Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Pressure Response at an Observation Well against Pressure Build-Up by Early Stage of CO2 Geological Storage Project

To ensure a safe and stable CO2 storage, pressure responses at an observation well is expected to be an important and useful field monitoring items to estimate the CO2 storage behaviors and the aquifer parameters during and after injecting CO2, because it can detect whether the injected CO2 leaks to the ground surface or the bottom of the sea. In this study, pressure responses were simulated to present design factors such as well location and pressure transmitter of the observation well. Numerical simulations on the pressure response and the time-delay from pressure build-up after CO2 injection were conducted by considering aquifer parameters and distance from the CO2 injection well to an observation well. The measurement resolution of a pressure transmitter installed in the observation well was presented based on numerical simulation results of the pressure response against pressure build-up at the injection well and CO2 plume front propagations. Furthermore, the pressure response at an observation well was estimated by comparing the numerical simulation results with the curve of CO2 saturation and relative permeability. It was also suggested that the analytical solution can be used for the analysis of the pressure response tendency using pressure build-up and dimensionless parameters of hydraulic diffusivity. Thus, a criterion was established for selecting a pressure transducer installed at an observation well to monitor the pressure responses with sufficient accuracy and resolution, considering the distance from the injection well and the pressure build-up at the injection well, for future CCS projects.
Carrot Yield and Shape Altered by Seeding Rate and Raised Beds in Clay-loam Soil

Carrots (Daucus carota L. var sativus) in the midwestern United States are generally raised commercially on sandy-loam or muck soils. Some smaller growers may not have the luxury of an ideal soil type, so raised beds are often recommended to improve taproot growth. To determine specific yield and shape responses of carrots to raised-bed culture in heavy soil, three hybrids (‘Cupar’, ‘Envy’, and ‘Naval’) were grown in 2019 and 2020 on raised or flat beds in clay-loam soil. In addition, two seeding rates (high or low) were incorporated into the split-split plot design. ‘Cupar’ was larger and less misshapen than the other hybrids, but total marketable yields were similar among all three. ‘Naval’ was the most cylindrical. High seeding rate generally resulted in more numerous but smaller marketable roots and no change in total marketable weight. Raised beds caused a 10.6% increase in total marketable weight by allowing more marketable roots classified as “short” (between 76 and 127 mm long, diameter >25 mm) to grow to lengths more than 127 mm long. The average taproot cylindricity was increased and diameter decreased by growing on raised beds. Soil penetration resistance at 7.6 cm was correlated with many of the measured responses.
Review On Reduction And Partial Oxidation of Organics In Photocatalytic (Membrane) Reactors

Traditional processes for making chemicals are unsustainable in terms of resources and environmental impact. The present pa- per is a review of the most recent advances in the application of selective photocatalytic reactions to organic synthesis, which, in the last years, has attracted the interest of the scientific community addressing on development of environmentally benign synthetic processes. Indeed, selective photocatalysis is operated at ambient temperature and pressure, needs no complex equipments, does not use dangerous chemical reagents and solvents, does not release harmful wastes into the environment and can utilize solar light. Reactions discussed in this paper, as a green approach for valuable fine chemical synthesis, are: i) photocatalytic hydrogenation and/or transfer hydrogenation of ketones and nitrocompounds by using both UV and visible light; ii) photocatalytic hydrogenation and selective partial hydrogenation of unsaturated compounds; iii) selective partial oxidation of alkanes, alkenes, alcohols, aliphatic acids, benzene and other aromatic com- pounds by using both UV and visible light. Use of Photocatalytic Membrane Reactors (PMRs) in reductions (e.g. CO2 to fuels) and in se- lective partial oxidations (e.g. benzene to phenol) is reported, evidencing that opening up of a new avenue is expected in organic synthe- ses, thanks to the synergy of heterogeneous photocatalysis and membrane processes. Nevertheless, these studies are still at nascent stady and much work is needed before taking advantage of PMRs potentiality at industrial level in this interdisciplinary area.
Inner and Outer Voices in Research: How Dialogical Approaches Can Enhance Knowledge Development in Mental Healthcare

This article contributes methodological reflections on how dialogical and reflective approaches can enhance many voices in research. An epistemological assumption in research with a participatory design is that knowledge can be developed by collaborative processes between researchers and individuals with lived experiences. The study was conducted by arranging a reflective process meeting with different participants: researchers and mental health service providers and users. Using reflective thematic analysis and an analytical perspective, it describes the reflec- tive process as the tailoring of different voices , which is a way of facilitating research that enables different participants to contribute their experiences in a dialogical process. The findings show that reflective processes can encourage people to both listen and talk and, in that sense, have both inner and outer dialogues that endorse the use of different types of knowledge, including research and lived experiences, to create new understandings together. This can have an impact on both collaborative research and practice in mental health services. it. Push ahead again, even though they have had many bad experiences. They give us a chance. So I can feel that I have a strong respect for that. It costs a lot .
Control of A Tomato Plant Root-Knot Nematode By Induced Resistance Of Oxalic Acid Derived From Aspergillus Niger

Aspergillus niger F22 producing oxalic acid (OA) as a nematicidal component is currently used as a microbial nematicide. OA is known to induce systemic resistance in plant diseases caused by fungi, bacteria, and viruses, but the induced resistance of OA has not yet been elucidated in plant diseases caused by root-knot nematodes (RKNs). In this study, we investigated the functional mechanism of induced resistance of A. niger F22 formulation (Nemafree, 20% SC) and OA in tomato plant RKN disease caused by Meloidogyne incognita and analyzed their effectiveness against the disease. Foliar spray and soil drench treatments of Nemafree and OA were effective in the management of M. incognita in tomato plant in-pot experiments. When Nemafree and OA were applied 4 days before inoculation of M. incognita eggs, the treatments of Nemafree (4,000-fold dilution) and OA (0.22 mM) reduced root gall formation by more than 50%. The soil drench treatment also effectively suppressed RKN disease in field experiments. Moreover, the treatments of Nemafree and OA enhanced the transcriptional expression of pathogenesis-related 1 gene, plant proteinase inhibitor-II, and polyphenol oxidase genes and improved the production of total phenols, flavonoids, and lignin in the tomato plants infected with M. incognita. These results demonstrate that RKN diseases can be effectively controlled by induced resistance even at low concentrations of Nemafree or OA. Accordingly, our study provides evidence for more economical and efficient application strategies of microbial nematicides that control RKNs under field conditions.
Effects of Occupational Drivers’ Traffic Accident History on Risk Perception, Work Attitudes, and Unstable Driving

In previous studies the risk perception of future accidents was the main variable likely to affect safe driving. However, findings on the relationship between traffic accident history and risk perception of future accidents have been inconsistent. Moreover, in the case of occupational drivers, work attitudes could be the main factor affecting safe driving. However, no research has been conducted on the direct relationship between traffic accident history and work attitudes. Therefore, present study examined the effect of occupational drivers’ traffic accident history on their risk perception, work attitudes, and unstable driving. Data analysis was based on a self-reported survey of Korean occupational drivers (n = 388) and their official traffic accident records. Results show that traffic accident history was associated significantly with professional pride, job satisfaction, and aggressive driving but not with risk perception of future accidents or job stress. Moreover, all variables measuring unstable driving behavior were significantly related to professional pride, job satisfaction, and job stress. Furthermore, professional pride turned out to mediate the relationship between traffic accident history and current unstable driving. The major finding is that there is no significant relationship between traffic accident history and risk perception of future accidents. Furthermore, traffic accident history has a significant effect on positive variables such as professional pride and job satisfaction but not on negative variables such as job stress. In addition, the significant mediator in the relationship between traffic accident history and current unstable driving behavior was only professional pride.
Policy manifold generation for multi-task multi-objective optimization of energy flexible machining systems

Abstract Contemporary organizations recognize the importance of lean and green production to realize ecological and economic benefits. Compared with the existing optimization methods, the multi-task multi-objective reinforcement learning (MT-MORL) offers an attractive means to address the dynamic, multi-target process-optimization problems associated with Energy-Flexible Machining (EFM). Despite the recent advances in reinforcement learning, the realization of an accurate Pareto frontier representation remains a major challenge. This article presents a generative manifold-based policy-search method to approximate the continuously distributed Pareto frontier for EFM optimization. To this end, multi-pass operations are formulated as part of a multi-policy Markov decision process, wherein the machining configurations witness dynamic changes. However, the traditional Gaussian distribution cannot accurately fit complex upper-level policies. Thus, a multi-layered generator was designed to map the high-dimensional policy manifold from a simple Gaussian distribution without performing complex calculations. Additionally, a hybrid multi-task training approach is proposed to handle the mode collapse and large task difference observed during the improvement of the generalization performance. Extensive computational testing and comparisons against existing baseline methods have been performed to demonstrate the improved Pareto frontier quality and computational efficiency of the proposed algorithm.
Radio Frequency Fingerprint Identification for Narrowband Systems, Modelling and Classification

Device authentication is essential for securing Internet of things. Radio frequency fingerprint identification (RFFI) is an emerging technique that exploits intrinsic and unique hardware impairments as the device identifier. The existing RFFI literature focuses on experimental exploration but comprehensive modelling is missing. This paper systematically models impairments of transmitter and receiver in narrowband systems and carries out extensive experiments and simulations to evaluate their effects on RFFI. The modelled impairments include oscillator imperfections, imbalance of inphase (I) and quadrature (Q) branches of mixers and power amplifier (PA) nonlinearity. We then propose a convolutional neural network-based RFFI protocol. We carry out experimental measurements over three months and demonstrate that oscillator imperfections are not suitable for RFFI due to their unpredictable time variation caused by temperature change. Our simulation results show that our protocol can classify 50 and 200 devices with uniformly and randomly distributed IQ imbalances and PA nonlinearities with high accuracy, namely 99% and 89%, respectively. We also show that the RFFI has some tolerance on different receiver imbalances during training and classification. Specifically, the accuracy is shown to degrade less than 20% when the residual receiver’s gain and phase imbalances are small. Based on the experimental and simulation results, we made recommendations for designing a robust RFFI protocol, namely compensate carrier frequency offset and calibrate IQ imbalances of receivers.
A Hybrid Seasonal Box Jenkins-ANN Approach for Water Level Forecasting in Thailand

Every year, many basins in Thailand face the perennial droughts and floods that lead to the great impact on agricultural segments. In order to reduce the impact, water management would be applied to the critical basin, for instance, Yom River basin. An importing task of management is quantitative prediction of water that is stated by water level. This study proposes the hybridized forecasting models between the stochastic approaches, seasonal autoregressive integrated moving average (SARIMA) models and machine learning approach, artificial neural network (ANN). The proposed hybrid model is called seasonal autoregressive integrated moving average and artificial neural network or SARIMANN model for average monthly water level (AMWL) time series of Yom River basin. The study period is from April 2007 to March 2020, over thirteen hydrological years. The forecasting performance is the minimum values of root mean squared error (RMSE) and mean absolute percentage error (MAPE) between SARIMA models, ANN models, and SARIMANN models. Results indicated that: The three models reveal the similarity of RMSE and MAPE for both four water level measurement stations for wet and dry seasons. The forecasting performance is the minimum values of RMSE and MAPE of three models. The SARIMA model is the best approach for Y.31 Station [Wet Season], Y.20 Station [Wet Season], Y.37 Station [Wet Season], Y.31 Station [Dry Season], Y.20 Station [Dry Season], and Y.1C Station [Dry Season, while the best method for Y.37 Station [Dry Season] is ANN model, furthermore the SARIMANN model is the best approach for Y.1C Station [Wet Season]. All methods have delivered the similar results in dry season, while both SARIMA and SARIMANN are better than ANN in wet season by RMSE for all stations. Even though the downstream is affected by many disturbances, it is still more accurate than the upstream. This is the visible evidence to indicate that the stochastic based models, SARIMA and SARIMANN proposed in this study are appropriate for the high fluctuation series. Furthermore, the dry season forecasting is more accurate than the wet season.
Performance Enhancement and Mechanistic Studies of Room-Temperature Sodium–Sulfur Batteries with a Carbon-Coated Functional Nafion Separator and a Na2S/Activated Carbon Nanofiber Cathode

Operation of sodium–sulfur batteries at room temperature has been proposed and studied for about a decade, but polysulfide-shuttle through the traditional battery separator and low-utilization of the sulfur cathode commonly have been the major challenges. Also, because of the highly active nature of the sodium metal, the conventional room temperature sodium–sulfur (RT Na–S) battery concept with the sodium–metal anode and elemental sulfur cathode imposes serious safety concerns. To overcome the above difficulties, we present here a RT Na–S system with an advanced membrane-electrode-assembly (MEA) comprising a carbon-coated, presodiated Nafion membrane (Na-Nafion) and a sodium sulfide (Na2S) cathode. The Na-Nafion membrane provides a facile Na+-ion conductive path and serves as a cation-selective shield to prevent the migration of the polysulfides to the anode. The carbon coating on the Na-Nafion plays an upper-current-collector role and thereby improves the electrochemical utilization of the active Na2S. E.
Electromagnetic Transparency of Composites of Unsaturated Polyester and Nanolignin: Morphological and Surface Energy Considerations

We introduce a simple spray drying method for the scaleup production of spherical organic (lignin) microparticles with controlled size distribution (0.85 to 1.57 mm). We assess the surface energy of the lignin particles by inverse gas chromatography and determine its role in nanocomposites synthesized from unsaturated polyester. Such nanocomposites are shown to be irradiation transparent (millimeter frequency region). The permittivity and tan d of the composite material reached values between 0.01 and 3.1 (28 GHz) with 10 per hundred resin filler content. Vinyl groups were introduced on the surface of the particles to achieve enhanced interfacial adhesion, and resulted in a reduced relative permittivity (2.75). Together with wave interactions, the mechanical and thermal properties of the composites are placed in perspective, opening new opportunities in next generation bio-based devices for 5G high-speed communication.
Ab Initio Determination of Ground and Excited State Oxidation Potentials of Organic Chromophores for Dye-Sensitized Solar Cells

Ab initio calculations of the ground state oxidation potential (GSOP) and excited state oxidation potential (ESOP) are reported for a set of four triphenylamine-based dyes for dye-sensitized solar cell (DSSC) applications, with increasing degree of charge transfer. The performance of DFT in predicting GSOP is evaluated by employing various exchange-correlation (x-c) functionals, with different amounts of Hartree−Fock exchange and different combinations of correlation functionals. The choice of the correlation part of the x-c functional was crucial in getting accurate GSOPs. For excited state geometry optimizations, needed to calculate the adiabatic excitation energies E0−0 and therefore the ESOPs, the use of hybrid functionals with a large amount (∼50%) of nonlocal Hartree−Fock exchange has been shown to be mandatory to avoid the formation of artificial minima in correspondence of a twisted geometries with a high degree of charge transfer. Our results show that a proper DFT/TDDFT approach can provide a re.
CT Image Segmentation Method of Liver Tumor Based on Artificial Intelligence Enabled Medical Imaging

Artificial intelligence (AI) has made various developments in the image segmentation techniques in the field of medical imaging. This article presents a liver tumor CT image segmentation method based on AI medical imaging-based technology. This study proposed an artificial intelligence-based K-means clustering (KMC) algorithm which is further compared with the region growing (RG) method. In this study, 120 patients with liver tumors in the Post Graduate Institute of Medical Education & Research Hospital, Chandigarh, India, were selected as the research objects, and they were classified according to liver function (Child–Pugh), with 58 cases in grade A and 62 cases in grade B. The experimentation indicates that liver tumor showed low density on plain CT scan, moderate enhancement in the arterial phase of the enhanced scan, and low-density filling defect in the involved blood vessel in the portal venous phase (PVP). It was observed that the CT examination is more sensitive to liver metastasis than hepatocellular carcinoma ( P < 0.05 ). The outcomes obtained depict the good deposition effect of lipiodol chemotherapy emulsion (LCTE) in the contrast group with rich blood type accounted for 53.14% and the patients with the poor blood type accounted for 25.73% showed poor deposition effect. The comparison with the state-of-the-art method reveals that the segmentation effect of the KMC algorithm is better than that of the conventional RG method.
Impact of probiotic intake on the glycemic control, lipid profile and inflammatory markers among patients with type 2 diabetes mellitus

Background and aims: Type 2 diabetes mellitus (T2DM) is a chronic disease with many dramatic complications. It has also been suggested that altered intestinal microbiota leads to increased intestinal permeability and mucosal immune response, contributing to the development of diabetes. We aimed to investigate the effect of introduction of probiotic products on glycemic control and inflammatory markers among patients with T2DM. Methods: the present work was carried on 150 patients with T2DM. The studied patients were subjected to full history taking, clinical examination and laboratory investigations including fasting blood glucose (FBG), 2 hours post prandial blood glucose (2hpp), glycated hemoglobin (HbA1c), total cholesterol (TC), triglycerides (TG), HDL-C, LDL-C, C-reactive protein (CRP), interleukin 6 (IL6) and tumor necrosis factor alpha (TNF α). They were divided into 3 groups each of 50 patients, they were all instructed to eat well balanced diet. The first group was instructed to eat the well balanced diet only, the second group received 2 cups of yogurt daily in addition to diet and the third group received one teaspoonful yeast daily in addition to diet. The effect of the intervention was evaluated after 16 weeks. Results: Patients receiving yogurt and the patients receiving yeast showed significant reduction of FBG,HbA1c, IL6, TNF α, CRP and significant elevation of HDL-C compared to patients on diet only. The 3 groups showed significant reduction in 2hpp blood glucose and LDL-C. Conclusion: Probiotic intake in patients with T2DM has beneficial effect on glycemic control, lipid profile and inflammatory markers after 16 weeks.
Dietary quality indices modify the effects of apolipoprotein B polymorphisms on cardio-metabolic risk factors in type 2 diabetes mellitus 

We tried to identify the interaction between dietary quality indices and apolipoprotein B Ins/Del and EcoR1 polymorphisms on cardio-metabolic risk factors in patients with type 2 diabetes mellitus (T2DM). This cross-sectional study recruited 700 adults with T2DM in Tehran. The genotypes of Ins/Del and EcoR1 single nucleotide polymorphisms (SNP) were explored via polymerase chain reaction (PCR). Dietary quality index-international (DQI-I), healthy eating index-2015 (HEI-2015) and dietary phytochemical index (DPI) were calculated by semi-quantitative food frequency questionnaire (FFQ). In both crude and adjusted model for confounding factors, we observed significant interactions between DQI-I and Ins/Del SNP on leptin in and 8-iso-prostaglandin F2 α (8-iso-PGF2α), DPI and EcoR1 SNP on total cholesterol (TC) and between Ins/Del SNP and HEI-2015 on interleukin-18 (IL-18). Furthermore, in crude model there were close to meaningful interactions between EcoR1 SNP and DQI-I on total antioxidant capacity (TAC) and between EcoR1 SNP and HEI-2015 on serum leptin and superoxide dismutase (SOD) levels. Our finding indicated that the association between DQI-I, HEI-2015 and DPI with IL-18, TC, leptin and 8-iso-PGF2α in patients with T2DM might be dependent on Ins/Del and EcoR1 variants in ApoB gene.