bluuebunny/crossref_metadata_2025 huggingface dataset:
A Fractional Grey Multivariable Model for Modeling Fresh Graduates’ Career Choice
Authors: Yang Xiaoen , Cui Taiming , Shou Minghuan
Published: July 2021

Aiming at exploring the effect of four factors on fresh graduate’s three popular career choices of continuing studying, working in state-owned enterprises, and working in private enterprises, this paper collects the specific information of 3237 students and builds the GM (0, N) model. The four variables include student’s grade point average (GPA), socioeconomic status (SES), gender, and whether the student comes from an urban household. Furthermore, this paper also considers the effect of the fractional order and proposes a fractional grey model (FGM (0, N) model) to enhance the performance of the traditional model. Eventually, the study finds that there are still some students with financial problems, which makes some negative effects on their choices of continuing studying and working in state-owned enterprises. Additionally, all the other three factors show the positive influence on the three choices. Besides, GPA shows the most positive effect on the choices of continuing studying as well as working in a state-owned enterprise; gender and SES have the greatest impact on the choice of working in a private enterprise.
Network Pharmacology-Based Mechanistic Investigation of Jinshui Huanxian Formula Acting on Idiopathic Pulmonary Fibrosis
Authors: Liu Tiantian , Xu Pengli , Qi Shuishui , Ke Shaorui , Hu Qin , Zhao Peng , Li Jiansheng
Published: July 2021

Idiopathic pulmonary fibrosis (IPF) is a chronic respiratory disease with high incidence, morbidity, and mortality rates. Jinshui Huanxian formula (JHF) is an empirical formula that targets the pathogenesis of lung-kidney qi deficiency and phlegm-blood stasis in pulmonary fibrosis (PF). The purpose of this study was to explore JHF’s potential pharmacological mechanisms in IPF therapy using network intersection analysis. JHF’s primary active components and corresponding target genes were predicted using various databases. Two sets of IPF disease genes were obtained from the DisGeNET and GEO databases and two sets of IPF drug targets were collected. The disease and drug target genes were analyzed. The JHF target genes that intersected with IPF’s differentially expressed genes were identified to predict JHF’s targets of action in IPF. The functions and pathways of predicted targets acting on IPF were analyzed using the DAVID and KEGG pathway databases. Finally, the resulting drug target mechanisms were validated in a rat model of PF. The initial analyses identified 494 active compounds and 1,304 corresponding targets for JHF. The intersection analysis revealed four common genes for the JHF targets, IPF disease, and anti-IPF drugs in the KEGG database. Furthermore, these genes were targeted by several JHF compounds. Seventy-two JHF targets were closely related to IPF, which suggests that they are therapeutically relevant. Target screening revealed that they regulate IPF through 18 pathways. The targets’ molecular functions included regulation of oxidoreductase activity, kinase regulator activity, phosphotransferase activity, and transmembrane receptor protein kinase activity. In vivo experiments showed that JHF alleviated the degree of PF, including decreases in collagen deposition and epithelial-mesenchymal transition. This study systematically explored JHF’s mechanisms to identify the specific target pathways involved in IPF. The generated pharmacological network, paired with in vivo validation, elucidates the potential roles and mechanisms of JHF in IPF therapy.
Research on World Food Production Efficiency and Environmental Sustainability Based on Entropy‐DEA Model
Authors: Zhang Min , Cui Wen-Kai , Zhang Yu-Jing , Xu Yun-Hua
Published: July 2021

At present, the contradiction between the high efficiency of the world’s food production and environmental pollution is becoming increasingly prominent. In order to study the related issues of the world’s food production efficiency and sustainability, this paper uses the method of entropy weight to extract 5 indicators as the environmental pollution assessment model from the environmental pollution of agricultural production, scores 10 major agricultural production countries in the world, and obtains the environmental pollution index. Subsequently, the DEA model was established for these countries, the environmental pollution index was included into the production efficiency system as an unexpected output, the Malmquist index was established to describe the changes in agricultural production efficiency from 2010 to 2018, and the cluster analysis was carried out for it. Subsequently, the OSL and Tobit models were used for regression of the influencing factors. In addition, the comprehensive evaluation model of efficiency and sustainability was established by controlling the amount of fertilizer used, which was applied in different countries.
A Novel User Collusion‐Resistant Decentralized Multi‐Authority Attribute‐Based Encryption Scheme Using the Deposit on a Blockchain
Authors: Noh Siwan , Kim Donghyun , Cai Zhipeng , Rhee Kyung-Hyune
Published: July 2021

Recently, the concept of a decentralized data marketplace is getting much attention to exchange user data. Multi‐authority attribute‐based encryption (ABE), which can provide flexibility and user‐centric access control, is previously widely used in decentralized data sharing applications and also becoming a foundation to build decentralized data trading applications. It is known that users in a multi‐authority ABE system can collude by sharing their secret information for malicious purposes. To address this issue, the collusion‐resistant multi‐authority ABE model was introduced in which a unique global identifier (GID) is issued by the central authority (CA) to each user. Unfortunately, such approach cannot be used directly to build a decentralized data marketplace as (a) such intervention of the CA is directly against the main motivation of the decentralized trading platform and, mostly importantly, (b) the CA can exploit its full knowledge on users’ GID to launch various attacks against users. Motivated by these observations, this paper introduces a novel user collusion‐resistant decentralized multi‐authority ABE scheme for privacy preserving data trading systems. In the existing multi‐authority ABE systems, users utilize his/her GID that is solely assigned by the CA to generate his/her secret keys throughout the collaboration with authorities and a user can compute multi‐authority keys by combining the secret keys (stem from the same GID) in various ways. In the proposed system, the CA only has a partial knowledge of users’ GIDs, and thus, users’ privacy can be protected. On the other hand, we set the user’s own partial GID as a secret which can be used to withdraw his/her deposit to discourage any possible collusion among users.
Interruption Risk Assessment and Transmission of Fresh Cold Chain Network Based on a Fuzzy Bayesian Network
Authors: Chen Huanwan , Zhang Qingnian , Luo Jing , Zhang Xiuxia , Chen Guopeng
Published: July 2021

The fresh cold chain network is complex, and the interruption risk can significantly impact it. Based on the Bayesian theory, we constructed a fresh cold chain network interruption risk topology structure. The probability of each root node was predicted and calculated based on the fuzzy set theory. The evaluation model was then validated and improved through the virus transmission model based on risk transmission. Sensitivity analysis was used to determine significant risk factors. Several strategies for minimizing interruption risks were identified.
[Retracted] Identifying COVID‐19‐Specific Transcriptomic Biomarkers with Machine Learning Methods
Authors: Chen Lei , Li Zhandong , Zeng Tao , Zhang Yu-Hang , Feng KaiYan , Huang Tao , Cai Yu-Dong
Published: July 2021

COVID‐19, a severe respiratory disease caused by a new type of coronavirus SARS‐CoV‐2, has been spreading all over the world. Patients infected with SARS‐CoV‐2 may have no pathogenic symptoms, i.e., presymptomatic patients and asymptomatic patients. Both patients could further spread the virus to other susceptible people, thereby making the control of COVID‐19 difficult. The two major challenges for COVID‐19 diagnosis at present are as follows: (1) patients could share similar symptoms with other respiratory infections, and (2) patients may not have any symptoms but could still spread the virus. Therefore, new biomarkers at different omics levels are required for the large‐scale screening and diagnosis of COVID‐19. Although some initial analyses could identify a group of candidate gene biomarkers for COVID‐19, the previous work still could not identify biomarkers capable for clinical use in COVID‐19, which requires disease‐specific diagnosis compared with other multiple infectious diseases. As an extension of the previous study, optimized machine learning models were applied in the present study to identify some specific qualitative host biomarkers associated with COVID‐19 infection on the basis of a publicly released transcriptomic dataset, which included healthy controls and patients with bacterial infection, influenza, COVID‐19, and other kinds of coronavirus. This dataset was first analysed by Boruta, Max‐Relevance and Min‐Redundancy feature selection methods one by one, resulting in a feature list. This list was fed into the incremental feature selection method, incorporating one of the classification algorithms to extract essential biomarkers and build efficient classifiers and classification rules. The capacity of these findings to distinguish COVID‐19 with other similar respiratory infectious diseases at the transcriptomic level was also validated, which may improve the efficacy and accuracy of COVID‐19 diagnosis.
Head and Neck Cancer Cell Death due to Mitochondrial Damage Induced by Reactive Oxygen Species from Nonthermal Plasma‐Activated Media: Based on Transcriptomic Analysis
Authors: Oh Chan , Won Ho-Ryun , Kang Woo Seok , Kim Dae-Woong , Jung Seung-Nam , Im Mi Ae , Liu Lihua , Jin Yan Li , Piao Yudan , Kim Hae Jong , Kang Yea Eun , Lee Min Joung , Heo Jun Young , Jun Sangmi , Sim Nam Suk , Lee Jeong Ho , Song Kunho , Kim Young Il , Chang Jae Won , Koo Bon Seok
Published: July 2021

Mitochondrial targeted therapy is a next‐generation therapeutic approach for cancer that is refractory to conventional treatments. Mitochondrial damage caused by the excessive accumulation of reactive oxygen species (ROS) is a principle of mitochondrial targeted therapy. ROS in nonthermal plasma‐activated media (NTPAM) are known to mediate anticancer effects in various cancers including head and neck cancer (HNC). However, the signaling mechanism of HNC cell death via NTPAM‐induced ROS has not been fully elucidated. This study evaluated the anticancer effects of NTPAM in HNC and investigated the mechanism using transcriptomic analysis. The viability of HNC cells decreased after NTPAM treatment due to enhanced apoptosis. A human fibroblast cell line and three HNC cell lines were profiled by RNA sequencing. In total, 1 610 differentially expressed genes were identified. Pathway analysis showed that activating transcription factor 4 (ATF4) and C/EBP homologous protein (CHOP) were upstream regulators. Mitochondrial damage was induced by NTPAM, which was associated with enhancements of mitochondrial ROS (mtROS) and ATF4/CHOP regulation. These results suggest that NTPAM induces HNC cell death through the upregulation of ATF4/CHOP activity by damaging mitochondria via excessive mtROS accumulation, similar to mitochondrial targeted therapy.
Simultaneous Determination of 78 Compounds of Rhodiola rosea Extract by Supercritical CO2-Extraction and HPLC-ESI-MS/MS Spectrometry
Authors: Zakharenko Alexander M. , Razgonova Mayya P. , Pikula Konstantin S. , Golokhvast Kirill S.
Published: July 2021

The plant Rhodiola rosea L. of family Crassulaceae was extracted using the supercritical CO2-extraction method. Several experimental conditions were investigated in the pressure range of 200–500 bar, with the used volume of cosolvent ethanol in the amount of 1% in the liquid phase at a temperature in the range of 31–70°C. The most effective extraction conditions are pressure 350 bar and temperature 60°C. The extracts were analyzed by HPLC with MS/MS identification. 78 target analytes were isolated from Rhodiola rosea (Russia) using a series of column chromatography and mass spectrometry experiments. The results of the analysis showed a spectrum of the main active ingredients Rh. rosea: salidroside, rhodiolosides (B and C), rhodiosin, luteolin, catechin, quercetin, quercitrin, herbacetin, sacranoside A, vimalin, and others. In addition to the reported metabolites, 29 metabolites were newly annotated in Rh. rosea. There were flavonols: dihydroquercetin, acacetin, mearnsetin, and taxifolin-O-pentoside; flavones: apigenin-O-hexoside derivative, tricetin trimethyl ether 7-O-hexosyl-hexoside, tricin 7-O-glucoronyl-O-hexoside, tricin O-pentoside, and tricin-O-dihexoside; flavanones: eriodictyol-7-O-glucoside; flavan-3-ols: gallocatechin, hydroxycinnamic acid caffeoylmalic acid, and di-O-caffeoylquinic acid; coumarins: esculetin; esculin: fraxin; and lignans: hinokinin, pinoresinol, L-ascorbic acid, glucaric acid, palmitic acid, and linolenic acid. The results of supercritical CO2-extraction from roots and rhizomes of Rh. rosea, in particular, indicate that the extract contained all biologically active components of the plant, as well as inert mixtures of extracted compositions.
Response of Crop Water Requirement and Yield of Irrigated Rice to Elevated Temperature in Bangladesh
Authors: Hossain Md. Belal , Roy Debjit , Maniruzzaman Md. , Biswas Jatish Chandra , Naher Umme Aminun , Haque Md. Mozammel , Kalra Naveen
Published: July 2021

In the changing climatic condition, temperature is the most vulnerable parameter and is projecting a trend of increase in the future. Crop growth and development process depend largely on air temperature. This study aims to determine the role of increasing air temperature in yield, crop water requirement (CWR), and other agronomic parameters of irrigated rice. Ceres-rice model associated in the Decision Support System for Agrotechnology Transfer (DSSAT) was used in 15 different locations of Bangladesh. Grain yield, growth duration, and crop water requirement of widely cultivated irrigated rice (Boro rice) variety BRRI dhan28 were analysed in normal temperature and elevated air temperature by 1°C, 2°C, 3°C, and 4°C. The result revealed detrimental effect of elevated temperature on growth duration and grain yield. The estimated highest growth duration reduction of 30 days was found in Moulvibazar for 4°C temperature rise. The grain yield reduction was projected by 0–17%, 16–35%, 31–49%, and 39–61% from the normal condition if the seasonal mean temperature increased by 1°C, 2°C, 3°C, and 4°C, respectively. The country average crop water requirement was found to be 405 mm of which the highest 445 mm and the lowest 358 mm were recorded in Moulvibazar and Chandpur, respectively. The study revealed that the country average rice CWR reduced by 5%, 8%, 12%, and 17% over the normal condition for 1°C, 2°C, 3°C, and 4°C rising temperature, respectively. For 1°C temperature rise, BRRI dhan28 life span shortened by 6.4 days, grain yield reduced by 695 kg, and estimated CWR decreased by 14 mm. The projected declining CWR indicated that irrigated rice will require less irrigation water, but it will cause considerable yield loss under elevated temperature. Though elevated temperature will save huge irrigation water used in country-wide Boro rice cultivation, the crop developers need to introduce new heat-tolerant cultivar to minimize yield loss.
Vibration Attenuation Investigations on a Distributed Phononic Crystals Beam for Rubber Concrete Structures
Authors: Li Chao , Zhang Sifeng , Gao Liyong , Huang Wei , Liu Zhaoxin
Published: July 2021

Locally resonant phononic crystals (LRPCs) beam is characterized by the band gaps; some frequency ranges within which flexural waves cannot propagate freely. So, the LRPCs beam can be used for noise or vibration isolation. In this paper, a LRPCs beam with distributed oscillators is proposed, and the general formula of band gaps and transmission spectrum are derived by the transfer matrix method (TMM) and spectrum element method (SEM). Subsequently, the parameter effects on band gaps are investigated in detail. Finally, a rubber concrete beam is designed to demonstrate the application of distributed LRPCs beam in civil engineering. Results reveal that the distributed LRPCs beam has multifrequency band gaps and the number of the band gaps is equal to that of the oscillators. Compared with others, the distributed LRPCs beam can reduce the stress concentration when subjected to vibration. The oscillator interval has no effect on the band gaps, which makes it more convenient to design structures. Individual changes of oscillator mass or stiffness affect the band gap location and width. When the resonance frequency of oscillator is fixed, the starting frequency of the band gap remains constant, and increasing oscillator mass of high-frequency band gap widens the high-frequency band gap, while increasing oscillator mass of low-frequency gap widens both high-frequency and low-frequency band gaps. External loads, such as the common uniform spring force provided by foundation in civil engineering, are conducive to the band gap, and when the spring force increases, all the band gaps are widened. Taken together, a configuration of LRPCs rubber concrete beam is designed, and it shows good isolation on the vibration induced by the railway. By the presented design flow chart, the research can serve as a reference for vibration isolation of LRPCs beams in civil engineering.
Rapamycin Pretreatment Rescues the Bone Marrow AML Cell Elimination Capacity of CAR-T Cells
Authors: Nian Zhigang , Zheng Xiaohu , Dou Yingchao , Du Xianghui , Zhou Li , Fu Binqing , Sun Rui , Tian Zhigang , Wei Haiming
Published: July 2021

Purpose:

Ongoing clinical trials show limited efficacy for Chimeric antigen receptor (CAR) T treatment for acute myeloid leukemia (AML). The aim of this study was to identify potential causes of the reported limited efficacy from CAR-T therapies against AML.

Experimental Design:

We generated CAR-T cells targeting Epithelial cell adhesion molecule (EpCAM) and evaluated their killing activity against AML cells. We examined the impacts of modulating mTORC1 and mTORC2 signaling in CAR-T cells in terms of CXCR4 levels. We examined the effects of a rapamycin pretreatment of EpCAM CAR-T cells (during ex vivo expansion) and assessed the in vivo antitumor efficacy of rapamycin-pretreated EpCAM CAR-T cells (including CXCR4 knockdown cells) and CD33 CAR-T cells in leukemia xenograft mouse models.

Results:

EpCAM CAR-T exhibited killing activity against AML cells but failed to eliminate AML cells in bone marrow. Subsequent investigations revealed that aberrantly activated mTORC1 signaling in CAR-T cells results in decreased bone marrow infiltration and decreased the levels of the rapamycin target CXCR4. Attenuating mTORC1 activity with the rapamycin pretreatment increased the capacity of CAR-T cells to infiltrate bone marrow and enhanced the extent of bone marrow AML cell elimination in leukemia xenograft mouse models. CXCR4 knockdown experiments showed that CXCR4 contributes to the enhanced bone marrow infiltration capacity of EpCAM CAR-T cells and the observed reduction in bone marrow AML cells.

Conclusions:

Our study reveals a potential cause for the limited efficacy of CAR-T reported from current AML clinical trials and illustrates an easy-to-implement pretreatment strategy, which enhances the anti-AML efficacy of CAR-T cells.

See related commentary by Maiti and Daver, p. 5739
Pharmacologic Targeting of Mcl-1 Induces Mitochondrial Dysfunction and Apoptosis in B-Cell Lymphoma Cells in a TP53- and BAX-Dependent Manner
Authors: Liu Tingting , Lam Vi , Thieme Elana , Sun Duanchen , Wang Xiaoguang , Xu Fei , Wang Lili , Danilova Olga V. , Xia Zheng , Tyner Jeffrey W. , Kurtz Stephen E. , Danilov Alexey V.
Published: July 2021

Purpose:

Bcl-2 has been effectively targeted in lymphoid malignancies. However, resistance is inevitable, and novel approaches to target mitochondrial apoptosis are necessary. AZD5991, a selective BH3-mimetic in clinical trials, inhibits Mcl-1 with high potency.

Experimental Design:

We explored the preclinical activity of AZD5991 in diffuse large B-cell lymphoma (DLBCL) and ibrutinib-resistant mantle cell lymphoma (MCL) cell lines, MCL patient samples, and mice bearing DLBCL and MCL xenografts using flow cytometry, immunoblotting, and Seahorse respirometry assay. Cas9 gene editing and ex vivo functional drug screen assays helped identify mechanisms of resistance to Mcl-1 inhibition.

Results:

Mcl-1 was expressed in DLBCL and MCL cell lines and primary tumors. Treatment with AZD5991 restricted growth of DLBCL cells independent of cell of origin and overcame ibrutinib resistance in MCL cells. Mcl-1 inhibition led to mitochondrial dysfunction as manifested by mitochondrial membrane depolarization, decreased mitochondrial mass, and induction of mitophagy. This was accompanied by impairment of oxidative phosphorylation. TP53 and BAX were essential for sensitivity to Mcl-1, and oxidative phosphorylation was implicated in resistance to Mcl-1 inhibition. Induction of prosurvival proteins (e.g., Bcl-xL) in stromal conditions that mimic the tumor microenvironment rendered protection of primary MCL cells from Mcl-1 inhibition, while BH3-mimetics targeting Bcl-2/xL sensitized lymphoid cells to AZD5991. Treatment with AZD5991 reduced tumor growth in murine lymphoma models and prolonged survival of MCL PDX mice.

Conclusions:

Selective targeting Mcl-1 is a promising therapeutic approach in lymphoid malignancies. TP53 apoptotic network and metabolic reprogramming underlie susceptibility to Mcl-1 inhibition.
Volume Balance in Chronic Kidney Disease: Evaluation Methodologies and Innovation Opportunities
Authors: La Porta Edoardo , Lanino Luca , Calatroni Marta , Caramella Elena , Avella Alessandro , Quinn Caroline , Faragli Alessandro , Estienne Luca , Alogna Alessio , Esposito Pasquale
Published: July 2021

Background: Patients affected by chronic kidney disease are at a risk of cardiovascular morbidity and mortality. Body fluids unbalance is one of the main characteristics of this condition, as fluid overload is highly prevalent in patients affected by the cardiorenal syndrome. Summary: We describe the state of the art and new insights into body volume evaluation. The mechanisms behind fluid balance are often complex, mainly because of the interplay of multiple regulatory systems. Consequently, its management may be challenging in clinical practice and even more so out-of-hospital. Availability of novel technologies offer new opportunities to improve the quality of care and patients’ outcome. Development and validation of new technologies could provide new tools to reduce costs for the healthcare system, promote personalized medicine, and boost home care. Due to the current COVID-19 pandemic, a proper monitoring of chronic patients suffering from fluid unbalances is extremely relevant. Key Message: We discuss the main mechanisms responsible for fluid overload in different clinical contexts, including hemodialysis, peritoneal dialysis, and heart failure, emphasizing the potential impact provided by the implementation of the new technologies.
Betahistine in Ménière’s Disease or Syndrome: A Systematic Review
Authors: Van Esch Babette , van der Zaag-Loonen Hester , Bruintjes Tjasse , van Benthem Peter Paul
Published: July 2021

Background: Ménière’s disease is characterized by recurrent episodes of vertigo, hearing loss, and tinnitus, often with a feeling of fullness in the ear. Although betahistine is thought to be specifically effective for Ménière’s disease, no evidence for a benefit from the use of betahistine exists, despite its widespread use. Reassessment of the effect of betahistine for Ménière’s disease is now warranted. Search Methods: We searched for randomized controlled trials (RCTs) in the Central Register of Controlled Trials (CENTRAL), Ovid Medline, Ovid Embase, CINAHL, Web of Science, Clinicaltrials.gov, ICTRP, and additional sources for published and unpublished trials, in which betahistine was compared to placebo. Data Collection and Analysis: Our outcomes involved vertigo, significant adverse effect (upper gastrointestinal discomfort), hearing loss, tinnitus, aural fullness, other adverse effects, and disease-specific health-related quality of life. We used GRADE to assess the quality of the evidence. Main Results: We included 10 studies: 5 studies used a crossover design and the remaining 5 were parallel-group RCTs. One study with a low risk of bias found no significant difference between the betahistine groups and placebo with respect to vertigo after a long-term follow-up period. No significant difference in the incidence of upper gastrointestinal discomfort was found in 2 studies (low-certainty evidence). No differences in hearing loss, tinnitus, or well-being and disease-specific health-related quality of life were found (low- to very low-certainty of evidence). Data on aural fullness could not be extracted. No significant difference between the betahistine and the placebo groups (low-certainty evidence) could be demonstrated in the other adverse effect outcome with respect to dull headache. The pooled risk ratio for other adverse effect in the long term demonstrated a lower risk in favor of placebo over betahistine. Conclusions: High-quality studies evaluating the effect of betahistine on patients with Ménière’s disease are lacking. However, one study with low risk of bias found no evidence of a difference in the effect of betahistine on the primary outcome, vertigo, in patients with Ménière’s disease when compared to placebo. The main focus of future research should be on the use of comparable outcome measures by means of patient-reported outcome measures.
A new look on performance of small-cell network with design of multiple antennas and full-duplex
Authors: Le Chi-Bao , Do Dinh-Thuan
Published: July 2021

A downlink of small-cell network is studied in this paper studies in term of outage performance. We beneﬁt by design of multiple antennas at the base station and fullduplex transmission mode. The scenario of multiple surrounded small-cell networks is considered to look the impact of interference. We derive the closed-form expression of outage probability to show performance of mobile user. We investigate target rate is main factor affecting to outage performance. According to the considered system, simulation results indicate reasonable value of outage probability and throughput as well. Finally, Monte-Carlo simulation method is deployed to determine exactness of main results found in this article. Finally, the considered system can exhibit improved performance if controlling interference term.
Electricity-theft detection in smart grids based on deep learning
Authors: Ibrahim Noor Mahmoud , Al-Janabi Sufyan T. Faraj , Al-Khateeb Belal
Published: July 2021

lectricity theft is a major concern for utilities. The smart grid (SG) infrastructure generates a massive amount of data, including the power consumption of individual users. Utilizing this data, machine learning, and deep learning techniques can accurately identify electricity theft users. A convolutional neural network (CNN) model for automatic electricity theft detection is presented. This work considers experimentation to find the best configuration of the sequential model (SM) for classifying and identifying electricity theft. The best performance has been obtained in two layers with the first layer consists of 128 nodes and the second layer is 64 nodes. The accuracy reached up to 0.92. This enables the design of high-performance electricity signal classifiers that can be used in several applications. Designing electricity signals classifiers has been achieved using a CNN and the data extracted from the electricity consumption dataset using an SM. In addition, the blue monkey (BM) algorithm is used to reduce the features in the dataset. In this respect, the focusing of this work is to reduce the features in the dataset to obtain high-performance electricity signals classifier models.
Spoken language identification using i-vectors, x-vectors, PLDA and logistic regression
Authors: Abdurrahman Ahmad Iqbal , Zahra Amalia
Published: July 2021

In this paper, i-vector and x-vector is used to extract the features from speech signal from local Indonesia languages, namely Javanese, Sundanese and Minang languages to help classifier identify the language spoken by the speaker. Probabilistic linear discriminant analysis (PLDA) are used as the baseline classifier and logistic regression technique are used because of prior studies showing logistic regression has better performance than PLDA for classifying speech data. Once these features are extracted. The feature is going to be classified using the classifier mentioned before. In the experiment, we tried to segment the test data to three segment such as 3, 10, and 30 seconds. This study is expanded by testing multiple parameters on the i-vector and x-vector method then comparing PLDA and logistic regression performance as its classifier. The x-vector has better score than i-vector for every segmented data while using PLDA as its classifier, except where the i-vector and x-vector is using logistic regression, i-vector still has better accuracy compared to x-vector.
Delta-sigma ADC modulator for multibit data converters using passive adder entrenched second order noise shaping
Authors: Nahar Ali Kareem , Khleaf Hussain K.
Published: July 2021

This paper introduces a multi-bit data converters (MDC) modulator of the 2nd order delta-sigma analog-to-digital converter use the passive adder proposed. The noise shaping quantizer can provide feedback that has generated quantization noise and perform additional shaping noise first-order by coupling noise method.Thus, two Integrator's with ring amplifier and the MDC is shaped by noise coupling quantizer know the 2nd-order noise coupled with somewhat of a DAC modulator. At a summing point, the inputs are summed and then filtered with a low pass filter. A cyclic second order response is generated with a data weighted averaging (DWA) technique in which the DACs ' outputs are limited to one of two states in the noise shaping responses. Mainly as a result of the harmonic distortion in circuits of amplifier. Transistor rate is equipped for the fully differential switched condenser integrator used, a comparator and DWA. The modulator with proposed DWA design, almost quarterly improved timing margin. A simulated SNDR of 92dB is obtained at 20 MHz sampling frequency; while a sinusoidal output of 4.112 dBFS is tested at 90µs besides 20 MHz as the bandwidth. The power consumption is 0.33 mW while the voltage of the supply is 1.2V.
An efficient and improved model for power theft detection in Pakistan
Authors: Afridi Abid , Wahab Abdul , Khan Shamsher , Ullah Wasi , Khan Sheharyar , Ul Islam Syed Zia , Hussain Kashif
Published: July 2021

This paper describes an improved model for the monitoring of power used by a party such as household users and different industries in Pakistan. The power theft detection was done using the intelligent internet of things (IoT) service system for calculating the user's power simultaneously. The power meter catches a theft detection device that is instantly transmitted to the central system which compares both the data by means of microcontroller and if there is any difference found, it informs the power utility about the hooking, meter relief or theft activities happen. Information of the theft detection through the global mobile communications system is transmitted and notified theft is displayed on the terminal monitor or won. As a result, although consumers continue to use excess fuel, the customer's power supply is cut in the electricity boards segment. The general radio package module system sends central circuit and meter data via an internet protocol address to a web server. GSM's IoT based perception is used to monitor the power supply and billing information calculated with a microcontroller continuously with the determination of the electricity table area. With this unit, the duplicate user can be located at the rear of the electricity office with the power meter status.
Convolutional neural network for semantic segmentation of fetal echocardiography based on four-chamber view
Authors: Rachmatullah M. N. , Nurmaini Siti , Sapitri A. I. , Darmawahyuni A. , Tutuko B. , Firdaus Firdaus
Published: July 2021

The acute shortage of trained and experienced sonographers causes the detection of congenital heart defects (CHDs) extremely difficult. In order to minimize this difficulty, an accurate fetal heart segmentation to the early location of such structural heart abnormalities prior to delivery is essential. However, the segmentation process is not an easy task due to the small size of the fetal heart structure. Moreover, the manual task for identifying the standard cardiac planes, primarily based on a four-chamber view, requires a well-trained clinician and experience. In this paper, a CNN method using U-Net architecture was proposed to automate fetal cardiac standard planes segmentation from ultrasound images. A total of 519 fetal cardiac images was obtained from three videos. All data is divided into training and testing data. The testing data consist of 106 slices of the four-chamber segmentation tasks, i.e. atrial septal defect (ASD), ventricular septal defect (VSD), and normal. The segmentation of the post-processing method is needed to enhanced the segmentation result. In this paper, a combination technique with U-Net and Otsu thresholding gives the best performances with 99.48%-pixel accuracy, 96.73% mean accuracy, 94.92% mean intersection over union, and 0.21% segmentation error. In the future, the implementation of Deep Learning in the study of CHDs holds significant potential for identifying novel CHDs in heterogeneous fetal hearts.
Electrical battery modeling for applications in wireless sensor networks and internet of things
Authors: Rasool Fahad , Drieberg Micheal , Badruddin Nasreen , Sebastian Patrick , Jun Qian Christopher Teh
Published: July 2021

Modeling the behavior of the battery is non-trivial. Nevertheless, an accurate battery model is required in the design and testing of systems such wireless sensor network (WSN) and internet of things (IoT). This paper presents the one resistive-capacitance (1RC) battery model with simple parameterization technique for nickel metal hydride (NiMH). This model offers a good trade-off between accuracy and parameterization effort. The model’s parameters are extracted through the pulse measurement technique and implemented in a physical and dynamic simulator. Finally, the performance of the model is validated with the real-life NiMH battery by applying current pulses and real wireless sensor node current profiles. The results of the voltage response obtained from both the model and experiments showed excellent accuracy, with difference of less than 2%.
Filipino Basic Education Teachers’ Awareness of and Attitude Towards the Child Protection Policy
Authors: Fuente Cleofe L. dela
Published: July 2021

Schools shall be conducive to children’s education, and that the children’s’ best interest shall be the primary consideration in all policies and actions of educational institutions. This descriptive cross-sectional survey gauged the Filipino public school teachers’ awareness of and attitudes towards the child protection policy (CPP). The study involved 99 basic education teachers in select public elementary and secondary schools in Zambales, Philippines. The basic education teachers are aware of the policy, and they have a favorable attitude toward its implementation. No significant difference has been found in their awareness and attitude towards CPP when grouped according to demographics. The study concludes that as the teachers become aware of the policy, they tend to have a more favorable attitude. The study recommends that the teachers be capacitated through continuing professional development programs to provide special protection to children who are seriously susceptible or threatened by situations that distress their normal growth. Further study may also be conducted to probe other CPP dimensions in basic education to come up with relevant and research-based recommendations towards the policy’s improved implementation in the public schools in the Philippine context.
Implementation of an Android Mobile Location-Based Service Application for General Auto Repair Shops
Authors: Guevarra Bea S. , Ignacio Aris E.
Published: July 2021

The need of a location-based service more specifically as a mobile application sparked the interest of this paper to develop an Android Mobile Application using Location-based services. Yelp and Zomato are one of the few examples. The application created is specific to locating the nearest auto repair shops used via smartphones that detect the location of the user in order to perform the task. This application will not only benefit the customers in need for a nearby auto shop but as well as the providers of the service. The application was developed using Android Studio and was tested by using five (5) nearest auto shops around the vicinity. The results showed the directions getting to the shops as well as the type of services being provided to customers. An acceptability survey was conducted to validate the applicability of the mobile application. The survey was conducted using a controlled group consisting of the nearest auto shops and thirty (30) automobile enthusiasts. The survey presents an applicable and engaging application in assisting possible customers in case of emergency instances arise. Using the survey as basis, an enhancement of the application was completed. Finally, it was suggested that the application will reach its full potential once additional functions are implemented. Registration or Google verification of shop owners is key as it will add to the service provider directory to enable a broad listing.
Clinical Conditions and Their Impact on Utility of Genetic Scores for Prediction of Acute Coronary Syndrome
Authors: Lee Jiwoo , Kiiskinen Tuomo , Mars Nina , Jukarainen Sakari , Ingelsson Erik , Neale Benjamin , Ripatti Samuli , Natarajan Pradeep , Ganna Andrea
Published: July 2021

Background:

Acute coronary syndrome (ACS) is a clinically significant presentation of coronary heart disease. Genetic information has been proposed to improve prediction beyond well-established clinical risk factors. While polygenic scores (PS) can capture an individual’s genetic risk for ACS, its prediction performance may vary in the context of diverse correlated clinical conditions. Here, we aimed to test whether clinical conditions impact the association between PS and ACS.

Methods:

We explored the association between 405 clinical conditions diagnosed before baseline and 9080 incident cases of ACS in 387 832 individuals from the UK Biobank. Results were replicated in 6430 incident cases of ACS in 177 876 individuals from FinnGen.

Results:

We identified 80 conventional (eg, stable angina pectoris and type 2 diabetes) and unconventional (eg, diaphragmatic hernia and inguinal hernia) associations with ACS. The association between PS and ACS was consistent in individuals with and without most clinical conditions. However, a diagnosis of stable angina pectoris yielded a differential association between PS and ACS. PS was associated with a significantly reduced (interaction
P
=2.87×10
−8
) risk for ACS in individuals with stable angina pectoris (hazard ratio, 1.163 [95% CI, 1.082–1.251]) compared with individuals without stable angina pectoris (hazard ratio, 1.531 [95% CI, 1.497–1.565]). These findings were replicated in FinnGen (interaction
P
=1.38×10
−6
).

Conclusions:

In summary, while most clinical conditions did not impact utility of PS for prediction of ACS, we found that PS was substantially less predictive of ACS in individuals with prevalent stable coronary heart disease. PS may be more appropriate for prediction of ACS in asymptomatic individuals than symptomatic individuals with clinical suspicion for coronary heart disease.
Disturbance in the Outlines of Sextus Empiricus
Authors: Svavarsson Svavar Hrafn
Published: July 2021

Sextus seems to offer inconsistent accounts of the sceptics’ achievement of tranquillity, apparently saying both that the sceptics’ tranquillity is achieved by suspending judgement on all issues and that it is achieved by suspending judgement only on the issue of there being objective goods and evils. It is argued that Sextus does not make the latter claim. The reason for the sceptics’ achievement of tranquillity is to be found in the original perplexity that instigated scepticism and left them immune to the value beliefs that disturb everyone else. After discussing this perplexity that gave rise to scepticism, the paper focuses on Sextus’ explanation of sceptical tranquillity and dogmatic disturbance.
The Vow to Kill Elisha: Function and Meaning in 2 Kings 6:31–33
Authors: Kislev Itamar
Published: July 2021

In the story of the siege of Samaria (2 Kgs 6:24–7:20), the passage in which the king surprisingly threatens to kill Elisha (6:31–33) is problematic. This passage also recounts the preparations by Elisha and the elders who are with him for the arrival of the king’s messenger who comes to kill the prophet (6:32). Eventually, and without explanation, the king abandons his initial intention to kill Elisha (6:33). This strange passage does not promote the plot and its function in the story is not clear.

An analysis of this passage in its context leads to the recognition that the story is not unified and reveals the stages of its development. Understanding the motivation for developing the story leads to another conclusion: that the formation of this story is closely related to the wider context, namely the redaction of the Elisha cycle.
1 Samuel 2:6: Time and Wayyiqtol in Hannah’s Song
Authors: Jones Ethan C.
Published: July 2021

This article challenges the ideas that we should either re-read the form or appeal to a present tense rendering of וַיָּעַל in 1 Sam 2:6. Instead, I argue that the prospect of gnomic semantics due to the surrounding participles is leveraged to highlight a past time wayyiqtol “he raised up.” This past time makes sense of the context both within the poem itself (1 Sam 2) and the preceding narrative (1 Sam 1). What is more, a past tense meaning of וַיָּעַל is corroborated by recent robust linguistic research of the form. Reading the wayyiqtol as past makes reference to a specific, historical action done to Hannah. This reference to the past tightens the cohesion of and provides further coherence for Hannah’s narrative (1 Sam 1) and her song (1 Sam 2).
Tu, felix Salomon, nube: Solomon’s Marriages in Early Christian and East Syrian Biblical Interpretation
Authors: Pragt Marion
Published: July 2021

This article explores the political portrayal of Solomon’s marriages presented by three East Syrian authors. It will be shown that whereas Jewish and early Christian interpreters often pointed to desire and demonic influence to explain Solomon’s many marriages, Theodore bar Koni, Ishoʿdad of Merv and the commentators of the anonymous manuscript olim Diyarbakır 22 instead portrayed the marriages as a form of nuptial politics intended to provide peace. The article examines the role of this political motif against the background of Theodore of Mopsuestia’s views on Solomon and the Song of Songs. It will be argued that the ways in which the East Syrian authors evaluated Solomon’s marriages are related to their different attitudes to the Song. The article illustrates how Greek exegesis could be transmitted and transformed in the East Syrian tradition of scriptural interpretation.
The Unity and Multiplicity of the Holy Spirit in Origen of Alexandria
Authors: Miller Micah M.
Published: July 2021

In his study on angelomorphic traditions in early Christian pneumatology, Bogdan Bucur suggests that Origen is both indebted to and develops upon Clement of Alexandria’s pneumatology. This article takes up Bucur’s claim, offering the first examination of Origen’s pneumatology in light of previous research on early Christian angelomorphic traditions. It argues that Origen interprets the traditional understanding of the Holy Spirit as one and seven in terms of a philosophical notion of power, allowing him to explain how the one Holy Spirit can distribute many different gifts.
Landscapes of Memories: A Study of Representation for Translocal Chinese Cultural Heritage in Kaiping, Guangdong, China
Authors: Chiang Bo-wei
Published: July 2021

Beginning in the mid-nineteenth century, many young people emigrated from Guangdong to the American West in search of a better living, mainly through building the Pacific Railroad and panning for gold in California. Some of these overseas Chinese who eventually accumulated wealth sent remittances back to their hometowns to provide their families with a better life, or they built mansions for their own retirement. They also used their wealth to renovate ancestral halls, establish schools, get involved in local politics and issues of local public security, public hygiene, etc. The overseas Chinese were one of the important new rising social strata in modern China before the 1960s.

This paper will focus on translocal Chinese cultural heritage in Guangdong and try to discuss how people memorize, narrate, preserve, and represent their migration history in these hometowns. Meanwhile, the meaning of the tangible cultural heritage as a landscape of memories in local society in China will also be discussed. Firstly, I think that there are three types of overseas Chinese memories: the memory of suffering, the memory of making fortunes, and the memory of a philanthropic image; secondly, I will deal with the narrative and representation of the collective memories since the 1990s and check how the collective memory became the cultural heritage beneath the state’s discourse; and finally, I will analyze how the overseas Chinese cultural heritage became resources for cultural tourism and local economic development, and show a process of commercialization of those landscapes.
Across, Between, and Beyond Nation States: Overseas Chinese Private Remittance Networks, 1850s–1930s
Authors: Mah-Gricuk Ania
Published: July 2021

This paper examines the development of private remittance networks that came into being in response to the practice of migrants sending financial resources back to their families in China from 1850 to 1930s and analyses them through the lens of transnational space. It discusses the transnational space between the diaspora and the homeland and the structures that link them. My research has shown that these networks contributed to a space transcending national borders. The material comprising the basis of this research project includes newspapers from the diaspora, remittance letters and receipts, and reports conducted by the Taiwanese governmental institutions and secondary material focused on both emigrant home villages in China and communities in destinations. In the diasporic context, space is created through shared experiences of migrants, who are physically separated from their families but remain linked through networks such as the remittance trade.