Grazing management in temperate grassland of Kumaun Himalaya for soil water conservation

Overgrazing by livestock has caused major changes in the productivity and composition of rangeland vegetation in India. The main problem stems from the fact that the carrying capacity of rangelands is low as a result of low vegetation cover, and is decreasing with range degradation. This has an impact on land degradation which affects the rangeland hydrology. Thus the aim of this study was to determine the physio-hydrological responses of soil to different intensities of livestock grazing and land management by comparing the effect of uncontrolled grazed land and fenced off (ungrazed) land. There is a need to understand the hydrology of rangeland so as to propose ways of improving carrying capacity of rangeland. The study site had two different treatments: fenced off to prevent grazing, and uncontrolled grazed treatments. Plant biomass was measured at the end of the season. The results showed that there is a significant difference in infiltration rate and soil moisture among the two treatments. Infiltration rates were substantially greater in summer than in winter. On day 1 the steady infiltration rate in summer was twice the winter rate. The infiltration rate in summer on day 2, which is a better measure of the steady rate, was 2.5 times the winter rate. The differences between seasons were statistically very significant (p < 0.001). The effect of treatments on soil moisture was proportional to the effect of vegetation, as well as the effect of soil type on soil moisture, thus vegetation production depends on soil moisture

Small class number fields in the family Q(9m2+4m)\mathbb{Q}(\sqrt{9m^2+4m})

We study the class number one problem for real quadratic fields $\mathbb{Q}(\sqrt{9m^2+ 4m})$, where $m$ is an odd integer. We show that for $m \equiv 1 \pmod 3$ there is only one such field with class number one and only one such field with class number two.Comment: 20 pages. Comments are welcom

Separation of Gravity Anomaly Data considering Statistical Independence among Signals : Application to Severely Contaminated Data Obtained by Prototype Mobile Gravimeter

The ground motion (GM) characteristics are affected by local subsurface structure. Gravity method is one of the useful methods to know the information on subsurface structure. The gravity anomaly data obtained by gravity survey can be correlated with the lateral variation of subsurface rock densities. For gravity survey, spring type gravimeter has been used so far. This gravimeter gives accurate resolution but they are very expensive and diffcult to handle. Recently, Team Morikawa have developed a prototype mobile gravimeter that uses Force-Balanced (FB) accelerometer. This prototype is light weight, compact, easy to handle and inexpensive. It also offers the resolution that is good enough for preparing gravity map for subsurface modelling. However, unlike the conventional spring-type gravimeter, this newly developed FB gravimeter is highly sensitive to high frequency noise. The observed data by this gravimeter are easily contaminated by various kinds of disturbances in a small size carrier like engine vibration, carrier acceleration, wind velocity and carrier tilting accompanied by sensor drifts, electrical noise etc. The amplitudes of such noises can be upto 100,000 times larger than the gravity anomaly. In order to extract the gravity anomaly from such observation, data processing is essential. Conventionally, the data was observed in a large carrier (ship) on a more stable environment and the sensor was not sensitive to high frequency noise, so the noise contamination was not severe. The data processing techniques like low pass filtering and Second order statistics method (such as SOBI) were used. However, in case of severely contaminated data, low pass filtering might not be enough. SOBI is an advanced blind source separation (BSS) technique that separates source and noise blindly by exploiting the statistical property of data. It separates the target source by assuming that source and unwanted data are un-correlated at various time-lags. The gravity anomaly and other noises are generated from independent physical sources. It can be safely assumed that gravity anomaly and other data are independent but, it can not be strictly claimed that they have no correlation. So, further improvement than second order statistics method is desired. As a scheme of considering independence of signals to blind source separation, Independent Component Analysis (ICA) has been used in the field of BSS since 1990's. It separates the sources by maximizing the independence of linearly transformed observed signals. Both mixing matrix and source signals are identified when only the mixed data are available. Further, independence between signals has nothing to do with their amplitudes. The huge difference in amplitudes among gravity anomaly and noise does not affect their independence. So ICA is suitable for our purpose. ICA renders ambiguity in amplitude of separated signal but this problem has little significance in our case since an appropriate scalar multiple can be estimated with the help of information of gravity at few known points. Thus it is proposed to use ICA for separating gravity anomaly data from its mixture with several noises. The survey data is observed at Toyama bay, Japan. The National Institute of Advanced Industrial Science and Technology (AIST), Japan has provided the gravity map for the same place. This map is used to calculate the reference data that facilitates us to verify the performance of the proposed scheme. The prototype gravimeter consisted of group of sensors. Since ICA requires at least two sets of data, the major data obtained by Analog servo (VSE) was combined with data by other sensors as supplementary data. Following Team Morikawa's approach, the performance of various sensors are compared. The application of low pass filtering(LPF) as a pre-processing to ICA is realized to be important. The presence of high frequency noise in the data is found to be unfavourable for the separation of gravity anomaly data. Both SOBI and ICA work only after the application of LPF. The choice of an appropriate cut-off filter was also observed to affect the results. The combination of VSE data and vertical component of Accelerometer Titan (Taurus-Z) as an iput to ICA gives good result. When other horizontal components were used with VSE data the results are not satisfactory. Further, ICA is found to perform better at certain conditions of data acquisition environment. At the portions when ship motion is unidirectional the trend of ICA separated data is harmonious with reference data. When the ship velocity was lesser while proceeding towards the sea, the ICA result is matching very well with reference data. When the ship was highly unstable during ship stopping time ICA result are deviating away from the reference data. At other relatively stable sections the ICA separated data follows the trend of reference data well. The separation of input data by ICA into different output components verifies that the source gravity anomaly and other data are independent. Thus it satisfies our assumption. The harmony of ICA separated data with trend of reference data at major sections verifies the applicability of ICA, under certain data acquisition environments. The accuracy of properly separated data by ICA is good enough for preparing gravity map for the purpose of subsurface modelling. However, there is still a room for further improvement. An effort is made to study time-frequency characteristics of data without observing any clear merit so far. The further improvement in methodology is considered to be the part of future works. Based on the results and considering the applicability of ICA so far, it can be concluded that a positive sign is observed for the improvement of mobility of gravity method.報告番号: ; 学位授与年月日: 2012-09-27 ; 学位の種別: 修士 ; 学位の種類: 修士（工学） ; 学位記番号: ; 研究科・専攻: 工学系研究科社会基盤学専

Green supply chain performance assessment: exploration fuzzy logic to tackle linguistic evaluation information

Green Supply Chain Management (GSCM) has appeared as an environmental innovation integrating environmental concerns into the supply chain management. Due to recent modification in environmental requirements, Govt. rules and regulations that affect manufacturing operations and services; growing attention is being given towards inclusion of environmental management strategies into traditional concept of supply chains. A Green Supply Chain (GSC) aims at confining the wastes within the industrial system so as to conserve energy and prevent the dissipation of harmful materials into the environment. In order to assess GSC performance extent, ‘green attributes’ must be considered along with traditional SC performance indices. The present work aims to discuss a methodology to deal with linguistic evaluation information through fuzzy logic for evaluating green supply chain performance and also attempts in identifying and prioritizing the key factors towards increasing ‘green competitiveness’. Here, the performance criteria/attributes have been evaluated by the expert group through linguistic variables which have further been transformed into Generalized Trapezoidal Fuzzy Numbers (GTFNs). Linguistic assessment of GSCM has been carried out based on different attributes, such as customer value, quality evaluation, performance measurement, appropriate price and environmental effect. Each attribute is followed by several criterions. Because of the vague and inconsistent nature of decision-makers’ linguistic evaluation information associated with GSCM; a fuzzy-based approach is indeed required to convert linguistic data into appropriate fuzzy numbers, for the analysis purpose. Apart from computing overall green performance extent, this research has been extended to identify ill-performing areas of an organizational GSC. Moreover, a case study has been reported in support of application feasibility of the proposed module

The incidence and the co-morbidities which affect the surgical site infection: a hospital based study

Aim: to assess the incidence and various co-morbiditiesassociated with surgical site infection.Materials and Methods: The study was carried out on 144 patients who underwent various surgeries in the Department of General Surgery of IGIMS, Patna, Bihar, India from February 2016 to December  2016.A predesigned protocol was used to collect the data. Surgical site infections were examined and graded. Data was analyzed by SPSS.20 software. Results: Among 144 patients, 24 developed surgical site infection. Among 24 patients, 13 were grade 3 and 11 were grade 4 type of infection. Surgical site infections were most commonly found among males, aged, diabetics, anaemic and hypertensive patients.Conclusions: The incidence of surgical site infection is high. Age, gender, diabetes, blood transfusion and prolonged hospital stay were the important risk factors for surgical site infections. So implementing proper antibiotic policies and infection control measures can reduce SSIs to great extent

MOSDEN: A Scalable Mobile Collaborative Platform for Opportunistic Sensing Applications

Mobile smartphones along with embedded sensors have become an efficient enabler for various mobile applications including opportunistic sensing. The hi-tech advances in smartphones are opening up a world of possibilities. This paper proposes a mobile collaborative platform called MOSDEN that enables and supports opportunistic sensing at run time. MOSDEN captures and shares sensor data across multiple apps, smartphones and users. MOSDEN supports the emerging trend of separating sensors from application-specific processing, storing and sharing. MOSDEN promotes reuse and re-purposing of sensor data hence reducing the efforts in developing novel opportunistic sensing applications. MOSDEN has been implemented on Android-based smartphones and tablets. Experimental evaluations validate the scalability and energy efficiency of MOSDEN and its suitability towards real world applications. The results of evaluation and lessons learned are presented and discussed in this paper.Comment: Accepted to be published in Transactions on Collaborative Computing, 2014. arXiv admin note: substantial text overlap with arXiv:1310.405

Divisibility of the class numbers of imaginary quadratic fields

For a given odd integer $n>1$, we provide some families of imaginary quadratic number fields of the form $\mathbb{Q}(\sqrt{x^2-t^n})$ whose ideal class group has a subgroup isomorphic to $\mathbb{Z}/n\mathbb{Z}$.Comment: 10 pages, accepted for publication in Journal of Number Theory (2017

Efficient Opportunistic Sensing using Mobile Collaborative Platform MOSDEN

Mobile devices are rapidly becoming the primary computing device in people's lives. Application delivery platforms like Google Play, Apple App Store have transformed mobile phones into intelligent computing devices by the means of applications that can be downloaded and installed instantly. Many of these applications take advantage of the plethora of sensors installed on the mobile device to deliver enhanced user experience. The sensors on the smartphone provide the opportunity to develop innovative mobile opportunistic sensing applications in many sectors including healthcare, environmental monitoring and transportation. In this paper, we present a collaborative mobile sensing framework namely Mobile Sensor Data EngiNe (MOSDEN) that can operate on smartphones capturing and sharing sensed data between multiple distributed applications and users. MOSDEN follows a component-based design philosophy promoting reuse for easy and quick opportunistic sensing application deployments. MOSDEN separates the application-specific processing from the sensing, storing and sharing. MOSDEN is scalable and requires minimal development effort from the application developer. We have implemented our framework on Android-based mobile platforms and evaluate its performance to validate the feasibility and efficiency of MOSDEN to operate collaboratively in mobile opportunistic sensing applications. Experimental outcomes and lessons learnt conclude the paper

Nickel (II) Removal from Aqueous Solutions by Adsorption on Fly-ash.

The feasibility of Ni(II) removal from water was investigated by adsorption on fly-ash. The equilibrium data of Ni(II) removal thus obtained is well fitted to Langmuir equation. The mono layer adsorption capacity was calculated and found to be 0.293 mg-1 at 30C. The batch adsorption kinetics follows first order reaction and appears to be diffusion controlled. The values of mass transfer and pore diffusion coefficients were 1.14 X 10-5 cm S-I and 6.2 xlO -1l cm2 s-J respectively at 30C. The influence of initial nickel concentration, residence time, temperature and pH on metal adsorption process was studied, An increase in the solution temperature, pH and decrease in concentration favour the removal of nickel by fly-ash. The maximum adsorption of Ni(II) ions was noted at pH 7.0. The various thermodynamic parameters were calculated for the present system. The empirical model has been tested for the kinetics join(II) removal by adsorption on fly ash and the parameters for the continuous operation of the removal process were determined

Composition, productivity and impact of grazing on the biodiversity of a grazing land in Almora District

Biodiversity of Almora district is heavily affected in the areas with heavy grazing pressure, although moderate grazing enhanced the biodiversity of the area. In the present study site a total of 45 herbaceous species were present and therophytes were dominant among them. Live shoot biomass of plants varied from 175.0±3.5 to 1862.0±5.75 kg/ha and 87.0±3.25 to 1303.0±7.50 kg/ha in ungrazed and grazed plots respectively. Aboveground primary productivity was significantly higher on control plot (3082.2 kg/ha) over grazed plot (2644.0 kg/ha). The average bite frequency per hour was recorded maximum for goats (1106.5 bite/hr) and least for buffalos (920 bites/hr). The monthly dry matter consumption per animal was amounted to 157.15, 154.51, 68.66 and 61.34 kg for cow, buffalo, sheep and goat respectively under nomadic open grazing. The percent herbage exploitation was observed maximum by sheep (9.82%) and minimum by buffalo (8.75%)