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Abstract Background Zambia has made profound strides in reducing both the incidence and prevalence of malaria followed by reducing malaria related deaths between 2009 and 2018. The number of partners providing malaria funding has significantly increased in the same period. The increasing number of partners and the subsequent reduction of the number of reported malaria cases in the Ministry of Health main data repository Health Management Information System (HMIS) stimulated this research. The study aimed at (1) identifying major sources of malaria funding in Zambia; (2) describe malaria funding per targeted interventions and (3) relating malaria funding with malaria disease burden. Methods Data was collected using extensive literature review of institutional strategic document between the year 2009 to 2018, assuming one-year time lag between investment and the health outcome across all interventions. The National’s Health Management Information System (HMIS) provided information on annual malaria admission cases and outpatient clinic record. The statistical package for social sciences (SPSS) alongside Microsoft excel was used to analyze data in the year 2019. Results The investigation observed that about 30% of the funding came from PMI/USAID, 26% from the global funds, the government of Zambia contributed 17% and other partners sharing the remaining 27%. Multivariate regression analysis suggests a positive correlation between reducing reported malaria disease burden in HMIS 2009–2018 and concurrent increasing program/intervention funding towards ITNs, IRS, MDA, and Case Management with r2 = 77% (r2 > 0.77; 95% CI: 0.72–0.81). Furthermore, IRS showed a p-value 0.018 while ITNs, Case Management and MDA having 0.029, 0.030 and 0.040 respectively. Conclusion Our findings highlight annual funding towards specific malaria intervention reduced the number of malaria admission cases.

Heterotrimeric G-proteins are fundamental signal transducers highly conserved in plant species, which play crucial roles in regulating plant growth, development, and responses to abiotic stresses. Identification of G-protein members and their expression patterns in plants are essential for improving crop resilience against environmental stresses. Here, we identified eight heterotrimeric G-protein genes localized on four chromosomes within the barley genome by using comprehensive genome-wide analysis. Phylogenetic analysis classified these genes into four distinct subgroups with obvious evolutionary relationships. Further analysis on gene structure, protein motif, and structure indicated that G-proteins within each evolutionary branch exhibited similar exon-intron organization, conserved motif patterns, and structural features. Collinearity analysis showed no significant collinear relationships among those G-protein genes, indicating a unique evolutionary trajectory within barley. Moreover, cis-regulatory elements detected in the upstream sequences of these genes were involved in response to plant hormones and signaling molecules. Expression analyses revealed tissue-specific expression patterns and differential regulation in response to abiotic stresses. The expression patterns of G-protein genes were further validated using a quantitative real-time PCR (qRT-PCR) technique, indicating the reliability of transcriptomic data, as well as special responses to salt, drought, and waterlogging stresses. These findings may provide underlying mechanisms by which G-protein genes participate in salt tolerance of barley, and also highlight candidate genes for potential genetic engineering applications in improving crop resilience to salinity stress. [ABSTRACT FROM AUTHOR]

G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins and are important drug targets. The discovery of drugs targeting these receptors and their G protein signaling properties are based on assays mainly performed with modified receptors expressed in heterologous cells. However, GPCR responses may differ in their native environment. Here, by using highly sensitive Gi/o sensors, we reveal specific properties of Gi/o protein-mediated responses triggered by GABAB, α2 adrenergic and cannabinoid CB1 receptors in primary neurons, different from those in heterologous cells. These include different profiles in the Gi/o protein subtypes-mediated responses, and differences in the potencies of some ligands even at similar receptor expression levels. Altogether, our results show the importance of using biosensors compatible with primary cells for evaluating the activities of endogenous GPCRs in their native environment. G protein responses mediated by GPCRs may differ depending on their environment. Here, using highly sensitive Gi/o sensors, the authors reveal the specific pharmacological and Gi/o protein responses of some native GPCRs in neurons, and the influence of G protein composition. [ABSTRACT FROM AUTHOR]

We extracted Sal B and TIIA from Salvia miltiorrhiza using enzymatic-assisted ethanol extraction. ACONN predicted optimal process conditions. Enzymolysis and alcohol extraction were used, optimizing conditions and evaluating antioxidant activity. ACONN analyzed data and ACO optimized conditions. Lab verification comprehensively evaluated the conditions. The correlation between Sal B, TIIA, and their antioxidant activities was examined. Weights of 0.5739 and 0.4260 evaluated Sal B and TIIA. ACONN had a 97.46% fitting degree. Optimized extraction conditions improved yield and quality, yielding a comprehensive evaluation value of 27.69 with 4.46% average errors. This approach enhances extraction and compound quality. Antioxidant activity strongly correlated with component yield, influenced by extraction conditions. ACONN-optimized extraction improved Sal B and TIIA yield and quality, with potential as natural antioxidants. Integrating machine learning and optimization algorithms in industrial extraction enhances efficiency and environmental preservation. [ABSTRACT FROM AUTHOR]

The assimilation of remote sensing data into mechanistic models of crop growth has become an available method for estimating yield. The objective of this study was to explore an effective assimilation approach for estimating maize grain protein content and yield using a canopy remote sensing data and crop growth model. Based on two years of field experiment data, the remote sensing inversion model using assimilation intermediate variables, namely leaf area index (LAI) and leaf nitrogen accumulation (LNA), was constructed with an R2 greater than 0.80 and a low root-mean-square error (RMSE). The different data assimilation approaches showed that when the LAI and LNA variables were used together in the assimilation process (VLAI+LNA), better accuracy was achieved for LNA estimations than the assimilation process using single variables of LAI or LNA (VLAI or VLNA). Similar differences in estimation accuracy were found in the maize yield and grain protein content (GPC) simulations. When the LAI and LNA were both intermediate variables in the assimilation process, the estimation accuracy of the yield and GPC were better than that of the assimilation process with only one variable. In summary, these results indicate that two physiological and biochemical parameters of maize retrieved from hyperspectral data can be combined with the crop growth model through the assimilation method, which provides a feasible method for improving the estimation accuracy of maize LAI, LNA, GPC and yield. [ABSTRACT FROM AUTHOR]

Although numerous channel estimation and multiuser detection approaches have appeared for long-code uplink CDMA systems, joint performance study of channel estimators and symbol detectors remains largely open. In this paper, we construct three typical symbol-level linear receivers upon existing channel estimation method, known as zero-forcing (ZF), minimum mean-square-error (MMSE), and RAKE receivers, for symbol detection. Since the channel estimation error is rippled to the linear receivers, performance of all receivers is thus jointly analyzed with the channel estimator from a perturbation perspective. Extensive simulation examples involving different communication environments demonstrate high consistency between our analysis and experimental results.

Text-to-speech (TTS) synthesizers have been widely used as a vital assistive tool in various fields. Traditional sequence-to-sequence (seq2seq) TTS such as Tacotron2 uses a single soft attention mechanism for encoder and decoder alignment tasks, which is the biggest shortcoming that incorrectly or repeatedly generates words when dealing with long sentences. It may also generate sentences with run-on and wrong breaks regardless of punctuation marks, which causes the synthesized waveform to lack emotion and sound unnatural. In this paper, we propose an end-to-end neural generative TTS model that is based on the deep-inherited attention (DIA) mechanism along with an adjustable local-sensitive factor (LSF). The inheritance mechanism allows multiple iterations of the DIA by sharing the same training parameter, which tightens the token–frame correlation, as well as fastens the alignment process. In addition, LSF is adopted to enhance the context connection by expanding the DIA concentration region. In addition, a multi-RNN block is used in the decoder for better acoustic feature extraction and generation. Hidden-state information driven from the multi-RNN layers is utilized for attention alignment. The collaborative work of the DIA and multi-RNN layers contributes to outperformance in the high-quality prediction of the phrase breaks of the synthesized speech. We used WaveGlow as a vocoder for real-time, human-like audio synthesis. Human subjective experiments show that the DIA-TTS achieved a mean opinion score (MOS) of 4.48 in terms of naturalness. Ablation studies further prove the superiority of the DIA mechanism for the enhancement of phrase breaks and attention robustness. [ABSTRACT FROM AUTHOR]

Optical wireless communication (OWC) in the deep‐ultraviolet (DUV) band requires an efficient DUV light source with large bandwidth characteristics. In this work, a feasible approach is reported to enlarge the light output power as well as the bandwidth of a DUV light‐emitting diode (LED) by embedding a SiO2‐based microcavity on which an aluminum (Al) reflector is simultaneously deposited. Consequently, on the one hand, the microcavity with the Al‐reflector can facilitate photon escape from the LED to increase the light extraction efficiency, thus enhancing the light output power of the devices. On the other hand, the LED incorporated with a microcavity structure exhibits a reduced resistance–capacitance time constant, leading to an increase in the modulation bandwidth of the LED. Strikingly, the DUV LED incorporated with microcavities represents a significant enhancement of light output power by nearly 30% at 80 mA while exhibiting a higher modulation bandwidth of 12% in comparison to the conventional LED without microcavities. Thus, the implementation of the microcavity and Al reflector on top of a classic LED can enlarge the light output power and modulation bandwidth, eventually facilitating to establish viable high‐speed OWC systems. [ABSTRACT FROM AUTHOR]

In this paper, we develop medium access control (MAC) schemes for both contention and contention-free accesses over wireless local area networks and give performance analysis of these MAC protocols. User detection and multirate adaptation (MRA) modules are proposed in the physical layer (PHY) to assist link differentiation. With these two modules, for contention accesses, a new distributed queuing MAC protocol (PALD-DQMP) is proposed. Based on different users' channel states, PALD-DQMP makes use of a distributed queuing system to schedule transmissions. To support multimedia transmissions, an enhanced PALD-DQMP (E-PALD-DQMP) is designed by providing two-level optimized transmission scheduling for four access categories, thus eliminating both external and internal collisions among mobile stations. For contention-free accesses, based on the same PHY-assisted link differentiation provided by the two modules, a new multipolling MAC protocol (PALD-MPMP) is proposed, which not only reduces the polling overhead but also prioritizes transmissions according to their delay requirements. Performance analysis and simulation results show that our proposed protocols outperform the standard MAC protocols for both delay-sensitive and best-effort traffics. All these improvements are mainly attributed to the awareness of cross-layer channel state information and the consequent MRA scheme. Index Terms--Cross-layer design, medium access control (MAC), physical-layer-assisted link differentation (PALD), user detetion, 802.11 wireless local area network (WLAN).

In this paper, blind multiuser detection is studied for a direct-sequence (DS) code-division multiple access (CDMA) system with unknown multipath channels. The receiver is designed to follow a minimum mean-square-error (MMSE) form parameterized by a channel-like constraint vector, which is then optimized by the conventional constant modulus algorithm in a much smaller dimensional space. It is analytically established that the constraint vector asymptotically converges to the channel vector of the user of interest. Correspondingly, the receiver converges to the desired user's MMSE receiver, ensuring detection of the desired signals. When the constraint vector is treated as a channel estimate, the performance of the channel estimator is analyzed using a perturbation technique. Simulation results show a satisfactory performance of the proposed approach, which is also observed to be superior to other approaches in many scenarios. Index Terms--Constant modulus algorithm (CMA), constrained optimization, multiuser detection.

In blind and group-blind multiuser detection, different detectors can be designed using either the sample data covariance matrix directly or its eigencomponents. Due to finite-sample effect in practice, their performance deviates from the corresponding optimum. A perturbation technique is developed rigorously and systematically to analyze these detectors in this work. Subject to the assumption that the first-order perturbation dominates, corresponding results can be applied to a practical system of a given sample size. In particular, performance of the following typical detectors is studied for either flat or estimated multipath channels: direct-matrix-inversion (DMI) blind minimum mean-square error (MMSE) detector, subspace blind MMSE detector, direct zero-forcing (ZF) detector, subspace ZF detector, and group-blind hybrid detector. Simulation examples further verify various analytical results. Index Terms--Asymptotic performance, multiuser detection, perturbation analysis, subspace decomposition.

Data covariance is typically estimated by a sample average method. The second-order statistics of this sample covariance are encountered in evaluating the performance of many covariance-based processing methods. This correspondence derives closed-form expressions for the second-order statistics of a vectored sample covariance. Given a baseband communication system model, the results explicitly rely on the channel parameters and the second- and fourth-order statistics of the channel noise and inputs. They can be directly applied to study statistical properties of covariance-based methods such as a correlation-matching-based channel-estimation method in a code-division multiple-access system. Numerical examples are provided to further verify the derived results. Index Terms--Channel estimation, code-division multiple access (CDMA), covariance estimation, performance analysis.

The minimum output energy (MOE) multi-user receiver is shown to approach the minimum mean-square-error (MMSE) receiver at high signal-to-noise ratio (SNR). Adaptive implementation of the proposed methods exhibits very robust performance in a dynamic loading environment.

This paper investigates the physical-layer security for water-to-air (W2A) visible light communication (VLC). The impacts of surface fluctuation and underwater scattering on the channel gain are theoretically analyzed, which is verified in a laboratory W2A-VLC link. The statistical properties of wave slope under experimental conditions are measured by image processing and the probability density function of the slope can be approximated by a logistic distribution. We observe that dynamic waves can cause information leakage and experimental results indicate that the probability of secure communication increases from 90.39% to 96.18% as the eavesdropper’s elevation increases from 1.15 m to 1.42 m, which are approximately consistent with the numerical results. To investigate the parameters affecting the secrecy performance, several secrecy performance metrics are numerically calculated under different wave intensities, eavesdropper’s locations, divergence angles of LED, underwater scattering coefficients and wavelengths of transmitted beam. It is seen that the secrecy performance is degraded as the wave intensity increases, while random scattering can mitigate the water surface fluctuations and reduce the probability of information leakage. [ABSTRACT FROM AUTHOR]

The emerging photoelectrochemical‐type photodetector (PEC‐PD), because of its unique device architecture by using an aqueous electrolyte, is naturally applicable in the pursuit of underwater optical communication without sophisticated device packaging and assembling. Unfortunately, the traditional PEC detecting process typically involves a large electrochemical workstation with long cables and wire connections for photo signal acquisition, which hinders its applications in wireless optical communication. In this work, an AlGaN nanowire‐based self‐powered PEC‐PD is fabricated that uses seawater as an electrolyte, and then an optical communication system including the PEC‐PD and a portable electrochemical workstation as the signal receiver for data communication is built. Essentially, the self‐power PEC‐PD shows a high responsivity of −15.5 mA W–1, a fast response/recovery time of ≈100 ms, and high stability operation in the seawater electrolyte. Foremost, the optical communication system shows high accuracy in wireless transmission of ASCII code signals in a seawater environment. Such a demonstration offers a new device architecture for possible under‐seawater communication systems by leveraging the unique operation principle of photoelectrochemical devices in the future. [ABSTRACT FROM AUTHOR]

The method of proximal VNIR-SWIR (with a spectral region of 400–2500 nm) spectroscopy in a laboratory setting has been widely employed in soil property estimations. Increasing attention has been focused recently on establishing an agreed-upon protocol for soil spectral measurement, fueled by the recognition that studies carried out under different laboratory settings have made future data sharing and model comparisons difficult. This study aimed to explore the key factors in a lab-based spectral measurement procedure to provide recommendations for enhancing the spectra quality and promoting the development of the spectral measurement protocol. To this aim, with the support of the standard spectral laboratory at Jilin University, China, we designed and performed control experiments on four key factors—the light interference in the measurement course, soil temperature, soil moisture, and soil particle size—to quantify the variation in the spectra quality by the subsequent estimation accuracies of different estimation models developed with different spectra obtained from control groups. The results showed that (1) the soil–probe contact measurement derived the optimum spectra quality and estimation accuracy; however, close-non-contact measurement also achieved acceptable results; (2) sieving the soil sample into particle sizes below 1 mm and drying before spectral measurement effectively enhanced spectra quality and estimation accuracy; (3) the variation in soil temperature did not have a distinct influence on spectra quality, and the estimation accuracies of models developed based on soil samples at 20–50 °C were all acceptable. Moreover, a 30-min warm-up of the spectrometer and contact probe was found to be effective. We carried out a complete and detailed control experiment process, the results of which offer a guide for optimizing the process of laboratory-based soil proximal spectral measurement to enhance spectra quality and corresponding estimation accuracy. Furthermore, we present theoretical support for the development of the spectral measurement protocol. We also present optional guidance with relatively lower accuracy but effective results, which are save time and are low cost for future spectral measurement projects. [ABSTRACT FROM AUTHOR]

We adopt artificial $\Lambda $ -type three-level system with superconducting devices for microwave signal detection, where the signal intensity reaches the level of discrete photons instead of continuous waveform. Based on the state transition principles of the three-level system, we propose a statistical model for microwave signal detection. In addition, achievable transmission rates and signal detection based on the proposed statistical models are investigated for low temperature conditions in deep space communication scenario. It is predicted that high sensitivity can be achieved by the proposed system. We further characterize the received signal considering the saturation phenomenon of three-level system, which reveals negligible performance degradation caused by saturation under weak received power regime. [ABSTRACT FROM AUTHOR]

We investigate the achievable rate and capacity of a non-perfect photon-counting receiver assuming that the shot and thermal noise is negligible, and that the sampling interval is not shorter than the dead time. For long and fixed symbol duration, the achievable rate under on-off keying modulation is investigated based on Kullback-Leibler divergence and Chernoff divergence. We prove the tightness of the derived bounds for large peak power with zero background radiation at an exponential convergence rates, and for low peak power at an order-two convergence rates. Moreover, we propose an approximation on the achievable rate, which is more accurate compared with the derived bounds in the medium signal to noise ratio (SNR) regime. We also verify the accuracy of the proposed model on the achievable rate analysis via the comparison with the model with non-negligible shot and thermal noise. As for the capacity analysis, we assume that the symbol duration can be arbitrarily short, and demonstrate that the capacity approaches that of the continuous-time Poisson channel as both the sampling interval and the symbol duration approach zero, and the sampling interval equals the symbol duration. For large peak power, the capacity with a non-perfect receiver converges, while that of continuous Poisson capacity channel linearly increases. [ABSTRACT FROM AUTHOR]