Miracle-dz/UniFAR-FTUs huggingface dataset:
Research of parameters affecting sludge digestion process

The parameters characterizing and affecting anaerobic sludge digestion process in three Lithuanian cities are investigated. Results showed that digestion process was effective in all three objects: specific biogas production varied between 0.77 and 0.86 m3/kg volatile solids destroyed, methane content in the biogas varied between 64 and 67% and they complied with the values presented in the scientific references. The increase of VS loading (up to 2.6 kg VS/m3/day) led to the higher level of VS destruction which was up to 59%. The sludge retention time (hydraulic retention time) values must be in ranges of 20–25 days for the digestion process in order to get the design VS destruction, as well the biogas production. In a case of lack of raw materials, the application of wastes from food industry can help to reach the design parameters. The application of wastes from milk industry showed positive results in the digestion process.
Dating Low‐Grade Deformation: Role of Lithology and Strain Partitioning on Ar Isotope Records in the Alpi Apuane of Northern Apennines (Italy)

The Alpi Apuane (northern Apennines) represent a key area for understanding the processes related to the Apennines building and geodynamic evolution of the central Mediterranean, but the timing of tectono‐metamorphic events is still debated. White mica from cover rocks of the Massa and Apuane units was investigated by the 40Ar‐39Ar in situ and step‐heating techniques. Samples recorded several episodes of deformation developed under low‐grade conditions and resulting in a D1 composite schistosity followed by a variably developed D2 retrograde crenulation. In the Massa Unit, D2 crenulation was accompanied by replacement of muscovite‐phengite by paragonite, whereas the composition of phengite from the Apuane Unit does not vary noticeably, irrespective of whether phengite is aligned along D1 or D2 schistosities. Both units exhibit a significant intrasample scatter of in situ ages and variably discordant age spectra from step‐heating data, due to partial reequilibration of white mica along a deformation path lasting ≥10 Ma, with dates approaching the time of younger events as retrogression becomes more pervasive. The onset of deformation has a minimum age of ∼20 Ma, as documented by 40Ar‐39Ar data for the composite D1 foliation in the Massa Unit. D2 deformation shows a common temporal evolution at the scale of the region and is recorded for at least ∼2.5 Ma, starting not after ∼12.5 Ma and ending at ∼10.5 Ma. Results highlight the importance of a detailed microscale characterization and of a careful preselection of samples, as compositionally different domains a few millimeters apart may yield different results because of compositionally driven strain partitioning.
Application of metabolomics on marine sponges and sponge-associated microorganisms: A review

Sponges and their associated microorganisms have tremendous potential in the medical world to be explored. However, improper exploration will cause habitat destruction and cost much. The application of metabolomics to sponges and their associted microbes can be the best solution in their exploration, which involves a combination of chemical profiling and multivariate analysis (chemometrics). In this , we 47 genera of sponges and 24 genera of their associated microorganisms that were studied with a metabolomic approach until July 2021. The sponges most often studied in metabolomics-related research are Geodia , Xestospongia , Agelas and Aplysina . There are four analytical techniques that are often used, namely, liquid chromatography-mass spectrometry, polymerase chain reaction, nuclear magnetic resonance, and gas chromatography-mass spectrometry, in determining the chemical/genomic profile. There are eight chemometric analyses that are often used in metabolomic applications on sponges and their associated microbes, namely, similarity analysis, principal component analysis, hierarchical cluster analysis, partial least square, partial least square-discriminant analysis, orthogonal projections to latent structures, orthogonal projections to latent structures-discriminant analysis, and linear discriminant analysis. The most widely used metabolomic applications for sponges and their associated microbes for the last decade are for identification and dereplication purposes, for quality control purposes, and for the purpose of linking chemical profiles and bioactivity patterns. The purpose of other metabolomic applications, namely, to determine bioavailability to quantitatively determine bioactivity, and to test safety and toxicity, has yet to be carried out because research on sponges and their associated microbes is still around the discovery of new compounds and quality control.
Coupled operation of a wind farm and pumped storage facility: techno-economic modelling and stochastic optimization.

This thesis applies a stochastic programming approach to the techno-economic analysis of a wind farm coupled with a pumped storage facility. The production of an optimal day-ahead generating schedule is considered. Wind forecasts contain an element of random error, and several methods of addressing this uncertainty in the optimization process are compared. The methods include robust and reliabilitybased design optimization in addition to a combination of both approaches, and results indicate that reliability-based design optimization is best-suited to this particular problem. Based on a set of wind forecast error scenarios and historical data, a probability-weighted forecast wind generation scenario set is developed. Reliability constraints are imposed to meet a minimum of 80% of the generating schedule time intervals. This methodology is applied to a case study on Vancouver Island. Preliminary results show that when compared to the base case of a standalone wind farm on Vancouver Island, a wind farm coupled with pumped storage can prove to be economically competitive with pumped storage capital costs below $1.53 million/MW installed pumped storage capacity and a firm energy price of $130/MWh.
Anomaly detection of industrial state quantity time-Series data based on correlation and long short-term memory

ABSTRACT Anomaly detection of multi-dimensional time-series data is a key research area, and the analysis of control, switching, and other state signals (i.e., industrial state quantity time series) is of particular importance to the operational sciences. When only the limited values of industrial state quantities are taken in the discrete set, there is no continuous change trend, making it difficult to achieve good results when applying analogue anomaly detection methods directly. In this study, assuming a correlation between the time series of state and analogue quantities in industrial systems, a model for anomaly detection in state quantity time-series data is built through a correlation supported by long short-term memory, and the model is verified using real physical process data. These results demonstrate that the proposed method is superior to extant industrial time-series models. Thus far, no studies focusing on the anomaly detection of two-state quantity time-series outliers have been performed. We believe that the research problem addressed herein and the proposed method contribute an interesting design methodology for the anomaly detection of time-series data in IIoT.
Analysing the adoption of Lean production in remanufacturing industry

Purpose: This paper aims to analyse the challenges of lean manufacturing implementation in the remanufacturing industry. The research was undertaken in three types of remanufacturing company, torque converter, gearbox, and jet engine remanufacturers. This paper describes the characteristics of remanufacturing companies and compares them with the best practice company adopting lean manufacturing best practice: Toyota Motor Company. Through a comparison of the characteristics of the manufacturing environment, macro, and external condition, the challenges of adopting lean manufacturing are identified.Design/methodology/approach: This study utilised a case study method to analyse qualitative data collected from interviews, observations, and focus group discussions. Although case studies are typically used in inductive research, this study followed a deductive approach.Findings: The analysis demonstrated that remanufacturing companies experience challenges due to contextual differences to the benchmark company. The research found that there are some practices that are embedded in remanufacturing companies, but that the companies do not realise that these are lean manufacturing practices. On the other hand, there are a number of external factors that are beyond the remanufacturers’ control that hinder the adoption of lean manufacturing. In addition, the aftermarket business of remanufacturers has resulted in a number of distinctive macro condition characteristics that make the adoption of lean manufacturing more complex.Practical implications: Successfully addressing barriers to lean manufacturing adoption might enhance the performance of remanufacturing process. This is because the business of remanufacturing is not value creation, but capturing value from used products.Originality/value: This paper contributes to existing literature examining lean production in remanufacturing companies. It is novel in the sense that it is the first study examining lean production in the remanufacturing industry from organisational and managerial perspectives.
Collaborative multiple micro air vehicles’ localization and target tracking in GPS-denied environment from range–velocity measurements

We treat the problem of simultaneous collaborative multiple micro air vehicles’ localization and target tracking using time-varying range and (relative and absolute) velocity measurements. The proposed solution combines robustly local nonlinear observers that estimate the relative positions between agents and their neighbors, and cooperative filters that fuse each agent’s local estimates to globally localize them with respect to the target (and therefore to each other). These estimates are then introduced in a dynamic consensus-type control law that ensures the global collective target tracking while simultaneously estimating the target’s velocity, without needing any external reference which makes it applicable in GPS-denied environments. Finally, a simulation scenario is studied in order to show the efficiency of the proposed solution.
Energy Efficient Flash ADC With PVT Variability Compensation Through Advanced Body Biasing

This brief presents the design of an energy efficient flash analogue-to-digital converter (ADC) with threshold inverter quantiser comparator employing advanced body biasing to compensate for the effects of parameter variability. The proposed calibration scheme is verified against process, voltage, and temperature corners as well as random parameter variability (mismatch). Two proof-of-concept ADCs of 4- and 6-bit precision are designed and verified in simulations in 28 nm fully depleted silicon on insulator technology. The 6-bit converter achieves sampling rate of 3 GS/s, energy efficiency per conversion step below 20 fJ, and precision of 5.2 effective number of bits. The proposed ADC architecture is dedicated to high-speed and low-precision applications, such as communication transceivers and data acquisition systems where area and energy efficiency are paramount.
Syllabus Design in the Action-oriented Curriculum

The Common European Framework of Reference for Languages (CEFR) introduces a new goal for language teaching, that of training social actors rather than mere communicators. Thus, social action as a new reference action corresponding to this new reference goal in English language teaching necessitates a departure from taking interaction or communication as the ultimate goal in an ELT curriculum. This paper argues that mini-projects, which are the best models of social action compatible with the constraints of school education, should be the basic units in an action-oriented curriculum. Syllabus in such an action-oriented curriculum functions primarily as linguistic resources needed by the students to be able to carry out the proposed mini-projects. Thus, the task of the syllabus designer is to select and grade the language content according to the mini-projects proposed in an action-oriented curriculum, even in a second phase, a posteriori control of this content and its progression must be carried out, which may lead, in a third phase, to modify the mini-projects or even their chronological order.
Preterm Infants on Early Solid Foods and Iron Status in the First Year of Life—A Secondary Outcome Analysis of a Randomized Controlled Trial

Introduction of solid foods and iron status in the first year of life of preterm infants are highly discussed topics. The aim of this study was to examine whether two timepoints of introduction of standardized solid foods in preterm infants have an impact on ferritin and other hematologic parameters important for iron status in the first year of life. This is a secondary outcome analysis of a prospective, randomized intervention trial in very low birth weight (VLBW) infants randomized to an early (10–12th week corrected age) or a late (16–18th week corrected age) complementary feeding group. Iron status was assessed with blood samples taken at 6 weeks, 6 months, and 12 months corrected age. In total, 177 infants were randomized (early group: n = 89, late group: n = 88). Ferritin showed no differences between study groups throughout the first year of life, as did all other parameters associated with iron status. At 12 months corrected age, the incidence of iron deficiency was significantly higher in the early feeding group. There is room for improvement of iron status in VLBW preterm infants, regular blood checks should be introduced, and current recommendations may need to be a reconsidered.
Optimal Resource Allocation for Projects

Out of the opportunities available management must decide which ones will be pursued and how many resources will be assigned to each. Usually, these opportunities (projects) are evaluated for economic feasibility, and then the favorable ones pursued. Several questions arise regarding the allocation of available resources to the approved projects: In which order should the projects be done, or should they be done concurrently? How many resources should be assigned to each project? Given the multitude of factors affecting such decisions, one would expect complex formulas to describe the optimal allocation of resources. Contrary to expectations, the formulas describing optimal allocation are intelligible and practical in use.
Computer Vision-Based Structural Displacement Monitoring and Modal Identification with Subpixel Localization Refinement

In conventional structural health monitoring (SHM), the installation of sensors and data acquisition devices will affect the regular operation of structures to a certain extent and is also expensive. In order to overcome these shortcomings, the computer vision- (CV-) based method has been introduced into SHM, and its practical applications are increasing. In this paper, CV-based SHM methods such as template matching and Hough circle transform are described. In order to improve the accuracy of pixel localization, the subpixel localization refinement method is introduced. The displacement monitoring experiment of an aluminum alloy cantilever with three targets is conducted by using the two CV-based SHM methods and the laser displacement sensors simultaneously. The displacement monitoring results of CV-based methods agree well with those measured by the laser transducer system in the time domain. After that, the first two modes of the cantilever are identified from the monitoring results. In addition, the experimental modes identified from the monitoring data and those calculated from the finite element model are also consistent. Therefore, the developed CV-based methods can obtain accurate displacement results in both time and frequency domains, which could be applied to complex structures with more monitoring targets.
IAES International Journal of Artificial Intelligence (IJ-AI)

Received Oct 16, 2021 Revised Apr 5, 2022 Accepted Apr 25, 2022 Monitoring forest cover changes is an important task for forest resource management and planning. In this context, remote sensing images have shown a high potential in forest cover changes detection. In Vietnam, although the existence of a large number of such images and ground-truth labels, current researches still relied on classical methods employed manual indices, such as multi-variant change vector analysis (MVCA) and normalized difference vegetation index. These methods highly require domain knowledge to determine threshold values for forest change that are applicable only for studied areas. Therefore, in this paper, we propose a method to detect coastal forest cover changes, which can exploit available dataset and ground-truth labels. Moreover, the proposed method does not require much domain knowledge. We used multi-temporal Sentinel-2 imagery to train a segmentation model, that is based on the U-Net network. It was used then to detect forest areas at the same location taken at different times. Lastly, we compared obtained results to identify forest disturbances. Experimental results demonstrated that our method provided a high accuracy of 95.4% on the testing set. Furthermore, we compared our model with the MVCA method and found that our model outperforms this popular method by 3.8%.
A family of non-isolated three-port converters based on H-bridge

In order to satisfy the charging and discharging circuits of energy storage element (ESE), a family of non-isolated three-port converter (TPC) by embedding a ESE-centric H-bridge cell into the classic buck, boost and buck/boost converters are proposed. There are two types of embedding method: (1) Without connecting with component of the classic converter, H-bridge is inserted into the classic converter directly. (2) Connected with component of the classic converter in a specific way, the H-bridge is connected with the rest part of the classic converter. The operating mode and port voltage restriction of the obtained TPCs are analyzed and summarized, which features high integration and compact size. Experimental results of one of the proposed TPCs, named LP-3-buck/boost, have been presented to verify the analysis results.
3-(N,N-Diphenylamino)carbazole Donor Containing Bipolar Derivatives with Very High Glass Transition Temperatures as Potential TADF Emitters for OLEDs

Well-defined electroactive bipolar derivatives of new structure have been synthesized from 3-(N,N-diphenylamino)-9H-carbazole and bis(4-fluorophenyl)sulfone, 4-fluorophenylsulfone or 4,4′-difluorobenzophenone, respectively. The full characterization of their structure is described. The amorphous materials with very high glass transition temperatures of 111–173 °C also possess high thermal stability, with onset decomposition temperatures of 351–398 °C. Some of the compounds having the best solubility were tested as the emitters dispersed in 4,4′-bis(N-carbazolyl)-1,1′-biphenyl (CBP) host for preparation of organic light emitting diodes (OLEDs). A device containing 15 wt% of the guest bis[4-{3-(N,N-diphenylamino)carbazol-9-yl}phenyl] sulfone demonstrated the best overall characteristics with maximum brightness exceeding 2630 cd/m2, current efficiency of 3.2 cd/A, power efficiency of 2.2 lm/W, and external quantum efficiency exceeding 1.7% at 100 cd/m2.
Cationic Covalent Organic Framework as Separator Coating for High-Performance Lithium Selenium Disulfide Batteries

Selenium disulfide that combines the advantages of S and Se elements is a new material for Li-chalcogen battery cathodes. However, like Li-S batteries, the shuttle effect seriously restricts the performance of Li-SeS2 batteries. In this work, we have synthesized a kind of nitrogen-rich lithophilic covalent organic framework (ATG-DMTZ-COF) as a separator coating material for Li-SeS2 batteries. Here, the N atom in the ATG-DMTZ-COF channel preferentially interacts with the lithium ion in the electrolyte to form N…Li bond, which significantly improves the diffusion coefficient of lithium ions during the charge and discharge. More importantly, we prove that the pore size of ATG-DMTZ-COF will decrease sharply because there is a large amount of TFSI- in the channel, and finally the shuttling of polysulfide and polyselenide is suppressed by the sieving effect. As a consequence, Li-SeS2 batteries using the ATG-DMTZ-COF separator coating show excellent performances with an initial discharge capacity of 1028.7 mAh g−1 at 0.5 C under a SeS2 loading of 2.38 mg cm−2. Furthermore, when the current density is 1C, the specific capacity of 404.7 mAh g−1 can be maintained after 700 cycles.
Research on Image Retrieval Optimization Based on Eye Movement Experiment Data

Satisfying a user's actual underlying needs in the image retrieval process is a difficult challenge facing image retrieval technology. The aim of this study is to improve the performance of a retrieval system and provide users with optimized search results using the feedback of eye movement. We analyzed the eye movement signals of the user’s image retrieval process from cognitive and mathematical perspectives. Data collected for 25 designers in eye tracking experiments were used to train and evaluate the model. In statistical analysis, eight eye movement features were statistically significantly different between selected and unselected groups of images (p < 0.05). An optimal selection of input features resulted in overall accuracy of the support vector machine prediction model of 87.16%. Judging the user’s requirements in the image retrieval process through eye movement behaviors was shown to be effective.
Controlling Gas Generation of Li-Ion Battery through Divinyl Sulfone Electrolyte Additive

The focus of mainstream lithium-ion battery (LIB) research is on increasing the battery’s capacity and performance; however, more effort should be invested in LIB safety for widespread use. One aspect of major concern for LIB cells is the gas generation phenomenon. Following conventional battery engineering practices with electrolyte additives, we examined the potential usage of electrolyte additives to address this specific issue and found a feasible candidate in divinyl sulfone (DVSF). We manufactured four identical battery cells and employed an electrolyte mixture with four different DVSF concentrations (0%, 0.5%, 1.0%, and 2.0%). By measuring the generated gas volume from each battery cell, we demonstrated the potential of DVSF additives as an effective approach for reducing the gas generation in LIB cells. We found that a DVSF concentration of only 1% was necessary to reduce the gas generation by approximately 50% while simultaneously experiencing a negligible impact on the cycle life. To better understand this effect on a molecular level, we examined possible electrochemical reactions through ab initio molecular dynamics (AIMD) based on the density functional theory (DFT). From the electrolyte mixture’s exposure to either an electrochemically reductive or an oxidative environment, we determined the reaction pathways for the generation of CO2 gas and the mechanism by which DVSF additives effectively blocked the gas’s generation. The key reaction was merging DVSF with cyclic carbonates, such as FEC. Therefore, we concluded that DVSF additives could offer a relatively simplistic and effective approach for controlling the gas generation in lithium-ion batteries.