Miracle-dz/UniFAR-FTUs huggingface dataset:
Antibiogram profile of pathogens isolated from processed cow meat from Ekpoma and Irrua metropolis, Edo state, Nigeria.

This study determined the extent of bacterial contamination of cow meat processed and sold in Ekpoma and Irrua abattoirs in Edo State, Nigeria, and their antibiotic susceptibility patterns. One hundred and twenty (120) samples comprising 40 samples each, from blood, table surfaces and processed row meat, were collected from the sampled abattoirs and analyzed using standard bacteriological procedures. The results showed that 60 samples, representing 50% prevalence, were positive for different bacteria species, but the table surface samples were the most contaminated. The comparative difference in rates of contamination, were observed to be statistically significant (p<0.05). Of note, is the fact that the bacteria specie - Bacillus cereus (31; 51.7%), accounted for most of the bacteria isolate, while the antibiotic resistance tests revealed varied, but interesting susceptibility patterns. Our findings does highlight the fact that there exist obvious vehicles for pathogenic bacteria proliferation within our abattoirs, and hence, the need for caution. Key words: Abattoirs, Bos taurus , Pathogenic bacteria, Antibiotics, Resistance
Description of a new termite species from Cyprus and the Aegean area: Reticulitermes aegeus sp. nov.

Reticulitermes aegeus sp. nov. (Rhinotermitidae) is described, based on samples of alates and soldiers collected on the island of Cyprus. The range of the species includes the island of Lošinj (Croatia), north-eastern Greece (Halkidiki and north-eastern Greece), Eastern Peloponnese, Northern Turkey, Crete, Cyprus and Amorgos (Cyclades Islands). The ascertained range of R. aegeus does not overlap with the ranges of other species occurring in the eastern Mediterranean lands. From the phylogenetic point of view, R. aegeus belongs to the eastern Mediterranean Reticulitermes clade, that also includes R. urbis, R. balkanensis and R. clypeatus, as well as taxa not yet described from Turkey and the island of Samos. R. aegeus is genetically distinct from other eastern Mediterranean Reticulitermes species, while its morphological characters do not allow a reliable diagnosis without further support. DNA analysis provides such corroboration.
Two new moss records in the family Grimmiaceae from Turkey, Southwest Asia.

Grimmia incurva Schwagr. and Schistidium umbrosum (J.E.Zetterst.) H.H. Blom (Grimmiaceae) are reported for the first time from Turkey, Southwest Asia. Turkish plants are described and illustrated from material collected from Golludag Volcano in the Central Anatolia (Nigde) which has a semi-arid, continental climate with a severe frost period in winter.
Current Opinion in Colloid & Interface Science

abstract Article history:Received 15 September 2009Accepted 19 November 2009Available online 27 November 2009Keywords:InterfaceProteinDigestionBiosurfactantEnzymeEmulsion The increase in food related health issues has sparked an interest in research on the digestion processes ofthe gastrointestinal tract. Because of the difﬁculty and expense of undertaking human trials or even animalexperiments, much of the current research uses in vitro models that simulate various aspects of digestion.The results of this research indicate that the rate and extent of protein digestion is governed by accessibilityof the cleavage sites to enzymes and local ﬂexibility of the substrate molecule. However, results have alsoshown that digestion of an allergenic protein to small fragments does not necessarily mean that it will nolonger be immunologically active. Other factors are also important. For example, adsorption to an interfaceincreased rates of digestion as did the presence of bile acids. In fact, interaction with a range of physiologicalsurfactants has been shown to be extremely important in protein digestion. When protein is adsorbed to anemulsiﬁed food it can be displaced by the surfactants in either the stomach or the small intestine. Lipidinteraction with the protein in solution has been demonstrated to be important in effecting rates ofproteolysis and phospholipids in particular have provided a protective effect for some milk proteins.Conversely the presence of speciﬁc proteins has been shown to affect rates of lipid digestion. The number ofsuch colloidal interactions that we now know may play a role in protein digestion highlights the importanceof this area to understanding how we can produce food that optimises nutrition for the consumer. © 2009 Elsevier Ltd. All rights reserved.
Diet of the Torrent Sculpin, Cottus rhotheus, in the Cedar River, Washington: Effect of Season, Habitat Type, and Predator Size with Emphasis on Piscivory

Abstract Torrent Sculpin (Cottus rhotheus) can play an important role in riverine ecosystems in the Pacific Northwest, but factors that influence their feeding ecology are not well understood. To better understand how environmental conditions may influence the diet of Torrent Sculpin in the Cedar River, Washington, we collected diet information from fish across seasons and habitats. Numerically, aquatic insects were usually the dominant prey type for each size class in each sampling effort. Overall, Torrent Sculpin prey on a wide variety of aquatic invertebrates but can also take advantage of other prey types, such as fry of Sockeye Salmon (Oncorhynchus nerka), juvenile Chinook Salmon (O. tshawytscha), and eggs of Largescale Suckers (Catostomus macrocheilus), when these prey become abundant. In February and March, predation on Sockeye Salmon fry was substantially higher in large, deep pools (>2.5-m depth) than in either riffles or slow-water secondary habitats. Besides fry of Sockeye Salmon, the only salmonid observed in the diet of Torrent Sculpin was juvenile Chinook Salmon. Sculpin (Cottus spp.) were an important prey type of Torrent Sculpin ≥100 mm total length (TL) in each sampling effort. This was especially evident during the summer when sculpin represented over 90% of the diet by weight of Torrent Sculpin ≥100 mm TL. Feeding strategy plots demonstrated that Torrent Sculpin exhibit an opportunistic feeding strategy for large-bodied prey (for example, fish, oligochaetes, and large plecopterans) and a more generalized feeding strategy for small-bodied prey (chironomids and small-bodied ephemeropterans). Prey size, abundance, and activity are likely important factors influencing prey selection in Torrent Sculpin. Because of their size, abundance, wide range in habitat use, and breadth of diet, Torrent Sculpin are an important species in the Cedar River food web.
Complete mitochondrial genome of Perny's long-nosed squirrel Dremomys pernyi (Rodentia: Sciuridae)

Abstract The complete mitochondrial genome of Perny's long-nosed squirrel (Dremomys pernyi) was firstly sequenced and characterized. The genome was 16,573 bp in length, and its composition and arrangement of genes were analogous to other rodents. The sequences of 13 protein-coding genes were used to construct phylogenetic tree for D. pernyi and other 13 sciurid species available on GenBank. To date, this is the first species whose complete mitochondrial genome sequence was sequenced in genus Dremomys. Our results will provide information for further molecular studies.
Perinatal Regulation of a Novel Mouse Cytochrome P450 Induced by Pregnancy

Pregnancy alters substrate metabolism by altering cytochrome P450 (CYP) enzymes. This superfamily is classified by amino acid sequence identity. CYP3Al is the first member of family 3, subfamily A. An HPLC method was used to identify a specific protein, cytochrome P450gest, that is induced in maternal liver during gestation in the C57Bl/6J mouse but is not induced by known exogenous CYP inducers. This study examines the regulation of P450gest in mice in different hormonal states and reports its purification, metabolic function and N-terminal sequence. Hepatic microsomal P450gest content decreased after parturition in both lactating and nonlactating mothers then increased to the pregnant mouse level in lactating mothers. In virgin females, prolactin treatment for seventeen days had a small inducing effect on P450gest. Growth hormone plus hydrocortisone induced P450gest to the pregnant level. Estradiol, progesterone or both added to the growth hormone, hydrocortisone treatment had no further effect on P450gest. Prolactin added to growth hormone and hydrocortisone decreased P450gest to the virgin female level. P450gest was purified from pregnant mouse hepatic
A Spatial Feature-Based Adaptive Technique to Match Models for Motor Imagery EEG Signals

In recent years, deep learning has been widely used in the field of motor imagery brain-computer interfaces, facilitating great improvements in classification accuracy in this field. However, due to the specificity of EEG data, the same model has uneven learning effects on different subject features. The difference in learning effects means that training with only one model results in signals that are not correctly identified in some subjects, which is not conducive to the diffusion of motor imagery EEG signal classification techniques. During the study, we found that each subject data has a suitable model for it, and assigning a suitable model to the data for training can better ensure a better classification accuracy for each subject. In this paper, we propose a technique for automatic matching of motion imagery EEG signals with recognition models. This is a technique for extracting spatial features of motor imagery EEG signals based on graph convolution. Because the spatial features are highly stable and all time steps are included in the extraction of spatial features, the features extracted are macroscopic in nature. Based on the big data screening, we selected four excellent motor imagery EEG signal classification models and put the data of subjects who performed well on these models into the graph convolution model for supervised learning. The completed learning graph convolution model can be well trained to assign appropriate classical models of EEG signals to different subjects based on spatial features. After using this method, we achieved an average classification accuracy of 88$\%$ on the BCI Competition IV dataset 2a.
Evidence for Range Contraction of Snowshoe Hare in Pennsylvania

Abstract In Pennsylvania, Lepus americanus (Snowshoe Hare) is near the southern limits of its range and at risk of range contraction because of loss of early-successional forest and impacts of climate change. We used hunter-harvest data to investigate changes in the distribution of Snowshoe Hare in Pennsylvania (1983–2011), forest inventory and land-use data to assess changes in amount and distribution of early-successional forest (1988–2011), and occupancy modeling (2004) to identify habitat and climate variables that explain the current distribution of Snowshoe Hare. We determined presence of Snowshoe Hare based on visual sightings, observations of tracks, and DNA analysis of fecal pellets, and used repeated visits to sampling sites and occupancy models to estimate occupancy rates (Ψ). Hunter-harvest data indicated the range of Snowshoe Hare in Pennsylvania contracted towards northwestern and northeastern portions of the state. Based on occupancy modeling, Snowshoe Hare were most likely to occupy early-successional and mixed deciduous—coniferous forest types and areas with colder winter temperatures, which coincided with the distribution of hunter harvests. Among the 4 forest types, we estimated Ψ = 0.52–0.79 and Ψ = 0.10–0.32 where winter temperatures were coldest and warmest, respectively. Total forest loss was <1% during 1988–2011, and the loss of early-successional forest in the current and former range of Snowshoe Hares was similar as were mean patch size and a fragmentation metric of early-successional habitat. Thus, changes in forest characteristics did not explain the range contraction we observed. We used climate-model predictions and our occupancy model to predict that average occupancy probability across northern Pennsylvania may decline from 0.27 in 2004 to 0.10–0.18 by 2050–2059, depending on the climate model. The range of Snowshoe Hare in Pennsylvania has contracted to regions of Pennsylvania with the coldest winter temperatures and most persistent snowpack, and based on projected climate change, our results suggest further range contraction of Snowshoe Hare in Pennsylvania.
Bioconversion 기술 연구동향

미생물학적 물질변환에 대해서는 인류 초기에서부터 효모를 이용하여 빵, 유제품, 알코올, 음료 등의 생산에 이용하여 왔으며, 주로 농업분야 또는 식품 분야에 국한되어 왔다. 1862년 Pasteur에 의해 bacterium xylinum의 순수 배양균주를 사용하여 알코올로부터 초산을 만드는데 응용한 것이 본격적인 시발점으로 보아 무방하겠다. 그 후 acetobacter aceti에 의한 포도당으로부터 gluconic acid 생산과 acetobacter sp. 에서의 sorbitol로부터 sorbose 생산 등이 이루어졌고 정통적인 유기합성 방법에 의해 쉽게 만들 수 없는 반응들에 응용되기 시작하였다. 인류 초기의 혼합배양에 의한 물질변환에의 응용과는 달리 순수배양으로 미생물, 식물세포, 혹은 정제된 효소들에 의해 반응이 이루어지게 되었고 순수한 특정 물질에 대한 새로운 순수물질로의 선별적인 수식도 가능해지게 되었다. 특히 발효와 bioconversion의 차이는 racemates의 분리, 비슷한 반응성을 갖는 여러 기들로부터 특정기능을 갖는 기만의 선별적인 수식, 입체 이성체(chiral center)의 제작, 특정 비활성화된 탄소의 기능 등이 bioconversion에서만 수행할 수 있는 독특한 영역으로서 정밀화학분야, energy 분야, 환경오염분야에서의 특히 미래의 관심 기술로 대두되고 있다.
Die Sambucus nigra-Robinia pseudacacia-Gesellschaft und ihre geographische Gliederung

Robinia stands are shown not to represent the association status, thus contradicting JURKOs proposal (JURKO 1963) to establish a separate class Robinietea. The term: Sambucus nigra-Robin ia pseudacaciasociety is proposed. This type can be subdivided into a West European, a Central European and an East European Vikariante.
Efficacy of GPS cluster analysis for predicting carnivory sites of a wide‐ranging omnivore: the American black bear

The capacity to describe and quantify predation by large carnivores expanded considerably with the advent of GPS technology. Analyzing clusters of GPS locations formed by carnivores facilitates the detection of predation events by identifying characteristics which distinguish predation sites. We present a performance assessment of GPS cluster analysis as applied to the predation and scavenging of an omnivore, the American black bear (Ursus americanus), on ungulate prey and carrion. Through field investigations of 6854 GPS locations from 24 individual bears, we identified 54 sites where black bears formed a cluster of locations while predating or scavenging elk (Cervus elaphus), mule deer (Odocoileus hemionus), or cattle (Bos spp.). We developed models for three data sets to predict whether a GPS cluster was formed at a carnivory site vs. a non-carnivory site (e.g., bed sites or non-ungulate foraging sites). Two full-season data sets contained GPS locations logged at either 3-h or 30-min intervals from April to November, and a third data set contained 30-min interval data from April through July corresponding to the calving period for elk. Longer fix intervals resulted in the detection of fewer carnivory sites. Clusters were more likely to be carnivory sites if they occurred in open or edge habitats, if they occurred in the early season, if the mean distance between all pairs of GPS locations within the cluster was less, and if the cluster endured for a longer period of time. Clusters were less likely to be carnivory sites if they were initiated in the morning or night compared to the day. The top models for each data set performed well and successfully predicted 71–96% of field-verified carnivory events, 55–75% of non–carnivory events, and 58–76% of clusters overall. Refinement of this method will benefit from further application across species and ecological systems.
The complete chloroplast genome of Eclipta prostrata L. (Asteraceae)

Abstract Eclipta prostrata is an herbal medicinal plant belonging to the Asteraceae family. In this study, complete chloroplast genome sequence of the E. prostrata was characterized by de novo assembly using whole genome sequence data. The genome of E. prostrata was 151,757 bp in length, which was composed of large single copy region of 83,285 bp, small single copy region of 18,346 bp and a pair of inverted repeat regions of 25,063 bp. The genome harboured 80 protein coding sequences, 30 tRNA genes and 4 rRNA genes. We confirmed close taxonomic relationship between E. prostrata and Helianthus annuus through phylogenetic analysis with chloroplast protein-coding genes.
Nutritional and bioactive compounds of adzuki beans cultivars using chemometric approach

Azuki beans are small red grains rich in several essential nutrients used in traditional dishes in Asia that, nowadays present many applications around the world. This work aimed at evaluating angularis and niponensis cultivars from south region of Brazil. Both cultivars presented proximal composition similar to literature and the majority fatty acids were 18:2n-6, 16:0 and 18:3n-3. All samples showed polyunsatured fatty acids prevalence and nutritional indices and ratios considered adequate for biological system maintenance of a healthy organism. The grains presented significant contents of tocopherols and vitamin E activity, resulting in a high contribution to the dietary reference intake. Significant contents of iron, manganese and zinc were also found in the azuki beans, and they are very important mainly due to their function as cofactors in metabolic reactions. Phenolic compounds and flavonoids corroborated with other studies and contributed to the antioxidant activity. The principal components multivariate analysis allowed distinguishing the cultivars, and the two principal components could explain 92.28% of data variance.
Design of A Broadband Switched Filter Bank Based on System in Package Technology

This paper proposes an 8-channel switched filter bank based on system in package (SIP) technology. With the combination of filters, the operating frequency of the module can cover 8 to 18.5 GHz. The influence of ball grid array (BGA) package is simulated and analyzed. The whole filter bank is packaged with ceramic material to form a SIP filter to realize high integration and miniaturization. The measured results show that the proposed filter bank has good selectivity in each sub-band.
Prediction of Cardio Vascular Disease by Deep Learning and Machine Learning-A Combined Data Science Approach

Machine learning is the process in which the computer system can automatically learn from the data. It's an application of Artificial Intelligence without being explicitly programmed. Making use of Machine learning and AI an efficient algorithm for prediction of Cardio Vascular Disease (CVD) can be done. By combing Deep learning method to the ML model, a high-level abstract feature with improved performance can be obtained. Heart disease or Cardio Vascular disease is the predominant disease all over the world. Accurate prediction of heart disease is a challenging task. The accuracy of prediction can be improved by applying Machine learning algorithms. Results with high accuracy can be produced by combining a Machine learning model with Statistical concepts. The main objective of this research is to predict high accurate CVD by applying Deep learning model combined with Machine learning algorithm. By recognizing the symptoms of the disease, people can get prompt treatment on time.
ISOLATION AND CHARACTERIZATION OF BIOACTIVE STREPTOMYCES FROM MANGROVE ECOSYSTEM OF MACHILIPATNAM, KRISHNA DISTRICT, ANDHRA PRADESH

ABSTRACT Objective: The aim of the present study was to isolate, identify, and analyze the taxonomic characteristics of the potent actinobacterial strains VJSY-2 and VJSY-3 isolated from mangrove soils of Gilakaladindi, Machilipatnam, Krishna District of Andhra Pradesh. Methods: Soil samples pretreated with calcium carbonate were used for isolation of potent actinobacterial strains. Identification of the strains was carried out by studying the cultural, morphological, biochemical, and physiological characteristics. The phylogenetic study of the strains was carried out by employing 16S r DNA sequence-based analysis. Phylogenetic tree was constructed using the molecular evolutionary genetic analysis software version 6. Results: Based on the polyphasic taxonomic studies, the potent strains belong to Streptomyces genus. The bioactive metabolites produced by the strains were active against Gram-positive bacteria (Staphylococcus aureus, Bacillus subtilis, and Bacillus megaterium), Gram-negative bacteria (Xanthomonas campestris, Pseudomonas aeruginosa, and Escherichia coli), and fungi (Aspergillus niger, Fusarium solani, Fusarium oxysporum, and Candida albicans). Conclusion: The results of the experiment showed that the crude ethyl acetate extract of the strains VJSY-2 and VJSY-3 showed significant antimicrobial potential; hence, they can be used for isolation of compounds with pharmaceutical importance. Keywords : Mangrove Actinobacteria, Streptomyces, Bioactive metabolites.
SEQUENCE ANALYSIS OF THE CYTOCHROME OXIDASE I GENE IN AEDES ALBOPICTUS ISOLATED FROM TAMAN BUKIT KINRARA AND PJS7, SELANGOR

Aedes albopictus is one of the most invasive mosquitoes in the world that harbors and can transmit many arboviruses, most notably dengue and chikungunya virus. In recent time, Ae. aegypti has gained more attention during dengue outbreaks compared to its counter parts, obscuring the role of Ae. albopictus as a vector. Moreover, existing data regarding Ae. albopictus is also currently limited in Malaysia. Hence, the present study was conducted to determine the genetic diversity of Ae. albopictus using molecular techniques from two dengue infested areas in Subang Jaya, Selangor, namely Taman Bukit Kinrara (TBK) and PJS7. Cytochrome oxidase 1 ( CO1 ) gene from field collected mosquitoes were analyzed and compared to the USM laboratory strain (F135) together with sequences from the GenBank. Results from this study revealed that the field collected mosquitoes from TBK and PJS7 are genetically similar with each other. However, the samples exhibited polymorphism with the laboratory strain by 47 variable nucleotide sites. Our local samples are related with the Ae. albopictus populations from India, probably due to its migration across these two regions via several human activities. This study shows that the CO1 gene is a valuable marker for the detection of Ae. albopictus and can be utilized to study its worldwide geographical distribution. Further analysis is strongly recommended using larger sample size and different localities to validate and substantiate our findings.
Soil Moisture Estimation Using Hyperspectral Imagery Based on Metric Learning

Soil moisture plays important roles in the land-atmosphere interaction, rainfall–runoff process, climate and weather forecast, and crop yield. An accurate estimation of soil moisture creates opportunities to improve the understanding of soil moisture-related processes in atmospheric sciences, hydrology, and agriculture. Traditional methods to measure soil moisture mainly rely on in-situ measurements which are usually costly and reliant on the use of field instrumentation and point data. A robust remote sensing technique is highly needed to frequently monitor the soil moisture content over a large region or landscape. This paper presents a metric learning-based regression algorithm to learn the mapping function from the input hyperspectral data to the output soil moisture. In particular, the proposed soil moisture estimation method employs the Gaussian process to model the joint distribution of spectral bands over functions. It further incorporates the learning of distance function to find feature subspace for improving soil estimation performance. Experimental results on a real dataset show that the proposed metric learning-based soil moisture estimation method can significantly improve the performance compared to the state-of-the-art soil moisture estimation methods using principle component analysis for feature reduction.