Survival and Causes of Mortality of Relocated and Resident Northern Bobwhites in East Texas

We estimated survival of 3 groups of northern bobwhites (Colinus virginianus) on a 563-ha intensively managed study area in eastern Texas. During the 3-year study, 155 bobwhites from South Texas and 136 bobwhites from East Texas were captured, radio-marked, and relocated to the study area; 139 bobwhites that were resident on the study area were also captured, radio-marked, and released at the point of capture. There were no differences (P \u3e 0.05) in survival among the 3 groups of bobwhites. However, survival of bobwhites from South Texas were consistently lower than those of the other 2 groups during each year; both bobwhites from East Texas and resident bobwhites survived better than bobwhites relocated from South Texas. Avian predation claimed 57.6% of 243 known-fate birds, mammalian predation and apparent capture stress each caused 9.1 % mortality, while 1.2% of the birds died of snake predation and 14.0% were lost to unidentifiable causes

Reproduction of Relocated and Resident Northern Bobwhites in East Texas

We examined reproduction by relocated and resident northern bobwhites (Colinus virginianus) on an intensively managed 563-ha study area in Trinity County, eastern Texas. During the late winters of 1990-1992, 155 South Texas (84 hens, 71 cocks) and 136 East Texas (64 hens, 72 cocks) bobwhites were captured, radio-tagged, and relocated to the study area; 139 resident birds (73 hens, 66 cocks) were also captured, radio-tagged, and released at the point of capture. For the 3 years combined, the 33 South Texas, 33 East Texas, and 39 resident hens alive at the beginning of the breeding season produced 6, 13, and 22 documented nests (P = 0.004) and 0, 3, and 4 fledged broods. Pooled, the number of nests by East Texas and resident hens was higher than that of South Texas hens (P = 0.003); numbers of nests of East Texas and resident hens were similar (P = 0.150). Our results do not support relocation of South Texas bobwhites into the East Texas Pineywoods

Reproduction of Relocated and Resident Northern Bobwhites in East Texas

We examined reproduction by relocated and resident northern bobwhites (Colinus virginianus) on an intensively managed 563-ha study area in Trinity County, eastern Texas. During the late winters of 1990-1992, 155 South Texas (84 hens, 71 cocks) and 136 East Texas (64 hens, 72 cocks) bobwhites were captured, radio-tagged, and relocated to the study area; 139 resident birds (73 hens, 66 cocks) were also captured, radio-tagged, and released at the point of capture. For the 3 years combined, the 33 South Texas, 33 East Texas, and 39 resident hens alive at the beginning of the breeding season produced 6, 13, and 22 documented nests (P = 0.004) and 0, 3, and 4 fledged broods. Pooled, the number of nests by East Texas and resident hens was higher than that of South Texas hens (P = 0.003); numbers of nests of East Texas and resident hens were similar (P = 0.150). Our results do not support relocation of South Texas bobwhites into the East Texas Pineywoods

Survival and Causes of Mortality of Relocated and Resident Northern Bobwhites in East Texas

We estimated survival of 3 groups of northern bobwhites (Colinus virginianus) on a 563-ha intensively managed study area in eastern Texas. During the 3-year study, 155 bobwhites from South Texas and 136 bobwhites from East Texas were captured, radio-marked, and relocated to the study area; 139 bobwhites that were resident on the study area were also captured, radio-marked, and released at the point of capture. There were no differences (P \u3e 0.05) in survival among the 3 groups of bobwhites. However, survival of bobwhites from South Texas were consistently lower than those of the other 2 groups during each year; both bobwhites from East Texas and resident bobwhites survived better than bobwhites relocated from South Texas. Avian predation claimed 57.6% of 243 known-fate birds, mammalian predation and apparent capture stress each caused 9.1 % mortality, while 1.2% of the birds died of snake predation and 14.0% were lost to unidentifiable causes

The effect of volume change and stack pressure on solid‐state battery cathodes

Solid-state lithium batteries may provide increased energy density and improved safety compared with Li-ion technology. However, in a solid-state composite cathode, mechanical degradation due to repeated cathode volume changes during cycling may occur, which may be partially mitigated by applying a significant, but often impractical, uniaxial stack pressure. Herein, we compare the behavior of composite electrodes based on Li4Ti5O12 (LTO) (negligible volume change) and Nb2O5 (+4% expansion) cycled at different stack pressures. The initial LTO capacity and retention are not affected by pressure but for Nb2O5, they are significantly lower when a stack pressure of <2 MPa is applied, due to inter-particle cracking and solid-solid contact loss because of cyclic volume changes. This work confirms the importance of cathode mechanical stability and the stack pressures for long-term cyclability for solid-state batteries. This suggests that low volume-change cathode materials or a proper buffer layer are required for solid-state batteries, especially at low stack pressures

Achieving ultra‐high rate planar and dendrite‐free zinc electroplating for aqueous zinc battery anodes

Despite being one of the most promising candidates for grid-level energy storage, practical aqueous zinc batteries are limited by dendrite formation, which leads to significantly compromised safety and cycling performance. In this study, by using single-crystal Zn-metal anodes, reversible electrodeposition of planar Zn with a high capacity of 8 mAh cm−2 can be achieved at an unprecedentedly high current density of 200 mA cm−2. This dendrite-free electrode is well maintained even after prolonged cycling (>1200 cycles at 50 mA cm−2). Such excellent electrochemical performance is due to single-crystal Zn suppressing the major sources of defect generation during electroplating and heavily favoring planar deposition morphologies. As so few defect sites form, including those that would normally be found along grain boundaries or to accommodate lattice mismatch, there is little opportunity for dendritic structures to nucleate, even under extreme plating rates. This scarcity of defects is in part due to perfect atomic-stitching between merging Zn islands, ensuring no defective shallow-angle grain boundaries are formed and thus removing a significant source of non-planar Zn nucleation. It is demonstrated that an ideal high-rate Zn anode should offer perfect lattice matching as this facilitates planar epitaxial Zn growth and minimizes the formation of any defective regions

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

ALDELE: all-purpose deep learning toolkits for predicting the biocatalytic activities of enzymes

Rapidly predicting enzyme properties for catalyzing specific substrates is essential for identifying potential enzymes for industrial transformations. The demand for sustainable production of valuable industry chemicals utilizing biological resources raised a pressing need to speed up biocatalyst screening using machine learning techniques. In this research, we developed an all-purpose deep-learning-based multiple-toolkit (ALDELE) workflow for screening enzyme catalysts. ALDELE incorporates both structural and sequence representations of proteins, alongside representations of ligands by subgraphs and overall physicochemical properties. Comprehensive evaluation demonstrated that ALDELE can predict the catalytic activities of enzymes, and particularly, it identifies residue-based hotspots to guide enzyme engineering and generates substrate heat maps to explore the substrate scope for a given biocatalyst. Moreover, our models notably match empirical data, reinforcing the practicality and reliability of our approach through the alignment with confirmed mutation sites. ALDELE offers a facile and comprehensive solution by integrating different toolkits tailored for different purposes at affordable computational cost and therefore would be valuable to speed up the discovery of new functional enzymes for their exploitation by the industry.<br/

ALDELE: All-Purpose Deep Learning Toolkits for Predicting the Biocatalytic Activities of Enzymes

Rapidly predicting enzyme properties for catalyzing specific substrates is essential for identifying potential enzymes for industrial transformations. The demand for sustainable production of valuable industry chemicals utilizing biological resources raised a pressing need to speed up biocatalyst screening using machine learning techniques. In this research, we developed an all-purpose deep-learning-based multiple-toolkit (ALDELE) workflow for screening enzyme catalysts. ALDELE incorporates both structural and sequence representations of proteins, alongside representations of ligands by subgraphs and overall physicochemical properties. Comprehensive evaluation demonstrated that ALDELE can predict the catalytic activities of enzymes, and particularly, it identifies residue-based hotspots to guide enzyme engineering and generates substrate heat maps to explore the substrate scope for a given biocatalyst. Moreover, our models notably match empirical data, reinforcing the practicality and reliability of our approach through the alignment with confirmed mutation sites. ALDELE offers a facile and comprehensive solution by integrating different toolkits tailored for different purposes at affordable computational cost and therefore would be valuable to speed up the discovery of new functional enzymes for their exploitation by the industry