Academic literature on the topic 'Sparton Classified type'

Indonesia was classified as an agricultural country and the potential in agricultural cultivation includes plantation crops, horticulture, food crops and others. Eggplant plants were easy to grow and were liked by the public because of their delicious taste and high nutritional value and various types, namely Dutch eggplant, purple eggplant, sparrow eggplant and others. The purpose of the research was to study the proximate content of fresh and dried leaves, especially the sparrow eggplant found in the Mojokerto area, Kediri, Malang. The research method is a quantitative chemical test with parameters such as water content, ash content, protein, fat, carbohydrates in the leaves. The results of the analysis obtained were as follows: Mojokerto Region: Fresh leaves have a moisture content of 64.29%; Ash content 3, 46%; Protein 22, 87%, Fat 4.47%; Carbohydrates 4.91%, Dried leaves: 7.51%; 12.32%; 25.46%; 3.28%, 51.43%. Kediri area, fresh leaves: 64.89%; 3, 78%,; 23.18%, 4.93%; 3.22% while dry leaves : 7.38%, 12.46%, 25.75%, 3.65%; 50.76%. Malang location fresh leaves: 65.07%; 2, 96%, 24,50%, , 5.41%; 4.46%; dry leaves : 6.70%; 7.20%, 26.80%, 4.70%, 54.58 %. So the effective growing location for sparrow eggplant is Malang because of the potential for optimal proximate content

Introduction. Oirat folklore traditions include typologically different tales that remain vastly understudied. Folklore materials of Xinjiang Oirats used to be printed in Clear Script type up to the late 1980s, but currently those are primarily published in Classical Mongolian, which makes it difficult for Russian folklorists to study them. So, the paper attempts an insight into one folklore genre of Xinjiang Oirats — animal tales. Goals. The article classifies animal tales of XUAR-based Oirats (China) in accordance with the universally accepted comparative approach. Materials. The work examines The White-Collared Sparrow (Betege caγān boqširγo) animal tale collection issued by Xinjiang People’s Publishing House in 1981. Results. The study identifies 24 (of 31) plots in standard world classification systems of folklore and mythological motifs, while 7 samples prove essentially local. Some plots are referred to as etiological myths.

Birds undergo numerous changes as they progress through life-history stages, yet relatively few studies have examined how birds adapt to both the dynamic energetic and mechanical demands associated with such transitions. Myosin heavy chain (MyHC) expression, often linked with muscle fibre type, is strongly correlated with a muscle's mechanical power-generating capability, thus we examined several morphological properties, including MyHC expression of the pectoralis, in a long-distance migrant, the white-crowned sparrow ( Zonotrichia leucophrys gambelii ) throughout the progression from winter, spring departure and arrival on breeding grounds. White-crowned sparrows demonstrated significant phenotypic flexibility throughout the seasonal transition, including changes in prealternate moult status, lipid fuelling, body condition and flight muscle morphology. Pectoral MyHC expression also varied significantly over the course of the study. Wintering birds expressed a single, newly classified adult fast 2 isoform. At spring departure, pectoral isoform expression included two MyHC isoforms: the adult fast 2 isoform along with a smaller proportion of a newly present adult fast 1 isoform. By spring arrival, both adult fast isoforms present at departure remained, yet expression had shifted to a greater relative proportion of the adult fast 1 isoform. Altering pectoral MyHC isoform expression in preparation for and during spring migration may represent an adaptation to modulate muscle mechanical output to support long-distance flight.

BackgroundFollowing the failure of initial biological treatment in spondyloarthritis, switching to an alternative biological drug is possible. However, the data regarding the choice of the drug is limited. ASAS/EULAR guideline on axial spondyloarthritis does not make a distinction between TNFi, IL-17i or JAKi, with certain precautions regarding JAKi [1]. On the other hand, ACR/SAA/SPARTAN guideline recommends IL-17i over a different TNFi in primary failure, based on the assumption that TNF is not the key inflammatory mediator in these patients [2].ObjectivesOur main objective was to compare and contrast the clinical and laboratory features of the patients who received either a TNFi or IL-17i following the failure of the initial biologic treatment in our cohort of spondyloarthritis patients.MethodsSpondyloarthritis patients followed in our institution between 2014 and 2022 who received a secondary bDMARD following primary or secondary biologic failure were included in our study. ASAS criteria were used to classify patients as having axial or peripheral SpA. Failure was defined as lack of clinical improvement following at least 12 weeks of therapy. Demographic, clinical, laboratory and radiological features of the patients, along with clinical and laboratory response following the second line bDMARD treatment were recorded.Results90 patients were included in our study. 51% were female (N=46), mean age at diagnosis was 35 (SD: 11.9, %95 CI: 32.5–37.6), median duration of disease was 9 years (IQR: 10, minimum: 2 years, maximum: 38 years). 76% (N=68) of patients were classified as axial SpA, remaining 22 were classsifed as peripheral SpA. 68% (N=58) were HLA-B27 positive. Median ASDAS-CRP before the intial bDMARD was 3.7 (IQR: 1.3, min-max: 2.6–5.9). Adalimumab was the most used initial TNFi (48%, N=43). Most common reason of treatment switch was secondary failure (51%, N=41), followed by primary failure (25%, N=20) and side effects (19%, N=15).Following initial treatment failure, 30% of patients (N=27) were switched to a drug with an alternative pathway, with most of them being secukinumab (N=22). Median ASDAS-CRP after initial treatment failure was 3.8 (IQR: 1.0, min-max: 2.5–6.0). There was no difference in type of spondylarthritis, HLA-B27 positivity, ASDAS-CRP score and choice of bDMARD between primary and secondary failure groups. 24% of patients (N=22) achieved clinical remision in the secondary line of bDMARD treatment. The rate of clinical remission was 5% for TNFi and 75% for IL-17i (P<0.001). Duration of disease was shorter for responders (median 4 years vs. 11 years, P=0,03). Gender, HLA-B27 status, presence of enthesitis, dactylitis, uveitis, skin involvement, gastrointestinal involvement and initial ASDAS-CRP score did not differ between responders and non-responders (Table 1).Table 1.Characteristics of responders and non-responders to secondary line treatmentSecondary bDMARDPNon-responderResponderDisease duration11 years (IQR: 12)4 years (IQR: 5)0.033SpA classification Ax-SpA52 (77%)23 (24%)0.722 Per-SpA16 (72%)6 (27%)HLA-B27 Negative18 (67%)9 (33%)0.285 Positive45 (78%)13 (22%)Second line bDMARD TNFi59 (95%)3 (5%)<0.001 IL-17i6 (25%)18 (75%) Other3 (%75)1 (%25)Second line TNFi ADA12 (86%)2 (%14)0.116 ETN26 (100%)0 GOL4 (80%)1 (20%) IFX9 (100%)0 CZP8 (100%)0ConclusionThe rate of remission for IL-17i was significantly higher than TNFi following the failure of initial bDMARD failure. There was no difference between clinical and laboratory features of responders and non-responders, except for duration of disease. These findings suggest using an alternative pathway in case of TNFi failure may be preferable.References[1]Ramiro S, Nikiphorou E, Sepriano A,et al.ASAS-EULAR recommendations for the management of axial spondyloarthritis: 2022 update.Ann Rheum Dis2023;82:19–34.[2]Ward MM, Deodhar A, Gensler LS,et al.2019 Update of the ACR/SAA/SPARTAN Recommendations for the Treatment of Ankylosing Spondylitis and Nonradiographic Axial Spondyloarthritis.Arthritis Rheumatol Hoboken NJ2019;71:1599–613.Acknowledgements:NIL.Disclosure of InterestsNone Declared.

BackgroundFrailty is a syndrome characterized by an increased vulnerability to stressors and is associated with disability and early mortality. Frailty may be accelerated in patients with vasculitis. The prevalence of frailty in patients with vasculitis remains unexplored.ObjectivesTo describe the prevalence of self-reported frailty in patients with vasculitis.MethodsVascStrong is a longitudinal study utilizing the Vasculitis Patient-Powered Research Network (VPPRN), an internet-based prospective longitudinal cohort. Data elements collected included type of vasculitis, demographic, and use of medications. Frailty was measured by the FRAIL scale, a self-report measure which queries on 5 domains: 1. Fatigue, 2. Resistance (inability to climb 10 stairs), 3. Ambulation (inability to walk several blocks), 4. Illnesses (≥5/11 comorbidities), and 5. Loss of Weight (≥5% weight loss in the last year). Patients were classified as robust, pre-frail, and frail based on 0, 1-2, or ≥ 3 criteria, respectively.ResultsThe survey collected information from October 8, 2021-January 15, 2022. For this preliminary analysis, 228 responses were included. Clinical characteristics and study data are outlined in Table 1. Prevalence of robustness, pre-frailty, and frailty was 28.5%, 47.8%, and 23.7%, respectively. The majority of patients with each form of vasculitis were rated as frail or pre-frail. Among the individual FRAIL domains, fatigue and loss of weight were the most frequent (48.7% and 42.5%, respectively) while illnesses, was the least common (3.5%). When compared to robust patients, frail and pre-frail patients were younger, more frequently female, more likely to be obese and reported more frequent use of glucocorticoids. Patients with urticarial vasculitis and Takayasu’s arteritis were more commonly pre-frail or frail, compared to patients with other types of vasculitis.Table 1.Characteristics for overall cohort and by frailty classificationOverall N = 228Robust N = 65Pre-frail N = 109Frail N = 54Age, years, mean (SD)57.6 (15.3)62.4 (14.8)55.1 (15.6)57.1 (14.3)Sex, female163 (71.5%)40 (61.5%)84 (77.1%)39 (72.2%)Race, white204 (89.5%)60 (92.3%)98 (89.9%)46 (85.2%)Ethnicity, non-Hispanic195 (85.5%)57 (87.7%)97 (89.0%)41 (75.9%)Disease duration, years, mean (SD)8.5 (7.9)8.6 (6.8)8.4 (8.4)8.8 (8.0)Employment statusEmployed98 (43.0%)24 (36.9%)60 (55.0%)14 (26.0%)Retired66 (28.9%)29 (44.6%)24 (22.0%)13 (24.1%)Disabled (unable to work)34 (14.9%)4 (6.2%)12 (11.0%)18 (33.3%)Other/missing30 (13.2%)8 (12.3%)13 (12.0%)9 (16.7%)DiagnosisGranulomatosis with polyangiitis89 (100.0%)29 (32.6%)42 (47.2%)18 (20.2%)Eosinophilic granulomatosis with polyangiitis26 (100.0%)9 (34.6%)11 (42.3%)6 (23.1%)Microscopic polyangiitis23 (100.0%)7 (30.4%)12 (52.2%)4 (17.4%)Giant cell arteritis17 (100.0%)5 (29.4%)8 (47.1%)4 (23.5%)Urticarial vasculitis14 (100.0%)2 (14.3%)5 (35.7%)7 (50.0%)Takayasu's arteritis10 (100.0%)0 (0%)7 (70.0%)3 (30.0%)Other*49 (100.0%)8 (26.5%)16 (49.0%)8 (24.5%)Body Mass IndexaUnderweight6 (2.6%)2 (3.1%)4 (3.7%)0 (0%)Normal86 (37.7%)35 (53.8%)40 (36.7%)11 (20.4%)Overweight63 (27.6%)19 (29.2%)29 (26.6%)15 (27.8%)Obese73 (32.0%)9 (13.8%)36 (33.0%)28 (51.9%)Currently on glucocorticoids104 (45.6%)19 (29.2%)52 (47.7%)33 (61.1%)Current glucocorticoid dose, prednisone equivalent (mg/d), mean (SD)13.1 (18.0)12.6 (17.1)11.3 (18.6)16.4 (17.4)Data presented as n (%), unless specified otherwise*Other diagnosis: Behçet’s disease, primary angiitis central nervous system, cryoglobulinemic vasculitis, IgA vasculitis, polyarteritis nodosa, and other/suspected diagnosisaBased on World Health Organization Body Mass Index categoriesConclusionSelf-reported frailty or pre-frailty is prevalent in the majority of patients with multiple forms of vasculitis. Future analysis will focus on identifying factors associated with frailty in patients with vasculitis, to allow earlier identification and prevention in this population at high-risk for frailty.AcknowledgementsThe investigators want to thank all participants.Disclosure of InterestsSebastian E. Sattui Grant/research support from: receives research funding related to clinical trials by AstraZeneca (MANDARA), John Stadler: None declared, Cristina Burroughs: None declared, Kalen Larson: None declared, Peter A. Merkel Consultant of: CSL Behring, Dynacure, EMDSerono, Immagene, Jannsen, Kiniksa, Kyverna, Magenta, MiroBio, Mitsubishi, Novartis, Pfizer, Regeneron, Sparrow, Talaris, AbbVie, AstraZeneca, Boeringher-Ingelheim, Bristol-Myers Squibb, ChemoCentryx, Forbius, Genentech/Roche, Genzyme/Sanofi, GlaxoSmithKline, InflaRx, Neutrolis, Takeda., Grant/research support from: AbbVie, AstraZeneca, Boeringher-Ingelheim, Bristol-Myers Squibb, ChemoCentryx, Forbius, Genentech/Roche, Genzyme/Sanofi, GlaxoSmithKline, InflaRx, Neutrolis, Takeda., Robert Spiera Consultant of: Chemocentryx, Grant/research support from: Chemocentryx

Bird call, which is widely used in all species of birds, is short, simple, and functionally diverse in comparison to song. Here, we have recorded call types of Eurasian tree sparrows ( Passer montanus) at multiple situations and various communal behaviors. The Eurasian tree sparrow belongs to the oscine (song-learning) group of songbirds, but their calls are more developed than their song. The calls are used to communicate a variety of behaviors in their social flock. In this study, we categorized call types and usages in relation to the situation on the basis of visual categorization of spectrograms and descriptive measurements. Adult Eurasian tree sparrows have 9 call types (including 9 sub-types at A1 family) and chicks have one (including 2 sub-types). Each call type could be classified as A1 contact call, A2 Fight-intention call, A3 Aerial call, A4 Alarm/Anxiety call, A5 Emergency call, A6 Warning/Threat call, A7 Stimulate call, A8 Screaming call, A9 Social calling, and C1 Begging call. Our results suggest that the diversity of Eurasian tree sparrow’s call types is related to the complex social structure of the species, and might be associated to evolution of sociality. Further research on correlation between various call types and social behavior is needed to find social communication characteristics of Eurasian tree sparrows and other social weaver species with similar ecology may reveal whether evolutionary pressures of sociality lead to increased call complexity.

Abstract Background MathWorks has provided an invaluable tool for designing and implementing FPGAs. MATLAB HDL coder serves a dual purpose, providing a quick proof of concept on the one hand and providing the g an easy-to-use platform for testing and verification on the other. It has main drawbacks over these advantages; it generates a code that is not optimized for both area and frequency. Results In this paper, we provide a technique for optimizing both area and frequency without losing the main advantages. The most affecting problem we found is loops. This paper classifies loop writing purposes into two types. The first one is preferable and introduces ease of writing a few lines instead of repeating the code. The second type is the problem that we intended to solve. Type II loop is appearing when the algorithm should perform these lines for several clock cycles. Writing it traditionally, force the synthesizer to implement all the repetitive clock cycles as repetitive hardware to be done in one clock cycle. This clock cycle is wide in time and is slow in frequency. This paper introduces an optimization technique for this problem. We compare before and after the implementation of our proposed technique. Conclusions We used Xilinx Spartan 6 XC6SLX4-2CPG196 FPGA. Our proposed technique improves the number of slice LUTs (Look Up Tables) requirement from 366 to 72%. The frequency improved from: 26.574 to 185.355 MHz. Based on that, we now recommend using MATLAB HDL coder in FPGA Design.

Abstract Enhancing the operational reliability of rotary machinery relies significantly on the effective diagnosis of faults in rolling bearings. This study introduces an innovative method to improve the accuracy of fault diagnosis of rolling bearings during operation. First, we propose a sine empirical mode decomposition (SEMD) designed to effectively mitigate mode mixing and decompose the vibration signals of rolling bearings into a series of intrinsic mode functions. Subsequently, we constructed and optimized a kernel extreme learning machine classifier (KELMC) using the improved sparrow search algorithm (ISSA). Within ISSA, the Opposition-based Learning method is refined and applied to enhance the optimization performance of the sparrow search algorithm. Finally, the paper presents a novel method for the fault diagnosis of rolling bearings based on SEMD and ISSA-KELMC, which can effectively extract the fault features and accurately recognize the fault types of rolling bearings by taking advantage of the SEMD and ISSA-KELMC. The effectiveness of the proposed method was verified through two simulation and fault diagnosis experiments. The results demonstrated the efficiency of the method in diagnosing faults in rolling bearings under both consistent and variable working conditions. This approach is valuable for fault diagnosis and condition monitoring of rotating machinery. &#xD;

AbstractThe hypothesis of associating pseudoscorpions with bird nest types was tested on the basis of an analysis of 480 specimens. Eleven pseudoscorpion species were found in 171 nests of 28 different bird species collected in Slovakia, Austria and the Czech Republic. The frequent appearance of Cheiridium museorum, Dactylochelifer latreillii, Chernes hahnii, Dendrochernes cyrneus and Allochernes wideri was confirmed. High proportion and association of Pselaphochernes scorpioides in hoopoe hollow nests with decomposed substrate, D. cyrneus in the Eurasian tree sparrow nest boxes and A. wideri in the nests of the tawny owls, the European scops owls and the European roller was proved. In contrast, C. hahnii and D. latreillii were related to the nest fauna of blackbirds and song thrushes, C. museorum to the nests of white wagtails situated on the ground and on buildings and C. cancroides to the nests in synanthropic habitats. Until present, the occurrence of 22 pseudoscorpion species has been confirmed in the bird nests of Central Europe based on the obtained results and published resources. According to the association to bird nests these pseudoscorpions were classified as (1) nidixenous species — Chthonius fuscimanus, C. tetrachelatus, Mundochthonius styriacus, Neobisium carcinoides, N. crassifemoratum, N. inaequale, N. sylvaticum, Chernes cimicoides, C. similis, C. vicinus, Allochernes powelli, Lamprochernes chyzeri, L. nodosus and Larca lata; and (2) nidiphilous species — C. museorum, C. cancroides, A. wideri, D. cyrneus, D. latreillii, C. hahnii, D. panzeri and P. scorpioides.

The Gulf Islands National Seashore (GUIS) vegetation inventory project classified and mapped vegetation on park-owned lands within the administrative boundary and estimated thematic map accuracy quantitatively. The project began in June 2016. National Park Service (NPS) Vegetation Mapping Inventory Program provided technical guidance. The overall process included initial planning and scoping, imagery procurement, field data collection, data analysis, imagery interpretation/classification, accuracy assessment (AA), and report writing and database development. Initial planning and scoping meetings took place during May, 2016 in Ocean Springs, Mississippi where representatives gathered from GUIS, the NPS Gulf Coast Inventory and Monitoring Network, and Colorado State University. Primary imagery used for interpretation was 4-band (RGB and CIR) orthoimages from 2014 and 2016 with resolutions of 15 centimeters (cm) (Florida only) and 30 cm. Supplemental imagery with varying coverage across the study area included National Aerial Imagery Program 50 cm imagery for Mississippi (2016) and Florida (2017), 15 and 30 cm true color Digital Earth Model imagery for Mississippi (2016 and 2017), and current and historical true-color Google Earth and Bing Map imagery. National Oceanic Atmospheric Administration National Geodetic Survey 30 cm true color imagery from 2017 (post Hurricane Nate) supported remapping the Mississippi barrier islands after Hurricane Nate. The preliminary vegetation classification included 59 United States National Vegetation Classification (USNVC) associations. Existing vegetation and mapping data combined with vegetation plot data contributed to the final vegetation classification. Quantitative classification using hierarchical clustering and professional expertise was supported by vegetation data collected from 250 plots in 2016 and 29 plots in 2017 and 2018, as well as other observational data. The final vegetation classification includes 39 USNVC associations and 5 park special types; 18 forest and woodland, 7 shrubland, 17 herbaceous, and 2 sparse vegetation types were identified. The final GUIS map consists of 38 map classes. Land cover classes include four types: non-vegetated barren land / borrow pit, developed open space, developed low – high intensity, and water/ocean. Of the 34 vegetation map classes, 26 represent a single USNVC association/park special, six map classes contain two USNVC associations/park specials, and two map classes contain three USNVC associations/park specials. Forest and woodland associations had an abundance of sand pine (Pinus clausa), slash pine (Pinus elliottii), sand live oak (Quercus geminata), yaupon (Ilex vomitoria), wax myrtle (Morella cerifera), and saw palmetto (Serenoa repens). Shrubland associations supported dominant species such as eastern baccharis (Baccharis halimifolia), yaupon (Ilex vomitoria), wax myrtle (Morella cerifera), saw palmetto (Serenoa repens), and sand live oak (Quercus geminata). Herbaceous associations commonly included camphorweed (Heterotheca subaxillaris), needlegrass rush (Juncus roemerianus), bitter seabeach grass (Panicum amarum var. amarum), gulf bluestem (Schizachyrium maritimum), saltmeadow cordgrass (Spartina patens), and sea oats (Uniola paniculata). The final GUIS vegetation map consists of 1,268 polygons totaling 35,769.0 hectares (ha) or 88,387.2 acres (ac). Mean polygon size excluding water is 3.6 ha (8.9 ac). The most abundant land cover class is open water/ocean which accounts for approximately 31,437.7 ha (77,684.2 ac) or 87.9% of the total mapped area. Natural and ruderal vegetation consists of 4,176.8 ha (10,321.1 ac) or 11.6% of the total area. Within the natural and ruderal vegetation types, herbaceous types are the most extensive with 1945.1 ha (4,806.4 ac) or 46.5%, followed by forest and woodland types with 804.9 ha (1,989.0 ac) or 19.3%, sparse vegetation types with 726.9 ha (1,796.1 ac) or 17.4%, and shrubland types with 699.9 ha (1,729.5 ac) or 16.8%. Developed open space, which can include a matrix of roads, parking lots, park-like areas and campgrounds account for 153.8 ha (380.0 ac) or 0.43% of the total mapped area. Artificially non-vegetated barren land is rare and only accounts for 0.74 ha (1.82 ac) or 0.002% of the total area. We collected 701 AA samples to evaluate the thematic accuracy of the vegetation map. Final thematic accuracy, as a simple proportion of correct versus incorrect field calls, is 93.0%. Overall weighted map class accuracy is 93.6%, where the area of each map class was weighted in proportion to the percentage of total park area. This method provides more weight to larger map classes in the park. Each map class had an individual thematic accuracy goal of at least 80%. The hurricane impact area map class was the only class that fell below this target with an accuracy of 73.5%. The vegetation communities impacted by the hurricane are highly dynamic and regenerated quickly following the disturbance event, contributing to map class disagreement during the accuracy assessment phase. No other map classes fell below the 80% accuracy threshold. In addition to the vegetation polygon database and map, several products to support park resource management are provided including the vegetation classification, field key to the associations, local association descriptions, photographic database, project geodatabase, ArcGIS .mxd files for map posters, and aerial imagery acquired for the project. The project geodatabase links the spatial vegetation data layer to vegetation classification, plot photos, project boundary extent, AA points, and the PLOTS database. The geodatabase includes USNVC hierarchy tables allowing for spatial queries of data associated with a vegetation polygon or sample point. All geospatial products are projected using North American Datum 1983 (NAD83) in Universal Transverse Mercator (UTM) Zone 16 N. The final report includes methods and results, contingency tables showing AA results, field forms, species list, and a guide to imagery interpretation. These products provide useful information to assist with management of park resources and inform future management decisions. Use of standard national vegetation classification and mapping protocols facilitates effective resource stewardship by ensuring the compatibility and widespread use throughout the NPS as well as other federal and state agencies. Products support a wide variety of resource assessments, park management and planning needs. Associated information provides a structure for framing and answering critical scientific questions about vegetation communities and their relationship to environmental processes across the landscape.