Synthesis and photodynamic antimicrobial chemotherapy against multi-drug resistant Proteus mirabilis of ornithine-porphyrin conjugates in vitro and in vivo

For the treatment of bacterial infections, photodynamic antimicrobial chemotherapy (PACT) has the advantage of circumventing multi-drug resistance. In this work, new cationic photosensitizers against multi-drug resistant Proteus mirabilis (MRPM) were designed and synthesized by the conjugation of amino phenyl porphyrin with basic amino acid L-ornithine. Their photoinactivation efficacies against MRPM in vitro were reported and include the influence of laser energy, uptake, MIC and MBC, dose-dependent photoinactivation effects, membrane integrity, and fluorescence imaging. The PACT in vivo was evaluated using a wound mouse model infected by MRPM. Photosensitizer 4d displayed high photo inactivation efficacy against MRPM at 7.81 μM under illumination, and it could accelerate wound healing via bactericidal effect. These ornithine-porphyrin conjugates are potential photosensitizers for PACT in the treatment of MRPM infection

Theoretical and technological system for Highly efficient development of deep coalbed methane in the Eastern edge of Erdos Basin

Aiming at the development problems of deep coal reservoirs, such as deep burial, low permeability and complex stress field, this paper clarifies that the resource enrichment conditions, effective fracturing volume, effective horizontal section length, and good reservoir conditions are the key factors for high productivity on the basis of summarizing the exploration and development practice of the Daning-Jixian Block in the past five years. Under the guidance of the theory of “artificial gas reservoir” development, a technical system for the efficient development of deep coalbed methane was preliminarily established as follows. ① According to the reservoir resource conditions, structural preservation conditions and engineering fracturing conditions, a total of 11 indicators in three categories established the geological-engineering “dessert” evaluation standards of deep coalbed methane. ② Based on the techniques such as microstructural characterization, multi-scale fracture prediction, and 3D geological model construction, the quantitative and visual characterization of all elements of “geology + engineering” of deep coal seam was achieved. ③ Based on the guiding idea of “geological small scale, three-dimensional seismic microscale, drill along the target, less adjustment and fast drilling”, a three-stage geological-engineering geo-steering technology with an excellent design of pre-drilling trajectory, precise target entry and post-target fine-tuning as the core was developed.④ The optimization design of the five-in-one well network based on “in-situ stress field, natural fracture field, artificial fracture field, well type and orientation, well network and well spacing” realized the maximization of resource utilization and the maximization of gas field recovery. ⑤ According to the occurrence characteristics, seepage mechanism and production characteristics of deep coalbed methane, a reasonable production capacity evaluation and EUR prediction technology based on the rate-transient analysis method, the empirical production decline method, the numerical simulation method, and the empirical analogy method was formed. ⑥ Following to the design principle of “four-in-one” precision fracturing section and “fracture staggering + differentiation between fracturing segments”, a large-scale volumetric fracturing technology aimed at constructing artificial gas reservoirs was proposed.⑦ According to the characteristics of gas-water variation in gas wells, the optimal control technology of drainage and production in different production stages through the whole life cycle of wells was put forwarded. ⑧ Combined with the current progress of AI technology, and the characteristics of deep coalbed methane development law, gathering and transportation, the technology of gathering, transportation and digital intelligence integrating geological, engineering, and ground aspects was explored. Under the guidance of this achievement, 29 horizontal wells that have been put into production，with an initial production of 5×104−16×104 m3/d, an average of 10.2×104 m3/d, and the daily gas production of the block has exceeded 3 million cubic meters, which has important guiding significance for accelerating the large-scale production of deep coalbed methane in the eastern margin of the Ordos basin. Also the study establishes a reference and standard for the efficient development of similar resources

A Techno-Economic Study of 100% Renewable Energy for a Residential Household in China

In the context of global warming and energy shortage, this paper discusses the techno-economic feasibility of a residential household based on 100% renewable energy in China. The energy storage life, equipment’s residual value, system shortage capacity and atmospheric pollution emissions were considered comprehensively. A life cycle evaluation model based on the net present value (NPV) was built. Taking a real household as an example, the levelised cost of energy (LCOE) is 0.146 $/kW and the unmet load is only 0.86$8079 in 25 years when the LCOE is −0.062 $/kW. The effects of the allowed shortage capacity, renewable energy resources, battery price and the allowed depth of discharge on the economy and energy structure were examined. For example, due to the features of the residential load, the influence of wind resource richness is more obvious than the irradiance. The maximum depth of discharge has less impact on the economy. This paper verifies the techno-economic rationality and feasibility of 100% renewable energy for a household

Adaptive ISAR Imaging of Maneuvering Targets Based on a Modified Fourier Transform

Focusing on the inverse synthetic aperture radar (ISAR) imaging of maneuvering targets, this paper presents a new imaging method which works well when the target’s maneuvering is not too severe. After translational motion compensation, we describe the equivalent rotation of maneuvering targets by two variables—the relative chirp rate of the linear frequency modulated (LFM) signal and the Doppler focus shift. The first variable indicates the target’s motion status, and the second one represents the possible residual error of the translational motion compensation. With them, a modified Fourier transform matrix is constructed and then used for cross-range compression. Consequently, the imaging of maneuvering is converted into a two-dimensional parameter optimization problem in which a stable and clear ISAR image is guaranteed. A gradient descent optimization scheme is employed to obtain the accurate relative chirp rate and Doppler focus shift. Moreover, we designed an efficient and robust initialization process for the gradient descent method, thus, the well-focused ISAR images of maneuvering targets can be achieved adaptively. Human intervention is not needed, and it is quite convenient for practical ISAR imaging systems. Compared to precedent imaging methods, the new method achieves better imaging quality under reasonable computational cost. Simulation results are provided to validate the effectiveness and advantages of the proposed method

Inverse Synthetic Aperture Radar Imaging of Targets with Complex Motion based on Optimized Non-Uniform Rotation Transform

Focusing on the inverse synthetic aperture radar (ISAR) imaging of targets with complex motion, this paper proposes a modified version of the Fourier transform, called non-uniform rotation transform, to achieve cross-range compression. After translational motion compensation, the target’s complex motion is converted into non-uniform rotation. We define two variables—relative angular acceleration (RAA) and relative angular jerk (RAJ)—to describe the rotational nonuniformity. With the estimated RAA and RAJ, rotational nonuniformity compensation is carried out in the non-uniform rotation transform matrix, after which, a focused ISAR image can be obtained. Moreover, considering the possible deviation of RAA and RAJ, we design an optimization scheme to obtain the optimal RAA and RAJ according to the optimal quality of the ISAR image. Consequently, the ISAR imaging of targets with complex motion is converted into a parameter optimization problem in which a stable and clear ISAR image is guaranteed. Compared to precedent imaging methods, the new method achieves better imaging results with a reasonable computational cost. Experimental results verify the effectiveness and advantages of the proposed algorithm

Micro-Motion Parameter Extraction for Ballistic Missile with Wideband Radar Using Improved Ensemble EMD Method

Micro-motion parameters extraction is crucial in recognizing ballistic missiles with a wideband radar. It is known that the phase-derived range (PDR) method can provide a sub-wavelength level accuracy. However, it is sensitive and unstable when the signal-to-noise ratio (SNR) is low. In this paper, an improved PDR method is proposed to reduce the impacts of low SNRs. First, the high range resolution profile (HRRP) is divided into a series of segments so that each segment contains a single scattering point. Then, the peak values of each segment are viewed as non-stationary signals, which are further decomposed into a series of intrinsic mode functions (IMFs) with different energy, using the ensemble empirical mode decomposition with the complementary adaptive noise (EEMDCAN) method. In the EEMDCAN decomposition, positive and negative adaptive noise pairs are added to each IMF layer to effectively eliminate the mode-mixing phenomenon that exists in the original empirical mode decomposition (EMD) method. An energy threshold is designed to select proper IMFs to reconstruct the envelop for high estimation accuracy and low noise effects. Finally, the least-square algorithm is used to do the ambiguous phases unwrapping to obtain the micro-curve, which can be further used to estimate the micro-motion parameters of the warhead. Simulation results show that the proposed method performs well with SNR at −5 dB with an accuracy level of sub-wavelength

Investigating Individuals’ Preferences in Determining the Functions of Smartphone Apps for Fighting Pandemics: Best-Worst Scaling Survey Study

BackgroundSmartphone apps have been beneficial in controlling and preventing the COVID-19 pandemic. However, there is a gap in research surrounding the importance of smartphone app functions from a user’s perspective. Although the insights and opinions of different stakeholders, such as policymakers and medical professionals, can influence the success of a public health policy, any strategy will face difficulty in achieving the expected effect if it is not based on a method that users can accept. ObjectiveThis study aimed to assess the importance of a hypothetical smartphone app’s functions for managing health during a pandemic based on the perspective of user preferences. MethodsA cross-sectional and web-based survey using the best-worst scaling (BWS) method was used to investigate the general population’s preferences for important smartphone app functions. Participants were recruited from a professional surveying company’s web-based surveying panel. The attributes of the BWS questionnaire were developed based on a robust process, including literature review, interviews, and expert discussion. A balanced incomplete block design was used to construct the choice task to ensure the effectiveness of the research design. Count analysis, conditional logit model analysis, and mixed logit analysis were used to estimate preference heterogeneity among respondents. ResultsThe responses of 2153 participants were eligible for analysis. Nearly 55% (1192/2153) were female, and the mean age was 31.4 years. Most participants (1765/2153, 81.9%) had completed tertiary or higher education, and approximately 70% (1523/2153) were urban residents. The 3 most vital functions according to their selection were “surveillance and monitoring of infected cases,” “quick self-screening,” and “early detection of infected cases.” The mixed logit regression model identified significant heterogeneity in preferences among respondents, and stratified analysis showed that some heterogeneities varied in respondents by demographics and COVID-19–related characteristics. Participants who preferred to use the app were more likely to assign a high weight to the preventive functions than those who did not prefer to use it. Conversely, participants who showed lower willingness to use the app tended to indicate a higher preference for supportive functions than those who preferred to use it. ConclusionsThis study ranks the importance of smartphone app features that provide health care services during a pandemic based on the general population’s preferences in China. It provides empirical evidence for decision-makers to develop eHealth policies and strategies that address future public health crises from a person-centered care perspective. Continued use of apps and smart investment in digital health can help improve health outcomes and reduce the burden of disease on individuals and communities

Joint ISAR imaging and azimuth scaling under low SNR using parameterized compensation and calibration method with entropy minimum criterion

Abstract In general, the method of conventional motion compensation for inverse synthetic aperture radar (ISAR) imaging is divided into translational motion compensation (TMC) and rotational motion compensation (RMC) in sequence. TMC is the premise of rotational compensation and the most critical procedure is range alignment. However, the deviation of echo correlation results in the poor performance of range alignment under low signal-to-noise ratio (SNR). Therefore, a new high-resolution ISAR imaging and azimuth scaling method under low SNR using parameterized compensation and calibration is proposed in this paper. Firstly, the target motion is modeled, in which translational motion is modeled as formula of the polynomial coefficient vector. In addition, entropy minimization corresponding to echo signal with compensation term based on coefficients is taken as objective function. Moreover, the particle swarm optimization (PSO) algorithm is utilized to search the global optimal parameters to be estimated precisely and efficiently to implement joint motion compensation and azimuth scaling. The experimental results from both simulated and real data verify the effectiveness and robustness of the method

RESOLUTION INVESTIGATION FOR THE LONGITUDINAL-TRANSVERSE MODE MAGNETOELECTRIC LAMINATE COMPOSITES

Signal resolution reflects the lowest detectable signal of a sensor; and it is more important in practical sensor applications. In this paper, we will investigate the signal resolution of the longitudinal-transverse (L-T) mode magnetoelectric (ME) laminate composites in considering the intrinsic noise through the signal-to-noise ratio. We will provide the optimized thickness ratio n(opt) of the magnetostrictive/piezoelectric phase for the L-T mode Terfenol-D/PZT-5 and Metglass/PZT-5 ME laminates for the lowest detectable signal consideration. This research is helpful for scientists and engineers to construct high sensitive passive ME laminates sensors