Switching costs in stochastic environments drive the emergence of matching behaviour in animal decision-making through the promotion of reward learning strategies

A principle of choice in animal decision-making named probability matching (PM) has long been detected in animals, and can arise from different decision-making strategies. Little is known about how environmental stochasticity may influence the switching time of these different decision-making strategies. Here we address this problem using a combination of behavioral and theoretical approaches, and show, that although a simple Win-Stay-Loss-Shift (WSLS) strategy can generate PM in binary-choice tasks theoretically, budgerigars (Melopsittacus undulates) actually apply a range of sub-tactics more often when they are expected to make more accurate decisions. Surprisingly, budgerigars did not get more rewards than would be predicted when adopting a WSLS strategy, and their decisions also exhibited PM. Instead, budgerigars followed a learning strategy based on reward history, which potentially benefits individuals indirectly from paying lower switching costs. Furthermore, our data suggest that more stochastic environments may promote reward learning through significantly less switching. We suggest that switching costs driven by the stochasticity of an environmental niche can potentially represent an important selection pressure associated with decision-making that may play a key role in driving the evolution of complex cognition in animals

The research on the immuno-modulatory defect of Mesenchymal Stem Cell from Chronic Myeloid Leukemia patients

Overwhelming evidence from leukemia research has shown that the clonal population of neoplastic cells exhibits marked heterogeneity with respect to proliferation and differentiation. There are rare stem cells within the leukemic population that possess extensive proliferation and self-renewal capacity not found in the majority of the leukemic cells. These leukemic stem cells are necessary and sufficient to maintain the leukemia. While the hematopoietic stem cell (HSC) origin of CML was first suggested over 30 years ago, recently CML-initiating cells beyond HSCs are also being investigated. We have previously isolated fetal liver kinase-1-positive (Flk1+) cells carrying the BCR/ABL fusion gene from the bone marrow of Philadelphia chromosome-positive (Ph+) patients with hemangioblast property. Here, we showed that CML patient-derived Flk1+CD31-CD34-MSCs had normal morphology, phenotype and karyotype but appeared impaired in immuno-modulatory function. The capacity of patient Flk1+CD31-CD34- MSCs to inhibit T lymphocyte activation and proliferation was impaired in vitro. CML patient-derived MSCs have impaired immuno-modulatory functions, suggesting that the dysregulation of hematopoiesis and immune response may originate from MSCs rather than HSCs. MSCs might be a potential target for developing efficacious cures for CML

A GA and SVM Classification Model for Pine Wilt Disease Detection Using UAV-Based Hyperspectral Imagery

Pine wilt disease (PWD), caused by the pine wood nematode (Bursaphelenchus xylophilus), is a global destructive threat to forests and has led to serious economic losses all over the world. Therefore, it is necessary to establish a feasible and effective method to accurately monitor and estimate PWD infection. In this study, we used hyperspectral imagery (HI) collected by an unmanned airship with a hyperspectral imaging spectrometer to detect PWD in healthy, early, middle and serious infection stages. To avoid massive calculations on the full spectral dimensions of the HI, 16 spectral features were extracted from the HI, and a genetic algorithm (GA) was implemented to identify the optimal ones with the least fitness. Simultaneously, a support vector machine (SVM) classifier was established to predict the PWD infection stage for an individual pine tree. The following results were obtained: (1) the spectral characteristics for pine trees in different PWD infection stages were distinctive in the green region (510–580 nm), red edge (680–760 nm) and near-infrared (780–1000 nm) spectra; (2) the six optimal spectral features (Dgreen, SDgreen, Dred, DRE, DNIR, SDNIR) selected with the GA effectively distinguished the PWD infection stages of pine trees with a lower calculation cost; (3) compared with the traditional classifiers, such as k-nearest neighbor (KNN), random forest (RF) and single SVM, the proposed GA and SVM classifier achieved the highest overall accuracy (95.24%) and Kappa coefficient (0.9234). The approach could also be employed for monitoring and detecting other forest pests

Preparation of In/Sn Nanoparticles (In3Sn and InSn4) by Wet Chemical One-Step Reduction and Performance Study

The preparation of binary alloys by surfactant-assisted chemical reduction in aqueous solution at room temperature has become a hot topic. In this article low melting point tin/indium (Sn/In) nanoparticles are synthesized. The formation process of the alloy was studied. Scanning electron microscopy, energy spectrometry, and X-ray diffraction are used to determine the morphology, composition, and crystal structure of the nanoparticles. Study found that fully alloyed indium-tin nanoparticles can be obtained by wet chemical method and the main phases of indium-tin alloy are β-phase (In3Sn) and γ-phase (InSn4). However, the Sn phase appears at a low content of indium (40 wt%). When the content of indium increases to 45 (wt%), the tin phase disappears. In addition, the most important finding is that the composition of the indium-tin alloy can be changed by ratio control, and the content of In3Sn increases with the increase of indium content. The relative content of In3Sn attains a maximum when the content of indium increases to 60 (wt%). In contrast, the content of InSn4 decreases. Finally, differential scanning calorimetry measurements is performed to understand the melting behavior of the nanoparticles and low melting temperatures are achieved for a wide range of indium compositions (from 40% to 60%). The melting temperature is found to be in the range of 125–132 °C and it increased with increasing In3Sn (also the increase of indium content). This gives us a new understanding into the binary alloy nano-system and gives important information for the application of low temperature alloy solders. The choice of composition can be based on the corresponding melting point

Experimental Study of the Effect of the Expansion Segment Geometry on the Atomization of a Plain-Jet Airblast Atomizer

In this paper, the idea of adding an expansion segment over traditional airblast atomizer is proposed to improve the spray performance. According to the systematic experiments, the Sauter mean diameter, the droplet size distribution, and the droplet axial mean velocity were obtained to evaluate the spray performance. The correlations between spray performance and four geometrical parameters of the expansion segment which include the length, the angle, the throat area, and position of liquid jet are considered. The atomizer operates at atmospheric pressure and temperature, and the air liquid ratio range is from 0.48 to 2.85. The data of the results were measured by Phase Doppler Particle Analyzer. The results show that more uniform droplet size distribution can be achieved with the addition of expansion segment, and the droplet size distribution factor q of the case adding the expansion segment is 52.8% bigger than that of the case with no expansion segment. q increases as the length and angle of expansion segment increase. The Sauter mean diameter can be reduced by either reducing the length or angle of expansion segment. As for droplet velocity, it is determined that the droplet velocity increases along the radial direction, which is noteworthy because opposite trend is reported for traditional plain-jet atomizers. With an increase of the length, angle, and throat area of the expansion segment, the droplet axial velocity decays

A Coarse-to-Fine Transformer-Based Network for 3D Reconstruction from Non-Overlapping Multi-View Images

Reconstructing 3D structures from non-overlapping multi-view images is a crucial task in the field of 3D computer vision, since it is difficult to establish feature correspondences and infer depth from overlapping parts of views. Previous methods, whether generating the surface mesh or volume of an object, face challenges in simultaneously ensuring the accuracy of detailed topology and the integrity of the overall structure. In this paper, we introduce a novel coarse-to-fine Transformer-based reconstruction network to generate precise point clouds from multiple input images at sparse and non-overlapping viewpoints. Specifically, we firstly employ a general point cloud generation architecture enhanced by the concept of adaptive centroid constraint for the coarse point cloud corresponding to the object. Subsequently, a Transformer-based refinement module applies deformation to each point. We design an attention-based encoder to encode both image projection features and point cloud geometric features, along with a decoder to calculate deformation residuals. Experiments on ShapeNet demonstrate that our proposed method outperforms other competing methods

Quantification of Niacin and Its Metabolite Nicotinuric Acid in Human Plasma by LC-MS/MS: Application to a Clinical Trial of a Fixed Dose Combination Tablet of Niacin Extended-Release/Simvastatin (500 mg/10 mg) in Healthy Chinese Volunteers

Our paper aimed to develop rapid, sensitive, and specific LC-MS/MS method for the quantification of niacin (NA) and its metabolite nicotinuric acid (NUA) in human plasma. Following protein precipitation with acetonitrile, the NA, NUA, and internal standard (5-fluorouracil) were separated on a Zorbax 300SB-C8 column (250 mm × 4.6 mm, 5 μm) with a mobile phase consisting of methanol-2 mM ammonium acetate (3 : 97, v/v) at a flow rate of 1 mL/min (split 1 : 1). A tandem mass spectrometer equipped with electrospray ionization source was used as the detector and operated in negative ion mode. The linear concentration ranges of the calibration curves were 5–800 ng/mL for NA and NUA. The intra-assay RSD for quality control (QC) samples were from 5.0% to 8.7% for NA, and 5.5% to 7.6% for NUA. The interassay RSD for QC samples were from 2.8% to 9.4% for NA, and 3.7% to 5.8% for NUA. The relative errors for QC samples were from −2.2% to 2.3% for NA, and −0.6% to 3.2% for NUA. The method was successfully applied to the investigation of the pharmacokinetic profiles of NA, NUA in human after single dose administration of Niacin extended-release/Simvastatin tablet (500 mg/10 mg)

Isotactic polycondensation of L-lactic acid with biogenic creatinine

a b s t r a c t Isotactic polycondensation of L-lactic acid (LLA) catalyzed by biogenic creatinine was carried out at 140e175 C under sequentially reduced pressure (30e10 torr). The product poly-LLA (PLLA) possesses high optical purity (e.e. 96.1e98.7%) as well as narrow molecular weight distribution (PDI 1.74e1.85). 13 C NMR follow-up monitor of the polymerization demonstrated that the isotacticity of PLLA formed in the polymerization kept constant high values (isotacticity 97.8e99.5%) throughout the polymerization. The 1 H NMR structural characterization of the growing polymeric species in progress of the polycondensation revealed that the active catalytic species is a guanidinium formed in situ. A possible mechanism of the creatinine-catalyzed polycondensation was proposed