Candidate Signals Research Articles

Reduction of PAPR Without Side Information for SFBC MIMO-OFDM Systems

A novel peak-to-average power ratio (PAPR) reduction scheme designated as extended selected mapping (eSLM) is proposed for space-frequency block coding (SFBC) multi-input multi-output orthogonal frequency division multiplexing systems. In the eSLM method, extension matrices comprising amplitude extensions and phase rotations are constructed to indicate the selected signal index without the need for side information and to minimize the PAPR, respectively. To reduce the computational complexity incurred by the inverse discrete Fourier transform operation in generating the candidate signals, a low-complexity eSLM scheme (LC-eSLM) is developed by constructing equivalent candidate signals in the time domain. Notably, the extension matrices in both schemes preserve the orthogonality of the SFBC code, thereby facilitating low-complexity decoding. The simulation results show that the proposed eSLM scheme not only outperforms existing blind SLM-based methods. Compared with the costly ordinary SLM scheme, the eSLM scheme has a lower computational complexity with a performance loss of less than 0.3 dB and requires no side information. Furthermore, the computational complexity of the LC-eSLM scheme is around 40%–50% lower than that of the eSLM scheme with only a marginal degradation in the PAPR reduction performance.

Porpoise click classifier (PorCC): A high-accuracy classifier to study harbour porpoises (Phocoena phocoena) in the wild.

Harbour porpoises are well-suited for passive acoustic monitoring (PAM) as they produce highly stereotyped narrow-band high-frequency (NBHF) echolocation clicks. PAM systems must be coupled with a classification algorithm to identify the signals of interest. Here, the authors present a harbour porpoise click classifier (PorCC) developed in matlab, which uses the coefficients of two logistic regression models in a decision-making pathway to assign candidate signals to one of three categories: high-quality clicks (HQ), low-quality clicks (LQ), or high-frequency noise. The receiver operating characteristics of PorCC was compared to that of PAMGuard's Porpoise Click Detector/Classifier Module. PorCC outperformed PAMGuard's classifier achieving higher hit rates (correctly classified clicks) and lower false alarm levels (noise classified as HQ or LQ clicks). Additionally, the detectability index (d') for HQ clicks for PAMGuard was 2.2 (overall d' = 2.0) versus 4.1 for PorCC (overall d' = 3.4). PorCC classification algorithm is a rapid and highly accurate method to classify NBHF clicks, which could be applied for real time monitoring, as well as to study harbour porpoises, and potentially other NBHF species, throughout their distribution range from data collected using towed hydrophones or static recorders. Moreover, PorCC is suitable for studies of acoustic communication of porpoises.

DIVA: Exploration and Validation of Hypothesized Drug‐Drug Interactions

AbstractAdverse reactions caused by drug‐drug interactions are a major public health concern. Currently, adverse reaction signals are detected through a tedious manual process in which drug safety analysts review a large number of reports collected through post‐marketing drug surveillance. While computational techniques in support of this signal analysis are necessary, alone they are not sufficient. In particular, when machine learning techniques are applied to extract candidate signals from reports, the resulting set is (1) too large in size, i.e., exponential to the number of unique drugs and reactions in reports, (2) disconnected from the underlying reports that serve as evidence and context, and (3) ultimately requires human intervention to be validated in the domain context as a true signal warranting action. In this work, we address these challenges though a visual analytics system, DIVA, designed to align with the drug safety analysis workflow by supporting the detection, screening, and verification of candidate drug interaction signals. DTVA's abstractions and encodings are informed by formative interviews with drug safety analysts. DIVA's coordinated visualizations realize a proposed novel augmented interaction data model (AIM) which links signals generated by machine learning techniques with domain‐specific metadata critical for signal analysis. DIVA's alignment with the drug review process allows an analyst to interactively screen for important signals, triage signals for in‐depth investigation, and validate signals by reviewing the underlying reports that serve as evidence. The evaluation of DIVA encompasses case‐studies and interviews by drug analysts at the US Food and Drug Administration ‐ both of which confirm that DIVA indeed is effective in supporting analysts in the critical task of exploring and verifying dangerous drug‐drug interactions.

Evaluation of osteoclast-derived exosomal miRNA under simulated microgravity conditions using next-generation sequencing

The important role of osteoclast-derived exosomes in bone remodeling of microgravity-induced osteoporosis has been validated. However, the underlying mechanism remains unclear. A set of total miRNAs expressed in osteoclast-derived exosomes may configure the specific signature of the bone tissue in the microgravity condition. This study aimed to investigate the miRNA expression profile of osteoclast-derived exosomes in simulated microgravity using next-generation sequencing. Cell culture supernatant of osteoclasts under normal gravity conditions and simulated microgravity conditions were harvested for the extraction of exosomes and exosomal miRNAs. Our results revealed that 116 aberrantly expressed exosomal miRNAs including 29 up-regulated miRNAs and 87 down-regulated miRNAs were found in the simulated microgravity group compared to the normal gravity control group. The candidate target genes and signaling pathways of 15 selected differentially expressed miRNAs were identified via target genes prediction, GO and KEGG analyses. Furthermore, miRNA qPCR assay was performed to validate the RNA sequencing results. Collectively, these analyses provide insight regarding the effects of microgravity in modulating the extracellular miRNA profile through exosomes released from osteoclasts. The selective packaging of miRNA cargo in exosomes under microgravity could facilitate the development of promising and effective targets for the diagnosis, prevention, and treatment of microgravity-induced osteoporosis.

The Queen of the Paper Wasp Polistes jokahamae (Vespidae: Polistinae) Is Not Aggressive but Maintains Her Reproductive Priority

The behaviors performed on the nest by the foundress queen and workers of the paper wasp Polistes jokahamae were observed in three colonies in the field and one colony in a cage set in the field. Each queen was rarely ranked top in the dominance hierarchy determined by the pairwise dominance–subordinate interactions and did not display more frequent direct aggression toward the top-ranked worker than toward other workers. Furthermore, the queen exhibited aggression less frequently than did the most aggressive workers in all four colonies. The dominance order among the workers was positively correlated with the emergence order, with older workers being more dominant. The queen laid eggs in a dominant or monopolized way; some dominant workers laid eggs in three colonies. These observations suggest that the queen maintained her queen status, including her reproductive priority, using signals rather than aggression. Lateral vibrations (rapidly laterally vibrating the abdomen) and abdominal rubbing (rubbing the abdomen onto the comb) appeared to be candidate signals of the fertility or reproductive potential of the performer. Lateral vibrations were performed only by the queen, and their frequency was positively correlated with the frequency of ovipositing. The queen and some dominant workers performed abdominal rubbing; the frequency was higher for the queen than for any of the dominant workers early in the colony’s development, but not later. Although performers of abdominal rubbing were more likely to lay eggs than non-performers, the frequency of abdominal rubbing was not a predictor of the frequency of ovipositing.

Search for Gravitational Waves from a Long-lived Remnant of the Binary Neutron Star Merger GW170817

Abstract One unanswered question about the binary neutron star coalescence GW170817 is the nature of its post-merger remnant. A previous search for post-merger gravitational waves targeted high-frequency signals from a possible neutron star remnant with a maximum signal duration of 500 s. Here, we revisit the neutron star remnant scenario and focus on longer signal durations, up until the end of the second Advanced LIGO-Virgo observing run, which was 8.5 days after the coalescence of GW170817. The main physical scenario for this emission is the power-law spindown of a massive magnetar-like remnant. We use four independent search algorithms with varying degrees of restrictiveness on the signal waveform and different ways of dealing with noise artefacts. In agreement with theoretical estimates, we find no significant signal candidates. Through simulated signals, we quantify that with the current detector sensitivity, nowhere in the studied parameter space are we sensitive to a signal from more than 1 Mpc away, compared to the actual distance of 40 Mpc. However, this study serves as a prototype for post-merger analyses in future observing runs with expected higher sensitivity.

Single cell RNA sequencing identifies TGFβ as a key regenerative cue following LPS-induced lung injury.

Many lung diseases result from a failure of efficient regeneration of damaged alveolar epithelial cells (AECs) after lung injury. During regeneration, AEC2s proliferate to replace lost cells, after which proliferation halts and some AEC2s transdifferentiate into AEC1s to restore normal alveolar structure and function. Although the mechanisms underlying AEC2 proliferation have been studied, the mechanisms responsible for halting proliferation and inducing transdifferentiation are poorly understood. To identify candidate signaling pathways responsible for halting proliferation and inducing transdifferentiation, we performed single cell RNA sequencing on AEC2s during regeneration in a murine model of lung injury induced by intratracheal LPS. Unsupervised clustering revealed distinct subpopulations of regenerating AEC2s: proliferating, cell cycle arrest, and transdifferentiating. Gene expression analysis of these transitional subpopulations revealed that TGFβ signaling was highly upregulated in the cell cycle arrest subpopulation and relatively downregulated in transdifferentiating cells. In cultured AEC2s, TGFβ was necessary for cell cycle arrest but impeded transdifferentiation. We conclude that during regeneration after LPS-induced lung injury, TGFβ is a critical signal halting AEC2 proliferation but must be inactivated to allow transdifferentiation. This study provides insight into the molecular mechanisms regulating alveolar regeneration and the pathogenesis of diseases resulting from a failure of regeneration.

Data Mining and Validation of AMPK Pathway as a Novel Candidate Role Affecting Intramuscular Fat Content in Pigs.

Simple SummaryIntramuscular fat (IMF) is increasingly being recognized as a key meat trait in the modern pork industry. The aims of this research were to identify potential signaling pathways associated with IMF content in the longissimus dorsi (LD) muscle of different pig breeds and investigate the gene expression levels in the screened signaling pathways. Our results indicated that the AMPK signaling pathway may be related to IMF deposition in the LD muscle of pigs. The results of qRT-PCR analysis showed that the expression of ten key hub genes (AMPK, ADIPOR1, ADIPOR2, LKB1, CAMKKβ, CPT1A, CPT1B, PGC-1α, CD36, and ACC1) differed between the LD muscle of Min and Large White pigs. The protein expression levels of AMPK, LKB1, CaMKK2, CPT1A, and ACC1 were similar to the genes expression patterns in the LD muscle of Large White pigs. The results of this study provide novel insights into the regulatory function of the AMPK signaling pathway in relation to the IMF content in the LD muscle of different pigs.Intramuscular fat (IMF) is an important economic trait for pork quality and a complex quantitative trait regulated by multiple genes. The objective of this work was to investigate the novel transcriptional effects of a multigene pathway on IMF deposition in the longissimus dorsi (LD) muscles of pigs. Potential signaling pathways were screened by mining data from three gene expression profiles in the Gene Expression Omnibus (GEO) database. We designed quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) arrays for the candidate signaling pathways to verify the results in the LD muscles of two pig breeds with different IMF contents (Large White and Min). Western blot analysis was used to detect the expression levels of several candidate proteins. Our results showed that the AMPK signaling pathway was screened via bioinformatics analysis. Ten key hub genes of this signaling pathway (AMPK, ADIPOR1, ADIPOR2, LKB1, CAMKKβ, CPT1A, CPT1B, PGC-1α, CD36, and ACC1) were differentially expressed between the Large White and Min pigs. Western blot analysis further confirmed that LKB1/CaMKK2-AMPK-ACC1-CPT1A axis dominates the activity of AMPK signaling pathway. Statistical analyses revealed that AMPK signaling pathway activity clearly varied among the two pig breeds. Based on these results, we concluded that the activation of the AMPK signaling pathway plays a positive role in reducing IMF deposition in pigs.

A novel approach for reducing complexity in the SLM-GFDM system

The flexible nature of generalized frequency division multiplexing (GFDM) leads to superimposition of multiple subsymbols in time domain, the consequence of which is high PAPR. Selective mapping (SLM) is one of the prominent PAPR reduction techniques in GFDM, which uses bank of modulation matrices to generate a set of alternative signal representations. This procedure increases the complexity of the GFDM system enormously. In this paper, we utilize the concepts of conversion matrices and linearity to achieve low complexity with respect to the modulation matrices in the conventional SLM method. By using the proposed conversions we evolve at three modified SLM schemes which have much lower complexity. The first method uses the principle of linearity and two GFDM signals to generate the set of candidate signals while the second one uses only one GFDM signal along with conversion matrix. By adhering the advantages of two methods, the third method adds the concept of shifting matrix, which is an effective solution for tradeoff between PAPR performance and computational complexity. The obtained simulation results indicate that, when compared to conventional SLM scheme, the first proposed approach has inferior PAPR reduction performance, whereas, second and third proposed methods almost reach the performance of the conventional SLM scheme.

A comprehensive real-time analysis model at the LHCb experiment

An evolved real-time data processing strategy is proposed for high-energy physics experiments, and its implementation at the LHCb experiment is presented. The reduced event model allows not only the signal candidate firing the trigger to be persisted, as previously available, but also an arbitrary set of other reconstructed or raw objects from the event. This allows for higher trigger rates for a given output data bandwidth, when compared to the traditional model of saving the full raw detector data for each trigger, whilst accommodating inclusive triggers and preserving data mining capabilities. The gains in physics reach and savings in computing resources already made possible by the model are discussed, along with the prospects of employing it more widely for Run 3 of the Large Hadron Collider.

Pulsar candidate selection using ensemble networks for FAST drift-scan survey

The Commensal Radio Astronomy Five-hundred-meter Aperture Spherical radio Telescope (FAST) Survey (CRAFTS) utilizes the novel drift-scan commensal survey mode of FAST and can generate billions of pulsar candidate signals. The human experts are not likely to thoroughly examine these signals, and various machine sorting methods are used to aid the classification of the FAST candidates. In this study, we propose a new ensemble classification system for pulsar candidates. This system denotes the further development of the pulsar image-based classification system (PICS), which was used in the Arecibo Telescope pulsar survey, and has been retrained and customized for the FAST drift-scan survey. In this study, we designed a residual network model comprising 15 layers to replace the convolutional neural networks (CNNs) in PICS. The results of this study demonstrate that the new model can sort >96% of real pulsars to belong the top 1% of all candidates and classify >1.6 million candidates per day using a dual--GPU and 24--core computer. This increased speed and efficiency can help to facilitate real-time or quasi-real-time processing of the pulsar-search data stream obtained from CRAFTS. In addition, we have published the labeled FAST data used in this study online, which can aid in the development of new deep learning techniques for performing pulsar searches.

Effective-field-theory arguments for pursuing lepton-flavor-violating K decays at LHCb

We provide general effective-theory arguments relating present-day discrepancies in semi-leptonic $B$-meson decays to signals in kaon physics, in particular lepton-flavour violating ones of the kind $K \to (\pi) e^\pm \mu^\mp$. We show that $K$-decay branching ratios of around $10^{-12} - 10^{-13}$ are possible, for effective-theory cutoffs around $5-15$ TeV compatible with discrepancies in $B\to K^{(\ast)} \mu\mu$ decays. We perform a feasibility study of the reach for such decays at LHCb, taking $K^+ \to \pi^+ \mu^\pm e^\mp$ as a benchmark. In spite of the long lifetime of the $K^+$ compared to the detector size, the huge statistics anticipated as well as the overall detector performance translate into encouraging results. These include the possibility to reach the $10^{-12}$ ballpark, and thereby significantly improve current limits. Our results advocate LHC's high-luminosity Upgrade phase, and support analogous sensitivity studies at other facilities. Given the performance uncertainties inherent in the Upgrade phase, our conclusions are based on a range of assumptions we deem realistic on the particle identification performance as well as on the kinematic reconstruction thresholds for the signal candidates.

A deep XMM-Newton look on the thermally emitting isolated neutron star RX J1605.3+3249

Previous XMM-Newton observations of the thermally emitting isolated neutron star RX J1605.3+3249 provided a candidate for a shallow periodic signal and evidence of a fast spin down, which suggested a high dipolar magnetic field and an evolution from a magnetar. We obtained a large programme with XMM-Newton to confirm its candidate timing solution, understand the energy-dependent amplitude of the modulation, and investigate the spectral features of the source. We performed extensive high-resolution and broadband periodicity searches in the new observations, using the combined photons of the three EPIC cameras and allowing for moderate changes of pulsed fraction and the optimal energy range for detection. We also investigated the EPIC and RGS spectra of the source with unprecedented statistics and detail. A deep 4σ upper limit of 1.33(6)% for modulations in the relevant frequency range conservatively rules out the candidate period previously reported. Blind searches revealed no other periodic signal above the 1.5% level (3σ; P > 0.15 s; 0.3–1.35 keV) in any of the four new observations. While theoretical models fall short at physically describing the complex energy distribution of the source, best-fit X-ray spectral parameters are obtained for a fully or partially ionized neutron star hydrogen atmosphere model with B = 1013 G, modified by a broad Gaussian absorption line at energy ϵ = 385 ± 10 eV. A double-temperature blackbody model, although a good fit to the source spectrum, is disfavoured as it would require a particularly improbable viewing geometry to explain the lack of X-ray pulsations associated with small hotspots on the surface of the neutron star. We identified a low significance (1σ) temporal trend on the parameters of the source in the analysis of RGS data dating back to 2002, which may be explained by unaccounted calibration issues and spectral model uncertainties. The new dataset also shows no evidence of the previously reported narrow absorption feature at ϵ ∼ 570 eV, whose possible transient nature disfavours an atmospheric origin.

A Quantitative Analytical Framework for Photon Transfer Curve-Based Preflight Characterization of the Indian Remote Sensing Imaging Systems

Preflight performance characterization of spaceborne imaging systems offers high-quality images for scientific applications. A key challenge in the laboratory characterization process is to identify the candidate signal chains requiring performance optimization. For the Indian Remote Sensing (IRS) imaging systems, light transfer characterization has been identified as a standard process for performance characterization. Photon transfer curve (PTC) is another powerful and widely used tool to characterize the imaging systems in terms of camera gain ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$e^{-}$ </tex-math></inline-formula> /DN), read noise ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$e^{-}$ </tex-math></inline-formula> ), charge-to-voltage conversion factor (CVF), signal-to-noise ratio, mean–variance linearity, and so on. There have been no detailed investigations on the PTC characteristics of the IRS imaging systems. We present here PTC-based characterization studies on two high-resolution IRS imaging systems, namely, Cartosat-1 and Cartosat-2. For this, a quantitative analytical framework has been developed, which enables comparative studies among multiple signal chains by applying various statistical measures on the PTC derived parameters. This framework provides not only a quantitative assessment of performance deviations but also enables performance traceability up to detector level. Taken together, our analysis shows that all the signal chains have well behaved PTC characteristics, and performance deviations are less than 10%. In particular, performance traceability is established by the close match of the system-level CVF values within the detector manufacturer’s specified range. Studies on the adequacy of linear approximation of the PTC curve reveal large residual errors in the lower dynamic range due to an increase in read noise floor. The analytical framework developed here can significantly help optimize future IRS imaging systems.

Transcriptome analysis provides insights into the molecular mechanisms responsible for evisceration behavior in the sea cucumber Apostichopus japonicus

The sea cucumber Apostichopus japonicus (Selenka) is a valuable economic species in Southeast Asia. It has many fascinating behavioral characteristics, such as autolysis, aestivation, regeneration, and evisceration, thus it is a notable species for studies of special behaviors. Evisceration and autotomy are controlled by the neural network and involve a complicated physiological process. The occurrence of evisceration behavior in sea cucumbers is strongly related to their environment, and it negatively impacts their economic value. Evisceration behavior plays a pivotal role in the survival of A. japonicus, and when it is induced by dramatic changes in the coastal ecological environment and the aquaculture setting it can strongly affect the economic performance of this species. Although numerous studies have focused on intestinal regeneration of A. japonicus, less is known about evisceration behavior, especially its underlying molecular mechanisms. Thus, identification of genes that regulate evisceration in the sea cucumber likely will provide a scientific explanation for this significant specific behavior. In this study, Illumina sequencing (RNA-Seq) was performed on A. japonicus specimens in three states: normal (TCQ), eviscerating (TCZ), and 3 h after evisceration (TCH). In total, 129,905 unigenes were generated with an N50 length of 2651 base pairs, and 54,787 unigenes were annotated from seven functional databases (KEGG, KOG, GO, NR, NT, Interpro, and Swiss-Prot). Additionally, 190, 191, and 320 genes were identified as differentially expressed genes (DEGs) in the comparisons of TCQ vs. TCZ, TCZ vs. TCH, and TCQ vs. TCH, respectively. These DEGs mapped to 157, 113, and 190 signaling pathways in the KEGG database, respectively. KEGG analyses also revealed that potential DEGs enriched in the categories of “environmental information processing,” “organismal system,” “metabolism,” and “cellular processes,” and they were involved in evisceration behavior in A. japonicus. These DEGs are related to muscle contraction, hormone and neurotransmitter secretion, nerve and muscle damage, energy support, cellular stress, and apoptosis. In conclusion, through our comparative analysis of A. japonicus in different stages, we identified many candidate evisceration-related genes and signaling pathways that likely are involved in evisceration behavior. These results should help further elucidate the mechanisms underlying evisceration behavior in sea cucumbers.

First search for [formula omitted] using the decay-in-flight technique

The NA62 experiment at the CERN SPS reports the first search for K+→π+νν¯ using the decay-in-flight technique, based on a sample of 1.21×1011K+ decays collected in 2016. The single event sensitivity is 3.15×10−10, corresponding to 0.267 Standard Model events. One signal candidate is observed while the expected background is 0.152 events. This leads to an upper limit of 14×10−10 on the K+→π+νν¯ branching ratio at 95% CL.

Relation between Changes in Photosynthetic Rate and Changes in Canopy Level Chlorophyll Fluorescence Generated by Light Excitation of Different Led Colours in Various Background Light

Using light emitting diodes (LEDs) for greenhouse illumination enables the use of automatic control, since both light quality and quantity can be tuned. Potential candidate signals when using biological feedback for light optimisation are steady-state chlorophyll a fluorescence gains at 740 nm, defined as the difference in steady-state fluorescence at 740 nm divided by the difference in incident light quanta caused by (a small) excitation of different LED colours. In this study, experiments were conducted under various background light (quality and quantity) to evaluate if these fluorescence gains change relative to each other. The light regimes investigated were intensities in the range 160–1000 μ mol m − 2 s − 1 , and a spectral distribution ranging from 50% to 100% red light. No significant changes in the mutual relation of the fluorescence gains for the investigated LED colours (400, 420, 450, 530, 630 and 660 nm), could be observed when the background light quality was changed. However, changes were noticed as function of light quantity. When passing the photosynthesis saturate intensity level, no further changes in the mutual fluorescence gains could be observed.

An Enhanced Peak to Average Power Ratio Reduction Scheme for Interleaved and Sub-Band Orthogonal Frequency-Division Multiple Access Frameworks with Low Complexity

Orthogonal Frequency Division Multiplexing (OFDM) is a multicarrier transmission technique which has the major drawback namely Peak to Average Power Ratio (PAPR). The high PAPR influences the efficiency of the power amplifier. The Selected Level Mapping (SLM) gives reduced PAPR contrasted with different strategies but the complexity is high due to the necessity of various Inverse Fast Fourier Transform (IFFTs). With the end goal to reduce the complexity, the proposed design requires only one IFFT, the candidate signals are produced by cyclic shifting the original time domain signal then multiplying with the distinctive genuine positive numbers. At that point the candidate with most minimal PAPR is chosen for transmission.

PAPR Reduction in DCO-OFDM Visible Light Communication Systems Using Optimized Odd and Even Sequences Combination

This paper proposes a novel peak-to-average power ratio (PAPR) reduction scheme, which has several advantages, such as low-complexity candidate construction and no side information (SI) transmission in direct current-biased optical orthogonal frequency division multiplexing (DCO-OFDM) visible light communication (VLC) systems. In the proposed scheme, the candidates can be generated by linearly combining time-domain even and odd sequences with cyclic shift and phase rotation. Even and odd sequences are obtained by adopting an inverse fast Fourier transform on the even and odd parts of a Hermitian symmetry encoded signal, respectively. Furthermore, a deterministic and efficient selection method of cyclic shift and phase rotation is derived to improve PAPR reduction performance and ensure that each candidate is unique, so that the receiver can recover the transmitted candidate signal without the use of SI. Simulation results show that the proposed scheme can achieve comparable PAPR reduction performance with the conventional selected mapping (CSLM) scheme with random and chaotic sequences, but at a considerably low computational complexity. Moreover, the proposed blind SI detection scheme provides almost the same bit error rate (BER) performance as that of the CSLM scheme with a perfect SI detection and symmetric selected mapping for a DCO-OFDM VLC system with 1024 subcarriers and 16-QAM. In contrast to other related time-domain sequences that combine methods used for DCO-OFDM systems, the proposed scheme improves BER performance with a slight increase in computational complexity and PAPR.

Shading of mature leaves systemically regulates photosynthesis and leaf area of new developing leaves via hormones

In order to explore whether leaf area of developing leaves was regulated by systemic irradiance signal from mature leaves, we investigated the leaf area, leaf anatomy, photosynthesis, auxin, gibberellin, and cytokinin contents of new developing leaves in soybean growing under conditions of shaded mature leaves (MS), shaded whole plants (WS), and under full sunlight (NS). The results showed that developing leaves under MS exhibited the higher leaf area and leaf mass than that of WS. Blade thickness, palisade tissue thickness, sponge tissue thickness, cell size, cell numbers, net photosynthetic rate, stomatal conductance, transpiration rate, and cytokinin content of developing leaves under MS were lower, while auxin and gibberellin contents were higher than that of NS. These results indicate that the leaf area, leaf anatomy, and photosynthesis of developing leaves were regulated by the shading environment of mature leaves. Growth hormones may possibly act as candidate signal substances to systemic regulation of leaf area development.