Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Sensor Aboveground Biomass Estimation in the Broadleaved Hyrcanian Forest of Iran

Abstract In this study, the capability of Landsat-8 (L8), Sentinel-2 (S2), Sentinel-1 (S1), and their combination was investigated for estimating aboveground biomass (AGB). A pure stand of Fagus Orientalis located in the Hyrcanian forest of Iran was selected as the study area. The performance of a parametric approach, i.e., Multiple Linear Regression (MLR) model and non-parametric approaches, i.e., k-Nearest Neighbor (k-NN), Random Forest (RF), and Support Vector Regression (SVR), were also evaluated for AGB estimations. Our results indicated that among S2 metrics, the FAPAR canopy biophysical index and NDVI index based on the red-edge band (NIR-b8a) have the highest correlation coefficient (r) of 0.420 and 0.417, respectively. The results of AGB estimation showed that a combination of S2 and S1 datasets using the k-NN algorithm had the best accuracy (R 2 of 0.57 and rRMSE of 14.68%). The best rRMSE using L8, S2, and S1 datasets was 18.95, 16.99, and 19.17% using k-NN, k-NN, and MLR algorithms, respectively. The combination of L8 with S1 dataset also improved the rRMSE relative to L8 and S1 separately by 0.96 and 1.18%, respectively. We concluded that the combination of optical data (L8 or S2) with SAR data (S1) improves the broadleaved Hyrcanian AGB estimation.
Normal Pressure Hydrocephalus: Revisiting the Hydrodynamics of the Brain

Normal pressure hydrocephalus syndrome is the most common form of hydrocephalus in the elderly and produces a dementia which can be reversible surgically. It is characterized by ventriculomegaly and the classic triad of symmetric gait disturbance, cognitive decline and urinary incontinence, also known as Hakim’s triad. To date, the exact etiology of the disease has not been elucidated and the only effective treatment is a cerebrospinal fluid shunting procedure which can be a ventriculoatrial, ventriculoperitoneal or lumboperitoneal shunt. The most important problem is the high rate of underdiagnosis or misdiagnosis due to similarities in symptoms with other neurodegenerative disorders, and in some cases, coexistence. Hence, increasing awareness amongst the community and medical professionals in order to increase clinical suspicion, timely diagnosis and treatment are paramount. The best way to achieve this is by having a structured protocol with patient-centered tests that evaluates the entire myriad of alterations a clinician might encounter whenever treating patients with this disorder. Recent advances in imaging technology as well as cerebrospinal fluid biomarkers have given interesting insight into the pathophysiology of the disease and will certainly contribute greatly in diagnostic advancements. We finally present an institutional protocol which has been accredited by international peers with promising results in diagnostic and outcome rates.
In-Class Multitasking with Smartphones and Laptops: Exploring Student Experiences and Perceptions

Abstract Although multitasking with laptops and mobile phones has become endemic on university campuses, we still don’t have adequate understanding of this phenomenon. There is especially a lack of qualitative studies offering detailed and rich description of how and why students multitask. This exploratory study provides a nuanced understanding of in-class multitasking with smartphones and laptops. The study involves sixteen students from a comprehensive university in Hong Kong in in-depth interviews. The results indicate that the university students mainly multitask with mobile phones on activities unrelated to the ongoing class. Lectures and peer presentation are reported as the activities students felt least engaged with. The study has revealed a new type of multitasking behavior, that is learning-related yet off-task. The multitasking behavior also fluctuates on an array of factors associated with motivation, classroom context, and the presence of technology.
Dissecting the Inorganic Nanoparticle-Driven Interferences on Adhesome Dynamics

Inorganic nanoparticles have emerged as an attractive theranostic tool applied to different pathologies such as cancer. However, the increment in inorganic nanoparticle application in biomedicine has prompted the scientific community to assess their potential toxicities, often preventing them from entering clinical settings. Cytoskeleton network and the related adhesomes nest are present in most cellular processes such as proliferation, migration, and cell death. The nanoparticle treatment can interfere with the cytoskeleton and adhesome dynamics, thus inflicting cellular damage. Therefore, it is crucial dissecting the molecular mechanisms involved in nanoparticle cytotoxicity. This review will briefly address the main characteristics of different adhesion structures and focus on the most relevant effects of inorganic nanoparticles with biomedical potential on cellular adhesome dynamics. Besides, the review put into perspective the use of inorganic nanoparticles for cytoskeleton targeting or study as a versatile tool. The dissection of the molecular mechanisms involved in the nanoparticle-driven interference of adhesome dynamics will facilitate the future development of nanotheranostics targeting cytoskeleton and adhesomes to tackle several diseases, such as cancer.
Involvement of Residues Asp8, Asn13, Glu145, Asp168, and Thr173 in the Chaperone Activity of a Recombinant DnaK from Bacillus licheniformis

Based on the sequence homology, we have modeled the three-dimensional structure of Bacillus licheniformis DnaK (BlDnaK), a counterpart of Hsp70, and identified five different amino acids that might be responsible for maintaining ADP-Mg2+-Pi in the correct configuration at the ATP-binding cleft of the protein. As compared with wild-type BlDnaK, site-directed mutant proteins D8A, N13D, E145A, D168A, and T173A had a dramatic reduction in their chaperone activities. Complementation test revealed that the mutant proteins lost completely the ability to rescue the temperature-sensitive growth defect of Escherichia colidnaK756-ts. Wild-type BlDnak assisted the refolding of denatured firefly luciferase, whereas a significant decrease in this ability was observed for the mutant proteins. Simultaneous addition of B. licheniformis DnaJ, BlGrpE, and NR-peptide, did not synergistically stimulate the ATPase activity of D8A, E145A, D168A and T173A. Circular dichroism spectra were nearly identical for wild-type and mutant proteins, and they, except D8A, also exhibited a similar sensitivity towards temperature-induced denaturation. These results suggest that the selected residues are critical for the proper function of BlDnaK.
Interacción de bacterias y plantas en la fijación del nitrógeno

El ecosistema está constituido por las interrelaciones de los factores bióticos y abióticos, en la cual se sostiene la vida. Las leguminosas y otras plantas, viven de forma simbiótica con bacterias que proliferan en el suelo y son capaces de fijar nitrógeno atmosférico (N₂), elemento vital, para la nutrición de las plantas. Las bacterias del género Rhizobium y las de diazótrofos tienen la capacidad de fijar N₂ convirtiendo este a una forma asimilable por las plantas. Las bacterias promotoras del crecimiento en plantas, (PGPB) por sus siglas en inglés son importantes en diferentes ecosistemas donde se presentan adversidades de sequía, baja fertilidad de los suelos cultivables y bajo rendimiento de la producción. La distribución, identificación y predicción de las funciones de la diversidad microbiana ayuda al manejo productivo e incrementa el rendimiento en cultivos agrícolas. Este artículo de revisión estudia la fijación biológica del nitrógeno a través de la interacción y simbiosis de plantas-bacterias.
Reliable Estimates of Interpretable Cue Effects with Active Learning in Psycholinguistic Research

Studying the relative weighting of different cues for the interpretation of a linguistic phenomenon is a core element in psycholinguistic research. This research needs to strike a balance between two things: generalisability to diverse lexical settings, which requires a high number of different lexicalisations and the investigation of a large number of different cues, which requires a high number of different test conditions. Optimizing both is impossible with classical psycholinguistic designs as this would leave the participants with too many experimental trials. Previously we showed that Active Learning (AL) systems allow to test numerous conditions (eight) and items (32) within the same experiment. As stimulus selection was informed by the system’s learning mechanism, AL sped-up the labelling process. In the present study, we extend the use case to an experiment with 16 conditions, manipulated through four binary factors (the experimental setting and three prosodic cues; two levels each). Our findings show that the AL system correctly predicted the intended result pattern after twelve trials only. Hence, AL further confirmed previous findings and proved to be an efficient tool, which offers a promising solution to complex study designs in psycholinguistic research.
Group Identity and Ingroup Bias: The Social Identity Approach

This article discusses the social identity approach (social identity theory and self-categorization theory) for understanding children’s ingroup biases in attitudes and behaviors. It is argued that developmental research on ingroup bias will be enhanced by more fully considering the implications of this approach. These implications include (a) the conceptualization of group identity, (b) the importance of social reality and children’s epistemic motivation, (c) the role of processes of normative influence and social projection, and (d) the relevance of moral considerations. These four implications have not been fully considered in the developmental literature but indicate that the social identity approach offers the possibility for theoretically integrating and empirically examining various processes involved in children’s ingroup biases.
Effectiveness of Loaded Wheel Tracking Test to Ascertain Moisture Susceptibility of Asphalt Mixtures

Moisture damage of asphalt mixtures is a major distress affecting the durability of asphalt pavements. The loaded wheel tracking (LWT) test is gaining popularity in determining moisture damage because of its ability to relate laboratory performance to field performance. However, the accuracy of LWT’s “pass/fail” criteria for screening mixtures is limited. The objective of this study was to evaluate the capability of the LWT test to identify moisture susceptibility of asphalt mixtures with different moisture conditioning protocols. Seven 12.5 mm asphalt mixtures with two asphalt binder types (unmodified PG 67-22 and modified PG 70-22), and three aggregate types (limestone, crushed gravel, and a semi-crushed gravel) were utilized. Asphalt binder and mixture samples were subjected to five conditioning levels, namely, a control; single freeze–thaw-; triple freeze–thaw-; MiST 3500 cycles; and MiST 7000 cycles. Frequency sweep at multiple temperatures and frequencies, and multiple stress creep recovery tests were performed to evaluate asphalt binders. LWT test was used to evaluate the asphalt mixture samples. Freeze–thaw and MiST conditioning resulted in an increase in stiffness in the asphalt binders as compared with the control. Further, freeze–thaw and MiST conditioning resulted in an increase in rut depth compared with the control asphalt mixture. The conditioning protocols evaluated were effective in exposing moisture-sensitive mixtures, which initially showed compliance with Louisiana asphalt mixture design specifications.
Research on Driver Status Recognition System of Intelligent Vehicle Terminal Based on Deep Learning

Automobile safety driving technology is a hot topic in today’s society, which is very significant to the social transportation system. Vehicle driving behavior monitoring is the foundation and core of safe driving techniques. The research on existing vehicle safety technology can not only improve the understanding of current safe driving research progress, but also provide reference for future researchers. This paper proposes a state recognition system based on a three-dimensional convolutional neural network, which can identify several improper states frequently encountered by drivers during driving, including drinking, making phone calls, and smoking, and can also issue alarm interventions. The system takes the collected continuous video frame information as the input of the three-dimensional convolutional network, carries out multi-level feature extraction and spatio-temporal information fusion, and identifies the driver state according to the extracted spatio-temporal features. The state is judged by the facial feature points of the video stream, and the design of the video surveillance driver state recognition system is completed. Then, the driver status recognition is improved and optimized, and finally, the actual deployment of the driver status recognition system on the mobile terminal is completed. A large number of experimental results show that the driver status recognition system proposed in this paper has achieved upper identification accuracy.
Effect of different double-sided plastic films on chemical and fermentation characteristics of corn silage

Abstract The objective of this study was to evaluate the efficiency of different double-sided plastic films on chemical and fermentation characteristics, dry matter digestibility, aerobic stability, physical and dry matter losses in corn silages stored in bunker silos. This was a completely randomized experimental design consisting of three treatments: DF110µm - double-sided polyethylene with 110 µm thickness; DF200µm - double-sided polyethylene with 200 µm thickness; and DFBO - oxygen-impermeable film consisted of double-sided polyethylene with 80 µm thickness overlaid with a translucent vacuum polyamide film with 20 µm thickness. The use of DF200µm film increased the ruminal dry matter digestibility by 4.58% and reduced the silage temperature by 3.1 °C, as well as the physical losses of the corn silage were reduced by 118.9 g kg-1 DM using DFBO and 95 g kg-1 DM with DF200µm; DFBO resulted in the highest aerobic stability (127 hours) of corn silage. The use of DF200µm and DFBO is recommended for preserving corn silage in bunker silos.
Acoustic Echo Cancellation Using Deep Complex Neural Network with Nonlinear Magnitude Compression and Phase Information

This paper describes a two-stage acoustic echo cancellation (AEC) and suppression framework for the INTER-SPEECH2021 AEC Challenge. In the ﬁrst stage, four parallel partitioned block frequency domain adaptive ﬁlters are used to cancel the linear echo components, where the far-end signal is delayed 0ms, 320ms, 640ms and 960ms for these four adaptive ﬁlters, respectively, thus a maximum 1280 ms time delay can be well handled in the blind test dataset. The error signal with minimum energy and its corresponding reference signal are chosen as the input for the second stage, where a gate complex convolutional recurrent neural network (GCCRN) is trained to further suppress the residual echo, late reverberation and environmental noise simultaneously. To improve the performance of GCCRN, we compress both the magnitude of the error signal and that of the far-end reference signal, and then the two compressed magnitudes are combined with the phase of the error signal to regenerate the complex spectra as the input features of GCCRN. Numerous experimental results show that the proposed framework is robust to the blind test dataset, and achieves a promising result with the P.808 evaluation.
THE IMPACT OF OIL PRICES ON INVESTMENT IN CROATIA

If we look at economic growth as a function of labour and capital then, aside from the labour force, investment is a key determinant of capital accumulation and, accordingly, a prerequisite for economic growth and prosperity. During the analysed period (1996:Q1-2015:Q4) investment in Croatia demonstrated pro-cyclically behaviour but showed a higher level of fluctuation then personal consumption or GDP. The aim of the paper is to examine the influence of oil prices on investment during the analysed period using Vector Autoregression (VAR) analysis and to determine the nature of their relationship by permuting four different oil price indicators. The results indicate that investment initially react positively to the growth of oil prices after which their reaction to oil price growth becomes negative (and more pronounced than the initial positive reaction). Contribution of oil price changes to investment fluctuations were also found.
Building the Bridge: Topic Modeling for Comparative Research

ABSTRACT In communication research, topic modeling is primarily used for discovering systematic patterns in monolingual text corpora. To advance the usage, we provide an overview of recently presented strategies to extract topics from multilingual text collections for the purpose of comparative research. Moreover, we discuss, demonstrate, and facilitate the usability of the “Polylingual Topic Model” (PLTM) for such analyses. The appeal of this model is that it derives lists of related clustered words in different languages with little reliance on translation or multilingual dictionaries and without the need for manual post-hoc matching of topics. PLTM bridges the gap between languages by making use of document connections in training documents. As these training documents are the crucial resource for the model, we compare model evaluation metrics for different strategies to build training documents. By discussing the advantages and limitations of the different strategies in respect to different scenarios, our study contributes to the methodological discussion on automated content analysis of multilingual text corpora.
Online Streaming End-to-End Neural Diarization Handling Overlapping Speech and Flexible Numbers of Speakers

We propose a streaming diarization method based on an end-to-end neural diarization (EEND) model, which handles ﬂexi-ble numbers of speakers and overlapping speech. In our previous study, the speaker-tracing buffer (STB) mechanism was proposed to achieve a chunk-wise streaming diarization us-ing a pre-trained EEND model. STB traces the speaker information in previous chunks to map the speakers in a new chunk. However, it only worked with two-speaker recordings. In this paper, we propose an extended STB for ﬂexible numbers of speakers, FLEX-STB. The proposed method uses a zero-padding followed by speaker-tracing, which alleviates the difference in the number of speakers between a buffer and a current chunk. We also examine buffer update strategies to select important frames for tracing multiple speakers. Experiments on CALLHOME and DIHARD II datasets show that the proposed method achieves comparable performance to the ofﬂine EEND method with 1-second latency. The results also show that our proposed method outperforms recently proposed chunk-wise diarization methods based on EEND (BW-EDA-EEND).
Role of Stem Cells in Augmenting Dental Implant Osseointegration: A Systematic Review

Dental implants are a widely used treatment modality for oral rehabilitation. Implant failures can be a result of many factors, with poor osseointegration being the main culprit. The present systematic review aimed to assess the effect of stem cells on the osseointegration of dental implants. An electronic search of the MEDLINE, LILACS, and EMBASE databases was conducted. We examined quantitative preclinical studies that reported on the effect of mesenchymal stem cells on bone healing after implant insertion. Eighteen studies that fulfilled the inclusion criteria were included. Various surface modification strategies, sites of placement, and cell origins were analyzed. The majority of the selected studies showed a high risk of bias, indicating that caution must be exercised in their interpretation. All the included studies reported that the stem cells used with graft material and scaffolds promoted osseointegration with higher levels of new bone formation. The mesenchymal cells attached to the implant surface facilitated the expression of bio-functionalized biomaterial surfaces, to boost bone formation and osseointegration at the bone–implant interfaces. There was a promotion of osteogenic differentiation of human mesenchymal cells and osseointegration of biomaterial implants, both in vitro and in vivo. These results highlight the significance of biomodified implant surfaces that can enhance osseointegration. These innovations can improve the stability and success rate of the implants used for oral rehabilitation.
Tunability Investigation in the BaTiO3-CaTiO3-BaZrO3 Phase Diagram Using a Refined Combinatorial Thin Film Approach

Tunable ferroelectric capacitors, which exhibit a decrease in the dielectric permittivity under an electric field, are widely used in electronics for RF tunable applications. Current devices use barium strontium titanate (BST) as the tunable dielectric, but new applications call for tunable materials with specific performance improvements. It is then of crucial importance to dispose of a large panel of electrically characterized materials to identify the most suited compound for a given set of device specifications. Here, we report on the dielectric tuning properties of Ba1−xCaxTi1−yZryO3 (BCTZ) thin films libraries (0 ≤ x ≤ 30% and 0 ≤ y ≤ 28.5%) synthesized by combinatorial pulsed laser deposition (CPLD). An original CPLD approach allowing reliable and statistical ternary phase diagrams exploration is reported. The effects of Ca and Zr content on tunability, breakdown voltage and dielectric losses are explicated and shown to be beneficial up to a certain amount. Compounds close to (Ba0.84Ca0.16)(Ti0.8Zr0.2)O3 exhibit the highest figures of merit, while a zone with compositions around (Ba0.91Ca0.09)(Ti0.81Zr0.19)O3 show the best compromise between tuning ratio and figure of merit. These results highlight the potential of BCTZ thin films for electrically tunable applications.
Role of Active Morphing in the Aerodynamic Performance of Flapping Wings in Formation Flight

Migratory birds have the ability to save energy during flight by arranging themselves in a V-formation. This arrangement enables an increase in the overall efficiency of the group because the wake vortices shed by each of the birds provide additional lift and thrust to every member. Therefore, the aerodynamic advantages of such a flight arrangement can be exploited in the design process of micro air vehicles. One significant difference when comparing the anatomy of birds to the design of most micro air vehicles is that bird wings are not completely rigid. Birds have the ability to actively morph their wings during the flapping cycle. Given these aspects of avian flight, the objective of this work is to incorporate active bending and torsion into multiple pairs of flapping wings arranged in a V-formation and to investigate their aerodynamic behavior using the unsteady vortex lattice method. To do so, the first two bending and torsional mode shapes of a cantilever beam are considered and the aerodynamic characteristics of morphed wings for a range of V-formation angles, while changing the group size in order to determine the optimal configuration that results in maximum propulsive efficiency, are examined. The aerodynamic simulator incorporating the prescribed morphing is qualitatively verified using experimental data taken from trained kestrel flights. The simulation results demonstrate that coupled bending and twisting of the first mode shape yields the highest propulsive efficiency over a range of formation angles. Furthermore, the optimal configuration in terms of propulsive efficiency is found to be a five-body V-formation incorporating coupled bending and twisting of the first mode at a formation angle of 140 degrees. These results indicate the potential improvement in the aerodynamic performance of the formation flight when introducing active morphing and bioinspiration.