Miracle-dz/UniFAR-FTUs huggingface dataset:
Foliar Application of Wood Distillate Alleviates Ozone-Induced Damage in Lettuce (Lactuca sativa L.)

This study examined whether foliar applications of wood distillate (WD) have a protective effect on photosynthesis and the antioxidant power of lettuce when exposed to an ecologically relevant O3 concentration. Seedlings of lettuce (Lactuca sativa L.) were fumigated daily with 60 ppb of O3 for 30 days, five hours per day. Once per week, 50% of the fumigated plants were treated with foliar applications of 0.2% WD, while control plants were treated with water. The results clearly showed the ability of WD to protect lettuce plants from ozone-induced damage. Specifically, WD-treated plants exhibited lower damage to the photosynthetic machinery, assessed through a series of chlorophyll fluorescence parameters, a higher chlorophyll content, higher antioxidant power, as well as antioxidant molecules, i.e., caffeic acid and quercetin, and higher biomass. Counteracting the overproduction of ozone-generated reactive oxygen species (ROS) is speculated to be the main mechanism by which WD protects the plant from ozone-induced damage.
Performance Comparison of Micro strip Band pass Filter Topologies On Different Substrates

This paper presents the design of five pole microstrip bandpass filters with hairpin and combline configurations with a center frequency of 4.8 GHz The simulation is performed using ADS simulation tool. The filters are designed for different substrates like FR4, RT/Duroid 6010, and RO3010. The filter performance is compared for these substrates in terms of insertion loss and return loss. The simulated results show that both filters are operating well for the desired specifications and the substrate with higher dielectric constant provides higher return loss and lower insertion loss for both filter configurations.
Learning How to Transfer from Uplink to Downlink via Hyper-Recurrent Neural Network for FDD Massive MIMO

In order to unlock the full advantages of massive multiple-input multiple-output (MIMO) in the downlink, the base station (BS) must leverage information about the downlink fading channels. However, in frequency division duplex (FDD) systems, full channel reciprocity does not hold, and acquiring information about the downlink channels generally requires downlink pilot transmission followed by uplink feedback. Prior work proposed to design pilot transmission, feedback, and channel state information (CSI) estimation, or directly downlink beamforming, via deep learning in an end-to-end manner. While previous work only used downlink pilots in a single slot, in this work, we introduce an enhanced end-to-end design that leverages partial uplink-downlink reciprocity and temporal correlation of the fading processes by utilizing jointly downlink and uplink pilots across multiple time slots. The proposed method is based on a novel deep learning architecture – HyperRNN – that combines hypernetworks and recurrent neural networks (RNNs) to optimize the transfer of long-term invariant channel features from uplink to downlink. Simulation results demonstrate that the HyperRNN achieves a lower normalized mean square error (NMSE) performance in terms of channel estimation, and that it attains a larger achievable sum-rate when applied to multi-user beamforming, as compared to the state of the art.
Modeling uncertainty of expert-elicited data for use in risk-based, capital budgeting and underground mine production scheduling optimization models

This dissertation consists of three papers in various stages of publication. The first paper, “Consistent Notation for Presenting Complex Optimization Models in Technical Writing,” is published in Surveys in Operations Research and Management Science. The topics we discuss are: (i) conventions for defining sets, parameters, and variables, (ii) ways of presenting the objective and constraints, and (iii) means by which to organize formulations as they pertain to mathematical programming. A second paper, “Modeling uncertainty of expert elicitation for use in risk-based optimization,” is under review, at the time of this submission, in Annals of Operation Research. We derive, for the first time, a three-dimensional density estimate with epi-splines from which we generate scenarios to implement in a superquantile risk-based, capital budgeting optimization model. The last paper, “Optimizing underground mine scheduling under production rate uncertainty,” is awaiting the company’s letter of endorsement necessary for submission to Interfaces. We employ a risk-based optimization model, with uncertain ground conditions, to demonstrate the effects geotechnical risk has on an underground mine production schedule.
Propagating Seismic Waves in VTI Attenuating Media Using Fractional Viscoelastic Wave Equation

Seismic velocity and attenuation anisotropy are ubiquitous in the crust and upper mantle, significantly modulating the characteristics of seismic wave propagation in the Earth's interior. Accurate seismic wave modeling of velocity and attenuation anisotropy is essential for the understanding of wave propagation in the Earth's interior as well as constructing global and region‐scale seismic full waveform tomography. Here, we derive a decoupled fractional Laplacian (DFL) viscoelastic wave equation to characterize the Earth's frequency‐independent Q behavior in the vertical transversely isotropic (VTI) media. We verify the accuracy of the proposed viscoelastic wave equation by 2D synthetic examples; to show its applicability in crustal‐scale seismic modeling, we present an example of 3D seismic wave propagation in the realistic Salton Trough model. Through extensive numerical tests, we conclude that the proposed viscoelastic wave equation is superior in four aspects. First, the viscoelastic wave equation takes VTI anisotropy of both velocity and attenuation into account and can describe the strong direction‐dependent attenuation. Second, our derivation contains spatially independent Laplacians, and thus the proposed wave equation enjoys higher simulation accuracy for heterogeneous Q media. Third, the new viscoelastic wave equation can decouple the amplitude decay and the phase distortion, which is appealing for improving the resolution in seismic imaging and inversion. Lastly, compared to viscoelastic wave equations with time‐fractional operators, our scheme has higher computational efficiency by avoiding substantial wavefield storage.
Large Divergence in Tropical Hydrological Projections Caused by Model Spread in Vegetation Responses to Elevated CO2

Increasing atmospheric CO2 and associated global warming are expected to alter the global hydrological cycle, thereby posing widespread threats to freshwater availability. However, future hydrological projections differ greatly between models, particularly over the tropical regions. The large difference between model projections directly limits policy planning efforts, and the responsible modeling processes remain unclear. Here, we identify the primary processes accounting for model differences in tropical hydrological changes using multiple CO2 sensitivity experiments in the Coupled Model Intercomparison Project. We show that differences in projected changes to tropical evapotranspiration, precipitation, and surface water availability mainly arise from model representations of vegetation cover and stomatal conductance responses to elevated CO2 and associated changes in atmospheric moisture and circulation. Atmospheric responses to sea surface warming contribute additionally to the divergence in hydrological projections. Given the importance of vegetation responses to elevated CO2 and associated atmosphere feedbacks, our results underscore the need to improve representations of the vegetation physiological response to rising CO2 and its coupling to the atmosphere, to provide reliable tropical hydrological projections.
Conventional Treatment of Burn Wound Infections versus Phage Therapy

Wound infections are the primary cause of sepsis in burn wound patients and increase burn-related morbidity and mortality. Gram-negative and Gram-positive bacteria induce infections in burn wounds. Conventional antimicrobial therapy is recognized as the most successful therapeutic intervention to combat infections of burn wounds. Unfortunately, antimicrobial resistance could be catastrophic and lead to treatment failure. Burn wound infections need topical treatment. Phages as an alternative for antibiotics can be used as a monotherapy for infections with antibiotic-resistant pathogens or can be applied in combination with antibiotic therapy. Phages are species-specific bacterial natural viruses. Worldwide, many phage-producing companies are emerging. However, not many countries implement phage therapy in their patient management. Clinical trials are needed to convince the health care system in those countries that do not have confidence in phage therapy in infectious diseases. This study reviewed several aspects of phage therapy in burn wound patients.
Accuracy assessment of ALOS World 3D-30m DEMs using field data from Lagos and Federal Capital Territory, Nigeria

Abstract To assess the quality and performance of ALOS World3D-30m (AW3D30–30m) Digital Elevation Model (DEM) on the Nigerian terrain, this study evaluates the accuracy of three versions of AW3D30 – the average (v1.1AVE) and median (v1.1MED) products of version 1.1, and version 2.1 (v2.1). Tested against highly accurate Ground Control Points in Lagos and the Federal Capital Territory (FCT), Nigeria, emerging results showed that v1.1MED had the highest accuracy over Lagos (RMSE: 4.38 m; SD: 4.13 m) while v1.1AVE had the highest accuracy over FCT (RMSE: 9.10 m; SD: 9.01 m). However, at a terrain level of 0–200 m in FCT which has some level of correspondence with the height level of Lagos, the accuracy of all three versions surpassed accuracy values obtained in Lagos, with the highest accuracy observed in version 2.1. Although v2.1 is more recent, it did not show an overarching superiority over the previous versions in terms of accuracy at both locations.
Semiquantitative 3T Brain Magnetic Resonance Imaging for Dynamic Visualization of the Glymphatic-Lymphatic Fluid Transport System in Humans

Objectives Recently, a novel clearing system for interstitial solutes of the brain was described as a perivascular pathway named the glymphatic system. Furthermore, lymphatic vessels were found in the meninges to drain interstitial fluids. It is hypothesized that interstitial solutes, such as amyloid β, are firstly processed through the brain by the glymphatic system and secondly drained out of the brain by lymphatic vessels (glymphatic-lymphatic fluid transport system [GLS]). Since then, various neurological disorders, such as Alzheimer disease, have been associated with a dysfunction of the GLS. In the current study, we aimed to establish a clinical magnetic resonance imaging (MRI) study protocol for visualizing lymphatic vessels as part of the GLS in humans. More importantly, we aimed to describe the dynamic changes of a contrast agent in these lymphatic vessels over time. Materials and Methods Twenty volunteers with an unremarkable neurological/psychiatric history were included in this 3T MRI study. Serial MRI sequence blocks were performed at 3 predefined time points (TPs): TP 1, precontrast MRI before administration of a gadolinium-based contrast agent (GBCA); TP 2, immediately post-GBCA (early ce-MRI); and TP 3, 60 minutes post-GBCA (late ce-MRI). Each MRI block contained the following sequences obtained in the same order: whole-brain 3D T1-MPRAGE, whole-brain 3D T2-FLAIR, focused 2D T2-FLAIR, and whole-brain 3D T1-SPACE. Signal intensity (SI) in compartments of the GLS adjacent to the superior sagittal sinus, gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) was calculated by manually placed regions of interest. The time course of the signal intensities was examined by generalized linear mixed models. The data were adjusted for age, cognitive function (Montreal-Cognitive-Assessment test), and sleep quality (Pittsburgh Sleep Quality Index questionnaire). Results The GLS was best visualized in the 2D T2-FLAIR and 3D T1-SPACE sequences, enabling further SI measurement. In precontrast (TP 1), the SI within the GLS was significantly higher than in CSF and significantly lower than in GM and WM. In post-GBCA, a significant increase (TP 2) and decrease (TP 3), respectively, of the GLS SI values were noted (86.3 ± 25.2% increase and subsequent decrease by 25.4 ± 9% in the 3D T1-SPACE sequence). The SI values of CSF, GM, and WM did not change significantly between the 3 TPs. Conclusions A clinical MRI study protocol was established for the visualization of lymphatic vessels as an important part of the GLS and therefore the brain’s clearing mechanism of interstitial solutes. Furthermore, dynamic changes in the GLS were described over time, possibly reflecting the clearing function of the GLS. This might constitute the basis for evaluating the GLS function in manifold neurological pathologies in the future.
Can environmental tax curb air pollution: evidence from China

ABSTRACT Using the environmental tax reform implemented in 2018 in China as a quasi-experiment, this paper employs PSM, DID, and DDD methods to investigate the causal impact of environmental tax on air pollution. Viewing those provinces that choose to set a higher tax rate than the original pollution fee rate as the treatment group and provinces that do not increase the tax rate as the control group, this paper provides robust evidence that the environmental tax reform is effective in reducing PM2.5 and SO2 concentration level, while the effect is smaller and inconsistent for NO2. A back-of-the-envelope welfare analysis suggests that a 1-unit increase in the environmental tax rate is associated with a reduction of 5,616 in total deaths and a welfare gain of $28.256 billion in 2005 USD for all Chinese households.
Mango “Ataulfo” Peel Extract Improves Metabolic Dysregulation in Prediabetic Wistar Rats

The hypoglycemic effect of functional phytochemicals has been evaluated in diabetic rodents but scarcely in its premorbid condition (prediabetes; PD). This study aimed to evaluate a mango (cv. Ataulfo) peel hydroethanolic (20:80) extract (MPE) for in vivo glycemic/lipidemic-normalizing effect and in vitro enzyme inhibitory (α-amylase/α-glucosidase) activity. The polyphenolic MPE (138 mg EAG.g−1, mainly gallic acid and mangiferin) with antioxidant capacity (DPPH• 34 mgTE.g−1) was fed to PD rats (induction: high-fat diet (60% energy) + single dose streptozotocin (35 mg·kg−1), 4 weeks). At the 8th week, fasting glycemia (FG), oral glucose tolerance test, and insulin sensitivity indexes (HOMA-IR, HOMA-β) > blood lipid-normalizing effect were documented as healthy controls > MPE > disease (PD) controls, which was possibly related to the extract’s concentration–response in vitro enzyme inhibitory activity (IC50 ≈ 0.085 mg·mL−1). MPE is a rich source of glucose-lowering phytochemicals for the primary prevention of type 2 diabetes.
Image Classification for Edge-Cloud Setting: A Comparison Study for OCR Application

The increasing number of smart devices has led to a rise in the complexity and volume of the image generated. Deep learning is an increasingly common approach for image classification, a fundamental task in many applications. Due to its high computational requirements, implementation in edge devices becomes challenging. Cloud computing serves as an enabler, allowing devices with limited resources to perform deep learning. For cloud computing, however, latency is an issue and is undesirable. Edge computing addresses the issue by redistributing data and tasks closer to the edge. Still, a suitable offloading strategy is required to ensure optimal performance with methods such as LeNet-5, OAHR, and Autoencoder (ANC) as feature extractors paired with different classifiers (such as artificial neural network (ANN) and support vector machine (SVM)). In this study, models are evaluated using a dataset representing Optical Character Recognition (OCR) task. The OCR application has recently been used in many task-offloading studies. The evaluation is based on the time performance and scoring criteria. In terms of time performance, a fully connected ANN using features from the ANC is faster by a factor of over 60 times compared to the fastest performing SVM. Moreover, scoring performance shows that the SVM is less prone to overfit in the case of a noisy or imbalanced dataset in comparison with ANN. So, adopting SVM in which the data distribution is unspecified will be wiser as there is a lower tendency to overfit. The training and inference time, however, are generally higher than ANN.
BMRMI Reduces Depressive Rumination Possibly through Improving Abnormal FC of Dorsal ACC

Rumination is a common symptom of major depressive disorder (MDD) and has been characterized as a vulnerability factor for the onset or recurrence of MDD. However, the neurobiological mechanisms underlying rumination and appropriate treatment strategies remain unclear. In the current study, we used resting-state functional magnetic resonance imaging to investigate the effects of body-mind relaxation meditation induction (BMRMI) intervention in MDD with rumination. To this aim, we have recruited 25 MDD and 24 healthy controls (HCs). Changes in functional connectivity (FC) of the anterior cingulate cortex (ACC) subregion and the scores of clinical measurements were examined using correlation analysis. At baseline, MDD showed stronger FC between the right dorsal ACC (dACC) and right superior frontal gyrus than did the HC group. Compared to baseline, the HC group showed a significantly enhanced FC between the right dACC and right superior frontal gyrus, and the MDD group demonstrated a significantly weaker FC between the left dACC and right middle frontal gyrus (MFG) after the intervention. Furthermore, the FC between the right dACC and right superior frontal gyrus was positively associated with rumination scores across all participants at baseline. The above results indicate that BMRMI may regulate self-referential processing and cognitive function through modulating FC of the dACC in MDD with rumination.
The opportunity of public intervention in the market for fuels

not the case: in Europe roughly the 0.5% of total vehicles (cars, buses and trucks) uses NG; worldwide the share soars to 1.5% thanks to (in this sense) virtuous countries such as Pakistan (89% of NGV out of total), Bangladesh (59%), Armenia (55%), Iran (23%), Argentina, Bolivia and Colombia (15%). Italy (1.83%) places above worldwide average and well above European’s. 73 countries out of 83 surveyed adopt NGVs by less than 10%. This pivotal exploitation of PB fuel is, nonetheless, likely to be the consequence of an increasing returns rolling snowball (Nelson, 2005), due to a high level of cumulativeness in the underlying technology. Quoting Dosi et al. (2010): [. ] in the case of the history of automobile engine technology — according to the cumulative technology interpretation — gasoline engines, steam engines, and electrical engines, all were plausible alternative technologies for powering cars, and it was not clear which of these means would turn out to be superior. Reflecting this uncertainty, different inventors tended to make different technological bets. Assume, however, that simply as a matter of chance (or marginal choice or political decision), a large share of these efforts just happened to focus on one of the variants — for example, the internal combustion engine — [. ] as a result, over this period there was much more overall improvement in the design of internal combustion engines than in the design of the two alternative power sources.
Novel optoelectronic devices for mid-infrared applications: From intersubband thermophotovoltaic detectors to germanium nanomembrane light emitters

Optoelectronic devices operating in the mid-infrared spectral region are attracting increasing attention due to potential applications in a wide range of disciplines. For example, mid-infrared photodetectors play a key role in thermophotovoltaic (TPV) energy conversion, whereby a photovoltaic device is used to extract electrical power from heat radiation. This technology is attractive for waste heat harvesting and clean energy production in several different environments. Similarly, mid-infrared light sources are particularly useful for biochemical sensing and spectroscopy, where the distinctive absorption features of many molecular species of interest can be exploited for their sensitive identification and detection. Both devices are investigated in this thesis work. In the area of TPV energy conversion, I have studied the use of intersubband transitions in semiconductor quantum cascade structures as a means to overcome the fundamental limitations of existing TPV devices using mature InP-based technology. Very efficient coverage of the incident radiation spectrum and optimal current matching can be achieved using multiple quantum-cascade structures monolithically integrated with a p-n junction, by taking advantage of their intrinsic cascading scheme, spectral viii agility, and design flexibility. Numerical simulations indicate that this approach can effectively double the present state-of-the-art in TPV output electrical power. In the area of mid-infrared light sources, my work has focused on developing efficient light emitters based on tensilely strained Germanium nanomembranes (Ge NMs). These ultrathin (a few ten nanometers) single-crystal membranes are good candidates for the development of CMOS-compatible Group-IV light sources, by virtue of their ability to sustain large strain levels and in the process become direct-bandgap materials. My research efforts have concentrated on the development of optical cavities based on Ge NMs that can satisfy the mechanical flexibility requirement of this materials platform. In particular, photonic-crystal (PhC) cavities in the form of disconnected dielectric-column arrays have been designed and fabricated based on a novel membrane assembly method, producing clear cavity-mode features in NM photoluminescence spectra.
Selection Criteria for Data Mining Software: A Study

Nowadays software are flooded in the market, there is a need for selection criteria of software package that should be available for individuals and organizations. As the number of software continues to grow and new features added to the new software the selection of the most suitable software package is becoming more and more difficult. Wrong or immature decision would result in great loss of time and money. Research is being carried out throughout the world to evaluate the software. Researchers have not reached to consensus to generalize such selection and evaluation criteria. Improper selection of software package can lead to be a costly affair and adversely affect the business.