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ObjectiveIn order to improve the safe and stable operation level of compressor equipment, this paper puts forward a rapid diagnosis method of surge states based on hybrid deep learning parameter identification, and proposes an active disturbance rejection control (ADRC) strategy to realize compressor anti-surge. MethodFirst, a long-short-term memory neural network (LSTM) is used to process the time series relationship of the input and output data for compressor parameter identification; the interval probability estimation ability of Gaussian process regression (GPR) is integrated; a combination of LSTM and GPR (LSTM-GPR) is proposed; and a hybrid deep learning parameter identification algorithm is used to realize the rapid diagnosis of the compressor surge state. Then, based on the ADRC method, the parameters of the compressor's throttle valve are controlled, and the accurate control of the surge state of the compressor is realized through the compensation of the throttle valve parameters by the control amount. ResultsThe results show that the hybrid deep learning parameter identification algorithm can accurately identify the critical Greitzer parameters of the compressor and quickly and accurately judge whether it is in a surge state, and the ADRC-based control strategy can effectively allow the compressor to exit the surge state, which is faster and more effective than traditional PID control and nonlinear feedback control without losing the working range of the compressor. ConclusionThe proposed parameter identification and ADRC method can be applied to the surge diagnosis and active control of compressors to improve their safety and stability.

ObjectiveIn order to overcome the influence of the nonlinear time-varying characteristics of gas turbines on dynamic control and performance monitoring，this paper combines the time series memory and nonlinear relation expression ability of a long short-term memory neural network (LSTM) with the interval probability estimation ability of Gaussian process regression (GPR) to propose an online parameter identification algorithm for the key dynamic parameters of gas turbines based on an LSTM and GPR-based hybrid deep learning model (LSTM-GPR). MethodsFirst, the dynamic mechanism model of a gas turbine is established, and a large amount of training data is generated by taking fuel calorific value, compressor efficiency and load power moment as the parameters to be identified. Next, the parameter identification network model of LSTM-GPR is constructed, and the training data is input for network training and weight coefficient learning. Finally, the trained LSTM-GPR hybrid deep learning model is used to identify the dynamic operating parameters of the gas turbine model online, and the identification results are analyzed to verify the effectiveness of the proposed algorithm.ResultsThe simulation results show that the online identification results of the proposed LSTM-GPR hybrid model algorithm are accurate, with a recognition error of less than 1% and good real-time performance. Compared with the LSTM single model, the proposed algorithm can obtain a better mean estimation effect and provide a reliable confidence interval range. ConclusionsThe LSTM-GPR hybrid algorithm can be effectively applied to the online parameter identification of a gas turbine model, laying a foundation for its further application to the dynamic operation parameter identification of practical units.

Abstract Platinum‐based ordered alloy catalysts possess higher intrinsic activity in oxygen reduction reactions (ORR). High‐temperature annealing during ordered alloy formation frequently results in larger nanoparticles, and the strategy for obtaining ordered alloys at 600 °C is still undefined. Herein, an ordered Fe‐doped PtCo catalyst (O‐PtCoFe/C) with a size of sub‐4 nm was prepared at 600 °C derived from PtFe@CoO. CoO can generate oxygen vacancies by H2 reduction, lowering the atomic migration barrier and serving as a protective layer to inhibit nanoparticle migration. Experimental analyses showed the formation of O‐PtCoFe/C and electron‐rich Pt atoms due to Pt, Co, and Fe, which was advantageous for ORR performance. The mass activity of the prepared catalyst for ORR was 382.8 mA mgPt−1, which is 5.4 times greater than Pt/C. After 10000 potential cycles, the half‐wave potential was only negatively shifted by 10 mV. In PEMFC (proton exchange membrane fuel cells) tests, the O‐PtCoFe/C showed only 3 % decay after 3000 cycles, whereas the Pt/C showed a significant loss (18.4 %). This work provides an effective method for preparing ordered PtCo alloys for fuel cell cathode catalysts at 600 °C.

Abstract Southeast Asia comprises 11 countries that span mainland Asia across to numerous islands that stretch from the Andaman Sea to the South China Sea and Indian Ocean. This region harbors an impressive diversity of history, culture, religion and biology. Indigenous people of Malaysia display substantial phenotypic, linguistic, and anthropological diversity. Despite this remarkable diversity which has been documented for centuries, the genetic history and structure of indigenous Malaysians remain under-studied. To have a better understanding about the genetic history of these people, especially Malaysian Negritos, we sequenced whole genomes of 15 individuals belonging to five indigenous groups from Peninsular Malaysia and one from North Borneo to high coverage (30X). Our results demonstrate that indigenous populations of Malaysia are genetically close to East Asian populations. We show that present-day Malaysian Negritos can be modeled as an admixture of ancient Hoabinhian hunter-gatherers and Neolithic farmers. We observe gene flow from South Asian populations into the Malaysian indigenous groups, but not into Dusun of North Borneo. Our study proposes that Malaysian indigenous people originated from at least three distinct ancestral populations related to the Hoabinhian hunter-gatherers, Neolithic farmers and Austronesian speakers.

With the rapid development of deep learning-based detection algorithms, deep learning is widely used in the field of infrared small target detection. However, well-designed adversarial samples can fool human visual perception, directly causing a serious decline in the detection quality of the recognition model. In this paper, an adversarial defense technology for small infrared targets is proposed to improve model robustness. The adversarial samples with strong migration can not only improve the generalization of defense technology, but also save the training cost. Therefore, this study adopts the concept of maximizing multidimensional feature distortion, applying noise to clean samples to serve as subsequent training samples. On this basis, this study proposes an inverse perturbation elimination method based on Generative Adversarial Networks (GAN) to realize the adversarial defense, and design the generator and discriminator for infrared small targets, aiming to make both of them compete with each other to continuously improve the performance of the model, find out the commonalities and differences between the adversarial samples and the original samples. Through experimental verification, our defense algorithm is not only able to cope with multiple attacks but also performs well on different recognition models compared to commonly used defense algorithms, making it a plug-and-play efficient adversarial defense technique. [ABSTRACT FROM AUTHOR]

Abstract Crop straws represent enormous biomass resource convertible for biofuels and bioproducts, but lignocellulose recalcitrance restricts its saccharification for commercial utility. Despite genetic modification of lignin biosynthesis being attempted to reduce recalcitrance in bioenergy crops, it remains challenging to optimize lignin deposition without an unacceptable yield penalty. Based on gene expression analysis and phylogenetic tree profiling, a cinnamyl alcohol dehydrogenase gene (OsCAD2) as the target for genetic engineering of lignin biosynthesis in rice was selected in this study. Using CRISPR/Cas9 technology, independent homozygous transgenic lines with precise site mutation of OsCAD2, which showed slightly reduced lignin levels but markedly decreased p‐hydroxyphenyl (H) contents in lignin by 34% and increased guaiacyl (G) contents by 16%, compared to the wild type were generated in this study. Under mild alkali pretreatment (1% NaOH, 50°C), the OsCAD2 site‐modified lines showed effective lignin extraction up to 70% (of total lignin) from mature rice straws, which caused either significantly increased biomass porosity and cellulose accessibility or remarkably reduced cellulase adsorption to lignin in pretreated lignocellulose residues. These consequently led to almost complete biomass enzymatic saccharification with increased hexoses yields by 61%–72% in the modified lines, being much higher than those of the lignin‐altered lines reported in previous studies. Hence, this study has demonstrated a novel genetic engineering strategy to reduce lignocellulose recalcitrance with minimized biomass loss for cost‐effective biomass conversion to bioethanol in rice and bioenergy crops.

Abstract Background In the process of adaptation of humans to their environment, positive or adaptive selection has played a main role. Positive selection has, however, been under-studied in African populations, despite their diversity and importance for understanding human history. Results Here, we have used 119 available whole-genome sequences from five Ethiopian populations (Amhara, Oromo, Somali, Wolayta and Gumuz) to investigate the modes and targets of positive selection in this part of the world. The site frequency spectrum-based test SFselect was applied to idfentify a wide range of events of selection (old and recent), and the haplotype-based statistic integrated haplotype score to detect more recent events, in each case with evaluation of the significance of candidate signals by extensive simulations. Additional insights were provided by considering admixture proportions and functional categories of genes. We identified both individual loci that are likely targets of classic sweeps and groups of genes that may have experienced polygenic adaptation. We found population-specific as well as shared signals of selection, with folate metabolism and the related ultraviolet response and skin pigmentation standing out as a shared pathway, perhaps as a response to the high levels of ultraviolet irradiation, and in addition strong signals in genes such as IFNA, MRC1, immunoglobulins and T-cell receptors which contribute to defend against pathogens. Conclusions Signals of positive selection were detected in Ethiopian populations revealing novel adaptations in East Africa, and abundant targets for functional follow-up.

The past and present status of Grapholita pallifrontana in Cambridgeshire has been investigated. The species was discovered in Cambridgeshire by William Warren, most likely in 1887; the next published record was in 2021. Its sole larval foodplant, Wild Liquorice Astragalus glycyphyllos has been well-documented by botanists since 1660. We visited the 15 monads with post-1985 records and relocated plants in 11 of them, plus one new adjacent monad. We subsequently revisited these 12 monads during the season when larvae are detectable within the seedpods, and found G. pallifrontana in six of the monads, concentrated in the southeast and southwest of VC29. The botanical history of these sites suggests that Wild Liquorice has probably only been present in these locations for the last half-century, and that both foodplant and moth must therefore be quite mobile. Records from adjacent vicecounties demonstrate an overall L-shaped G. pallifrontana distribution, with the Cambridgeshire colonies at its eastern extremity, and raise the question of whether most may belong to a single meta-population. [ABSTRACT FROM AUTHOR]

Abstract Background Large palindromes (inverted repeats) make up substantial proportions of mammalian sex chromosomes, often contain genes, and have high rates of structural variation arising via ectopic recombination. As a result, they underlie many genomic disorders. Maintenance of the palindromic structure by gene conversion between the arms has been documented, but over longer time periods, palindromes are remarkably labile. Mechanisms of origin and loss of palindromes have, however, received little attention. Results Here, we use fiber-FISH, 10x Genomics Linked-Read sequencing, and breakpoint PCR sequencing to characterize the structural variation of the P8 palindrome on the human Y chromosome, which contains two copies of the VCY (Variable Charge Y) gene. We find a deletion of almost an entire arm of the palindrome, leading to death of the palindrome, a size increase by recruitment of adjacent sequence, and other complex changes including the formation of an entire new palindrome nearby. Together, these changes are found in ~ 1% of men, and we can assign likely molecular mechanisms to these mutational events. As a result, healthy men can have 1–4 copies of VCY. Conclusions Gross changes, especially duplications, in palindrome structure can be relatively frequent and facilitate the evolution of sex chromosomes in humans, and potentially also in other mammalian species.

Male infertility is a prevalent condition, affecting 5–10% of men. So far, few genetic factors have been described as contributors to spermatogenic failure. Here, we report the first re-sequencing study of the Y-chromosomal Azoospermia Factor c (AZFc) region, combined with gene dosage analysis of the multicopy DAZ, BPY2, and CDYgenes and Y-haplogroup determination. In analysing 2324 Estonian men, we uncovered a novel structural variant as a high-penetrance risk factor for male infertility. The Y lineage R1a1-M458, reported at >20% frequency in several European populations, carries a fixed ~1.6 Mb r2/r3 inversion, destabilizing the AZFc region and predisposing to large recurrent microdeletions. Such complex rearrangements were significantly enriched among severe oligozoospermia cases. The carrier vs non-carrier risk for spermatogenic failure was increased 8.6-fold (p=6.0×10−4). This finding contributes to improved molecular diagnostics and clinical management of infertility. Carrier identification at young age will facilitate timely counselling and reproductive decision-making.

The article focuses on the distribution and conservation of the Liquorice Piercer moth, Grapholita pallifrontana, in Huntingdonshire, VC31. Topics include the moth's status as a category 3 Red Data Book species, its reliance on Wild Liquorice (Astragalus glycophillus) as a foodplant, and the increasing interest in tracking its current distribution for conservation efforts.

Latin Americans trace their ancestry to the admixture of Native Americans, Europeans and Sub-Saharan Africans. Here, the authors develop a novel haplotype-based approach and analyse over 6,500 Latin Americans to infer the geographically-detailed genetic structure of this population.

We report the results of a second six-year study of the macromoths in a village-edge garden in southern England. 121 additional species were recorded, mainly by light trapping, but also by daytime recording (including pheromones) or early stages. One-third were likely to be residents nearby and a few were migrants from overseas, but the majority were considered likely wanderers from more distant locations in England. Species previously identified as expanding or declining nationally generally showed similar patterns in our garden, but with a few striking exceptions. The rate of species addition with time showed no sign of levelling off and trapping when the night-time maximum temperature exceeded 20°C was identified as the most effective way to record low-frequency wanderers and thus add further species. [ABSTRACT FROM AUTHOR]

Abstract As one of promising clean and low-emission energy, wind power is being rapidly developed in China. However, it faces serious problem of wind curtailment, particularly in northeast China, where combined heat and power (CHP) units cover a large proportion of the district heat supply. Due to the inherent strong coupling between the power and the heat load, the operational flexibility of CHP units is severely restricted in winter to meet the heat supply demand, which imparts considerable stress on the wind power connection to the grid. To promote the integration of wind power and enhance the flexibility of CHP units, this paper presented a method of heat and power load dispatching by exploring the energy storage ability of electric heating boilers and district heating systems. The optimization results indicate that the proposed method can integrate additional wind power into the grid and reduce the coal consumption of CHP units over the optimized period. Furthermore, the thermal inertia of a district heating system is found to contribute more to the reduction of coal consumption, whereas the electric heating boilers contribute to lower wind curtailment.

Abstract We present a new method, Fine-Mapping of Adaptive Variation (FineMAV), which combines population differentiation, derived allele frequency, and molecular functionality to prioritize positively selected candidate variants for functional follow-up. We calibrate and test FineMAV using eight experimentally validated “gold standard” positively selected variants and simulations. FineMAV has good sensitivity and a low false discovery rate. Applying FineMAV to the 1000 Genomes Project Phase 3 SNP dataset, we report many novel selected variants, including ones in TGM3 and PRSS53 associated with hair phenotypes that we validate using available independent data. FineMAV is widely applicable to sequence data from both human and other species.

Estimates of human mutation rates differ substantially based on the approach. Here, the authors present a multi-generational estimate from the autozygous segment in a non-European population that gives insight into the contribution of post-zygotic mutations and population-specific mutational processes.

Isolated populations often have special genetic compositions that can be leveraged for genetic association studies. Here, Xue and colleagues generate and analyse 3,059 low-depth whole-genome sequences from eight European isolated populations and two matched general populations.

Isolated populations can provide useful information on low-frequency variants for dissecting genetic architecture of complex traits. Here, Zeggini and colleagues show enrichment of rare and low-frequency variants and 8 novel low-frequency variant signals for cardiometabolic traits in two Greek isolated populations

Abstract The Sahara was once fertile; a recent study identifies human Y-chromosomal lineages that flourished in this Green Sahara and their relation to present-day populations.

Thermal process is typically nonlinear and uncertain. The control design becomes even more challenging in the presence of time-varying delay. Active disturbance rejection control (ADRC) has been shown to be an effective tool in dealing with real world problems of dynamic uncertainties and nonlinearities. In particular, to overcome the time-varying delay, time delay compensation based ADRC method is addressed. Contrary to Smith predictor, the most ef?cient feature of the proposed method is that it works without time delay models. The influence of time delay is regarded as the external disturbance, and is estimated by the designed disturbance observer. Validity of the proposed method in the cases of both constant delay and time-varying delay with unknown disturbance for the typical thermal process is verified by simulation results.

This paper investigates the problem of precise and quick tracking for gyrostabilized platform (GSP) with unknown hysteresis, unknown control directions, and unknown compound disturbance. Firstly, the dynamic model of GSP is transformed into a strict feedback formulation by designed FD to facilitate the backstepping control system. Secondly, performance functions are constructed at each step of backstepping design to force tracking errors to fall within the prescribed boundaries. Besides, through ingenious transformation, radial basis function neural network (RBFNN) is applied to estimate the unknown control gains preceded by hysteresis. Hence, the problem of prescribed performance control with unknown compound disturbances, unknown hysteresis, and unknown control directions is creatively solved. Furthermore, the exploited controllers are accurate model independent, which guarantees satisfactory robustness of control laws against unknown uncertainties. Finally, the stability of the closed-loop control system is confirmed via Lyapunov stability theory, and numerical simulations are given for a GSP to validate the effectiveness of the proposed controller.