A rare case of uterine myxoid leiomyosarcoma

Myxoid leiomyosarcoma is an uncommon tumour and in most cases, it is recognised only after the surgery. A 65 years old female patient got admitted at our hospital with history of rapidly growing abdominal mass with pain in abdomen since last 3 months. During abdominal examination 32 weeks huge mass was noted and on prevaginal examination mass couldn’t be separated from uterus. LDH was elevated, USG suggestive of vascular tumour of with neoplastic etiology of ovarain origin. CECT was done and findings suggestive of uterine adenocarcinoma with peritoneal carcinomatosis. Exploratory laparotomy with total abdominal hysterectomy with bilateral salphingoopherectomy with omentectomy with debulking surgery was performed. HPR reports suggestive of myxoid leiomyosarcoma with mitotic index of 10 with tumour cell necrosis suggestive of poor prognosis. Post-operative period patient had developed sudden myocardial infarction and shifted to ICU where she died due to ventricular fibrillation.

Low-flow Characteristics for Selected Streams in the Big Sioux River Basin, South Dakota

Thirty-two flow gaging stations from South Dakota, Minnesota, and Iowa were chosen for the low flow frequency analysis. A common base period of 68 years (1930- 1997) for the flow records of South Dakota streams was developed. Thirty-two gaging stations located in the Big Sioux River Basin were fit for the record extension. The flow records for 32 gaging stations were extended using Maintenance of Variance Extension Type 1 (MOVE.1) method. A new approach, the nonparametric method, is introduced to analyze low flow frequency for South Dakota streams. Low-flow frequency analysis was performed with log-Pearson Type III and nonparametric approaches. Seven-, 14-, and 30-day low flow magnitudes were determined for recurrence intervals of 1.25, 2, 5, 10, 20, 50, and 100 years for 32 gaging stations. The flow magnitudes for different recurrence intervals determined from log-Pearson Type III were slightly higher than those from nonparametric method were. The expected flows for different recurrence intervals from both the methods were compared with the observed flow magnitudes and recurrence intervals. Seven-day low-flow characteristics were presented graphically. Overall seasonal low-flow statistics for selected gaging sites were also presented. Total Maximum Daily Load (TMDL) for ammonia, waste load allocation, and load allocation for the Big Sioux River near Brookings were determined. Both 30-day average and daily maximum loads were determined to maintain the surface water quality standards for ammonia

Measurements and modeling of throughfall variability for five forest communities in the southeastern US

The temporal variability of interception losses was measured for contrasting forest communities in the southeastern United States. Throughfall was measured simultaneously at Fort Benning in western Georgia for the five forest communities that are characteristic of the region. The measured interception losses over the study period were 22.3, 18.6, 17.7, 17.6, and 17.4% of the total precipitation in the pine, mixed forest, lowland hardwood, pine plantation, and upland hardwood forests, respectively. The Gash model with a wet canopy Penman–Monteith evaporation, using annual average canopy cover values, predicted interception losses with an agreement of −8.1–10.5% on an annual basis. The model improved accuracy for all forest communities when seasonal changes in canopy cover were included. The Gash model\u27s assumption of a constant canopy storage capacity was examined for pine and lowland hardwood plots with varying densities and found to have good agreement for mature pine forests having 64, 44, and 29% canopy cover. However, riparian wetland forest predictions required corrections for species composition and understory vegetation

The Chemical Composition of Rainfall and Throughfall in Five Forest Communities: A Case Study in Fort Benning, Georgia

In order to investigate the effects of canopy-dependent processes on throughfall chemistry, comparative studies on the chemical composition of throughfall were carried out in five characteristic forest types of the southeastern United States within Fort Benning Military Installation from January 2002 to August 2003. The concentrations and fluxes of and total organic carbon (TOC), total Kjeldahl nitrogen (TKN), and total phosphorus (TP) were determined in rainfall and throughfall. Seasonal variations in chemical fluxes were also evaluated. Throughfall concentrations of TOC, TKN, and TP in matured pine stand were higher than in rainfall and other forest stands. Throughfall nutrient concentrations in wetland were lowest as compared to rainfall as well as hardwood, mixed, plantation, and pine stands. The average TOC, TKN, and TP concentrations in the matured pine stand were 17.2, 0.74, and 0.057 mg/L, respectively. In wetland stands, average concentrations of TOC, TKN, and TP were 4.0, 0.54, and 0.034 mg/L, respectively. Hardwood stand had the lowest TKN concentration of 0.53 mg/L. Nutrient fluxes were generally higher during the dormant season (November–April) as compared to the growing season (May–October). The highest and lowest TOC fluxes during dormant season were contributed from pine stand (801.7 g/ha) and wetland stand (186.2 g/ha), respectively. Rainfall was the major contributor of TKN fluxes in growing season (32.3 g/ha) as well as in dormant season (34.1 g/ha). Similarly, highest TP flux was produced in mixed stand (2.7 g/ha) during the dormant season. Enrichment ratios of nutrients reveal that, in general, forest stands used up nutrients during growing season and washed off during the dormant season

Multi-Label Classification from Multiple Noisy Sources Using Topic Models

Multi-label classification is a well-known supervised machine learning setting where each instance is associated with multiple classes. Examples include annotation of images with multiple labels, assigning multiple tags for a web page, etc. Since several labels can be assigned to a single instance, one of the key challenges in this problem is to learn the correlations between the classes. Our first contribution assumes labels from a perfect source. Towards this, we propose a novel topic model (ML-PA-LDA). The distinguishing feature in our model is that classes that are present as well as the classes that are absent generate the latent topics and hence the words. Extensive experimentation on real world datasets reveals the superior performance of the proposed model. A natural source for procuring the training dataset is through mining user-generated content or directly through users in a crowdsourcing platform. In this more practical scenario of crowdsourcing, an additional challenge arises as the labels of the training instances are provided by noisy, heterogeneous crowd-workers with unknown qualities. With this motivation, we further augment our topic model to the scenario where the labels are provided by multiple noisy sources and refer to this model as ML-PA-LDA-MNS. With experiments on simulated noisy annotators, the proposed model learns the qualities of the annotators well, even with minimal training data

Relationships between stream water chemistry and military land use in forested watersheds in Fort Benning, Georgia

Within a military land activity context, relationships between stream water chemistry and watershed land use, topography and vegetation were explored at the Fort Benning Military Installation, Georgia. Water quality parameters, including pH, temperature, conductivity, total Kjeldahl nitrogen, total phosphorus, total organic carbon, chloride, and total suspended solids, were routinely measured in seven watersheds from October 2001 to September 2003. Military land use was categorized by the bare ground extent, road network, and designated military zones in each watershed as well as by soil characteristics and forest type. Natural watershed variables, area and soil texture, influenced the stream water pH and total phosphorus, respectively. The stream water total phosphorus, total Kjeldahl nitrogen, total organic carbon, and total suspended solids were well predicted by at least one aspect of military management as an explanatory variable. Stream water total Kjeldahl nitrogen and total organic carbon were negatively correlated with military land extent. While the military land extent did not show significant relationships with either total phosphorus or chloride, the road network used to support military training had significant relationships with both total phosphorus and chloride

Relationships between military land use and storm-based indices of hydrologic variability

This paper examines the influence of military land use parameters on dimensionless indices related to storm flow, baseflow, and precipitation for five watersheds with areas ranging from 0.76 to 25.01 km2 within the Fort Benning Military Installation in southeastern US. Average magnitude and variability of these indices are grouped into four key hydrologic regimes—magnitude, frequency, duration, and rate of change. Correlation and regression analyses were performed to determine the relationship among the watershed physical characteristics and indices. A number of significant relationships were found. The correlation results show that the increase in road density increased the variability in the peak discharges and the slopes of the rising limb. The increase in the military training land increased the variability in the time base. The number of roads crossing streams is positively correlated with the response lag. Stepwise multiple correlations showed that the storm-based magnitude and variability in peak discharge, baseflow index, and the bankfull discharge have been significantly affected by military management related watershed characteristics. The relationship among the watershed physical characteristics and the storm-based hydrologic indices indicated that the greatest impact of land management is found with statistically significant predictive models for indices of time base, response lag, and time of rise. Military training land, road density, and the number of roads crossing streams were the three management variables that impacted storm responses

A comparison of storm-based and annual-based indices of hydrologic variability: a case study in Fort Benning, Georgia

The magnitude, frequency, duration, timing, and rate of change of hydrologic conditions regulate ecological processes in aquatic ecosystems. Conditions are typically characterized using annual-based hydrologic indices derived from daily and/or monthly stream flow data. In this study, we present an alternative approach to identify hydrologic indices based on storm hydrographs. Hydrologic indices derived from long-term daily flow data were compared to those from storm events for two headwater watersheds in Fort Benning, Georgia. Five hydrologic indices derived from daily flow data and storm events shared common features. Storm-based magnitude of mean peak discharge and mean response factor, frequency of bankfull discharge, rate of change in mean slopes of rising, and falling limb of the hydrograph were consistent with the results from long-term daily flow data. The annual flow increases and decreases were well matched by stormflow rising and falling. Both indicators showed one watershed having three times the response rates as compared to the other. Results suggested that select storm-based indices may be used as surrogates to the indices derived from long-term data