Woodruffhu7212

17% and 2.47%, respectively; the removal efficiencies of NH4+ were 55.95%, 96.71%, 38.11%, 20.71% and 7.43%, respectively. This study provides a method for mitigating the toxicity of CuO-NPs on functional microorganisms.Identification of typical vegetation succession types and their important influencing factors is an important prerequisite to implement differential vegetation and soil management after land abandonment on the Loess Plateau, China. However, there is no reported study specifically on the identification of vegetation types and their important factors as well as the thresholds of the important factors for classification of the vegetation types, based on the medium- to long-term succession of natural vegetation after cropland abandonment. We collected vegetation and soil data on the natural vegetation with the longest 60-year-old forest communities that developed after cropland abandonment and analyzed the data using two-way indicator species analysis, detrended correspondence analysis, direct canonical correspondence analysis and classification tree model. The vegetation communities were classified into five distinct vegetation types, including Artemisia scoparia, Lespedeza davurica and Stipa bungeana, Artemisia giraldii pamp, Sophora viciifolia, Quercus liaotungensis and Biota orientalis. The years after cropland abandonment and soil C/N were further identified as important factors determining the types of vegetation. Likewise, it was observed that most of the investigated soil nutrient variables and soil texture-related variables improved with the vegetation succession while soil water in the surface layers showed a decreasing trend. These findings may provide an ecological basis for site-specific management of vegetation types after cropland abandonment in the medium-long term on the Loess Plateau. Our results encourage further exploration of vegetation succession and their important factors based on longer periods of vegetation succession after cropland abandonment under more soil and climatic conditions on the mountainous areas as the Loess Plateau.There are increasing concerns regarding bat mortality at wind energy facilities, especially as installed capacity continues to grow. In North America, wind energy development has recently expanded into the Lower Rio Grande Valley in south Texas where bat species had not previously been exposed to wind turbines. Our study sought to characterize genetic diversity, population structure, and effective population size in Dasypterus ega and D. intermedius, two tree-roosting yellow bats native to this region and for which little is known about their population biology and seasonal movements. There was no evidence of population substructure in either species. Genetic diversity at mitochondrial and microsatellite loci was lower in these yellow bat taxa than in previously studied migratory tree bat species in North America, which may be due to the non-migratory nature of these species at our study site, the fact that our study site is located at a geographic range end for both taxa, and possibly weak ascertainment bias at microsatellite loci. Historical effective population size (NEF) was large for both species, while current estimates of Ne had upper 95% confidence limits that encompassed infinity. We found evidence of strong mitochondrial differentiation between the two putative subspecies of D. intermedius (D. i. floridanus and D. i. intermedius) which are sympatric in this region of Texas, yet little differentiation using microsatellite loci. We suggest this pattern is due to secondary contact and hybridization and possibly incomplete lineage sorting at microsatellite loci. We also found evidence of some hybridization between D. ega and D. intermedius in this region of Texas. We recommend that our data serve as a starting point for the long-term genetic monitoring of these species in order to better understand the impacts of wind-related mortality on these populations over time.

The one-humped camels are economically important for several countries in Africa, Asia, and the Arabian Peninsula. Coccidiosis causes significant economic impact. Studies on coccidian parasite species causing such infections are limited. The present study aimed to carry out a survey of

spp. in camels from Riyadh and Al-Qassim, Saudi Arabia



A total of 209 fecal samples from

(

)

slaughtered in West Abattoir in Riyadh and Onaizah Modern abattoir in Al-Qassim were collected. this website Samples were examined by flotation methods and oocyst sporulation.

Of the 209 examined fecal samples, 75 were positive for

spp..The prevalence of oocysts in Riyadh and Al-Qassim were 33.89% (40/118) and 38.46% (35/92), respectively. The prevalence in young male camels was 41.02% (32/78) and 39.62% (21/53), respectively and in adult males was 19.35% (6/31) and 36% (9/25), respectively. Adult females displayed a prevalence of 22.22% (2/9) and 38.46% (5/13) in Riyadh and Al-Qassim, respectively. Three

spp. were identified;

,

, and

. The presence of

is considered the first record in Saudi Arabia.

Of the 209 examined fecal samples, 75 were positive for Eimeria spp..The prevalence of oocysts in Riyadh and Al-Qassim were 33.89% (40/118) and 38.46% (35/92), respectively. The prevalence in young male camels was 41.02% (32/78) and 39.62% (21/53), respectively and in adult males was 19.35% (6/31) and 36% (9/25), respectively. Adult females displayed a prevalence of 22.22% (2/9) and 38.46% (5/13) in Riyadh and Al-Qassim, respectively. Three Eimeria spp. were identified; E. cameli, E. rajasthani, and E. pellerdyi. The presence of E. pellerdyi is considered the first record in Saudi Arabia.Stem cells are primitive and precursor cells with the potential to reproduce into diverse mature and functional cell types in the body throughout the developmental stages of life. Their remarkable potential has led to numerous medical discoveries and breakthroughs in science. As a result, stem cell-based therapy has emerged as a new subspecialty in medicine. One promising stem cell being investigated is the induced pluripotent stem cell (iPSC), which is obtained by genetically reprogramming mature cells to convert them into embryonic-like stem cells. These iPSCs are used to study the onset of disease, drug development, and medical therapies. However, functional studies on iPSCs involve the analysis of iPSC-derived colonies through manual identification, which is time-consuming, error-prone, and training-dependent. Thus, an automated instrument for the analysis of iPSC colonies is needed. Recently, artificial intelligence (AI) has emerged as a novel technology to tackle this challenge. In particular, deep learning, a subfield of AI, offers an automated platform for analyzing iPSC colonies and other colony-forming stem cells.