Miracle-dz/UniFAR-FTUs huggingface dataset:
Smart Way for Consistent Cement Bond Evaluation and Reducing Human Bias Using Machine Learning

Cement evaluation data acquired in oil and gas wells for confirmation of zonal isolation, channeling in cement behind casing and well integrity. All available technologies for cement evaluations are primarily measurements of acoustic parameters like amplitude of first arrival, full waveform recording of refracted wave, impedance and attenuation or there a combination. Generally, operationsPetrophysicist, petroleum engineer or service providers are responsible for evaluation of cement bond logs and propose remedial jobs if required. This cement bond log interpretation is quite subjective if performed through pure visual interpretation and its accuracy depends on objective of well, work pressure and experience of interpreter. This paper talks about how ADNOC Onshore has leveraged machine learning (ML) for interpretation of various cement bond logs from several service providers. In green fields, cement evaluation is very important in all new wells to ensure good cement quality and zonal isolation and it is also equally important in in brown fields where 1000s of wells were drilled where well integrity issues are of common occurrence. Major challenges in evaluation are inconsistency and human bias in interpretation and as a result, interpretation may vary from one interpreter to the other. Authors have tested different ML techniques (Random Forest Classification & Neural Net) and smart way of data training. Final recommendation is to use nested models instead of single model. In this technique, input measurements and required solutions will be classified and divided into different classes, a separate ML model will be built for each class and combine all the models to get final cement evaluation and recommendations. Final results include data quality flags, cement bond quality, zonal isolation, channeling, micro annuals, areal cement map (if analyzed field wise), anomaly maps (if analyzed data from offset wells at different times), and recommendation. In this project, a simple easy to use user interface has been developed to browse the cement logs and use the trained ML models to predict the cement evaluations with a click of a button. This ML based cement bond evaluation is proved to be very effective and saved 75% of efforts by operational Petrophysicists. The interpretation accuracy has been significantly improved. This method has potential to be used at rig site. These models are very cost effective with, minimum human bias, and improves consistency as well as independent of wells or type of reservoirs. These models are tested across ADNOC Onshore Wells and can be extended to any well irrespective of geographic locations. This paper discusses machine-learning approach, evaluation of various algorithms and testing results for cement evaluation log from various service providers.
Identification of IFN-Induced Transmembrane Protein 1 With Prognostic Value in Pancreatic Cancer Using Network Module-Based Analysis

Despite improvements reported in diagnosis and treatments in recent decades, pancreatic cancer is still characterized by poor prognosis and low survival rate among solid tumors. Intensive interests have grown in exploring novel predictive biomarkers, aiming to enhance the efficiency in early detection and treatment prognosis. In this study, we identified the differentially expressed genes (DEGs) in pancreatic cancer by analyzing five gene expression profiles and established the functional modules according to the functional interaction (FI) network between the DEGs. A significant upregulation of the selected DEG, interferon (IFN)-induced transmembrane protein 1 (IFITM1), was evaluated in several bioinformatics online tools and verified with immunohistochemistry staining from samples of 90 patients with pancreatic cancer. Prognostic data showed that high expression of IFITM1 associated with poor survival, and multivariate Cox regression analysis showed IFITM1 was one of the independent prognostic factors for overall survival. Meanwhile, significant correlations of the expression of IFITM1 and the infiltration of immune cells were found by TIMER. Furthermore, a higher level of IFITM1 was assessed in pancreatic cancer cell lines compared to normal human pancreatic duct epithelial cells, and silencing IFITM1 in tumor cells remarkedly inhibited cancer tumorigenicity. Collectively, our findings suggested that IFITM1 might have promising utility for pancreatic cancer.
Job satisfaction, burnout, and depression in nurses working in level 2 and level 3 intensive care units

Aim: This study aimed to determine the burnout, job satisfaction and depression levels of second and third level intensive care unit (ICU) nurses and whether there was a difference between the groups in terms of these characteristics. The relationship between burnout, job satisfaction, and depression levels in ICU nurses was also investigated. Material and Methods: The study included 42 level 2 and 43 level 3 ICU nurses. A sociodemographic data form, the Minnesota Job Satisfaction Scale (MJS), Maslach Burnout Inventory (MBI), and Beck Depression Inventory (BDI) were applied to the participants. Statistical analysis was performed using the t-test, Pearson correlation, and multiple linear regression analysis. Results: There was no significant difference between the groups in terms of MJS, MBI subscales, and BDI scores. There was a negative correlation between the duration of work in ICU and job satisfaction however, no significant correlation between the duration of work in ICU and burnout and depression levels. There was a negative correlation between job satisfaction and emotional exhaustion, depersonalization, depression levels also a positive correlation between personal accomplishments. Emotional exhaustion and personal accomplishment predicted job satisfaction, whereas depersonalization and depression did not. Conclusion: To protect mental health and increase job satisfaction of ICU nurses, precautions should be taken to reduce burnout and depression.
Creating Virtual Models with Digital Photogrammetry: Pertev Paşa Mosque (İzmit, Turkey)

Abstract:The use of photogrammetry as a tool to aid in the documentation of cultural heritage sites has a long history in creating scalable documents from 2D photographs. Recent advances in technology paired with the greater accessibility of photogrammetric software present ever-growing opportunities to document heritage sites. Documentation can be achieved with minimal training, a consumer-grade camera, and available software. Software applications manage almost the entire initial photogrammetric process, including image registration, object matching, photo-stitching, 3D mesh generation, and rendering. Digital photogrammetry starts with the on-site capture of digital photographs. Photographs are collected for processing by automated modeling software. Based on two algorithms, structure from motion (SfM) and multi-view stereo (MVS), the software analyzes the photographic images to create a 3D polygonal mesh with photorealistic texture maps. These files can then be post-processed and the models refined using 3D surface modeling software to create a final virtual model. Digital photogrammetry using a digital single lens reflex camera and cloud-based processing software can make digital documentation more applicable to historic building documentation. This article presents a straightforward approach to using digital photogrammetry to document heritage sites located in remote regions of the world, where access and digital applications may be limited.
Hybrid Computing and Decision Technologies in Improving Accuracy of Structural Equation Model for Sustainable Environmentally Friendly Product Management

Main purpose of this research is to study influential variables of green innovation strategy, corporate social responsibility, government policy, transformation leadership including human resource development on the success level in managing sustainable environmentally friendly products of industrial plants. The sequential procedures on statistical techniques are proposed with the survey data on both quantitative and qualitative research elements. Confirmatory factor and path analysis including the structural equation modeling are mixed to identify the causal relationship between variables and the dependent variables. In this article, two metaheuristic algorithms namely sequential evolutionary elements based on variable neighborhood search and particle swarm optimization algorithms are proposed to enhance the sustainable environmentally friendly product management model. The results show that all performance measures of the particle swarm optimization algorithm are better, but not statistically significant when compared. Evolutionary elements from Metaheuristic approaches are the powerful tool for generating the management model and aiding the industries for decision making. The qualitative research was from the multistage sampling and in-depth interviews to finally provide guidelines for managing environmentally friendly products. From the numerical results all of proposed variables affected the success at a high level of opinions. The results of this research will be efficiently used to promote sustainable environmentally friendly products for the manufacturing in Thailand.
Energy Efficient Relay Selection and Resource Allocation in D2D-Enabled Mobile Edge Computing

In order to improve resource utilization and network capacity, we propose the Device-to-Device (D2D) enabled Mobile Edge Computing (MEC) system, where multiple Smart Devices (SDs) transmit the offloading data to the MEC server with the help of wireless access point (WAP) selected from multiple WAPs. The SD uses the chosen WAP as the communication relay between the MEC server and itself. Aimed to minimize the total energy consumption of the system and satisfy the SDs demand on delay, we jointly optimize relay selection and resource allocation in D2D-enabled MEC system. The problem is formulated as an integer-mixed non-convex optimization problem which is a NP-hard problem. We thus propose a two-phase optimization algorithm that jointly optimizes relay selection policy and resource allocation strategy. In first phase, the original problem is converted into a convex optimization problem by using convex optimization techniques, and the optimal relay selection policy can be achieved by solving the relay selection problem. After obtaining the relay selection policy, the original problem is transformed into a resource allocation problem solved by leveraging the Lagrange Method in the second phase. Furthermore, the proposed algorithm is a low-complexity algorithm which is associated with the root finding method. The optimal relay selection policy and resource allocation strategy can be found in polynomial time. The extensive simulation results are provided to indicate that the D2D-enabled MEC system achieves remarkable results in energy saving. Compared with other baseline methods, our proposed algorithm can not only achieve the optimal solution with less time cost, but also improve the energy efficiency and network capacity.
Simultaneous determination of As and Sb in soil using hydride generation capacitively coupled plasma microtorch optical emission spectrometry – comparison with inductively coupled plasma optical emission spectrometry

A method using a miniature analytical system based on hydride generation capacitively coupled plasma microtorch optical emission spectrometry with a QE65 Pro microspectrometer was developed and evaluated for the simultaneous determination of As and Sb in soil samples. The use of this microspectrometer allows the examination of the spectral range between 190 and 220 nm where the continuum background emission of the plasma is low and the most intense resonance lines As 193.759; 197.262 nm and Sb 206.833; 217.581 nm are located. The method involves microwave-assisted digestion of samples in aqua regia, prereduction of As(V) and Sb(V) to their (+3) species with 0.3% L-cysteine by heating in a boiling water bath at 90 ± 5 °C and hydride generation in 0.01 mol L−1 HCl (pH = 2.00 ± 0.01) medium with 0.5% NaBH4 solution. The method was optimized in order to provide the simultaneous determination of As and Sb. The figures of merit were evaluated at different emission wavelengths under the optimum conditions of plasma microtorch operation (10 W, 150 mL min−1 Ar), and the best performances were obtained at 193.759 nm (As) and 217.581 nm (Sb). The figures of merit of the method were compared to those of the traditional hydride generation inductively coupled plasma optical emission spectrometry taken as a reference method. Analysis of CRMs revealed recoveries of 101 ± 9% As and 102 ± 3% Sb comparable to 102 ± 7% As and 98 ± 4% Sb in the reference method. The precision of determinations was 2–10% for 90–210 mg kg−1 As and 40–130 mg kg−1 Sb, close to 3–8% in hydride generation inductively coupled plasma optical emission spectrometry. The Bland and Altman test performed on 10 soil samples indicated no significant difference between the results obtained by the two methods, so that the miniature analytical system could be successfully applied for As and Sb monitoring in environmental samples. The proposed method is attractive in terms of analytical costs due to limited consumption of high purity HCl, power and Ar to sustain the plasma, and therefore more advantageous than hydride generation inductively coupled plasma optical emission spectrometry.
The Entanglement of a Two-Atomic System in the Presence of a Silver Nanosphere

In this paper, we study the entanglement of two-level atoms near a spherical silver nanoparticle. By employing the Von Neumann equation and utilizing of the electromagnetic Green’s tensor associated with a dispersive and dissipative dielectric sphere, the decay rates and the Lamb shift of the atomic system are obtained. Then, by using the concurrence measure, we calculate the degree of entanglement of the atomic system. We observe that the decay rates severely increase near the excitation frequency of the localized plasmon-polariton, while the concurrence value is nearly zero.
Role of Talent Development on Talent Engagement and Self-Efficacy: A Structural Model

Article History The purpose of this research is to examine the influence of talent development (TD) on talent engagement (TE) and self-efficacy (SE). Data were collected through a questionnaire from the trainees of Bangladesh Institute of Human Resource Management (BIHRM). Two hypotheses were developed and tested on the collected data. Structural equation modeling (SEM) is performed which includes both measurement model and structural model. Average variance extracted (AVE), Cronbach’s alpha ( α ), composite reliability (CR) and factor’s loading have been shown under the measurement model whereas path diagram is used to present the relationship among the constructs under the structural model. The results of the study support that talent development has significant impact on both talent engagement and self-efficacy of talented employees. The outcome of the study is highly consistent with the previous literature and the results have strong logical argument. The research implies that organizations should emphasize to improve knowledge and abilities of the talents which foster more attachment and conviction towards jobs as well as enhance the level of talents’ self -efficacy. a unique model which connects talent development, talent engagement and self-efficacy together. Moreover, this study one of very few studies empirically impact on talent engagement self-efficacy talent engagement and self-efficacy. development BIHRM to trainees’ self -efficacy engagement propensity to the in the of engaging talents and self-efficacy of the trainees evaluating the success and effectiveness of training and development to develop employees. The of the to the of of the to in a to perform better the of self-confidence to the of
High-Capacity MVDC Interruption Based on IGCT Current Sharing Integrated With Freewheeling

Medium-voltage dc (MVdc) distribution systems have the advantages of high power density, low line loss and fast system response. However, the high rise rate and large peak value of short circuit current make the fault current interruption a critical problem in MVdc systems. To solve this problem, a novel circuit breaker scheme based on integrated gate-commutated thyristor (IGCTs) current sharing integrated with freewheeling is proposed in this article, which not only can ensure a high breaking capacity and short interruption time in the full current range, but also have superior vacuum interrupter recovery performance and high breaking reliability. The analysis of key factors, including stray parameters, inductance-capacitance (LC) parameters and arcing time, on the current commutation characteristics is presented, and the optimal design principle of the circuit breaker parameters is obtained. Finally, the proposed MVdc circuit breaker is verified with a 64.2 kA/10 kV fault current interruption experiment.
Enhancement Supercapcitive Behaviour of Cobalt(II) Tetrasulfanilamide
Phthalocyanine with Composite rGO on Modified GCE

A novel method for the fabrication of tetrasulfanilamide cobalt(II) phthalocyanine (CoTSPC) was developed and the synthesized product was characterized using various techniques namely UV-visible, infrared and X-ray diffraction spectroscopic and thermal gravimetric analysis. An electrode with glassy carbon was modified on CoTSPC with an rGO composite. The effect of experimental parameters, such as precipitation agent, precursor concentration, reaction time and stabilizing agent, was systematically studied to investigate possible CoTSPC formation. The electrochemical properties of prepared CoTSPC/rGO/GCE were explored through cyclic voltammetry (CV) by using a three-electrode system. The results showed that the specific capacitances and sizes of the fabricated compounds are related. Due to a large surface area, within an operated voltage range of −0.2 to 0.4 V, synthesized CoTSPC/rGO/GCE exhibited an excellent long-cycle life and the highest capacitance (157 F g−1), thereby indicating that fabricated CoTSPC/rGO/GCE can be used as an outstanding electrode material in supercapacitors.
SafeDrive: A New Model for Driving Risk Analysis Based on Crash Avoidance

Driving risk evaluation is a critical issue in driving safety analysis. In traditional driving risk evaluation models, vehicles are analyzed as isolated units. Nevertheless, vehicles are surrounded by other vehicles during driving in a real setting, and therefore, the driving patterns of target vehicles are inevitably affected by surrounding vehicles. In this paper, we proposed a new driving risk evaluation model incorporating the driving patterns of the target vehicle, the driving patterns of surrounding vehicles, and the interactions between the target vehicle and surrounding vehicles to improve driving safety in situations like car-following and merging situations. According to experiments on real data, our proposed method outperformed the state-of-the-art methods by at least 14.2% in terms of precision. Our work verified that factors like the driving patterns of surrounding vehicles and the interactions between a target vehicle and surrounding vehicles can enhance the performance of driving risk evaluation. The experimental results also showed that the driving patterns of surrounding vehicles in different positions vary in evaluating the driving risk of the target vehicle. More specifically, the surrounding vehicles in cross positions casted the strongest influence, followed by the surrounding vehicles in the diagonal cross positions. In summary, our study provided a novel way to enhance driving risk evaluation performance for driving safety improvement.
Self-assembled polyaniline nanotubes grown from a polymeric acid solution

Polyaniline (PANI) nanotubes were obtained by a self-assembly process, from a solution containing poly(methyl vinyl ether-alt-maleic acid) (PMVEA) by oxidative polymerization using ammonium persulfate as the oxidant. The size of the nanotubes was greatly affected by the weight ratio of polymeric acid to aniline as measured by SEM images. The outer diameter of the nanotubes increased from 65 to 160 nm as the weight ratio of PMVEA to aniline increased from 1 to 4 wt/wt%. The structural features of the nanotubes were characterized by FTIR, XPS and EPR spectroscopies, which confirmed the presence of the polymeric acid in the PANI nanotubes and their electronic conductive nature. The electrochemical properties were further analysed using cyclic voltammetry.
A New Application for the Motor Rehabilitation at Home: Structure and Usability of Bal-App

The aim of this paper is to present an innovative tablet-based application with 360° videos for the motor rehabilitation of frail elderly, Bal-App. This app was developed for iPad and exploits the potentiality of 360° videos to improve balance in frail patients through several exercises with an increasing level of difficulty. The app includes 10 sessions to be played 3 times a week for 3 weeks. The results of the usability study are very encouraging, and patients are very interested in trying this app at home like a guide for the motor rehabilitation. Only few non-substantial adjustments before the clinical trial are planned.
Hybrid MAC Protocol for Brain–Computer Interface Applications

Brain–computer interface (BCI) can permit individuals to use their thoughts as the sole means to control objects such as smart homes and robots. While BCI is a promising interdisciplinary tool, researchers are confronting network lifetime as an obstacle to further development. Furthermore, the medium access control (MAC) protocol is the bottleneck of the network reliability. There are many standards for MAC protocols that can be utilized for productive and dependable transmission by altering the control parameters. Modifying these parameters is another source of concern due to the scarcity in knowledge about its effect. In addition, there is no instrument accessible to receive and actualize these parameters on transmitters embedded inside the cerebrum. In this article, we give the transmission instrument to both ultrahigh-frequency (UHF) radio frequency identification (RFID) and ultra-wideband (UWB) signals for multiple transmitters and ultrasonic technology mimicking the neural dusts by modifying the superframe structure. In this article, a hybrid MAC protocol is proposed, and the results show that the traffic received can be increased by 700% for UHF-RFID and more than 100% for UWB and ultrasonic technology. Comparative results for wireless channel MAC protocols using these different transmission techniques are discussed in terms of network delay, data dropped, traffic sent, and traffic received.
The anharmonic potential function of methylene fluoride. SCF ab initio computations of the cubic force field and analysis of vibration-rotation interaction constants

The harmonic and the cubic force fields of CH2F2 have been evaluated ab initio from the SCF energy expression by analytic derivative methods. The computed cubic force constants were used as starting values in a least squares analysis of the experimental vibration–rotation constants of CH2F2 and CD2F2. A simple scaling procedure of the ab initio cubic force constants provides a complete cubic force field for the molecule and the best fit with the experimental data.