Exploring the effects of noise pollution on physiology and ptilochronology of birds.

Short and long-term sound-induced stress on daily basis can affect the physiology of avian individuals because they are more susceptible to sound stress in an open environment. OBJECTIVES: An ex-situ study was carried out to determine the impact of noise on physiology and ptilochronology of non-breeding male domesticated quail birds. METHODOLOGY: During 60-days long trial, male quail birds, aged 5-weeks, weighing (c.100gm) were used. Out of 72 experimental birds, 18 birds were assigned to the Control Group (G1) while remaining 54 birds were divided equally into 3 treatment groups: Road Traffic noise (G2), Military activity noise (G3) and Human Activities noise (G4). Birds were housed in standard-sized separate cages (20 ×45 × 20 cm), every bird was kept apart in separate cage in open laboratory under maintained environmental conditions. Millet seeds and water were provided to all the experimental birds ad libitum. Noise originated from several sources of recorded high-intensity music (1125 Hz/ 90 dB), was administered for 5-6 hours per day. Observations were recorded in the morning and afternoon. The experiment was conducted during the non-breeding season from August to October in triplicate. Blood sampling was done after 60 days. RESULTS: According to the current study, noise stress significantly (p<0.05) increased the concentrations of creatinine, aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), bilirubin, uric acid, cholesterol, triglycerides, total protein, and glucose while a decline in the levels of albumin was seen in treatment birds of G3. While in terms of hematology, total white blood cells count (TWBC), total red blood cells count (TRBC), mean cell volume (MCV) & packed cell volume (PCV) concentrations were raised in blood of treatment birds of G3. In terms of hormones, noise stress significantly (p<0.05) increased the serum concentrations of Corticosterone in G3 while a significant (p<0.05) decline was observed in the concentrations of luteinizing hormone (LH), thyroid stimulating hormone (TSH), and follicle stimulating hormone (FSH) in the same group. Moreover, fault bar formation in G3 was more prominent than others. CONCLUSION: Noise stress can significantly affect serology, hematology, hormonal physiology and ptilochronology in quail birds.

Curriculum learning-based strategy for low-density archaeological mound detection from historical maps in India and Pakistan.

This paper presents two algorithms for the large-scale automatic detection and instance segmentation of potential archaeological mounds on historical maps. Historical maps present a unique source of information for the reconstruction of ancient landscapes. The last 100 years have seen unprecedented landscape modifications with the introduction and large-scale implementation of mechanised agriculture, channel-based irrigation schemes, and urban expansion to name but a few. Historical maps offer a window onto disappearing landscapes where many historical and archaeological elements that no longer exist today are depicted. The algorithms focus on the detection and shape extraction of mound features with high probability of being archaeological settlements, mounds being one of the most commonly documented archaeological features to be found in the Survey of India historical map series, although not necessarily recognised as such at the time of surveying. Mound features with high archaeological potential are most commonly depicted through hachures or contour-equivalent form-lines, therefore, an algorithm has been designed to detect each of those features. Our proposed approach addresses two of the most common issues in archaeological automated survey, the low-density of archaeological features to be detected, and the small amount of training data available. It has been applied to all types of maps available of the historic 1″ to 1-mile series, thus increasing the complexity of the detection. Moreover, the inclusion of synthetic data, along with a Curriculum Learning strategy, has allowed the algorithm to better understand what the mound features look like. Likewise, a series of filters based on topographic setting, form, and size have been applied to improve the accuracy of the models. The resulting algorithms have a recall value of 52.61% and a precision of 82.31% for the hachure mounds, and a recall value of 70.80% and a precision of 70.29% for the form-line mounds, which allowed the detection of nearly 6000 mound features over an area of 470,500 km2, the largest such approach to have ever been applied. If we restrict our focus to the maps most similar to those used in the algorithm training, we reach recall values greater than 60% and precision values greater than 90%. This approach has shown the potential to implement an adaptive algorithm that allows, after a small amount of retraining with data detected from a new map, a better general mound feature detection in the same map.

LKB1 regulates polarity remodeling and adherens junction formation in the Drosophila eye.

The serine-threonine kinase LKB1 regulates cell polarity from Caenorhabditis elegans to man. Loss of lkb1 leads to a cancer predisposition, known as Peutz-Jeghers Syndrome. Biochemical analysis indicates that LKB1 can phosphorylate and activate a family of AMPK- like kinases, however, the precise contribution of these kinases to the establishment and maintenance of cell polarity is still unclear. Recent studies propose that LKB1 acts primarily through the AMP kinase to establish and/or maintain cell polarity. To determine whether this simple model of how LKB1 regulates cell polarity has relevance to complex tissues, we examined lkb1 mutants in the Drosophila eye. We show that adherens junctions expand and apical, junctional, and basolateral domains mix in lkb1 mutants. Surprisingly, we find LKB1 does not act primarily through AMPK to regulate cell polarity in the retina. Unlike lkb1 mutants, ampk retinas do not show elongated rhabdomeres or expansion of apical and junctional markers into the basolateral domain. In addition, nutrient deprivation does not reveal a more dramatic polarity phenotype in lkb1 photoreceptors. These data suggest that AMPK is not the primary target of LKB1 during eye development. Instead, we find that a number of other AMPK-like kinase, such as SIK, NUAK, Par-1, KP78a, and KP78b show phenotypes similar to weak lkb1 loss of function in the eye. These data suggest that in complex tissues, LKB1 acts on an array of targets to regulate cell polarity.