416 research outputs found
단순 포진 바이러스 1형에 의해 유도된 베체트병 마우스 모델에서 CCR1 발현의 역할
No full textDoctor1. INTRODUCTION 1
2. MATERIALS AND METHODS 3
2.1. Animal experiments 3
2.2. Symptoms of Behçet's disease in mice 3
2.3. Flow cytometry 4
2.4. Western blot analysis 4
2.5. Administration of cytokines, ligand, and antagonist 5
2.6. Drug treatments 6
2.7. Patients with Behçet's disease 6
2.8. CCL3 ELISA 7
2.9. Statistical analysis 8
3. RESULTS 9
3.1. Frequencies of CCR1+ cells in Behçet's disease mice 9
3.2. Interleukin-10 and GM-CSF affect frequencies of CCR1+ cells in normal mice 14
3.3. Interleukin-10 and GM-CSF up-regulate frequencies of CCR1+ cells in Behçet's disease mice 18
3.4. CCL3 down-regulates the expression of CCR1+ cells in normal mice 23
3.5. BX471, a CCR1 antagonist, does not down-regulate CCR1+ cells in normal mice 27
3.6. CCL3 and BX-471 regulates the expression of CCR1+ cells and deteriorates symptoms in Behçet's disease mice 30
3.7. Drug treatment regulates frequencies of CCR1+ cells in normal mice 34
3.8. Drug treatment regulates frequencies of CCR1+ cells in Behçet's disease mice 38
3.9. Anti-CCL3 antibody up-regulates the expression of CCR1+ cells normal mice 43
3.10. Anti-CCL3 antibody up-regulates the expression of CCR1+ cells and improves symptoms in Behçet's disease mice 47
3.11. Behcet's disease patient clinical and therapeutic history 53
3.12. Plasma levels of CCL3 in patients with Behçet's disease 56
4. DISCUSSION 58
5. CONCLUSION 6
PV Generation and Consumption Dataset of an Estonian Residential Dwelling
No full text<p>This is a Residential PV generation and consumption data set from an Estonian house. At the time of submission, one year (2023) of data was available. The data was logged at a 10-second resolution. The untouched dataset can be found in the raw data folder, which is separated month-wise. A few missing points in the dataset were filled with a simple KNN algorithm. However, improved data imputation methods based on machine learning are also possible. To carry out the imputing, run the scripts in the script folder one by one in the numerical serial order (SC1..py, SC2..py, etc.).</p>
<p>Data Descriptor (Scientific Data): <a title="Solar PV Generation and Consumption Dataset of an Estonian Residential Dwelling" href="https://doi.org/10.1038/s41597-025-04747-w">https://doi.org/10.1038/s41597-025-04747-w</a></p>
<p><strong>General Information:</strong></p>
<p><strong>Duration:</strong> January 2023 – December 2023</p>
<p><strong>Resolution:</strong> 10 seconds</p>
<p><strong>Dataset Type:</strong> Aggregated consumption and PV generation data</p>
<p><strong>Logging Device:</strong> Camile Bauer PQ1000 (×2)</p>
<p><strong>Load/Appliance Information:</strong></p>
<ul>
<li>5 kW Rooftop PV array connected to AC Bus via 4.2kW 3-ϕ Inverter</li>
<li>Air conditioner: 0.44 kW (Cooling), 0.62 kW (Heating)</li>
<li>Air to Water (ATW) Heat Pump: 2.5kW (Cooling), 2.6 kW (Heating)</li>
<li>ATW Cylinder unit: 0.21 kW (Controller), 9 kW (Booster Heater)</li>
<li>Microwave oven: 0.9 kW</li>
<li>Coffee Maker: 1 kW</li>
<li>Cooktop Hot Plate: 4.6 kW</li>
<li>TV: 0.103 kW</li>
<li>Vacuum Cleaner: 1.5 kW</li>
<li>Ventilation: 0.1 kW</li>
<li>Washing Machine: 2.2 kW</li>
<li>Electric Sauna: 10 kW</li>
<li>Lighting: 0.25 kW</li>
<li>EV charger: 2.4 kW 1-ϕ</li>
</ul>
<p><strong>Measurement Points:</strong></p>
<ol>
<li>PV converter-side current transformer, potential transformer (Measurement of PV generation).</li>
<li>Utility meter-side current transformer, potential transformer (Measurement of power exchange with the grid).</li>
</ol>
<p><strong>Measured Parameters:</strong></p>
<ul>
<li>Per-phase mean power recorded within the sampling period</li>
<li>Per-phase Minimum power recorded within the sampling period</li>
<li>Per-phase maximum power recorded within the sampling period</li>
<li>Quadrant-wise mean power recorded within the sampling period (1st + 3rd), (2nd + 4th)</li>
<li>Quadrant-wise minimum power recorded within the sampling period (1st + 3rd), (2nd + 4th)</li>
<li>Quadrant-wise maximum power recorded within the sampling period (1st + 3rd), (2nd + 4th)</li>
<li>mean power Factor recorded within the sampling period</li>
<li>Minimum power Factor recorded within the sampling period</li>
<li>Maximum power Factor recorded within the sampling period</li>
<li>System Voltage</li>
<li>Minimum system Voltage</li>
<li>Maximum system Voltage</li>
<li>Mean Voltage between phase and neutral</li>
<li>Minimum voltage between phase and neutral</li>
<li>Maximum voltage between phase and neutral</li>
<li>Zero displacement voltage 4-wire systems (mean, min, max)</li>
</ul>
<p><strong>Script Description:</strong></p>
<p><strong>SC1_PV_auto_sort.py</strong> : This fixes timestamp continuity by resampling at the original sampling rate for PV generation data.</p>
<p><strong>SC2_L2_auto_sort.py</strong> : This fixes timestamp continuity by resampling at the original sampling rate for meter-side measurement data.</p>
<p><strong>SC3_PV_KNN_impute.py</strong> : Filling missing data points by simple KNN for PV generation data.</p>
<p><strong>SC4_L2_KNN_impute.py</strong> : Filling missing data points by simple KNN for meter-side measurement data.</p>
<p><strong>SC5_Final_data_gen.py</strong> : Merge PV and meter-side measurement data, and calculate load consumption.</p>
<p>The dataset provides all the outcomes (CSV files) from the scripts. All processed variables (PV generation, load, power import, and export) are expressed in kW units.</p>
<p>Update: 'SC1_PV_auto_sort.py' & 'SC2_L2_auto_sort.py' are adequate for cleaning up data and making the missing point visible. 'SC3_PV_KNN_impute.py' & 'SC4_L2_KNN_impute.py' work fine for short-range missing data points; however, these two scripts won't help much for missing data points for a longer period. They are provided as examples of one method of processing data. Future updates will include proper ML-based forecasting to predict missing data points. </p>
<p><br><strong>Funding Agency and Grant Number:</strong></p>
<ol>
<li>European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 955614.</li>
<li>Estonian Research Council under Grant PRG1086.</li>
<li>Estonian Centre of Excellence in Energy Efficiency, ENER, funded by the Estonian Ministry of Education and Research under Grant TK230.</li>
</ol>
sj-docx-1-nah-10.1177_02601060231200521 - Supplemental material for Contribution of socio-economic and demographic factors to maternal and child malnutrition in Bangladesh: Insights from a nationwide survey
No full textSupplemental material, sj-docx-1-nah-10.1177_02601060231200521 for Contribution of socio-economic and demographic factors to maternal and child malnutrition in Bangladesh: Insights from a nationwide survey by Abu Sayeed, Ema Akter, Promit Barua Chowdhury and
Md. Saiful Islam, Mst. Sadia Sultana, Nowrin Nusrat, Lubna Hossain, Rita Karmoker, Ritu Rana, Manika Saha, M. Tasdik Hasan in Nutrition and Health</p
Minding the gap between policy and practice amongst extension workers : lessons from KwaZulu Natal
No full textCITATION: Mohamed Sayeed, C.N., Reddy, P.S. & Pillay, P. 2015. Minding the gap between policy and practice amongst extension workers: Lessons from KwaZulu Natal. South African Journal of Agricultural Extension, 43(1):57-65.The original publication is available from http://www.scielo.org.za20 years into a post-apartheid South Africa, the National Development Plan (NDP) provides the contextual and institutional framework for all of governments activities. As a result, there is a call for extension to increasingly become associated with efficient and effective delivery of services in line with government policy to improve the quality of public services which are critical to achieving a transformed racially equitable public service. This article interrogates the issue of a gap between policy and implementation amongst Extension Workers by reflecting on the findings of research conducted as part of a doctoral study in Public Administration by the main author at the University of KwaZulu Natal. The article makes reference to the findings related to policy knowledge amongst Extension Workers and the challenges related to policy implementation in KwaZulu Natal, and seeks to use the findings of this research to present opportunities and challenges for the implementation of the NDP and concludes that whilst Extension Workers are now challenged to find a balance between their functionality within extension and as public servants, it is important for some consideration to be made by government and education institutions for the changing roles of Extension Workers.http://www.scielo.org.za/scielo.php?script=sci_abstract&pid=S0301-603X2015000100006&lng=en&nrm=iso&tlng=enPublisher's versio
Prevalence and associated factors of depression among Bangladeshi university students: A cross-sectional study
No full textObjective: The study aimed to assess the prevalence of depression and its associated factors among university students in Bangladesh. Participants: A total of 403 undergraduate students from Patuakhali Science and Technology University, and Barisal University participated in the study. Method: A cross-sectional study was conducted using Beck’s Depression Inventory (BDI). Result: The prevalence of depression (BDI ≥ 14) was 47.14%. Depression was 3.4 times (95% CI: 1.6–7.1), 3.8 times (95% CI: 1.7–8.6), and 3.9 times (95% CI: 1.5–8.9) higher among 2nd, 3rd, and 4th-year students, respectively than 1st-year students. Students with a history of stressful life events (aOR = 2.7, 95% CI: 1.7–4.4), suicidal attempts (aOR = 3.0, 95% CI: 1.2–7.9), and who received inadequate monthly allowance from their family (aOR = 0.53 95% CI: 0.3–0.9) were more likely to develop depressive symptoms. Conclusion: This study reports a high level of depression among university students which needs further discussion, exploration, and calls for designing appropriate interventions.No Full Tex
Batch polymerization of styrene and isoprene by n-butyl lithium initiator
No full textDue to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to [email protected], referencing the URI of the item.Not availabl
An integrated methodology for optimum operation and economic capacity expansion of stochastic multi-facility systems
No full textThe objective of this research is to develop a computer methodology for optimum operating criteria and economic capacity expansion decisions for large multi-facility systems with stochastic inputs and demands. This work is based on a previous theoretical study by Curry and Helm. The goal is to minimize the total cost of operation and expansion during the entire planning horizon while satisfying the demand constraints, the storage capacity constraints and other constraints characterized by the particular system. The specific systems considered in the present study are a multiple multi-purpose linked reservoir system with stochastic inflows and demands, and a multi-plant, multi-warehouse system with stochastic demands. Based on the chance constrained models for stochastic multi-reservoir system by Curry and Helm, a computational scheme for operational decisions for large systems is developed. The operational problem is a large linear programming problem. The problem is formulated in Fortran and the solution is obtained by MPS/360. Interfacing between the Fortran and MP/360 is accomplished by the use of Read Communications Format (READCOMM). Expansion of the water resources is also considered. The expansion decision problem is formulated in "yes-no" type binary variables with values 1 or 0. Balas' zero-on integer linear programming is applied for its solution. Then the operational and expansion problem is integrated. The integrated model is a mixed continuous-integer programming problem. Bender's portioning procedure is applied for the solution of the integrated model. Since expansion may not take place in all periods of the planning horizon due to financial or construction lag time, a preferred time expansion scheme is incorporated into the solution methodology. The concept of multi-reservoir operation and expansion is extended to multi-plant multi warehouse system. A chance constrained model for operation and expansion of this system is developed. Several example systems are used to demonstrate the methodology at its various stages
Recovery of Oil From Oil Shale -- An Overall Technological Perspective
No full textThe hydrocarbon content of oil shale can be converted into liquid oil which is a possible energy resource for the future. Different aspects of shale oil recovery is briefly discussed. The technology of modified in situ oil shale retorting, which is receiving increasing attention for commercialization, is discussed in a little more detail
A new digital overcurrent relay
No full textDue to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to [email protected], referencing the URI of the item.Includes bibliographical references.Not availabl
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