Miracle-dz/UniFAR-FTUs huggingface dataset:
Older Eastern White Pine Trees and Stands Accumulate Carbon for Many Decades and Maximize Cumulative Carbon

Pre-settlement New England was heavily forested, with trees exceeding 2 m in diameter. The forests have regrown since farm abandonment, representing what is arguably the most successful regional reforestation on record and identified recently in the “Global Safety Net. ” Temperate “old-growth” forest and remnant stands demonstrate that native tree species can live several hundred years and continue to add to forest biomass and structural and ecological complexity. Forests globally are an essential natural climate solution that accumulate carbon and reduce annual increases in atmospheric CO2 by approximately 30%. Some studies emphasize young, fast-growing trees and forests while others highlight carbon storage and accumulation in old trees and intact forests. We addressed this directly within New England with long-term, accurate field measurements and volume modeling of individual trees and two stands of eastern white pines (Pinaceae: Pinus strobus) and compared our results to models developed by the U.S. Forest Service. Within this sample and species, our major findings complement and clarify previous findings and are threefold: (1) beyond 80 years, an intact eastern white pine forest can accumulate carbon above-ground in living trees at a high rate and double the carbon stored in this compartment in subsequent years; (2) large trees dominate above-ground carbon and can continue to accumulate carbon; (3) productive stands can continue to accumulate high amounts of carbon in live trees for well over 150 years. Because the next decades are critical in addressing the climate emergency, and most New England forests are less than 100 years old, a major implication of this work is that maintaining and accumulating carbon in some existing forests—proforestation—is a powerful regional climate solution. Furthermore, older and old-growth trees and forests are rare, complex, highly dynamic and biodiverse: dedication of some forests to proforestation will produce large carbon-dense trees and also protect ecosystem integrity, special habitats, and native biodiversity long-term. In sum, strategic policies to grow and protect suitable existing forests in New England will optimize a proven, low cost, natural climate solution that also protects and restores biodiversity across the landscape.
Cluster-Based Cooperative Cache Deployment and Coded Delivery Strategy in C-V2X Networks

Cellular vehicle-to-everything- (C-V2X-) based communications can support various content-oriented applications and have gained significant progress in recent years. However, the limited backhaul bandwidth and dynamic topology make it difficult to obtain the multimedia service with high-reliability and low-latency communication in C-V2X networks, which may degrade the quality of experience (QoE). In this paper, we propose a novel cluster-based cooperative cache deployment and coded delivery strategy for C-V2X networks to improve the cache hit ratio and response time, reduce the request-response delay, and improve the bandwidth efficiency. To begin with, we design an effective vehicle cluster method. Based on the constructed cluster, we propose a two-level cooperative cache deployment approach to cache the frequently requested files on the edge nodes, LTE evolved NodeB (eNodeB) and cluster head (CH), to maximize the overall cache hit ratio. Furthermore, we propose an effective coded delivery strategy to minimize the network load and the ratio of redundant files. Simulation results demonstrate that our proposed method can effectively reduce the average response delay and network load and improve both the hit ratio and the ratio of redundant files.
Neuroimmune Pathophysiology in Asthma

Asthma is a chronic inflammation of lower airway disease, characterized by bronchial hyperresponsiveness. Type I hypersensitivity underlies all atopic diseases including allergic asthma. However, the role of neurotransmitters (NT) and neuropeptides (NP) in this disease has been less explored in comparison with inflammatory mechanisms. Indeed, the airway epithelium contains pulmonary neuroendocrine cells filled with neurotransmitters (serotonin and GABA) and neuropeptides (substance P[SP], neurokinin A [NKA], vasoactive intestinal peptide [VIP], Calcitonin-gene related peptide [CGRP], and orphanins-[N/OFQ]), which are released after allergen exposure. Likewise, the autonomic airway fibers produce acetylcholine (ACh) and the neuropeptide Y(NPY). These NT/NP differ in their effects; SP, NKA, and serotonin exert pro-inflammatory effects, whereas VIP, N/OFQ, and GABA show anti-inflammatory activity. However, CGPR and ACh have dual effects. For example, the ACh-M3 axis induces goblet cell metaplasia, extracellular matrix deposition, and bronchoconstriction; the CGRP-RAMP1 axis enhances Th2 and Th9 responses; and the SP-NK1R axis promotes the synthesis of chemokines in eosinophils, mast cells, and neutrophils. In contrast, the ACh-α7nAChR axis in ILC2 diminishes the synthesis of TNF-α, IL-1, and IL-6, attenuating lung inflammation whereas, VIP-VPAC1, N/OFQ-NOP axes cause bronchodilation and anti-inflammatory effects. Some NT/NP as 5-HT and NKA could be used as biomarkers to monitor asthma patients. In fact, the asthma treatment based on inhaled corticosteroids and anticholinergics blocks M3 and TRPV1 receptors. Moreover, the administration of experimental agents such as NK1R/NK2R antagonists and exogenous VIP decrease inflammatory mediators, suggesting that regulating the effects of NT/NP represents a potential novel approach for the treatment of asthma.
Hyper-Interleukin-6 Protects Against Renal Ischemic-Reperfusion Injury—A Mouse Model

Background: Most of the ischemia-reperfusion injury (IR-I) occurs during reperfusion and is mediated by the immune system. In this study we determined whether immunomodulation with hyper-Interleukin-6 (a recombinant designer cytokine composed of interleukin-6 linked to its soluble receptor) is protective against IR-I in mice kidneys. Methods: Hyper-Interleukin-6 (HIL-6) was administered by in vivo plasmid DNA transfection to 10 male mice. Twenty-four hours later, unilateral nephrectomy was done. IR-I immediately followed by closure of the remaining kidney vascular pedicle for 40 min. Seven mice transfected with non-coding control plasmid served as the control group. The functional and morphological effects of IR-I and its effect on mice longevity were explored. This was done by serial blood tests and by histopathology done upon sacrifice of the animals at post-operative day 7. Findings: Mice pretreated with HIL-6 had a mean creatinine level at post-operative day 1 of 35.45 ± 4.03 μmol/l and mean Urea level was 14.18 ± 2.69 mmol/l, whereas mean creatinine was 89.33 ± 69.27 μmol/l (P = 0.025), and mean urea was 38.17 ± 20.77 mmol/l (P = 0.0024) in the control group. Histological changes in the control group included inflammatory infiltration, tubular damage, and architectural distortion. These were not seen in the treatment group. Seven days post-operatively the survival rate of treated mice was 100% compared to 50% in the control group (P = 0.015). Interpretation: In this single kidney mouse model, pretreatment with HIL-6 administration effectively protected against IR-I both morphologically and functionally. Further studies are needed to better understand the mechanism and feasibility of using this immunomodulator.
Bidirectional threshold switching characteristics in Ag/ZrO2/Pt electrochemical metallization cells

A bidirectional threshold switching (TS) characteristic was demonstrated in Ag/ZrO2/Pt electrochemical metallization cells by using the electrochemical active Ag electrode and appropriate programming operation strategies The volatile TS was stable and reproducible and the rectify ratio could be tuned to ∼107 by engineering the compliance current. We infer that the volatile behavior is essentially due to the moisture absorption in the electron beam evaporated films, which remarkably improved the anodic oxidation as well as the migration of Ag+ ions. The resultant electromotive force would act as a driving force for the metal filaments dissolution, leading to the spontaneous volatile characteristics. Moreover, conductance quantization behaviors were also achieved owing to formation and annihilation of atomic scale metal filaments in the film matrix. Our results illustrate that the Ag/ZrO2/Pt device with superior TS performances is a promising candidate for selector applications in passive crossbar arrays.
Reconstructing 3D Model from Single-View Sketch with Deep Neural Network

In this paper, we introduce a novel 3D shape reconstruction method from a single-view sketch image based on a deep neural network. The proposed pipeline is mainly composed of three modules. The first module is sketch component segmentation based on multimodal DNN fusion and is used to segment a given sketch into a series of basic units and build a transformation template by the knots between them. The second module is a nonlinear transformation network for multifarious sketch generation with the obtained transformation template. It creates the transformation representation of a sketch by extracting the shape features of an input sketch and transformation template samples. The third module is deep 3D shape reconstruction using multifarious sketches, which takes the obtained sketches as input to reconstruct 3D shapes with a generative model. It fuses and optimizes features of multiple views and thus is more likely to generate high-quality 3D shapes. To evaluate the effectiveness of the proposed method, we conduct extensive experiments on a public 3D reconstruction dataset. The results demonstrate that our model can achieve better reconstruction performance than peer methods. Specifically, compared to the state-of-the-art method, the proposed model achieves a performance gain in terms of the five evaluation metrics by an average of 25.5% on the man-made model dataset and 23.4% on the character object dataset using synthetic sketches and by an average of 31.8% and 29.5% on the two datasets, respectively, using human drawing sketches.
Concise and Informative Article Title Throughput Maximization through Joint User Association and Power Allocation for a UAV-Integrated H-CRAN

The heterogeneous cloud radio access network (H-CRAN) is considered a promising solution to expand the coverage and capacity required by fifth-generation (5G) networks. UAV, also known as wireless aerial platforms, can be employed to improve both the network coverage and capacity. In this paper, we integrate small drone cells into a H-CRAN. However, new complications and challenges, including 3D drone deployment, user association, admission control, and power allocation, emerge. In order to address these issues, we formulate the problem by maximizing the network throughput through jointly optimizing UAV 3D positions, user association, admission control, and power allocation in H-CRAN networks. However, the formulated problem is a mixed integer nonlinear problem (MINLP), which is NP-hard. In this regard, we propose an algorithm that combines the genetic convex optimization algorithm (GCOA) and particle swarm optimization (PSO) approach to obtain an accurate solution. Simulation results validate the feasibility of our proposed algorithm, and it outperforms the traditional genetic and K-means algorithms.
Link Prediction and Node Classification Based on Multitask Graph Autoencoder

The goal of network representation learning is to extract deep-level abstraction from data features that can also be viewed as a process of transforming the high-dimensional data to low-dimensional features. Learning the mapping functions between two vector spaces is an essential problem. In this paper, we propose a new similarity index based on traditional machine learning, which integrates the concepts of common neighbor, local path, and preferential attachment. Furthermore, for applying the link prediction methods to the field of node classification, we have innovatively established an architecture named multitask graph autoencoder. Specifically, in the context of structural deep network embedding, the architecture designs a framework of high-order loss function by calculating the node similarity from multiple angles so that the model can make up for the deficiency of the second-order loss function. Through the parameter fine-tuning, the high-order loss function is introduced into the optimized autoencoder. Proved by the effective experiments, the framework is generally applicable to the majority of classical similarity indexes.
A Novel PAPR Reduction Scheme for OFDM Systems Based on Neural Networks

Orthogonal frequency division multiplexing (OFDM) is extensively applied in the downlink of narrowband Internet of Things (NB-IoT). However, the high peak-to-average power ratio (PAPR) of OFDM systems leads to a decrease in transmitter efficiency. Therefore, the researchers proposed the artificial neural network (ANN) based PAPR reduction schemes. However, these schemes have the disadvantages of high complexity or cannot overcome the defects of traditional schemes. In this paper, a novel PAPR reduction scheme based on neural networks (NNs) is proposed for OFDM systems. This scheme establishes a PAPR reduction module based on NN, which is trained using the low PAPR data obtained by the simplified clipping and filtering (SCF) method. To overcome the defect of poor BER performance of the SCF scheme, a recovery module is introduced at the receiver, to recover the distorted signal. To realize the improvement of BER performance and the reduction of PAPR simultaneously, the two modules are jointly trained based on multiobjective optimization. Experimental results based on a 100 MHz OFDM signal show that this scheme can reduce PAPR by 4.5 dB. Meanwhile, the BER of this scheme can be reduced to 0.001 times that of the SCF scheme.
Electrical features, liquid composition and toxicant emissions from ‘pod-mod’-like disposable electronic cigarettes

Introduction Use of flavoured pod-mod-like disposable electronic cigarettes (e-cigarettes) has grown rapidly, particularly among cost-sensitive youth and young adults. To date, little is known about their design characteristics and toxicant emissions. In this study, we analysed the electrical and chemical characteristics and nicotine and pulmonary toxicant emission profiles of five commonly available flavoured disposable e-cigarettes and compared these data with those of a JUUL, a cartridge-based e-cigarette device that pod-mod-like disposables emulate in size and shape. Methods Device construction, electrical power and liquid composition were determined. Machine-generated aerosol emissions including particulate matter, nicotine, carbonyl compounds and heavy metals were also measured. Liquid and aerosol composition were measured by high-performance liquid chromatography, gas chromatography-mass spectrometry/flame ionisation detection, and inductively coupled plasma mass spectrometry. Results We found that unlike JUUL, disposable devices did not incorporate a microcontroller to regulate electrical power to the heating coil. Quality of construction varied widely. Disposable e-cigarette power ranged between 5 and 9 W and liquid nicotine concentration ranged between 53 and 85 mg/mL (~95% in the protonated form). In 15 puffs, total nicotine yield for the disposables ranged between 1.6 and 6.7 mg, total carbonyls ranged between 28 and 138 µg, and total metals ranged between 1084 and 5804 ng. JUUL emissions were near the floors of all of these ranges. Conclusions Disposable e-cigarettes are designed with high nicotine concentration liquids and are capable of emitting much higher nicotine and carbonyl species relative to rechargeable look-alike e-cigarettes. These differences are likely due to the lower quality in construction, unreliable labelling and lack of temperature control regulation that limits the power during operation. From a public health perspective, regulating these devices is important to limit user exposure to carbonyls and nicotine, particularly because these devices are popular with youth and young adults.
Trajectory Mining-Based City-Level Mobility Model for 5G NB-IoT Networks

Due to the large coverage of 5G NB-IoT networks, a more realistic mobility model for a macroscopic scene will greatly facilitate the development of optimal radio resource management algorithms. However, models devised for a random motion scene are no longer applicable in circumstances. Therefore, in this paper, a city-level mobility model is proposed based on the feature mining of the real trajectory of vehicles in the city of Shenzhen. The proposed model is separately designed in the motion trajectory to reduce the mutual influence between the time and spatial sequence. Simulation results show that it can better present specific node motions with the physical constraints of the city layout, which are motivated with a high degree of fit in terms of self-similarity, hotspots, and long-tail features.
SIGNALING EFFECT OF DIVIDEND ANNOUNCEMENTS IN INDIA

A cash dividend is cash payment to a corporation’ s shar eholders, distributed fr om curent earnings or accumulated pr ofits. An announcement of cash dividends would instantly seem to have some impact on a stock’ s returns. To move a stock’ s price, however , the amount of the dividend or the natur e of the dividend must be a surprise. The dividend can be of almost any amount and shar eholders have no guarantee of dividend payments. Decr easing or eliminating a dividend is tantamount to an announcement that the firm is financially distr essed. Directors weigh dividend policies ver y carefully, rarely lowering dividends unless they have to, and not raising dividends unless they ar e confident that they can be sustained. Dividends are consider ed important because investors view them as a signal about a company’ s future profitability. When a company announces a lar ger than expected dividend or unexpectedly announces a dividend cut, the market r eaction is dramatic and sudden. This paper investigates and tests the following: 1) Signaling effect of dividend announcements 2) The market reaction to dividend announcements. S tandard event-study pr ocedures wer e used to calculate the abnormal r eturns. The analysis uses data of 21 firms in the BSE 500 index, which announced dividends during the period 2002 –2004. An examination of shar e price behaviour around dividend announcements pr oves the signaling effect of these announcements. Consistent with pr evious studies, the r esults show that dividend initiations have significantly positive effects on stock r eturns. Dividend announcements r ecorded high cumulative abnor mal returns of 2.1 per cent within one day of the event. S udies indicate that stock prices typically change to r eflect dividend policy changes within the trading day of the announcement. With market reaction this quick, it is difficult, if not impossible, for investors to make extra money after the announcement has been made. The only way for an individual to take advantage of a positive or negative surprise dividend announcement is to be positioned prior to the announcement.
Effect of Corporate Restructuring on Employee Morale: Evidence from Airtel Nigeria Limited

Corporate restructuring is the act of re-organizing the operations of a firm in order to eliminate waste, promote efficiency, increase profitability, and ensure organizational sustainability. Yet, there has been a dearth of empirical studies on the effect of corporate restructuring on employee morale. The study sought to examine the extent to which work process has effect on employee punctuality, the extent to which organizational structure affects employee turnover rate and how an altered physical environment influences interpersonal relationships among employees. Data were sourced from three hundred and eighty (380) participants. The results of the regression analyses showed that change in the work process has a significant effect on employee punctuality at work, change in organizational structure has a significant effect on employee turnover rate and altered physical environment influences inter-personal relationships among workers. It was recommended that corporate organizations embarking on restructuring should take into consideration the effect of the exercise on employee morale in the interest of superior performance.
Using of Gum Arabic to Ameliorate Liver Disorders Induced by Benzo(a)pyrene in Rats

This study was carried out to evaluate the effects of Gum Arabic (GA) in liver functions of rats treated withbenzo(a)pyrene(B(a)P). Thirty sixmale mature albino rats weighted 130-150g per each, were used in this study and divided two main groups, the first group(Group 1, 5 rats as a negative control group) still fed on basal diet and injected with the vehicle alone (5 ml/kg body weight), while the other main group (25 rats) was were challenged with an ip injection of B[a]P (100 mg/5 ml/kg body weight) dissolved in 0.9% NaCL solution containing 0.1% Tween 20 to induce liver impaired. The tested plant powder were given to the rats as a percent of 1,2,3 and 4% from the basel diet for 28 days . At the end of the experiment,Glotamic oxalic transaminase (AST),Glotamicpyrofic transaminase (ALT), alkaline phosphatase (ALP), GSH was determined by HPLC , Liver glycogen levels determined after digestion of liver and precipitation of glycogen by glycogen assay kit II,lipid peroxide levels measured as malondialdehyde in serum and liver were determined as thiobarbituric acid reactive substances (TBARS). According to the results,Gum Arabic (GA) could be used for improvement of liver functions and the best treatment was for group 6 (treated with 4% GA powder).
The effect of zinc fertilization and cow dung on sterility and quantitative traits of rice

The grain yield of rice is far below from its potential yield due low organic matter and micronutrients in the soil. Application of cow dung and zinc fertilizer increases grain yield and quality. A field experiment was, therefore, conducted to evaluate the effect of zinc fertilization and well decomposed cow dung on the spikelet sterility, yield, zinc concentration in grains and plants of aromatic rice (cv. Tulshimala). In this experiment, two levels of well decomposed cowd ung (CD) of 0, 10 tha-1, and four doses of zinc fertilization viz. 0, 2.16, 4.32, 6.48 kg ha-1 of zinc were used following eight treatment combinations. The experiment was laid out in a factorial randomized complete block design (RCBD) with replication thrice. The data revealed that zinc fertilization remarkably increased the grain yield of Tulshimala by reducing the spikelet sterility percentages in both conditions of CD and the efficiency of zinc fertilization was superior in manuring (CD) condition to non-manuring condition. However, zinc fertilization at the rate of 4.32 kg ha-1 of zinc produced the maximum grain yields under manuring and non-manuring conditions. Zinc fertilization increased the concentration of Zn in the rice plants and grains without and with CD. The strong linear relationship between the grain yield and zinc concentration in the rice plants and grains was found with in this study. Zinc fertilization increased the grain yield and quality by decreasing sterility percentage under CD. Hence, for increasing productivity towards food security in future generation, integrated use organic and inorganic fertilizers should be used.