We report on an improved ytterbium-doped yttrium aluminum garnet thin-disk multi-pass amplifier for kilowatt-level ultrafast lasers, showcasing excellent beam quality. At a repetition rate of 800 kHz, the 6.8 ps, 276 W seed laser is amplified up to an average power of 1075 W, corresponding to a pulse energy of 1.34 mJ. The 36-pass amplifier is designed as a compact mirror array in which the beam alternately propagates between the mirrors and the disk by a quasi-collimated state. We adopted a quasi-collimated propagation to confine stray and diffracted light by the slight curvature of the disk, which enables us to achieve an outstanding extraction efficiency of up to 57% with excellent beam quality in stable laser operation at high power. The beam quality at 1075 W was measured to be M2 < 1.51. Furthermore, stability testing was demonstrated with a root-mean-square power fluctuation of less than 1.67% for 10 min.

Machine learning methods have been used in identifying omics markers for a variety of phenotypes. We aimed to examine whether a supervised machine learning algorithm can improve identification of alcohol-associated transcriptomic markers. In this study, we analysed array-based, whole-blood derived expression data for 17 873 gene transcripts in 5508 Framingham Heart Study participants. By using the Boruta algorithm, a supervised random forest (RF)-based feature selection method, we selected twenty-five alcohol-associated transcripts. In a testing set (30 % of entire study participants), AUC (area under the receiver operating characteristics curve) of these twenty-five transcripts were 0·73, 0·69 and 0·66 for non-drinkers v. moderate drinkers, non-drinkers v. heavy drinkers and moderate drinkers v. heavy drinkers, respectively. The AUC of the selected transcripts by the Boruta method were comparable to those identified using conventional linear regression models, for example, AUC of 1958 transcripts identified by conventional linear regression models (false discovery rate < 0·2) were 0·74, 0·66 and 0·65, respectively. With Bonferroni correction for the twenty-five Boruta method-selected transcripts and three CVD risk factors (i.e. at P < 6·7e-4), we observed thirteen transcripts were associated with obesity, three transcripts with type 2 diabetes and one transcript with hypertension. For example, we observed that alcohol consumption was inversely associated with the expression of DOCK4, IL4R, and SORT1, and DOCK4 and SORT1 were positively associated with obesity, and IL4R was inversely associated with hypertension. In conclusion, using a supervised machine learning method, the RF-based Boruta algorithm, we identified novel alcohol-associated gene transcripts.

Cyclic adenosine monophosphate (cAMP)-dependent protein kinase A (PKA) is a distinctive member of the serine–threonine protein AGC kinase family and an effective kinase for cAMP signal transduction. In recent years, scuticociliate has caused a lot of losses in domestic fishery farming, therefore, we have carried out morphological and molecular biological studies. In this study, diseased guppies (Poecilia reticulata) were collected from an ornamental fish market, and scuticociliate Philaster apodigitiformis Miao et al., 2009 was isolated. In our prior transcriptome sequencing research, we discovered significant expression of the β-PKA gene in P. apodigitiformis during its infection process, leading us to speculate its involvement in pathogenesis. A complete sequence of the β-PKA gene was cloned, and quantified by quantitative reverse transcription-polymerase chain reaction to analyse or to evaluate the functional characteristics of the β-PKA gene. Morphological identification and phylogenetic analysis based on small subunit rRNA sequence, infection experiments and haematoxylin–eosin staining method were also carried out, in order to study the pathological characteristics and infection mechanism of scuticociliate. The present results showed that: (1) our results revealed that β-PKA is a crucial gene involved in P. apodigitiformis infection in guppies, and the findings provide valuable insights for future studies on scuticociliatosis; (2) we characterized a complete gene, β-PKA, that is generally expressed in parasitic organisms during infection stage and (3) the present study indicates that PKA plays a critical role in scuticociliate when infection occurs by controlling essential steps such as cell growth, development and regulating the activity of the sensory body structures and the irritability system.

We present an effective approach to realize a highly efficient, high-power and chirped pulse amplification-free ultrafast ytterbium-doped yttrium aluminum garnet thin-disk regenerative amplifier pumped by a zero-phonon line 969 nm laser diode. The amplifier delivers an output power exceeding 154 W at a pulse repetition rate of 1 MHz with custom-designed 48 pump passes. The exceptional thermal management on the thin disk through high-quality bonding, efficient heat dissipation and a fully locked spectrum collectively contributes to achieving a remarkable optical-to-optical efficiency of 61% and a near-diffraction-limit beam quality with an M2 factor of 1.06. To the best of our knowledge, this represents the highest conversion efficiency reported in ultrafast thin-disk regenerative amplifiers. Furthermore, the amplifier operates at room temperature and exhibits exceptional stability, with root mean square stability of less than 0.33%. This study significantly represents advances in the field of laser amplification systems, particularly in terms of efficiency and average power. This advantageous combination of high efficiency and diffraction limitation positions the thin-disk regenerative amplifier as a promising solution for a wide range of scientific and industrial applications.

High-power femtosecond mid-infrared (MIR) lasers are of vast importance to both fundamental research and applications. We report a high-power femtosecond master oscillator power amplifier laser system consisting of a single-mode Er:ZBLAN fiber mode-locked oscillator and pre-amplifier followed by a large-mode-area Er:ZBLAN fiber main amplifier. The main amplifier is actively cooled and bidirectionally pumped at 976 nm, generating a slope efficiency of 26.9%. Pulses of 8.12 W, 148 fs at 2.8 μm with a repetition rate of 69.65 MHz are achieved. To the best of our knowledge, this is the highest average power ever achieved from a femtosecond MIR laser source. Such a compact ultrafast laser system is promising for a wide range of applications, such as medical surgery and material processing.

Low-cost La(FexSi1-x)13 alloys exhibiting the large magnetocaloric effect (MCE) are one of the most promising magnetic refrigerant candidates for room temperature magnetic refrigeration. The NaZn13-type phase (hereinafter 1:13 phase) is believed to play a key role in the MCE of these alloys. While the formation of the 1:13 phase directly from the melt upon cooling was challenging, in this paper we demonstrate that the 1:13 phase can be formed directly during solidification. We found that three kinds of solidification microstructure were formed because a competitive nucleation occurred between the 1:13 and α-(Fe,Si) phase during the solidification of LaFe11.5Si1.5 alloy. In case of a high cooling speed, a large amount of NaZn13–type phase with equiaxed grains and a small amount of α-(Fe,Si) phase were formed because of a dominant nucleation rate of 1:13 phase. When the cooling rate was small, a large number of α-(Fe,Si) phase with dendrites were formed because the nucleation rate of α-(Fe,Si) phase is larger than that of the 1:13 phase. These results revealed that nucleation rates of phases is very important to the composition formation and microstructure of LaFe11.5Si1.5 alloys.

Multilayer thin films have been widely used for their enhanced mechanical and tribological properties relative to the monolayers of equivalent thickness. However, the mechanical properties of the each constituent layer are rarely investigated due to the difficulty in separating the effects of the constituent layers. An inverse analysis method to identify the elastic moduli of the constituent layers of multilayer films is developed by fitting the finite element calculations with indentation measurements within the framework of numerical optimization. The method is verified against typical monolayer, bilayer, and trilayer film structures both numerically and experimentally. Uniqueness and substrate-independence of the extracted moduli are ensured by the multiple loading–unloading cycles of the indentation tests. The method provides a feasible way to characterize the intrinsic mechanical properties of the constituent layers of multilayered thin films and further to explore the dominant mechanism for the enhancement of their mechanical properties.