Taoist Ecology in the Context of the Global Climate Crisis

The major principles of Taoism are a reverence for life and conforming to the laws of nature. These are also principles of the ecological movement. They come from Laozi’s non-human centered theory. This paper contends that Taoism has an important contribution to environmental ethics. Today Taoists actively devote themselves to protecting the environment and are respected by international organizations including the United Nations

Novel Small Molecule Positive Allosteric Modulator SPAM1 Triggers the Nuclear Translocation of PAC1-R to Exert Neuroprotective Effects through Neuron-Restrictive Silencer Factor

The neuropeptide pituitary adenylate cyclase-activating polypeptide (PACAP) exerts effective neuroprotective activity through its specific receptor, PAC1-R. We accidentally discovered that as a positive allosteric modulator (PAM) of PAC1-R, the small-molecule PAM (SPAM1) has a hydrazide-like structure, but different binding characteristics, from hydrazide for the N-terminal extracellular domain of PAC1-R (PAC1-R-EC1). SPAM1 had a significant neuroprotective effect against oxidative stress, both in a cell model treated with hydrogen peroxide (H2O2) and an aging mouse model induced by D-galactose (D-gal). SPAM1 was found to block the decrease in PACAP levels in brain tissues induced by D-gal and significantly induced the nuclear translocation of PAC1-R in PAC1R-CHO cells and mouse retinal ganglion cells. Nuclear PAC1-R was subjected to fragmentation and the nuclear 35 kDa, but not the 15 kDa fragments, of PAC1-R interacted with SP1 to upregulate the expression of Huntingtin (Htt), which then exerted a neuroprotective effect by attenuating the binding availability of the neuron-restrictive silencer factor (NRSF) to the neuron-restrictive silencer element (NRSE). This resulted in an upregulation of the expression of NRSF-related neuropeptides, including PACAP, the brain-derived neurotrophic factor (BDNF), tyrosine hydroxylase (TH), and synapsin-1 (SYN1). The novel mechanism reported in this study indicates that SPAM1 has potential use as a drug, as it exerts a neuroprotective effect by regulating NRSF

In-Field Calibration of Triaxial Accelerometer Based on Beetle Swarm Antenna Search Algorithm

Traditional calibration method is usually performed with expensive equipments such as three-axis turntable in a laboratory environment. However in practice, in order to ensure the accuracy and stability of the inertial navigation system (INS), it is usually necessary to recalibrate the inertial measurement unit (IMU) without external equipment in the field. In this paper, a new in-field recalibration method for triaxial accelerometer based on beetle swarm antenna search (BSAS) algorithm is proposed. Firstly, as a new intelligent optimization algorithm, BSAS algorithm and its improvements based on basic beetle antennae search (BAS) algorithm are introduced in detail. Secondly, the nonlinear mathematical model of triaxial accelerometer is established for higher calibration accuracy, and then 24 optimal measurement positions are designed by theoretical analysis. In addition, the calibration procedures are improved according to the characteristics of BSAS algorithm, then 15 calibration parameters in the nonlinear method are optimized by BSAS algorithm. Besides, the results of BSAS algorithm and basic BAS algorithm are compared by simulation, which shows the priority of BSAS algorithm in calibration field. Finally, two experiments demonstrate that the proposed method can achieve high precision in-field calibration without any external equipment, and meet the accuracy requirements of the INS

Optimized Small Waterbird Detection Method Using Surveillance Videos Based on YOLOv7

Waterbird monitoring is the foundation of conservation and management strategies in almost all types of wetland ecosystems. China’s improved wetland protection infrastructure, which includes remote devices for the collection of larger quantities of acoustic and visual data on wildlife species, increased the need for data filtration and analysis techniques. Object detection based on deep learning has emerged as a basic solution for big data analysis that has been tested in several application fields. However, these deep learning techniques have not yet been tested for small waterbird detection from real-time surveillance videos, which can address the challenge of waterbird monitoring in real time. We propose an improved detection method by adding an extra prediction head, SimAM attention module, and sequential frame to YOLOv7, termed as YOLOv7-waterbird, for real-time video surveillance devices to identify attention regions and perform waterbird monitoring tasks. With the Waterbird Dataset, the mean average precision (mAP) value of YOLOv7-waterbird was 67.3%, which was approximately 5% higher than that of the baseline model. Furthermore, the improved method achieved a recall of 87.9% (precision = 85%) and 79.1% for small waterbirds (defined as pixels less than 40 × 40), suggesting a better performance for small object detection than the original method. This algorithm could be used by the administration of protected areas or other groups to monitor waterbirds with higher accuracy using existing surveillance cameras and can aid in wildlife conservation to some extent

Species Distribution Modeling of the Breeding Site Distribution and Conservation Gaps of Lesser White-Fronted Goose in Siberia under Climate Change

Climate change has become an important cause of the loss of bird habitat and changes in bird migration and reproduction. The lesser white-fronted goose (Anser erythropus) has a wide range of migratory habits and is listed as vulnerable on the IUCN (International Union for Conservation of Nature) Red List. In this study, the distribution of suitable breeding grounds for the lesser white-fronted goose was assessed in Siberia, Russia, using a combination of satellite tracking and climate change data. The characteristics of the distribution of suitable breeding sites under different climate scenarios in the future were predicted using the Maxent model, and protection gaps were assessed. The analysis showed that under the background of future climate change, temperature and precipitation will be the main climatic factors affecting the distribution of breeding grounds, and the area associated with suitable breeding habitats will present a decreasing trend. Areas listed as an optimal habitat only accounted for 3.22% of the protected distribution; however, 1,029,386.341 km2 of optimal habitat was observed outside the protected area. Obtaining species distribution data is important for developing habitat protection in remote areas. The results presented here can provide a basis for developing species-specific habitat management strategies and indicate that additional attention should be focused on protecting open spaces

Species Distribution Modeling of the Breeding Site Distribution and Conservation Gaps of Lesser White-Fronted Goose in Siberia under Climate Change

Climate change has become an important cause of the loss of bird habitat and changes in bird migration and reproduction. The lesser white-fronted goose (Anser erythropus) has a wide range of migratory habits and is listed as vulnerable on the IUCN (International Union for Conservation of Nature) Red List. In this study, the distribution of suitable breeding grounds for the lesser white-fronted goose was assessed in Siberia, Russia, using a combination of satellite tracking and climate change data. The characteristics of the distribution of suitable breeding sites under different climate scenarios in the future were predicted using the Maxent model, and protection gaps were assessed. The analysis showed that under the background of future climate change, temperature and precipitation will be the main climatic factors affecting the distribution of breeding grounds, and the area associated with suitable breeding habitats will present a decreasing trend. Areas listed as an optimal habitat only accounted for 3.22% of the protected distribution; however, 1,029,386.341 km2 of optimal habitat was observed outside the protected area. Obtaining species distribution data is important for developing habitat protection in remote areas. The results presented here can provide a basis for developing species-specific habitat management strategies and indicate that additional attention should be focused on protecting open spaces

Scaly-sided Merganser (Mergus squamatus) equalizes foraging costs with depth by switching foraging tactics

Throughout evolutionary history, animals are finely tuned to adjust their behaviors corresponding to environmental variations. Behavioral flexibility represents an important component of a species' adaptive capacity in the face of rapid anthropogenetic environmental change, and knowledge of animal behaviors is increasingly recognized in conservation biology. In aquatic ecosystem, variation of water depth is a key factor affecting the availability of food; thus, the foraging behaviors of many waterbirds, especially piscivores. In this study, we compared the foraging behaviors of the Scaly-sided Merganser (Mergus squamatus), an endangered migratory diving duck endemic to East Asia, in habitats with different water depths (Shallow waters: 0–40 ​cm; Deep waters: 40–300 ​cm), using video camera records obtained from the known wintering sites during three winters from 2018 to 2020. Further, the energy expenditure of foraging behavior profile and energy intake based on fish sizes were calculated to study the foraging energetics. In total, 200 effective video footages that contained 1086 ​min with 17,995 behaviors and 163 events of catching fish were recorded. Results showed that: 1) time length for fishing (including eye-submerging, head-dipping, diving and food handling) of M. squamatus in shallow waters was significantly more than in deep waters; 2) M. squamatuss spent significantly more time for preparing (including vigilance, preening and swimming) in deep waters than in shallow waters; 3) the mean catch rate was 0.28 fish/min in shallow waters, which is significantly higher than the value of 0.13 fish/min in deep waters; 4) despite the distinct foraging behavior profiles and energy intakes, M. squamatus showed similar energetics in shallow and deep waters. We concluded that M. squamatus is a good example of behavioral flexibility that aligns with expectations of optimal foraging theory, in that it behaves in accordance to resource availability in different environments, resulting in high foraging efficiency

A new genomic framework to categorize pediatric acute myeloid leukemia.

Recent studies on pediatric acute myeloid leukemia (pAML) have revealed pediatric-specific driver alterations, many of which are underrepresented in the current classification schemas. To comprehensively define the genomic landscape of pAML, we systematically categorized 887 pAML into 23 mutually distinct molecular categories, including new major entities such as UBTF or BCL11B, covering 91.4% of the cohort. These molecular categories were associated with unique expression profiles and mutational patterns. For instance, molecular categories characterized by specific HOXA or HOXB expression signatures showed distinct mutation patterns of RAS pathway genes, FLT3 or WT1, suggesting shared biological mechanisms. We show that molecular categories were strongly associated with clinical outcomes using two independent cohorts, leading to the establishment of a new prognostic framework for pAML based on these updated molecular categories and minimal residual disease. Together, this comprehensive diagnostic and prognostic framework forms the basis for future classification of pAML and treatment strategies