Investigation on the Performance of UPQC-Q for Voltage Sag Mitigation and PQ Improvement at a Critical Load Point

The unified power quality conditioner (UPQC) is one of the major custom power solutions, which is capable of mitigating the effect of supply voltage sag at the load end or at the point of common coupling (PCC) in a distributed network. It also prevents the propagation of the load current harmonics to the utility and improves the input power factor of the load. The control of series compensator (SERC) of the UPQC is such that it injects voltage in quadrature advance to the supply current. Thus, the SERC consumes no active power at steady state. The other advantage of the proposed control scheme is that the SERC can share the lagging VAR demand of the load with the shunt compensator (SHUC) and can ease its loading. The UPQC employing this type of quadrature voltage injection in series is termed as UPQC-Q. The VA requirement issues of SERC and SHUCs of a UPQC-Q are discussed. A PC-based new hybrid control has been proposed and the performance of the UPQC-Q is verified in a laboratory prototype. The phasor diagram, control block diagram, simulations and experimental results are presented to confirm the validity of the theory

Experimental investigation of performance of a single phase UPQC for voltage sensitive and non-linear loads

A unified power quality conditioner (UPQC) is proposed in this paper. It protects the consumer at the load end from supply voltage sag, and provides unity power factor condition at the utility for different values of load power factor. A PC-based closed loop control scheme is proposed and experimental investigation is carried out in the laboratory. Selected experimental results are reported along with control circuit and phasor diagram to validate the proposition

Knowledge-driven Natural Language Understanding of English Text and its Applications

Understanding the meaning of a text is a fundamental challenge of natural language understanding (NLU) research. An ideal NLU system should process a language in a way that is not exclusive to a single task or a dataset. Keeping this in mind, we have introduced a novel knowledge driven semantic representation approach for English text. By leveraging the VerbNet lexicon, we are able to map syntax tree of the text to its commonsense meaning represented using basic knowledge primitives. The general purpose knowledge represented from our approach can be used to build any reasoning based NLU system that can also provide justification. We applied this approach to construct two NLU applications that we present here: SQuARE (Semantic-based Question Answering and Reasoning Engine) and StaCACK (Stateful Conversational Agent using Commonsense Knowledge). Both these systems work by "truly understanding" the natural language text they process and both provide natural language explanations for their responses while maintaining high accuracy.Comment: Preprint. Accepted by the 35th AAAI Conference (AAAI-21) Main Track

Detection of off-pulse emission from PSR B0525+21 and PSR B2045-16

We report the detection of off-pulse emission from two long period pulsars PSR B0525+21 and PSR B2045-16 using the Giant Metrewave Radio Telescope (GMRT). We recorded high time resolution interferometric data at 325 MHz and gated the data offline to separate the on- and off-pulse sections of the pulsar. On imaging the two temporal sections separately, we detected a point source in the off-pulse images of both the pulsars coincident with the pulsar locations in the on-pulse images. The long periods (3.75 and 1.96 s respectively) and low spin-down energies (E ~ 10exp(31) erg s-1) of the two pulsars argue against a pulsar wind nebula (PWN) origin for the off-pulse emission. The derived estimates of the ISM particle density required to drive a PWN do not support such an interpretation. A magnetospheric origin for the off-pulse emission raises questions regarding the location of the emission region, which is an important input into pulsar emission models.Comment: 15 pages, 11 figure

Developing nephrology services in low income countries: A case of Tanzania

Background: The burden of kidney diseases is reported to be higher in lower- and middle-income countries as compared to developed countries, and countries in sub-Saharan Africa are reported to be most affected. Health systems in most sub-Sahara African countries have limited capacity in the form of trained and skilled health care providers, diagnostic support, equipment and policies to provide nephrology services. Several initiatives have been implemented to support establishment of these services. Methods: This is a situation analysis to examine the nephrology services in Tanzania. It was conducted by interviewing key personnel in institutions providing nephrology services aiming at describing available services and international collaborators supporting nephrology services. Results: Tanzania is a low-income country in Sub-Saharan Africa with a population of more than 55 million that has seen remarkable improvement in the provision of nephrology services and these include increase in the number of nephrologists to 14 in 2018 from one in 2006, increase in number of dialysis units from one unit (0.03 unit per million) before 2007 to 28 units (0.5 units per million) in 2018 and improved diagnostic services with introduction of nephropathology services. Government of Tanzania has been providing kidney transplantation services by funding referral of donor and recipients abroad and has now introduced local transplantation services in two hospitals. There have been strong international collaborators who have supported nephrology services and establishment of nephrology training in Tanzania. Conclusion: Tanzania has seen remarkable achievement in provision of nephrology services and provides an interesting model to be used in supporting nephrology services in low income countries.publishedVersio

Calculation of true coincidence summing correction factor for a Broad Energy Germanium (BEGe) detector using standard and fabricated sources

The true coincidence summing (TCS) correction factor for a Broad Energy Germanium (BEGe) detector has been calculated at far and close geometry measurement using multi-energetic radioactive $\gamma$-ray sources $^{60}$Co, $^{133}$Ba and $^{152}$Eu. The correction factors were calculated using experimental method and analytical method. Photopeak efficiency and total efficiency required to calculate the correction factor were obtained using Geant4 Monte Carlo simulation code. A few standard as well as fabricated mono-energetic sources were also included in the $\gamma$-ray efficiency measurements. The simulated efficiencies of mono-energetic $\gamma$-ray sources were matched to experimental $\gamma$-ray efficiencies by optimizing the detector parameters. The same parameters were used to obtain the photopeak and total efficiency for $\gamma$-ray of our interest and coincident $\gamma$-ray. Analytical correction factors and experimental correction factors were found in good agreement with each other

Using geospatial technology to strengthen data systems in developing countries: the case of agricultural statistics in India

Despite significant progress in the development of quantitative geography techniques and methods and a general recognition of the need to improve the quality of geographic data, few studies have exploited the potential of geospatial tools to augment the quality of available data methods in developing countries. This paper uses data from an extensive deployment of geospatial technology in India to compare crop areas estimated using geospatial technology to crop areas estimated by conventional methods and assess the differences between the methods. The results presented here show that crop area estimates based on geospatial technology generally exceed the estimates obtained using conventional methods. This suggests that conventional methods are unable to respond quickly to changes in cropping patterns and therefore do not accurately record the area under high-value cash crops. This finding has wider implications for commercializing agriculture and the delivery of farm credit and insurance services in developing countries. Significant data errors found in the conventional methods could affect critical policy interventions such as planning for food security. Some research and policy implications are discussed

A major dengue epidemic in 2022 in Nepal: need of an efficient early-warning system

Dengue has become a recurrent and growing threat to public health in Nepal. The epidemic in 2022 was the largest ever reported, with cases being reported in all of the country’s seven provinces and 77 districts. Despite the establishment of an early-warning and reporting system (EWARS) in 1997, the lack of clear criteria for alarm signals and outbreak definitions in national guidelines delayed the epidemic declaration in 2022, which resulted in an increased number of cases and fatalities. For this article, we analyzed national data from previous years, which demonstrate that an epidemic could have been declared early in July, and that that would have resulted in fewer cases and fatalities if clear criteria for outbreak declarations had also been put in place. We also reviewed the existing national guidelines for dengue prevention and control, and propose recommendations to improve their implementation, particularly with regard to vector control measures. This article also highlights the need for a coordinated effort between multisector stakeholders, strengthened disease surveillance systems, and the establishment of predefined alarm signals and epidemic declaration criteria so that future epidemics are identified in a timely manner. The early outbreak warning system can potentially prevent future large outbreaks and minimize their negative impacts on the country’s health systems and economy