Miracle-dz/UniFAR-FTUs huggingface dataset:
Intercomparison of Aerosol Instrumental Responses Using AEROTRAK, SMPS, and APS in a Simulated Building

In this work, three aerosol instruments were intercompared by using data collected from field campaigns in a simulated building environment during the last quarter of 2020 from October to December at Oak Ridge National Laboratory. The three aerosol instruments—AeroTrak Model 9110, Scanning Mobility Particle Spectrometer (SMPS) 3080L + 3025A, and Aerodynamic Particle Sizer (APS) 3320—were manufactured by TSI Inc. to perform in situ measurements of particle number concentration in the air. These instruments were co-located in one room in which an aerosol generator was used to produce a defined aerosol population for the instruments to sample and detect in each campaign. The SMPS measured aerosol particles with diameters from 0.01 to 0.7 µ m, APS measured aerosol particles with diameters from 0.5 to 20 µ m, and AeroTrak measured aerosol particles with diameters from 0.1 to 10 µ m. The results suggest that although AeroTrak is fast and easy to use, it does not provide measurements comparable with those obtained by SMPS and APS. The differences in particle counts were orders of magnitude in size (i.e., the AeroTrak data were unreasonably small in the tested scenarios). The results clearly indicate that AeroTrak should not be used in ambient applications in which the level of particle concentration is expected to be high. This would cause difficulty to a campaign in which the dilution factor is unknow a priori. The high particle concentration could also lead to an erroneous aerosol size distribution (e.g., a bimodal size distribution was measured as opposed to a single-mode one). The number concentration limit that AeroTrak is expected to run reliably (i.e., with a counting coincidence error less than ± 10%) is approximately three to four per cubic centimeter. This suggests that the instrument is best used in a clean room environment, not in an ambient or indoor application, such as the Flexible Research Platform campaigns.
Correlation between ESP syllabus design and material adaptation based on needs analysis: A review of literature

This paper aims to review the development of ESP Syllabus design theory and material adaptation based on the need’s analysis of the students. Besides, it explores and presents the references on the relationship between ESP syllabus design and material adaptation. ESP syllabus design deals with the kinds and importance of a syllabus. The materials in it discuss authenticity, material evaluation, and material writing. Need analysis covers the meaning, type, practice, and register of an analysis.
Enrichment of some leafy vegetables with magnesium

Two thirds of the world’s population do not consume the recommended amounts of magnesium (Mg). Hence, there is an increasing interest in producing plants enriched with this element. However, while designing any enrichment treatment, the effects of the amended supply of ions on the quantity, quality and safety of food products must be considered. Leafy vegetables are readily consumed and can be a promising source of Mg and antioxidants. An attempt has been made to evaluate the effect of enriching selected cultivars of lettuce (Romaine lettuce cv. Amadeusz and head lettuce cv. Omega) and endive (cv. Burundi) with Mg (40 – optimal, 80, 120 and 160 mg Mg dm-3) on the (1) concentration of Mg and other elements (K, Ca, Fe and Zn), and the impact of higher Mg concentrations on the (2) biomass accumulation, (3) efficiency of the photosynthetic apparatus, (4) level of reactive oxygen species (ROS), (5) activity of antioxidant enzymes and (6) the content of phenolic compounds. Although plants enriched with Mg had a higher concentration of Mg, they usually contained less Fe. The content of Mg in plants was sufficiently high for them to be considered as an alternative dietary source of this element, but the results varied from species to species. A higher concentration of Mg had a minor effect on the biomass accumulation and the efficiency of the photosynthetic apparatus, but significantly affected the generation of ROS and changed the activity of the examined antioxidant system’s components. These findings demonstrate that enrichment with Mg may simultaneously elevate levels of ROS, which must be taken into consideration prior to implementing any enrichment technology. Among the tested cultivars, endive cv. Burundi proved to be most suitable for Mg enrichment. Plants of this cultivar grown in the presence of Mg in concentrations up to 120 mg Mg dm-3 accumulated considerable amounts of Mg, without any negative side effects.
Creative Activities for a Child with Anxiety Problems: A Case Report

Introduction: This case report aimed to report the effectiveness of creative occupations on a child with anxiety problems in a mental health center in Iran. Case Presentation: This case report has been performed in 12 sessions with a three-month follow-up. The Spence Children's Anxiety Scale (SCAS) and a structured clinical interview were used to collect information. The child's score on SCAS was 66 at the first session, which was then reduced to 41 at the sixth session, and 27 at the twelfth session. The child's father also confirmed the positive effects of the intervention on the child's behavior. Conclusions: Creative occupations showed a positive effect on reducing the severity of anxiety symptoms. These effects remained to a large extent during the intervention.
Phytochemical investigation and thin layer chromatography of methanolic extracts of some selected grain legumes

The experiment was conducted on the following grain legumes: Phaseolus vulgaris, two varieties of Phaseolus lunatus, Vigna unguiculata and Vigna sesquipedalis. It was conducted to characterize them on the basis of their phytochemical properties. Total phenol content ranged between 2.84 and 13.04 mg/g GAE about a mean of 11.27 mg/g GAE. Total flavonoid content also ranged from 2.30 to 14.30 mg/g RUE with a mean of 13.41 mg/g RUE. Alkaloid was present in all the extracts of the samples with exception of white seeded Phaseolus lunatus which did not show any activity. Flavonoid, saponin and terpene were present in all methanolic extracts of all the four samples. A total of 17 different bands were recorded for flavonoid with Rf values ranging between 0.06 and 0.82. Saponin gave a total of 19 different bands with Rf values ranging from 0.08 to 0.93. A total of 15 different bands were recorded for terpenes with Rf values ranging from 0.05 to 0.91. From the phytochemical analysis and the thin layer chromatograph profiles the methanolic extracts of the grain legumes investigated are of medicinal values.
An Accuracy Analysis Comparison of Supervised Classification Methods for Mapping Land Cover Using Sentinel 2 Images in the Al‑Hawizeh Marsh Area, Southern Iraq

Land cover mapping of marshland areas from satellite images data is not a sim‐ ple process, due to the similarity of the spectral characteristics of the land cov‐ er. This leads to challenges being encountered with some land covers classes, especially in wetlands classes. In this study, satellite images from the Senti‐ nel 2B by ESA (European Space Agency) were used to classify the land cover of Al ‐Hawizeh marsh/Iraq ‐Iran border. Three classification methods were used aimed at comparing their accuracy, using multispectral satellite images with a spatial resolution of 10 m. The classification process was performed using three different algorithms, namely: Maximum Likelihood Classification (MLC), Artificial Neural Networks (ANN), and Support Vector Machine (SVM). The classification algorithms were carried out using ENVI 5.1 software to detect six land cover classes: deep water marsh, shallow water marsh, marsh vegetation (aquatic vegetation), urban area (built ‐up area), agriculture area, and barren soil. The results showed that the MLC method applied to Sentinel 2B imag‐ es provides a higher overall accuracy and the kappa coefficient compared to the ANN and SVM methods. Overall accuracy values for MLC, ANN, and SVM methods were 85.32%, 70.64%, and 77.01% respectively.
CO2-plant effects do not account for the gap between dryness indices and projected dryness impacts in CMIP6 or CMIP5

Recent studies have found that terrestrial dryness indices like the Palmer Drought Severity Index (PDSI), Standardized Precipitation Evapotranspiration Index (SPEI), and Aridity Index calculated from future climate model projections are mostly negative, implying a drying land surface with warming. Yet, the same models’ future runoff and bulk soil moisture projections instead show regional signals of varying sign, and their vegetation projections show widespread greening, suggesting that the dryness indices could overstate climate change’s direct impacts. Most modeling studies have attributed this gap to the indices’ omission of CO2-driven stomatal closure. However, here we show that the index-impact gap is still wide even in future-like model experiments that switch off CO2 effects on plants. In these simulations, mean PDSI, Aridity Index, and SPEI still decline broadly with strong warming, while mean runoff, bulk soil moisture, and vegetation still respond more equivocally. This implies that CO2-plant effects are not the dominant or sole reason for the simulated index-impact gap. We discuss several alternative mechanisms that may explain it.
Effect of Cross-Orientation Normalization on Different Neural Measures in Macaque Primary Visual Cortex

Abstract Divisive normalization is a canonical mechanism that can explain a variety of sensory phenomena. While normalization models have been used to explain spiking activity in response to different stimulus/behavioral conditions in multiple brain areas, it is unclear whether similar models can also explain modulation in population-level neural measures such as power at various frequencies in local field potentials (LFPs) or steady-state visually evoked potential (SSVEP) that is produced by flickering stimuli and popular in electroencephalogram studies. To address this, we manipulated normalization strength by presenting static as well as flickering orthogonal superimposed gratings (plaids) at varying contrasts to 2 female monkeys while recording multiunit activity (MUA) and LFP from the primary visual cortex and quantified the modulation in MUA, gamma (32–80 Hz), high-gamma (104–248 Hz) power, as well as SSVEP. Even under similar stimulus conditions, normalization strength was different for the 4 measures and increased as: spikes, high-gamma, SSVEP, and gamma. However, these results could be explained using a normalization model that was modified for population responses, by varying the tuned normalization parameter and semisaturation constant. Our results show that different neural measures can reflect the effect of stimulus normalization in different ways, which can be modeled by a simple normalization model.
Countertransference in Forensic Patients with Psychosis: Associations with Symptomatology, Inpatient Violence, and Psychopathic Personality Traits

ABSTRACT Countertransference can instigate poor or even iatrogenic treatment effects. This study investigated the extent to which psychotic symptoms, inpatient violence and disruptive behavior, and psychopathic/antisocial personality traits are associated with countertransference. Eighty-nine patients with psychotic disorders in a forensic medium-secure unit were assessed twice for countertransference using the Therapist Response Questionnaire. We found that psychopathic/antisocial personality traits had a larger impact on countertransference in patients than did psychotic symptoms and inpatient violence and behavior. Although differences existed between psychologists/psychiatrists and nursing personnel, all patient-related variables were associated with increased negative countertransference and decreased positive countertransference. Differences in association magnitude and clinical implications are discussed.
Finding optimal hyperparameters of feedforward neural networks for solving differential equations using a genetic algorithm

In this work, feedforward neural networks are used to solve 2D Laplace equation on rectangular domains. Optimal values of weights and biases of a network are recursively computed during the network training by minimizing a least-squares loss function using data at collocation points to approximate the true solution. The performance of the network largely depends on network architecture and model capability. In this work, an optimal set of hyperparameters is searched on various values of relative error. The genetic algorithm is used to find the optimal activation function, optimization algorithm, and weight initialization. In addition, we also searched for the optimal value of the number of hidden layers for a specific value of total parameters. Numerical results show that we can successfully obtain an optimal set of hyperparameters that is consistent across many values of relative error.
Characteristic Thermal Parameters in Electric Motors: Comparison Between Induction- and Permanent Magnet Excited Machine

The thermal modeling and design process of highly utilized electric machines is a complex task. The main heat paths within an electric drive are influenced by a variety of different thermal interfaces, that can mainly be described by thermal conduction and convection. The proper selection and estimation of these design parameters is challenging especially in the early design stage. This paper provides a systematic investigation evaluating inaccuracies and design influences of single thermal resistances, such as the convective heat transfer in the rotor-stator annulus, in the cooling jacket or interfaces between different machine components. Within the study, electromagnetic finite element models and thermal lumped parameter models of two traction drives are developed and validated using test bench measurements. The thermal design parameters are varied in a range resulting from intensive literature research and own laboratory experience. The influence of the design parameters in different operational points of the drives are studied in a sensitivity analysis.
Factors Affecting Young Adults’ Willingness to Try Novel Health-Enhancing Nature-Based Products

Abstract One of the megatrends that affects consumers’ preferences is a growing interest in health, well-being and self-care. This study explores consumer perceptions of a health-enhancing nature-based substance. Based on a survey data (N = 944) collected among national and international students in Finland, we examined factors that affect young adults’ willingness to try products containing the substance. The results showed a relatively high willingness to try the products, particularly among female and non-Finnish respondents. Relationship to nature and beliefs related to the health benefits or risks of soil microbes influenced willingness to try products. The results highlight the importance of accounting for consumer perceptions in the innovation process.
Joint Resource Allocation for Linear Precoding in Downlink Massive MIMO Systems

We study joint proportional-fair (PF) resource allocation (RA), including user selection, linear precoding design, power optimization, and modulation and coding scheme selection, in a single-cell downlink massive MIMO (m-MIMO) system over consecutive time-slots when taking per-antenna power constraints (PAPCs) into account. We formulate the general PF joint RA optimization problem as a weighted sum-rate maximization problem at each time-slot and develop a solution technique to obtain a quasi-optimal feasible solution via the introduction of auxiliary variables and a carefully chosen approximation of the spectral-efficiency function. To obtain results for larger settings (i.e., larger number of antennas and users), we propose an approximation to the general problem that yields quasi-optimal feasible solutions. Moreover, we consider state-of-the-art linear precoding techniques and propose a general heuristic RA scheme that takes PAPCs into account. Numerical results show that PAPCs have significant impact on performance even for a very large number of antennas, and that the best existing linear precoding technique, RZFT (regularized zero-forcing transmission) performs very well when RA is performed carefully as long as the PAPCs are not tight. However, RZFT is far from optimal under tight PAPCs, which highlights the need for practical PAPC-aware precoding techniques in this regime.
Investigation on rejection efficiency, flux and morphology of PES-surfactant membranes using RSM-CCD methodology and SEM assessment

A well-functioning membrane such as high rejection efficiency and high flux rate is indeed the main goal in a study. In fact, so many studies on the factors that affect the membrane are carried out, such as pressure rate, polymer type, additive type, temperature effect during fabrication and so on. Therefore, the development of analytical modeling is vital to predict the optimal performance in good membrane production. Therefore, in this study, the main objective is to develop analytical modeling using Response Surface (RS) methodology for Sodium Dodecyl Sulfate (SDS) surfactant membrane, and also to determine the factors used such as polymer concentration and dye concentration in the experiment is statistically significant. The performance selected in this study were the rejection efficiency and the flux rate. Through the choice of Central Composite Design (CCD) that have been selected from the RS methodology, analytical modeling has been made through the development of an experimental framework that will be used to collect input. Modeling from the RS methodology will provide insights to predict the relationship between response parameters as well as statistically significant factors between input and output. Through the experimental data collected, the data were processed through ANOVA to determine the statistical validation of the adopted RS methodology. From the results of the experiments, the highest rejection efficiency and flux rate were 99.3% and 43.962 (L.m2 / h), respectively. 3D graphs, 2d contours, and equations for rejection efficiency and flux rate were developed as a result of analysis of Variance (ANOVA). Membrane surface morphology was analysed using Scanning Electron Microscopy (SEM) in determining membrane structures such as macrovoids, finger-like and spongy.
GENERATIONAL DYNAMICS, SOCIAL POSITIONS AND POLITICAL BEHAVIOR

RESUMO Apresentamos, neste artigo, uma discussão de caráter eminentemente teórico, com implicações metodológicas, a respeito da formação e da transformação de opiniões, comportamentos e atitudes políticas a partir dos processos de transmissão e herança de posições sociais, ao longo do curso da vida. Assim, os comportamentos políticos, constituídos em função de múltiplas variáveis, seriam também determinados pela realização ou frustração de projetos intergeracionais de transmissão e herança de posições sociais, o que é vivenciado de modo diverso nas diferentes etapas da vida. Para tanto, apoiamos-nos em uma discussão com autores(as) franceses(as), em especial, Pierre Bourdieu, Annick Percheron e Anne Muxel, bem como no diálogo com a produção bibliográfica brasileira da última década sobre o tema.
Characterization and Predictive Analysis of Volatile Financial Markets Using Detrended Fluctuation Analysis, Wavelet Decomposition, and Machine Learning

This paper proposes a granular framework for examining the dynamics of stock indexes that exhibit nonparametric and highly volatile behavior, and subsequently carries out the predictive analytics task by integrating detrended fluctuation analysis (DFA), maximal overlap discrete wavelet transformation (MODWT), and machine learning algorithms. DFA test ascertains the key temporal characteristics of the daily closing prices. MODWT decomposes the time series into granular components. Four pattern recognition algorithms—adaptive neuro fuzzy inference system (ANFIS), dynamic evolving neural-fuzzy inference system (DENFIS), bagging and deep belief network (DBN)—are then used on the decomposed components to obtain granular level forecasts. The entire exercise is performed on daily closing prices of Dow Jones Industrial Average (DJIA), National Stock Exchange of India (NIFTY), Karachi Stock Exchange (KSE), Taiwan Stock Exchange (TWSE), Financial Times Stock Exchange (FTSE), and German Stock Exchange (DAX). MODWT-Bagging and MODWT-DBN appear as superior forecasting models.
Structural Safety Evaluation of Tunnel Based on the Dynamic Monitoring Data during Construction

It is still a challenge to accurately evaluate the structural safety of tunnel during the process of construction. To address this issue, a safety evaluation approach of tunnel based on the monitoring data during construction is proposed in this study. Firstly, the detailed description of modelling the tunnel excavation, releasing the load acting on the tunnel, and selecting the constitutive relationship of surrounding rock of tunnel is introduced. Secondly, aiming at an actual shallow-buried tunnel with underground excavation, utilizing the analytical results of deformation of tunnel, the structural safety of tunnel is evaluated by using a reliability-based method. Finally, the effectiveness of the proposed method is demonstrated by using the dynamic monitoring data obtained during the construction of an actual tunnel.
Development of novel deep multimodal representation learning‐based model for the differentiation of liver tumors on B‐mode ultrasound images

Recently, multimodal representation learning for images and other information such as numbers or language has gained much attention. The aim of the current study was to analyze the diagnostic performance of deep multimodal representation model‐based integration of tumor image, patient background, and blood biomarkers for the differentiation of liver tumors observed using B‐mode ultrasonography (US).
On the Impact of Open Parcel Lockers on Traffic

The last-mile in the courier express parcel (CEP) sector is the most challenging part of the overall transport chain. This is, among other reasons, because many recipients are not at home when deliveries take place. On the other hand, it is for many recipients inconvenient that they have to collect their parcels at different pickup shops varying from logistics service provider (LSP) to LSP. One solution is to employ (open) parcel lockers which are conveniently located for recipients and which allow successful (first) deliveries for LSPs. In this paper, we investigate the impact of parcel lockers with respect to traveled distances as well as CO2 emissions. We show that under certain situations, parcel lockers positively contribute to both aforementioned performance indexes. Based on our observations, we formulate recommendations how to support the implementation of parcel lockers.
Modeling, approximation, and time optimal temperature control for binder removal from ceramics

The process of binder removal from green ceramic components-a reaction-gas transport problem in porous media-has been analyzed with a number of mathematical techniques: 1) non-dimensionalization of the governing decomposition-reaction ordinary differential equation (ODE) and of the reaction gas-permeability partial differential equation (PDE); 2) development of a pseudo steady state approximation (PSSA) for the PDE, including error analysis via \begin{document}$ L^2 $\end{document} norm and singular perturbation methods; 3) derivation and analysis of a discrete model approximation; and 4) development of a time optimal control strategy to minimize processing time with temperature and pressure constraints. Theoretical analyses indicate the conditions under which the PSSA and discrete models are viable approximations. Numerical results indicate that under a range of conditions corresponding to practical binder burnout conditions, utilization of the optimal temperature protocol leads to shorter cycle times as compared to typical industrial practice.