny of Conventional Simple Ratio Scaling Assumptions
Authors: Lolli Lorenzo , Johnson Amanda , Monaco Mauricio , Di Salvo Valter , Atkinson Greg , Gregson Warren
Published: October 2022

Purpose: To assess conventional assumptions that underpin the percentage of mature height index as the simple ratio of screening height (numerator) divided by actual or predicted adult height (denominator). Methods: We examined cross-sectional data from 99 academy youth soccer players (chronological age range, 11.5 to 17.7 y) skeletally immature at the screening time and with adult height measurements available at follow-up. Results: The y-intercept value of −60 cm (95% confidence interval, −115 to −6 cm) from linear regression between screening height and adult height indicated the failure to meet the zero y-intercept assumption. The correlation coefficient between present height and adult height of .64 (95% confidence interval, .50 to .74) was not equal to the ratio of coefficient of variations between these variables (CVx/CVy = 0.46) suggesting Tanner’s special circumstance was violated. The non-zero correlation between the ratio and the denominator of .21 (95% confidence interval, .01 to .39) indicated that the percentage of mature height was biased low for players with generally shorter adult height, and vice versa. Conclusion: For the first time, we have demonstrated that the percentage of mature height is an inconsistent statistic for determining the extent of completed growth, leading to potentially biased inferences for research and applied purposes.
Modulation by macrocyclic peptides
Authors: Foley John F.
Published: October 2022

Cell-permeable, macrocyclic peptides antagonize either the active or the inactive states of Gα
s
to fine-tune signaling.
Supplemental Material: Tracing the protoliths of the garnet amphibolitic and retrogressed eclogitic slices and a conceptual tectonic model for their emplacement onto the Central Menderes Massif, Turkey: New geochemical data and laser ablation–inductively coupled plasma–mass spectrometry
Authors: Gürsu Semih , al. et
Published: October 2022

Figures S1–S5 and Tables S1–S12.
Exploring the intensity, barriers and correlates of physical activity In Iranian pregnant women: a cross-sectional study
Authors: Ahmadi Katayon , Amiri-Farahani Leila , Haghani Shima , Hasanpoor‑Azghady Seyedeh Batool , Pezaro Sally
Published: October 2022

Objectives

To determine the intensity, barriers and correlates of physical activity (PA) in Iranian pregnant women.

Methods

This cross-sectional study was carried out with 300 eligible pregnant women referred to the Ilam health centres and bases using stratified random sampling with proportional allocation. Data collection tools included a demographic and obstetrical history questionnaire, the Pregnancy Physical Activity Questionnaire and the Exercise Benefits/Barriers Scale. The association between demographic and obstetrical characteristics and PA intensity and barriers were studied using multiple linear regression models.

Results

The mean and SD of the total score of PA intensity were 47.15 and 26.25 metabolic equivalent of task (MET)-hour/week, respectively. The highest and the lowest barriers were related to the time expenditure (42.77±18.04) and family discouragement (50.72±24.99) constructs, respectively. The PA intensity was significantly associated with prepregnancy or early pregnancy body mass index (B=25.6), ethnicity (B=16.94), level of education (B=−8.77), number of children (B=5.95), gestational age (B=0.81), participation in childbirth preparation classes (B=−11.27), habitual exercise before pregnancy (B=6.09), income (B=−9.22). The PA barriers were significantly associated with ethnicity (B=−4.96), income (B=2.23) and habitual exercise before pregnancy (B =−1.35).

Conclusion

PA intensity may be enhanced by encouraging individuals to be more physically active before pregnancy. Additionally, strategies to enhance support from friends and family to engage in PA throughout pregnancy and PA interventions focused on women with lower levels of income and education are required.
Urban–rural disparities in mild cognitive impairment and its functional subtypes among community-dwelling older residents in central China
Authors: Liu Dan , Li Lin , An Lina , Cheng Guirong , Chen Cong , Zou Mingjun , Zhang Bo , Gan Xuguang , Xu Lang , Ou Yangming , Wu Qingming , Wang Ru , Zeng Yan
Published: October 2022

Background

Substantial variations in the prevalence of mild cognitive impairment (MCI) and its subtypes have been reported, although mostly in geographically defined developed countries and regions. Less is known about MCI and its subtypes in rural areas of less developed central China.

Aims

The study aimed to compare the prevalence of MCI and its subtypes in residents aged 65 years or older in urban and rural areas of Hubei Province, China.

Methods

Participants aged 65 years or older were recruited between 2018 and 2019. Inperson structured interviews and clinical and neuropsychological assessments were performed at city health community centres and township hospitals.

Results

Among 2644 participants without dementia, 735 had MCI, resulting in a prevalence of 27.8% for total MCI, 20.9% for amnestic MCI (aMCI) and 6.9% for non-amnestic MCI (naMCI). The prevalence of MCI in urban and rural areas was 20.2% and 44.1%, respectively. After adjusting for demographic factors, the prevalence of total MCI, aMCI and naMCI differed significantly between rural and urban areas (adjusted odds ratio (OR) 2.10, 1.44 and 3.76, respectively). Subgroup analysis revealed an association between rural socioeconomic and lifestyle disadvantage and MCI and its subtypes.

Conclusions

Our findings suggest that the prevalence of MCI among urban residents in central China is consistent with that in other metropolis areas, such as Shanghai, but the prevalence in rural areas is twice that in urban areas. Prospective studies and dementia prevention in China should focus on rural areas.
Conditioned CAR-T cells by hypoxia-inducible transcription amplification (HiTA) system significantly enhances systemic safety and retains antitumor efficacy
Authors: He Huan , Liao Qibin , Zhao Chen , Zhu Cuisong , Feng Meiqi , Liu Zhuoqun , Jiang Lang , Zhang Linxia , Ding Xiangqing , Yuan Min , Zhang Xiaoyan , Xu Jianqing
Published: October 2022

Background

Hypoxia is a striking feature of most solid tumors and could be used to discriminate tumors from normoxic tissues. Therefore, the design of hypoxia-conditioned Chimeric Antigen Receptor (CAR) T cells is a promising strategy to reduce on-target off-tumor toxicity in adoptive cell therapy. However, existing hypoxia-conditioned CAR-T designs have been only partially successful in enhancing safety profile but accompanied with reduced cytotoxic efficacy. Our goal is to further improve safety profile with retained excellent antitumor efficacy.

Methods

In this study, we designed and constructed a hypoxia-inducible transcription amplification system (HiTA-system) to control the expression of CAR in T (HiTA-CAR-T) cells. CAR expression was determined by Flow cytometry, and the activation and cytotoxicity of HiTA-CAR-T cells in vitro were evaluated in response to antigenic stimulations under hypoxic or normoxic conditions. The safety of HiTA-CAR-T cells was profiled in a mouse model for its on-target toxicity to normal liver and other tissues, and antitumor efficacy in vivo was monitored in murine xenograft models.

Results

Our results showed that HiTA-CAR-T cells are highly restricted to hypoxia for their CAR expression, activation and cytotoxicity to tumor cells in vitro. In a mouse model in vivo, HiTA-CAR-T cells targeting Her2 antigen showed undetectable CAR expression in all different normoxic tissues including human Her2-expresing liver, accordingly, no liver and systemic toxicity were observed; In contrast, regular CAR-T cells targeting Her2 displayed significant toxicity on human Her2-expression liver. Importantly, HiTA-CAR-T cells were able to achieve signiﬁcant tumor suppression in murine xenograft models.

Conclusion

Our HiTA system showed a remarkable improvement in hypoxia-restricted transgene expression in comparison with currently available systems. HiTA-CAR-T cells presented significant antitumor activities in absence of any significant liver or systemic toxicity in vivo. This approach could be also applied to design CAR-T cell targeting other tumor antigens.
High-precision mass measurement of doubly magic $$^{208}$$Pb
Authors: Kromer Kathrin , Lyu Chunhai , Door Menno , Filianin Pavel , Harman Zoltán , Herkenhoff Jost , Huang Wenjia , Keitel Christoph H. , Lange Daniel , Novikov Yuri N. , Schweiger Christoph , Eliseev Sergey , Blaum Klaus
Published: October 2022

The absolute atomic mass of $$^{208}$$

208

Pb has been determined with a fractional uncertainty of $$7\times 10^{-11}$$

7
×

10

-
11

by measuring the cyclotron-frequency ratio R of $$^{208}$$

208

Pb$$^{41+}$$

41
+

to $$^{132}$$

132

Xe$$^{26+}$$

26
+

with the high-precision Penning-trap mass spectrometer Pentatrap and computing the binding energies $$E_{\text {Pb}}$$

E
Pb

and $$E_{\text {Xe}}$$

E
Xe

of the missing 41 and 26 atomic electrons, respectively, with the ab initio fully relativistic multi-configuration Dirac–Hartree–Fock (MCDHF) method. R has been measured with a relative precision of $$9\times 10^{-12}$$

9
×

10

-
12

. $$E_{\text {Pb}}$$

E
Pb

and $$E_{\text {Xe}}$$

E
Xe

have been computed with an uncertainty of 9.1 eV and 2.1 eV, respectively, yielding $$207.976\,650\,571(14)$$

207.976

650

571
(
14
)

 u ($$\text {u}=9.314\,941\,024\,2(28)\times 10^{8}$$

u
=
9.314

941

024

2

(
28
)

×

10
8

 eV/c$$^2$$

2

) for the $$^{208}$$

208

Pb neutral atomic mass. This result agrees within $$1.2\sigma $$

1.2
σ

with that from the Atomic-Mass Evaluation (AME) 2020, while improving the precision by almost two orders of magnitude. The new mass value directly improves the mass precision of 14 nuclides in the region of Z = 81–84 and is the most precise mass value with $$A>200$$

A
>
200

. Thus, the measurement establishes a new region of reference mass values which can be used e.g. for precision mass determination of transuranium nuclides, including the superheavies.
Synchronization in a network of map-based neurons with memristive synapse
Authors: Wang Zhen , Tian Huaigu , Krejcar Ondrej , Namazi Hamidreza
Published: October 2022

The synchronization of coupled neurons has been an important field of study in neuroscience. In this paper, the synchronization in coupled map-based neurons is studied. It is assumed that the neurons are coupled via a memristor. Firstly, the case of two-coupled neurons is investigated, and then two neurons are used as the units of a ring network. It is shown that the memristive coupling coefficient and the initial condition of the flux variable affect the synchronization of two neurons. By increasing the memristive coupling coefficient, multiple synchronous and asynchronous regions are observed. In the ring network, two neurons in each unit can become synchronous, but the whole network does not reach complete synchronization.
Debiased Representation Learning in Recommendation via Information Bottleneck
Authors: Liu Dugang , Cheng Pengxiang , Zhu Hong , Dong Zhenhua , He Xiuqiang , Pan Weike , Ming Zhong
Published: October 2022

How to effectively mitigate the bias of feedback in recommender systems is an important research topic. In this article, we first describe the generation process of the biased and unbiased feedback in recommender systems via two respective causal diagrams, where the difference between them can be regarded as the source of system-induced biases. We then define this difference as a confounding bias and propose a new perspective on debiased representation learning to alleviate it. Specifically, for the case with biased feedback alone, we derive the conditions that need to be satisfied to obtain a debiased representation from the causal diagrams. Then, we propose a novel framework called debiased information bottleneck (DIB) to optimize these conditions and then find a tractable solution for it. The proposed framework constrains the model to learn a biased embedding vector with independent biased and unbiased components in the training phase, and uses only the unbiased component in the test phase to deliver more accurate recommendations. We further propose a variant of DIB by relaxing the independence between the biased and unbiased components. Finally, we conduct extensive experiments on a public dataset and a real product dataset to verify the effectiveness of the proposed framework.
Cost-sensitive Tensor-based Dual-stage Attention LSTM with Feature Selection for Data Center Server Power Forecasting
Authors: Shen Ziyu , Liu Binghui , Zhou Qing , Liu Zheng , Xia Bin , Li Yun
Published: October 2022

Power forecasting has a guiding effect on power-aware scheduling strategies to reduce unnecessary power consumption in data centers. Many metrics related to power consumption can be collected in physical servers, such as the status of CPU, memory, and other components. However, most existing methods empirically exploit a small number of metrics to forecast power consumption. To this end, this article uses feature selection based on causality to explore the metrics that strongly influence the power consumption of different tasks. Moreover, we propose a tensor-based dual-stage attention LSTM to forecast the non-linear and non-periodic power consumption. In the proposed model, a multi-way delay embedding transform is utilized to convert the time series into tensors along the temporal direction. The LSTM combines with the tensor technique and the attention mechanism to capture the temporal pattern effectively. In addition, we adopt the cost-sensitive loss function to optimize the specific power forecasting problem in data centers. The experimental results demonstrate that our method can achieve up to 1.4% to 4.3% forecasting accuracy improvement compared with the state-of-the-art models.
Identification of therapeutic targets in a murine model of severe exertional heat stroke
Authors: Oki Kentaro , Henderson Chloe G. , Ward Shauna M. , Ward Jermaine A. , Plamper Mark L. , Mayer Thomas A. , Caldwell Aaron R. , Leon Lisa R.
Published: October 2022

Exertional heat stroke (EHS) is a potentially lethal condition resulting from high core body temperatures (TC) in combination with a systemic inflammatory response syndrome (SIRS) with varying degrees of severity across victims, and limited understanding of the underlying mechanism(s). We established a mouse model of severe EHS to identify mechanisms of hyperthermia/inflammation that may be responsible for organ damage. Mice were forced to run on a motorized wheel in a 37.5°C chamber until loss of consciousness and were either removed immediately (exertional heat injury or EHI; TCMax = 42.4 ± 0.2°C) or remained in the chamber an additional 20 min (EHS; TCMax = 42.5 ± 0.4°C). Exercise control mice (ExC) experienced identical procedures to EHS at 25°C. At 3 h post-EHS, there was evidence for an immune/inflammatory response as elevated blood chemokine [interferon γ-induced protein 10 (IP-10), keratinocytes-derived chemokine (KC), macrophage inflammatory proteins (MIP-1α), MIP-1β, MIP-2] and cytokine [granulocyte colony-stimulating factor (G-CSF), interleukins (IL-10), IL-6] levels peaked and were highest in EHS mice compared with EHI and ExC mice. Immunoblotting of organs susceptible to EHS damage indicated that several kinases were sensitive to stress associated with heat/inflammation and exercise; specifically, phosphorylation of liver c-Jun NH2-terminal kinase (JNK) at threonine 183/tyrosine 185 immediately (0 h) postheating related to heat illness severity. We have established a mouse EHS model, and JNK [or its downstream target(s)] could underlie EHS symptomatology, allowing the identification of molecular pathways or countermeasure targets to mitigate heat illness severity, enable complete recovery, and decrease overall EHS-related fatalities.
The Effect of an Extract and Fractions of Date Pits on Some Plasma Constituents, Reproductive Hormones, and Testicular Histology in Male Mice
Authors: Al Za’abi Mohammed , Ali Badreldin H. , Ali Haytham , Manoj Priyadarsini , Ashique Mohammed , Nemmar Abderrahim , Cahlíková Lucie
Published: October 2022

Pits of dates (Phoenix dactylifera L.) have numerous nutritional benefits that could have wide-ranging applications. This study aimed to examine the effects of administering three extracts from powdered date pits on some basic physiological parameters, plasma constituents, reproductive hormones, and testicular histology in CD1 male mice. Three groups received doses of 100 mg/kg/day of lyophilized extract, a nonpolar fraction, and a polar fraction of date pits by oral gavage for 28 consecutive days. For the control, one group was administered a 1 mL/kg concentration of distilled water. The three different extracts significantly increased the plasma testosterone level but showed no significant effect on estradiol or luteinizing hormone levels, except for estradiol reduction in the polar extract group. The measured physiological or biochemical parameters or testicular histology also demonstrated no significant differences between the control mice and those mice treated with the three extracts, except for reductions in plasma urea in all extracts and in total protein in the nonpolar extract. Therefore, date pit extracts may potentially be used as a safe and effective dietary supplement. However, further investigation is needed.
A Novel Ensemble Earthquake Prediction Method (EEPM) by Combining Parameters and Precursors
Authors: Mukherjee Sumita , Gupta Prinima , Sagar Pinki , Varshney Neeraj , Chhetri Manoj
Published: October 2022

A leading cause of death from natural disasters over the last 50years is witnessed by none other than earthquake occurrences which have a negative economic impact on the world and claimed thousands of lives over the years, causing devastation to properties. In this paper, a novel Ensemble Earthquake Prediction Method (EEPM) is proposed and implemented to produce a strong learner (ensemble method) having better accuracy in prediction, less variance, and less errors. Data (parameters) which is continuous in nature is collected from two countries, India and Nepal, for five years, and surveyor’s data (precursor) which is categorical in nature is collected from three countries India, Nepal, and Kenya for five years on the specific earthquake-prone regions. The preprocessed data is generated by combining parameters and precursor data. EEPM focuses on detecting the accurate and better early signs of an earthquake and finding the probability of occurrence of an earthquake in the specified region, i.e., better prediction and robustness. The results of EEPM produced better

R

2

and less variance and less error in comparison to individual machine learning methods as well as better accuracy 87.8%, compared to state-of-the-art ensemble methods. The prediction of earthquake will alarm not only the people of the society but also the different organizations to explain the appropriate range of magnitude and dynamics of occurrence of earthquake.
Identification of a New Variant of the MBTPS1 Gene of the Kondo-Fu Type of Spondyloepiphyseal Dysplasia (SEDKF) in a Saudi Patient
Authors: Alotaibi Maha , Aldossari Ali , Khan Imran , Alotaibi Leena
Published: October 2022

Spondyloepiphyseal dysplasia (SEDKF) is a rare skeletal dysplasia associated with kyphosis and low bone mineral density, significantly delayed growth, and skeletal deformities. Blood lysosomal enzyme levels have also been shown to be elevated with a delay in development. The first variant described was compound heterozygosity for mutations in the MBTPS1 gene: a 1-bp duplication and a missense mutation. In the current study, we examined a Saudi consanguineous family. Clinical features like spondyloepiphyseal dysplasia, indicative of characteristic skeletal abnormalities, and impaired cognitive abilities were observed. Our patient has dysmorphic facial features, short stature, and significant skeletal deformities. A homozygous missense MBTPS1 (c.2634C > A p. (Ser878Arg)) with unknown significance was discovered in the whole exome; pathogenic MBTPS1 variants cause the autosomal recessive Kondo-Fu type of spondyloepiphyseal dysplasia (SEDKF, OMIM®: 618392). The whole exome sequence, which described a homozygous missense variant of unknown clinical significance (VUS, class 3 variant) in the MBTPS1 gene, was heterozygous in both asymptomatic parents. We are mindful that changing the classification of a variant of unknown significance is challenging. Considering clinical phenotypes and radiological findings produced by the pathogenic mutation in the MBTPS1 gene, the identified c.2634C > A variant is supported and may be categorized as likely pathogenic based on clinical symptoms.
Downregulation of MCF2L Promoted the Ferroptosis of Hepatocellular Carcinoma Cells through PI3K/mTOR Pathway in a RhoA/Rac1 Dependent Manner
Authors: Huang Si-cong , Chen Yi-mei , Hu Ying-yu , Shi Yong-jie , Xiao Qi-wen , Li Zhe , Kang Jia-le , Zhou Qiang , Shen Gang , Jia Hong-yun
Published: October 2022

Backgound. Multiple patients with hepatocellular carcinoma (HCC) received sorafenib therapy presented primary or secondary chemoresistance. The underlying mechanisms of chemoresistance are rather vague, ferroptosis is a new kind of cell death, and its discovery provides new opportunities to overcome sorafenib resistance. Therefore, it is essential to investigate the regulators of ferroptosis and implement a corresponding therapy strategy. Methods and Results. The levels of MCF2L were detected by PCR and western blotting assay. The effect of MCF2L on ferroptosis was confirmed by MTT, colony formation assay, Brdu, in vivo animal experiment, and the content of Iron, GSH, ROS, and MDA. The underlying mechanisms were explored by PCR, western blotting, and affinity precipitation assay. Our findings demonstrated that MCF2L is remarkedly upregulated in HCC tissues, and sorafenib can induce the levels of MCF2L, suggesting that MCF2L might function in sorafenib resistance of HCC. Further analysis showed that downregulation of MCF2L enhances HCC cell death induced by sorafenib, and ferroptosis inhibitor can reverse this process. Subsequent experiments showed that downregulation of MCF2L elevates the content of Iron, ROS, and MDA, which are all indicators of ferroptosis. Finally, mechanism analysis showed that MCF2L regulates the PI3K/AKT pathway in a RhoA/Rac1 dependent manner. Conclusions. Our study showed that targeting MCF2L may be a hopeful method to overcome sorafenib-resistance through inducing ferroptosis in HCC.
Synthesis and Biological Evaluation of 2,4-Diaminoquinazolines as Potential Antitumor Agents
Authors: Alassaf Mohammad A. , Selim Khalid B. , Nasr Magda N. A.
Published: October 2022

In the present study, a set of 2-anilino-4-alkylaminoquinazoline derivatives were synthesized and tested for their antitumor activities in vitro against a panel of four human cancer cell lines and for their DNA-binding affinity. Among the synthesized compounds, 4c and 5b with 4-substitution at the phenyl ring were found to have the highest inhibitory effects against breast adenocarcinoma (MCF-7), colon cancer (HCT-116), hepatocellular carcinoma (HePG-2), and human skin cancer (HFB4). Further investigation revealed that compounds 4a and 5d exhibited better affinity to bind with DNA than other tested compounds.
An Extragastrointestinal Tumor Diagnosed as a Vaginal Mass during Pregnancy
Authors: Ando Reo , Taniguchi Shuichi , Arita Shuji , Aman Murasaki , Marutsuka Kousuke , Shimamoto Tomihiro
Published: October 2022

We report a case of an extragastrointestinal stromal tumor diagnosed as a vaginal mass during pregnancy. The mass was detected during routine examination at 24 weeks of gestation. At 26 weeks, the patient underwent transvaginal ultrasonography and magnetic resonance imaging, which revealed a blood flow-rich mass of approximately

50
×
30
 
mm

in the rectovaginal septum. At 29 weeks of gestation, we resected the mass vaginally and the pathological diagnosis was a gastrointestinal stromal tumor. Chemotherapy was withheld until after full-term birth because the proliferation index of the tumor cells was low. The patient delivered a healthy infant. Imatinib was commenced at 1 month postpartum, with no recurrence or metastasis after 2.5 years. An extragastrointestinal stromal tumor as a vaginal mass in pregnancy has not been reported; however, our case suggests that the tumor should be considered a differential diagnosis of a vaginal mass in pregnancy.
Using a Pore-Scale Modelling Approach to Study Solute Dilution Process through Cemented Porous Media
Authors: Hou Yusong , Hu Bill X. , Liu Su , Xin Hu , Wu Jichun
Published: October 2022

In this study, a pore-scale simulation method is applied to quantitatively study the variation of solute dilution through porous media with different cementation degrees and explore the corresponding mechanisms. The study results indicated that the cementation degrees of the solid grains had a significant effect on the solute dilution process and that the influence was very complicated. The complexity was manifested in that the effect of rising cementation degree on the solute dilution process would be different or even completely opposite in the porous media in which the solid grains cement slightly with that in porous media with a higher cementation degree. For example, for the porous media in which the solid grains were slightly cemented (the percentage of the cemented solid grains

P

c

is less than 40%), the dilution effects became enhanced with the increase of cementation degree. Then, after

P

c

increased to about 55%, the dilution effect was obviously weakened, and the solute was in an incomplete dilution state for a long period of time. In addition, this study found that the properties of the flow fields may vary greatly in porous media with different cementation degrees and that those differences in the flow fields resulted in the distinct behavior of the solute dilution. It is interesting to note that a more heterogeneous flow field had not necessarily led to the enhancement of the dilution process.
Pharmacological Landscape of FDA-Approved Anticancer Drugs Reveals Sensitivities to Ixabepilone, Romidepsin, Omacetaxine, and Carfilzomib in Aggressive Meningiomas
Authors: Jungwirth Gerhard , Yu Tao , Liu Fang , Cao Junguo , Alaa Eddine Montadar , Moustafa Mahmoud , Abdollahi Amir , Warta Rolf , Unterberg Andreas , Herold-Mende Christel
Published: October 2022

Purpose:

To date, there are no systemic treatment options for patients with recurrent or refractory meningioma.

Experimental Design:

To identify effective drugs, we performed a large-scale drug screening using FDA-approved drugs on several meningioma cell lines. The impact of the top four compounds was assessed on cell viability, proliferation, colony formation, migration, and apoptosis. In addition, the antineoplastic effects of the selected drugs were validated in a heterotopic xenograft mouse model.

Results:

Analyses of the viability of meningioma cells treated with 119 antineoplastic FDA-approved drugs resulted in categorization into sensitive and resistant drug–response groups based on the mean IC50 values and peak serum concentrations (Cmax) in patients. Eighty drugs, including 15 alkylating agents, 14 antimetabolites, and 13 tyrosine kinase inhibitors, were classified as resistant (IC50 > Cmax). The sensitive drug–response group (n = 29, IC50 < Cmax) included RNA/protein synthesis inhibitors, proteasome inhibitors, topoisomerase, tyrosine-kinase, and partial histone deacetylase and microtubule inhibitors. The IC50 value of the four most effective compounds (carfilzomib, omacetaxine, ixabepilone, and romidepsin) ranged from 0.12 to 9.5 nmol/L. Most of them caused cell-cycle arrest in the G2–M-phase and induced apoptosis. Furthermore, all drugs except romidepsin significantly inhibited tumor growth in vivo. The strongest antineoplastic effect was observed for ixabepilone, which reduced tumor volume by 86%.

Conclusions:

In summary, a large-scale drug screening provides a comprehensive insight into the anti-meningioma activities of FDA-approved drugs, and identified carfilzomib, omacetaxine, ixabepilone, and romidepsin as novel potent antineoplastic agents for the treatment of aggressive meningiomas. The most pronounced effects were observed with ixabepilone mandating for further clinical investigation.
Prediction of recovery energy from ultimate analysis of waste generation in Depok City, Indonesia
Authors: Muitiara Sari Mega , Septiariva Iva Yenis , Fauziah Eva Nur , Ummatin Kuntum Khoiro , Arifianti Qurrotin Ayunina Maulida Okta , Faria Niswatun , Lim Jun-Wei , Suryawan I Wayan Koko
Published: October 2022

Refuse derived fuel (RDF) is an environmentally friendly renewable fuel developed to reduce waste generation. RDF can consist of various kinds of waste such as paper and gardens. One of the critical parameters is the chemical element and calorific value. The purpose of this study was to determine the potential for waste reduction and the relationship of ultimate longevity in RDF to the calorific value. This study's paper and garden waste mixture were P0 (100% paper), P25 (75% paper and 25% garden), P50 (50% paper and 50% garden), P75 (25% paper and 75% garden), and P100 (100% garden). The calorific value of the mixture can reach 3.6-5.2 kWh/kg. Simultaneously the relationship of ultimate elements nitrogen (N), hydrogen (H), oxygen (O), and ash affects the heating value of RDF. Sampling the application in Depok City can reduce waste by 6.67%, with the potential for electrical energy from paper and garden wastes of 358,903.8 kWh and 48,681 kWh, respectively. This shows that this energy waste can supply 0.1% of the total daily electricity demand in Depok City.
Matching data detection for the integration system
Authors: El Abassi Merieme , Amnai Mohamed , Choukri Ali , Fakhri Youssef , Gherabi Noreddine
Published: October 2022

The purpose of data integration is to integrate the multiple sources of heterogeneous data available on the internet, such as text, image, and video. After this stage, the data becomes large. Therefore, it is necessary to analyze the data that can be used for the efficient execution of the query. However, we have problems with solving entities, so it is necessary to use different techniques to analyze and verify the data quality in order to obtain good data management. Then, when we have a single database, we call this mechanism deduplication. To solve the problems above, we propose in this article a method to calculate the similarity between the potential duplicate data. This solution is based on graphics technology to narrow the search field for similar features. Then, a composite mechanism is used to locate the most similar records in our database to improve the quality of the data to make good decisions from heterogeneous sources.
An efficient stacking based NSGA-II approach for predicting type 2 diabetes
Authors: Patil Ratna Nitin , Rawandale Shitalkumar , Rawandale Nirmalkumar , Rawandale Ujjwala , Patil Shrishti
Published: October 2022

Diabetes has been acknowledged as a well-known risk factor for renal and cardiovascular disorders, cardiac stroke and leads to a lot of morbidity in the society. Reducing the disease prevalence in the community will provide substantial benefits to the community and lessen the burden on the public health care system. So far, to detect the disease innumerable data mining approaches have been used. These days, incorporation of machine learning is conducive for the construction of a faster, accurate and reliable model. Several methods based on ensemble classifiers are being used by researchers for the prediction of diabetes. The proposed framework of prediction of diabetes mellitus employs an approach called stacking based ensemble using non-dominated sorting genetic algorithm (NSGA-II) scheme. The primary objective of the work is to develop a more accurate prediction model that reduces the lead time i.e., the time between the onset of diabetes and clinical diagnosis. Proposed NSGA-II stacking approach has been compared with Boosting, Bagging, Random Forest and Random Subspace method. The performance of Stacking approach has eclipsed the other conventional ensemble methods. It has been noted that k-nearest neighbors (KNN) gives a better performance over decision tree as a stacking combiner.
Source-load-variable voltage regulated cascaded DC/DC converter for a DC microgrid system
Authors: Salyam Radhika , Margaret Vijaya
Published: October 2022

Solar energy is available abundantly, the utilization of solar energy is developing rapidly and the photovoltaic based direct current (DC) microgrid system design is under demand but the stability of the DC voltage is of most important issue, as the variation of the output DC voltage is a common problem when the load or source voltage varies, hence a regulated DC output voltage converter is proposed. This paper presents source-load-variable (SLV) voltage regulated cascaded DC/DC converter which is used to obtain regulated output voltage of 203.1 V DC at 0.4 duty ratio with ±2% voltage fluctuations for the variation in the input source voltage and ±1.5% voltage fluctuations for the variation in load resistance of the nominal value with lower output voltage ripple and without use of sub circuits. A simulation model of SLV voltage regulated cascaded DC/DC converter in LTspice XVII software environment for the assessment of converter performance at different input source voltages and load resistances are verified.
Synonym based feature expansion for Indonesian hate speech detection
Authors: Ghozali Imam , Sungkono Kelly Rossa , Sarno Riyanarto , Abdullah Rachmad
Published: October 2022

Online hate speech is one of the negative impacts of internet-based social media development. Hate speech occurs due to a lack of public understanding of criticism and hate speech. The Indonesian government has regulations regarding hate speech, and most of the existing research about hate speech only focuses on feature extraction and classification methods. Therefore, this paper proposes methods to identify hate speech before a crime occurs. This paper presents an approach to detect hate speech by expanding synonyms in word embedding and shows the classification comparison result between Word2Vec and FastText with bidirectional long short-term memory which are processed using synonym expanding process and without it. The goal is to classify hate speech and non-hate speech. The best accuracy result without the synonym expanding process is 0.90, and the expanding synonym process is 0.93.
Deep learning algorithms for intrusion detection systems in internet of things using CIC-IDS 2017 dataset
Authors: Jose Jinsi , Jose Deepa V.
Published: October 2022

Due to technological advancements in recent years, the availability and usage of smart electronic gadgets have drastically increased. Adoption of these smart devices for a variety of applications in our day-to-day life has become a new normal. As these devices collect and store data, which is of prime importance, securing is a mandatory requirement by being vigilant against intruders. Many traditional techniques are prevailing for the same, but they may not be a good solution for the devices with resource constraints. The impact of artificial intelligence is not negligible in this concern. This study is an attempt to understand and analyze the performance of deep learning algorithms in intrusion detection. A comparative analysis of the performance of deep neural network, convolutional neural network, and long short-term memory using the CIC-IDS 2017 dataset.
Real-time wireless temperature measurement system of infant incubator
Authors: Sukma Irawan , Ardiatna Wuwus , Novitasari Novitasari , Permatasari Vera , Hidayat Siddiq Wahyu , Hidayat Asep Rahmat , Khotimah Khusnul , Supono Ihsan
Published: October 2022

The internet of things (IoT) has allowed for ubiquitous measurement. Infant incubator temperature is one of crucial parts that need to be measured, especially for the stability and uniformity temperature. Based on the interpretation of IEC 60601-2-19, we proposed measurement method using IoT with the message queue telemetry transport (MQTT). In the 10,000 packet, the result shows the quality of service (QoS) level 2 of the system has the highest delay, however it has the lowest packet loss data than the other QoS. For 1 hour, the uniformity result and stability can fulfill the standards. Uniformity of 32°C, the lowest difference is point C with 0.32 °C, and the highest difference is point B with 0.75 °C. Uniformity of 36 °C, the lowest difference is point B with 0.27 °C, and the highest difference is point C with 0.79 °C. The stability of 32 °C and 36 °C is 0.32 °C and 0.44 °C, respectively. Moreover, the Kruskal Wallis test shows the highest difference average from point M is point A and B. It occurred because of the point A and B located far from the heater part, so the point A and B colder than point C.