bluuebunny/crossref_metadata_2025_split huggingface dataset:
A&nbsp;Novel&nbsp;Feature&nbsp;Extraction&nbsp;Based&nbsp;Person&nbsp;Recognition&nbsp;Using&nbsp;Local&nbsp;Phase&nbsp;Quantization&nbsp;and&nbsp;Geometric&nbsp;Features
Authors: Karuppanan P , Dhanalakshmi K. 
Published: March 2021

Abstract
At present, it is simple for everyone to generate digital pictures of their routine life and use them for different purposes. Similarly, facial recognition is a trending technology that can identify or verify an individual from a video frame or digital image from any source. There are numerous techniques involved in the working principle of facial recognition. But the simplified method is feature extraction by comparing the particular facial features of the images from the collected dataset. Multiple algorithms are existing for feature extraction, but they fail to give high accuracy. The proposed algorithm based on deep learning provides a high recognition rate by using a convolutional neural network for classification. For feature extraction, Local Phase quantization, Geometric-based features, and directional graph-based methods are implemented. Various performance metrics, such as recognition rate, classification accuracy, accuracy, precision, recall, F1-score is evaluated. The proposed method achieves high-performance values when it is compared with other existing methods. It is mainly developed to calculate the casual visit of a person to the mall, and it is also deployed for criminal identification.
Design of Adaptive Array Antenna for Wireless Communications
Authors: Kumar Pramod , P. Shiwani Y. , Kumari H. K. Kanchana 
Published: March 2021

Abstract
In the ad hoc networks, it consists of many sensor nodes, and each sensor node is equipped with five units. The transmission unit cares for the transmission and receiving of data through the antenna. In this paper, the microstrip patch and 1x2 array antennas are designed and fabricated. The results of simulated and measured results are compared at operating frequency 5.4GHz. The results show the enhancement in the bandwidth and low VSWR which shows the maximum radiation of power. The array antenna can be operated for the wideband with better reflection coefficient, gain, bandwidth, and VSWR and radiation pattern. This smart antenna is self-efficient to configure with multiple high directivity beam to save the power, range and use reuse of channels. Such smart antennas are used for the ad-hoc network, Wi-Fi, UWB, and high-speed LTE applications.
Long-range magnetic order in real icosahedral quasicrystals
Authors: Tamura Ryuji , Ishikawa Asuka , Suzuki Shintaro , Kotajima Akihiro , Tanaka Yujiro , Seki Takehito , Shibata Naoya , Yamada Tsunetomo , Fujii Takenori , Wang Chin-Wei , Avdeev Maxim , Sato Taku 
Published: March 2021

Abstract
Quasicrystals (QCs), first discovered in 1984, generally do not exhibit long-range magnetic order. Here, we report on long-range magnetic order in the real icosahedral quasicrystals (i QCs) Au–Ga–Gd and Au–Ga–Tb. The Au65Ga20Gd15 i QC exhibits a ferromagnetic transition at TC = 23 K, manifested as a sharp anomaly in both magnetic-susceptibility and specific-heat measurements. Quick magnetic saturation to almost the full moment (7μB/Gd3+) is observed under 100 Oe at 2 K. This is the first observation of long-range magnetic order in a real quasicrystal, in contrast to the spin-glass-like behaviours observed for the other magnetic quasicrystals found to date. Moreover, when Gd is replaced by Tb, i.e. for the Au65Ga20Tb15 i QC, a ferromagnetic behaviour is still retained with TC = 16 K. Although the sharp anomaly in the specific heat observed for the Au65Ga20Gd15 i QC is significantly broadened upon Tb substitution, neutron-diffraction experiments clearly show the marked development of magnetic Bragg peaks below TC, indicating long-range magnetic order for the Au65Ga20Tb15 i QC also. Our findings can contribute to the further investigation of exotic magnetic orders formed on real quasiperiodic lattices with unprecedented highest global symmetry, i.e. icosahedral symmetry.
Model for Life Cycle Sustainability Assessment of Coal Based Electricity Generation in India
Authors: Shah Binita , Unnikrishnan Seema 
Published: March 2021

Abstract
Purpose: This study evaluates the environmental efficiency of coal-based electricity generation in India. The study further proposes a new paradigm of life cycle assessment model named CEEPA - Coal Electricity Environmental Performance Assessment (CEEPA). Methods: Life cycle assessment methodology has been used to quantify the impacts of electricity generation from coal. An emission revision model based on pollution and waste produced and its effect categories were proposed after an analytical comparison between three coal-fired thermal power plants in different regions of the country.ReCiPe method was used to conduct the assessment in this study. Software SimaPro was used for LCA analysis. The study was carried out “from cradle to gate” and the functional unit was 1 KWh electricity at the consumer levelResults: The total Global Warming Potential (GWP) values for the three power plants (PP1, PP2 & PP3) are 1,100 g CO2eq/kWh, 1,287 g CO2eq/kWh and 898 g CO2eq/kWh respectively. PP1, PP2 uses Indian coal for electricity generation which is supplied domestically and later sent to the grid, whereas PP3 uses Indonesian coal.Conclusion: The evaluation performed in this study illustrate the latest environmental assessment situation for various technologies in power generation. It also provides an opportunity to suggest areas for possible improvements in the existing electricity generation system based on the quality and quantity of coal used. The empirical findings indicate that the production of coal-based electricity generation has a substantial effect on the use of natural resources, the environment and human health. The implementation of high-efficiency low emission coal-fired power plants is the first step along a pathway to near-zero emissions from coal with carbon capture, use, and storage.
Security and Privacy Issues of IoT at Fog Layer Architecture
Authors: Michael Vinay 
Published: March 2021

Abstract
Internet of Things (IoT) based applications and systems are gaining attention in the recent days because of their vast benefits such as efficient utilization of resources, enhanced data collection, improved security, lesser human efforts and reduced time. Security of sensitive data in IoT based fog environments is inevitable to prevent those data to be misused by the attackers. In this study, we present an improved hybrid algorithm termed as HQCP-ABE (Hybrid Quantum key Cipher text Policy Attribute based Encryption with Cipher text update) that integrates highly effective algorithms such as CP-ABE, Quantum key cryptography and cipher text update. The proposed algorithm eliminates the need of costly pairing during decryptions and efficiently performs data encryption, decryption and user authorization. The proposed protocol is demonstrated to be highly efficient in terms of encryption and decryption while compared to other existing methods. It also achieves lesser packet loss, reduced control overheads, reduced computational overhead during encryption and decryption processes, lesser delay, improved security, packet delivery ratio, throughput, network lifetime with limited bandwidth and user privacy. We further considered energy consumption in this study. The proposed HQCP-ABE method is demonstrated using ns3 simulation and compared with existing CP-ABE and PA-CPABE methods.
dentification of novel insulin resistance related ceRNA network: LncRNA, RP11‐773H22.4; miR-3163, miR-1; mRNAs:RET , IGF1-R, m-TOR, GLUT-4, AKT2 in T2DM and its potential editing by CRISPR/Cas9
Authors: Matboli Marwa , Kamel Marwa Mostafa , Essawy Nada , Bekhit Meram Mohamed , Abdulrahman Basant , Mohamed Ghada , Eissa Sanaa 
Published: March 2021

Abstract
Background: In this study, we aimed to construct Insilco, a competing endogenous RNAs (ceRNAs) network linked to the pathogenesis of insulin resistance followed by its experimental validation in patients’, matched control and cell line samples. And also, to evaluate the efficacy of CRISPR/Cas9 as a potential therapeutic strategy to modulate the expression of this deregulated network. By applying bioinformatic tools, we identified and verified a ceRNA network panel of lncRNA, miRNAs and mRNAs related to insulin resistance and then we validated its expression in 123 patients’ and 106 matched controls and cell line samples using real time PCR. Results: LncRNA-RP11‐773H22.4, together with RET , IGF1-R and m-TOR mRNAs showed significant upregulation in T2DM compared with matched controls while miRNAs: miR-3163, miR-1 and mRNAs: GLUT-4 and AKT2 expression displayed marked downregulation in diabetic samples.Two guide RNAs were designed to target the sequence flanking LncRNA/miRNAs interaction by CRISPER/Cas9 in cell culture. Gene editing tool efficacy was assessed by measurement of the network downstream proteins, GLUT4 and mTOR by immunofluorescence. CRISPR/Cas9 successfully knockout LncRNA-RP11-773H22.4 as evidenced by the reversal of the gene expression of the identified network at RNA and protein levels to the normal expression pattern after gene editing. Conclusion: The presented study provides the significance of this ceRNA based network and its related target genes panel both in the pathogenesis of insulin resistance and as a therapeutic target for gene editing in T2DM.
Determinants of health-related quality of life in patients with celiac disease: a structural equation modeling
Authors: Nikniaz Zeinab , Jafarabadi Mohammad Asghari , Farhangi Mahdieh Abbasalizad , Shirmohammadi Masood , Nikniaz Leila 
Published: March 2021

Abstract
Purpose

We employed the structure equation modeling (SEM) for investigating the determinants of Helath-related quality of life (HRQOL) in Iranian patients with celiac disease (CD).

Methods

In the present cross-sectional study, a total of 170 patients with CD were recruited. The information regarding adherence to diet, symptom severity and HRQOL were collected using celiac disease adherence test (CDAT), gastrointestinal symptom rating scale (GSRS) and SF-36 questionnaire respectively. Association between various studied variables and HRQOL was assessed using SEM. The standardized regression weights was used to assess total, direct and indirect effects. The model fit was assessed to determine the “goodness of fit” between the hypothesized model.

Results

The mean age of participants was 37.57 ± 9.59 years. The results of SEM indicated that the overall fit of our model was acceptable. Adherence to the diet, GSRS score, occupation, and education level were significantly related to PCS of SF-36; and adherence to the diet, GSRS score, and education level were significantly correlated to MCS of SF-36. The analysis of indirect effect indicated that only adherence to diet indirectly via GSRS score was significantly associated with PCS and MCS of SF-36. There were significant differences between males and females regarding the relationship between education and adherence to diet (p<0.001) and education level and MCS of SF-36 (p=0.03).

Conclusion

In adult patients with celiac disease, HRQoL was affected by age, education level, adherence to GFD, and GSRS score. Additionally, occupation and disease duration were associated with HRQoL only in women and men respectively.
Rainfall Analysis by Using Mann-Kendall Trend, Sen’s Slope and Variability at Six Stations of Andaman &amp; Nicobar Islands
Authors: Roy Sukumar , Chakravarty Nabajit 
Published: March 2021

Abstract
On analysis of thirty five years rainfall data ( 1980-2015 ) of six stations of Andaman & Nicobar islands it was found through Mann-Kendall trend , Sen’s slope and Regression slope , that annual and monsoon rainfall at Mayabandar, LongIsland, PortBlair and Carnicobar showed increasing trend while that of HutBay and Nuncowrie showed decreasing trend. The monsoon season ( summer monsoon ) rainfall variability of 49.78% in Mayabandar, 52.12% in Long Island, 24.09 % in Port Blair, 49.39% in HutBay , 47.26% in Carnicobar and 51.91% in Nuncowrie has been recorded in this time span. The high coefficient of variation ( CV) denoted that the variability of rainfall is not equally distributed. A low standard deviation indicates that the data points tend to be close to the mean of the set, while a high standard deviation indicates that the data points are spread out over a wide range of values. High SD was reported at all the five stations of study in comparison to Port Blair which also had a low coefficient of variation. The rainfall distribution of different season viz. pre monsoon , monsoon , post monsoon and winter , it was observed that the highest present contribution of rainfall was observed during monsoon season followed by post monsoon in all the six stations of Andaman & Nicobar islands . Rainfall contribution during May to November was most in all the six stations studied , while in remaining months it was 5.3% in Mayabandar , 6.4% LongIsland, 10.2% in Port Blair, 12.3% in HutBay , 16.9% in CarNicobar and 21.1 % in Nuncowrie.
Structure and magnetic properties of coprecipitated nickel-zinc ferrite doped rare earth elements of Sc, Dy, and Gd
Authors: Shiwen Li , Jiatong Pan , Feng Gao , Deqian Zeng , Qin Feng , Chunling He , Dodbiba Gjergj , Wei Yuezou , Fujita Toyohisa 
Published: March 2021

Abstract
This research is the basic study of temperature-sensitive ferrite characteristics prepared by coprecipitation with doping different typical sizes of rare earth elements. Ni 0.5 Zn 0.5 Re x Fe 2-x O 4 (NZRF) (X = 0.02, 0.05, 0.07 and 0.09) nanoparticles (NPs) doped by Sc, Dy and Gd prepared by chemical coprecipitation method. The structure and properties of Ni 0.5 Zn 0.5 Re x Fe 2-x O 4 were analyzed by various characterization methods. XRD results show that the grain size of Ni 0.5 Zn 0.5 Re x Fe 2-x O 4 is from 10.6 to 12.4 nm, which is close to the average grain size of 13.9 nm observed on TEM images. It is also found that the ferrite particles are spherical and slightly agglomerated in TEM images. FTIR measurements between 400 and 4000 cm -1 have confirmed the intrinsic cation vibration of the spinel structure. The concentrations of nickel, zinc, iron, and rare earth elements have been determined by ICP-AES, and all ions have participated in the reaction. The magnetic properties of Sc, Dy, and Gd 3+ doped NZRF NPs at room temperature are recorded by a physical property measurement system (PPMS-9). It is found that the magnetization can be changed by adding rare-earth ions. When X = 0.07, Gd 3+ doped Ni 0.5 Zn 0.5 Fe 2 O 4 (NZF) exhibits the highest saturation magnetization. The magnetic properties of NZGd 0.07 vary the most with temperature. The thermomagnetic coefficient of NZGd 0.07 nanoparticles stabilized to 0.18 emu/gK at 0-100℃. Hence, NZGd 0.07 with low Curie temperature and the high thermomagnetic coefficient can be used to prepare temperature-sensitive ferrofluid. All the samples exhibit very small coercivity and almost zero remanences, which indicates the superparamagnetism of the synthesized nanoparticles.
The Resident Voice: Identifying Qualities of Resident Leadership with a Focus Group of Second Year Residents
Authors: Chaiklin Charlotte , Hassneiah Dana , Issenberg Barry , Taldone Sabrina 
Published: March 2021

Abstract
Background The Accreditation Council for Graduate Medical Education (ACGME) Internal Medicine Residency Program Guidelines identifies leadership as a core competency. The definition of strong resident leadership is not clearly defined. Prior studies have identified characteristics of resident leadership from the perspective of residency program leaders with little emphasis on the resident point of view. Objective This study aims to identify qualities of effective resident leadership from the perspective of Internal Medicine (IM) residents. Methods Participants were recruited through email invitations. An online focus group with five IM residents was conducted in September 2020. The transcribed discussion was inductively analyzed using thematic data analysis.Results Analysis resulted in four main themes of strong resident leadership: mentorship, team ownership, communication, and emotional intelligence. All four themes were further characterized by subthemes. Being a mentor as a resident leader was described as having the ability to guide, motivate, and empower team members. Team ownership was defined as caring about team image, adaptability, and accountability for team performance. Communication skills included setting expectations, giving feedback, and utilizing closed-loop communication. Emotional intelligence was characterized as practicing empathy, psychological safety, and appreciation.Conclusions Strong resident leadership is crucial to providing effective residency training and the highest level of patient care. This study identifies from the perspective of residents, the principal characteristics of strong resident leadership: mentorship, communication, team ownership, and emotional intelligence. The identification of these characteristics provides an opportunity to create leadership curricula for residents that focus on developing these specific skills. Trial Registration The University of Miami institutional review board (IRB) approved this study: IRB number MOD0041899 on September 14, 2020.
Enhanced Thermoelectric Properties of Cu3SbSe4 Compounds by Isovalent Bismuth Doping
Authors: Zhao Lijun , Wang Mingyuan , Yang Jian , Hu Jiabin , Zhu Yuan , Liu Guiwu , Hussain Shahid , Shao Haicheng , Lei Shuangying , Wan Neng , Shi Zhongqi , Qiao Guanjun 
Published: March 2021

Abstract
Cu3SbSe4, featuring its earth-abundant, cheap, nontoxic and environmentally-friendly constituent elements, can be considered as a promising intermediate temperature thermoelectric (TE) material. Herein, a series of p-type Bi-doped Cu3Sb1 − xBixSe4 (x = 0-0.04) samples were fabricated through melting and hot pressing (HP) process, and the effects of isovalent Bi-doping on their TE properties were comparatively investigated by experimental and computational methods. TEM analysis indicates that Bi-doped samples consist of Cu3SbSe4 and Cu2 − xSe impurity phases, which is in good agreement with the results of XRD, SEM and XPS. For Bi-doped samples, the reduced electrical resistivity (ρ) caused by the optimized carrier concentrations and enhanced Seebeck coefficient derived from the densities of states near the Fermi level give rise to a high power factor of ~ 1000 µWcm− 1K− 2 at 673 K for the Cu3Sb0.985Bi0.015Se4 sample. Additionally, the multiscale defects of Cu3SbSe4-based materials involving point defects, nanoprecipitates, amorphous phases and grain boundaries can strongly scatter phonons to depress lattice thermal conductivity (κlat), resulting in a low κlat of ~ 0.53 Wm− 1K− 1 and thermal conductivity (κtot) of ~ 0.62 Wm− 1K− 1 at 673 K for the Cu3Sb0.98Bi0.02Se4 sample. As a consequence, a maximum ZT value ~ 0.95 at 673 K is obtained for the Cu3Sb0.985Bi0.015Se4 sample, which is ~ 1.9 times more than that of pristine Cu3SbSe4. This work shows that isovalent heavy-element doping is an effective strategy to optimize thermoelectric properties of copper-based chalcogenides.
Aggregate suitability and Geo-chemical investigation of limestone for construction industries in Pakistan: An approach for economic development
Authors: Kamran Asad , Ali Liaqat , Ahmed Waqas , Zoreen Sobia , Jehan Shah 
Published: March 2021

Abstract
This study investigated the aggregate suitability and geo-chemical characteristics of limestone (LS) for construction industries. The results of aggregate parameters for different applications revealed that specific gravity (SG = 2.6), water absorption (WA = 0.47%), bulk density (BD = 1.58 g/cm3), flakiness index (FI = 16.8%), elongation index (EI = 16.39%), soundness (S = 1.6%), aggregate impact value (AIV = 14%), Los Angles Abrasion value (LAAV = 23.51%), clay lumps (CL = 0.35%), uniaxial compressive strength (UCS = 86.7 MPa), point load test (PLT = 5.18 MPa), ultrasonic pulse velocity (UPV = 5290 m/s) and Schmidt hammer rebound test (SHRT = 49 N) are in accordance with ASTM, ISRM and BSI. Petrographically, the LS is dominantly composed of ooids, peloids, bioclasts and calcite (CaCO3) with trace concentration of the dolomite. Geochemical results (n = 18) indicated that the LS is dominantly made up of calcite (95.81%); while on average it is composed of 52.08 wt.% CaO, 1.13 wt. % SiO2, 0.66 wt. %, MgO, 0.80 wt. % Al2O3, 0.76 wt. % Fe2O3 and LOI were recorded as 42.13 wt. %. Whereas, P2O5, TiO2, MnO, K2O and Na2O are found in trace amount. Regression analysis demonstrates that the empirical correlation equation for estimating uniaxial compressive strength with ultrasonic pulse velocity is more reliable than Schmidt hammer rebound test and point load test. The findings of this study strongly suggest LS of the area has a great potential as a raw material in construction industries.
Analysis and Estimation of Seepage Through Earth Dams with Internal Cut Off
Authors: Razek Mohamed Abdel , Salam Adel Abdel , Attia Michael 
Published: March 2021

Abstract
The study of seepage through earth-fill dams is very important for the constructed dams to ensure that the control of seepage is sufficient for the safe and sustainable operation of the dam. It is also important in the design and construction of new dams to ensure that the seepage through and under the dam will be well controlled. Construction horizontal, inclined, trapezoidal or pipe filters one of the dam protection methods. Cut off also can be constructed to minimize seepage discharge directed to the downstream face of the dam. Seepage through an earth dam with internal cut off is experimentally studied in the laboratory of Irrigation Engineering and Hydraulics Department, Faculty of Engineering, Alexandria University, Egypt on a Hele-Shaw model. Also, using computer program SEEP/W (which is a sub-program of Geo-Studio). The experimental and numerical analyses of seepage through earth-fill dam with internal cut off is conducted. Results from solutions are compared with each other.
Evaluation of hydrological response under future climate change by revising meteorological data in the source region of the Yangtze River, China
Authors: Chen Xiaohong , Jin Haoyu , Wu Pan , Xia Wenjun , Zhong Ruida , Song Chao 
Published: March 2021

Abstract
The source region of the Yangtze River (SRYR) is located in the hinterland of the Tibetan Plateau (TP). The natural environment is hash, and the hydrological and meteorological stations are less distributed, making the observed data are relatively scarce. In order to overcome the impact of lack of data, the China Meteorological Forcing Dataset (CMFD) was used to correct the meteorological data, to make the data more closer to the real distribution on the SRYR surface. This paper used the Soil and Water Assessment Tool (SWAT) to verify interpolation effect. Since the SRYR is an important water resource protection area, have a great significance to study the hydrological response under future climate change. The Back Propagation (BP) neural network algorithm was used to integrate data extracted from the six Global Climate Models (GCMs), and then the SWAT model was used to predict runoff changes in the future status. The results show that the CMFD data set has a high precision in the SRYR, and can be used for meteorological data correction. After the meteorological data correction, the Nash-Sutcliffe efficiency increased from 0.64 to 0.70. Under the future climate change, the runoff in the SRYR shows a decreasing trend, and the distribution of runoff during the year changes greatly. This reflects the amount of water resources in the SRYR will be decreased, which will brings challenges to water resources management in the SRYR.